From 48ddcdde8363d4fd7e807f203308694ab85456e5 Mon Sep 17 00:00:00 2001 From: KAZUYUKI TANIMURA Date: Mon, 3 Jun 2024 16:03:00 -0700 Subject: [PATCH] build: Enable comet tests with spark-4.0 profile (#493) ## Rationale for this change To be ready for Spark 4.0 ## What changes are included in this PR? This PR enables the comet tests with the spark-4.0 profile ## How are these changes tested? Tests with the spark-4.0 profile now should pass. (But Spark tests do not yet) --- .github/workflows/pr_build.yml | 18 +- .../scala/org/apache/comet/CometConf.scala | 9 +- .../apache/comet/shims/ShimCometConf.scala | 25 + .../apache/comet/shims/ShimCometConf.scala | 25 + docs/source/contributor-guide/development.md | 4 + docs/source/user-guide/configs.md | 1 - .../comet/CometSparkSessionExtensions.scala | 4 + .../apache/comet/serde/QueryPlanSerde.scala | 3 +- .../spark/sql/ExtendedExplainGenerator.scala | 0 .../q1/explain.txt | 274 +++++ .../q1/simplified.txt | 68 ++ .../q10/explain.txt | 286 +++++ .../q10/simplified.txt | 75 ++ .../q11/explain.txt | 482 ++++++++ .../q11/simplified.txt | 123 ++ .../q12/explain.txt | 150 +++ .../q12/simplified.txt | 40 + .../q13/explain.txt | 232 ++++ .../q13/simplified.txt | 59 + .../q14a/explain.txt | 800 +++++++++++++ .../q14a/simplified.txt | 214 ++++ .../q14b/explain.txt | 759 ++++++++++++ .../q14b/simplified.txt | 204 ++++ .../q15/explain.txt | 164 +++ .../q15/simplified.txt | 41 + .../q16/explain.txt | 260 ++++ .../q16/simplified.txt | 74 ++ .../q17/explain.txt | 298 +++++ .../q17/simplified.txt | 76 ++ .../q18/explain.txt | 281 +++++ .../q18/simplified.txt | 71 ++ .../q19/explain.txt | 227 ++++ .../q19/simplified.txt | 58 + .../q2/explain.txt | 210 ++++ .../q2/simplified.txt | 54 + .../q20/explain.txt | 150 +++ .../q20/simplified.txt | 40 + .../q21/explain.txt | 169 +++ .../q21/simplified.txt | 42 + .../q22/explain.txt | 169 +++ .../q22/simplified.txt | 42 + .../q23a/explain.txt | 570 +++++++++ .../q23a/simplified.txt | 155 +++ .../q23b/explain.txt | 694 +++++++++++ .../q23b/simplified.txt | 188 +++ .../q24a/explain.txt | 427 +++++++ .../q24a/simplified.txt | 118 ++ .../q24b/explain.txt | 427 +++++++ .../q24b/simplified.txt | 118 ++ .../q25/explain.txt | 298 +++++ .../q25/simplified.txt | 76 ++ .../q26/explain.txt | 208 ++++ .../q26/simplified.txt | 52 + .../q27/explain.txt | 208 ++++ .../q27/simplified.txt | 52 + .../q28/explain.txt | 437 +++++++ .../q28/simplified.txt | 111 ++ .../q29/explain.txt | 326 +++++ .../q29/simplified.txt | 83 ++ .../q3/explain.txt | 125 ++ .../q3/simplified.txt | 31 + .../q30/explain.txt | 324 +++++ .../q30/simplified.txt | 81 ++ .../q31/explain.txt | 616 ++++++++++ .../q31/simplified.txt | 159 +++ .../q32/explain.txt | 209 ++++ .../q32/simplified.txt | 52 + .../q33/explain.txt | 405 +++++++ .../q33/simplified.txt | 105 ++ .../q34/explain.txt | 218 ++++ .../q34/simplified.txt | 56 + .../q35/explain.txt | 281 +++++ .../q35/simplified.txt | 74 ++ .../q36/explain.txt | 194 +++ .../q36/simplified.txt | 51 + .../q37/explain.txt | 179 +++ .../q37/simplified.txt | 44 + .../q38/explain.txt | 321 +++++ .../q38/simplified.txt | 81 ++ .../q39a/explain.txt | 318 +++++ .../q39a/simplified.txt | 81 ++ .../q39b/explain.txt | 318 +++++ .../q39b/simplified.txt | 81 ++ .../q4/explain.txt | 698 +++++++++++ .../q4/simplified.txt | 179 +++ .../q40/explain.txt | 218 ++++ .../q40/simplified.txt | 60 + .../q41/explain.txt | 119 ++ .../q41/simplified.txt | 29 + .../q42/explain.txt | 125 ++ .../q42/simplified.txt | 31 + .../q43/explain.txt | 125 ++ .../q43/simplified.txt | 31 + .../q44/explain.txt | 286 +++++ .../q44/simplified.txt | 81 ++ .../q45/explain.txt | 242 ++++ .../q45/simplified.txt | 61 + .../q46/explain.txt | 258 ++++ .../q46/simplified.txt | 65 + .../q47/explain.txt | 279 +++++ .../q47/simplified.txt | 81 ++ .../q48/explain.txt | 198 +++ .../q48/simplified.txt | 50 + .../q49/explain.txt | 456 +++++++ .../q49/simplified.txt | 121 ++ .../q5/explain.txt | 457 +++++++ .../q5/simplified.txt | 111 ++ .../q50/explain.txt | 199 +++ .../q50/simplified.txt | 50 + .../q51/explain.txt | 245 ++++ .../q51/simplified.txt | 75 ++ .../q52/explain.txt | 125 ++ .../q52/simplified.txt | 31 + .../q53/explain.txt | 194 +++ .../q53/simplified.txt | 51 + .../q54/explain.txt | 483 ++++++++ .../q54/simplified.txt | 123 ++ .../q55/explain.txt | 125 ++ .../q55/simplified.txt | 31 + .../q56/explain.txt | 405 +++++++ .../q56/simplified.txt | 105 ++ .../q57/explain.txt | 279 +++++ .../q57/simplified.txt | 81 ++ .../q58/explain.txt | 386 ++++++ .../q58/simplified.txt | 98 ++ .../q59/explain.txt | 256 ++++ .../q59/simplified.txt | 66 + .../q6/explain.txt | 309 +++++ .../q6/simplified.txt | 79 ++ .../q60/explain.txt | 405 +++++++ .../q60/simplified.txt | 105 ++ .../q61/explain.txt | 417 +++++++ .../q61/simplified.txt | 106 ++ .../q62/explain.txt | 187 +++ .../q62/simplified.txt | 48 + .../q63/explain.txt | 194 +++ .../q63/simplified.txt | 51 + .../q64/explain.txt | 1064 +++++++++++++++++ .../q64/simplified.txt | 281 +++++ .../q65/explain.txt | 269 +++++ .../q65/simplified.txt | 67 ++ .../q66/explain.txt | 332 +++++ .../q66/simplified.txt | 86 ++ .../q67/explain.txt | 204 ++++ .../q67/simplified.txt | 53 + .../q68/explain.txt | 258 ++++ .../q68/simplified.txt | 65 + .../q69/explain.txt | 281 +++++ .../q69/simplified.txt | 74 ++ .../q7/explain.txt | 208 ++++ .../q7/simplified.txt | 52 + .../q70/explain.txt | 283 +++++ .../q70/simplified.txt | 75 ++ .../q71/explain.txt | 254 ++++ .../q71/simplified.txt | 69 ++ .../q72/explain.txt | 433 +++++++ .../q72/simplified.txt | 116 ++ .../q73/explain.txt | 218 ++++ .../q73/simplified.txt | 56 + .../q74/explain.txt | 477 ++++++++ .../q74/simplified.txt | 122 ++ .../q75/explain.txt | 779 ++++++++++++ .../q75/simplified.txt | 240 ++++ .../q76/explain.txt | 218 ++++ .../q76/simplified.txt | 58 + .../q77/explain.txt | 547 +++++++++ .../q77/simplified.txt | 143 +++ .../q78/explain.txt | 431 +++++++ .../q78/simplified.txt | 127 ++ .../q79/explain.txt | 208 ++++ .../q79/simplified.txt | 52 + .../q8/explain.txt | 288 +++++ .../q8/simplified.txt | 72 ++ .../q80/explain.txt | 645 ++++++++++ .../q80/simplified.txt | 182 +++ .../q81/explain.txt | 319 +++++ .../q81/simplified.txt | 80 ++ .../q82/explain.txt | 179 +++ .../q82/simplified.txt | 44 + .../q83.ansi/explain.txt | 372 ++++++ .../q83.ansi/simplified.txt | 95 ++ .../q84/explain.txt | 210 ++++ .../q84/simplified.txt | 54 + .../q85/explain.txt | 305 +++++ .../q85/simplified.txt | 75 ++ .../q86/explain.txt | 155 +++ .../q86/simplified.txt | 41 + .../q87/explain.txt | 321 +++++ .../q87/simplified.txt | 81 ++ .../q88/explain.txt | 1031 ++++++++++++++++ .../q88/simplified.txt | 265 ++++ .../q89/explain.txt | 189 +++ .../q89/simplified.txt | 50 + .../q9/explain.txt | 303 +++++ .../q9/simplified.txt | 81 ++ .../q90/explain.txt | 292 +++++ .../q90/simplified.txt | 74 ++ .../q91/explain.txt | 281 +++++ .../q91/simplified.txt | 73 ++ .../q92/explain.txt | 209 ++++ .../q92/simplified.txt | 52 + .../q93/explain.txt | 138 +++ .../q93/simplified.txt | 40 + .../q94/explain.txt | 260 ++++ .../q94/simplified.txt | 74 ++ .../q95/explain.txt | 330 +++++ .../q95/simplified.txt | 102 ++ .../q96/explain.txt | 163 +++ .../q96/simplified.txt | 41 + .../q97/explain.txt | 179 +++ .../q97/simplified.txt | 47 + .../q98/explain.txt | 160 +++ .../q98/simplified.txt | 44 + .../q99/explain.txt | 187 +++ .../q99/simplified.txt | 48 + .../q10a/explain.txt | 272 +++++ .../q10a/simplified.txt | 72 ++ .../q11/explain.txt | 477 ++++++++ .../q11/simplified.txt | 122 ++ .../q12/explain.txt | 150 +++ .../q12/simplified.txt | 40 + .../q14/explain.txt | 759 ++++++++++++ .../q14/simplified.txt | 204 ++++ .../q14a/explain.txt | 964 +++++++++++++++ .../q14a/simplified.txt | 261 ++++ .../q18a/explain.txt | 909 ++++++++++++++ .../q18a/simplified.txt | 233 ++++ .../q20/explain.txt | 150 +++ .../q20/simplified.txt | 40 + .../q22/explain.txt | 161 +++ .../q22/simplified.txt | 41 + .../q22a/explain.txt | 315 +++++ .../q22a/simplified.txt | 80 ++ .../q24/explain.txt | 437 +++++++ .../q24/simplified.txt | 122 ++ .../q27a/explain.txt | 457 +++++++ .../q27a/simplified.txt | 117 ++ .../q34/explain.txt | 218 ++++ .../q34/simplified.txt | 56 + .../q35/explain.txt | 281 +++++ .../q35/simplified.txt | 74 ++ .../q35a/explain.txt | 267 +++++ .../q35a/simplified.txt | 71 ++ .../q36a/explain.txt | 279 +++++ .../q36a/simplified.txt | 76 ++ .../q47/explain.txt | 279 +++++ .../q47/simplified.txt | 81 ++ .../q49/explain.txt | 456 +++++++ .../q49/simplified.txt | 121 ++ .../q51a/explain.txt | 416 +++++++ .../q51a/simplified.txt | 124 ++ .../q57/explain.txt | 279 +++++ .../q57/simplified.txt | 81 ++ .../q5a/explain.txt | 542 +++++++++ .../q5a/simplified.txt | 136 +++ .../q6/explain.txt | 309 +++++ .../q6/simplified.txt | 79 ++ .../q64/explain.txt | 1064 +++++++++++++++++ .../q64/simplified.txt | 281 +++++ .../q67a/explain.txt | 466 ++++++++ .../q67a/simplified.txt | 127 ++ .../q70a/explain.txt | 368 ++++++ .../q70a/simplified.txt | 100 ++ .../q72/explain.txt | 433 +++++++ .../q72/simplified.txt | 116 ++ .../q74/explain.txt | 477 ++++++++ .../q74/simplified.txt | 122 ++ .../q75/explain.txt | 779 ++++++++++++ .../q75/simplified.txt | 240 ++++ .../q77a/explain.txt | 632 ++++++++++ .../q77a/simplified.txt | 168 +++ .../q78/explain.txt | 431 +++++++ .../q78/simplified.txt | 127 ++ .../q80a/explain.txt | 730 +++++++++++ .../q80a/simplified.txt | 207 ++++ .../q86a/explain.txt | 240 ++++ .../q86a/simplified.txt | 66 + .../q98/explain.txt | 155 +++ .../q98/simplified.txt | 43 + .../org/apache/comet/CometCastSuite.scala | 14 +- .../apache/comet/exec/CometExecSuite.scala | 8 +- .../comet/parquet/ParquetReadSuite.scala | 10 +- .../sql/comet/CometPlanStabilitySuite.scala | 10 +- .../comet/ParquetDatetimeRebaseSuite.scala | 10 +- .../comet/CometExpression3_3PlusSuite.scala | 1 - .../comet/exec/CometExec3_4PlusSuite.scala | 1 - 286 files changed, 59332 insertions(+), 36 deletions(-) create mode 100644 common/src/main/spark-3.x/org/apache/comet/shims/ShimCometConf.scala create mode 100644 common/src/main/spark-4.0/org/apache/comet/shims/ShimCometConf.scala rename spark/src/main/{scala => spark-3.x}/org/apache/spark/sql/ExtendedExplainGenerator.scala (100%) create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q1/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q1/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q10/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q10/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q11/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q11/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q12/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q12/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q13/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q13/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14a/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14a/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14b/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14b/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q15/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q15/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q16/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q16/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q17/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q17/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q18/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q18/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q19/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q19/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q2/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q2/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q20/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q20/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q21/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q21/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q22/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q22/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23a/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23a/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23b/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23b/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24a/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24a/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24b/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24b/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q25/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q25/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q26/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q26/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q27/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q27/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q28/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q28/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q29/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q29/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q3/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q3/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q30/explain.txt create mode 100644 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100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q35/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q35/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q36/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q36/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q37/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q37/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q38/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q38/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39a/explain.txt create 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100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q72/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q74/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q74/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q75/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q75/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q77a/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q77a/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q78/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q78/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q80a/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q80a/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q86a/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q86a/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q98/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q98/simplified.txt diff --git a/.github/workflows/pr_build.yml b/.github/workflows/pr_build.yml index 410f1e1fe8..7de198a471 100644 --- a/.github/workflows/pr_build.yml +++ b/.github/workflows/pr_build.yml @@ -109,10 +109,8 @@ jobs: - name: Java test steps uses: ./.github/actions/java-test with: - # TODO: remove -DskipTests after fixing tests - maven_opts: "-Pspark-${{ matrix.spark-version }} -DskipTests" - # TODO: upload test reports after enabling tests - upload-test-reports: false + maven_opts: -Pspark-${{ matrix.spark-version }} + upload-test-reports: true linux-test-with-old-spark: strategy: @@ -237,10 +235,8 @@ jobs: - name: Java test steps uses: ./.github/actions/java-test with: - # TODO: remove -DskipTests after fixing tests - maven_opts: "-Pspark-${{ matrix.spark-version }} -DskipTests" - # TODO: upload test reports after enabling tests - upload-test-reports: false + maven_opts: -Pspark-${{ matrix.spark-version }} + upload-test-reports: true macos-aarch64-test-with-spark4_0: strategy: @@ -277,10 +273,8 @@ jobs: - name: Java test steps uses: ./.github/actions/java-test with: - # TODO: remove -DskipTests after fixing tests - maven_opts: "-Pspark-${{ matrix.spark-version }} -DskipTests" - # TODO: upload test reports after enabling tests - upload-test-reports: false + maven_opts: -Pspark-${{ matrix.spark-version }} + upload-test-reports: true macos-aarch64-test-with-old-spark: strategy: diff --git a/common/src/main/scala/org/apache/comet/CometConf.scala b/common/src/main/scala/org/apache/comet/CometConf.scala index 5aee02f118..42fb5fb4c0 100644 --- a/common/src/main/scala/org/apache/comet/CometConf.scala +++ b/common/src/main/scala/org/apache/comet/CometConf.scala @@ -29,6 +29,8 @@ import org.apache.spark.network.util.JavaUtils import org.apache.spark.sql.comet.util.Utils import org.apache.spark.sql.internal.SQLConf +import org.apache.comet.shims.ShimCometConf + /** * Configurations for a Comet application. Mostly inspired by [[SQLConf]] in Spark. * @@ -41,7 +43,7 @@ import org.apache.spark.sql.internal.SQLConf * which retrieves the config value from the thread-local [[SQLConf]] object. Alternatively, you * can also explicitly pass a [[SQLConf]] object to the `get` method. */ -object CometConf { +object CometConf extends ShimCometConf { /** List of all configs that is used for generating documentation */ val allConfs = new ListBuffer[ConfigEntry[_]] @@ -361,7 +363,7 @@ object CometConf { "column to a long column, a float column to a double column, etc. This is automatically" + "enabled when reading from Iceberg tables.") .booleanConf - .createWithDefault(false) + .createWithDefault(COMET_SCHEMA_EVOLUTION_ENABLED_DEFAULT) val COMET_ROW_TO_COLUMNAR_ENABLED: ConfigEntry[Boolean] = conf("spark.comet.rowToColumnar.enabled") @@ -382,12 +384,13 @@ object CometConf { .createWithDefault(Seq("Range,InMemoryTableScan")) val COMET_ANSI_MODE_ENABLED: ConfigEntry[Boolean] = conf("spark.comet.ansi.enabled") + .internal() .doc( "Comet does not respect ANSI mode in most cases and by default will not accelerate " + "queries when ansi mode is enabled. Enable this setting to test Comet's experimental " + "support for ANSI mode. This should not be used in production.") .booleanConf - .createWithDefault(false) + .createWithDefault(COMET_ANSI_MODE_ENABLED_DEFAULT) val COMET_CAST_ALLOW_INCOMPATIBLE: ConfigEntry[Boolean] = conf("spark.comet.cast.allowIncompatible") diff --git a/common/src/main/spark-3.x/org/apache/comet/shims/ShimCometConf.scala b/common/src/main/spark-3.x/org/apache/comet/shims/ShimCometConf.scala new file mode 100644 index 0000000000..dc84a7525a --- /dev/null +++ b/common/src/main/spark-3.x/org/apache/comet/shims/ShimCometConf.scala @@ -0,0 +1,25 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + +package org.apache.comet.shims + +trait ShimCometConf { + protected val COMET_SCHEMA_EVOLUTION_ENABLED_DEFAULT = false + protected val COMET_ANSI_MODE_ENABLED_DEFAULT = false +} diff --git a/common/src/main/spark-4.0/org/apache/comet/shims/ShimCometConf.scala b/common/src/main/spark-4.0/org/apache/comet/shims/ShimCometConf.scala new file mode 100644 index 0000000000..13da6bc107 --- /dev/null +++ b/common/src/main/spark-4.0/org/apache/comet/shims/ShimCometConf.scala @@ -0,0 +1,25 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + +package org.apache.comet.shims + +trait ShimCometConf { + protected val COMET_SCHEMA_EVOLUTION_ENABLED_DEFAULT = true + protected val COMET_ANSI_MODE_ENABLED_DEFAULT = true +} diff --git a/docs/source/contributor-guide/development.md b/docs/source/contributor-guide/development.md index 0121d9f469..913eea408e 100644 --- a/docs/source/contributor-guide/development.md +++ b/docs/source/contributor-guide/development.md @@ -92,11 +92,13 @@ The plan stability testing framework is located in the `spark` module and can be ```sh ./mvnw -pl spark -Dsuites="org.apache.spark.sql.comet.CometTPCDSV1_4_PlanStabilitySuite" test +./mvnw -pl spark -Dsuites="org.apache.spark.sql.comet.CometTPCDSV1_4_PlanStabilitySuite" -Pspark-4.0 -nsu test ``` and ```sh ./mvnw -pl spark -Dsuites="org.apache.spark.sql.comet.CometTPCDSV2_7_PlanStabilitySuite" test +./mvnw -pl spark -Dsuites="org.apache.spark.sql.comet.CometTPCDSV2_7_PlanStabilitySuite" -Pspark-4.0 -nsu test ``` If your pull request changes the query plans generated by Comet, you should regenerate the golden files. @@ -104,11 +106,13 @@ To regenerate the golden files, you can run the following command: ```sh SPARK_GENERATE_GOLDEN_FILES=1 ./mvnw -pl spark -Dsuites="org.apache.spark.sql.comet.CometTPCDSV1_4_PlanStabilitySuite" test +SPARK_GENERATE_GOLDEN_FILES=1 ./mvnw -pl spark -Dsuites="org.apache.spark.sql.comet.CometTPCDSV1_4_PlanStabilitySuite" -Pspark-4.0 -nsu test ``` and ```sh SPARK_GENERATE_GOLDEN_FILES=1 ./mvnw -pl spark -Dsuites="org.apache.spark.sql.comet.CometTPCDSV2_7_PlanStabilitySuite" test +SPARK_GENERATE_GOLDEN_FILES=1 ./mvnw -pl spark -Dsuites="org.apache.spark.sql.comet.CometTPCDSV2_7_PlanStabilitySuite" -Pspark-4.0 -nsu test ``` ## Benchmark diff --git a/docs/source/user-guide/configs.md b/docs/source/user-guide/configs.md index eb349b3493..104f29ce80 100644 --- a/docs/source/user-guide/configs.md +++ b/docs/source/user-guide/configs.md @@ -23,7 +23,6 @@ Comet provides the following configuration settings. | Config | Description | Default Value | |--------|-------------|---------------| -| spark.comet.ansi.enabled | Comet does not respect ANSI mode in most cases and by default will not accelerate queries when ansi mode is enabled. Enable this setting to test Comet's experimental support for ANSI mode. This should not be used in production. | false | | spark.comet.batchSize | The columnar batch size, i.e., the maximum number of rows that a batch can contain. | 8192 | | spark.comet.cast.allowIncompatible | Comet is not currently fully compatible with Spark for all cast operations. Set this config to true to allow them anyway. See compatibility guide for more information. | false | | spark.comet.columnar.shuffle.async.enabled | Whether to enable asynchronous shuffle for Arrow-based shuffle. By default, this config is false. | false | diff --git a/spark/src/main/scala/org/apache/comet/CometSparkSessionExtensions.scala b/spark/src/main/scala/org/apache/comet/CometSparkSessionExtensions.scala index 168d2bb52d..d6ec85f5be 100644 --- a/spark/src/main/scala/org/apache/comet/CometSparkSessionExtensions.scala +++ b/spark/src/main/scala/org/apache/comet/CometSparkSessionExtensions.scala @@ -1030,6 +1030,10 @@ object CometSparkSessionExtensions extends Logging { org.apache.spark.SPARK_VERSION >= "3.4" } + def isSpark40Plus: Boolean = { + org.apache.spark.SPARK_VERSION >= "4.0" + } + /** Calculates required memory overhead in MB per executor process for Comet. */ def getCometMemoryOverheadInMiB(sparkConf: SparkConf): Long = { // `spark.executor.memory` default value is 1g diff --git a/spark/src/main/scala/org/apache/comet/serde/QueryPlanSerde.scala b/spark/src/main/scala/org/apache/comet/serde/QueryPlanSerde.scala index 5fe290cf65..439ec4ebb5 100644 --- a/spark/src/main/scala/org/apache/comet/serde/QueryPlanSerde.scala +++ b/spark/src/main/scala/org/apache/comet/serde/QueryPlanSerde.scala @@ -2244,7 +2244,8 @@ object QueryPlanSerde extends Logging with ShimQueryPlanSerde with CometExprShim } def nullIfWhenPrimitive(expression: Expression): Expression = if (isPrimitive(expression)) { - new NullIf(expression, Literal.default(expression.dataType)).child + val zero = Literal.default(expression.dataType) + If(EqualTo(expression, zero), Literal.create(null, expression.dataType), expression) } else { expression } diff --git a/spark/src/main/scala/org/apache/spark/sql/ExtendedExplainGenerator.scala b/spark/src/main/spark-3.x/org/apache/spark/sql/ExtendedExplainGenerator.scala similarity index 100% rename from spark/src/main/scala/org/apache/spark/sql/ExtendedExplainGenerator.scala rename to spark/src/main/spark-3.x/org/apache/spark/sql/ExtendedExplainGenerator.scala diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q1/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q1/explain.txt new file mode 100644 index 0000000000..762f3a4f6a --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q1/explain.txt @@ -0,0 +1,274 @@ +== Physical Plan == +TakeOrderedAndProject (40) ++- * Project (39) + +- * BroadcastHashJoin Inner BuildRight (38) + :- * Project (33) + : +- * BroadcastHashJoin Inner BuildRight (32) + : :- * Project (26) + : : +- * BroadcastHashJoin Inner BuildRight (25) + : : :- * Filter (10) + : : : +- * HashAggregate (9) + : : : +- Exchange (8) + : : : +- * HashAggregate (7) + : : : +- * Project (6) + : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.store_returns (1) + : : : +- ReusedExchange (4) + : : +- BroadcastExchange (24) + : : +- * Filter (23) + : : +- * HashAggregate (22) + : : +- Exchange (21) + : : +- * HashAggregate (20) + : : +- * HashAggregate (19) + : : +- Exchange (18) + : : +- * HashAggregate (17) + : : +- * Project (16) + : : +- * BroadcastHashJoin Inner BuildRight (15) + : : :- * ColumnarToRow (13) + : : : +- CometFilter (12) + : : : +- CometScan parquet spark_catalog.default.store_returns (11) + : : +- ReusedExchange (14) + : +- BroadcastExchange (31) + : +- * ColumnarToRow (30) + : +- CometProject (29) + : +- CometFilter (28) + : +- CometScan parquet spark_catalog.default.store (27) + +- BroadcastExchange (37) + +- * ColumnarToRow (36) + +- CometFilter (35) + +- CometScan parquet spark_catalog.default.customer (34) + + +(1) Scan parquet spark_catalog.default.store_returns +Output [4]: [sr_customer_sk#1, sr_store_sk#2, sr_return_amt#3, sr_returned_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(sr_returned_date_sk#4), dynamicpruningexpression(sr_returned_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(sr_store_sk), IsNotNull(sr_customer_sk)] +ReadSchema: struct + +(2) CometFilter +Input [4]: [sr_customer_sk#1, sr_store_sk#2, sr_return_amt#3, sr_returned_date_sk#4] +Condition : (isnotnull(sr_store_sk#2) AND isnotnull(sr_customer_sk#1)) + +(3) ColumnarToRow [codegen id : 2] +Input [4]: [sr_customer_sk#1, sr_store_sk#2, sr_return_amt#3, sr_returned_date_sk#4] + +(4) ReusedExchange [Reuses operator id: 45] +Output [1]: [d_date_sk#6] + +(5) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [sr_returned_date_sk#4] +Right keys [1]: [d_date_sk#6] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 2] +Output [3]: [sr_customer_sk#1, sr_store_sk#2, sr_return_amt#3] +Input [5]: [sr_customer_sk#1, sr_store_sk#2, sr_return_amt#3, sr_returned_date_sk#4, d_date_sk#6] + +(7) HashAggregate [codegen id : 2] +Input [3]: [sr_customer_sk#1, sr_store_sk#2, sr_return_amt#3] +Keys [2]: [sr_customer_sk#1, sr_store_sk#2] +Functions [1]: [partial_sum(UnscaledValue(sr_return_amt#3))] +Aggregate Attributes [1]: [sum#7] +Results [3]: [sr_customer_sk#1, sr_store_sk#2, sum#8] + +(8) Exchange +Input [3]: [sr_customer_sk#1, sr_store_sk#2, sum#8] +Arguments: hashpartitioning(sr_customer_sk#1, sr_store_sk#2, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(9) HashAggregate [codegen id : 9] +Input [3]: [sr_customer_sk#1, sr_store_sk#2, sum#8] +Keys [2]: [sr_customer_sk#1, sr_store_sk#2] +Functions [1]: [sum(UnscaledValue(sr_return_amt#3))] +Aggregate Attributes [1]: [sum(UnscaledValue(sr_return_amt#3))#9] +Results [3]: [sr_customer_sk#1 AS ctr_customer_sk#10, sr_store_sk#2 AS ctr_store_sk#11, MakeDecimal(sum(UnscaledValue(sr_return_amt#3))#9,17,2) AS ctr_total_return#12] + +(10) Filter [codegen id : 9] +Input [3]: [ctr_customer_sk#10, ctr_store_sk#11, ctr_total_return#12] +Condition : isnotnull(ctr_total_return#12) + +(11) Scan parquet spark_catalog.default.store_returns +Output [4]: [sr_customer_sk#13, sr_store_sk#14, sr_return_amt#15, sr_returned_date_sk#16] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(sr_returned_date_sk#16), dynamicpruningexpression(sr_returned_date_sk#16 IN dynamicpruning#17)] +PushedFilters: [IsNotNull(sr_store_sk)] +ReadSchema: struct + +(12) CometFilter +Input [4]: [sr_customer_sk#13, sr_store_sk#14, sr_return_amt#15, sr_returned_date_sk#16] +Condition : isnotnull(sr_store_sk#14) + +(13) ColumnarToRow [codegen id : 4] +Input [4]: [sr_customer_sk#13, sr_store_sk#14, sr_return_amt#15, sr_returned_date_sk#16] + +(14) ReusedExchange [Reuses operator id: 45] +Output [1]: [d_date_sk#18] + +(15) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [sr_returned_date_sk#16] +Right keys [1]: [d_date_sk#18] +Join type: Inner +Join condition: None + +(16) Project [codegen id : 4] +Output [3]: [sr_customer_sk#13, sr_store_sk#14, sr_return_amt#15] +Input [5]: [sr_customer_sk#13, sr_store_sk#14, sr_return_amt#15, sr_returned_date_sk#16, d_date_sk#18] + +(17) HashAggregate [codegen id : 4] +Input [3]: [sr_customer_sk#13, sr_store_sk#14, sr_return_amt#15] +Keys [2]: [sr_customer_sk#13, sr_store_sk#14] +Functions [1]: [partial_sum(UnscaledValue(sr_return_amt#15))] +Aggregate Attributes [1]: [sum#19] +Results [3]: [sr_customer_sk#13, sr_store_sk#14, sum#20] + +(18) Exchange +Input [3]: [sr_customer_sk#13, sr_store_sk#14, sum#20] +Arguments: hashpartitioning(sr_customer_sk#13, sr_store_sk#14, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(19) HashAggregate [codegen id : 5] +Input [3]: [sr_customer_sk#13, sr_store_sk#14, sum#20] +Keys [2]: [sr_customer_sk#13, sr_store_sk#14] +Functions [1]: [sum(UnscaledValue(sr_return_amt#15))] +Aggregate Attributes [1]: [sum(UnscaledValue(sr_return_amt#15))#9] +Results [2]: [sr_store_sk#14 AS ctr_store_sk#21, MakeDecimal(sum(UnscaledValue(sr_return_amt#15))#9,17,2) AS ctr_total_return#22] + +(20) HashAggregate [codegen id : 5] +Input [2]: [ctr_store_sk#21, ctr_total_return#22] +Keys [1]: [ctr_store_sk#21] +Functions [1]: [partial_avg(ctr_total_return#22)] +Aggregate Attributes [2]: [sum#23, count#24] +Results [3]: [ctr_store_sk#21, sum#25, count#26] + +(21) Exchange +Input [3]: [ctr_store_sk#21, sum#25, count#26] +Arguments: hashpartitioning(ctr_store_sk#21, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(22) HashAggregate [codegen id : 6] +Input [3]: [ctr_store_sk#21, sum#25, count#26] +Keys [1]: [ctr_store_sk#21] +Functions [1]: [avg(ctr_total_return#22)] +Aggregate Attributes [1]: [avg(ctr_total_return#22)#27] +Results [2]: [(avg(ctr_total_return#22)#27 * 1.2) AS (avg(ctr_total_return) * 1.2)#28, ctr_store_sk#21] + +(23) Filter [codegen id : 6] +Input [2]: [(avg(ctr_total_return) * 1.2)#28, ctr_store_sk#21] +Condition : isnotnull((avg(ctr_total_return) * 1.2)#28) + +(24) BroadcastExchange +Input [2]: [(avg(ctr_total_return) * 1.2)#28, ctr_store_sk#21] +Arguments: HashedRelationBroadcastMode(List(cast(input[1, int, true] as bigint)),false), [plan_id=4] + +(25) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ctr_store_sk#11] +Right keys [1]: [ctr_store_sk#21] +Join type: Inner +Join condition: (cast(ctr_total_return#12 as decimal(24,7)) > (avg(ctr_total_return) * 1.2)#28) + +(26) Project [codegen id : 9] +Output [2]: [ctr_customer_sk#10, ctr_store_sk#11] +Input [5]: [ctr_customer_sk#10, ctr_store_sk#11, ctr_total_return#12, (avg(ctr_total_return) * 1.2)#28, ctr_store_sk#21] + +(27) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#29, s_state#30] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_state), EqualTo(s_state,TN), IsNotNull(s_store_sk)] +ReadSchema: struct + +(28) CometFilter +Input [2]: [s_store_sk#29, s_state#30] +Condition : ((isnotnull(s_state#30) AND (s_state#30 = TN)) AND isnotnull(s_store_sk#29)) + +(29) CometProject +Input [2]: [s_store_sk#29, s_state#30] +Arguments: [s_store_sk#29], [s_store_sk#29] + +(30) ColumnarToRow [codegen id : 7] +Input [1]: [s_store_sk#29] + +(31) BroadcastExchange +Input [1]: [s_store_sk#29] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +(32) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ctr_store_sk#11] +Right keys [1]: [s_store_sk#29] +Join type: Inner +Join condition: None + +(33) Project [codegen id : 9] +Output [1]: [ctr_customer_sk#10] +Input [3]: [ctr_customer_sk#10, ctr_store_sk#11, s_store_sk#29] + +(34) Scan parquet spark_catalog.default.customer +Output [2]: [c_customer_sk#31, c_customer_id#32] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk)] +ReadSchema: struct + +(35) CometFilter +Input [2]: [c_customer_sk#31, c_customer_id#32] +Condition : isnotnull(c_customer_sk#31) + +(36) ColumnarToRow [codegen id : 8] +Input [2]: [c_customer_sk#31, c_customer_id#32] + +(37) BroadcastExchange +Input [2]: [c_customer_sk#31, c_customer_id#32] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6] + +(38) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ctr_customer_sk#10] +Right keys [1]: [c_customer_sk#31] +Join type: Inner +Join condition: None + +(39) Project [codegen id : 9] +Output [1]: [c_customer_id#32] +Input [3]: [ctr_customer_sk#10, c_customer_sk#31, c_customer_id#32] + +(40) TakeOrderedAndProject +Input [1]: [c_customer_id#32] +Arguments: 100, [c_customer_id#32 ASC NULLS FIRST], [c_customer_id#32] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = sr_returned_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (45) ++- * ColumnarToRow (44) + +- CometProject (43) + +- CometFilter (42) + +- CometScan parquet spark_catalog.default.date_dim (41) + + +(41) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#6, d_year#33] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2000), IsNotNull(d_date_sk)] +ReadSchema: struct + +(42) CometFilter +Input [2]: [d_date_sk#6, d_year#33] +Condition : ((isnotnull(d_year#33) AND (d_year#33 = 2000)) AND isnotnull(d_date_sk#6)) + +(43) CometProject +Input [2]: [d_date_sk#6, d_year#33] +Arguments: [d_date_sk#6], [d_date_sk#6] + +(44) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#6] + +(45) BroadcastExchange +Input [1]: [d_date_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +Subquery:2 Hosting operator id = 11 Hosting Expression = sr_returned_date_sk#16 IN dynamicpruning#5 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q1/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q1/simplified.txt new file mode 100644 index 0000000000..688fb69a8e --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q1/simplified.txt @@ -0,0 +1,68 @@ +TakeOrderedAndProject [c_customer_id] + WholeStageCodegen (9) + Project [c_customer_id] + BroadcastHashJoin [ctr_customer_sk,c_customer_sk] + Project [ctr_customer_sk] + BroadcastHashJoin [ctr_store_sk,s_store_sk] + Project [ctr_customer_sk,ctr_store_sk] + BroadcastHashJoin [ctr_store_sk,ctr_store_sk,ctr_total_return,(avg(ctr_total_return) * 1.2)] + Filter [ctr_total_return] + HashAggregate [sr_customer_sk,sr_store_sk,sum] [sum(UnscaledValue(sr_return_amt)),ctr_customer_sk,ctr_store_sk,ctr_total_return,sum] + InputAdapter + Exchange [sr_customer_sk,sr_store_sk] #1 + WholeStageCodegen (2) + HashAggregate [sr_customer_sk,sr_store_sk,sr_return_amt] [sum,sum] + Project [sr_customer_sk,sr_store_sk,sr_return_amt] + BroadcastHashJoin [sr_returned_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [sr_store_sk,sr_customer_sk] + CometScan parquet spark_catalog.default.store_returns [sr_customer_sk,sr_store_sk,sr_return_amt,sr_returned_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (6) + Filter [(avg(ctr_total_return) * 1.2)] + HashAggregate [ctr_store_sk,sum,count] [avg(ctr_total_return),(avg(ctr_total_return) * 1.2),sum,count] + InputAdapter + Exchange [ctr_store_sk] #4 + WholeStageCodegen (5) + HashAggregate [ctr_store_sk,ctr_total_return] [sum,count,sum,count] + HashAggregate [sr_customer_sk,sr_store_sk,sum] [sum(UnscaledValue(sr_return_amt)),ctr_store_sk,ctr_total_return,sum] + InputAdapter + Exchange [sr_customer_sk,sr_store_sk] #5 + WholeStageCodegen (4) + HashAggregate [sr_customer_sk,sr_store_sk,sr_return_amt] [sum,sum] + Project [sr_customer_sk,sr_store_sk,sr_return_amt] + BroadcastHashJoin [sr_returned_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [sr_store_sk] + CometScan parquet spark_catalog.default.store_returns [sr_customer_sk,sr_store_sk,sr_return_amt,sr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (7) + ColumnarToRow + InputAdapter + CometProject [s_store_sk] + CometFilter [s_state,s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk,s_state] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (8) + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q10/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q10/explain.txt new file mode 100644 index 0000000000..15490b87d7 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q10/explain.txt @@ -0,0 +1,286 @@ +== Physical Plan == +TakeOrderedAndProject (43) ++- * HashAggregate (42) + +- Exchange (41) + +- * HashAggregate (40) + +- * Project (39) + +- * BroadcastHashJoin Inner BuildRight (38) + :- * Project (33) + : +- * BroadcastHashJoin Inner BuildRight (32) + : :- * Project (26) + : : +- * Filter (25) + : : +- * BroadcastHashJoin ExistenceJoin(exists#1) BuildRight (24) + : : :- * BroadcastHashJoin ExistenceJoin(exists#2) BuildRight (17) + : : : :- * BroadcastHashJoin LeftSemi BuildRight (10) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) + : : : : : +- CometScan parquet spark_catalog.default.customer (1) + : : : : +- BroadcastExchange (9) + : : : : +- * Project (8) + : : : : +- * BroadcastHashJoin Inner BuildRight (7) + : : : : :- * ColumnarToRow (5) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (4) + : : : : +- ReusedExchange (6) + : : : +- BroadcastExchange (16) + : : : +- * Project (15) + : : : +- * BroadcastHashJoin Inner BuildRight (14) + : : : :- * ColumnarToRow (12) + : : : : +- CometScan parquet spark_catalog.default.web_sales (11) + : : : +- ReusedExchange (13) + : : +- BroadcastExchange (23) + : : +- * Project (22) + : : +- * BroadcastHashJoin Inner BuildRight (21) + : : :- * ColumnarToRow (19) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (18) + : : +- ReusedExchange (20) + : +- BroadcastExchange (31) + : +- * ColumnarToRow (30) + : +- CometProject (29) + : +- CometFilter (28) + : +- CometScan parquet spark_catalog.default.customer_address (27) + +- BroadcastExchange (37) + +- * ColumnarToRow (36) + +- CometFilter (35) + +- CometScan parquet spark_catalog.default.customer_demographics (34) + + +(1) Scan parquet spark_catalog.default.customer +Output [3]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_current_addr_sk), IsNotNull(c_current_cdemo_sk)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5] +Condition : (isnotnull(c_current_addr_sk#5) AND isnotnull(c_current_cdemo_sk#4)) + +(3) ColumnarToRow [codegen id : 9] +Input [3]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5] + +(4) Scan parquet spark_catalog.default.store_sales +Output [2]: [ss_customer_sk#6, ss_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sold_date_sk#7 IN dynamicpruning#8)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 2] +Input [2]: [ss_customer_sk#6, ss_sold_date_sk#7] + +(6) ReusedExchange [Reuses operator id: 48] +Output [1]: [d_date_sk#9] + +(7) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [ss_sold_date_sk#7] +Right keys [1]: [d_date_sk#9] +Join type: Inner +Join condition: None + +(8) Project [codegen id : 2] +Output [1]: [ss_customer_sk#6] +Input [3]: [ss_customer_sk#6, ss_sold_date_sk#7, d_date_sk#9] + +(9) BroadcastExchange +Input [1]: [ss_customer_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(10) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_customer_sk#3] +Right keys [1]: [ss_customer_sk#6] +Join type: LeftSemi +Join condition: None + +(11) Scan parquet spark_catalog.default.web_sales +Output [2]: [ws_bill_customer_sk#10, ws_sold_date_sk#11] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#11), dynamicpruningexpression(ws_sold_date_sk#11 IN dynamicpruning#12)] +ReadSchema: struct + +(12) ColumnarToRow [codegen id : 4] +Input [2]: [ws_bill_customer_sk#10, ws_sold_date_sk#11] + +(13) ReusedExchange [Reuses operator id: 48] +Output [1]: [d_date_sk#13] + +(14) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ws_sold_date_sk#11] +Right keys [1]: [d_date_sk#13] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 4] +Output [1]: [ws_bill_customer_sk#10] +Input [3]: [ws_bill_customer_sk#10, ws_sold_date_sk#11, d_date_sk#13] + +(16) BroadcastExchange +Input [1]: [ws_bill_customer_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(17) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_customer_sk#3] +Right keys [1]: [ws_bill_customer_sk#10] +Join type: ExistenceJoin(exists#2) +Join condition: None + +(18) Scan parquet spark_catalog.default.catalog_sales +Output [2]: [cs_ship_customer_sk#14, cs_sold_date_sk#15] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#15), dynamicpruningexpression(cs_sold_date_sk#15 IN dynamicpruning#16)] +ReadSchema: struct + +(19) ColumnarToRow [codegen id : 6] +Input [2]: [cs_ship_customer_sk#14, cs_sold_date_sk#15] + +(20) ReusedExchange [Reuses operator id: 48] +Output [1]: [d_date_sk#17] + +(21) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [cs_sold_date_sk#15] +Right keys [1]: [d_date_sk#17] +Join type: Inner +Join condition: None + +(22) Project [codegen id : 6] +Output [1]: [cs_ship_customer_sk#14] +Input [3]: [cs_ship_customer_sk#14, cs_sold_date_sk#15, d_date_sk#17] + +(23) BroadcastExchange +Input [1]: [cs_ship_customer_sk#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_customer_sk#3] +Right keys [1]: [cs_ship_customer_sk#14] +Join type: ExistenceJoin(exists#1) +Join condition: None + +(25) Filter [codegen id : 9] +Input [5]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5, exists#2, exists#1] +Condition : (exists#2 OR exists#1) + +(26) Project [codegen id : 9] +Output [2]: [c_current_cdemo_sk#4, c_current_addr_sk#5] +Input [5]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5, exists#2, exists#1] + +(27) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#18, ca_county#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [In(ca_county, [Dona Ana County,Jefferson County,La Porte County,Rush County,Toole County]), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(28) CometFilter +Input [2]: [ca_address_sk#18, ca_county#19] +Condition : (ca_county#19 IN (Rush County,Toole County,Jefferson County,Dona Ana County,La Porte County) AND isnotnull(ca_address_sk#18)) + +(29) CometProject +Input [2]: [ca_address_sk#18, ca_county#19] +Arguments: [ca_address_sk#18], [ca_address_sk#18] + +(30) ColumnarToRow [codegen id : 7] +Input [1]: [ca_address_sk#18] + +(31) BroadcastExchange +Input [1]: [ca_address_sk#18] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(32) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_current_addr_sk#5] +Right keys [1]: [ca_address_sk#18] +Join type: Inner +Join condition: None + +(33) Project [codegen id : 9] +Output [1]: [c_current_cdemo_sk#4] +Input [3]: [c_current_cdemo_sk#4, c_current_addr_sk#5, ca_address_sk#18] + +(34) Scan parquet spark_catalog.default.customer_demographics +Output [9]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(35) CometFilter +Input [9]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] +Condition : isnotnull(cd_demo_sk#20) + +(36) ColumnarToRow [codegen id : 8] +Input [9]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] + +(37) BroadcastExchange +Input [9]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(38) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_current_cdemo_sk#4] +Right keys [1]: [cd_demo_sk#20] +Join type: Inner +Join condition: None + +(39) Project [codegen id : 9] +Output [8]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] +Input [10]: [c_current_cdemo_sk#4, cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] + +(40) HashAggregate [codegen id : 9] +Input [8]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] +Keys [8]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#29] +Results [9]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28, count#30] + +(41) Exchange +Input [9]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28, count#30] +Arguments: hashpartitioning(cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(42) HashAggregate [codegen id : 10] +Input [9]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28, count#30] +Keys [8]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#31] +Results [14]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, count(1)#31 AS cnt1#32, cd_purchase_estimate#24, count(1)#31 AS cnt2#33, cd_credit_rating#25, count(1)#31 AS cnt3#34, cd_dep_count#26, count(1)#31 AS cnt4#35, cd_dep_employed_count#27, count(1)#31 AS cnt5#36, cd_dep_college_count#28, count(1)#31 AS cnt6#37] + +(43) TakeOrderedAndProject +Input [14]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, cnt1#32, cd_purchase_estimate#24, cnt2#33, cd_credit_rating#25, cnt3#34, cd_dep_count#26, cnt4#35, cd_dep_employed_count#27, cnt5#36, cd_dep_college_count#28, cnt6#37] +Arguments: 100, [cd_gender#21 ASC NULLS FIRST, cd_marital_status#22 ASC NULLS FIRST, cd_education_status#23 ASC NULLS FIRST, cd_purchase_estimate#24 ASC NULLS FIRST, cd_credit_rating#25 ASC NULLS FIRST, cd_dep_count#26 ASC NULLS FIRST, cd_dep_employed_count#27 ASC NULLS FIRST, cd_dep_college_count#28 ASC NULLS FIRST], [cd_gender#21, cd_marital_status#22, cd_education_status#23, cnt1#32, cd_purchase_estimate#24, cnt2#33, cd_credit_rating#25, cnt3#34, cd_dep_count#26, cnt4#35, cd_dep_employed_count#27, cnt5#36, cd_dep_college_count#28, cnt6#37] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (48) ++- * ColumnarToRow (47) + +- CometProject (46) + +- CometFilter (45) + +- CometScan parquet spark_catalog.default.date_dim (44) + + +(44) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#9, d_year#38, d_moy#39] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2002), GreaterThanOrEqual(d_moy,1), LessThanOrEqual(d_moy,4), IsNotNull(d_date_sk)] +ReadSchema: struct + +(45) CometFilter +Input [3]: [d_date_sk#9, d_year#38, d_moy#39] +Condition : (((((isnotnull(d_year#38) AND isnotnull(d_moy#39)) AND (d_year#38 = 2002)) AND (d_moy#39 >= 1)) AND (d_moy#39 <= 4)) AND isnotnull(d_date_sk#9)) + +(46) CometProject +Input [3]: [d_date_sk#9, d_year#38, d_moy#39] +Arguments: [d_date_sk#9], [d_date_sk#9] + +(47) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#9] + +(48) BroadcastExchange +Input [1]: [d_date_sk#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +Subquery:2 Hosting operator id = 11 Hosting Expression = ws_sold_date_sk#11 IN dynamicpruning#8 + +Subquery:3 Hosting operator id = 18 Hosting Expression = cs_sold_date_sk#15 IN dynamicpruning#8 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q10/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q10/simplified.txt new file mode 100644 index 0000000000..89893c831e --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q10/simplified.txt @@ -0,0 +1,75 @@ +TakeOrderedAndProject [cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating,cd_dep_count,cd_dep_employed_count,cd_dep_college_count,cnt1,cnt2,cnt3,cnt4,cnt5,cnt6] + WholeStageCodegen (10) + HashAggregate [cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating,cd_dep_count,cd_dep_employed_count,cd_dep_college_count,count] [count(1),cnt1,cnt2,cnt3,cnt4,cnt5,cnt6,count] + InputAdapter + Exchange [cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] #1 + WholeStageCodegen (9) + HashAggregate [cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] [count,count] + Project [cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk] + Project [c_current_cdemo_sk] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [c_current_cdemo_sk,c_current_addr_sk] + Filter [exists,exists] + BroadcastHashJoin [c_customer_sk,cs_ship_customer_sk] + BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + ColumnarToRow + InputAdapter + CometFilter [c_current_addr_sk,c_current_cdemo_sk] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (2) + Project [ss_customer_sk] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_moy,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (4) + Project [ws_bill_customer_sk] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (6) + Project [cs_ship_customer_sk] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_ship_customer_sk,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (7) + ColumnarToRow + InputAdapter + CometProject [ca_address_sk] + CometFilter [ca_county,ca_address_sk] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_county] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (8) + ColumnarToRow + InputAdapter + CometFilter [cd_demo_sk] + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q11/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q11/explain.txt new file mode 100644 index 0000000000..c663d46886 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q11/explain.txt @@ -0,0 +1,482 @@ +== Physical Plan == +TakeOrderedAndProject (72) ++- * Project (71) + +- * BroadcastHashJoin Inner BuildRight (70) + :- * Project (53) + : +- * BroadcastHashJoin Inner BuildRight (52) + : :- * Project (34) + : : +- * BroadcastHashJoin Inner BuildRight (33) + : : :- * Filter (16) + : : : +- * HashAggregate (15) + : : : +- Exchange (14) + : : : +- * HashAggregate (13) + : : : +- * Project (12) + : : : +- * BroadcastHashJoin Inner BuildRight (11) + : : : :- * Project (9) + : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) + : : : : : +- CometScan parquet spark_catalog.default.customer (1) + : : : : +- BroadcastExchange (7) + : : : : +- * ColumnarToRow (6) + : : : : +- CometFilter (5) + : : : : +- CometScan parquet spark_catalog.default.store_sales (4) + : : : +- ReusedExchange (10) + : : +- BroadcastExchange (32) + : : +- * HashAggregate (31) + : : +- Exchange (30) + : : +- * HashAggregate (29) + : : +- * Project (28) + : : +- * BroadcastHashJoin Inner BuildRight (27) + : : :- * Project (25) + : : : +- * BroadcastHashJoin Inner BuildRight (24) + : : : :- * ColumnarToRow (19) + : : : : +- CometFilter (18) + : : : : +- CometScan parquet spark_catalog.default.customer (17) + : : : +- BroadcastExchange (23) + : : : +- * ColumnarToRow (22) + : : : +- CometFilter (21) + : : : +- CometScan parquet spark_catalog.default.store_sales (20) + : : +- ReusedExchange (26) + : +- BroadcastExchange (51) + : +- * Filter (50) + : +- * HashAggregate (49) + : +- Exchange (48) + : +- * HashAggregate (47) + : +- * Project (46) + : +- * BroadcastHashJoin Inner BuildRight (45) + : :- * Project (43) + : : +- * BroadcastHashJoin Inner BuildRight (42) + : : :- * ColumnarToRow (37) + : : : +- CometFilter (36) + : : : +- CometScan parquet spark_catalog.default.customer (35) + : : +- BroadcastExchange (41) + : : +- * ColumnarToRow (40) + : : +- CometFilter (39) + : : +- CometScan parquet spark_catalog.default.web_sales (38) + : +- ReusedExchange (44) + +- BroadcastExchange (69) + +- * HashAggregate (68) + +- Exchange (67) + +- * HashAggregate (66) + +- * Project (65) + +- * BroadcastHashJoin Inner BuildRight (64) + :- * Project (62) + : +- * BroadcastHashJoin Inner BuildRight (61) + : :- * ColumnarToRow (56) + : : +- CometFilter (55) + : : +- CometScan parquet spark_catalog.default.customer (54) + : +- BroadcastExchange (60) + : +- * ColumnarToRow (59) + : +- CometFilter (58) + : +- CometScan parquet spark_catalog.default.web_sales (57) + +- ReusedExchange (63) + + +(1) Scan parquet spark_catalog.default.customer +Output [8]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(2) CometFilter +Input [8]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8] +Condition : (isnotnull(c_customer_sk#1) AND isnotnull(c_customer_id#2)) + +(3) ColumnarToRow [codegen id : 3] +Input [8]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8] + +(4) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#12), dynamicpruningexpression(ss_sold_date_sk#12 IN dynamicpruning#13)] +PushedFilters: [IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(5) CometFilter +Input [4]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12] +Condition : isnotnull(ss_customer_sk#9) + +(6) ColumnarToRow [codegen id : 1] +Input [4]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12] + +(7) BroadcastExchange +Input [4]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [c_customer_sk#1] +Right keys [1]: [ss_customer_sk#9] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 3] +Output [10]: [c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12] +Input [12]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12] + +(10) ReusedExchange [Reuses operator id: 76] +Output [2]: [d_date_sk#14, d_year#15] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_sold_date_sk#12] +Right keys [1]: [d_date_sk#14] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [10]: [c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, ss_ext_discount_amt#10, ss_ext_list_price#11, d_year#15] +Input [12]: [c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12, d_date_sk#14, d_year#15] + +(13) HashAggregate [codegen id : 3] +Input [10]: [c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, ss_ext_discount_amt#10, ss_ext_list_price#11, d_year#15] +Keys [8]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#15, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8] +Functions [1]: [partial_sum(UnscaledValue((ss_ext_list_price#11 - ss_ext_discount_amt#10)))] +Aggregate Attributes [1]: [sum#16] +Results [9]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#15, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, sum#17] + +(14) Exchange +Input [9]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#15, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, sum#17] +Arguments: hashpartitioning(c_customer_id#2, c_first_name#3, c_last_name#4, d_year#15, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 16] +Input [9]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#15, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, sum#17] +Keys [8]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#15, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8] +Functions [1]: [sum(UnscaledValue((ss_ext_list_price#11 - ss_ext_discount_amt#10)))] +Aggregate Attributes [1]: [sum(UnscaledValue((ss_ext_list_price#11 - ss_ext_discount_amt#10)))#18] +Results [2]: [c_customer_id#2 AS customer_id#19, MakeDecimal(sum(UnscaledValue((ss_ext_list_price#11 - ss_ext_discount_amt#10)))#18,18,2) AS year_total#20] + +(16) Filter [codegen id : 16] +Input [2]: [customer_id#19, year_total#20] +Condition : (isnotnull(year_total#20) AND (year_total#20 > 0.00)) + +(17) Scan parquet spark_catalog.default.customer +Output [8]: [c_customer_sk#21, c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(18) CometFilter +Input [8]: [c_customer_sk#21, c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28] +Condition : (isnotnull(c_customer_sk#21) AND isnotnull(c_customer_id#22)) + +(19) ColumnarToRow [codegen id : 6] +Input [8]: [c_customer_sk#21, c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28] + +(20) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_customer_sk#29, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#32), dynamicpruningexpression(ss_sold_date_sk#32 IN dynamicpruning#33)] +PushedFilters: [IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(21) CometFilter +Input [4]: [ss_customer_sk#29, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32] +Condition : isnotnull(ss_customer_sk#29) + +(22) ColumnarToRow [codegen id : 4] +Input [4]: [ss_customer_sk#29, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32] + +(23) BroadcastExchange +Input [4]: [ss_customer_sk#29, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [c_customer_sk#21] +Right keys [1]: [ss_customer_sk#29] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 6] +Output [10]: [c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32] +Input [12]: [c_customer_sk#21, c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, ss_customer_sk#29, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32] + +(26) ReusedExchange [Reuses operator id: 80] +Output [2]: [d_date_sk#34, d_year#35] + +(27) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_sold_date_sk#32] +Right keys [1]: [d_date_sk#34] +Join type: Inner +Join condition: None + +(28) Project [codegen id : 6] +Output [10]: [c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, ss_ext_discount_amt#30, ss_ext_list_price#31, d_year#35] +Input [12]: [c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32, d_date_sk#34, d_year#35] + +(29) HashAggregate [codegen id : 6] +Input [10]: [c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, ss_ext_discount_amt#30, ss_ext_list_price#31, d_year#35] +Keys [8]: [c_customer_id#22, c_first_name#23, c_last_name#24, d_year#35, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28] +Functions [1]: [partial_sum(UnscaledValue((ss_ext_list_price#31 - ss_ext_discount_amt#30)))] +Aggregate Attributes [1]: [sum#36] +Results [9]: [c_customer_id#22, c_first_name#23, c_last_name#24, d_year#35, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, sum#37] + +(30) Exchange +Input [9]: [c_customer_id#22, c_first_name#23, c_last_name#24, d_year#35, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, sum#37] +Arguments: hashpartitioning(c_customer_id#22, c_first_name#23, c_last_name#24, d_year#35, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(31) HashAggregate [codegen id : 7] +Input [9]: [c_customer_id#22, c_first_name#23, c_last_name#24, d_year#35, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, sum#37] +Keys [8]: [c_customer_id#22, c_first_name#23, c_last_name#24, d_year#35, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28] +Functions [1]: [sum(UnscaledValue((ss_ext_list_price#31 - ss_ext_discount_amt#30)))] +Aggregate Attributes [1]: [sum(UnscaledValue((ss_ext_list_price#31 - ss_ext_discount_amt#30)))#18] +Results [3]: [c_customer_id#22 AS customer_id#38, c_preferred_cust_flag#25 AS customer_preferred_cust_flag#39, MakeDecimal(sum(UnscaledValue((ss_ext_list_price#31 - ss_ext_discount_amt#30)))#18,18,2) AS year_total#40] + +(32) BroadcastExchange +Input [3]: [customer_id#38, customer_preferred_cust_flag#39, year_total#40] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=5] + +(33) BroadcastHashJoin [codegen id : 16] +Left keys [1]: [customer_id#19] +Right keys [1]: [customer_id#38] +Join type: Inner +Join condition: None + +(34) Project [codegen id : 16] +Output [4]: [customer_id#19, year_total#20, customer_preferred_cust_flag#39, year_total#40] +Input [5]: [customer_id#19, year_total#20, customer_id#38, customer_preferred_cust_flag#39, year_total#40] + +(35) Scan parquet spark_catalog.default.customer +Output [8]: [c_customer_sk#41, c_customer_id#42, c_first_name#43, c_last_name#44, c_preferred_cust_flag#45, c_birth_country#46, c_login#47, c_email_address#48] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(36) CometFilter +Input [8]: [c_customer_sk#41, c_customer_id#42, c_first_name#43, c_last_name#44, c_preferred_cust_flag#45, c_birth_country#46, c_login#47, c_email_address#48] +Condition : (isnotnull(c_customer_sk#41) AND isnotnull(c_customer_id#42)) + +(37) ColumnarToRow [codegen id : 10] +Input [8]: [c_customer_sk#41, c_customer_id#42, c_first_name#43, c_last_name#44, c_preferred_cust_flag#45, c_birth_country#46, c_login#47, c_email_address#48] + +(38) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_bill_customer_sk#49, ws_ext_discount_amt#50, ws_ext_list_price#51, ws_sold_date_sk#52] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#52), dynamicpruningexpression(ws_sold_date_sk#52 IN dynamicpruning#53)] +PushedFilters: [IsNotNull(ws_bill_customer_sk)] +ReadSchema: struct + +(39) CometFilter +Input [4]: [ws_bill_customer_sk#49, ws_ext_discount_amt#50, ws_ext_list_price#51, ws_sold_date_sk#52] +Condition : isnotnull(ws_bill_customer_sk#49) + +(40) ColumnarToRow [codegen id : 8] +Input [4]: [ws_bill_customer_sk#49, ws_ext_discount_amt#50, ws_ext_list_price#51, ws_sold_date_sk#52] + +(41) BroadcastExchange +Input [4]: [ws_bill_customer_sk#49, ws_ext_discount_amt#50, ws_ext_list_price#51, ws_sold_date_sk#52] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6] + +(42) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [c_customer_sk#41] +Right keys [1]: [ws_bill_customer_sk#49] +Join type: Inner +Join condition: None + +(43) Project [codegen id : 10] +Output [10]: [c_customer_id#42, c_first_name#43, c_last_name#44, c_preferred_cust_flag#45, c_birth_country#46, c_login#47, c_email_address#48, ws_ext_discount_amt#50, ws_ext_list_price#51, ws_sold_date_sk#52] +Input [12]: [c_customer_sk#41, c_customer_id#42, c_first_name#43, c_last_name#44, c_preferred_cust_flag#45, c_birth_country#46, c_login#47, c_email_address#48, ws_bill_customer_sk#49, ws_ext_discount_amt#50, ws_ext_list_price#51, ws_sold_date_sk#52] + +(44) ReusedExchange [Reuses operator id: 76] +Output [2]: [d_date_sk#54, d_year#55] + +(45) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [ws_sold_date_sk#52] +Right keys [1]: [d_date_sk#54] +Join type: Inner +Join condition: None + +(46) Project [codegen id : 10] +Output [10]: [c_customer_id#42, c_first_name#43, c_last_name#44, c_preferred_cust_flag#45, c_birth_country#46, c_login#47, c_email_address#48, ws_ext_discount_amt#50, ws_ext_list_price#51, d_year#55] +Input [12]: [c_customer_id#42, c_first_name#43, c_last_name#44, c_preferred_cust_flag#45, c_birth_country#46, c_login#47, c_email_address#48, ws_ext_discount_amt#50, ws_ext_list_price#51, ws_sold_date_sk#52, d_date_sk#54, d_year#55] + +(47) HashAggregate [codegen id : 10] +Input [10]: [c_customer_id#42, c_first_name#43, c_last_name#44, c_preferred_cust_flag#45, c_birth_country#46, c_login#47, c_email_address#48, ws_ext_discount_amt#50, ws_ext_list_price#51, d_year#55] +Keys [8]: [c_customer_id#42, c_first_name#43, c_last_name#44, c_preferred_cust_flag#45, c_birth_country#46, c_login#47, c_email_address#48, d_year#55] +Functions [1]: [partial_sum(UnscaledValue((ws_ext_list_price#51 - ws_ext_discount_amt#50)))] +Aggregate Attributes [1]: [sum#56] +Results [9]: [c_customer_id#42, c_first_name#43, c_last_name#44, c_preferred_cust_flag#45, c_birth_country#46, c_login#47, c_email_address#48, d_year#55, sum#57] + +(48) Exchange +Input [9]: [c_customer_id#42, c_first_name#43, c_last_name#44, c_preferred_cust_flag#45, c_birth_country#46, c_login#47, c_email_address#48, d_year#55, sum#57] +Arguments: hashpartitioning(c_customer_id#42, c_first_name#43, c_last_name#44, c_preferred_cust_flag#45, c_birth_country#46, c_login#47, c_email_address#48, d_year#55, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(49) HashAggregate [codegen id : 11] +Input [9]: [c_customer_id#42, c_first_name#43, c_last_name#44, c_preferred_cust_flag#45, c_birth_country#46, c_login#47, c_email_address#48, d_year#55, sum#57] +Keys [8]: [c_customer_id#42, c_first_name#43, c_last_name#44, c_preferred_cust_flag#45, c_birth_country#46, c_login#47, c_email_address#48, d_year#55] +Functions [1]: [sum(UnscaledValue((ws_ext_list_price#51 - ws_ext_discount_amt#50)))] +Aggregate Attributes [1]: [sum(UnscaledValue((ws_ext_list_price#51 - ws_ext_discount_amt#50)))#58] +Results [2]: [c_customer_id#42 AS customer_id#59, MakeDecimal(sum(UnscaledValue((ws_ext_list_price#51 - ws_ext_discount_amt#50)))#58,18,2) AS year_total#60] + +(50) Filter [codegen id : 11] +Input [2]: [customer_id#59, year_total#60] +Condition : (isnotnull(year_total#60) AND (year_total#60 > 0.00)) + +(51) BroadcastExchange +Input [2]: [customer_id#59, year_total#60] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=8] + +(52) BroadcastHashJoin [codegen id : 16] +Left keys [1]: [customer_id#19] +Right keys [1]: [customer_id#59] +Join type: Inner +Join condition: None + +(53) Project [codegen id : 16] +Output [5]: [customer_id#19, year_total#20, customer_preferred_cust_flag#39, year_total#40, year_total#60] +Input [6]: [customer_id#19, year_total#20, customer_preferred_cust_flag#39, year_total#40, customer_id#59, year_total#60] + +(54) Scan parquet spark_catalog.default.customer +Output [8]: [c_customer_sk#61, c_customer_id#62, c_first_name#63, c_last_name#64, c_preferred_cust_flag#65, c_birth_country#66, c_login#67, c_email_address#68] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(55) CometFilter +Input [8]: [c_customer_sk#61, c_customer_id#62, c_first_name#63, c_last_name#64, c_preferred_cust_flag#65, c_birth_country#66, c_login#67, c_email_address#68] +Condition : (isnotnull(c_customer_sk#61) AND isnotnull(c_customer_id#62)) + +(56) ColumnarToRow [codegen id : 14] +Input [8]: [c_customer_sk#61, c_customer_id#62, c_first_name#63, c_last_name#64, c_preferred_cust_flag#65, c_birth_country#66, c_login#67, c_email_address#68] + +(57) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_bill_customer_sk#69, ws_ext_discount_amt#70, ws_ext_list_price#71, ws_sold_date_sk#72] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#72), dynamicpruningexpression(ws_sold_date_sk#72 IN dynamicpruning#73)] +PushedFilters: [IsNotNull(ws_bill_customer_sk)] +ReadSchema: struct + +(58) CometFilter +Input [4]: [ws_bill_customer_sk#69, ws_ext_discount_amt#70, ws_ext_list_price#71, ws_sold_date_sk#72] +Condition : isnotnull(ws_bill_customer_sk#69) + +(59) ColumnarToRow [codegen id : 12] +Input [4]: [ws_bill_customer_sk#69, ws_ext_discount_amt#70, ws_ext_list_price#71, ws_sold_date_sk#72] + +(60) BroadcastExchange +Input [4]: [ws_bill_customer_sk#69, ws_ext_discount_amt#70, ws_ext_list_price#71, ws_sold_date_sk#72] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=9] + +(61) BroadcastHashJoin [codegen id : 14] +Left keys [1]: [c_customer_sk#61] +Right keys [1]: [ws_bill_customer_sk#69] +Join type: Inner +Join condition: None + +(62) Project [codegen id : 14] +Output [10]: [c_customer_id#62, c_first_name#63, c_last_name#64, c_preferred_cust_flag#65, c_birth_country#66, c_login#67, c_email_address#68, ws_ext_discount_amt#70, ws_ext_list_price#71, ws_sold_date_sk#72] +Input [12]: [c_customer_sk#61, c_customer_id#62, c_first_name#63, c_last_name#64, c_preferred_cust_flag#65, c_birth_country#66, c_login#67, c_email_address#68, ws_bill_customer_sk#69, ws_ext_discount_amt#70, ws_ext_list_price#71, ws_sold_date_sk#72] + +(63) ReusedExchange [Reuses operator id: 80] +Output [2]: [d_date_sk#74, d_year#75] + +(64) BroadcastHashJoin [codegen id : 14] +Left keys [1]: [ws_sold_date_sk#72] +Right keys [1]: [d_date_sk#74] +Join type: Inner +Join condition: None + +(65) Project [codegen id : 14] +Output [10]: [c_customer_id#62, c_first_name#63, c_last_name#64, c_preferred_cust_flag#65, c_birth_country#66, c_login#67, c_email_address#68, ws_ext_discount_amt#70, ws_ext_list_price#71, d_year#75] +Input [12]: [c_customer_id#62, c_first_name#63, c_last_name#64, c_preferred_cust_flag#65, c_birth_country#66, c_login#67, c_email_address#68, ws_ext_discount_amt#70, ws_ext_list_price#71, ws_sold_date_sk#72, d_date_sk#74, d_year#75] + +(66) HashAggregate [codegen id : 14] +Input [10]: [c_customer_id#62, c_first_name#63, c_last_name#64, c_preferred_cust_flag#65, c_birth_country#66, c_login#67, c_email_address#68, ws_ext_discount_amt#70, ws_ext_list_price#71, d_year#75] +Keys [8]: [c_customer_id#62, c_first_name#63, c_last_name#64, c_preferred_cust_flag#65, c_birth_country#66, c_login#67, c_email_address#68, d_year#75] +Functions [1]: [partial_sum(UnscaledValue((ws_ext_list_price#71 - ws_ext_discount_amt#70)))] +Aggregate Attributes [1]: [sum#76] +Results [9]: [c_customer_id#62, c_first_name#63, c_last_name#64, c_preferred_cust_flag#65, c_birth_country#66, c_login#67, c_email_address#68, d_year#75, sum#77] + +(67) Exchange +Input [9]: [c_customer_id#62, c_first_name#63, c_last_name#64, c_preferred_cust_flag#65, c_birth_country#66, c_login#67, c_email_address#68, d_year#75, sum#77] +Arguments: hashpartitioning(c_customer_id#62, c_first_name#63, c_last_name#64, c_preferred_cust_flag#65, c_birth_country#66, c_login#67, c_email_address#68, d_year#75, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(68) HashAggregate [codegen id : 15] +Input [9]: [c_customer_id#62, c_first_name#63, c_last_name#64, c_preferred_cust_flag#65, c_birth_country#66, c_login#67, c_email_address#68, d_year#75, sum#77] +Keys [8]: [c_customer_id#62, c_first_name#63, c_last_name#64, c_preferred_cust_flag#65, c_birth_country#66, c_login#67, c_email_address#68, d_year#75] +Functions [1]: [sum(UnscaledValue((ws_ext_list_price#71 - ws_ext_discount_amt#70)))] +Aggregate Attributes [1]: [sum(UnscaledValue((ws_ext_list_price#71 - ws_ext_discount_amt#70)))#58] +Results [2]: [c_customer_id#62 AS customer_id#78, MakeDecimal(sum(UnscaledValue((ws_ext_list_price#71 - ws_ext_discount_amt#70)))#58,18,2) AS year_total#79] + +(69) BroadcastExchange +Input [2]: [customer_id#78, year_total#79] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=11] + +(70) BroadcastHashJoin [codegen id : 16] +Left keys [1]: [customer_id#19] +Right keys [1]: [customer_id#78] +Join type: Inner +Join condition: (CASE WHEN (year_total#60 > 0.00) THEN (year_total#79 / year_total#60) END > CASE WHEN (year_total#20 > 0.00) THEN (year_total#40 / year_total#20) END) + +(71) Project [codegen id : 16] +Output [1]: [customer_preferred_cust_flag#39] +Input [7]: [customer_id#19, year_total#20, customer_preferred_cust_flag#39, year_total#40, year_total#60, customer_id#78, year_total#79] + +(72) TakeOrderedAndProject +Input [1]: [customer_preferred_cust_flag#39] +Arguments: 100, [customer_preferred_cust_flag#39 ASC NULLS FIRST], [customer_preferred_cust_flag#39] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#12 IN dynamicpruning#13 +BroadcastExchange (76) ++- * ColumnarToRow (75) + +- CometFilter (74) + +- CometScan parquet spark_catalog.default.date_dim (73) + + +(73) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#14, d_year#15] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(74) CometFilter +Input [2]: [d_date_sk#14, d_year#15] +Condition : ((isnotnull(d_year#15) AND (d_year#15 = 2001)) AND isnotnull(d_date_sk#14)) + +(75) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#14, d_year#15] + +(76) BroadcastExchange +Input [2]: [d_date_sk#14, d_year#15] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=12] + +Subquery:2 Hosting operator id = 20 Hosting Expression = ss_sold_date_sk#32 IN dynamicpruning#33 +BroadcastExchange (80) ++- * ColumnarToRow (79) + +- CometFilter (78) + +- CometScan parquet spark_catalog.default.date_dim (77) + + +(77) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#34, d_year#35] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2002), IsNotNull(d_date_sk)] +ReadSchema: struct + +(78) CometFilter +Input [2]: [d_date_sk#34, d_year#35] +Condition : ((isnotnull(d_year#35) AND (d_year#35 = 2002)) AND isnotnull(d_date_sk#34)) + +(79) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#34, d_year#35] + +(80) BroadcastExchange +Input [2]: [d_date_sk#34, d_year#35] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=13] + +Subquery:3 Hosting operator id = 38 Hosting Expression = ws_sold_date_sk#52 IN dynamicpruning#13 + +Subquery:4 Hosting operator id = 57 Hosting Expression = ws_sold_date_sk#72 IN dynamicpruning#33 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q11/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q11/simplified.txt new file mode 100644 index 0000000000..562b5fdf29 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q11/simplified.txt @@ -0,0 +1,123 @@ +TakeOrderedAndProject [customer_preferred_cust_flag] + WholeStageCodegen (16) + Project [customer_preferred_cust_flag] + BroadcastHashJoin [customer_id,customer_id,year_total,year_total,year_total,year_total] + Project [customer_id,year_total,customer_preferred_cust_flag,year_total,year_total] + BroadcastHashJoin [customer_id,customer_id] + Project [customer_id,year_total,customer_preferred_cust_flag,year_total] + BroadcastHashJoin [customer_id,customer_id] + Filter [year_total] + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,sum] [sum(UnscaledValue((ss_ext_list_price - ss_ext_discount_amt))),customer_id,year_total,sum] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,d_year,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] #1 + WholeStageCodegen (3) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_list_price,ss_ext_discount_amt] [sum,sum] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_discount_amt,ss_ext_list_price,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_discount_amt,ss_ext_list_price,ss_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk] + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_ext_discount_amt,ss_ext_list_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk,d_year] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (7) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,sum] [sum(UnscaledValue((ss_ext_list_price - ss_ext_discount_amt))),customer_id,customer_preferred_cust_flag,year_total,sum] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,d_year,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] #5 + WholeStageCodegen (6) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_list_price,ss_ext_discount_amt] [sum,sum] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_discount_amt,ss_ext_list_price,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_discount_amt,ss_ext_list_price,ss_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (4) + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk] + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_ext_discount_amt,ss_ext_list_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #7 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk,d_year] #7 + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (11) + Filter [year_total] + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,sum] [sum(UnscaledValue((ws_ext_list_price - ws_ext_discount_amt))),customer_id,year_total,sum] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year] #9 + WholeStageCodegen (10) + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,ws_ext_list_price,ws_ext_discount_amt] [sum,sum] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ws_ext_discount_amt,ws_ext_list_price,d_year] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ws_ext_discount_amt,ws_ext_list_price,ws_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] + InputAdapter + BroadcastExchange #10 + WholeStageCodegen (8) + ColumnarToRow + InputAdapter + CometFilter [ws_bill_customer_sk] + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_ext_discount_amt,ws_ext_list_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk,d_year] #3 + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (15) + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,sum] [sum(UnscaledValue((ws_ext_list_price - ws_ext_discount_amt))),customer_id,year_total,sum] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year] #12 + WholeStageCodegen (14) + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,ws_ext_list_price,ws_ext_discount_amt] [sum,sum] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ws_ext_discount_amt,ws_ext_list_price,d_year] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ws_ext_discount_amt,ws_ext_list_price,ws_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] + InputAdapter + BroadcastExchange #13 + WholeStageCodegen (12) + ColumnarToRow + InputAdapter + CometFilter [ws_bill_customer_sk] + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_ext_discount_amt,ws_ext_list_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk,d_year] #7 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q12/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q12/explain.txt new file mode 100644 index 0000000000..6cf7f4b088 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q12/explain.txt @@ -0,0 +1,150 @@ +== Physical Plan == +TakeOrderedAndProject (20) ++- * Project (19) + +- Window (18) + +- * Sort (17) + +- Exchange (16) + +- * HashAggregate (15) + +- Exchange (14) + +- * HashAggregate (13) + +- * Project (12) + +- * BroadcastHashJoin Inner BuildRight (11) + :- * Project (9) + : +- * BroadcastHashJoin Inner BuildRight (8) + : :- * ColumnarToRow (3) + : : +- CometFilter (2) + : : +- CometScan parquet spark_catalog.default.web_sales (1) + : +- BroadcastExchange (7) + : +- * ColumnarToRow (6) + : +- CometFilter (5) + : +- CometScan parquet spark_catalog.default.item (4) + +- ReusedExchange (10) + + +(1) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_item_sk#1, ws_ext_sales_price#2, ws_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#3), dynamicpruningexpression(ws_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [ws_item_sk#1, ws_ext_sales_price#2, ws_sold_date_sk#3] +Condition : isnotnull(ws_item_sk#1) + +(3) ColumnarToRow [codegen id : 3] +Input [3]: [ws_item_sk#1, ws_ext_sales_price#2, ws_sold_date_sk#3] + +(4) Scan parquet spark_catalog.default.item +Output [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [In(i_category, [Books ,Home ,Sports ]), IsNotNull(i_item_sk)] +ReadSchema: struct + +(5) CometFilter +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Condition : (i_category#10 IN (Sports ,Books ,Home ) AND isnotnull(i_item_sk#5)) + +(6) ColumnarToRow [codegen id : 1] +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] + +(7) BroadcastExchange +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ws_item_sk#1] +Right keys [1]: [i_item_sk#5] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 3] +Output [7]: [ws_ext_sales_price#2, ws_sold_date_sk#3, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Input [9]: [ws_item_sk#1, ws_ext_sales_price#2, ws_sold_date_sk#3, i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] + +(10) ReusedExchange [Reuses operator id: 25] +Output [1]: [d_date_sk#11] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ws_sold_date_sk#3] +Right keys [1]: [d_date_sk#11] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [6]: [ws_ext_sales_price#2, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Input [8]: [ws_ext_sales_price#2, ws_sold_date_sk#3, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10, d_date_sk#11] + +(13) HashAggregate [codegen id : 3] +Input [6]: [ws_ext_sales_price#2, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Keys [5]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8] +Functions [1]: [partial_sum(UnscaledValue(ws_ext_sales_price#2))] +Aggregate Attributes [1]: [sum#12] +Results [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] + +(14) Exchange +Input [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] +Arguments: hashpartitioning(i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 4] +Input [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] +Keys [5]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8] +Functions [1]: [sum(UnscaledValue(ws_ext_sales_price#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_ext_sales_price#2))#14] +Results [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, MakeDecimal(sum(UnscaledValue(ws_ext_sales_price#2))#14,17,2) AS itemrevenue#15, MakeDecimal(sum(UnscaledValue(ws_ext_sales_price#2))#14,17,2) AS _w0#16, i_item_id#6] + +(16) Exchange +Input [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16, i_item_id#6] +Arguments: hashpartitioning(i_class#9, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(17) Sort [codegen id : 5] +Input [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16, i_item_id#6] +Arguments: [i_class#9 ASC NULLS FIRST], false, 0 + +(18) Window +Input [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16, i_item_id#6] +Arguments: [sum(_w0#16) windowspecdefinition(i_class#9, specifiedwindowframe(RowFrame, unboundedpreceding$(), unboundedfollowing$())) AS _we0#17], [i_class#9] + +(19) Project [codegen id : 6] +Output [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, ((_w0#16 * 100) / _we0#17) AS revenueratio#18, i_item_id#6] +Input [8]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16, i_item_id#6, _we0#17] + +(20) TakeOrderedAndProject +Input [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, revenueratio#18, i_item_id#6] +Arguments: 100, [i_category#10 ASC NULLS FIRST, i_class#9 ASC NULLS FIRST, i_item_id#6 ASC NULLS FIRST, i_item_desc#7 ASC NULLS FIRST, revenueratio#18 ASC NULLS FIRST], [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, revenueratio#18] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (25) ++- * ColumnarToRow (24) + +- CometProject (23) + +- CometFilter (22) + +- CometScan parquet spark_catalog.default.date_dim (21) + + +(21) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#11, d_date#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,1999-02-22), LessThanOrEqual(d_date,1999-03-24), IsNotNull(d_date_sk)] +ReadSchema: struct + +(22) CometFilter +Input [2]: [d_date_sk#11, d_date#19] +Condition : (((isnotnull(d_date#19) AND (d_date#19 >= 1999-02-22)) AND (d_date#19 <= 1999-03-24)) AND isnotnull(d_date_sk#11)) + +(23) CometProject +Input [2]: [d_date_sk#11, d_date#19] +Arguments: [d_date_sk#11], [d_date_sk#11] + +(24) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#11] + +(25) BroadcastExchange +Input [1]: [d_date_sk#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q12/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q12/simplified.txt new file mode 100644 index 0000000000..fae1c6dba1 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q12/simplified.txt @@ -0,0 +1,40 @@ +TakeOrderedAndProject [i_category,i_class,i_item_id,i_item_desc,revenueratio,i_current_price,itemrevenue] + WholeStageCodegen (6) + Project [i_item_desc,i_category,i_class,i_current_price,itemrevenue,_w0,_we0,i_item_id] + InputAdapter + Window [_w0,i_class] + WholeStageCodegen (5) + Sort [i_class] + InputAdapter + Exchange [i_class] #1 + WholeStageCodegen (4) + HashAggregate [i_item_id,i_item_desc,i_category,i_class,i_current_price,sum] [sum(UnscaledValue(ws_ext_sales_price)),itemrevenue,_w0,sum] + InputAdapter + Exchange [i_item_id,i_item_desc,i_category,i_class,i_current_price] #2 + WholeStageCodegen (3) + HashAggregate [i_item_id,i_item_desc,i_category,i_class,i_current_price,ws_ext_sales_price] [sum,sum] + Project [ws_ext_sales_price,i_item_id,i_item_desc,i_current_price,i_class,i_category] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_ext_sales_price,ws_sold_date_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] + BroadcastHashJoin [ws_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_ext_sales_price,ws_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [i_category,i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] + InputAdapter + ReusedExchange [d_date_sk] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q13/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q13/explain.txt new file mode 100644 index 0000000000..a647b1f053 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q13/explain.txt @@ -0,0 +1,232 @@ +== Physical Plan == +* HashAggregate (34) ++- Exchange (33) + +- * HashAggregate (32) + +- * Project (31) + +- * BroadcastHashJoin Inner BuildRight (30) + :- * Project (25) + : +- * BroadcastHashJoin Inner BuildRight (24) + : :- * Project (19) + : : +- * BroadcastHashJoin Inner BuildRight (18) + : : :- * Project (16) + : : : +- * BroadcastHashJoin Inner BuildRight (15) + : : : :- * Project (9) + : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : +- BroadcastExchange (7) + : : : : +- * ColumnarToRow (6) + : : : : +- CometFilter (5) + : : : : +- CometScan parquet spark_catalog.default.store (4) + : : : +- BroadcastExchange (14) + : : : +- * ColumnarToRow (13) + : : : +- CometProject (12) + : : : +- CometFilter (11) + : : : +- CometScan parquet spark_catalog.default.customer_address (10) + : : +- ReusedExchange (17) + : +- BroadcastExchange (23) + : +- * ColumnarToRow (22) + : +- CometFilter (21) + : +- CometScan parquet spark_catalog.default.customer_demographics (20) + +- BroadcastExchange (29) + +- * ColumnarToRow (28) + +- CometFilter (27) + +- CometScan parquet spark_catalog.default.household_demographics (26) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [10]: [ss_cdemo_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8, ss_net_profit#9, ss_sold_date_sk#10] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#10), dynamicpruningexpression(ss_sold_date_sk#10 IN dynamicpruning#11)] +PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_addr_sk), IsNotNull(ss_cdemo_sk), IsNotNull(ss_hdemo_sk), Or(Or(And(GreaterThanOrEqual(ss_net_profit,100.00),LessThanOrEqual(ss_net_profit,200.00)),And(GreaterThanOrEqual(ss_net_profit,150.00),LessThanOrEqual(ss_net_profit,300.00))),And(GreaterThanOrEqual(ss_net_profit,50.00),LessThanOrEqual(ss_net_profit,250.00))), Or(Or(And(GreaterThanOrEqual(ss_sales_price,100.00),LessThanOrEqual(ss_sales_price,150.00)),And(GreaterThanOrEqual(ss_sales_price,50.00),LessThanOrEqual(ss_sales_price,100.00))),And(GreaterThanOrEqual(ss_sales_price,150.00),LessThanOrEqual(ss_sales_price,200.00)))] +ReadSchema: struct + +(2) CometFilter +Input [10]: [ss_cdemo_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8, ss_net_profit#9, ss_sold_date_sk#10] +Condition : (((((isnotnull(ss_store_sk#4) AND isnotnull(ss_addr_sk#3)) AND isnotnull(ss_cdemo_sk#1)) AND isnotnull(ss_hdemo_sk#2)) AND ((((ss_net_profit#9 >= 100.00) AND (ss_net_profit#9 <= 200.00)) OR ((ss_net_profit#9 >= 150.00) AND (ss_net_profit#9 <= 300.00))) OR ((ss_net_profit#9 >= 50.00) AND (ss_net_profit#9 <= 250.00)))) AND ((((ss_sales_price#6 >= 100.00) AND (ss_sales_price#6 <= 150.00)) OR ((ss_sales_price#6 >= 50.00) AND (ss_sales_price#6 <= 100.00))) OR ((ss_sales_price#6 >= 150.00) AND (ss_sales_price#6 <= 200.00)))) + +(3) ColumnarToRow [codegen id : 6] +Input [10]: [ss_cdemo_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8, ss_net_profit#9, ss_sold_date_sk#10] + +(4) Scan parquet spark_catalog.default.store +Output [1]: [s_store_sk#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(5) CometFilter +Input [1]: [s_store_sk#12] +Condition : isnotnull(s_store_sk#12) + +(6) ColumnarToRow [codegen id : 1] +Input [1]: [s_store_sk#12] + +(7) BroadcastExchange +Input [1]: [s_store_sk#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_store_sk#4] +Right keys [1]: [s_store_sk#12] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 6] +Output [9]: [ss_cdemo_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8, ss_net_profit#9, ss_sold_date_sk#10] +Input [11]: [ss_cdemo_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8, ss_net_profit#9, ss_sold_date_sk#10, s_store_sk#12] + +(10) Scan parquet spark_catalog.default.customer_address +Output [3]: [ca_address_sk#13, ca_state#14, ca_country#15] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_country), EqualTo(ca_country,United States), IsNotNull(ca_address_sk), Or(Or(In(ca_state, [OH,TX]),In(ca_state, [KY,NM,OR])),In(ca_state, [MS,TX,VA]))] +ReadSchema: struct + +(11) CometFilter +Input [3]: [ca_address_sk#13, ca_state#14, ca_country#15] +Condition : (((isnotnull(ca_country#15) AND (ca_country#15 = United States)) AND isnotnull(ca_address_sk#13)) AND ((ca_state#14 IN (TX,OH) OR ca_state#14 IN (OR,NM,KY)) OR ca_state#14 IN (VA,TX,MS))) + +(12) CometProject +Input [3]: [ca_address_sk#13, ca_state#14, ca_country#15] +Arguments: [ca_address_sk#13, ca_state#14], [ca_address_sk#13, ca_state#14] + +(13) ColumnarToRow [codegen id : 2] +Input [2]: [ca_address_sk#13, ca_state#14] + +(14) BroadcastExchange +Input [2]: [ca_address_sk#13, ca_state#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(15) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_addr_sk#3] +Right keys [1]: [ca_address_sk#13] +Join type: Inner +Join condition: ((((ca_state#14 IN (TX,OH) AND (ss_net_profit#9 >= 100.00)) AND (ss_net_profit#9 <= 200.00)) OR ((ca_state#14 IN (OR,NM,KY) AND (ss_net_profit#9 >= 150.00)) AND (ss_net_profit#9 <= 300.00))) OR ((ca_state#14 IN (VA,TX,MS) AND (ss_net_profit#9 >= 50.00)) AND (ss_net_profit#9 <= 250.00))) + +(16) Project [codegen id : 6] +Output [7]: [ss_cdemo_sk#1, ss_hdemo_sk#2, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8, ss_sold_date_sk#10] +Input [11]: [ss_cdemo_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8, ss_net_profit#9, ss_sold_date_sk#10, ca_address_sk#13, ca_state#14] + +(17) ReusedExchange [Reuses operator id: 39] +Output [1]: [d_date_sk#16] + +(18) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_sold_date_sk#10] +Right keys [1]: [d_date_sk#16] +Join type: Inner +Join condition: None + +(19) Project [codegen id : 6] +Output [6]: [ss_cdemo_sk#1, ss_hdemo_sk#2, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8] +Input [8]: [ss_cdemo_sk#1, ss_hdemo_sk#2, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8, ss_sold_date_sk#10, d_date_sk#16] + +(20) Scan parquet spark_catalog.default.customer_demographics +Output [3]: [cd_demo_sk#17, cd_marital_status#18, cd_education_status#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_demo_sk), Or(Or(And(EqualTo(cd_marital_status,M),EqualTo(cd_education_status,Advanced Degree )),And(EqualTo(cd_marital_status,S),EqualTo(cd_education_status,College ))),And(EqualTo(cd_marital_status,W),EqualTo(cd_education_status,2 yr Degree )))] +ReadSchema: struct + +(21) CometFilter +Input [3]: [cd_demo_sk#17, cd_marital_status#18, cd_education_status#19] +Condition : (isnotnull(cd_demo_sk#17) AND ((((cd_marital_status#18 = M) AND (cd_education_status#19 = Advanced Degree )) OR ((cd_marital_status#18 = S) AND (cd_education_status#19 = College ))) OR ((cd_marital_status#18 = W) AND (cd_education_status#19 = 2 yr Degree )))) + +(22) ColumnarToRow [codegen id : 4] +Input [3]: [cd_demo_sk#17, cd_marital_status#18, cd_education_status#19] + +(23) BroadcastExchange +Input [3]: [cd_demo_sk#17, cd_marital_status#18, cd_education_status#19] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_cdemo_sk#1] +Right keys [1]: [cd_demo_sk#17] +Join type: Inner +Join condition: ((((((cd_marital_status#18 = M) AND (cd_education_status#19 = Advanced Degree )) AND (ss_sales_price#6 >= 100.00)) AND (ss_sales_price#6 <= 150.00)) OR ((((cd_marital_status#18 = S) AND (cd_education_status#19 = College )) AND (ss_sales_price#6 >= 50.00)) AND (ss_sales_price#6 <= 100.00))) OR ((((cd_marital_status#18 = W) AND (cd_education_status#19 = 2 yr Degree )) AND (ss_sales_price#6 >= 150.00)) AND (ss_sales_price#6 <= 200.00))) + +(25) Project [codegen id : 6] +Output [7]: [ss_hdemo_sk#2, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8, cd_marital_status#18, cd_education_status#19] +Input [9]: [ss_cdemo_sk#1, ss_hdemo_sk#2, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8, cd_demo_sk#17, cd_marital_status#18, cd_education_status#19] + +(26) Scan parquet spark_catalog.default.household_demographics +Output [2]: [hd_demo_sk#20, hd_dep_count#21] +Batched: true +Location [not included in comparison]/{warehouse_dir}/household_demographics] +PushedFilters: [IsNotNull(hd_demo_sk), Or(EqualTo(hd_dep_count,3),EqualTo(hd_dep_count,1))] +ReadSchema: struct + +(27) CometFilter +Input [2]: [hd_demo_sk#20, hd_dep_count#21] +Condition : (isnotnull(hd_demo_sk#20) AND ((hd_dep_count#21 = 3) OR (hd_dep_count#21 = 1))) + +(28) ColumnarToRow [codegen id : 5] +Input [2]: [hd_demo_sk#20, hd_dep_count#21] + +(29) BroadcastExchange +Input [2]: [hd_demo_sk#20, hd_dep_count#21] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(30) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_hdemo_sk#2] +Right keys [1]: [hd_demo_sk#20] +Join type: Inner +Join condition: (((((((cd_marital_status#18 = M) AND (cd_education_status#19 = Advanced Degree )) AND (ss_sales_price#6 >= 100.00)) AND (ss_sales_price#6 <= 150.00)) AND (hd_dep_count#21 = 3)) OR (((((cd_marital_status#18 = S) AND (cd_education_status#19 = College )) AND (ss_sales_price#6 >= 50.00)) AND (ss_sales_price#6 <= 100.00)) AND (hd_dep_count#21 = 1))) OR (((((cd_marital_status#18 = W) AND (cd_education_status#19 = 2 yr Degree )) AND (ss_sales_price#6 >= 150.00)) AND (ss_sales_price#6 <= 200.00)) AND (hd_dep_count#21 = 1))) + +(31) Project [codegen id : 6] +Output [3]: [ss_quantity#5, ss_ext_sales_price#7, ss_ext_wholesale_cost#8] +Input [9]: [ss_hdemo_sk#2, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8, cd_marital_status#18, cd_education_status#19, hd_demo_sk#20, hd_dep_count#21] + +(32) HashAggregate [codegen id : 6] +Input [3]: [ss_quantity#5, ss_ext_sales_price#7, ss_ext_wholesale_cost#8] +Keys: [] +Functions [4]: [partial_avg(ss_quantity#5), partial_avg(UnscaledValue(ss_ext_sales_price#7)), partial_avg(UnscaledValue(ss_ext_wholesale_cost#8)), partial_sum(UnscaledValue(ss_ext_wholesale_cost#8))] +Aggregate Attributes [7]: [sum#22, count#23, sum#24, count#25, sum#26, count#27, sum#28] +Results [7]: [sum#29, count#30, sum#31, count#32, sum#33, count#34, sum#35] + +(33) Exchange +Input [7]: [sum#29, count#30, sum#31, count#32, sum#33, count#34, sum#35] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=5] + +(34) HashAggregate [codegen id : 7] +Input [7]: [sum#29, count#30, sum#31, count#32, sum#33, count#34, sum#35] +Keys: [] +Functions [4]: [avg(ss_quantity#5), avg(UnscaledValue(ss_ext_sales_price#7)), avg(UnscaledValue(ss_ext_wholesale_cost#8)), sum(UnscaledValue(ss_ext_wholesale_cost#8))] +Aggregate Attributes [4]: [avg(ss_quantity#5)#36, avg(UnscaledValue(ss_ext_sales_price#7))#37, avg(UnscaledValue(ss_ext_wholesale_cost#8))#38, sum(UnscaledValue(ss_ext_wholesale_cost#8))#39] +Results [4]: [avg(ss_quantity#5)#36 AS avg(ss_quantity)#40, cast((avg(UnscaledValue(ss_ext_sales_price#7))#37 / 100.0) as decimal(11,6)) AS avg(ss_ext_sales_price)#41, cast((avg(UnscaledValue(ss_ext_wholesale_cost#8))#38 / 100.0) as decimal(11,6)) AS avg(ss_ext_wholesale_cost)#42, MakeDecimal(sum(UnscaledValue(ss_ext_wholesale_cost#8))#39,17,2) AS sum(ss_ext_wholesale_cost)#43] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#10 IN dynamicpruning#11 +BroadcastExchange (39) ++- * ColumnarToRow (38) + +- CometProject (37) + +- CometFilter (36) + +- CometScan parquet spark_catalog.default.date_dim (35) + + +(35) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#16, d_year#44] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(36) CometFilter +Input [2]: [d_date_sk#16, d_year#44] +Condition : ((isnotnull(d_year#44) AND (d_year#44 = 2001)) AND isnotnull(d_date_sk#16)) + +(37) CometProject +Input [2]: [d_date_sk#16, d_year#44] +Arguments: [d_date_sk#16], [d_date_sk#16] + +(38) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#16] + +(39) BroadcastExchange +Input [1]: [d_date_sk#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q13/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q13/simplified.txt new file mode 100644 index 0000000000..5e5fc41f83 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q13/simplified.txt @@ -0,0 +1,59 @@ +WholeStageCodegen (7) + HashAggregate [sum,count,sum,count,sum,count,sum] [avg(ss_quantity),avg(UnscaledValue(ss_ext_sales_price)),avg(UnscaledValue(ss_ext_wholesale_cost)),sum(UnscaledValue(ss_ext_wholesale_cost)),avg(ss_quantity),avg(ss_ext_sales_price),avg(ss_ext_wholesale_cost),sum(ss_ext_wholesale_cost),sum,count,sum,count,sum,count,sum] + InputAdapter + Exchange #1 + WholeStageCodegen (6) + HashAggregate [ss_quantity,ss_ext_sales_price,ss_ext_wholesale_cost] [sum,count,sum,count,sum,count,sum,sum,count,sum,count,sum,count,sum] + Project [ss_quantity,ss_ext_sales_price,ss_ext_wholesale_cost] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk,cd_marital_status,cd_education_status,ss_sales_price,hd_dep_count] + Project [ss_hdemo_sk,ss_quantity,ss_sales_price,ss_ext_sales_price,ss_ext_wholesale_cost,cd_marital_status,cd_education_status] + BroadcastHashJoin [ss_cdemo_sk,cd_demo_sk,cd_marital_status,cd_education_status,ss_sales_price] + Project [ss_cdemo_sk,ss_hdemo_sk,ss_quantity,ss_sales_price,ss_ext_sales_price,ss_ext_wholesale_cost] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_cdemo_sk,ss_hdemo_sk,ss_quantity,ss_sales_price,ss_ext_sales_price,ss_ext_wholesale_cost,ss_sold_date_sk] + BroadcastHashJoin [ss_addr_sk,ca_address_sk,ca_state,ss_net_profit] + Project [ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_quantity,ss_sales_price,ss_ext_sales_price,ss_ext_wholesale_cost,ss_net_profit,ss_sold_date_sk] + BroadcastHashJoin [ss_store_sk,s_store_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk,ss_addr_sk,ss_cdemo_sk,ss_hdemo_sk,ss_net_profit,ss_sales_price] + CometScan parquet spark_catalog.default.store_sales [ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_quantity,ss_sales_price,ss_ext_sales_price,ss_ext_wholesale_cost,ss_net_profit,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometProject [ca_address_sk,ca_state] + CometFilter [ca_country,ca_address_sk,ca_state] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state,ca_country] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (4) + ColumnarToRow + InputAdapter + CometFilter [cd_demo_sk,cd_marital_status,cd_education_status] + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_marital_status,cd_education_status] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (5) + ColumnarToRow + InputAdapter + CometFilter [hd_demo_sk,hd_dep_count] + CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_dep_count] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14a/explain.txt new file mode 100644 index 0000000000..565cb97da6 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14a/explain.txt @@ -0,0 +1,800 @@ +== Physical Plan == +TakeOrderedAndProject (105) ++- * HashAggregate (104) + +- Exchange (103) + +- * HashAggregate (102) + +- * Expand (101) + +- Union (100) + :- * Project (67) + : +- * Filter (66) + : +- * HashAggregate (65) + : +- Exchange (64) + : +- * HashAggregate (63) + : +- * Project (62) + : +- * BroadcastHashJoin Inner BuildRight (61) + : :- * Project (59) + : : +- * BroadcastHashJoin Inner BuildRight (58) + : : :- * BroadcastHashJoin LeftSemi BuildRight (51) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- BroadcastExchange (50) + : : : +- * Project (49) + : : : +- * BroadcastHashJoin Inner BuildRight (48) + : : : :- * ColumnarToRow (6) + : : : : +- CometFilter (5) + : : : : +- CometScan parquet spark_catalog.default.item (4) + : : : +- BroadcastExchange (47) + : : : +- * BroadcastHashJoin LeftSemi BuildRight (46) + : : : :- * HashAggregate (35) + : : : : +- Exchange (34) + : : : : +- * HashAggregate (33) + : : : : +- * Project (32) + : : : : +- * BroadcastHashJoin Inner BuildRight (31) + : : : : :- * Project (29) + : : : : : +- * BroadcastHashJoin Inner BuildRight (28) + : : : : : :- * ColumnarToRow (9) + : : : : : : +- CometFilter (8) + : : : : : : +- CometScan parquet spark_catalog.default.store_sales (7) + : : : : : +- BroadcastExchange (27) + : : : : : +- * BroadcastHashJoin LeftSemi BuildRight (26) + : : : : : :- * ColumnarToRow (12) + : : : : : : +- CometFilter (11) + : : : : : : +- CometScan parquet spark_catalog.default.item (10) + : : : : : +- BroadcastExchange (25) + : : : : : +- * Project (24) + : : : : : +- * BroadcastHashJoin Inner BuildRight (23) + : : : : : :- * Project (21) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (20) + : : : : : : :- * ColumnarToRow (15) + : : : : : : : +- CometFilter (14) + : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (13) + : : : : : : +- BroadcastExchange (19) + : : : : : : +- * ColumnarToRow (18) + : : : : : : +- CometFilter (17) + : : : : : : +- CometScan parquet spark_catalog.default.item (16) + : : : : : +- ReusedExchange (22) + : : : : +- ReusedExchange (30) + : : : +- BroadcastExchange (45) + : : : +- * Project (44) + : : : +- * BroadcastHashJoin Inner BuildRight (43) + : : : :- * Project (41) + : : : : +- * BroadcastHashJoin Inner BuildRight (40) + : : : : :- * ColumnarToRow (38) + : : : : : +- CometFilter (37) + : : : : : +- CometScan parquet spark_catalog.default.web_sales (36) + : : : : +- ReusedExchange (39) + : : : +- ReusedExchange (42) + : : +- BroadcastExchange (57) + : : +- * BroadcastHashJoin LeftSemi BuildRight (56) + : : :- * ColumnarToRow (54) + : : : +- CometFilter (53) + : : : +- CometScan parquet spark_catalog.default.item (52) + : : +- ReusedExchange (55) + : +- ReusedExchange (60) + :- * Project (83) + : +- * Filter (82) + : +- * HashAggregate (81) + : +- Exchange (80) + : +- * HashAggregate (79) + : +- * Project (78) + : +- * BroadcastHashJoin Inner BuildRight (77) + : :- * Project (75) + : : +- * BroadcastHashJoin Inner BuildRight (74) + : : :- * BroadcastHashJoin LeftSemi BuildRight (72) + : : : :- * ColumnarToRow (70) + : : : : +- CometFilter (69) + : : : : +- CometScan parquet spark_catalog.default.catalog_sales (68) + : : : +- ReusedExchange (71) + : : +- ReusedExchange (73) + : +- ReusedExchange (76) + +- * Project (99) + +- * Filter (98) + +- * HashAggregate (97) + +- Exchange (96) + +- * HashAggregate (95) + +- * Project (94) + +- * BroadcastHashJoin Inner BuildRight (93) + :- * Project (91) + : +- * BroadcastHashJoin Inner BuildRight (90) + : :- * BroadcastHashJoin LeftSemi BuildRight (88) + : : :- * ColumnarToRow (86) + : : : +- CometFilter (85) + : : : +- CometScan parquet spark_catalog.default.web_sales (84) + : : +- ReusedExchange (87) + : +- ReusedExchange (89) + +- ReusedExchange (92) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#4), dynamicpruningexpression(ss_sold_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4] +Condition : isnotnull(ss_item_sk#1) + +(3) ColumnarToRow [codegen id : 25] +Input [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4] + +(4) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id)] +ReadSchema: struct + +(5) CometFilter +Input [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] +Condition : ((isnotnull(i_brand_id#7) AND isnotnull(i_class_id#8)) AND isnotnull(i_category_id#9)) + +(6) ColumnarToRow [codegen id : 11] +Input [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] + +(7) Scan parquet spark_catalog.default.store_sales +Output [2]: [ss_item_sk#10, ss_sold_date_sk#11] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#11), dynamicpruningexpression(ss_sold_date_sk#11 IN dynamicpruning#12)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(8) CometFilter +Input [2]: [ss_item_sk#10, ss_sold_date_sk#11] +Condition : isnotnull(ss_item_sk#10) + +(9) ColumnarToRow [codegen id : 6] +Input [2]: [ss_item_sk#10, ss_sold_date_sk#11] + +(10) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id)] +ReadSchema: struct + +(11) CometFilter +Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] +Condition : (((isnotnull(i_item_sk#13) AND isnotnull(i_brand_id#14)) AND isnotnull(i_class_id#15)) AND isnotnull(i_category_id#16)) + +(12) ColumnarToRow [codegen id : 4] +Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] + +(13) Scan parquet spark_catalog.default.catalog_sales +Output [2]: [cs_item_sk#17, cs_sold_date_sk#18] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#18), dynamicpruningexpression(cs_sold_date_sk#18 IN dynamicpruning#19)] +PushedFilters: [IsNotNull(cs_item_sk)] +ReadSchema: struct + +(14) CometFilter +Input [2]: [cs_item_sk#17, cs_sold_date_sk#18] +Condition : isnotnull(cs_item_sk#17) + +(15) ColumnarToRow [codegen id : 3] +Input [2]: [cs_item_sk#17, cs_sold_date_sk#18] + +(16) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(17) CometFilter +Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] +Condition : isnotnull(i_item_sk#20) + +(18) ColumnarToRow [codegen id : 1] +Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] + +(19) BroadcastExchange +Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(20) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cs_item_sk#17] +Right keys [1]: [i_item_sk#20] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 3] +Output [4]: [cs_sold_date_sk#18, i_brand_id#21, i_class_id#22, i_category_id#23] +Input [6]: [cs_item_sk#17, cs_sold_date_sk#18, i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] + +(22) ReusedExchange [Reuses operator id: 134] +Output [1]: [d_date_sk#24] + +(23) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cs_sold_date_sk#18] +Right keys [1]: [d_date_sk#24] +Join type: Inner +Join condition: None + +(24) Project [codegen id : 3] +Output [3]: [i_brand_id#21, i_class_id#22, i_category_id#23] +Input [5]: [cs_sold_date_sk#18, i_brand_id#21, i_class_id#22, i_category_id#23, d_date_sk#24] + +(25) BroadcastExchange +Input [3]: [i_brand_id#21, i_class_id#22, i_category_id#23] +Arguments: HashedRelationBroadcastMode(List(coalesce(input[0, int, true], 0), isnull(input[0, int, true]), coalesce(input[1, int, true], 0), isnull(input[1, int, true]), coalesce(input[2, int, true], 0), isnull(input[2, int, true])),false), [plan_id=2] + +(26) BroadcastHashJoin [codegen id : 4] +Left keys [6]: [coalesce(i_brand_id#14, 0), isnull(i_brand_id#14), coalesce(i_class_id#15, 0), isnull(i_class_id#15), coalesce(i_category_id#16, 0), isnull(i_category_id#16)] +Right keys [6]: [coalesce(i_brand_id#21, 0), isnull(i_brand_id#21), coalesce(i_class_id#22, 0), isnull(i_class_id#22), coalesce(i_category_id#23, 0), isnull(i_category_id#23)] +Join type: LeftSemi +Join condition: None + +(27) BroadcastExchange +Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(28) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_item_sk#10] +Right keys [1]: [i_item_sk#13] +Join type: Inner +Join condition: None + +(29) Project [codegen id : 6] +Output [4]: [ss_sold_date_sk#11, i_brand_id#14, i_class_id#15, i_category_id#16] +Input [6]: [ss_item_sk#10, ss_sold_date_sk#11, i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] + +(30) ReusedExchange [Reuses operator id: 134] +Output [1]: [d_date_sk#25] + +(31) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_sold_date_sk#11] +Right keys [1]: [d_date_sk#25] +Join type: Inner +Join condition: None + +(32) Project [codegen id : 6] +Output [3]: [i_brand_id#14 AS brand_id#26, i_class_id#15 AS class_id#27, i_category_id#16 AS category_id#28] +Input [5]: [ss_sold_date_sk#11, i_brand_id#14, i_class_id#15, i_category_id#16, d_date_sk#25] + +(33) HashAggregate [codegen id : 6] +Input [3]: [brand_id#26, class_id#27, category_id#28] +Keys [3]: [brand_id#26, class_id#27, category_id#28] +Functions: [] +Aggregate Attributes: [] +Results [3]: [brand_id#26, class_id#27, category_id#28] + +(34) Exchange +Input [3]: [brand_id#26, class_id#27, category_id#28] +Arguments: hashpartitioning(brand_id#26, class_id#27, category_id#28, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(35) HashAggregate [codegen id : 10] +Input [3]: [brand_id#26, class_id#27, category_id#28] +Keys [3]: [brand_id#26, class_id#27, category_id#28] +Functions: [] +Aggregate Attributes: [] +Results [3]: [brand_id#26, class_id#27, category_id#28] + +(36) Scan parquet spark_catalog.default.web_sales +Output [2]: [ws_item_sk#29, ws_sold_date_sk#30] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#30), dynamicpruningexpression(ws_sold_date_sk#30 IN dynamicpruning#31)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(37) CometFilter +Input [2]: [ws_item_sk#29, ws_sold_date_sk#30] +Condition : isnotnull(ws_item_sk#29) + +(38) ColumnarToRow [codegen id : 9] +Input [2]: [ws_item_sk#29, ws_sold_date_sk#30] + +(39) ReusedExchange [Reuses operator id: 19] +Output [4]: [i_item_sk#32, i_brand_id#33, i_class_id#34, i_category_id#35] + +(40) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ws_item_sk#29] +Right keys [1]: [i_item_sk#32] +Join type: Inner +Join condition: None + +(41) Project [codegen id : 9] +Output [4]: [ws_sold_date_sk#30, i_brand_id#33, i_class_id#34, i_category_id#35] +Input [6]: [ws_item_sk#29, ws_sold_date_sk#30, i_item_sk#32, i_brand_id#33, i_class_id#34, i_category_id#35] + +(42) ReusedExchange [Reuses operator id: 134] +Output [1]: [d_date_sk#36] + +(43) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ws_sold_date_sk#30] +Right keys [1]: [d_date_sk#36] +Join type: Inner +Join condition: None + +(44) Project [codegen id : 9] +Output [3]: [i_brand_id#33, i_class_id#34, i_category_id#35] +Input [5]: [ws_sold_date_sk#30, i_brand_id#33, i_class_id#34, i_category_id#35, d_date_sk#36] + +(45) BroadcastExchange +Input [3]: [i_brand_id#33, i_class_id#34, i_category_id#35] +Arguments: HashedRelationBroadcastMode(List(coalesce(input[0, int, true], 0), isnull(input[0, int, true]), coalesce(input[1, int, true], 0), isnull(input[1, int, true]), coalesce(input[2, int, true], 0), isnull(input[2, int, true])),false), [plan_id=5] + +(46) BroadcastHashJoin [codegen id : 10] +Left keys [6]: [coalesce(brand_id#26, 0), isnull(brand_id#26), coalesce(class_id#27, 0), isnull(class_id#27), coalesce(category_id#28, 0), isnull(category_id#28)] +Right keys [6]: [coalesce(i_brand_id#33, 0), isnull(i_brand_id#33), coalesce(i_class_id#34, 0), isnull(i_class_id#34), coalesce(i_category_id#35, 0), isnull(i_category_id#35)] +Join type: LeftSemi +Join condition: None + +(47) BroadcastExchange +Input [3]: [brand_id#26, class_id#27, category_id#28] +Arguments: HashedRelationBroadcastMode(List(input[0, int, true], input[1, int, true], input[2, int, true]),false), [plan_id=6] + +(48) BroadcastHashJoin [codegen id : 11] +Left keys [3]: [i_brand_id#7, i_class_id#8, i_category_id#9] +Right keys [3]: [brand_id#26, class_id#27, category_id#28] +Join type: Inner +Join condition: None + +(49) Project [codegen id : 11] +Output [1]: [i_item_sk#6 AS ss_item_sk#37] +Input [7]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9, brand_id#26, class_id#27, category_id#28] + +(50) BroadcastExchange +Input [1]: [ss_item_sk#37] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +(51) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [ss_item_sk#37] +Join type: LeftSemi +Join condition: None + +(52) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(53) CometFilter +Input [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] +Condition : isnotnull(i_item_sk#38) + +(54) ColumnarToRow [codegen id : 23] +Input [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] + +(55) ReusedExchange [Reuses operator id: 50] +Output [1]: [ss_item_sk#37] + +(56) BroadcastHashJoin [codegen id : 23] +Left keys [1]: [i_item_sk#38] +Right keys [1]: [ss_item_sk#37] +Join type: LeftSemi +Join condition: None + +(57) BroadcastExchange +Input [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8] + +(58) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#38] +Join type: Inner +Join condition: None + +(59) Project [codegen id : 25] +Output [6]: [ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4, i_brand_id#39, i_class_id#40, i_category_id#41] +Input [8]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4, i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] + +(60) ReusedExchange [Reuses operator id: 129] +Output [1]: [d_date_sk#42] + +(61) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_sold_date_sk#4] +Right keys [1]: [d_date_sk#42] +Join type: Inner +Join condition: None + +(62) Project [codegen id : 25] +Output [5]: [ss_quantity#2, ss_list_price#3, i_brand_id#39, i_class_id#40, i_category_id#41] +Input [7]: [ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4, i_brand_id#39, i_class_id#40, i_category_id#41, d_date_sk#42] + +(63) HashAggregate [codegen id : 25] +Input [5]: [ss_quantity#2, ss_list_price#3, i_brand_id#39, i_class_id#40, i_category_id#41] +Keys [3]: [i_brand_id#39, i_class_id#40, i_category_id#41] +Functions [2]: [partial_sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3)), partial_count(1)] +Aggregate Attributes [3]: [sum#43, isEmpty#44, count#45] +Results [6]: [i_brand_id#39, i_class_id#40, i_category_id#41, sum#46, isEmpty#47, count#48] + +(64) Exchange +Input [6]: [i_brand_id#39, i_class_id#40, i_category_id#41, sum#46, isEmpty#47, count#48] +Arguments: hashpartitioning(i_brand_id#39, i_class_id#40, i_category_id#41, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(65) HashAggregate [codegen id : 26] +Input [6]: [i_brand_id#39, i_class_id#40, i_category_id#41, sum#46, isEmpty#47, count#48] +Keys [3]: [i_brand_id#39, i_class_id#40, i_category_id#41] +Functions [2]: [sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3)), count(1)] +Aggregate Attributes [2]: [sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3))#49, count(1)#50] +Results [5]: [i_brand_id#39, i_class_id#40, i_category_id#41, sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3))#49 AS sales#51, count(1)#50 AS number_sales#52] + +(66) Filter [codegen id : 26] +Input [5]: [i_brand_id#39, i_class_id#40, i_category_id#41, sales#51, number_sales#52] +Condition : (isnotnull(sales#51) AND (cast(sales#51 as decimal(32,6)) > cast(Subquery scalar-subquery#53, [id=#54] as decimal(32,6)))) + +(67) Project [codegen id : 26] +Output [6]: [sales#51, number_sales#52, store AS channel#55, i_brand_id#39 AS i_brand_id#56, i_class_id#40 AS i_class_id#57, i_category_id#41 AS i_category_id#58] +Input [5]: [i_brand_id#39, i_class_id#40, i_category_id#41, sales#51, number_sales#52] + +(68) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_item_sk#59, cs_quantity#60, cs_list_price#61, cs_sold_date_sk#62] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#62), dynamicpruningexpression(cs_sold_date_sk#62 IN dynamicpruning#63)] +PushedFilters: [IsNotNull(cs_item_sk)] +ReadSchema: struct + +(69) CometFilter +Input [4]: [cs_item_sk#59, cs_quantity#60, cs_list_price#61, cs_sold_date_sk#62] +Condition : isnotnull(cs_item_sk#59) + +(70) ColumnarToRow [codegen id : 51] +Input [4]: [cs_item_sk#59, cs_quantity#60, cs_list_price#61, cs_sold_date_sk#62] + +(71) ReusedExchange [Reuses operator id: 50] +Output [1]: [ss_item_sk#64] + +(72) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [cs_item_sk#59] +Right keys [1]: [ss_item_sk#64] +Join type: LeftSemi +Join condition: None + +(73) ReusedExchange [Reuses operator id: 57] +Output [4]: [i_item_sk#65, i_brand_id#66, i_class_id#67, i_category_id#68] + +(74) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [cs_item_sk#59] +Right keys [1]: [i_item_sk#65] +Join type: Inner +Join condition: None + +(75) Project [codegen id : 51] +Output [6]: [cs_quantity#60, cs_list_price#61, cs_sold_date_sk#62, i_brand_id#66, i_class_id#67, i_category_id#68] +Input [8]: [cs_item_sk#59, cs_quantity#60, cs_list_price#61, cs_sold_date_sk#62, i_item_sk#65, i_brand_id#66, i_class_id#67, i_category_id#68] + +(76) ReusedExchange [Reuses operator id: 129] +Output [1]: [d_date_sk#69] + +(77) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [cs_sold_date_sk#62] +Right keys [1]: [d_date_sk#69] +Join type: Inner +Join condition: None + +(78) Project [codegen id : 51] +Output [5]: [cs_quantity#60, cs_list_price#61, i_brand_id#66, i_class_id#67, i_category_id#68] +Input [7]: [cs_quantity#60, cs_list_price#61, cs_sold_date_sk#62, i_brand_id#66, i_class_id#67, i_category_id#68, d_date_sk#69] + +(79) HashAggregate [codegen id : 51] +Input [5]: [cs_quantity#60, cs_list_price#61, i_brand_id#66, i_class_id#67, i_category_id#68] +Keys [3]: [i_brand_id#66, i_class_id#67, i_category_id#68] +Functions [2]: [partial_sum((cast(cs_quantity#60 as decimal(10,0)) * cs_list_price#61)), partial_count(1)] +Aggregate Attributes [3]: [sum#70, isEmpty#71, count#72] +Results [6]: [i_brand_id#66, i_class_id#67, i_category_id#68, sum#73, isEmpty#74, count#75] + +(80) Exchange +Input [6]: [i_brand_id#66, i_class_id#67, i_category_id#68, sum#73, isEmpty#74, count#75] +Arguments: hashpartitioning(i_brand_id#66, i_class_id#67, i_category_id#68, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(81) HashAggregate [codegen id : 52] +Input [6]: [i_brand_id#66, i_class_id#67, i_category_id#68, sum#73, isEmpty#74, count#75] +Keys [3]: [i_brand_id#66, i_class_id#67, i_category_id#68] +Functions [2]: [sum((cast(cs_quantity#60 as decimal(10,0)) * cs_list_price#61)), count(1)] +Aggregate Attributes [2]: [sum((cast(cs_quantity#60 as decimal(10,0)) * cs_list_price#61))#76, count(1)#77] +Results [5]: [i_brand_id#66, i_class_id#67, i_category_id#68, sum((cast(cs_quantity#60 as decimal(10,0)) * cs_list_price#61))#76 AS sales#78, count(1)#77 AS number_sales#79] + +(82) Filter [codegen id : 52] +Input [5]: [i_brand_id#66, i_class_id#67, i_category_id#68, sales#78, number_sales#79] +Condition : (isnotnull(sales#78) AND (cast(sales#78 as decimal(32,6)) > cast(ReusedSubquery Subquery scalar-subquery#53, [id=#54] as decimal(32,6)))) + +(83) Project [codegen id : 52] +Output [6]: [sales#78, number_sales#79, catalog AS channel#80, i_brand_id#66, i_class_id#67, i_category_id#68] +Input [5]: [i_brand_id#66, i_class_id#67, i_category_id#68, sales#78, number_sales#79] + +(84) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_item_sk#81, ws_quantity#82, ws_list_price#83, ws_sold_date_sk#84] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#84), dynamicpruningexpression(ws_sold_date_sk#84 IN dynamicpruning#85)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(85) CometFilter +Input [4]: [ws_item_sk#81, ws_quantity#82, ws_list_price#83, ws_sold_date_sk#84] +Condition : isnotnull(ws_item_sk#81) + +(86) ColumnarToRow [codegen id : 77] +Input [4]: [ws_item_sk#81, ws_quantity#82, ws_list_price#83, ws_sold_date_sk#84] + +(87) ReusedExchange [Reuses operator id: 50] +Output [1]: [ss_item_sk#86] + +(88) BroadcastHashJoin [codegen id : 77] +Left keys [1]: [ws_item_sk#81] +Right keys [1]: [ss_item_sk#86] +Join type: LeftSemi +Join condition: None + +(89) ReusedExchange [Reuses operator id: 57] +Output [4]: [i_item_sk#87, i_brand_id#88, i_class_id#89, i_category_id#90] + +(90) BroadcastHashJoin [codegen id : 77] +Left keys [1]: [ws_item_sk#81] +Right keys [1]: [i_item_sk#87] +Join type: Inner +Join condition: None + +(91) Project [codegen id : 77] +Output [6]: [ws_quantity#82, ws_list_price#83, ws_sold_date_sk#84, i_brand_id#88, i_class_id#89, i_category_id#90] +Input [8]: [ws_item_sk#81, ws_quantity#82, ws_list_price#83, ws_sold_date_sk#84, i_item_sk#87, i_brand_id#88, i_class_id#89, i_category_id#90] + +(92) ReusedExchange [Reuses operator id: 129] +Output [1]: [d_date_sk#91] + +(93) BroadcastHashJoin [codegen id : 77] +Left keys [1]: [ws_sold_date_sk#84] +Right keys [1]: [d_date_sk#91] +Join type: Inner +Join condition: None + +(94) Project [codegen id : 77] +Output [5]: [ws_quantity#82, ws_list_price#83, i_brand_id#88, i_class_id#89, i_category_id#90] +Input [7]: [ws_quantity#82, ws_list_price#83, ws_sold_date_sk#84, i_brand_id#88, i_class_id#89, i_category_id#90, d_date_sk#91] + +(95) HashAggregate [codegen id : 77] +Input [5]: [ws_quantity#82, ws_list_price#83, i_brand_id#88, i_class_id#89, i_category_id#90] +Keys [3]: [i_brand_id#88, i_class_id#89, i_category_id#90] +Functions [2]: [partial_sum((cast(ws_quantity#82 as decimal(10,0)) * ws_list_price#83)), partial_count(1)] +Aggregate Attributes [3]: [sum#92, isEmpty#93, count#94] +Results [6]: [i_brand_id#88, i_class_id#89, i_category_id#90, sum#95, isEmpty#96, count#97] + +(96) Exchange +Input [6]: [i_brand_id#88, i_class_id#89, i_category_id#90, sum#95, isEmpty#96, count#97] +Arguments: hashpartitioning(i_brand_id#88, i_class_id#89, i_category_id#90, 5), ENSURE_REQUIREMENTS, [plan_id=11] + +(97) HashAggregate [codegen id : 78] +Input [6]: [i_brand_id#88, i_class_id#89, i_category_id#90, sum#95, isEmpty#96, count#97] +Keys [3]: [i_brand_id#88, i_class_id#89, i_category_id#90] +Functions [2]: [sum((cast(ws_quantity#82 as decimal(10,0)) * ws_list_price#83)), count(1)] +Aggregate Attributes [2]: [sum((cast(ws_quantity#82 as decimal(10,0)) * ws_list_price#83))#98, count(1)#99] +Results [5]: [i_brand_id#88, i_class_id#89, i_category_id#90, sum((cast(ws_quantity#82 as decimal(10,0)) * ws_list_price#83))#98 AS sales#100, count(1)#99 AS number_sales#101] + +(98) Filter [codegen id : 78] +Input [5]: [i_brand_id#88, i_class_id#89, i_category_id#90, sales#100, number_sales#101] +Condition : (isnotnull(sales#100) AND (cast(sales#100 as decimal(32,6)) > cast(ReusedSubquery Subquery scalar-subquery#53, [id=#54] as decimal(32,6)))) + +(99) Project [codegen id : 78] +Output [6]: [sales#100, number_sales#101, web AS channel#102, i_brand_id#88, i_class_id#89, i_category_id#90] +Input [5]: [i_brand_id#88, i_class_id#89, i_category_id#90, sales#100, number_sales#101] + +(100) Union + +(101) Expand [codegen id : 79] +Input [6]: [sales#51, number_sales#52, channel#55, i_brand_id#56, i_class_id#57, i_category_id#58] +Arguments: [[sales#51, number_sales#52, channel#55, i_brand_id#56, i_class_id#57, i_category_id#58, 0], [sales#51, number_sales#52, channel#55, i_brand_id#56, i_class_id#57, null, 1], [sales#51, number_sales#52, channel#55, i_brand_id#56, null, null, 3], [sales#51, number_sales#52, channel#55, null, null, null, 7], [sales#51, number_sales#52, null, null, null, null, 15]], [sales#51, number_sales#52, channel#103, i_brand_id#104, i_class_id#105, i_category_id#106, spark_grouping_id#107] + +(102) HashAggregate [codegen id : 79] +Input [7]: [sales#51, number_sales#52, channel#103, i_brand_id#104, i_class_id#105, i_category_id#106, spark_grouping_id#107] +Keys [5]: [channel#103, i_brand_id#104, i_class_id#105, i_category_id#106, spark_grouping_id#107] +Functions [2]: [partial_sum(sales#51), partial_sum(number_sales#52)] +Aggregate Attributes [3]: [sum#108, isEmpty#109, sum#110] +Results [8]: [channel#103, i_brand_id#104, i_class_id#105, i_category_id#106, spark_grouping_id#107, sum#111, isEmpty#112, sum#113] + +(103) Exchange +Input [8]: [channel#103, i_brand_id#104, i_class_id#105, i_category_id#106, spark_grouping_id#107, sum#111, isEmpty#112, sum#113] +Arguments: hashpartitioning(channel#103, i_brand_id#104, i_class_id#105, i_category_id#106, spark_grouping_id#107, 5), ENSURE_REQUIREMENTS, [plan_id=12] + +(104) HashAggregate [codegen id : 80] +Input [8]: [channel#103, i_brand_id#104, i_class_id#105, i_category_id#106, spark_grouping_id#107, sum#111, isEmpty#112, sum#113] +Keys [5]: [channel#103, i_brand_id#104, i_class_id#105, i_category_id#106, spark_grouping_id#107] +Functions [2]: [sum(sales#51), sum(number_sales#52)] +Aggregate Attributes [2]: [sum(sales#51)#114, sum(number_sales#52)#115] +Results [6]: [channel#103, i_brand_id#104, i_class_id#105, i_category_id#106, sum(sales#51)#114 AS sum(sales)#116, sum(number_sales#52)#115 AS sum(number_sales)#117] + +(105) TakeOrderedAndProject +Input [6]: [channel#103, i_brand_id#104, i_class_id#105, i_category_id#106, sum(sales)#116, sum(number_sales)#117] +Arguments: 100, [channel#103 ASC NULLS FIRST, i_brand_id#104 ASC NULLS FIRST, i_class_id#105 ASC NULLS FIRST, i_category_id#106 ASC NULLS FIRST], [channel#103, i_brand_id#104, i_class_id#105, i_category_id#106, sum(sales)#116, sum(number_sales)#117] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 66 Hosting Expression = Subquery scalar-subquery#53, [id=#54] +* HashAggregate (124) ++- Exchange (123) + +- * HashAggregate (122) + +- Union (121) + :- * Project (110) + : +- * BroadcastHashJoin Inner BuildRight (109) + : :- * ColumnarToRow (107) + : : +- CometScan parquet spark_catalog.default.store_sales (106) + : +- ReusedExchange (108) + :- * Project (115) + : +- * BroadcastHashJoin Inner BuildRight (114) + : :- * ColumnarToRow (112) + : : +- CometScan parquet spark_catalog.default.catalog_sales (111) + : +- ReusedExchange (113) + +- * Project (120) + +- * BroadcastHashJoin Inner BuildRight (119) + :- * ColumnarToRow (117) + : +- CometScan parquet spark_catalog.default.web_sales (116) + +- ReusedExchange (118) + + +(106) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_quantity#118, ss_list_price#119, ss_sold_date_sk#120] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#120), dynamicpruningexpression(ss_sold_date_sk#120 IN dynamicpruning#121)] +ReadSchema: struct + +(107) ColumnarToRow [codegen id : 2] +Input [3]: [ss_quantity#118, ss_list_price#119, ss_sold_date_sk#120] + +(108) ReusedExchange [Reuses operator id: 134] +Output [1]: [d_date_sk#122] + +(109) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [ss_sold_date_sk#120] +Right keys [1]: [d_date_sk#122] +Join type: Inner +Join condition: None + +(110) Project [codegen id : 2] +Output [2]: [ss_quantity#118 AS quantity#123, ss_list_price#119 AS list_price#124] +Input [4]: [ss_quantity#118, ss_list_price#119, ss_sold_date_sk#120, d_date_sk#122] + +(111) Scan parquet spark_catalog.default.catalog_sales +Output [3]: [cs_quantity#125, cs_list_price#126, cs_sold_date_sk#127] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#127), dynamicpruningexpression(cs_sold_date_sk#127 IN dynamicpruning#128)] +ReadSchema: struct + +(112) ColumnarToRow [codegen id : 4] +Input [3]: [cs_quantity#125, cs_list_price#126, cs_sold_date_sk#127] + +(113) ReusedExchange [Reuses operator id: 134] +Output [1]: [d_date_sk#129] + +(114) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [cs_sold_date_sk#127] +Right keys [1]: [d_date_sk#129] +Join type: Inner +Join condition: None + +(115) Project [codegen id : 4] +Output [2]: [cs_quantity#125 AS quantity#130, cs_list_price#126 AS list_price#131] +Input [4]: [cs_quantity#125, cs_list_price#126, cs_sold_date_sk#127, d_date_sk#129] + +(116) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_quantity#132, ws_list_price#133, ws_sold_date_sk#134] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#134), dynamicpruningexpression(ws_sold_date_sk#134 IN dynamicpruning#135)] +ReadSchema: struct + +(117) ColumnarToRow [codegen id : 6] +Input [3]: [ws_quantity#132, ws_list_price#133, ws_sold_date_sk#134] + +(118) ReusedExchange [Reuses operator id: 134] +Output [1]: [d_date_sk#136] + +(119) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ws_sold_date_sk#134] +Right keys [1]: [d_date_sk#136] +Join type: Inner +Join condition: None + +(120) Project [codegen id : 6] +Output [2]: [ws_quantity#132 AS quantity#137, ws_list_price#133 AS list_price#138] +Input [4]: [ws_quantity#132, ws_list_price#133, ws_sold_date_sk#134, d_date_sk#136] + +(121) Union + +(122) HashAggregate [codegen id : 7] +Input [2]: [quantity#123, list_price#124] +Keys: [] +Functions [1]: [partial_avg((cast(quantity#123 as decimal(10,0)) * list_price#124))] +Aggregate Attributes [2]: [sum#139, count#140] +Results [2]: [sum#141, count#142] + +(123) Exchange +Input [2]: [sum#141, count#142] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=13] + +(124) HashAggregate [codegen id : 8] +Input [2]: [sum#141, count#142] +Keys: [] +Functions [1]: [avg((cast(quantity#123 as decimal(10,0)) * list_price#124))] +Aggregate Attributes [1]: [avg((cast(quantity#123 as decimal(10,0)) * list_price#124))#143] +Results [1]: [avg((cast(quantity#123 as decimal(10,0)) * list_price#124))#143 AS average_sales#144] + +Subquery:2 Hosting operator id = 106 Hosting Expression = ss_sold_date_sk#120 IN dynamicpruning#12 + +Subquery:3 Hosting operator id = 111 Hosting Expression = cs_sold_date_sk#127 IN dynamicpruning#12 + +Subquery:4 Hosting operator id = 116 Hosting Expression = ws_sold_date_sk#134 IN dynamicpruning#12 + +Subquery:5 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (129) ++- * ColumnarToRow (128) + +- CometProject (127) + +- CometFilter (126) + +- CometScan parquet spark_catalog.default.date_dim (125) + + +(125) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#42, d_year#145, d_moy#146] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2001), EqualTo(d_moy,11), IsNotNull(d_date_sk)] +ReadSchema: struct + +(126) CometFilter +Input [3]: [d_date_sk#42, d_year#145, d_moy#146] +Condition : ((((isnotnull(d_year#145) AND isnotnull(d_moy#146)) AND (d_year#145 = 2001)) AND (d_moy#146 = 11)) AND isnotnull(d_date_sk#42)) + +(127) CometProject +Input [3]: [d_date_sk#42, d_year#145, d_moy#146] +Arguments: [d_date_sk#42], [d_date_sk#42] + +(128) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#42] + +(129) BroadcastExchange +Input [1]: [d_date_sk#42] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=14] + +Subquery:6 Hosting operator id = 7 Hosting Expression = ss_sold_date_sk#11 IN dynamicpruning#12 +BroadcastExchange (134) ++- * ColumnarToRow (133) + +- CometProject (132) + +- CometFilter (131) + +- CometScan parquet spark_catalog.default.date_dim (130) + + +(130) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#25, d_year#147] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), GreaterThanOrEqual(d_year,1999), LessThanOrEqual(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(131) CometFilter +Input [2]: [d_date_sk#25, d_year#147] +Condition : (((isnotnull(d_year#147) AND (d_year#147 >= 1999)) AND (d_year#147 <= 2001)) AND isnotnull(d_date_sk#25)) + +(132) CometProject +Input [2]: [d_date_sk#25, d_year#147] +Arguments: [d_date_sk#25], [d_date_sk#25] + +(133) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#25] + +(134) BroadcastExchange +Input [1]: [d_date_sk#25] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=15] + +Subquery:7 Hosting operator id = 13 Hosting Expression = cs_sold_date_sk#18 IN dynamicpruning#12 + +Subquery:8 Hosting operator id = 36 Hosting Expression = ws_sold_date_sk#30 IN dynamicpruning#12 + +Subquery:9 Hosting operator id = 82 Hosting Expression = ReusedSubquery Subquery scalar-subquery#53, [id=#54] + +Subquery:10 Hosting operator id = 68 Hosting Expression = cs_sold_date_sk#62 IN dynamicpruning#5 + +Subquery:11 Hosting operator id = 98 Hosting Expression = ReusedSubquery Subquery scalar-subquery#53, [id=#54] + +Subquery:12 Hosting operator id = 84 Hosting Expression = ws_sold_date_sk#84 IN dynamicpruning#5 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14a/simplified.txt new file mode 100644 index 0000000000..cf688c4486 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14a/simplified.txt @@ -0,0 +1,214 @@ +TakeOrderedAndProject [channel,i_brand_id,i_class_id,i_category_id,sum(sales),sum(number_sales)] + WholeStageCodegen (80) + HashAggregate [channel,i_brand_id,i_class_id,i_category_id,spark_grouping_id,sum,isEmpty,sum] [sum(sales),sum(number_salesL),sum(sales),sum(number_sales),sum,isEmpty,sum] + InputAdapter + Exchange [channel,i_brand_id,i_class_id,i_category_id,spark_grouping_id] #1 + WholeStageCodegen (79) + HashAggregate [channel,i_brand_id,i_class_id,i_category_id,spark_grouping_id,sales,number_sales] [sum,isEmpty,sum,sum,isEmpty,sum] + Expand [sales,number_sales,channel,i_brand_id,i_class_id,i_category_id] + InputAdapter + Union + WholeStageCodegen (26) + Project [sales,number_sales,i_brand_id,i_class_id,i_category_id] + Filter [sales] + Subquery #3 + WholeStageCodegen (8) + HashAggregate [sum,count] [avg((cast(quantity as decimal(10,0)) * list_price)),average_sales,sum,count] + InputAdapter + Exchange #13 + WholeStageCodegen (7) + HashAggregate [quantity,list_price] [sum,count,sum,count] + InputAdapter + Union + WholeStageCodegen (2) + Project [ss_quantity,ss_list_price] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_list_price,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk] #7 + WholeStageCodegen (4) + Project [cs_quantity,cs_list_price] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_quantity,cs_list_price,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk] #7 + WholeStageCodegen (6) + Project [ws_quantity,ws_list_price] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_quantity,ws_list_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk] #7 + HashAggregate [i_brand_id,i_class_id,i_category_id,sum,isEmpty,count] [sum((cast(ss_quantity as decimal(10,0)) * ss_list_price)),count(1),sales,number_sales,sum,isEmpty,count] + InputAdapter + Exchange [i_brand_id,i_class_id,i_category_id] #2 + WholeStageCodegen (25) + HashAggregate [i_brand_id,i_class_id,i_category_id,ss_quantity,ss_list_price] [sum,isEmpty,count,sum,isEmpty,count] + Project [ss_quantity,ss_list_price,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_quantity,ss_list_price,ss_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + BroadcastHashJoin [ss_item_sk,ss_item_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_quantity,ss_list_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_moy,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (11) + Project [i_item_sk] + BroadcastHashJoin [i_brand_id,i_class_id,i_category_id,brand_id,class_id,category_id] + ColumnarToRow + InputAdapter + CometFilter [i_brand_id,i_class_id,i_category_id] + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (10) + BroadcastHashJoin [brand_id,class_id,category_id,i_brand_id,i_class_id,i_category_id] + HashAggregate [brand_id,class_id,category_id] + InputAdapter + Exchange [brand_id,class_id,category_id] #6 + WholeStageCodegen (6) + HashAggregate [brand_id,class_id,category_id] + Project [i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #7 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (4) + BroadcastHashJoin [i_brand_id,i_class_id,i_category_id,i_brand_id,i_class_id,i_category_id] + ColumnarToRow + InputAdapter + CometFilter [i_item_sk,i_brand_id,i_class_id,i_category_id] + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] + InputAdapter + BroadcastExchange #9 + WholeStageCodegen (3) + Project [i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + BroadcastExchange #10 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] + InputAdapter + ReusedExchange [d_date_sk] #7 + InputAdapter + ReusedExchange [d_date_sk] #7 + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (9) + Project [i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ws_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id] #10 + InputAdapter + ReusedExchange [d_date_sk] #7 + InputAdapter + BroadcastExchange #12 + WholeStageCodegen (23) + BroadcastHashJoin [i_item_sk,ss_item_sk] + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] + InputAdapter + ReusedExchange [ss_item_sk] #4 + InputAdapter + ReusedExchange [d_date_sk] #3 + WholeStageCodegen (52) + Project [sales,number_sales,i_brand_id,i_class_id,i_category_id] + Filter [sales] + ReusedSubquery [average_sales] #3 + HashAggregate [i_brand_id,i_class_id,i_category_id,sum,isEmpty,count] [sum((cast(cs_quantity as decimal(10,0)) * cs_list_price)),count(1),sales,number_sales,sum,isEmpty,count] + InputAdapter + Exchange [i_brand_id,i_class_id,i_category_id] #14 + WholeStageCodegen (51) + HashAggregate [i_brand_id,i_class_id,i_category_id,cs_quantity,cs_list_price] [sum,isEmpty,count,sum,isEmpty,count] + Project [cs_quantity,cs_list_price,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_quantity,cs_list_price,cs_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + BroadcastHashJoin [cs_item_sk,ss_item_sk] + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_quantity,cs_list_price,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [ss_item_sk] #4 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id] #12 + InputAdapter + ReusedExchange [d_date_sk] #3 + WholeStageCodegen (78) + Project [sales,number_sales,i_brand_id,i_class_id,i_category_id] + Filter [sales] + ReusedSubquery [average_sales] #3 + HashAggregate [i_brand_id,i_class_id,i_category_id,sum,isEmpty,count] [sum((cast(ws_quantity as decimal(10,0)) * ws_list_price)),count(1),sales,number_sales,sum,isEmpty,count] + InputAdapter + Exchange [i_brand_id,i_class_id,i_category_id] #15 + WholeStageCodegen (77) + HashAggregate [i_brand_id,i_class_id,i_category_id,ws_quantity,ws_list_price] [sum,isEmpty,count,sum,isEmpty,count] + Project [ws_quantity,ws_list_price,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_quantity,ws_list_price,ws_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ws_item_sk,i_item_sk] + BroadcastHashJoin [ws_item_sk,ss_item_sk] + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_quantity,ws_list_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [ss_item_sk] #4 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id] #12 + InputAdapter + ReusedExchange [d_date_sk] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14b/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14b/explain.txt new file mode 100644 index 0000000000..265909ec28 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14b/explain.txt @@ -0,0 +1,759 @@ +== Physical Plan == +TakeOrderedAndProject (84) ++- * BroadcastHashJoin Inner BuildRight (83) + :- * Filter (66) + : +- * HashAggregate (65) + : +- Exchange (64) + : +- * HashAggregate (63) + : +- * Project (62) + : +- * BroadcastHashJoin Inner BuildRight (61) + : :- * Project (59) + : : +- * BroadcastHashJoin Inner BuildRight (58) + : : :- * BroadcastHashJoin LeftSemi BuildRight (51) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- BroadcastExchange (50) + : : : +- * Project (49) + : : : +- * BroadcastHashJoin Inner BuildRight (48) + : : : :- * ColumnarToRow (6) + : : : : +- CometFilter (5) + : : : : +- CometScan parquet spark_catalog.default.item (4) + : : : +- BroadcastExchange (47) + : : : +- * BroadcastHashJoin LeftSemi BuildRight (46) + : : : :- * HashAggregate (35) + : : : : +- Exchange (34) + : : : : +- * HashAggregate (33) + : : : : +- * Project (32) + : : : : +- * BroadcastHashJoin Inner BuildRight (31) + : : : : :- * Project (29) + : : : : : +- * BroadcastHashJoin Inner BuildRight (28) + : : : : : :- * ColumnarToRow (9) + : : : : : : +- CometFilter (8) + : : : : : : +- CometScan parquet spark_catalog.default.store_sales (7) + : : : : : +- BroadcastExchange (27) + : : : : : +- * BroadcastHashJoin LeftSemi BuildRight (26) + : : : : : :- * ColumnarToRow (12) + : : : : : : +- CometFilter (11) + : : : : : : +- CometScan parquet spark_catalog.default.item (10) + : : : : : +- BroadcastExchange (25) + : : : : : +- * Project (24) + : : : : : +- * BroadcastHashJoin Inner BuildRight (23) + : : : : : :- * Project (21) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (20) + : : : : : : :- * ColumnarToRow (15) + : : : : : : : +- CometFilter (14) + : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (13) + : : : : : : +- BroadcastExchange (19) + : : : : : : +- * ColumnarToRow (18) + : : : : : : +- CometFilter (17) + : : : : : : +- CometScan parquet spark_catalog.default.item (16) + : : : : : +- ReusedExchange (22) + : : : : +- ReusedExchange (30) + : : : +- BroadcastExchange (45) + : : : +- * Project (44) + : : : +- * BroadcastHashJoin Inner BuildRight (43) + : : : :- * Project (41) + : : : : +- * BroadcastHashJoin Inner BuildRight (40) + : : : : :- * ColumnarToRow (38) + : : : : : +- CometFilter (37) + : : : : : +- CometScan parquet spark_catalog.default.web_sales (36) + : : : : +- ReusedExchange (39) + : : : +- ReusedExchange (42) + : : +- BroadcastExchange (57) + : : +- * BroadcastHashJoin LeftSemi BuildRight (56) + : : :- * ColumnarToRow (54) + : : : +- CometFilter (53) + : : : +- CometScan parquet spark_catalog.default.item (52) + : : +- ReusedExchange (55) + : +- ReusedExchange (60) + +- BroadcastExchange (82) + +- * Filter (81) + +- * HashAggregate (80) + +- Exchange (79) + +- * HashAggregate (78) + +- * Project (77) + +- * BroadcastHashJoin Inner BuildRight (76) + :- * Project (74) + : +- * BroadcastHashJoin Inner BuildRight (73) + : :- * BroadcastHashJoin LeftSemi BuildRight (71) + : : :- * ColumnarToRow (69) + : : : +- CometFilter (68) + : : : +- CometScan parquet spark_catalog.default.store_sales (67) + : : +- ReusedExchange (70) + : +- ReusedExchange (72) + +- ReusedExchange (75) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#4), dynamicpruningexpression(ss_sold_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4] +Condition : isnotnull(ss_item_sk#1) + +(3) ColumnarToRow [codegen id : 25] +Input [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4] + +(4) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id)] +ReadSchema: struct + +(5) CometFilter +Input [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] +Condition : ((isnotnull(i_brand_id#7) AND isnotnull(i_class_id#8)) AND isnotnull(i_category_id#9)) + +(6) ColumnarToRow [codegen id : 11] +Input [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] + +(7) Scan parquet spark_catalog.default.store_sales +Output [2]: [ss_item_sk#10, ss_sold_date_sk#11] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#11), dynamicpruningexpression(ss_sold_date_sk#11 IN dynamicpruning#12)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(8) CometFilter +Input [2]: [ss_item_sk#10, ss_sold_date_sk#11] +Condition : isnotnull(ss_item_sk#10) + +(9) ColumnarToRow [codegen id : 6] +Input [2]: [ss_item_sk#10, ss_sold_date_sk#11] + +(10) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id)] +ReadSchema: struct + +(11) CometFilter +Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] +Condition : (((isnotnull(i_item_sk#13) AND isnotnull(i_brand_id#14)) AND isnotnull(i_class_id#15)) AND isnotnull(i_category_id#16)) + +(12) ColumnarToRow [codegen id : 4] +Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] + +(13) Scan parquet spark_catalog.default.catalog_sales +Output [2]: [cs_item_sk#17, cs_sold_date_sk#18] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#18), dynamicpruningexpression(cs_sold_date_sk#18 IN dynamicpruning#19)] +PushedFilters: [IsNotNull(cs_item_sk)] +ReadSchema: struct + +(14) CometFilter +Input [2]: [cs_item_sk#17, cs_sold_date_sk#18] +Condition : isnotnull(cs_item_sk#17) + +(15) ColumnarToRow [codegen id : 3] +Input [2]: [cs_item_sk#17, cs_sold_date_sk#18] + +(16) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(17) CometFilter +Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] +Condition : isnotnull(i_item_sk#20) + +(18) ColumnarToRow [codegen id : 1] +Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] + +(19) BroadcastExchange +Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(20) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cs_item_sk#17] +Right keys [1]: [i_item_sk#20] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 3] +Output [4]: [cs_sold_date_sk#18, i_brand_id#21, i_class_id#22, i_category_id#23] +Input [6]: [cs_item_sk#17, cs_sold_date_sk#18, i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] + +(22) ReusedExchange [Reuses operator id: 117] +Output [1]: [d_date_sk#24] + +(23) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cs_sold_date_sk#18] +Right keys [1]: [d_date_sk#24] +Join type: Inner +Join condition: None + +(24) Project [codegen id : 3] +Output [3]: [i_brand_id#21, i_class_id#22, i_category_id#23] +Input [5]: [cs_sold_date_sk#18, i_brand_id#21, i_class_id#22, i_category_id#23, d_date_sk#24] + +(25) BroadcastExchange +Input [3]: [i_brand_id#21, i_class_id#22, i_category_id#23] +Arguments: HashedRelationBroadcastMode(List(coalesce(input[0, int, true], 0), isnull(input[0, int, true]), coalesce(input[1, int, true], 0), isnull(input[1, int, true]), coalesce(input[2, int, true], 0), isnull(input[2, int, true])),false), [plan_id=2] + +(26) BroadcastHashJoin [codegen id : 4] +Left keys [6]: [coalesce(i_brand_id#14, 0), isnull(i_brand_id#14), coalesce(i_class_id#15, 0), isnull(i_class_id#15), coalesce(i_category_id#16, 0), isnull(i_category_id#16)] +Right keys [6]: [coalesce(i_brand_id#21, 0), isnull(i_brand_id#21), coalesce(i_class_id#22, 0), isnull(i_class_id#22), coalesce(i_category_id#23, 0), isnull(i_category_id#23)] +Join type: LeftSemi +Join condition: None + +(27) BroadcastExchange +Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(28) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_item_sk#10] +Right keys [1]: [i_item_sk#13] +Join type: Inner +Join condition: None + +(29) Project [codegen id : 6] +Output [4]: [ss_sold_date_sk#11, i_brand_id#14, i_class_id#15, i_category_id#16] +Input [6]: [ss_item_sk#10, ss_sold_date_sk#11, i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] + +(30) ReusedExchange [Reuses operator id: 117] +Output [1]: [d_date_sk#25] + +(31) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_sold_date_sk#11] +Right keys [1]: [d_date_sk#25] +Join type: Inner +Join condition: None + +(32) Project [codegen id : 6] +Output [3]: [i_brand_id#14 AS brand_id#26, i_class_id#15 AS class_id#27, i_category_id#16 AS category_id#28] +Input [5]: [ss_sold_date_sk#11, i_brand_id#14, i_class_id#15, i_category_id#16, d_date_sk#25] + +(33) HashAggregate [codegen id : 6] +Input [3]: [brand_id#26, class_id#27, category_id#28] +Keys [3]: [brand_id#26, class_id#27, category_id#28] +Functions: [] +Aggregate Attributes: [] +Results [3]: [brand_id#26, class_id#27, category_id#28] + +(34) Exchange +Input [3]: [brand_id#26, class_id#27, category_id#28] +Arguments: hashpartitioning(brand_id#26, class_id#27, category_id#28, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(35) HashAggregate [codegen id : 10] +Input [3]: [brand_id#26, class_id#27, category_id#28] +Keys [3]: [brand_id#26, class_id#27, category_id#28] +Functions: [] +Aggregate Attributes: [] +Results [3]: [brand_id#26, class_id#27, category_id#28] + +(36) Scan parquet spark_catalog.default.web_sales +Output [2]: [ws_item_sk#29, ws_sold_date_sk#30] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#30), dynamicpruningexpression(ws_sold_date_sk#30 IN dynamicpruning#31)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(37) CometFilter +Input [2]: [ws_item_sk#29, ws_sold_date_sk#30] +Condition : isnotnull(ws_item_sk#29) + +(38) ColumnarToRow [codegen id : 9] +Input [2]: [ws_item_sk#29, ws_sold_date_sk#30] + +(39) ReusedExchange [Reuses operator id: 19] +Output [4]: [i_item_sk#32, i_brand_id#33, i_class_id#34, i_category_id#35] + +(40) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ws_item_sk#29] +Right keys [1]: [i_item_sk#32] +Join type: Inner +Join condition: None + +(41) Project [codegen id : 9] +Output [4]: [ws_sold_date_sk#30, i_brand_id#33, i_class_id#34, i_category_id#35] +Input [6]: [ws_item_sk#29, ws_sold_date_sk#30, i_item_sk#32, i_brand_id#33, i_class_id#34, i_category_id#35] + +(42) ReusedExchange [Reuses operator id: 117] +Output [1]: [d_date_sk#36] + +(43) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ws_sold_date_sk#30] +Right keys [1]: [d_date_sk#36] +Join type: Inner +Join condition: None + +(44) Project [codegen id : 9] +Output [3]: [i_brand_id#33, i_class_id#34, i_category_id#35] +Input [5]: [ws_sold_date_sk#30, i_brand_id#33, i_class_id#34, i_category_id#35, d_date_sk#36] + +(45) BroadcastExchange +Input [3]: [i_brand_id#33, i_class_id#34, i_category_id#35] +Arguments: HashedRelationBroadcastMode(List(coalesce(input[0, int, true], 0), isnull(input[0, int, true]), coalesce(input[1, int, true], 0), isnull(input[1, int, true]), coalesce(input[2, int, true], 0), isnull(input[2, int, true])),false), [plan_id=5] + +(46) BroadcastHashJoin [codegen id : 10] +Left keys [6]: [coalesce(brand_id#26, 0), isnull(brand_id#26), coalesce(class_id#27, 0), isnull(class_id#27), coalesce(category_id#28, 0), isnull(category_id#28)] +Right keys [6]: [coalesce(i_brand_id#33, 0), isnull(i_brand_id#33), coalesce(i_class_id#34, 0), isnull(i_class_id#34), coalesce(i_category_id#35, 0), isnull(i_category_id#35)] +Join type: LeftSemi +Join condition: None + +(47) BroadcastExchange +Input [3]: [brand_id#26, class_id#27, category_id#28] +Arguments: HashedRelationBroadcastMode(List(input[0, int, true], input[1, int, true], input[2, int, true]),false), [plan_id=6] + +(48) BroadcastHashJoin [codegen id : 11] +Left keys [3]: [i_brand_id#7, i_class_id#8, i_category_id#9] +Right keys [3]: [brand_id#26, class_id#27, category_id#28] +Join type: Inner +Join condition: None + +(49) Project [codegen id : 11] +Output [1]: [i_item_sk#6 AS ss_item_sk#37] +Input [7]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9, brand_id#26, class_id#27, category_id#28] + +(50) BroadcastExchange +Input [1]: [ss_item_sk#37] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +(51) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [ss_item_sk#37] +Join type: LeftSemi +Join condition: None + +(52) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id)] +ReadSchema: struct + +(53) CometFilter +Input [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] +Condition : (((isnotnull(i_item_sk#38) AND isnotnull(i_brand_id#39)) AND isnotnull(i_class_id#40)) AND isnotnull(i_category_id#41)) + +(54) ColumnarToRow [codegen id : 23] +Input [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] + +(55) ReusedExchange [Reuses operator id: 50] +Output [1]: [ss_item_sk#37] + +(56) BroadcastHashJoin [codegen id : 23] +Left keys [1]: [i_item_sk#38] +Right keys [1]: [ss_item_sk#37] +Join type: LeftSemi +Join condition: None + +(57) BroadcastExchange +Input [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8] + +(58) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#38] +Join type: Inner +Join condition: None + +(59) Project [codegen id : 25] +Output [6]: [ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4, i_brand_id#39, i_class_id#40, i_category_id#41] +Input [8]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4, i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] + +(60) ReusedExchange [Reuses operator id: 108] +Output [1]: [d_date_sk#42] + +(61) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_sold_date_sk#4] +Right keys [1]: [d_date_sk#42] +Join type: Inner +Join condition: None + +(62) Project [codegen id : 25] +Output [5]: [ss_quantity#2, ss_list_price#3, i_brand_id#39, i_class_id#40, i_category_id#41] +Input [7]: [ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4, i_brand_id#39, i_class_id#40, i_category_id#41, d_date_sk#42] + +(63) HashAggregate [codegen id : 25] +Input [5]: [ss_quantity#2, ss_list_price#3, i_brand_id#39, i_class_id#40, i_category_id#41] +Keys [3]: [i_brand_id#39, i_class_id#40, i_category_id#41] +Functions [2]: [partial_sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3)), partial_count(1)] +Aggregate Attributes [3]: [sum#43, isEmpty#44, count#45] +Results [6]: [i_brand_id#39, i_class_id#40, i_category_id#41, sum#46, isEmpty#47, count#48] + +(64) Exchange +Input [6]: [i_brand_id#39, i_class_id#40, i_category_id#41, sum#46, isEmpty#47, count#48] +Arguments: hashpartitioning(i_brand_id#39, i_class_id#40, i_category_id#41, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(65) HashAggregate [codegen id : 52] +Input [6]: [i_brand_id#39, i_class_id#40, i_category_id#41, sum#46, isEmpty#47, count#48] +Keys [3]: [i_brand_id#39, i_class_id#40, i_category_id#41] +Functions [2]: [sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3)), count(1)] +Aggregate Attributes [2]: [sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3))#49, count(1)#50] +Results [6]: [store AS channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3))#49 AS sales#52, count(1)#50 AS number_sales#53] + +(66) Filter [codegen id : 52] +Input [6]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sales#52, number_sales#53] +Condition : (isnotnull(sales#52) AND (cast(sales#52 as decimal(32,6)) > cast(Subquery scalar-subquery#54, [id=#55] as decimal(32,6)))) + +(67) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#56, ss_quantity#57, ss_list_price#58, ss_sold_date_sk#59] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#59), dynamicpruningexpression(ss_sold_date_sk#59 IN dynamicpruning#60)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(68) CometFilter +Input [4]: [ss_item_sk#56, ss_quantity#57, ss_list_price#58, ss_sold_date_sk#59] +Condition : isnotnull(ss_item_sk#56) + +(69) ColumnarToRow [codegen id : 50] +Input [4]: [ss_item_sk#56, ss_quantity#57, ss_list_price#58, ss_sold_date_sk#59] + +(70) ReusedExchange [Reuses operator id: 50] +Output [1]: [ss_item_sk#61] + +(71) BroadcastHashJoin [codegen id : 50] +Left keys [1]: [ss_item_sk#56] +Right keys [1]: [ss_item_sk#61] +Join type: LeftSemi +Join condition: None + +(72) ReusedExchange [Reuses operator id: 57] +Output [4]: [i_item_sk#62, i_brand_id#63, i_class_id#64, i_category_id#65] + +(73) BroadcastHashJoin [codegen id : 50] +Left keys [1]: [ss_item_sk#56] +Right keys [1]: [i_item_sk#62] +Join type: Inner +Join condition: None + +(74) Project [codegen id : 50] +Output [6]: [ss_quantity#57, ss_list_price#58, ss_sold_date_sk#59, i_brand_id#63, i_class_id#64, i_category_id#65] +Input [8]: [ss_item_sk#56, ss_quantity#57, ss_list_price#58, ss_sold_date_sk#59, i_item_sk#62, i_brand_id#63, i_class_id#64, i_category_id#65] + +(75) ReusedExchange [Reuses operator id: 122] +Output [1]: [d_date_sk#66] + +(76) BroadcastHashJoin [codegen id : 50] +Left keys [1]: [ss_sold_date_sk#59] +Right keys [1]: [d_date_sk#66] +Join type: Inner +Join condition: None + +(77) Project [codegen id : 50] +Output [5]: [ss_quantity#57, ss_list_price#58, i_brand_id#63, i_class_id#64, i_category_id#65] +Input [7]: [ss_quantity#57, ss_list_price#58, ss_sold_date_sk#59, i_brand_id#63, i_class_id#64, i_category_id#65, d_date_sk#66] + +(78) HashAggregate [codegen id : 50] +Input [5]: [ss_quantity#57, ss_list_price#58, i_brand_id#63, i_class_id#64, i_category_id#65] +Keys [3]: [i_brand_id#63, i_class_id#64, i_category_id#65] +Functions [2]: [partial_sum((cast(ss_quantity#57 as decimal(10,0)) * ss_list_price#58)), partial_count(1)] +Aggregate Attributes [3]: [sum#67, isEmpty#68, count#69] +Results [6]: [i_brand_id#63, i_class_id#64, i_category_id#65, sum#70, isEmpty#71, count#72] + +(79) Exchange +Input [6]: [i_brand_id#63, i_class_id#64, i_category_id#65, sum#70, isEmpty#71, count#72] +Arguments: hashpartitioning(i_brand_id#63, i_class_id#64, i_category_id#65, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(80) HashAggregate [codegen id : 51] +Input [6]: [i_brand_id#63, i_class_id#64, i_category_id#65, sum#70, isEmpty#71, count#72] +Keys [3]: [i_brand_id#63, i_class_id#64, i_category_id#65] +Functions [2]: [sum((cast(ss_quantity#57 as decimal(10,0)) * ss_list_price#58)), count(1)] +Aggregate Attributes [2]: [sum((cast(ss_quantity#57 as decimal(10,0)) * ss_list_price#58))#73, count(1)#74] +Results [6]: [store AS channel#75, i_brand_id#63, i_class_id#64, i_category_id#65, sum((cast(ss_quantity#57 as decimal(10,0)) * ss_list_price#58))#73 AS sales#76, count(1)#74 AS number_sales#77] + +(81) Filter [codegen id : 51] +Input [6]: [channel#75, i_brand_id#63, i_class_id#64, i_category_id#65, sales#76, number_sales#77] +Condition : (isnotnull(sales#76) AND (cast(sales#76 as decimal(32,6)) > cast(ReusedSubquery Subquery scalar-subquery#54, [id=#55] as decimal(32,6)))) + +(82) BroadcastExchange +Input [6]: [channel#75, i_brand_id#63, i_class_id#64, i_category_id#65, sales#76, number_sales#77] +Arguments: HashedRelationBroadcastMode(List(input[1, int, true], input[2, int, true], input[3, int, true]),false), [plan_id=11] + +(83) BroadcastHashJoin [codegen id : 52] +Left keys [3]: [i_brand_id#39, i_class_id#40, i_category_id#41] +Right keys [3]: [i_brand_id#63, i_class_id#64, i_category_id#65] +Join type: Inner +Join condition: None + +(84) TakeOrderedAndProject +Input [12]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sales#52, number_sales#53, channel#75, i_brand_id#63, i_class_id#64, i_category_id#65, sales#76, number_sales#77] +Arguments: 100, [i_brand_id#39 ASC NULLS FIRST, i_class_id#40 ASC NULLS FIRST, i_category_id#41 ASC NULLS FIRST], [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sales#52, number_sales#53, channel#75, i_brand_id#63, i_class_id#64, i_category_id#65, sales#76, number_sales#77] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 66 Hosting Expression = Subquery scalar-subquery#54, [id=#55] +* HashAggregate (103) ++- Exchange (102) + +- * HashAggregate (101) + +- Union (100) + :- * Project (89) + : +- * BroadcastHashJoin Inner BuildRight (88) + : :- * ColumnarToRow (86) + : : +- CometScan parquet spark_catalog.default.store_sales (85) + : +- ReusedExchange (87) + :- * Project (94) + : +- * BroadcastHashJoin Inner BuildRight (93) + : :- * ColumnarToRow (91) + : : +- CometScan parquet spark_catalog.default.catalog_sales (90) + : +- ReusedExchange (92) + +- * Project (99) + +- * BroadcastHashJoin Inner BuildRight (98) + :- * ColumnarToRow (96) + : +- CometScan parquet spark_catalog.default.web_sales (95) + +- ReusedExchange (97) + + +(85) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_quantity#78, ss_list_price#79, ss_sold_date_sk#80] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#80), dynamicpruningexpression(ss_sold_date_sk#80 IN dynamicpruning#81)] +ReadSchema: struct + +(86) ColumnarToRow [codegen id : 2] +Input [3]: [ss_quantity#78, ss_list_price#79, ss_sold_date_sk#80] + +(87) ReusedExchange [Reuses operator id: 117] +Output [1]: [d_date_sk#82] + +(88) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [ss_sold_date_sk#80] +Right keys [1]: [d_date_sk#82] +Join type: Inner +Join condition: None + +(89) Project [codegen id : 2] +Output [2]: [ss_quantity#78 AS quantity#83, ss_list_price#79 AS list_price#84] +Input [4]: [ss_quantity#78, ss_list_price#79, ss_sold_date_sk#80, d_date_sk#82] + +(90) Scan parquet spark_catalog.default.catalog_sales +Output [3]: [cs_quantity#85, cs_list_price#86, cs_sold_date_sk#87] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#87), dynamicpruningexpression(cs_sold_date_sk#87 IN dynamicpruning#88)] +ReadSchema: struct + +(91) ColumnarToRow [codegen id : 4] +Input [3]: [cs_quantity#85, cs_list_price#86, cs_sold_date_sk#87] + +(92) ReusedExchange [Reuses operator id: 117] +Output [1]: [d_date_sk#89] + +(93) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [cs_sold_date_sk#87] +Right keys [1]: [d_date_sk#89] +Join type: Inner +Join condition: None + +(94) Project [codegen id : 4] +Output [2]: [cs_quantity#85 AS quantity#90, cs_list_price#86 AS list_price#91] +Input [4]: [cs_quantity#85, cs_list_price#86, cs_sold_date_sk#87, d_date_sk#89] + +(95) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_quantity#92, ws_list_price#93, ws_sold_date_sk#94] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#94), dynamicpruningexpression(ws_sold_date_sk#94 IN dynamicpruning#95)] +ReadSchema: struct + +(96) ColumnarToRow [codegen id : 6] +Input [3]: [ws_quantity#92, ws_list_price#93, ws_sold_date_sk#94] + +(97) ReusedExchange [Reuses operator id: 117] +Output [1]: [d_date_sk#96] + +(98) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ws_sold_date_sk#94] +Right keys [1]: [d_date_sk#96] +Join type: Inner +Join condition: None + +(99) Project [codegen id : 6] +Output [2]: [ws_quantity#92 AS quantity#97, ws_list_price#93 AS list_price#98] +Input [4]: [ws_quantity#92, ws_list_price#93, ws_sold_date_sk#94, d_date_sk#96] + +(100) Union + +(101) HashAggregate [codegen id : 7] +Input [2]: [quantity#83, list_price#84] +Keys: [] +Functions [1]: [partial_avg((cast(quantity#83 as decimal(10,0)) * list_price#84))] +Aggregate Attributes [2]: [sum#99, count#100] +Results [2]: [sum#101, count#102] + +(102) Exchange +Input [2]: [sum#101, count#102] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=12] + +(103) HashAggregate [codegen id : 8] +Input [2]: [sum#101, count#102] +Keys: [] +Functions [1]: [avg((cast(quantity#83 as decimal(10,0)) * list_price#84))] +Aggregate Attributes [1]: [avg((cast(quantity#83 as decimal(10,0)) * list_price#84))#103] +Results [1]: [avg((cast(quantity#83 as decimal(10,0)) * list_price#84))#103 AS average_sales#104] + +Subquery:2 Hosting operator id = 85 Hosting Expression = ss_sold_date_sk#80 IN dynamicpruning#12 + +Subquery:3 Hosting operator id = 90 Hosting Expression = cs_sold_date_sk#87 IN dynamicpruning#12 + +Subquery:4 Hosting operator id = 95 Hosting Expression = ws_sold_date_sk#94 IN dynamicpruning#12 + +Subquery:5 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (108) ++- * ColumnarToRow (107) + +- CometProject (106) + +- CometFilter (105) + +- CometScan parquet spark_catalog.default.date_dim (104) + + +(104) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#42, d_week_seq#105] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_week_seq), EqualTo(d_week_seq,ScalarSubquery#106), IsNotNull(d_date_sk)] +ReadSchema: struct + +(105) CometFilter +Input [2]: [d_date_sk#42, d_week_seq#105] +Condition : ((isnotnull(d_week_seq#105) AND (d_week_seq#105 = ReusedSubquery Subquery scalar-subquery#106, [id=#107])) AND isnotnull(d_date_sk#42)) + +(106) CometProject +Input [2]: [d_date_sk#42, d_week_seq#105] +Arguments: [d_date_sk#42], [d_date_sk#42] + +(107) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#42] + +(108) BroadcastExchange +Input [1]: [d_date_sk#42] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=13] + +Subquery:6 Hosting operator id = 105 Hosting Expression = ReusedSubquery Subquery scalar-subquery#106, [id=#107] + +Subquery:7 Hosting operator id = 104 Hosting Expression = Subquery scalar-subquery#106, [id=#107] +* ColumnarToRow (112) ++- CometProject (111) + +- CometFilter (110) + +- CometScan parquet spark_catalog.default.date_dim (109) + + +(109) Scan parquet spark_catalog.default.date_dim +Output [4]: [d_week_seq#108, d_year#109, d_moy#110, d_dom#111] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), IsNotNull(d_dom), EqualTo(d_year,2000), EqualTo(d_moy,12), EqualTo(d_dom,11)] +ReadSchema: struct + +(110) CometFilter +Input [4]: [d_week_seq#108, d_year#109, d_moy#110, d_dom#111] +Condition : (((((isnotnull(d_year#109) AND isnotnull(d_moy#110)) AND isnotnull(d_dom#111)) AND (d_year#109 = 2000)) AND (d_moy#110 = 12)) AND (d_dom#111 = 11)) + +(111) CometProject +Input [4]: [d_week_seq#108, d_year#109, d_moy#110, d_dom#111] +Arguments: [d_week_seq#108], [d_week_seq#108] + +(112) ColumnarToRow [codegen id : 1] +Input [1]: [d_week_seq#108] + +Subquery:8 Hosting operator id = 7 Hosting Expression = ss_sold_date_sk#11 IN dynamicpruning#12 +BroadcastExchange (117) ++- * ColumnarToRow (116) + +- CometProject (115) + +- CometFilter (114) + +- CometScan parquet spark_catalog.default.date_dim (113) + + +(113) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#25, d_year#112] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), GreaterThanOrEqual(d_year,1999), LessThanOrEqual(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(114) CometFilter +Input [2]: [d_date_sk#25, d_year#112] +Condition : (((isnotnull(d_year#112) AND (d_year#112 >= 1999)) AND (d_year#112 <= 2001)) AND isnotnull(d_date_sk#25)) + +(115) CometProject +Input [2]: [d_date_sk#25, d_year#112] +Arguments: [d_date_sk#25], [d_date_sk#25] + +(116) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#25] + +(117) BroadcastExchange +Input [1]: [d_date_sk#25] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=14] + +Subquery:9 Hosting operator id = 13 Hosting Expression = cs_sold_date_sk#18 IN dynamicpruning#12 + +Subquery:10 Hosting operator id = 36 Hosting Expression = ws_sold_date_sk#30 IN dynamicpruning#12 + +Subquery:11 Hosting operator id = 81 Hosting Expression = ReusedSubquery Subquery scalar-subquery#54, [id=#55] + +Subquery:12 Hosting operator id = 67 Hosting Expression = ss_sold_date_sk#59 IN dynamicpruning#60 +BroadcastExchange (122) ++- * ColumnarToRow (121) + +- CometProject (120) + +- CometFilter (119) + +- CometScan parquet spark_catalog.default.date_dim (118) + + +(118) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#66, d_week_seq#113] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_week_seq), EqualTo(d_week_seq,ScalarSubquery#114), IsNotNull(d_date_sk)] +ReadSchema: struct + +(119) CometFilter +Input [2]: [d_date_sk#66, d_week_seq#113] +Condition : ((isnotnull(d_week_seq#113) AND (d_week_seq#113 = ReusedSubquery Subquery scalar-subquery#114, [id=#115])) AND isnotnull(d_date_sk#66)) + +(120) CometProject +Input [2]: [d_date_sk#66, d_week_seq#113] +Arguments: [d_date_sk#66], [d_date_sk#66] + +(121) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#66] + +(122) BroadcastExchange +Input [1]: [d_date_sk#66] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=15] + +Subquery:13 Hosting operator id = 119 Hosting Expression = ReusedSubquery Subquery scalar-subquery#114, [id=#115] + +Subquery:14 Hosting operator id = 118 Hosting Expression = Subquery scalar-subquery#114, [id=#115] +* ColumnarToRow (126) ++- CometProject (125) + +- CometFilter (124) + +- CometScan parquet spark_catalog.default.date_dim (123) + + +(123) Scan parquet spark_catalog.default.date_dim +Output [4]: [d_week_seq#116, d_year#117, d_moy#118, d_dom#119] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), IsNotNull(d_dom), EqualTo(d_year,1999), EqualTo(d_moy,12), EqualTo(d_dom,11)] +ReadSchema: struct + +(124) CometFilter +Input [4]: [d_week_seq#116, d_year#117, d_moy#118, d_dom#119] +Condition : (((((isnotnull(d_year#117) AND isnotnull(d_moy#118)) AND isnotnull(d_dom#119)) AND (d_year#117 = 1999)) AND (d_moy#118 = 12)) AND (d_dom#119 = 11)) + +(125) CometProject +Input [4]: [d_week_seq#116, d_year#117, d_moy#118, d_dom#119] +Arguments: [d_week_seq#116], [d_week_seq#116] + +(126) ColumnarToRow [codegen id : 1] +Input [1]: [d_week_seq#116] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14b/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14b/simplified.txt new file mode 100644 index 0000000000..55aa823ab8 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14b/simplified.txt @@ -0,0 +1,204 @@ +TakeOrderedAndProject [i_brand_id,i_class_id,i_category_id,channel,sales,number_sales,channel,i_brand_id,i_class_id,i_category_id,sales,number_sales] + WholeStageCodegen (52) + BroadcastHashJoin [i_brand_id,i_class_id,i_category_id,i_brand_id,i_class_id,i_category_id] + Filter [sales] + Subquery #4 + WholeStageCodegen (8) + HashAggregate [sum,count] [avg((cast(quantity as decimal(10,0)) * list_price)),average_sales,sum,count] + InputAdapter + Exchange #12 + WholeStageCodegen (7) + HashAggregate [quantity,list_price] [sum,count,sum,count] + InputAdapter + Union + WholeStageCodegen (2) + Project [ss_quantity,ss_list_price] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_list_price,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #3 + InputAdapter + ReusedExchange [d_date_sk] #6 + WholeStageCodegen (4) + Project [cs_quantity,cs_list_price] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_quantity,cs_list_price,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #3 + InputAdapter + ReusedExchange [d_date_sk] #6 + WholeStageCodegen (6) + Project [ws_quantity,ws_list_price] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_quantity,ws_list_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #3 + InputAdapter + ReusedExchange [d_date_sk] #6 + HashAggregate [i_brand_id,i_class_id,i_category_id,sum,isEmpty,count] [sum((cast(ss_quantity as decimal(10,0)) * ss_list_price)),count(1),channel,sales,number_sales,sum,isEmpty,count] + InputAdapter + Exchange [i_brand_id,i_class_id,i_category_id] #1 + WholeStageCodegen (25) + HashAggregate [i_brand_id,i_class_id,i_category_id,ss_quantity,ss_list_price] [sum,isEmpty,count,sum,isEmpty,count] + Project [ss_quantity,ss_list_price,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_quantity,ss_list_price,ss_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + BroadcastHashJoin [ss_item_sk,ss_item_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_quantity,ss_list_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_week_seq,d_date_sk] + ReusedSubquery [d_week_seq] #2 + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_week_seq] + Subquery #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_week_seq] + CometFilter [d_year,d_moy,d_dom] + CometScan parquet spark_catalog.default.date_dim [d_week_seq,d_year,d_moy,d_dom] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (11) + Project [i_item_sk] + BroadcastHashJoin [i_brand_id,i_class_id,i_category_id,brand_id,class_id,category_id] + ColumnarToRow + InputAdapter + CometFilter [i_brand_id,i_class_id,i_category_id] + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (10) + BroadcastHashJoin [brand_id,class_id,category_id,i_brand_id,i_class_id,i_category_id] + HashAggregate [brand_id,class_id,category_id] + InputAdapter + Exchange [brand_id,class_id,category_id] #5 + WholeStageCodegen (6) + HashAggregate [brand_id,class_id,category_id] + Project [i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #3 + BroadcastExchange #6 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (4) + BroadcastHashJoin [i_brand_id,i_class_id,i_category_id,i_brand_id,i_class_id,i_category_id] + ColumnarToRow + InputAdapter + CometFilter [i_item_sk,i_brand_id,i_class_id,i_category_id] + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (3) + Project [i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #3 + InputAdapter + BroadcastExchange #9 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] + InputAdapter + ReusedExchange [d_date_sk] #6 + InputAdapter + ReusedExchange [d_date_sk] #6 + InputAdapter + BroadcastExchange #10 + WholeStageCodegen (9) + Project [i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ws_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #3 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id] #9 + InputAdapter + ReusedExchange [d_date_sk] #6 + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (23) + BroadcastHashJoin [i_item_sk,ss_item_sk] + ColumnarToRow + InputAdapter + CometFilter [i_item_sk,i_brand_id,i_class_id,i_category_id] + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] + InputAdapter + ReusedExchange [ss_item_sk] #3 + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #13 + WholeStageCodegen (51) + Filter [sales] + ReusedSubquery [average_sales] #4 + HashAggregate [i_brand_id,i_class_id,i_category_id,sum,isEmpty,count] [sum((cast(ss_quantity as decimal(10,0)) * ss_list_price)),count(1),channel,sales,number_sales,sum,isEmpty,count] + InputAdapter + Exchange [i_brand_id,i_class_id,i_category_id] #14 + WholeStageCodegen (50) + HashAggregate [i_brand_id,i_class_id,i_category_id,ss_quantity,ss_list_price] [sum,isEmpty,count,sum,isEmpty,count] + Project [ss_quantity,ss_list_price,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_quantity,ss_list_price,ss_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + BroadcastHashJoin [ss_item_sk,ss_item_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_quantity,ss_list_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #5 + BroadcastExchange #15 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_week_seq,d_date_sk] + ReusedSubquery [d_week_seq] #6 + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_week_seq] + Subquery #6 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_week_seq] + CometFilter [d_year,d_moy,d_dom] + CometScan parquet spark_catalog.default.date_dim [d_week_seq,d_year,d_moy,d_dom] + InputAdapter + ReusedExchange [ss_item_sk] #3 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id] #11 + InputAdapter + ReusedExchange [d_date_sk] #15 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q15/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q15/explain.txt new file mode 100644 index 0000000000..13a621f773 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q15/explain.txt @@ -0,0 +1,164 @@ +== Physical Plan == +TakeOrderedAndProject (22) ++- * HashAggregate (21) + +- Exchange (20) + +- * HashAggregate (19) + +- * Project (18) + +- * BroadcastHashJoin Inner BuildRight (17) + :- * Project (15) + : +- * BroadcastHashJoin Inner BuildRight (14) + : :- * Project (9) + : : +- * BroadcastHashJoin Inner BuildRight (8) + : : :- * ColumnarToRow (3) + : : : +- CometFilter (2) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) + : : +- BroadcastExchange (7) + : : +- * ColumnarToRow (6) + : : +- CometFilter (5) + : : +- CometScan parquet spark_catalog.default.customer (4) + : +- BroadcastExchange (13) + : +- * ColumnarToRow (12) + : +- CometFilter (11) + : +- CometScan parquet spark_catalog.default.customer_address (10) + +- ReusedExchange (16) + + +(1) Scan parquet spark_catalog.default.catalog_sales +Output [3]: [cs_bill_customer_sk#1, cs_sales_price#2, cs_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#3), dynamicpruningexpression(cs_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(cs_bill_customer_sk)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [cs_bill_customer_sk#1, cs_sales_price#2, cs_sold_date_sk#3] +Condition : isnotnull(cs_bill_customer_sk#1) + +(3) ColumnarToRow [codegen id : 4] +Input [3]: [cs_bill_customer_sk#1, cs_sales_price#2, cs_sold_date_sk#3] + +(4) Scan parquet spark_catalog.default.customer +Output [2]: [c_customer_sk#5, c_current_addr_sk#6] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_current_addr_sk)] +ReadSchema: struct + +(5) CometFilter +Input [2]: [c_customer_sk#5, c_current_addr_sk#6] +Condition : (isnotnull(c_customer_sk#5) AND isnotnull(c_current_addr_sk#6)) + +(6) ColumnarToRow [codegen id : 1] +Input [2]: [c_customer_sk#5, c_current_addr_sk#6] + +(7) BroadcastExchange +Input [2]: [c_customer_sk#5, c_current_addr_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [cs_bill_customer_sk#1] +Right keys [1]: [c_customer_sk#5] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 4] +Output [3]: [cs_sales_price#2, cs_sold_date_sk#3, c_current_addr_sk#6] +Input [5]: [cs_bill_customer_sk#1, cs_sales_price#2, cs_sold_date_sk#3, c_customer_sk#5, c_current_addr_sk#6] + +(10) Scan parquet spark_catalog.default.customer_address +Output [3]: [ca_address_sk#7, ca_state#8, ca_zip#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk)] +ReadSchema: struct + +(11) CometFilter +Input [3]: [ca_address_sk#7, ca_state#8, ca_zip#9] +Condition : isnotnull(ca_address_sk#7) + +(12) ColumnarToRow [codegen id : 2] +Input [3]: [ca_address_sk#7, ca_state#8, ca_zip#9] + +(13) BroadcastExchange +Input [3]: [ca_address_sk#7, ca_state#8, ca_zip#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(14) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [c_current_addr_sk#6] +Right keys [1]: [ca_address_sk#7] +Join type: Inner +Join condition: ((substr(ca_zip#9, 1, 5) IN (85669,86197,88274,83405,86475,85392,85460,80348,81792) OR ca_state#8 IN (CA,WA,GA)) OR (cs_sales_price#2 > 500.00)) + +(15) Project [codegen id : 4] +Output [3]: [cs_sales_price#2, cs_sold_date_sk#3, ca_zip#9] +Input [6]: [cs_sales_price#2, cs_sold_date_sk#3, c_current_addr_sk#6, ca_address_sk#7, ca_state#8, ca_zip#9] + +(16) ReusedExchange [Reuses operator id: 27] +Output [1]: [d_date_sk#10] + +(17) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [cs_sold_date_sk#3] +Right keys [1]: [d_date_sk#10] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 4] +Output [2]: [cs_sales_price#2, ca_zip#9] +Input [4]: [cs_sales_price#2, cs_sold_date_sk#3, ca_zip#9, d_date_sk#10] + +(19) HashAggregate [codegen id : 4] +Input [2]: [cs_sales_price#2, ca_zip#9] +Keys [1]: [ca_zip#9] +Functions [1]: [partial_sum(UnscaledValue(cs_sales_price#2))] +Aggregate Attributes [1]: [sum#11] +Results [2]: [ca_zip#9, sum#12] + +(20) Exchange +Input [2]: [ca_zip#9, sum#12] +Arguments: hashpartitioning(ca_zip#9, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(21) HashAggregate [codegen id : 5] +Input [2]: [ca_zip#9, sum#12] +Keys [1]: [ca_zip#9] +Functions [1]: [sum(UnscaledValue(cs_sales_price#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(cs_sales_price#2))#13] +Results [2]: [ca_zip#9, MakeDecimal(sum(UnscaledValue(cs_sales_price#2))#13,17,2) AS sum(cs_sales_price)#14] + +(22) TakeOrderedAndProject +Input [2]: [ca_zip#9, sum(cs_sales_price)#14] +Arguments: 100, [ca_zip#9 ASC NULLS FIRST], [ca_zip#9, sum(cs_sales_price)#14] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (27) ++- * ColumnarToRow (26) + +- CometProject (25) + +- CometFilter (24) + +- CometScan parquet spark_catalog.default.date_dim (23) + + +(23) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#10, d_year#15, d_qoy#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_qoy), IsNotNull(d_year), EqualTo(d_qoy,2), EqualTo(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(24) CometFilter +Input [3]: [d_date_sk#10, d_year#15, d_qoy#16] +Condition : ((((isnotnull(d_qoy#16) AND isnotnull(d_year#15)) AND (d_qoy#16 = 2)) AND (d_year#15 = 2001)) AND isnotnull(d_date_sk#10)) + +(25) CometProject +Input [3]: [d_date_sk#10, d_year#15, d_qoy#16] +Arguments: [d_date_sk#10], [d_date_sk#10] + +(26) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#10] + +(27) BroadcastExchange +Input [1]: [d_date_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q15/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q15/simplified.txt new file mode 100644 index 0000000000..5c750b2db8 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q15/simplified.txt @@ -0,0 +1,41 @@ +TakeOrderedAndProject [ca_zip,sum(cs_sales_price)] + WholeStageCodegen (5) + HashAggregate [ca_zip,sum] [sum(UnscaledValue(cs_sales_price)),sum(cs_sales_price),sum] + InputAdapter + Exchange [ca_zip] #1 + WholeStageCodegen (4) + HashAggregate [ca_zip,cs_sales_price] [sum,sum] + Project [cs_sales_price,ca_zip] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_sales_price,cs_sold_date_sk,ca_zip] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk,ca_zip,ca_state,cs_sales_price] + Project [cs_sales_price,cs_sold_date_sk,c_current_addr_sk] + BroadcastHashJoin [cs_bill_customer_sk,c_customer_sk] + ColumnarToRow + InputAdapter + CometFilter [cs_bill_customer_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_sales_price,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_qoy,d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_qoy] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_current_addr_sk] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_addr_sk] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state,ca_zip] + InputAdapter + ReusedExchange [d_date_sk] #2 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q16/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q16/explain.txt new file mode 100644 index 0000000000..ccec341ad3 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q16/explain.txt @@ -0,0 +1,260 @@ +== Physical Plan == +* HashAggregate (45) ++- Exchange (44) + +- * HashAggregate (43) + +- * HashAggregate (42) + +- * HashAggregate (41) + +- * Project (40) + +- * BroadcastHashJoin Inner BuildRight (39) + :- * Project (33) + : +- * BroadcastHashJoin Inner BuildRight (32) + : :- * Project (26) + : : +- * BroadcastHashJoin Inner BuildRight (25) + : : :- * SortMergeJoin LeftAnti (19) + : : : :- * Project (13) + : : : : +- * SortMergeJoin LeftSemi (12) + : : : : :- * Sort (6) + : : : : : +- Exchange (5) + : : : : : +- * ColumnarToRow (4) + : : : : : +- CometProject (3) + : : : : : +- CometFilter (2) + : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) + : : : : +- * Sort (11) + : : : : +- Exchange (10) + : : : : +- * ColumnarToRow (9) + : : : : +- CometProject (8) + : : : : +- CometScan parquet spark_catalog.default.catalog_sales (7) + : : : +- * Sort (18) + : : : +- Exchange (17) + : : : +- * ColumnarToRow (16) + : : : +- CometProject (15) + : : : +- CometScan parquet spark_catalog.default.catalog_returns (14) + : : +- BroadcastExchange (24) + : : +- * ColumnarToRow (23) + : : +- CometProject (22) + : : +- CometFilter (21) + : : +- CometScan parquet spark_catalog.default.date_dim (20) + : +- BroadcastExchange (31) + : +- * ColumnarToRow (30) + : +- CometProject (29) + : +- CometFilter (28) + : +- CometScan parquet spark_catalog.default.customer_address (27) + +- BroadcastExchange (38) + +- * ColumnarToRow (37) + +- CometProject (36) + +- CometFilter (35) + +- CometScan parquet spark_catalog.default.call_center (34) + + +(1) Scan parquet spark_catalog.default.catalog_sales +Output [8]: [cs_ship_date_sk#1, cs_ship_addr_sk#2, cs_call_center_sk#3, cs_warehouse_sk#4, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7, cs_sold_date_sk#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_sales] +PushedFilters: [IsNotNull(cs_ship_date_sk), IsNotNull(cs_ship_addr_sk), IsNotNull(cs_call_center_sk)] +ReadSchema: struct + +(2) CometFilter +Input [8]: [cs_ship_date_sk#1, cs_ship_addr_sk#2, cs_call_center_sk#3, cs_warehouse_sk#4, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7, cs_sold_date_sk#8] +Condition : ((isnotnull(cs_ship_date_sk#1) AND isnotnull(cs_ship_addr_sk#2)) AND isnotnull(cs_call_center_sk#3)) + +(3) CometProject +Input [8]: [cs_ship_date_sk#1, cs_ship_addr_sk#2, cs_call_center_sk#3, cs_warehouse_sk#4, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7, cs_sold_date_sk#8] +Arguments: [cs_ship_date_sk#1, cs_ship_addr_sk#2, cs_call_center_sk#3, cs_warehouse_sk#4, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7], [cs_ship_date_sk#1, cs_ship_addr_sk#2, cs_call_center_sk#3, cs_warehouse_sk#4, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7] + +(4) ColumnarToRow [codegen id : 1] +Input [7]: [cs_ship_date_sk#1, cs_ship_addr_sk#2, cs_call_center_sk#3, cs_warehouse_sk#4, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7] + +(5) Exchange +Input [7]: [cs_ship_date_sk#1, cs_ship_addr_sk#2, cs_call_center_sk#3, cs_warehouse_sk#4, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7] +Arguments: hashpartitioning(cs_order_number#5, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(6) Sort [codegen id : 2] +Input [7]: [cs_ship_date_sk#1, cs_ship_addr_sk#2, cs_call_center_sk#3, cs_warehouse_sk#4, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7] +Arguments: [cs_order_number#5 ASC NULLS FIRST], false, 0 + +(7) Scan parquet spark_catalog.default.catalog_sales +Output [3]: [cs_warehouse_sk#9, cs_order_number#10, cs_sold_date_sk#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_sales] +ReadSchema: struct + +(8) CometProject +Input [3]: [cs_warehouse_sk#9, cs_order_number#10, cs_sold_date_sk#11] +Arguments: [cs_warehouse_sk#9, cs_order_number#10], [cs_warehouse_sk#9, cs_order_number#10] + +(9) ColumnarToRow [codegen id : 3] +Input [2]: [cs_warehouse_sk#9, cs_order_number#10] + +(10) Exchange +Input [2]: [cs_warehouse_sk#9, cs_order_number#10] +Arguments: hashpartitioning(cs_order_number#10, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(11) Sort [codegen id : 4] +Input [2]: [cs_warehouse_sk#9, cs_order_number#10] +Arguments: [cs_order_number#10 ASC NULLS FIRST], false, 0 + +(12) SortMergeJoin [codegen id : 5] +Left keys [1]: [cs_order_number#5] +Right keys [1]: [cs_order_number#10] +Join type: LeftSemi +Join condition: NOT (cs_warehouse_sk#4 = cs_warehouse_sk#9) + +(13) Project [codegen id : 5] +Output [6]: [cs_ship_date_sk#1, cs_ship_addr_sk#2, cs_call_center_sk#3, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7] +Input [7]: [cs_ship_date_sk#1, cs_ship_addr_sk#2, cs_call_center_sk#3, cs_warehouse_sk#4, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7] + +(14) Scan parquet spark_catalog.default.catalog_returns +Output [2]: [cr_order_number#12, cr_returned_date_sk#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_returns] +ReadSchema: struct + +(15) CometProject +Input [2]: [cr_order_number#12, cr_returned_date_sk#13] +Arguments: [cr_order_number#12], [cr_order_number#12] + +(16) ColumnarToRow [codegen id : 6] +Input [1]: [cr_order_number#12] + +(17) Exchange +Input [1]: [cr_order_number#12] +Arguments: hashpartitioning(cr_order_number#12, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(18) Sort [codegen id : 7] +Input [1]: [cr_order_number#12] +Arguments: [cr_order_number#12 ASC NULLS FIRST], false, 0 + +(19) SortMergeJoin [codegen id : 11] +Left keys [1]: [cs_order_number#5] +Right keys [1]: [cr_order_number#12] +Join type: LeftAnti +Join condition: None + +(20) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#14, d_date#15] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,2002-02-01), LessThanOrEqual(d_date,2002-04-02), IsNotNull(d_date_sk)] +ReadSchema: struct + +(21) CometFilter +Input [2]: [d_date_sk#14, d_date#15] +Condition : (((isnotnull(d_date#15) AND (d_date#15 >= 2002-02-01)) AND (d_date#15 <= 2002-04-02)) AND isnotnull(d_date_sk#14)) + +(22) CometProject +Input [2]: [d_date_sk#14, d_date#15] +Arguments: [d_date_sk#14], [d_date_sk#14] + +(23) ColumnarToRow [codegen id : 8] +Input [1]: [d_date_sk#14] + +(24) BroadcastExchange +Input [1]: [d_date_sk#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(25) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [cs_ship_date_sk#1] +Right keys [1]: [d_date_sk#14] +Join type: Inner +Join condition: None + +(26) Project [codegen id : 11] +Output [5]: [cs_ship_addr_sk#2, cs_call_center_sk#3, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7] +Input [7]: [cs_ship_date_sk#1, cs_ship_addr_sk#2, cs_call_center_sk#3, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7, d_date_sk#14] + +(27) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#16, ca_state#17] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_state), EqualTo(ca_state,GA), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(28) CometFilter +Input [2]: [ca_address_sk#16, ca_state#17] +Condition : ((isnotnull(ca_state#17) AND (ca_state#17 = GA)) AND isnotnull(ca_address_sk#16)) + +(29) CometProject +Input [2]: [ca_address_sk#16, ca_state#17] +Arguments: [ca_address_sk#16], [ca_address_sk#16] + +(30) ColumnarToRow [codegen id : 9] +Input [1]: [ca_address_sk#16] + +(31) BroadcastExchange +Input [1]: [ca_address_sk#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +(32) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [cs_ship_addr_sk#2] +Right keys [1]: [ca_address_sk#16] +Join type: Inner +Join condition: None + +(33) Project [codegen id : 11] +Output [4]: [cs_call_center_sk#3, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7] +Input [6]: [cs_ship_addr_sk#2, cs_call_center_sk#3, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7, ca_address_sk#16] + +(34) Scan parquet spark_catalog.default.call_center +Output [2]: [cc_call_center_sk#18, cc_county#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/call_center] +PushedFilters: [IsNotNull(cc_county), EqualTo(cc_county,Williamson County), IsNotNull(cc_call_center_sk)] +ReadSchema: struct + +(35) CometFilter +Input [2]: [cc_call_center_sk#18, cc_county#19] +Condition : ((isnotnull(cc_county#19) AND (cc_county#19 = Williamson County)) AND isnotnull(cc_call_center_sk#18)) + +(36) CometProject +Input [2]: [cc_call_center_sk#18, cc_county#19] +Arguments: [cc_call_center_sk#18], [cc_call_center_sk#18] + +(37) ColumnarToRow [codegen id : 10] +Input [1]: [cc_call_center_sk#18] + +(38) BroadcastExchange +Input [1]: [cc_call_center_sk#18] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6] + +(39) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [cs_call_center_sk#3] +Right keys [1]: [cc_call_center_sk#18] +Join type: Inner +Join condition: None + +(40) Project [codegen id : 11] +Output [3]: [cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7] +Input [5]: [cs_call_center_sk#3, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7, cc_call_center_sk#18] + +(41) HashAggregate [codegen id : 11] +Input [3]: [cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7] +Keys [1]: [cs_order_number#5] +Functions [2]: [partial_sum(UnscaledValue(cs_ext_ship_cost#6)), partial_sum(UnscaledValue(cs_net_profit#7))] +Aggregate Attributes [2]: [sum(UnscaledValue(cs_ext_ship_cost#6))#20, sum(UnscaledValue(cs_net_profit#7))#21] +Results [3]: [cs_order_number#5, sum#22, sum#23] + +(42) HashAggregate [codegen id : 11] +Input [3]: [cs_order_number#5, sum#22, sum#23] +Keys [1]: [cs_order_number#5] +Functions [2]: [merge_sum(UnscaledValue(cs_ext_ship_cost#6)), merge_sum(UnscaledValue(cs_net_profit#7))] +Aggregate Attributes [2]: [sum(UnscaledValue(cs_ext_ship_cost#6))#20, sum(UnscaledValue(cs_net_profit#7))#21] +Results [3]: [cs_order_number#5, sum#22, sum#23] + +(43) HashAggregate [codegen id : 11] +Input [3]: [cs_order_number#5, sum#22, sum#23] +Keys: [] +Functions [3]: [merge_sum(UnscaledValue(cs_ext_ship_cost#6)), merge_sum(UnscaledValue(cs_net_profit#7)), partial_count(distinct cs_order_number#5)] +Aggregate Attributes [3]: [sum(UnscaledValue(cs_ext_ship_cost#6))#20, sum(UnscaledValue(cs_net_profit#7))#21, count(cs_order_number#5)#24] +Results [3]: [sum#22, sum#23, count#25] + +(44) Exchange +Input [3]: [sum#22, sum#23, count#25] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=7] + +(45) HashAggregate [codegen id : 12] +Input [3]: [sum#22, sum#23, count#25] +Keys: [] +Functions [3]: [sum(UnscaledValue(cs_ext_ship_cost#6)), sum(UnscaledValue(cs_net_profit#7)), count(distinct cs_order_number#5)] +Aggregate Attributes [3]: [sum(UnscaledValue(cs_ext_ship_cost#6))#20, sum(UnscaledValue(cs_net_profit#7))#21, count(cs_order_number#5)#24] +Results [3]: [count(cs_order_number#5)#24 AS order count #26, MakeDecimal(sum(UnscaledValue(cs_ext_ship_cost#6))#20,17,2) AS total shipping cost #27, MakeDecimal(sum(UnscaledValue(cs_net_profit#7))#21,17,2) AS total net profit #28] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q16/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q16/simplified.txt new file mode 100644 index 0000000000..a55c182bed --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q16/simplified.txt @@ -0,0 +1,74 @@ +WholeStageCodegen (12) + HashAggregate [sum,sum,count] [sum(UnscaledValue(cs_ext_ship_cost)),sum(UnscaledValue(cs_net_profit)),count(cs_order_number),order count ,total shipping cost ,total net profit ,sum,sum,count] + InputAdapter + Exchange #1 + WholeStageCodegen (11) + HashAggregate [cs_order_number] [sum(UnscaledValue(cs_ext_ship_cost)),sum(UnscaledValue(cs_net_profit)),count(cs_order_number),sum,sum,count,sum,sum,count] + HashAggregate [cs_order_number] [sum(UnscaledValue(cs_ext_ship_cost)),sum(UnscaledValue(cs_net_profit)),sum,sum,sum,sum] + HashAggregate [cs_order_number,cs_ext_ship_cost,cs_net_profit] [sum(UnscaledValue(cs_ext_ship_cost)),sum(UnscaledValue(cs_net_profit)),sum,sum,sum,sum] + Project [cs_order_number,cs_ext_ship_cost,cs_net_profit] + BroadcastHashJoin [cs_call_center_sk,cc_call_center_sk] + Project [cs_call_center_sk,cs_order_number,cs_ext_ship_cost,cs_net_profit] + BroadcastHashJoin [cs_ship_addr_sk,ca_address_sk] + Project [cs_ship_addr_sk,cs_call_center_sk,cs_order_number,cs_ext_ship_cost,cs_net_profit] + BroadcastHashJoin [cs_ship_date_sk,d_date_sk] + SortMergeJoin [cs_order_number,cr_order_number] + InputAdapter + WholeStageCodegen (5) + Project [cs_ship_date_sk,cs_ship_addr_sk,cs_call_center_sk,cs_order_number,cs_ext_ship_cost,cs_net_profit] + SortMergeJoin [cs_order_number,cs_order_number,cs_warehouse_sk,cs_warehouse_sk] + InputAdapter + WholeStageCodegen (2) + Sort [cs_order_number] + InputAdapter + Exchange [cs_order_number] #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [cs_ship_date_sk,cs_ship_addr_sk,cs_call_center_sk,cs_warehouse_sk,cs_order_number,cs_ext_ship_cost,cs_net_profit] + CometFilter [cs_ship_date_sk,cs_ship_addr_sk,cs_call_center_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_ship_date_sk,cs_ship_addr_sk,cs_call_center_sk,cs_warehouse_sk,cs_order_number,cs_ext_ship_cost,cs_net_profit,cs_sold_date_sk] + InputAdapter + WholeStageCodegen (4) + Sort [cs_order_number] + InputAdapter + Exchange [cs_order_number] #3 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometProject [cs_warehouse_sk,cs_order_number] + CometScan parquet spark_catalog.default.catalog_sales [cs_warehouse_sk,cs_order_number,cs_sold_date_sk] + InputAdapter + WholeStageCodegen (7) + Sort [cr_order_number] + InputAdapter + Exchange [cr_order_number] #4 + WholeStageCodegen (6) + ColumnarToRow + InputAdapter + CometProject [cr_order_number] + CometScan parquet spark_catalog.default.catalog_returns [cr_order_number,cr_returned_date_sk] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (8) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (9) + ColumnarToRow + InputAdapter + CometProject [ca_address_sk] + CometFilter [ca_state,ca_address_sk] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (10) + ColumnarToRow + InputAdapter + CometProject [cc_call_center_sk] + CometFilter [cc_county,cc_call_center_sk] + CometScan parquet spark_catalog.default.call_center [cc_call_center_sk,cc_county] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q17/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q17/explain.txt new file mode 100644 index 0000000000..0de98cfb0f --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q17/explain.txt @@ -0,0 +1,298 @@ +== Physical Plan == +TakeOrderedAndProject (40) ++- * HashAggregate (39) + +- Exchange (38) + +- * HashAggregate (37) + +- * Project (36) + +- * BroadcastHashJoin Inner BuildRight (35) + :- * Project (30) + : +- * BroadcastHashJoin Inner BuildRight (29) + : :- * Project (24) + : : +- * BroadcastHashJoin Inner BuildRight (23) + : : :- * Project (21) + : : : +- * BroadcastHashJoin Inner BuildRight (20) + : : : :- * Project (18) + : : : : +- * BroadcastHashJoin Inner BuildRight (17) + : : : : :- * Project (15) + : : : : : +- * BroadcastHashJoin Inner BuildRight (14) + : : : : : :- * Project (9) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : : : :- * ColumnarToRow (3) + : : : : : : : +- CometFilter (2) + : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : : : +- BroadcastExchange (7) + : : : : : : +- * ColumnarToRow (6) + : : : : : : +- CometFilter (5) + : : : : : : +- CometScan parquet spark_catalog.default.store_returns (4) + : : : : : +- BroadcastExchange (13) + : : : : : +- * ColumnarToRow (12) + : : : : : +- CometFilter (11) + : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (10) + : : : : +- ReusedExchange (16) + : : : +- ReusedExchange (19) + : : +- ReusedExchange (22) + : +- BroadcastExchange (28) + : +- * ColumnarToRow (27) + : +- CometFilter (26) + : +- CometScan parquet spark_catalog.default.store (25) + +- BroadcastExchange (34) + +- * ColumnarToRow (33) + +- CometFilter (32) + +- CometScan parquet spark_catalog.default.item (31) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_quantity#5, ss_sold_date_sk#6] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#6), dynamicpruningexpression(ss_sold_date_sk#6 IN dynamicpruning#7)] +PushedFilters: [IsNotNull(ss_customer_sk), IsNotNull(ss_item_sk), IsNotNull(ss_ticket_number), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(2) CometFilter +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_quantity#5, ss_sold_date_sk#6] +Condition : (((isnotnull(ss_customer_sk#2) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_ticket_number#4)) AND isnotnull(ss_store_sk#3)) + +(3) ColumnarToRow [codegen id : 8] +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_quantity#5, ss_sold_date_sk#6] + +(4) Scan parquet spark_catalog.default.store_returns +Output [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_return_quantity#11, sr_returned_date_sk#12] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(sr_returned_date_sk#12), dynamicpruningexpression(sr_returned_date_sk#12 IN dynamicpruning#13)] +PushedFilters: [IsNotNull(sr_customer_sk), IsNotNull(sr_item_sk), IsNotNull(sr_ticket_number)] +ReadSchema: struct + +(5) CometFilter +Input [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_return_quantity#11, sr_returned_date_sk#12] +Condition : ((isnotnull(sr_customer_sk#9) AND isnotnull(sr_item_sk#8)) AND isnotnull(sr_ticket_number#10)) + +(6) ColumnarToRow [codegen id : 1] +Input [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_return_quantity#11, sr_returned_date_sk#12] + +(7) BroadcastExchange +Input [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_return_quantity#11, sr_returned_date_sk#12] +Arguments: HashedRelationBroadcastMode(List(input[1, int, false], input[0, int, false], input[2, int, false]),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 8] +Left keys [3]: [ss_customer_sk#2, ss_item_sk#1, ss_ticket_number#4] +Right keys [3]: [sr_customer_sk#9, sr_item_sk#8, sr_ticket_number#10] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 8] +Output [8]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, ss_sold_date_sk#6, sr_item_sk#8, sr_customer_sk#9, sr_return_quantity#11, sr_returned_date_sk#12] +Input [11]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_quantity#5, ss_sold_date_sk#6, sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_return_quantity#11, sr_returned_date_sk#12] + +(10) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_quantity#16, cs_sold_date_sk#17] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#17), dynamicpruningexpression(cs_sold_date_sk#17 IN dynamicpruning#18)] +PushedFilters: [IsNotNull(cs_bill_customer_sk), IsNotNull(cs_item_sk)] +ReadSchema: struct + +(11) CometFilter +Input [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_quantity#16, cs_sold_date_sk#17] +Condition : (isnotnull(cs_bill_customer_sk#14) AND isnotnull(cs_item_sk#15)) + +(12) ColumnarToRow [codegen id : 2] +Input [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_quantity#16, cs_sold_date_sk#17] + +(13) BroadcastExchange +Input [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_quantity#16, cs_sold_date_sk#17] +Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[0, int, false] as bigint), 32) | (cast(input[1, int, false] as bigint) & 4294967295))),false), [plan_id=2] + +(14) BroadcastHashJoin [codegen id : 8] +Left keys [2]: [sr_customer_sk#9, sr_item_sk#8] +Right keys [2]: [cs_bill_customer_sk#14, cs_item_sk#15] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 8] +Output [8]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, ss_sold_date_sk#6, sr_return_quantity#11, sr_returned_date_sk#12, cs_quantity#16, cs_sold_date_sk#17] +Input [12]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, ss_sold_date_sk#6, sr_item_sk#8, sr_customer_sk#9, sr_return_quantity#11, sr_returned_date_sk#12, cs_bill_customer_sk#14, cs_item_sk#15, cs_quantity#16, cs_sold_date_sk#17] + +(16) ReusedExchange [Reuses operator id: 45] +Output [1]: [d_date_sk#19] + +(17) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_sold_date_sk#6] +Right keys [1]: [d_date_sk#19] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 8] +Output [7]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, sr_returned_date_sk#12, cs_quantity#16, cs_sold_date_sk#17] +Input [9]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, ss_sold_date_sk#6, sr_return_quantity#11, sr_returned_date_sk#12, cs_quantity#16, cs_sold_date_sk#17, d_date_sk#19] + +(19) ReusedExchange [Reuses operator id: 50] +Output [1]: [d_date_sk#20] + +(20) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [sr_returned_date_sk#12] +Right keys [1]: [d_date_sk#20] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 8] +Output [6]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, cs_quantity#16, cs_sold_date_sk#17] +Input [8]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, sr_returned_date_sk#12, cs_quantity#16, cs_sold_date_sk#17, d_date_sk#20] + +(22) ReusedExchange [Reuses operator id: 50] +Output [1]: [d_date_sk#21] + +(23) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [cs_sold_date_sk#17] +Right keys [1]: [d_date_sk#21] +Join type: Inner +Join condition: None + +(24) Project [codegen id : 8] +Output [5]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, cs_quantity#16] +Input [7]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, cs_quantity#16, cs_sold_date_sk#17, d_date_sk#21] + +(25) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#22, s_state#23] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(26) CometFilter +Input [2]: [s_store_sk#22, s_state#23] +Condition : isnotnull(s_store_sk#22) + +(27) ColumnarToRow [codegen id : 6] +Input [2]: [s_store_sk#22, s_state#23] + +(28) BroadcastExchange +Input [2]: [s_store_sk#22, s_state#23] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(29) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_store_sk#3] +Right keys [1]: [s_store_sk#22] +Join type: Inner +Join condition: None + +(30) Project [codegen id : 8] +Output [5]: [ss_item_sk#1, ss_quantity#5, sr_return_quantity#11, cs_quantity#16, s_state#23] +Input [7]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, cs_quantity#16, s_store_sk#22, s_state#23] + +(31) Scan parquet spark_catalog.default.item +Output [3]: [i_item_sk#24, i_item_id#25, i_item_desc#26] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(32) CometFilter +Input [3]: [i_item_sk#24, i_item_id#25, i_item_desc#26] +Condition : isnotnull(i_item_sk#24) + +(33) ColumnarToRow [codegen id : 7] +Input [3]: [i_item_sk#24, i_item_id#25, i_item_desc#26] + +(34) BroadcastExchange +Input [3]: [i_item_sk#24, i_item_id#25, i_item_desc#26] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(35) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#24] +Join type: Inner +Join condition: None + +(36) Project [codegen id : 8] +Output [6]: [ss_quantity#5, sr_return_quantity#11, cs_quantity#16, s_state#23, i_item_id#25, i_item_desc#26] +Input [8]: [ss_item_sk#1, ss_quantity#5, sr_return_quantity#11, cs_quantity#16, s_state#23, i_item_sk#24, i_item_id#25, i_item_desc#26] + +(37) HashAggregate [codegen id : 8] +Input [6]: [ss_quantity#5, sr_return_quantity#11, cs_quantity#16, s_state#23, i_item_id#25, i_item_desc#26] +Keys [3]: [i_item_id#25, i_item_desc#26, s_state#23] +Functions [9]: [partial_count(ss_quantity#5), partial_avg(ss_quantity#5), partial_stddev_samp(cast(ss_quantity#5 as double)), partial_count(sr_return_quantity#11), partial_avg(sr_return_quantity#11), partial_stddev_samp(cast(sr_return_quantity#11 as double)), partial_count(cs_quantity#16), partial_avg(cs_quantity#16), partial_stddev_samp(cast(cs_quantity#16 as double))] +Aggregate Attributes [18]: [count#27, sum#28, count#29, n#30, avg#31, m2#32, count#33, sum#34, count#35, n#36, avg#37, m2#38, count#39, sum#40, count#41, n#42, avg#43, m2#44] +Results [21]: [i_item_id#25, i_item_desc#26, s_state#23, count#45, sum#46, count#47, n#48, avg#49, m2#50, count#51, sum#52, count#53, n#54, avg#55, m2#56, count#57, sum#58, count#59, n#60, avg#61, m2#62] + +(38) Exchange +Input [21]: [i_item_id#25, i_item_desc#26, s_state#23, count#45, sum#46, count#47, n#48, avg#49, m2#50, count#51, sum#52, count#53, n#54, avg#55, m2#56, count#57, sum#58, count#59, n#60, avg#61, m2#62] +Arguments: hashpartitioning(i_item_id#25, i_item_desc#26, s_state#23, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(39) HashAggregate [codegen id : 9] +Input [21]: [i_item_id#25, i_item_desc#26, s_state#23, count#45, sum#46, count#47, n#48, avg#49, m2#50, count#51, sum#52, count#53, n#54, avg#55, m2#56, count#57, sum#58, count#59, n#60, avg#61, m2#62] +Keys [3]: [i_item_id#25, i_item_desc#26, s_state#23] +Functions [9]: [count(ss_quantity#5), avg(ss_quantity#5), stddev_samp(cast(ss_quantity#5 as double)), count(sr_return_quantity#11), avg(sr_return_quantity#11), stddev_samp(cast(sr_return_quantity#11 as double)), count(cs_quantity#16), avg(cs_quantity#16), stddev_samp(cast(cs_quantity#16 as double))] +Aggregate Attributes [9]: [count(ss_quantity#5)#63, avg(ss_quantity#5)#64, stddev_samp(cast(ss_quantity#5 as double))#65, count(sr_return_quantity#11)#66, avg(sr_return_quantity#11)#67, stddev_samp(cast(sr_return_quantity#11 as double))#68, count(cs_quantity#16)#69, avg(cs_quantity#16)#70, stddev_samp(cast(cs_quantity#16 as double))#71] +Results [15]: [i_item_id#25, i_item_desc#26, s_state#23, count(ss_quantity#5)#63 AS store_sales_quantitycount#72, avg(ss_quantity#5)#64 AS store_sales_quantityave#73, stddev_samp(cast(ss_quantity#5 as double))#65 AS store_sales_quantitystdev#74, (stddev_samp(cast(ss_quantity#5 as double))#65 / avg(ss_quantity#5)#64) AS store_sales_quantitycov#75, count(sr_return_quantity#11)#66 AS as_store_returns_quantitycount#76, avg(sr_return_quantity#11)#67 AS as_store_returns_quantityave#77, stddev_samp(cast(sr_return_quantity#11 as double))#68 AS as_store_returns_quantitystdev#78, (stddev_samp(cast(sr_return_quantity#11 as double))#68 / avg(sr_return_quantity#11)#67) AS store_returns_quantitycov#79, count(cs_quantity#16)#69 AS catalog_sales_quantitycount#80, avg(cs_quantity#16)#70 AS catalog_sales_quantityave#81, (stddev_samp(cast(cs_quantity#16 as double))#71 / avg(cs_quantity#16)#70) AS catalog_sales_quantitystdev#82, (stddev_samp(cast(cs_quantity#16 as double))#71 / avg(cs_quantity#16)#70) AS catalog_sales_quantitycov#83] + +(40) TakeOrderedAndProject +Input [15]: [i_item_id#25, i_item_desc#26, s_state#23, store_sales_quantitycount#72, store_sales_quantityave#73, store_sales_quantitystdev#74, store_sales_quantitycov#75, as_store_returns_quantitycount#76, as_store_returns_quantityave#77, as_store_returns_quantitystdev#78, store_returns_quantitycov#79, catalog_sales_quantitycount#80, catalog_sales_quantityave#81, catalog_sales_quantitystdev#82, catalog_sales_quantitycov#83] +Arguments: 100, [i_item_id#25 ASC NULLS FIRST, i_item_desc#26 ASC NULLS FIRST, s_state#23 ASC NULLS FIRST], [i_item_id#25, i_item_desc#26, s_state#23, store_sales_quantitycount#72, store_sales_quantityave#73, store_sales_quantitystdev#74, store_sales_quantitycov#75, as_store_returns_quantitycount#76, as_store_returns_quantityave#77, as_store_returns_quantitystdev#78, store_returns_quantitycov#79, catalog_sales_quantitycount#80, catalog_sales_quantityave#81, catalog_sales_quantitystdev#82, catalog_sales_quantitycov#83] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#6 IN dynamicpruning#7 +BroadcastExchange (45) ++- * ColumnarToRow (44) + +- CometProject (43) + +- CometFilter (42) + +- CometScan parquet spark_catalog.default.date_dim (41) + + +(41) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#19, d_quarter_name#84] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_quarter_name), EqualTo(d_quarter_name,2001Q1), IsNotNull(d_date_sk)] +ReadSchema: struct + +(42) CometFilter +Input [2]: [d_date_sk#19, d_quarter_name#84] +Condition : ((isnotnull(d_quarter_name#84) AND (d_quarter_name#84 = 2001Q1)) AND isnotnull(d_date_sk#19)) + +(43) CometProject +Input [2]: [d_date_sk#19, d_quarter_name#84] +Arguments: [d_date_sk#19], [d_date_sk#19] + +(44) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#19] + +(45) BroadcastExchange +Input [1]: [d_date_sk#19] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6] + +Subquery:2 Hosting operator id = 4 Hosting Expression = sr_returned_date_sk#12 IN dynamicpruning#13 +BroadcastExchange (50) ++- * ColumnarToRow (49) + +- CometProject (48) + +- CometFilter (47) + +- CometScan parquet spark_catalog.default.date_dim (46) + + +(46) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#20, d_quarter_name#85] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [In(d_quarter_name, [2001Q1,2001Q2,2001Q3]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(47) CometFilter +Input [2]: [d_date_sk#20, d_quarter_name#85] +Condition : (d_quarter_name#85 IN (2001Q1,2001Q2,2001Q3) AND isnotnull(d_date_sk#20)) + +(48) CometProject +Input [2]: [d_date_sk#20, d_quarter_name#85] +Arguments: [d_date_sk#20], [d_date_sk#20] + +(49) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#20] + +(50) BroadcastExchange +Input [1]: [d_date_sk#20] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +Subquery:3 Hosting operator id = 10 Hosting Expression = cs_sold_date_sk#17 IN dynamicpruning#13 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q17/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q17/simplified.txt new file mode 100644 index 0000000000..9f4d67decc --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q17/simplified.txt @@ -0,0 +1,76 @@ +TakeOrderedAndProject [i_item_id,i_item_desc,s_state,store_sales_quantitycount,store_sales_quantityave,store_sales_quantitystdev,store_sales_quantitycov,as_store_returns_quantitycount,as_store_returns_quantityave,as_store_returns_quantitystdev,store_returns_quantitycov,catalog_sales_quantitycount,catalog_sales_quantityave,catalog_sales_quantitystdev,catalog_sales_quantitycov] + WholeStageCodegen (9) + HashAggregate [i_item_id,i_item_desc,s_state,count,sum,count,n,avg,m2,count,sum,count,n,avg,m2,count,sum,count,n,avg,m2] [count(ss_quantity),avg(ss_quantity),stddev_samp(cast(ss_quantity as double)),count(sr_return_quantity),avg(sr_return_quantity),stddev_samp(cast(sr_return_quantity as double)),count(cs_quantity),avg(cs_quantity),stddev_samp(cast(cs_quantity as double)),store_sales_quantitycount,store_sales_quantityave,store_sales_quantitystdev,store_sales_quantitycov,as_store_returns_quantitycount,as_store_returns_quantityave,as_store_returns_quantitystdev,store_returns_quantitycov,catalog_sales_quantitycount,catalog_sales_quantityave,catalog_sales_quantitystdev,catalog_sales_quantitycov,count,sum,count,n,avg,m2,count,sum,count,n,avg,m2,count,sum,count,n,avg,m2] + InputAdapter + Exchange [i_item_id,i_item_desc,s_state] #1 + WholeStageCodegen (8) + HashAggregate [i_item_id,i_item_desc,s_state,ss_quantity,sr_return_quantity,cs_quantity] [count,sum,count,n,avg,m2,count,sum,count,n,avg,m2,count,sum,count,n,avg,m2,count,sum,count,n,avg,m2,count,sum,count,n,avg,m2,count,sum,count,n,avg,m2] + Project [ss_quantity,sr_return_quantity,cs_quantity,s_state,i_item_id,i_item_desc] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_quantity,sr_return_quantity,cs_quantity,s_state] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,sr_return_quantity,cs_quantity] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,sr_return_quantity,cs_quantity,cs_sold_date_sk] + BroadcastHashJoin [sr_returned_date_sk,d_date_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,sr_return_quantity,sr_returned_date_sk,cs_quantity,cs_sold_date_sk] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,ss_sold_date_sk,sr_return_quantity,sr_returned_date_sk,cs_quantity,cs_sold_date_sk] + BroadcastHashJoin [sr_customer_sk,sr_item_sk,cs_bill_customer_sk,cs_item_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,ss_sold_date_sk,sr_item_sk,sr_customer_sk,sr_return_quantity,sr_returned_date_sk] + BroadcastHashJoin [ss_customer_sk,ss_item_sk,ss_ticket_number,sr_customer_sk,sr_item_sk,sr_ticket_number] + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk,ss_item_sk,ss_ticket_number,ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_quantity,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_quarter_name,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_quarter_name] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [sr_customer_sk,sr_item_sk,sr_ticket_number] + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_customer_sk,sr_ticket_number,sr_return_quantity,sr_returned_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_quarter_name,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_quarter_name] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [cs_bill_customer_sk,cs_item_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (6) + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk,s_state] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (7) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_item_desc] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q18/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q18/explain.txt new file mode 100644 index 0000000000..1e9c660c55 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q18/explain.txt @@ -0,0 +1,281 @@ +== Physical Plan == +TakeOrderedAndProject (43) ++- * HashAggregate (42) + +- Exchange (41) + +- * HashAggregate (40) + +- * Expand (39) + +- * Project (38) + +- * BroadcastHashJoin Inner BuildRight (37) + :- * Project (32) + : +- * BroadcastHashJoin Inner BuildRight (31) + : :- * Project (29) + : : +- * BroadcastHashJoin Inner BuildRight (28) + : : :- * Project (23) + : : : +- * BroadcastHashJoin Inner BuildRight (22) + : : : :- * Project (17) + : : : : +- * BroadcastHashJoin Inner BuildRight (16) + : : : : :- * Project (10) + : : : : : +- * BroadcastHashJoin Inner BuildRight (9) + : : : : : :- * ColumnarToRow (3) + : : : : : : +- CometFilter (2) + : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) + : : : : : +- BroadcastExchange (8) + : : : : : +- * ColumnarToRow (7) + : : : : : +- CometProject (6) + : : : : : +- CometFilter (5) + : : : : : +- CometScan parquet spark_catalog.default.customer_demographics (4) + : : : : +- BroadcastExchange (15) + : : : : +- * ColumnarToRow (14) + : : : : +- CometProject (13) + : : : : +- CometFilter (12) + : : : : +- CometScan parquet spark_catalog.default.customer (11) + : : : +- BroadcastExchange (21) + : : : +- * ColumnarToRow (20) + : : : +- CometFilter (19) + : : : +- CometScan parquet spark_catalog.default.customer_demographics (18) + : : +- BroadcastExchange (27) + : : +- * ColumnarToRow (26) + : : +- CometFilter (25) + : : +- CometScan parquet spark_catalog.default.customer_address (24) + : +- ReusedExchange (30) + +- BroadcastExchange (36) + +- * ColumnarToRow (35) + +- CometFilter (34) + +- CometScan parquet spark_catalog.default.item (33) + + +(1) Scan parquet spark_catalog.default.catalog_sales +Output [9]: [cs_bill_customer_sk#1, cs_bill_cdemo_sk#2, cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#9), dynamicpruningexpression(cs_sold_date_sk#9 IN dynamicpruning#10)] +PushedFilters: [IsNotNull(cs_bill_cdemo_sk), IsNotNull(cs_bill_customer_sk), IsNotNull(cs_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [9]: [cs_bill_customer_sk#1, cs_bill_cdemo_sk#2, cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9] +Condition : ((isnotnull(cs_bill_cdemo_sk#2) AND isnotnull(cs_bill_customer_sk#1)) AND isnotnull(cs_item_sk#3)) + +(3) ColumnarToRow [codegen id : 7] +Input [9]: [cs_bill_customer_sk#1, cs_bill_cdemo_sk#2, cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9] + +(4) Scan parquet spark_catalog.default.customer_demographics +Output [4]: [cd_demo_sk#11, cd_gender#12, cd_education_status#13, cd_dep_count#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_gender), IsNotNull(cd_education_status), EqualTo(cd_gender,F), EqualTo(cd_education_status,Unknown ), IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(5) CometFilter +Input [4]: [cd_demo_sk#11, cd_gender#12, cd_education_status#13, cd_dep_count#14] +Condition : ((((isnotnull(cd_gender#12) AND isnotnull(cd_education_status#13)) AND (cd_gender#12 = F)) AND (cd_education_status#13 = Unknown )) AND isnotnull(cd_demo_sk#11)) + +(6) CometProject +Input [4]: [cd_demo_sk#11, cd_gender#12, cd_education_status#13, cd_dep_count#14] +Arguments: [cd_demo_sk#11, cd_dep_count#14], [cd_demo_sk#11, cd_dep_count#14] + +(7) ColumnarToRow [codegen id : 1] +Input [2]: [cd_demo_sk#11, cd_dep_count#14] + +(8) BroadcastExchange +Input [2]: [cd_demo_sk#11, cd_dep_count#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [cs_bill_cdemo_sk#2] +Right keys [1]: [cd_demo_sk#11] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 7] +Output [9]: [cs_bill_customer_sk#1, cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14] +Input [11]: [cs_bill_customer_sk#1, cs_bill_cdemo_sk#2, cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_demo_sk#11, cd_dep_count#14] + +(11) Scan parquet spark_catalog.default.customer +Output [5]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_month#18, c_birth_year#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [In(c_birth_month, [1,12,2,6,8,9]), IsNotNull(c_customer_sk), IsNotNull(c_current_cdemo_sk), IsNotNull(c_current_addr_sk)] +ReadSchema: struct + +(12) CometFilter +Input [5]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_month#18, c_birth_year#19] +Condition : (((c_birth_month#18 IN (1,6,8,9,12,2) AND isnotnull(c_customer_sk#15)) AND isnotnull(c_current_cdemo_sk#16)) AND isnotnull(c_current_addr_sk#17)) + +(13) CometProject +Input [5]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_month#18, c_birth_year#19] +Arguments: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19], [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19] + +(14) ColumnarToRow [codegen id : 2] +Input [4]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19] + +(15) BroadcastExchange +Input [4]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(16) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [cs_bill_customer_sk#1] +Right keys [1]: [c_customer_sk#15] +Join type: Inner +Join condition: None + +(17) Project [codegen id : 7] +Output [11]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19] +Input [13]: [cs_bill_customer_sk#1, cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14, c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19] + +(18) Scan parquet spark_catalog.default.customer_demographics +Output [1]: [cd_demo_sk#20] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(19) CometFilter +Input [1]: [cd_demo_sk#20] +Condition : isnotnull(cd_demo_sk#20) + +(20) ColumnarToRow [codegen id : 3] +Input [1]: [cd_demo_sk#20] + +(21) BroadcastExchange +Input [1]: [cd_demo_sk#20] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(22) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [c_current_cdemo_sk#16] +Right keys [1]: [cd_demo_sk#20] +Join type: Inner +Join condition: None + +(23) Project [codegen id : 7] +Output [10]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14, c_current_addr_sk#17, c_birth_year#19] +Input [12]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19, cd_demo_sk#20] + +(24) Scan parquet spark_catalog.default.customer_address +Output [4]: [ca_address_sk#21, ca_county#22, ca_state#23, ca_country#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [In(ca_state, [IN,MS,ND,NM,OK,VA]), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(25) CometFilter +Input [4]: [ca_address_sk#21, ca_county#22, ca_state#23, ca_country#24] +Condition : (ca_state#23 IN (MS,IN,ND,OK,NM,VA) AND isnotnull(ca_address_sk#21)) + +(26) ColumnarToRow [codegen id : 4] +Input [4]: [ca_address_sk#21, ca_county#22, ca_state#23, ca_country#24] + +(27) BroadcastExchange +Input [4]: [ca_address_sk#21, ca_county#22, ca_state#23, ca_country#24] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(28) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [c_current_addr_sk#17] +Right keys [1]: [ca_address_sk#21] +Join type: Inner +Join condition: None + +(29) Project [codegen id : 7] +Output [12]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14, c_birth_year#19, ca_county#22, ca_state#23, ca_country#24] +Input [14]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14, c_current_addr_sk#17, c_birth_year#19, ca_address_sk#21, ca_county#22, ca_state#23, ca_country#24] + +(30) ReusedExchange [Reuses operator id: 48] +Output [1]: [d_date_sk#25] + +(31) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [cs_sold_date_sk#9] +Right keys [1]: [d_date_sk#25] +Join type: Inner +Join condition: None + +(32) Project [codegen id : 7] +Output [11]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, ca_county#22, ca_state#23, ca_country#24] +Input [13]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14, c_birth_year#19, ca_county#22, ca_state#23, ca_country#24, d_date_sk#25] + +(33) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#26, i_item_id#27] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(34) CometFilter +Input [2]: [i_item_sk#26, i_item_id#27] +Condition : isnotnull(i_item_sk#26) + +(35) ColumnarToRow [codegen id : 6] +Input [2]: [i_item_sk#26, i_item_id#27] + +(36) BroadcastExchange +Input [2]: [i_item_sk#26, i_item_id#27] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(37) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [cs_item_sk#3] +Right keys [1]: [i_item_sk#26] +Join type: Inner +Join condition: None + +(38) Project [codegen id : 7] +Output [11]: [cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, i_item_id#27, ca_country#24, ca_state#23, ca_county#22] +Input [13]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, ca_county#22, ca_state#23, ca_country#24, i_item_sk#26, i_item_id#27] + +(39) Expand [codegen id : 7] +Input [11]: [cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, i_item_id#27, ca_country#24, ca_state#23, ca_county#22] +Arguments: [[cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, i_item_id#27, ca_country#24, ca_state#23, ca_county#22, 0], [cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, i_item_id#27, ca_country#24, ca_state#23, null, 1], [cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, i_item_id#27, ca_country#24, null, null, 3], [cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, i_item_id#27, null, null, null, 7], [cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, null, null, null, null, 15]], [cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32] + +(40) HashAggregate [codegen id : 7] +Input [12]: [cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32] +Keys [5]: [i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32] +Functions [7]: [partial_avg(cast(cs_quantity#4 as decimal(12,2))), partial_avg(cast(cs_list_price#5 as decimal(12,2))), partial_avg(cast(cs_coupon_amt#7 as decimal(12,2))), partial_avg(cast(cs_sales_price#6 as decimal(12,2))), partial_avg(cast(cs_net_profit#8 as decimal(12,2))), partial_avg(cast(c_birth_year#19 as decimal(12,2))), partial_avg(cast(cd_dep_count#14 as decimal(12,2)))] +Aggregate Attributes [14]: [sum#33, count#34, sum#35, count#36, sum#37, count#38, sum#39, count#40, sum#41, count#42, sum#43, count#44, sum#45, count#46] +Results [19]: [i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32, sum#47, count#48, sum#49, count#50, sum#51, count#52, sum#53, count#54, sum#55, count#56, sum#57, count#58, sum#59, count#60] + +(41) Exchange +Input [19]: [i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32, sum#47, count#48, sum#49, count#50, sum#51, count#52, sum#53, count#54, sum#55, count#56, sum#57, count#58, sum#59, count#60] +Arguments: hashpartitioning(i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(42) HashAggregate [codegen id : 8] +Input [19]: [i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32, sum#47, count#48, sum#49, count#50, sum#51, count#52, sum#53, count#54, sum#55, count#56, sum#57, count#58, sum#59, count#60] +Keys [5]: [i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32] +Functions [7]: [avg(cast(cs_quantity#4 as decimal(12,2))), avg(cast(cs_list_price#5 as decimal(12,2))), avg(cast(cs_coupon_amt#7 as decimal(12,2))), avg(cast(cs_sales_price#6 as decimal(12,2))), avg(cast(cs_net_profit#8 as decimal(12,2))), avg(cast(c_birth_year#19 as decimal(12,2))), avg(cast(cd_dep_count#14 as decimal(12,2)))] +Aggregate Attributes [7]: [avg(cast(cs_quantity#4 as decimal(12,2)))#61, avg(cast(cs_list_price#5 as decimal(12,2)))#62, avg(cast(cs_coupon_amt#7 as decimal(12,2)))#63, avg(cast(cs_sales_price#6 as decimal(12,2)))#64, avg(cast(cs_net_profit#8 as decimal(12,2)))#65, avg(cast(c_birth_year#19 as decimal(12,2)))#66, avg(cast(cd_dep_count#14 as decimal(12,2)))#67] +Results [11]: [i_item_id#28, ca_country#29, ca_state#30, ca_county#31, avg(cast(cs_quantity#4 as decimal(12,2)))#61 AS agg1#68, avg(cast(cs_list_price#5 as decimal(12,2)))#62 AS agg2#69, avg(cast(cs_coupon_amt#7 as decimal(12,2)))#63 AS agg3#70, avg(cast(cs_sales_price#6 as decimal(12,2)))#64 AS agg4#71, avg(cast(cs_net_profit#8 as decimal(12,2)))#65 AS agg5#72, avg(cast(c_birth_year#19 as decimal(12,2)))#66 AS agg6#73, avg(cast(cd_dep_count#14 as decimal(12,2)))#67 AS agg7#74] + +(43) TakeOrderedAndProject +Input [11]: [i_item_id#28, ca_country#29, ca_state#30, ca_county#31, agg1#68, agg2#69, agg3#70, agg4#71, agg5#72, agg6#73, agg7#74] +Arguments: 100, [ca_country#29 ASC NULLS FIRST, ca_state#30 ASC NULLS FIRST, ca_county#31 ASC NULLS FIRST, i_item_id#28 ASC NULLS FIRST], [i_item_id#28, ca_country#29, ca_state#30, ca_county#31, agg1#68, agg2#69, agg3#70, agg4#71, agg5#72, agg6#73, agg7#74] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#9 IN dynamicpruning#10 +BroadcastExchange (48) ++- * ColumnarToRow (47) + +- CometProject (46) + +- CometFilter (45) + +- CometScan parquet spark_catalog.default.date_dim (44) + + +(44) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#25, d_year#75] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,1998), IsNotNull(d_date_sk)] +ReadSchema: struct + +(45) CometFilter +Input [2]: [d_date_sk#25, d_year#75] +Condition : ((isnotnull(d_year#75) AND (d_year#75 = 1998)) AND isnotnull(d_date_sk#25)) + +(46) CometProject +Input [2]: [d_date_sk#25, d_year#75] +Arguments: [d_date_sk#25], [d_date_sk#25] + +(47) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#25] + +(48) BroadcastExchange +Input [1]: [d_date_sk#25] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q18/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q18/simplified.txt new file mode 100644 index 0000000000..47911b9ba3 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q18/simplified.txt @@ -0,0 +1,71 @@ +TakeOrderedAndProject [ca_country,ca_state,ca_county,i_item_id,agg1,agg2,agg3,agg4,agg5,agg6,agg7] + WholeStageCodegen (8) + HashAggregate [i_item_id,ca_country,ca_state,ca_county,spark_grouping_id,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] [avg(cast(cs_quantity as decimal(12,2))),avg(cast(cs_list_price as decimal(12,2))),avg(cast(cs_coupon_amt as decimal(12,2))),avg(cast(cs_sales_price as decimal(12,2))),avg(cast(cs_net_profit as decimal(12,2))),avg(cast(c_birth_year as decimal(12,2))),avg(cast(cd_dep_count as decimal(12,2))),agg1,agg2,agg3,agg4,agg5,agg6,agg7,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + InputAdapter + Exchange [i_item_id,ca_country,ca_state,ca_county,spark_grouping_id] #1 + WholeStageCodegen (7) + HashAggregate [i_item_id,ca_country,ca_state,ca_county,spark_grouping_id,cs_quantity,cs_list_price,cs_coupon_amt,cs_sales_price,cs_net_profit,c_birth_year,cd_dep_count] [sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + Expand [cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cd_dep_count,c_birth_year,i_item_id,ca_country,ca_state,ca_county] + Project [cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cd_dep_count,c_birth_year,i_item_id,ca_country,ca_state,ca_county] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cd_dep_count,c_birth_year,ca_county,ca_state,ca_country] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_birth_year,ca_county,ca_state,ca_country] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_current_addr_sk,c_birth_year] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_current_cdemo_sk,c_current_addr_sk,c_birth_year] + BroadcastHashJoin [cs_bill_customer_sk,c_customer_sk] + Project [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count] + BroadcastHashJoin [cs_bill_cdemo_sk,cd_demo_sk] + ColumnarToRow + InputAdapter + CometFilter [cs_bill_cdemo_sk,cs_bill_customer_sk,cs_item_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_bill_cdemo_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [cd_demo_sk,cd_dep_count] + CometFilter [cd_gender,cd_education_status,cd_demo_sk] + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_education_status,cd_dep_count] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometProject [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk,c_birth_year] + CometFilter [c_birth_month,c_customer_sk,c_current_cdemo_sk,c_current_addr_sk] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk,c_birth_month,c_birth_year] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometFilter [cd_demo_sk] + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (4) + ColumnarToRow + InputAdapter + CometFilter [ca_state,ca_address_sk] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_county,ca_state,ca_country] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (6) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q19/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q19/explain.txt new file mode 100644 index 0000000000..999fec8383 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q19/explain.txt @@ -0,0 +1,227 @@ +== Physical Plan == +TakeOrderedAndProject (39) ++- * HashAggregate (38) + +- Exchange (37) + +- * HashAggregate (36) + +- * Project (35) + +- * BroadcastHashJoin Inner BuildRight (34) + :- * Project (29) + : +- * BroadcastHashJoin Inner BuildRight (28) + : :- * Project (23) + : : +- * BroadcastHashJoin Inner BuildRight (22) + : : :- * Project (17) + : : : +- * BroadcastHashJoin Inner BuildRight (16) + : : : :- * Project (10) + : : : : +- * BroadcastHashJoin Inner BuildRight (9) + : : : : :- * ColumnarToRow (4) + : : : : : +- CometProject (3) + : : : : : +- CometFilter (2) + : : : : : +- CometScan parquet spark_catalog.default.date_dim (1) + : : : : +- BroadcastExchange (8) + : : : : +- * ColumnarToRow (7) + : : : : +- CometFilter (6) + : : : : +- CometScan parquet spark_catalog.default.store_sales (5) + : : : +- BroadcastExchange (15) + : : : +- * ColumnarToRow (14) + : : : +- CometProject (13) + : : : +- CometFilter (12) + : : : +- CometScan parquet spark_catalog.default.item (11) + : : +- BroadcastExchange (21) + : : +- * ColumnarToRow (20) + : : +- CometFilter (19) + : : +- CometScan parquet spark_catalog.default.customer (18) + : +- BroadcastExchange (27) + : +- * ColumnarToRow (26) + : +- CometFilter (25) + : +- CometScan parquet spark_catalog.default.customer_address (24) + +- BroadcastExchange (33) + +- * ColumnarToRow (32) + +- CometFilter (31) + +- CometScan parquet spark_catalog.default.store (30) + + +(1) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#1, d_year#2, d_moy#3] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), EqualTo(d_moy,11), EqualTo(d_year,1998), IsNotNull(d_date_sk)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [d_date_sk#1, d_year#2, d_moy#3] +Condition : ((((isnotnull(d_moy#3) AND isnotnull(d_year#2)) AND (d_moy#3 = 11)) AND (d_year#2 = 1998)) AND isnotnull(d_date_sk#1)) + +(3) CometProject +Input [3]: [d_date_sk#1, d_year#2, d_moy#3] +Arguments: [d_date_sk#1], [d_date_sk#1] + +(4) ColumnarToRow [codegen id : 6] +Input [1]: [d_date_sk#1] + +(5) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_item_sk#4, ss_customer_sk#5, ss_store_sk#6, ss_ext_sales_price#7, ss_sold_date_sk#8] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#8), dynamicpruningexpression(true)] +PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_customer_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(6) CometFilter +Input [5]: [ss_item_sk#4, ss_customer_sk#5, ss_store_sk#6, ss_ext_sales_price#7, ss_sold_date_sk#8] +Condition : ((isnotnull(ss_item_sk#4) AND isnotnull(ss_customer_sk#5)) AND isnotnull(ss_store_sk#6)) + +(7) ColumnarToRow [codegen id : 1] +Input [5]: [ss_item_sk#4, ss_customer_sk#5, ss_store_sk#6, ss_ext_sales_price#7, ss_sold_date_sk#8] + +(8) BroadcastExchange +Input [5]: [ss_item_sk#4, ss_customer_sk#5, ss_store_sk#6, ss_ext_sales_price#7, ss_sold_date_sk#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[4, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [d_date_sk#1] +Right keys [1]: [ss_sold_date_sk#8] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 6] +Output [4]: [ss_item_sk#4, ss_customer_sk#5, ss_store_sk#6, ss_ext_sales_price#7] +Input [6]: [d_date_sk#1, ss_item_sk#4, ss_customer_sk#5, ss_store_sk#6, ss_ext_sales_price#7, ss_sold_date_sk#8] + +(11) Scan parquet spark_catalog.default.item +Output [6]: [i_item_sk#9, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13, i_manager_id#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_manager_id), EqualTo(i_manager_id,8), IsNotNull(i_item_sk)] +ReadSchema: struct + +(12) CometFilter +Input [6]: [i_item_sk#9, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13, i_manager_id#14] +Condition : ((isnotnull(i_manager_id#14) AND (i_manager_id#14 = 8)) AND isnotnull(i_item_sk#9)) + +(13) CometProject +Input [6]: [i_item_sk#9, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13, i_manager_id#14] +Arguments: [i_item_sk#9, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13], [i_item_sk#9, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13] + +(14) ColumnarToRow [codegen id : 2] +Input [5]: [i_item_sk#9, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13] + +(15) BroadcastExchange +Input [5]: [i_item_sk#9, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(16) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_item_sk#4] +Right keys [1]: [i_item_sk#9] +Join type: Inner +Join condition: None + +(17) Project [codegen id : 6] +Output [7]: [ss_customer_sk#5, ss_store_sk#6, ss_ext_sales_price#7, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13] +Input [9]: [ss_item_sk#4, ss_customer_sk#5, ss_store_sk#6, ss_ext_sales_price#7, i_item_sk#9, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13] + +(18) Scan parquet spark_catalog.default.customer +Output [2]: [c_customer_sk#15, c_current_addr_sk#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_current_addr_sk)] +ReadSchema: struct + +(19) CometFilter +Input [2]: [c_customer_sk#15, c_current_addr_sk#16] +Condition : (isnotnull(c_customer_sk#15) AND isnotnull(c_current_addr_sk#16)) + +(20) ColumnarToRow [codegen id : 3] +Input [2]: [c_customer_sk#15, c_current_addr_sk#16] + +(21) BroadcastExchange +Input [2]: [c_customer_sk#15, c_current_addr_sk#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(22) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_customer_sk#5] +Right keys [1]: [c_customer_sk#15] +Join type: Inner +Join condition: None + +(23) Project [codegen id : 6] +Output [7]: [ss_store_sk#6, ss_ext_sales_price#7, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13, c_current_addr_sk#16] +Input [9]: [ss_customer_sk#5, ss_store_sk#6, ss_ext_sales_price#7, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13, c_customer_sk#15, c_current_addr_sk#16] + +(24) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#17, ca_zip#18] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk), IsNotNull(ca_zip)] +ReadSchema: struct + +(25) CometFilter +Input [2]: [ca_address_sk#17, ca_zip#18] +Condition : (isnotnull(ca_address_sk#17) AND isnotnull(ca_zip#18)) + +(26) ColumnarToRow [codegen id : 4] +Input [2]: [ca_address_sk#17, ca_zip#18] + +(27) BroadcastExchange +Input [2]: [ca_address_sk#17, ca_zip#18] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(28) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [c_current_addr_sk#16] +Right keys [1]: [ca_address_sk#17] +Join type: Inner +Join condition: None + +(29) Project [codegen id : 6] +Output [7]: [ss_store_sk#6, ss_ext_sales_price#7, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13, ca_zip#18] +Input [9]: [ss_store_sk#6, ss_ext_sales_price#7, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13, c_current_addr_sk#16, ca_address_sk#17, ca_zip#18] + +(30) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#19, s_zip#20] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_zip), IsNotNull(s_store_sk)] +ReadSchema: struct + +(31) CometFilter +Input [2]: [s_store_sk#19, s_zip#20] +Condition : (isnotnull(s_zip#20) AND isnotnull(s_store_sk#19)) + +(32) ColumnarToRow [codegen id : 5] +Input [2]: [s_store_sk#19, s_zip#20] + +(33) BroadcastExchange +Input [2]: [s_store_sk#19, s_zip#20] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(34) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_store_sk#6] +Right keys [1]: [s_store_sk#19] +Join type: Inner +Join condition: NOT (substr(ca_zip#18, 1, 5) = substr(s_zip#20, 1, 5)) + +(35) Project [codegen id : 6] +Output [5]: [ss_ext_sales_price#7, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13] +Input [9]: [ss_store_sk#6, ss_ext_sales_price#7, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13, ca_zip#18, s_store_sk#19, s_zip#20] + +(36) HashAggregate [codegen id : 6] +Input [5]: [ss_ext_sales_price#7, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13] +Keys [4]: [i_brand#11, i_brand_id#10, i_manufact_id#12, i_manufact#13] +Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#7))] +Aggregate Attributes [1]: [sum#21] +Results [5]: [i_brand#11, i_brand_id#10, i_manufact_id#12, i_manufact#13, sum#22] + +(37) Exchange +Input [5]: [i_brand#11, i_brand_id#10, i_manufact_id#12, i_manufact#13, sum#22] +Arguments: hashpartitioning(i_brand#11, i_brand_id#10, i_manufact_id#12, i_manufact#13, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(38) HashAggregate [codegen id : 7] +Input [5]: [i_brand#11, i_brand_id#10, i_manufact_id#12, i_manufact#13, sum#22] +Keys [4]: [i_brand#11, i_brand_id#10, i_manufact_id#12, i_manufact#13] +Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#7))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#7))#23] +Results [5]: [i_brand_id#10 AS brand_id#24, i_brand#11 AS brand#25, i_manufact_id#12, i_manufact#13, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#7))#23,17,2) AS ext_price#26] + +(39) TakeOrderedAndProject +Input [5]: [brand_id#24, brand#25, i_manufact_id#12, i_manufact#13, ext_price#26] +Arguments: 100, [ext_price#26 DESC NULLS LAST, brand#25 ASC NULLS FIRST, brand_id#24 ASC NULLS FIRST, i_manufact_id#12 ASC NULLS FIRST, i_manufact#13 ASC NULLS FIRST], [brand_id#24, brand#25, i_manufact_id#12, i_manufact#13, ext_price#26] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q19/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q19/simplified.txt new file mode 100644 index 0000000000..c2f5d1a876 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q19/simplified.txt @@ -0,0 +1,58 @@ +TakeOrderedAndProject [ext_price,brand,brand_id,i_manufact_id,i_manufact] + WholeStageCodegen (7) + HashAggregate [i_brand,i_brand_id,i_manufact_id,i_manufact,sum] [sum(UnscaledValue(ss_ext_sales_price)),brand_id,brand,ext_price,sum] + InputAdapter + Exchange [i_brand,i_brand_id,i_manufact_id,i_manufact] #1 + WholeStageCodegen (6) + HashAggregate [i_brand,i_brand_id,i_manufact_id,i_manufact,ss_ext_sales_price] [sum,sum] + Project [ss_ext_sales_price,i_brand_id,i_brand,i_manufact_id,i_manufact] + BroadcastHashJoin [ss_store_sk,s_store_sk,ca_zip,s_zip] + Project [ss_store_sk,ss_ext_sales_price,i_brand_id,i_brand,i_manufact_id,i_manufact,ca_zip] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [ss_store_sk,ss_ext_sales_price,i_brand_id,i_brand,i_manufact_id,i_manufact,c_current_addr_sk] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Project [ss_customer_sk,ss_store_sk,ss_ext_sales_price,i_brand_id,i_brand,i_manufact_id,i_manufact] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ext_sales_price] + BroadcastHashJoin [d_date_sk,ss_sold_date_sk] + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_moy,d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk,ss_customer_sk,ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ext_sales_price,ss_sold_date_sk] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometProject [i_item_sk,i_brand_id,i_brand,i_manufact_id,i_manufact] + CometFilter [i_manager_id,i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_brand,i_manufact_id,i_manufact,i_manager_id] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_current_addr_sk] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_addr_sk] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (4) + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk,ca_zip] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_zip] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (5) + ColumnarToRow + InputAdapter + CometFilter [s_zip,s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk,s_zip] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q2/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q2/explain.txt new file mode 100644 index 0000000000..1215adf3f0 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q2/explain.txt @@ -0,0 +1,210 @@ +== Physical Plan == +* Sort (36) ++- Exchange (35) + +- * Project (34) + +- * BroadcastHashJoin Inner BuildRight (33) + :- * Project (22) + : +- * BroadcastHashJoin Inner BuildRight (21) + : :- * HashAggregate (15) + : : +- Exchange (14) + : : +- * HashAggregate (13) + : : +- * Project (12) + : : +- * BroadcastHashJoin Inner BuildRight (11) + : : :- * ColumnarToRow (6) + : : : +- CometUnion (5) + : : : :- CometProject (2) + : : : : +- CometScan parquet spark_catalog.default.web_sales (1) + : : : +- CometProject (4) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (3) + : : +- BroadcastExchange (10) + : : +- * ColumnarToRow (9) + : : +- CometFilter (8) + : : +- CometScan parquet spark_catalog.default.date_dim (7) + : +- BroadcastExchange (20) + : +- * ColumnarToRow (19) + : +- CometProject (18) + : +- CometFilter (17) + : +- CometScan parquet spark_catalog.default.date_dim (16) + +- BroadcastExchange (32) + +- * Project (31) + +- * BroadcastHashJoin Inner BuildRight (30) + :- * HashAggregate (24) + : +- ReusedExchange (23) + +- BroadcastExchange (29) + +- * ColumnarToRow (28) + +- CometProject (27) + +- CometFilter (26) + +- CometScan parquet spark_catalog.default.date_dim (25) + + +(1) Scan parquet spark_catalog.default.web_sales +Output [2]: [ws_ext_sales_price#1, ws_sold_date_sk#2] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#2)] +ReadSchema: struct + +(2) CometProject +Input [2]: [ws_ext_sales_price#1, ws_sold_date_sk#2] +Arguments: [sold_date_sk#3, sales_price#4], [ws_sold_date_sk#2 AS sold_date_sk#3, ws_ext_sales_price#1 AS sales_price#4] + +(3) Scan parquet spark_catalog.default.catalog_sales +Output [2]: [cs_ext_sales_price#5, cs_sold_date_sk#6] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#6)] +ReadSchema: struct + +(4) CometProject +Input [2]: [cs_ext_sales_price#5, cs_sold_date_sk#6] +Arguments: [sold_date_sk#7, sales_price#8], [cs_sold_date_sk#6 AS sold_date_sk#7, cs_ext_sales_price#5 AS sales_price#8] + +(5) CometUnion +Child 0 Input [2]: [sold_date_sk#3, sales_price#4] +Child 1 Input [2]: [sold_date_sk#7, sales_price#8] + +(6) ColumnarToRow [codegen id : 2] +Input [2]: [sold_date_sk#3, sales_price#4] + +(7) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#9, d_week_seq#10, d_day_name#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date_sk), IsNotNull(d_week_seq)] +ReadSchema: struct + +(8) CometFilter +Input [3]: [d_date_sk#9, d_week_seq#10, d_day_name#11] +Condition : (isnotnull(d_date_sk#9) AND isnotnull(d_week_seq#10)) + +(9) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#9, d_week_seq#10, d_day_name#11] + +(10) BroadcastExchange +Input [3]: [d_date_sk#9, d_week_seq#10, d_day_name#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(11) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [sold_date_sk#3] +Right keys [1]: [d_date_sk#9] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 2] +Output [3]: [sales_price#4, d_week_seq#10, d_day_name#11] +Input [5]: [sold_date_sk#3, sales_price#4, d_date_sk#9, d_week_seq#10, d_day_name#11] + +(13) HashAggregate [codegen id : 2] +Input [3]: [sales_price#4, d_week_seq#10, d_day_name#11] +Keys [1]: [d_week_seq#10] +Functions [7]: [partial_sum(UnscaledValue(CASE WHEN (d_day_name#11 = Sunday ) THEN sales_price#4 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#11 = Monday ) THEN sales_price#4 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#11 = Tuesday ) THEN sales_price#4 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#11 = Wednesday) THEN sales_price#4 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#11 = Thursday ) THEN sales_price#4 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#11 = Friday ) THEN sales_price#4 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#11 = Saturday ) THEN sales_price#4 END))] +Aggregate Attributes [7]: [sum#12, sum#13, sum#14, sum#15, sum#16, sum#17, sum#18] +Results [8]: [d_week_seq#10, sum#19, sum#20, sum#21, sum#22, sum#23, sum#24, sum#25] + +(14) Exchange +Input [8]: [d_week_seq#10, sum#19, sum#20, sum#21, sum#22, sum#23, sum#24, sum#25] +Arguments: hashpartitioning(d_week_seq#10, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 8] +Input [8]: [d_week_seq#10, sum#19, sum#20, sum#21, sum#22, sum#23, sum#24, sum#25] +Keys [1]: [d_week_seq#10] +Functions [7]: [sum(UnscaledValue(CASE WHEN (d_day_name#11 = Sunday ) THEN sales_price#4 END)), sum(UnscaledValue(CASE WHEN (d_day_name#11 = Monday ) THEN sales_price#4 END)), sum(UnscaledValue(CASE WHEN (d_day_name#11 = Tuesday ) THEN sales_price#4 END)), sum(UnscaledValue(CASE WHEN (d_day_name#11 = Wednesday) THEN sales_price#4 END)), sum(UnscaledValue(CASE WHEN (d_day_name#11 = Thursday ) THEN sales_price#4 END)), sum(UnscaledValue(CASE WHEN (d_day_name#11 = Friday ) THEN sales_price#4 END)), sum(UnscaledValue(CASE WHEN (d_day_name#11 = Saturday ) THEN sales_price#4 END))] +Aggregate Attributes [7]: [sum(UnscaledValue(CASE WHEN (d_day_name#11 = Sunday ) THEN sales_price#4 END))#26, sum(UnscaledValue(CASE WHEN (d_day_name#11 = Monday ) THEN sales_price#4 END))#27, sum(UnscaledValue(CASE WHEN (d_day_name#11 = Tuesday ) THEN sales_price#4 END))#28, sum(UnscaledValue(CASE WHEN (d_day_name#11 = Wednesday) THEN sales_price#4 END))#29, sum(UnscaledValue(CASE WHEN (d_day_name#11 = Thursday ) THEN sales_price#4 END))#30, sum(UnscaledValue(CASE WHEN (d_day_name#11 = Friday ) THEN sales_price#4 END))#31, sum(UnscaledValue(CASE WHEN (d_day_name#11 = Saturday ) THEN sales_price#4 END))#32] +Results [8]: [d_week_seq#10, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#11 = Sunday ) THEN sales_price#4 END))#26,17,2) AS sun_sales#33, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#11 = Monday ) THEN sales_price#4 END))#27,17,2) AS mon_sales#34, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#11 = Tuesday ) THEN sales_price#4 END))#28,17,2) AS tue_sales#35, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#11 = Wednesday) THEN sales_price#4 END))#29,17,2) AS wed_sales#36, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#11 = Thursday ) THEN sales_price#4 END))#30,17,2) AS thu_sales#37, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#11 = Friday ) THEN sales_price#4 END))#31,17,2) AS fri_sales#38, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#11 = Saturday ) THEN sales_price#4 END))#32,17,2) AS sat_sales#39] + +(16) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_week_seq#40, d_year#41] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_week_seq)] +ReadSchema: struct + +(17) CometFilter +Input [2]: [d_week_seq#40, d_year#41] +Condition : ((isnotnull(d_year#41) AND (d_year#41 = 2001)) AND isnotnull(d_week_seq#40)) + +(18) CometProject +Input [2]: [d_week_seq#40, d_year#41] +Arguments: [d_week_seq#40], [d_week_seq#40] + +(19) ColumnarToRow [codegen id : 3] +Input [1]: [d_week_seq#40] + +(20) BroadcastExchange +Input [1]: [d_week_seq#40] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(21) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [d_week_seq#10] +Right keys [1]: [d_week_seq#40] +Join type: Inner +Join condition: None + +(22) Project [codegen id : 8] +Output [8]: [d_week_seq#10 AS d_week_seq1#42, sun_sales#33 AS sun_sales1#43, mon_sales#34 AS mon_sales1#44, tue_sales#35 AS tue_sales1#45, wed_sales#36 AS wed_sales1#46, thu_sales#37 AS thu_sales1#47, fri_sales#38 AS fri_sales1#48, sat_sales#39 AS sat_sales1#49] +Input [9]: [d_week_seq#10, sun_sales#33, mon_sales#34, tue_sales#35, wed_sales#36, thu_sales#37, fri_sales#38, sat_sales#39, d_week_seq#40] + +(23) ReusedExchange [Reuses operator id: 14] +Output [8]: [d_week_seq#50, sum#51, sum#52, sum#53, sum#54, sum#55, sum#56, sum#57] + +(24) HashAggregate [codegen id : 7] +Input [8]: [d_week_seq#50, sum#51, sum#52, sum#53, sum#54, sum#55, sum#56, sum#57] +Keys [1]: [d_week_seq#50] +Functions [7]: [sum(UnscaledValue(CASE WHEN (d_day_name#58 = Sunday ) THEN sales_price#59 END)), sum(UnscaledValue(CASE WHEN (d_day_name#58 = Monday ) THEN sales_price#59 END)), sum(UnscaledValue(CASE WHEN (d_day_name#58 = Tuesday ) THEN sales_price#59 END)), sum(UnscaledValue(CASE WHEN (d_day_name#58 = Wednesday) THEN sales_price#59 END)), sum(UnscaledValue(CASE WHEN (d_day_name#58 = Thursday ) THEN sales_price#59 END)), sum(UnscaledValue(CASE WHEN (d_day_name#58 = Friday ) THEN sales_price#59 END)), sum(UnscaledValue(CASE WHEN (d_day_name#58 = Saturday ) THEN sales_price#59 END))] +Aggregate Attributes [7]: [sum(UnscaledValue(CASE WHEN (d_day_name#58 = Sunday ) THEN sales_price#59 END))#26, sum(UnscaledValue(CASE WHEN (d_day_name#58 = Monday ) THEN sales_price#59 END))#27, sum(UnscaledValue(CASE WHEN (d_day_name#58 = Tuesday ) THEN sales_price#59 END))#28, sum(UnscaledValue(CASE WHEN (d_day_name#58 = Wednesday) THEN sales_price#59 END))#29, sum(UnscaledValue(CASE WHEN (d_day_name#58 = Thursday ) THEN sales_price#59 END))#30, sum(UnscaledValue(CASE WHEN (d_day_name#58 = Friday ) THEN sales_price#59 END))#31, sum(UnscaledValue(CASE WHEN (d_day_name#58 = Saturday ) THEN sales_price#59 END))#32] +Results [8]: [d_week_seq#50, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#58 = Sunday ) THEN sales_price#59 END))#26,17,2) AS sun_sales#60, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#58 = Monday ) THEN sales_price#59 END))#27,17,2) AS mon_sales#61, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#58 = Tuesday ) THEN sales_price#59 END))#28,17,2) AS tue_sales#62, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#58 = Wednesday) THEN sales_price#59 END))#29,17,2) AS wed_sales#63, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#58 = Thursday ) THEN sales_price#59 END))#30,17,2) AS thu_sales#64, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#58 = Friday ) THEN sales_price#59 END))#31,17,2) AS fri_sales#65, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#58 = Saturday ) THEN sales_price#59 END))#32,17,2) AS sat_sales#66] + +(25) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_week_seq#67, d_year#68] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2002), IsNotNull(d_week_seq)] +ReadSchema: struct + +(26) CometFilter +Input [2]: [d_week_seq#67, d_year#68] +Condition : ((isnotnull(d_year#68) AND (d_year#68 = 2002)) AND isnotnull(d_week_seq#67)) + +(27) CometProject +Input [2]: [d_week_seq#67, d_year#68] +Arguments: [d_week_seq#67], [d_week_seq#67] + +(28) ColumnarToRow [codegen id : 6] +Input [1]: [d_week_seq#67] + +(29) BroadcastExchange +Input [1]: [d_week_seq#67] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(30) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [d_week_seq#50] +Right keys [1]: [d_week_seq#67] +Join type: Inner +Join condition: None + +(31) Project [codegen id : 7] +Output [8]: [d_week_seq#50 AS d_week_seq2#69, sun_sales#60 AS sun_sales2#70, mon_sales#61 AS mon_sales2#71, tue_sales#62 AS tue_sales2#72, wed_sales#63 AS wed_sales2#73, thu_sales#64 AS thu_sales2#74, fri_sales#65 AS fri_sales2#75, sat_sales#66 AS sat_sales2#76] +Input [9]: [d_week_seq#50, sun_sales#60, mon_sales#61, tue_sales#62, wed_sales#63, thu_sales#64, fri_sales#65, sat_sales#66, d_week_seq#67] + +(32) BroadcastExchange +Input [8]: [d_week_seq2#69, sun_sales2#70, mon_sales2#71, tue_sales2#72, wed_sales2#73, thu_sales2#74, fri_sales2#75, sat_sales2#76] +Arguments: HashedRelationBroadcastMode(List(cast((input[0, int, true] - 53) as bigint)),false), [plan_id=5] + +(33) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [d_week_seq1#42] +Right keys [1]: [(d_week_seq2#69 - 53)] +Join type: Inner +Join condition: None + +(34) Project [codegen id : 8] +Output [8]: [d_week_seq1#42, round((sun_sales1#43 / sun_sales2#70), 2) AS round((sun_sales1 / sun_sales2), 2)#77, round((mon_sales1#44 / mon_sales2#71), 2) AS round((mon_sales1 / mon_sales2), 2)#78, round((tue_sales1#45 / tue_sales2#72), 2) AS round((tue_sales1 / tue_sales2), 2)#79, round((wed_sales1#46 / wed_sales2#73), 2) AS round((wed_sales1 / wed_sales2), 2)#80, round((thu_sales1#47 / thu_sales2#74), 2) AS round((thu_sales1 / thu_sales2), 2)#81, round((fri_sales1#48 / fri_sales2#75), 2) AS round((fri_sales1 / fri_sales2), 2)#82, round((sat_sales1#49 / sat_sales2#76), 2) AS round((sat_sales1 / sat_sales2), 2)#83] +Input [16]: [d_week_seq1#42, sun_sales1#43, mon_sales1#44, tue_sales1#45, wed_sales1#46, thu_sales1#47, fri_sales1#48, sat_sales1#49, d_week_seq2#69, sun_sales2#70, mon_sales2#71, tue_sales2#72, wed_sales2#73, thu_sales2#74, fri_sales2#75, sat_sales2#76] + +(35) Exchange +Input [8]: [d_week_seq1#42, round((sun_sales1 / sun_sales2), 2)#77, round((mon_sales1 / mon_sales2), 2)#78, round((tue_sales1 / tue_sales2), 2)#79, round((wed_sales1 / wed_sales2), 2)#80, round((thu_sales1 / thu_sales2), 2)#81, round((fri_sales1 / fri_sales2), 2)#82, round((sat_sales1 / sat_sales2), 2)#83] +Arguments: rangepartitioning(d_week_seq1#42 ASC NULLS FIRST, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(36) Sort [codegen id : 9] +Input [8]: [d_week_seq1#42, round((sun_sales1 / sun_sales2), 2)#77, round((mon_sales1 / mon_sales2), 2)#78, round((tue_sales1 / tue_sales2), 2)#79, round((wed_sales1 / wed_sales2), 2)#80, round((thu_sales1 / thu_sales2), 2)#81, round((fri_sales1 / fri_sales2), 2)#82, round((sat_sales1 / sat_sales2), 2)#83] +Arguments: [d_week_seq1#42 ASC NULLS FIRST], true, 0 + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q2/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q2/simplified.txt new file mode 100644 index 0000000000..8856ce80d2 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q2/simplified.txt @@ -0,0 +1,54 @@ +WholeStageCodegen (9) + Sort [d_week_seq1] + InputAdapter + Exchange [d_week_seq1] #1 + WholeStageCodegen (8) + Project [d_week_seq1,sun_sales1,sun_sales2,mon_sales1,mon_sales2,tue_sales1,tue_sales2,wed_sales1,wed_sales2,thu_sales1,thu_sales2,fri_sales1,fri_sales2,sat_sales1,sat_sales2] + BroadcastHashJoin [d_week_seq1,d_week_seq2] + Project [d_week_seq,sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales] + BroadcastHashJoin [d_week_seq,d_week_seq] + HashAggregate [d_week_seq,sum,sum,sum,sum,sum,sum,sum] [sum(UnscaledValue(CASE WHEN (d_day_name = Sunday ) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Monday ) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Tuesday ) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Wednesday) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Thursday ) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Friday ) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Saturday ) THEN sales_price END)),sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales,sum,sum,sum,sum,sum,sum,sum] + InputAdapter + Exchange [d_week_seq] #2 + WholeStageCodegen (2) + HashAggregate [d_week_seq,d_day_name,sales_price] [sum,sum,sum,sum,sum,sum,sum,sum,sum,sum,sum,sum,sum,sum] + Project [sales_price,d_week_seq,d_day_name] + BroadcastHashJoin [sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometUnion + CometProject [ws_sold_date_sk,ws_ext_sales_price] [sold_date_sk,sales_price] + CometScan parquet spark_catalog.default.web_sales [ws_ext_sales_price,ws_sold_date_sk] + CometProject [cs_sold_date_sk,cs_ext_sales_price] [sold_date_sk,sales_price] + CometScan parquet spark_catalog.default.catalog_sales [cs_ext_sales_price,cs_sold_date_sk] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_date_sk,d_week_seq] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_week_seq,d_day_name] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometProject [d_week_seq] + CometFilter [d_year,d_week_seq] + CometScan parquet spark_catalog.default.date_dim [d_week_seq,d_year] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (7) + Project [d_week_seq,sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales] + BroadcastHashJoin [d_week_seq,d_week_seq] + HashAggregate [d_week_seq,sum,sum,sum,sum,sum,sum,sum] [sum(UnscaledValue(CASE WHEN (d_day_name = Sunday ) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Monday ) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Tuesday ) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Wednesday) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Thursday ) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Friday ) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Saturday ) THEN sales_price END)),sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales,sum,sum,sum,sum,sum,sum,sum] + InputAdapter + ReusedExchange [d_week_seq,sum,sum,sum,sum,sum,sum,sum] #2 + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (6) + ColumnarToRow + InputAdapter + CometProject [d_week_seq] + CometFilter [d_year,d_week_seq] + CometScan parquet spark_catalog.default.date_dim [d_week_seq,d_year] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q20/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q20/explain.txt new file mode 100644 index 0000000000..333ef218c6 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q20/explain.txt @@ -0,0 +1,150 @@ +== Physical Plan == +TakeOrderedAndProject (20) ++- * Project (19) + +- Window (18) + +- * Sort (17) + +- Exchange (16) + +- * HashAggregate (15) + +- Exchange (14) + +- * HashAggregate (13) + +- * Project (12) + +- * BroadcastHashJoin Inner BuildRight (11) + :- * Project (9) + : +- * BroadcastHashJoin Inner BuildRight (8) + : :- * ColumnarToRow (3) + : : +- CometFilter (2) + : : +- CometScan parquet spark_catalog.default.catalog_sales (1) + : +- BroadcastExchange (7) + : +- * ColumnarToRow (6) + : +- CometFilter (5) + : +- CometScan parquet spark_catalog.default.item (4) + +- ReusedExchange (10) + + +(1) Scan parquet spark_catalog.default.catalog_sales +Output [3]: [cs_item_sk#1, cs_ext_sales_price#2, cs_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#3), dynamicpruningexpression(cs_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(cs_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [cs_item_sk#1, cs_ext_sales_price#2, cs_sold_date_sk#3] +Condition : isnotnull(cs_item_sk#1) + +(3) ColumnarToRow [codegen id : 3] +Input [3]: [cs_item_sk#1, cs_ext_sales_price#2, cs_sold_date_sk#3] + +(4) Scan parquet spark_catalog.default.item +Output [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [In(i_category, [Books ,Home ,Sports ]), IsNotNull(i_item_sk)] +ReadSchema: struct + +(5) CometFilter +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Condition : (i_category#10 IN (Sports ,Books ,Home ) AND isnotnull(i_item_sk#5)) + +(6) ColumnarToRow [codegen id : 1] +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] + +(7) BroadcastExchange +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cs_item_sk#1] +Right keys [1]: [i_item_sk#5] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 3] +Output [7]: [cs_ext_sales_price#2, cs_sold_date_sk#3, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Input [9]: [cs_item_sk#1, cs_ext_sales_price#2, cs_sold_date_sk#3, i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] + +(10) ReusedExchange [Reuses operator id: 25] +Output [1]: [d_date_sk#11] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cs_sold_date_sk#3] +Right keys [1]: [d_date_sk#11] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [6]: [cs_ext_sales_price#2, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Input [8]: [cs_ext_sales_price#2, cs_sold_date_sk#3, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10, d_date_sk#11] + +(13) HashAggregate [codegen id : 3] +Input [6]: [cs_ext_sales_price#2, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Keys [5]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8] +Functions [1]: [partial_sum(UnscaledValue(cs_ext_sales_price#2))] +Aggregate Attributes [1]: [sum#12] +Results [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] + +(14) Exchange +Input [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] +Arguments: hashpartitioning(i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 4] +Input [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] +Keys [5]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8] +Functions [1]: [sum(UnscaledValue(cs_ext_sales_price#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(cs_ext_sales_price#2))#14] +Results [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, MakeDecimal(sum(UnscaledValue(cs_ext_sales_price#2))#14,17,2) AS itemrevenue#15, MakeDecimal(sum(UnscaledValue(cs_ext_sales_price#2))#14,17,2) AS _w0#16, i_item_id#6] + +(16) Exchange +Input [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16, i_item_id#6] +Arguments: hashpartitioning(i_class#9, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(17) Sort [codegen id : 5] +Input [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16, i_item_id#6] +Arguments: [i_class#9 ASC NULLS FIRST], false, 0 + +(18) Window +Input [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16, i_item_id#6] +Arguments: [sum(_w0#16) windowspecdefinition(i_class#9, specifiedwindowframe(RowFrame, unboundedpreceding$(), unboundedfollowing$())) AS _we0#17], [i_class#9] + +(19) Project [codegen id : 6] +Output [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, ((_w0#16 * 100) / _we0#17) AS revenueratio#18, i_item_id#6] +Input [8]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16, i_item_id#6, _we0#17] + +(20) TakeOrderedAndProject +Input [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, revenueratio#18, i_item_id#6] +Arguments: 100, [i_category#10 ASC NULLS FIRST, i_class#9 ASC NULLS FIRST, i_item_id#6 ASC NULLS FIRST, i_item_desc#7 ASC NULLS FIRST, revenueratio#18 ASC NULLS FIRST], [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, revenueratio#18] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (25) ++- * ColumnarToRow (24) + +- CometProject (23) + +- CometFilter (22) + +- CometScan parquet spark_catalog.default.date_dim (21) + + +(21) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#11, d_date#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,1999-02-22), LessThanOrEqual(d_date,1999-03-24), IsNotNull(d_date_sk)] +ReadSchema: struct + +(22) CometFilter +Input [2]: [d_date_sk#11, d_date#19] +Condition : (((isnotnull(d_date#19) AND (d_date#19 >= 1999-02-22)) AND (d_date#19 <= 1999-03-24)) AND isnotnull(d_date_sk#11)) + +(23) CometProject +Input [2]: [d_date_sk#11, d_date#19] +Arguments: [d_date_sk#11], [d_date_sk#11] + +(24) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#11] + +(25) BroadcastExchange +Input [1]: [d_date_sk#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q20/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q20/simplified.txt new file mode 100644 index 0000000000..52c42bdf2b --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q20/simplified.txt @@ -0,0 +1,40 @@ +TakeOrderedAndProject [i_category,i_class,i_item_id,i_item_desc,revenueratio,i_current_price,itemrevenue] + WholeStageCodegen (6) + Project [i_item_desc,i_category,i_class,i_current_price,itemrevenue,_w0,_we0,i_item_id] + InputAdapter + Window [_w0,i_class] + WholeStageCodegen (5) + Sort [i_class] + InputAdapter + Exchange [i_class] #1 + WholeStageCodegen (4) + HashAggregate [i_item_id,i_item_desc,i_category,i_class,i_current_price,sum] [sum(UnscaledValue(cs_ext_sales_price)),itemrevenue,_w0,sum] + InputAdapter + Exchange [i_item_id,i_item_desc,i_category,i_class,i_current_price] #2 + WholeStageCodegen (3) + HashAggregate [i_item_id,i_item_desc,i_category,i_class,i_current_price,cs_ext_sales_price] [sum,sum] + Project [cs_ext_sales_price,i_item_id,i_item_desc,i_current_price,i_class,i_category] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_ext_sales_price,cs_sold_date_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] + BroadcastHashJoin [cs_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_ext_sales_price,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [i_category,i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] + InputAdapter + ReusedExchange [d_date_sk] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q21/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q21/explain.txt new file mode 100644 index 0000000000..77f17c7f36 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q21/explain.txt @@ -0,0 +1,169 @@ +== Physical Plan == +TakeOrderedAndProject (24) ++- * Filter (23) + +- * HashAggregate (22) + +- Exchange (21) + +- * HashAggregate (20) + +- * Project (19) + +- * BroadcastHashJoin Inner BuildRight (18) + :- * Project (16) + : +- * BroadcastHashJoin Inner BuildRight (15) + : :- * Project (9) + : : +- * BroadcastHashJoin Inner BuildRight (8) + : : :- * ColumnarToRow (3) + : : : +- CometFilter (2) + : : : +- CometScan parquet spark_catalog.default.inventory (1) + : : +- BroadcastExchange (7) + : : +- * ColumnarToRow (6) + : : +- CometFilter (5) + : : +- CometScan parquet spark_catalog.default.warehouse (4) + : +- BroadcastExchange (14) + : +- * ColumnarToRow (13) + : +- CometProject (12) + : +- CometFilter (11) + : +- CometScan parquet spark_catalog.default.item (10) + +- ReusedExchange (17) + + +(1) Scan parquet spark_catalog.default.inventory +Output [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(inv_date_sk#4), dynamicpruningexpression(inv_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(inv_warehouse_sk), IsNotNull(inv_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] +Condition : (isnotnull(inv_warehouse_sk#2) AND isnotnull(inv_item_sk#1)) + +(3) ColumnarToRow [codegen id : 4] +Input [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] + +(4) Scan parquet spark_catalog.default.warehouse +Output [2]: [w_warehouse_sk#6, w_warehouse_name#7] +Batched: true +Location [not included in comparison]/{warehouse_dir}/warehouse] +PushedFilters: [IsNotNull(w_warehouse_sk)] +ReadSchema: struct + +(5) CometFilter +Input [2]: [w_warehouse_sk#6, w_warehouse_name#7] +Condition : isnotnull(w_warehouse_sk#6) + +(6) ColumnarToRow [codegen id : 1] +Input [2]: [w_warehouse_sk#6, w_warehouse_name#7] + +(7) BroadcastExchange +Input [2]: [w_warehouse_sk#6, w_warehouse_name#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [inv_warehouse_sk#2] +Right keys [1]: [w_warehouse_sk#6] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 4] +Output [4]: [inv_item_sk#1, inv_quantity_on_hand#3, inv_date_sk#4, w_warehouse_name#7] +Input [6]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4, w_warehouse_sk#6, w_warehouse_name#7] + +(10) Scan parquet spark_catalog.default.item +Output [3]: [i_item_sk#8, i_item_id#9, i_current_price#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_current_price), GreaterThanOrEqual(i_current_price,0.99), LessThanOrEqual(i_current_price,1.49), IsNotNull(i_item_sk)] +ReadSchema: struct + +(11) CometFilter +Input [3]: [i_item_sk#8, i_item_id#9, i_current_price#10] +Condition : (((isnotnull(i_current_price#10) AND (i_current_price#10 >= 0.99)) AND (i_current_price#10 <= 1.49)) AND isnotnull(i_item_sk#8)) + +(12) CometProject +Input [3]: [i_item_sk#8, i_item_id#9, i_current_price#10] +Arguments: [i_item_sk#8, i_item_id#9], [i_item_sk#8, i_item_id#9] + +(13) ColumnarToRow [codegen id : 2] +Input [2]: [i_item_sk#8, i_item_id#9] + +(14) BroadcastExchange +Input [2]: [i_item_sk#8, i_item_id#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(15) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [inv_item_sk#1] +Right keys [1]: [i_item_sk#8] +Join type: Inner +Join condition: None + +(16) Project [codegen id : 4] +Output [4]: [inv_quantity_on_hand#3, inv_date_sk#4, w_warehouse_name#7, i_item_id#9] +Input [6]: [inv_item_sk#1, inv_quantity_on_hand#3, inv_date_sk#4, w_warehouse_name#7, i_item_sk#8, i_item_id#9] + +(17) ReusedExchange [Reuses operator id: 28] +Output [2]: [d_date_sk#11, d_date#12] + +(18) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [inv_date_sk#4] +Right keys [1]: [d_date_sk#11] +Join type: Inner +Join condition: None + +(19) Project [codegen id : 4] +Output [4]: [inv_quantity_on_hand#3, w_warehouse_name#7, i_item_id#9, d_date#12] +Input [6]: [inv_quantity_on_hand#3, inv_date_sk#4, w_warehouse_name#7, i_item_id#9, d_date_sk#11, d_date#12] + +(20) HashAggregate [codegen id : 4] +Input [4]: [inv_quantity_on_hand#3, w_warehouse_name#7, i_item_id#9, d_date#12] +Keys [2]: [w_warehouse_name#7, i_item_id#9] +Functions [2]: [partial_sum(CASE WHEN (d_date#12 < 2000-03-11) THEN inv_quantity_on_hand#3 ELSE 0 END), partial_sum(CASE WHEN (d_date#12 >= 2000-03-11) THEN inv_quantity_on_hand#3 ELSE 0 END)] +Aggregate Attributes [2]: [sum#13, sum#14] +Results [4]: [w_warehouse_name#7, i_item_id#9, sum#15, sum#16] + +(21) Exchange +Input [4]: [w_warehouse_name#7, i_item_id#9, sum#15, sum#16] +Arguments: hashpartitioning(w_warehouse_name#7, i_item_id#9, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(22) HashAggregate [codegen id : 5] +Input [4]: [w_warehouse_name#7, i_item_id#9, sum#15, sum#16] +Keys [2]: [w_warehouse_name#7, i_item_id#9] +Functions [2]: [sum(CASE WHEN (d_date#12 < 2000-03-11) THEN inv_quantity_on_hand#3 ELSE 0 END), sum(CASE WHEN (d_date#12 >= 2000-03-11) THEN inv_quantity_on_hand#3 ELSE 0 END)] +Aggregate Attributes [2]: [sum(CASE WHEN (d_date#12 < 2000-03-11) THEN inv_quantity_on_hand#3 ELSE 0 END)#17, sum(CASE WHEN (d_date#12 >= 2000-03-11) THEN inv_quantity_on_hand#3 ELSE 0 END)#18] +Results [4]: [w_warehouse_name#7, i_item_id#9, sum(CASE WHEN (d_date#12 < 2000-03-11) THEN inv_quantity_on_hand#3 ELSE 0 END)#17 AS inv_before#19, sum(CASE WHEN (d_date#12 >= 2000-03-11) THEN inv_quantity_on_hand#3 ELSE 0 END)#18 AS inv_after#20] + +(23) Filter [codegen id : 5] +Input [4]: [w_warehouse_name#7, i_item_id#9, inv_before#19, inv_after#20] +Condition : (CASE WHEN (inv_before#19 > 0) THEN ((cast(inv_after#20 as double) / cast(inv_before#19 as double)) >= 0.666667) END AND CASE WHEN (inv_before#19 > 0) THEN ((cast(inv_after#20 as double) / cast(inv_before#19 as double)) <= 1.5) END) + +(24) TakeOrderedAndProject +Input [4]: [w_warehouse_name#7, i_item_id#9, inv_before#19, inv_after#20] +Arguments: 100, [w_warehouse_name#7 ASC NULLS FIRST, i_item_id#9 ASC NULLS FIRST], [w_warehouse_name#7, i_item_id#9, inv_before#19, inv_after#20] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = inv_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (28) ++- * ColumnarToRow (27) + +- CometFilter (26) + +- CometScan parquet spark_catalog.default.date_dim (25) + + +(25) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#11, d_date#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,2000-02-10), LessThanOrEqual(d_date,2000-04-10), IsNotNull(d_date_sk)] +ReadSchema: struct + +(26) CometFilter +Input [2]: [d_date_sk#11, d_date#12] +Condition : (((isnotnull(d_date#12) AND (d_date#12 >= 2000-02-10)) AND (d_date#12 <= 2000-04-10)) AND isnotnull(d_date_sk#11)) + +(27) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#11, d_date#12] + +(28) BroadcastExchange +Input [2]: [d_date_sk#11, d_date#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q21/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q21/simplified.txt new file mode 100644 index 0000000000..e20755e12f --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q21/simplified.txt @@ -0,0 +1,42 @@ +TakeOrderedAndProject [w_warehouse_name,i_item_id,inv_before,inv_after] + WholeStageCodegen (5) + Filter [inv_before,inv_after] + HashAggregate [w_warehouse_name,i_item_id,sum,sum] [sum(CASE WHEN (d_date < 2000-03-11) THEN inv_quantity_on_hand ELSE 0 END),sum(CASE WHEN (d_date >= 2000-03-11) THEN inv_quantity_on_hand ELSE 0 END),inv_before,inv_after,sum,sum] + InputAdapter + Exchange [w_warehouse_name,i_item_id] #1 + WholeStageCodegen (4) + HashAggregate [w_warehouse_name,i_item_id,d_date,inv_quantity_on_hand] [sum,sum,sum,sum] + Project [inv_quantity_on_hand,w_warehouse_name,i_item_id,d_date] + BroadcastHashJoin [inv_date_sk,d_date_sk] + Project [inv_quantity_on_hand,inv_date_sk,w_warehouse_name,i_item_id] + BroadcastHashJoin [inv_item_sk,i_item_sk] + Project [inv_item_sk,inv_quantity_on_hand,inv_date_sk,w_warehouse_name] + BroadcastHashJoin [inv_warehouse_sk,w_warehouse_sk] + ColumnarToRow + InputAdapter + CometFilter [inv_warehouse_sk,inv_item_sk] + CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_date,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [w_warehouse_sk] + CometScan parquet spark_catalog.default.warehouse [w_warehouse_sk,w_warehouse_name] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometProject [i_item_sk,i_item_id] + CometFilter [i_current_price,i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_current_price] + InputAdapter + ReusedExchange [d_date_sk,d_date] #2 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q22/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q22/explain.txt new file mode 100644 index 0000000000..9f5771fed2 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q22/explain.txt @@ -0,0 +1,169 @@ +== Physical Plan == +TakeOrderedAndProject (23) ++- * HashAggregate (22) + +- Exchange (21) + +- * HashAggregate (20) + +- * Expand (19) + +- * Project (18) + +- * BroadcastHashJoin Inner BuildRight (17) + :- * Project (12) + : +- * BroadcastHashJoin Inner BuildRight (11) + : :- * Project (6) + : : +- * BroadcastHashJoin Inner BuildRight (5) + : : :- * ColumnarToRow (3) + : : : +- CometFilter (2) + : : : +- CometScan parquet spark_catalog.default.inventory (1) + : : +- ReusedExchange (4) + : +- BroadcastExchange (10) + : +- * ColumnarToRow (9) + : +- CometFilter (8) + : +- CometScan parquet spark_catalog.default.item (7) + +- BroadcastExchange (16) + +- * ColumnarToRow (15) + +- CometFilter (14) + +- CometScan parquet spark_catalog.default.warehouse (13) + + +(1) Scan parquet spark_catalog.default.inventory +Output [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(inv_date_sk#4), dynamicpruningexpression(inv_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(inv_item_sk), IsNotNull(inv_warehouse_sk)] +ReadSchema: struct + +(2) CometFilter +Input [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] +Condition : (isnotnull(inv_item_sk#1) AND isnotnull(inv_warehouse_sk#2)) + +(3) ColumnarToRow [codegen id : 4] +Input [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] + +(4) ReusedExchange [Reuses operator id: 28] +Output [1]: [d_date_sk#6] + +(5) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [inv_date_sk#4] +Right keys [1]: [d_date_sk#6] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 4] +Output [3]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3] +Input [5]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4, d_date_sk#6] + +(7) Scan parquet spark_catalog.default.item +Output [5]: [i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(8) CometFilter +Input [5]: [i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11] +Condition : isnotnull(i_item_sk#7) + +(9) ColumnarToRow [codegen id : 2] +Input [5]: [i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11] + +(10) BroadcastExchange +Input [5]: [i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(11) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [inv_item_sk#1] +Right keys [1]: [i_item_sk#7] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 4] +Output [6]: [inv_warehouse_sk#2, inv_quantity_on_hand#3, i_brand#8, i_class#9, i_category#10, i_product_name#11] +Input [8]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11] + +(13) Scan parquet spark_catalog.default.warehouse +Output [1]: [w_warehouse_sk#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/warehouse] +PushedFilters: [IsNotNull(w_warehouse_sk)] +ReadSchema: struct + +(14) CometFilter +Input [1]: [w_warehouse_sk#12] +Condition : isnotnull(w_warehouse_sk#12) + +(15) ColumnarToRow [codegen id : 3] +Input [1]: [w_warehouse_sk#12] + +(16) BroadcastExchange +Input [1]: [w_warehouse_sk#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(17) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [inv_warehouse_sk#2] +Right keys [1]: [w_warehouse_sk#12] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 4] +Output [5]: [inv_quantity_on_hand#3, i_product_name#11, i_brand#8, i_class#9, i_category#10] +Input [7]: [inv_warehouse_sk#2, inv_quantity_on_hand#3, i_brand#8, i_class#9, i_category#10, i_product_name#11, w_warehouse_sk#12] + +(19) Expand [codegen id : 4] +Input [5]: [inv_quantity_on_hand#3, i_product_name#11, i_brand#8, i_class#9, i_category#10] +Arguments: [[inv_quantity_on_hand#3, i_product_name#11, i_brand#8, i_class#9, i_category#10, 0], [inv_quantity_on_hand#3, i_product_name#11, i_brand#8, i_class#9, null, 1], [inv_quantity_on_hand#3, i_product_name#11, i_brand#8, null, null, 3], [inv_quantity_on_hand#3, i_product_name#11, null, null, null, 7], [inv_quantity_on_hand#3, null, null, null, null, 15]], [inv_quantity_on_hand#3, i_product_name#13, i_brand#14, i_class#15, i_category#16, spark_grouping_id#17] + +(20) HashAggregate [codegen id : 4] +Input [6]: [inv_quantity_on_hand#3, i_product_name#13, i_brand#14, i_class#15, i_category#16, spark_grouping_id#17] +Keys [5]: [i_product_name#13, i_brand#14, i_class#15, i_category#16, spark_grouping_id#17] +Functions [1]: [partial_avg(inv_quantity_on_hand#3)] +Aggregate Attributes [2]: [sum#18, count#19] +Results [7]: [i_product_name#13, i_brand#14, i_class#15, i_category#16, spark_grouping_id#17, sum#20, count#21] + +(21) Exchange +Input [7]: [i_product_name#13, i_brand#14, i_class#15, i_category#16, spark_grouping_id#17, sum#20, count#21] +Arguments: hashpartitioning(i_product_name#13, i_brand#14, i_class#15, i_category#16, spark_grouping_id#17, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(22) HashAggregate [codegen id : 5] +Input [7]: [i_product_name#13, i_brand#14, i_class#15, i_category#16, spark_grouping_id#17, sum#20, count#21] +Keys [5]: [i_product_name#13, i_brand#14, i_class#15, i_category#16, spark_grouping_id#17] +Functions [1]: [avg(inv_quantity_on_hand#3)] +Aggregate Attributes [1]: [avg(inv_quantity_on_hand#3)#22] +Results [5]: [i_product_name#13, i_brand#14, i_class#15, i_category#16, avg(inv_quantity_on_hand#3)#22 AS qoh#23] + +(23) TakeOrderedAndProject +Input [5]: [i_product_name#13, i_brand#14, i_class#15, i_category#16, qoh#23] +Arguments: 100, [qoh#23 ASC NULLS FIRST, i_product_name#13 ASC NULLS FIRST, i_brand#14 ASC NULLS FIRST, i_class#15 ASC NULLS FIRST, i_category#16 ASC NULLS FIRST], [i_product_name#13, i_brand#14, i_class#15, i_category#16, qoh#23] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = inv_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (28) ++- * ColumnarToRow (27) + +- CometProject (26) + +- CometFilter (25) + +- CometScan parquet spark_catalog.default.date_dim (24) + + +(24) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#6, d_month_seq#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)] +ReadSchema: struct + +(25) CometFilter +Input [2]: [d_date_sk#6, d_month_seq#24] +Condition : (((isnotnull(d_month_seq#24) AND (d_month_seq#24 >= 1200)) AND (d_month_seq#24 <= 1211)) AND isnotnull(d_date_sk#6)) + +(26) CometProject +Input [2]: [d_date_sk#6, d_month_seq#24] +Arguments: [d_date_sk#6], [d_date_sk#6] + +(27) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#6] + +(28) BroadcastExchange +Input [1]: [d_date_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q22/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q22/simplified.txt new file mode 100644 index 0000000000..92714bb02d --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q22/simplified.txt @@ -0,0 +1,42 @@ +TakeOrderedAndProject [qoh,i_product_name,i_brand,i_class,i_category] + WholeStageCodegen (5) + HashAggregate [i_product_name,i_brand,i_class,i_category,spark_grouping_id,sum,count] [avg(inv_quantity_on_hand),qoh,sum,count] + InputAdapter + Exchange [i_product_name,i_brand,i_class,i_category,spark_grouping_id] #1 + WholeStageCodegen (4) + HashAggregate [i_product_name,i_brand,i_class,i_category,spark_grouping_id,inv_quantity_on_hand] [sum,count,sum,count] + Expand [inv_quantity_on_hand,i_product_name,i_brand,i_class,i_category] + Project [inv_quantity_on_hand,i_product_name,i_brand,i_class,i_category] + BroadcastHashJoin [inv_warehouse_sk,w_warehouse_sk] + Project [inv_warehouse_sk,inv_quantity_on_hand,i_brand,i_class,i_category,i_product_name] + BroadcastHashJoin [inv_item_sk,i_item_sk] + Project [inv_item_sk,inv_warehouse_sk,inv_quantity_on_hand] + BroadcastHashJoin [inv_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [inv_item_sk,inv_warehouse_sk] + CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_month_seq,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_class,i_category,i_product_name] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometFilter [w_warehouse_sk] + CometScan parquet spark_catalog.default.warehouse [w_warehouse_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23a/explain.txt new file mode 100644 index 0000000000..328a8d3536 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23a/explain.txt @@ -0,0 +1,570 @@ +== Physical Plan == +* HashAggregate (66) ++- Exchange (65) + +- * HashAggregate (64) + +- Union (63) + :- * Project (45) + : +- * BroadcastHashJoin Inner BuildRight (44) + : :- * Project (42) + : : +- * SortMergeJoin LeftSemi (41) + : : :- * Sort (24) + : : : +- Exchange (23) + : : : +- * Project (22) + : : : +- * BroadcastHashJoin LeftSemi BuildRight (21) + : : : :- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) + : : : +- BroadcastExchange (20) + : : : +- * Project (19) + : : : +- * Filter (18) + : : : +- * HashAggregate (17) + : : : +- Exchange (16) + : : : +- * HashAggregate (15) + : : : +- * Project (14) + : : : +- * BroadcastHashJoin Inner BuildRight (13) + : : : :- * Project (8) + : : : : +- * BroadcastHashJoin Inner BuildRight (7) + : : : : :- * ColumnarToRow (5) + : : : : : +- CometFilter (4) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (3) + : : : : +- ReusedExchange (6) + : : : +- BroadcastExchange (12) + : : : +- * ColumnarToRow (11) + : : : +- CometFilter (10) + : : : +- CometScan parquet spark_catalog.default.item (9) + : : +- * Sort (40) + : : +- * Project (39) + : : +- * Filter (38) + : : +- * HashAggregate (37) + : : +- Exchange (36) + : : +- * HashAggregate (35) + : : +- * Project (34) + : : +- * BroadcastHashJoin Inner BuildRight (33) + : : :- * ColumnarToRow (28) + : : : +- CometProject (27) + : : : +- CometFilter (26) + : : : +- CometScan parquet spark_catalog.default.store_sales (25) + : : +- BroadcastExchange (32) + : : +- * ColumnarToRow (31) + : : +- CometFilter (30) + : : +- CometScan parquet spark_catalog.default.customer (29) + : +- ReusedExchange (43) + +- * Project (62) + +- * BroadcastHashJoin Inner BuildRight (61) + :- * Project (59) + : +- * SortMergeJoin LeftSemi (58) + : :- * Sort (52) + : : +- Exchange (51) + : : +- * Project (50) + : : +- * BroadcastHashJoin LeftSemi BuildRight (49) + : : :- * ColumnarToRow (47) + : : : +- CometScan parquet spark_catalog.default.web_sales (46) + : : +- ReusedExchange (48) + : +- * Sort (57) + : +- * Project (56) + : +- * Filter (55) + : +- * HashAggregate (54) + : +- ReusedExchange (53) + +- ReusedExchange (60) + + +(1) Scan parquet spark_catalog.default.catalog_sales +Output [5]: [cs_bill_customer_sk#1, cs_item_sk#2, cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#5), dynamicpruningexpression(cs_sold_date_sk#5 IN dynamicpruning#6)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 5] +Input [5]: [cs_bill_customer_sk#1, cs_item_sk#2, cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5] + +(3) Scan parquet spark_catalog.default.store_sales +Output [2]: [ss_item_sk#7, ss_sold_date_sk#8] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#8), dynamicpruningexpression(ss_sold_date_sk#8 IN dynamicpruning#9)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(4) CometFilter +Input [2]: [ss_item_sk#7, ss_sold_date_sk#8] +Condition : isnotnull(ss_item_sk#7) + +(5) ColumnarToRow [codegen id : 3] +Input [2]: [ss_item_sk#7, ss_sold_date_sk#8] + +(6) ReusedExchange [Reuses operator id: 76] +Output [2]: [d_date_sk#10, d_date#11] + +(7) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_sold_date_sk#8] +Right keys [1]: [d_date_sk#10] +Join type: Inner +Join condition: None + +(8) Project [codegen id : 3] +Output [2]: [ss_item_sk#7, d_date#11] +Input [4]: [ss_item_sk#7, ss_sold_date_sk#8, d_date_sk#10, d_date#11] + +(9) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#12, i_item_desc#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(10) CometFilter +Input [2]: [i_item_sk#12, i_item_desc#13] +Condition : isnotnull(i_item_sk#12) + +(11) ColumnarToRow [codegen id : 2] +Input [2]: [i_item_sk#12, i_item_desc#13] + +(12) BroadcastExchange +Input [2]: [i_item_sk#12, i_item_desc#13] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(13) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_item_sk#7] +Right keys [1]: [i_item_sk#12] +Join type: Inner +Join condition: None + +(14) Project [codegen id : 3] +Output [3]: [d_date#11, i_item_sk#12, substr(i_item_desc#13, 1, 30) AS _groupingexpression#14] +Input [4]: [ss_item_sk#7, d_date#11, i_item_sk#12, i_item_desc#13] + +(15) HashAggregate [codegen id : 3] +Input [3]: [d_date#11, i_item_sk#12, _groupingexpression#14] +Keys [3]: [_groupingexpression#14, i_item_sk#12, d_date#11] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#15] +Results [4]: [_groupingexpression#14, i_item_sk#12, d_date#11, count#16] + +(16) Exchange +Input [4]: [_groupingexpression#14, i_item_sk#12, d_date#11, count#16] +Arguments: hashpartitioning(_groupingexpression#14, i_item_sk#12, d_date#11, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(17) HashAggregate [codegen id : 4] +Input [4]: [_groupingexpression#14, i_item_sk#12, d_date#11, count#16] +Keys [3]: [_groupingexpression#14, i_item_sk#12, d_date#11] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#17] +Results [2]: [i_item_sk#12 AS item_sk#18, count(1)#17 AS cnt#19] + +(18) Filter [codegen id : 4] +Input [2]: [item_sk#18, cnt#19] +Condition : (cnt#19 > 4) + +(19) Project [codegen id : 4] +Output [1]: [item_sk#18] +Input [2]: [item_sk#18, cnt#19] + +(20) BroadcastExchange +Input [1]: [item_sk#18] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(21) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [cs_item_sk#2] +Right keys [1]: [item_sk#18] +Join type: LeftSemi +Join condition: None + +(22) Project [codegen id : 5] +Output [4]: [cs_bill_customer_sk#1, cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5] +Input [5]: [cs_bill_customer_sk#1, cs_item_sk#2, cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5] + +(23) Exchange +Input [4]: [cs_bill_customer_sk#1, cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5] +Arguments: hashpartitioning(cs_bill_customer_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(24) Sort [codegen id : 6] +Input [4]: [cs_bill_customer_sk#1, cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5] +Arguments: [cs_bill_customer_sk#1 ASC NULLS FIRST], false, 0 + +(25) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22, ss_sold_date_sk#23] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(26) CometFilter +Input [4]: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22, ss_sold_date_sk#23] +Condition : isnotnull(ss_customer_sk#20) + +(27) CometProject +Input [4]: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22, ss_sold_date_sk#23] +Arguments: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22], [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22] + +(28) ColumnarToRow [codegen id : 8] +Input [3]: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22] + +(29) Scan parquet spark_catalog.default.customer +Output [1]: [c_customer_sk#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk)] +ReadSchema: struct + +(30) CometFilter +Input [1]: [c_customer_sk#24] +Condition : isnotnull(c_customer_sk#24) + +(31) ColumnarToRow [codegen id : 7] +Input [1]: [c_customer_sk#24] + +(32) BroadcastExchange +Input [1]: [c_customer_sk#24] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(33) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_customer_sk#20] +Right keys [1]: [c_customer_sk#24] +Join type: Inner +Join condition: None + +(34) Project [codegen id : 8] +Output [3]: [ss_quantity#21, ss_sales_price#22, c_customer_sk#24] +Input [4]: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22, c_customer_sk#24] + +(35) HashAggregate [codegen id : 8] +Input [3]: [ss_quantity#21, ss_sales_price#22, c_customer_sk#24] +Keys [1]: [c_customer_sk#24] +Functions [1]: [partial_sum((cast(ss_quantity#21 as decimal(10,0)) * ss_sales_price#22))] +Aggregate Attributes [2]: [sum#25, isEmpty#26] +Results [3]: [c_customer_sk#24, sum#27, isEmpty#28] + +(36) Exchange +Input [3]: [c_customer_sk#24, sum#27, isEmpty#28] +Arguments: hashpartitioning(c_customer_sk#24, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(37) HashAggregate [codegen id : 9] +Input [3]: [c_customer_sk#24, sum#27, isEmpty#28] +Keys [1]: [c_customer_sk#24] +Functions [1]: [sum((cast(ss_quantity#21 as decimal(10,0)) * ss_sales_price#22))] +Aggregate Attributes [1]: [sum((cast(ss_quantity#21 as decimal(10,0)) * ss_sales_price#22))#29] +Results [2]: [c_customer_sk#24, sum((cast(ss_quantity#21 as decimal(10,0)) * ss_sales_price#22))#29 AS ssales#30] + +(38) Filter [codegen id : 9] +Input [2]: [c_customer_sk#24, ssales#30] +Condition : (isnotnull(ssales#30) AND (cast(ssales#30 as decimal(38,8)) > (0.500000 * Subquery scalar-subquery#31, [id=#32]))) + +(39) Project [codegen id : 9] +Output [1]: [c_customer_sk#24] +Input [2]: [c_customer_sk#24, ssales#30] + +(40) Sort [codegen id : 9] +Input [1]: [c_customer_sk#24] +Arguments: [c_customer_sk#24 ASC NULLS FIRST], false, 0 + +(41) SortMergeJoin [codegen id : 11] +Left keys [1]: [cs_bill_customer_sk#1] +Right keys [1]: [c_customer_sk#24] +Join type: LeftSemi +Join condition: None + +(42) Project [codegen id : 11] +Output [3]: [cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5] +Input [4]: [cs_bill_customer_sk#1, cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5] + +(43) ReusedExchange [Reuses operator id: 71] +Output [1]: [d_date_sk#33] + +(44) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [cs_sold_date_sk#5] +Right keys [1]: [d_date_sk#33] +Join type: Inner +Join condition: None + +(45) Project [codegen id : 11] +Output [1]: [(cast(cs_quantity#3 as decimal(10,0)) * cs_list_price#4) AS sales#34] +Input [4]: [cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5, d_date_sk#33] + +(46) Scan parquet spark_catalog.default.web_sales +Output [5]: [ws_item_sk#35, ws_bill_customer_sk#36, ws_quantity#37, ws_list_price#38, ws_sold_date_sk#39] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#39), dynamicpruningexpression(ws_sold_date_sk#39 IN dynamicpruning#40)] +ReadSchema: struct + +(47) ColumnarToRow [codegen id : 16] +Input [5]: [ws_item_sk#35, ws_bill_customer_sk#36, ws_quantity#37, ws_list_price#38, ws_sold_date_sk#39] + +(48) ReusedExchange [Reuses operator id: 20] +Output [1]: [item_sk#41] + +(49) BroadcastHashJoin [codegen id : 16] +Left keys [1]: [ws_item_sk#35] +Right keys [1]: [item_sk#41] +Join type: LeftSemi +Join condition: None + +(50) Project [codegen id : 16] +Output [4]: [ws_bill_customer_sk#36, ws_quantity#37, ws_list_price#38, ws_sold_date_sk#39] +Input [5]: [ws_item_sk#35, ws_bill_customer_sk#36, ws_quantity#37, ws_list_price#38, ws_sold_date_sk#39] + +(51) Exchange +Input [4]: [ws_bill_customer_sk#36, ws_quantity#37, ws_list_price#38, ws_sold_date_sk#39] +Arguments: hashpartitioning(ws_bill_customer_sk#36, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(52) Sort [codegen id : 17] +Input [4]: [ws_bill_customer_sk#36, ws_quantity#37, ws_list_price#38, ws_sold_date_sk#39] +Arguments: [ws_bill_customer_sk#36 ASC NULLS FIRST], false, 0 + +(53) ReusedExchange [Reuses operator id: 36] +Output [3]: [c_customer_sk#42, sum#43, isEmpty#44] + +(54) HashAggregate [codegen id : 20] +Input [3]: [c_customer_sk#42, sum#43, isEmpty#44] +Keys [1]: [c_customer_sk#42] +Functions [1]: [sum((cast(ss_quantity#45 as decimal(10,0)) * ss_sales_price#46))] +Aggregate Attributes [1]: [sum((cast(ss_quantity#45 as decimal(10,0)) * ss_sales_price#46))#29] +Results [2]: [c_customer_sk#42, sum((cast(ss_quantity#45 as decimal(10,0)) * ss_sales_price#46))#29 AS ssales#47] + +(55) Filter [codegen id : 20] +Input [2]: [c_customer_sk#42, ssales#47] +Condition : (isnotnull(ssales#47) AND (cast(ssales#47 as decimal(38,8)) > (0.500000 * ReusedSubquery Subquery scalar-subquery#31, [id=#32]))) + +(56) Project [codegen id : 20] +Output [1]: [c_customer_sk#42] +Input [2]: [c_customer_sk#42, ssales#47] + +(57) Sort [codegen id : 20] +Input [1]: [c_customer_sk#42] +Arguments: [c_customer_sk#42 ASC NULLS FIRST], false, 0 + +(58) SortMergeJoin [codegen id : 22] +Left keys [1]: [ws_bill_customer_sk#36] +Right keys [1]: [c_customer_sk#42] +Join type: LeftSemi +Join condition: None + +(59) Project [codegen id : 22] +Output [3]: [ws_quantity#37, ws_list_price#38, ws_sold_date_sk#39] +Input [4]: [ws_bill_customer_sk#36, ws_quantity#37, ws_list_price#38, ws_sold_date_sk#39] + +(60) ReusedExchange [Reuses operator id: 71] +Output [1]: [d_date_sk#48] + +(61) BroadcastHashJoin [codegen id : 22] +Left keys [1]: [ws_sold_date_sk#39] +Right keys [1]: [d_date_sk#48] +Join type: Inner +Join condition: None + +(62) Project [codegen id : 22] +Output [1]: [(cast(ws_quantity#37 as decimal(10,0)) * ws_list_price#38) AS sales#49] +Input [4]: [ws_quantity#37, ws_list_price#38, ws_sold_date_sk#39, d_date_sk#48] + +(63) Union + +(64) HashAggregate [codegen id : 23] +Input [1]: [sales#34] +Keys: [] +Functions [1]: [partial_sum(sales#34)] +Aggregate Attributes [2]: [sum#50, isEmpty#51] +Results [2]: [sum#52, isEmpty#53] + +(65) Exchange +Input [2]: [sum#52, isEmpty#53] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=8] + +(66) HashAggregate [codegen id : 24] +Input [2]: [sum#52, isEmpty#53] +Keys: [] +Functions [1]: [sum(sales#34)] +Aggregate Attributes [1]: [sum(sales#34)#54] +Results [1]: [sum(sales#34)#54 AS sum(sales)#55] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#5 IN dynamicpruning#6 +BroadcastExchange (71) ++- * ColumnarToRow (70) + +- CometProject (69) + +- CometFilter (68) + +- CometScan parquet spark_catalog.default.date_dim (67) + + +(67) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#33, d_year#56, d_moy#57] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2000), EqualTo(d_moy,2), IsNotNull(d_date_sk)] +ReadSchema: struct + +(68) CometFilter +Input [3]: [d_date_sk#33, d_year#56, d_moy#57] +Condition : ((((isnotnull(d_year#56) AND isnotnull(d_moy#57)) AND (d_year#56 = 2000)) AND (d_moy#57 = 2)) AND isnotnull(d_date_sk#33)) + +(69) CometProject +Input [3]: [d_date_sk#33, d_year#56, d_moy#57] +Arguments: [d_date_sk#33], [d_date_sk#33] + +(70) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#33] + +(71) BroadcastExchange +Input [1]: [d_date_sk#33] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=9] + +Subquery:2 Hosting operator id = 3 Hosting Expression = ss_sold_date_sk#8 IN dynamicpruning#9 +BroadcastExchange (76) ++- * ColumnarToRow (75) + +- CometProject (74) + +- CometFilter (73) + +- CometScan parquet spark_catalog.default.date_dim (72) + + +(72) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#10, d_date#11, d_year#58] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [In(d_year, [2000,2001,2002,2003]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(73) CometFilter +Input [3]: [d_date_sk#10, d_date#11, d_year#58] +Condition : (d_year#58 IN (2000,2001,2002,2003) AND isnotnull(d_date_sk#10)) + +(74) CometProject +Input [3]: [d_date_sk#10, d_date#11, d_year#58] +Arguments: [d_date_sk#10, d_date#11], [d_date_sk#10, d_date#11] + +(75) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#10, d_date#11] + +(76) BroadcastExchange +Input [2]: [d_date_sk#10, d_date#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=10] + +Subquery:3 Hosting operator id = 38 Hosting Expression = Subquery scalar-subquery#31, [id=#32] +* HashAggregate (91) ++- Exchange (90) + +- * HashAggregate (89) + +- * HashAggregate (88) + +- Exchange (87) + +- * HashAggregate (86) + +- * Project (85) + +- * BroadcastHashJoin Inner BuildRight (84) + :- * Project (82) + : +- * BroadcastHashJoin Inner BuildRight (81) + : :- * ColumnarToRow (79) + : : +- CometFilter (78) + : : +- CometScan parquet spark_catalog.default.store_sales (77) + : +- ReusedExchange (80) + +- ReusedExchange (83) + + +(77) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_customer_sk#59, ss_quantity#60, ss_sales_price#61, ss_sold_date_sk#62] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#62), dynamicpruningexpression(ss_sold_date_sk#62 IN dynamicpruning#63)] +PushedFilters: [IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(78) CometFilter +Input [4]: [ss_customer_sk#59, ss_quantity#60, ss_sales_price#61, ss_sold_date_sk#62] +Condition : isnotnull(ss_customer_sk#59) + +(79) ColumnarToRow [codegen id : 3] +Input [4]: [ss_customer_sk#59, ss_quantity#60, ss_sales_price#61, ss_sold_date_sk#62] + +(80) ReusedExchange [Reuses operator id: 32] +Output [1]: [c_customer_sk#64] + +(81) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_customer_sk#59] +Right keys [1]: [c_customer_sk#64] +Join type: Inner +Join condition: None + +(82) Project [codegen id : 3] +Output [4]: [ss_quantity#60, ss_sales_price#61, ss_sold_date_sk#62, c_customer_sk#64] +Input [5]: [ss_customer_sk#59, ss_quantity#60, ss_sales_price#61, ss_sold_date_sk#62, c_customer_sk#64] + +(83) ReusedExchange [Reuses operator id: 96] +Output [1]: [d_date_sk#65] + +(84) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_sold_date_sk#62] +Right keys [1]: [d_date_sk#65] +Join type: Inner +Join condition: None + +(85) Project [codegen id : 3] +Output [3]: [ss_quantity#60, ss_sales_price#61, c_customer_sk#64] +Input [5]: [ss_quantity#60, ss_sales_price#61, ss_sold_date_sk#62, c_customer_sk#64, d_date_sk#65] + +(86) HashAggregate [codegen id : 3] +Input [3]: [ss_quantity#60, ss_sales_price#61, c_customer_sk#64] +Keys [1]: [c_customer_sk#64] +Functions [1]: [partial_sum((cast(ss_quantity#60 as decimal(10,0)) * ss_sales_price#61))] +Aggregate Attributes [2]: [sum#66, isEmpty#67] +Results [3]: [c_customer_sk#64, sum#68, isEmpty#69] + +(87) Exchange +Input [3]: [c_customer_sk#64, sum#68, isEmpty#69] +Arguments: hashpartitioning(c_customer_sk#64, 5), ENSURE_REQUIREMENTS, [plan_id=11] + +(88) HashAggregate [codegen id : 4] +Input [3]: [c_customer_sk#64, sum#68, isEmpty#69] +Keys [1]: [c_customer_sk#64] +Functions [1]: [sum((cast(ss_quantity#60 as decimal(10,0)) * ss_sales_price#61))] +Aggregate Attributes [1]: [sum((cast(ss_quantity#60 as decimal(10,0)) * ss_sales_price#61))#70] +Results [1]: [sum((cast(ss_quantity#60 as decimal(10,0)) * ss_sales_price#61))#70 AS csales#71] + +(89) HashAggregate [codegen id : 4] +Input [1]: [csales#71] +Keys: [] +Functions [1]: [partial_max(csales#71)] +Aggregate Attributes [1]: [max#72] +Results [1]: [max#73] + +(90) Exchange +Input [1]: [max#73] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=12] + +(91) HashAggregate [codegen id : 5] +Input [1]: [max#73] +Keys: [] +Functions [1]: [max(csales#71)] +Aggregate Attributes [1]: [max(csales#71)#74] +Results [1]: [max(csales#71)#74 AS tpcds_cmax#75] + +Subquery:4 Hosting operator id = 77 Hosting Expression = ss_sold_date_sk#62 IN dynamicpruning#63 +BroadcastExchange (96) ++- * ColumnarToRow (95) + +- CometProject (94) + +- CometFilter (93) + +- CometScan parquet spark_catalog.default.date_dim (92) + + +(92) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#65, d_year#76] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [In(d_year, [2000,2001,2002,2003]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(93) CometFilter +Input [2]: [d_date_sk#65, d_year#76] +Condition : (d_year#76 IN (2000,2001,2002,2003) AND isnotnull(d_date_sk#65)) + +(94) CometProject +Input [2]: [d_date_sk#65, d_year#76] +Arguments: [d_date_sk#65], [d_date_sk#65] + +(95) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#65] + +(96) BroadcastExchange +Input [1]: [d_date_sk#65] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=13] + +Subquery:5 Hosting operator id = 46 Hosting Expression = ws_sold_date_sk#39 IN dynamicpruning#6 + +Subquery:6 Hosting operator id = 55 Hosting Expression = ReusedSubquery Subquery scalar-subquery#31, [id=#32] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23a/simplified.txt new file mode 100644 index 0000000000..0ec56d0e72 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23a/simplified.txt @@ -0,0 +1,155 @@ +WholeStageCodegen (24) + HashAggregate [sum,isEmpty] [sum(sales),sum(sales),sum,isEmpty] + InputAdapter + Exchange #1 + WholeStageCodegen (23) + HashAggregate [sales] [sum,isEmpty,sum,isEmpty] + InputAdapter + Union + WholeStageCodegen (11) + Project [cs_quantity,cs_list_price] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_quantity,cs_list_price,cs_sold_date_sk] + SortMergeJoin [cs_bill_customer_sk,c_customer_sk] + InputAdapter + WholeStageCodegen (6) + Sort [cs_bill_customer_sk] + InputAdapter + Exchange [cs_bill_customer_sk] #2 + WholeStageCodegen (5) + Project [cs_bill_customer_sk,cs_quantity,cs_list_price,cs_sold_date_sk] + BroadcastHashJoin [cs_item_sk,item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_moy,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (4) + Project [item_sk] + Filter [cnt] + HashAggregate [_groupingexpression,i_item_sk,d_date,count] [count(1),item_sk,cnt,count] + InputAdapter + Exchange [_groupingexpression,i_item_sk,d_date] #5 + WholeStageCodegen (3) + HashAggregate [_groupingexpression,i_item_sk,d_date] [count,count] + Project [d_date,i_item_sk,i_item_desc] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,d_date] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #6 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_date] + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date,d_year] + InputAdapter + ReusedExchange [d_date_sk,d_date] #6 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_desc] + InputAdapter + WholeStageCodegen (9) + Sort [c_customer_sk] + Project [c_customer_sk] + Filter [ssales] + Subquery #3 + WholeStageCodegen (5) + HashAggregate [max] [max(csales),tpcds_cmax,max] + InputAdapter + Exchange #10 + WholeStageCodegen (4) + HashAggregate [csales] [max,max] + HashAggregate [c_customer_sk,sum,isEmpty] [sum((cast(ss_quantity as decimal(10,0)) * ss_sales_price)),csales,sum,isEmpty] + InputAdapter + Exchange [c_customer_sk] #11 + WholeStageCodegen (3) + HashAggregate [c_customer_sk,ss_quantity,ss_sales_price] [sum,isEmpty,sum,isEmpty] + Project [ss_quantity,ss_sales_price,c_customer_sk] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_quantity,ss_sales_price,ss_sold_date_sk,c_customer_sk] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk] + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_quantity,ss_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #4 + BroadcastExchange #12 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [c_customer_sk] #9 + InputAdapter + ReusedExchange [d_date_sk] #12 + HashAggregate [c_customer_sk,sum,isEmpty] [sum((cast(ss_quantity as decimal(10,0)) * ss_sales_price)),ssales,sum,isEmpty] + InputAdapter + Exchange [c_customer_sk] #8 + WholeStageCodegen (8) + HashAggregate [c_customer_sk,ss_quantity,ss_sales_price] [sum,isEmpty,sum,isEmpty] + Project [ss_quantity,ss_sales_price,c_customer_sk] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + ColumnarToRow + InputAdapter + CometProject [ss_customer_sk,ss_quantity,ss_sales_price] + CometFilter [ss_customer_sk] + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_quantity,ss_sales_price,ss_sold_date_sk] + InputAdapter + BroadcastExchange #9 + WholeStageCodegen (7) + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk] + CometScan parquet spark_catalog.default.customer [c_customer_sk] + InputAdapter + ReusedExchange [d_date_sk] #3 + WholeStageCodegen (22) + Project [ws_quantity,ws_list_price] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_quantity,ws_list_price,ws_sold_date_sk] + SortMergeJoin [ws_bill_customer_sk,c_customer_sk] + InputAdapter + WholeStageCodegen (17) + Sort [ws_bill_customer_sk] + InputAdapter + Exchange [ws_bill_customer_sk] #13 + WholeStageCodegen (16) + Project [ws_bill_customer_sk,ws_quantity,ws_list_price,ws_sold_date_sk] + BroadcastHashJoin [ws_item_sk,item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_bill_customer_sk,ws_quantity,ws_list_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [item_sk] #4 + InputAdapter + WholeStageCodegen (20) + Sort [c_customer_sk] + Project [c_customer_sk] + Filter [ssales] + ReusedSubquery [tpcds_cmax] #3 + HashAggregate [c_customer_sk,sum,isEmpty] [sum((cast(ss_quantity as decimal(10,0)) * ss_sales_price)),ssales,sum,isEmpty] + InputAdapter + ReusedExchange [c_customer_sk,sum,isEmpty] #8 + InputAdapter + ReusedExchange [d_date_sk] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23b/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23b/explain.txt new file mode 100644 index 0000000000..840f9734aa --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23b/explain.txt @@ -0,0 +1,694 @@ +== Physical Plan == +TakeOrderedAndProject (87) ++- Union (86) + :- * HashAggregate (62) + : +- Exchange (61) + : +- * HashAggregate (60) + : +- * Project (59) + : +- * BroadcastHashJoin Inner BuildRight (58) + : :- * Project (56) + : : +- * BroadcastHashJoin Inner BuildRight (55) + : : :- * SortMergeJoin LeftSemi (42) + : : : :- * Sort (25) + : : : : +- Exchange (24) + : : : : +- * Project (23) + : : : : +- * BroadcastHashJoin LeftSemi BuildRight (22) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) + : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) + : : : : +- BroadcastExchange (21) + : : : : +- * Project (20) + : : : : +- * Filter (19) + : : : : +- * HashAggregate (18) + : : : : +- Exchange (17) + : : : : +- * HashAggregate (16) + : : : : +- * Project (15) + : : : : +- * BroadcastHashJoin Inner BuildRight (14) + : : : : :- * Project (9) + : : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : : :- * ColumnarToRow (6) + : : : : : : +- CometFilter (5) + : : : : : : +- CometScan parquet spark_catalog.default.store_sales (4) + : : : : : +- ReusedExchange (7) + : : : : +- BroadcastExchange (13) + : : : : +- * ColumnarToRow (12) + : : : : +- CometFilter (11) + : : : : +- CometScan parquet spark_catalog.default.item (10) + : : : +- * Sort (41) + : : : +- * Project (40) + : : : +- * Filter (39) + : : : +- * HashAggregate (38) + : : : +- Exchange (37) + : : : +- * HashAggregate (36) + : : : +- * Project (35) + : : : +- * BroadcastHashJoin Inner BuildRight (34) + : : : :- * ColumnarToRow (29) + : : : : +- CometProject (28) + : : : : +- CometFilter (27) + : : : : +- CometScan parquet spark_catalog.default.store_sales (26) + : : : +- BroadcastExchange (33) + : : : +- * ColumnarToRow (32) + : : : +- CometFilter (31) + : : : +- CometScan parquet spark_catalog.default.customer (30) + : : +- BroadcastExchange (54) + : : +- * SortMergeJoin LeftSemi (53) + : : :- * Sort (47) + : : : +- Exchange (46) + : : : +- * ColumnarToRow (45) + : : : +- CometFilter (44) + : : : +- CometScan parquet spark_catalog.default.customer (43) + : : +- * Sort (52) + : : +- * Project (51) + : : +- * Filter (50) + : : +- * HashAggregate (49) + : : +- ReusedExchange (48) + : +- ReusedExchange (57) + +- * HashAggregate (85) + +- Exchange (84) + +- * HashAggregate (83) + +- * Project (82) + +- * BroadcastHashJoin Inner BuildRight (81) + :- * Project (79) + : +- * BroadcastHashJoin Inner BuildRight (78) + : :- * SortMergeJoin LeftSemi (76) + : : :- * Sort (70) + : : : +- Exchange (69) + : : : +- * Project (68) + : : : +- * BroadcastHashJoin LeftSemi BuildRight (67) + : : : :- * ColumnarToRow (65) + : : : : +- CometFilter (64) + : : : : +- CometScan parquet spark_catalog.default.web_sales (63) + : : : +- ReusedExchange (66) + : : +- * Sort (75) + : : +- * Project (74) + : : +- * Filter (73) + : : +- * HashAggregate (72) + : : +- ReusedExchange (71) + : +- ReusedExchange (77) + +- ReusedExchange (80) + + +(1) Scan parquet spark_catalog.default.catalog_sales +Output [5]: [cs_bill_customer_sk#1, cs_item_sk#2, cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#5), dynamicpruningexpression(cs_sold_date_sk#5 IN dynamicpruning#6)] +PushedFilters: [IsNotNull(cs_bill_customer_sk)] +ReadSchema: struct + +(2) CometFilter +Input [5]: [cs_bill_customer_sk#1, cs_item_sk#2, cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5] +Condition : isnotnull(cs_bill_customer_sk#1) + +(3) ColumnarToRow [codegen id : 5] +Input [5]: [cs_bill_customer_sk#1, cs_item_sk#2, cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5] + +(4) Scan parquet spark_catalog.default.store_sales +Output [2]: [ss_item_sk#7, ss_sold_date_sk#8] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#8), dynamicpruningexpression(ss_sold_date_sk#8 IN dynamicpruning#9)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(5) CometFilter +Input [2]: [ss_item_sk#7, ss_sold_date_sk#8] +Condition : isnotnull(ss_item_sk#7) + +(6) ColumnarToRow [codegen id : 3] +Input [2]: [ss_item_sk#7, ss_sold_date_sk#8] + +(7) ReusedExchange [Reuses operator id: 97] +Output [2]: [d_date_sk#10, d_date#11] + +(8) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_sold_date_sk#8] +Right keys [1]: [d_date_sk#10] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 3] +Output [2]: [ss_item_sk#7, d_date#11] +Input [4]: [ss_item_sk#7, ss_sold_date_sk#8, d_date_sk#10, d_date#11] + +(10) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#12, i_item_desc#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(11) CometFilter +Input [2]: [i_item_sk#12, i_item_desc#13] +Condition : isnotnull(i_item_sk#12) + +(12) ColumnarToRow [codegen id : 2] +Input [2]: [i_item_sk#12, i_item_desc#13] + +(13) BroadcastExchange +Input [2]: [i_item_sk#12, i_item_desc#13] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(14) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_item_sk#7] +Right keys [1]: [i_item_sk#12] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 3] +Output [3]: [d_date#11, i_item_sk#12, substr(i_item_desc#13, 1, 30) AS _groupingexpression#14] +Input [4]: [ss_item_sk#7, d_date#11, i_item_sk#12, i_item_desc#13] + +(16) HashAggregate [codegen id : 3] +Input [3]: [d_date#11, i_item_sk#12, _groupingexpression#14] +Keys [3]: [_groupingexpression#14, i_item_sk#12, d_date#11] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#15] +Results [4]: [_groupingexpression#14, i_item_sk#12, d_date#11, count#16] + +(17) Exchange +Input [4]: [_groupingexpression#14, i_item_sk#12, d_date#11, count#16] +Arguments: hashpartitioning(_groupingexpression#14, i_item_sk#12, d_date#11, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(18) HashAggregate [codegen id : 4] +Input [4]: [_groupingexpression#14, i_item_sk#12, d_date#11, count#16] +Keys [3]: [_groupingexpression#14, i_item_sk#12, d_date#11] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#17] +Results [2]: [i_item_sk#12 AS item_sk#18, count(1)#17 AS cnt#19] + +(19) Filter [codegen id : 4] +Input [2]: [item_sk#18, cnt#19] +Condition : (cnt#19 > 4) + +(20) Project [codegen id : 4] +Output [1]: [item_sk#18] +Input [2]: [item_sk#18, cnt#19] + +(21) BroadcastExchange +Input [1]: [item_sk#18] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(22) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [cs_item_sk#2] +Right keys [1]: [item_sk#18] +Join type: LeftSemi +Join condition: None + +(23) Project [codegen id : 5] +Output [4]: [cs_bill_customer_sk#1, cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5] +Input [5]: [cs_bill_customer_sk#1, cs_item_sk#2, cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5] + +(24) Exchange +Input [4]: [cs_bill_customer_sk#1, cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5] +Arguments: hashpartitioning(cs_bill_customer_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(25) Sort [codegen id : 6] +Input [4]: [cs_bill_customer_sk#1, cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5] +Arguments: [cs_bill_customer_sk#1 ASC NULLS FIRST], false, 0 + +(26) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22, ss_sold_date_sk#23] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(27) CometFilter +Input [4]: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22, ss_sold_date_sk#23] +Condition : isnotnull(ss_customer_sk#20) + +(28) CometProject +Input [4]: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22, ss_sold_date_sk#23] +Arguments: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22], [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22] + +(29) ColumnarToRow [codegen id : 8] +Input [3]: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22] + +(30) Scan parquet spark_catalog.default.customer +Output [1]: [c_customer_sk#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk)] +ReadSchema: struct + +(31) CometFilter +Input [1]: [c_customer_sk#24] +Condition : isnotnull(c_customer_sk#24) + +(32) ColumnarToRow [codegen id : 7] +Input [1]: [c_customer_sk#24] + +(33) BroadcastExchange +Input [1]: [c_customer_sk#24] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(34) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_customer_sk#20] +Right keys [1]: [c_customer_sk#24] +Join type: Inner +Join condition: None + +(35) Project [codegen id : 8] +Output [3]: [ss_quantity#21, ss_sales_price#22, c_customer_sk#24] +Input [4]: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22, c_customer_sk#24] + +(36) HashAggregate [codegen id : 8] +Input [3]: [ss_quantity#21, ss_sales_price#22, c_customer_sk#24] +Keys [1]: [c_customer_sk#24] +Functions [1]: [partial_sum((cast(ss_quantity#21 as decimal(10,0)) * ss_sales_price#22))] +Aggregate Attributes [2]: [sum#25, isEmpty#26] +Results [3]: [c_customer_sk#24, sum#27, isEmpty#28] + +(37) Exchange +Input [3]: [c_customer_sk#24, sum#27, isEmpty#28] +Arguments: hashpartitioning(c_customer_sk#24, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(38) HashAggregate [codegen id : 9] +Input [3]: [c_customer_sk#24, sum#27, isEmpty#28] +Keys [1]: [c_customer_sk#24] +Functions [1]: [sum((cast(ss_quantity#21 as decimal(10,0)) * ss_sales_price#22))] +Aggregate Attributes [1]: [sum((cast(ss_quantity#21 as decimal(10,0)) * ss_sales_price#22))#29] +Results [2]: [c_customer_sk#24, sum((cast(ss_quantity#21 as decimal(10,0)) * ss_sales_price#22))#29 AS ssales#30] + +(39) Filter [codegen id : 9] +Input [2]: [c_customer_sk#24, ssales#30] +Condition : (isnotnull(ssales#30) AND (cast(ssales#30 as decimal(38,8)) > (0.500000 * Subquery scalar-subquery#31, [id=#32]))) + +(40) Project [codegen id : 9] +Output [1]: [c_customer_sk#24] +Input [2]: [c_customer_sk#24, ssales#30] + +(41) Sort [codegen id : 9] +Input [1]: [c_customer_sk#24] +Arguments: [c_customer_sk#24 ASC NULLS FIRST], false, 0 + +(42) SortMergeJoin [codegen id : 17] +Left keys [1]: [cs_bill_customer_sk#1] +Right keys [1]: [c_customer_sk#24] +Join type: LeftSemi +Join condition: None + +(43) Scan parquet spark_catalog.default.customer +Output [3]: [c_customer_sk#33, c_first_name#34, c_last_name#35] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk)] +ReadSchema: struct + +(44) CometFilter +Input [3]: [c_customer_sk#33, c_first_name#34, c_last_name#35] +Condition : isnotnull(c_customer_sk#33) + +(45) ColumnarToRow [codegen id : 10] +Input [3]: [c_customer_sk#33, c_first_name#34, c_last_name#35] + +(46) Exchange +Input [3]: [c_customer_sk#33, c_first_name#34, c_last_name#35] +Arguments: hashpartitioning(c_customer_sk#33, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(47) Sort [codegen id : 11] +Input [3]: [c_customer_sk#33, c_first_name#34, c_last_name#35] +Arguments: [c_customer_sk#33 ASC NULLS FIRST], false, 0 + +(48) ReusedExchange [Reuses operator id: 37] +Output [3]: [c_customer_sk#24, sum#27, isEmpty#28] + +(49) HashAggregate [codegen id : 14] +Input [3]: [c_customer_sk#24, sum#27, isEmpty#28] +Keys [1]: [c_customer_sk#24] +Functions [1]: [sum((cast(ss_quantity#21 as decimal(10,0)) * ss_sales_price#22))] +Aggregate Attributes [1]: [sum((cast(ss_quantity#21 as decimal(10,0)) * ss_sales_price#22))#29] +Results [2]: [c_customer_sk#24, sum((cast(ss_quantity#21 as decimal(10,0)) * ss_sales_price#22))#29 AS ssales#30] + +(50) Filter [codegen id : 14] +Input [2]: [c_customer_sk#24, ssales#30] +Condition : (isnotnull(ssales#30) AND (cast(ssales#30 as decimal(38,8)) > (0.500000 * ReusedSubquery Subquery scalar-subquery#31, [id=#32]))) + +(51) Project [codegen id : 14] +Output [1]: [c_customer_sk#24] +Input [2]: [c_customer_sk#24, ssales#30] + +(52) Sort [codegen id : 14] +Input [1]: [c_customer_sk#24] +Arguments: [c_customer_sk#24 ASC NULLS FIRST], false, 0 + +(53) SortMergeJoin [codegen id : 15] +Left keys [1]: [c_customer_sk#33] +Right keys [1]: [c_customer_sk#24] +Join type: LeftSemi +Join condition: None + +(54) BroadcastExchange +Input [3]: [c_customer_sk#33, c_first_name#34, c_last_name#35] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8] + +(55) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [cs_bill_customer_sk#1] +Right keys [1]: [c_customer_sk#33] +Join type: Inner +Join condition: None + +(56) Project [codegen id : 17] +Output [5]: [cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5, c_first_name#34, c_last_name#35] +Input [7]: [cs_bill_customer_sk#1, cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5, c_customer_sk#33, c_first_name#34, c_last_name#35] + +(57) ReusedExchange [Reuses operator id: 92] +Output [1]: [d_date_sk#36] + +(58) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [cs_sold_date_sk#5] +Right keys [1]: [d_date_sk#36] +Join type: Inner +Join condition: None + +(59) Project [codegen id : 17] +Output [4]: [cs_quantity#3, cs_list_price#4, c_first_name#34, c_last_name#35] +Input [6]: [cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5, c_first_name#34, c_last_name#35, d_date_sk#36] + +(60) HashAggregate [codegen id : 17] +Input [4]: [cs_quantity#3, cs_list_price#4, c_first_name#34, c_last_name#35] +Keys [2]: [c_last_name#35, c_first_name#34] +Functions [1]: [partial_sum((cast(cs_quantity#3 as decimal(10,0)) * cs_list_price#4))] +Aggregate Attributes [2]: [sum#37, isEmpty#38] +Results [4]: [c_last_name#35, c_first_name#34, sum#39, isEmpty#40] + +(61) Exchange +Input [4]: [c_last_name#35, c_first_name#34, sum#39, isEmpty#40] +Arguments: hashpartitioning(c_last_name#35, c_first_name#34, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(62) HashAggregate [codegen id : 18] +Input [4]: [c_last_name#35, c_first_name#34, sum#39, isEmpty#40] +Keys [2]: [c_last_name#35, c_first_name#34] +Functions [1]: [sum((cast(cs_quantity#3 as decimal(10,0)) * cs_list_price#4))] +Aggregate Attributes [1]: [sum((cast(cs_quantity#3 as decimal(10,0)) * cs_list_price#4))#41] +Results [3]: [c_last_name#35, c_first_name#34, sum((cast(cs_quantity#3 as decimal(10,0)) * cs_list_price#4))#41 AS sales#42] + +(63) Scan parquet spark_catalog.default.web_sales +Output [5]: [ws_item_sk#43, ws_bill_customer_sk#44, ws_quantity#45, ws_list_price#46, ws_sold_date_sk#47] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#47), dynamicpruningexpression(ws_sold_date_sk#47 IN dynamicpruning#48)] +PushedFilters: [IsNotNull(ws_bill_customer_sk)] +ReadSchema: struct + +(64) CometFilter +Input [5]: [ws_item_sk#43, ws_bill_customer_sk#44, ws_quantity#45, ws_list_price#46, ws_sold_date_sk#47] +Condition : isnotnull(ws_bill_customer_sk#44) + +(65) ColumnarToRow [codegen id : 23] +Input [5]: [ws_item_sk#43, ws_bill_customer_sk#44, ws_quantity#45, ws_list_price#46, ws_sold_date_sk#47] + +(66) ReusedExchange [Reuses operator id: 21] +Output [1]: [item_sk#49] + +(67) BroadcastHashJoin [codegen id : 23] +Left keys [1]: [ws_item_sk#43] +Right keys [1]: [item_sk#49] +Join type: LeftSemi +Join condition: None + +(68) Project [codegen id : 23] +Output [4]: [ws_bill_customer_sk#44, ws_quantity#45, ws_list_price#46, ws_sold_date_sk#47] +Input [5]: [ws_item_sk#43, ws_bill_customer_sk#44, ws_quantity#45, ws_list_price#46, ws_sold_date_sk#47] + +(69) Exchange +Input [4]: [ws_bill_customer_sk#44, ws_quantity#45, ws_list_price#46, ws_sold_date_sk#47] +Arguments: hashpartitioning(ws_bill_customer_sk#44, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(70) Sort [codegen id : 24] +Input [4]: [ws_bill_customer_sk#44, ws_quantity#45, ws_list_price#46, ws_sold_date_sk#47] +Arguments: [ws_bill_customer_sk#44 ASC NULLS FIRST], false, 0 + +(71) ReusedExchange [Reuses operator id: 37] +Output [3]: [c_customer_sk#50, sum#51, isEmpty#52] + +(72) HashAggregate [codegen id : 27] +Input [3]: [c_customer_sk#50, sum#51, isEmpty#52] +Keys [1]: [c_customer_sk#50] +Functions [1]: [sum((cast(ss_quantity#53 as decimal(10,0)) * ss_sales_price#54))] +Aggregate Attributes [1]: [sum((cast(ss_quantity#53 as decimal(10,0)) * ss_sales_price#54))#29] +Results [2]: [c_customer_sk#50, sum((cast(ss_quantity#53 as decimal(10,0)) * ss_sales_price#54))#29 AS ssales#55] + +(73) Filter [codegen id : 27] +Input [2]: [c_customer_sk#50, ssales#55] +Condition : (isnotnull(ssales#55) AND (cast(ssales#55 as decimal(38,8)) > (0.500000 * ReusedSubquery Subquery scalar-subquery#31, [id=#32]))) + +(74) Project [codegen id : 27] +Output [1]: [c_customer_sk#50] +Input [2]: [c_customer_sk#50, ssales#55] + +(75) Sort [codegen id : 27] +Input [1]: [c_customer_sk#50] +Arguments: [c_customer_sk#50 ASC NULLS FIRST], false, 0 + +(76) SortMergeJoin [codegen id : 35] +Left keys [1]: [ws_bill_customer_sk#44] +Right keys [1]: [c_customer_sk#50] +Join type: LeftSemi +Join condition: None + +(77) ReusedExchange [Reuses operator id: 54] +Output [3]: [c_customer_sk#56, c_first_name#57, c_last_name#58] + +(78) BroadcastHashJoin [codegen id : 35] +Left keys [1]: [ws_bill_customer_sk#44] +Right keys [1]: [c_customer_sk#56] +Join type: Inner +Join condition: None + +(79) Project [codegen id : 35] +Output [5]: [ws_quantity#45, ws_list_price#46, ws_sold_date_sk#47, c_first_name#57, c_last_name#58] +Input [7]: [ws_bill_customer_sk#44, ws_quantity#45, ws_list_price#46, ws_sold_date_sk#47, c_customer_sk#56, c_first_name#57, c_last_name#58] + +(80) ReusedExchange [Reuses operator id: 92] +Output [1]: [d_date_sk#59] + +(81) BroadcastHashJoin [codegen id : 35] +Left keys [1]: [ws_sold_date_sk#47] +Right keys [1]: [d_date_sk#59] +Join type: Inner +Join condition: None + +(82) Project [codegen id : 35] +Output [4]: [ws_quantity#45, ws_list_price#46, c_first_name#57, c_last_name#58] +Input [6]: [ws_quantity#45, ws_list_price#46, ws_sold_date_sk#47, c_first_name#57, c_last_name#58, d_date_sk#59] + +(83) HashAggregate [codegen id : 35] +Input [4]: [ws_quantity#45, ws_list_price#46, c_first_name#57, c_last_name#58] +Keys [2]: [c_last_name#58, c_first_name#57] +Functions [1]: [partial_sum((cast(ws_quantity#45 as decimal(10,0)) * ws_list_price#46))] +Aggregate Attributes [2]: [sum#60, isEmpty#61] +Results [4]: [c_last_name#58, c_first_name#57, sum#62, isEmpty#63] + +(84) Exchange +Input [4]: [c_last_name#58, c_first_name#57, sum#62, isEmpty#63] +Arguments: hashpartitioning(c_last_name#58, c_first_name#57, 5), ENSURE_REQUIREMENTS, [plan_id=11] + +(85) HashAggregate [codegen id : 36] +Input [4]: [c_last_name#58, c_first_name#57, sum#62, isEmpty#63] +Keys [2]: [c_last_name#58, c_first_name#57] +Functions [1]: [sum((cast(ws_quantity#45 as decimal(10,0)) * ws_list_price#46))] +Aggregate Attributes [1]: [sum((cast(ws_quantity#45 as decimal(10,0)) * ws_list_price#46))#64] +Results [3]: [c_last_name#58, c_first_name#57, sum((cast(ws_quantity#45 as decimal(10,0)) * ws_list_price#46))#64 AS sales#65] + +(86) Union + +(87) TakeOrderedAndProject +Input [3]: [c_last_name#35, c_first_name#34, sales#42] +Arguments: 100, [c_last_name#35 ASC NULLS FIRST, c_first_name#34 ASC NULLS FIRST, sales#42 ASC NULLS FIRST], [c_last_name#35, c_first_name#34, sales#42] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#5 IN dynamicpruning#6 +BroadcastExchange (92) ++- * ColumnarToRow (91) + +- CometProject (90) + +- CometFilter (89) + +- CometScan parquet spark_catalog.default.date_dim (88) + + +(88) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#36, d_year#66, d_moy#67] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2000), EqualTo(d_moy,2), IsNotNull(d_date_sk)] +ReadSchema: struct + +(89) CometFilter +Input [3]: [d_date_sk#36, d_year#66, d_moy#67] +Condition : ((((isnotnull(d_year#66) AND isnotnull(d_moy#67)) AND (d_year#66 = 2000)) AND (d_moy#67 = 2)) AND isnotnull(d_date_sk#36)) + +(90) CometProject +Input [3]: [d_date_sk#36, d_year#66, d_moy#67] +Arguments: [d_date_sk#36], [d_date_sk#36] + +(91) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#36] + +(92) BroadcastExchange +Input [1]: [d_date_sk#36] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=12] + +Subquery:2 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#8 IN dynamicpruning#9 +BroadcastExchange (97) ++- * ColumnarToRow (96) + +- CometProject (95) + +- CometFilter (94) + +- CometScan parquet spark_catalog.default.date_dim (93) + + +(93) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#10, d_date#11, d_year#68] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [In(d_year, [2000,2001,2002,2003]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(94) CometFilter +Input [3]: [d_date_sk#10, d_date#11, d_year#68] +Condition : (d_year#68 IN (2000,2001,2002,2003) AND isnotnull(d_date_sk#10)) + +(95) CometProject +Input [3]: [d_date_sk#10, d_date#11, d_year#68] +Arguments: [d_date_sk#10, d_date#11], [d_date_sk#10, d_date#11] + +(96) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#10, d_date#11] + +(97) BroadcastExchange +Input [2]: [d_date_sk#10, d_date#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=13] + +Subquery:3 Hosting operator id = 39 Hosting Expression = Subquery scalar-subquery#31, [id=#32] +* HashAggregate (112) ++- Exchange (111) + +- * HashAggregate (110) + +- * HashAggregate (109) + +- Exchange (108) + +- * HashAggregate (107) + +- * Project (106) + +- * BroadcastHashJoin Inner BuildRight (105) + :- * Project (103) + : +- * BroadcastHashJoin Inner BuildRight (102) + : :- * ColumnarToRow (100) + : : +- CometFilter (99) + : : +- CometScan parquet spark_catalog.default.store_sales (98) + : +- ReusedExchange (101) + +- ReusedExchange (104) + + +(98) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_customer_sk#69, ss_quantity#70, ss_sales_price#71, ss_sold_date_sk#72] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#72), dynamicpruningexpression(ss_sold_date_sk#72 IN dynamicpruning#73)] +PushedFilters: [IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(99) CometFilter +Input [4]: [ss_customer_sk#69, ss_quantity#70, ss_sales_price#71, ss_sold_date_sk#72] +Condition : isnotnull(ss_customer_sk#69) + +(100) ColumnarToRow [codegen id : 3] +Input [4]: [ss_customer_sk#69, ss_quantity#70, ss_sales_price#71, ss_sold_date_sk#72] + +(101) ReusedExchange [Reuses operator id: 33] +Output [1]: [c_customer_sk#74] + +(102) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_customer_sk#69] +Right keys [1]: [c_customer_sk#74] +Join type: Inner +Join condition: None + +(103) Project [codegen id : 3] +Output [4]: [ss_quantity#70, ss_sales_price#71, ss_sold_date_sk#72, c_customer_sk#74] +Input [5]: [ss_customer_sk#69, ss_quantity#70, ss_sales_price#71, ss_sold_date_sk#72, c_customer_sk#74] + +(104) ReusedExchange [Reuses operator id: 117] +Output [1]: [d_date_sk#75] + +(105) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_sold_date_sk#72] +Right keys [1]: [d_date_sk#75] +Join type: Inner +Join condition: None + +(106) Project [codegen id : 3] +Output [3]: [ss_quantity#70, ss_sales_price#71, c_customer_sk#74] +Input [5]: [ss_quantity#70, ss_sales_price#71, ss_sold_date_sk#72, c_customer_sk#74, d_date_sk#75] + +(107) HashAggregate [codegen id : 3] +Input [3]: [ss_quantity#70, ss_sales_price#71, c_customer_sk#74] +Keys [1]: [c_customer_sk#74] +Functions [1]: [partial_sum((cast(ss_quantity#70 as decimal(10,0)) * ss_sales_price#71))] +Aggregate Attributes [2]: [sum#76, isEmpty#77] +Results [3]: [c_customer_sk#74, sum#78, isEmpty#79] + +(108) Exchange +Input [3]: [c_customer_sk#74, sum#78, isEmpty#79] +Arguments: hashpartitioning(c_customer_sk#74, 5), ENSURE_REQUIREMENTS, [plan_id=14] + +(109) HashAggregate [codegen id : 4] +Input [3]: [c_customer_sk#74, sum#78, isEmpty#79] +Keys [1]: [c_customer_sk#74] +Functions [1]: [sum((cast(ss_quantity#70 as decimal(10,0)) * ss_sales_price#71))] +Aggregate Attributes [1]: [sum((cast(ss_quantity#70 as decimal(10,0)) * ss_sales_price#71))#80] +Results [1]: [sum((cast(ss_quantity#70 as decimal(10,0)) * ss_sales_price#71))#80 AS csales#81] + +(110) HashAggregate [codegen id : 4] +Input [1]: [csales#81] +Keys: [] +Functions [1]: [partial_max(csales#81)] +Aggregate Attributes [1]: [max#82] +Results [1]: [max#83] + +(111) Exchange +Input [1]: [max#83] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=15] + +(112) HashAggregate [codegen id : 5] +Input [1]: [max#83] +Keys: [] +Functions [1]: [max(csales#81)] +Aggregate Attributes [1]: [max(csales#81)#84] +Results [1]: [max(csales#81)#84 AS tpcds_cmax#85] + +Subquery:4 Hosting operator id = 98 Hosting Expression = ss_sold_date_sk#72 IN dynamicpruning#73 +BroadcastExchange (117) ++- * ColumnarToRow (116) + +- CometProject (115) + +- CometFilter (114) + +- CometScan parquet spark_catalog.default.date_dim (113) + + +(113) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#75, d_year#86] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [In(d_year, [2000,2001,2002,2003]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(114) CometFilter +Input [2]: [d_date_sk#75, d_year#86] +Condition : (d_year#86 IN (2000,2001,2002,2003) AND isnotnull(d_date_sk#75)) + +(115) CometProject +Input [2]: [d_date_sk#75, d_year#86] +Arguments: [d_date_sk#75], [d_date_sk#75] + +(116) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#75] + +(117) BroadcastExchange +Input [1]: [d_date_sk#75] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=16] + +Subquery:5 Hosting operator id = 50 Hosting Expression = ReusedSubquery Subquery scalar-subquery#31, [id=#32] + +Subquery:6 Hosting operator id = 63 Hosting Expression = ws_sold_date_sk#47 IN dynamicpruning#6 + +Subquery:7 Hosting operator id = 73 Hosting Expression = ReusedSubquery Subquery scalar-subquery#31, [id=#32] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23b/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23b/simplified.txt new file mode 100644 index 0000000000..49ddeaef82 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23b/simplified.txt @@ -0,0 +1,188 @@ +TakeOrderedAndProject [c_last_name,c_first_name,sales] + Union + WholeStageCodegen (18) + HashAggregate [c_last_name,c_first_name,sum,isEmpty] [sum((cast(cs_quantity as decimal(10,0)) * cs_list_price)),sales,sum,isEmpty] + InputAdapter + Exchange [c_last_name,c_first_name] #1 + WholeStageCodegen (17) + HashAggregate [c_last_name,c_first_name,cs_quantity,cs_list_price] [sum,isEmpty,sum,isEmpty] + Project [cs_quantity,cs_list_price,c_first_name,c_last_name] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_quantity,cs_list_price,cs_sold_date_sk,c_first_name,c_last_name] + BroadcastHashJoin [cs_bill_customer_sk,c_customer_sk] + SortMergeJoin [cs_bill_customer_sk,c_customer_sk] + InputAdapter + WholeStageCodegen (6) + Sort [cs_bill_customer_sk] + InputAdapter + Exchange [cs_bill_customer_sk] #2 + WholeStageCodegen (5) + Project [cs_bill_customer_sk,cs_quantity,cs_list_price,cs_sold_date_sk] + BroadcastHashJoin [cs_item_sk,item_sk] + ColumnarToRow + InputAdapter + CometFilter [cs_bill_customer_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_moy,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (4) + Project [item_sk] + Filter [cnt] + HashAggregate [_groupingexpression,i_item_sk,d_date,count] [count(1),item_sk,cnt,count] + InputAdapter + Exchange [_groupingexpression,i_item_sk,d_date] #5 + WholeStageCodegen (3) + HashAggregate [_groupingexpression,i_item_sk,d_date] [count,count] + Project [d_date,i_item_sk,i_item_desc] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,d_date] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #6 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_date] + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date,d_year] + InputAdapter + ReusedExchange [d_date_sk,d_date] #6 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_desc] + InputAdapter + WholeStageCodegen (9) + Sort [c_customer_sk] + Project [c_customer_sk] + Filter [ssales] + Subquery #3 + WholeStageCodegen (5) + HashAggregate [max] [max(csales),tpcds_cmax,max] + InputAdapter + Exchange #10 + WholeStageCodegen (4) + HashAggregate [csales] [max,max] + HashAggregate [c_customer_sk,sum,isEmpty] [sum((cast(ss_quantity as decimal(10,0)) * ss_sales_price)),csales,sum,isEmpty] + InputAdapter + Exchange [c_customer_sk] #11 + WholeStageCodegen (3) + HashAggregate [c_customer_sk,ss_quantity,ss_sales_price] [sum,isEmpty,sum,isEmpty] + Project [ss_quantity,ss_sales_price,c_customer_sk] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_quantity,ss_sales_price,ss_sold_date_sk,c_customer_sk] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk] + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_quantity,ss_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #4 + BroadcastExchange #12 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [c_customer_sk] #9 + InputAdapter + ReusedExchange [d_date_sk] #12 + HashAggregate [c_customer_sk,sum,isEmpty] [sum((cast(ss_quantity as decimal(10,0)) * ss_sales_price)),ssales,sum,isEmpty] + InputAdapter + Exchange [c_customer_sk] #8 + WholeStageCodegen (8) + HashAggregate [c_customer_sk,ss_quantity,ss_sales_price] [sum,isEmpty,sum,isEmpty] + Project [ss_quantity,ss_sales_price,c_customer_sk] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + ColumnarToRow + InputAdapter + CometProject [ss_customer_sk,ss_quantity,ss_sales_price] + CometFilter [ss_customer_sk] + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_quantity,ss_sales_price,ss_sold_date_sk] + InputAdapter + BroadcastExchange #9 + WholeStageCodegen (7) + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk] + CometScan parquet spark_catalog.default.customer [c_customer_sk] + InputAdapter + BroadcastExchange #13 + WholeStageCodegen (15) + SortMergeJoin [c_customer_sk,c_customer_sk] + InputAdapter + WholeStageCodegen (11) + Sort [c_customer_sk] + InputAdapter + Exchange [c_customer_sk] #14 + WholeStageCodegen (10) + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_first_name,c_last_name] + InputAdapter + WholeStageCodegen (14) + Sort [c_customer_sk] + Project [c_customer_sk] + Filter [ssales] + ReusedSubquery [tpcds_cmax] #3 + HashAggregate [c_customer_sk,sum,isEmpty] [sum((cast(ss_quantity as decimal(10,0)) * ss_sales_price)),ssales,sum,isEmpty] + InputAdapter + ReusedExchange [c_customer_sk,sum,isEmpty] #8 + InputAdapter + ReusedExchange [d_date_sk] #3 + WholeStageCodegen (36) + HashAggregate [c_last_name,c_first_name,sum,isEmpty] [sum((cast(ws_quantity as decimal(10,0)) * ws_list_price)),sales,sum,isEmpty] + InputAdapter + Exchange [c_last_name,c_first_name] #15 + WholeStageCodegen (35) + HashAggregate [c_last_name,c_first_name,ws_quantity,ws_list_price] [sum,isEmpty,sum,isEmpty] + Project [ws_quantity,ws_list_price,c_first_name,c_last_name] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_quantity,ws_list_price,ws_sold_date_sk,c_first_name,c_last_name] + BroadcastHashJoin [ws_bill_customer_sk,c_customer_sk] + SortMergeJoin [ws_bill_customer_sk,c_customer_sk] + InputAdapter + WholeStageCodegen (24) + Sort [ws_bill_customer_sk] + InputAdapter + Exchange [ws_bill_customer_sk] #16 + WholeStageCodegen (23) + Project [ws_bill_customer_sk,ws_quantity,ws_list_price,ws_sold_date_sk] + BroadcastHashJoin [ws_item_sk,item_sk] + ColumnarToRow + InputAdapter + CometFilter [ws_bill_customer_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_bill_customer_sk,ws_quantity,ws_list_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [item_sk] #4 + InputAdapter + WholeStageCodegen (27) + Sort [c_customer_sk] + Project [c_customer_sk] + Filter [ssales] + ReusedSubquery [tpcds_cmax] #3 + HashAggregate [c_customer_sk,sum,isEmpty] [sum((cast(ss_quantity as decimal(10,0)) * ss_sales_price)),ssales,sum,isEmpty] + InputAdapter + ReusedExchange [c_customer_sk,sum,isEmpty] #8 + InputAdapter + ReusedExchange [c_customer_sk,c_first_name,c_last_name] #13 + InputAdapter + ReusedExchange [d_date_sk] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24a/explain.txt new file mode 100644 index 0000000000..7241b5ea0a --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24a/explain.txt @@ -0,0 +1,427 @@ +== Physical Plan == +* Filter (46) ++- * HashAggregate (45) + +- Exchange (44) + +- * HashAggregate (43) + +- * HashAggregate (42) + +- Exchange (41) + +- * HashAggregate (40) + +- * Project (39) + +- * BroadcastHashJoin Inner BuildRight (38) + :- * Project (33) + : +- * BroadcastHashJoin Inner BuildRight (32) + : :- * Project (27) + : : +- * BroadcastHashJoin Inner BuildRight (26) + : : :- * Project (21) + : : : +- * BroadcastHashJoin Inner BuildRight (20) + : : : :- * Project (14) + : : : : +- * SortMergeJoin Inner (13) + : : : : :- * Sort (6) + : : : : : +- Exchange (5) + : : : : : +- * ColumnarToRow (4) + : : : : : +- CometProject (3) + : : : : : +- CometFilter (2) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : +- * Sort (12) + : : : : +- Exchange (11) + : : : : +- * ColumnarToRow (10) + : : : : +- CometProject (9) + : : : : +- CometFilter (8) + : : : : +- CometScan parquet spark_catalog.default.store_returns (7) + : : : +- BroadcastExchange (19) + : : : +- * ColumnarToRow (18) + : : : +- CometProject (17) + : : : +- CometFilter (16) + : : : +- CometScan parquet spark_catalog.default.store (15) + : : +- BroadcastExchange (25) + : : +- * ColumnarToRow (24) + : : +- CometFilter (23) + : : +- CometScan parquet spark_catalog.default.item (22) + : +- BroadcastExchange (31) + : +- * ColumnarToRow (30) + : +- CometFilter (29) + : +- CometScan parquet spark_catalog.default.customer (28) + +- BroadcastExchange (37) + +- * ColumnarToRow (36) + +- CometFilter (35) + +- CometScan parquet spark_catalog.default.customer_address (34) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, ss_sold_date_sk#6] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_ticket_number), IsNotNull(ss_item_sk), IsNotNull(ss_store_sk), IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(2) CometFilter +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, ss_sold_date_sk#6] +Condition : (((isnotnull(ss_ticket_number#4) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_store_sk#3)) AND isnotnull(ss_customer_sk#2)) + +(3) CometProject +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, ss_sold_date_sk#6] +Arguments: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5], [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5] + +(4) ColumnarToRow [codegen id : 1] +Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5] + +(5) Exchange +Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5] +Arguments: hashpartitioning(ss_ticket_number#4, ss_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(6) Sort [codegen id : 2] +Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5] +Arguments: [ss_ticket_number#4 ASC NULLS FIRST, ss_item_sk#1 ASC NULLS FIRST], false, 0 + +(7) Scan parquet spark_catalog.default.store_returns +Output [3]: [sr_item_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_returns] +PushedFilters: [IsNotNull(sr_ticket_number), IsNotNull(sr_item_sk)] +ReadSchema: struct + +(8) CometFilter +Input [3]: [sr_item_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] +Condition : (isnotnull(sr_ticket_number#8) AND isnotnull(sr_item_sk#7)) + +(9) CometProject +Input [3]: [sr_item_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] +Arguments: [sr_item_sk#7, sr_ticket_number#8], [sr_item_sk#7, sr_ticket_number#8] + +(10) ColumnarToRow [codegen id : 3] +Input [2]: [sr_item_sk#7, sr_ticket_number#8] + +(11) Exchange +Input [2]: [sr_item_sk#7, sr_ticket_number#8] +Arguments: hashpartitioning(sr_ticket_number#8, sr_item_sk#7, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(12) Sort [codegen id : 4] +Input [2]: [sr_item_sk#7, sr_ticket_number#8] +Arguments: [sr_ticket_number#8 ASC NULLS FIRST, sr_item_sk#7 ASC NULLS FIRST], false, 0 + +(13) SortMergeJoin [codegen id : 9] +Left keys [2]: [ss_ticket_number#4, ss_item_sk#1] +Right keys [2]: [sr_ticket_number#8, sr_item_sk#7] +Join type: Inner +Join condition: None + +(14) Project [codegen id : 9] +Output [4]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_net_paid#5] +Input [7]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, sr_item_sk#7, sr_ticket_number#8] + +(15) Scan parquet spark_catalog.default.store +Output [5]: [s_store_sk#10, s_store_name#11, s_market_id#12, s_state#13, s_zip#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_market_id), EqualTo(s_market_id,8), IsNotNull(s_store_sk), IsNotNull(s_zip)] +ReadSchema: struct + +(16) CometFilter +Input [5]: [s_store_sk#10, s_store_name#11, s_market_id#12, s_state#13, s_zip#14] +Condition : (((isnotnull(s_market_id#12) AND (s_market_id#12 = 8)) AND isnotnull(s_store_sk#10)) AND isnotnull(s_zip#14)) + +(17) CometProject +Input [5]: [s_store_sk#10, s_store_name#11, s_market_id#12, s_state#13, s_zip#14] +Arguments: [s_store_sk#10, s_store_name#11, s_state#13, s_zip#14], [s_store_sk#10, s_store_name#11, s_state#13, s_zip#14] + +(18) ColumnarToRow [codegen id : 5] +Input [4]: [s_store_sk#10, s_store_name#11, s_state#13, s_zip#14] + +(19) BroadcastExchange +Input [4]: [s_store_sk#10, s_store_name#11, s_state#13, s_zip#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(20) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_store_sk#3] +Right keys [1]: [s_store_sk#10] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 9] +Output [6]: [ss_item_sk#1, ss_customer_sk#2, ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14] +Input [8]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_net_paid#5, s_store_sk#10, s_store_name#11, s_state#13, s_zip#14] + +(22) Scan parquet spark_catalog.default.item +Output [6]: [i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_color), EqualTo(i_color,pale ), IsNotNull(i_item_sk)] +ReadSchema: struct + +(23) CometFilter +Input [6]: [i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] +Condition : ((isnotnull(i_color#18) AND (i_color#18 = pale )) AND isnotnull(i_item_sk#15)) + +(24) ColumnarToRow [codegen id : 6] +Input [6]: [i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] + +(25) BroadcastExchange +Input [6]: [i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(26) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#15] +Join type: Inner +Join condition: None + +(27) Project [codegen id : 9] +Output [10]: [ss_customer_sk#2, ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] +Input [12]: [ss_item_sk#1, ss_customer_sk#2, ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14, i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] + +(28) Scan parquet spark_catalog.default.customer +Output [4]: [c_customer_sk#21, c_first_name#22, c_last_name#23, c_birth_country#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_birth_country)] +ReadSchema: struct + +(29) CometFilter +Input [4]: [c_customer_sk#21, c_first_name#22, c_last_name#23, c_birth_country#24] +Condition : (isnotnull(c_customer_sk#21) AND isnotnull(c_birth_country#24)) + +(30) ColumnarToRow [codegen id : 7] +Input [4]: [c_customer_sk#21, c_first_name#22, c_last_name#23, c_birth_country#24] + +(31) BroadcastExchange +Input [4]: [c_customer_sk#21, c_first_name#22, c_last_name#23, c_birth_country#24] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(32) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_customer_sk#2] +Right keys [1]: [c_customer_sk#21] +Join type: Inner +Join condition: None + +(33) Project [codegen id : 9] +Output [12]: [ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20, c_first_name#22, c_last_name#23, c_birth_country#24] +Input [14]: [ss_customer_sk#2, ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20, c_customer_sk#21, c_first_name#22, c_last_name#23, c_birth_country#24] + +(34) Scan parquet spark_catalog.default.customer_address +Output [3]: [ca_state#25, ca_zip#26, ca_country#27] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_country), IsNotNull(ca_zip)] +ReadSchema: struct + +(35) CometFilter +Input [3]: [ca_state#25, ca_zip#26, ca_country#27] +Condition : (isnotnull(ca_country#27) AND isnotnull(ca_zip#26)) + +(36) ColumnarToRow [codegen id : 8] +Input [3]: [ca_state#25, ca_zip#26, ca_country#27] + +(37) BroadcastExchange +Input [3]: [ca_state#25, ca_zip#26, ca_country#27] +Arguments: HashedRelationBroadcastMode(List(upper(input[2, string, false]), input[1, string, false]),false), [plan_id=6] + +(38) BroadcastHashJoin [codegen id : 9] +Left keys [2]: [c_birth_country#24, s_zip#14] +Right keys [2]: [upper(ca_country#27), ca_zip#26] +Join type: Inner +Join condition: None + +(39) Project [codegen id : 9] +Output [11]: [ss_net_paid#5, s_store_name#11, s_state#13, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20, c_first_name#22, c_last_name#23, ca_state#25] +Input [15]: [ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20, c_first_name#22, c_last_name#23, c_birth_country#24, ca_state#25, ca_zip#26, ca_country#27] + +(40) HashAggregate [codegen id : 9] +Input [11]: [ss_net_paid#5, s_store_name#11, s_state#13, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20, c_first_name#22, c_last_name#23, ca_state#25] +Keys [10]: [c_last_name#23, c_first_name#22, s_store_name#11, ca_state#25, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17] +Functions [1]: [partial_sum(UnscaledValue(ss_net_paid#5))] +Aggregate Attributes [1]: [sum#28] +Results [11]: [c_last_name#23, c_first_name#22, s_store_name#11, ca_state#25, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17, sum#29] + +(41) Exchange +Input [11]: [c_last_name#23, c_first_name#22, s_store_name#11, ca_state#25, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17, sum#29] +Arguments: hashpartitioning(c_last_name#23, c_first_name#22, s_store_name#11, ca_state#25, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(42) HashAggregate [codegen id : 10] +Input [11]: [c_last_name#23, c_first_name#22, s_store_name#11, ca_state#25, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17, sum#29] +Keys [10]: [c_last_name#23, c_first_name#22, s_store_name#11, ca_state#25, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17] +Functions [1]: [sum(UnscaledValue(ss_net_paid#5))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_paid#5))#30] +Results [4]: [c_last_name#23, c_first_name#22, s_store_name#11, MakeDecimal(sum(UnscaledValue(ss_net_paid#5))#30,17,2) AS netpaid#31] + +(43) HashAggregate [codegen id : 10] +Input [4]: [c_last_name#23, c_first_name#22, s_store_name#11, netpaid#31] +Keys [3]: [c_last_name#23, c_first_name#22, s_store_name#11] +Functions [1]: [partial_sum(netpaid#31)] +Aggregate Attributes [2]: [sum#32, isEmpty#33] +Results [5]: [c_last_name#23, c_first_name#22, s_store_name#11, sum#34, isEmpty#35] + +(44) Exchange +Input [5]: [c_last_name#23, c_first_name#22, s_store_name#11, sum#34, isEmpty#35] +Arguments: hashpartitioning(c_last_name#23, c_first_name#22, s_store_name#11, 5), ENSURE_REQUIREMENTS, [plan_id=8] + +(45) HashAggregate [codegen id : 11] +Input [5]: [c_last_name#23, c_first_name#22, s_store_name#11, sum#34, isEmpty#35] +Keys [3]: [c_last_name#23, c_first_name#22, s_store_name#11] +Functions [1]: [sum(netpaid#31)] +Aggregate Attributes [1]: [sum(netpaid#31)#36] +Results [4]: [c_last_name#23, c_first_name#22, s_store_name#11, sum(netpaid#31)#36 AS paid#37] + +(46) Filter [codegen id : 11] +Input [4]: [c_last_name#23, c_first_name#22, s_store_name#11, paid#37] +Condition : (isnotnull(paid#37) AND (cast(paid#37 as decimal(33,8)) > cast(Subquery scalar-subquery#38, [id=#39] as decimal(33,8)))) + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 46 Hosting Expression = Subquery scalar-subquery#38, [id=#39] +* HashAggregate (73) ++- Exchange (72) + +- * HashAggregate (71) + +- * HashAggregate (70) + +- Exchange (69) + +- * HashAggregate (68) + +- * Project (67) + +- * BroadcastHashJoin Inner BuildRight (66) + :- * Project (64) + : +- * BroadcastHashJoin Inner BuildRight (63) + : :- * Project (61) + : : +- * BroadcastHashJoin Inner BuildRight (60) + : : :- * Project (55) + : : : +- * BroadcastHashJoin Inner BuildRight (54) + : : : :- * Project (52) + : : : : +- * SortMergeJoin Inner (51) + : : : : :- * Sort (48) + : : : : : +- ReusedExchange (47) + : : : : +- * Sort (50) + : : : : +- ReusedExchange (49) + : : : +- ReusedExchange (53) + : : +- BroadcastExchange (59) + : : +- * ColumnarToRow (58) + : : +- CometFilter (57) + : : +- CometScan parquet spark_catalog.default.item (56) + : +- ReusedExchange (62) + +- ReusedExchange (65) + + +(47) ReusedExchange [Reuses operator id: 5] +Output [5]: [ss_item_sk#40, ss_customer_sk#41, ss_store_sk#42, ss_ticket_number#43, ss_net_paid#44] + +(48) Sort [codegen id : 2] +Input [5]: [ss_item_sk#40, ss_customer_sk#41, ss_store_sk#42, ss_ticket_number#43, ss_net_paid#44] +Arguments: [ss_ticket_number#43 ASC NULLS FIRST, ss_item_sk#40 ASC NULLS FIRST], false, 0 + +(49) ReusedExchange [Reuses operator id: 11] +Output [2]: [sr_item_sk#45, sr_ticket_number#46] + +(50) Sort [codegen id : 4] +Input [2]: [sr_item_sk#45, sr_ticket_number#46] +Arguments: [sr_ticket_number#46 ASC NULLS FIRST, sr_item_sk#45 ASC NULLS FIRST], false, 0 + +(51) SortMergeJoin [codegen id : 9] +Left keys [2]: [ss_ticket_number#43, ss_item_sk#40] +Right keys [2]: [sr_ticket_number#46, sr_item_sk#45] +Join type: Inner +Join condition: None + +(52) Project [codegen id : 9] +Output [4]: [ss_item_sk#40, ss_customer_sk#41, ss_store_sk#42, ss_net_paid#44] +Input [7]: [ss_item_sk#40, ss_customer_sk#41, ss_store_sk#42, ss_ticket_number#43, ss_net_paid#44, sr_item_sk#45, sr_ticket_number#46] + +(53) ReusedExchange [Reuses operator id: 19] +Output [4]: [s_store_sk#47, s_store_name#48, s_state#49, s_zip#50] + +(54) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_store_sk#42] +Right keys [1]: [s_store_sk#47] +Join type: Inner +Join condition: None + +(55) Project [codegen id : 9] +Output [6]: [ss_item_sk#40, ss_customer_sk#41, ss_net_paid#44, s_store_name#48, s_state#49, s_zip#50] +Input [8]: [ss_item_sk#40, ss_customer_sk#41, ss_store_sk#42, ss_net_paid#44, s_store_sk#47, s_store_name#48, s_state#49, s_zip#50] + +(56) Scan parquet spark_catalog.default.item +Output [6]: [i_item_sk#51, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(57) CometFilter +Input [6]: [i_item_sk#51, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56] +Condition : isnotnull(i_item_sk#51) + +(58) ColumnarToRow [codegen id : 6] +Input [6]: [i_item_sk#51, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56] + +(59) BroadcastExchange +Input [6]: [i_item_sk#51, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=9] + +(60) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_item_sk#40] +Right keys [1]: [i_item_sk#51] +Join type: Inner +Join condition: None + +(61) Project [codegen id : 9] +Output [10]: [ss_customer_sk#41, ss_net_paid#44, s_store_name#48, s_state#49, s_zip#50, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56] +Input [12]: [ss_item_sk#40, ss_customer_sk#41, ss_net_paid#44, s_store_name#48, s_state#49, s_zip#50, i_item_sk#51, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56] + +(62) ReusedExchange [Reuses operator id: 31] +Output [4]: [c_customer_sk#57, c_first_name#58, c_last_name#59, c_birth_country#60] + +(63) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_customer_sk#41] +Right keys [1]: [c_customer_sk#57] +Join type: Inner +Join condition: None + +(64) Project [codegen id : 9] +Output [12]: [ss_net_paid#44, s_store_name#48, s_state#49, s_zip#50, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56, c_first_name#58, c_last_name#59, c_birth_country#60] +Input [14]: [ss_customer_sk#41, ss_net_paid#44, s_store_name#48, s_state#49, s_zip#50, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56, c_customer_sk#57, c_first_name#58, c_last_name#59, c_birth_country#60] + +(65) ReusedExchange [Reuses operator id: 37] +Output [3]: [ca_state#61, ca_zip#62, ca_country#63] + +(66) BroadcastHashJoin [codegen id : 9] +Left keys [2]: [c_birth_country#60, s_zip#50] +Right keys [2]: [upper(ca_country#63), ca_zip#62] +Join type: Inner +Join condition: None + +(67) Project [codegen id : 9] +Output [11]: [ss_net_paid#44, s_store_name#48, s_state#49, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56, c_first_name#58, c_last_name#59, ca_state#61] +Input [15]: [ss_net_paid#44, s_store_name#48, s_state#49, s_zip#50, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56, c_first_name#58, c_last_name#59, c_birth_country#60, ca_state#61, ca_zip#62, ca_country#63] + +(68) HashAggregate [codegen id : 9] +Input [11]: [ss_net_paid#44, s_store_name#48, s_state#49, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56, c_first_name#58, c_last_name#59, ca_state#61] +Keys [10]: [c_last_name#59, c_first_name#58, s_store_name#48, ca_state#61, s_state#49, i_color#54, i_current_price#52, i_manager_id#56, i_units#55, i_size#53] +Functions [1]: [partial_sum(UnscaledValue(ss_net_paid#44))] +Aggregate Attributes [1]: [sum#64] +Results [11]: [c_last_name#59, c_first_name#58, s_store_name#48, ca_state#61, s_state#49, i_color#54, i_current_price#52, i_manager_id#56, i_units#55, i_size#53, sum#65] + +(69) Exchange +Input [11]: [c_last_name#59, c_first_name#58, s_store_name#48, ca_state#61, s_state#49, i_color#54, i_current_price#52, i_manager_id#56, i_units#55, i_size#53, sum#65] +Arguments: hashpartitioning(c_last_name#59, c_first_name#58, s_store_name#48, ca_state#61, s_state#49, i_color#54, i_current_price#52, i_manager_id#56, i_units#55, i_size#53, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(70) HashAggregate [codegen id : 10] +Input [11]: [c_last_name#59, c_first_name#58, s_store_name#48, ca_state#61, s_state#49, i_color#54, i_current_price#52, i_manager_id#56, i_units#55, i_size#53, sum#65] +Keys [10]: [c_last_name#59, c_first_name#58, s_store_name#48, ca_state#61, s_state#49, i_color#54, i_current_price#52, i_manager_id#56, i_units#55, i_size#53] +Functions [1]: [sum(UnscaledValue(ss_net_paid#44))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_paid#44))#30] +Results [1]: [MakeDecimal(sum(UnscaledValue(ss_net_paid#44))#30,17,2) AS netpaid#66] + +(71) HashAggregate [codegen id : 10] +Input [1]: [netpaid#66] +Keys: [] +Functions [1]: [partial_avg(netpaid#66)] +Aggregate Attributes [2]: [sum#67, count#68] +Results [2]: [sum#69, count#70] + +(72) Exchange +Input [2]: [sum#69, count#70] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=11] + +(73) HashAggregate [codegen id : 11] +Input [2]: [sum#69, count#70] +Keys: [] +Functions [1]: [avg(netpaid#66)] +Aggregate Attributes [1]: [avg(netpaid#66)#71] +Results [1]: [(0.05 * avg(netpaid#66)#71) AS (0.05 * avg(netpaid))#72] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24a/simplified.txt new file mode 100644 index 0000000000..8ebd45fd18 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24a/simplified.txt @@ -0,0 +1,118 @@ +WholeStageCodegen (11) + Filter [paid] + Subquery #1 + WholeStageCodegen (11) + HashAggregate [sum,count] [avg(netpaid),(0.05 * avg(netpaid)),sum,count] + InputAdapter + Exchange #9 + WholeStageCodegen (10) + HashAggregate [netpaid] [sum,count,sum,count] + HashAggregate [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size,sum] [sum(UnscaledValue(ss_net_paid)),netpaid,sum] + InputAdapter + Exchange [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size] #10 + WholeStageCodegen (9) + HashAggregate [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size,ss_net_paid] [sum,sum] + Project [ss_net_paid,s_store_name,s_state,i_current_price,i_size,i_color,i_units,i_manager_id,c_first_name,c_last_name,ca_state] + BroadcastHashJoin [c_birth_country,s_zip,ca_country,ca_zip] + Project [ss_net_paid,s_store_name,s_state,s_zip,i_current_price,i_size,i_color,i_units,i_manager_id,c_first_name,c_last_name,c_birth_country] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Project [ss_customer_sk,ss_net_paid,s_store_name,s_state,s_zip,i_current_price,i_size,i_color,i_units,i_manager_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_customer_sk,ss_net_paid,s_store_name,s_state,s_zip] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_customer_sk,ss_store_sk,ss_net_paid] + SortMergeJoin [ss_ticket_number,ss_item_sk,sr_ticket_number,sr_item_sk] + InputAdapter + WholeStageCodegen (2) + Sort [ss_ticket_number,ss_item_sk] + InputAdapter + ReusedExchange [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_net_paid] #3 + InputAdapter + WholeStageCodegen (4) + Sort [sr_ticket_number,sr_item_sk] + InputAdapter + ReusedExchange [sr_item_sk,sr_ticket_number] #4 + InputAdapter + ReusedExchange [s_store_sk,s_store_name,s_state,s_zip] #5 + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (6) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price,i_size,i_color,i_units,i_manager_id] + InputAdapter + ReusedExchange [c_customer_sk,c_first_name,c_last_name,c_birth_country] #7 + InputAdapter + ReusedExchange [ca_state,ca_zip,ca_country] #8 + HashAggregate [c_last_name,c_first_name,s_store_name,sum,isEmpty] [sum(netpaid),paid,sum,isEmpty] + InputAdapter + Exchange [c_last_name,c_first_name,s_store_name] #1 + WholeStageCodegen (10) + HashAggregate [c_last_name,c_first_name,s_store_name,netpaid] [sum,isEmpty,sum,isEmpty] + HashAggregate [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size,sum] [sum(UnscaledValue(ss_net_paid)),netpaid,sum] + InputAdapter + Exchange [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size] #2 + WholeStageCodegen (9) + HashAggregate [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size,ss_net_paid] [sum,sum] + Project [ss_net_paid,s_store_name,s_state,i_current_price,i_size,i_color,i_units,i_manager_id,c_first_name,c_last_name,ca_state] + BroadcastHashJoin [c_birth_country,s_zip,ca_country,ca_zip] + Project [ss_net_paid,s_store_name,s_state,s_zip,i_current_price,i_size,i_color,i_units,i_manager_id,c_first_name,c_last_name,c_birth_country] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Project [ss_customer_sk,ss_net_paid,s_store_name,s_state,s_zip,i_current_price,i_size,i_color,i_units,i_manager_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_customer_sk,ss_net_paid,s_store_name,s_state,s_zip] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_customer_sk,ss_store_sk,ss_net_paid] + SortMergeJoin [ss_ticket_number,ss_item_sk,sr_ticket_number,sr_item_sk] + InputAdapter + WholeStageCodegen (2) + Sort [ss_ticket_number,ss_item_sk] + InputAdapter + Exchange [ss_ticket_number,ss_item_sk] #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_net_paid] + CometFilter [ss_ticket_number,ss_item_sk,ss_store_sk,ss_customer_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_net_paid,ss_sold_date_sk] + InputAdapter + WholeStageCodegen (4) + Sort [sr_ticket_number,sr_item_sk] + InputAdapter + Exchange [sr_ticket_number,sr_item_sk] #4 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometProject [sr_item_sk,sr_ticket_number] + CometFilter [sr_ticket_number,sr_item_sk] + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_returned_date_sk] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (5) + ColumnarToRow + InputAdapter + CometProject [s_store_sk,s_store_name,s_state,s_zip] + CometFilter [s_market_id,s_store_sk,s_zip] + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name,s_market_id,s_state,s_zip] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (6) + ColumnarToRow + InputAdapter + CometFilter [i_color,i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price,i_size,i_color,i_units,i_manager_id] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (7) + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_birth_country] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_first_name,c_last_name,c_birth_country] + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (8) + ColumnarToRow + InputAdapter + CometFilter [ca_country,ca_zip] + CometScan parquet spark_catalog.default.customer_address [ca_state,ca_zip,ca_country] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24b/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24b/explain.txt new file mode 100644 index 0000000000..0ac5639b78 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24b/explain.txt @@ -0,0 +1,427 @@ +== Physical Plan == +* Filter (46) ++- * HashAggregate (45) + +- Exchange (44) + +- * HashAggregate (43) + +- * HashAggregate (42) + +- Exchange (41) + +- * HashAggregate (40) + +- * Project (39) + +- * BroadcastHashJoin Inner BuildRight (38) + :- * Project (33) + : +- * BroadcastHashJoin Inner BuildRight (32) + : :- * Project (27) + : : +- * BroadcastHashJoin Inner BuildRight (26) + : : :- * Project (21) + : : : +- * BroadcastHashJoin Inner BuildRight (20) + : : : :- * Project (14) + : : : : +- * SortMergeJoin Inner (13) + : : : : :- * Sort (6) + : : : : : +- Exchange (5) + : : : : : +- * ColumnarToRow (4) + : : : : : +- CometProject (3) + : : : : : +- CometFilter (2) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : +- * Sort (12) + : : : : +- Exchange (11) + : : : : +- * ColumnarToRow (10) + : : : : +- CometProject (9) + : : : : +- CometFilter (8) + : : : : +- CometScan parquet spark_catalog.default.store_returns (7) + : : : +- BroadcastExchange (19) + : : : +- * ColumnarToRow (18) + : : : +- CometProject (17) + : : : +- CometFilter (16) + : : : +- CometScan parquet spark_catalog.default.store (15) + : : +- BroadcastExchange (25) + : : +- * ColumnarToRow (24) + : : +- CometFilter (23) + : : +- CometScan parquet spark_catalog.default.item (22) + : +- BroadcastExchange (31) + : +- * ColumnarToRow (30) + : +- CometFilter (29) + : +- CometScan parquet spark_catalog.default.customer (28) + +- BroadcastExchange (37) + +- * ColumnarToRow (36) + +- CometFilter (35) + +- CometScan parquet spark_catalog.default.customer_address (34) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, ss_sold_date_sk#6] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_ticket_number), IsNotNull(ss_item_sk), IsNotNull(ss_store_sk), IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(2) CometFilter +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, ss_sold_date_sk#6] +Condition : (((isnotnull(ss_ticket_number#4) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_store_sk#3)) AND isnotnull(ss_customer_sk#2)) + +(3) CometProject +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, ss_sold_date_sk#6] +Arguments: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5], [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5] + +(4) ColumnarToRow [codegen id : 1] +Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5] + +(5) Exchange +Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5] +Arguments: hashpartitioning(ss_ticket_number#4, ss_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(6) Sort [codegen id : 2] +Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5] +Arguments: [ss_ticket_number#4 ASC NULLS FIRST, ss_item_sk#1 ASC NULLS FIRST], false, 0 + +(7) Scan parquet spark_catalog.default.store_returns +Output [3]: [sr_item_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_returns] +PushedFilters: [IsNotNull(sr_ticket_number), IsNotNull(sr_item_sk)] +ReadSchema: struct + +(8) CometFilter +Input [3]: [sr_item_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] +Condition : (isnotnull(sr_ticket_number#8) AND isnotnull(sr_item_sk#7)) + +(9) CometProject +Input [3]: [sr_item_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] +Arguments: [sr_item_sk#7, sr_ticket_number#8], [sr_item_sk#7, sr_ticket_number#8] + +(10) ColumnarToRow [codegen id : 3] +Input [2]: [sr_item_sk#7, sr_ticket_number#8] + +(11) Exchange +Input [2]: [sr_item_sk#7, sr_ticket_number#8] +Arguments: hashpartitioning(sr_ticket_number#8, sr_item_sk#7, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(12) Sort [codegen id : 4] +Input [2]: [sr_item_sk#7, sr_ticket_number#8] +Arguments: [sr_ticket_number#8 ASC NULLS FIRST, sr_item_sk#7 ASC NULLS FIRST], false, 0 + +(13) SortMergeJoin [codegen id : 9] +Left keys [2]: [ss_ticket_number#4, ss_item_sk#1] +Right keys [2]: [sr_ticket_number#8, sr_item_sk#7] +Join type: Inner +Join condition: None + +(14) Project [codegen id : 9] +Output [4]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_net_paid#5] +Input [7]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, sr_item_sk#7, sr_ticket_number#8] + +(15) Scan parquet spark_catalog.default.store +Output [5]: [s_store_sk#10, s_store_name#11, s_market_id#12, s_state#13, s_zip#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_market_id), EqualTo(s_market_id,8), IsNotNull(s_store_sk), IsNotNull(s_zip)] +ReadSchema: struct + +(16) CometFilter +Input [5]: [s_store_sk#10, s_store_name#11, s_market_id#12, s_state#13, s_zip#14] +Condition : (((isnotnull(s_market_id#12) AND (s_market_id#12 = 8)) AND isnotnull(s_store_sk#10)) AND isnotnull(s_zip#14)) + +(17) CometProject +Input [5]: [s_store_sk#10, s_store_name#11, s_market_id#12, s_state#13, s_zip#14] +Arguments: [s_store_sk#10, s_store_name#11, s_state#13, s_zip#14], [s_store_sk#10, s_store_name#11, s_state#13, s_zip#14] + +(18) ColumnarToRow [codegen id : 5] +Input [4]: [s_store_sk#10, s_store_name#11, s_state#13, s_zip#14] + +(19) BroadcastExchange +Input [4]: [s_store_sk#10, s_store_name#11, s_state#13, s_zip#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(20) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_store_sk#3] +Right keys [1]: [s_store_sk#10] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 9] +Output [6]: [ss_item_sk#1, ss_customer_sk#2, ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14] +Input [8]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_net_paid#5, s_store_sk#10, s_store_name#11, s_state#13, s_zip#14] + +(22) Scan parquet spark_catalog.default.item +Output [6]: [i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_color), EqualTo(i_color,chiffon ), IsNotNull(i_item_sk)] +ReadSchema: struct + +(23) CometFilter +Input [6]: [i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] +Condition : ((isnotnull(i_color#18) AND (i_color#18 = chiffon )) AND isnotnull(i_item_sk#15)) + +(24) ColumnarToRow [codegen id : 6] +Input [6]: [i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] + +(25) BroadcastExchange +Input [6]: [i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(26) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#15] +Join type: Inner +Join condition: None + +(27) Project [codegen id : 9] +Output [10]: [ss_customer_sk#2, ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] +Input [12]: [ss_item_sk#1, ss_customer_sk#2, ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14, i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] + +(28) Scan parquet spark_catalog.default.customer +Output [4]: [c_customer_sk#21, c_first_name#22, c_last_name#23, c_birth_country#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_birth_country)] +ReadSchema: struct + +(29) CometFilter +Input [4]: [c_customer_sk#21, c_first_name#22, c_last_name#23, c_birth_country#24] +Condition : (isnotnull(c_customer_sk#21) AND isnotnull(c_birth_country#24)) + +(30) ColumnarToRow [codegen id : 7] +Input [4]: [c_customer_sk#21, c_first_name#22, c_last_name#23, c_birth_country#24] + +(31) BroadcastExchange +Input [4]: [c_customer_sk#21, c_first_name#22, c_last_name#23, c_birth_country#24] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(32) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_customer_sk#2] +Right keys [1]: [c_customer_sk#21] +Join type: Inner +Join condition: None + +(33) Project [codegen id : 9] +Output [12]: [ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20, c_first_name#22, c_last_name#23, c_birth_country#24] +Input [14]: [ss_customer_sk#2, ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20, c_customer_sk#21, c_first_name#22, c_last_name#23, c_birth_country#24] + +(34) Scan parquet spark_catalog.default.customer_address +Output [3]: [ca_state#25, ca_zip#26, ca_country#27] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_country), IsNotNull(ca_zip)] +ReadSchema: struct + +(35) CometFilter +Input [3]: [ca_state#25, ca_zip#26, ca_country#27] +Condition : (isnotnull(ca_country#27) AND isnotnull(ca_zip#26)) + +(36) ColumnarToRow [codegen id : 8] +Input [3]: [ca_state#25, ca_zip#26, ca_country#27] + +(37) BroadcastExchange +Input [3]: [ca_state#25, ca_zip#26, ca_country#27] +Arguments: HashedRelationBroadcastMode(List(upper(input[2, string, false]), input[1, string, false]),false), [plan_id=6] + +(38) BroadcastHashJoin [codegen id : 9] +Left keys [2]: [c_birth_country#24, s_zip#14] +Right keys [2]: [upper(ca_country#27), ca_zip#26] +Join type: Inner +Join condition: None + +(39) Project [codegen id : 9] +Output [11]: [ss_net_paid#5, s_store_name#11, s_state#13, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20, c_first_name#22, c_last_name#23, ca_state#25] +Input [15]: [ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20, c_first_name#22, c_last_name#23, c_birth_country#24, ca_state#25, ca_zip#26, ca_country#27] + +(40) HashAggregate [codegen id : 9] +Input [11]: [ss_net_paid#5, s_store_name#11, s_state#13, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20, c_first_name#22, c_last_name#23, ca_state#25] +Keys [10]: [c_last_name#23, c_first_name#22, s_store_name#11, ca_state#25, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17] +Functions [1]: [partial_sum(UnscaledValue(ss_net_paid#5))] +Aggregate Attributes [1]: [sum#28] +Results [11]: [c_last_name#23, c_first_name#22, s_store_name#11, ca_state#25, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17, sum#29] + +(41) Exchange +Input [11]: [c_last_name#23, c_first_name#22, s_store_name#11, ca_state#25, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17, sum#29] +Arguments: hashpartitioning(c_last_name#23, c_first_name#22, s_store_name#11, ca_state#25, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(42) HashAggregate [codegen id : 10] +Input [11]: [c_last_name#23, c_first_name#22, s_store_name#11, ca_state#25, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17, sum#29] +Keys [10]: [c_last_name#23, c_first_name#22, s_store_name#11, ca_state#25, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17] +Functions [1]: [sum(UnscaledValue(ss_net_paid#5))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_paid#5))#30] +Results [4]: [c_last_name#23, c_first_name#22, s_store_name#11, MakeDecimal(sum(UnscaledValue(ss_net_paid#5))#30,17,2) AS netpaid#31] + +(43) HashAggregate [codegen id : 10] +Input [4]: [c_last_name#23, c_first_name#22, s_store_name#11, netpaid#31] +Keys [3]: [c_last_name#23, c_first_name#22, s_store_name#11] +Functions [1]: [partial_sum(netpaid#31)] +Aggregate Attributes [2]: [sum#32, isEmpty#33] +Results [5]: [c_last_name#23, c_first_name#22, s_store_name#11, sum#34, isEmpty#35] + +(44) Exchange +Input [5]: [c_last_name#23, c_first_name#22, s_store_name#11, sum#34, isEmpty#35] +Arguments: hashpartitioning(c_last_name#23, c_first_name#22, s_store_name#11, 5), ENSURE_REQUIREMENTS, [plan_id=8] + +(45) HashAggregate [codegen id : 11] +Input [5]: [c_last_name#23, c_first_name#22, s_store_name#11, sum#34, isEmpty#35] +Keys [3]: [c_last_name#23, c_first_name#22, s_store_name#11] +Functions [1]: [sum(netpaid#31)] +Aggregate Attributes [1]: [sum(netpaid#31)#36] +Results [4]: [c_last_name#23, c_first_name#22, s_store_name#11, sum(netpaid#31)#36 AS paid#37] + +(46) Filter [codegen id : 11] +Input [4]: [c_last_name#23, c_first_name#22, s_store_name#11, paid#37] +Condition : (isnotnull(paid#37) AND (cast(paid#37 as decimal(33,8)) > cast(Subquery scalar-subquery#38, [id=#39] as decimal(33,8)))) + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 46 Hosting Expression = Subquery scalar-subquery#38, [id=#39] +* HashAggregate (73) ++- Exchange (72) + +- * HashAggregate (71) + +- * HashAggregate (70) + +- Exchange (69) + +- * HashAggregate (68) + +- * Project (67) + +- * BroadcastHashJoin Inner BuildRight (66) + :- * Project (64) + : +- * BroadcastHashJoin Inner BuildRight (63) + : :- * Project (61) + : : +- * BroadcastHashJoin Inner BuildRight (60) + : : :- * Project (55) + : : : +- * BroadcastHashJoin Inner BuildRight (54) + : : : :- * Project (52) + : : : : +- * SortMergeJoin Inner (51) + : : : : :- * Sort (48) + : : : : : +- ReusedExchange (47) + : : : : +- * Sort (50) + : : : : +- ReusedExchange (49) + : : : +- ReusedExchange (53) + : : +- BroadcastExchange (59) + : : +- * ColumnarToRow (58) + : : +- CometFilter (57) + : : +- CometScan parquet spark_catalog.default.item (56) + : +- ReusedExchange (62) + +- ReusedExchange (65) + + +(47) ReusedExchange [Reuses operator id: 5] +Output [5]: [ss_item_sk#40, ss_customer_sk#41, ss_store_sk#42, ss_ticket_number#43, ss_net_paid#44] + +(48) Sort [codegen id : 2] +Input [5]: [ss_item_sk#40, ss_customer_sk#41, ss_store_sk#42, ss_ticket_number#43, ss_net_paid#44] +Arguments: [ss_ticket_number#43 ASC NULLS FIRST, ss_item_sk#40 ASC NULLS FIRST], false, 0 + +(49) ReusedExchange [Reuses operator id: 11] +Output [2]: [sr_item_sk#45, sr_ticket_number#46] + +(50) Sort [codegen id : 4] +Input [2]: [sr_item_sk#45, sr_ticket_number#46] +Arguments: [sr_ticket_number#46 ASC NULLS FIRST, sr_item_sk#45 ASC NULLS FIRST], false, 0 + +(51) SortMergeJoin [codegen id : 9] +Left keys [2]: [ss_ticket_number#43, ss_item_sk#40] +Right keys [2]: [sr_ticket_number#46, sr_item_sk#45] +Join type: Inner +Join condition: None + +(52) Project [codegen id : 9] +Output [4]: [ss_item_sk#40, ss_customer_sk#41, ss_store_sk#42, ss_net_paid#44] +Input [7]: [ss_item_sk#40, ss_customer_sk#41, ss_store_sk#42, ss_ticket_number#43, ss_net_paid#44, sr_item_sk#45, sr_ticket_number#46] + +(53) ReusedExchange [Reuses operator id: 19] +Output [4]: [s_store_sk#47, s_store_name#48, s_state#49, s_zip#50] + +(54) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_store_sk#42] +Right keys [1]: [s_store_sk#47] +Join type: Inner +Join condition: None + +(55) Project [codegen id : 9] +Output [6]: [ss_item_sk#40, ss_customer_sk#41, ss_net_paid#44, s_store_name#48, s_state#49, s_zip#50] +Input [8]: [ss_item_sk#40, ss_customer_sk#41, ss_store_sk#42, ss_net_paid#44, s_store_sk#47, s_store_name#48, s_state#49, s_zip#50] + +(56) Scan parquet spark_catalog.default.item +Output [6]: [i_item_sk#51, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(57) CometFilter +Input [6]: [i_item_sk#51, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56] +Condition : isnotnull(i_item_sk#51) + +(58) ColumnarToRow [codegen id : 6] +Input [6]: [i_item_sk#51, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56] + +(59) BroadcastExchange +Input [6]: [i_item_sk#51, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=9] + +(60) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_item_sk#40] +Right keys [1]: [i_item_sk#51] +Join type: Inner +Join condition: None + +(61) Project [codegen id : 9] +Output [10]: [ss_customer_sk#41, ss_net_paid#44, s_store_name#48, s_state#49, s_zip#50, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56] +Input [12]: [ss_item_sk#40, ss_customer_sk#41, ss_net_paid#44, s_store_name#48, s_state#49, s_zip#50, i_item_sk#51, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56] + +(62) ReusedExchange [Reuses operator id: 31] +Output [4]: [c_customer_sk#57, c_first_name#58, c_last_name#59, c_birth_country#60] + +(63) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_customer_sk#41] +Right keys [1]: [c_customer_sk#57] +Join type: Inner +Join condition: None + +(64) Project [codegen id : 9] +Output [12]: [ss_net_paid#44, s_store_name#48, s_state#49, s_zip#50, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56, c_first_name#58, c_last_name#59, c_birth_country#60] +Input [14]: [ss_customer_sk#41, ss_net_paid#44, s_store_name#48, s_state#49, s_zip#50, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56, c_customer_sk#57, c_first_name#58, c_last_name#59, c_birth_country#60] + +(65) ReusedExchange [Reuses operator id: 37] +Output [3]: [ca_state#61, ca_zip#62, ca_country#63] + +(66) BroadcastHashJoin [codegen id : 9] +Left keys [2]: [c_birth_country#60, s_zip#50] +Right keys [2]: [upper(ca_country#63), ca_zip#62] +Join type: Inner +Join condition: None + +(67) Project [codegen id : 9] +Output [11]: [ss_net_paid#44, s_store_name#48, s_state#49, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56, c_first_name#58, c_last_name#59, ca_state#61] +Input [15]: [ss_net_paid#44, s_store_name#48, s_state#49, s_zip#50, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56, c_first_name#58, c_last_name#59, c_birth_country#60, ca_state#61, ca_zip#62, ca_country#63] + +(68) HashAggregate [codegen id : 9] +Input [11]: [ss_net_paid#44, s_store_name#48, s_state#49, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56, c_first_name#58, c_last_name#59, ca_state#61] +Keys [10]: [c_last_name#59, c_first_name#58, s_store_name#48, ca_state#61, s_state#49, i_color#54, i_current_price#52, i_manager_id#56, i_units#55, i_size#53] +Functions [1]: [partial_sum(UnscaledValue(ss_net_paid#44))] +Aggregate Attributes [1]: [sum#64] +Results [11]: [c_last_name#59, c_first_name#58, s_store_name#48, ca_state#61, s_state#49, i_color#54, i_current_price#52, i_manager_id#56, i_units#55, i_size#53, sum#65] + +(69) Exchange +Input [11]: [c_last_name#59, c_first_name#58, s_store_name#48, ca_state#61, s_state#49, i_color#54, i_current_price#52, i_manager_id#56, i_units#55, i_size#53, sum#65] +Arguments: hashpartitioning(c_last_name#59, c_first_name#58, s_store_name#48, ca_state#61, s_state#49, i_color#54, i_current_price#52, i_manager_id#56, i_units#55, i_size#53, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(70) HashAggregate [codegen id : 10] +Input [11]: [c_last_name#59, c_first_name#58, s_store_name#48, ca_state#61, s_state#49, i_color#54, i_current_price#52, i_manager_id#56, i_units#55, i_size#53, sum#65] +Keys [10]: [c_last_name#59, c_first_name#58, s_store_name#48, ca_state#61, s_state#49, i_color#54, i_current_price#52, i_manager_id#56, i_units#55, i_size#53] +Functions [1]: [sum(UnscaledValue(ss_net_paid#44))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_paid#44))#30] +Results [1]: [MakeDecimal(sum(UnscaledValue(ss_net_paid#44))#30,17,2) AS netpaid#66] + +(71) HashAggregate [codegen id : 10] +Input [1]: [netpaid#66] +Keys: [] +Functions [1]: [partial_avg(netpaid#66)] +Aggregate Attributes [2]: [sum#67, count#68] +Results [2]: [sum#69, count#70] + +(72) Exchange +Input [2]: [sum#69, count#70] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=11] + +(73) HashAggregate [codegen id : 11] +Input [2]: [sum#69, count#70] +Keys: [] +Functions [1]: [avg(netpaid#66)] +Aggregate Attributes [1]: [avg(netpaid#66)#71] +Results [1]: [(0.05 * avg(netpaid#66)#71) AS (0.05 * avg(netpaid))#72] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24b/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24b/simplified.txt new file mode 100644 index 0000000000..8ebd45fd18 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24b/simplified.txt @@ -0,0 +1,118 @@ +WholeStageCodegen (11) + Filter [paid] + Subquery #1 + WholeStageCodegen (11) + HashAggregate [sum,count] [avg(netpaid),(0.05 * avg(netpaid)),sum,count] + InputAdapter + Exchange #9 + WholeStageCodegen (10) + HashAggregate [netpaid] [sum,count,sum,count] + HashAggregate [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size,sum] [sum(UnscaledValue(ss_net_paid)),netpaid,sum] + InputAdapter + Exchange [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size] #10 + WholeStageCodegen (9) + HashAggregate [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size,ss_net_paid] [sum,sum] + Project [ss_net_paid,s_store_name,s_state,i_current_price,i_size,i_color,i_units,i_manager_id,c_first_name,c_last_name,ca_state] + BroadcastHashJoin [c_birth_country,s_zip,ca_country,ca_zip] + Project [ss_net_paid,s_store_name,s_state,s_zip,i_current_price,i_size,i_color,i_units,i_manager_id,c_first_name,c_last_name,c_birth_country] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Project [ss_customer_sk,ss_net_paid,s_store_name,s_state,s_zip,i_current_price,i_size,i_color,i_units,i_manager_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_customer_sk,ss_net_paid,s_store_name,s_state,s_zip] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_customer_sk,ss_store_sk,ss_net_paid] + SortMergeJoin [ss_ticket_number,ss_item_sk,sr_ticket_number,sr_item_sk] + InputAdapter + WholeStageCodegen (2) + Sort [ss_ticket_number,ss_item_sk] + InputAdapter + ReusedExchange [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_net_paid] #3 + InputAdapter + WholeStageCodegen (4) + Sort [sr_ticket_number,sr_item_sk] + InputAdapter + ReusedExchange [sr_item_sk,sr_ticket_number] #4 + InputAdapter + ReusedExchange [s_store_sk,s_store_name,s_state,s_zip] #5 + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (6) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price,i_size,i_color,i_units,i_manager_id] + InputAdapter + ReusedExchange [c_customer_sk,c_first_name,c_last_name,c_birth_country] #7 + InputAdapter + ReusedExchange [ca_state,ca_zip,ca_country] #8 + HashAggregate [c_last_name,c_first_name,s_store_name,sum,isEmpty] [sum(netpaid),paid,sum,isEmpty] + InputAdapter + Exchange [c_last_name,c_first_name,s_store_name] #1 + WholeStageCodegen (10) + HashAggregate [c_last_name,c_first_name,s_store_name,netpaid] [sum,isEmpty,sum,isEmpty] + HashAggregate [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size,sum] [sum(UnscaledValue(ss_net_paid)),netpaid,sum] + InputAdapter + Exchange [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size] #2 + WholeStageCodegen (9) + HashAggregate [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size,ss_net_paid] [sum,sum] + Project [ss_net_paid,s_store_name,s_state,i_current_price,i_size,i_color,i_units,i_manager_id,c_first_name,c_last_name,ca_state] + BroadcastHashJoin [c_birth_country,s_zip,ca_country,ca_zip] + Project [ss_net_paid,s_store_name,s_state,s_zip,i_current_price,i_size,i_color,i_units,i_manager_id,c_first_name,c_last_name,c_birth_country] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Project [ss_customer_sk,ss_net_paid,s_store_name,s_state,s_zip,i_current_price,i_size,i_color,i_units,i_manager_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_customer_sk,ss_net_paid,s_store_name,s_state,s_zip] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_customer_sk,ss_store_sk,ss_net_paid] + SortMergeJoin [ss_ticket_number,ss_item_sk,sr_ticket_number,sr_item_sk] + InputAdapter + WholeStageCodegen (2) + Sort [ss_ticket_number,ss_item_sk] + InputAdapter + Exchange [ss_ticket_number,ss_item_sk] #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_net_paid] + CometFilter [ss_ticket_number,ss_item_sk,ss_store_sk,ss_customer_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_net_paid,ss_sold_date_sk] + InputAdapter + WholeStageCodegen (4) + Sort [sr_ticket_number,sr_item_sk] + InputAdapter + Exchange [sr_ticket_number,sr_item_sk] #4 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometProject [sr_item_sk,sr_ticket_number] + CometFilter [sr_ticket_number,sr_item_sk] + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_returned_date_sk] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (5) + ColumnarToRow + InputAdapter + CometProject [s_store_sk,s_store_name,s_state,s_zip] + CometFilter [s_market_id,s_store_sk,s_zip] + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name,s_market_id,s_state,s_zip] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (6) + ColumnarToRow + InputAdapter + CometFilter [i_color,i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price,i_size,i_color,i_units,i_manager_id] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (7) + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_birth_country] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_first_name,c_last_name,c_birth_country] + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (8) + ColumnarToRow + InputAdapter + CometFilter [ca_country,ca_zip] + CometScan parquet spark_catalog.default.customer_address [ca_state,ca_zip,ca_country] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q25/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q25/explain.txt new file mode 100644 index 0000000000..2635546e44 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q25/explain.txt @@ -0,0 +1,298 @@ +== Physical Plan == +TakeOrderedAndProject (40) ++- * HashAggregate (39) + +- Exchange (38) + +- * HashAggregate (37) + +- * Project (36) + +- * BroadcastHashJoin Inner BuildRight (35) + :- * Project (30) + : +- * BroadcastHashJoin Inner BuildRight (29) + : :- * Project (24) + : : +- * BroadcastHashJoin Inner BuildRight (23) + : : :- * Project (21) + : : : +- * BroadcastHashJoin Inner BuildRight (20) + : : : :- * Project (18) + : : : : +- * BroadcastHashJoin Inner BuildRight (17) + : : : : :- * Project (15) + : : : : : +- * BroadcastHashJoin Inner BuildRight (14) + : : : : : :- * Project (9) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : : : :- * ColumnarToRow (3) + : : : : : : : +- CometFilter (2) + : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : : : +- BroadcastExchange (7) + : : : : : : +- * ColumnarToRow (6) + : : : : : : +- CometFilter (5) + : : : : : : +- CometScan parquet spark_catalog.default.store_returns (4) + : : : : : +- BroadcastExchange (13) + : : : : : +- * ColumnarToRow (12) + : : : : : +- CometFilter (11) + : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (10) + : : : : +- ReusedExchange (16) + : : : +- ReusedExchange (19) + : : +- ReusedExchange (22) + : +- BroadcastExchange (28) + : +- * ColumnarToRow (27) + : +- CometFilter (26) + : +- CometScan parquet spark_catalog.default.store (25) + +- BroadcastExchange (34) + +- * ColumnarToRow (33) + +- CometFilter (32) + +- CometScan parquet spark_catalog.default.item (31) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_profit#5, ss_sold_date_sk#6] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#6), dynamicpruningexpression(ss_sold_date_sk#6 IN dynamicpruning#7)] +PushedFilters: [IsNotNull(ss_customer_sk), IsNotNull(ss_item_sk), IsNotNull(ss_ticket_number), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(2) CometFilter +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_profit#5, ss_sold_date_sk#6] +Condition : (((isnotnull(ss_customer_sk#2) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_ticket_number#4)) AND isnotnull(ss_store_sk#3)) + +(3) ColumnarToRow [codegen id : 8] +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_profit#5, ss_sold_date_sk#6] + +(4) Scan parquet spark_catalog.default.store_returns +Output [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_net_loss#11, sr_returned_date_sk#12] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(sr_returned_date_sk#12), dynamicpruningexpression(sr_returned_date_sk#12 IN dynamicpruning#13)] +PushedFilters: [IsNotNull(sr_customer_sk), IsNotNull(sr_item_sk), IsNotNull(sr_ticket_number)] +ReadSchema: struct + +(5) CometFilter +Input [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_net_loss#11, sr_returned_date_sk#12] +Condition : ((isnotnull(sr_customer_sk#9) AND isnotnull(sr_item_sk#8)) AND isnotnull(sr_ticket_number#10)) + +(6) ColumnarToRow [codegen id : 1] +Input [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_net_loss#11, sr_returned_date_sk#12] + +(7) BroadcastExchange +Input [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_net_loss#11, sr_returned_date_sk#12] +Arguments: HashedRelationBroadcastMode(List(input[1, int, false], input[0, int, false], input[2, int, false]),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 8] +Left keys [3]: [ss_customer_sk#2, ss_item_sk#1, ss_ticket_number#4] +Right keys [3]: [sr_customer_sk#9, sr_item_sk#8, sr_ticket_number#10] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 8] +Output [8]: [ss_item_sk#1, ss_store_sk#3, ss_net_profit#5, ss_sold_date_sk#6, sr_item_sk#8, sr_customer_sk#9, sr_net_loss#11, sr_returned_date_sk#12] +Input [11]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_profit#5, ss_sold_date_sk#6, sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_net_loss#11, sr_returned_date_sk#12] + +(10) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_net_profit#16, cs_sold_date_sk#17] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#17), dynamicpruningexpression(cs_sold_date_sk#17 IN dynamicpruning#18)] +PushedFilters: [IsNotNull(cs_bill_customer_sk), IsNotNull(cs_item_sk)] +ReadSchema: struct + +(11) CometFilter +Input [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_net_profit#16, cs_sold_date_sk#17] +Condition : (isnotnull(cs_bill_customer_sk#14) AND isnotnull(cs_item_sk#15)) + +(12) ColumnarToRow [codegen id : 2] +Input [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_net_profit#16, cs_sold_date_sk#17] + +(13) BroadcastExchange +Input [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_net_profit#16, cs_sold_date_sk#17] +Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[0, int, false] as bigint), 32) | (cast(input[1, int, false] as bigint) & 4294967295))),false), [plan_id=2] + +(14) BroadcastHashJoin [codegen id : 8] +Left keys [2]: [sr_customer_sk#9, sr_item_sk#8] +Right keys [2]: [cs_bill_customer_sk#14, cs_item_sk#15] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 8] +Output [8]: [ss_item_sk#1, ss_store_sk#3, ss_net_profit#5, ss_sold_date_sk#6, sr_net_loss#11, sr_returned_date_sk#12, cs_net_profit#16, cs_sold_date_sk#17] +Input [12]: [ss_item_sk#1, ss_store_sk#3, ss_net_profit#5, ss_sold_date_sk#6, sr_item_sk#8, sr_customer_sk#9, sr_net_loss#11, sr_returned_date_sk#12, cs_bill_customer_sk#14, cs_item_sk#15, cs_net_profit#16, cs_sold_date_sk#17] + +(16) ReusedExchange [Reuses operator id: 45] +Output [1]: [d_date_sk#19] + +(17) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_sold_date_sk#6] +Right keys [1]: [d_date_sk#19] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 8] +Output [7]: [ss_item_sk#1, ss_store_sk#3, ss_net_profit#5, sr_net_loss#11, sr_returned_date_sk#12, cs_net_profit#16, cs_sold_date_sk#17] +Input [9]: [ss_item_sk#1, ss_store_sk#3, ss_net_profit#5, ss_sold_date_sk#6, sr_net_loss#11, sr_returned_date_sk#12, cs_net_profit#16, cs_sold_date_sk#17, d_date_sk#19] + +(19) ReusedExchange [Reuses operator id: 50] +Output [1]: [d_date_sk#20] + +(20) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [sr_returned_date_sk#12] +Right keys [1]: [d_date_sk#20] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 8] +Output [6]: [ss_item_sk#1, ss_store_sk#3, ss_net_profit#5, sr_net_loss#11, cs_net_profit#16, cs_sold_date_sk#17] +Input [8]: [ss_item_sk#1, ss_store_sk#3, ss_net_profit#5, sr_net_loss#11, sr_returned_date_sk#12, cs_net_profit#16, cs_sold_date_sk#17, d_date_sk#20] + +(22) ReusedExchange [Reuses operator id: 50] +Output [1]: [d_date_sk#21] + +(23) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [cs_sold_date_sk#17] +Right keys [1]: [d_date_sk#21] +Join type: Inner +Join condition: None + +(24) Project [codegen id : 8] +Output [5]: [ss_item_sk#1, ss_store_sk#3, ss_net_profit#5, sr_net_loss#11, cs_net_profit#16] +Input [7]: [ss_item_sk#1, ss_store_sk#3, ss_net_profit#5, sr_net_loss#11, cs_net_profit#16, cs_sold_date_sk#17, d_date_sk#21] + +(25) Scan parquet spark_catalog.default.store +Output [3]: [s_store_sk#22, s_store_id#23, s_store_name#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(26) CometFilter +Input [3]: [s_store_sk#22, s_store_id#23, s_store_name#24] +Condition : isnotnull(s_store_sk#22) + +(27) ColumnarToRow [codegen id : 6] +Input [3]: [s_store_sk#22, s_store_id#23, s_store_name#24] + +(28) BroadcastExchange +Input [3]: [s_store_sk#22, s_store_id#23, s_store_name#24] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(29) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_store_sk#3] +Right keys [1]: [s_store_sk#22] +Join type: Inner +Join condition: None + +(30) Project [codegen id : 8] +Output [6]: [ss_item_sk#1, ss_net_profit#5, sr_net_loss#11, cs_net_profit#16, s_store_id#23, s_store_name#24] +Input [8]: [ss_item_sk#1, ss_store_sk#3, ss_net_profit#5, sr_net_loss#11, cs_net_profit#16, s_store_sk#22, s_store_id#23, s_store_name#24] + +(31) Scan parquet spark_catalog.default.item +Output [3]: [i_item_sk#25, i_item_id#26, i_item_desc#27] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(32) CometFilter +Input [3]: [i_item_sk#25, i_item_id#26, i_item_desc#27] +Condition : isnotnull(i_item_sk#25) + +(33) ColumnarToRow [codegen id : 7] +Input [3]: [i_item_sk#25, i_item_id#26, i_item_desc#27] + +(34) BroadcastExchange +Input [3]: [i_item_sk#25, i_item_id#26, i_item_desc#27] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(35) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#25] +Join type: Inner +Join condition: None + +(36) Project [codegen id : 8] +Output [7]: [ss_net_profit#5, sr_net_loss#11, cs_net_profit#16, s_store_id#23, s_store_name#24, i_item_id#26, i_item_desc#27] +Input [9]: [ss_item_sk#1, ss_net_profit#5, sr_net_loss#11, cs_net_profit#16, s_store_id#23, s_store_name#24, i_item_sk#25, i_item_id#26, i_item_desc#27] + +(37) HashAggregate [codegen id : 8] +Input [7]: [ss_net_profit#5, sr_net_loss#11, cs_net_profit#16, s_store_id#23, s_store_name#24, i_item_id#26, i_item_desc#27] +Keys [4]: [i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24] +Functions [3]: [partial_sum(UnscaledValue(ss_net_profit#5)), partial_sum(UnscaledValue(sr_net_loss#11)), partial_sum(UnscaledValue(cs_net_profit#16))] +Aggregate Attributes [3]: [sum#28, sum#29, sum#30] +Results [7]: [i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24, sum#31, sum#32, sum#33] + +(38) Exchange +Input [7]: [i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24, sum#31, sum#32, sum#33] +Arguments: hashpartitioning(i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(39) HashAggregate [codegen id : 9] +Input [7]: [i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24, sum#31, sum#32, sum#33] +Keys [4]: [i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24] +Functions [3]: [sum(UnscaledValue(ss_net_profit#5)), sum(UnscaledValue(sr_net_loss#11)), sum(UnscaledValue(cs_net_profit#16))] +Aggregate Attributes [3]: [sum(UnscaledValue(ss_net_profit#5))#34, sum(UnscaledValue(sr_net_loss#11))#35, sum(UnscaledValue(cs_net_profit#16))#36] +Results [7]: [i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24, MakeDecimal(sum(UnscaledValue(ss_net_profit#5))#34,17,2) AS store_sales_profit#37, MakeDecimal(sum(UnscaledValue(sr_net_loss#11))#35,17,2) AS store_returns_loss#38, MakeDecimal(sum(UnscaledValue(cs_net_profit#16))#36,17,2) AS catalog_sales_profit#39] + +(40) TakeOrderedAndProject +Input [7]: [i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24, store_sales_profit#37, store_returns_loss#38, catalog_sales_profit#39] +Arguments: 100, [i_item_id#26 ASC NULLS FIRST, i_item_desc#27 ASC NULLS FIRST, s_store_id#23 ASC NULLS FIRST, s_store_name#24 ASC NULLS FIRST], [i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24, store_sales_profit#37, store_returns_loss#38, catalog_sales_profit#39] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#6 IN dynamicpruning#7 +BroadcastExchange (45) ++- * ColumnarToRow (44) + +- CometProject (43) + +- CometFilter (42) + +- CometScan parquet spark_catalog.default.date_dim (41) + + +(41) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#19, d_year#40, d_moy#41] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), EqualTo(d_moy,4), EqualTo(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(42) CometFilter +Input [3]: [d_date_sk#19, d_year#40, d_moy#41] +Condition : ((((isnotnull(d_moy#41) AND isnotnull(d_year#40)) AND (d_moy#41 = 4)) AND (d_year#40 = 2001)) AND isnotnull(d_date_sk#19)) + +(43) CometProject +Input [3]: [d_date_sk#19, d_year#40, d_moy#41] +Arguments: [d_date_sk#19], [d_date_sk#19] + +(44) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#19] + +(45) BroadcastExchange +Input [1]: [d_date_sk#19] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6] + +Subquery:2 Hosting operator id = 4 Hosting Expression = sr_returned_date_sk#12 IN dynamicpruning#13 +BroadcastExchange (50) ++- * ColumnarToRow (49) + +- CometProject (48) + +- CometFilter (47) + +- CometScan parquet spark_catalog.default.date_dim (46) + + +(46) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#20, d_year#42, d_moy#43] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), GreaterThanOrEqual(d_moy,4), LessThanOrEqual(d_moy,10), EqualTo(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(47) CometFilter +Input [3]: [d_date_sk#20, d_year#42, d_moy#43] +Condition : (((((isnotnull(d_moy#43) AND isnotnull(d_year#42)) AND (d_moy#43 >= 4)) AND (d_moy#43 <= 10)) AND (d_year#42 = 2001)) AND isnotnull(d_date_sk#20)) + +(48) CometProject +Input [3]: [d_date_sk#20, d_year#42, d_moy#43] +Arguments: [d_date_sk#20], [d_date_sk#20] + +(49) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#20] + +(50) BroadcastExchange +Input [1]: [d_date_sk#20] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +Subquery:3 Hosting operator id = 10 Hosting Expression = cs_sold_date_sk#17 IN dynamicpruning#13 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q25/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q25/simplified.txt new file mode 100644 index 0000000000..eda7f6b64d --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q25/simplified.txt @@ -0,0 +1,76 @@ +TakeOrderedAndProject [i_item_id,i_item_desc,s_store_id,s_store_name,store_sales_profit,store_returns_loss,catalog_sales_profit] + WholeStageCodegen (9) + HashAggregate [i_item_id,i_item_desc,s_store_id,s_store_name,sum,sum,sum] [sum(UnscaledValue(ss_net_profit)),sum(UnscaledValue(sr_net_loss)),sum(UnscaledValue(cs_net_profit)),store_sales_profit,store_returns_loss,catalog_sales_profit,sum,sum,sum] + InputAdapter + Exchange [i_item_id,i_item_desc,s_store_id,s_store_name] #1 + WholeStageCodegen (8) + HashAggregate [i_item_id,i_item_desc,s_store_id,s_store_name,ss_net_profit,sr_net_loss,cs_net_profit] [sum,sum,sum,sum,sum,sum] + Project [ss_net_profit,sr_net_loss,cs_net_profit,s_store_id,s_store_name,i_item_id,i_item_desc] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_net_profit,sr_net_loss,cs_net_profit,s_store_id,s_store_name] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_store_sk,ss_net_profit,sr_net_loss,cs_net_profit] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_store_sk,ss_net_profit,sr_net_loss,cs_net_profit,cs_sold_date_sk] + BroadcastHashJoin [sr_returned_date_sk,d_date_sk] + Project [ss_item_sk,ss_store_sk,ss_net_profit,sr_net_loss,sr_returned_date_sk,cs_net_profit,cs_sold_date_sk] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_store_sk,ss_net_profit,ss_sold_date_sk,sr_net_loss,sr_returned_date_sk,cs_net_profit,cs_sold_date_sk] + BroadcastHashJoin [sr_customer_sk,sr_item_sk,cs_bill_customer_sk,cs_item_sk] + Project [ss_item_sk,ss_store_sk,ss_net_profit,ss_sold_date_sk,sr_item_sk,sr_customer_sk,sr_net_loss,sr_returned_date_sk] + BroadcastHashJoin [ss_customer_sk,ss_item_sk,ss_ticket_number,sr_customer_sk,sr_item_sk,sr_ticket_number] + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk,ss_item_sk,ss_ticket_number,ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_net_profit,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_moy,d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [sr_customer_sk,sr_item_sk,sr_ticket_number] + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_customer_sk,sr_ticket_number,sr_net_loss,sr_returned_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_moy,d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [cs_bill_customer_sk,cs_item_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_item_sk,cs_net_profit,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (6) + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_id,s_store_name] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (7) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_item_desc] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q26/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q26/explain.txt new file mode 100644 index 0000000000..c90dcd0243 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q26/explain.txt @@ -0,0 +1,208 @@ +== Physical Plan == +TakeOrderedAndProject (30) ++- * HashAggregate (29) + +- Exchange (28) + +- * HashAggregate (27) + +- * Project (26) + +- * BroadcastHashJoin Inner BuildRight (25) + :- * Project (19) + : +- * BroadcastHashJoin Inner BuildRight (18) + : :- * Project (13) + : : +- * BroadcastHashJoin Inner BuildRight (12) + : : :- * Project (10) + : : : +- * BroadcastHashJoin Inner BuildRight (9) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) + : : : +- BroadcastExchange (8) + : : : +- * ColumnarToRow (7) + : : : +- CometProject (6) + : : : +- CometFilter (5) + : : : +- CometScan parquet spark_catalog.default.customer_demographics (4) + : : +- ReusedExchange (11) + : +- BroadcastExchange (17) + : +- * ColumnarToRow (16) + : +- CometFilter (15) + : +- CometScan parquet spark_catalog.default.item (14) + +- BroadcastExchange (24) + +- * ColumnarToRow (23) + +- CometProject (22) + +- CometFilter (21) + +- CometScan parquet spark_catalog.default.promotion (20) + + +(1) Scan parquet spark_catalog.default.catalog_sales +Output [8]: [cs_bill_cdemo_sk#1, cs_item_sk#2, cs_promo_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_sold_date_sk#8] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#8), dynamicpruningexpression(cs_sold_date_sk#8 IN dynamicpruning#9)] +PushedFilters: [IsNotNull(cs_bill_cdemo_sk), IsNotNull(cs_item_sk), IsNotNull(cs_promo_sk)] +ReadSchema: struct + +(2) CometFilter +Input [8]: [cs_bill_cdemo_sk#1, cs_item_sk#2, cs_promo_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_sold_date_sk#8] +Condition : ((isnotnull(cs_bill_cdemo_sk#1) AND isnotnull(cs_item_sk#2)) AND isnotnull(cs_promo_sk#3)) + +(3) ColumnarToRow [codegen id : 5] +Input [8]: [cs_bill_cdemo_sk#1, cs_item_sk#2, cs_promo_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_sold_date_sk#8] + +(4) Scan parquet spark_catalog.default.customer_demographics +Output [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_gender), IsNotNull(cd_marital_status), IsNotNull(cd_education_status), EqualTo(cd_gender,M), EqualTo(cd_marital_status,S), EqualTo(cd_education_status,College ), IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(5) CometFilter +Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] +Condition : ((((((isnotnull(cd_gender#11) AND isnotnull(cd_marital_status#12)) AND isnotnull(cd_education_status#13)) AND (cd_gender#11 = M)) AND (cd_marital_status#12 = S)) AND (cd_education_status#13 = College )) AND isnotnull(cd_demo_sk#10)) + +(6) CometProject +Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] +Arguments: [cd_demo_sk#10], [cd_demo_sk#10] + +(7) ColumnarToRow [codegen id : 1] +Input [1]: [cd_demo_sk#10] + +(8) BroadcastExchange +Input [1]: [cd_demo_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [cs_bill_cdemo_sk#1] +Right keys [1]: [cd_demo_sk#10] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 5] +Output [7]: [cs_item_sk#2, cs_promo_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_sold_date_sk#8] +Input [9]: [cs_bill_cdemo_sk#1, cs_item_sk#2, cs_promo_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_sold_date_sk#8, cd_demo_sk#10] + +(11) ReusedExchange [Reuses operator id: 35] +Output [1]: [d_date_sk#14] + +(12) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [cs_sold_date_sk#8] +Right keys [1]: [d_date_sk#14] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 5] +Output [6]: [cs_item_sk#2, cs_promo_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7] +Input [8]: [cs_item_sk#2, cs_promo_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_sold_date_sk#8, d_date_sk#14] + +(14) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#15, i_item_id#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(15) CometFilter +Input [2]: [i_item_sk#15, i_item_id#16] +Condition : isnotnull(i_item_sk#15) + +(16) ColumnarToRow [codegen id : 3] +Input [2]: [i_item_sk#15, i_item_id#16] + +(17) BroadcastExchange +Input [2]: [i_item_sk#15, i_item_id#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(18) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [cs_item_sk#2] +Right keys [1]: [i_item_sk#15] +Join type: Inner +Join condition: None + +(19) Project [codegen id : 5] +Output [6]: [cs_promo_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, i_item_id#16] +Input [8]: [cs_item_sk#2, cs_promo_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, i_item_sk#15, i_item_id#16] + +(20) Scan parquet spark_catalog.default.promotion +Output [3]: [p_promo_sk#17, p_channel_email#18, p_channel_event#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/promotion] +PushedFilters: [Or(EqualTo(p_channel_email,N),EqualTo(p_channel_event,N)), IsNotNull(p_promo_sk)] +ReadSchema: struct + +(21) CometFilter +Input [3]: [p_promo_sk#17, p_channel_email#18, p_channel_event#19] +Condition : (((p_channel_email#18 = N) OR (p_channel_event#19 = N)) AND isnotnull(p_promo_sk#17)) + +(22) CometProject +Input [3]: [p_promo_sk#17, p_channel_email#18, p_channel_event#19] +Arguments: [p_promo_sk#17], [p_promo_sk#17] + +(23) ColumnarToRow [codegen id : 4] +Input [1]: [p_promo_sk#17] + +(24) BroadcastExchange +Input [1]: [p_promo_sk#17] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(25) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [cs_promo_sk#3] +Right keys [1]: [p_promo_sk#17] +Join type: Inner +Join condition: None + +(26) Project [codegen id : 5] +Output [5]: [cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, i_item_id#16] +Input [7]: [cs_promo_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, i_item_id#16, p_promo_sk#17] + +(27) HashAggregate [codegen id : 5] +Input [5]: [cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, i_item_id#16] +Keys [1]: [i_item_id#16] +Functions [4]: [partial_avg(cs_quantity#4), partial_avg(UnscaledValue(cs_list_price#5)), partial_avg(UnscaledValue(cs_coupon_amt#7)), partial_avg(UnscaledValue(cs_sales_price#6))] +Aggregate Attributes [8]: [sum#20, count#21, sum#22, count#23, sum#24, count#25, sum#26, count#27] +Results [9]: [i_item_id#16, sum#28, count#29, sum#30, count#31, sum#32, count#33, sum#34, count#35] + +(28) Exchange +Input [9]: [i_item_id#16, sum#28, count#29, sum#30, count#31, sum#32, count#33, sum#34, count#35] +Arguments: hashpartitioning(i_item_id#16, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(29) HashAggregate [codegen id : 6] +Input [9]: [i_item_id#16, sum#28, count#29, sum#30, count#31, sum#32, count#33, sum#34, count#35] +Keys [1]: [i_item_id#16] +Functions [4]: [avg(cs_quantity#4), avg(UnscaledValue(cs_list_price#5)), avg(UnscaledValue(cs_coupon_amt#7)), avg(UnscaledValue(cs_sales_price#6))] +Aggregate Attributes [4]: [avg(cs_quantity#4)#36, avg(UnscaledValue(cs_list_price#5))#37, avg(UnscaledValue(cs_coupon_amt#7))#38, avg(UnscaledValue(cs_sales_price#6))#39] +Results [5]: [i_item_id#16, avg(cs_quantity#4)#36 AS agg1#40, cast((avg(UnscaledValue(cs_list_price#5))#37 / 100.0) as decimal(11,6)) AS agg2#41, cast((avg(UnscaledValue(cs_coupon_amt#7))#38 / 100.0) as decimal(11,6)) AS agg3#42, cast((avg(UnscaledValue(cs_sales_price#6))#39 / 100.0) as decimal(11,6)) AS agg4#43] + +(30) TakeOrderedAndProject +Input [5]: [i_item_id#16, agg1#40, agg2#41, agg3#42, agg4#43] +Arguments: 100, [i_item_id#16 ASC NULLS FIRST], [i_item_id#16, agg1#40, agg2#41, agg3#42, agg4#43] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#8 IN dynamicpruning#9 +BroadcastExchange (35) ++- * ColumnarToRow (34) + +- CometProject (33) + +- CometFilter (32) + +- CometScan parquet spark_catalog.default.date_dim (31) + + +(31) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#14, d_year#44] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2000), IsNotNull(d_date_sk)] +ReadSchema: struct + +(32) CometFilter +Input [2]: [d_date_sk#14, d_year#44] +Condition : ((isnotnull(d_year#44) AND (d_year#44 = 2000)) AND isnotnull(d_date_sk#14)) + +(33) CometProject +Input [2]: [d_date_sk#14, d_year#44] +Arguments: [d_date_sk#14], [d_date_sk#14] + +(34) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#14] + +(35) BroadcastExchange +Input [1]: [d_date_sk#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q26/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q26/simplified.txt new file mode 100644 index 0000000000..7d38936244 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q26/simplified.txt @@ -0,0 +1,52 @@ +TakeOrderedAndProject [i_item_id,agg1,agg2,agg3,agg4] + WholeStageCodegen (6) + HashAggregate [i_item_id,sum,count,sum,count,sum,count,sum,count] [avg(cs_quantity),avg(UnscaledValue(cs_list_price)),avg(UnscaledValue(cs_coupon_amt)),avg(UnscaledValue(cs_sales_price)),agg1,agg2,agg3,agg4,sum,count,sum,count,sum,count,sum,count] + InputAdapter + Exchange [i_item_id] #1 + WholeStageCodegen (5) + HashAggregate [i_item_id,cs_quantity,cs_list_price,cs_coupon_amt,cs_sales_price] [sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + Project [cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,i_item_id] + BroadcastHashJoin [cs_promo_sk,p_promo_sk] + Project [cs_promo_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,i_item_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Project [cs_item_sk,cs_promo_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_item_sk,cs_promo_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_sold_date_sk] + BroadcastHashJoin [cs_bill_cdemo_sk,cd_demo_sk] + ColumnarToRow + InputAdapter + CometFilter [cs_bill_cdemo_sk,cs_item_sk,cs_promo_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_cdemo_sk,cs_item_sk,cs_promo_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [cd_demo_sk] + CometFilter [cd_gender,cd_marital_status,cd_education_status,cd_demo_sk] + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_marital_status,cd_education_status] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (4) + ColumnarToRow + InputAdapter + CometProject [p_promo_sk] + CometFilter [p_channel_email,p_channel_event,p_promo_sk] + CometScan parquet spark_catalog.default.promotion [p_promo_sk,p_channel_email,p_channel_event] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q27/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q27/explain.txt new file mode 100644 index 0000000000..e41077ed30 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q27/explain.txt @@ -0,0 +1,208 @@ +== Physical Plan == +TakeOrderedAndProject (30) ++- * HashAggregate (29) + +- Exchange (28) + +- * HashAggregate (27) + +- * Expand (26) + +- * Project (25) + +- * BroadcastHashJoin Inner BuildRight (24) + :- * Project (19) + : +- * BroadcastHashJoin Inner BuildRight (18) + : :- * Project (13) + : : +- * BroadcastHashJoin Inner BuildRight (12) + : : :- * Project (10) + : : : +- * BroadcastHashJoin Inner BuildRight (9) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- BroadcastExchange (8) + : : : +- * ColumnarToRow (7) + : : : +- CometProject (6) + : : : +- CometFilter (5) + : : : +- CometScan parquet spark_catalog.default.customer_demographics (4) + : : +- ReusedExchange (11) + : +- BroadcastExchange (17) + : +- * ColumnarToRow (16) + : +- CometFilter (15) + : +- CometScan parquet spark_catalog.default.store (14) + +- BroadcastExchange (23) + +- * ColumnarToRow (22) + +- CometFilter (21) + +- CometScan parquet spark_catalog.default.item (20) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [8]: [ss_item_sk#1, ss_cdemo_sk#2, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#8), dynamicpruningexpression(ss_sold_date_sk#8 IN dynamicpruning#9)] +PushedFilters: [IsNotNull(ss_cdemo_sk), IsNotNull(ss_store_sk), IsNotNull(ss_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [8]: [ss_item_sk#1, ss_cdemo_sk#2, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8] +Condition : ((isnotnull(ss_cdemo_sk#2) AND isnotnull(ss_store_sk#3)) AND isnotnull(ss_item_sk#1)) + +(3) ColumnarToRow [codegen id : 5] +Input [8]: [ss_item_sk#1, ss_cdemo_sk#2, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8] + +(4) Scan parquet spark_catalog.default.customer_demographics +Output [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_gender), IsNotNull(cd_marital_status), IsNotNull(cd_education_status), EqualTo(cd_gender,M), EqualTo(cd_marital_status,S), EqualTo(cd_education_status,College ), IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(5) CometFilter +Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] +Condition : ((((((isnotnull(cd_gender#11) AND isnotnull(cd_marital_status#12)) AND isnotnull(cd_education_status#13)) AND (cd_gender#11 = M)) AND (cd_marital_status#12 = S)) AND (cd_education_status#13 = College )) AND isnotnull(cd_demo_sk#10)) + +(6) CometProject +Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] +Arguments: [cd_demo_sk#10], [cd_demo_sk#10] + +(7) ColumnarToRow [codegen id : 1] +Input [1]: [cd_demo_sk#10] + +(8) BroadcastExchange +Input [1]: [cd_demo_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_cdemo_sk#2] +Right keys [1]: [cd_demo_sk#10] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 5] +Output [7]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8] +Input [9]: [ss_item_sk#1, ss_cdemo_sk#2, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8, cd_demo_sk#10] + +(11) ReusedExchange [Reuses operator id: 35] +Output [1]: [d_date_sk#14] + +(12) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_sold_date_sk#8] +Right keys [1]: [d_date_sk#14] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 5] +Output [6]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7] +Input [8]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8, d_date_sk#14] + +(14) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#15, s_state#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_state), EqualTo(s_state,TN), IsNotNull(s_store_sk)] +ReadSchema: struct + +(15) CometFilter +Input [2]: [s_store_sk#15, s_state#16] +Condition : ((isnotnull(s_state#16) AND (s_state#16 = TN)) AND isnotnull(s_store_sk#15)) + +(16) ColumnarToRow [codegen id : 3] +Input [2]: [s_store_sk#15, s_state#16] + +(17) BroadcastExchange +Input [2]: [s_store_sk#15, s_state#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(18) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_store_sk#3] +Right keys [1]: [s_store_sk#15] +Join type: Inner +Join condition: None + +(19) Project [codegen id : 5] +Output [6]: [ss_item_sk#1, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, s_state#16] +Input [8]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, s_store_sk#15, s_state#16] + +(20) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#17, i_item_id#18] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(21) CometFilter +Input [2]: [i_item_sk#17, i_item_id#18] +Condition : isnotnull(i_item_sk#17) + +(22) ColumnarToRow [codegen id : 4] +Input [2]: [i_item_sk#17, i_item_id#18] + +(23) BroadcastExchange +Input [2]: [i_item_sk#17, i_item_id#18] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#17] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 5] +Output [6]: [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#18, s_state#16] +Input [8]: [ss_item_sk#1, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, s_state#16, i_item_sk#17, i_item_id#18] + +(26) Expand [codegen id : 5] +Input [6]: [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#18, s_state#16] +Arguments: [[ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#18, s_state#16, 0], [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#18, null, 1], [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, null, null, 3]], [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#19, s_state#20, spark_grouping_id#21] + +(27) HashAggregate [codegen id : 5] +Input [7]: [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#19, s_state#20, spark_grouping_id#21] +Keys [3]: [i_item_id#19, s_state#20, spark_grouping_id#21] +Functions [4]: [partial_avg(ss_quantity#4), partial_avg(UnscaledValue(ss_list_price#5)), partial_avg(UnscaledValue(ss_coupon_amt#7)), partial_avg(UnscaledValue(ss_sales_price#6))] +Aggregate Attributes [8]: [sum#22, count#23, sum#24, count#25, sum#26, count#27, sum#28, count#29] +Results [11]: [i_item_id#19, s_state#20, spark_grouping_id#21, sum#30, count#31, sum#32, count#33, sum#34, count#35, sum#36, count#37] + +(28) Exchange +Input [11]: [i_item_id#19, s_state#20, spark_grouping_id#21, sum#30, count#31, sum#32, count#33, sum#34, count#35, sum#36, count#37] +Arguments: hashpartitioning(i_item_id#19, s_state#20, spark_grouping_id#21, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(29) HashAggregate [codegen id : 6] +Input [11]: [i_item_id#19, s_state#20, spark_grouping_id#21, sum#30, count#31, sum#32, count#33, sum#34, count#35, sum#36, count#37] +Keys [3]: [i_item_id#19, s_state#20, spark_grouping_id#21] +Functions [4]: [avg(ss_quantity#4), avg(UnscaledValue(ss_list_price#5)), avg(UnscaledValue(ss_coupon_amt#7)), avg(UnscaledValue(ss_sales_price#6))] +Aggregate Attributes [4]: [avg(ss_quantity#4)#38, avg(UnscaledValue(ss_list_price#5))#39, avg(UnscaledValue(ss_coupon_amt#7))#40, avg(UnscaledValue(ss_sales_price#6))#41] +Results [7]: [i_item_id#19, s_state#20, cast((shiftright(spark_grouping_id#21, 0) & 1) as tinyint) AS g_state#42, avg(ss_quantity#4)#38 AS agg1#43, cast((avg(UnscaledValue(ss_list_price#5))#39 / 100.0) as decimal(11,6)) AS agg2#44, cast((avg(UnscaledValue(ss_coupon_amt#7))#40 / 100.0) as decimal(11,6)) AS agg3#45, cast((avg(UnscaledValue(ss_sales_price#6))#41 / 100.0) as decimal(11,6)) AS agg4#46] + +(30) TakeOrderedAndProject +Input [7]: [i_item_id#19, s_state#20, g_state#42, agg1#43, agg2#44, agg3#45, agg4#46] +Arguments: 100, [i_item_id#19 ASC NULLS FIRST, s_state#20 ASC NULLS FIRST], [i_item_id#19, s_state#20, g_state#42, agg1#43, agg2#44, agg3#45, agg4#46] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#8 IN dynamicpruning#9 +BroadcastExchange (35) ++- * ColumnarToRow (34) + +- CometProject (33) + +- CometFilter (32) + +- CometScan parquet spark_catalog.default.date_dim (31) + + +(31) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#14, d_year#47] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2002), IsNotNull(d_date_sk)] +ReadSchema: struct + +(32) CometFilter +Input [2]: [d_date_sk#14, d_year#47] +Condition : ((isnotnull(d_year#47) AND (d_year#47 = 2002)) AND isnotnull(d_date_sk#14)) + +(33) CometProject +Input [2]: [d_date_sk#14, d_year#47] +Arguments: [d_date_sk#14], [d_date_sk#14] + +(34) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#14] + +(35) BroadcastExchange +Input [1]: [d_date_sk#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q27/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q27/simplified.txt new file mode 100644 index 0000000000..9d073ff67c --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q27/simplified.txt @@ -0,0 +1,52 @@ +TakeOrderedAndProject [i_item_id,s_state,g_state,agg1,agg2,agg3,agg4] + WholeStageCodegen (6) + HashAggregate [i_item_id,s_state,spark_grouping_id,sum,count,sum,count,sum,count,sum,count] [avg(ss_quantity),avg(UnscaledValue(ss_list_price)),avg(UnscaledValue(ss_coupon_amt)),avg(UnscaledValue(ss_sales_price)),g_state,agg1,agg2,agg3,agg4,sum,count,sum,count,sum,count,sum,count] + InputAdapter + Exchange [i_item_id,s_state,spark_grouping_id] #1 + WholeStageCodegen (5) + HashAggregate [i_item_id,s_state,spark_grouping_id,ss_quantity,ss_list_price,ss_coupon_amt,ss_sales_price] [sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + Expand [ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,i_item_id,s_state] + Project [ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,i_item_id,s_state] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,s_state] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,ss_sold_date_sk] + BroadcastHashJoin [ss_cdemo_sk,cd_demo_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_cdemo_sk,ss_store_sk,ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_cdemo_sk,ss_store_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [cd_demo_sk] + CometFilter [cd_gender,cd_marital_status,cd_education_status,cd_demo_sk] + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_marital_status,cd_education_status] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometFilter [s_state,s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk,s_state] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (4) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q28/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q28/explain.txt new file mode 100644 index 0000000000..de4ab3a2c9 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q28/explain.txt @@ -0,0 +1,437 @@ +== Physical Plan == +* BroadcastNestedLoopJoin Inner BuildRight (70) +:- * BroadcastNestedLoopJoin Inner BuildRight (58) +: :- * BroadcastNestedLoopJoin Inner BuildRight (46) +: : :- * BroadcastNestedLoopJoin Inner BuildRight (34) +: : : :- * BroadcastNestedLoopJoin Inner BuildRight (22) +: : : : :- * HashAggregate (10) +: : : : : +- Exchange (9) +: : : : : +- * HashAggregate (8) +: : : : : +- * HashAggregate (7) +: : : : : +- Exchange (6) +: : : : : +- * HashAggregate (5) +: : : : : +- * ColumnarToRow (4) +: : : : : +- CometProject (3) +: : : : : +- CometFilter (2) +: : : : : +- CometScan parquet spark_catalog.default.store_sales (1) +: : : : +- BroadcastExchange (21) +: : : : +- * HashAggregate (20) +: : : : +- Exchange (19) +: : : : +- * HashAggregate (18) +: : : : +- * HashAggregate (17) +: : : : +- Exchange (16) +: : : : +- * HashAggregate (15) +: : : : +- * ColumnarToRow (14) +: : : : +- CometProject (13) +: : : : +- CometFilter (12) +: : : : +- CometScan parquet spark_catalog.default.store_sales (11) +: : : +- BroadcastExchange (33) +: : : +- * HashAggregate (32) +: : : +- Exchange (31) +: : : +- * HashAggregate (30) +: : : +- * HashAggregate (29) +: : : +- Exchange (28) +: : : +- * HashAggregate (27) +: : : +- * ColumnarToRow (26) +: : : +- CometProject (25) +: : : +- CometFilter (24) +: : : +- CometScan parquet spark_catalog.default.store_sales (23) +: : +- BroadcastExchange (45) +: : +- * HashAggregate (44) +: : +- Exchange (43) +: : +- * HashAggregate (42) +: : +- * HashAggregate (41) +: : +- Exchange (40) +: : +- * HashAggregate (39) +: : +- * ColumnarToRow (38) +: : +- CometProject (37) +: : +- CometFilter (36) +: : +- CometScan parquet spark_catalog.default.store_sales (35) +: +- BroadcastExchange (57) +: +- * HashAggregate (56) +: +- Exchange (55) +: +- * HashAggregate (54) +: +- * HashAggregate (53) +: +- Exchange (52) +: +- * HashAggregate (51) +: +- * ColumnarToRow (50) +: +- CometProject (49) +: +- CometFilter (48) +: +- CometScan parquet spark_catalog.default.store_sales (47) ++- BroadcastExchange (69) + +- * HashAggregate (68) + +- Exchange (67) + +- * HashAggregate (66) + +- * HashAggregate (65) + +- Exchange (64) + +- * HashAggregate (63) + +- * ColumnarToRow (62) + +- CometProject (61) + +- CometFilter (60) + +- CometScan parquet spark_catalog.default.store_sales (59) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_quantity#1, ss_wholesale_cost#2, ss_list_price#3, ss_coupon_amt#4, ss_sold_date_sk#5] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_quantity), GreaterThanOrEqual(ss_quantity,0), LessThanOrEqual(ss_quantity,5), Or(Or(And(GreaterThanOrEqual(ss_list_price,8.00),LessThanOrEqual(ss_list_price,18.00)),And(GreaterThanOrEqual(ss_coupon_amt,459.00),LessThanOrEqual(ss_coupon_amt,1459.00))),And(GreaterThanOrEqual(ss_wholesale_cost,57.00),LessThanOrEqual(ss_wholesale_cost,77.00)))] +ReadSchema: struct + +(2) CometFilter +Input [5]: [ss_quantity#1, ss_wholesale_cost#2, ss_list_price#3, ss_coupon_amt#4, ss_sold_date_sk#5] +Condition : (((isnotnull(ss_quantity#1) AND (ss_quantity#1 >= 0)) AND (ss_quantity#1 <= 5)) AND ((((ss_list_price#3 >= 8.00) AND (ss_list_price#3 <= 18.00)) OR ((ss_coupon_amt#4 >= 459.00) AND (ss_coupon_amt#4 <= 1459.00))) OR ((ss_wholesale_cost#2 >= 57.00) AND (ss_wholesale_cost#2 <= 77.00)))) + +(3) CometProject +Input [5]: [ss_quantity#1, ss_wholesale_cost#2, ss_list_price#3, ss_coupon_amt#4, ss_sold_date_sk#5] +Arguments: [ss_list_price#3], [ss_list_price#3] + +(4) ColumnarToRow [codegen id : 1] +Input [1]: [ss_list_price#3] + +(5) HashAggregate [codegen id : 1] +Input [1]: [ss_list_price#3] +Keys [1]: [ss_list_price#3] +Functions [2]: [partial_avg(UnscaledValue(ss_list_price#3)), partial_count(ss_list_price#3)] +Aggregate Attributes [2]: [avg(UnscaledValue(ss_list_price#3))#6, count(ss_list_price#3)#7] +Results [4]: [ss_list_price#3, sum#8, count#9, count#10] + +(6) Exchange +Input [4]: [ss_list_price#3, sum#8, count#9, count#10] +Arguments: hashpartitioning(ss_list_price#3, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(7) HashAggregate [codegen id : 2] +Input [4]: [ss_list_price#3, sum#8, count#9, count#10] +Keys [1]: [ss_list_price#3] +Functions [2]: [merge_avg(UnscaledValue(ss_list_price#3)), merge_count(ss_list_price#3)] +Aggregate Attributes [2]: [avg(UnscaledValue(ss_list_price#3))#6, count(ss_list_price#3)#7] +Results [4]: [ss_list_price#3, sum#8, count#9, count#10] + +(8) HashAggregate [codegen id : 2] +Input [4]: [ss_list_price#3, sum#8, count#9, count#10] +Keys: [] +Functions [3]: [merge_avg(UnscaledValue(ss_list_price#3)), merge_count(ss_list_price#3), partial_count(distinct ss_list_price#3)] +Aggregate Attributes [3]: [avg(UnscaledValue(ss_list_price#3))#6, count(ss_list_price#3)#7, count(ss_list_price#3)#11] +Results [4]: [sum#8, count#9, count#10, count#12] + +(9) Exchange +Input [4]: [sum#8, count#9, count#10, count#12] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=2] + +(10) HashAggregate [codegen id : 18] +Input [4]: [sum#8, count#9, count#10, count#12] +Keys: [] +Functions [3]: [avg(UnscaledValue(ss_list_price#3)), count(ss_list_price#3), count(distinct ss_list_price#3)] +Aggregate Attributes [3]: [avg(UnscaledValue(ss_list_price#3))#6, count(ss_list_price#3)#7, count(ss_list_price#3)#11] +Results [3]: [cast((avg(UnscaledValue(ss_list_price#3))#6 / 100.0) as decimal(11,6)) AS B1_LP#13, count(ss_list_price#3)#7 AS B1_CNT#14, count(ss_list_price#3)#11 AS B1_CNTD#15] + +(11) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_quantity#16, ss_wholesale_cost#17, ss_list_price#18, ss_coupon_amt#19, ss_sold_date_sk#20] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_quantity), GreaterThanOrEqual(ss_quantity,6), LessThanOrEqual(ss_quantity,10), Or(Or(And(GreaterThanOrEqual(ss_list_price,90.00),LessThanOrEqual(ss_list_price,100.00)),And(GreaterThanOrEqual(ss_coupon_amt,2323.00),LessThanOrEqual(ss_coupon_amt,3323.00))),And(GreaterThanOrEqual(ss_wholesale_cost,31.00),LessThanOrEqual(ss_wholesale_cost,51.00)))] +ReadSchema: struct + +(12) CometFilter +Input [5]: [ss_quantity#16, ss_wholesale_cost#17, ss_list_price#18, ss_coupon_amt#19, ss_sold_date_sk#20] +Condition : (((isnotnull(ss_quantity#16) AND (ss_quantity#16 >= 6)) AND (ss_quantity#16 <= 10)) AND ((((ss_list_price#18 >= 90.00) AND (ss_list_price#18 <= 100.00)) OR ((ss_coupon_amt#19 >= 2323.00) AND (ss_coupon_amt#19 <= 3323.00))) OR ((ss_wholesale_cost#17 >= 31.00) AND (ss_wholesale_cost#17 <= 51.00)))) + +(13) CometProject +Input [5]: [ss_quantity#16, ss_wholesale_cost#17, ss_list_price#18, ss_coupon_amt#19, ss_sold_date_sk#20] +Arguments: [ss_list_price#18], [ss_list_price#18] + +(14) ColumnarToRow [codegen id : 3] +Input [1]: [ss_list_price#18] + +(15) HashAggregate [codegen id : 3] +Input [1]: [ss_list_price#18] +Keys [1]: [ss_list_price#18] +Functions [2]: [partial_avg(UnscaledValue(ss_list_price#18)), partial_count(ss_list_price#18)] +Aggregate Attributes [2]: [avg(UnscaledValue(ss_list_price#18))#21, count(ss_list_price#18)#22] +Results [4]: [ss_list_price#18, sum#23, count#24, count#25] + +(16) Exchange +Input [4]: [ss_list_price#18, sum#23, count#24, count#25] +Arguments: hashpartitioning(ss_list_price#18, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(17) HashAggregate [codegen id : 4] +Input [4]: [ss_list_price#18, sum#23, count#24, count#25] +Keys [1]: [ss_list_price#18] +Functions [2]: [merge_avg(UnscaledValue(ss_list_price#18)), merge_count(ss_list_price#18)] +Aggregate Attributes [2]: [avg(UnscaledValue(ss_list_price#18))#21, count(ss_list_price#18)#22] +Results [4]: [ss_list_price#18, sum#23, count#24, count#25] + +(18) HashAggregate [codegen id : 4] +Input [4]: [ss_list_price#18, sum#23, count#24, count#25] +Keys: [] +Functions [3]: [merge_avg(UnscaledValue(ss_list_price#18)), merge_count(ss_list_price#18), partial_count(distinct ss_list_price#18)] +Aggregate Attributes [3]: [avg(UnscaledValue(ss_list_price#18))#21, count(ss_list_price#18)#22, count(ss_list_price#18)#26] +Results [4]: [sum#23, count#24, count#25, count#27] + +(19) Exchange +Input [4]: [sum#23, count#24, count#25, count#27] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=4] + +(20) HashAggregate [codegen id : 5] +Input [4]: [sum#23, count#24, count#25, count#27] +Keys: [] +Functions [3]: [avg(UnscaledValue(ss_list_price#18)), count(ss_list_price#18), count(distinct ss_list_price#18)] +Aggregate Attributes [3]: [avg(UnscaledValue(ss_list_price#18))#21, count(ss_list_price#18)#22, count(ss_list_price#18)#26] +Results [3]: [cast((avg(UnscaledValue(ss_list_price#18))#21 / 100.0) as decimal(11,6)) AS B2_LP#28, count(ss_list_price#18)#22 AS B2_CNT#29, count(ss_list_price#18)#26 AS B2_CNTD#30] + +(21) BroadcastExchange +Input [3]: [B2_LP#28, B2_CNT#29, B2_CNTD#30] +Arguments: IdentityBroadcastMode, [plan_id=5] + +(22) BroadcastNestedLoopJoin [codegen id : 18] +Join type: Inner +Join condition: None + +(23) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_quantity#31, ss_wholesale_cost#32, ss_list_price#33, ss_coupon_amt#34, ss_sold_date_sk#35] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_quantity), GreaterThanOrEqual(ss_quantity,11), LessThanOrEqual(ss_quantity,15), Or(Or(And(GreaterThanOrEqual(ss_list_price,142.00),LessThanOrEqual(ss_list_price,152.00)),And(GreaterThanOrEqual(ss_coupon_amt,12214.00),LessThanOrEqual(ss_coupon_amt,13214.00))),And(GreaterThanOrEqual(ss_wholesale_cost,79.00),LessThanOrEqual(ss_wholesale_cost,99.00)))] +ReadSchema: struct + +(24) CometFilter +Input [5]: [ss_quantity#31, ss_wholesale_cost#32, ss_list_price#33, ss_coupon_amt#34, ss_sold_date_sk#35] +Condition : (((isnotnull(ss_quantity#31) AND (ss_quantity#31 >= 11)) AND (ss_quantity#31 <= 15)) AND ((((ss_list_price#33 >= 142.00) AND (ss_list_price#33 <= 152.00)) OR ((ss_coupon_amt#34 >= 12214.00) AND (ss_coupon_amt#34 <= 13214.00))) OR ((ss_wholesale_cost#32 >= 79.00) AND (ss_wholesale_cost#32 <= 99.00)))) + +(25) CometProject +Input [5]: [ss_quantity#31, ss_wholesale_cost#32, ss_list_price#33, ss_coupon_amt#34, ss_sold_date_sk#35] +Arguments: [ss_list_price#33], [ss_list_price#33] + +(26) ColumnarToRow [codegen id : 6] +Input [1]: [ss_list_price#33] + +(27) HashAggregate [codegen id : 6] +Input [1]: [ss_list_price#33] +Keys [1]: [ss_list_price#33] +Functions [2]: [partial_avg(UnscaledValue(ss_list_price#33)), partial_count(ss_list_price#33)] +Aggregate Attributes [2]: [avg(UnscaledValue(ss_list_price#33))#36, count(ss_list_price#33)#37] +Results [4]: [ss_list_price#33, sum#38, count#39, count#40] + +(28) Exchange +Input [4]: [ss_list_price#33, sum#38, count#39, count#40] +Arguments: hashpartitioning(ss_list_price#33, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(29) HashAggregate [codegen id : 7] +Input [4]: [ss_list_price#33, sum#38, count#39, count#40] +Keys [1]: [ss_list_price#33] +Functions [2]: [merge_avg(UnscaledValue(ss_list_price#33)), merge_count(ss_list_price#33)] +Aggregate Attributes [2]: [avg(UnscaledValue(ss_list_price#33))#36, count(ss_list_price#33)#37] +Results [4]: [ss_list_price#33, sum#38, count#39, count#40] + +(30) HashAggregate [codegen id : 7] +Input [4]: [ss_list_price#33, sum#38, count#39, count#40] +Keys: [] +Functions [3]: [merge_avg(UnscaledValue(ss_list_price#33)), merge_count(ss_list_price#33), partial_count(distinct ss_list_price#33)] +Aggregate Attributes [3]: [avg(UnscaledValue(ss_list_price#33))#36, count(ss_list_price#33)#37, count(ss_list_price#33)#41] +Results [4]: [sum#38, count#39, count#40, count#42] + +(31) Exchange +Input [4]: [sum#38, count#39, count#40, count#42] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=7] + +(32) HashAggregate [codegen id : 8] +Input [4]: [sum#38, count#39, count#40, count#42] +Keys: [] +Functions [3]: [avg(UnscaledValue(ss_list_price#33)), count(ss_list_price#33), count(distinct ss_list_price#33)] +Aggregate Attributes [3]: [avg(UnscaledValue(ss_list_price#33))#36, count(ss_list_price#33)#37, count(ss_list_price#33)#41] +Results [3]: [cast((avg(UnscaledValue(ss_list_price#33))#36 / 100.0) as decimal(11,6)) AS B3_LP#43, count(ss_list_price#33)#37 AS B3_CNT#44, count(ss_list_price#33)#41 AS B3_CNTD#45] + +(33) BroadcastExchange +Input [3]: [B3_LP#43, B3_CNT#44, B3_CNTD#45] +Arguments: IdentityBroadcastMode, [plan_id=8] + +(34) BroadcastNestedLoopJoin [codegen id : 18] +Join type: Inner +Join condition: None + +(35) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_quantity#46, ss_wholesale_cost#47, ss_list_price#48, ss_coupon_amt#49, ss_sold_date_sk#50] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_quantity), GreaterThanOrEqual(ss_quantity,16), LessThanOrEqual(ss_quantity,20), Or(Or(And(GreaterThanOrEqual(ss_list_price,135.00),LessThanOrEqual(ss_list_price,145.00)),And(GreaterThanOrEqual(ss_coupon_amt,6071.00),LessThanOrEqual(ss_coupon_amt,7071.00))),And(GreaterThanOrEqual(ss_wholesale_cost,38.00),LessThanOrEqual(ss_wholesale_cost,58.00)))] +ReadSchema: struct + +(36) CometFilter +Input [5]: [ss_quantity#46, ss_wholesale_cost#47, ss_list_price#48, ss_coupon_amt#49, ss_sold_date_sk#50] +Condition : (((isnotnull(ss_quantity#46) AND (ss_quantity#46 >= 16)) AND (ss_quantity#46 <= 20)) AND ((((ss_list_price#48 >= 135.00) AND (ss_list_price#48 <= 145.00)) OR ((ss_coupon_amt#49 >= 6071.00) AND (ss_coupon_amt#49 <= 7071.00))) OR ((ss_wholesale_cost#47 >= 38.00) AND (ss_wholesale_cost#47 <= 58.00)))) + +(37) CometProject +Input [5]: [ss_quantity#46, ss_wholesale_cost#47, ss_list_price#48, ss_coupon_amt#49, ss_sold_date_sk#50] +Arguments: [ss_list_price#48], [ss_list_price#48] + +(38) ColumnarToRow [codegen id : 9] +Input [1]: [ss_list_price#48] + +(39) HashAggregate [codegen id : 9] +Input [1]: [ss_list_price#48] +Keys [1]: [ss_list_price#48] +Functions [2]: [partial_avg(UnscaledValue(ss_list_price#48)), partial_count(ss_list_price#48)] +Aggregate Attributes [2]: [avg(UnscaledValue(ss_list_price#48))#51, count(ss_list_price#48)#52] +Results [4]: [ss_list_price#48, sum#53, count#54, count#55] + +(40) Exchange +Input [4]: [ss_list_price#48, sum#53, count#54, count#55] +Arguments: hashpartitioning(ss_list_price#48, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(41) HashAggregate [codegen id : 10] +Input [4]: [ss_list_price#48, sum#53, count#54, count#55] +Keys [1]: [ss_list_price#48] +Functions [2]: [merge_avg(UnscaledValue(ss_list_price#48)), merge_count(ss_list_price#48)] +Aggregate Attributes [2]: [avg(UnscaledValue(ss_list_price#48))#51, count(ss_list_price#48)#52] +Results [4]: [ss_list_price#48, sum#53, count#54, count#55] + +(42) HashAggregate [codegen id : 10] +Input [4]: [ss_list_price#48, sum#53, count#54, count#55] +Keys: [] +Functions [3]: [merge_avg(UnscaledValue(ss_list_price#48)), merge_count(ss_list_price#48), partial_count(distinct ss_list_price#48)] +Aggregate Attributes [3]: [avg(UnscaledValue(ss_list_price#48))#51, count(ss_list_price#48)#52, count(ss_list_price#48)#56] +Results [4]: [sum#53, count#54, count#55, count#57] + +(43) Exchange +Input [4]: [sum#53, count#54, count#55, count#57] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=10] + +(44) HashAggregate [codegen id : 11] +Input [4]: [sum#53, count#54, count#55, count#57] +Keys: [] +Functions [3]: [avg(UnscaledValue(ss_list_price#48)), count(ss_list_price#48), count(distinct ss_list_price#48)] +Aggregate Attributes [3]: [avg(UnscaledValue(ss_list_price#48))#51, count(ss_list_price#48)#52, count(ss_list_price#48)#56] +Results [3]: [cast((avg(UnscaledValue(ss_list_price#48))#51 / 100.0) as decimal(11,6)) AS B4_LP#58, count(ss_list_price#48)#52 AS B4_CNT#59, count(ss_list_price#48)#56 AS B4_CNTD#60] + +(45) BroadcastExchange +Input [3]: [B4_LP#58, B4_CNT#59, B4_CNTD#60] +Arguments: IdentityBroadcastMode, [plan_id=11] + +(46) BroadcastNestedLoopJoin [codegen id : 18] +Join type: Inner +Join condition: None + +(47) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_quantity#61, ss_wholesale_cost#62, ss_list_price#63, ss_coupon_amt#64, ss_sold_date_sk#65] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_quantity), GreaterThanOrEqual(ss_quantity,21), LessThanOrEqual(ss_quantity,25), Or(Or(And(GreaterThanOrEqual(ss_list_price,122.00),LessThanOrEqual(ss_list_price,132.00)),And(GreaterThanOrEqual(ss_coupon_amt,836.00),LessThanOrEqual(ss_coupon_amt,1836.00))),And(GreaterThanOrEqual(ss_wholesale_cost,17.00),LessThanOrEqual(ss_wholesale_cost,37.00)))] +ReadSchema: struct + +(48) CometFilter +Input [5]: [ss_quantity#61, ss_wholesale_cost#62, ss_list_price#63, ss_coupon_amt#64, ss_sold_date_sk#65] +Condition : (((isnotnull(ss_quantity#61) AND (ss_quantity#61 >= 21)) AND (ss_quantity#61 <= 25)) AND ((((ss_list_price#63 >= 122.00) AND (ss_list_price#63 <= 132.00)) OR ((ss_coupon_amt#64 >= 836.00) AND (ss_coupon_amt#64 <= 1836.00))) OR ((ss_wholesale_cost#62 >= 17.00) AND (ss_wholesale_cost#62 <= 37.00)))) + +(49) CometProject +Input [5]: [ss_quantity#61, ss_wholesale_cost#62, ss_list_price#63, ss_coupon_amt#64, ss_sold_date_sk#65] +Arguments: [ss_list_price#63], [ss_list_price#63] + +(50) ColumnarToRow [codegen id : 12] +Input [1]: [ss_list_price#63] + +(51) HashAggregate [codegen id : 12] +Input [1]: [ss_list_price#63] +Keys [1]: [ss_list_price#63] +Functions [2]: [partial_avg(UnscaledValue(ss_list_price#63)), partial_count(ss_list_price#63)] +Aggregate Attributes [2]: [avg(UnscaledValue(ss_list_price#63))#66, count(ss_list_price#63)#67] +Results [4]: [ss_list_price#63, sum#68, count#69, count#70] + +(52) Exchange +Input [4]: [ss_list_price#63, sum#68, count#69, count#70] +Arguments: hashpartitioning(ss_list_price#63, 5), ENSURE_REQUIREMENTS, [plan_id=12] + +(53) HashAggregate [codegen id : 13] +Input [4]: [ss_list_price#63, sum#68, count#69, count#70] +Keys [1]: [ss_list_price#63] +Functions [2]: [merge_avg(UnscaledValue(ss_list_price#63)), merge_count(ss_list_price#63)] +Aggregate Attributes [2]: [avg(UnscaledValue(ss_list_price#63))#66, count(ss_list_price#63)#67] +Results [4]: [ss_list_price#63, sum#68, count#69, count#70] + +(54) HashAggregate [codegen id : 13] +Input [4]: [ss_list_price#63, sum#68, count#69, count#70] +Keys: [] +Functions [3]: [merge_avg(UnscaledValue(ss_list_price#63)), merge_count(ss_list_price#63), partial_count(distinct ss_list_price#63)] +Aggregate Attributes [3]: [avg(UnscaledValue(ss_list_price#63))#66, count(ss_list_price#63)#67, count(ss_list_price#63)#71] +Results [4]: [sum#68, count#69, count#70, count#72] + +(55) Exchange +Input [4]: [sum#68, count#69, count#70, count#72] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=13] + +(56) HashAggregate [codegen id : 14] +Input [4]: [sum#68, count#69, count#70, count#72] +Keys: [] +Functions [3]: [avg(UnscaledValue(ss_list_price#63)), count(ss_list_price#63), count(distinct ss_list_price#63)] +Aggregate Attributes [3]: [avg(UnscaledValue(ss_list_price#63))#66, count(ss_list_price#63)#67, count(ss_list_price#63)#71] +Results [3]: [cast((avg(UnscaledValue(ss_list_price#63))#66 / 100.0) as decimal(11,6)) AS B5_LP#73, count(ss_list_price#63)#67 AS B5_CNT#74, count(ss_list_price#63)#71 AS B5_CNTD#75] + +(57) BroadcastExchange +Input [3]: [B5_LP#73, B5_CNT#74, B5_CNTD#75] +Arguments: IdentityBroadcastMode, [plan_id=14] + +(58) BroadcastNestedLoopJoin [codegen id : 18] +Join type: Inner +Join condition: None + +(59) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_quantity#76, ss_wholesale_cost#77, ss_list_price#78, ss_coupon_amt#79, ss_sold_date_sk#80] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_quantity), GreaterThanOrEqual(ss_quantity,26), LessThanOrEqual(ss_quantity,30), Or(Or(And(GreaterThanOrEqual(ss_list_price,154.00),LessThanOrEqual(ss_list_price,164.00)),And(GreaterThanOrEqual(ss_coupon_amt,7326.00),LessThanOrEqual(ss_coupon_amt,8326.00))),And(GreaterThanOrEqual(ss_wholesale_cost,7.00),LessThanOrEqual(ss_wholesale_cost,27.00)))] +ReadSchema: struct + +(60) CometFilter +Input [5]: [ss_quantity#76, ss_wholesale_cost#77, ss_list_price#78, ss_coupon_amt#79, ss_sold_date_sk#80] +Condition : (((isnotnull(ss_quantity#76) AND (ss_quantity#76 >= 26)) AND (ss_quantity#76 <= 30)) AND ((((ss_list_price#78 >= 154.00) AND (ss_list_price#78 <= 164.00)) OR ((ss_coupon_amt#79 >= 7326.00) AND (ss_coupon_amt#79 <= 8326.00))) OR ((ss_wholesale_cost#77 >= 7.00) AND (ss_wholesale_cost#77 <= 27.00)))) + +(61) CometProject +Input [5]: [ss_quantity#76, ss_wholesale_cost#77, ss_list_price#78, ss_coupon_amt#79, ss_sold_date_sk#80] +Arguments: [ss_list_price#78], [ss_list_price#78] + +(62) ColumnarToRow [codegen id : 15] +Input [1]: [ss_list_price#78] + +(63) HashAggregate [codegen id : 15] +Input [1]: [ss_list_price#78] +Keys [1]: [ss_list_price#78] +Functions [2]: [partial_avg(UnscaledValue(ss_list_price#78)), partial_count(ss_list_price#78)] +Aggregate Attributes [2]: [avg(UnscaledValue(ss_list_price#78))#81, count(ss_list_price#78)#82] +Results [4]: [ss_list_price#78, sum#83, count#84, count#85] + +(64) Exchange +Input [4]: [ss_list_price#78, sum#83, count#84, count#85] +Arguments: hashpartitioning(ss_list_price#78, 5), ENSURE_REQUIREMENTS, [plan_id=15] + +(65) HashAggregate [codegen id : 16] +Input [4]: [ss_list_price#78, sum#83, count#84, count#85] +Keys [1]: [ss_list_price#78] +Functions [2]: [merge_avg(UnscaledValue(ss_list_price#78)), merge_count(ss_list_price#78)] +Aggregate Attributes [2]: [avg(UnscaledValue(ss_list_price#78))#81, count(ss_list_price#78)#82] +Results [4]: [ss_list_price#78, sum#83, count#84, count#85] + +(66) HashAggregate [codegen id : 16] +Input [4]: [ss_list_price#78, sum#83, count#84, count#85] +Keys: [] +Functions [3]: [merge_avg(UnscaledValue(ss_list_price#78)), merge_count(ss_list_price#78), partial_count(distinct ss_list_price#78)] +Aggregate Attributes [3]: [avg(UnscaledValue(ss_list_price#78))#81, count(ss_list_price#78)#82, count(ss_list_price#78)#86] +Results [4]: [sum#83, count#84, count#85, count#87] + +(67) Exchange +Input [4]: [sum#83, count#84, count#85, count#87] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=16] + +(68) HashAggregate [codegen id : 17] +Input [4]: [sum#83, count#84, count#85, count#87] +Keys: [] +Functions [3]: [avg(UnscaledValue(ss_list_price#78)), count(ss_list_price#78), count(distinct ss_list_price#78)] +Aggregate Attributes [3]: [avg(UnscaledValue(ss_list_price#78))#81, count(ss_list_price#78)#82, count(ss_list_price#78)#86] +Results [3]: [cast((avg(UnscaledValue(ss_list_price#78))#81 / 100.0) as decimal(11,6)) AS B6_LP#88, count(ss_list_price#78)#82 AS B6_CNT#89, count(ss_list_price#78)#86 AS B6_CNTD#90] + +(69) BroadcastExchange +Input [3]: [B6_LP#88, B6_CNT#89, B6_CNTD#90] +Arguments: IdentityBroadcastMode, [plan_id=17] + +(70) BroadcastNestedLoopJoin [codegen id : 18] +Join type: Inner +Join condition: None + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q28/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q28/simplified.txt new file mode 100644 index 0000000000..a7a3f9537e --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q28/simplified.txt @@ -0,0 +1,111 @@ +WholeStageCodegen (18) + BroadcastNestedLoopJoin + BroadcastNestedLoopJoin + BroadcastNestedLoopJoin + BroadcastNestedLoopJoin + BroadcastNestedLoopJoin + HashAggregate [sum,count,count,count] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),count(ss_list_price),B1_LP,B1_CNT,B1_CNTD,sum,count,count,count] + InputAdapter + Exchange #1 + WholeStageCodegen (2) + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),count(ss_list_price),sum,count,count,count,sum,count,count,count] + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),sum,count,count,sum,count,count] + InputAdapter + Exchange [ss_list_price] #2 + WholeStageCodegen (1) + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),sum,count,count,sum,count,count] + ColumnarToRow + InputAdapter + CometProject [ss_list_price] + CometFilter [ss_quantity,ss_list_price,ss_coupon_amt,ss_wholesale_cost] + CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (5) + HashAggregate [sum,count,count,count] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),count(ss_list_price),B2_LP,B2_CNT,B2_CNTD,sum,count,count,count] + InputAdapter + Exchange #4 + WholeStageCodegen (4) + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),count(ss_list_price),sum,count,count,count,sum,count,count,count] + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),sum,count,count,sum,count,count] + InputAdapter + Exchange [ss_list_price] #5 + WholeStageCodegen (3) + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),sum,count,count,sum,count,count] + ColumnarToRow + InputAdapter + CometProject [ss_list_price] + CometFilter [ss_quantity,ss_list_price,ss_coupon_amt,ss_wholesale_cost] + CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (8) + HashAggregate [sum,count,count,count] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),count(ss_list_price),B3_LP,B3_CNT,B3_CNTD,sum,count,count,count] + InputAdapter + Exchange #7 + WholeStageCodegen (7) + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),count(ss_list_price),sum,count,count,count,sum,count,count,count] + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),sum,count,count,sum,count,count] + InputAdapter + Exchange [ss_list_price] #8 + WholeStageCodegen (6) + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),sum,count,count,sum,count,count] + ColumnarToRow + InputAdapter + CometProject [ss_list_price] + CometFilter [ss_quantity,ss_list_price,ss_coupon_amt,ss_wholesale_cost] + CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + InputAdapter + BroadcastExchange #9 + WholeStageCodegen (11) + HashAggregate [sum,count,count,count] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),count(ss_list_price),B4_LP,B4_CNT,B4_CNTD,sum,count,count,count] + InputAdapter + Exchange #10 + WholeStageCodegen (10) + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),count(ss_list_price),sum,count,count,count,sum,count,count,count] + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),sum,count,count,sum,count,count] + InputAdapter + Exchange [ss_list_price] #11 + WholeStageCodegen (9) + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),sum,count,count,sum,count,count] + ColumnarToRow + InputAdapter + CometProject [ss_list_price] + CometFilter [ss_quantity,ss_list_price,ss_coupon_amt,ss_wholesale_cost] + CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + InputAdapter + BroadcastExchange #12 + WholeStageCodegen (14) + HashAggregate [sum,count,count,count] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),count(ss_list_price),B5_LP,B5_CNT,B5_CNTD,sum,count,count,count] + InputAdapter + Exchange #13 + WholeStageCodegen (13) + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),count(ss_list_price),sum,count,count,count,sum,count,count,count] + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),sum,count,count,sum,count,count] + InputAdapter + Exchange [ss_list_price] #14 + WholeStageCodegen (12) + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),sum,count,count,sum,count,count] + ColumnarToRow + InputAdapter + CometProject [ss_list_price] + CometFilter [ss_quantity,ss_list_price,ss_coupon_amt,ss_wholesale_cost] + CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + InputAdapter + BroadcastExchange #15 + WholeStageCodegen (17) + HashAggregate [sum,count,count,count] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),count(ss_list_price),B6_LP,B6_CNT,B6_CNTD,sum,count,count,count] + InputAdapter + Exchange #16 + WholeStageCodegen (16) + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),count(ss_list_price),sum,count,count,count,sum,count,count,count] + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),sum,count,count,sum,count,count] + InputAdapter + Exchange [ss_list_price] #17 + WholeStageCodegen (15) + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),sum,count,count,sum,count,count] + ColumnarToRow + InputAdapter + CometProject [ss_list_price] + CometFilter [ss_quantity,ss_list_price,ss_coupon_amt,ss_wholesale_cost] + CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q29/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q29/explain.txt new file mode 100644 index 0000000000..522754cbc0 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q29/explain.txt @@ -0,0 +1,326 @@ +== Physical Plan == +TakeOrderedAndProject (40) ++- * HashAggregate (39) + +- Exchange (38) + +- * HashAggregate (37) + +- * Project (36) + +- * BroadcastHashJoin Inner BuildRight (35) + :- * Project (30) + : +- * BroadcastHashJoin Inner BuildRight (29) + : :- * Project (24) + : : +- * BroadcastHashJoin Inner BuildRight (23) + : : :- * Project (21) + : : : +- * BroadcastHashJoin Inner BuildRight (20) + : : : :- * Project (18) + : : : : +- * BroadcastHashJoin Inner BuildRight (17) + : : : : :- * Project (15) + : : : : : +- * BroadcastHashJoin Inner BuildRight (14) + : : : : : :- * Project (9) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : : : :- * ColumnarToRow (3) + : : : : : : : +- CometFilter (2) + : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : : : +- BroadcastExchange (7) + : : : : : : +- * ColumnarToRow (6) + : : : : : : +- CometFilter (5) + : : : : : : +- CometScan parquet spark_catalog.default.store_returns (4) + : : : : : +- BroadcastExchange (13) + : : : : : +- * ColumnarToRow (12) + : : : : : +- CometFilter (11) + : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (10) + : : : : +- ReusedExchange (16) + : : : +- ReusedExchange (19) + : : +- ReusedExchange (22) + : +- BroadcastExchange (28) + : +- * ColumnarToRow (27) + : +- CometFilter (26) + : +- CometScan parquet spark_catalog.default.store (25) + +- BroadcastExchange (34) + +- * ColumnarToRow (33) + +- CometFilter (32) + +- CometScan parquet spark_catalog.default.item (31) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_quantity#5, ss_sold_date_sk#6] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#6), dynamicpruningexpression(ss_sold_date_sk#6 IN dynamicpruning#7)] +PushedFilters: [IsNotNull(ss_customer_sk), IsNotNull(ss_item_sk), IsNotNull(ss_ticket_number), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(2) CometFilter +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_quantity#5, ss_sold_date_sk#6] +Condition : (((isnotnull(ss_customer_sk#2) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_ticket_number#4)) AND isnotnull(ss_store_sk#3)) + +(3) ColumnarToRow [codegen id : 8] +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_quantity#5, ss_sold_date_sk#6] + +(4) Scan parquet spark_catalog.default.store_returns +Output [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_return_quantity#11, sr_returned_date_sk#12] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(sr_returned_date_sk#12), dynamicpruningexpression(sr_returned_date_sk#12 IN dynamicpruning#13)] +PushedFilters: [IsNotNull(sr_customer_sk), IsNotNull(sr_item_sk), IsNotNull(sr_ticket_number)] +ReadSchema: struct + +(5) CometFilter +Input [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_return_quantity#11, sr_returned_date_sk#12] +Condition : ((isnotnull(sr_customer_sk#9) AND isnotnull(sr_item_sk#8)) AND isnotnull(sr_ticket_number#10)) + +(6) ColumnarToRow [codegen id : 1] +Input [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_return_quantity#11, sr_returned_date_sk#12] + +(7) BroadcastExchange +Input [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_return_quantity#11, sr_returned_date_sk#12] +Arguments: HashedRelationBroadcastMode(List(input[1, int, false], input[0, int, false], input[2, int, false]),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 8] +Left keys [3]: [ss_customer_sk#2, ss_item_sk#1, ss_ticket_number#4] +Right keys [3]: [sr_customer_sk#9, sr_item_sk#8, sr_ticket_number#10] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 8] +Output [8]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, ss_sold_date_sk#6, sr_item_sk#8, sr_customer_sk#9, sr_return_quantity#11, sr_returned_date_sk#12] +Input [11]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_quantity#5, ss_sold_date_sk#6, sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_return_quantity#11, sr_returned_date_sk#12] + +(10) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_quantity#16, cs_sold_date_sk#17] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#17), dynamicpruningexpression(cs_sold_date_sk#17 IN dynamicpruning#18)] +PushedFilters: [IsNotNull(cs_bill_customer_sk), IsNotNull(cs_item_sk)] +ReadSchema: struct + +(11) CometFilter +Input [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_quantity#16, cs_sold_date_sk#17] +Condition : (isnotnull(cs_bill_customer_sk#14) AND isnotnull(cs_item_sk#15)) + +(12) ColumnarToRow [codegen id : 2] +Input [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_quantity#16, cs_sold_date_sk#17] + +(13) BroadcastExchange +Input [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_quantity#16, cs_sold_date_sk#17] +Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[0, int, false] as bigint), 32) | (cast(input[1, int, false] as bigint) & 4294967295))),false), [plan_id=2] + +(14) BroadcastHashJoin [codegen id : 8] +Left keys [2]: [sr_customer_sk#9, sr_item_sk#8] +Right keys [2]: [cs_bill_customer_sk#14, cs_item_sk#15] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 8] +Output [8]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, ss_sold_date_sk#6, sr_return_quantity#11, sr_returned_date_sk#12, cs_quantity#16, cs_sold_date_sk#17] +Input [12]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, ss_sold_date_sk#6, sr_item_sk#8, sr_customer_sk#9, sr_return_quantity#11, sr_returned_date_sk#12, cs_bill_customer_sk#14, cs_item_sk#15, cs_quantity#16, cs_sold_date_sk#17] + +(16) ReusedExchange [Reuses operator id: 45] +Output [1]: [d_date_sk#19] + +(17) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_sold_date_sk#6] +Right keys [1]: [d_date_sk#19] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 8] +Output [7]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, sr_returned_date_sk#12, cs_quantity#16, cs_sold_date_sk#17] +Input [9]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, ss_sold_date_sk#6, sr_return_quantity#11, sr_returned_date_sk#12, cs_quantity#16, cs_sold_date_sk#17, d_date_sk#19] + +(19) ReusedExchange [Reuses operator id: 50] +Output [1]: [d_date_sk#20] + +(20) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [sr_returned_date_sk#12] +Right keys [1]: [d_date_sk#20] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 8] +Output [6]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, cs_quantity#16, cs_sold_date_sk#17] +Input [8]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, sr_returned_date_sk#12, cs_quantity#16, cs_sold_date_sk#17, d_date_sk#20] + +(22) ReusedExchange [Reuses operator id: 55] +Output [1]: [d_date_sk#21] + +(23) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [cs_sold_date_sk#17] +Right keys [1]: [d_date_sk#21] +Join type: Inner +Join condition: None + +(24) Project [codegen id : 8] +Output [5]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, cs_quantity#16] +Input [7]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, cs_quantity#16, cs_sold_date_sk#17, d_date_sk#21] + +(25) Scan parquet spark_catalog.default.store +Output [3]: [s_store_sk#22, s_store_id#23, s_store_name#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(26) CometFilter +Input [3]: [s_store_sk#22, s_store_id#23, s_store_name#24] +Condition : isnotnull(s_store_sk#22) + +(27) ColumnarToRow [codegen id : 6] +Input [3]: [s_store_sk#22, s_store_id#23, s_store_name#24] + +(28) BroadcastExchange +Input [3]: [s_store_sk#22, s_store_id#23, s_store_name#24] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(29) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_store_sk#3] +Right keys [1]: [s_store_sk#22] +Join type: Inner +Join condition: None + +(30) Project [codegen id : 8] +Output [6]: [ss_item_sk#1, ss_quantity#5, sr_return_quantity#11, cs_quantity#16, s_store_id#23, s_store_name#24] +Input [8]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, cs_quantity#16, s_store_sk#22, s_store_id#23, s_store_name#24] + +(31) Scan parquet spark_catalog.default.item +Output [3]: [i_item_sk#25, i_item_id#26, i_item_desc#27] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(32) CometFilter +Input [3]: [i_item_sk#25, i_item_id#26, i_item_desc#27] +Condition : isnotnull(i_item_sk#25) + +(33) ColumnarToRow [codegen id : 7] +Input [3]: [i_item_sk#25, i_item_id#26, i_item_desc#27] + +(34) BroadcastExchange +Input [3]: [i_item_sk#25, i_item_id#26, i_item_desc#27] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(35) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#25] +Join type: Inner +Join condition: None + +(36) Project [codegen id : 8] +Output [7]: [ss_quantity#5, sr_return_quantity#11, cs_quantity#16, s_store_id#23, s_store_name#24, i_item_id#26, i_item_desc#27] +Input [9]: [ss_item_sk#1, ss_quantity#5, sr_return_quantity#11, cs_quantity#16, s_store_id#23, s_store_name#24, i_item_sk#25, i_item_id#26, i_item_desc#27] + +(37) HashAggregate [codegen id : 8] +Input [7]: [ss_quantity#5, sr_return_quantity#11, cs_quantity#16, s_store_id#23, s_store_name#24, i_item_id#26, i_item_desc#27] +Keys [4]: [i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24] +Functions [3]: [partial_sum(ss_quantity#5), partial_sum(sr_return_quantity#11), partial_sum(cs_quantity#16)] +Aggregate Attributes [3]: [sum#28, sum#29, sum#30] +Results [7]: [i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24, sum#31, sum#32, sum#33] + +(38) Exchange +Input [7]: [i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24, sum#31, sum#32, sum#33] +Arguments: hashpartitioning(i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(39) HashAggregate [codegen id : 9] +Input [7]: [i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24, sum#31, sum#32, sum#33] +Keys [4]: [i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24] +Functions [3]: [sum(ss_quantity#5), sum(sr_return_quantity#11), sum(cs_quantity#16)] +Aggregate Attributes [3]: [sum(ss_quantity#5)#34, sum(sr_return_quantity#11)#35, sum(cs_quantity#16)#36] +Results [7]: [i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24, sum(ss_quantity#5)#34 AS store_sales_quantity#37, sum(sr_return_quantity#11)#35 AS store_returns_quantity#38, sum(cs_quantity#16)#36 AS catalog_sales_quantity#39] + +(40) TakeOrderedAndProject +Input [7]: [i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24, store_sales_quantity#37, store_returns_quantity#38, catalog_sales_quantity#39] +Arguments: 100, [i_item_id#26 ASC NULLS FIRST, i_item_desc#27 ASC NULLS FIRST, s_store_id#23 ASC NULLS FIRST, s_store_name#24 ASC NULLS FIRST], [i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24, store_sales_quantity#37, store_returns_quantity#38, catalog_sales_quantity#39] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#6 IN dynamicpruning#7 +BroadcastExchange (45) ++- * ColumnarToRow (44) + +- CometProject (43) + +- CometFilter (42) + +- CometScan parquet spark_catalog.default.date_dim (41) + + +(41) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#19, d_year#40, d_moy#41] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), EqualTo(d_moy,9), EqualTo(d_year,1999), IsNotNull(d_date_sk)] +ReadSchema: struct + +(42) CometFilter +Input [3]: [d_date_sk#19, d_year#40, d_moy#41] +Condition : ((((isnotnull(d_moy#41) AND isnotnull(d_year#40)) AND (d_moy#41 = 9)) AND (d_year#40 = 1999)) AND isnotnull(d_date_sk#19)) + +(43) CometProject +Input [3]: [d_date_sk#19, d_year#40, d_moy#41] +Arguments: [d_date_sk#19], [d_date_sk#19] + +(44) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#19] + +(45) BroadcastExchange +Input [1]: [d_date_sk#19] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6] + +Subquery:2 Hosting operator id = 4 Hosting Expression = sr_returned_date_sk#12 IN dynamicpruning#13 +BroadcastExchange (50) ++- * ColumnarToRow (49) + +- CometProject (48) + +- CometFilter (47) + +- CometScan parquet spark_catalog.default.date_dim (46) + + +(46) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#20, d_year#42, d_moy#43] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), GreaterThanOrEqual(d_moy,9), LessThanOrEqual(d_moy,12), EqualTo(d_year,1999), IsNotNull(d_date_sk)] +ReadSchema: struct + +(47) CometFilter +Input [3]: [d_date_sk#20, d_year#42, d_moy#43] +Condition : (((((isnotnull(d_moy#43) AND isnotnull(d_year#42)) AND (d_moy#43 >= 9)) AND (d_moy#43 <= 12)) AND (d_year#42 = 1999)) AND isnotnull(d_date_sk#20)) + +(48) CometProject +Input [3]: [d_date_sk#20, d_year#42, d_moy#43] +Arguments: [d_date_sk#20], [d_date_sk#20] + +(49) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#20] + +(50) BroadcastExchange +Input [1]: [d_date_sk#20] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +Subquery:3 Hosting operator id = 10 Hosting Expression = cs_sold_date_sk#17 IN dynamicpruning#18 +BroadcastExchange (55) ++- * ColumnarToRow (54) + +- CometProject (53) + +- CometFilter (52) + +- CometScan parquet spark_catalog.default.date_dim (51) + + +(51) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#21, d_year#44] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [In(d_year, [1999,2000,2001]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(52) CometFilter +Input [2]: [d_date_sk#21, d_year#44] +Condition : (d_year#44 IN (1999,2000,2001) AND isnotnull(d_date_sk#21)) + +(53) CometProject +Input [2]: [d_date_sk#21, d_year#44] +Arguments: [d_date_sk#21], [d_date_sk#21] + +(54) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#21] + +(55) BroadcastExchange +Input [1]: [d_date_sk#21] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q29/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q29/simplified.txt new file mode 100644 index 0000000000..68a127d357 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q29/simplified.txt @@ -0,0 +1,83 @@ +TakeOrderedAndProject [i_item_id,i_item_desc,s_store_id,s_store_name,store_sales_quantity,store_returns_quantity,catalog_sales_quantity] + WholeStageCodegen (9) + HashAggregate [i_item_id,i_item_desc,s_store_id,s_store_name,sum,sum,sum] [sum(ss_quantity),sum(sr_return_quantity),sum(cs_quantity),store_sales_quantity,store_returns_quantity,catalog_sales_quantity,sum,sum,sum] + InputAdapter + Exchange [i_item_id,i_item_desc,s_store_id,s_store_name] #1 + WholeStageCodegen (8) + HashAggregate [i_item_id,i_item_desc,s_store_id,s_store_name,ss_quantity,sr_return_quantity,cs_quantity] [sum,sum,sum,sum,sum,sum] + Project [ss_quantity,sr_return_quantity,cs_quantity,s_store_id,s_store_name,i_item_id,i_item_desc] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_quantity,sr_return_quantity,cs_quantity,s_store_id,s_store_name] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,sr_return_quantity,cs_quantity] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,sr_return_quantity,cs_quantity,cs_sold_date_sk] + BroadcastHashJoin [sr_returned_date_sk,d_date_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,sr_return_quantity,sr_returned_date_sk,cs_quantity,cs_sold_date_sk] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,ss_sold_date_sk,sr_return_quantity,sr_returned_date_sk,cs_quantity,cs_sold_date_sk] + BroadcastHashJoin [sr_customer_sk,sr_item_sk,cs_bill_customer_sk,cs_item_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,ss_sold_date_sk,sr_item_sk,sr_customer_sk,sr_return_quantity,sr_returned_date_sk] + BroadcastHashJoin [ss_customer_sk,ss_item_sk,ss_ticket_number,sr_customer_sk,sr_item_sk,sr_ticket_number] + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk,ss_item_sk,ss_ticket_number,ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_quantity,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_moy,d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [sr_customer_sk,sr_item_sk,sr_ticket_number] + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_customer_sk,sr_ticket_number,sr_return_quantity,sr_returned_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_moy,d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [cs_bill_customer_sk,cs_item_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #3 + BroadcastExchange #6 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + ReusedExchange [d_date_sk] #6 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (6) + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_id,s_store_name] + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (7) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_item_desc] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q3/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q3/explain.txt new file mode 100644 index 0000000000..e89cfe1fff --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q3/explain.txt @@ -0,0 +1,125 @@ +== Physical Plan == +TakeOrderedAndProject (21) ++- * HashAggregate (20) + +- Exchange (19) + +- * HashAggregate (18) + +- * Project (17) + +- * BroadcastHashJoin Inner BuildRight (16) + :- * Project (10) + : +- * BroadcastHashJoin Inner BuildRight (9) + : :- * ColumnarToRow (4) + : : +- CometProject (3) + : : +- CometFilter (2) + : : +- CometScan parquet spark_catalog.default.date_dim (1) + : +- BroadcastExchange (8) + : +- * ColumnarToRow (7) + : +- CometFilter (6) + : +- CometScan parquet spark_catalog.default.store_sales (5) + +- BroadcastExchange (15) + +- * ColumnarToRow (14) + +- CometProject (13) + +- CometFilter (12) + +- CometScan parquet spark_catalog.default.item (11) + + +(1) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#1, d_year#2, d_moy#3] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_moy), EqualTo(d_moy,11), IsNotNull(d_date_sk)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [d_date_sk#1, d_year#2, d_moy#3] +Condition : ((isnotnull(d_moy#3) AND (d_moy#3 = 11)) AND isnotnull(d_date_sk#1)) + +(3) CometProject +Input [3]: [d_date_sk#1, d_year#2, d_moy#3] +Arguments: [d_date_sk#1, d_year#2], [d_date_sk#1, d_year#2] + +(4) ColumnarToRow [codegen id : 3] +Input [2]: [d_date_sk#1, d_year#2] + +(5) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#6), dynamicpruningexpression(true)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(6) CometFilter +Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] +Condition : isnotnull(ss_item_sk#4) + +(7) ColumnarToRow [codegen id : 1] +Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] + +(8) BroadcastExchange +Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[2, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [d_date_sk#1] +Right keys [1]: [ss_sold_date_sk#6] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 3] +Output [3]: [d_year#2, ss_item_sk#4, ss_ext_sales_price#5] +Input [5]: [d_date_sk#1, d_year#2, ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] + +(11) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#7, i_brand_id#8, i_brand#9, i_manufact_id#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_manufact_id), EqualTo(i_manufact_id,128), IsNotNull(i_item_sk)] +ReadSchema: struct + +(12) CometFilter +Input [4]: [i_item_sk#7, i_brand_id#8, i_brand#9, i_manufact_id#10] +Condition : ((isnotnull(i_manufact_id#10) AND (i_manufact_id#10 = 128)) AND isnotnull(i_item_sk#7)) + +(13) CometProject +Input [4]: [i_item_sk#7, i_brand_id#8, i_brand#9, i_manufact_id#10] +Arguments: [i_item_sk#7, i_brand_id#8, i_brand#9], [i_item_sk#7, i_brand_id#8, i_brand#9] + +(14) ColumnarToRow [codegen id : 2] +Input [3]: [i_item_sk#7, i_brand_id#8, i_brand#9] + +(15) BroadcastExchange +Input [3]: [i_item_sk#7, i_brand_id#8, i_brand#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(16) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_item_sk#4] +Right keys [1]: [i_item_sk#7] +Join type: Inner +Join condition: None + +(17) Project [codegen id : 3] +Output [4]: [d_year#2, ss_ext_sales_price#5, i_brand_id#8, i_brand#9] +Input [6]: [d_year#2, ss_item_sk#4, ss_ext_sales_price#5, i_item_sk#7, i_brand_id#8, i_brand#9] + +(18) HashAggregate [codegen id : 3] +Input [4]: [d_year#2, ss_ext_sales_price#5, i_brand_id#8, i_brand#9] +Keys [3]: [d_year#2, i_brand#9, i_brand_id#8] +Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#5))] +Aggregate Attributes [1]: [sum#11] +Results [4]: [d_year#2, i_brand#9, i_brand_id#8, sum#12] + +(19) Exchange +Input [4]: [d_year#2, i_brand#9, i_brand_id#8, sum#12] +Arguments: hashpartitioning(d_year#2, i_brand#9, i_brand_id#8, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(20) HashAggregate [codegen id : 4] +Input [4]: [d_year#2, i_brand#9, i_brand_id#8, sum#12] +Keys [3]: [d_year#2, i_brand#9, i_brand_id#8] +Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#5))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#5))#13] +Results [4]: [d_year#2, i_brand_id#8 AS brand_id#14, i_brand#9 AS brand#15, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#5))#13,17,2) AS sum_agg#16] + +(21) TakeOrderedAndProject +Input [4]: [d_year#2, brand_id#14, brand#15, sum_agg#16] +Arguments: 100, [d_year#2 ASC NULLS FIRST, sum_agg#16 DESC NULLS LAST, brand_id#14 ASC NULLS FIRST], [d_year#2, brand_id#14, brand#15, sum_agg#16] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q3/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q3/simplified.txt new file mode 100644 index 0000000000..3946c0cd8f --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q3/simplified.txt @@ -0,0 +1,31 @@ +TakeOrderedAndProject [d_year,sum_agg,brand_id,brand] + WholeStageCodegen (4) + HashAggregate [d_year,i_brand,i_brand_id,sum] [sum(UnscaledValue(ss_ext_sales_price)),brand_id,brand,sum_agg,sum] + InputAdapter + Exchange [d_year,i_brand,i_brand_id] #1 + WholeStageCodegen (3) + HashAggregate [d_year,i_brand,i_brand_id,ss_ext_sales_price] [sum,sum] + Project [d_year,ss_ext_sales_price,i_brand_id,i_brand] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [d_year,ss_item_sk,ss_ext_sales_price] + BroadcastHashJoin [d_date_sk,ss_sold_date_sk] + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_year] + CometFilter [d_moy,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ext_sales_price,ss_sold_date_sk] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometProject [i_item_sk,i_brand_id,i_brand] + CometFilter [i_manufact_id,i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_brand,i_manufact_id] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q30/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q30/explain.txt new file mode 100644 index 0000000000..098d008246 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q30/explain.txt @@ -0,0 +1,324 @@ +== Physical Plan == +TakeOrderedAndProject (49) ++- * Project (48) + +- * BroadcastHashJoin Inner BuildRight (47) + :- * Project (41) + : +- * BroadcastHashJoin Inner BuildRight (40) + : :- * Project (35) + : : +- * BroadcastHashJoin Inner BuildRight (34) + : : :- * Filter (16) + : : : +- * HashAggregate (15) + : : : +- Exchange (14) + : : : +- * HashAggregate (13) + : : : +- * Project (12) + : : : +- * BroadcastHashJoin Inner BuildRight (11) + : : : :- * Project (6) + : : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) + : : : : : +- CometScan parquet spark_catalog.default.web_returns (1) + : : : : +- ReusedExchange (4) + : : : +- BroadcastExchange (10) + : : : +- * ColumnarToRow (9) + : : : +- CometFilter (8) + : : : +- CometScan parquet spark_catalog.default.customer_address (7) + : : +- BroadcastExchange (33) + : : +- * Filter (32) + : : +- * HashAggregate (31) + : : +- Exchange (30) + : : +- * HashAggregate (29) + : : +- * HashAggregate (28) + : : +- Exchange (27) + : : +- * HashAggregate (26) + : : +- * Project (25) + : : +- * BroadcastHashJoin Inner BuildRight (24) + : : :- * Project (22) + : : : +- * BroadcastHashJoin Inner BuildRight (21) + : : : :- * ColumnarToRow (19) + : : : : +- CometFilter (18) + : : : : +- CometScan parquet spark_catalog.default.web_returns (17) + : : : +- ReusedExchange (20) + : : +- ReusedExchange (23) + : +- BroadcastExchange (39) + : +- * ColumnarToRow (38) + : +- CometFilter (37) + : +- CometScan parquet spark_catalog.default.customer (36) + +- BroadcastExchange (46) + +- * ColumnarToRow (45) + +- CometProject (44) + +- CometFilter (43) + +- CometScan parquet spark_catalog.default.customer_address (42) + + +(1) Scan parquet spark_catalog.default.web_returns +Output [4]: [wr_returning_customer_sk#1, wr_returning_addr_sk#2, wr_return_amt#3, wr_returned_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(wr_returned_date_sk#4), dynamicpruningexpression(wr_returned_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(wr_returning_addr_sk), IsNotNull(wr_returning_customer_sk)] +ReadSchema: struct + +(2) CometFilter +Input [4]: [wr_returning_customer_sk#1, wr_returning_addr_sk#2, wr_return_amt#3, wr_returned_date_sk#4] +Condition : (isnotnull(wr_returning_addr_sk#2) AND isnotnull(wr_returning_customer_sk#1)) + +(3) ColumnarToRow [codegen id : 3] +Input [4]: [wr_returning_customer_sk#1, wr_returning_addr_sk#2, wr_return_amt#3, wr_returned_date_sk#4] + +(4) ReusedExchange [Reuses operator id: 54] +Output [1]: [d_date_sk#6] + +(5) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [wr_returned_date_sk#4] +Right keys [1]: [d_date_sk#6] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 3] +Output [3]: [wr_returning_customer_sk#1, wr_returning_addr_sk#2, wr_return_amt#3] +Input [5]: [wr_returning_customer_sk#1, wr_returning_addr_sk#2, wr_return_amt#3, wr_returned_date_sk#4, d_date_sk#6] + +(7) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#7, ca_state#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk), IsNotNull(ca_state)] +ReadSchema: struct + +(8) CometFilter +Input [2]: [ca_address_sk#7, ca_state#8] +Condition : (isnotnull(ca_address_sk#7) AND isnotnull(ca_state#8)) + +(9) ColumnarToRow [codegen id : 2] +Input [2]: [ca_address_sk#7, ca_state#8] + +(10) BroadcastExchange +Input [2]: [ca_address_sk#7, ca_state#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [wr_returning_addr_sk#2] +Right keys [1]: [ca_address_sk#7] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [3]: [wr_returning_customer_sk#1, wr_return_amt#3, ca_state#8] +Input [5]: [wr_returning_customer_sk#1, wr_returning_addr_sk#2, wr_return_amt#3, ca_address_sk#7, ca_state#8] + +(13) HashAggregate [codegen id : 3] +Input [3]: [wr_returning_customer_sk#1, wr_return_amt#3, ca_state#8] +Keys [2]: [wr_returning_customer_sk#1, ca_state#8] +Functions [1]: [partial_sum(UnscaledValue(wr_return_amt#3))] +Aggregate Attributes [1]: [sum#9] +Results [3]: [wr_returning_customer_sk#1, ca_state#8, sum#10] + +(14) Exchange +Input [3]: [wr_returning_customer_sk#1, ca_state#8, sum#10] +Arguments: hashpartitioning(wr_returning_customer_sk#1, ca_state#8, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 11] +Input [3]: [wr_returning_customer_sk#1, ca_state#8, sum#10] +Keys [2]: [wr_returning_customer_sk#1, ca_state#8] +Functions [1]: [sum(UnscaledValue(wr_return_amt#3))] +Aggregate Attributes [1]: [sum(UnscaledValue(wr_return_amt#3))#11] +Results [3]: [wr_returning_customer_sk#1 AS ctr_customer_sk#12, ca_state#8 AS ctr_state#13, MakeDecimal(sum(UnscaledValue(wr_return_amt#3))#11,17,2) AS ctr_total_return#14] + +(16) Filter [codegen id : 11] +Input [3]: [ctr_customer_sk#12, ctr_state#13, ctr_total_return#14] +Condition : isnotnull(ctr_total_return#14) + +(17) Scan parquet spark_catalog.default.web_returns +Output [4]: [wr_returning_customer_sk#15, wr_returning_addr_sk#16, wr_return_amt#17, wr_returned_date_sk#18] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(wr_returned_date_sk#18), dynamicpruningexpression(wr_returned_date_sk#18 IN dynamicpruning#19)] +PushedFilters: [IsNotNull(wr_returning_addr_sk)] +ReadSchema: struct + +(18) CometFilter +Input [4]: [wr_returning_customer_sk#15, wr_returning_addr_sk#16, wr_return_amt#17, wr_returned_date_sk#18] +Condition : isnotnull(wr_returning_addr_sk#16) + +(19) ColumnarToRow [codegen id : 6] +Input [4]: [wr_returning_customer_sk#15, wr_returning_addr_sk#16, wr_return_amt#17, wr_returned_date_sk#18] + +(20) ReusedExchange [Reuses operator id: 54] +Output [1]: [d_date_sk#20] + +(21) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [wr_returned_date_sk#18] +Right keys [1]: [d_date_sk#20] +Join type: Inner +Join condition: None + +(22) Project [codegen id : 6] +Output [3]: [wr_returning_customer_sk#15, wr_returning_addr_sk#16, wr_return_amt#17] +Input [5]: [wr_returning_customer_sk#15, wr_returning_addr_sk#16, wr_return_amt#17, wr_returned_date_sk#18, d_date_sk#20] + +(23) ReusedExchange [Reuses operator id: 10] +Output [2]: [ca_address_sk#21, ca_state#22] + +(24) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [wr_returning_addr_sk#16] +Right keys [1]: [ca_address_sk#21] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 6] +Output [3]: [wr_returning_customer_sk#15, wr_return_amt#17, ca_state#22] +Input [5]: [wr_returning_customer_sk#15, wr_returning_addr_sk#16, wr_return_amt#17, ca_address_sk#21, ca_state#22] + +(26) HashAggregate [codegen id : 6] +Input [3]: [wr_returning_customer_sk#15, wr_return_amt#17, ca_state#22] +Keys [2]: [wr_returning_customer_sk#15, ca_state#22] +Functions [1]: [partial_sum(UnscaledValue(wr_return_amt#17))] +Aggregate Attributes [1]: [sum#23] +Results [3]: [wr_returning_customer_sk#15, ca_state#22, sum#24] + +(27) Exchange +Input [3]: [wr_returning_customer_sk#15, ca_state#22, sum#24] +Arguments: hashpartitioning(wr_returning_customer_sk#15, ca_state#22, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(28) HashAggregate [codegen id : 7] +Input [3]: [wr_returning_customer_sk#15, ca_state#22, sum#24] +Keys [2]: [wr_returning_customer_sk#15, ca_state#22] +Functions [1]: [sum(UnscaledValue(wr_return_amt#17))] +Aggregate Attributes [1]: [sum(UnscaledValue(wr_return_amt#17))#11] +Results [2]: [ca_state#22 AS ctr_state#25, MakeDecimal(sum(UnscaledValue(wr_return_amt#17))#11,17,2) AS ctr_total_return#26] + +(29) HashAggregate [codegen id : 7] +Input [2]: [ctr_state#25, ctr_total_return#26] +Keys [1]: [ctr_state#25] +Functions [1]: [partial_avg(ctr_total_return#26)] +Aggregate Attributes [2]: [sum#27, count#28] +Results [3]: [ctr_state#25, sum#29, count#30] + +(30) Exchange +Input [3]: [ctr_state#25, sum#29, count#30] +Arguments: hashpartitioning(ctr_state#25, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(31) HashAggregate [codegen id : 8] +Input [3]: [ctr_state#25, sum#29, count#30] +Keys [1]: [ctr_state#25] +Functions [1]: [avg(ctr_total_return#26)] +Aggregate Attributes [1]: [avg(ctr_total_return#26)#31] +Results [2]: [(avg(ctr_total_return#26)#31 * 1.2) AS (avg(ctr_total_return) * 1.2)#32, ctr_state#25] + +(32) Filter [codegen id : 8] +Input [2]: [(avg(ctr_total_return) * 1.2)#32, ctr_state#25] +Condition : isnotnull((avg(ctr_total_return) * 1.2)#32) + +(33) BroadcastExchange +Input [2]: [(avg(ctr_total_return) * 1.2)#32, ctr_state#25] +Arguments: HashedRelationBroadcastMode(List(input[1, string, true]),false), [plan_id=5] + +(34) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [ctr_state#13] +Right keys [1]: [ctr_state#25] +Join type: Inner +Join condition: (cast(ctr_total_return#14 as decimal(24,7)) > (avg(ctr_total_return) * 1.2)#32) + +(35) Project [codegen id : 11] +Output [2]: [ctr_customer_sk#12, ctr_total_return#14] +Input [5]: [ctr_customer_sk#12, ctr_state#13, ctr_total_return#14, (avg(ctr_total_return) * 1.2)#32, ctr_state#25] + +(36) Scan parquet spark_catalog.default.customer +Output [14]: [c_customer_sk#33, c_customer_id#34, c_current_addr_sk#35, c_salutation#36, c_first_name#37, c_last_name#38, c_preferred_cust_flag#39, c_birth_day#40, c_birth_month#41, c_birth_year#42, c_birth_country#43, c_login#44, c_email_address#45, c_last_review_date#46] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_current_addr_sk)] +ReadSchema: struct + +(37) CometFilter +Input [14]: [c_customer_sk#33, c_customer_id#34, c_current_addr_sk#35, c_salutation#36, c_first_name#37, c_last_name#38, c_preferred_cust_flag#39, c_birth_day#40, c_birth_month#41, c_birth_year#42, c_birth_country#43, c_login#44, c_email_address#45, c_last_review_date#46] +Condition : (isnotnull(c_customer_sk#33) AND isnotnull(c_current_addr_sk#35)) + +(38) ColumnarToRow [codegen id : 9] +Input [14]: [c_customer_sk#33, c_customer_id#34, c_current_addr_sk#35, c_salutation#36, c_first_name#37, c_last_name#38, c_preferred_cust_flag#39, c_birth_day#40, c_birth_month#41, c_birth_year#42, c_birth_country#43, c_login#44, c_email_address#45, c_last_review_date#46] + +(39) BroadcastExchange +Input [14]: [c_customer_sk#33, c_customer_id#34, c_current_addr_sk#35, c_salutation#36, c_first_name#37, c_last_name#38, c_preferred_cust_flag#39, c_birth_day#40, c_birth_month#41, c_birth_year#42, c_birth_country#43, c_login#44, c_email_address#45, c_last_review_date#46] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6] + +(40) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [ctr_customer_sk#12] +Right keys [1]: [c_customer_sk#33] +Join type: Inner +Join condition: None + +(41) Project [codegen id : 11] +Output [14]: [ctr_total_return#14, c_customer_id#34, c_current_addr_sk#35, c_salutation#36, c_first_name#37, c_last_name#38, c_preferred_cust_flag#39, c_birth_day#40, c_birth_month#41, c_birth_year#42, c_birth_country#43, c_login#44, c_email_address#45, c_last_review_date#46] +Input [16]: [ctr_customer_sk#12, ctr_total_return#14, c_customer_sk#33, c_customer_id#34, c_current_addr_sk#35, c_salutation#36, c_first_name#37, c_last_name#38, c_preferred_cust_flag#39, c_birth_day#40, c_birth_month#41, c_birth_year#42, c_birth_country#43, c_login#44, c_email_address#45, c_last_review_date#46] + +(42) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#47, ca_state#48] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_state), EqualTo(ca_state,GA), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(43) CometFilter +Input [2]: [ca_address_sk#47, ca_state#48] +Condition : ((isnotnull(ca_state#48) AND (ca_state#48 = GA)) AND isnotnull(ca_address_sk#47)) + +(44) CometProject +Input [2]: [ca_address_sk#47, ca_state#48] +Arguments: [ca_address_sk#47], [ca_address_sk#47] + +(45) ColumnarToRow [codegen id : 10] +Input [1]: [ca_address_sk#47] + +(46) BroadcastExchange +Input [1]: [ca_address_sk#47] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +(47) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [c_current_addr_sk#35] +Right keys [1]: [ca_address_sk#47] +Join type: Inner +Join condition: None + +(48) Project [codegen id : 11] +Output [13]: [c_customer_id#34, c_salutation#36, c_first_name#37, c_last_name#38, c_preferred_cust_flag#39, c_birth_day#40, c_birth_month#41, c_birth_year#42, c_birth_country#43, c_login#44, c_email_address#45, c_last_review_date#46, ctr_total_return#14] +Input [15]: [ctr_total_return#14, c_customer_id#34, c_current_addr_sk#35, c_salutation#36, c_first_name#37, c_last_name#38, c_preferred_cust_flag#39, c_birth_day#40, c_birth_month#41, c_birth_year#42, c_birth_country#43, c_login#44, c_email_address#45, c_last_review_date#46, ca_address_sk#47] + +(49) TakeOrderedAndProject +Input [13]: [c_customer_id#34, c_salutation#36, c_first_name#37, c_last_name#38, c_preferred_cust_flag#39, c_birth_day#40, c_birth_month#41, c_birth_year#42, c_birth_country#43, c_login#44, c_email_address#45, c_last_review_date#46, ctr_total_return#14] +Arguments: 100, [c_customer_id#34 ASC NULLS FIRST, c_salutation#36 ASC NULLS FIRST, c_first_name#37 ASC NULLS FIRST, c_last_name#38 ASC NULLS FIRST, c_preferred_cust_flag#39 ASC NULLS FIRST, c_birth_day#40 ASC NULLS FIRST, c_birth_month#41 ASC NULLS FIRST, c_birth_year#42 ASC NULLS FIRST, c_birth_country#43 ASC NULLS FIRST, c_login#44 ASC NULLS FIRST, c_email_address#45 ASC NULLS FIRST, c_last_review_date#46 ASC NULLS FIRST, ctr_total_return#14 ASC NULLS FIRST], [c_customer_id#34, c_salutation#36, c_first_name#37, c_last_name#38, c_preferred_cust_flag#39, c_birth_day#40, c_birth_month#41, c_birth_year#42, c_birth_country#43, c_login#44, c_email_address#45, c_last_review_date#46, ctr_total_return#14] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = wr_returned_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (54) ++- * ColumnarToRow (53) + +- CometProject (52) + +- CometFilter (51) + +- CometScan parquet spark_catalog.default.date_dim (50) + + +(50) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#6, d_year#49] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2002), IsNotNull(d_date_sk)] +ReadSchema: struct + +(51) CometFilter +Input [2]: [d_date_sk#6, d_year#49] +Condition : ((isnotnull(d_year#49) AND (d_year#49 = 2002)) AND isnotnull(d_date_sk#6)) + +(52) CometProject +Input [2]: [d_date_sk#6, d_year#49] +Arguments: [d_date_sk#6], [d_date_sk#6] + +(53) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#6] + +(54) BroadcastExchange +Input [1]: [d_date_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + +Subquery:2 Hosting operator id = 17 Hosting Expression = wr_returned_date_sk#18 IN dynamicpruning#5 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q30/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q30/simplified.txt new file mode 100644 index 0000000000..365f7f973e --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q30/simplified.txt @@ -0,0 +1,81 @@ +TakeOrderedAndProject [c_customer_id,c_salutation,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_day,c_birth_month,c_birth_year,c_birth_country,c_login,c_email_address,c_last_review_date,ctr_total_return] + WholeStageCodegen (11) + Project [c_customer_id,c_salutation,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_day,c_birth_month,c_birth_year,c_birth_country,c_login,c_email_address,c_last_review_date,ctr_total_return] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [ctr_total_return,c_customer_id,c_current_addr_sk,c_salutation,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_day,c_birth_month,c_birth_year,c_birth_country,c_login,c_email_address,c_last_review_date] + BroadcastHashJoin [ctr_customer_sk,c_customer_sk] + Project [ctr_customer_sk,ctr_total_return] + BroadcastHashJoin [ctr_state,ctr_state,ctr_total_return,(avg(ctr_total_return) * 1.2)] + Filter [ctr_total_return] + HashAggregate [wr_returning_customer_sk,ca_state,sum] [sum(UnscaledValue(wr_return_amt)),ctr_customer_sk,ctr_state,ctr_total_return,sum] + InputAdapter + Exchange [wr_returning_customer_sk,ca_state] #1 + WholeStageCodegen (3) + HashAggregate [wr_returning_customer_sk,ca_state,wr_return_amt] [sum,sum] + Project [wr_returning_customer_sk,wr_return_amt,ca_state] + BroadcastHashJoin [wr_returning_addr_sk,ca_address_sk] + Project [wr_returning_customer_sk,wr_returning_addr_sk,wr_return_amt] + BroadcastHashJoin [wr_returned_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [wr_returning_addr_sk,wr_returning_customer_sk] + CometScan parquet spark_catalog.default.web_returns [wr_returning_customer_sk,wr_returning_addr_sk,wr_return_amt,wr_returned_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk,ca_state] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (8) + Filter [(avg(ctr_total_return) * 1.2)] + HashAggregate [ctr_state,sum,count] [avg(ctr_total_return),(avg(ctr_total_return) * 1.2),sum,count] + InputAdapter + Exchange [ctr_state] #5 + WholeStageCodegen (7) + HashAggregate [ctr_state,ctr_total_return] [sum,count,sum,count] + HashAggregate [wr_returning_customer_sk,ca_state,sum] [sum(UnscaledValue(wr_return_amt)),ctr_state,ctr_total_return,sum] + InputAdapter + Exchange [wr_returning_customer_sk,ca_state] #6 + WholeStageCodegen (6) + HashAggregate [wr_returning_customer_sk,ca_state,wr_return_amt] [sum,sum] + Project [wr_returning_customer_sk,wr_return_amt,ca_state] + BroadcastHashJoin [wr_returning_addr_sk,ca_address_sk] + Project [wr_returning_customer_sk,wr_returning_addr_sk,wr_return_amt] + BroadcastHashJoin [wr_returned_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [wr_returning_addr_sk] + CometScan parquet spark_catalog.default.web_returns [wr_returning_customer_sk,wr_returning_addr_sk,wr_return_amt,wr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + ReusedExchange [ca_address_sk,ca_state] #3 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (9) + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_current_addr_sk] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_current_addr_sk,c_salutation,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_day,c_birth_month,c_birth_year,c_birth_country,c_login,c_email_address,c_last_review_date] + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (10) + ColumnarToRow + InputAdapter + CometProject [ca_address_sk] + CometFilter [ca_state,ca_address_sk] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q31/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q31/explain.txt new file mode 100644 index 0000000000..e20d454864 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q31/explain.txt @@ -0,0 +1,616 @@ +== Physical Plan == +* Sort (90) ++- Exchange (89) + +- * Project (88) + +- * BroadcastHashJoin Inner BuildRight (87) + :- * Project (73) + : +- * BroadcastHashJoin Inner BuildRight (72) + : :- * BroadcastHashJoin Inner BuildRight (58) + : : :- * Project (44) + : : : +- * BroadcastHashJoin Inner BuildRight (43) + : : : :- * BroadcastHashJoin Inner BuildRight (29) + : : : : :- * HashAggregate (15) + : : : : : +- Exchange (14) + : : : : : +- * HashAggregate (13) + : : : : : +- * Project (12) + : : : : : +- * BroadcastHashJoin Inner BuildRight (11) + : : : : : :- * Project (6) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : : : : :- * ColumnarToRow (3) + : : : : : : : +- CometFilter (2) + : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : : : +- ReusedExchange (4) + : : : : : +- BroadcastExchange (10) + : : : : : +- * ColumnarToRow (9) + : : : : : +- CometFilter (8) + : : : : : +- CometScan parquet spark_catalog.default.customer_address (7) + : : : : +- BroadcastExchange (28) + : : : : +- * HashAggregate (27) + : : : : +- Exchange (26) + : : : : +- * HashAggregate (25) + : : : : +- * Project (24) + : : : : +- * BroadcastHashJoin Inner BuildRight (23) + : : : : :- * Project (21) + : : : : : +- * BroadcastHashJoin Inner BuildRight (20) + : : : : : :- * ColumnarToRow (18) + : : : : : : +- CometFilter (17) + : : : : : : +- CometScan parquet spark_catalog.default.store_sales (16) + : : : : : +- ReusedExchange (19) + : : : : +- ReusedExchange (22) + : : : +- BroadcastExchange (42) + : : : +- * HashAggregate (41) + : : : +- Exchange (40) + : : : +- * HashAggregate (39) + : : : +- * Project (38) + : : : +- * BroadcastHashJoin Inner BuildRight (37) + : : : :- * Project (35) + : : : : +- * BroadcastHashJoin Inner BuildRight (34) + : : : : :- * ColumnarToRow (32) + : : : : : +- CometFilter (31) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (30) + : : : : +- ReusedExchange (33) + : : : +- ReusedExchange (36) + : : +- BroadcastExchange (57) + : : +- * HashAggregate (56) + : : +- Exchange (55) + : : +- * HashAggregate (54) + : : +- * Project (53) + : : +- * BroadcastHashJoin Inner BuildRight (52) + : : :- * Project (50) + : : : +- * BroadcastHashJoin Inner BuildRight (49) + : : : :- * ColumnarToRow (47) + : : : : +- CometFilter (46) + : : : : +- CometScan parquet spark_catalog.default.web_sales (45) + : : : +- ReusedExchange (48) + : : +- ReusedExchange (51) + : +- BroadcastExchange (71) + : +- * HashAggregate (70) + : +- Exchange (69) + : +- * HashAggregate (68) + : +- * Project (67) + : +- * BroadcastHashJoin Inner BuildRight (66) + : :- * Project (64) + : : +- * BroadcastHashJoin Inner BuildRight (63) + : : :- * ColumnarToRow (61) + : : : +- CometFilter (60) + : : : +- CometScan parquet spark_catalog.default.web_sales (59) + : : +- ReusedExchange (62) + : +- ReusedExchange (65) + +- BroadcastExchange (86) + +- * HashAggregate (85) + +- Exchange (84) + +- * HashAggregate (83) + +- * Project (82) + +- * BroadcastHashJoin Inner BuildRight (81) + :- * Project (79) + : +- * BroadcastHashJoin Inner BuildRight (78) + : :- * ColumnarToRow (76) + : : +- CometFilter (75) + : : +- CometScan parquet spark_catalog.default.web_sales (74) + : +- ReusedExchange (77) + +- ReusedExchange (80) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_addr_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#3), dynamicpruningexpression(ss_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(ss_addr_sk)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [ss_addr_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3] +Condition : isnotnull(ss_addr_sk#1) + +(3) ColumnarToRow [codegen id : 3] +Input [3]: [ss_addr_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3] + +(4) ReusedExchange [Reuses operator id: 94] +Output [3]: [d_date_sk#5, d_year#6, d_qoy#7] + +(5) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_sold_date_sk#3] +Right keys [1]: [d_date_sk#5] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 3] +Output [4]: [ss_addr_sk#1, ss_ext_sales_price#2, d_year#6, d_qoy#7] +Input [6]: [ss_addr_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3, d_date_sk#5, d_year#6, d_qoy#7] + +(7) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#8, ca_county#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk), IsNotNull(ca_county)] +ReadSchema: struct + +(8) CometFilter +Input [2]: [ca_address_sk#8, ca_county#9] +Condition : (isnotnull(ca_address_sk#8) AND isnotnull(ca_county#9)) + +(9) ColumnarToRow [codegen id : 2] +Input [2]: [ca_address_sk#8, ca_county#9] + +(10) BroadcastExchange +Input [2]: [ca_address_sk#8, ca_county#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_addr_sk#1] +Right keys [1]: [ca_address_sk#8] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [4]: [ss_ext_sales_price#2, d_year#6, d_qoy#7, ca_county#9] +Input [6]: [ss_addr_sk#1, ss_ext_sales_price#2, d_year#6, d_qoy#7, ca_address_sk#8, ca_county#9] + +(13) HashAggregate [codegen id : 3] +Input [4]: [ss_ext_sales_price#2, d_year#6, d_qoy#7, ca_county#9] +Keys [3]: [ca_county#9, d_qoy#7, d_year#6] +Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#2))] +Aggregate Attributes [1]: [sum#10] +Results [4]: [ca_county#9, d_qoy#7, d_year#6, sum#11] + +(14) Exchange +Input [4]: [ca_county#9, d_qoy#7, d_year#6, sum#11] +Arguments: hashpartitioning(ca_county#9, d_qoy#7, d_year#6, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 24] +Input [4]: [ca_county#9, d_qoy#7, d_year#6, sum#11] +Keys [3]: [ca_county#9, d_qoy#7, d_year#6] +Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#2))#12] +Results [3]: [ca_county#9, d_year#6, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#2))#12,17,2) AS store_sales#13] + +(16) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_addr_sk#14, ss_ext_sales_price#15, ss_sold_date_sk#16] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#16), dynamicpruningexpression(ss_sold_date_sk#16 IN dynamicpruning#17)] +PushedFilters: [IsNotNull(ss_addr_sk)] +ReadSchema: struct + +(17) CometFilter +Input [3]: [ss_addr_sk#14, ss_ext_sales_price#15, ss_sold_date_sk#16] +Condition : isnotnull(ss_addr_sk#14) + +(18) ColumnarToRow [codegen id : 6] +Input [3]: [ss_addr_sk#14, ss_ext_sales_price#15, ss_sold_date_sk#16] + +(19) ReusedExchange [Reuses operator id: 98] +Output [3]: [d_date_sk#18, d_year#19, d_qoy#20] + +(20) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_sold_date_sk#16] +Right keys [1]: [d_date_sk#18] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 6] +Output [4]: [ss_addr_sk#14, ss_ext_sales_price#15, d_year#19, d_qoy#20] +Input [6]: [ss_addr_sk#14, ss_ext_sales_price#15, ss_sold_date_sk#16, d_date_sk#18, d_year#19, d_qoy#20] + +(22) ReusedExchange [Reuses operator id: 10] +Output [2]: [ca_address_sk#21, ca_county#22] + +(23) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_addr_sk#14] +Right keys [1]: [ca_address_sk#21] +Join type: Inner +Join condition: None + +(24) Project [codegen id : 6] +Output [4]: [ss_ext_sales_price#15, d_year#19, d_qoy#20, ca_county#22] +Input [6]: [ss_addr_sk#14, ss_ext_sales_price#15, d_year#19, d_qoy#20, ca_address_sk#21, ca_county#22] + +(25) HashAggregate [codegen id : 6] +Input [4]: [ss_ext_sales_price#15, d_year#19, d_qoy#20, ca_county#22] +Keys [3]: [ca_county#22, d_qoy#20, d_year#19] +Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#15))] +Aggregate Attributes [1]: [sum#23] +Results [4]: [ca_county#22, d_qoy#20, d_year#19, sum#24] + +(26) Exchange +Input [4]: [ca_county#22, d_qoy#20, d_year#19, sum#24] +Arguments: hashpartitioning(ca_county#22, d_qoy#20, d_year#19, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(27) HashAggregate [codegen id : 7] +Input [4]: [ca_county#22, d_qoy#20, d_year#19, sum#24] +Keys [3]: [ca_county#22, d_qoy#20, d_year#19] +Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#15))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#15))#12] +Results [2]: [ca_county#22, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#15))#12,17,2) AS store_sales#25] + +(28) BroadcastExchange +Input [2]: [ca_county#22, store_sales#25] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=4] + +(29) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [ca_county#9] +Right keys [1]: [ca_county#22] +Join type: Inner +Join condition: None + +(30) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_addr_sk#26, ss_ext_sales_price#27, ss_sold_date_sk#28] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#28), dynamicpruningexpression(ss_sold_date_sk#28 IN dynamicpruning#29)] +PushedFilters: [IsNotNull(ss_addr_sk)] +ReadSchema: struct + +(31) CometFilter +Input [3]: [ss_addr_sk#26, ss_ext_sales_price#27, ss_sold_date_sk#28] +Condition : isnotnull(ss_addr_sk#26) + +(32) ColumnarToRow [codegen id : 10] +Input [3]: [ss_addr_sk#26, ss_ext_sales_price#27, ss_sold_date_sk#28] + +(33) ReusedExchange [Reuses operator id: 102] +Output [3]: [d_date_sk#30, d_year#31, d_qoy#32] + +(34) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [ss_sold_date_sk#28] +Right keys [1]: [d_date_sk#30] +Join type: Inner +Join condition: None + +(35) Project [codegen id : 10] +Output [4]: [ss_addr_sk#26, ss_ext_sales_price#27, d_year#31, d_qoy#32] +Input [6]: [ss_addr_sk#26, ss_ext_sales_price#27, ss_sold_date_sk#28, d_date_sk#30, d_year#31, d_qoy#32] + +(36) ReusedExchange [Reuses operator id: 10] +Output [2]: [ca_address_sk#33, ca_county#34] + +(37) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [ss_addr_sk#26] +Right keys [1]: [ca_address_sk#33] +Join type: Inner +Join condition: None + +(38) Project [codegen id : 10] +Output [4]: [ss_ext_sales_price#27, d_year#31, d_qoy#32, ca_county#34] +Input [6]: [ss_addr_sk#26, ss_ext_sales_price#27, d_year#31, d_qoy#32, ca_address_sk#33, ca_county#34] + +(39) HashAggregate [codegen id : 10] +Input [4]: [ss_ext_sales_price#27, d_year#31, d_qoy#32, ca_county#34] +Keys [3]: [ca_county#34, d_qoy#32, d_year#31] +Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#27))] +Aggregate Attributes [1]: [sum#35] +Results [4]: [ca_county#34, d_qoy#32, d_year#31, sum#36] + +(40) Exchange +Input [4]: [ca_county#34, d_qoy#32, d_year#31, sum#36] +Arguments: hashpartitioning(ca_county#34, d_qoy#32, d_year#31, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(41) HashAggregate [codegen id : 11] +Input [4]: [ca_county#34, d_qoy#32, d_year#31, sum#36] +Keys [3]: [ca_county#34, d_qoy#32, d_year#31] +Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#27))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#27))#12] +Results [2]: [ca_county#34, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#27))#12,17,2) AS store_sales#37] + +(42) BroadcastExchange +Input [2]: [ca_county#34, store_sales#37] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=6] + +(43) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [ca_county#22] +Right keys [1]: [ca_county#34] +Join type: Inner +Join condition: None + +(44) Project [codegen id : 24] +Output [5]: [ca_county#9, d_year#6, store_sales#13, store_sales#25, store_sales#37] +Input [7]: [ca_county#9, d_year#6, store_sales#13, ca_county#22, store_sales#25, ca_county#34, store_sales#37] + +(45) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_bill_addr_sk#38, ws_ext_sales_price#39, ws_sold_date_sk#40] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#40), dynamicpruningexpression(ws_sold_date_sk#40 IN dynamicpruning#41)] +PushedFilters: [IsNotNull(ws_bill_addr_sk)] +ReadSchema: struct + +(46) CometFilter +Input [3]: [ws_bill_addr_sk#38, ws_ext_sales_price#39, ws_sold_date_sk#40] +Condition : isnotnull(ws_bill_addr_sk#38) + +(47) ColumnarToRow [codegen id : 14] +Input [3]: [ws_bill_addr_sk#38, ws_ext_sales_price#39, ws_sold_date_sk#40] + +(48) ReusedExchange [Reuses operator id: 94] +Output [3]: [d_date_sk#42, d_year#43, d_qoy#44] + +(49) BroadcastHashJoin [codegen id : 14] +Left keys [1]: [ws_sold_date_sk#40] +Right keys [1]: [d_date_sk#42] +Join type: Inner +Join condition: None + +(50) Project [codegen id : 14] +Output [4]: [ws_bill_addr_sk#38, ws_ext_sales_price#39, d_year#43, d_qoy#44] +Input [6]: [ws_bill_addr_sk#38, ws_ext_sales_price#39, ws_sold_date_sk#40, d_date_sk#42, d_year#43, d_qoy#44] + +(51) ReusedExchange [Reuses operator id: 10] +Output [2]: [ca_address_sk#45, ca_county#46] + +(52) BroadcastHashJoin [codegen id : 14] +Left keys [1]: [ws_bill_addr_sk#38] +Right keys [1]: [ca_address_sk#45] +Join type: Inner +Join condition: None + +(53) Project [codegen id : 14] +Output [4]: [ws_ext_sales_price#39, d_year#43, d_qoy#44, ca_county#46] +Input [6]: [ws_bill_addr_sk#38, ws_ext_sales_price#39, d_year#43, d_qoy#44, ca_address_sk#45, ca_county#46] + +(54) HashAggregate [codegen id : 14] +Input [4]: [ws_ext_sales_price#39, d_year#43, d_qoy#44, ca_county#46] +Keys [3]: [ca_county#46, d_qoy#44, d_year#43] +Functions [1]: [partial_sum(UnscaledValue(ws_ext_sales_price#39))] +Aggregate Attributes [1]: [sum#47] +Results [4]: [ca_county#46, d_qoy#44, d_year#43, sum#48] + +(55) Exchange +Input [4]: [ca_county#46, d_qoy#44, d_year#43, sum#48] +Arguments: hashpartitioning(ca_county#46, d_qoy#44, d_year#43, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(56) HashAggregate [codegen id : 15] +Input [4]: [ca_county#46, d_qoy#44, d_year#43, sum#48] +Keys [3]: [ca_county#46, d_qoy#44, d_year#43] +Functions [1]: [sum(UnscaledValue(ws_ext_sales_price#39))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_ext_sales_price#39))#49] +Results [2]: [ca_county#46, MakeDecimal(sum(UnscaledValue(ws_ext_sales_price#39))#49,17,2) AS web_sales#50] + +(57) BroadcastExchange +Input [2]: [ca_county#46, web_sales#50] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=8] + +(58) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [ca_county#9] +Right keys [1]: [ca_county#46] +Join type: Inner +Join condition: None + +(59) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_bill_addr_sk#51, ws_ext_sales_price#52, ws_sold_date_sk#53] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#53), dynamicpruningexpression(ws_sold_date_sk#53 IN dynamicpruning#54)] +PushedFilters: [IsNotNull(ws_bill_addr_sk)] +ReadSchema: struct + +(60) CometFilter +Input [3]: [ws_bill_addr_sk#51, ws_ext_sales_price#52, ws_sold_date_sk#53] +Condition : isnotnull(ws_bill_addr_sk#51) + +(61) ColumnarToRow [codegen id : 18] +Input [3]: [ws_bill_addr_sk#51, ws_ext_sales_price#52, ws_sold_date_sk#53] + +(62) ReusedExchange [Reuses operator id: 98] +Output [3]: [d_date_sk#55, d_year#56, d_qoy#57] + +(63) BroadcastHashJoin [codegen id : 18] +Left keys [1]: [ws_sold_date_sk#53] +Right keys [1]: [d_date_sk#55] +Join type: Inner +Join condition: None + +(64) Project [codegen id : 18] +Output [4]: [ws_bill_addr_sk#51, ws_ext_sales_price#52, d_year#56, d_qoy#57] +Input [6]: [ws_bill_addr_sk#51, ws_ext_sales_price#52, ws_sold_date_sk#53, d_date_sk#55, d_year#56, d_qoy#57] + +(65) ReusedExchange [Reuses operator id: 10] +Output [2]: [ca_address_sk#58, ca_county#59] + +(66) BroadcastHashJoin [codegen id : 18] +Left keys [1]: [ws_bill_addr_sk#51] +Right keys [1]: [ca_address_sk#58] +Join type: Inner +Join condition: None + +(67) Project [codegen id : 18] +Output [4]: [ws_ext_sales_price#52, d_year#56, d_qoy#57, ca_county#59] +Input [6]: [ws_bill_addr_sk#51, ws_ext_sales_price#52, d_year#56, d_qoy#57, ca_address_sk#58, ca_county#59] + +(68) HashAggregate [codegen id : 18] +Input [4]: [ws_ext_sales_price#52, d_year#56, d_qoy#57, ca_county#59] +Keys [3]: [ca_county#59, d_qoy#57, d_year#56] +Functions [1]: [partial_sum(UnscaledValue(ws_ext_sales_price#52))] +Aggregate Attributes [1]: [sum#60] +Results [4]: [ca_county#59, d_qoy#57, d_year#56, sum#61] + +(69) Exchange +Input [4]: [ca_county#59, d_qoy#57, d_year#56, sum#61] +Arguments: hashpartitioning(ca_county#59, d_qoy#57, d_year#56, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(70) HashAggregate [codegen id : 19] +Input [4]: [ca_county#59, d_qoy#57, d_year#56, sum#61] +Keys [3]: [ca_county#59, d_qoy#57, d_year#56] +Functions [1]: [sum(UnscaledValue(ws_ext_sales_price#52))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_ext_sales_price#52))#49] +Results [2]: [ca_county#59, MakeDecimal(sum(UnscaledValue(ws_ext_sales_price#52))#49,17,2) AS web_sales#62] + +(71) BroadcastExchange +Input [2]: [ca_county#59, web_sales#62] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=10] + +(72) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [ca_county#46] +Right keys [1]: [ca_county#59] +Join type: Inner +Join condition: (CASE WHEN (web_sales#50 > 0.00) THEN (web_sales#62 / web_sales#50) END > CASE WHEN (store_sales#13 > 0.00) THEN (store_sales#25 / store_sales#13) END) + +(73) Project [codegen id : 24] +Output [8]: [ca_county#9, d_year#6, store_sales#13, store_sales#25, store_sales#37, ca_county#46, web_sales#50, web_sales#62] +Input [9]: [ca_county#9, d_year#6, store_sales#13, store_sales#25, store_sales#37, ca_county#46, web_sales#50, ca_county#59, web_sales#62] + +(74) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_bill_addr_sk#63, ws_ext_sales_price#64, ws_sold_date_sk#65] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#65), dynamicpruningexpression(ws_sold_date_sk#65 IN dynamicpruning#66)] +PushedFilters: [IsNotNull(ws_bill_addr_sk)] +ReadSchema: struct + +(75) CometFilter +Input [3]: [ws_bill_addr_sk#63, ws_ext_sales_price#64, ws_sold_date_sk#65] +Condition : isnotnull(ws_bill_addr_sk#63) + +(76) ColumnarToRow [codegen id : 22] +Input [3]: [ws_bill_addr_sk#63, ws_ext_sales_price#64, ws_sold_date_sk#65] + +(77) ReusedExchange [Reuses operator id: 102] +Output [3]: [d_date_sk#67, d_year#68, d_qoy#69] + +(78) BroadcastHashJoin [codegen id : 22] +Left keys [1]: [ws_sold_date_sk#65] +Right keys [1]: [d_date_sk#67] +Join type: Inner +Join condition: None + +(79) Project [codegen id : 22] +Output [4]: [ws_bill_addr_sk#63, ws_ext_sales_price#64, d_year#68, d_qoy#69] +Input [6]: [ws_bill_addr_sk#63, ws_ext_sales_price#64, ws_sold_date_sk#65, d_date_sk#67, d_year#68, d_qoy#69] + +(80) ReusedExchange [Reuses operator id: 10] +Output [2]: [ca_address_sk#70, ca_county#71] + +(81) BroadcastHashJoin [codegen id : 22] +Left keys [1]: [ws_bill_addr_sk#63] +Right keys [1]: [ca_address_sk#70] +Join type: Inner +Join condition: None + +(82) Project [codegen id : 22] +Output [4]: [ws_ext_sales_price#64, d_year#68, d_qoy#69, ca_county#71] +Input [6]: [ws_bill_addr_sk#63, ws_ext_sales_price#64, d_year#68, d_qoy#69, ca_address_sk#70, ca_county#71] + +(83) HashAggregate [codegen id : 22] +Input [4]: [ws_ext_sales_price#64, d_year#68, d_qoy#69, ca_county#71] +Keys [3]: [ca_county#71, d_qoy#69, d_year#68] +Functions [1]: [partial_sum(UnscaledValue(ws_ext_sales_price#64))] +Aggregate Attributes [1]: [sum#72] +Results [4]: [ca_county#71, d_qoy#69, d_year#68, sum#73] + +(84) Exchange +Input [4]: [ca_county#71, d_qoy#69, d_year#68, sum#73] +Arguments: hashpartitioning(ca_county#71, d_qoy#69, d_year#68, 5), ENSURE_REQUIREMENTS, [plan_id=11] + +(85) HashAggregate [codegen id : 23] +Input [4]: [ca_county#71, d_qoy#69, d_year#68, sum#73] +Keys [3]: [ca_county#71, d_qoy#69, d_year#68] +Functions [1]: [sum(UnscaledValue(ws_ext_sales_price#64))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_ext_sales_price#64))#49] +Results [2]: [ca_county#71, MakeDecimal(sum(UnscaledValue(ws_ext_sales_price#64))#49,17,2) AS web_sales#74] + +(86) BroadcastExchange +Input [2]: [ca_county#71, web_sales#74] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=12] + +(87) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [ca_county#46] +Right keys [1]: [ca_county#71] +Join type: Inner +Join condition: (CASE WHEN (web_sales#62 > 0.00) THEN (web_sales#74 / web_sales#62) END > CASE WHEN (store_sales#25 > 0.00) THEN (store_sales#37 / store_sales#25) END) + +(88) Project [codegen id : 24] +Output [6]: [ca_county#9, d_year#6, (web_sales#62 / web_sales#50) AS web_q1_q2_increase#75, (store_sales#25 / store_sales#13) AS store_q1_q2_increase#76, (web_sales#74 / web_sales#62) AS web_q2_q3_increase#77, (store_sales#37 / store_sales#25) AS store_q2_q3_increase#78] +Input [10]: [ca_county#9, d_year#6, store_sales#13, store_sales#25, store_sales#37, ca_county#46, web_sales#50, web_sales#62, ca_county#71, web_sales#74] + +(89) Exchange +Input [6]: [ca_county#9, d_year#6, web_q1_q2_increase#75, store_q1_q2_increase#76, web_q2_q3_increase#77, store_q2_q3_increase#78] +Arguments: rangepartitioning(ca_county#9 ASC NULLS FIRST, 5), ENSURE_REQUIREMENTS, [plan_id=13] + +(90) Sort [codegen id : 25] +Input [6]: [ca_county#9, d_year#6, web_q1_q2_increase#75, store_q1_q2_increase#76, web_q2_q3_increase#77, store_q2_q3_increase#78] +Arguments: [ca_county#9 ASC NULLS FIRST], true, 0 + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (94) ++- * ColumnarToRow (93) + +- CometFilter (92) + +- CometScan parquet spark_catalog.default.date_dim (91) + + +(91) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#5, d_year#6, d_qoy#7] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_qoy), IsNotNull(d_year), EqualTo(d_qoy,1), EqualTo(d_year,2000), IsNotNull(d_date_sk)] +ReadSchema: struct + +(92) CometFilter +Input [3]: [d_date_sk#5, d_year#6, d_qoy#7] +Condition : ((((isnotnull(d_qoy#7) AND isnotnull(d_year#6)) AND (d_qoy#7 = 1)) AND (d_year#6 = 2000)) AND isnotnull(d_date_sk#5)) + +(93) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#5, d_year#6, d_qoy#7] + +(94) BroadcastExchange +Input [3]: [d_date_sk#5, d_year#6, d_qoy#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=14] + +Subquery:2 Hosting operator id = 16 Hosting Expression = ss_sold_date_sk#16 IN dynamicpruning#17 +BroadcastExchange (98) ++- * ColumnarToRow (97) + +- CometFilter (96) + +- CometScan parquet spark_catalog.default.date_dim (95) + + +(95) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#18, d_year#19, d_qoy#20] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_qoy), IsNotNull(d_year), EqualTo(d_qoy,2), EqualTo(d_year,2000), IsNotNull(d_date_sk)] +ReadSchema: struct + +(96) CometFilter +Input [3]: [d_date_sk#18, d_year#19, d_qoy#20] +Condition : ((((isnotnull(d_qoy#20) AND isnotnull(d_year#19)) AND (d_qoy#20 = 2)) AND (d_year#19 = 2000)) AND isnotnull(d_date_sk#18)) + +(97) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#18, d_year#19, d_qoy#20] + +(98) BroadcastExchange +Input [3]: [d_date_sk#18, d_year#19, d_qoy#20] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=15] + +Subquery:3 Hosting operator id = 30 Hosting Expression = ss_sold_date_sk#28 IN dynamicpruning#29 +BroadcastExchange (102) ++- * ColumnarToRow (101) + +- CometFilter (100) + +- CometScan parquet spark_catalog.default.date_dim (99) + + +(99) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#30, d_year#31, d_qoy#32] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_qoy), IsNotNull(d_year), EqualTo(d_qoy,3), EqualTo(d_year,2000), IsNotNull(d_date_sk)] +ReadSchema: struct + +(100) CometFilter +Input [3]: [d_date_sk#30, d_year#31, d_qoy#32] +Condition : ((((isnotnull(d_qoy#32) AND isnotnull(d_year#31)) AND (d_qoy#32 = 3)) AND (d_year#31 = 2000)) AND isnotnull(d_date_sk#30)) + +(101) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#30, d_year#31, d_qoy#32] + +(102) BroadcastExchange +Input [3]: [d_date_sk#30, d_year#31, d_qoy#32] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=16] + +Subquery:4 Hosting operator id = 45 Hosting Expression = ws_sold_date_sk#40 IN dynamicpruning#4 + +Subquery:5 Hosting operator id = 59 Hosting Expression = ws_sold_date_sk#53 IN dynamicpruning#17 + +Subquery:6 Hosting operator id = 74 Hosting Expression = ws_sold_date_sk#65 IN dynamicpruning#29 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q31/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q31/simplified.txt new file mode 100644 index 0000000000..f4bf6a89d0 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q31/simplified.txt @@ -0,0 +1,159 @@ +WholeStageCodegen (25) + Sort [ca_county] + InputAdapter + Exchange [ca_county] #1 + WholeStageCodegen (24) + Project [ca_county,d_year,web_sales,web_sales,store_sales,store_sales,web_sales,store_sales] + BroadcastHashJoin [ca_county,ca_county,web_sales,web_sales,store_sales,store_sales] + Project [ca_county,d_year,store_sales,store_sales,store_sales,ca_county,web_sales,web_sales] + BroadcastHashJoin [ca_county,ca_county,web_sales,web_sales,store_sales,store_sales] + BroadcastHashJoin [ca_county,ca_county] + Project [ca_county,d_year,store_sales,store_sales,store_sales] + BroadcastHashJoin [ca_county,ca_county] + BroadcastHashJoin [ca_county,ca_county] + HashAggregate [ca_county,d_qoy,d_year,sum] [sum(UnscaledValue(ss_ext_sales_price)),store_sales,sum] + InputAdapter + Exchange [ca_county,d_qoy,d_year] #2 + WholeStageCodegen (3) + HashAggregate [ca_county,d_qoy,d_year,ss_ext_sales_price] [sum,sum] + Project [ss_ext_sales_price,d_year,d_qoy,ca_county] + BroadcastHashJoin [ss_addr_sk,ca_address_sk] + Project [ss_addr_sk,ss_ext_sales_price,d_year,d_qoy] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_addr_sk] + CometScan parquet spark_catalog.default.store_sales [ss_addr_sk,ss_ext_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_qoy,d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_qoy] + InputAdapter + ReusedExchange [d_date_sk,d_year,d_qoy] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk,ca_county] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_county] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (7) + HashAggregate [ca_county,d_qoy,d_year,sum] [sum(UnscaledValue(ss_ext_sales_price)),store_sales,sum] + InputAdapter + Exchange [ca_county,d_qoy,d_year] #6 + WholeStageCodegen (6) + HashAggregate [ca_county,d_qoy,d_year,ss_ext_sales_price] [sum,sum] + Project [ss_ext_sales_price,d_year,d_qoy,ca_county] + BroadcastHashJoin [ss_addr_sk,ca_address_sk] + Project [ss_addr_sk,ss_ext_sales_price,d_year,d_qoy] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_addr_sk] + CometScan parquet spark_catalog.default.store_sales [ss_addr_sk,ss_ext_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #7 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_qoy,d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_qoy] + InputAdapter + ReusedExchange [d_date_sk,d_year,d_qoy] #7 + InputAdapter + ReusedExchange [ca_address_sk,ca_county] #4 + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (11) + HashAggregate [ca_county,d_qoy,d_year,sum] [sum(UnscaledValue(ss_ext_sales_price)),store_sales,sum] + InputAdapter + Exchange [ca_county,d_qoy,d_year] #9 + WholeStageCodegen (10) + HashAggregate [ca_county,d_qoy,d_year,ss_ext_sales_price] [sum,sum] + Project [ss_ext_sales_price,d_year,d_qoy,ca_county] + BroadcastHashJoin [ss_addr_sk,ca_address_sk] + Project [ss_addr_sk,ss_ext_sales_price,d_year,d_qoy] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_addr_sk] + CometScan parquet spark_catalog.default.store_sales [ss_addr_sk,ss_ext_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #3 + BroadcastExchange #10 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_qoy,d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_qoy] + InputAdapter + ReusedExchange [d_date_sk,d_year,d_qoy] #10 + InputAdapter + ReusedExchange [ca_address_sk,ca_county] #4 + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (15) + HashAggregate [ca_county,d_qoy,d_year,sum] [sum(UnscaledValue(ws_ext_sales_price)),web_sales,sum] + InputAdapter + Exchange [ca_county,d_qoy,d_year] #12 + WholeStageCodegen (14) + HashAggregate [ca_county,d_qoy,d_year,ws_ext_sales_price] [sum,sum] + Project [ws_ext_sales_price,d_year,d_qoy,ca_county] + BroadcastHashJoin [ws_bill_addr_sk,ca_address_sk] + Project [ws_bill_addr_sk,ws_ext_sales_price,d_year,d_qoy] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ws_bill_addr_sk] + CometScan parquet spark_catalog.default.web_sales [ws_bill_addr_sk,ws_ext_sales_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk,d_year,d_qoy] #3 + InputAdapter + ReusedExchange [ca_address_sk,ca_county] #4 + InputAdapter + BroadcastExchange #13 + WholeStageCodegen (19) + HashAggregate [ca_county,d_qoy,d_year,sum] [sum(UnscaledValue(ws_ext_sales_price)),web_sales,sum] + InputAdapter + Exchange [ca_county,d_qoy,d_year] #14 + WholeStageCodegen (18) + HashAggregate [ca_county,d_qoy,d_year,ws_ext_sales_price] [sum,sum] + Project [ws_ext_sales_price,d_year,d_qoy,ca_county] + BroadcastHashJoin [ws_bill_addr_sk,ca_address_sk] + Project [ws_bill_addr_sk,ws_ext_sales_price,d_year,d_qoy] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ws_bill_addr_sk] + CometScan parquet spark_catalog.default.web_sales [ws_bill_addr_sk,ws_ext_sales_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk,d_year,d_qoy] #7 + InputAdapter + ReusedExchange [ca_address_sk,ca_county] #4 + InputAdapter + BroadcastExchange #15 + WholeStageCodegen (23) + HashAggregate [ca_county,d_qoy,d_year,sum] [sum(UnscaledValue(ws_ext_sales_price)),web_sales,sum] + InputAdapter + Exchange [ca_county,d_qoy,d_year] #16 + WholeStageCodegen (22) + HashAggregate [ca_county,d_qoy,d_year,ws_ext_sales_price] [sum,sum] + Project [ws_ext_sales_price,d_year,d_qoy,ca_county] + BroadcastHashJoin [ws_bill_addr_sk,ca_address_sk] + Project [ws_bill_addr_sk,ws_ext_sales_price,d_year,d_qoy] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ws_bill_addr_sk] + CometScan parquet spark_catalog.default.web_sales [ws_bill_addr_sk,ws_ext_sales_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #3 + InputAdapter + ReusedExchange [d_date_sk,d_year,d_qoy] #10 + InputAdapter + ReusedExchange [ca_address_sk,ca_county] #4 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q32/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q32/explain.txt new file mode 100644 index 0000000000..bd7caaaa11 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q32/explain.txt @@ -0,0 +1,209 @@ +== Physical Plan == +* HashAggregate (29) ++- Exchange (28) + +- * HashAggregate (27) + +- * Project (26) + +- * BroadcastHashJoin Inner BuildRight (25) + :- * Project (23) + : +- * BroadcastHashJoin Inner BuildRight (22) + : :- * Project (10) + : : +- * BroadcastHashJoin Inner BuildRight (9) + : : :- * ColumnarToRow (3) + : : : +- CometFilter (2) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) + : : +- BroadcastExchange (8) + : : +- * ColumnarToRow (7) + : : +- CometProject (6) + : : +- CometFilter (5) + : : +- CometScan parquet spark_catalog.default.item (4) + : +- BroadcastExchange (21) + : +- * Filter (20) + : +- * HashAggregate (19) + : +- Exchange (18) + : +- * HashAggregate (17) + : +- * Project (16) + : +- * BroadcastHashJoin Inner BuildRight (15) + : :- * ColumnarToRow (13) + : : +- CometFilter (12) + : : +- CometScan parquet spark_catalog.default.catalog_sales (11) + : +- ReusedExchange (14) + +- ReusedExchange (24) + + +(1) Scan parquet spark_catalog.default.catalog_sales +Output [3]: [cs_item_sk#1, cs_ext_discount_amt#2, cs_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#3), dynamicpruningexpression(cs_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(cs_item_sk), IsNotNull(cs_ext_discount_amt)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [cs_item_sk#1, cs_ext_discount_amt#2, cs_sold_date_sk#3] +Condition : (isnotnull(cs_item_sk#1) AND isnotnull(cs_ext_discount_amt#2)) + +(3) ColumnarToRow [codegen id : 6] +Input [3]: [cs_item_sk#1, cs_ext_discount_amt#2, cs_sold_date_sk#3] + +(4) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#5, i_manufact_id#6] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_manufact_id), EqualTo(i_manufact_id,977), IsNotNull(i_item_sk)] +ReadSchema: struct + +(5) CometFilter +Input [2]: [i_item_sk#5, i_manufact_id#6] +Condition : ((isnotnull(i_manufact_id#6) AND (i_manufact_id#6 = 977)) AND isnotnull(i_item_sk#5)) + +(6) CometProject +Input [2]: [i_item_sk#5, i_manufact_id#6] +Arguments: [i_item_sk#5], [i_item_sk#5] + +(7) ColumnarToRow [codegen id : 1] +Input [1]: [i_item_sk#5] + +(8) BroadcastExchange +Input [1]: [i_item_sk#5] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [cs_item_sk#1] +Right keys [1]: [i_item_sk#5] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 6] +Output [3]: [cs_ext_discount_amt#2, cs_sold_date_sk#3, i_item_sk#5] +Input [4]: [cs_item_sk#1, cs_ext_discount_amt#2, cs_sold_date_sk#3, i_item_sk#5] + +(11) Scan parquet spark_catalog.default.catalog_sales +Output [3]: [cs_item_sk#7, cs_ext_discount_amt#8, cs_sold_date_sk#9] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#9), dynamicpruningexpression(cs_sold_date_sk#9 IN dynamicpruning#10)] +PushedFilters: [IsNotNull(cs_item_sk)] +ReadSchema: struct + +(12) CometFilter +Input [3]: [cs_item_sk#7, cs_ext_discount_amt#8, cs_sold_date_sk#9] +Condition : isnotnull(cs_item_sk#7) + +(13) ColumnarToRow [codegen id : 3] +Input [3]: [cs_item_sk#7, cs_ext_discount_amt#8, cs_sold_date_sk#9] + +(14) ReusedExchange [Reuses operator id: 34] +Output [1]: [d_date_sk#11] + +(15) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cs_sold_date_sk#9] +Right keys [1]: [d_date_sk#11] +Join type: Inner +Join condition: None + +(16) Project [codegen id : 3] +Output [2]: [cs_item_sk#7, cs_ext_discount_amt#8] +Input [4]: [cs_item_sk#7, cs_ext_discount_amt#8, cs_sold_date_sk#9, d_date_sk#11] + +(17) HashAggregate [codegen id : 3] +Input [2]: [cs_item_sk#7, cs_ext_discount_amt#8] +Keys [1]: [cs_item_sk#7] +Functions [1]: [partial_avg(UnscaledValue(cs_ext_discount_amt#8))] +Aggregate Attributes [2]: [sum#12, count#13] +Results [3]: [cs_item_sk#7, sum#14, count#15] + +(18) Exchange +Input [3]: [cs_item_sk#7, sum#14, count#15] +Arguments: hashpartitioning(cs_item_sk#7, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(19) HashAggregate [codegen id : 4] +Input [3]: [cs_item_sk#7, sum#14, count#15] +Keys [1]: [cs_item_sk#7] +Functions [1]: [avg(UnscaledValue(cs_ext_discount_amt#8))] +Aggregate Attributes [1]: [avg(UnscaledValue(cs_ext_discount_amt#8))#16] +Results [2]: [(1.3 * cast((avg(UnscaledValue(cs_ext_discount_amt#8))#16 / 100.0) as decimal(11,6))) AS (1.3 * avg(cs_ext_discount_amt))#17, cs_item_sk#7] + +(20) Filter [codegen id : 4] +Input [2]: [(1.3 * avg(cs_ext_discount_amt))#17, cs_item_sk#7] +Condition : isnotnull((1.3 * avg(cs_ext_discount_amt))#17) + +(21) BroadcastExchange +Input [2]: [(1.3 * avg(cs_ext_discount_amt))#17, cs_item_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[1, int, true] as bigint)),false), [plan_id=3] + +(22) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [i_item_sk#5] +Right keys [1]: [cs_item_sk#7] +Join type: Inner +Join condition: (cast(cs_ext_discount_amt#2 as decimal(14,7)) > (1.3 * avg(cs_ext_discount_amt))#17) + +(23) Project [codegen id : 6] +Output [2]: [cs_ext_discount_amt#2, cs_sold_date_sk#3] +Input [5]: [cs_ext_discount_amt#2, cs_sold_date_sk#3, i_item_sk#5, (1.3 * avg(cs_ext_discount_amt))#17, cs_item_sk#7] + +(24) ReusedExchange [Reuses operator id: 34] +Output [1]: [d_date_sk#18] + +(25) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [cs_sold_date_sk#3] +Right keys [1]: [d_date_sk#18] +Join type: Inner +Join condition: None + +(26) Project [codegen id : 6] +Output [1]: [cs_ext_discount_amt#2] +Input [3]: [cs_ext_discount_amt#2, cs_sold_date_sk#3, d_date_sk#18] + +(27) HashAggregate [codegen id : 6] +Input [1]: [cs_ext_discount_amt#2] +Keys: [] +Functions [1]: [partial_sum(UnscaledValue(cs_ext_discount_amt#2))] +Aggregate Attributes [1]: [sum#19] +Results [1]: [sum#20] + +(28) Exchange +Input [1]: [sum#20] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=4] + +(29) HashAggregate [codegen id : 7] +Input [1]: [sum#20] +Keys: [] +Functions [1]: [sum(UnscaledValue(cs_ext_discount_amt#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(cs_ext_discount_amt#2))#21] +Results [1]: [MakeDecimal(sum(UnscaledValue(cs_ext_discount_amt#2))#21,17,2) AS excess discount amount#22] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (34) ++- * ColumnarToRow (33) + +- CometProject (32) + +- CometFilter (31) + +- CometScan parquet spark_catalog.default.date_dim (30) + + +(30) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#18, d_date#23] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,2000-01-27), LessThanOrEqual(d_date,2000-04-26), IsNotNull(d_date_sk)] +ReadSchema: struct + +(31) CometFilter +Input [2]: [d_date_sk#18, d_date#23] +Condition : (((isnotnull(d_date#23) AND (d_date#23 >= 2000-01-27)) AND (d_date#23 <= 2000-04-26)) AND isnotnull(d_date_sk#18)) + +(32) CometProject +Input [2]: [d_date_sk#18, d_date#23] +Arguments: [d_date_sk#18], [d_date_sk#18] + +(33) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#18] + +(34) BroadcastExchange +Input [1]: [d_date_sk#18] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +Subquery:2 Hosting operator id = 11 Hosting Expression = cs_sold_date_sk#9 IN dynamicpruning#4 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q32/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q32/simplified.txt new file mode 100644 index 0000000000..146a33fdd2 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q32/simplified.txt @@ -0,0 +1,52 @@ +WholeStageCodegen (7) + HashAggregate [sum] [sum(UnscaledValue(cs_ext_discount_amt)),excess discount amount,sum] + InputAdapter + Exchange #1 + WholeStageCodegen (6) + HashAggregate [cs_ext_discount_amt] [sum,sum] + Project [cs_ext_discount_amt] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_ext_discount_amt,cs_sold_date_sk] + BroadcastHashJoin [i_item_sk,cs_item_sk,cs_ext_discount_amt,(1.3 * avg(cs_ext_discount_amt))] + Project [cs_ext_discount_amt,cs_sold_date_sk,i_item_sk] + BroadcastHashJoin [cs_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk,cs_ext_discount_amt] + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_ext_discount_amt,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [i_item_sk] + CometFilter [i_manufact_id,i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_manufact_id] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (4) + Filter [(1.3 * avg(cs_ext_discount_amt))] + HashAggregate [cs_item_sk,sum,count] [avg(UnscaledValue(cs_ext_discount_amt)),(1.3 * avg(cs_ext_discount_amt)),sum,count] + InputAdapter + Exchange [cs_item_sk] #5 + WholeStageCodegen (3) + HashAggregate [cs_item_sk,cs_ext_discount_amt] [sum,count,sum,count] + Project [cs_item_sk,cs_ext_discount_amt] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_ext_discount_amt,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk] #2 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q33/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q33/explain.txt new file mode 100644 index 0000000000..f9541481cd --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q33/explain.txt @@ -0,0 +1,405 @@ +== Physical Plan == +TakeOrderedAndProject (63) ++- * HashAggregate (62) + +- Exchange (61) + +- * HashAggregate (60) + +- Union (59) + :- * HashAggregate (28) + : +- Exchange (27) + : +- * HashAggregate (26) + : +- * Project (25) + : +- * BroadcastHashJoin Inner BuildRight (24) + : :- * Project (13) + : : +- * BroadcastHashJoin Inner BuildRight (12) + : : :- * Project (6) + : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- ReusedExchange (4) + : : +- BroadcastExchange (11) + : : +- * ColumnarToRow (10) + : : +- CometProject (9) + : : +- CometFilter (8) + : : +- CometScan parquet spark_catalog.default.customer_address (7) + : +- BroadcastExchange (23) + : +- * BroadcastHashJoin LeftSemi BuildRight (22) + : :- * ColumnarToRow (16) + : : +- CometFilter (15) + : : +- CometScan parquet spark_catalog.default.item (14) + : +- BroadcastExchange (21) + : +- * ColumnarToRow (20) + : +- CometProject (19) + : +- CometFilter (18) + : +- CometScan parquet spark_catalog.default.item (17) + :- * HashAggregate (43) + : +- Exchange (42) + : +- * HashAggregate (41) + : +- * Project (40) + : +- * BroadcastHashJoin Inner BuildRight (39) + : :- * Project (37) + : : +- * BroadcastHashJoin Inner BuildRight (36) + : : :- * Project (34) + : : : +- * BroadcastHashJoin Inner BuildRight (33) + : : : :- * ColumnarToRow (31) + : : : : +- CometFilter (30) + : : : : +- CometScan parquet spark_catalog.default.catalog_sales (29) + : : : +- ReusedExchange (32) + : : +- ReusedExchange (35) + : +- ReusedExchange (38) + +- * HashAggregate (58) + +- Exchange (57) + +- * HashAggregate (56) + +- * Project (55) + +- * BroadcastHashJoin Inner BuildRight (54) + :- * Project (52) + : +- * BroadcastHashJoin Inner BuildRight (51) + : :- * Project (49) + : : +- * BroadcastHashJoin Inner BuildRight (48) + : : :- * ColumnarToRow (46) + : : : +- CometFilter (45) + : : : +- CometScan parquet spark_catalog.default.web_sales (44) + : : +- ReusedExchange (47) + : +- ReusedExchange (50) + +- ReusedExchange (53) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#4), dynamicpruningexpression(ss_sold_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(ss_addr_sk), IsNotNull(ss_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [4]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4] +Condition : (isnotnull(ss_addr_sk#2) AND isnotnull(ss_item_sk#1)) + +(3) ColumnarToRow [codegen id : 5] +Input [4]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4] + +(4) ReusedExchange [Reuses operator id: 68] +Output [1]: [d_date_sk#6] + +(5) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_sold_date_sk#4] +Right keys [1]: [d_date_sk#6] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 5] +Output [3]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3] +Input [5]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4, d_date_sk#6] + +(7) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#7, ca_gmt_offset#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_gmt_offset), EqualTo(ca_gmt_offset,-5.00), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(8) CometFilter +Input [2]: [ca_address_sk#7, ca_gmt_offset#8] +Condition : ((isnotnull(ca_gmt_offset#8) AND (ca_gmt_offset#8 = -5.00)) AND isnotnull(ca_address_sk#7)) + +(9) CometProject +Input [2]: [ca_address_sk#7, ca_gmt_offset#8] +Arguments: [ca_address_sk#7], [ca_address_sk#7] + +(10) ColumnarToRow [codegen id : 2] +Input [1]: [ca_address_sk#7] + +(11) BroadcastExchange +Input [1]: [ca_address_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(12) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_addr_sk#2] +Right keys [1]: [ca_address_sk#7] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 5] +Output [2]: [ss_item_sk#1, ss_ext_sales_price#3] +Input [4]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ca_address_sk#7] + +(14) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#9, i_manufact_id#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(15) CometFilter +Input [2]: [i_item_sk#9, i_manufact_id#10] +Condition : isnotnull(i_item_sk#9) + +(16) ColumnarToRow [codegen id : 4] +Input [2]: [i_item_sk#9, i_manufact_id#10] + +(17) Scan parquet spark_catalog.default.item +Output [2]: [i_category#11, i_manufact_id#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_category), EqualTo(i_category,Electronics )] +ReadSchema: struct + +(18) CometFilter +Input [2]: [i_category#11, i_manufact_id#12] +Condition : (isnotnull(i_category#11) AND (i_category#11 = Electronics )) + +(19) CometProject +Input [2]: [i_category#11, i_manufact_id#12] +Arguments: [i_manufact_id#12], [i_manufact_id#12] + +(20) ColumnarToRow [codegen id : 3] +Input [1]: [i_manufact_id#12] + +(21) BroadcastExchange +Input [1]: [i_manufact_id#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(22) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [i_manufact_id#10] +Right keys [1]: [i_manufact_id#12] +Join type: LeftSemi +Join condition: None + +(23) BroadcastExchange +Input [2]: [i_item_sk#9, i_manufact_id#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#9] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 5] +Output [2]: [ss_ext_sales_price#3, i_manufact_id#10] +Input [4]: [ss_item_sk#1, ss_ext_sales_price#3, i_item_sk#9, i_manufact_id#10] + +(26) HashAggregate [codegen id : 5] +Input [2]: [ss_ext_sales_price#3, i_manufact_id#10] +Keys [1]: [i_manufact_id#10] +Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#3))] +Aggregate Attributes [1]: [sum#13] +Results [2]: [i_manufact_id#10, sum#14] + +(27) Exchange +Input [2]: [i_manufact_id#10, sum#14] +Arguments: hashpartitioning(i_manufact_id#10, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(28) HashAggregate [codegen id : 6] +Input [2]: [i_manufact_id#10, sum#14] +Keys [1]: [i_manufact_id#10] +Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#3))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#3))#15] +Results [2]: [i_manufact_id#10, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#3))#15,17,2) AS total_sales#16] + +(29) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, cs_sold_date_sk#20] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#20), dynamicpruningexpression(cs_sold_date_sk#20 IN dynamicpruning#21)] +PushedFilters: [IsNotNull(cs_bill_addr_sk), IsNotNull(cs_item_sk)] +ReadSchema: struct + +(30) CometFilter +Input [4]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, cs_sold_date_sk#20] +Condition : (isnotnull(cs_bill_addr_sk#17) AND isnotnull(cs_item_sk#18)) + +(31) ColumnarToRow [codegen id : 11] +Input [4]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, cs_sold_date_sk#20] + +(32) ReusedExchange [Reuses operator id: 68] +Output [1]: [d_date_sk#22] + +(33) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [cs_sold_date_sk#20] +Right keys [1]: [d_date_sk#22] +Join type: Inner +Join condition: None + +(34) Project [codegen id : 11] +Output [3]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19] +Input [5]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, cs_sold_date_sk#20, d_date_sk#22] + +(35) ReusedExchange [Reuses operator id: 11] +Output [1]: [ca_address_sk#23] + +(36) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [cs_bill_addr_sk#17] +Right keys [1]: [ca_address_sk#23] +Join type: Inner +Join condition: None + +(37) Project [codegen id : 11] +Output [2]: [cs_item_sk#18, cs_ext_sales_price#19] +Input [4]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, ca_address_sk#23] + +(38) ReusedExchange [Reuses operator id: 23] +Output [2]: [i_item_sk#24, i_manufact_id#25] + +(39) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [cs_item_sk#18] +Right keys [1]: [i_item_sk#24] +Join type: Inner +Join condition: None + +(40) Project [codegen id : 11] +Output [2]: [cs_ext_sales_price#19, i_manufact_id#25] +Input [4]: [cs_item_sk#18, cs_ext_sales_price#19, i_item_sk#24, i_manufact_id#25] + +(41) HashAggregate [codegen id : 11] +Input [2]: [cs_ext_sales_price#19, i_manufact_id#25] +Keys [1]: [i_manufact_id#25] +Functions [1]: [partial_sum(UnscaledValue(cs_ext_sales_price#19))] +Aggregate Attributes [1]: [sum#26] +Results [2]: [i_manufact_id#25, sum#27] + +(42) Exchange +Input [2]: [i_manufact_id#25, sum#27] +Arguments: hashpartitioning(i_manufact_id#25, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(43) HashAggregate [codegen id : 12] +Input [2]: [i_manufact_id#25, sum#27] +Keys [1]: [i_manufact_id#25] +Functions [1]: [sum(UnscaledValue(cs_ext_sales_price#19))] +Aggregate Attributes [1]: [sum(UnscaledValue(cs_ext_sales_price#19))#28] +Results [2]: [i_manufact_id#25, MakeDecimal(sum(UnscaledValue(cs_ext_sales_price#19))#28,17,2) AS total_sales#29] + +(44) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ws_sold_date_sk#33] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#33), dynamicpruningexpression(ws_sold_date_sk#33 IN dynamicpruning#34)] +PushedFilters: [IsNotNull(ws_bill_addr_sk), IsNotNull(ws_item_sk)] +ReadSchema: struct + +(45) CometFilter +Input [4]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ws_sold_date_sk#33] +Condition : (isnotnull(ws_bill_addr_sk#31) AND isnotnull(ws_item_sk#30)) + +(46) ColumnarToRow [codegen id : 17] +Input [4]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ws_sold_date_sk#33] + +(47) ReusedExchange [Reuses operator id: 68] +Output [1]: [d_date_sk#35] + +(48) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ws_sold_date_sk#33] +Right keys [1]: [d_date_sk#35] +Join type: Inner +Join condition: None + +(49) Project [codegen id : 17] +Output [3]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32] +Input [5]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ws_sold_date_sk#33, d_date_sk#35] + +(50) ReusedExchange [Reuses operator id: 11] +Output [1]: [ca_address_sk#36] + +(51) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ws_bill_addr_sk#31] +Right keys [1]: [ca_address_sk#36] +Join type: Inner +Join condition: None + +(52) Project [codegen id : 17] +Output [2]: [ws_item_sk#30, ws_ext_sales_price#32] +Input [4]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ca_address_sk#36] + +(53) ReusedExchange [Reuses operator id: 23] +Output [2]: [i_item_sk#37, i_manufact_id#38] + +(54) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ws_item_sk#30] +Right keys [1]: [i_item_sk#37] +Join type: Inner +Join condition: None + +(55) Project [codegen id : 17] +Output [2]: [ws_ext_sales_price#32, i_manufact_id#38] +Input [4]: [ws_item_sk#30, ws_ext_sales_price#32, i_item_sk#37, i_manufact_id#38] + +(56) HashAggregate [codegen id : 17] +Input [2]: [ws_ext_sales_price#32, i_manufact_id#38] +Keys [1]: [i_manufact_id#38] +Functions [1]: [partial_sum(UnscaledValue(ws_ext_sales_price#32))] +Aggregate Attributes [1]: [sum#39] +Results [2]: [i_manufact_id#38, sum#40] + +(57) Exchange +Input [2]: [i_manufact_id#38, sum#40] +Arguments: hashpartitioning(i_manufact_id#38, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(58) HashAggregate [codegen id : 18] +Input [2]: [i_manufact_id#38, sum#40] +Keys [1]: [i_manufact_id#38] +Functions [1]: [sum(UnscaledValue(ws_ext_sales_price#32))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_ext_sales_price#32))#41] +Results [2]: [i_manufact_id#38, MakeDecimal(sum(UnscaledValue(ws_ext_sales_price#32))#41,17,2) AS total_sales#42] + +(59) Union + +(60) HashAggregate [codegen id : 19] +Input [2]: [i_manufact_id#10, total_sales#16] +Keys [1]: [i_manufact_id#10] +Functions [1]: [partial_sum(total_sales#16)] +Aggregate Attributes [2]: [sum#43, isEmpty#44] +Results [3]: [i_manufact_id#10, sum#45, isEmpty#46] + +(61) Exchange +Input [3]: [i_manufact_id#10, sum#45, isEmpty#46] +Arguments: hashpartitioning(i_manufact_id#10, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(62) HashAggregate [codegen id : 20] +Input [3]: [i_manufact_id#10, sum#45, isEmpty#46] +Keys [1]: [i_manufact_id#10] +Functions [1]: [sum(total_sales#16)] +Aggregate Attributes [1]: [sum(total_sales#16)#47] +Results [2]: [i_manufact_id#10, sum(total_sales#16)#47 AS total_sales#48] + +(63) TakeOrderedAndProject +Input [2]: [i_manufact_id#10, total_sales#48] +Arguments: 100, [total_sales#48 ASC NULLS FIRST], [i_manufact_id#10, total_sales#48] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (68) ++- * ColumnarToRow (67) + +- CometProject (66) + +- CometFilter (65) + +- CometScan parquet spark_catalog.default.date_dim (64) + + +(64) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#6, d_year#49, d_moy#50] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,1998), EqualTo(d_moy,5), IsNotNull(d_date_sk)] +ReadSchema: struct + +(65) CometFilter +Input [3]: [d_date_sk#6, d_year#49, d_moy#50] +Condition : ((((isnotnull(d_year#49) AND isnotnull(d_moy#50)) AND (d_year#49 = 1998)) AND (d_moy#50 = 5)) AND isnotnull(d_date_sk#6)) + +(66) CometProject +Input [3]: [d_date_sk#6, d_year#49, d_moy#50] +Arguments: [d_date_sk#6], [d_date_sk#6] + +(67) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#6] + +(68) BroadcastExchange +Input [1]: [d_date_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + +Subquery:2 Hosting operator id = 29 Hosting Expression = cs_sold_date_sk#20 IN dynamicpruning#5 + +Subquery:3 Hosting operator id = 44 Hosting Expression = ws_sold_date_sk#33 IN dynamicpruning#5 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q33/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q33/simplified.txt new file mode 100644 index 0000000000..4ab82379ff --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q33/simplified.txt @@ -0,0 +1,105 @@ +TakeOrderedAndProject [total_sales,i_manufact_id] + WholeStageCodegen (20) + HashAggregate [i_manufact_id,sum,isEmpty] [sum(total_sales),total_sales,sum,isEmpty] + InputAdapter + Exchange [i_manufact_id] #1 + WholeStageCodegen (19) + HashAggregate [i_manufact_id,total_sales] [sum,isEmpty,sum,isEmpty] + InputAdapter + Union + WholeStageCodegen (6) + HashAggregate [i_manufact_id,sum] [sum(UnscaledValue(ss_ext_sales_price)),total_sales,sum] + InputAdapter + Exchange [i_manufact_id] #2 + WholeStageCodegen (5) + HashAggregate [i_manufact_id,ss_ext_sales_price] [sum,sum] + Project [ss_ext_sales_price,i_manufact_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_ext_sales_price] + BroadcastHashJoin [ss_addr_sk,ca_address_sk] + Project [ss_item_sk,ss_addr_sk,ss_ext_sales_price] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_addr_sk,ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_addr_sk,ss_ext_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_moy,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometProject [ca_address_sk] + CometFilter [ca_gmt_offset,ca_address_sk] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_gmt_offset] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (4) + BroadcastHashJoin [i_manufact_id,i_manufact_id] + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_manufact_id] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometProject [i_manufact_id] + CometFilter [i_category] + CometScan parquet spark_catalog.default.item [i_category,i_manufact_id] + WholeStageCodegen (12) + HashAggregate [i_manufact_id,sum] [sum(UnscaledValue(cs_ext_sales_price)),total_sales,sum] + InputAdapter + Exchange [i_manufact_id] #7 + WholeStageCodegen (11) + HashAggregate [i_manufact_id,cs_ext_sales_price] [sum,sum] + Project [cs_ext_sales_price,i_manufact_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Project [cs_item_sk,cs_ext_sales_price] + BroadcastHashJoin [cs_bill_addr_sk,ca_address_sk] + Project [cs_bill_addr_sk,cs_item_sk,cs_ext_sales_price] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [cs_bill_addr_sk,cs_item_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_addr_sk,cs_item_sk,cs_ext_sales_price,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + ReusedExchange [ca_address_sk] #4 + InputAdapter + ReusedExchange [i_item_sk,i_manufact_id] #5 + WholeStageCodegen (18) + HashAggregate [i_manufact_id,sum] [sum(UnscaledValue(ws_ext_sales_price)),total_sales,sum] + InputAdapter + Exchange [i_manufact_id] #8 + WholeStageCodegen (17) + HashAggregate [i_manufact_id,ws_ext_sales_price] [sum,sum] + Project [ws_ext_sales_price,i_manufact_id] + BroadcastHashJoin [ws_item_sk,i_item_sk] + Project [ws_item_sk,ws_ext_sales_price] + BroadcastHashJoin [ws_bill_addr_sk,ca_address_sk] + Project [ws_item_sk,ws_bill_addr_sk,ws_ext_sales_price] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ws_bill_addr_sk,ws_item_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_bill_addr_sk,ws_ext_sales_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + ReusedExchange [ca_address_sk] #4 + InputAdapter + ReusedExchange [i_item_sk,i_manufact_id] #5 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q34/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q34/explain.txt new file mode 100644 index 0000000000..d0f166fe9d --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q34/explain.txt @@ -0,0 +1,218 @@ +== Physical Plan == +* Sort (32) ++- Exchange (31) + +- * Project (30) + +- * BroadcastHashJoin Inner BuildRight (29) + :- * Filter (24) + : +- * HashAggregate (23) + : +- Exchange (22) + : +- * HashAggregate (21) + : +- * Project (20) + : +- * BroadcastHashJoin Inner BuildRight (19) + : :- * Project (13) + : : +- * BroadcastHashJoin Inner BuildRight (12) + : : :- * Project (6) + : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- ReusedExchange (4) + : : +- BroadcastExchange (11) + : : +- * ColumnarToRow (10) + : : +- CometProject (9) + : : +- CometFilter (8) + : : +- CometScan parquet spark_catalog.default.store (7) + : +- BroadcastExchange (18) + : +- * ColumnarToRow (17) + : +- CometProject (16) + : +- CometFilter (15) + : +- CometScan parquet spark_catalog.default.household_demographics (14) + +- BroadcastExchange (28) + +- * ColumnarToRow (27) + +- CometFilter (26) + +- CometScan parquet spark_catalog.default.customer (25) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#5), dynamicpruningexpression(ss_sold_date_sk#5 IN dynamicpruning#6)] +PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_hdemo_sk), IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(2) CometFilter +Input [5]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5] +Condition : ((isnotnull(ss_store_sk#3) AND isnotnull(ss_hdemo_sk#2)) AND isnotnull(ss_customer_sk#1)) + +(3) ColumnarToRow [codegen id : 4] +Input [5]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5] + +(4) ReusedExchange [Reuses operator id: 37] +Output [1]: [d_date_sk#7] + +(5) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_date_sk#5] +Right keys [1]: [d_date_sk#7] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 4] +Output [4]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4] +Input [6]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5, d_date_sk#7] + +(7) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#8, s_county#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_county), EqualTo(s_county,Williamson County), IsNotNull(s_store_sk)] +ReadSchema: struct + +(8) CometFilter +Input [2]: [s_store_sk#8, s_county#9] +Condition : ((isnotnull(s_county#9) AND (s_county#9 = Williamson County)) AND isnotnull(s_store_sk#8)) + +(9) CometProject +Input [2]: [s_store_sk#8, s_county#9] +Arguments: [s_store_sk#8], [s_store_sk#8] + +(10) ColumnarToRow [codegen id : 2] +Input [1]: [s_store_sk#8] + +(11) BroadcastExchange +Input [1]: [s_store_sk#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(12) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_store_sk#3] +Right keys [1]: [s_store_sk#8] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 4] +Output [3]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_ticket_number#4] +Input [5]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, s_store_sk#8] + +(14) Scan parquet spark_catalog.default.household_demographics +Output [4]: [hd_demo_sk#10, hd_buy_potential#11, hd_dep_count#12, hd_vehicle_count#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/household_demographics] +PushedFilters: [IsNotNull(hd_vehicle_count), Or(EqualTo(hd_buy_potential,>10000 ),EqualTo(hd_buy_potential,unknown )), GreaterThan(hd_vehicle_count,0), IsNotNull(hd_demo_sk)] +ReadSchema: struct + +(15) CometFilter +Input [4]: [hd_demo_sk#10, hd_buy_potential#11, hd_dep_count#12, hd_vehicle_count#13] +Condition : ((((isnotnull(hd_vehicle_count#13) AND ((hd_buy_potential#11 = >10000 ) OR (hd_buy_potential#11 = unknown ))) AND (hd_vehicle_count#13 > 0)) AND CASE WHEN (hd_vehicle_count#13 > 0) THEN ((cast(hd_dep_count#12 as double) / cast(hd_vehicle_count#13 as double)) > 1.2) END) AND isnotnull(hd_demo_sk#10)) + +(16) CometProject +Input [4]: [hd_demo_sk#10, hd_buy_potential#11, hd_dep_count#12, hd_vehicle_count#13] +Arguments: [hd_demo_sk#10], [hd_demo_sk#10] + +(17) ColumnarToRow [codegen id : 3] +Input [1]: [hd_demo_sk#10] + +(18) BroadcastExchange +Input [1]: [hd_demo_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(19) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_hdemo_sk#2] +Right keys [1]: [hd_demo_sk#10] +Join type: Inner +Join condition: None + +(20) Project [codegen id : 4] +Output [2]: [ss_customer_sk#1, ss_ticket_number#4] +Input [4]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_ticket_number#4, hd_demo_sk#10] + +(21) HashAggregate [codegen id : 4] +Input [2]: [ss_customer_sk#1, ss_ticket_number#4] +Keys [2]: [ss_ticket_number#4, ss_customer_sk#1] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#14] +Results [3]: [ss_ticket_number#4, ss_customer_sk#1, count#15] + +(22) Exchange +Input [3]: [ss_ticket_number#4, ss_customer_sk#1, count#15] +Arguments: hashpartitioning(ss_ticket_number#4, ss_customer_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(23) HashAggregate [codegen id : 6] +Input [3]: [ss_ticket_number#4, ss_customer_sk#1, count#15] +Keys [2]: [ss_ticket_number#4, ss_customer_sk#1] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#16] +Results [3]: [ss_ticket_number#4, ss_customer_sk#1, count(1)#16 AS cnt#17] + +(24) Filter [codegen id : 6] +Input [3]: [ss_ticket_number#4, ss_customer_sk#1, cnt#17] +Condition : ((cnt#17 >= 15) AND (cnt#17 <= 20)) + +(25) Scan parquet spark_catalog.default.customer +Output [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk)] +ReadSchema: struct + +(26) CometFilter +Input [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] +Condition : isnotnull(c_customer_sk#18) + +(27) ColumnarToRow [codegen id : 5] +Input [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] + +(28) BroadcastExchange +Input [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(29) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_customer_sk#1] +Right keys [1]: [c_customer_sk#18] +Join type: Inner +Join condition: None + +(30) Project [codegen id : 6] +Output [6]: [c_last_name#21, c_first_name#20, c_salutation#19, c_preferred_cust_flag#22, ss_ticket_number#4, cnt#17] +Input [8]: [ss_ticket_number#4, ss_customer_sk#1, cnt#17, c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] + +(31) Exchange +Input [6]: [c_last_name#21, c_first_name#20, c_salutation#19, c_preferred_cust_flag#22, ss_ticket_number#4, cnt#17] +Arguments: rangepartitioning(c_last_name#21 ASC NULLS FIRST, c_first_name#20 ASC NULLS FIRST, c_salutation#19 ASC NULLS FIRST, c_preferred_cust_flag#22 DESC NULLS LAST, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(32) Sort [codegen id : 7] +Input [6]: [c_last_name#21, c_first_name#20, c_salutation#19, c_preferred_cust_flag#22, ss_ticket_number#4, cnt#17] +Arguments: [c_last_name#21 ASC NULLS FIRST, c_first_name#20 ASC NULLS FIRST, c_salutation#19 ASC NULLS FIRST, c_preferred_cust_flag#22 DESC NULLS LAST], true, 0 + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6 +BroadcastExchange (37) ++- * ColumnarToRow (36) + +- CometProject (35) + +- CometFilter (34) + +- CometScan parquet spark_catalog.default.date_dim (33) + + +(33) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#7, d_year#23, d_dom#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [Or(And(GreaterThanOrEqual(d_dom,1),LessThanOrEqual(d_dom,3)),And(GreaterThanOrEqual(d_dom,25),LessThanOrEqual(d_dom,28))), In(d_year, [1999,2000,2001]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(34) CometFilter +Input [3]: [d_date_sk#7, d_year#23, d_dom#24] +Condition : (((((d_dom#24 >= 1) AND (d_dom#24 <= 3)) OR ((d_dom#24 >= 25) AND (d_dom#24 <= 28))) AND d_year#23 IN (1999,2000,2001)) AND isnotnull(d_date_sk#7)) + +(35) CometProject +Input [3]: [d_date_sk#7, d_year#23, d_dom#24] +Arguments: [d_date_sk#7], [d_date_sk#7] + +(36) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#7] + +(37) BroadcastExchange +Input [1]: [d_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q34/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q34/simplified.txt new file mode 100644 index 0000000000..80405a784d --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q34/simplified.txt @@ -0,0 +1,56 @@ +WholeStageCodegen (7) + Sort [c_last_name,c_first_name,c_salutation,c_preferred_cust_flag] + InputAdapter + Exchange [c_last_name,c_first_name,c_salutation,c_preferred_cust_flag] #1 + WholeStageCodegen (6) + Project [c_last_name,c_first_name,c_salutation,c_preferred_cust_flag,ss_ticket_number,cnt] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Filter [cnt] + HashAggregate [ss_ticket_number,ss_customer_sk,count] [count(1),cnt,count] + InputAdapter + Exchange [ss_ticket_number,ss_customer_sk] #2 + WholeStageCodegen (4) + HashAggregate [ss_ticket_number,ss_customer_sk] [count,count] + Project [ss_customer_sk,ss_ticket_number] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + Project [ss_customer_sk,ss_hdemo_sk,ss_ticket_number] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_customer_sk,ss_hdemo_sk,ss_store_sk,ss_ticket_number] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk,ss_hdemo_sk,ss_customer_sk] + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_hdemo_sk,ss_store_sk,ss_ticket_number,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_dom,d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_dom] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometProject [s_store_sk] + CometFilter [s_county,s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk,s_county] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometProject [hd_demo_sk] + CometFilter [hd_vehicle_count,hd_buy_potential,hd_dep_count,hd_demo_sk] + CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_buy_potential,hd_dep_count,hd_vehicle_count] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (5) + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_salutation,c_first_name,c_last_name,c_preferred_cust_flag] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q35/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q35/explain.txt new file mode 100644 index 0000000000..a46018cdd0 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q35/explain.txt @@ -0,0 +1,281 @@ +== Physical Plan == +TakeOrderedAndProject (42) ++- * HashAggregate (41) + +- Exchange (40) + +- * HashAggregate (39) + +- * Project (38) + +- * BroadcastHashJoin Inner BuildRight (37) + :- * Project (32) + : +- * BroadcastHashJoin Inner BuildRight (31) + : :- * Project (26) + : : +- * Filter (25) + : : +- * BroadcastHashJoin ExistenceJoin(exists#1) BuildRight (24) + : : :- * BroadcastHashJoin ExistenceJoin(exists#2) BuildRight (17) + : : : :- * BroadcastHashJoin LeftSemi BuildRight (10) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) + : : : : : +- CometScan parquet spark_catalog.default.customer (1) + : : : : +- BroadcastExchange (9) + : : : : +- * Project (8) + : : : : +- * BroadcastHashJoin Inner BuildRight (7) + : : : : :- * ColumnarToRow (5) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (4) + : : : : +- ReusedExchange (6) + : : : +- BroadcastExchange (16) + : : : +- * Project (15) + : : : +- * BroadcastHashJoin Inner BuildRight (14) + : : : :- * ColumnarToRow (12) + : : : : +- CometScan parquet spark_catalog.default.web_sales (11) + : : : +- ReusedExchange (13) + : : +- BroadcastExchange (23) + : : +- * Project (22) + : : +- * BroadcastHashJoin Inner BuildRight (21) + : : :- * ColumnarToRow (19) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (18) + : : +- ReusedExchange (20) + : +- BroadcastExchange (30) + : +- * ColumnarToRow (29) + : +- CometFilter (28) + : +- CometScan parquet spark_catalog.default.customer_address (27) + +- BroadcastExchange (36) + +- * ColumnarToRow (35) + +- CometFilter (34) + +- CometScan parquet spark_catalog.default.customer_demographics (33) + + +(1) Scan parquet spark_catalog.default.customer +Output [3]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_current_addr_sk), IsNotNull(c_current_cdemo_sk)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5] +Condition : (isnotnull(c_current_addr_sk#5) AND isnotnull(c_current_cdemo_sk#4)) + +(3) ColumnarToRow [codegen id : 9] +Input [3]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5] + +(4) Scan parquet spark_catalog.default.store_sales +Output [2]: [ss_customer_sk#6, ss_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sold_date_sk#7 IN dynamicpruning#8)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 2] +Input [2]: [ss_customer_sk#6, ss_sold_date_sk#7] + +(6) ReusedExchange [Reuses operator id: 47] +Output [1]: [d_date_sk#9] + +(7) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [ss_sold_date_sk#7] +Right keys [1]: [d_date_sk#9] +Join type: Inner +Join condition: None + +(8) Project [codegen id : 2] +Output [1]: [ss_customer_sk#6] +Input [3]: [ss_customer_sk#6, ss_sold_date_sk#7, d_date_sk#9] + +(9) BroadcastExchange +Input [1]: [ss_customer_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(10) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_customer_sk#3] +Right keys [1]: [ss_customer_sk#6] +Join type: LeftSemi +Join condition: None + +(11) Scan parquet spark_catalog.default.web_sales +Output [2]: [ws_bill_customer_sk#10, ws_sold_date_sk#11] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#11), dynamicpruningexpression(ws_sold_date_sk#11 IN dynamicpruning#12)] +ReadSchema: struct + +(12) ColumnarToRow [codegen id : 4] +Input [2]: [ws_bill_customer_sk#10, ws_sold_date_sk#11] + +(13) ReusedExchange [Reuses operator id: 47] +Output [1]: [d_date_sk#13] + +(14) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ws_sold_date_sk#11] +Right keys [1]: [d_date_sk#13] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 4] +Output [1]: [ws_bill_customer_sk#10] +Input [3]: [ws_bill_customer_sk#10, ws_sold_date_sk#11, d_date_sk#13] + +(16) BroadcastExchange +Input [1]: [ws_bill_customer_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(17) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_customer_sk#3] +Right keys [1]: [ws_bill_customer_sk#10] +Join type: ExistenceJoin(exists#2) +Join condition: None + +(18) Scan parquet spark_catalog.default.catalog_sales +Output [2]: [cs_ship_customer_sk#14, cs_sold_date_sk#15] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#15), dynamicpruningexpression(cs_sold_date_sk#15 IN dynamicpruning#16)] +ReadSchema: struct + +(19) ColumnarToRow [codegen id : 6] +Input [2]: [cs_ship_customer_sk#14, cs_sold_date_sk#15] + +(20) ReusedExchange [Reuses operator id: 47] +Output [1]: [d_date_sk#17] + +(21) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [cs_sold_date_sk#15] +Right keys [1]: [d_date_sk#17] +Join type: Inner +Join condition: None + +(22) Project [codegen id : 6] +Output [1]: [cs_ship_customer_sk#14] +Input [3]: [cs_ship_customer_sk#14, cs_sold_date_sk#15, d_date_sk#17] + +(23) BroadcastExchange +Input [1]: [cs_ship_customer_sk#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_customer_sk#3] +Right keys [1]: [cs_ship_customer_sk#14] +Join type: ExistenceJoin(exists#1) +Join condition: None + +(25) Filter [codegen id : 9] +Input [5]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5, exists#2, exists#1] +Condition : (exists#2 OR exists#1) + +(26) Project [codegen id : 9] +Output [2]: [c_current_cdemo_sk#4, c_current_addr_sk#5] +Input [5]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5, exists#2, exists#1] + +(27) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#18, ca_state#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk)] +ReadSchema: struct + +(28) CometFilter +Input [2]: [ca_address_sk#18, ca_state#19] +Condition : isnotnull(ca_address_sk#18) + +(29) ColumnarToRow [codegen id : 7] +Input [2]: [ca_address_sk#18, ca_state#19] + +(30) BroadcastExchange +Input [2]: [ca_address_sk#18, ca_state#19] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(31) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_current_addr_sk#5] +Right keys [1]: [ca_address_sk#18] +Join type: Inner +Join condition: None + +(32) Project [codegen id : 9] +Output [2]: [c_current_cdemo_sk#4, ca_state#19] +Input [4]: [c_current_cdemo_sk#4, c_current_addr_sk#5, ca_address_sk#18, ca_state#19] + +(33) Scan parquet spark_catalog.default.customer_demographics +Output [6]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(34) CometFilter +Input [6]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Condition : isnotnull(cd_demo_sk#20) + +(35) ColumnarToRow [codegen id : 8] +Input [6]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] + +(36) BroadcastExchange +Input [6]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(37) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_current_cdemo_sk#4] +Right keys [1]: [cd_demo_sk#20] +Join type: Inner +Join condition: None + +(38) Project [codegen id : 9] +Output [6]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Input [8]: [c_current_cdemo_sk#4, ca_state#19, cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] + +(39) HashAggregate [codegen id : 9] +Input [6]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Keys [6]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Functions [10]: [partial_count(1), partial_min(cd_dep_count#23), partial_max(cd_dep_count#23), partial_avg(cd_dep_count#23), partial_min(cd_dep_employed_count#24), partial_max(cd_dep_employed_count#24), partial_avg(cd_dep_employed_count#24), partial_min(cd_dep_college_count#25), partial_max(cd_dep_college_count#25), partial_avg(cd_dep_college_count#25)] +Aggregate Attributes [13]: [count#26, min#27, max#28, sum#29, count#30, min#31, max#32, sum#33, count#34, min#35, max#36, sum#37, count#38] +Results [19]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25, count#39, min#40, max#41, sum#42, count#43, min#44, max#45, sum#46, count#47, min#48, max#49, sum#50, count#51] + +(40) Exchange +Input [19]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25, count#39, min#40, max#41, sum#42, count#43, min#44, max#45, sum#46, count#47, min#48, max#49, sum#50, count#51] +Arguments: hashpartitioning(ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(41) HashAggregate [codegen id : 10] +Input [19]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25, count#39, min#40, max#41, sum#42, count#43, min#44, max#45, sum#46, count#47, min#48, max#49, sum#50, count#51] +Keys [6]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Functions [10]: [count(1), min(cd_dep_count#23), max(cd_dep_count#23), avg(cd_dep_count#23), min(cd_dep_employed_count#24), max(cd_dep_employed_count#24), avg(cd_dep_employed_count#24), min(cd_dep_college_count#25), max(cd_dep_college_count#25), avg(cd_dep_college_count#25)] +Aggregate Attributes [10]: [count(1)#52, min(cd_dep_count#23)#53, max(cd_dep_count#23)#54, avg(cd_dep_count#23)#55, min(cd_dep_employed_count#24)#56, max(cd_dep_employed_count#24)#57, avg(cd_dep_employed_count#24)#58, min(cd_dep_college_count#25)#59, max(cd_dep_college_count#25)#60, avg(cd_dep_college_count#25)#61] +Results [18]: [ca_state#19, cd_gender#21, cd_marital_status#22, count(1)#52 AS cnt1#62, min(cd_dep_count#23)#53 AS min(cd_dep_count)#63, max(cd_dep_count#23)#54 AS max(cd_dep_count)#64, avg(cd_dep_count#23)#55 AS avg(cd_dep_count)#65, cd_dep_employed_count#24, count(1)#52 AS cnt2#66, min(cd_dep_employed_count#24)#56 AS min(cd_dep_employed_count)#67, max(cd_dep_employed_count#24)#57 AS max(cd_dep_employed_count)#68, avg(cd_dep_employed_count#24)#58 AS avg(cd_dep_employed_count)#69, cd_dep_college_count#25, count(1)#52 AS cnt3#70, min(cd_dep_college_count#25)#59 AS min(cd_dep_college_count)#71, max(cd_dep_college_count#25)#60 AS max(cd_dep_college_count)#72, avg(cd_dep_college_count#25)#61 AS avg(cd_dep_college_count)#73, cd_dep_count#23] + +(42) TakeOrderedAndProject +Input [18]: [ca_state#19, cd_gender#21, cd_marital_status#22, cnt1#62, min(cd_dep_count)#63, max(cd_dep_count)#64, avg(cd_dep_count)#65, cd_dep_employed_count#24, cnt2#66, min(cd_dep_employed_count)#67, max(cd_dep_employed_count)#68, avg(cd_dep_employed_count)#69, cd_dep_college_count#25, cnt3#70, min(cd_dep_college_count)#71, max(cd_dep_college_count)#72, avg(cd_dep_college_count)#73, cd_dep_count#23] +Arguments: 100, [ca_state#19 ASC NULLS FIRST, cd_gender#21 ASC NULLS FIRST, cd_marital_status#22 ASC NULLS FIRST, cd_dep_count#23 ASC NULLS FIRST, cd_dep_employed_count#24 ASC NULLS FIRST, cd_dep_college_count#25 ASC NULLS FIRST], [ca_state#19, cd_gender#21, cd_marital_status#22, cnt1#62, min(cd_dep_count)#63, max(cd_dep_count)#64, avg(cd_dep_count)#65, cd_dep_employed_count#24, cnt2#66, min(cd_dep_employed_count)#67, max(cd_dep_employed_count)#68, avg(cd_dep_employed_count)#69, cd_dep_college_count#25, cnt3#70, min(cd_dep_college_count)#71, max(cd_dep_college_count)#72, avg(cd_dep_college_count)#73] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (47) ++- * ColumnarToRow (46) + +- CometProject (45) + +- CometFilter (44) + +- CometScan parquet spark_catalog.default.date_dim (43) + + +(43) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#9, d_year#74, d_qoy#75] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_qoy), EqualTo(d_year,2002), LessThan(d_qoy,4), IsNotNull(d_date_sk)] +ReadSchema: struct + +(44) CometFilter +Input [3]: [d_date_sk#9, d_year#74, d_qoy#75] +Condition : ((((isnotnull(d_year#74) AND isnotnull(d_qoy#75)) AND (d_year#74 = 2002)) AND (d_qoy#75 < 4)) AND isnotnull(d_date_sk#9)) + +(45) CometProject +Input [3]: [d_date_sk#9, d_year#74, d_qoy#75] +Arguments: [d_date_sk#9], [d_date_sk#9] + +(46) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#9] + +(47) BroadcastExchange +Input [1]: [d_date_sk#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +Subquery:2 Hosting operator id = 11 Hosting Expression = ws_sold_date_sk#11 IN dynamicpruning#8 + +Subquery:3 Hosting operator id = 18 Hosting Expression = cs_sold_date_sk#15 IN dynamicpruning#8 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q35/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q35/simplified.txt new file mode 100644 index 0000000000..ea0ef274ea --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q35/simplified.txt @@ -0,0 +1,74 @@ +TakeOrderedAndProject [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count,cnt1,min(cd_dep_count),max(cd_dep_count),avg(cd_dep_count),cnt2,min(cd_dep_employed_count),max(cd_dep_employed_count),avg(cd_dep_employed_count),cnt3,min(cd_dep_college_count),max(cd_dep_college_count),avg(cd_dep_college_count)] + WholeStageCodegen (10) + HashAggregate [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count,count,min,max,sum,count,min,max,sum,count,min,max,sum,count] [count(1),min(cd_dep_count),max(cd_dep_count),avg(cd_dep_count),min(cd_dep_employed_count),max(cd_dep_employed_count),avg(cd_dep_employed_count),min(cd_dep_college_count),max(cd_dep_college_count),avg(cd_dep_college_count),cnt1,min(cd_dep_count),max(cd_dep_count),avg(cd_dep_count),cnt2,min(cd_dep_employed_count),max(cd_dep_employed_count),avg(cd_dep_employed_count),cnt3,min(cd_dep_college_count),max(cd_dep_college_count),avg(cd_dep_college_count),count,min,max,sum,count,min,max,sum,count,min,max,sum,count] + InputAdapter + Exchange [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] #1 + WholeStageCodegen (9) + HashAggregate [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] [count,min,max,sum,count,min,max,sum,count,min,max,sum,count,count,min,max,sum,count,min,max,sum,count,min,max,sum,count] + Project [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk] + Project [c_current_cdemo_sk,ca_state] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [c_current_cdemo_sk,c_current_addr_sk] + Filter [exists,exists] + BroadcastHashJoin [c_customer_sk,cs_ship_customer_sk] + BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + ColumnarToRow + InputAdapter + CometFilter [c_current_addr_sk,c_current_cdemo_sk] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (2) + Project [ss_customer_sk] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_qoy,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_qoy] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (4) + Project [ws_bill_customer_sk] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (6) + Project [cs_ship_customer_sk] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_ship_customer_sk,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (7) + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (8) + ColumnarToRow + InputAdapter + CometFilter [cd_demo_sk] + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q36/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q36/explain.txt new file mode 100644 index 0000000000..39b8381577 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q36/explain.txt @@ -0,0 +1,194 @@ +== Physical Plan == +TakeOrderedAndProject (28) ++- * Project (27) + +- Window (26) + +- * Sort (25) + +- Exchange (24) + +- * HashAggregate (23) + +- Exchange (22) + +- * HashAggregate (21) + +- * Expand (20) + +- * Project (19) + +- * BroadcastHashJoin Inner BuildRight (18) + :- * Project (12) + : +- * BroadcastHashJoin Inner BuildRight (11) + : :- * Project (6) + : : +- * BroadcastHashJoin Inner BuildRight (5) + : : :- * ColumnarToRow (3) + : : : +- CometFilter (2) + : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : +- ReusedExchange (4) + : +- BroadcastExchange (10) + : +- * ColumnarToRow (9) + : +- CometFilter (8) + : +- CometScan parquet spark_catalog.default.item (7) + +- BroadcastExchange (17) + +- * ColumnarToRow (16) + +- CometProject (15) + +- CometFilter (14) + +- CometScan parquet spark_catalog.default.store (13) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, ss_sold_date_sk#5] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#5), dynamicpruningexpression(ss_sold_date_sk#5 IN dynamicpruning#6)] +PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(2) CometFilter +Input [5]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, ss_sold_date_sk#5] +Condition : (isnotnull(ss_item_sk#1) AND isnotnull(ss_store_sk#2)) + +(3) ColumnarToRow [codegen id : 4] +Input [5]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, ss_sold_date_sk#5] + +(4) ReusedExchange [Reuses operator id: 33] +Output [1]: [d_date_sk#7] + +(5) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_date_sk#5] +Right keys [1]: [d_date_sk#7] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 4] +Output [4]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4] +Input [6]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, ss_sold_date_sk#5, d_date_sk#7] + +(7) Scan parquet spark_catalog.default.item +Output [3]: [i_item_sk#8, i_class#9, i_category#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(8) CometFilter +Input [3]: [i_item_sk#8, i_class#9, i_category#10] +Condition : isnotnull(i_item_sk#8) + +(9) ColumnarToRow [codegen id : 2] +Input [3]: [i_item_sk#8, i_class#9, i_category#10] + +(10) BroadcastExchange +Input [3]: [i_item_sk#8, i_class#9, i_category#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(11) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#8] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 4] +Output [5]: [ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, i_class#9, i_category#10] +Input [7]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, i_item_sk#8, i_class#9, i_category#10] + +(13) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#11, s_state#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_state), EqualTo(s_state,TN), IsNotNull(s_store_sk)] +ReadSchema: struct + +(14) CometFilter +Input [2]: [s_store_sk#11, s_state#12] +Condition : ((isnotnull(s_state#12) AND (s_state#12 = TN)) AND isnotnull(s_store_sk#11)) + +(15) CometProject +Input [2]: [s_store_sk#11, s_state#12] +Arguments: [s_store_sk#11], [s_store_sk#11] + +(16) ColumnarToRow [codegen id : 3] +Input [1]: [s_store_sk#11] + +(17) BroadcastExchange +Input [1]: [s_store_sk#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(18) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_store_sk#2] +Right keys [1]: [s_store_sk#11] +Join type: Inner +Join condition: None + +(19) Project [codegen id : 4] +Output [4]: [ss_ext_sales_price#3, ss_net_profit#4, i_category#10, i_class#9] +Input [6]: [ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, i_class#9, i_category#10, s_store_sk#11] + +(20) Expand [codegen id : 4] +Input [4]: [ss_ext_sales_price#3, ss_net_profit#4, i_category#10, i_class#9] +Arguments: [[ss_ext_sales_price#3, ss_net_profit#4, i_category#10, i_class#9, 0], [ss_ext_sales_price#3, ss_net_profit#4, i_category#10, null, 1], [ss_ext_sales_price#3, ss_net_profit#4, null, null, 3]], [ss_ext_sales_price#3, ss_net_profit#4, i_category#13, i_class#14, spark_grouping_id#15] + +(21) HashAggregate [codegen id : 4] +Input [5]: [ss_ext_sales_price#3, ss_net_profit#4, i_category#13, i_class#14, spark_grouping_id#15] +Keys [3]: [i_category#13, i_class#14, spark_grouping_id#15] +Functions [2]: [partial_sum(UnscaledValue(ss_net_profit#4)), partial_sum(UnscaledValue(ss_ext_sales_price#3))] +Aggregate Attributes [2]: [sum#16, sum#17] +Results [5]: [i_category#13, i_class#14, spark_grouping_id#15, sum#18, sum#19] + +(22) Exchange +Input [5]: [i_category#13, i_class#14, spark_grouping_id#15, sum#18, sum#19] +Arguments: hashpartitioning(i_category#13, i_class#14, spark_grouping_id#15, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(23) HashAggregate [codegen id : 5] +Input [5]: [i_category#13, i_class#14, spark_grouping_id#15, sum#18, sum#19] +Keys [3]: [i_category#13, i_class#14, spark_grouping_id#15] +Functions [2]: [sum(UnscaledValue(ss_net_profit#4)), sum(UnscaledValue(ss_ext_sales_price#3))] +Aggregate Attributes [2]: [sum(UnscaledValue(ss_net_profit#4))#20, sum(UnscaledValue(ss_ext_sales_price#3))#21] +Results [7]: [(MakeDecimal(sum(UnscaledValue(ss_net_profit#4))#20,17,2) / MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#3))#21,17,2)) AS gross_margin#22, i_category#13, i_class#14, (cast((shiftright(spark_grouping_id#15, 1) & 1) as tinyint) + cast((shiftright(spark_grouping_id#15, 0) & 1) as tinyint)) AS lochierarchy#23, (MakeDecimal(sum(UnscaledValue(ss_net_profit#4))#20,17,2) / MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#3))#21,17,2)) AS _w0#24, (cast((shiftright(spark_grouping_id#15, 1) & 1) as tinyint) + cast((shiftright(spark_grouping_id#15, 0) & 1) as tinyint)) AS _w1#25, CASE WHEN (cast((shiftright(spark_grouping_id#15, 0) & 1) as tinyint) = 0) THEN i_category#13 END AS _w2#26] + +(24) Exchange +Input [7]: [gross_margin#22, i_category#13, i_class#14, lochierarchy#23, _w0#24, _w1#25, _w2#26] +Arguments: hashpartitioning(_w1#25, _w2#26, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(25) Sort [codegen id : 6] +Input [7]: [gross_margin#22, i_category#13, i_class#14, lochierarchy#23, _w0#24, _w1#25, _w2#26] +Arguments: [_w1#25 ASC NULLS FIRST, _w2#26 ASC NULLS FIRST, _w0#24 ASC NULLS FIRST], false, 0 + +(26) Window +Input [7]: [gross_margin#22, i_category#13, i_class#14, lochierarchy#23, _w0#24, _w1#25, _w2#26] +Arguments: [rank(_w0#24) windowspecdefinition(_w1#25, _w2#26, _w0#24 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rank_within_parent#27], [_w1#25, _w2#26], [_w0#24 ASC NULLS FIRST] + +(27) Project [codegen id : 7] +Output [5]: [gross_margin#22, i_category#13, i_class#14, lochierarchy#23, rank_within_parent#27] +Input [8]: [gross_margin#22, i_category#13, i_class#14, lochierarchy#23, _w0#24, _w1#25, _w2#26, rank_within_parent#27] + +(28) TakeOrderedAndProject +Input [5]: [gross_margin#22, i_category#13, i_class#14, lochierarchy#23, rank_within_parent#27] +Arguments: 100, [lochierarchy#23 DESC NULLS LAST, CASE WHEN (lochierarchy#23 = 0) THEN i_category#13 END ASC NULLS FIRST, rank_within_parent#27 ASC NULLS FIRST], [gross_margin#22, i_category#13, i_class#14, lochierarchy#23, rank_within_parent#27] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6 +BroadcastExchange (33) ++- * ColumnarToRow (32) + +- CometProject (31) + +- CometFilter (30) + +- CometScan parquet spark_catalog.default.date_dim (29) + + +(29) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#7, d_year#28] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(30) CometFilter +Input [2]: [d_date_sk#7, d_year#28] +Condition : ((isnotnull(d_year#28) AND (d_year#28 = 2001)) AND isnotnull(d_date_sk#7)) + +(31) CometProject +Input [2]: [d_date_sk#7, d_year#28] +Arguments: [d_date_sk#7], [d_date_sk#7] + +(32) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#7] + +(33) BroadcastExchange +Input [1]: [d_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q36/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q36/simplified.txt new file mode 100644 index 0000000000..7eeb607c3b --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q36/simplified.txt @@ -0,0 +1,51 @@ +TakeOrderedAndProject [lochierarchy,i_category,rank_within_parent,gross_margin,i_class] + WholeStageCodegen (7) + Project [gross_margin,i_category,i_class,lochierarchy,rank_within_parent] + InputAdapter + Window [_w0,_w1,_w2] + WholeStageCodegen (6) + Sort [_w1,_w2,_w0] + InputAdapter + Exchange [_w1,_w2] #1 + WholeStageCodegen (5) + HashAggregate [i_category,i_class,spark_grouping_id,sum,sum] [sum(UnscaledValue(ss_net_profit)),sum(UnscaledValue(ss_ext_sales_price)),gross_margin,lochierarchy,_w0,_w1,_w2,sum,sum] + InputAdapter + Exchange [i_category,i_class,spark_grouping_id] #2 + WholeStageCodegen (4) + HashAggregate [i_category,i_class,spark_grouping_id,ss_net_profit,ss_ext_sales_price] [sum,sum,sum,sum] + Expand [ss_ext_sales_price,ss_net_profit,i_category,i_class] + Project [ss_ext_sales_price,ss_net_profit,i_category,i_class] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_store_sk,ss_ext_sales_price,ss_net_profit,i_class,i_category] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_store_sk,ss_ext_sales_price,ss_net_profit] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk,ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_ext_sales_price,ss_net_profit,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_class,i_category] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometProject [s_store_sk] + CometFilter [s_state,s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk,s_state] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q37/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q37/explain.txt new file mode 100644 index 0000000000..23c4ae742b --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q37/explain.txt @@ -0,0 +1,179 @@ +== Physical Plan == +TakeOrderedAndProject (25) ++- * HashAggregate (24) + +- Exchange (23) + +- * HashAggregate (22) + +- * Project (21) + +- * BroadcastHashJoin Inner BuildLeft (20) + :- BroadcastExchange (15) + : +- * Project (14) + : +- * BroadcastHashJoin Inner BuildRight (13) + : :- * Project (11) + : : +- * BroadcastHashJoin Inner BuildRight (10) + : : :- * ColumnarToRow (4) + : : : +- CometProject (3) + : : : +- CometFilter (2) + : : : +- CometScan parquet spark_catalog.default.item (1) + : : +- BroadcastExchange (9) + : : +- * ColumnarToRow (8) + : : +- CometProject (7) + : : +- CometFilter (6) + : : +- CometScan parquet spark_catalog.default.inventory (5) + : +- ReusedExchange (12) + +- * ColumnarToRow (19) + +- CometProject (18) + +- CometFilter (17) + +- CometScan parquet spark_catalog.default.catalog_sales (16) + + +(1) Scan parquet spark_catalog.default.item +Output [5]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, i_manufact_id#5] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_current_price), GreaterThanOrEqual(i_current_price,68.00), LessThanOrEqual(i_current_price,98.00), In(i_manufact_id, [677,694,808,940]), IsNotNull(i_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [5]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, i_manufact_id#5] +Condition : ((((isnotnull(i_current_price#4) AND (i_current_price#4 >= 68.00)) AND (i_current_price#4 <= 98.00)) AND i_manufact_id#5 IN (677,940,694,808)) AND isnotnull(i_item_sk#1)) + +(3) CometProject +Input [5]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, i_manufact_id#5] +Arguments: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4], [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4] + +(4) ColumnarToRow [codegen id : 3] +Input [4]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4] + +(5) Scan parquet spark_catalog.default.inventory +Output [3]: [inv_item_sk#6, inv_quantity_on_hand#7, inv_date_sk#8] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(inv_date_sk#8), dynamicpruningexpression(inv_date_sk#8 IN dynamicpruning#9)] +PushedFilters: [IsNotNull(inv_quantity_on_hand), GreaterThanOrEqual(inv_quantity_on_hand,100), LessThanOrEqual(inv_quantity_on_hand,500), IsNotNull(inv_item_sk)] +ReadSchema: struct + +(6) CometFilter +Input [3]: [inv_item_sk#6, inv_quantity_on_hand#7, inv_date_sk#8] +Condition : (((isnotnull(inv_quantity_on_hand#7) AND (inv_quantity_on_hand#7 >= 100)) AND (inv_quantity_on_hand#7 <= 500)) AND isnotnull(inv_item_sk#6)) + +(7) CometProject +Input [3]: [inv_item_sk#6, inv_quantity_on_hand#7, inv_date_sk#8] +Arguments: [inv_item_sk#6, inv_date_sk#8], [inv_item_sk#6, inv_date_sk#8] + +(8) ColumnarToRow [codegen id : 1] +Input [2]: [inv_item_sk#6, inv_date_sk#8] + +(9) BroadcastExchange +Input [2]: [inv_item_sk#6, inv_date_sk#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(10) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [i_item_sk#1] +Right keys [1]: [inv_item_sk#6] +Join type: Inner +Join condition: None + +(11) Project [codegen id : 3] +Output [5]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, inv_date_sk#8] +Input [6]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, inv_item_sk#6, inv_date_sk#8] + +(12) ReusedExchange [Reuses operator id: 30] +Output [1]: [d_date_sk#10] + +(13) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [inv_date_sk#8] +Right keys [1]: [d_date_sk#10] +Join type: Inner +Join condition: None + +(14) Project [codegen id : 3] +Output [4]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4] +Input [6]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, inv_date_sk#8, d_date_sk#10] + +(15) BroadcastExchange +Input [4]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(16) Scan parquet spark_catalog.default.catalog_sales +Output [2]: [cs_item_sk#11, cs_sold_date_sk#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_sales] +PushedFilters: [IsNotNull(cs_item_sk)] +ReadSchema: struct + +(17) CometFilter +Input [2]: [cs_item_sk#11, cs_sold_date_sk#12] +Condition : isnotnull(cs_item_sk#11) + +(18) CometProject +Input [2]: [cs_item_sk#11, cs_sold_date_sk#12] +Arguments: [cs_item_sk#11], [cs_item_sk#11] + +(19) ColumnarToRow +Input [1]: [cs_item_sk#11] + +(20) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [i_item_sk#1] +Right keys [1]: [cs_item_sk#11] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 4] +Output [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] +Input [5]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, cs_item_sk#11] + +(22) HashAggregate [codegen id : 4] +Input [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] +Keys [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] +Functions: [] +Aggregate Attributes: [] +Results [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] + +(23) Exchange +Input [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] +Arguments: hashpartitioning(i_item_id#2, i_item_desc#3, i_current_price#4, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(24) HashAggregate [codegen id : 5] +Input [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] +Keys [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] +Functions: [] +Aggregate Attributes: [] +Results [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] + +(25) TakeOrderedAndProject +Input [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] +Arguments: 100, [i_item_id#2 ASC NULLS FIRST], [i_item_id#2, i_item_desc#3, i_current_price#4] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 5 Hosting Expression = inv_date_sk#8 IN dynamicpruning#9 +BroadcastExchange (30) ++- * ColumnarToRow (29) + +- CometProject (28) + +- CometFilter (27) + +- CometScan parquet spark_catalog.default.date_dim (26) + + +(26) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#10, d_date#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,2000-02-01), LessThanOrEqual(d_date,2000-04-01), IsNotNull(d_date_sk)] +ReadSchema: struct + +(27) CometFilter +Input [2]: [d_date_sk#10, d_date#13] +Condition : (((isnotnull(d_date#13) AND (d_date#13 >= 2000-02-01)) AND (d_date#13 <= 2000-04-01)) AND isnotnull(d_date_sk#10)) + +(28) CometProject +Input [2]: [d_date_sk#10, d_date#13] +Arguments: [d_date_sk#10], [d_date_sk#10] + +(29) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#10] + +(30) BroadcastExchange +Input [1]: [d_date_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q37/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q37/simplified.txt new file mode 100644 index 0000000000..65bb06348b --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q37/simplified.txt @@ -0,0 +1,44 @@ +TakeOrderedAndProject [i_item_id,i_item_desc,i_current_price] + WholeStageCodegen (5) + HashAggregate [i_item_id,i_item_desc,i_current_price] + InputAdapter + Exchange [i_item_id,i_item_desc,i_current_price] #1 + WholeStageCodegen (4) + HashAggregate [i_item_id,i_item_desc,i_current_price] + Project [i_item_id,i_item_desc,i_current_price] + BroadcastHashJoin [i_item_sk,cs_item_sk] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (3) + Project [i_item_sk,i_item_id,i_item_desc,i_current_price] + BroadcastHashJoin [inv_date_sk,d_date_sk] + Project [i_item_sk,i_item_id,i_item_desc,i_current_price,inv_date_sk] + BroadcastHashJoin [i_item_sk,inv_item_sk] + ColumnarToRow + InputAdapter + CometProject [i_item_sk,i_item_id,i_item_desc,i_current_price] + CometFilter [i_current_price,i_manufact_id,i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_item_desc,i_current_price,i_manufact_id] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [inv_item_sk,inv_date_sk] + CometFilter [inv_quantity_on_hand,inv_item_sk] + CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_quantity_on_hand,inv_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + ReusedExchange [d_date_sk] #4 + ColumnarToRow + InputAdapter + CometProject [cs_item_sk] + CometFilter [cs_item_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_sold_date_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q38/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q38/explain.txt new file mode 100644 index 0000000000..5503439ee4 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q38/explain.txt @@ -0,0 +1,321 @@ +== Physical Plan == +* HashAggregate (47) ++- Exchange (46) + +- * HashAggregate (45) + +- * Project (44) + +- * BroadcastHashJoin LeftSemi BuildRight (43) + :- * BroadcastHashJoin LeftSemi BuildRight (29) + : :- * HashAggregate (15) + : : +- Exchange (14) + : : +- * HashAggregate (13) + : : +- * Project (12) + : : +- * BroadcastHashJoin Inner BuildRight (11) + : : :- * Project (6) + : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- ReusedExchange (4) + : : +- BroadcastExchange (10) + : : +- * ColumnarToRow (9) + : : +- CometFilter (8) + : : +- CometScan parquet spark_catalog.default.customer (7) + : +- BroadcastExchange (28) + : +- * HashAggregate (27) + : +- Exchange (26) + : +- * HashAggregate (25) + : +- * Project (24) + : +- * BroadcastHashJoin Inner BuildRight (23) + : :- * Project (21) + : : +- * BroadcastHashJoin Inner BuildRight (20) + : : :- * ColumnarToRow (18) + : : : +- CometFilter (17) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (16) + : : +- ReusedExchange (19) + : +- ReusedExchange (22) + +- BroadcastExchange (42) + +- * HashAggregate (41) + +- Exchange (40) + +- * HashAggregate (39) + +- * Project (38) + +- * BroadcastHashJoin Inner BuildRight (37) + :- * Project (35) + : +- * BroadcastHashJoin Inner BuildRight (34) + : :- * ColumnarToRow (32) + : : +- CometFilter (31) + : : +- CometScan parquet spark_catalog.default.web_sales (30) + : +- ReusedExchange (33) + +- ReusedExchange (36) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [2]: [ss_customer_sk#1, ss_sold_date_sk#2] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#2), dynamicpruningexpression(ss_sold_date_sk#2 IN dynamicpruning#3)] +PushedFilters: [IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(2) CometFilter +Input [2]: [ss_customer_sk#1, ss_sold_date_sk#2] +Condition : isnotnull(ss_customer_sk#1) + +(3) ColumnarToRow [codegen id : 3] +Input [2]: [ss_customer_sk#1, ss_sold_date_sk#2] + +(4) ReusedExchange [Reuses operator id: 52] +Output [2]: [d_date_sk#4, d_date#5] + +(5) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_sold_date_sk#2] +Right keys [1]: [d_date_sk#4] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 3] +Output [2]: [ss_customer_sk#1, d_date#5] +Input [4]: [ss_customer_sk#1, ss_sold_date_sk#2, d_date_sk#4, d_date#5] + +(7) Scan parquet spark_catalog.default.customer +Output [3]: [c_customer_sk#6, c_first_name#7, c_last_name#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk)] +ReadSchema: struct + +(8) CometFilter +Input [3]: [c_customer_sk#6, c_first_name#7, c_last_name#8] +Condition : isnotnull(c_customer_sk#6) + +(9) ColumnarToRow [codegen id : 2] +Input [3]: [c_customer_sk#6, c_first_name#7, c_last_name#8] + +(10) BroadcastExchange +Input [3]: [c_customer_sk#6, c_first_name#7, c_last_name#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_customer_sk#1] +Right keys [1]: [c_customer_sk#6] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [3]: [c_last_name#8, c_first_name#7, d_date#5] +Input [5]: [ss_customer_sk#1, d_date#5, c_customer_sk#6, c_first_name#7, c_last_name#8] + +(13) HashAggregate [codegen id : 3] +Input [3]: [c_last_name#8, c_first_name#7, d_date#5] +Keys [3]: [c_last_name#8, c_first_name#7, d_date#5] +Functions: [] +Aggregate Attributes: [] +Results [3]: [c_last_name#8, c_first_name#7, d_date#5] + +(14) Exchange +Input [3]: [c_last_name#8, c_first_name#7, d_date#5] +Arguments: hashpartitioning(c_last_name#8, c_first_name#7, d_date#5, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 12] +Input [3]: [c_last_name#8, c_first_name#7, d_date#5] +Keys [3]: [c_last_name#8, c_first_name#7, d_date#5] +Functions: [] +Aggregate Attributes: [] +Results [3]: [c_last_name#8, c_first_name#7, d_date#5] + +(16) Scan parquet spark_catalog.default.catalog_sales +Output [2]: [cs_bill_customer_sk#9, cs_sold_date_sk#10] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#10), dynamicpruningexpression(cs_sold_date_sk#10 IN dynamicpruning#11)] +PushedFilters: [IsNotNull(cs_bill_customer_sk)] +ReadSchema: struct + +(17) CometFilter +Input [2]: [cs_bill_customer_sk#9, cs_sold_date_sk#10] +Condition : isnotnull(cs_bill_customer_sk#9) + +(18) ColumnarToRow [codegen id : 6] +Input [2]: [cs_bill_customer_sk#9, cs_sold_date_sk#10] + +(19) ReusedExchange [Reuses operator id: 52] +Output [2]: [d_date_sk#12, d_date#13] + +(20) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [cs_sold_date_sk#10] +Right keys [1]: [d_date_sk#12] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 6] +Output [2]: [cs_bill_customer_sk#9, d_date#13] +Input [4]: [cs_bill_customer_sk#9, cs_sold_date_sk#10, d_date_sk#12, d_date#13] + +(22) ReusedExchange [Reuses operator id: 10] +Output [3]: [c_customer_sk#14, c_first_name#15, c_last_name#16] + +(23) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [cs_bill_customer_sk#9] +Right keys [1]: [c_customer_sk#14] +Join type: Inner +Join condition: None + +(24) Project [codegen id : 6] +Output [3]: [c_last_name#16, c_first_name#15, d_date#13] +Input [5]: [cs_bill_customer_sk#9, d_date#13, c_customer_sk#14, c_first_name#15, c_last_name#16] + +(25) HashAggregate [codegen id : 6] +Input [3]: [c_last_name#16, c_first_name#15, d_date#13] +Keys [3]: [c_last_name#16, c_first_name#15, d_date#13] +Functions: [] +Aggregate Attributes: [] +Results [3]: [c_last_name#16, c_first_name#15, d_date#13] + +(26) Exchange +Input [3]: [c_last_name#16, c_first_name#15, d_date#13] +Arguments: hashpartitioning(c_last_name#16, c_first_name#15, d_date#13, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(27) HashAggregate [codegen id : 7] +Input [3]: [c_last_name#16, c_first_name#15, d_date#13] +Keys [3]: [c_last_name#16, c_first_name#15, d_date#13] +Functions: [] +Aggregate Attributes: [] +Results [3]: [c_last_name#16, c_first_name#15, d_date#13] + +(28) BroadcastExchange +Input [3]: [c_last_name#16, c_first_name#15, d_date#13] +Arguments: HashedRelationBroadcastMode(List(coalesce(input[0, string, true], ), isnull(input[0, string, true]), coalesce(input[1, string, true], ), isnull(input[1, string, true]), coalesce(input[2, date, true], 1970-01-01), isnull(input[2, date, true])),false), [plan_id=4] + +(29) BroadcastHashJoin [codegen id : 12] +Left keys [6]: [coalesce(c_last_name#8, ), isnull(c_last_name#8), coalesce(c_first_name#7, ), isnull(c_first_name#7), coalesce(d_date#5, 1970-01-01), isnull(d_date#5)] +Right keys [6]: [coalesce(c_last_name#16, ), isnull(c_last_name#16), coalesce(c_first_name#15, ), isnull(c_first_name#15), coalesce(d_date#13, 1970-01-01), isnull(d_date#13)] +Join type: LeftSemi +Join condition: None + +(30) Scan parquet spark_catalog.default.web_sales +Output [2]: [ws_bill_customer_sk#17, ws_sold_date_sk#18] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#18), dynamicpruningexpression(ws_sold_date_sk#18 IN dynamicpruning#19)] +PushedFilters: [IsNotNull(ws_bill_customer_sk)] +ReadSchema: struct + +(31) CometFilter +Input [2]: [ws_bill_customer_sk#17, ws_sold_date_sk#18] +Condition : isnotnull(ws_bill_customer_sk#17) + +(32) ColumnarToRow [codegen id : 10] +Input [2]: [ws_bill_customer_sk#17, ws_sold_date_sk#18] + +(33) ReusedExchange [Reuses operator id: 52] +Output [2]: [d_date_sk#20, d_date#21] + +(34) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [ws_sold_date_sk#18] +Right keys [1]: [d_date_sk#20] +Join type: Inner +Join condition: None + +(35) Project [codegen id : 10] +Output [2]: [ws_bill_customer_sk#17, d_date#21] +Input [4]: [ws_bill_customer_sk#17, ws_sold_date_sk#18, d_date_sk#20, d_date#21] + +(36) ReusedExchange [Reuses operator id: 10] +Output [3]: [c_customer_sk#22, c_first_name#23, c_last_name#24] + +(37) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [ws_bill_customer_sk#17] +Right keys [1]: [c_customer_sk#22] +Join type: Inner +Join condition: None + +(38) Project [codegen id : 10] +Output [3]: [c_last_name#24, c_first_name#23, d_date#21] +Input [5]: [ws_bill_customer_sk#17, d_date#21, c_customer_sk#22, c_first_name#23, c_last_name#24] + +(39) HashAggregate [codegen id : 10] +Input [3]: [c_last_name#24, c_first_name#23, d_date#21] +Keys [3]: [c_last_name#24, c_first_name#23, d_date#21] +Functions: [] +Aggregate Attributes: [] +Results [3]: [c_last_name#24, c_first_name#23, d_date#21] + +(40) Exchange +Input [3]: [c_last_name#24, c_first_name#23, d_date#21] +Arguments: hashpartitioning(c_last_name#24, c_first_name#23, d_date#21, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(41) HashAggregate [codegen id : 11] +Input [3]: [c_last_name#24, c_first_name#23, d_date#21] +Keys [3]: [c_last_name#24, c_first_name#23, d_date#21] +Functions: [] +Aggregate Attributes: [] +Results [3]: [c_last_name#24, c_first_name#23, d_date#21] + +(42) BroadcastExchange +Input [3]: [c_last_name#24, c_first_name#23, d_date#21] +Arguments: HashedRelationBroadcastMode(List(coalesce(input[0, string, true], ), isnull(input[0, string, true]), coalesce(input[1, string, true], ), isnull(input[1, string, true]), coalesce(input[2, date, true], 1970-01-01), isnull(input[2, date, true])),false), [plan_id=6] + +(43) BroadcastHashJoin [codegen id : 12] +Left keys [6]: [coalesce(c_last_name#8, ), isnull(c_last_name#8), coalesce(c_first_name#7, ), isnull(c_first_name#7), coalesce(d_date#5, 1970-01-01), isnull(d_date#5)] +Right keys [6]: [coalesce(c_last_name#24, ), isnull(c_last_name#24), coalesce(c_first_name#23, ), isnull(c_first_name#23), coalesce(d_date#21, 1970-01-01), isnull(d_date#21)] +Join type: LeftSemi +Join condition: None + +(44) Project [codegen id : 12] +Output: [] +Input [3]: [c_last_name#8, c_first_name#7, d_date#5] + +(45) HashAggregate [codegen id : 12] +Input: [] +Keys: [] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#25] +Results [1]: [count#26] + +(46) Exchange +Input [1]: [count#26] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=7] + +(47) HashAggregate [codegen id : 13] +Input [1]: [count#26] +Keys: [] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#27] +Results [1]: [count(1)#27 AS count(1)#28] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#2 IN dynamicpruning#3 +BroadcastExchange (52) ++- * ColumnarToRow (51) + +- CometProject (50) + +- CometFilter (49) + +- CometScan parquet spark_catalog.default.date_dim (48) + + +(48) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#4, d_date#5, d_month_seq#29] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)] +ReadSchema: struct + +(49) CometFilter +Input [3]: [d_date_sk#4, d_date#5, d_month_seq#29] +Condition : (((isnotnull(d_month_seq#29) AND (d_month_seq#29 >= 1200)) AND (d_month_seq#29 <= 1211)) AND isnotnull(d_date_sk#4)) + +(50) CometProject +Input [3]: [d_date_sk#4, d_date#5, d_month_seq#29] +Arguments: [d_date_sk#4, d_date#5], [d_date_sk#4, d_date#5] + +(51) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#4, d_date#5] + +(52) BroadcastExchange +Input [2]: [d_date_sk#4, d_date#5] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + +Subquery:2 Hosting operator id = 16 Hosting Expression = cs_sold_date_sk#10 IN dynamicpruning#3 + +Subquery:3 Hosting operator id = 30 Hosting Expression = ws_sold_date_sk#18 IN dynamicpruning#3 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q38/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q38/simplified.txt new file mode 100644 index 0000000000..315afe6602 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q38/simplified.txt @@ -0,0 +1,81 @@ +WholeStageCodegen (13) + HashAggregate [count] [count(1),count(1),count] + InputAdapter + Exchange #1 + WholeStageCodegen (12) + HashAggregate [count,count] + Project + BroadcastHashJoin [c_last_name,c_first_name,d_date,c_last_name,c_first_name,d_date] + BroadcastHashJoin [c_last_name,c_first_name,d_date,c_last_name,c_first_name,d_date] + HashAggregate [c_last_name,c_first_name,d_date] + InputAdapter + Exchange [c_last_name,c_first_name,d_date] #2 + WholeStageCodegen (3) + HashAggregate [c_last_name,c_first_name,d_date] + Project [c_last_name,c_first_name,d_date] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Project [ss_customer_sk,d_date] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk] + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_date] + CometFilter [d_month_seq,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date,d_month_seq] + InputAdapter + ReusedExchange [d_date_sk,d_date] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_first_name,c_last_name] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (7) + HashAggregate [c_last_name,c_first_name,d_date] + InputAdapter + Exchange [c_last_name,c_first_name,d_date] #6 + WholeStageCodegen (6) + HashAggregate [c_last_name,c_first_name,d_date] + Project [c_last_name,c_first_name,d_date] + BroadcastHashJoin [cs_bill_customer_sk,c_customer_sk] + Project [cs_bill_customer_sk,d_date] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [cs_bill_customer_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk,d_date] #3 + InputAdapter + ReusedExchange [c_customer_sk,c_first_name,c_last_name] #4 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (11) + HashAggregate [c_last_name,c_first_name,d_date] + InputAdapter + Exchange [c_last_name,c_first_name,d_date] #8 + WholeStageCodegen (10) + HashAggregate [c_last_name,c_first_name,d_date] + Project [c_last_name,c_first_name,d_date] + BroadcastHashJoin [ws_bill_customer_sk,c_customer_sk] + Project [ws_bill_customer_sk,d_date] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ws_bill_customer_sk] + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk,d_date] #3 + InputAdapter + ReusedExchange [c_customer_sk,c_first_name,c_last_name] #4 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39a/explain.txt new file mode 100644 index 0000000000..d851f61bf1 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39a/explain.txt @@ -0,0 +1,318 @@ +== Physical Plan == +* Sort (44) ++- Exchange (43) + +- * BroadcastHashJoin Inner BuildRight (42) + :- * Project (23) + : +- * Filter (22) + : +- * HashAggregate (21) + : +- Exchange (20) + : +- * HashAggregate (19) + : +- * Project (18) + : +- * BroadcastHashJoin Inner BuildRight (17) + : :- * Project (15) + : : +- * BroadcastHashJoin Inner BuildRight (14) + : : :- * Project (9) + : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.inventory (1) + : : : +- BroadcastExchange (7) + : : : +- * ColumnarToRow (6) + : : : +- CometFilter (5) + : : : +- CometScan parquet spark_catalog.default.item (4) + : : +- BroadcastExchange (13) + : : +- * ColumnarToRow (12) + : : +- CometFilter (11) + : : +- CometScan parquet spark_catalog.default.warehouse (10) + : +- ReusedExchange (16) + +- BroadcastExchange (41) + +- * Project (40) + +- * Filter (39) + +- * HashAggregate (38) + +- Exchange (37) + +- * HashAggregate (36) + +- * Project (35) + +- * BroadcastHashJoin Inner BuildRight (34) + :- * Project (32) + : +- * BroadcastHashJoin Inner BuildRight (31) + : :- * Project (29) + : : +- * BroadcastHashJoin Inner BuildRight (28) + : : :- * ColumnarToRow (26) + : : : +- CometFilter (25) + : : : +- CometScan parquet spark_catalog.default.inventory (24) + : : +- ReusedExchange (27) + : +- ReusedExchange (30) + +- ReusedExchange (33) + + +(1) Scan parquet spark_catalog.default.inventory +Output [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(inv_date_sk#4), dynamicpruningexpression(inv_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(inv_item_sk), IsNotNull(inv_warehouse_sk)] +ReadSchema: struct + +(2) CometFilter +Input [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] +Condition : (isnotnull(inv_item_sk#1) AND isnotnull(inv_warehouse_sk#2)) + +(3) ColumnarToRow [codegen id : 4] +Input [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] + +(4) Scan parquet spark_catalog.default.item +Output [1]: [i_item_sk#6] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(5) CometFilter +Input [1]: [i_item_sk#6] +Condition : isnotnull(i_item_sk#6) + +(6) ColumnarToRow [codegen id : 1] +Input [1]: [i_item_sk#6] + +(7) BroadcastExchange +Input [1]: [i_item_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [inv_item_sk#1] +Right keys [1]: [i_item_sk#6] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 4] +Output [4]: [inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4, i_item_sk#6] +Input [5]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4, i_item_sk#6] + +(10) Scan parquet spark_catalog.default.warehouse +Output [2]: [w_warehouse_sk#7, w_warehouse_name#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/warehouse] +PushedFilters: [IsNotNull(w_warehouse_sk)] +ReadSchema: struct + +(11) CometFilter +Input [2]: [w_warehouse_sk#7, w_warehouse_name#8] +Condition : isnotnull(w_warehouse_sk#7) + +(12) ColumnarToRow [codegen id : 2] +Input [2]: [w_warehouse_sk#7, w_warehouse_name#8] + +(13) BroadcastExchange +Input [2]: [w_warehouse_sk#7, w_warehouse_name#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(14) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [inv_warehouse_sk#2] +Right keys [1]: [w_warehouse_sk#7] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 4] +Output [5]: [inv_quantity_on_hand#3, inv_date_sk#4, i_item_sk#6, w_warehouse_sk#7, w_warehouse_name#8] +Input [6]: [inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4, i_item_sk#6, w_warehouse_sk#7, w_warehouse_name#8] + +(16) ReusedExchange [Reuses operator id: 49] +Output [2]: [d_date_sk#9, d_moy#10] + +(17) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [inv_date_sk#4] +Right keys [1]: [d_date_sk#9] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 4] +Output [5]: [inv_quantity_on_hand#3, i_item_sk#6, w_warehouse_sk#7, w_warehouse_name#8, d_moy#10] +Input [7]: [inv_quantity_on_hand#3, inv_date_sk#4, i_item_sk#6, w_warehouse_sk#7, w_warehouse_name#8, d_date_sk#9, d_moy#10] + +(19) HashAggregate [codegen id : 4] +Input [5]: [inv_quantity_on_hand#3, i_item_sk#6, w_warehouse_sk#7, w_warehouse_name#8, d_moy#10] +Keys [4]: [w_warehouse_name#8, w_warehouse_sk#7, i_item_sk#6, d_moy#10] +Functions [2]: [partial_stddev_samp(cast(inv_quantity_on_hand#3 as double)), partial_avg(inv_quantity_on_hand#3)] +Aggregate Attributes [5]: [n#11, avg#12, m2#13, sum#14, count#15] +Results [9]: [w_warehouse_name#8, w_warehouse_sk#7, i_item_sk#6, d_moy#10, n#16, avg#17, m2#18, sum#19, count#20] + +(20) Exchange +Input [9]: [w_warehouse_name#8, w_warehouse_sk#7, i_item_sk#6, d_moy#10, n#16, avg#17, m2#18, sum#19, count#20] +Arguments: hashpartitioning(w_warehouse_name#8, w_warehouse_sk#7, i_item_sk#6, d_moy#10, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(21) HashAggregate [codegen id : 10] +Input [9]: [w_warehouse_name#8, w_warehouse_sk#7, i_item_sk#6, d_moy#10, n#16, avg#17, m2#18, sum#19, count#20] +Keys [4]: [w_warehouse_name#8, w_warehouse_sk#7, i_item_sk#6, d_moy#10] +Functions [2]: [stddev_samp(cast(inv_quantity_on_hand#3 as double)), avg(inv_quantity_on_hand#3)] +Aggregate Attributes [2]: [stddev_samp(cast(inv_quantity_on_hand#3 as double))#21, avg(inv_quantity_on_hand#3)#22] +Results [5]: [w_warehouse_sk#7, i_item_sk#6, d_moy#10, stddev_samp(cast(inv_quantity_on_hand#3 as double))#21 AS stdev#23, avg(inv_quantity_on_hand#3)#22 AS mean#24] + +(22) Filter [codegen id : 10] +Input [5]: [w_warehouse_sk#7, i_item_sk#6, d_moy#10, stdev#23, mean#24] +Condition : CASE WHEN (mean#24 = 0.0) THEN false ELSE ((stdev#23 / mean#24) > 1.0) END + +(23) Project [codegen id : 10] +Output [5]: [w_warehouse_sk#7, i_item_sk#6, d_moy#10, mean#24, CASE WHEN (mean#24 = 0.0) THEN null ELSE (stdev#23 / mean#24) END AS cov#25] +Input [5]: [w_warehouse_sk#7, i_item_sk#6, d_moy#10, stdev#23, mean#24] + +(24) Scan parquet spark_catalog.default.inventory +Output [4]: [inv_item_sk#26, inv_warehouse_sk#27, inv_quantity_on_hand#28, inv_date_sk#29] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(inv_date_sk#29), dynamicpruningexpression(inv_date_sk#29 IN dynamicpruning#30)] +PushedFilters: [IsNotNull(inv_item_sk), IsNotNull(inv_warehouse_sk)] +ReadSchema: struct + +(25) CometFilter +Input [4]: [inv_item_sk#26, inv_warehouse_sk#27, inv_quantity_on_hand#28, inv_date_sk#29] +Condition : (isnotnull(inv_item_sk#26) AND isnotnull(inv_warehouse_sk#27)) + +(26) ColumnarToRow [codegen id : 8] +Input [4]: [inv_item_sk#26, inv_warehouse_sk#27, inv_quantity_on_hand#28, inv_date_sk#29] + +(27) ReusedExchange [Reuses operator id: 7] +Output [1]: [i_item_sk#31] + +(28) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [inv_item_sk#26] +Right keys [1]: [i_item_sk#31] +Join type: Inner +Join condition: None + +(29) Project [codegen id : 8] +Output [4]: [inv_warehouse_sk#27, inv_quantity_on_hand#28, inv_date_sk#29, i_item_sk#31] +Input [5]: [inv_item_sk#26, inv_warehouse_sk#27, inv_quantity_on_hand#28, inv_date_sk#29, i_item_sk#31] + +(30) ReusedExchange [Reuses operator id: 13] +Output [2]: [w_warehouse_sk#32, w_warehouse_name#33] + +(31) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [inv_warehouse_sk#27] +Right keys [1]: [w_warehouse_sk#32] +Join type: Inner +Join condition: None + +(32) Project [codegen id : 8] +Output [5]: [inv_quantity_on_hand#28, inv_date_sk#29, i_item_sk#31, w_warehouse_sk#32, w_warehouse_name#33] +Input [6]: [inv_warehouse_sk#27, inv_quantity_on_hand#28, inv_date_sk#29, i_item_sk#31, w_warehouse_sk#32, w_warehouse_name#33] + +(33) ReusedExchange [Reuses operator id: 54] +Output [2]: [d_date_sk#34, d_moy#35] + +(34) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [inv_date_sk#29] +Right keys [1]: [d_date_sk#34] +Join type: Inner +Join condition: None + +(35) Project [codegen id : 8] +Output [5]: [inv_quantity_on_hand#28, i_item_sk#31, w_warehouse_sk#32, w_warehouse_name#33, d_moy#35] +Input [7]: [inv_quantity_on_hand#28, inv_date_sk#29, i_item_sk#31, w_warehouse_sk#32, w_warehouse_name#33, d_date_sk#34, d_moy#35] + +(36) HashAggregate [codegen id : 8] +Input [5]: [inv_quantity_on_hand#28, i_item_sk#31, w_warehouse_sk#32, w_warehouse_name#33, d_moy#35] +Keys [4]: [w_warehouse_name#33, w_warehouse_sk#32, i_item_sk#31, d_moy#35] +Functions [2]: [partial_stddev_samp(cast(inv_quantity_on_hand#28 as double)), partial_avg(inv_quantity_on_hand#28)] +Aggregate Attributes [5]: [n#36, avg#37, m2#38, sum#39, count#40] +Results [9]: [w_warehouse_name#33, w_warehouse_sk#32, i_item_sk#31, d_moy#35, n#41, avg#42, m2#43, sum#44, count#45] + +(37) Exchange +Input [9]: [w_warehouse_name#33, w_warehouse_sk#32, i_item_sk#31, d_moy#35, n#41, avg#42, m2#43, sum#44, count#45] +Arguments: hashpartitioning(w_warehouse_name#33, w_warehouse_sk#32, i_item_sk#31, d_moy#35, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(38) HashAggregate [codegen id : 9] +Input [9]: [w_warehouse_name#33, w_warehouse_sk#32, i_item_sk#31, d_moy#35, n#41, avg#42, m2#43, sum#44, count#45] +Keys [4]: [w_warehouse_name#33, w_warehouse_sk#32, i_item_sk#31, d_moy#35] +Functions [2]: [stddev_samp(cast(inv_quantity_on_hand#28 as double)), avg(inv_quantity_on_hand#28)] +Aggregate Attributes [2]: [stddev_samp(cast(inv_quantity_on_hand#28 as double))#21, avg(inv_quantity_on_hand#28)#22] +Results [5]: [w_warehouse_sk#32, i_item_sk#31, d_moy#35, stddev_samp(cast(inv_quantity_on_hand#28 as double))#21 AS stdev#46, avg(inv_quantity_on_hand#28)#22 AS mean#47] + +(39) Filter [codegen id : 9] +Input [5]: [w_warehouse_sk#32, i_item_sk#31, d_moy#35, stdev#46, mean#47] +Condition : CASE WHEN (mean#47 = 0.0) THEN false ELSE ((stdev#46 / mean#47) > 1.0) END + +(40) Project [codegen id : 9] +Output [5]: [w_warehouse_sk#32, i_item_sk#31, d_moy#35, mean#47, CASE WHEN (mean#47 = 0.0) THEN null ELSE (stdev#46 / mean#47) END AS cov#48] +Input [5]: [w_warehouse_sk#32, i_item_sk#31, d_moy#35, stdev#46, mean#47] + +(41) BroadcastExchange +Input [5]: [w_warehouse_sk#32, i_item_sk#31, d_moy#35, mean#47, cov#48] +Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[1, int, true] as bigint), 32) | (cast(input[0, int, true] as bigint) & 4294967295))),false), [plan_id=5] + +(42) BroadcastHashJoin [codegen id : 10] +Left keys [2]: [i_item_sk#6, w_warehouse_sk#7] +Right keys [2]: [i_item_sk#31, w_warehouse_sk#32] +Join type: Inner +Join condition: None + +(43) Exchange +Input [10]: [w_warehouse_sk#7, i_item_sk#6, d_moy#10, mean#24, cov#25, w_warehouse_sk#32, i_item_sk#31, d_moy#35, mean#47, cov#48] +Arguments: rangepartitioning(w_warehouse_sk#7 ASC NULLS FIRST, i_item_sk#6 ASC NULLS FIRST, d_moy#10 ASC NULLS FIRST, mean#24 ASC NULLS FIRST, cov#25 ASC NULLS FIRST, d_moy#35 ASC NULLS FIRST, mean#47 ASC NULLS FIRST, cov#48 ASC NULLS FIRST, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(44) Sort [codegen id : 11] +Input [10]: [w_warehouse_sk#7, i_item_sk#6, d_moy#10, mean#24, cov#25, w_warehouse_sk#32, i_item_sk#31, d_moy#35, mean#47, cov#48] +Arguments: [w_warehouse_sk#7 ASC NULLS FIRST, i_item_sk#6 ASC NULLS FIRST, d_moy#10 ASC NULLS FIRST, mean#24 ASC NULLS FIRST, cov#25 ASC NULLS FIRST, d_moy#35 ASC NULLS FIRST, mean#47 ASC NULLS FIRST, cov#48 ASC NULLS FIRST], true, 0 + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = inv_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (49) ++- * ColumnarToRow (48) + +- CometProject (47) + +- CometFilter (46) + +- CometScan parquet spark_catalog.default.date_dim (45) + + +(45) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#9, d_year#49, d_moy#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2001), EqualTo(d_moy,1), IsNotNull(d_date_sk)] +ReadSchema: struct + +(46) CometFilter +Input [3]: [d_date_sk#9, d_year#49, d_moy#10] +Condition : ((((isnotnull(d_year#49) AND isnotnull(d_moy#10)) AND (d_year#49 = 2001)) AND (d_moy#10 = 1)) AND isnotnull(d_date_sk#9)) + +(47) CometProject +Input [3]: [d_date_sk#9, d_year#49, d_moy#10] +Arguments: [d_date_sk#9, d_moy#10], [d_date_sk#9, d_moy#10] + +(48) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#9, d_moy#10] + +(49) BroadcastExchange +Input [2]: [d_date_sk#9, d_moy#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +Subquery:2 Hosting operator id = 24 Hosting Expression = inv_date_sk#29 IN dynamicpruning#30 +BroadcastExchange (54) ++- * ColumnarToRow (53) + +- CometProject (52) + +- CometFilter (51) + +- CometScan parquet spark_catalog.default.date_dim (50) + + +(50) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#34, d_year#50, d_moy#35] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2001), EqualTo(d_moy,2), IsNotNull(d_date_sk)] +ReadSchema: struct + +(51) CometFilter +Input [3]: [d_date_sk#34, d_year#50, d_moy#35] +Condition : ((((isnotnull(d_year#50) AND isnotnull(d_moy#35)) AND (d_year#50 = 2001)) AND (d_moy#35 = 2)) AND isnotnull(d_date_sk#34)) + +(52) CometProject +Input [3]: [d_date_sk#34, d_year#50, d_moy#35] +Arguments: [d_date_sk#34, d_moy#35], [d_date_sk#34, d_moy#35] + +(53) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#34, d_moy#35] + +(54) BroadcastExchange +Input [2]: [d_date_sk#34, d_moy#35] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39a/simplified.txt new file mode 100644 index 0000000000..002266e76e --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39a/simplified.txt @@ -0,0 +1,81 @@ +WholeStageCodegen (11) + Sort [w_warehouse_sk,i_item_sk,d_moy,mean,cov,d_moy,mean,cov] + InputAdapter + Exchange [w_warehouse_sk,i_item_sk,d_moy,mean,cov,d_moy,mean,cov] #1 + WholeStageCodegen (10) + BroadcastHashJoin [i_item_sk,w_warehouse_sk,i_item_sk,w_warehouse_sk] + Project [w_warehouse_sk,i_item_sk,d_moy,mean,stdev] + Filter [mean,stdev] + HashAggregate [w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy,n,avg,m2,sum,count] [stddev_samp(cast(inv_quantity_on_hand as double)),avg(inv_quantity_on_hand),stdev,mean,n,avg,m2,sum,count] + InputAdapter + Exchange [w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy] #2 + WholeStageCodegen (4) + HashAggregate [w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy,inv_quantity_on_hand] [n,avg,m2,sum,count,n,avg,m2,sum,count] + Project [inv_quantity_on_hand,i_item_sk,w_warehouse_sk,w_warehouse_name,d_moy] + BroadcastHashJoin [inv_date_sk,d_date_sk] + Project [inv_quantity_on_hand,inv_date_sk,i_item_sk,w_warehouse_sk,w_warehouse_name] + BroadcastHashJoin [inv_warehouse_sk,w_warehouse_sk] + Project [inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk,i_item_sk] + BroadcastHashJoin [inv_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [inv_item_sk,inv_warehouse_sk] + CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_moy] + CometFilter [d_year,d_moy,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [w_warehouse_sk] + CometScan parquet spark_catalog.default.warehouse [w_warehouse_sk,w_warehouse_name] + InputAdapter + ReusedExchange [d_date_sk,d_moy] #3 + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (9) + Project [w_warehouse_sk,i_item_sk,d_moy,mean,stdev] + Filter [mean,stdev] + HashAggregate [w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy,n,avg,m2,sum,count] [stddev_samp(cast(inv_quantity_on_hand as double)),avg(inv_quantity_on_hand),stdev,mean,n,avg,m2,sum,count] + InputAdapter + Exchange [w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy] #7 + WholeStageCodegen (8) + HashAggregate [w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy,inv_quantity_on_hand] [n,avg,m2,sum,count,n,avg,m2,sum,count] + Project [inv_quantity_on_hand,i_item_sk,w_warehouse_sk,w_warehouse_name,d_moy] + BroadcastHashJoin [inv_date_sk,d_date_sk] + Project [inv_quantity_on_hand,inv_date_sk,i_item_sk,w_warehouse_sk,w_warehouse_name] + BroadcastHashJoin [inv_warehouse_sk,w_warehouse_sk] + Project [inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk,i_item_sk] + BroadcastHashJoin [inv_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [inv_item_sk,inv_warehouse_sk] + CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #8 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_moy] + CometFilter [d_year,d_moy,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + ReusedExchange [i_item_sk] #4 + InputAdapter + ReusedExchange [w_warehouse_sk,w_warehouse_name] #5 + InputAdapter + ReusedExchange [d_date_sk,d_moy] #8 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39b/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39b/explain.txt new file mode 100644 index 0000000000..a4184150e6 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39b/explain.txt @@ -0,0 +1,318 @@ +== Physical Plan == +* Sort (44) ++- Exchange (43) + +- * BroadcastHashJoin Inner BuildRight (42) + :- * Project (23) + : +- * Filter (22) + : +- * HashAggregate (21) + : +- Exchange (20) + : +- * HashAggregate (19) + : +- * Project (18) + : +- * BroadcastHashJoin Inner BuildRight (17) + : :- * Project (15) + : : +- * BroadcastHashJoin Inner BuildRight (14) + : : :- * Project (9) + : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.inventory (1) + : : : +- BroadcastExchange (7) + : : : +- * ColumnarToRow (6) + : : : +- CometFilter (5) + : : : +- CometScan parquet spark_catalog.default.item (4) + : : +- BroadcastExchange (13) + : : +- * ColumnarToRow (12) + : : +- CometFilter (11) + : : +- CometScan parquet spark_catalog.default.warehouse (10) + : +- ReusedExchange (16) + +- BroadcastExchange (41) + +- * Project (40) + +- * Filter (39) + +- * HashAggregate (38) + +- Exchange (37) + +- * HashAggregate (36) + +- * Project (35) + +- * BroadcastHashJoin Inner BuildRight (34) + :- * Project (32) + : +- * BroadcastHashJoin Inner BuildRight (31) + : :- * Project (29) + : : +- * BroadcastHashJoin Inner BuildRight (28) + : : :- * ColumnarToRow (26) + : : : +- CometFilter (25) + : : : +- CometScan parquet spark_catalog.default.inventory (24) + : : +- ReusedExchange (27) + : +- ReusedExchange (30) + +- ReusedExchange (33) + + +(1) Scan parquet spark_catalog.default.inventory +Output [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(inv_date_sk#4), dynamicpruningexpression(inv_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(inv_item_sk), IsNotNull(inv_warehouse_sk)] +ReadSchema: struct + +(2) CometFilter +Input [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] +Condition : (isnotnull(inv_item_sk#1) AND isnotnull(inv_warehouse_sk#2)) + +(3) ColumnarToRow [codegen id : 4] +Input [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] + +(4) Scan parquet spark_catalog.default.item +Output [1]: [i_item_sk#6] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(5) CometFilter +Input [1]: [i_item_sk#6] +Condition : isnotnull(i_item_sk#6) + +(6) ColumnarToRow [codegen id : 1] +Input [1]: [i_item_sk#6] + +(7) BroadcastExchange +Input [1]: [i_item_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [inv_item_sk#1] +Right keys [1]: [i_item_sk#6] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 4] +Output [4]: [inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4, i_item_sk#6] +Input [5]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4, i_item_sk#6] + +(10) Scan parquet spark_catalog.default.warehouse +Output [2]: [w_warehouse_sk#7, w_warehouse_name#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/warehouse] +PushedFilters: [IsNotNull(w_warehouse_sk)] +ReadSchema: struct + +(11) CometFilter +Input [2]: [w_warehouse_sk#7, w_warehouse_name#8] +Condition : isnotnull(w_warehouse_sk#7) + +(12) ColumnarToRow [codegen id : 2] +Input [2]: [w_warehouse_sk#7, w_warehouse_name#8] + +(13) BroadcastExchange +Input [2]: [w_warehouse_sk#7, w_warehouse_name#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(14) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [inv_warehouse_sk#2] +Right keys [1]: [w_warehouse_sk#7] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 4] +Output [5]: [inv_quantity_on_hand#3, inv_date_sk#4, i_item_sk#6, w_warehouse_sk#7, w_warehouse_name#8] +Input [6]: [inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4, i_item_sk#6, w_warehouse_sk#7, w_warehouse_name#8] + +(16) ReusedExchange [Reuses operator id: 49] +Output [2]: [d_date_sk#9, d_moy#10] + +(17) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [inv_date_sk#4] +Right keys [1]: [d_date_sk#9] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 4] +Output [5]: [inv_quantity_on_hand#3, i_item_sk#6, w_warehouse_sk#7, w_warehouse_name#8, d_moy#10] +Input [7]: [inv_quantity_on_hand#3, inv_date_sk#4, i_item_sk#6, w_warehouse_sk#7, w_warehouse_name#8, d_date_sk#9, d_moy#10] + +(19) HashAggregate [codegen id : 4] +Input [5]: [inv_quantity_on_hand#3, i_item_sk#6, w_warehouse_sk#7, w_warehouse_name#8, d_moy#10] +Keys [4]: [w_warehouse_name#8, w_warehouse_sk#7, i_item_sk#6, d_moy#10] +Functions [2]: [partial_stddev_samp(cast(inv_quantity_on_hand#3 as double)), partial_avg(inv_quantity_on_hand#3)] +Aggregate Attributes [5]: [n#11, avg#12, m2#13, sum#14, count#15] +Results [9]: [w_warehouse_name#8, w_warehouse_sk#7, i_item_sk#6, d_moy#10, n#16, avg#17, m2#18, sum#19, count#20] + +(20) Exchange +Input [9]: [w_warehouse_name#8, w_warehouse_sk#7, i_item_sk#6, d_moy#10, n#16, avg#17, m2#18, sum#19, count#20] +Arguments: hashpartitioning(w_warehouse_name#8, w_warehouse_sk#7, i_item_sk#6, d_moy#10, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(21) HashAggregate [codegen id : 10] +Input [9]: [w_warehouse_name#8, w_warehouse_sk#7, i_item_sk#6, d_moy#10, n#16, avg#17, m2#18, sum#19, count#20] +Keys [4]: [w_warehouse_name#8, w_warehouse_sk#7, i_item_sk#6, d_moy#10] +Functions [2]: [stddev_samp(cast(inv_quantity_on_hand#3 as double)), avg(inv_quantity_on_hand#3)] +Aggregate Attributes [2]: [stddev_samp(cast(inv_quantity_on_hand#3 as double))#21, avg(inv_quantity_on_hand#3)#22] +Results [5]: [w_warehouse_sk#7, i_item_sk#6, d_moy#10, stddev_samp(cast(inv_quantity_on_hand#3 as double))#21 AS stdev#23, avg(inv_quantity_on_hand#3)#22 AS mean#24] + +(22) Filter [codegen id : 10] +Input [5]: [w_warehouse_sk#7, i_item_sk#6, d_moy#10, stdev#23, mean#24] +Condition : (CASE WHEN (mean#24 = 0.0) THEN false ELSE ((stdev#23 / mean#24) > 1.0) END AND CASE WHEN (mean#24 = 0.0) THEN false ELSE ((stdev#23 / mean#24) > 1.5) END) + +(23) Project [codegen id : 10] +Output [5]: [w_warehouse_sk#7, i_item_sk#6, d_moy#10, mean#24, CASE WHEN (mean#24 = 0.0) THEN null ELSE (stdev#23 / mean#24) END AS cov#25] +Input [5]: [w_warehouse_sk#7, i_item_sk#6, d_moy#10, stdev#23, mean#24] + +(24) Scan parquet spark_catalog.default.inventory +Output [4]: [inv_item_sk#26, inv_warehouse_sk#27, inv_quantity_on_hand#28, inv_date_sk#29] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(inv_date_sk#29), dynamicpruningexpression(inv_date_sk#29 IN dynamicpruning#30)] +PushedFilters: [IsNotNull(inv_item_sk), IsNotNull(inv_warehouse_sk)] +ReadSchema: struct + +(25) CometFilter +Input [4]: [inv_item_sk#26, inv_warehouse_sk#27, inv_quantity_on_hand#28, inv_date_sk#29] +Condition : (isnotnull(inv_item_sk#26) AND isnotnull(inv_warehouse_sk#27)) + +(26) ColumnarToRow [codegen id : 8] +Input [4]: [inv_item_sk#26, inv_warehouse_sk#27, inv_quantity_on_hand#28, inv_date_sk#29] + +(27) ReusedExchange [Reuses operator id: 7] +Output [1]: [i_item_sk#31] + +(28) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [inv_item_sk#26] +Right keys [1]: [i_item_sk#31] +Join type: Inner +Join condition: None + +(29) Project [codegen id : 8] +Output [4]: [inv_warehouse_sk#27, inv_quantity_on_hand#28, inv_date_sk#29, i_item_sk#31] +Input [5]: [inv_item_sk#26, inv_warehouse_sk#27, inv_quantity_on_hand#28, inv_date_sk#29, i_item_sk#31] + +(30) ReusedExchange [Reuses operator id: 13] +Output [2]: [w_warehouse_sk#32, w_warehouse_name#33] + +(31) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [inv_warehouse_sk#27] +Right keys [1]: [w_warehouse_sk#32] +Join type: Inner +Join condition: None + +(32) Project [codegen id : 8] +Output [5]: [inv_quantity_on_hand#28, inv_date_sk#29, i_item_sk#31, w_warehouse_sk#32, w_warehouse_name#33] +Input [6]: [inv_warehouse_sk#27, inv_quantity_on_hand#28, inv_date_sk#29, i_item_sk#31, w_warehouse_sk#32, w_warehouse_name#33] + +(33) ReusedExchange [Reuses operator id: 54] +Output [2]: [d_date_sk#34, d_moy#35] + +(34) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [inv_date_sk#29] +Right keys [1]: [d_date_sk#34] +Join type: Inner +Join condition: None + +(35) Project [codegen id : 8] +Output [5]: [inv_quantity_on_hand#28, i_item_sk#31, w_warehouse_sk#32, w_warehouse_name#33, d_moy#35] +Input [7]: [inv_quantity_on_hand#28, inv_date_sk#29, i_item_sk#31, w_warehouse_sk#32, w_warehouse_name#33, d_date_sk#34, d_moy#35] + +(36) HashAggregate [codegen id : 8] +Input [5]: [inv_quantity_on_hand#28, i_item_sk#31, w_warehouse_sk#32, w_warehouse_name#33, d_moy#35] +Keys [4]: [w_warehouse_name#33, w_warehouse_sk#32, i_item_sk#31, d_moy#35] +Functions [2]: [partial_stddev_samp(cast(inv_quantity_on_hand#28 as double)), partial_avg(inv_quantity_on_hand#28)] +Aggregate Attributes [5]: [n#36, avg#37, m2#38, sum#39, count#40] +Results [9]: [w_warehouse_name#33, w_warehouse_sk#32, i_item_sk#31, d_moy#35, n#41, avg#42, m2#43, sum#44, count#45] + +(37) Exchange +Input [9]: [w_warehouse_name#33, w_warehouse_sk#32, i_item_sk#31, d_moy#35, n#41, avg#42, m2#43, sum#44, count#45] +Arguments: hashpartitioning(w_warehouse_name#33, w_warehouse_sk#32, i_item_sk#31, d_moy#35, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(38) HashAggregate [codegen id : 9] +Input [9]: [w_warehouse_name#33, w_warehouse_sk#32, i_item_sk#31, d_moy#35, n#41, avg#42, m2#43, sum#44, count#45] +Keys [4]: [w_warehouse_name#33, w_warehouse_sk#32, i_item_sk#31, d_moy#35] +Functions [2]: [stddev_samp(cast(inv_quantity_on_hand#28 as double)), avg(inv_quantity_on_hand#28)] +Aggregate Attributes [2]: [stddev_samp(cast(inv_quantity_on_hand#28 as double))#21, avg(inv_quantity_on_hand#28)#22] +Results [5]: [w_warehouse_sk#32, i_item_sk#31, d_moy#35, stddev_samp(cast(inv_quantity_on_hand#28 as double))#21 AS stdev#46, avg(inv_quantity_on_hand#28)#22 AS mean#47] + +(39) Filter [codegen id : 9] +Input [5]: [w_warehouse_sk#32, i_item_sk#31, d_moy#35, stdev#46, mean#47] +Condition : CASE WHEN (mean#47 = 0.0) THEN false ELSE ((stdev#46 / mean#47) > 1.0) END + +(40) Project [codegen id : 9] +Output [5]: [w_warehouse_sk#32, i_item_sk#31, d_moy#35, mean#47, CASE WHEN (mean#47 = 0.0) THEN null ELSE (stdev#46 / mean#47) END AS cov#48] +Input [5]: [w_warehouse_sk#32, i_item_sk#31, d_moy#35, stdev#46, mean#47] + +(41) BroadcastExchange +Input [5]: [w_warehouse_sk#32, i_item_sk#31, d_moy#35, mean#47, cov#48] +Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[1, int, true] as bigint), 32) | (cast(input[0, int, true] as bigint) & 4294967295))),false), [plan_id=5] + +(42) BroadcastHashJoin [codegen id : 10] +Left keys [2]: [i_item_sk#6, w_warehouse_sk#7] +Right keys [2]: [i_item_sk#31, w_warehouse_sk#32] +Join type: Inner +Join condition: None + +(43) Exchange +Input [10]: [w_warehouse_sk#7, i_item_sk#6, d_moy#10, mean#24, cov#25, w_warehouse_sk#32, i_item_sk#31, d_moy#35, mean#47, cov#48] +Arguments: rangepartitioning(w_warehouse_sk#7 ASC NULLS FIRST, i_item_sk#6 ASC NULLS FIRST, d_moy#10 ASC NULLS FIRST, mean#24 ASC NULLS FIRST, cov#25 ASC NULLS FIRST, d_moy#35 ASC NULLS FIRST, mean#47 ASC NULLS FIRST, cov#48 ASC NULLS FIRST, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(44) Sort [codegen id : 11] +Input [10]: [w_warehouse_sk#7, i_item_sk#6, d_moy#10, mean#24, cov#25, w_warehouse_sk#32, i_item_sk#31, d_moy#35, mean#47, cov#48] +Arguments: [w_warehouse_sk#7 ASC NULLS FIRST, i_item_sk#6 ASC NULLS FIRST, d_moy#10 ASC NULLS FIRST, mean#24 ASC NULLS FIRST, cov#25 ASC NULLS FIRST, d_moy#35 ASC NULLS FIRST, mean#47 ASC NULLS FIRST, cov#48 ASC NULLS FIRST], true, 0 + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = inv_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (49) ++- * ColumnarToRow (48) + +- CometProject (47) + +- CometFilter (46) + +- CometScan parquet spark_catalog.default.date_dim (45) + + +(45) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#9, d_year#49, d_moy#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2001), EqualTo(d_moy,1), IsNotNull(d_date_sk)] +ReadSchema: struct + +(46) CometFilter +Input [3]: [d_date_sk#9, d_year#49, d_moy#10] +Condition : ((((isnotnull(d_year#49) AND isnotnull(d_moy#10)) AND (d_year#49 = 2001)) AND (d_moy#10 = 1)) AND isnotnull(d_date_sk#9)) + +(47) CometProject +Input [3]: [d_date_sk#9, d_year#49, d_moy#10] +Arguments: [d_date_sk#9, d_moy#10], [d_date_sk#9, d_moy#10] + +(48) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#9, d_moy#10] + +(49) BroadcastExchange +Input [2]: [d_date_sk#9, d_moy#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +Subquery:2 Hosting operator id = 24 Hosting Expression = inv_date_sk#29 IN dynamicpruning#30 +BroadcastExchange (54) ++- * ColumnarToRow (53) + +- CometProject (52) + +- CometFilter (51) + +- CometScan parquet spark_catalog.default.date_dim (50) + + +(50) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#34, d_year#50, d_moy#35] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2001), EqualTo(d_moy,2), IsNotNull(d_date_sk)] +ReadSchema: struct + +(51) CometFilter +Input [3]: [d_date_sk#34, d_year#50, d_moy#35] +Condition : ((((isnotnull(d_year#50) AND isnotnull(d_moy#35)) AND (d_year#50 = 2001)) AND (d_moy#35 = 2)) AND isnotnull(d_date_sk#34)) + +(52) CometProject +Input [3]: [d_date_sk#34, d_year#50, d_moy#35] +Arguments: [d_date_sk#34, d_moy#35], [d_date_sk#34, d_moy#35] + +(53) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#34, d_moy#35] + +(54) BroadcastExchange +Input [2]: [d_date_sk#34, d_moy#35] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39b/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39b/simplified.txt new file mode 100644 index 0000000000..002266e76e --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39b/simplified.txt @@ -0,0 +1,81 @@ +WholeStageCodegen (11) + Sort [w_warehouse_sk,i_item_sk,d_moy,mean,cov,d_moy,mean,cov] + InputAdapter + Exchange [w_warehouse_sk,i_item_sk,d_moy,mean,cov,d_moy,mean,cov] #1 + WholeStageCodegen (10) + BroadcastHashJoin [i_item_sk,w_warehouse_sk,i_item_sk,w_warehouse_sk] + Project [w_warehouse_sk,i_item_sk,d_moy,mean,stdev] + Filter [mean,stdev] + HashAggregate [w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy,n,avg,m2,sum,count] [stddev_samp(cast(inv_quantity_on_hand as double)),avg(inv_quantity_on_hand),stdev,mean,n,avg,m2,sum,count] + InputAdapter + Exchange [w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy] #2 + WholeStageCodegen (4) + HashAggregate [w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy,inv_quantity_on_hand] [n,avg,m2,sum,count,n,avg,m2,sum,count] + Project [inv_quantity_on_hand,i_item_sk,w_warehouse_sk,w_warehouse_name,d_moy] + BroadcastHashJoin [inv_date_sk,d_date_sk] + Project [inv_quantity_on_hand,inv_date_sk,i_item_sk,w_warehouse_sk,w_warehouse_name] + BroadcastHashJoin [inv_warehouse_sk,w_warehouse_sk] + Project [inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk,i_item_sk] + BroadcastHashJoin [inv_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [inv_item_sk,inv_warehouse_sk] + CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_moy] + CometFilter [d_year,d_moy,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [w_warehouse_sk] + CometScan parquet spark_catalog.default.warehouse [w_warehouse_sk,w_warehouse_name] + InputAdapter + ReusedExchange [d_date_sk,d_moy] #3 + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (9) + Project [w_warehouse_sk,i_item_sk,d_moy,mean,stdev] + Filter [mean,stdev] + HashAggregate [w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy,n,avg,m2,sum,count] [stddev_samp(cast(inv_quantity_on_hand as double)),avg(inv_quantity_on_hand),stdev,mean,n,avg,m2,sum,count] + InputAdapter + Exchange [w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy] #7 + WholeStageCodegen (8) + HashAggregate [w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy,inv_quantity_on_hand] [n,avg,m2,sum,count,n,avg,m2,sum,count] + Project [inv_quantity_on_hand,i_item_sk,w_warehouse_sk,w_warehouse_name,d_moy] + BroadcastHashJoin [inv_date_sk,d_date_sk] + Project [inv_quantity_on_hand,inv_date_sk,i_item_sk,w_warehouse_sk,w_warehouse_name] + BroadcastHashJoin [inv_warehouse_sk,w_warehouse_sk] + Project [inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk,i_item_sk] + BroadcastHashJoin [inv_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [inv_item_sk,inv_warehouse_sk] + CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #8 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_moy] + CometFilter [d_year,d_moy,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + ReusedExchange [i_item_sk] #4 + InputAdapter + ReusedExchange [w_warehouse_sk,w_warehouse_name] #5 + InputAdapter + ReusedExchange [d_date_sk,d_moy] #8 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q4/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q4/explain.txt new file mode 100644 index 0000000000..a854a1041b --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q4/explain.txt @@ -0,0 +1,698 @@ +== Physical Plan == +TakeOrderedAndProject (108) ++- * Project (107) + +- * BroadcastHashJoin Inner BuildRight (106) + :- * Project (89) + : +- * BroadcastHashJoin Inner BuildRight (88) + : :- * Project (70) + : : +- * BroadcastHashJoin Inner BuildRight (69) + : : :- * Project (52) + : : : +- * BroadcastHashJoin Inner BuildRight (51) + : : : :- * BroadcastHashJoin Inner BuildRight (33) + : : : : :- * Filter (16) + : : : : : +- * HashAggregate (15) + : : : : : +- Exchange (14) + : : : : : +- * HashAggregate (13) + : : : : : +- * Project (12) + : : : : : +- * BroadcastHashJoin Inner BuildRight (11) + : : : : : :- * Project (9) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : : : :- * ColumnarToRow (3) + : : : : : : : +- CometFilter (2) + : : : : : : : +- CometScan parquet spark_catalog.default.customer (1) + : : : : : : +- BroadcastExchange (7) + : : : : : : +- * ColumnarToRow (6) + : : : : : : +- CometFilter (5) + : : : : : : +- CometScan parquet spark_catalog.default.store_sales (4) + : : : : : +- ReusedExchange (10) + : : : : +- BroadcastExchange (32) + : : : : +- * HashAggregate (31) + : : : : +- Exchange (30) + : : : : +- * HashAggregate (29) + : : : : +- * Project (28) + : : : : +- * BroadcastHashJoin Inner BuildRight (27) + : : : : :- * Project (25) + : : : : : +- * BroadcastHashJoin Inner BuildRight (24) + : : : : : :- * ColumnarToRow (19) + : : : : : : +- CometFilter (18) + : : : : : : +- CometScan parquet spark_catalog.default.customer (17) + : : : : : +- BroadcastExchange (23) + : : : : : +- * ColumnarToRow (22) + : : : : : +- CometFilter (21) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (20) + : : : : +- ReusedExchange (26) + : : : +- BroadcastExchange (50) + : : : +- * Filter (49) + : : : +- * HashAggregate (48) + : : : +- Exchange (47) + : : : +- * HashAggregate (46) + : : : +- * Project (45) + : : : +- * BroadcastHashJoin Inner BuildRight (44) + : : : :- * Project (42) + : : : : +- * BroadcastHashJoin Inner BuildRight (41) + : : : : :- * ColumnarToRow (36) + : : : : : +- CometFilter (35) + : : : : : +- CometScan parquet spark_catalog.default.customer (34) + : : : : +- BroadcastExchange (40) + : : : : +- * ColumnarToRow (39) + : : : : +- CometFilter (38) + : : : : +- CometScan parquet spark_catalog.default.catalog_sales (37) + : : : +- ReusedExchange (43) + : : +- BroadcastExchange (68) + : : +- * HashAggregate (67) + : : +- Exchange (66) + : : +- * HashAggregate (65) + : : +- * Project (64) + : : +- * BroadcastHashJoin Inner BuildRight (63) + : : :- * Project (61) + : : : +- * BroadcastHashJoin Inner BuildRight (60) + : : : :- * ColumnarToRow (55) + : : : : +- CometFilter (54) + : : : : +- CometScan parquet spark_catalog.default.customer (53) + : : : +- BroadcastExchange (59) + : : : +- * ColumnarToRow (58) + : : : +- CometFilter (57) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (56) + : : +- ReusedExchange (62) + : +- BroadcastExchange (87) + : +- * Filter (86) + : +- * HashAggregate (85) + : +- Exchange (84) + : +- * HashAggregate (83) + : +- * Project (82) + : +- * BroadcastHashJoin Inner BuildRight (81) + : :- * Project (79) + : : +- * BroadcastHashJoin Inner BuildRight (78) + : : :- * ColumnarToRow (73) + : : : +- CometFilter (72) + : : : +- CometScan parquet spark_catalog.default.customer (71) + : : +- BroadcastExchange (77) + : : +- * ColumnarToRow (76) + : : +- CometFilter (75) + : : +- CometScan parquet spark_catalog.default.web_sales (74) + : +- ReusedExchange (80) + +- BroadcastExchange (105) + +- * HashAggregate (104) + +- Exchange (103) + +- * HashAggregate (102) + +- * Project (101) + +- * BroadcastHashJoin Inner BuildRight (100) + :- * Project (98) + : +- * BroadcastHashJoin Inner BuildRight (97) + : :- * ColumnarToRow (92) + : : +- CometFilter (91) + : : +- CometScan parquet spark_catalog.default.customer (90) + : +- BroadcastExchange (96) + : +- * ColumnarToRow (95) + : +- CometFilter (94) + : +- CometScan parquet spark_catalog.default.web_sales (93) + +- ReusedExchange (99) + + +(1) Scan parquet spark_catalog.default.customer +Output [8]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(2) CometFilter +Input [8]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8] +Condition : (isnotnull(c_customer_sk#1) AND isnotnull(c_customer_id#2)) + +(3) ColumnarToRow [codegen id : 3] +Input [8]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8] + +(4) Scan parquet spark_catalog.default.store_sales +Output [6]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_sales_price#11, ss_ext_wholesale_cost#12, ss_ext_list_price#13, ss_sold_date_sk#14] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#14), dynamicpruningexpression(ss_sold_date_sk#14 IN dynamicpruning#15)] +PushedFilters: [IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(5) CometFilter +Input [6]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_sales_price#11, ss_ext_wholesale_cost#12, ss_ext_list_price#13, ss_sold_date_sk#14] +Condition : isnotnull(ss_customer_sk#9) + +(6) ColumnarToRow [codegen id : 1] +Input [6]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_sales_price#11, ss_ext_wholesale_cost#12, ss_ext_list_price#13, ss_sold_date_sk#14] + +(7) BroadcastExchange +Input [6]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_sales_price#11, ss_ext_wholesale_cost#12, ss_ext_list_price#13, ss_sold_date_sk#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [c_customer_sk#1] +Right keys [1]: [ss_customer_sk#9] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 3] +Output [12]: [c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, ss_ext_discount_amt#10, ss_ext_sales_price#11, ss_ext_wholesale_cost#12, ss_ext_list_price#13, ss_sold_date_sk#14] +Input [14]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_sales_price#11, ss_ext_wholesale_cost#12, ss_ext_list_price#13, ss_sold_date_sk#14] + +(10) ReusedExchange [Reuses operator id: 112] +Output [2]: [d_date_sk#16, d_year#17] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_sold_date_sk#14] +Right keys [1]: [d_date_sk#16] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [12]: [c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, ss_ext_discount_amt#10, ss_ext_sales_price#11, ss_ext_wholesale_cost#12, ss_ext_list_price#13, d_year#17] +Input [14]: [c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, ss_ext_discount_amt#10, ss_ext_sales_price#11, ss_ext_wholesale_cost#12, ss_ext_list_price#13, ss_sold_date_sk#14, d_date_sk#16, d_year#17] + +(13) HashAggregate [codegen id : 3] +Input [12]: [c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, ss_ext_discount_amt#10, ss_ext_sales_price#11, ss_ext_wholesale_cost#12, ss_ext_list_price#13, d_year#17] +Keys [8]: [c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, d_year#17] +Functions [1]: [partial_sum(((((ss_ext_list_price#13 - ss_ext_wholesale_cost#12) - ss_ext_discount_amt#10) + ss_ext_sales_price#11) / 2))] +Aggregate Attributes [2]: [sum#18, isEmpty#19] +Results [10]: [c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, d_year#17, sum#20, isEmpty#21] + +(14) Exchange +Input [10]: [c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, d_year#17, sum#20, isEmpty#21] +Arguments: hashpartitioning(c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, d_year#17, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 24] +Input [10]: [c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, d_year#17, sum#20, isEmpty#21] +Keys [8]: [c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, d_year#17] +Functions [1]: [sum(((((ss_ext_list_price#13 - ss_ext_wholesale_cost#12) - ss_ext_discount_amt#10) + ss_ext_sales_price#11) / 2))] +Aggregate Attributes [1]: [sum(((((ss_ext_list_price#13 - ss_ext_wholesale_cost#12) - ss_ext_discount_amt#10) + ss_ext_sales_price#11) / 2))#22] +Results [2]: [c_customer_id#2 AS customer_id#23, sum(((((ss_ext_list_price#13 - ss_ext_wholesale_cost#12) - ss_ext_discount_amt#10) + ss_ext_sales_price#11) / 2))#22 AS year_total#24] + +(16) Filter [codegen id : 24] +Input [2]: [customer_id#23, year_total#24] +Condition : (isnotnull(year_total#24) AND (year_total#24 > 0.000000)) + +(17) Scan parquet spark_catalog.default.customer +Output [8]: [c_customer_sk#25, c_customer_id#26, c_first_name#27, c_last_name#28, c_preferred_cust_flag#29, c_birth_country#30, c_login#31, c_email_address#32] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(18) CometFilter +Input [8]: [c_customer_sk#25, c_customer_id#26, c_first_name#27, c_last_name#28, c_preferred_cust_flag#29, c_birth_country#30, c_login#31, c_email_address#32] +Condition : (isnotnull(c_customer_sk#25) AND isnotnull(c_customer_id#26)) + +(19) ColumnarToRow [codegen id : 6] +Input [8]: [c_customer_sk#25, c_customer_id#26, c_first_name#27, c_last_name#28, c_preferred_cust_flag#29, c_birth_country#30, c_login#31, c_email_address#32] + +(20) Scan parquet spark_catalog.default.store_sales +Output [6]: [ss_customer_sk#33, ss_ext_discount_amt#34, ss_ext_sales_price#35, ss_ext_wholesale_cost#36, ss_ext_list_price#37, ss_sold_date_sk#38] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#38), dynamicpruningexpression(ss_sold_date_sk#38 IN dynamicpruning#39)] +PushedFilters: [IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(21) CometFilter +Input [6]: [ss_customer_sk#33, ss_ext_discount_amt#34, ss_ext_sales_price#35, ss_ext_wholesale_cost#36, ss_ext_list_price#37, ss_sold_date_sk#38] +Condition : isnotnull(ss_customer_sk#33) + +(22) ColumnarToRow [codegen id : 4] +Input [6]: [ss_customer_sk#33, ss_ext_discount_amt#34, ss_ext_sales_price#35, ss_ext_wholesale_cost#36, ss_ext_list_price#37, ss_sold_date_sk#38] + +(23) BroadcastExchange +Input [6]: [ss_customer_sk#33, ss_ext_discount_amt#34, ss_ext_sales_price#35, ss_ext_wholesale_cost#36, ss_ext_list_price#37, ss_sold_date_sk#38] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [c_customer_sk#25] +Right keys [1]: [ss_customer_sk#33] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 6] +Output [12]: [c_customer_id#26, c_first_name#27, c_last_name#28, c_preferred_cust_flag#29, c_birth_country#30, c_login#31, c_email_address#32, ss_ext_discount_amt#34, ss_ext_sales_price#35, ss_ext_wholesale_cost#36, ss_ext_list_price#37, ss_sold_date_sk#38] +Input [14]: [c_customer_sk#25, c_customer_id#26, c_first_name#27, c_last_name#28, c_preferred_cust_flag#29, c_birth_country#30, c_login#31, c_email_address#32, ss_customer_sk#33, ss_ext_discount_amt#34, ss_ext_sales_price#35, ss_ext_wholesale_cost#36, ss_ext_list_price#37, ss_sold_date_sk#38] + +(26) ReusedExchange [Reuses operator id: 116] +Output [2]: [d_date_sk#40, d_year#41] + +(27) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_sold_date_sk#38] +Right keys [1]: [d_date_sk#40] +Join type: Inner +Join condition: None + +(28) Project [codegen id : 6] +Output [12]: [c_customer_id#26, c_first_name#27, c_last_name#28, c_preferred_cust_flag#29, c_birth_country#30, c_login#31, c_email_address#32, ss_ext_discount_amt#34, ss_ext_sales_price#35, ss_ext_wholesale_cost#36, ss_ext_list_price#37, d_year#41] +Input [14]: [c_customer_id#26, c_first_name#27, c_last_name#28, c_preferred_cust_flag#29, c_birth_country#30, c_login#31, c_email_address#32, ss_ext_discount_amt#34, ss_ext_sales_price#35, ss_ext_wholesale_cost#36, ss_ext_list_price#37, ss_sold_date_sk#38, d_date_sk#40, d_year#41] + +(29) HashAggregate [codegen id : 6] +Input [12]: [c_customer_id#26, c_first_name#27, c_last_name#28, c_preferred_cust_flag#29, c_birth_country#30, c_login#31, c_email_address#32, ss_ext_discount_amt#34, ss_ext_sales_price#35, ss_ext_wholesale_cost#36, ss_ext_list_price#37, d_year#41] +Keys [8]: [c_customer_id#26, c_first_name#27, c_last_name#28, c_preferred_cust_flag#29, c_birth_country#30, c_login#31, c_email_address#32, d_year#41] +Functions [1]: [partial_sum(((((ss_ext_list_price#37 - ss_ext_wholesale_cost#36) - ss_ext_discount_amt#34) + ss_ext_sales_price#35) / 2))] +Aggregate Attributes [2]: [sum#42, isEmpty#43] +Results [10]: [c_customer_id#26, c_first_name#27, c_last_name#28, c_preferred_cust_flag#29, c_birth_country#30, c_login#31, c_email_address#32, d_year#41, sum#44, isEmpty#45] + +(30) Exchange +Input [10]: [c_customer_id#26, c_first_name#27, c_last_name#28, c_preferred_cust_flag#29, c_birth_country#30, c_login#31, c_email_address#32, d_year#41, sum#44, isEmpty#45] +Arguments: hashpartitioning(c_customer_id#26, c_first_name#27, c_last_name#28, c_preferred_cust_flag#29, c_birth_country#30, c_login#31, c_email_address#32, d_year#41, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(31) HashAggregate [codegen id : 7] +Input [10]: [c_customer_id#26, c_first_name#27, c_last_name#28, c_preferred_cust_flag#29, c_birth_country#30, c_login#31, c_email_address#32, d_year#41, sum#44, isEmpty#45] +Keys [8]: [c_customer_id#26, c_first_name#27, c_last_name#28, c_preferred_cust_flag#29, c_birth_country#30, c_login#31, c_email_address#32, d_year#41] +Functions [1]: [sum(((((ss_ext_list_price#37 - ss_ext_wholesale_cost#36) - ss_ext_discount_amt#34) + ss_ext_sales_price#35) / 2))] +Aggregate Attributes [1]: [sum(((((ss_ext_list_price#37 - ss_ext_wholesale_cost#36) - ss_ext_discount_amt#34) + ss_ext_sales_price#35) / 2))#22] +Results [8]: [c_customer_id#26 AS customer_id#46, c_first_name#27 AS customer_first_name#47, c_last_name#28 AS customer_last_name#48, c_preferred_cust_flag#29 AS customer_preferred_cust_flag#49, c_birth_country#30 AS customer_birth_country#50, c_login#31 AS customer_login#51, c_email_address#32 AS customer_email_address#52, sum(((((ss_ext_list_price#37 - ss_ext_wholesale_cost#36) - ss_ext_discount_amt#34) + ss_ext_sales_price#35) / 2))#22 AS year_total#53] + +(32) BroadcastExchange +Input [8]: [customer_id#46, customer_first_name#47, customer_last_name#48, customer_preferred_cust_flag#49, customer_birth_country#50, customer_login#51, customer_email_address#52, year_total#53] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=5] + +(33) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [customer_id#23] +Right keys [1]: [customer_id#46] +Join type: Inner +Join condition: None + +(34) Scan parquet spark_catalog.default.customer +Output [8]: [c_customer_sk#54, c_customer_id#55, c_first_name#56, c_last_name#57, c_preferred_cust_flag#58, c_birth_country#59, c_login#60, c_email_address#61] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(35) CometFilter +Input [8]: [c_customer_sk#54, c_customer_id#55, c_first_name#56, c_last_name#57, c_preferred_cust_flag#58, c_birth_country#59, c_login#60, c_email_address#61] +Condition : (isnotnull(c_customer_sk#54) AND isnotnull(c_customer_id#55)) + +(36) ColumnarToRow [codegen id : 10] +Input [8]: [c_customer_sk#54, c_customer_id#55, c_first_name#56, c_last_name#57, c_preferred_cust_flag#58, c_birth_country#59, c_login#60, c_email_address#61] + +(37) Scan parquet spark_catalog.default.catalog_sales +Output [6]: [cs_bill_customer_sk#62, cs_ext_discount_amt#63, cs_ext_sales_price#64, cs_ext_wholesale_cost#65, cs_ext_list_price#66, cs_sold_date_sk#67] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#67), dynamicpruningexpression(cs_sold_date_sk#67 IN dynamicpruning#68)] +PushedFilters: [IsNotNull(cs_bill_customer_sk)] +ReadSchema: struct + +(38) CometFilter +Input [6]: [cs_bill_customer_sk#62, cs_ext_discount_amt#63, cs_ext_sales_price#64, cs_ext_wholesale_cost#65, cs_ext_list_price#66, cs_sold_date_sk#67] +Condition : isnotnull(cs_bill_customer_sk#62) + +(39) ColumnarToRow [codegen id : 8] +Input [6]: [cs_bill_customer_sk#62, cs_ext_discount_amt#63, cs_ext_sales_price#64, cs_ext_wholesale_cost#65, cs_ext_list_price#66, cs_sold_date_sk#67] + +(40) BroadcastExchange +Input [6]: [cs_bill_customer_sk#62, cs_ext_discount_amt#63, cs_ext_sales_price#64, cs_ext_wholesale_cost#65, cs_ext_list_price#66, cs_sold_date_sk#67] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6] + +(41) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [c_customer_sk#54] +Right keys [1]: [cs_bill_customer_sk#62] +Join type: Inner +Join condition: None + +(42) Project [codegen id : 10] +Output [12]: [c_customer_id#55, c_first_name#56, c_last_name#57, c_preferred_cust_flag#58, c_birth_country#59, c_login#60, c_email_address#61, cs_ext_discount_amt#63, cs_ext_sales_price#64, cs_ext_wholesale_cost#65, cs_ext_list_price#66, cs_sold_date_sk#67] +Input [14]: [c_customer_sk#54, c_customer_id#55, c_first_name#56, c_last_name#57, c_preferred_cust_flag#58, c_birth_country#59, c_login#60, c_email_address#61, cs_bill_customer_sk#62, cs_ext_discount_amt#63, cs_ext_sales_price#64, cs_ext_wholesale_cost#65, cs_ext_list_price#66, cs_sold_date_sk#67] + +(43) ReusedExchange [Reuses operator id: 112] +Output [2]: [d_date_sk#69, d_year#70] + +(44) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_sold_date_sk#67] +Right keys [1]: [d_date_sk#69] +Join type: Inner +Join condition: None + +(45) Project [codegen id : 10] +Output [12]: [c_customer_id#55, c_first_name#56, c_last_name#57, c_preferred_cust_flag#58, c_birth_country#59, c_login#60, c_email_address#61, cs_ext_discount_amt#63, cs_ext_sales_price#64, cs_ext_wholesale_cost#65, cs_ext_list_price#66, d_year#70] +Input [14]: [c_customer_id#55, c_first_name#56, c_last_name#57, c_preferred_cust_flag#58, c_birth_country#59, c_login#60, c_email_address#61, cs_ext_discount_amt#63, cs_ext_sales_price#64, cs_ext_wholesale_cost#65, cs_ext_list_price#66, cs_sold_date_sk#67, d_date_sk#69, d_year#70] + +(46) HashAggregate [codegen id : 10] +Input [12]: [c_customer_id#55, c_first_name#56, c_last_name#57, c_preferred_cust_flag#58, c_birth_country#59, c_login#60, c_email_address#61, cs_ext_discount_amt#63, cs_ext_sales_price#64, cs_ext_wholesale_cost#65, cs_ext_list_price#66, d_year#70] +Keys [8]: [c_customer_id#55, c_first_name#56, c_last_name#57, c_preferred_cust_flag#58, c_birth_country#59, c_login#60, c_email_address#61, d_year#70] +Functions [1]: [partial_sum(((((cs_ext_list_price#66 - cs_ext_wholesale_cost#65) - cs_ext_discount_amt#63) + cs_ext_sales_price#64) / 2))] +Aggregate Attributes [2]: [sum#71, isEmpty#72] +Results [10]: [c_customer_id#55, c_first_name#56, c_last_name#57, c_preferred_cust_flag#58, c_birth_country#59, c_login#60, c_email_address#61, d_year#70, sum#73, isEmpty#74] + +(47) Exchange +Input [10]: [c_customer_id#55, c_first_name#56, c_last_name#57, c_preferred_cust_flag#58, c_birth_country#59, c_login#60, c_email_address#61, d_year#70, sum#73, isEmpty#74] +Arguments: hashpartitioning(c_customer_id#55, c_first_name#56, c_last_name#57, c_preferred_cust_flag#58, c_birth_country#59, c_login#60, c_email_address#61, d_year#70, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(48) HashAggregate [codegen id : 11] +Input [10]: [c_customer_id#55, c_first_name#56, c_last_name#57, c_preferred_cust_flag#58, c_birth_country#59, c_login#60, c_email_address#61, d_year#70, sum#73, isEmpty#74] +Keys [8]: [c_customer_id#55, c_first_name#56, c_last_name#57, c_preferred_cust_flag#58, c_birth_country#59, c_login#60, c_email_address#61, d_year#70] +Functions [1]: [sum(((((cs_ext_list_price#66 - cs_ext_wholesale_cost#65) - cs_ext_discount_amt#63) + cs_ext_sales_price#64) / 2))] +Aggregate Attributes [1]: [sum(((((cs_ext_list_price#66 - cs_ext_wholesale_cost#65) - cs_ext_discount_amt#63) + cs_ext_sales_price#64) / 2))#75] +Results [2]: [c_customer_id#55 AS customer_id#76, sum(((((cs_ext_list_price#66 - cs_ext_wholesale_cost#65) - cs_ext_discount_amt#63) + cs_ext_sales_price#64) / 2))#75 AS year_total#77] + +(49) Filter [codegen id : 11] +Input [2]: [customer_id#76, year_total#77] +Condition : (isnotnull(year_total#77) AND (year_total#77 > 0.000000)) + +(50) BroadcastExchange +Input [2]: [customer_id#76, year_total#77] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=8] + +(51) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [customer_id#23] +Right keys [1]: [customer_id#76] +Join type: Inner +Join condition: None + +(52) Project [codegen id : 24] +Output [11]: [customer_id#23, year_total#24, customer_id#46, customer_first_name#47, customer_last_name#48, customer_preferred_cust_flag#49, customer_birth_country#50, customer_login#51, customer_email_address#52, year_total#53, year_total#77] +Input [12]: [customer_id#23, year_total#24, customer_id#46, customer_first_name#47, customer_last_name#48, customer_preferred_cust_flag#49, customer_birth_country#50, customer_login#51, customer_email_address#52, year_total#53, customer_id#76, year_total#77] + +(53) Scan parquet spark_catalog.default.customer +Output [8]: [c_customer_sk#78, c_customer_id#79, c_first_name#80, c_last_name#81, c_preferred_cust_flag#82, c_birth_country#83, c_login#84, c_email_address#85] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(54) CometFilter +Input [8]: [c_customer_sk#78, c_customer_id#79, c_first_name#80, c_last_name#81, c_preferred_cust_flag#82, c_birth_country#83, c_login#84, c_email_address#85] +Condition : (isnotnull(c_customer_sk#78) AND isnotnull(c_customer_id#79)) + +(55) ColumnarToRow [codegen id : 14] +Input [8]: [c_customer_sk#78, c_customer_id#79, c_first_name#80, c_last_name#81, c_preferred_cust_flag#82, c_birth_country#83, c_login#84, c_email_address#85] + +(56) Scan parquet spark_catalog.default.catalog_sales +Output [6]: [cs_bill_customer_sk#86, cs_ext_discount_amt#87, cs_ext_sales_price#88, cs_ext_wholesale_cost#89, cs_ext_list_price#90, cs_sold_date_sk#91] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#91), dynamicpruningexpression(cs_sold_date_sk#91 IN dynamicpruning#92)] +PushedFilters: [IsNotNull(cs_bill_customer_sk)] +ReadSchema: struct + +(57) CometFilter +Input [6]: [cs_bill_customer_sk#86, cs_ext_discount_amt#87, cs_ext_sales_price#88, cs_ext_wholesale_cost#89, cs_ext_list_price#90, cs_sold_date_sk#91] +Condition : isnotnull(cs_bill_customer_sk#86) + +(58) ColumnarToRow [codegen id : 12] +Input [6]: [cs_bill_customer_sk#86, cs_ext_discount_amt#87, cs_ext_sales_price#88, cs_ext_wholesale_cost#89, cs_ext_list_price#90, cs_sold_date_sk#91] + +(59) BroadcastExchange +Input [6]: [cs_bill_customer_sk#86, cs_ext_discount_amt#87, cs_ext_sales_price#88, cs_ext_wholesale_cost#89, cs_ext_list_price#90, cs_sold_date_sk#91] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=9] + +(60) BroadcastHashJoin [codegen id : 14] +Left keys [1]: [c_customer_sk#78] +Right keys [1]: [cs_bill_customer_sk#86] +Join type: Inner +Join condition: None + +(61) Project [codegen id : 14] +Output [12]: [c_customer_id#79, c_first_name#80, c_last_name#81, c_preferred_cust_flag#82, c_birth_country#83, c_login#84, c_email_address#85, cs_ext_discount_amt#87, cs_ext_sales_price#88, cs_ext_wholesale_cost#89, cs_ext_list_price#90, cs_sold_date_sk#91] +Input [14]: [c_customer_sk#78, c_customer_id#79, c_first_name#80, c_last_name#81, c_preferred_cust_flag#82, c_birth_country#83, c_login#84, c_email_address#85, cs_bill_customer_sk#86, cs_ext_discount_amt#87, cs_ext_sales_price#88, cs_ext_wholesale_cost#89, cs_ext_list_price#90, cs_sold_date_sk#91] + +(62) ReusedExchange [Reuses operator id: 116] +Output [2]: [d_date_sk#93, d_year#94] + +(63) BroadcastHashJoin [codegen id : 14] +Left keys [1]: [cs_sold_date_sk#91] +Right keys [1]: [d_date_sk#93] +Join type: Inner +Join condition: None + +(64) Project [codegen id : 14] +Output [12]: [c_customer_id#79, c_first_name#80, c_last_name#81, c_preferred_cust_flag#82, c_birth_country#83, c_login#84, c_email_address#85, cs_ext_discount_amt#87, cs_ext_sales_price#88, cs_ext_wholesale_cost#89, cs_ext_list_price#90, d_year#94] +Input [14]: [c_customer_id#79, c_first_name#80, c_last_name#81, c_preferred_cust_flag#82, c_birth_country#83, c_login#84, c_email_address#85, cs_ext_discount_amt#87, cs_ext_sales_price#88, cs_ext_wholesale_cost#89, cs_ext_list_price#90, cs_sold_date_sk#91, d_date_sk#93, d_year#94] + +(65) HashAggregate [codegen id : 14] +Input [12]: [c_customer_id#79, c_first_name#80, c_last_name#81, c_preferred_cust_flag#82, c_birth_country#83, c_login#84, c_email_address#85, cs_ext_discount_amt#87, cs_ext_sales_price#88, cs_ext_wholesale_cost#89, cs_ext_list_price#90, d_year#94] +Keys [8]: [c_customer_id#79, c_first_name#80, c_last_name#81, c_preferred_cust_flag#82, c_birth_country#83, c_login#84, c_email_address#85, d_year#94] +Functions [1]: [partial_sum(((((cs_ext_list_price#90 - cs_ext_wholesale_cost#89) - cs_ext_discount_amt#87) + cs_ext_sales_price#88) / 2))] +Aggregate Attributes [2]: [sum#95, isEmpty#96] +Results [10]: [c_customer_id#79, c_first_name#80, c_last_name#81, c_preferred_cust_flag#82, c_birth_country#83, c_login#84, c_email_address#85, d_year#94, sum#97, isEmpty#98] + +(66) Exchange +Input [10]: [c_customer_id#79, c_first_name#80, c_last_name#81, c_preferred_cust_flag#82, c_birth_country#83, c_login#84, c_email_address#85, d_year#94, sum#97, isEmpty#98] +Arguments: hashpartitioning(c_customer_id#79, c_first_name#80, c_last_name#81, c_preferred_cust_flag#82, c_birth_country#83, c_login#84, c_email_address#85, d_year#94, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(67) HashAggregate [codegen id : 15] +Input [10]: [c_customer_id#79, c_first_name#80, c_last_name#81, c_preferred_cust_flag#82, c_birth_country#83, c_login#84, c_email_address#85, d_year#94, sum#97, isEmpty#98] +Keys [8]: [c_customer_id#79, c_first_name#80, c_last_name#81, c_preferred_cust_flag#82, c_birth_country#83, c_login#84, c_email_address#85, d_year#94] +Functions [1]: [sum(((((cs_ext_list_price#90 - cs_ext_wholesale_cost#89) - cs_ext_discount_amt#87) + cs_ext_sales_price#88) / 2))] +Aggregate Attributes [1]: [sum(((((cs_ext_list_price#90 - cs_ext_wholesale_cost#89) - cs_ext_discount_amt#87) + cs_ext_sales_price#88) / 2))#75] +Results [2]: [c_customer_id#79 AS customer_id#99, sum(((((cs_ext_list_price#90 - cs_ext_wholesale_cost#89) - cs_ext_discount_amt#87) + cs_ext_sales_price#88) / 2))#75 AS year_total#100] + +(68) BroadcastExchange +Input [2]: [customer_id#99, year_total#100] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=11] + +(69) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [customer_id#23] +Right keys [1]: [customer_id#99] +Join type: Inner +Join condition: (CASE WHEN (year_total#77 > 0.000000) THEN (year_total#100 / year_total#77) END > CASE WHEN (year_total#24 > 0.000000) THEN (year_total#53 / year_total#24) END) + +(70) Project [codegen id : 24] +Output [10]: [customer_id#23, customer_id#46, customer_first_name#47, customer_last_name#48, customer_preferred_cust_flag#49, customer_birth_country#50, customer_login#51, customer_email_address#52, year_total#77, year_total#100] +Input [13]: [customer_id#23, year_total#24, customer_id#46, customer_first_name#47, customer_last_name#48, customer_preferred_cust_flag#49, customer_birth_country#50, customer_login#51, customer_email_address#52, year_total#53, year_total#77, customer_id#99, year_total#100] + +(71) Scan parquet spark_catalog.default.customer +Output [8]: [c_customer_sk#101, c_customer_id#102, c_first_name#103, c_last_name#104, c_preferred_cust_flag#105, c_birth_country#106, c_login#107, c_email_address#108] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(72) CometFilter +Input [8]: [c_customer_sk#101, c_customer_id#102, c_first_name#103, c_last_name#104, c_preferred_cust_flag#105, c_birth_country#106, c_login#107, c_email_address#108] +Condition : (isnotnull(c_customer_sk#101) AND isnotnull(c_customer_id#102)) + +(73) ColumnarToRow [codegen id : 18] +Input [8]: [c_customer_sk#101, c_customer_id#102, c_first_name#103, c_last_name#104, c_preferred_cust_flag#105, c_birth_country#106, c_login#107, c_email_address#108] + +(74) Scan parquet spark_catalog.default.web_sales +Output [6]: [ws_bill_customer_sk#109, ws_ext_discount_amt#110, ws_ext_sales_price#111, ws_ext_wholesale_cost#112, ws_ext_list_price#113, ws_sold_date_sk#114] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#114), dynamicpruningexpression(ws_sold_date_sk#114 IN dynamicpruning#115)] +PushedFilters: [IsNotNull(ws_bill_customer_sk)] +ReadSchema: struct + +(75) CometFilter +Input [6]: [ws_bill_customer_sk#109, ws_ext_discount_amt#110, ws_ext_sales_price#111, ws_ext_wholesale_cost#112, ws_ext_list_price#113, ws_sold_date_sk#114] +Condition : isnotnull(ws_bill_customer_sk#109) + +(76) ColumnarToRow [codegen id : 16] +Input [6]: [ws_bill_customer_sk#109, ws_ext_discount_amt#110, ws_ext_sales_price#111, ws_ext_wholesale_cost#112, ws_ext_list_price#113, ws_sold_date_sk#114] + +(77) BroadcastExchange +Input [6]: [ws_bill_customer_sk#109, ws_ext_discount_amt#110, ws_ext_sales_price#111, ws_ext_wholesale_cost#112, ws_ext_list_price#113, ws_sold_date_sk#114] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=12] + +(78) BroadcastHashJoin [codegen id : 18] +Left keys [1]: [c_customer_sk#101] +Right keys [1]: [ws_bill_customer_sk#109] +Join type: Inner +Join condition: None + +(79) Project [codegen id : 18] +Output [12]: [c_customer_id#102, c_first_name#103, c_last_name#104, c_preferred_cust_flag#105, c_birth_country#106, c_login#107, c_email_address#108, ws_ext_discount_amt#110, ws_ext_sales_price#111, ws_ext_wholesale_cost#112, ws_ext_list_price#113, ws_sold_date_sk#114] +Input [14]: [c_customer_sk#101, c_customer_id#102, c_first_name#103, c_last_name#104, c_preferred_cust_flag#105, c_birth_country#106, c_login#107, c_email_address#108, ws_bill_customer_sk#109, ws_ext_discount_amt#110, ws_ext_sales_price#111, ws_ext_wholesale_cost#112, ws_ext_list_price#113, ws_sold_date_sk#114] + +(80) ReusedExchange [Reuses operator id: 112] +Output [2]: [d_date_sk#116, d_year#117] + +(81) BroadcastHashJoin [codegen id : 18] +Left keys [1]: [ws_sold_date_sk#114] +Right keys [1]: [d_date_sk#116] +Join type: Inner +Join condition: None + +(82) Project [codegen id : 18] +Output [12]: [c_customer_id#102, c_first_name#103, c_last_name#104, c_preferred_cust_flag#105, c_birth_country#106, c_login#107, c_email_address#108, ws_ext_discount_amt#110, ws_ext_sales_price#111, ws_ext_wholesale_cost#112, ws_ext_list_price#113, d_year#117] +Input [14]: [c_customer_id#102, c_first_name#103, c_last_name#104, c_preferred_cust_flag#105, c_birth_country#106, c_login#107, c_email_address#108, ws_ext_discount_amt#110, ws_ext_sales_price#111, ws_ext_wholesale_cost#112, ws_ext_list_price#113, ws_sold_date_sk#114, d_date_sk#116, d_year#117] + +(83) HashAggregate [codegen id : 18] +Input [12]: [c_customer_id#102, c_first_name#103, c_last_name#104, c_preferred_cust_flag#105, c_birth_country#106, c_login#107, c_email_address#108, ws_ext_discount_amt#110, ws_ext_sales_price#111, ws_ext_wholesale_cost#112, ws_ext_list_price#113, d_year#117] +Keys [8]: [c_customer_id#102, c_first_name#103, c_last_name#104, c_preferred_cust_flag#105, c_birth_country#106, c_login#107, c_email_address#108, d_year#117] +Functions [1]: [partial_sum(((((ws_ext_list_price#113 - ws_ext_wholesale_cost#112) - ws_ext_discount_amt#110) + ws_ext_sales_price#111) / 2))] +Aggregate Attributes [2]: [sum#118, isEmpty#119] +Results [10]: [c_customer_id#102, c_first_name#103, c_last_name#104, c_preferred_cust_flag#105, c_birth_country#106, c_login#107, c_email_address#108, d_year#117, sum#120, isEmpty#121] + +(84) Exchange +Input [10]: [c_customer_id#102, c_first_name#103, c_last_name#104, c_preferred_cust_flag#105, c_birth_country#106, c_login#107, c_email_address#108, d_year#117, sum#120, isEmpty#121] +Arguments: hashpartitioning(c_customer_id#102, c_first_name#103, c_last_name#104, c_preferred_cust_flag#105, c_birth_country#106, c_login#107, c_email_address#108, d_year#117, 5), ENSURE_REQUIREMENTS, [plan_id=13] + +(85) HashAggregate [codegen id : 19] +Input [10]: [c_customer_id#102, c_first_name#103, c_last_name#104, c_preferred_cust_flag#105, c_birth_country#106, c_login#107, c_email_address#108, d_year#117, sum#120, isEmpty#121] +Keys [8]: [c_customer_id#102, c_first_name#103, c_last_name#104, c_preferred_cust_flag#105, c_birth_country#106, c_login#107, c_email_address#108, d_year#117] +Functions [1]: [sum(((((ws_ext_list_price#113 - ws_ext_wholesale_cost#112) - ws_ext_discount_amt#110) + ws_ext_sales_price#111) / 2))] +Aggregate Attributes [1]: [sum(((((ws_ext_list_price#113 - ws_ext_wholesale_cost#112) - ws_ext_discount_amt#110) + ws_ext_sales_price#111) / 2))#122] +Results [2]: [c_customer_id#102 AS customer_id#123, sum(((((ws_ext_list_price#113 - ws_ext_wholesale_cost#112) - ws_ext_discount_amt#110) + ws_ext_sales_price#111) / 2))#122 AS year_total#124] + +(86) Filter [codegen id : 19] +Input [2]: [customer_id#123, year_total#124] +Condition : (isnotnull(year_total#124) AND (year_total#124 > 0.000000)) + +(87) BroadcastExchange +Input [2]: [customer_id#123, year_total#124] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=14] + +(88) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [customer_id#23] +Right keys [1]: [customer_id#123] +Join type: Inner +Join condition: None + +(89) Project [codegen id : 24] +Output [11]: [customer_id#23, customer_id#46, customer_first_name#47, customer_last_name#48, customer_preferred_cust_flag#49, customer_birth_country#50, customer_login#51, customer_email_address#52, year_total#77, year_total#100, year_total#124] +Input [12]: [customer_id#23, customer_id#46, customer_first_name#47, customer_last_name#48, customer_preferred_cust_flag#49, customer_birth_country#50, customer_login#51, customer_email_address#52, year_total#77, year_total#100, customer_id#123, year_total#124] + +(90) Scan parquet spark_catalog.default.customer +Output [8]: [c_customer_sk#125, c_customer_id#126, c_first_name#127, c_last_name#128, c_preferred_cust_flag#129, c_birth_country#130, c_login#131, c_email_address#132] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(91) CometFilter +Input [8]: [c_customer_sk#125, c_customer_id#126, c_first_name#127, c_last_name#128, c_preferred_cust_flag#129, c_birth_country#130, c_login#131, c_email_address#132] +Condition : (isnotnull(c_customer_sk#125) AND isnotnull(c_customer_id#126)) + +(92) ColumnarToRow [codegen id : 22] +Input [8]: [c_customer_sk#125, c_customer_id#126, c_first_name#127, c_last_name#128, c_preferred_cust_flag#129, c_birth_country#130, c_login#131, c_email_address#132] + +(93) Scan parquet spark_catalog.default.web_sales +Output [6]: [ws_bill_customer_sk#133, ws_ext_discount_amt#134, ws_ext_sales_price#135, ws_ext_wholesale_cost#136, ws_ext_list_price#137, ws_sold_date_sk#138] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#138), dynamicpruningexpression(ws_sold_date_sk#138 IN dynamicpruning#139)] +PushedFilters: [IsNotNull(ws_bill_customer_sk)] +ReadSchema: struct + +(94) CometFilter +Input [6]: [ws_bill_customer_sk#133, ws_ext_discount_amt#134, ws_ext_sales_price#135, ws_ext_wholesale_cost#136, ws_ext_list_price#137, ws_sold_date_sk#138] +Condition : isnotnull(ws_bill_customer_sk#133) + +(95) ColumnarToRow [codegen id : 20] +Input [6]: [ws_bill_customer_sk#133, ws_ext_discount_amt#134, ws_ext_sales_price#135, ws_ext_wholesale_cost#136, ws_ext_list_price#137, ws_sold_date_sk#138] + +(96) BroadcastExchange +Input [6]: [ws_bill_customer_sk#133, ws_ext_discount_amt#134, ws_ext_sales_price#135, ws_ext_wholesale_cost#136, ws_ext_list_price#137, ws_sold_date_sk#138] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=15] + +(97) BroadcastHashJoin [codegen id : 22] +Left keys [1]: [c_customer_sk#125] +Right keys [1]: [ws_bill_customer_sk#133] +Join type: Inner +Join condition: None + +(98) Project [codegen id : 22] +Output [12]: [c_customer_id#126, c_first_name#127, c_last_name#128, c_preferred_cust_flag#129, c_birth_country#130, c_login#131, c_email_address#132, ws_ext_discount_amt#134, ws_ext_sales_price#135, ws_ext_wholesale_cost#136, ws_ext_list_price#137, ws_sold_date_sk#138] +Input [14]: [c_customer_sk#125, c_customer_id#126, c_first_name#127, c_last_name#128, c_preferred_cust_flag#129, c_birth_country#130, c_login#131, c_email_address#132, ws_bill_customer_sk#133, ws_ext_discount_amt#134, ws_ext_sales_price#135, ws_ext_wholesale_cost#136, ws_ext_list_price#137, ws_sold_date_sk#138] + +(99) ReusedExchange [Reuses operator id: 116] +Output [2]: [d_date_sk#140, d_year#141] + +(100) BroadcastHashJoin [codegen id : 22] +Left keys [1]: [ws_sold_date_sk#138] +Right keys [1]: [d_date_sk#140] +Join type: Inner +Join condition: None + +(101) Project [codegen id : 22] +Output [12]: [c_customer_id#126, c_first_name#127, c_last_name#128, c_preferred_cust_flag#129, c_birth_country#130, c_login#131, c_email_address#132, ws_ext_discount_amt#134, ws_ext_sales_price#135, ws_ext_wholesale_cost#136, ws_ext_list_price#137, d_year#141] +Input [14]: [c_customer_id#126, c_first_name#127, c_last_name#128, c_preferred_cust_flag#129, c_birth_country#130, c_login#131, c_email_address#132, ws_ext_discount_amt#134, ws_ext_sales_price#135, ws_ext_wholesale_cost#136, ws_ext_list_price#137, ws_sold_date_sk#138, d_date_sk#140, d_year#141] + +(102) HashAggregate [codegen id : 22] +Input [12]: [c_customer_id#126, c_first_name#127, c_last_name#128, c_preferred_cust_flag#129, c_birth_country#130, c_login#131, c_email_address#132, ws_ext_discount_amt#134, ws_ext_sales_price#135, ws_ext_wholesale_cost#136, ws_ext_list_price#137, d_year#141] +Keys [8]: [c_customer_id#126, c_first_name#127, c_last_name#128, c_preferred_cust_flag#129, c_birth_country#130, c_login#131, c_email_address#132, d_year#141] +Functions [1]: [partial_sum(((((ws_ext_list_price#137 - ws_ext_wholesale_cost#136) - ws_ext_discount_amt#134) + ws_ext_sales_price#135) / 2))] +Aggregate Attributes [2]: [sum#142, isEmpty#143] +Results [10]: [c_customer_id#126, c_first_name#127, c_last_name#128, c_preferred_cust_flag#129, c_birth_country#130, c_login#131, c_email_address#132, d_year#141, sum#144, isEmpty#145] + +(103) Exchange +Input [10]: [c_customer_id#126, c_first_name#127, c_last_name#128, c_preferred_cust_flag#129, c_birth_country#130, c_login#131, c_email_address#132, d_year#141, sum#144, isEmpty#145] +Arguments: hashpartitioning(c_customer_id#126, c_first_name#127, c_last_name#128, c_preferred_cust_flag#129, c_birth_country#130, c_login#131, c_email_address#132, d_year#141, 5), ENSURE_REQUIREMENTS, [plan_id=16] + +(104) HashAggregate [codegen id : 23] +Input [10]: [c_customer_id#126, c_first_name#127, c_last_name#128, c_preferred_cust_flag#129, c_birth_country#130, c_login#131, c_email_address#132, d_year#141, sum#144, isEmpty#145] +Keys [8]: [c_customer_id#126, c_first_name#127, c_last_name#128, c_preferred_cust_flag#129, c_birth_country#130, c_login#131, c_email_address#132, d_year#141] +Functions [1]: [sum(((((ws_ext_list_price#137 - ws_ext_wholesale_cost#136) - ws_ext_discount_amt#134) + ws_ext_sales_price#135) / 2))] +Aggregate Attributes [1]: [sum(((((ws_ext_list_price#137 - ws_ext_wholesale_cost#136) - ws_ext_discount_amt#134) + ws_ext_sales_price#135) / 2))#122] +Results [2]: [c_customer_id#126 AS customer_id#146, sum(((((ws_ext_list_price#137 - ws_ext_wholesale_cost#136) - ws_ext_discount_amt#134) + ws_ext_sales_price#135) / 2))#122 AS year_total#147] + +(105) BroadcastExchange +Input [2]: [customer_id#146, year_total#147] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=17] + +(106) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [customer_id#23] +Right keys [1]: [customer_id#146] +Join type: Inner +Join condition: (CASE WHEN (year_total#77 > 0.000000) THEN (year_total#100 / year_total#77) END > CASE WHEN (year_total#124 > 0.000000) THEN (year_total#147 / year_total#124) END) + +(107) Project [codegen id : 24] +Output [7]: [customer_id#46, customer_first_name#47, customer_last_name#48, customer_preferred_cust_flag#49, customer_birth_country#50, customer_login#51, customer_email_address#52] +Input [13]: [customer_id#23, customer_id#46, customer_first_name#47, customer_last_name#48, customer_preferred_cust_flag#49, customer_birth_country#50, customer_login#51, customer_email_address#52, year_total#77, year_total#100, year_total#124, customer_id#146, year_total#147] + +(108) TakeOrderedAndProject +Input [7]: [customer_id#46, customer_first_name#47, customer_last_name#48, customer_preferred_cust_flag#49, customer_birth_country#50, customer_login#51, customer_email_address#52] +Arguments: 100, [customer_id#46 ASC NULLS FIRST, customer_first_name#47 ASC NULLS FIRST, customer_last_name#48 ASC NULLS FIRST, customer_preferred_cust_flag#49 ASC NULLS FIRST, customer_birth_country#50 ASC NULLS FIRST, customer_login#51 ASC NULLS FIRST, customer_email_address#52 ASC NULLS FIRST], [customer_id#46, customer_first_name#47, customer_last_name#48, customer_preferred_cust_flag#49, customer_birth_country#50, customer_login#51, customer_email_address#52] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#14 IN dynamicpruning#15 +BroadcastExchange (112) ++- * ColumnarToRow (111) + +- CometFilter (110) + +- CometScan parquet spark_catalog.default.date_dim (109) + + +(109) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#16, d_year#17] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(110) CometFilter +Input [2]: [d_date_sk#16, d_year#17] +Condition : ((isnotnull(d_year#17) AND (d_year#17 = 2001)) AND isnotnull(d_date_sk#16)) + +(111) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#16, d_year#17] + +(112) BroadcastExchange +Input [2]: [d_date_sk#16, d_year#17] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=18] + +Subquery:2 Hosting operator id = 20 Hosting Expression = ss_sold_date_sk#38 IN dynamicpruning#39 +BroadcastExchange (116) ++- * ColumnarToRow (115) + +- CometFilter (114) + +- CometScan parquet spark_catalog.default.date_dim (113) + + +(113) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#40, d_year#41] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2002), IsNotNull(d_date_sk)] +ReadSchema: struct + +(114) CometFilter +Input [2]: [d_date_sk#40, d_year#41] +Condition : ((isnotnull(d_year#41) AND (d_year#41 = 2002)) AND isnotnull(d_date_sk#40)) + +(115) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#40, d_year#41] + +(116) BroadcastExchange +Input [2]: [d_date_sk#40, d_year#41] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=19] + +Subquery:3 Hosting operator id = 37 Hosting Expression = cs_sold_date_sk#67 IN dynamicpruning#15 + +Subquery:4 Hosting operator id = 56 Hosting Expression = cs_sold_date_sk#91 IN dynamicpruning#39 + +Subquery:5 Hosting operator id = 74 Hosting Expression = ws_sold_date_sk#114 IN dynamicpruning#15 + +Subquery:6 Hosting operator id = 93 Hosting Expression = ws_sold_date_sk#138 IN dynamicpruning#39 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q4/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q4/simplified.txt new file mode 100644 index 0000000000..99e255a0e4 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q4/simplified.txt @@ -0,0 +1,179 @@ +TakeOrderedAndProject [customer_id,customer_first_name,customer_last_name,customer_preferred_cust_flag,customer_birth_country,customer_login,customer_email_address] + WholeStageCodegen (24) + Project [customer_id,customer_first_name,customer_last_name,customer_preferred_cust_flag,customer_birth_country,customer_login,customer_email_address] + BroadcastHashJoin [customer_id,customer_id,year_total,year_total,year_total,year_total] + Project [customer_id,customer_id,customer_first_name,customer_last_name,customer_preferred_cust_flag,customer_birth_country,customer_login,customer_email_address,year_total,year_total,year_total] + BroadcastHashJoin [customer_id,customer_id] + Project [customer_id,customer_id,customer_first_name,customer_last_name,customer_preferred_cust_flag,customer_birth_country,customer_login,customer_email_address,year_total,year_total] + BroadcastHashJoin [customer_id,customer_id,year_total,year_total,year_total,year_total] + Project [customer_id,year_total,customer_id,customer_first_name,customer_last_name,customer_preferred_cust_flag,customer_birth_country,customer_login,customer_email_address,year_total,year_total] + BroadcastHashJoin [customer_id,customer_id] + BroadcastHashJoin [customer_id,customer_id] + Filter [year_total] + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,sum,isEmpty] [sum(((((ss_ext_list_price - ss_ext_wholesale_cost) - ss_ext_discount_amt) + ss_ext_sales_price) / 2)),customer_id,year_total,sum,isEmpty] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year] #1 + WholeStageCodegen (3) + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,ss_ext_list_price,ss_ext_wholesale_cost,ss_ext_discount_amt,ss_ext_sales_price] [sum,isEmpty,sum,isEmpty] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_discount_amt,ss_ext_sales_price,ss_ext_wholesale_cost,ss_ext_list_price,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_discount_amt,ss_ext_sales_price,ss_ext_wholesale_cost,ss_ext_list_price,ss_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk] + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_ext_discount_amt,ss_ext_sales_price,ss_ext_wholesale_cost,ss_ext_list_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk,d_year] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (7) + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,sum,isEmpty] [sum(((((ss_ext_list_price - ss_ext_wholesale_cost) - ss_ext_discount_amt) + ss_ext_sales_price) / 2)),customer_id,customer_first_name,customer_last_name,customer_preferred_cust_flag,customer_birth_country,customer_login,customer_email_address,year_total,sum,isEmpty] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year] #5 + WholeStageCodegen (6) + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,ss_ext_list_price,ss_ext_wholesale_cost,ss_ext_discount_amt,ss_ext_sales_price] [sum,isEmpty,sum,isEmpty] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_discount_amt,ss_ext_sales_price,ss_ext_wholesale_cost,ss_ext_list_price,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_discount_amt,ss_ext_sales_price,ss_ext_wholesale_cost,ss_ext_list_price,ss_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (4) + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk] + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_ext_discount_amt,ss_ext_sales_price,ss_ext_wholesale_cost,ss_ext_list_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #7 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk,d_year] #7 + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (11) + Filter [year_total] + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,sum,isEmpty] [sum(((((cs_ext_list_price - cs_ext_wholesale_cost) - cs_ext_discount_amt) + cs_ext_sales_price) / 2)),customer_id,year_total,sum,isEmpty] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year] #9 + WholeStageCodegen (10) + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,cs_ext_list_price,cs_ext_wholesale_cost,cs_ext_discount_amt,cs_ext_sales_price] [sum,isEmpty,sum,isEmpty] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,cs_ext_discount_amt,cs_ext_sales_price,cs_ext_wholesale_cost,cs_ext_list_price,d_year] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,cs_ext_discount_amt,cs_ext_sales_price,cs_ext_wholesale_cost,cs_ext_list_price,cs_sold_date_sk] + BroadcastHashJoin [c_customer_sk,cs_bill_customer_sk] + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] + InputAdapter + BroadcastExchange #10 + WholeStageCodegen (8) + ColumnarToRow + InputAdapter + CometFilter [cs_bill_customer_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_ext_discount_amt,cs_ext_sales_price,cs_ext_wholesale_cost,cs_ext_list_price,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk,d_year] #3 + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (15) + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,sum,isEmpty] [sum(((((cs_ext_list_price - cs_ext_wholesale_cost) - cs_ext_discount_amt) + cs_ext_sales_price) / 2)),customer_id,year_total,sum,isEmpty] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year] #12 + WholeStageCodegen (14) + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,cs_ext_list_price,cs_ext_wholesale_cost,cs_ext_discount_amt,cs_ext_sales_price] [sum,isEmpty,sum,isEmpty] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,cs_ext_discount_amt,cs_ext_sales_price,cs_ext_wholesale_cost,cs_ext_list_price,d_year] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,cs_ext_discount_amt,cs_ext_sales_price,cs_ext_wholesale_cost,cs_ext_list_price,cs_sold_date_sk] + BroadcastHashJoin [c_customer_sk,cs_bill_customer_sk] + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] + InputAdapter + BroadcastExchange #13 + WholeStageCodegen (12) + ColumnarToRow + InputAdapter + CometFilter [cs_bill_customer_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_ext_discount_amt,cs_ext_sales_price,cs_ext_wholesale_cost,cs_ext_list_price,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk,d_year] #7 + InputAdapter + BroadcastExchange #14 + WholeStageCodegen (19) + Filter [year_total] + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,sum,isEmpty] [sum(((((ws_ext_list_price - ws_ext_wholesale_cost) - ws_ext_discount_amt) + ws_ext_sales_price) / 2)),customer_id,year_total,sum,isEmpty] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year] #15 + WholeStageCodegen (18) + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,ws_ext_list_price,ws_ext_wholesale_cost,ws_ext_discount_amt,ws_ext_sales_price] [sum,isEmpty,sum,isEmpty] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ws_ext_discount_amt,ws_ext_sales_price,ws_ext_wholesale_cost,ws_ext_list_price,d_year] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ws_ext_discount_amt,ws_ext_sales_price,ws_ext_wholesale_cost,ws_ext_list_price,ws_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] + InputAdapter + BroadcastExchange #16 + WholeStageCodegen (16) + ColumnarToRow + InputAdapter + CometFilter [ws_bill_customer_sk] + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_ext_discount_amt,ws_ext_sales_price,ws_ext_wholesale_cost,ws_ext_list_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk,d_year] #3 + InputAdapter + BroadcastExchange #17 + WholeStageCodegen (23) + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,sum,isEmpty] [sum(((((ws_ext_list_price - ws_ext_wholesale_cost) - ws_ext_discount_amt) + ws_ext_sales_price) / 2)),customer_id,year_total,sum,isEmpty] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year] #18 + WholeStageCodegen (22) + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,ws_ext_list_price,ws_ext_wholesale_cost,ws_ext_discount_amt,ws_ext_sales_price] [sum,isEmpty,sum,isEmpty] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ws_ext_discount_amt,ws_ext_sales_price,ws_ext_wholesale_cost,ws_ext_list_price,d_year] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ws_ext_discount_amt,ws_ext_sales_price,ws_ext_wholesale_cost,ws_ext_list_price,ws_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] + InputAdapter + BroadcastExchange #19 + WholeStageCodegen (20) + ColumnarToRow + InputAdapter + CometFilter [ws_bill_customer_sk] + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_ext_discount_amt,ws_ext_sales_price,ws_ext_wholesale_cost,ws_ext_list_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk,d_year] #7 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q40/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q40/explain.txt new file mode 100644 index 0000000000..f63b94658c --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q40/explain.txt @@ -0,0 +1,218 @@ +== Physical Plan == +TakeOrderedAndProject (33) ++- * HashAggregate (32) + +- Exchange (31) + +- * HashAggregate (30) + +- * Project (29) + +- * BroadcastHashJoin Inner BuildRight (28) + :- * Project (26) + : +- * BroadcastHashJoin Inner BuildRight (25) + : :- * Project (19) + : : +- * BroadcastHashJoin Inner BuildRight (18) + : : :- * Project (13) + : : : +- * SortMergeJoin LeftOuter (12) + : : : :- * Sort (5) + : : : : +- Exchange (4) + : : : : +- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) + : : : +- * Sort (11) + : : : +- Exchange (10) + : : : +- * ColumnarToRow (9) + : : : +- CometProject (8) + : : : +- CometFilter (7) + : : : +- CometScan parquet spark_catalog.default.catalog_returns (6) + : : +- BroadcastExchange (17) + : : +- * ColumnarToRow (16) + : : +- CometFilter (15) + : : +- CometScan parquet spark_catalog.default.warehouse (14) + : +- BroadcastExchange (24) + : +- * ColumnarToRow (23) + : +- CometProject (22) + : +- CometFilter (21) + : +- CometScan parquet spark_catalog.default.item (20) + +- ReusedExchange (27) + + +(1) Scan parquet spark_catalog.default.catalog_sales +Output [5]: [cs_warehouse_sk#1, cs_item_sk#2, cs_order_number#3, cs_sales_price#4, cs_sold_date_sk#5] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#5), dynamicpruningexpression(cs_sold_date_sk#5 IN dynamicpruning#6)] +PushedFilters: [IsNotNull(cs_warehouse_sk), IsNotNull(cs_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [5]: [cs_warehouse_sk#1, cs_item_sk#2, cs_order_number#3, cs_sales_price#4, cs_sold_date_sk#5] +Condition : (isnotnull(cs_warehouse_sk#1) AND isnotnull(cs_item_sk#2)) + +(3) ColumnarToRow [codegen id : 1] +Input [5]: [cs_warehouse_sk#1, cs_item_sk#2, cs_order_number#3, cs_sales_price#4, cs_sold_date_sk#5] + +(4) Exchange +Input [5]: [cs_warehouse_sk#1, cs_item_sk#2, cs_order_number#3, cs_sales_price#4, cs_sold_date_sk#5] +Arguments: hashpartitioning(cs_order_number#3, cs_item_sk#2, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(5) Sort [codegen id : 2] +Input [5]: [cs_warehouse_sk#1, cs_item_sk#2, cs_order_number#3, cs_sales_price#4, cs_sold_date_sk#5] +Arguments: [cs_order_number#3 ASC NULLS FIRST, cs_item_sk#2 ASC NULLS FIRST], false, 0 + +(6) Scan parquet spark_catalog.default.catalog_returns +Output [4]: [cr_item_sk#7, cr_order_number#8, cr_refunded_cash#9, cr_returned_date_sk#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_returns] +PushedFilters: [IsNotNull(cr_order_number), IsNotNull(cr_item_sk)] +ReadSchema: struct + +(7) CometFilter +Input [4]: [cr_item_sk#7, cr_order_number#8, cr_refunded_cash#9, cr_returned_date_sk#10] +Condition : (isnotnull(cr_order_number#8) AND isnotnull(cr_item_sk#7)) + +(8) CometProject +Input [4]: [cr_item_sk#7, cr_order_number#8, cr_refunded_cash#9, cr_returned_date_sk#10] +Arguments: [cr_item_sk#7, cr_order_number#8, cr_refunded_cash#9], [cr_item_sk#7, cr_order_number#8, cr_refunded_cash#9] + +(9) ColumnarToRow [codegen id : 3] +Input [3]: [cr_item_sk#7, cr_order_number#8, cr_refunded_cash#9] + +(10) Exchange +Input [3]: [cr_item_sk#7, cr_order_number#8, cr_refunded_cash#9] +Arguments: hashpartitioning(cr_order_number#8, cr_item_sk#7, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(11) Sort [codegen id : 4] +Input [3]: [cr_item_sk#7, cr_order_number#8, cr_refunded_cash#9] +Arguments: [cr_order_number#8 ASC NULLS FIRST, cr_item_sk#7 ASC NULLS FIRST], false, 0 + +(12) SortMergeJoin [codegen id : 8] +Left keys [2]: [cs_order_number#3, cs_item_sk#2] +Right keys [2]: [cr_order_number#8, cr_item_sk#7] +Join type: LeftOuter +Join condition: None + +(13) Project [codegen id : 8] +Output [5]: [cs_warehouse_sk#1, cs_item_sk#2, cs_sales_price#4, cs_sold_date_sk#5, cr_refunded_cash#9] +Input [8]: [cs_warehouse_sk#1, cs_item_sk#2, cs_order_number#3, cs_sales_price#4, cs_sold_date_sk#5, cr_item_sk#7, cr_order_number#8, cr_refunded_cash#9] + +(14) Scan parquet spark_catalog.default.warehouse +Output [2]: [w_warehouse_sk#11, w_state#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/warehouse] +PushedFilters: [IsNotNull(w_warehouse_sk)] +ReadSchema: struct + +(15) CometFilter +Input [2]: [w_warehouse_sk#11, w_state#12] +Condition : isnotnull(w_warehouse_sk#11) + +(16) ColumnarToRow [codegen id : 5] +Input [2]: [w_warehouse_sk#11, w_state#12] + +(17) BroadcastExchange +Input [2]: [w_warehouse_sk#11, w_state#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(18) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [cs_warehouse_sk#1] +Right keys [1]: [w_warehouse_sk#11] +Join type: Inner +Join condition: None + +(19) Project [codegen id : 8] +Output [5]: [cs_item_sk#2, cs_sales_price#4, cs_sold_date_sk#5, cr_refunded_cash#9, w_state#12] +Input [7]: [cs_warehouse_sk#1, cs_item_sk#2, cs_sales_price#4, cs_sold_date_sk#5, cr_refunded_cash#9, w_warehouse_sk#11, w_state#12] + +(20) Scan parquet spark_catalog.default.item +Output [3]: [i_item_sk#13, i_item_id#14, i_current_price#15] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_current_price), GreaterThanOrEqual(i_current_price,0.99), LessThanOrEqual(i_current_price,1.49), IsNotNull(i_item_sk)] +ReadSchema: struct + +(21) CometFilter +Input [3]: [i_item_sk#13, i_item_id#14, i_current_price#15] +Condition : (((isnotnull(i_current_price#15) AND (i_current_price#15 >= 0.99)) AND (i_current_price#15 <= 1.49)) AND isnotnull(i_item_sk#13)) + +(22) CometProject +Input [3]: [i_item_sk#13, i_item_id#14, i_current_price#15] +Arguments: [i_item_sk#13, i_item_id#14], [i_item_sk#13, i_item_id#14] + +(23) ColumnarToRow [codegen id : 6] +Input [2]: [i_item_sk#13, i_item_id#14] + +(24) BroadcastExchange +Input [2]: [i_item_sk#13, i_item_id#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(25) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [cs_item_sk#2] +Right keys [1]: [i_item_sk#13] +Join type: Inner +Join condition: None + +(26) Project [codegen id : 8] +Output [5]: [cs_sales_price#4, cs_sold_date_sk#5, cr_refunded_cash#9, w_state#12, i_item_id#14] +Input [7]: [cs_item_sk#2, cs_sales_price#4, cs_sold_date_sk#5, cr_refunded_cash#9, w_state#12, i_item_sk#13, i_item_id#14] + +(27) ReusedExchange [Reuses operator id: 37] +Output [2]: [d_date_sk#16, d_date#17] + +(28) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [cs_sold_date_sk#5] +Right keys [1]: [d_date_sk#16] +Join type: Inner +Join condition: None + +(29) Project [codegen id : 8] +Output [5]: [cs_sales_price#4, cr_refunded_cash#9, w_state#12, i_item_id#14, d_date#17] +Input [7]: [cs_sales_price#4, cs_sold_date_sk#5, cr_refunded_cash#9, w_state#12, i_item_id#14, d_date_sk#16, d_date#17] + +(30) HashAggregate [codegen id : 8] +Input [5]: [cs_sales_price#4, cr_refunded_cash#9, w_state#12, i_item_id#14, d_date#17] +Keys [2]: [w_state#12, i_item_id#14] +Functions [2]: [partial_sum(CASE WHEN (d_date#17 < 2000-03-11) THEN (cs_sales_price#4 - coalesce(cast(cr_refunded_cash#9 as decimal(12,2)), 0.00)) ELSE 0.00 END), partial_sum(CASE WHEN (d_date#17 >= 2000-03-11) THEN (cs_sales_price#4 - coalesce(cast(cr_refunded_cash#9 as decimal(12,2)), 0.00)) ELSE 0.00 END)] +Aggregate Attributes [4]: [sum#18, isEmpty#19, sum#20, isEmpty#21] +Results [6]: [w_state#12, i_item_id#14, sum#22, isEmpty#23, sum#24, isEmpty#25] + +(31) Exchange +Input [6]: [w_state#12, i_item_id#14, sum#22, isEmpty#23, sum#24, isEmpty#25] +Arguments: hashpartitioning(w_state#12, i_item_id#14, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(32) HashAggregate [codegen id : 9] +Input [6]: [w_state#12, i_item_id#14, sum#22, isEmpty#23, sum#24, isEmpty#25] +Keys [2]: [w_state#12, i_item_id#14] +Functions [2]: [sum(CASE WHEN (d_date#17 < 2000-03-11) THEN (cs_sales_price#4 - coalesce(cast(cr_refunded_cash#9 as decimal(12,2)), 0.00)) ELSE 0.00 END), sum(CASE WHEN (d_date#17 >= 2000-03-11) THEN (cs_sales_price#4 - coalesce(cast(cr_refunded_cash#9 as decimal(12,2)), 0.00)) ELSE 0.00 END)] +Aggregate Attributes [2]: [sum(CASE WHEN (d_date#17 < 2000-03-11) THEN (cs_sales_price#4 - coalesce(cast(cr_refunded_cash#9 as decimal(12,2)), 0.00)) ELSE 0.00 END)#26, sum(CASE WHEN (d_date#17 >= 2000-03-11) THEN (cs_sales_price#4 - coalesce(cast(cr_refunded_cash#9 as decimal(12,2)), 0.00)) ELSE 0.00 END)#27] +Results [4]: [w_state#12, i_item_id#14, sum(CASE WHEN (d_date#17 < 2000-03-11) THEN (cs_sales_price#4 - coalesce(cast(cr_refunded_cash#9 as decimal(12,2)), 0.00)) ELSE 0.00 END)#26 AS sales_before#28, sum(CASE WHEN (d_date#17 >= 2000-03-11) THEN (cs_sales_price#4 - coalesce(cast(cr_refunded_cash#9 as decimal(12,2)), 0.00)) ELSE 0.00 END)#27 AS sales_after#29] + +(33) TakeOrderedAndProject +Input [4]: [w_state#12, i_item_id#14, sales_before#28, sales_after#29] +Arguments: 100, [w_state#12 ASC NULLS FIRST, i_item_id#14 ASC NULLS FIRST], [w_state#12, i_item_id#14, sales_before#28, sales_after#29] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#5 IN dynamicpruning#6 +BroadcastExchange (37) ++- * ColumnarToRow (36) + +- CometFilter (35) + +- CometScan parquet spark_catalog.default.date_dim (34) + + +(34) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#16, d_date#17] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,2000-02-10), LessThanOrEqual(d_date,2000-04-10), IsNotNull(d_date_sk)] +ReadSchema: struct + +(35) CometFilter +Input [2]: [d_date_sk#16, d_date#17] +Condition : (((isnotnull(d_date#17) AND (d_date#17 >= 2000-02-10)) AND (d_date#17 <= 2000-04-10)) AND isnotnull(d_date_sk#16)) + +(36) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#16, d_date#17] + +(37) BroadcastExchange +Input [2]: [d_date_sk#16, d_date#17] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q40/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q40/simplified.txt new file mode 100644 index 0000000000..10e0735b4b --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q40/simplified.txt @@ -0,0 +1,60 @@ +TakeOrderedAndProject [w_state,i_item_id,sales_before,sales_after] + WholeStageCodegen (9) + HashAggregate [w_state,i_item_id,sum,isEmpty,sum,isEmpty] [sum(CASE WHEN (d_date < 2000-03-11) THEN (cs_sales_price - coalesce(cast(cr_refunded_cash as decimal(12,2)), 0.00)) ELSE 0.00 END),sum(CASE WHEN (d_date >= 2000-03-11) THEN (cs_sales_price - coalesce(cast(cr_refunded_cash as decimal(12,2)), 0.00)) ELSE 0.00 END),sales_before,sales_after,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [w_state,i_item_id] #1 + WholeStageCodegen (8) + HashAggregate [w_state,i_item_id,d_date,cs_sales_price,cr_refunded_cash] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + Project [cs_sales_price,cr_refunded_cash,w_state,i_item_id,d_date] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_sales_price,cs_sold_date_sk,cr_refunded_cash,w_state,i_item_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Project [cs_item_sk,cs_sales_price,cs_sold_date_sk,cr_refunded_cash,w_state] + BroadcastHashJoin [cs_warehouse_sk,w_warehouse_sk] + Project [cs_warehouse_sk,cs_item_sk,cs_sales_price,cs_sold_date_sk,cr_refunded_cash] + SortMergeJoin [cs_order_number,cs_item_sk,cr_order_number,cr_item_sk] + InputAdapter + WholeStageCodegen (2) + Sort [cs_order_number,cs_item_sk] + InputAdapter + Exchange [cs_order_number,cs_item_sk] #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [cs_warehouse_sk,cs_item_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_warehouse_sk,cs_item_sk,cs_order_number,cs_sales_price,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_date,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + WholeStageCodegen (4) + Sort [cr_order_number,cr_item_sk] + InputAdapter + Exchange [cr_order_number,cr_item_sk] #4 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometProject [cr_item_sk,cr_order_number,cr_refunded_cash] + CometFilter [cr_order_number,cr_item_sk] + CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_refunded_cash,cr_returned_date_sk] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (5) + ColumnarToRow + InputAdapter + CometFilter [w_warehouse_sk] + CometScan parquet spark_catalog.default.warehouse [w_warehouse_sk,w_state] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (6) + ColumnarToRow + InputAdapter + CometProject [i_item_sk,i_item_id] + CometFilter [i_current_price,i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_current_price] + InputAdapter + ReusedExchange [d_date_sk,d_date] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q41/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q41/explain.txt new file mode 100644 index 0000000000..07196ba8cc --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q41/explain.txt @@ -0,0 +1,119 @@ +== Physical Plan == +TakeOrderedAndProject (20) ++- * HashAggregate (19) + +- Exchange (18) + +- * HashAggregate (17) + +- * Project (16) + +- * BroadcastHashJoin Inner BuildRight (15) + :- * ColumnarToRow (4) + : +- CometProject (3) + : +- CometFilter (2) + : +- CometScan parquet spark_catalog.default.item (1) + +- BroadcastExchange (14) + +- * Project (13) + +- * Filter (12) + +- * HashAggregate (11) + +- Exchange (10) + +- * ColumnarToRow (9) + +- CometHashAggregate (8) + +- CometProject (7) + +- CometFilter (6) + +- CometScan parquet spark_catalog.default.item (5) + + +(1) Scan parquet spark_catalog.default.item +Output [3]: [i_manufact_id#1, i_manufact#2, i_product_name#3] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_manufact_id), GreaterThanOrEqual(i_manufact_id,738), LessThanOrEqual(i_manufact_id,778), IsNotNull(i_manufact)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [i_manufact_id#1, i_manufact#2, i_product_name#3] +Condition : (((isnotnull(i_manufact_id#1) AND (i_manufact_id#1 >= 738)) AND (i_manufact_id#1 <= 778)) AND isnotnull(i_manufact#2)) + +(3) CometProject +Input [3]: [i_manufact_id#1, i_manufact#2, i_product_name#3] +Arguments: [i_manufact#2, i_product_name#3], [i_manufact#2, i_product_name#3] + +(4) ColumnarToRow [codegen id : 3] +Input [2]: [i_manufact#2, i_product_name#3] + +(5) Scan parquet spark_catalog.default.item +Output [5]: [i_category#4, i_manufact#5, i_size#6, i_color#7, i_units#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [Or(Or(And(EqualTo(i_category,Women ),Or(And(And(Or(EqualTo(i_color,powder ),EqualTo(i_color,khaki )),Or(EqualTo(i_units,Ounce ),EqualTo(i_units,Oz ))),Or(EqualTo(i_size,medium ),EqualTo(i_size,extra large ))),And(And(Or(EqualTo(i_color,brown ),EqualTo(i_color,honeydew )),Or(EqualTo(i_units,Bunch ),EqualTo(i_units,Ton ))),Or(EqualTo(i_size,N/A ),EqualTo(i_size,small ))))),And(EqualTo(i_category,Men ),Or(And(And(Or(EqualTo(i_color,floral ),EqualTo(i_color,deep )),Or(EqualTo(i_units,N/A ),EqualTo(i_units,Dozen ))),Or(EqualTo(i_size,petite ),EqualTo(i_size,large ))),And(And(Or(EqualTo(i_color,light ),EqualTo(i_color,cornflower )),Or(EqualTo(i_units,Box ),EqualTo(i_units,Pound ))),Or(EqualTo(i_size,medium ),EqualTo(i_size,extra large )))))),Or(And(EqualTo(i_category,Women ),Or(And(And(Or(EqualTo(i_color,midnight ),EqualTo(i_color,snow )),Or(EqualTo(i_units,Pallet ),EqualTo(i_units,Gross ))),Or(EqualTo(i_size,medium ),EqualTo(i_size,extra large ))),And(And(Or(EqualTo(i_color,cyan ),EqualTo(i_color,papaya )),Or(EqualTo(i_units,Cup ),EqualTo(i_units,Dram ))),Or(EqualTo(i_size,N/A ),EqualTo(i_size,small ))))),And(EqualTo(i_category,Men ),Or(And(And(Or(EqualTo(i_color,orange ),EqualTo(i_color,frosted )),Or(EqualTo(i_units,Each ),EqualTo(i_units,Tbl ))),Or(EqualTo(i_size,petite ),EqualTo(i_size,large ))),And(And(Or(EqualTo(i_color,forest ),EqualTo(i_color,ghost )),Or(EqualTo(i_units,Lb ),EqualTo(i_units,Bundle ))),Or(EqualTo(i_size,medium ),EqualTo(i_size,extra large ))))))), IsNotNull(i_manufact)] +ReadSchema: struct + +(6) CometFilter +Input [5]: [i_category#4, i_manufact#5, i_size#6, i_color#7, i_units#8] +Condition : (((((i_category#4 = Women ) AND (((((i_color#7 = powder ) OR (i_color#7 = khaki )) AND ((i_units#8 = Ounce ) OR (i_units#8 = Oz ))) AND ((i_size#6 = medium ) OR (i_size#6 = extra large ))) OR ((((i_color#7 = brown ) OR (i_color#7 = honeydew )) AND ((i_units#8 = Bunch ) OR (i_units#8 = Ton ))) AND ((i_size#6 = N/A ) OR (i_size#6 = small ))))) OR ((i_category#4 = Men ) AND (((((i_color#7 = floral ) OR (i_color#7 = deep )) AND ((i_units#8 = N/A ) OR (i_units#8 = Dozen ))) AND ((i_size#6 = petite ) OR (i_size#6 = large ))) OR ((((i_color#7 = light ) OR (i_color#7 = cornflower )) AND ((i_units#8 = Box ) OR (i_units#8 = Pound ))) AND ((i_size#6 = medium ) OR (i_size#6 = extra large )))))) OR (((i_category#4 = Women ) AND (((((i_color#7 = midnight ) OR (i_color#7 = snow )) AND ((i_units#8 = Pallet ) OR (i_units#8 = Gross ))) AND ((i_size#6 = medium ) OR (i_size#6 = extra large ))) OR ((((i_color#7 = cyan ) OR (i_color#7 = papaya )) AND ((i_units#8 = Cup ) OR (i_units#8 = Dram ))) AND ((i_size#6 = N/A ) OR (i_size#6 = small ))))) OR ((i_category#4 = Men ) AND (((((i_color#7 = orange ) OR (i_color#7 = frosted )) AND ((i_units#8 = Each ) OR (i_units#8 = Tbl ))) AND ((i_size#6 = petite ) OR (i_size#6 = large ))) OR ((((i_color#7 = forest ) OR (i_color#7 = ghost )) AND ((i_units#8 = Lb ) OR (i_units#8 = Bundle ))) AND ((i_size#6 = medium ) OR (i_size#6 = extra large ))))))) AND isnotnull(i_manufact#5)) + +(7) CometProject +Input [5]: [i_category#4, i_manufact#5, i_size#6, i_color#7, i_units#8] +Arguments: [i_manufact#5], [i_manufact#5] + +(8) CometHashAggregate +Input [1]: [i_manufact#5] +Keys [1]: [i_manufact#5] +Functions [1]: [partial_count(1)] + +(9) ColumnarToRow [codegen id : 1] +Input [2]: [i_manufact#5, count#9] + +(10) Exchange +Input [2]: [i_manufact#5, count#9] +Arguments: hashpartitioning(i_manufact#5, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(11) HashAggregate [codegen id : 2] +Input [2]: [i_manufact#5, count#9] +Keys [1]: [i_manufact#5] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#10] +Results [2]: [count(1)#10 AS item_cnt#11, i_manufact#5] + +(12) Filter [codegen id : 2] +Input [2]: [item_cnt#11, i_manufact#5] +Condition : (item_cnt#11 > 0) + +(13) Project [codegen id : 2] +Output [1]: [i_manufact#5] +Input [2]: [item_cnt#11, i_manufact#5] + +(14) BroadcastExchange +Input [1]: [i_manufact#5] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=2] + +(15) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [i_manufact#2] +Right keys [1]: [i_manufact#5] +Join type: Inner +Join condition: None + +(16) Project [codegen id : 3] +Output [1]: [i_product_name#3] +Input [3]: [i_manufact#2, i_product_name#3, i_manufact#5] + +(17) HashAggregate [codegen id : 3] +Input [1]: [i_product_name#3] +Keys [1]: [i_product_name#3] +Functions: [] +Aggregate Attributes: [] +Results [1]: [i_product_name#3] + +(18) Exchange +Input [1]: [i_product_name#3] +Arguments: hashpartitioning(i_product_name#3, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(19) HashAggregate [codegen id : 4] +Input [1]: [i_product_name#3] +Keys [1]: [i_product_name#3] +Functions: [] +Aggregate Attributes: [] +Results [1]: [i_product_name#3] + +(20) TakeOrderedAndProject +Input [1]: [i_product_name#3] +Arguments: 100, [i_product_name#3 ASC NULLS FIRST], [i_product_name#3] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q41/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q41/simplified.txt new file mode 100644 index 0000000000..e31217066b --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q41/simplified.txt @@ -0,0 +1,29 @@ +TakeOrderedAndProject [i_product_name] + WholeStageCodegen (4) + HashAggregate [i_product_name] + InputAdapter + Exchange [i_product_name] #1 + WholeStageCodegen (3) + HashAggregate [i_product_name] + Project [i_product_name] + BroadcastHashJoin [i_manufact,i_manufact] + ColumnarToRow + InputAdapter + CometProject [i_manufact,i_product_name] + CometFilter [i_manufact_id,i_manufact] + CometScan parquet spark_catalog.default.item [i_manufact_id,i_manufact,i_product_name] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (2) + Project [i_manufact] + Filter [item_cnt] + HashAggregate [i_manufact,count] [count(1),item_cnt,count] + InputAdapter + Exchange [i_manufact] #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometHashAggregate [i_manufact] + CometProject [i_manufact] + CometFilter [i_category,i_color,i_units,i_size,i_manufact] + CometScan parquet spark_catalog.default.item [i_category,i_manufact,i_size,i_color,i_units] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q42/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q42/explain.txt new file mode 100644 index 0000000000..d51d63d8a5 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q42/explain.txt @@ -0,0 +1,125 @@ +== Physical Plan == +TakeOrderedAndProject (21) ++- * HashAggregate (20) + +- Exchange (19) + +- * HashAggregate (18) + +- * Project (17) + +- * BroadcastHashJoin Inner BuildRight (16) + :- * Project (10) + : +- * BroadcastHashJoin Inner BuildRight (9) + : :- * ColumnarToRow (4) + : : +- CometProject (3) + : : +- CometFilter (2) + : : +- CometScan parquet spark_catalog.default.date_dim (1) + : +- BroadcastExchange (8) + : +- * ColumnarToRow (7) + : +- CometFilter (6) + : +- CometScan parquet spark_catalog.default.store_sales (5) + +- BroadcastExchange (15) + +- * ColumnarToRow (14) + +- CometProject (13) + +- CometFilter (12) + +- CometScan parquet spark_catalog.default.item (11) + + +(1) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#1, d_year#2, d_moy#3] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), EqualTo(d_moy,11), EqualTo(d_year,2000), IsNotNull(d_date_sk)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [d_date_sk#1, d_year#2, d_moy#3] +Condition : ((((isnotnull(d_moy#3) AND isnotnull(d_year#2)) AND (d_moy#3 = 11)) AND (d_year#2 = 2000)) AND isnotnull(d_date_sk#1)) + +(3) CometProject +Input [3]: [d_date_sk#1, d_year#2, d_moy#3] +Arguments: [d_date_sk#1, d_year#2], [d_date_sk#1, d_year#2] + +(4) ColumnarToRow [codegen id : 3] +Input [2]: [d_date_sk#1, d_year#2] + +(5) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#6), dynamicpruningexpression(true)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(6) CometFilter +Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] +Condition : isnotnull(ss_item_sk#4) + +(7) ColumnarToRow [codegen id : 1] +Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] + +(8) BroadcastExchange +Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[2, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [d_date_sk#1] +Right keys [1]: [ss_sold_date_sk#6] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 3] +Output [3]: [d_year#2, ss_item_sk#4, ss_ext_sales_price#5] +Input [5]: [d_date_sk#1, d_year#2, ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] + +(11) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#7, i_category_id#8, i_category#9, i_manager_id#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_manager_id), EqualTo(i_manager_id,1), IsNotNull(i_item_sk)] +ReadSchema: struct + +(12) CometFilter +Input [4]: [i_item_sk#7, i_category_id#8, i_category#9, i_manager_id#10] +Condition : ((isnotnull(i_manager_id#10) AND (i_manager_id#10 = 1)) AND isnotnull(i_item_sk#7)) + +(13) CometProject +Input [4]: [i_item_sk#7, i_category_id#8, i_category#9, i_manager_id#10] +Arguments: [i_item_sk#7, i_category_id#8, i_category#9], [i_item_sk#7, i_category_id#8, i_category#9] + +(14) ColumnarToRow [codegen id : 2] +Input [3]: [i_item_sk#7, i_category_id#8, i_category#9] + +(15) BroadcastExchange +Input [3]: [i_item_sk#7, i_category_id#8, i_category#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(16) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_item_sk#4] +Right keys [1]: [i_item_sk#7] +Join type: Inner +Join condition: None + +(17) Project [codegen id : 3] +Output [4]: [d_year#2, ss_ext_sales_price#5, i_category_id#8, i_category#9] +Input [6]: [d_year#2, ss_item_sk#4, ss_ext_sales_price#5, i_item_sk#7, i_category_id#8, i_category#9] + +(18) HashAggregate [codegen id : 3] +Input [4]: [d_year#2, ss_ext_sales_price#5, i_category_id#8, i_category#9] +Keys [3]: [d_year#2, i_category_id#8, i_category#9] +Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#5))] +Aggregate Attributes [1]: [sum#11] +Results [4]: [d_year#2, i_category_id#8, i_category#9, sum#12] + +(19) Exchange +Input [4]: [d_year#2, i_category_id#8, i_category#9, sum#12] +Arguments: hashpartitioning(d_year#2, i_category_id#8, i_category#9, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(20) HashAggregate [codegen id : 4] +Input [4]: [d_year#2, i_category_id#8, i_category#9, sum#12] +Keys [3]: [d_year#2, i_category_id#8, i_category#9] +Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#5))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#5))#13] +Results [4]: [d_year#2, i_category_id#8, i_category#9, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#5))#13,17,2) AS sum(ss_ext_sales_price)#14] + +(21) TakeOrderedAndProject +Input [4]: [d_year#2, i_category_id#8, i_category#9, sum(ss_ext_sales_price)#14] +Arguments: 100, [sum(ss_ext_sales_price)#14 DESC NULLS LAST, d_year#2 ASC NULLS FIRST, i_category_id#8 ASC NULLS FIRST, i_category#9 ASC NULLS FIRST], [d_year#2, i_category_id#8, i_category#9, sum(ss_ext_sales_price)#14] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q42/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q42/simplified.txt new file mode 100644 index 0000000000..67906b8c7a --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q42/simplified.txt @@ -0,0 +1,31 @@ +TakeOrderedAndProject [sum(ss_ext_sales_price),d_year,i_category_id,i_category] + WholeStageCodegen (4) + HashAggregate [d_year,i_category_id,i_category,sum] [sum(UnscaledValue(ss_ext_sales_price)),sum(ss_ext_sales_price),sum] + InputAdapter + Exchange [d_year,i_category_id,i_category] #1 + WholeStageCodegen (3) + HashAggregate [d_year,i_category_id,i_category,ss_ext_sales_price] [sum,sum] + Project [d_year,ss_ext_sales_price,i_category_id,i_category] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [d_year,ss_item_sk,ss_ext_sales_price] + BroadcastHashJoin [d_date_sk,ss_sold_date_sk] + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_year] + CometFilter [d_moy,d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ext_sales_price,ss_sold_date_sk] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometProject [i_item_sk,i_category_id,i_category] + CometFilter [i_manager_id,i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_category_id,i_category,i_manager_id] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q43/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q43/explain.txt new file mode 100644 index 0000000000..e892aa4694 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q43/explain.txt @@ -0,0 +1,125 @@ +== Physical Plan == +TakeOrderedAndProject (21) ++- * HashAggregate (20) + +- Exchange (19) + +- * HashAggregate (18) + +- * Project (17) + +- * BroadcastHashJoin Inner BuildRight (16) + :- * Project (10) + : +- * BroadcastHashJoin Inner BuildRight (9) + : :- * ColumnarToRow (4) + : : +- CometProject (3) + : : +- CometFilter (2) + : : +- CometScan parquet spark_catalog.default.date_dim (1) + : +- BroadcastExchange (8) + : +- * ColumnarToRow (7) + : +- CometFilter (6) + : +- CometScan parquet spark_catalog.default.store_sales (5) + +- BroadcastExchange (15) + +- * ColumnarToRow (14) + +- CometProject (13) + +- CometFilter (12) + +- CometScan parquet spark_catalog.default.store (11) + + +(1) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#1, d_year#2, d_day_name#3] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2000), IsNotNull(d_date_sk)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [d_date_sk#1, d_year#2, d_day_name#3] +Condition : ((isnotnull(d_year#2) AND (d_year#2 = 2000)) AND isnotnull(d_date_sk#1)) + +(3) CometProject +Input [3]: [d_date_sk#1, d_year#2, d_day_name#3] +Arguments: [d_date_sk#1, d_day_name#3], [d_date_sk#1, d_day_name#3] + +(4) ColumnarToRow [codegen id : 3] +Input [2]: [d_date_sk#1, d_day_name#3] + +(5) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_store_sk#4, ss_sales_price#5, ss_sold_date_sk#6] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#6), dynamicpruningexpression(true)] +PushedFilters: [IsNotNull(ss_store_sk)] +ReadSchema: struct + +(6) CometFilter +Input [3]: [ss_store_sk#4, ss_sales_price#5, ss_sold_date_sk#6] +Condition : isnotnull(ss_store_sk#4) + +(7) ColumnarToRow [codegen id : 1] +Input [3]: [ss_store_sk#4, ss_sales_price#5, ss_sold_date_sk#6] + +(8) BroadcastExchange +Input [3]: [ss_store_sk#4, ss_sales_price#5, ss_sold_date_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[2, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [d_date_sk#1] +Right keys [1]: [ss_sold_date_sk#6] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 3] +Output [3]: [d_day_name#3, ss_store_sk#4, ss_sales_price#5] +Input [5]: [d_date_sk#1, d_day_name#3, ss_store_sk#4, ss_sales_price#5, ss_sold_date_sk#6] + +(11) Scan parquet spark_catalog.default.store +Output [4]: [s_store_sk#7, s_store_id#8, s_store_name#9, s_gmt_offset#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_gmt_offset), EqualTo(s_gmt_offset,-5.00), IsNotNull(s_store_sk)] +ReadSchema: struct + +(12) CometFilter +Input [4]: [s_store_sk#7, s_store_id#8, s_store_name#9, s_gmt_offset#10] +Condition : ((isnotnull(s_gmt_offset#10) AND (s_gmt_offset#10 = -5.00)) AND isnotnull(s_store_sk#7)) + +(13) CometProject +Input [4]: [s_store_sk#7, s_store_id#8, s_store_name#9, s_gmt_offset#10] +Arguments: [s_store_sk#7, s_store_id#8, s_store_name#9], [s_store_sk#7, s_store_id#8, s_store_name#9] + +(14) ColumnarToRow [codegen id : 2] +Input [3]: [s_store_sk#7, s_store_id#8, s_store_name#9] + +(15) BroadcastExchange +Input [3]: [s_store_sk#7, s_store_id#8, s_store_name#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(16) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_store_sk#4] +Right keys [1]: [s_store_sk#7] +Join type: Inner +Join condition: None + +(17) Project [codegen id : 3] +Output [4]: [d_day_name#3, ss_sales_price#5, s_store_id#8, s_store_name#9] +Input [6]: [d_day_name#3, ss_store_sk#4, ss_sales_price#5, s_store_sk#7, s_store_id#8, s_store_name#9] + +(18) HashAggregate [codegen id : 3] +Input [4]: [d_day_name#3, ss_sales_price#5, s_store_id#8, s_store_name#9] +Keys [2]: [s_store_name#9, s_store_id#8] +Functions [7]: [partial_sum(UnscaledValue(CASE WHEN (d_day_name#3 = Sunday ) THEN ss_sales_price#5 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#3 = Monday ) THEN ss_sales_price#5 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#3 = Tuesday ) THEN ss_sales_price#5 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#3 = Wednesday) THEN ss_sales_price#5 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#3 = Thursday ) THEN ss_sales_price#5 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#3 = Friday ) THEN ss_sales_price#5 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#3 = Saturday ) THEN ss_sales_price#5 END))] +Aggregate Attributes [7]: [sum#11, sum#12, sum#13, sum#14, sum#15, sum#16, sum#17] +Results [9]: [s_store_name#9, s_store_id#8, sum#18, sum#19, sum#20, sum#21, sum#22, sum#23, sum#24] + +(19) Exchange +Input [9]: [s_store_name#9, s_store_id#8, sum#18, sum#19, sum#20, sum#21, sum#22, sum#23, sum#24] +Arguments: hashpartitioning(s_store_name#9, s_store_id#8, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(20) HashAggregate [codegen id : 4] +Input [9]: [s_store_name#9, s_store_id#8, sum#18, sum#19, sum#20, sum#21, sum#22, sum#23, sum#24] +Keys [2]: [s_store_name#9, s_store_id#8] +Functions [7]: [sum(UnscaledValue(CASE WHEN (d_day_name#3 = Sunday ) THEN ss_sales_price#5 END)), sum(UnscaledValue(CASE WHEN (d_day_name#3 = Monday ) THEN ss_sales_price#5 END)), sum(UnscaledValue(CASE WHEN (d_day_name#3 = Tuesday ) THEN ss_sales_price#5 END)), sum(UnscaledValue(CASE WHEN (d_day_name#3 = Wednesday) THEN ss_sales_price#5 END)), sum(UnscaledValue(CASE WHEN (d_day_name#3 = Thursday ) THEN ss_sales_price#5 END)), sum(UnscaledValue(CASE WHEN (d_day_name#3 = Friday ) THEN ss_sales_price#5 END)), sum(UnscaledValue(CASE WHEN (d_day_name#3 = Saturday ) THEN ss_sales_price#5 END))] +Aggregate Attributes [7]: [sum(UnscaledValue(CASE WHEN (d_day_name#3 = Sunday ) THEN ss_sales_price#5 END))#25, sum(UnscaledValue(CASE WHEN (d_day_name#3 = Monday ) THEN ss_sales_price#5 END))#26, sum(UnscaledValue(CASE WHEN (d_day_name#3 = Tuesday ) THEN ss_sales_price#5 END))#27, sum(UnscaledValue(CASE WHEN (d_day_name#3 = Wednesday) THEN ss_sales_price#5 END))#28, sum(UnscaledValue(CASE WHEN (d_day_name#3 = Thursday ) THEN ss_sales_price#5 END))#29, sum(UnscaledValue(CASE WHEN (d_day_name#3 = Friday ) THEN ss_sales_price#5 END))#30, sum(UnscaledValue(CASE WHEN (d_day_name#3 = Saturday ) THEN ss_sales_price#5 END))#31] +Results [9]: [s_store_name#9, s_store_id#8, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#3 = Sunday ) THEN ss_sales_price#5 END))#25,17,2) AS sun_sales#32, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#3 = Monday ) THEN ss_sales_price#5 END))#26,17,2) AS mon_sales#33, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#3 = Tuesday ) THEN ss_sales_price#5 END))#27,17,2) AS tue_sales#34, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#3 = Wednesday) THEN ss_sales_price#5 END))#28,17,2) AS wed_sales#35, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#3 = Thursday ) THEN ss_sales_price#5 END))#29,17,2) AS thu_sales#36, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#3 = Friday ) THEN ss_sales_price#5 END))#30,17,2) AS fri_sales#37, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#3 = Saturday ) THEN ss_sales_price#5 END))#31,17,2) AS sat_sales#38] + +(21) TakeOrderedAndProject +Input [9]: [s_store_name#9, s_store_id#8, sun_sales#32, mon_sales#33, tue_sales#34, wed_sales#35, thu_sales#36, fri_sales#37, sat_sales#38] +Arguments: 100, [s_store_name#9 ASC NULLS FIRST, s_store_id#8 ASC NULLS FIRST, sun_sales#32 ASC NULLS FIRST, mon_sales#33 ASC NULLS FIRST, tue_sales#34 ASC NULLS FIRST, wed_sales#35 ASC NULLS FIRST, thu_sales#36 ASC NULLS FIRST, fri_sales#37 ASC NULLS FIRST, sat_sales#38 ASC NULLS FIRST], [s_store_name#9, s_store_id#8, sun_sales#32, mon_sales#33, tue_sales#34, wed_sales#35, thu_sales#36, fri_sales#37, sat_sales#38] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q43/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q43/simplified.txt new file mode 100644 index 0000000000..ef20430969 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q43/simplified.txt @@ -0,0 +1,31 @@ +TakeOrderedAndProject [s_store_name,s_store_id,sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales] + WholeStageCodegen (4) + HashAggregate [s_store_name,s_store_id,sum,sum,sum,sum,sum,sum,sum] [sum(UnscaledValue(CASE WHEN (d_day_name = Sunday ) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Monday ) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Tuesday ) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Wednesday) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Thursday ) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Friday ) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Saturday ) THEN ss_sales_price END)),sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales,sum,sum,sum,sum,sum,sum,sum] + InputAdapter + Exchange [s_store_name,s_store_id] #1 + WholeStageCodegen (3) + HashAggregate [s_store_name,s_store_id,d_day_name,ss_sales_price] [sum,sum,sum,sum,sum,sum,sum,sum,sum,sum,sum,sum,sum,sum] + Project [d_day_name,ss_sales_price,s_store_id,s_store_name] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [d_day_name,ss_store_sk,ss_sales_price] + BroadcastHashJoin [d_date_sk,ss_sold_date_sk] + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_day_name] + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_day_name] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_store_sk,ss_sales_price,ss_sold_date_sk] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometProject [s_store_sk,s_store_id,s_store_name] + CometFilter [s_gmt_offset,s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_id,s_store_name,s_gmt_offset] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q44/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q44/explain.txt new file mode 100644 index 0000000000..812f9f391e --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q44/explain.txt @@ -0,0 +1,286 @@ +== Physical Plan == +TakeOrderedAndProject (43) ++- * Project (42) + +- * BroadcastHashJoin Inner BuildRight (41) + :- * Project (39) + : +- * BroadcastHashJoin Inner BuildRight (38) + : :- * Project (33) + : : +- * SortMergeJoin Inner (32) + : : :- * Sort (18) + : : : +- Exchange (17) + : : : +- * Project (16) + : : : +- * Filter (15) + : : : +- Window (14) + : : : +- WindowGroupLimit (13) + : : : +- * Sort (12) + : : : +- Exchange (11) + : : : +- WindowGroupLimit (10) + : : : +- * Sort (9) + : : : +- * Filter (8) + : : : +- * HashAggregate (7) + : : : +- Exchange (6) + : : : +- * HashAggregate (5) + : : : +- * ColumnarToRow (4) + : : : +- CometProject (3) + : : : +- CometFilter (2) + : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : +- * Sort (31) + : : +- Exchange (30) + : : +- * Project (29) + : : +- * Filter (28) + : : +- Window (27) + : : +- WindowGroupLimit (26) + : : +- * Sort (25) + : : +- Exchange (24) + : : +- WindowGroupLimit (23) + : : +- * Sort (22) + : : +- * Filter (21) + : : +- * HashAggregate (20) + : : +- ReusedExchange (19) + : +- BroadcastExchange (37) + : +- * ColumnarToRow (36) + : +- CometFilter (35) + : +- CometScan parquet spark_catalog.default.item (34) + +- ReusedExchange (40) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#1, ss_store_sk#2, ss_net_profit#3, ss_sold_date_sk#4] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_store_sk), EqualTo(ss_store_sk,4)] +ReadSchema: struct + +(2) CometFilter +Input [4]: [ss_item_sk#1, ss_store_sk#2, ss_net_profit#3, ss_sold_date_sk#4] +Condition : (isnotnull(ss_store_sk#2) AND (ss_store_sk#2 = 4)) + +(3) CometProject +Input [4]: [ss_item_sk#1, ss_store_sk#2, ss_net_profit#3, ss_sold_date_sk#4] +Arguments: [ss_item_sk#1, ss_net_profit#3], [ss_item_sk#1, ss_net_profit#3] + +(4) ColumnarToRow [codegen id : 1] +Input [2]: [ss_item_sk#1, ss_net_profit#3] + +(5) HashAggregate [codegen id : 1] +Input [2]: [ss_item_sk#1, ss_net_profit#3] +Keys [1]: [ss_item_sk#1] +Functions [1]: [partial_avg(UnscaledValue(ss_net_profit#3))] +Aggregate Attributes [2]: [sum#5, count#6] +Results [3]: [ss_item_sk#1, sum#7, count#8] + +(6) Exchange +Input [3]: [ss_item_sk#1, sum#7, count#8] +Arguments: hashpartitioning(ss_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(7) HashAggregate [codegen id : 2] +Input [3]: [ss_item_sk#1, sum#7, count#8] +Keys [1]: [ss_item_sk#1] +Functions [1]: [avg(UnscaledValue(ss_net_profit#3))] +Aggregate Attributes [1]: [avg(UnscaledValue(ss_net_profit#3))#9] +Results [2]: [ss_item_sk#1 AS item_sk#10, cast((avg(UnscaledValue(ss_net_profit#3))#9 / 100.0) as decimal(11,6)) AS rank_col#11] + +(8) Filter [codegen id : 2] +Input [2]: [item_sk#10, rank_col#11] +Condition : (isnotnull(rank_col#11) AND (cast(rank_col#11 as decimal(13,7)) > (0.9 * Subquery scalar-subquery#12, [id=#13]))) + +(9) Sort [codegen id : 2] +Input [2]: [item_sk#10, rank_col#11] +Arguments: [rank_col#11 ASC NULLS FIRST], false, 0 + +(10) WindowGroupLimit +Input [2]: [item_sk#10, rank_col#11] +Arguments: [rank_col#11 ASC NULLS FIRST], rank(rank_col#11), 10, Partial + +(11) Exchange +Input [2]: [item_sk#10, rank_col#11] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=2] + +(12) Sort [codegen id : 3] +Input [2]: [item_sk#10, rank_col#11] +Arguments: [rank_col#11 ASC NULLS FIRST], false, 0 + +(13) WindowGroupLimit +Input [2]: [item_sk#10, rank_col#11] +Arguments: [rank_col#11 ASC NULLS FIRST], rank(rank_col#11), 10, Final + +(14) Window +Input [2]: [item_sk#10, rank_col#11] +Arguments: [rank(rank_col#11) windowspecdefinition(rank_col#11 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rnk#14], [rank_col#11 ASC NULLS FIRST] + +(15) Filter [codegen id : 4] +Input [3]: [item_sk#10, rank_col#11, rnk#14] +Condition : ((rnk#14 < 11) AND isnotnull(item_sk#10)) + +(16) Project [codegen id : 4] +Output [2]: [item_sk#10, rnk#14] +Input [3]: [item_sk#10, rank_col#11, rnk#14] + +(17) Exchange +Input [2]: [item_sk#10, rnk#14] +Arguments: hashpartitioning(rnk#14, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(18) Sort [codegen id : 5] +Input [2]: [item_sk#10, rnk#14] +Arguments: [rnk#14 ASC NULLS FIRST], false, 0 + +(19) ReusedExchange [Reuses operator id: 6] +Output [3]: [ss_item_sk#15, sum#16, count#17] + +(20) HashAggregate [codegen id : 7] +Input [3]: [ss_item_sk#15, sum#16, count#17] +Keys [1]: [ss_item_sk#15] +Functions [1]: [avg(UnscaledValue(ss_net_profit#18))] +Aggregate Attributes [1]: [avg(UnscaledValue(ss_net_profit#18))#19] +Results [2]: [ss_item_sk#15 AS item_sk#20, cast((avg(UnscaledValue(ss_net_profit#18))#19 / 100.0) as decimal(11,6)) AS rank_col#21] + +(21) Filter [codegen id : 7] +Input [2]: [item_sk#20, rank_col#21] +Condition : (isnotnull(rank_col#21) AND (cast(rank_col#21 as decimal(13,7)) > (0.9 * ReusedSubquery Subquery scalar-subquery#12, [id=#13]))) + +(22) Sort [codegen id : 7] +Input [2]: [item_sk#20, rank_col#21] +Arguments: [rank_col#21 DESC NULLS LAST], false, 0 + +(23) WindowGroupLimit +Input [2]: [item_sk#20, rank_col#21] +Arguments: [rank_col#21 DESC NULLS LAST], rank(rank_col#21), 10, Partial + +(24) Exchange +Input [2]: [item_sk#20, rank_col#21] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=4] + +(25) Sort [codegen id : 8] +Input [2]: [item_sk#20, rank_col#21] +Arguments: [rank_col#21 DESC NULLS LAST], false, 0 + +(26) WindowGroupLimit +Input [2]: [item_sk#20, rank_col#21] +Arguments: [rank_col#21 DESC NULLS LAST], rank(rank_col#21), 10, Final + +(27) Window +Input [2]: [item_sk#20, rank_col#21] +Arguments: [rank(rank_col#21) windowspecdefinition(rank_col#21 DESC NULLS LAST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rnk#22], [rank_col#21 DESC NULLS LAST] + +(28) Filter [codegen id : 9] +Input [3]: [item_sk#20, rank_col#21, rnk#22] +Condition : ((rnk#22 < 11) AND isnotnull(item_sk#20)) + +(29) Project [codegen id : 9] +Output [2]: [item_sk#20, rnk#22] +Input [3]: [item_sk#20, rank_col#21, rnk#22] + +(30) Exchange +Input [2]: [item_sk#20, rnk#22] +Arguments: hashpartitioning(rnk#22, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(31) Sort [codegen id : 10] +Input [2]: [item_sk#20, rnk#22] +Arguments: [rnk#22 ASC NULLS FIRST], false, 0 + +(32) SortMergeJoin [codegen id : 13] +Left keys [1]: [rnk#14] +Right keys [1]: [rnk#22] +Join type: Inner +Join condition: None + +(33) Project [codegen id : 13] +Output [3]: [item_sk#10, rnk#14, item_sk#20] +Input [4]: [item_sk#10, rnk#14, item_sk#20, rnk#22] + +(34) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#23, i_product_name#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(35) CometFilter +Input [2]: [i_item_sk#23, i_product_name#24] +Condition : isnotnull(i_item_sk#23) + +(36) ColumnarToRow [codegen id : 11] +Input [2]: [i_item_sk#23, i_product_name#24] + +(37) BroadcastExchange +Input [2]: [i_item_sk#23, i_product_name#24] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6] + +(38) BroadcastHashJoin [codegen id : 13] +Left keys [1]: [item_sk#10] +Right keys [1]: [i_item_sk#23] +Join type: Inner +Join condition: None + +(39) Project [codegen id : 13] +Output [3]: [rnk#14, item_sk#20, i_product_name#24] +Input [5]: [item_sk#10, rnk#14, item_sk#20, i_item_sk#23, i_product_name#24] + +(40) ReusedExchange [Reuses operator id: 37] +Output [2]: [i_item_sk#25, i_product_name#26] + +(41) BroadcastHashJoin [codegen id : 13] +Left keys [1]: [item_sk#20] +Right keys [1]: [i_item_sk#25] +Join type: Inner +Join condition: None + +(42) Project [codegen id : 13] +Output [3]: [rnk#14, i_product_name#24 AS best_performing#27, i_product_name#26 AS worst_performing#28] +Input [5]: [rnk#14, item_sk#20, i_product_name#24, i_item_sk#25, i_product_name#26] + +(43) TakeOrderedAndProject +Input [3]: [rnk#14, best_performing#27, worst_performing#28] +Arguments: 100, [rnk#14 ASC NULLS FIRST], [rnk#14, best_performing#27, worst_performing#28] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 8 Hosting Expression = Subquery scalar-subquery#12, [id=#13] +* HashAggregate (50) ++- Exchange (49) + +- * HashAggregate (48) + +- * ColumnarToRow (47) + +- CometProject (46) + +- CometFilter (45) + +- CometScan parquet spark_catalog.default.store_sales (44) + + +(44) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_addr_sk#29, ss_store_sk#30, ss_net_profit#31, ss_sold_date_sk#32] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_store_sk), EqualTo(ss_store_sk,4), IsNull(ss_addr_sk)] +ReadSchema: struct + +(45) CometFilter +Input [4]: [ss_addr_sk#29, ss_store_sk#30, ss_net_profit#31, ss_sold_date_sk#32] +Condition : ((isnotnull(ss_store_sk#30) AND (ss_store_sk#30 = 4)) AND isnull(ss_addr_sk#29)) + +(46) CometProject +Input [4]: [ss_addr_sk#29, ss_store_sk#30, ss_net_profit#31, ss_sold_date_sk#32] +Arguments: [ss_store_sk#30, ss_net_profit#31], [ss_store_sk#30, ss_net_profit#31] + +(47) ColumnarToRow [codegen id : 1] +Input [2]: [ss_store_sk#30, ss_net_profit#31] + +(48) HashAggregate [codegen id : 1] +Input [2]: [ss_store_sk#30, ss_net_profit#31] +Keys [1]: [ss_store_sk#30] +Functions [1]: [partial_avg(UnscaledValue(ss_net_profit#31))] +Aggregate Attributes [2]: [sum#33, count#34] +Results [3]: [ss_store_sk#30, sum#35, count#36] + +(49) Exchange +Input [3]: [ss_store_sk#30, sum#35, count#36] +Arguments: hashpartitioning(ss_store_sk#30, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(50) HashAggregate [codegen id : 2] +Input [3]: [ss_store_sk#30, sum#35, count#36] +Keys [1]: [ss_store_sk#30] +Functions [1]: [avg(UnscaledValue(ss_net_profit#31))] +Aggregate Attributes [1]: [avg(UnscaledValue(ss_net_profit#31))#37] +Results [1]: [cast((avg(UnscaledValue(ss_net_profit#31))#37 / 100.0) as decimal(11,6)) AS rank_col#38] + +Subquery:2 Hosting operator id = 21 Hosting Expression = ReusedSubquery Subquery scalar-subquery#12, [id=#13] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q44/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q44/simplified.txt new file mode 100644 index 0000000000..35a3e9efa5 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q44/simplified.txt @@ -0,0 +1,81 @@ +TakeOrderedAndProject [rnk,best_performing,worst_performing] + WholeStageCodegen (13) + Project [rnk,i_product_name,i_product_name] + BroadcastHashJoin [item_sk,i_item_sk] + Project [rnk,item_sk,i_product_name] + BroadcastHashJoin [item_sk,i_item_sk] + Project [item_sk,rnk,item_sk] + SortMergeJoin [rnk,rnk] + InputAdapter + WholeStageCodegen (5) + Sort [rnk] + InputAdapter + Exchange [rnk] #1 + WholeStageCodegen (4) + Project [item_sk,rnk] + Filter [rnk,item_sk] + InputAdapter + Window [rank_col] + WindowGroupLimit [rank_col] + WholeStageCodegen (3) + Sort [rank_col] + InputAdapter + Exchange #2 + WindowGroupLimit [rank_col] + WholeStageCodegen (2) + Sort [rank_col] + Filter [rank_col] + Subquery #1 + WholeStageCodegen (2) + HashAggregate [ss_store_sk,sum,count] [avg(UnscaledValue(ss_net_profit)),rank_col,sum,count] + InputAdapter + Exchange [ss_store_sk] #4 + WholeStageCodegen (1) + HashAggregate [ss_store_sk,ss_net_profit] [sum,count,sum,count] + ColumnarToRow + InputAdapter + CometProject [ss_store_sk,ss_net_profit] + CometFilter [ss_store_sk,ss_addr_sk] + CometScan parquet spark_catalog.default.store_sales [ss_addr_sk,ss_store_sk,ss_net_profit,ss_sold_date_sk] + HashAggregate [ss_item_sk,sum,count] [avg(UnscaledValue(ss_net_profit)),item_sk,rank_col,sum,count] + InputAdapter + Exchange [ss_item_sk] #3 + WholeStageCodegen (1) + HashAggregate [ss_item_sk,ss_net_profit] [sum,count,sum,count] + ColumnarToRow + InputAdapter + CometProject [ss_item_sk,ss_net_profit] + CometFilter [ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_net_profit,ss_sold_date_sk] + InputAdapter + WholeStageCodegen (10) + Sort [rnk] + InputAdapter + Exchange [rnk] #5 + WholeStageCodegen (9) + Project [item_sk,rnk] + Filter [rnk,item_sk] + InputAdapter + Window [rank_col] + WindowGroupLimit [rank_col] + WholeStageCodegen (8) + Sort [rank_col] + InputAdapter + Exchange #6 + WindowGroupLimit [rank_col] + WholeStageCodegen (7) + Sort [rank_col] + Filter [rank_col] + ReusedSubquery [rank_col] #1 + HashAggregate [ss_item_sk,sum,count] [avg(UnscaledValue(ss_net_profit)),item_sk,rank_col,sum,count] + InputAdapter + ReusedExchange [ss_item_sk,sum,count] #3 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (11) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_product_name] + InputAdapter + ReusedExchange [i_item_sk,i_product_name] #7 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q45/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q45/explain.txt new file mode 100644 index 0000000000..d0d74569be --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q45/explain.txt @@ -0,0 +1,242 @@ +== Physical Plan == +TakeOrderedAndProject (36) ++- * HashAggregate (35) + +- Exchange (34) + +- * HashAggregate (33) + +- * Project (32) + +- * Filter (31) + +- * BroadcastHashJoin ExistenceJoin(exists#1) BuildRight (30) + :- * Project (24) + : +- * BroadcastHashJoin Inner BuildRight (23) + : :- * Project (18) + : : +- * BroadcastHashJoin Inner BuildRight (17) + : : :- * Project (15) + : : : +- * BroadcastHashJoin Inner BuildRight (14) + : : : :- * Project (9) + : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) + : : : : : +- CometScan parquet spark_catalog.default.web_sales (1) + : : : : +- BroadcastExchange (7) + : : : : +- * ColumnarToRow (6) + : : : : +- CometFilter (5) + : : : : +- CometScan parquet spark_catalog.default.customer (4) + : : : +- BroadcastExchange (13) + : : : +- * ColumnarToRow (12) + : : : +- CometFilter (11) + : : : +- CometScan parquet spark_catalog.default.customer_address (10) + : : +- ReusedExchange (16) + : +- BroadcastExchange (22) + : +- * ColumnarToRow (21) + : +- CometFilter (20) + : +- CometScan parquet spark_catalog.default.item (19) + +- BroadcastExchange (29) + +- * ColumnarToRow (28) + +- CometProject (27) + +- CometFilter (26) + +- CometScan parquet spark_catalog.default.item (25) + + +(1) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_item_sk#2, ws_bill_customer_sk#3, ws_sales_price#4, ws_sold_date_sk#5] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#5), dynamicpruningexpression(ws_sold_date_sk#5 IN dynamicpruning#6)] +PushedFilters: [IsNotNull(ws_bill_customer_sk), IsNotNull(ws_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [4]: [ws_item_sk#2, ws_bill_customer_sk#3, ws_sales_price#4, ws_sold_date_sk#5] +Condition : (isnotnull(ws_bill_customer_sk#3) AND isnotnull(ws_item_sk#2)) + +(3) ColumnarToRow [codegen id : 6] +Input [4]: [ws_item_sk#2, ws_bill_customer_sk#3, ws_sales_price#4, ws_sold_date_sk#5] + +(4) Scan parquet spark_catalog.default.customer +Output [2]: [c_customer_sk#7, c_current_addr_sk#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_current_addr_sk)] +ReadSchema: struct + +(5) CometFilter +Input [2]: [c_customer_sk#7, c_current_addr_sk#8] +Condition : (isnotnull(c_customer_sk#7) AND isnotnull(c_current_addr_sk#8)) + +(6) ColumnarToRow [codegen id : 1] +Input [2]: [c_customer_sk#7, c_current_addr_sk#8] + +(7) BroadcastExchange +Input [2]: [c_customer_sk#7, c_current_addr_sk#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ws_bill_customer_sk#3] +Right keys [1]: [c_customer_sk#7] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 6] +Output [4]: [ws_item_sk#2, ws_sales_price#4, ws_sold_date_sk#5, c_current_addr_sk#8] +Input [6]: [ws_item_sk#2, ws_bill_customer_sk#3, ws_sales_price#4, ws_sold_date_sk#5, c_customer_sk#7, c_current_addr_sk#8] + +(10) Scan parquet spark_catalog.default.customer_address +Output [3]: [ca_address_sk#9, ca_city#10, ca_zip#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk)] +ReadSchema: struct + +(11) CometFilter +Input [3]: [ca_address_sk#9, ca_city#10, ca_zip#11] +Condition : isnotnull(ca_address_sk#9) + +(12) ColumnarToRow [codegen id : 2] +Input [3]: [ca_address_sk#9, ca_city#10, ca_zip#11] + +(13) BroadcastExchange +Input [3]: [ca_address_sk#9, ca_city#10, ca_zip#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(14) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [c_current_addr_sk#8] +Right keys [1]: [ca_address_sk#9] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 6] +Output [5]: [ws_item_sk#2, ws_sales_price#4, ws_sold_date_sk#5, ca_city#10, ca_zip#11] +Input [7]: [ws_item_sk#2, ws_sales_price#4, ws_sold_date_sk#5, c_current_addr_sk#8, ca_address_sk#9, ca_city#10, ca_zip#11] + +(16) ReusedExchange [Reuses operator id: 41] +Output [1]: [d_date_sk#12] + +(17) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ws_sold_date_sk#5] +Right keys [1]: [d_date_sk#12] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 6] +Output [4]: [ws_item_sk#2, ws_sales_price#4, ca_city#10, ca_zip#11] +Input [6]: [ws_item_sk#2, ws_sales_price#4, ws_sold_date_sk#5, ca_city#10, ca_zip#11, d_date_sk#12] + +(19) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#13, i_item_id#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(20) CometFilter +Input [2]: [i_item_sk#13, i_item_id#14] +Condition : isnotnull(i_item_sk#13) + +(21) ColumnarToRow [codegen id : 4] +Input [2]: [i_item_sk#13, i_item_id#14] + +(22) BroadcastExchange +Input [2]: [i_item_sk#13, i_item_id#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(23) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ws_item_sk#2] +Right keys [1]: [i_item_sk#13] +Join type: Inner +Join condition: None + +(24) Project [codegen id : 6] +Output [4]: [ws_sales_price#4, ca_city#10, ca_zip#11, i_item_id#14] +Input [6]: [ws_item_sk#2, ws_sales_price#4, ca_city#10, ca_zip#11, i_item_sk#13, i_item_id#14] + +(25) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#15, i_item_id#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [In(i_item_sk, [11,13,17,19,2,23,29,3,5,7])] +ReadSchema: struct + +(26) CometFilter +Input [2]: [i_item_sk#15, i_item_id#16] +Condition : i_item_sk#15 IN (2,3,5,7,11,13,17,19,23,29) + +(27) CometProject +Input [2]: [i_item_sk#15, i_item_id#16] +Arguments: [i_item_id#16], [i_item_id#16] + +(28) ColumnarToRow [codegen id : 5] +Input [1]: [i_item_id#16] + +(29) BroadcastExchange +Input [1]: [i_item_id#16] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=4] + +(30) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [i_item_id#14] +Right keys [1]: [i_item_id#16] +Join type: ExistenceJoin(exists#1) +Join condition: None + +(31) Filter [codegen id : 6] +Input [5]: [ws_sales_price#4, ca_city#10, ca_zip#11, i_item_id#14, exists#1] +Condition : (substr(ca_zip#11, 1, 5) IN (85669,86197,88274,83405,86475,85392,85460,80348,81792) OR exists#1) + +(32) Project [codegen id : 6] +Output [3]: [ws_sales_price#4, ca_city#10, ca_zip#11] +Input [5]: [ws_sales_price#4, ca_city#10, ca_zip#11, i_item_id#14, exists#1] + +(33) HashAggregate [codegen id : 6] +Input [3]: [ws_sales_price#4, ca_city#10, ca_zip#11] +Keys [2]: [ca_zip#11, ca_city#10] +Functions [1]: [partial_sum(UnscaledValue(ws_sales_price#4))] +Aggregate Attributes [1]: [sum#17] +Results [3]: [ca_zip#11, ca_city#10, sum#18] + +(34) Exchange +Input [3]: [ca_zip#11, ca_city#10, sum#18] +Arguments: hashpartitioning(ca_zip#11, ca_city#10, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(35) HashAggregate [codegen id : 7] +Input [3]: [ca_zip#11, ca_city#10, sum#18] +Keys [2]: [ca_zip#11, ca_city#10] +Functions [1]: [sum(UnscaledValue(ws_sales_price#4))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_sales_price#4))#19] +Results [3]: [ca_zip#11, ca_city#10, MakeDecimal(sum(UnscaledValue(ws_sales_price#4))#19,17,2) AS sum(ws_sales_price)#20] + +(36) TakeOrderedAndProject +Input [3]: [ca_zip#11, ca_city#10, sum(ws_sales_price)#20] +Arguments: 100, [ca_zip#11 ASC NULLS FIRST, ca_city#10 ASC NULLS FIRST], [ca_zip#11, ca_city#10, sum(ws_sales_price)#20] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#5 IN dynamicpruning#6 +BroadcastExchange (41) ++- * ColumnarToRow (40) + +- CometProject (39) + +- CometFilter (38) + +- CometScan parquet spark_catalog.default.date_dim (37) + + +(37) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#12, d_year#21, d_qoy#22] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_qoy), IsNotNull(d_year), EqualTo(d_qoy,2), EqualTo(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(38) CometFilter +Input [3]: [d_date_sk#12, d_year#21, d_qoy#22] +Condition : ((((isnotnull(d_qoy#22) AND isnotnull(d_year#21)) AND (d_qoy#22 = 2)) AND (d_year#21 = 2001)) AND isnotnull(d_date_sk#12)) + +(39) CometProject +Input [3]: [d_date_sk#12, d_year#21, d_qoy#22] +Arguments: [d_date_sk#12], [d_date_sk#12] + +(40) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#12] + +(41) BroadcastExchange +Input [1]: [d_date_sk#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q45/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q45/simplified.txt new file mode 100644 index 0000000000..383cbb7e3b --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q45/simplified.txt @@ -0,0 +1,61 @@ +TakeOrderedAndProject [ca_zip,ca_city,sum(ws_sales_price)] + WholeStageCodegen (7) + HashAggregate [ca_zip,ca_city,sum] [sum(UnscaledValue(ws_sales_price)),sum(ws_sales_price),sum] + InputAdapter + Exchange [ca_zip,ca_city] #1 + WholeStageCodegen (6) + HashAggregate [ca_zip,ca_city,ws_sales_price] [sum,sum] + Project [ws_sales_price,ca_city,ca_zip] + Filter [ca_zip,exists] + BroadcastHashJoin [i_item_id,i_item_id] + Project [ws_sales_price,ca_city,ca_zip,i_item_id] + BroadcastHashJoin [ws_item_sk,i_item_sk] + Project [ws_item_sk,ws_sales_price,ca_city,ca_zip] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_item_sk,ws_sales_price,ws_sold_date_sk,ca_city,ca_zip] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [ws_item_sk,ws_sales_price,ws_sold_date_sk,c_current_addr_sk] + BroadcastHashJoin [ws_bill_customer_sk,c_customer_sk] + ColumnarToRow + InputAdapter + CometFilter [ws_bill_customer_sk,ws_item_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_bill_customer_sk,ws_sales_price,ws_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_qoy,d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_qoy] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_current_addr_sk] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_addr_sk] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_city,ca_zip] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (4) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (5) + ColumnarToRow + InputAdapter + CometProject [i_item_id] + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q46/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q46/explain.txt new file mode 100644 index 0000000000..e07e2ab242 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q46/explain.txt @@ -0,0 +1,258 @@ +== Physical Plan == +TakeOrderedAndProject (39) ++- * Project (38) + +- * BroadcastHashJoin Inner BuildRight (37) + :- * Project (35) + : +- * BroadcastHashJoin Inner BuildRight (34) + : :- * HashAggregate (29) + : : +- Exchange (28) + : : +- * HashAggregate (27) + : : +- * Project (26) + : : +- * BroadcastHashJoin Inner BuildRight (25) + : : :- * Project (20) + : : : +- * BroadcastHashJoin Inner BuildRight (19) + : : : :- * Project (13) + : : : : +- * BroadcastHashJoin Inner BuildRight (12) + : : : : :- * Project (6) + : : : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : : : :- * ColumnarToRow (3) + : : : : : : +- CometFilter (2) + : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : : +- ReusedExchange (4) + : : : : +- BroadcastExchange (11) + : : : : +- * ColumnarToRow (10) + : : : : +- CometProject (9) + : : : : +- CometFilter (8) + : : : : +- CometScan parquet spark_catalog.default.store (7) + : : : +- BroadcastExchange (18) + : : : +- * ColumnarToRow (17) + : : : +- CometProject (16) + : : : +- CometFilter (15) + : : : +- CometScan parquet spark_catalog.default.household_demographics (14) + : : +- BroadcastExchange (24) + : : +- * ColumnarToRow (23) + : : +- CometFilter (22) + : : +- CometScan parquet spark_catalog.default.customer_address (21) + : +- BroadcastExchange (33) + : +- * ColumnarToRow (32) + : +- CometFilter (31) + : +- CometScan parquet spark_catalog.default.customer (30) + +- ReusedExchange (36) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [8]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, ss_sold_date_sk#8] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#8), dynamicpruningexpression(ss_sold_date_sk#8 IN dynamicpruning#9)] +PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_hdemo_sk), IsNotNull(ss_addr_sk), IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(2) CometFilter +Input [8]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, ss_sold_date_sk#8] +Condition : (((isnotnull(ss_store_sk#4) AND isnotnull(ss_hdemo_sk#2)) AND isnotnull(ss_addr_sk#3)) AND isnotnull(ss_customer_sk#1)) + +(3) ColumnarToRow [codegen id : 5] +Input [8]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, ss_sold_date_sk#8] + +(4) ReusedExchange [Reuses operator id: 44] +Output [1]: [d_date_sk#10] + +(5) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_sold_date_sk#8] +Right keys [1]: [d_date_sk#10] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 5] +Output [7]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7] +Input [9]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, ss_sold_date_sk#8, d_date_sk#10] + +(7) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#11, s_city#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [In(s_city, [Fairview,Midway]), IsNotNull(s_store_sk)] +ReadSchema: struct + +(8) CometFilter +Input [2]: [s_store_sk#11, s_city#12] +Condition : (s_city#12 IN (Fairview,Midway) AND isnotnull(s_store_sk#11)) + +(9) CometProject +Input [2]: [s_store_sk#11, s_city#12] +Arguments: [s_store_sk#11], [s_store_sk#11] + +(10) ColumnarToRow [codegen id : 2] +Input [1]: [s_store_sk#11] + +(11) BroadcastExchange +Input [1]: [s_store_sk#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(12) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_store_sk#4] +Right keys [1]: [s_store_sk#11] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 5] +Output [6]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7] +Input [8]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, s_store_sk#11] + +(14) Scan parquet spark_catalog.default.household_demographics +Output [3]: [hd_demo_sk#13, hd_dep_count#14, hd_vehicle_count#15] +Batched: true +Location [not included in comparison]/{warehouse_dir}/household_demographics] +PushedFilters: [Or(EqualTo(hd_dep_count,4),EqualTo(hd_vehicle_count,3)), IsNotNull(hd_demo_sk)] +ReadSchema: struct + +(15) CometFilter +Input [3]: [hd_demo_sk#13, hd_dep_count#14, hd_vehicle_count#15] +Condition : (((hd_dep_count#14 = 4) OR (hd_vehicle_count#15 = 3)) AND isnotnull(hd_demo_sk#13)) + +(16) CometProject +Input [3]: [hd_demo_sk#13, hd_dep_count#14, hd_vehicle_count#15] +Arguments: [hd_demo_sk#13], [hd_demo_sk#13] + +(17) ColumnarToRow [codegen id : 3] +Input [1]: [hd_demo_sk#13] + +(18) BroadcastExchange +Input [1]: [hd_demo_sk#13] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(19) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_hdemo_sk#2] +Right keys [1]: [hd_demo_sk#13] +Join type: Inner +Join condition: None + +(20) Project [codegen id : 5] +Output [5]: [ss_customer_sk#1, ss_addr_sk#3, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7] +Input [7]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, hd_demo_sk#13] + +(21) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#16, ca_city#17] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk), IsNotNull(ca_city)] +ReadSchema: struct + +(22) CometFilter +Input [2]: [ca_address_sk#16, ca_city#17] +Condition : (isnotnull(ca_address_sk#16) AND isnotnull(ca_city#17)) + +(23) ColumnarToRow [codegen id : 4] +Input [2]: [ca_address_sk#16, ca_city#17] + +(24) BroadcastExchange +Input [2]: [ca_address_sk#16, ca_city#17] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(25) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_addr_sk#3] +Right keys [1]: [ca_address_sk#16] +Join type: Inner +Join condition: None + +(26) Project [codegen id : 5] +Output [6]: [ss_customer_sk#1, ss_addr_sk#3, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, ca_city#17] +Input [7]: [ss_customer_sk#1, ss_addr_sk#3, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, ca_address_sk#16, ca_city#17] + +(27) HashAggregate [codegen id : 5] +Input [6]: [ss_customer_sk#1, ss_addr_sk#3, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, ca_city#17] +Keys [4]: [ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, ca_city#17] +Functions [2]: [partial_sum(UnscaledValue(ss_coupon_amt#6)), partial_sum(UnscaledValue(ss_net_profit#7))] +Aggregate Attributes [2]: [sum#18, sum#19] +Results [6]: [ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, ca_city#17, sum#20, sum#21] + +(28) Exchange +Input [6]: [ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, ca_city#17, sum#20, sum#21] +Arguments: hashpartitioning(ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, ca_city#17, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(29) HashAggregate [codegen id : 8] +Input [6]: [ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, ca_city#17, sum#20, sum#21] +Keys [4]: [ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, ca_city#17] +Functions [2]: [sum(UnscaledValue(ss_coupon_amt#6)), sum(UnscaledValue(ss_net_profit#7))] +Aggregate Attributes [2]: [sum(UnscaledValue(ss_coupon_amt#6))#22, sum(UnscaledValue(ss_net_profit#7))#23] +Results [5]: [ss_ticket_number#5, ss_customer_sk#1, ca_city#17 AS bought_city#24, MakeDecimal(sum(UnscaledValue(ss_coupon_amt#6))#22,17,2) AS amt#25, MakeDecimal(sum(UnscaledValue(ss_net_profit#7))#23,17,2) AS profit#26] + +(30) Scan parquet spark_catalog.default.customer +Output [4]: [c_customer_sk#27, c_current_addr_sk#28, c_first_name#29, c_last_name#30] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_current_addr_sk)] +ReadSchema: struct + +(31) CometFilter +Input [4]: [c_customer_sk#27, c_current_addr_sk#28, c_first_name#29, c_last_name#30] +Condition : (isnotnull(c_customer_sk#27) AND isnotnull(c_current_addr_sk#28)) + +(32) ColumnarToRow [codegen id : 6] +Input [4]: [c_customer_sk#27, c_current_addr_sk#28, c_first_name#29, c_last_name#30] + +(33) BroadcastExchange +Input [4]: [c_customer_sk#27, c_current_addr_sk#28, c_first_name#29, c_last_name#30] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(34) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_customer_sk#1] +Right keys [1]: [c_customer_sk#27] +Join type: Inner +Join condition: None + +(35) Project [codegen id : 8] +Output [7]: [ss_ticket_number#5, bought_city#24, amt#25, profit#26, c_current_addr_sk#28, c_first_name#29, c_last_name#30] +Input [9]: [ss_ticket_number#5, ss_customer_sk#1, bought_city#24, amt#25, profit#26, c_customer_sk#27, c_current_addr_sk#28, c_first_name#29, c_last_name#30] + +(36) ReusedExchange [Reuses operator id: 24] +Output [2]: [ca_address_sk#31, ca_city#32] + +(37) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [c_current_addr_sk#28] +Right keys [1]: [ca_address_sk#31] +Join type: Inner +Join condition: NOT (ca_city#32 = bought_city#24) + +(38) Project [codegen id : 8] +Output [7]: [c_last_name#30, c_first_name#29, ca_city#32, bought_city#24, ss_ticket_number#5, amt#25, profit#26] +Input [9]: [ss_ticket_number#5, bought_city#24, amt#25, profit#26, c_current_addr_sk#28, c_first_name#29, c_last_name#30, ca_address_sk#31, ca_city#32] + +(39) TakeOrderedAndProject +Input [7]: [c_last_name#30, c_first_name#29, ca_city#32, bought_city#24, ss_ticket_number#5, amt#25, profit#26] +Arguments: 100, [c_last_name#30 ASC NULLS FIRST, c_first_name#29 ASC NULLS FIRST, ca_city#32 ASC NULLS FIRST, bought_city#24 ASC NULLS FIRST, ss_ticket_number#5 ASC NULLS FIRST], [c_last_name#30, c_first_name#29, ca_city#32, bought_city#24, ss_ticket_number#5, amt#25, profit#26] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#8 IN dynamicpruning#9 +BroadcastExchange (44) ++- * ColumnarToRow (43) + +- CometProject (42) + +- CometFilter (41) + +- CometScan parquet spark_catalog.default.date_dim (40) + + +(40) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#10, d_year#33, d_dow#34] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [In(d_dow, [0,6]), In(d_year, [1999,2000,2001]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(41) CometFilter +Input [3]: [d_date_sk#10, d_year#33, d_dow#34] +Condition : ((d_dow#34 IN (6,0) AND d_year#33 IN (1999,2000,2001)) AND isnotnull(d_date_sk#10)) + +(42) CometProject +Input [3]: [d_date_sk#10, d_year#33, d_dow#34] +Arguments: [d_date_sk#10], [d_date_sk#10] + +(43) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#10] + +(44) BroadcastExchange +Input [1]: [d_date_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q46/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q46/simplified.txt new file mode 100644 index 0000000000..04c59a2d35 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q46/simplified.txt @@ -0,0 +1,65 @@ +TakeOrderedAndProject [c_last_name,c_first_name,ca_city,bought_city,ss_ticket_number,amt,profit] + WholeStageCodegen (8) + Project [c_last_name,c_first_name,ca_city,bought_city,ss_ticket_number,amt,profit] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk,ca_city,bought_city] + Project [ss_ticket_number,bought_city,amt,profit,c_current_addr_sk,c_first_name,c_last_name] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + HashAggregate [ss_ticket_number,ss_customer_sk,ss_addr_sk,ca_city,sum,sum] [sum(UnscaledValue(ss_coupon_amt)),sum(UnscaledValue(ss_net_profit)),bought_city,amt,profit,sum,sum] + InputAdapter + Exchange [ss_ticket_number,ss_customer_sk,ss_addr_sk,ca_city] #1 + WholeStageCodegen (5) + HashAggregate [ss_ticket_number,ss_customer_sk,ss_addr_sk,ca_city,ss_coupon_amt,ss_net_profit] [sum,sum,sum,sum] + Project [ss_customer_sk,ss_addr_sk,ss_ticket_number,ss_coupon_amt,ss_net_profit,ca_city] + BroadcastHashJoin [ss_addr_sk,ca_address_sk] + Project [ss_customer_sk,ss_addr_sk,ss_ticket_number,ss_coupon_amt,ss_net_profit] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + Project [ss_customer_sk,ss_hdemo_sk,ss_addr_sk,ss_ticket_number,ss_coupon_amt,ss_net_profit] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_customer_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_ticket_number,ss_coupon_amt,ss_net_profit] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk,ss_hdemo_sk,ss_addr_sk,ss_customer_sk] + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_ticket_number,ss_coupon_amt,ss_net_profit,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_dow,d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_dow] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometProject [s_store_sk] + CometFilter [s_city,s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk,s_city] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometProject [hd_demo_sk] + CometFilter [hd_dep_count,hd_vehicle_count,hd_demo_sk] + CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_dep_count,hd_vehicle_count] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (4) + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk,ca_city] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_city] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (6) + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_current_addr_sk] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_addr_sk,c_first_name,c_last_name] + InputAdapter + ReusedExchange [ca_address_sk,ca_city] #5 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q47/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q47/explain.txt new file mode 100644 index 0000000000..fca7362ce8 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q47/explain.txt @@ -0,0 +1,279 @@ +== Physical Plan == +TakeOrderedAndProject (45) ++- * Project (44) + +- * BroadcastHashJoin Inner BuildRight (43) + :- * Project (37) + : +- * BroadcastHashJoin Inner BuildRight (36) + : :- * Project (28) + : : +- * Filter (27) + : : +- Window (26) + : : +- * Filter (25) + : : +- Window (24) + : : +- * Sort (23) + : : +- Exchange (22) + : : +- * HashAggregate (21) + : : +- Exchange (20) + : : +- * HashAggregate (19) + : : +- * Project (18) + : : +- * BroadcastHashJoin Inner BuildRight (17) + : : :- * Project (12) + : : : +- * BroadcastHashJoin Inner BuildRight (11) + : : : :- * Project (9) + : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) + : : : : : +- CometScan parquet spark_catalog.default.item (1) + : : : : +- BroadcastExchange (7) + : : : : +- * ColumnarToRow (6) + : : : : +- CometFilter (5) + : : : : +- CometScan parquet spark_catalog.default.store_sales (4) + : : : +- ReusedExchange (10) + : : +- BroadcastExchange (16) + : : +- * ColumnarToRow (15) + : : +- CometFilter (14) + : : +- CometScan parquet spark_catalog.default.store (13) + : +- BroadcastExchange (35) + : +- * Project (34) + : +- Window (33) + : +- * Sort (32) + : +- Exchange (31) + : +- * HashAggregate (30) + : +- ReusedExchange (29) + +- BroadcastExchange (42) + +- * Project (41) + +- Window (40) + +- * Sort (39) + +- ReusedExchange (38) + + +(1) Scan parquet spark_catalog.default.item +Output [3]: [i_item_sk#1, i_brand#2, i_category#3] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_category), IsNotNull(i_brand)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [i_item_sk#1, i_brand#2, i_category#3] +Condition : ((isnotnull(i_item_sk#1) AND isnotnull(i_category#3)) AND isnotnull(i_brand#2)) + +(3) ColumnarToRow [codegen id : 4] +Input [3]: [i_item_sk#1, i_brand#2, i_category#3] + +(4) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#4, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sold_date_sk#7 IN dynamicpruning#8)] +PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(5) CometFilter +Input [4]: [ss_item_sk#4, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7] +Condition : (isnotnull(ss_item_sk#4) AND isnotnull(ss_store_sk#5)) + +(6) ColumnarToRow [codegen id : 1] +Input [4]: [ss_item_sk#4, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7] + +(7) BroadcastExchange +Input [4]: [ss_item_sk#4, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [i_item_sk#1] +Right keys [1]: [ss_item_sk#4] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 4] +Output [5]: [i_brand#2, i_category#3, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7] +Input [7]: [i_item_sk#1, i_brand#2, i_category#3, ss_item_sk#4, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7] + +(10) ReusedExchange [Reuses operator id: 49] +Output [3]: [d_date_sk#9, d_year#10, d_moy#11] + +(11) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_date_sk#7] +Right keys [1]: [d_date_sk#9] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 4] +Output [6]: [i_brand#2, i_category#3, ss_store_sk#5, ss_sales_price#6, d_year#10, d_moy#11] +Input [8]: [i_brand#2, i_category#3, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7, d_date_sk#9, d_year#10, d_moy#11] + +(13) Scan parquet spark_catalog.default.store +Output [3]: [s_store_sk#12, s_store_name#13, s_company_name#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk), IsNotNull(s_store_name), IsNotNull(s_company_name)] +ReadSchema: struct + +(14) CometFilter +Input [3]: [s_store_sk#12, s_store_name#13, s_company_name#14] +Condition : ((isnotnull(s_store_sk#12) AND isnotnull(s_store_name#13)) AND isnotnull(s_company_name#14)) + +(15) ColumnarToRow [codegen id : 3] +Input [3]: [s_store_sk#12, s_store_name#13, s_company_name#14] + +(16) BroadcastExchange +Input [3]: [s_store_sk#12, s_store_name#13, s_company_name#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(17) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_store_sk#5] +Right keys [1]: [s_store_sk#12] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 4] +Output [7]: [i_brand#2, i_category#3, ss_sales_price#6, d_year#10, d_moy#11, s_store_name#13, s_company_name#14] +Input [9]: [i_brand#2, i_category#3, ss_store_sk#5, ss_sales_price#6, d_year#10, d_moy#11, s_store_sk#12, s_store_name#13, s_company_name#14] + +(19) HashAggregate [codegen id : 4] +Input [7]: [i_brand#2, i_category#3, ss_sales_price#6, d_year#10, d_moy#11, s_store_name#13, s_company_name#14] +Keys [6]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11] +Functions [1]: [partial_sum(UnscaledValue(ss_sales_price#6))] +Aggregate Attributes [1]: [sum#15] +Results [7]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum#16] + +(20) Exchange +Input [7]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum#16] +Arguments: hashpartitioning(i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(21) HashAggregate [codegen id : 5] +Input [7]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum#16] +Keys [6]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11] +Functions [1]: [sum(UnscaledValue(ss_sales_price#6))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_sales_price#6))#17] +Results [8]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, MakeDecimal(sum(UnscaledValue(ss_sales_price#6))#17,17,2) AS sum_sales#18, MakeDecimal(sum(UnscaledValue(ss_sales_price#6))#17,17,2) AS _w0#19] + +(22) Exchange +Input [8]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, _w0#19] +Arguments: hashpartitioning(i_category#3, i_brand#2, s_store_name#13, s_company_name#14, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(23) Sort [codegen id : 6] +Input [8]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, _w0#19] +Arguments: [i_category#3 ASC NULLS FIRST, i_brand#2 ASC NULLS FIRST, s_store_name#13 ASC NULLS FIRST, s_company_name#14 ASC NULLS FIRST, d_year#10 ASC NULLS FIRST, d_moy#11 ASC NULLS FIRST], false, 0 + +(24) Window +Input [8]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, _w0#19] +Arguments: [rank(d_year#10, d_moy#11) windowspecdefinition(i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10 ASC NULLS FIRST, d_moy#11 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rn#20], [i_category#3, i_brand#2, s_store_name#13, s_company_name#14], [d_year#10 ASC NULLS FIRST, d_moy#11 ASC NULLS FIRST] + +(25) Filter [codegen id : 7] +Input [9]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, _w0#19, rn#20] +Condition : (isnotnull(d_year#10) AND (d_year#10 = 1999)) + +(26) Window +Input [9]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, _w0#19, rn#20] +Arguments: [avg(_w0#19) windowspecdefinition(i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, specifiedwindowframe(RowFrame, unboundedpreceding$(), unboundedfollowing$())) AS avg_monthly_sales#21], [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10] + +(27) Filter [codegen id : 22] +Input [10]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, _w0#19, rn#20, avg_monthly_sales#21] +Condition : ((isnotnull(avg_monthly_sales#21) AND (avg_monthly_sales#21 > 0.000000)) AND CASE WHEN (avg_monthly_sales#21 > 0.000000) THEN ((abs((sum_sales#18 - avg_monthly_sales#21)) / avg_monthly_sales#21) > 0.1000000000000000) END) + +(28) Project [codegen id : 22] +Output [9]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, avg_monthly_sales#21, rn#20] +Input [10]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, _w0#19, rn#20, avg_monthly_sales#21] + +(29) ReusedExchange [Reuses operator id: 20] +Output [7]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26, d_moy#27, sum#28] + +(30) HashAggregate [codegen id : 12] +Input [7]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26, d_moy#27, sum#28] +Keys [6]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26, d_moy#27] +Functions [1]: [sum(UnscaledValue(ss_sales_price#29))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_sales_price#29))#17] +Results [7]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26, d_moy#27, MakeDecimal(sum(UnscaledValue(ss_sales_price#29))#17,17,2) AS sum_sales#30] + +(31) Exchange +Input [7]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26, d_moy#27, sum_sales#30] +Arguments: hashpartitioning(i_category#22, i_brand#23, s_store_name#24, s_company_name#25, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(32) Sort [codegen id : 13] +Input [7]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26, d_moy#27, sum_sales#30] +Arguments: [i_category#22 ASC NULLS FIRST, i_brand#23 ASC NULLS FIRST, s_store_name#24 ASC NULLS FIRST, s_company_name#25 ASC NULLS FIRST, d_year#26 ASC NULLS FIRST, d_moy#27 ASC NULLS FIRST], false, 0 + +(33) Window +Input [7]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26, d_moy#27, sum_sales#30] +Arguments: [rank(d_year#26, d_moy#27) windowspecdefinition(i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26 ASC NULLS FIRST, d_moy#27 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rn#31], [i_category#22, i_brand#23, s_store_name#24, s_company_name#25], [d_year#26 ASC NULLS FIRST, d_moy#27 ASC NULLS FIRST] + +(34) Project [codegen id : 14] +Output [6]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, sum_sales#30, rn#31] +Input [8]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26, d_moy#27, sum_sales#30, rn#31] + +(35) BroadcastExchange +Input [6]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, sum_sales#30, rn#31] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true], input[1, string, true], input[2, string, true], input[3, string, true], (input[5, int, false] + 1)),false), [plan_id=6] + +(36) BroadcastHashJoin [codegen id : 22] +Left keys [5]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, rn#20] +Right keys [5]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, (rn#31 + 1)] +Join type: Inner +Join condition: None + +(37) Project [codegen id : 22] +Output [10]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, avg_monthly_sales#21, rn#20, sum_sales#30] +Input [15]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, avg_monthly_sales#21, rn#20, i_category#22, i_brand#23, s_store_name#24, s_company_name#25, sum_sales#30, rn#31] + +(38) ReusedExchange [Reuses operator id: 31] +Output [7]: [i_category#32, i_brand#33, s_store_name#34, s_company_name#35, d_year#36, d_moy#37, sum_sales#38] + +(39) Sort [codegen id : 20] +Input [7]: [i_category#32, i_brand#33, s_store_name#34, s_company_name#35, d_year#36, d_moy#37, sum_sales#38] +Arguments: [i_category#32 ASC NULLS FIRST, i_brand#33 ASC NULLS FIRST, s_store_name#34 ASC NULLS FIRST, s_company_name#35 ASC NULLS FIRST, d_year#36 ASC NULLS FIRST, d_moy#37 ASC NULLS FIRST], false, 0 + +(40) Window +Input [7]: [i_category#32, i_brand#33, s_store_name#34, s_company_name#35, d_year#36, d_moy#37, sum_sales#38] +Arguments: [rank(d_year#36, d_moy#37) windowspecdefinition(i_category#32, i_brand#33, s_store_name#34, s_company_name#35, d_year#36 ASC NULLS FIRST, d_moy#37 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rn#39], [i_category#32, i_brand#33, s_store_name#34, s_company_name#35], [d_year#36 ASC NULLS FIRST, d_moy#37 ASC NULLS FIRST] + +(41) Project [codegen id : 21] +Output [6]: [i_category#32, i_brand#33, s_store_name#34, s_company_name#35, sum_sales#38, rn#39] +Input [8]: [i_category#32, i_brand#33, s_store_name#34, s_company_name#35, d_year#36, d_moy#37, sum_sales#38, rn#39] + +(42) BroadcastExchange +Input [6]: [i_category#32, i_brand#33, s_store_name#34, s_company_name#35, sum_sales#38, rn#39] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true], input[1, string, true], input[2, string, true], input[3, string, true], (input[5, int, false] - 1)),false), [plan_id=7] + +(43) BroadcastHashJoin [codegen id : 22] +Left keys [5]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, rn#20] +Right keys [5]: [i_category#32, i_brand#33, s_store_name#34, s_company_name#35, (rn#39 - 1)] +Join type: Inner +Join condition: None + +(44) Project [codegen id : 22] +Output [10]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, avg_monthly_sales#21, sum_sales#18, sum_sales#30 AS psum#40, sum_sales#38 AS nsum#41] +Input [16]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, avg_monthly_sales#21, rn#20, sum_sales#30, i_category#32, i_brand#33, s_store_name#34, s_company_name#35, sum_sales#38, rn#39] + +(45) TakeOrderedAndProject +Input [10]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, avg_monthly_sales#21, sum_sales#18, psum#40, nsum#41] +Arguments: 100, [(sum_sales#18 - avg_monthly_sales#21) ASC NULLS FIRST, s_store_name#13 ASC NULLS FIRST], [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, avg_monthly_sales#21, sum_sales#18, psum#40, nsum#41] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (49) ++- * ColumnarToRow (48) + +- CometFilter (47) + +- CometScan parquet spark_catalog.default.date_dim (46) + + +(46) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#9, d_year#10, d_moy#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [Or(Or(EqualTo(d_year,1999),And(EqualTo(d_year,1998),EqualTo(d_moy,12))),And(EqualTo(d_year,2000),EqualTo(d_moy,1))), IsNotNull(d_date_sk)] +ReadSchema: struct + +(47) CometFilter +Input [3]: [d_date_sk#9, d_year#10, d_moy#11] +Condition : ((((d_year#10 = 1999) OR ((d_year#10 = 1998) AND (d_moy#11 = 12))) OR ((d_year#10 = 2000) AND (d_moy#11 = 1))) AND isnotnull(d_date_sk#9)) + +(48) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#9, d_year#10, d_moy#11] + +(49) BroadcastExchange +Input [3]: [d_date_sk#9, d_year#10, d_moy#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q47/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q47/simplified.txt new file mode 100644 index 0000000000..80b8da7b14 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q47/simplified.txt @@ -0,0 +1,81 @@ +TakeOrderedAndProject [sum_sales,avg_monthly_sales,s_store_name,i_category,i_brand,s_company_name,d_year,d_moy,psum,nsum] + WholeStageCodegen (22) + Project [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy,avg_monthly_sales,sum_sales,sum_sales,sum_sales] + BroadcastHashJoin [i_category,i_brand,s_store_name,s_company_name,rn,i_category,i_brand,s_store_name,s_company_name,rn] + Project [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy,sum_sales,avg_monthly_sales,rn,sum_sales] + BroadcastHashJoin [i_category,i_brand,s_store_name,s_company_name,rn,i_category,i_brand,s_store_name,s_company_name,rn] + Project [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy,sum_sales,avg_monthly_sales,rn] + Filter [avg_monthly_sales,sum_sales] + InputAdapter + Window [_w0,i_category,i_brand,s_store_name,s_company_name,d_year] + WholeStageCodegen (7) + Filter [d_year] + InputAdapter + Window [d_year,d_moy,i_category,i_brand,s_store_name,s_company_name] + WholeStageCodegen (6) + Sort [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy] + InputAdapter + Exchange [i_category,i_brand,s_store_name,s_company_name] #1 + WholeStageCodegen (5) + HashAggregate [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy,sum] [sum(UnscaledValue(ss_sales_price)),sum_sales,_w0,sum] + InputAdapter + Exchange [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy] #2 + WholeStageCodegen (4) + HashAggregate [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy,ss_sales_price] [sum,sum] + Project [i_brand,i_category,ss_sales_price,d_year,d_moy,s_store_name,s_company_name] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [i_brand,i_category,ss_store_sk,ss_sales_price,d_year,d_moy] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [i_brand,i_category,ss_store_sk,ss_sales_price,ss_sold_date_sk] + BroadcastHashJoin [i_item_sk,ss_item_sk] + ColumnarToRow + InputAdapter + CometFilter [i_item_sk,i_category,i_brand] + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_category] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk,ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_year,d_moy,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + ReusedExchange [d_date_sk,d_year,d_moy] #4 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometFilter [s_store_sk,s_store_name,s_company_name] + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name,s_company_name] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (14) + Project [i_category,i_brand,s_store_name,s_company_name,sum_sales,rn] + InputAdapter + Window [d_year,d_moy,i_category,i_brand,s_store_name,s_company_name] + WholeStageCodegen (13) + Sort [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy] + InputAdapter + Exchange [i_category,i_brand,s_store_name,s_company_name] #7 + WholeStageCodegen (12) + HashAggregate [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy,sum] [sum(UnscaledValue(ss_sales_price)),sum_sales,sum] + InputAdapter + ReusedExchange [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy,sum] #2 + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (21) + Project [i_category,i_brand,s_store_name,s_company_name,sum_sales,rn] + InputAdapter + Window [d_year,d_moy,i_category,i_brand,s_store_name,s_company_name] + WholeStageCodegen (20) + Sort [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy] + InputAdapter + ReusedExchange [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy,sum_sales] #7 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q48/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q48/explain.txt new file mode 100644 index 0000000000..718f3fb317 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q48/explain.txt @@ -0,0 +1,198 @@ +== Physical Plan == +* HashAggregate (28) ++- Exchange (27) + +- * HashAggregate (26) + +- * Project (25) + +- * BroadcastHashJoin Inner BuildRight (24) + :- * Project (22) + : +- * BroadcastHashJoin Inner BuildRight (21) + : :- * Project (15) + : : +- * BroadcastHashJoin Inner BuildRight (14) + : : :- * Project (9) + : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- BroadcastExchange (7) + : : : +- * ColumnarToRow (6) + : : : +- CometFilter (5) + : : : +- CometScan parquet spark_catalog.default.store (4) + : : +- BroadcastExchange (13) + : : +- * ColumnarToRow (12) + : : +- CometFilter (11) + : : +- CometScan parquet spark_catalog.default.customer_demographics (10) + : +- BroadcastExchange (20) + : +- * ColumnarToRow (19) + : +- CometProject (18) + : +- CometFilter (17) + : +- CometScan parquet spark_catalog.default.customer_address (16) + +- ReusedExchange (23) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [7]: [ss_cdemo_sk#1, ss_addr_sk#2, ss_store_sk#3, ss_quantity#4, ss_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sold_date_sk#7 IN dynamicpruning#8)] +PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_cdemo_sk), IsNotNull(ss_addr_sk), Or(Or(And(GreaterThanOrEqual(ss_sales_price,100.00),LessThanOrEqual(ss_sales_price,150.00)),And(GreaterThanOrEqual(ss_sales_price,50.00),LessThanOrEqual(ss_sales_price,100.00))),And(GreaterThanOrEqual(ss_sales_price,150.00),LessThanOrEqual(ss_sales_price,200.00))), Or(Or(And(GreaterThanOrEqual(ss_net_profit,0.00),LessThanOrEqual(ss_net_profit,2000.00)),And(GreaterThanOrEqual(ss_net_profit,150.00),LessThanOrEqual(ss_net_profit,3000.00))),And(GreaterThanOrEqual(ss_net_profit,50.00),LessThanOrEqual(ss_net_profit,25000.00)))] +ReadSchema: struct + +(2) CometFilter +Input [7]: [ss_cdemo_sk#1, ss_addr_sk#2, ss_store_sk#3, ss_quantity#4, ss_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] +Condition : ((((isnotnull(ss_store_sk#3) AND isnotnull(ss_cdemo_sk#1)) AND isnotnull(ss_addr_sk#2)) AND ((((ss_sales_price#5 >= 100.00) AND (ss_sales_price#5 <= 150.00)) OR ((ss_sales_price#5 >= 50.00) AND (ss_sales_price#5 <= 100.00))) OR ((ss_sales_price#5 >= 150.00) AND (ss_sales_price#5 <= 200.00)))) AND ((((ss_net_profit#6 >= 0.00) AND (ss_net_profit#6 <= 2000.00)) OR ((ss_net_profit#6 >= 150.00) AND (ss_net_profit#6 <= 3000.00))) OR ((ss_net_profit#6 >= 50.00) AND (ss_net_profit#6 <= 25000.00)))) + +(3) ColumnarToRow [codegen id : 5] +Input [7]: [ss_cdemo_sk#1, ss_addr_sk#2, ss_store_sk#3, ss_quantity#4, ss_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] + +(4) Scan parquet spark_catalog.default.store +Output [1]: [s_store_sk#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(5) CometFilter +Input [1]: [s_store_sk#9] +Condition : isnotnull(s_store_sk#9) + +(6) ColumnarToRow [codegen id : 1] +Input [1]: [s_store_sk#9] + +(7) BroadcastExchange +Input [1]: [s_store_sk#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_store_sk#3] +Right keys [1]: [s_store_sk#9] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 5] +Output [6]: [ss_cdemo_sk#1, ss_addr_sk#2, ss_quantity#4, ss_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] +Input [8]: [ss_cdemo_sk#1, ss_addr_sk#2, ss_store_sk#3, ss_quantity#4, ss_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7, s_store_sk#9] + +(10) Scan parquet spark_catalog.default.customer_demographics +Output [3]: [cd_demo_sk#10, cd_marital_status#11, cd_education_status#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_demo_sk), Or(Or(And(EqualTo(cd_marital_status,M),EqualTo(cd_education_status,4 yr Degree )),And(EqualTo(cd_marital_status,D),EqualTo(cd_education_status,2 yr Degree ))),And(EqualTo(cd_marital_status,S),EqualTo(cd_education_status,College )))] +ReadSchema: struct + +(11) CometFilter +Input [3]: [cd_demo_sk#10, cd_marital_status#11, cd_education_status#12] +Condition : (isnotnull(cd_demo_sk#10) AND ((((cd_marital_status#11 = M) AND (cd_education_status#12 = 4 yr Degree )) OR ((cd_marital_status#11 = D) AND (cd_education_status#12 = 2 yr Degree ))) OR ((cd_marital_status#11 = S) AND (cd_education_status#12 = College )))) + +(12) ColumnarToRow [codegen id : 2] +Input [3]: [cd_demo_sk#10, cd_marital_status#11, cd_education_status#12] + +(13) BroadcastExchange +Input [3]: [cd_demo_sk#10, cd_marital_status#11, cd_education_status#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(14) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_cdemo_sk#1] +Right keys [1]: [cd_demo_sk#10] +Join type: Inner +Join condition: ((((((cd_marital_status#11 = M) AND (cd_education_status#12 = 4 yr Degree )) AND (ss_sales_price#5 >= 100.00)) AND (ss_sales_price#5 <= 150.00)) OR ((((cd_marital_status#11 = D) AND (cd_education_status#12 = 2 yr Degree )) AND (ss_sales_price#5 >= 50.00)) AND (ss_sales_price#5 <= 100.00))) OR ((((cd_marital_status#11 = S) AND (cd_education_status#12 = College )) AND (ss_sales_price#5 >= 150.00)) AND (ss_sales_price#5 <= 200.00))) + +(15) Project [codegen id : 5] +Output [4]: [ss_addr_sk#2, ss_quantity#4, ss_net_profit#6, ss_sold_date_sk#7] +Input [9]: [ss_cdemo_sk#1, ss_addr_sk#2, ss_quantity#4, ss_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7, cd_demo_sk#10, cd_marital_status#11, cd_education_status#12] + +(16) Scan parquet spark_catalog.default.customer_address +Output [3]: [ca_address_sk#13, ca_state#14, ca_country#15] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_country), EqualTo(ca_country,United States), IsNotNull(ca_address_sk), Or(Or(In(ca_state, [CO,OH,TX]),In(ca_state, [KY,MN,OR])),In(ca_state, [CA,MS,VA]))] +ReadSchema: struct + +(17) CometFilter +Input [3]: [ca_address_sk#13, ca_state#14, ca_country#15] +Condition : (((isnotnull(ca_country#15) AND (ca_country#15 = United States)) AND isnotnull(ca_address_sk#13)) AND ((ca_state#14 IN (CO,OH,TX) OR ca_state#14 IN (OR,MN,KY)) OR ca_state#14 IN (VA,CA,MS))) + +(18) CometProject +Input [3]: [ca_address_sk#13, ca_state#14, ca_country#15] +Arguments: [ca_address_sk#13, ca_state#14], [ca_address_sk#13, ca_state#14] + +(19) ColumnarToRow [codegen id : 3] +Input [2]: [ca_address_sk#13, ca_state#14] + +(20) BroadcastExchange +Input [2]: [ca_address_sk#13, ca_state#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(21) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_addr_sk#2] +Right keys [1]: [ca_address_sk#13] +Join type: Inner +Join condition: ((((ca_state#14 IN (CO,OH,TX) AND (ss_net_profit#6 >= 0.00)) AND (ss_net_profit#6 <= 2000.00)) OR ((ca_state#14 IN (OR,MN,KY) AND (ss_net_profit#6 >= 150.00)) AND (ss_net_profit#6 <= 3000.00))) OR ((ca_state#14 IN (VA,CA,MS) AND (ss_net_profit#6 >= 50.00)) AND (ss_net_profit#6 <= 25000.00))) + +(22) Project [codegen id : 5] +Output [2]: [ss_quantity#4, ss_sold_date_sk#7] +Input [6]: [ss_addr_sk#2, ss_quantity#4, ss_net_profit#6, ss_sold_date_sk#7, ca_address_sk#13, ca_state#14] + +(23) ReusedExchange [Reuses operator id: 33] +Output [1]: [d_date_sk#16] + +(24) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_sold_date_sk#7] +Right keys [1]: [d_date_sk#16] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 5] +Output [1]: [ss_quantity#4] +Input [3]: [ss_quantity#4, ss_sold_date_sk#7, d_date_sk#16] + +(26) HashAggregate [codegen id : 5] +Input [1]: [ss_quantity#4] +Keys: [] +Functions [1]: [partial_sum(ss_quantity#4)] +Aggregate Attributes [1]: [sum#17] +Results [1]: [sum#18] + +(27) Exchange +Input [1]: [sum#18] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=4] + +(28) HashAggregate [codegen id : 6] +Input [1]: [sum#18] +Keys: [] +Functions [1]: [sum(ss_quantity#4)] +Aggregate Attributes [1]: [sum(ss_quantity#4)#19] +Results [1]: [sum(ss_quantity#4)#19 AS sum(ss_quantity)#20] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (33) ++- * ColumnarToRow (32) + +- CometProject (31) + +- CometFilter (30) + +- CometScan parquet spark_catalog.default.date_dim (29) + + +(29) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#16, d_year#21] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(30) CometFilter +Input [2]: [d_date_sk#16, d_year#21] +Condition : ((isnotnull(d_year#21) AND (d_year#21 = 2001)) AND isnotnull(d_date_sk#16)) + +(31) CometProject +Input [2]: [d_date_sk#16, d_year#21] +Arguments: [d_date_sk#16], [d_date_sk#16] + +(32) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#16] + +(33) BroadcastExchange +Input [1]: [d_date_sk#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q48/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q48/simplified.txt new file mode 100644 index 0000000000..4022da74f1 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q48/simplified.txt @@ -0,0 +1,50 @@ +WholeStageCodegen (6) + HashAggregate [sum] [sum(ss_quantity),sum(ss_quantity),sum] + InputAdapter + Exchange #1 + WholeStageCodegen (5) + HashAggregate [ss_quantity] [sum,sum] + Project [ss_quantity] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_quantity,ss_sold_date_sk] + BroadcastHashJoin [ss_addr_sk,ca_address_sk,ca_state,ss_net_profit] + Project [ss_addr_sk,ss_quantity,ss_net_profit,ss_sold_date_sk] + BroadcastHashJoin [ss_cdemo_sk,cd_demo_sk,cd_marital_status,cd_education_status,ss_sales_price] + Project [ss_cdemo_sk,ss_addr_sk,ss_quantity,ss_sales_price,ss_net_profit,ss_sold_date_sk] + BroadcastHashJoin [ss_store_sk,s_store_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk,ss_cdemo_sk,ss_addr_sk,ss_sales_price,ss_net_profit] + CometScan parquet spark_catalog.default.store_sales [ss_cdemo_sk,ss_addr_sk,ss_store_sk,ss_quantity,ss_sales_price,ss_net_profit,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [cd_demo_sk,cd_marital_status,cd_education_status] + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_marital_status,cd_education_status] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometProject [ca_address_sk,ca_state] + CometFilter [ca_country,ca_address_sk,ca_state] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state,ca_country] + InputAdapter + ReusedExchange [d_date_sk] #2 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q49/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q49/explain.txt new file mode 100644 index 0000000000..bbb550e057 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q49/explain.txt @@ -0,0 +1,456 @@ +== Physical Plan == +TakeOrderedAndProject (74) ++- * HashAggregate (73) + +- Exchange (72) + +- * HashAggregate (71) + +- Union (70) + :- * Project (23) + : +- * Filter (22) + : +- Window (21) + : +- * Sort (20) + : +- Window (19) + : +- * Sort (18) + : +- Exchange (17) + : +- * HashAggregate (16) + : +- Exchange (15) + : +- * HashAggregate (14) + : +- * Project (13) + : +- * BroadcastHashJoin Inner BuildRight (12) + : :- * ColumnarToRow (10) + : : +- CometProject (9) + : : +- CometBroadcastHashJoin (8) + : : :- CometBroadcastExchange (4) + : : : +- CometProject (3) + : : : +- CometFilter (2) + : : : +- CometScan parquet spark_catalog.default.web_sales (1) + : : +- CometProject (7) + : : +- CometFilter (6) + : : +- CometScan parquet spark_catalog.default.web_returns (5) + : +- ReusedExchange (11) + :- * Project (46) + : +- * Filter (45) + : +- Window (44) + : +- * Sort (43) + : +- Window (42) + : +- * Sort (41) + : +- Exchange (40) + : +- * HashAggregate (39) + : +- Exchange (38) + : +- * HashAggregate (37) + : +- * Project (36) + : +- * BroadcastHashJoin Inner BuildRight (35) + : :- * ColumnarToRow (33) + : : +- CometProject (32) + : : +- CometBroadcastHashJoin (31) + : : :- CometBroadcastExchange (27) + : : : +- CometProject (26) + : : : +- CometFilter (25) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (24) + : : +- CometProject (30) + : : +- CometFilter (29) + : : +- CometScan parquet spark_catalog.default.catalog_returns (28) + : +- ReusedExchange (34) + +- * Project (69) + +- * Filter (68) + +- Window (67) + +- * Sort (66) + +- Window (65) + +- * Sort (64) + +- Exchange (63) + +- * HashAggregate (62) + +- Exchange (61) + +- * HashAggregate (60) + +- * Project (59) + +- * BroadcastHashJoin Inner BuildRight (58) + :- * ColumnarToRow (56) + : +- CometProject (55) + : +- CometBroadcastHashJoin (54) + : :- CometBroadcastExchange (50) + : : +- CometProject (49) + : : +- CometFilter (48) + : : +- CometScan parquet spark_catalog.default.store_sales (47) + : +- CometProject (53) + : +- CometFilter (52) + : +- CometScan parquet spark_catalog.default.store_returns (51) + +- ReusedExchange (57) + + +(1) Scan parquet spark_catalog.default.web_sales +Output [6]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_net_profit#5, ws_sold_date_sk#6] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#6), dynamicpruningexpression(ws_sold_date_sk#6 IN dynamicpruning#7)] +PushedFilters: [IsNotNull(ws_net_profit), IsNotNull(ws_net_paid), IsNotNull(ws_quantity), GreaterThan(ws_net_profit,1.00), GreaterThan(ws_net_paid,0.00), GreaterThan(ws_quantity,0), IsNotNull(ws_order_number), IsNotNull(ws_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [6]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_net_profit#5, ws_sold_date_sk#6] +Condition : (((((((isnotnull(ws_net_profit#5) AND isnotnull(ws_net_paid#4)) AND isnotnull(ws_quantity#3)) AND (ws_net_profit#5 > 1.00)) AND (ws_net_paid#4 > 0.00)) AND (ws_quantity#3 > 0)) AND isnotnull(ws_order_number#2)) AND isnotnull(ws_item_sk#1)) + +(3) CometProject +Input [6]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_net_profit#5, ws_sold_date_sk#6] +Arguments: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6], [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6] + +(4) CometBroadcastExchange +Input [5]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6] +Arguments: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6] + +(5) Scan parquet spark_catalog.default.web_returns +Output [5]: [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11, wr_returned_date_sk#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_returns] +PushedFilters: [IsNotNull(wr_return_amt), GreaterThan(wr_return_amt,10000.00), IsNotNull(wr_order_number), IsNotNull(wr_item_sk)] +ReadSchema: struct + +(6) CometFilter +Input [5]: [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11, wr_returned_date_sk#12] +Condition : (((isnotnull(wr_return_amt#11) AND (wr_return_amt#11 > 10000.00)) AND isnotnull(wr_order_number#9)) AND isnotnull(wr_item_sk#8)) + +(7) CometProject +Input [5]: [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11, wr_returned_date_sk#12] +Arguments: [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11], [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11] + +(8) CometBroadcastHashJoin +Left output [5]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6] +Right output [4]: [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11] +Arguments: [ws_order_number#2, ws_item_sk#1], [wr_order_number#9, wr_item_sk#8], Inner + +(9) CometProject +Input [9]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6, wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11] +Arguments: [ws_item_sk#1, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6, wr_return_quantity#10, wr_return_amt#11], [ws_item_sk#1, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6, wr_return_quantity#10, wr_return_amt#11] + +(10) ColumnarToRow [codegen id : 2] +Input [6]: [ws_item_sk#1, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6, wr_return_quantity#10, wr_return_amt#11] + +(11) ReusedExchange [Reuses operator id: 79] +Output [1]: [d_date_sk#13] + +(12) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [ws_sold_date_sk#6] +Right keys [1]: [d_date_sk#13] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 2] +Output [5]: [ws_item_sk#1, ws_quantity#3, ws_net_paid#4, wr_return_quantity#10, wr_return_amt#11] +Input [7]: [ws_item_sk#1, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6, wr_return_quantity#10, wr_return_amt#11, d_date_sk#13] + +(14) HashAggregate [codegen id : 2] +Input [5]: [ws_item_sk#1, ws_quantity#3, ws_net_paid#4, wr_return_quantity#10, wr_return_amt#11] +Keys [1]: [ws_item_sk#1] +Functions [4]: [partial_sum(coalesce(wr_return_quantity#10, 0)), partial_sum(coalesce(ws_quantity#3, 0)), partial_sum(coalesce(cast(wr_return_amt#11 as decimal(12,2)), 0.00)), partial_sum(coalesce(cast(ws_net_paid#4 as decimal(12,2)), 0.00))] +Aggregate Attributes [6]: [sum#14, sum#15, sum#16, isEmpty#17, sum#18, isEmpty#19] +Results [7]: [ws_item_sk#1, sum#20, sum#21, sum#22, isEmpty#23, sum#24, isEmpty#25] + +(15) Exchange +Input [7]: [ws_item_sk#1, sum#20, sum#21, sum#22, isEmpty#23, sum#24, isEmpty#25] +Arguments: hashpartitioning(ws_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(16) HashAggregate [codegen id : 3] +Input [7]: [ws_item_sk#1, sum#20, sum#21, sum#22, isEmpty#23, sum#24, isEmpty#25] +Keys [1]: [ws_item_sk#1] +Functions [4]: [sum(coalesce(wr_return_quantity#10, 0)), sum(coalesce(ws_quantity#3, 0)), sum(coalesce(cast(wr_return_amt#11 as decimal(12,2)), 0.00)), sum(coalesce(cast(ws_net_paid#4 as decimal(12,2)), 0.00))] +Aggregate Attributes [4]: [sum(coalesce(wr_return_quantity#10, 0))#26, sum(coalesce(ws_quantity#3, 0))#27, sum(coalesce(cast(wr_return_amt#11 as decimal(12,2)), 0.00))#28, sum(coalesce(cast(ws_net_paid#4 as decimal(12,2)), 0.00))#29] +Results [3]: [ws_item_sk#1 AS item#30, (cast(sum(coalesce(wr_return_quantity#10, 0))#26 as decimal(15,4)) / cast(sum(coalesce(ws_quantity#3, 0))#27 as decimal(15,4))) AS return_ratio#31, (cast(sum(coalesce(cast(wr_return_amt#11 as decimal(12,2)), 0.00))#28 as decimal(15,4)) / cast(sum(coalesce(cast(ws_net_paid#4 as decimal(12,2)), 0.00))#29 as decimal(15,4))) AS currency_ratio#32] + +(17) Exchange +Input [3]: [item#30, return_ratio#31, currency_ratio#32] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=2] + +(18) Sort [codegen id : 4] +Input [3]: [item#30, return_ratio#31, currency_ratio#32] +Arguments: [return_ratio#31 ASC NULLS FIRST], false, 0 + +(19) Window +Input [3]: [item#30, return_ratio#31, currency_ratio#32] +Arguments: [rank(return_ratio#31) windowspecdefinition(return_ratio#31 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS return_rank#33], [return_ratio#31 ASC NULLS FIRST] + +(20) Sort [codegen id : 5] +Input [4]: [item#30, return_ratio#31, currency_ratio#32, return_rank#33] +Arguments: [currency_ratio#32 ASC NULLS FIRST], false, 0 + +(21) Window +Input [4]: [item#30, return_ratio#31, currency_ratio#32, return_rank#33] +Arguments: [rank(currency_ratio#32) windowspecdefinition(currency_ratio#32 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS currency_rank#34], [currency_ratio#32 ASC NULLS FIRST] + +(22) Filter [codegen id : 6] +Input [5]: [item#30, return_ratio#31, currency_ratio#32, return_rank#33, currency_rank#34] +Condition : ((return_rank#33 <= 10) OR (currency_rank#34 <= 10)) + +(23) Project [codegen id : 6] +Output [5]: [web AS channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] +Input [5]: [item#30, return_ratio#31, currency_ratio#32, return_rank#33, currency_rank#34] + +(24) Scan parquet spark_catalog.default.catalog_sales +Output [6]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_net_profit#40, cs_sold_date_sk#41] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#41), dynamicpruningexpression(cs_sold_date_sk#41 IN dynamicpruning#42)] +PushedFilters: [IsNotNull(cs_net_profit), IsNotNull(cs_net_paid), IsNotNull(cs_quantity), GreaterThan(cs_net_profit,1.00), GreaterThan(cs_net_paid,0.00), GreaterThan(cs_quantity,0), IsNotNull(cs_order_number), IsNotNull(cs_item_sk)] +ReadSchema: struct + +(25) CometFilter +Input [6]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_net_profit#40, cs_sold_date_sk#41] +Condition : (((((((isnotnull(cs_net_profit#40) AND isnotnull(cs_net_paid#39)) AND isnotnull(cs_quantity#38)) AND (cs_net_profit#40 > 1.00)) AND (cs_net_paid#39 > 0.00)) AND (cs_quantity#38 > 0)) AND isnotnull(cs_order_number#37)) AND isnotnull(cs_item_sk#36)) + +(26) CometProject +Input [6]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_net_profit#40, cs_sold_date_sk#41] +Arguments: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41], [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41] + +(27) CometBroadcastExchange +Input [5]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41] +Arguments: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41] + +(28) Scan parquet spark_catalog.default.catalog_returns +Output [5]: [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46, cr_returned_date_sk#47] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_returns] +PushedFilters: [IsNotNull(cr_return_amount), GreaterThan(cr_return_amount,10000.00), IsNotNull(cr_order_number), IsNotNull(cr_item_sk)] +ReadSchema: struct + +(29) CometFilter +Input [5]: [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46, cr_returned_date_sk#47] +Condition : (((isnotnull(cr_return_amount#46) AND (cr_return_amount#46 > 10000.00)) AND isnotnull(cr_order_number#44)) AND isnotnull(cr_item_sk#43)) + +(30) CometProject +Input [5]: [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46, cr_returned_date_sk#47] +Arguments: [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46], [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46] + +(31) CometBroadcastHashJoin +Left output [5]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41] +Right output [4]: [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46] +Arguments: [cs_order_number#37, cs_item_sk#36], [cr_order_number#44, cr_item_sk#43], Inner + +(32) CometProject +Input [9]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41, cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46] +Arguments: [cs_item_sk#36, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41, cr_return_quantity#45, cr_return_amount#46], [cs_item_sk#36, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41, cr_return_quantity#45, cr_return_amount#46] + +(33) ColumnarToRow [codegen id : 8] +Input [6]: [cs_item_sk#36, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41, cr_return_quantity#45, cr_return_amount#46] + +(34) ReusedExchange [Reuses operator id: 79] +Output [1]: [d_date_sk#48] + +(35) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [cs_sold_date_sk#41] +Right keys [1]: [d_date_sk#48] +Join type: Inner +Join condition: None + +(36) Project [codegen id : 8] +Output [5]: [cs_item_sk#36, cs_quantity#38, cs_net_paid#39, cr_return_quantity#45, cr_return_amount#46] +Input [7]: [cs_item_sk#36, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41, cr_return_quantity#45, cr_return_amount#46, d_date_sk#48] + +(37) HashAggregate [codegen id : 8] +Input [5]: [cs_item_sk#36, cs_quantity#38, cs_net_paid#39, cr_return_quantity#45, cr_return_amount#46] +Keys [1]: [cs_item_sk#36] +Functions [4]: [partial_sum(coalesce(cr_return_quantity#45, 0)), partial_sum(coalesce(cs_quantity#38, 0)), partial_sum(coalesce(cast(cr_return_amount#46 as decimal(12,2)), 0.00)), partial_sum(coalesce(cast(cs_net_paid#39 as decimal(12,2)), 0.00))] +Aggregate Attributes [6]: [sum#49, sum#50, sum#51, isEmpty#52, sum#53, isEmpty#54] +Results [7]: [cs_item_sk#36, sum#55, sum#56, sum#57, isEmpty#58, sum#59, isEmpty#60] + +(38) Exchange +Input [7]: [cs_item_sk#36, sum#55, sum#56, sum#57, isEmpty#58, sum#59, isEmpty#60] +Arguments: hashpartitioning(cs_item_sk#36, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(39) HashAggregate [codegen id : 9] +Input [7]: [cs_item_sk#36, sum#55, sum#56, sum#57, isEmpty#58, sum#59, isEmpty#60] +Keys [1]: [cs_item_sk#36] +Functions [4]: [sum(coalesce(cr_return_quantity#45, 0)), sum(coalesce(cs_quantity#38, 0)), sum(coalesce(cast(cr_return_amount#46 as decimal(12,2)), 0.00)), sum(coalesce(cast(cs_net_paid#39 as decimal(12,2)), 0.00))] +Aggregate Attributes [4]: [sum(coalesce(cr_return_quantity#45, 0))#61, sum(coalesce(cs_quantity#38, 0))#62, sum(coalesce(cast(cr_return_amount#46 as decimal(12,2)), 0.00))#63, sum(coalesce(cast(cs_net_paid#39 as decimal(12,2)), 0.00))#64] +Results [3]: [cs_item_sk#36 AS item#65, (cast(sum(coalesce(cr_return_quantity#45, 0))#61 as decimal(15,4)) / cast(sum(coalesce(cs_quantity#38, 0))#62 as decimal(15,4))) AS return_ratio#66, (cast(sum(coalesce(cast(cr_return_amount#46 as decimal(12,2)), 0.00))#63 as decimal(15,4)) / cast(sum(coalesce(cast(cs_net_paid#39 as decimal(12,2)), 0.00))#64 as decimal(15,4))) AS currency_ratio#67] + +(40) Exchange +Input [3]: [item#65, return_ratio#66, currency_ratio#67] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=4] + +(41) Sort [codegen id : 10] +Input [3]: [item#65, return_ratio#66, currency_ratio#67] +Arguments: [return_ratio#66 ASC NULLS FIRST], false, 0 + +(42) Window +Input [3]: [item#65, return_ratio#66, currency_ratio#67] +Arguments: [rank(return_ratio#66) windowspecdefinition(return_ratio#66 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS return_rank#68], [return_ratio#66 ASC NULLS FIRST] + +(43) Sort [codegen id : 11] +Input [4]: [item#65, return_ratio#66, currency_ratio#67, return_rank#68] +Arguments: [currency_ratio#67 ASC NULLS FIRST], false, 0 + +(44) Window +Input [4]: [item#65, return_ratio#66, currency_ratio#67, return_rank#68] +Arguments: [rank(currency_ratio#67) windowspecdefinition(currency_ratio#67 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS currency_rank#69], [currency_ratio#67 ASC NULLS FIRST] + +(45) Filter [codegen id : 12] +Input [5]: [item#65, return_ratio#66, currency_ratio#67, return_rank#68, currency_rank#69] +Condition : ((return_rank#68 <= 10) OR (currency_rank#69 <= 10)) + +(46) Project [codegen id : 12] +Output [5]: [catalog AS channel#70, item#65, return_ratio#66, return_rank#68, currency_rank#69] +Input [5]: [item#65, return_ratio#66, currency_ratio#67, return_rank#68, currency_rank#69] + +(47) Scan parquet spark_catalog.default.store_sales +Output [6]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_net_profit#75, ss_sold_date_sk#76] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#76), dynamicpruningexpression(ss_sold_date_sk#76 IN dynamicpruning#77)] +PushedFilters: [IsNotNull(ss_net_profit), IsNotNull(ss_net_paid), IsNotNull(ss_quantity), GreaterThan(ss_net_profit,1.00), GreaterThan(ss_net_paid,0.00), GreaterThan(ss_quantity,0), IsNotNull(ss_ticket_number), IsNotNull(ss_item_sk)] +ReadSchema: struct + +(48) CometFilter +Input [6]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_net_profit#75, ss_sold_date_sk#76] +Condition : (((((((isnotnull(ss_net_profit#75) AND isnotnull(ss_net_paid#74)) AND isnotnull(ss_quantity#73)) AND (ss_net_profit#75 > 1.00)) AND (ss_net_paid#74 > 0.00)) AND (ss_quantity#73 > 0)) AND isnotnull(ss_ticket_number#72)) AND isnotnull(ss_item_sk#71)) + +(49) CometProject +Input [6]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_net_profit#75, ss_sold_date_sk#76] +Arguments: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76], [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76] + +(50) CometBroadcastExchange +Input [5]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76] +Arguments: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76] + +(51) Scan parquet spark_catalog.default.store_returns +Output [5]: [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81, sr_returned_date_sk#82] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_returns] +PushedFilters: [IsNotNull(sr_return_amt), GreaterThan(sr_return_amt,10000.00), IsNotNull(sr_ticket_number), IsNotNull(sr_item_sk)] +ReadSchema: struct + +(52) CometFilter +Input [5]: [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81, sr_returned_date_sk#82] +Condition : (((isnotnull(sr_return_amt#81) AND (sr_return_amt#81 > 10000.00)) AND isnotnull(sr_ticket_number#79)) AND isnotnull(sr_item_sk#78)) + +(53) CometProject +Input [5]: [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81, sr_returned_date_sk#82] +Arguments: [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81], [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81] + +(54) CometBroadcastHashJoin +Left output [5]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76] +Right output [4]: [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81] +Arguments: [ss_ticket_number#72, ss_item_sk#71], [sr_ticket_number#79, sr_item_sk#78], Inner + +(55) CometProject +Input [9]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76, sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81] +Arguments: [ss_item_sk#71, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76, sr_return_quantity#80, sr_return_amt#81], [ss_item_sk#71, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76, sr_return_quantity#80, sr_return_amt#81] + +(56) ColumnarToRow [codegen id : 14] +Input [6]: [ss_item_sk#71, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76, sr_return_quantity#80, sr_return_amt#81] + +(57) ReusedExchange [Reuses operator id: 79] +Output [1]: [d_date_sk#83] + +(58) BroadcastHashJoin [codegen id : 14] +Left keys [1]: [ss_sold_date_sk#76] +Right keys [1]: [d_date_sk#83] +Join type: Inner +Join condition: None + +(59) Project [codegen id : 14] +Output [5]: [ss_item_sk#71, ss_quantity#73, ss_net_paid#74, sr_return_quantity#80, sr_return_amt#81] +Input [7]: [ss_item_sk#71, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76, sr_return_quantity#80, sr_return_amt#81, d_date_sk#83] + +(60) HashAggregate [codegen id : 14] +Input [5]: [ss_item_sk#71, ss_quantity#73, ss_net_paid#74, sr_return_quantity#80, sr_return_amt#81] +Keys [1]: [ss_item_sk#71] +Functions [4]: [partial_sum(coalesce(sr_return_quantity#80, 0)), partial_sum(coalesce(ss_quantity#73, 0)), partial_sum(coalesce(cast(sr_return_amt#81 as decimal(12,2)), 0.00)), partial_sum(coalesce(cast(ss_net_paid#74 as decimal(12,2)), 0.00))] +Aggregate Attributes [6]: [sum#84, sum#85, sum#86, isEmpty#87, sum#88, isEmpty#89] +Results [7]: [ss_item_sk#71, sum#90, sum#91, sum#92, isEmpty#93, sum#94, isEmpty#95] + +(61) Exchange +Input [7]: [ss_item_sk#71, sum#90, sum#91, sum#92, isEmpty#93, sum#94, isEmpty#95] +Arguments: hashpartitioning(ss_item_sk#71, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(62) HashAggregate [codegen id : 15] +Input [7]: [ss_item_sk#71, sum#90, sum#91, sum#92, isEmpty#93, sum#94, isEmpty#95] +Keys [1]: [ss_item_sk#71] +Functions [4]: [sum(coalesce(sr_return_quantity#80, 0)), sum(coalesce(ss_quantity#73, 0)), sum(coalesce(cast(sr_return_amt#81 as decimal(12,2)), 0.00)), sum(coalesce(cast(ss_net_paid#74 as decimal(12,2)), 0.00))] +Aggregate Attributes [4]: [sum(coalesce(sr_return_quantity#80, 0))#96, sum(coalesce(ss_quantity#73, 0))#97, sum(coalesce(cast(sr_return_amt#81 as decimal(12,2)), 0.00))#98, sum(coalesce(cast(ss_net_paid#74 as decimal(12,2)), 0.00))#99] +Results [3]: [ss_item_sk#71 AS item#100, (cast(sum(coalesce(sr_return_quantity#80, 0))#96 as decimal(15,4)) / cast(sum(coalesce(ss_quantity#73, 0))#97 as decimal(15,4))) AS return_ratio#101, (cast(sum(coalesce(cast(sr_return_amt#81 as decimal(12,2)), 0.00))#98 as decimal(15,4)) / cast(sum(coalesce(cast(ss_net_paid#74 as decimal(12,2)), 0.00))#99 as decimal(15,4))) AS currency_ratio#102] + +(63) Exchange +Input [3]: [item#100, return_ratio#101, currency_ratio#102] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=6] + +(64) Sort [codegen id : 16] +Input [3]: [item#100, return_ratio#101, currency_ratio#102] +Arguments: [return_ratio#101 ASC NULLS FIRST], false, 0 + +(65) Window +Input [3]: [item#100, return_ratio#101, currency_ratio#102] +Arguments: [rank(return_ratio#101) windowspecdefinition(return_ratio#101 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS return_rank#103], [return_ratio#101 ASC NULLS FIRST] + +(66) Sort [codegen id : 17] +Input [4]: [item#100, return_ratio#101, currency_ratio#102, return_rank#103] +Arguments: [currency_ratio#102 ASC NULLS FIRST], false, 0 + +(67) Window +Input [4]: [item#100, return_ratio#101, currency_ratio#102, return_rank#103] +Arguments: [rank(currency_ratio#102) windowspecdefinition(currency_ratio#102 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS currency_rank#104], [currency_ratio#102 ASC NULLS FIRST] + +(68) Filter [codegen id : 18] +Input [5]: [item#100, return_ratio#101, currency_ratio#102, return_rank#103, currency_rank#104] +Condition : ((return_rank#103 <= 10) OR (currency_rank#104 <= 10)) + +(69) Project [codegen id : 18] +Output [5]: [store AS channel#105, item#100, return_ratio#101, return_rank#103, currency_rank#104] +Input [5]: [item#100, return_ratio#101, currency_ratio#102, return_rank#103, currency_rank#104] + +(70) Union + +(71) HashAggregate [codegen id : 19] +Input [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] +Keys [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] +Functions: [] +Aggregate Attributes: [] +Results [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] + +(72) Exchange +Input [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] +Arguments: hashpartitioning(channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(73) HashAggregate [codegen id : 20] +Input [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] +Keys [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] +Functions: [] +Aggregate Attributes: [] +Results [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] + +(74) TakeOrderedAndProject +Input [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] +Arguments: 100, [channel#35 ASC NULLS FIRST, return_rank#33 ASC NULLS FIRST, currency_rank#34 ASC NULLS FIRST], [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#6 IN dynamicpruning#7 +BroadcastExchange (79) ++- * ColumnarToRow (78) + +- CometProject (77) + +- CometFilter (76) + +- CometScan parquet spark_catalog.default.date_dim (75) + + +(75) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#13, d_year#106, d_moy#107] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2001), EqualTo(d_moy,12), IsNotNull(d_date_sk)] +ReadSchema: struct + +(76) CometFilter +Input [3]: [d_date_sk#13, d_year#106, d_moy#107] +Condition : ((((isnotnull(d_year#106) AND isnotnull(d_moy#107)) AND (d_year#106 = 2001)) AND (d_moy#107 = 12)) AND isnotnull(d_date_sk#13)) + +(77) CometProject +Input [3]: [d_date_sk#13, d_year#106, d_moy#107] +Arguments: [d_date_sk#13], [d_date_sk#13] + +(78) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#13] + +(79) BroadcastExchange +Input [1]: [d_date_sk#13] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + +Subquery:2 Hosting operator id = 24 Hosting Expression = cs_sold_date_sk#41 IN dynamicpruning#7 + +Subquery:3 Hosting operator id = 47 Hosting Expression = ss_sold_date_sk#76 IN dynamicpruning#7 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q49/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q49/simplified.txt new file mode 100644 index 0000000000..43ebf34cc0 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q49/simplified.txt @@ -0,0 +1,121 @@ +TakeOrderedAndProject [channel,return_rank,currency_rank,item,return_ratio] + WholeStageCodegen (20) + HashAggregate [channel,item,return_ratio,return_rank,currency_rank] + InputAdapter + Exchange [channel,item,return_ratio,return_rank,currency_rank] #1 + WholeStageCodegen (19) + HashAggregate [channel,item,return_ratio,return_rank,currency_rank] + InputAdapter + Union + WholeStageCodegen (6) + Project [item,return_ratio,return_rank,currency_rank] + Filter [return_rank,currency_rank] + InputAdapter + Window [currency_ratio] + WholeStageCodegen (5) + Sort [currency_ratio] + InputAdapter + Window [return_ratio] + WholeStageCodegen (4) + Sort [return_ratio] + InputAdapter + Exchange #2 + WholeStageCodegen (3) + HashAggregate [ws_item_sk,sum,sum,sum,isEmpty,sum,isEmpty] [sum(coalesce(wr_return_quantity, 0)),sum(coalesce(ws_quantity, 0)),sum(coalesce(cast(wr_return_amt as decimal(12,2)), 0.00)),sum(coalesce(cast(ws_net_paid as decimal(12,2)), 0.00)),item,return_ratio,currency_ratio,sum,sum,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [ws_item_sk] #3 + WholeStageCodegen (2) + HashAggregate [ws_item_sk,wr_return_quantity,ws_quantity,wr_return_amt,ws_net_paid] [sum,sum,sum,isEmpty,sum,isEmpty,sum,sum,sum,isEmpty,sum,isEmpty] + Project [ws_item_sk,ws_quantity,ws_net_paid,wr_return_quantity,wr_return_amt] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometProject [ws_item_sk,ws_quantity,ws_net_paid,ws_sold_date_sk,wr_return_quantity,wr_return_amt] + CometBroadcastHashJoin [ws_order_number,ws_item_sk,wr_order_number,wr_item_sk] + CometBroadcastExchange #4 + CometProject [ws_item_sk,ws_order_number,ws_quantity,ws_net_paid,ws_sold_date_sk] + CometFilter [ws_net_profit,ws_net_paid,ws_quantity,ws_order_number,ws_item_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_order_number,ws_quantity,ws_net_paid,ws_net_profit,ws_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #5 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_moy,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + CometProject [wr_item_sk,wr_order_number,wr_return_quantity,wr_return_amt] + CometFilter [wr_return_amt,wr_order_number,wr_item_sk] + CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_order_number,wr_return_quantity,wr_return_amt,wr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk] #5 + WholeStageCodegen (12) + Project [item,return_ratio,return_rank,currency_rank] + Filter [return_rank,currency_rank] + InputAdapter + Window [currency_ratio] + WholeStageCodegen (11) + Sort [currency_ratio] + InputAdapter + Window [return_ratio] + WholeStageCodegen (10) + Sort [return_ratio] + InputAdapter + Exchange #6 + WholeStageCodegen (9) + HashAggregate [cs_item_sk,sum,sum,sum,isEmpty,sum,isEmpty] [sum(coalesce(cr_return_quantity, 0)),sum(coalesce(cs_quantity, 0)),sum(coalesce(cast(cr_return_amount as decimal(12,2)), 0.00)),sum(coalesce(cast(cs_net_paid as decimal(12,2)), 0.00)),item,return_ratio,currency_ratio,sum,sum,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [cs_item_sk] #7 + WholeStageCodegen (8) + HashAggregate [cs_item_sk,cr_return_quantity,cs_quantity,cr_return_amount,cs_net_paid] [sum,sum,sum,isEmpty,sum,isEmpty,sum,sum,sum,isEmpty,sum,isEmpty] + Project [cs_item_sk,cs_quantity,cs_net_paid,cr_return_quantity,cr_return_amount] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometProject [cs_item_sk,cs_quantity,cs_net_paid,cs_sold_date_sk,cr_return_quantity,cr_return_amount] + CometBroadcastHashJoin [cs_order_number,cs_item_sk,cr_order_number,cr_item_sk] + CometBroadcastExchange #8 + CometProject [cs_item_sk,cs_order_number,cs_quantity,cs_net_paid,cs_sold_date_sk] + CometFilter [cs_net_profit,cs_net_paid,cs_quantity,cs_order_number,cs_item_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_order_number,cs_quantity,cs_net_paid,cs_net_profit,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + CometProject [cr_item_sk,cr_order_number,cr_return_quantity,cr_return_amount] + CometFilter [cr_return_amount,cr_order_number,cr_item_sk] + CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_return_quantity,cr_return_amount,cr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk] #5 + WholeStageCodegen (18) + Project [item,return_ratio,return_rank,currency_rank] + Filter [return_rank,currency_rank] + InputAdapter + Window [currency_ratio] + WholeStageCodegen (17) + Sort [currency_ratio] + InputAdapter + Window [return_ratio] + WholeStageCodegen (16) + Sort [return_ratio] + InputAdapter + Exchange #9 + WholeStageCodegen (15) + HashAggregate [ss_item_sk,sum,sum,sum,isEmpty,sum,isEmpty] [sum(coalesce(sr_return_quantity, 0)),sum(coalesce(ss_quantity, 0)),sum(coalesce(cast(sr_return_amt as decimal(12,2)), 0.00)),sum(coalesce(cast(ss_net_paid as decimal(12,2)), 0.00)),item,return_ratio,currency_ratio,sum,sum,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [ss_item_sk] #10 + WholeStageCodegen (14) + HashAggregate [ss_item_sk,sr_return_quantity,ss_quantity,sr_return_amt,ss_net_paid] [sum,sum,sum,isEmpty,sum,isEmpty,sum,sum,sum,isEmpty,sum,isEmpty] + Project [ss_item_sk,ss_quantity,ss_net_paid,sr_return_quantity,sr_return_amt] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometProject [ss_item_sk,ss_quantity,ss_net_paid,ss_sold_date_sk,sr_return_quantity,sr_return_amt] + CometBroadcastHashJoin [ss_ticket_number,ss_item_sk,sr_ticket_number,sr_item_sk] + CometBroadcastExchange #11 + CometProject [ss_item_sk,ss_ticket_number,ss_quantity,ss_net_paid,ss_sold_date_sk] + CometFilter [ss_net_profit,ss_net_paid,ss_quantity,ss_ticket_number,ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ticket_number,ss_quantity,ss_net_paid,ss_net_profit,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + CometProject [sr_item_sk,sr_ticket_number,sr_return_quantity,sr_return_amt] + CometFilter [sr_return_amt,sr_ticket_number,sr_item_sk] + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_return_quantity,sr_return_amt,sr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk] #5 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q5/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q5/explain.txt new file mode 100644 index 0000000000..e3f7538d1c --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q5/explain.txt @@ -0,0 +1,457 @@ +== Physical Plan == +TakeOrderedAndProject (70) ++- * HashAggregate (69) + +- Exchange (68) + +- * HashAggregate (67) + +- * Expand (66) + +- Union (65) + :- * HashAggregate (20) + : +- Exchange (19) + : +- * HashAggregate (18) + : +- * Project (17) + : +- * BroadcastHashJoin Inner BuildRight (16) + : :- * Project (11) + : : +- * BroadcastHashJoin Inner BuildRight (10) + : : :- * ColumnarToRow (8) + : : : +- CometUnion (7) + : : : :- CometProject (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- CometProject (6) + : : : +- CometFilter (5) + : : : +- CometScan parquet spark_catalog.default.store_returns (4) + : : +- ReusedExchange (9) + : +- BroadcastExchange (15) + : +- * ColumnarToRow (14) + : +- CometFilter (13) + : +- CometScan parquet spark_catalog.default.store (12) + :- * HashAggregate (40) + : +- Exchange (39) + : +- * HashAggregate (38) + : +- * Project (37) + : +- * BroadcastHashJoin Inner BuildRight (36) + : :- * Project (31) + : : +- * BroadcastHashJoin Inner BuildRight (30) + : : :- * ColumnarToRow (28) + : : : +- CometUnion (27) + : : : :- CometProject (23) + : : : : +- CometFilter (22) + : : : : +- CometScan parquet spark_catalog.default.catalog_sales (21) + : : : +- CometProject (26) + : : : +- CometFilter (25) + : : : +- CometScan parquet spark_catalog.default.catalog_returns (24) + : : +- ReusedExchange (29) + : +- BroadcastExchange (35) + : +- * ColumnarToRow (34) + : +- CometFilter (33) + : +- CometScan parquet spark_catalog.default.catalog_page (32) + +- * HashAggregate (64) + +- Exchange (63) + +- * HashAggregate (62) + +- * Project (61) + +- * BroadcastHashJoin Inner BuildRight (60) + :- * Project (55) + : +- * BroadcastHashJoin Inner BuildRight (54) + : :- * ColumnarToRow (52) + : : +- CometUnion (51) + : : :- CometProject (43) + : : : +- CometFilter (42) + : : : +- CometScan parquet spark_catalog.default.web_sales (41) + : : +- CometProject (50) + : : +- CometBroadcastHashJoin (49) + : : :- CometBroadcastExchange (45) + : : : +- CometScan parquet spark_catalog.default.web_returns (44) + : : +- CometProject (48) + : : +- CometFilter (47) + : : +- CometScan parquet spark_catalog.default.web_sales (46) + : +- ReusedExchange (53) + +- BroadcastExchange (59) + +- * ColumnarToRow (58) + +- CometFilter (57) + +- CometScan parquet spark_catalog.default.web_site (56) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#4), dynamicpruningexpression(ss_sold_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(ss_store_sk)] +ReadSchema: struct + +(2) CometFilter +Input [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] +Condition : isnotnull(ss_store_sk#1) + +(3) CometProject +Input [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] +Arguments: [store_sk#6, date_sk#7, sales_price#8, profit#9, return_amt#10, net_loss#11], [ss_store_sk#1 AS store_sk#6, ss_sold_date_sk#4 AS date_sk#7, ss_ext_sales_price#2 AS sales_price#8, ss_net_profit#3 AS profit#9, 0.00 AS return_amt#10, 0.00 AS net_loss#11] + +(4) Scan parquet spark_catalog.default.store_returns +Output [4]: [sr_store_sk#12, sr_return_amt#13, sr_net_loss#14, sr_returned_date_sk#15] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(sr_returned_date_sk#15), dynamicpruningexpression(sr_returned_date_sk#15 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(sr_store_sk)] +ReadSchema: struct + +(5) CometFilter +Input [4]: [sr_store_sk#12, sr_return_amt#13, sr_net_loss#14, sr_returned_date_sk#15] +Condition : isnotnull(sr_store_sk#12) + +(6) CometProject +Input [4]: [sr_store_sk#12, sr_return_amt#13, sr_net_loss#14, sr_returned_date_sk#15] +Arguments: [store_sk#16, date_sk#17, sales_price#18, profit#19, return_amt#20, net_loss#21], [sr_store_sk#12 AS store_sk#16, sr_returned_date_sk#15 AS date_sk#17, 0.00 AS sales_price#18, 0.00 AS profit#19, sr_return_amt#13 AS return_amt#20, sr_net_loss#14 AS net_loss#21] + +(7) CometUnion +Child 0 Input [6]: [store_sk#6, date_sk#7, sales_price#8, profit#9, return_amt#10, net_loss#11] +Child 1 Input [6]: [store_sk#16, date_sk#17, sales_price#18, profit#19, return_amt#20, net_loss#21] + +(8) ColumnarToRow [codegen id : 3] +Input [6]: [store_sk#6, date_sk#7, sales_price#8, profit#9, return_amt#10, net_loss#11] + +(9) ReusedExchange [Reuses operator id: 75] +Output [1]: [d_date_sk#22] + +(10) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [date_sk#7] +Right keys [1]: [d_date_sk#22] +Join type: Inner +Join condition: None + +(11) Project [codegen id : 3] +Output [5]: [store_sk#6, sales_price#8, profit#9, return_amt#10, net_loss#11] +Input [7]: [store_sk#6, date_sk#7, sales_price#8, profit#9, return_amt#10, net_loss#11, d_date_sk#22] + +(12) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#23, s_store_id#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(13) CometFilter +Input [2]: [s_store_sk#23, s_store_id#24] +Condition : isnotnull(s_store_sk#23) + +(14) ColumnarToRow [codegen id : 2] +Input [2]: [s_store_sk#23, s_store_id#24] + +(15) BroadcastExchange +Input [2]: [s_store_sk#23, s_store_id#24] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(16) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [store_sk#6] +Right keys [1]: [s_store_sk#23] +Join type: Inner +Join condition: None + +(17) Project [codegen id : 3] +Output [5]: [sales_price#8, profit#9, return_amt#10, net_loss#11, s_store_id#24] +Input [7]: [store_sk#6, sales_price#8, profit#9, return_amt#10, net_loss#11, s_store_sk#23, s_store_id#24] + +(18) HashAggregate [codegen id : 3] +Input [5]: [sales_price#8, profit#9, return_amt#10, net_loss#11, s_store_id#24] +Keys [1]: [s_store_id#24] +Functions [4]: [partial_sum(UnscaledValue(sales_price#8)), partial_sum(UnscaledValue(return_amt#10)), partial_sum(UnscaledValue(profit#9)), partial_sum(UnscaledValue(net_loss#11))] +Aggregate Attributes [4]: [sum#25, sum#26, sum#27, sum#28] +Results [5]: [s_store_id#24, sum#29, sum#30, sum#31, sum#32] + +(19) Exchange +Input [5]: [s_store_id#24, sum#29, sum#30, sum#31, sum#32] +Arguments: hashpartitioning(s_store_id#24, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(20) HashAggregate [codegen id : 4] +Input [5]: [s_store_id#24, sum#29, sum#30, sum#31, sum#32] +Keys [1]: [s_store_id#24] +Functions [4]: [sum(UnscaledValue(sales_price#8)), sum(UnscaledValue(return_amt#10)), sum(UnscaledValue(profit#9)), sum(UnscaledValue(net_loss#11))] +Aggregate Attributes [4]: [sum(UnscaledValue(sales_price#8))#33, sum(UnscaledValue(return_amt#10))#34, sum(UnscaledValue(profit#9))#35, sum(UnscaledValue(net_loss#11))#36] +Results [5]: [MakeDecimal(sum(UnscaledValue(sales_price#8))#33,17,2) AS sales#37, MakeDecimal(sum(UnscaledValue(return_amt#10))#34,17,2) AS returns#38, (MakeDecimal(sum(UnscaledValue(profit#9))#35,17,2) - MakeDecimal(sum(UnscaledValue(net_loss#11))#36,17,2)) AS profit#39, store channel AS channel#40, concat(store, s_store_id#24) AS id#41] + +(21) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_catalog_page_sk#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#45), dynamicpruningexpression(cs_sold_date_sk#45 IN dynamicpruning#46)] +PushedFilters: [IsNotNull(cs_catalog_page_sk)] +ReadSchema: struct + +(22) CometFilter +Input [4]: [cs_catalog_page_sk#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] +Condition : isnotnull(cs_catalog_page_sk#42) + +(23) CometProject +Input [4]: [cs_catalog_page_sk#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] +Arguments: [page_sk#47, date_sk#48, sales_price#49, profit#50, return_amt#51, net_loss#52], [cs_catalog_page_sk#42 AS page_sk#47, cs_sold_date_sk#45 AS date_sk#48, cs_ext_sales_price#43 AS sales_price#49, cs_net_profit#44 AS profit#50, 0.00 AS return_amt#51, 0.00 AS net_loss#52] + +(24) Scan parquet spark_catalog.default.catalog_returns +Output [4]: [cr_catalog_page_sk#53, cr_return_amount#54, cr_net_loss#55, cr_returned_date_sk#56] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cr_returned_date_sk#56), dynamicpruningexpression(cr_returned_date_sk#56 IN dynamicpruning#46)] +PushedFilters: [IsNotNull(cr_catalog_page_sk)] +ReadSchema: struct + +(25) CometFilter +Input [4]: [cr_catalog_page_sk#53, cr_return_amount#54, cr_net_loss#55, cr_returned_date_sk#56] +Condition : isnotnull(cr_catalog_page_sk#53) + +(26) CometProject +Input [4]: [cr_catalog_page_sk#53, cr_return_amount#54, cr_net_loss#55, cr_returned_date_sk#56] +Arguments: [page_sk#57, date_sk#58, sales_price#59, profit#60, return_amt#61, net_loss#62], [cr_catalog_page_sk#53 AS page_sk#57, cr_returned_date_sk#56 AS date_sk#58, 0.00 AS sales_price#59, 0.00 AS profit#60, cr_return_amount#54 AS return_amt#61, cr_net_loss#55 AS net_loss#62] + +(27) CometUnion +Child 0 Input [6]: [page_sk#47, date_sk#48, sales_price#49, profit#50, return_amt#51, net_loss#52] +Child 1 Input [6]: [page_sk#57, date_sk#58, sales_price#59, profit#60, return_amt#61, net_loss#62] + +(28) ColumnarToRow [codegen id : 7] +Input [6]: [page_sk#47, date_sk#48, sales_price#49, profit#50, return_amt#51, net_loss#52] + +(29) ReusedExchange [Reuses operator id: 75] +Output [1]: [d_date_sk#63] + +(30) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [date_sk#48] +Right keys [1]: [d_date_sk#63] +Join type: Inner +Join condition: None + +(31) Project [codegen id : 7] +Output [5]: [page_sk#47, sales_price#49, profit#50, return_amt#51, net_loss#52] +Input [7]: [page_sk#47, date_sk#48, sales_price#49, profit#50, return_amt#51, net_loss#52, d_date_sk#63] + +(32) Scan parquet spark_catalog.default.catalog_page +Output [2]: [cp_catalog_page_sk#64, cp_catalog_page_id#65] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_page] +PushedFilters: [IsNotNull(cp_catalog_page_sk)] +ReadSchema: struct + +(33) CometFilter +Input [2]: [cp_catalog_page_sk#64, cp_catalog_page_id#65] +Condition : isnotnull(cp_catalog_page_sk#64) + +(34) ColumnarToRow [codegen id : 6] +Input [2]: [cp_catalog_page_sk#64, cp_catalog_page_id#65] + +(35) BroadcastExchange +Input [2]: [cp_catalog_page_sk#64, cp_catalog_page_id#65] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(36) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [page_sk#47] +Right keys [1]: [cp_catalog_page_sk#64] +Join type: Inner +Join condition: None + +(37) Project [codegen id : 7] +Output [5]: [sales_price#49, profit#50, return_amt#51, net_loss#52, cp_catalog_page_id#65] +Input [7]: [page_sk#47, sales_price#49, profit#50, return_amt#51, net_loss#52, cp_catalog_page_sk#64, cp_catalog_page_id#65] + +(38) HashAggregate [codegen id : 7] +Input [5]: [sales_price#49, profit#50, return_amt#51, net_loss#52, cp_catalog_page_id#65] +Keys [1]: [cp_catalog_page_id#65] +Functions [4]: [partial_sum(UnscaledValue(sales_price#49)), partial_sum(UnscaledValue(return_amt#51)), partial_sum(UnscaledValue(profit#50)), partial_sum(UnscaledValue(net_loss#52))] +Aggregate Attributes [4]: [sum#66, sum#67, sum#68, sum#69] +Results [5]: [cp_catalog_page_id#65, sum#70, sum#71, sum#72, sum#73] + +(39) Exchange +Input [5]: [cp_catalog_page_id#65, sum#70, sum#71, sum#72, sum#73] +Arguments: hashpartitioning(cp_catalog_page_id#65, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(40) HashAggregate [codegen id : 8] +Input [5]: [cp_catalog_page_id#65, sum#70, sum#71, sum#72, sum#73] +Keys [1]: [cp_catalog_page_id#65] +Functions [4]: [sum(UnscaledValue(sales_price#49)), sum(UnscaledValue(return_amt#51)), sum(UnscaledValue(profit#50)), sum(UnscaledValue(net_loss#52))] +Aggregate Attributes [4]: [sum(UnscaledValue(sales_price#49))#74, sum(UnscaledValue(return_amt#51))#75, sum(UnscaledValue(profit#50))#76, sum(UnscaledValue(net_loss#52))#77] +Results [5]: [MakeDecimal(sum(UnscaledValue(sales_price#49))#74,17,2) AS sales#78, MakeDecimal(sum(UnscaledValue(return_amt#51))#75,17,2) AS returns#79, (MakeDecimal(sum(UnscaledValue(profit#50))#76,17,2) - MakeDecimal(sum(UnscaledValue(net_loss#52))#77,17,2)) AS profit#80, catalog channel AS channel#81, concat(catalog_page, cp_catalog_page_id#65) AS id#82] + +(41) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_web_site_sk#83, ws_ext_sales_price#84, ws_net_profit#85, ws_sold_date_sk#86] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#86), dynamicpruningexpression(ws_sold_date_sk#86 IN dynamicpruning#87)] +PushedFilters: [IsNotNull(ws_web_site_sk)] +ReadSchema: struct + +(42) CometFilter +Input [4]: [ws_web_site_sk#83, ws_ext_sales_price#84, ws_net_profit#85, ws_sold_date_sk#86] +Condition : isnotnull(ws_web_site_sk#83) + +(43) CometProject +Input [4]: [ws_web_site_sk#83, ws_ext_sales_price#84, ws_net_profit#85, ws_sold_date_sk#86] +Arguments: [wsr_web_site_sk#88, date_sk#89, sales_price#90, profit#91, return_amt#92, net_loss#93], [ws_web_site_sk#83 AS wsr_web_site_sk#88, ws_sold_date_sk#86 AS date_sk#89, ws_ext_sales_price#84 AS sales_price#90, ws_net_profit#85 AS profit#91, 0.00 AS return_amt#92, 0.00 AS net_loss#93] + +(44) Scan parquet spark_catalog.default.web_returns +Output [5]: [wr_item_sk#94, wr_order_number#95, wr_return_amt#96, wr_net_loss#97, wr_returned_date_sk#98] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(wr_returned_date_sk#98), dynamicpruningexpression(wr_returned_date_sk#98 IN dynamicpruning#87)] +ReadSchema: struct + +(45) CometBroadcastExchange +Input [5]: [wr_item_sk#94, wr_order_number#95, wr_return_amt#96, wr_net_loss#97, wr_returned_date_sk#98] +Arguments: [wr_item_sk#94, wr_order_number#95, wr_return_amt#96, wr_net_loss#97, wr_returned_date_sk#98] + +(46) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101, ws_sold_date_sk#102] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_sales] +PushedFilters: [IsNotNull(ws_item_sk), IsNotNull(ws_order_number), IsNotNull(ws_web_site_sk)] +ReadSchema: struct + +(47) CometFilter +Input [4]: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101, ws_sold_date_sk#102] +Condition : ((isnotnull(ws_item_sk#99) AND isnotnull(ws_order_number#101)) AND isnotnull(ws_web_site_sk#100)) + +(48) CometProject +Input [4]: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101, ws_sold_date_sk#102] +Arguments: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101], [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101] + +(49) CometBroadcastHashJoin +Left output [5]: [wr_item_sk#94, wr_order_number#95, wr_return_amt#96, wr_net_loss#97, wr_returned_date_sk#98] +Right output [3]: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101] +Arguments: [wr_item_sk#94, wr_order_number#95], [ws_item_sk#99, ws_order_number#101], Inner + +(50) CometProject +Input [8]: [wr_item_sk#94, wr_order_number#95, wr_return_amt#96, wr_net_loss#97, wr_returned_date_sk#98, ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101] +Arguments: [wsr_web_site_sk#103, date_sk#104, sales_price#105, profit#106, return_amt#107, net_loss#108], [ws_web_site_sk#100 AS wsr_web_site_sk#103, wr_returned_date_sk#98 AS date_sk#104, 0.00 AS sales_price#105, 0.00 AS profit#106, wr_return_amt#96 AS return_amt#107, wr_net_loss#97 AS net_loss#108] + +(51) CometUnion +Child 0 Input [6]: [wsr_web_site_sk#88, date_sk#89, sales_price#90, profit#91, return_amt#92, net_loss#93] +Child 1 Input [6]: [wsr_web_site_sk#103, date_sk#104, sales_price#105, profit#106, return_amt#107, net_loss#108] + +(52) ColumnarToRow [codegen id : 11] +Input [6]: [wsr_web_site_sk#88, date_sk#89, sales_price#90, profit#91, return_amt#92, net_loss#93] + +(53) ReusedExchange [Reuses operator id: 75] +Output [1]: [d_date_sk#109] + +(54) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [date_sk#89] +Right keys [1]: [d_date_sk#109] +Join type: Inner +Join condition: None + +(55) Project [codegen id : 11] +Output [5]: [wsr_web_site_sk#88, sales_price#90, profit#91, return_amt#92, net_loss#93] +Input [7]: [wsr_web_site_sk#88, date_sk#89, sales_price#90, profit#91, return_amt#92, net_loss#93, d_date_sk#109] + +(56) Scan parquet spark_catalog.default.web_site +Output [2]: [web_site_sk#110, web_site_id#111] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_site] +PushedFilters: [IsNotNull(web_site_sk)] +ReadSchema: struct + +(57) CometFilter +Input [2]: [web_site_sk#110, web_site_id#111] +Condition : isnotnull(web_site_sk#110) + +(58) ColumnarToRow [codegen id : 10] +Input [2]: [web_site_sk#110, web_site_id#111] + +(59) BroadcastExchange +Input [2]: [web_site_sk#110, web_site_id#111] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(60) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [wsr_web_site_sk#88] +Right keys [1]: [web_site_sk#110] +Join type: Inner +Join condition: None + +(61) Project [codegen id : 11] +Output [5]: [sales_price#90, profit#91, return_amt#92, net_loss#93, web_site_id#111] +Input [7]: [wsr_web_site_sk#88, sales_price#90, profit#91, return_amt#92, net_loss#93, web_site_sk#110, web_site_id#111] + +(62) HashAggregate [codegen id : 11] +Input [5]: [sales_price#90, profit#91, return_amt#92, net_loss#93, web_site_id#111] +Keys [1]: [web_site_id#111] +Functions [4]: [partial_sum(UnscaledValue(sales_price#90)), partial_sum(UnscaledValue(return_amt#92)), partial_sum(UnscaledValue(profit#91)), partial_sum(UnscaledValue(net_loss#93))] +Aggregate Attributes [4]: [sum#112, sum#113, sum#114, sum#115] +Results [5]: [web_site_id#111, sum#116, sum#117, sum#118, sum#119] + +(63) Exchange +Input [5]: [web_site_id#111, sum#116, sum#117, sum#118, sum#119] +Arguments: hashpartitioning(web_site_id#111, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(64) HashAggregate [codegen id : 12] +Input [5]: [web_site_id#111, sum#116, sum#117, sum#118, sum#119] +Keys [1]: [web_site_id#111] +Functions [4]: [sum(UnscaledValue(sales_price#90)), sum(UnscaledValue(return_amt#92)), sum(UnscaledValue(profit#91)), sum(UnscaledValue(net_loss#93))] +Aggregate Attributes [4]: [sum(UnscaledValue(sales_price#90))#120, sum(UnscaledValue(return_amt#92))#121, sum(UnscaledValue(profit#91))#122, sum(UnscaledValue(net_loss#93))#123] +Results [5]: [MakeDecimal(sum(UnscaledValue(sales_price#90))#120,17,2) AS sales#124, MakeDecimal(sum(UnscaledValue(return_amt#92))#121,17,2) AS returns#125, (MakeDecimal(sum(UnscaledValue(profit#91))#122,17,2) - MakeDecimal(sum(UnscaledValue(net_loss#93))#123,17,2)) AS profit#126, web channel AS channel#127, concat(web_site, web_site_id#111) AS id#128] + +(65) Union + +(66) Expand [codegen id : 13] +Input [5]: [sales#37, returns#38, profit#39, channel#40, id#41] +Arguments: [[sales#37, returns#38, profit#39, channel#40, id#41, 0], [sales#37, returns#38, profit#39, channel#40, null, 1], [sales#37, returns#38, profit#39, null, null, 3]], [sales#37, returns#38, profit#39, channel#129, id#130, spark_grouping_id#131] + +(67) HashAggregate [codegen id : 13] +Input [6]: [sales#37, returns#38, profit#39, channel#129, id#130, spark_grouping_id#131] +Keys [3]: [channel#129, id#130, spark_grouping_id#131] +Functions [3]: [partial_sum(sales#37), partial_sum(returns#38), partial_sum(profit#39)] +Aggregate Attributes [6]: [sum#132, isEmpty#133, sum#134, isEmpty#135, sum#136, isEmpty#137] +Results [9]: [channel#129, id#130, spark_grouping_id#131, sum#138, isEmpty#139, sum#140, isEmpty#141, sum#142, isEmpty#143] + +(68) Exchange +Input [9]: [channel#129, id#130, spark_grouping_id#131, sum#138, isEmpty#139, sum#140, isEmpty#141, sum#142, isEmpty#143] +Arguments: hashpartitioning(channel#129, id#130, spark_grouping_id#131, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(69) HashAggregate [codegen id : 14] +Input [9]: [channel#129, id#130, spark_grouping_id#131, sum#138, isEmpty#139, sum#140, isEmpty#141, sum#142, isEmpty#143] +Keys [3]: [channel#129, id#130, spark_grouping_id#131] +Functions [3]: [sum(sales#37), sum(returns#38), sum(profit#39)] +Aggregate Attributes [3]: [sum(sales#37)#144, sum(returns#38)#145, sum(profit#39)#146] +Results [5]: [channel#129, id#130, sum(sales#37)#144 AS sales#147, sum(returns#38)#145 AS returns#148, sum(profit#39)#146 AS profit#149] + +(70) TakeOrderedAndProject +Input [5]: [channel#129, id#130, sales#147, returns#148, profit#149] +Arguments: 100, [channel#129 ASC NULLS FIRST, id#130 ASC NULLS FIRST], [channel#129, id#130, sales#147, returns#148, profit#149] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (75) ++- * ColumnarToRow (74) + +- CometProject (73) + +- CometFilter (72) + +- CometScan parquet spark_catalog.default.date_dim (71) + + +(71) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#22, d_date#150] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,2000-08-23), LessThanOrEqual(d_date,2000-09-06), IsNotNull(d_date_sk)] +ReadSchema: struct + +(72) CometFilter +Input [2]: [d_date_sk#22, d_date#150] +Condition : (((isnotnull(d_date#150) AND (d_date#150 >= 2000-08-23)) AND (d_date#150 <= 2000-09-06)) AND isnotnull(d_date_sk#22)) + +(73) CometProject +Input [2]: [d_date_sk#22, d_date#150] +Arguments: [d_date_sk#22], [d_date_sk#22] + +(74) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#22] + +(75) BroadcastExchange +Input [1]: [d_date_sk#22] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + +Subquery:2 Hosting operator id = 4 Hosting Expression = sr_returned_date_sk#15 IN dynamicpruning#5 + +Subquery:3 Hosting operator id = 21 Hosting Expression = cs_sold_date_sk#45 IN dynamicpruning#5 + +Subquery:4 Hosting operator id = 24 Hosting Expression = cr_returned_date_sk#56 IN dynamicpruning#5 + +Subquery:5 Hosting operator id = 41 Hosting Expression = ws_sold_date_sk#86 IN dynamicpruning#5 + +Subquery:6 Hosting operator id = 44 Hosting Expression = wr_returned_date_sk#98 IN dynamicpruning#5 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q5/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q5/simplified.txt new file mode 100644 index 0000000000..3d539d5917 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q5/simplified.txt @@ -0,0 +1,111 @@ +TakeOrderedAndProject [channel,id,sales,returns,profit] + WholeStageCodegen (14) + HashAggregate [channel,id,spark_grouping_id,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [channel,id,spark_grouping_id] #1 + WholeStageCodegen (13) + HashAggregate [channel,id,spark_grouping_id,sales,returns,profit] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + Expand [sales,returns,profit,channel,id] + InputAdapter + Union + WholeStageCodegen (4) + HashAggregate [s_store_id,sum,sum,sum,sum] [sum(UnscaledValue(sales_price)),sum(UnscaledValue(return_amt)),sum(UnscaledValue(profit)),sum(UnscaledValue(net_loss)),sales,returns,profit,channel,id,sum,sum,sum,sum] + InputAdapter + Exchange [s_store_id] #2 + WholeStageCodegen (3) + HashAggregate [s_store_id,sales_price,return_amt,profit,net_loss] [sum,sum,sum,sum,sum,sum,sum,sum] + Project [sales_price,profit,return_amt,net_loss,s_store_id] + BroadcastHashJoin [store_sk,s_store_sk] + Project [store_sk,sales_price,profit,return_amt,net_loss] + BroadcastHashJoin [date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometUnion + CometProject [ss_store_sk,ss_sold_date_sk,ss_ext_sales_price,ss_net_profit] [store_sk,date_sk,sales_price,profit,return_amt,net_loss] + CometFilter [ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_store_sk,ss_ext_sales_price,ss_net_profit,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + CometProject [sr_store_sk,sr_returned_date_sk,sr_return_amt,sr_net_loss] [store_sk,date_sk,sales_price,profit,return_amt,net_loss] + CometFilter [sr_store_sk] + CometScan parquet spark_catalog.default.store_returns [sr_store_sk,sr_return_amt,sr_net_loss,sr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_id] + WholeStageCodegen (8) + HashAggregate [cp_catalog_page_id,sum,sum,sum,sum] [sum(UnscaledValue(sales_price)),sum(UnscaledValue(return_amt)),sum(UnscaledValue(profit)),sum(UnscaledValue(net_loss)),sales,returns,profit,channel,id,sum,sum,sum,sum] + InputAdapter + Exchange [cp_catalog_page_id] #5 + WholeStageCodegen (7) + HashAggregate [cp_catalog_page_id,sales_price,return_amt,profit,net_loss] [sum,sum,sum,sum,sum,sum,sum,sum] + Project [sales_price,profit,return_amt,net_loss,cp_catalog_page_id] + BroadcastHashJoin [page_sk,cp_catalog_page_sk] + Project [page_sk,sales_price,profit,return_amt,net_loss] + BroadcastHashJoin [date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometUnion + CometProject [cs_catalog_page_sk,cs_sold_date_sk,cs_ext_sales_price,cs_net_profit] [page_sk,date_sk,sales_price,profit,return_amt,net_loss] + CometFilter [cs_catalog_page_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_catalog_page_sk,cs_ext_sales_price,cs_net_profit,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + CometProject [cr_catalog_page_sk,cr_returned_date_sk,cr_return_amount,cr_net_loss] [page_sk,date_sk,sales_price,profit,return_amt,net_loss] + CometFilter [cr_catalog_page_sk] + CometScan parquet spark_catalog.default.catalog_returns [cr_catalog_page_sk,cr_return_amount,cr_net_loss,cr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (6) + ColumnarToRow + InputAdapter + CometFilter [cp_catalog_page_sk] + CometScan parquet spark_catalog.default.catalog_page [cp_catalog_page_sk,cp_catalog_page_id] + WholeStageCodegen (12) + HashAggregate [web_site_id,sum,sum,sum,sum] [sum(UnscaledValue(sales_price)),sum(UnscaledValue(return_amt)),sum(UnscaledValue(profit)),sum(UnscaledValue(net_loss)),sales,returns,profit,channel,id,sum,sum,sum,sum] + InputAdapter + Exchange [web_site_id] #7 + WholeStageCodegen (11) + HashAggregate [web_site_id,sales_price,return_amt,profit,net_loss] [sum,sum,sum,sum,sum,sum,sum,sum] + Project [sales_price,profit,return_amt,net_loss,web_site_id] + BroadcastHashJoin [wsr_web_site_sk,web_site_sk] + Project [wsr_web_site_sk,sales_price,profit,return_amt,net_loss] + BroadcastHashJoin [date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometUnion + CometProject [ws_web_site_sk,ws_sold_date_sk,ws_ext_sales_price,ws_net_profit] [wsr_web_site_sk,date_sk,sales_price,profit,return_amt,net_loss] + CometFilter [ws_web_site_sk] + CometScan parquet spark_catalog.default.web_sales [ws_web_site_sk,ws_ext_sales_price,ws_net_profit,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + CometProject [ws_web_site_sk,wr_returned_date_sk,wr_return_amt,wr_net_loss] [wsr_web_site_sk,date_sk,sales_price,profit,return_amt,net_loss] + CometBroadcastHashJoin [wr_item_sk,wr_order_number,ws_item_sk,ws_order_number] + CometBroadcastExchange #8 + CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_order_number,wr_return_amt,wr_net_loss,wr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + CometProject [ws_item_sk,ws_web_site_sk,ws_order_number] + CometFilter [ws_item_sk,ws_order_number,ws_web_site_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_web_site_sk,ws_order_number,ws_sold_date_sk] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #9 + WholeStageCodegen (10) + ColumnarToRow + InputAdapter + CometFilter [web_site_sk] + CometScan parquet spark_catalog.default.web_site [web_site_sk,web_site_id] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q50/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q50/explain.txt new file mode 100644 index 0000000000..0182e0ac1e --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q50/explain.txt @@ -0,0 +1,199 @@ +== Physical Plan == +TakeOrderedAndProject (28) ++- * HashAggregate (27) + +- Exchange (26) + +- * HashAggregate (25) + +- * Project (24) + +- * BroadcastHashJoin Inner BuildRight (23) + :- * Project (21) + : +- * BroadcastHashJoin Inner BuildRight (20) + : :- * Project (15) + : : +- * BroadcastHashJoin Inner BuildRight (14) + : : :- * Project (9) + : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- BroadcastExchange (7) + : : : +- * ColumnarToRow (6) + : : : +- CometFilter (5) + : : : +- CometScan parquet spark_catalog.default.store_returns (4) + : : +- BroadcastExchange (13) + : : +- * ColumnarToRow (12) + : : +- CometFilter (11) + : : +- CometScan parquet spark_catalog.default.store (10) + : +- BroadcastExchange (19) + : +- * ColumnarToRow (18) + : +- CometFilter (17) + : +- CometScan parquet spark_catalog.default.date_dim (16) + +- ReusedExchange (22) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#5)] +PushedFilters: [IsNotNull(ss_ticket_number), IsNotNull(ss_item_sk), IsNotNull(ss_customer_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(2) CometFilter +Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5] +Condition : (((isnotnull(ss_ticket_number#4) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_customer_sk#2)) AND isnotnull(ss_store_sk#3)) + +(3) ColumnarToRow [codegen id : 5] +Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5] + +(4) Scan parquet spark_catalog.default.store_returns +Output [4]: [sr_item_sk#6, sr_customer_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(sr_returned_date_sk#9), dynamicpruningexpression(sr_returned_date_sk#9 IN dynamicpruning#10)] +PushedFilters: [IsNotNull(sr_ticket_number), IsNotNull(sr_item_sk), IsNotNull(sr_customer_sk)] +ReadSchema: struct + +(5) CometFilter +Input [4]: [sr_item_sk#6, sr_customer_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] +Condition : ((isnotnull(sr_ticket_number#8) AND isnotnull(sr_item_sk#6)) AND isnotnull(sr_customer_sk#7)) + +(6) ColumnarToRow [codegen id : 1] +Input [4]: [sr_item_sk#6, sr_customer_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] + +(7) BroadcastExchange +Input [4]: [sr_item_sk#6, sr_customer_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] +Arguments: HashedRelationBroadcastMode(List(input[2, int, false], input[0, int, false], input[1, int, false]),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 5] +Left keys [3]: [ss_ticket_number#4, ss_item_sk#1, ss_customer_sk#2] +Right keys [3]: [sr_ticket_number#8, sr_item_sk#6, sr_customer_sk#7] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 5] +Output [3]: [ss_store_sk#3, ss_sold_date_sk#5, sr_returned_date_sk#9] +Input [9]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5, sr_item_sk#6, sr_customer_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] + +(10) Scan parquet spark_catalog.default.store +Output [11]: [s_store_sk#11, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(11) CometFilter +Input [11]: [s_store_sk#11, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21] +Condition : isnotnull(s_store_sk#11) + +(12) ColumnarToRow [codegen id : 2] +Input [11]: [s_store_sk#11, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21] + +(13) BroadcastExchange +Input [11]: [s_store_sk#11, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(14) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_store_sk#3] +Right keys [1]: [s_store_sk#11] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 5] +Output [12]: [ss_sold_date_sk#5, sr_returned_date_sk#9, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21] +Input [14]: [ss_store_sk#3, ss_sold_date_sk#5, sr_returned_date_sk#9, s_store_sk#11, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21] + +(16) Scan parquet spark_catalog.default.date_dim +Output [1]: [d_date_sk#22] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date_sk)] +ReadSchema: struct + +(17) CometFilter +Input [1]: [d_date_sk#22] +Condition : isnotnull(d_date_sk#22) + +(18) ColumnarToRow [codegen id : 3] +Input [1]: [d_date_sk#22] + +(19) BroadcastExchange +Input [1]: [d_date_sk#22] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(20) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_sold_date_sk#5] +Right keys [1]: [d_date_sk#22] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 5] +Output [12]: [ss_sold_date_sk#5, sr_returned_date_sk#9, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21] +Input [13]: [ss_sold_date_sk#5, sr_returned_date_sk#9, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21, d_date_sk#22] + +(22) ReusedExchange [Reuses operator id: 33] +Output [1]: [d_date_sk#23] + +(23) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [sr_returned_date_sk#9] +Right keys [1]: [d_date_sk#23] +Join type: Inner +Join condition: None + +(24) Project [codegen id : 5] +Output [12]: [ss_sold_date_sk#5, sr_returned_date_sk#9, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21] +Input [13]: [ss_sold_date_sk#5, sr_returned_date_sk#9, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21, d_date_sk#23] + +(25) HashAggregate [codegen id : 5] +Input [12]: [ss_sold_date_sk#5, sr_returned_date_sk#9, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21] +Keys [10]: [s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21] +Functions [5]: [partial_sum(CASE WHEN ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 30) THEN 1 ELSE 0 END), partial_sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 30) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 60)) THEN 1 ELSE 0 END), partial_sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 60) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 90)) THEN 1 ELSE 0 END), partial_sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 90) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 120)) THEN 1 ELSE 0 END), partial_sum(CASE WHEN ((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 120) THEN 1 ELSE 0 END)] +Aggregate Attributes [5]: [sum#24, sum#25, sum#26, sum#27, sum#28] +Results [15]: [s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21, sum#29, sum#30, sum#31, sum#32, sum#33] + +(26) Exchange +Input [15]: [s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21, sum#29, sum#30, sum#31, sum#32, sum#33] +Arguments: hashpartitioning(s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(27) HashAggregate [codegen id : 6] +Input [15]: [s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21, sum#29, sum#30, sum#31, sum#32, sum#33] +Keys [10]: [s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21] +Functions [5]: [sum(CASE WHEN ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 30) THEN 1 ELSE 0 END), sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 30) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 60)) THEN 1 ELSE 0 END), sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 60) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 90)) THEN 1 ELSE 0 END), sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 90) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 120)) THEN 1 ELSE 0 END), sum(CASE WHEN ((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 120) THEN 1 ELSE 0 END)] +Aggregate Attributes [5]: [sum(CASE WHEN ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 30) THEN 1 ELSE 0 END)#34, sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 30) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 60)) THEN 1 ELSE 0 END)#35, sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 60) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 90)) THEN 1 ELSE 0 END)#36, sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 90) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 120)) THEN 1 ELSE 0 END)#37, sum(CASE WHEN ((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 120) THEN 1 ELSE 0 END)#38] +Results [15]: [s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21, sum(CASE WHEN ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 30) THEN 1 ELSE 0 END)#34 AS 30 days #39, sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 30) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 60)) THEN 1 ELSE 0 END)#35 AS 31 - 60 days #40, sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 60) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 90)) THEN 1 ELSE 0 END)#36 AS 61 - 90 days #41, sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 90) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 120)) THEN 1 ELSE 0 END)#37 AS 91 - 120 days #42, sum(CASE WHEN ((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 120) THEN 1 ELSE 0 END)#38 AS >120 days #43] + +(28) TakeOrderedAndProject +Input [15]: [s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21, 30 days #39, 31 - 60 days #40, 61 - 90 days #41, 91 - 120 days #42, >120 days #43] +Arguments: 100, [s_store_name#12 ASC NULLS FIRST, s_company_id#13 ASC NULLS FIRST, s_street_number#14 ASC NULLS FIRST, s_street_name#15 ASC NULLS FIRST, s_street_type#16 ASC NULLS FIRST, s_suite_number#17 ASC NULLS FIRST, s_city#18 ASC NULLS FIRST, s_county#19 ASC NULLS FIRST, s_state#20 ASC NULLS FIRST, s_zip#21 ASC NULLS FIRST], [s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21, 30 days #39, 31 - 60 days #40, 61 - 90 days #41, 91 - 120 days #42, >120 days #43] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = sr_returned_date_sk#9 IN dynamicpruning#10 +BroadcastExchange (33) ++- * ColumnarToRow (32) + +- CometProject (31) + +- CometFilter (30) + +- CometScan parquet spark_catalog.default.date_dim (29) + + +(29) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#23, d_year#44, d_moy#45] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2001), EqualTo(d_moy,8), IsNotNull(d_date_sk)] +ReadSchema: struct + +(30) CometFilter +Input [3]: [d_date_sk#23, d_year#44, d_moy#45] +Condition : ((((isnotnull(d_year#44) AND isnotnull(d_moy#45)) AND (d_year#44 = 2001)) AND (d_moy#45 = 8)) AND isnotnull(d_date_sk#23)) + +(31) CometProject +Input [3]: [d_date_sk#23, d_year#44, d_moy#45] +Arguments: [d_date_sk#23], [d_date_sk#23] + +(32) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#23] + +(33) BroadcastExchange +Input [1]: [d_date_sk#23] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q50/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q50/simplified.txt new file mode 100644 index 0000000000..dfdcaf4975 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q50/simplified.txt @@ -0,0 +1,50 @@ +TakeOrderedAndProject [s_store_name,s_company_id,s_street_number,s_street_name,s_street_type,s_suite_number,s_city,s_county,s_state,s_zip,30 days ,31 - 60 days ,61 - 90 days ,91 - 120 days ,>120 days ] + WholeStageCodegen (6) + HashAggregate [s_store_name,s_company_id,s_street_number,s_street_name,s_street_type,s_suite_number,s_city,s_county,s_state,s_zip,sum,sum,sum,sum,sum] [sum(CASE WHEN ((sr_returned_date_sk - ss_sold_date_sk) <= 30) THEN 1 ELSE 0 END),sum(CASE WHEN (((sr_returned_date_sk - ss_sold_date_sk) > 30) AND ((sr_returned_date_sk - ss_sold_date_sk) <= 60)) THEN 1 ELSE 0 END),sum(CASE WHEN (((sr_returned_date_sk - ss_sold_date_sk) > 60) AND ((sr_returned_date_sk - ss_sold_date_sk) <= 90)) THEN 1 ELSE 0 END),sum(CASE WHEN (((sr_returned_date_sk - ss_sold_date_sk) > 90) AND ((sr_returned_date_sk - ss_sold_date_sk) <= 120)) THEN 1 ELSE 0 END),sum(CASE WHEN ((sr_returned_date_sk - ss_sold_date_sk) > 120) THEN 1 ELSE 0 END),30 days ,31 - 60 days ,61 - 90 days ,91 - 120 days ,>120 days ,sum,sum,sum,sum,sum] + InputAdapter + Exchange [s_store_name,s_company_id,s_street_number,s_street_name,s_street_type,s_suite_number,s_city,s_county,s_state,s_zip] #1 + WholeStageCodegen (5) + HashAggregate [s_store_name,s_company_id,s_street_number,s_street_name,s_street_type,s_suite_number,s_city,s_county,s_state,s_zip,sr_returned_date_sk,ss_sold_date_sk] [sum,sum,sum,sum,sum,sum,sum,sum,sum,sum] + Project [ss_sold_date_sk,sr_returned_date_sk,s_store_name,s_company_id,s_street_number,s_street_name,s_street_type,s_suite_number,s_city,s_county,s_state,s_zip] + BroadcastHashJoin [sr_returned_date_sk,d_date_sk] + Project [ss_sold_date_sk,sr_returned_date_sk,s_store_name,s_company_id,s_street_number,s_street_name,s_street_type,s_suite_number,s_city,s_county,s_state,s_zip] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_sold_date_sk,sr_returned_date_sk,s_store_name,s_company_id,s_street_number,s_street_name,s_street_type,s_suite_number,s_city,s_county,s_state,s_zip] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_store_sk,ss_sold_date_sk,sr_returned_date_sk] + BroadcastHashJoin [ss_ticket_number,ss_item_sk,ss_customer_sk,sr_ticket_number,sr_item_sk,sr_customer_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_ticket_number,ss_item_sk,ss_customer_sk,ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_sold_date_sk] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [sr_ticket_number,sr_item_sk,sr_customer_sk] + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_customer_sk,sr_ticket_number,sr_returned_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_moy,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name,s_company_id,s_street_number,s_street_name,s_street_type,s_suite_number,s_city,s_county,s_state,s_zip] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometFilter [d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk] + InputAdapter + ReusedExchange [d_date_sk] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q51/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q51/explain.txt new file mode 100644 index 0000000000..2613551f0c --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q51/explain.txt @@ -0,0 +1,245 @@ +== Physical Plan == +TakeOrderedAndProject (37) ++- * Filter (36) + +- Window (35) + +- * Sort (34) + +- Exchange (33) + +- * Project (32) + +- * SortMergeJoin FullOuter (31) + :- * Sort (15) + : +- Exchange (14) + : +- * Project (13) + : +- Window (12) + : +- * Sort (11) + : +- Exchange (10) + : +- * HashAggregate (9) + : +- Exchange (8) + : +- * HashAggregate (7) + : +- * Project (6) + : +- * BroadcastHashJoin Inner BuildRight (5) + : :- * ColumnarToRow (3) + : : +- CometFilter (2) + : : +- CometScan parquet spark_catalog.default.web_sales (1) + : +- ReusedExchange (4) + +- * Sort (30) + +- Exchange (29) + +- * Project (28) + +- Window (27) + +- * Sort (26) + +- Exchange (25) + +- * HashAggregate (24) + +- Exchange (23) + +- * HashAggregate (22) + +- * Project (21) + +- * BroadcastHashJoin Inner BuildRight (20) + :- * ColumnarToRow (18) + : +- CometFilter (17) + : +- CometScan parquet spark_catalog.default.store_sales (16) + +- ReusedExchange (19) + + +(1) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_item_sk#1, ws_sales_price#2, ws_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#3), dynamicpruningexpression(ws_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [ws_item_sk#1, ws_sales_price#2, ws_sold_date_sk#3] +Condition : isnotnull(ws_item_sk#1) + +(3) ColumnarToRow [codegen id : 2] +Input [3]: [ws_item_sk#1, ws_sales_price#2, ws_sold_date_sk#3] + +(4) ReusedExchange [Reuses operator id: 42] +Output [2]: [d_date_sk#5, d_date#6] + +(5) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [ws_sold_date_sk#3] +Right keys [1]: [d_date_sk#5] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 2] +Output [3]: [ws_item_sk#1, ws_sales_price#2, d_date#6] +Input [5]: [ws_item_sk#1, ws_sales_price#2, ws_sold_date_sk#3, d_date_sk#5, d_date#6] + +(7) HashAggregate [codegen id : 2] +Input [3]: [ws_item_sk#1, ws_sales_price#2, d_date#6] +Keys [2]: [ws_item_sk#1, d_date#6] +Functions [1]: [partial_sum(UnscaledValue(ws_sales_price#2))] +Aggregate Attributes [1]: [sum#7] +Results [3]: [ws_item_sk#1, d_date#6, sum#8] + +(8) Exchange +Input [3]: [ws_item_sk#1, d_date#6, sum#8] +Arguments: hashpartitioning(ws_item_sk#1, d_date#6, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(9) HashAggregate [codegen id : 3] +Input [3]: [ws_item_sk#1, d_date#6, sum#8] +Keys [2]: [ws_item_sk#1, d_date#6] +Functions [1]: [sum(UnscaledValue(ws_sales_price#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_sales_price#2))#9] +Results [4]: [ws_item_sk#1 AS item_sk#10, d_date#6, MakeDecimal(sum(UnscaledValue(ws_sales_price#2))#9,17,2) AS _w0#11, ws_item_sk#1] + +(10) Exchange +Input [4]: [item_sk#10, d_date#6, _w0#11, ws_item_sk#1] +Arguments: hashpartitioning(ws_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(11) Sort [codegen id : 4] +Input [4]: [item_sk#10, d_date#6, _w0#11, ws_item_sk#1] +Arguments: [ws_item_sk#1 ASC NULLS FIRST, d_date#6 ASC NULLS FIRST], false, 0 + +(12) Window +Input [4]: [item_sk#10, d_date#6, _w0#11, ws_item_sk#1] +Arguments: [sum(_w0#11) windowspecdefinition(ws_item_sk#1, d_date#6 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS cume_sales#12], [ws_item_sk#1], [d_date#6 ASC NULLS FIRST] + +(13) Project [codegen id : 5] +Output [3]: [item_sk#10, d_date#6, cume_sales#12] +Input [5]: [item_sk#10, d_date#6, _w0#11, ws_item_sk#1, cume_sales#12] + +(14) Exchange +Input [3]: [item_sk#10, d_date#6, cume_sales#12] +Arguments: hashpartitioning(item_sk#10, d_date#6, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(15) Sort [codegen id : 6] +Input [3]: [item_sk#10, d_date#6, cume_sales#12] +Arguments: [item_sk#10 ASC NULLS FIRST, d_date#6 ASC NULLS FIRST], false, 0 + +(16) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_item_sk#13, ss_sales_price#14, ss_sold_date_sk#15] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#15), dynamicpruningexpression(ss_sold_date_sk#15 IN dynamicpruning#16)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(17) CometFilter +Input [3]: [ss_item_sk#13, ss_sales_price#14, ss_sold_date_sk#15] +Condition : isnotnull(ss_item_sk#13) + +(18) ColumnarToRow [codegen id : 8] +Input [3]: [ss_item_sk#13, ss_sales_price#14, ss_sold_date_sk#15] + +(19) ReusedExchange [Reuses operator id: 42] +Output [2]: [d_date_sk#17, d_date#18] + +(20) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_sold_date_sk#15] +Right keys [1]: [d_date_sk#17] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 8] +Output [3]: [ss_item_sk#13, ss_sales_price#14, d_date#18] +Input [5]: [ss_item_sk#13, ss_sales_price#14, ss_sold_date_sk#15, d_date_sk#17, d_date#18] + +(22) HashAggregate [codegen id : 8] +Input [3]: [ss_item_sk#13, ss_sales_price#14, d_date#18] +Keys [2]: [ss_item_sk#13, d_date#18] +Functions [1]: [partial_sum(UnscaledValue(ss_sales_price#14))] +Aggregate Attributes [1]: [sum#19] +Results [3]: [ss_item_sk#13, d_date#18, sum#20] + +(23) Exchange +Input [3]: [ss_item_sk#13, d_date#18, sum#20] +Arguments: hashpartitioning(ss_item_sk#13, d_date#18, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(24) HashAggregate [codegen id : 9] +Input [3]: [ss_item_sk#13, d_date#18, sum#20] +Keys [2]: [ss_item_sk#13, d_date#18] +Functions [1]: [sum(UnscaledValue(ss_sales_price#14))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_sales_price#14))#21] +Results [4]: [ss_item_sk#13 AS item_sk#22, d_date#18, MakeDecimal(sum(UnscaledValue(ss_sales_price#14))#21,17,2) AS _w0#23, ss_item_sk#13] + +(25) Exchange +Input [4]: [item_sk#22, d_date#18, _w0#23, ss_item_sk#13] +Arguments: hashpartitioning(ss_item_sk#13, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(26) Sort [codegen id : 10] +Input [4]: [item_sk#22, d_date#18, _w0#23, ss_item_sk#13] +Arguments: [ss_item_sk#13 ASC NULLS FIRST, d_date#18 ASC NULLS FIRST], false, 0 + +(27) Window +Input [4]: [item_sk#22, d_date#18, _w0#23, ss_item_sk#13] +Arguments: [sum(_w0#23) windowspecdefinition(ss_item_sk#13, d_date#18 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS cume_sales#24], [ss_item_sk#13], [d_date#18 ASC NULLS FIRST] + +(28) Project [codegen id : 11] +Output [3]: [item_sk#22, d_date#18, cume_sales#24] +Input [5]: [item_sk#22, d_date#18, _w0#23, ss_item_sk#13, cume_sales#24] + +(29) Exchange +Input [3]: [item_sk#22, d_date#18, cume_sales#24] +Arguments: hashpartitioning(item_sk#22, d_date#18, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(30) Sort [codegen id : 12] +Input [3]: [item_sk#22, d_date#18, cume_sales#24] +Arguments: [item_sk#22 ASC NULLS FIRST, d_date#18 ASC NULLS FIRST], false, 0 + +(31) SortMergeJoin [codegen id : 13] +Left keys [2]: [item_sk#10, d_date#6] +Right keys [2]: [item_sk#22, d_date#18] +Join type: FullOuter +Join condition: None + +(32) Project [codegen id : 13] +Output [4]: [CASE WHEN isnotnull(item_sk#10) THEN item_sk#10 ELSE item_sk#22 END AS item_sk#25, CASE WHEN isnotnull(d_date#6) THEN d_date#6 ELSE d_date#18 END AS d_date#26, cume_sales#12 AS web_sales#27, cume_sales#24 AS store_sales#28] +Input [6]: [item_sk#10, d_date#6, cume_sales#12, item_sk#22, d_date#18, cume_sales#24] + +(33) Exchange +Input [4]: [item_sk#25, d_date#26, web_sales#27, store_sales#28] +Arguments: hashpartitioning(item_sk#25, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(34) Sort [codegen id : 14] +Input [4]: [item_sk#25, d_date#26, web_sales#27, store_sales#28] +Arguments: [item_sk#25 ASC NULLS FIRST, d_date#26 ASC NULLS FIRST], false, 0 + +(35) Window +Input [4]: [item_sk#25, d_date#26, web_sales#27, store_sales#28] +Arguments: [max(web_sales#27) windowspecdefinition(item_sk#25, d_date#26 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS web_cumulative#29, max(store_sales#28) windowspecdefinition(item_sk#25, d_date#26 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS store_cumulative#30], [item_sk#25], [d_date#26 ASC NULLS FIRST] + +(36) Filter [codegen id : 15] +Input [6]: [item_sk#25, d_date#26, web_sales#27, store_sales#28, web_cumulative#29, store_cumulative#30] +Condition : ((isnotnull(web_cumulative#29) AND isnotnull(store_cumulative#30)) AND (web_cumulative#29 > store_cumulative#30)) + +(37) TakeOrderedAndProject +Input [6]: [item_sk#25, d_date#26, web_sales#27, store_sales#28, web_cumulative#29, store_cumulative#30] +Arguments: 100, [item_sk#25 ASC NULLS FIRST, d_date#26 ASC NULLS FIRST], [item_sk#25, d_date#26, web_sales#27, store_sales#28, web_cumulative#29, store_cumulative#30] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (42) ++- * ColumnarToRow (41) + +- CometProject (40) + +- CometFilter (39) + +- CometScan parquet spark_catalog.default.date_dim (38) + + +(38) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#5, d_date#6, d_month_seq#31] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)] +ReadSchema: struct + +(39) CometFilter +Input [3]: [d_date_sk#5, d_date#6, d_month_seq#31] +Condition : (((isnotnull(d_month_seq#31) AND (d_month_seq#31 >= 1200)) AND (d_month_seq#31 <= 1211)) AND isnotnull(d_date_sk#5)) + +(40) CometProject +Input [3]: [d_date_sk#5, d_date#6, d_month_seq#31] +Arguments: [d_date_sk#5, d_date#6], [d_date_sk#5, d_date#6] + +(41) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#5, d_date#6] + +(42) BroadcastExchange +Input [2]: [d_date_sk#5, d_date#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + +Subquery:2 Hosting operator id = 16 Hosting Expression = ss_sold_date_sk#15 IN dynamicpruning#4 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q51/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q51/simplified.txt new file mode 100644 index 0000000000..181cd1b98c --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q51/simplified.txt @@ -0,0 +1,75 @@ +TakeOrderedAndProject [item_sk,d_date,web_sales,store_sales,web_cumulative,store_cumulative] + WholeStageCodegen (15) + Filter [web_cumulative,store_cumulative] + InputAdapter + Window [web_sales,item_sk,d_date,store_sales] + WholeStageCodegen (14) + Sort [item_sk,d_date] + InputAdapter + Exchange [item_sk] #1 + WholeStageCodegen (13) + Project [item_sk,item_sk,d_date,d_date,cume_sales,cume_sales] + SortMergeJoin [item_sk,d_date,item_sk,d_date] + InputAdapter + WholeStageCodegen (6) + Sort [item_sk,d_date] + InputAdapter + Exchange [item_sk,d_date] #2 + WholeStageCodegen (5) + Project [item_sk,d_date,cume_sales] + InputAdapter + Window [_w0,ws_item_sk,d_date] + WholeStageCodegen (4) + Sort [ws_item_sk,d_date] + InputAdapter + Exchange [ws_item_sk] #3 + WholeStageCodegen (3) + HashAggregate [ws_item_sk,d_date,sum] [sum(UnscaledValue(ws_sales_price)),item_sk,_w0,sum] + InputAdapter + Exchange [ws_item_sk,d_date] #4 + WholeStageCodegen (2) + HashAggregate [ws_item_sk,d_date,ws_sales_price] [sum,sum] + Project [ws_item_sk,ws_sales_price,d_date] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_sales_price,ws_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #5 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_date] + CometFilter [d_month_seq,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date,d_month_seq] + InputAdapter + ReusedExchange [d_date_sk,d_date] #5 + InputAdapter + WholeStageCodegen (12) + Sort [item_sk,d_date] + InputAdapter + Exchange [item_sk,d_date] #6 + WholeStageCodegen (11) + Project [item_sk,d_date,cume_sales] + InputAdapter + Window [_w0,ss_item_sk,d_date] + WholeStageCodegen (10) + Sort [ss_item_sk,d_date] + InputAdapter + Exchange [ss_item_sk] #7 + WholeStageCodegen (9) + HashAggregate [ss_item_sk,d_date,sum] [sum(UnscaledValue(ss_sales_price)),item_sk,_w0,sum] + InputAdapter + Exchange [ss_item_sk,d_date] #8 + WholeStageCodegen (8) + HashAggregate [ss_item_sk,d_date,ss_sales_price] [sum,sum] + Project [ss_item_sk,ss_sales_price,d_date] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_sales_price,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk,d_date] #5 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q52/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q52/explain.txt new file mode 100644 index 0000000000..3d5317eb0c --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q52/explain.txt @@ -0,0 +1,125 @@ +== Physical Plan == +TakeOrderedAndProject (21) ++- * HashAggregate (20) + +- Exchange (19) + +- * HashAggregate (18) + +- * Project (17) + +- * BroadcastHashJoin Inner BuildRight (16) + :- * Project (10) + : +- * BroadcastHashJoin Inner BuildRight (9) + : :- * ColumnarToRow (4) + : : +- CometProject (3) + : : +- CometFilter (2) + : : +- CometScan parquet spark_catalog.default.date_dim (1) + : +- BroadcastExchange (8) + : +- * ColumnarToRow (7) + : +- CometFilter (6) + : +- CometScan parquet spark_catalog.default.store_sales (5) + +- BroadcastExchange (15) + +- * ColumnarToRow (14) + +- CometProject (13) + +- CometFilter (12) + +- CometScan parquet spark_catalog.default.item (11) + + +(1) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#1, d_year#2, d_moy#3] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), EqualTo(d_moy,11), EqualTo(d_year,2000), IsNotNull(d_date_sk)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [d_date_sk#1, d_year#2, d_moy#3] +Condition : ((((isnotnull(d_moy#3) AND isnotnull(d_year#2)) AND (d_moy#3 = 11)) AND (d_year#2 = 2000)) AND isnotnull(d_date_sk#1)) + +(3) CometProject +Input [3]: [d_date_sk#1, d_year#2, d_moy#3] +Arguments: [d_date_sk#1, d_year#2], [d_date_sk#1, d_year#2] + +(4) ColumnarToRow [codegen id : 3] +Input [2]: [d_date_sk#1, d_year#2] + +(5) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#6), dynamicpruningexpression(true)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(6) CometFilter +Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] +Condition : isnotnull(ss_item_sk#4) + +(7) ColumnarToRow [codegen id : 1] +Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] + +(8) BroadcastExchange +Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[2, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [d_date_sk#1] +Right keys [1]: [ss_sold_date_sk#6] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 3] +Output [3]: [d_year#2, ss_item_sk#4, ss_ext_sales_price#5] +Input [5]: [d_date_sk#1, d_year#2, ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] + +(11) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#7, i_brand_id#8, i_brand#9, i_manager_id#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_manager_id), EqualTo(i_manager_id,1), IsNotNull(i_item_sk)] +ReadSchema: struct + +(12) CometFilter +Input [4]: [i_item_sk#7, i_brand_id#8, i_brand#9, i_manager_id#10] +Condition : ((isnotnull(i_manager_id#10) AND (i_manager_id#10 = 1)) AND isnotnull(i_item_sk#7)) + +(13) CometProject +Input [4]: [i_item_sk#7, i_brand_id#8, i_brand#9, i_manager_id#10] +Arguments: [i_item_sk#7, i_brand_id#8, i_brand#9], [i_item_sk#7, i_brand_id#8, i_brand#9] + +(14) ColumnarToRow [codegen id : 2] +Input [3]: [i_item_sk#7, i_brand_id#8, i_brand#9] + +(15) BroadcastExchange +Input [3]: [i_item_sk#7, i_brand_id#8, i_brand#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(16) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_item_sk#4] +Right keys [1]: [i_item_sk#7] +Join type: Inner +Join condition: None + +(17) Project [codegen id : 3] +Output [4]: [d_year#2, ss_ext_sales_price#5, i_brand_id#8, i_brand#9] +Input [6]: [d_year#2, ss_item_sk#4, ss_ext_sales_price#5, i_item_sk#7, i_brand_id#8, i_brand#9] + +(18) HashAggregate [codegen id : 3] +Input [4]: [d_year#2, ss_ext_sales_price#5, i_brand_id#8, i_brand#9] +Keys [3]: [d_year#2, i_brand#9, i_brand_id#8] +Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#5))] +Aggregate Attributes [1]: [sum#11] +Results [4]: [d_year#2, i_brand#9, i_brand_id#8, sum#12] + +(19) Exchange +Input [4]: [d_year#2, i_brand#9, i_brand_id#8, sum#12] +Arguments: hashpartitioning(d_year#2, i_brand#9, i_brand_id#8, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(20) HashAggregate [codegen id : 4] +Input [4]: [d_year#2, i_brand#9, i_brand_id#8, sum#12] +Keys [3]: [d_year#2, i_brand#9, i_brand_id#8] +Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#5))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#5))#13] +Results [4]: [d_year#2, i_brand_id#8 AS brand_id#14, i_brand#9 AS brand#15, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#5))#13,17,2) AS ext_price#16] + +(21) TakeOrderedAndProject +Input [4]: [d_year#2, brand_id#14, brand#15, ext_price#16] +Arguments: 100, [d_year#2 ASC NULLS FIRST, ext_price#16 DESC NULLS LAST, brand_id#14 ASC NULLS FIRST], [d_year#2, brand_id#14, brand#15, ext_price#16] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q52/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q52/simplified.txt new file mode 100644 index 0000000000..91fdc2f17d --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q52/simplified.txt @@ -0,0 +1,31 @@ +TakeOrderedAndProject [d_year,ext_price,brand_id,brand] + WholeStageCodegen (4) + HashAggregate [d_year,i_brand,i_brand_id,sum] [sum(UnscaledValue(ss_ext_sales_price)),brand_id,brand,ext_price,sum] + InputAdapter + Exchange [d_year,i_brand,i_brand_id] #1 + WholeStageCodegen (3) + HashAggregate [d_year,i_brand,i_brand_id,ss_ext_sales_price] [sum,sum] + Project [d_year,ss_ext_sales_price,i_brand_id,i_brand] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [d_year,ss_item_sk,ss_ext_sales_price] + BroadcastHashJoin [d_date_sk,ss_sold_date_sk] + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_year] + CometFilter [d_moy,d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ext_sales_price,ss_sold_date_sk] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometProject [i_item_sk,i_brand_id,i_brand] + CometFilter [i_manager_id,i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_brand,i_manager_id] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q53/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q53/explain.txt new file mode 100644 index 0000000000..335dc7fa2b --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q53/explain.txt @@ -0,0 +1,194 @@ +== Physical Plan == +TakeOrderedAndProject (28) ++- * Project (27) + +- * Filter (26) + +- Window (25) + +- * Sort (24) + +- Exchange (23) + +- * HashAggregate (22) + +- Exchange (21) + +- * HashAggregate (20) + +- * Project (19) + +- * BroadcastHashJoin Inner BuildRight (18) + :- * Project (13) + : +- * BroadcastHashJoin Inner BuildRight (12) + : :- * Project (10) + : : +- * BroadcastHashJoin Inner BuildRight (9) + : : :- * ColumnarToRow (4) + : : : +- CometProject (3) + : : : +- CometFilter (2) + : : : +- CometScan parquet spark_catalog.default.item (1) + : : +- BroadcastExchange (8) + : : +- * ColumnarToRow (7) + : : +- CometFilter (6) + : : +- CometScan parquet spark_catalog.default.store_sales (5) + : +- ReusedExchange (11) + +- BroadcastExchange (17) + +- * ColumnarToRow (16) + +- CometFilter (15) + +- CometScan parquet spark_catalog.default.store (14) + + +(1) Scan parquet spark_catalog.default.item +Output [5]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4, i_manufact_id#5] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [Or(And(And(In(i_category, [Books ,Children ,Electronics ]),In(i_class, [personal ,portable ,reference ,self-help ])),In(i_brand, [exportiunivamalg #6 ,scholaramalgamalg #7 ,scholaramalgamalg #8 ,scholaramalgamalg #6 ])),And(And(In(i_category, [Men ,Music ,Women ]),In(i_class, [accessories ,classical ,fragrances ,pants ])),In(i_brand, [amalgimporto #9 ,edu packscholar #9 ,exportiimporto #9 ,importoamalg #9 ]))), IsNotNull(i_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [5]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4, i_manufact_id#5] +Condition : ((((i_category#4 IN (Books ,Children ,Electronics ) AND i_class#3 IN (personal ,portable ,reference ,self-help )) AND i_brand#2 IN (scholaramalgamalg #7 ,scholaramalgamalg #8 ,exportiunivamalg #6 ,scholaramalgamalg #6 )) OR ((i_category#4 IN (Women ,Music ,Men ) AND i_class#3 IN (accessories ,classical ,fragrances ,pants )) AND i_brand#2 IN (amalgimporto #9 ,edu packscholar #9 ,exportiimporto #9 ,importoamalg #9 ))) AND isnotnull(i_item_sk#1)) + +(3) CometProject +Input [5]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4, i_manufact_id#5] +Arguments: [i_item_sk#1, i_manufact_id#5], [i_item_sk#1, i_manufact_id#5] + +(4) ColumnarToRow [codegen id : 4] +Input [2]: [i_item_sk#1, i_manufact_id#5] + +(5) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#10, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#13), dynamicpruningexpression(ss_sold_date_sk#13 IN dynamicpruning#14)] +PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(6) CometFilter +Input [4]: [ss_item_sk#10, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13] +Condition : (isnotnull(ss_item_sk#10) AND isnotnull(ss_store_sk#11)) + +(7) ColumnarToRow [codegen id : 1] +Input [4]: [ss_item_sk#10, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13] + +(8) BroadcastExchange +Input [4]: [ss_item_sk#10, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [i_item_sk#1] +Right keys [1]: [ss_item_sk#10] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 4] +Output [4]: [i_manufact_id#5, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13] +Input [6]: [i_item_sk#1, i_manufact_id#5, ss_item_sk#10, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13] + +(11) ReusedExchange [Reuses operator id: 33] +Output [2]: [d_date_sk#15, d_qoy#16] + +(12) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_date_sk#13] +Right keys [1]: [d_date_sk#15] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 4] +Output [4]: [i_manufact_id#5, ss_store_sk#11, ss_sales_price#12, d_qoy#16] +Input [6]: [i_manufact_id#5, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13, d_date_sk#15, d_qoy#16] + +(14) Scan parquet spark_catalog.default.store +Output [1]: [s_store_sk#17] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(15) CometFilter +Input [1]: [s_store_sk#17] +Condition : isnotnull(s_store_sk#17) + +(16) ColumnarToRow [codegen id : 3] +Input [1]: [s_store_sk#17] + +(17) BroadcastExchange +Input [1]: [s_store_sk#17] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(18) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_store_sk#11] +Right keys [1]: [s_store_sk#17] +Join type: Inner +Join condition: None + +(19) Project [codegen id : 4] +Output [3]: [i_manufact_id#5, ss_sales_price#12, d_qoy#16] +Input [5]: [i_manufact_id#5, ss_store_sk#11, ss_sales_price#12, d_qoy#16, s_store_sk#17] + +(20) HashAggregate [codegen id : 4] +Input [3]: [i_manufact_id#5, ss_sales_price#12, d_qoy#16] +Keys [2]: [i_manufact_id#5, d_qoy#16] +Functions [1]: [partial_sum(UnscaledValue(ss_sales_price#12))] +Aggregate Attributes [1]: [sum#18] +Results [3]: [i_manufact_id#5, d_qoy#16, sum#19] + +(21) Exchange +Input [3]: [i_manufact_id#5, d_qoy#16, sum#19] +Arguments: hashpartitioning(i_manufact_id#5, d_qoy#16, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(22) HashAggregate [codegen id : 5] +Input [3]: [i_manufact_id#5, d_qoy#16, sum#19] +Keys [2]: [i_manufact_id#5, d_qoy#16] +Functions [1]: [sum(UnscaledValue(ss_sales_price#12))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_sales_price#12))#20] +Results [3]: [i_manufact_id#5, MakeDecimal(sum(UnscaledValue(ss_sales_price#12))#20,17,2) AS sum_sales#21, MakeDecimal(sum(UnscaledValue(ss_sales_price#12))#20,17,2) AS _w0#22] + +(23) Exchange +Input [3]: [i_manufact_id#5, sum_sales#21, _w0#22] +Arguments: hashpartitioning(i_manufact_id#5, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(24) Sort [codegen id : 6] +Input [3]: [i_manufact_id#5, sum_sales#21, _w0#22] +Arguments: [i_manufact_id#5 ASC NULLS FIRST], false, 0 + +(25) Window +Input [3]: [i_manufact_id#5, sum_sales#21, _w0#22] +Arguments: [avg(_w0#22) windowspecdefinition(i_manufact_id#5, specifiedwindowframe(RowFrame, unboundedpreceding$(), unboundedfollowing$())) AS avg_quarterly_sales#23], [i_manufact_id#5] + +(26) Filter [codegen id : 7] +Input [4]: [i_manufact_id#5, sum_sales#21, _w0#22, avg_quarterly_sales#23] +Condition : CASE WHEN (avg_quarterly_sales#23 > 0.000000) THEN ((abs((sum_sales#21 - avg_quarterly_sales#23)) / avg_quarterly_sales#23) > 0.1000000000000000) ELSE false END + +(27) Project [codegen id : 7] +Output [3]: [i_manufact_id#5, sum_sales#21, avg_quarterly_sales#23] +Input [4]: [i_manufact_id#5, sum_sales#21, _w0#22, avg_quarterly_sales#23] + +(28) TakeOrderedAndProject +Input [3]: [i_manufact_id#5, sum_sales#21, avg_quarterly_sales#23] +Arguments: 100, [avg_quarterly_sales#23 ASC NULLS FIRST, sum_sales#21 ASC NULLS FIRST, i_manufact_id#5 ASC NULLS FIRST], [i_manufact_id#5, sum_sales#21, avg_quarterly_sales#23] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 5 Hosting Expression = ss_sold_date_sk#13 IN dynamicpruning#14 +BroadcastExchange (33) ++- * ColumnarToRow (32) + +- CometProject (31) + +- CometFilter (30) + +- CometScan parquet spark_catalog.default.date_dim (29) + + +(29) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#15, d_month_seq#24, d_qoy#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [In(d_month_seq, [1200,1201,1202,1203,1204,1205,1206,1207,1208,1209,1210,1211]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(30) CometFilter +Input [3]: [d_date_sk#15, d_month_seq#24, d_qoy#16] +Condition : (d_month_seq#24 INSET 1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211 AND isnotnull(d_date_sk#15)) + +(31) CometProject +Input [3]: [d_date_sk#15, d_month_seq#24, d_qoy#16] +Arguments: [d_date_sk#15, d_qoy#16], [d_date_sk#15, d_qoy#16] + +(32) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#15, d_qoy#16] + +(33) BroadcastExchange +Input [2]: [d_date_sk#15, d_qoy#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q53/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q53/simplified.txt new file mode 100644 index 0000000000..adda5c34f7 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q53/simplified.txt @@ -0,0 +1,51 @@ +TakeOrderedAndProject [avg_quarterly_sales,sum_sales,i_manufact_id] + WholeStageCodegen (7) + Project [i_manufact_id,sum_sales,avg_quarterly_sales] + Filter [avg_quarterly_sales,sum_sales] + InputAdapter + Window [_w0,i_manufact_id] + WholeStageCodegen (6) + Sort [i_manufact_id] + InputAdapter + Exchange [i_manufact_id] #1 + WholeStageCodegen (5) + HashAggregate [i_manufact_id,d_qoy,sum] [sum(UnscaledValue(ss_sales_price)),sum_sales,_w0,sum] + InputAdapter + Exchange [i_manufact_id,d_qoy] #2 + WholeStageCodegen (4) + HashAggregate [i_manufact_id,d_qoy,ss_sales_price] [sum,sum] + Project [i_manufact_id,ss_sales_price,d_qoy] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [i_manufact_id,ss_store_sk,ss_sales_price,d_qoy] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [i_manufact_id,ss_store_sk,ss_sales_price,ss_sold_date_sk] + BroadcastHashJoin [i_item_sk,ss_item_sk] + ColumnarToRow + InputAdapter + CometProject [i_item_sk,i_manufact_id] + CometFilter [i_category,i_class,i_brand,i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_class,i_category,i_manufact_id] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk,ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_qoy] + CometFilter [d_month_seq,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq,d_qoy] + InputAdapter + ReusedExchange [d_date_sk,d_qoy] #4 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q54/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q54/explain.txt new file mode 100644 index 0000000000..ca308b19a4 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q54/explain.txt @@ -0,0 +1,483 @@ +== Physical Plan == +TakeOrderedAndProject (55) ++- * HashAggregate (54) + +- Exchange (53) + +- * HashAggregate (52) + +- * HashAggregate (51) + +- Exchange (50) + +- * HashAggregate (49) + +- * Project (48) + +- * BroadcastHashJoin Inner BuildRight (47) + :- * Project (45) + : +- * BroadcastHashJoin Inner BuildRight (44) + : :- * Project (39) + : : +- * BroadcastHashJoin Inner BuildRight (38) + : : :- * Project (33) + : : : +- * BroadcastHashJoin Inner BuildRight (32) + : : : :- * HashAggregate (27) + : : : : +- Exchange (26) + : : : : +- * HashAggregate (25) + : : : : +- * Project (24) + : : : : +- * BroadcastHashJoin Inner BuildRight (23) + : : : : :- * Project (18) + : : : : : +- * BroadcastHashJoin Inner BuildRight (17) + : : : : : :- * Project (15) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (14) + : : : : : : :- * ColumnarToRow (8) + : : : : : : : +- CometUnion (7) + : : : : : : : :- CometProject (3) + : : : : : : : : +- CometFilter (2) + : : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) + : : : : : : : +- CometProject (6) + : : : : : : : +- CometFilter (5) + : : : : : : : +- CometScan parquet spark_catalog.default.web_sales (4) + : : : : : : +- BroadcastExchange (13) + : : : : : : +- * ColumnarToRow (12) + : : : : : : +- CometProject (11) + : : : : : : +- CometFilter (10) + : : : : : : +- CometScan parquet spark_catalog.default.item (9) + : : : : : +- ReusedExchange (16) + : : : : +- BroadcastExchange (22) + : : : : +- * ColumnarToRow (21) + : : : : +- CometFilter (20) + : : : : +- CometScan parquet spark_catalog.default.customer (19) + : : : +- BroadcastExchange (31) + : : : +- * ColumnarToRow (30) + : : : +- CometFilter (29) + : : : +- CometScan parquet spark_catalog.default.store_sales (28) + : : +- BroadcastExchange (37) + : : +- * ColumnarToRow (36) + : : +- CometFilter (35) + : : +- CometScan parquet spark_catalog.default.customer_address (34) + : +- BroadcastExchange (43) + : +- * ColumnarToRow (42) + : +- CometFilter (41) + : +- CometScan parquet spark_catalog.default.store (40) + +- ReusedExchange (46) + + +(1) Scan parquet spark_catalog.default.catalog_sales +Output [3]: [cs_bill_customer_sk#1, cs_item_sk#2, cs_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#3), dynamicpruningexpression(cs_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(cs_item_sk), IsNotNull(cs_bill_customer_sk)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [cs_bill_customer_sk#1, cs_item_sk#2, cs_sold_date_sk#3] +Condition : (isnotnull(cs_item_sk#2) AND isnotnull(cs_bill_customer_sk#1)) + +(3) CometProject +Input [3]: [cs_bill_customer_sk#1, cs_item_sk#2, cs_sold_date_sk#3] +Arguments: [sold_date_sk#5, customer_sk#6, item_sk#7], [cs_sold_date_sk#3 AS sold_date_sk#5, cs_bill_customer_sk#1 AS customer_sk#6, cs_item_sk#2 AS item_sk#7] + +(4) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_item_sk#8, ws_bill_customer_sk#9, ws_sold_date_sk#10] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#10), dynamicpruningexpression(ws_sold_date_sk#10 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(ws_item_sk), IsNotNull(ws_bill_customer_sk)] +ReadSchema: struct + +(5) CometFilter +Input [3]: [ws_item_sk#8, ws_bill_customer_sk#9, ws_sold_date_sk#10] +Condition : (isnotnull(ws_item_sk#8) AND isnotnull(ws_bill_customer_sk#9)) + +(6) CometProject +Input [3]: [ws_item_sk#8, ws_bill_customer_sk#9, ws_sold_date_sk#10] +Arguments: [sold_date_sk#11, customer_sk#12, item_sk#13], [ws_sold_date_sk#10 AS sold_date_sk#11, ws_bill_customer_sk#9 AS customer_sk#12, ws_item_sk#8 AS item_sk#13] + +(7) CometUnion +Child 0 Input [3]: [sold_date_sk#5, customer_sk#6, item_sk#7] +Child 1 Input [3]: [sold_date_sk#11, customer_sk#12, item_sk#13] + +(8) ColumnarToRow [codegen id : 4] +Input [3]: [sold_date_sk#5, customer_sk#6, item_sk#7] + +(9) Scan parquet spark_catalog.default.item +Output [3]: [i_item_sk#14, i_class#15, i_category#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_category), IsNotNull(i_class), EqualTo(i_category,Women ), EqualTo(i_class,maternity ), IsNotNull(i_item_sk)] +ReadSchema: struct + +(10) CometFilter +Input [3]: [i_item_sk#14, i_class#15, i_category#16] +Condition : ((((isnotnull(i_category#16) AND isnotnull(i_class#15)) AND (i_category#16 = Women )) AND (i_class#15 = maternity )) AND isnotnull(i_item_sk#14)) + +(11) CometProject +Input [3]: [i_item_sk#14, i_class#15, i_category#16] +Arguments: [i_item_sk#14], [i_item_sk#14] + +(12) ColumnarToRow [codegen id : 1] +Input [1]: [i_item_sk#14] + +(13) BroadcastExchange +Input [1]: [i_item_sk#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(14) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [item_sk#7] +Right keys [1]: [i_item_sk#14] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 4] +Output [2]: [sold_date_sk#5, customer_sk#6] +Input [4]: [sold_date_sk#5, customer_sk#6, item_sk#7, i_item_sk#14] + +(16) ReusedExchange [Reuses operator id: 60] +Output [1]: [d_date_sk#17] + +(17) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [sold_date_sk#5] +Right keys [1]: [d_date_sk#17] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 4] +Output [1]: [customer_sk#6] +Input [3]: [sold_date_sk#5, customer_sk#6, d_date_sk#17] + +(19) Scan parquet spark_catalog.default.customer +Output [2]: [c_customer_sk#18, c_current_addr_sk#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_current_addr_sk)] +ReadSchema: struct + +(20) CometFilter +Input [2]: [c_customer_sk#18, c_current_addr_sk#19] +Condition : (isnotnull(c_customer_sk#18) AND isnotnull(c_current_addr_sk#19)) + +(21) ColumnarToRow [codegen id : 3] +Input [2]: [c_customer_sk#18, c_current_addr_sk#19] + +(22) BroadcastExchange +Input [2]: [c_customer_sk#18, c_current_addr_sk#19] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(23) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [customer_sk#6] +Right keys [1]: [c_customer_sk#18] +Join type: Inner +Join condition: None + +(24) Project [codegen id : 4] +Output [2]: [c_customer_sk#18, c_current_addr_sk#19] +Input [3]: [customer_sk#6, c_customer_sk#18, c_current_addr_sk#19] + +(25) HashAggregate [codegen id : 4] +Input [2]: [c_customer_sk#18, c_current_addr_sk#19] +Keys [2]: [c_customer_sk#18, c_current_addr_sk#19] +Functions: [] +Aggregate Attributes: [] +Results [2]: [c_customer_sk#18, c_current_addr_sk#19] + +(26) Exchange +Input [2]: [c_customer_sk#18, c_current_addr_sk#19] +Arguments: hashpartitioning(c_customer_sk#18, c_current_addr_sk#19, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(27) HashAggregate [codegen id : 9] +Input [2]: [c_customer_sk#18, c_current_addr_sk#19] +Keys [2]: [c_customer_sk#18, c_current_addr_sk#19] +Functions: [] +Aggregate Attributes: [] +Results [2]: [c_customer_sk#18, c_current_addr_sk#19] + +(28) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_customer_sk#20, ss_ext_sales_price#21, ss_sold_date_sk#22] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#22), dynamicpruningexpression(ss_sold_date_sk#22 IN dynamicpruning#23)] +PushedFilters: [IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(29) CometFilter +Input [3]: [ss_customer_sk#20, ss_ext_sales_price#21, ss_sold_date_sk#22] +Condition : isnotnull(ss_customer_sk#20) + +(30) ColumnarToRow [codegen id : 5] +Input [3]: [ss_customer_sk#20, ss_ext_sales_price#21, ss_sold_date_sk#22] + +(31) BroadcastExchange +Input [3]: [ss_customer_sk#20, ss_ext_sales_price#21, ss_sold_date_sk#22] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(32) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_customer_sk#18] +Right keys [1]: [ss_customer_sk#20] +Join type: Inner +Join condition: None + +(33) Project [codegen id : 9] +Output [4]: [c_customer_sk#18, c_current_addr_sk#19, ss_ext_sales_price#21, ss_sold_date_sk#22] +Input [5]: [c_customer_sk#18, c_current_addr_sk#19, ss_customer_sk#20, ss_ext_sales_price#21, ss_sold_date_sk#22] + +(34) Scan parquet spark_catalog.default.customer_address +Output [3]: [ca_address_sk#24, ca_county#25, ca_state#26] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk), IsNotNull(ca_county), IsNotNull(ca_state)] +ReadSchema: struct + +(35) CometFilter +Input [3]: [ca_address_sk#24, ca_county#25, ca_state#26] +Condition : ((isnotnull(ca_address_sk#24) AND isnotnull(ca_county#25)) AND isnotnull(ca_state#26)) + +(36) ColumnarToRow [codegen id : 6] +Input [3]: [ca_address_sk#24, ca_county#25, ca_state#26] + +(37) BroadcastExchange +Input [3]: [ca_address_sk#24, ca_county#25, ca_state#26] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(38) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_current_addr_sk#19] +Right keys [1]: [ca_address_sk#24] +Join type: Inner +Join condition: None + +(39) Project [codegen id : 9] +Output [5]: [c_customer_sk#18, ss_ext_sales_price#21, ss_sold_date_sk#22, ca_county#25, ca_state#26] +Input [7]: [c_customer_sk#18, c_current_addr_sk#19, ss_ext_sales_price#21, ss_sold_date_sk#22, ca_address_sk#24, ca_county#25, ca_state#26] + +(40) Scan parquet spark_catalog.default.store +Output [2]: [s_county#27, s_state#28] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_county), IsNotNull(s_state)] +ReadSchema: struct + +(41) CometFilter +Input [2]: [s_county#27, s_state#28] +Condition : (isnotnull(s_county#27) AND isnotnull(s_state#28)) + +(42) ColumnarToRow [codegen id : 7] +Input [2]: [s_county#27, s_state#28] + +(43) BroadcastExchange +Input [2]: [s_county#27, s_state#28] +Arguments: HashedRelationBroadcastMode(List(input[0, string, false], input[1, string, false]),false), [plan_id=6] + +(44) BroadcastHashJoin [codegen id : 9] +Left keys [2]: [ca_county#25, ca_state#26] +Right keys [2]: [s_county#27, s_state#28] +Join type: Inner +Join condition: None + +(45) Project [codegen id : 9] +Output [3]: [c_customer_sk#18, ss_ext_sales_price#21, ss_sold_date_sk#22] +Input [7]: [c_customer_sk#18, ss_ext_sales_price#21, ss_sold_date_sk#22, ca_county#25, ca_state#26, s_county#27, s_state#28] + +(46) ReusedExchange [Reuses operator id: 65] +Output [1]: [d_date_sk#29] + +(47) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_sold_date_sk#22] +Right keys [1]: [d_date_sk#29] +Join type: Inner +Join condition: None + +(48) Project [codegen id : 9] +Output [2]: [c_customer_sk#18, ss_ext_sales_price#21] +Input [4]: [c_customer_sk#18, ss_ext_sales_price#21, ss_sold_date_sk#22, d_date_sk#29] + +(49) HashAggregate [codegen id : 9] +Input [2]: [c_customer_sk#18, ss_ext_sales_price#21] +Keys [1]: [c_customer_sk#18] +Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#21))] +Aggregate Attributes [1]: [sum#30] +Results [2]: [c_customer_sk#18, sum#31] + +(50) Exchange +Input [2]: [c_customer_sk#18, sum#31] +Arguments: hashpartitioning(c_customer_sk#18, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(51) HashAggregate [codegen id : 10] +Input [2]: [c_customer_sk#18, sum#31] +Keys [1]: [c_customer_sk#18] +Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#21))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#21))#32] +Results [1]: [cast((MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#21))#32,17,2) / 50) as int) AS segment#33] + +(52) HashAggregate [codegen id : 10] +Input [1]: [segment#33] +Keys [1]: [segment#33] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#34] +Results [2]: [segment#33, count#35] + +(53) Exchange +Input [2]: [segment#33, count#35] +Arguments: hashpartitioning(segment#33, 5), ENSURE_REQUIREMENTS, [plan_id=8] + +(54) HashAggregate [codegen id : 11] +Input [2]: [segment#33, count#35] +Keys [1]: [segment#33] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#36] +Results [3]: [segment#33, count(1)#36 AS num_customers#37, (segment#33 * 50) AS segment_base#38] + +(55) TakeOrderedAndProject +Input [3]: [segment#33, num_customers#37, segment_base#38] +Arguments: 100, [segment#33 ASC NULLS FIRST, num_customers#37 ASC NULLS FIRST], [segment#33, num_customers#37, segment_base#38] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (60) ++- * ColumnarToRow (59) + +- CometProject (58) + +- CometFilter (57) + +- CometScan parquet spark_catalog.default.date_dim (56) + + +(56) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#17, d_year#39, d_moy#40] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), EqualTo(d_moy,12), EqualTo(d_year,1998), IsNotNull(d_date_sk)] +ReadSchema: struct + +(57) CometFilter +Input [3]: [d_date_sk#17, d_year#39, d_moy#40] +Condition : ((((isnotnull(d_moy#40) AND isnotnull(d_year#39)) AND (d_moy#40 = 12)) AND (d_year#39 = 1998)) AND isnotnull(d_date_sk#17)) + +(58) CometProject +Input [3]: [d_date_sk#17, d_year#39, d_moy#40] +Arguments: [d_date_sk#17], [d_date_sk#17] + +(59) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#17] + +(60) BroadcastExchange +Input [1]: [d_date_sk#17] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=9] + +Subquery:2 Hosting operator id = 4 Hosting Expression = ws_sold_date_sk#10 IN dynamicpruning#4 + +Subquery:3 Hosting operator id = 28 Hosting Expression = ss_sold_date_sk#22 IN dynamicpruning#23 +BroadcastExchange (65) ++- * ColumnarToRow (64) + +- CometProject (63) + +- CometFilter (62) + +- CometScan parquet spark_catalog.default.date_dim (61) + + +(61) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#29, d_month_seq#41] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,ScalarSubquery#42), LessThanOrEqual(d_month_seq,ScalarSubquery#43), IsNotNull(d_date_sk)] +ReadSchema: struct + +(62) CometFilter +Input [2]: [d_date_sk#29, d_month_seq#41] +Condition : (((isnotnull(d_month_seq#41) AND (d_month_seq#41 >= ReusedSubquery Subquery scalar-subquery#42, [id=#44])) AND (d_month_seq#41 <= ReusedSubquery Subquery scalar-subquery#43, [id=#45])) AND isnotnull(d_date_sk#29)) + +(63) CometProject +Input [2]: [d_date_sk#29, d_month_seq#41] +Arguments: [d_date_sk#29], [d_date_sk#29] + +(64) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#29] + +(65) BroadcastExchange +Input [1]: [d_date_sk#29] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=10] + +Subquery:4 Hosting operator id = 62 Hosting Expression = ReusedSubquery Subquery scalar-subquery#42, [id=#44] + +Subquery:5 Hosting operator id = 62 Hosting Expression = ReusedSubquery Subquery scalar-subquery#43, [id=#45] + +Subquery:6 Hosting operator id = 61 Hosting Expression = Subquery scalar-subquery#42, [id=#44] +* HashAggregate (72) ++- Exchange (71) + +- * ColumnarToRow (70) + +- CometHashAggregate (69) + +- CometProject (68) + +- CometFilter (67) + +- CometScan parquet spark_catalog.default.date_dim (66) + + +(66) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_month_seq#46, d_year#47, d_moy#48] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,1998), EqualTo(d_moy,12)] +ReadSchema: struct + +(67) CometFilter +Input [3]: [d_month_seq#46, d_year#47, d_moy#48] +Condition : (((isnotnull(d_year#47) AND isnotnull(d_moy#48)) AND (d_year#47 = 1998)) AND (d_moy#48 = 12)) + +(68) CometProject +Input [3]: [d_month_seq#46, d_year#47, d_moy#48] +Arguments: [(d_month_seq + 1)#49], [(d_month_seq#46 + 1) AS (d_month_seq + 1)#49] + +(69) CometHashAggregate +Input [1]: [(d_month_seq + 1)#49] +Keys [1]: [(d_month_seq + 1)#49] +Functions: [] + +(70) ColumnarToRow [codegen id : 1] +Input [1]: [(d_month_seq + 1)#49] + +(71) Exchange +Input [1]: [(d_month_seq + 1)#49] +Arguments: hashpartitioning((d_month_seq + 1)#49, 5), ENSURE_REQUIREMENTS, [plan_id=11] + +(72) HashAggregate [codegen id : 2] +Input [1]: [(d_month_seq + 1)#49] +Keys [1]: [(d_month_seq + 1)#49] +Functions: [] +Aggregate Attributes: [] +Results [1]: [(d_month_seq + 1)#49] + +Subquery:7 Hosting operator id = 61 Hosting Expression = Subquery scalar-subquery#43, [id=#45] +* HashAggregate (79) ++- Exchange (78) + +- * ColumnarToRow (77) + +- CometHashAggregate (76) + +- CometProject (75) + +- CometFilter (74) + +- CometScan parquet spark_catalog.default.date_dim (73) + + +(73) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_month_seq#50, d_year#51, d_moy#52] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,1998), EqualTo(d_moy,12)] +ReadSchema: struct + +(74) CometFilter +Input [3]: [d_month_seq#50, d_year#51, d_moy#52] +Condition : (((isnotnull(d_year#51) AND isnotnull(d_moy#52)) AND (d_year#51 = 1998)) AND (d_moy#52 = 12)) + +(75) CometProject +Input [3]: [d_month_seq#50, d_year#51, d_moy#52] +Arguments: [(d_month_seq + 3)#53], [(d_month_seq#50 + 3) AS (d_month_seq + 3)#53] + +(76) CometHashAggregate +Input [1]: [(d_month_seq + 3)#53] +Keys [1]: [(d_month_seq + 3)#53] +Functions: [] + +(77) ColumnarToRow [codegen id : 1] +Input [1]: [(d_month_seq + 3)#53] + +(78) Exchange +Input [1]: [(d_month_seq + 3)#53] +Arguments: hashpartitioning((d_month_seq + 3)#53, 5), ENSURE_REQUIREMENTS, [plan_id=12] + +(79) HashAggregate [codegen id : 2] +Input [1]: [(d_month_seq + 3)#53] +Keys [1]: [(d_month_seq + 3)#53] +Functions: [] +Aggregate Attributes: [] +Results [1]: [(d_month_seq + 3)#53] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q54/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q54/simplified.txt new file mode 100644 index 0000000000..30ba4b743b --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q54/simplified.txt @@ -0,0 +1,123 @@ +TakeOrderedAndProject [segment,num_customers,segment_base] + WholeStageCodegen (11) + HashAggregate [segment,count] [count(1),num_customers,segment_base,count] + InputAdapter + Exchange [segment] #1 + WholeStageCodegen (10) + HashAggregate [segment] [count,count] + HashAggregate [c_customer_sk,sum] [sum(UnscaledValue(ss_ext_sales_price)),segment,sum] + InputAdapter + Exchange [c_customer_sk] #2 + WholeStageCodegen (9) + HashAggregate [c_customer_sk,ss_ext_sales_price] [sum,sum] + Project [c_customer_sk,ss_ext_sales_price] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [c_customer_sk,ss_ext_sales_price,ss_sold_date_sk] + BroadcastHashJoin [ca_county,ca_state,s_county,s_state] + Project [c_customer_sk,ss_ext_sales_price,ss_sold_date_sk,ca_county,ca_state] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [c_customer_sk,c_current_addr_sk,ss_ext_sales_price,ss_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + HashAggregate [c_customer_sk,c_current_addr_sk] + InputAdapter + Exchange [c_customer_sk,c_current_addr_sk] #3 + WholeStageCodegen (4) + HashAggregate [c_customer_sk,c_current_addr_sk] + Project [c_customer_sk,c_current_addr_sk] + BroadcastHashJoin [customer_sk,c_customer_sk] + Project [customer_sk] + BroadcastHashJoin [sold_date_sk,d_date_sk] + Project [sold_date_sk,customer_sk] + BroadcastHashJoin [item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometUnion + CometProject [cs_sold_date_sk,cs_bill_customer_sk,cs_item_sk] [sold_date_sk,customer_sk,item_sk] + CometFilter [cs_item_sk,cs_bill_customer_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_item_sk,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_moy,d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + CometProject [ws_sold_date_sk,ws_bill_customer_sk,ws_item_sk] [sold_date_sk,customer_sk,item_sk] + CometFilter [ws_item_sk,ws_bill_customer_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_bill_customer_sk,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [i_item_sk] + CometFilter [i_category,i_class,i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_class,i_category] + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_current_addr_sk] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_addr_sk] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (5) + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk] + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_ext_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #8 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_month_seq,d_date_sk] + ReusedSubquery [(d_month_seq + 1)] #3 + ReusedSubquery [(d_month_seq + 3)] #4 + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] + Subquery #3 + WholeStageCodegen (2) + HashAggregate [(d_month_seq + 1)] + InputAdapter + Exchange [(d_month_seq + 1)] #9 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometHashAggregate [(d_month_seq + 1)] + CometProject [d_month_seq] [(d_month_seq + 1)] + CometFilter [d_year,d_moy] + CometScan parquet spark_catalog.default.date_dim [d_month_seq,d_year,d_moy] + Subquery #4 + WholeStageCodegen (2) + HashAggregate [(d_month_seq + 3)] + InputAdapter + Exchange [(d_month_seq + 3)] #10 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometHashAggregate [(d_month_seq + 3)] + CometProject [d_month_seq] [(d_month_seq + 3)] + CometFilter [d_year,d_moy] + CometScan parquet spark_catalog.default.date_dim [d_month_seq,d_year,d_moy] + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (6) + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk,ca_county,ca_state] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_county,ca_state] + InputAdapter + BroadcastExchange #12 + WholeStageCodegen (7) + ColumnarToRow + InputAdapter + CometFilter [s_county,s_state] + CometScan parquet spark_catalog.default.store [s_county,s_state] + InputAdapter + ReusedExchange [d_date_sk] #8 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q55/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q55/explain.txt new file mode 100644 index 0000000000..3d1d689bc9 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q55/explain.txt @@ -0,0 +1,125 @@ +== Physical Plan == +TakeOrderedAndProject (21) ++- * HashAggregate (20) + +- Exchange (19) + +- * HashAggregate (18) + +- * Project (17) + +- * BroadcastHashJoin Inner BuildRight (16) + :- * Project (10) + : +- * BroadcastHashJoin Inner BuildRight (9) + : :- * ColumnarToRow (4) + : : +- CometProject (3) + : : +- CometFilter (2) + : : +- CometScan parquet spark_catalog.default.date_dim (1) + : +- BroadcastExchange (8) + : +- * ColumnarToRow (7) + : +- CometFilter (6) + : +- CometScan parquet spark_catalog.default.store_sales (5) + +- BroadcastExchange (15) + +- * ColumnarToRow (14) + +- CometProject (13) + +- CometFilter (12) + +- CometScan parquet spark_catalog.default.item (11) + + +(1) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#1, d_year#2, d_moy#3] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), EqualTo(d_moy,11), EqualTo(d_year,1999), IsNotNull(d_date_sk)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [d_date_sk#1, d_year#2, d_moy#3] +Condition : ((((isnotnull(d_moy#3) AND isnotnull(d_year#2)) AND (d_moy#3 = 11)) AND (d_year#2 = 1999)) AND isnotnull(d_date_sk#1)) + +(3) CometProject +Input [3]: [d_date_sk#1, d_year#2, d_moy#3] +Arguments: [d_date_sk#1], [d_date_sk#1] + +(4) ColumnarToRow [codegen id : 3] +Input [1]: [d_date_sk#1] + +(5) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#6), dynamicpruningexpression(true)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(6) CometFilter +Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] +Condition : isnotnull(ss_item_sk#4) + +(7) ColumnarToRow [codegen id : 1] +Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] + +(8) BroadcastExchange +Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[2, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [d_date_sk#1] +Right keys [1]: [ss_sold_date_sk#6] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 3] +Output [2]: [ss_item_sk#4, ss_ext_sales_price#5] +Input [4]: [d_date_sk#1, ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] + +(11) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#7, i_brand_id#8, i_brand#9, i_manager_id#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_manager_id), EqualTo(i_manager_id,28), IsNotNull(i_item_sk)] +ReadSchema: struct + +(12) CometFilter +Input [4]: [i_item_sk#7, i_brand_id#8, i_brand#9, i_manager_id#10] +Condition : ((isnotnull(i_manager_id#10) AND (i_manager_id#10 = 28)) AND isnotnull(i_item_sk#7)) + +(13) CometProject +Input [4]: [i_item_sk#7, i_brand_id#8, i_brand#9, i_manager_id#10] +Arguments: [i_item_sk#7, i_brand_id#8, i_brand#9], [i_item_sk#7, i_brand_id#8, i_brand#9] + +(14) ColumnarToRow [codegen id : 2] +Input [3]: [i_item_sk#7, i_brand_id#8, i_brand#9] + +(15) BroadcastExchange +Input [3]: [i_item_sk#7, i_brand_id#8, i_brand#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(16) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_item_sk#4] +Right keys [1]: [i_item_sk#7] +Join type: Inner +Join condition: None + +(17) Project [codegen id : 3] +Output [3]: [ss_ext_sales_price#5, i_brand_id#8, i_brand#9] +Input [5]: [ss_item_sk#4, ss_ext_sales_price#5, i_item_sk#7, i_brand_id#8, i_brand#9] + +(18) HashAggregate [codegen id : 3] +Input [3]: [ss_ext_sales_price#5, i_brand_id#8, i_brand#9] +Keys [2]: [i_brand#9, i_brand_id#8] +Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#5))] +Aggregate Attributes [1]: [sum#11] +Results [3]: [i_brand#9, i_brand_id#8, sum#12] + +(19) Exchange +Input [3]: [i_brand#9, i_brand_id#8, sum#12] +Arguments: hashpartitioning(i_brand#9, i_brand_id#8, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(20) HashAggregate [codegen id : 4] +Input [3]: [i_brand#9, i_brand_id#8, sum#12] +Keys [2]: [i_brand#9, i_brand_id#8] +Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#5))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#5))#13] +Results [3]: [i_brand_id#8 AS brand_id#14, i_brand#9 AS brand#15, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#5))#13,17,2) AS ext_price#16] + +(21) TakeOrderedAndProject +Input [3]: [brand_id#14, brand#15, ext_price#16] +Arguments: 100, [ext_price#16 DESC NULLS LAST, brand_id#14 ASC NULLS FIRST], [brand_id#14, brand#15, ext_price#16] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q55/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q55/simplified.txt new file mode 100644 index 0000000000..7a0fe88633 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q55/simplified.txt @@ -0,0 +1,31 @@ +TakeOrderedAndProject [ext_price,brand_id,brand] + WholeStageCodegen (4) + HashAggregate [i_brand,i_brand_id,sum] [sum(UnscaledValue(ss_ext_sales_price)),brand_id,brand,ext_price,sum] + InputAdapter + Exchange [i_brand,i_brand_id] #1 + WholeStageCodegen (3) + HashAggregate [i_brand,i_brand_id,ss_ext_sales_price] [sum,sum] + Project [ss_ext_sales_price,i_brand_id,i_brand] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_ext_sales_price] + BroadcastHashJoin [d_date_sk,ss_sold_date_sk] + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_moy,d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ext_sales_price,ss_sold_date_sk] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometProject [i_item_sk,i_brand_id,i_brand] + CometFilter [i_manager_id,i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_brand,i_manager_id] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q56/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q56/explain.txt new file mode 100644 index 0000000000..bbed7eea67 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q56/explain.txt @@ -0,0 +1,405 @@ +== Physical Plan == +TakeOrderedAndProject (63) ++- * HashAggregate (62) + +- Exchange (61) + +- * HashAggregate (60) + +- Union (59) + :- * HashAggregate (28) + : +- Exchange (27) + : +- * HashAggregate (26) + : +- * Project (25) + : +- * BroadcastHashJoin Inner BuildRight (24) + : :- * Project (13) + : : +- * BroadcastHashJoin Inner BuildRight (12) + : : :- * Project (6) + : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- ReusedExchange (4) + : : +- BroadcastExchange (11) + : : +- * ColumnarToRow (10) + : : +- CometProject (9) + : : +- CometFilter (8) + : : +- CometScan parquet spark_catalog.default.customer_address (7) + : +- BroadcastExchange (23) + : +- * BroadcastHashJoin LeftSemi BuildRight (22) + : :- * ColumnarToRow (16) + : : +- CometFilter (15) + : : +- CometScan parquet spark_catalog.default.item (14) + : +- BroadcastExchange (21) + : +- * ColumnarToRow (20) + : +- CometProject (19) + : +- CometFilter (18) + : +- CometScan parquet spark_catalog.default.item (17) + :- * HashAggregate (43) + : +- Exchange (42) + : +- * HashAggregate (41) + : +- * Project (40) + : +- * BroadcastHashJoin Inner BuildRight (39) + : :- * Project (37) + : : +- * BroadcastHashJoin Inner BuildRight (36) + : : :- * Project (34) + : : : +- * BroadcastHashJoin Inner BuildRight (33) + : : : :- * ColumnarToRow (31) + : : : : +- CometFilter (30) + : : : : +- CometScan parquet spark_catalog.default.catalog_sales (29) + : : : +- ReusedExchange (32) + : : +- ReusedExchange (35) + : +- ReusedExchange (38) + +- * HashAggregate (58) + +- Exchange (57) + +- * HashAggregate (56) + +- * Project (55) + +- * BroadcastHashJoin Inner BuildRight (54) + :- * Project (52) + : +- * BroadcastHashJoin Inner BuildRight (51) + : :- * Project (49) + : : +- * BroadcastHashJoin Inner BuildRight (48) + : : :- * ColumnarToRow (46) + : : : +- CometFilter (45) + : : : +- CometScan parquet spark_catalog.default.web_sales (44) + : : +- ReusedExchange (47) + : +- ReusedExchange (50) + +- ReusedExchange (53) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#4), dynamicpruningexpression(ss_sold_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(ss_addr_sk), IsNotNull(ss_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [4]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4] +Condition : (isnotnull(ss_addr_sk#2) AND isnotnull(ss_item_sk#1)) + +(3) ColumnarToRow [codegen id : 5] +Input [4]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4] + +(4) ReusedExchange [Reuses operator id: 68] +Output [1]: [d_date_sk#6] + +(5) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_sold_date_sk#4] +Right keys [1]: [d_date_sk#6] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 5] +Output [3]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3] +Input [5]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4, d_date_sk#6] + +(7) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#7, ca_gmt_offset#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_gmt_offset), EqualTo(ca_gmt_offset,-5.00), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(8) CometFilter +Input [2]: [ca_address_sk#7, ca_gmt_offset#8] +Condition : ((isnotnull(ca_gmt_offset#8) AND (ca_gmt_offset#8 = -5.00)) AND isnotnull(ca_address_sk#7)) + +(9) CometProject +Input [2]: [ca_address_sk#7, ca_gmt_offset#8] +Arguments: [ca_address_sk#7], [ca_address_sk#7] + +(10) ColumnarToRow [codegen id : 2] +Input [1]: [ca_address_sk#7] + +(11) BroadcastExchange +Input [1]: [ca_address_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(12) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_addr_sk#2] +Right keys [1]: [ca_address_sk#7] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 5] +Output [2]: [ss_item_sk#1, ss_ext_sales_price#3] +Input [4]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ca_address_sk#7] + +(14) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#9, i_item_id#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(15) CometFilter +Input [2]: [i_item_sk#9, i_item_id#10] +Condition : isnotnull(i_item_sk#9) + +(16) ColumnarToRow [codegen id : 4] +Input [2]: [i_item_sk#9, i_item_id#10] + +(17) Scan parquet spark_catalog.default.item +Output [2]: [i_item_id#11, i_color#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [In(i_color, [blanched ,burnished ,slate ])] +ReadSchema: struct + +(18) CometFilter +Input [2]: [i_item_id#11, i_color#12] +Condition : i_color#12 IN (slate ,blanched ,burnished ) + +(19) CometProject +Input [2]: [i_item_id#11, i_color#12] +Arguments: [i_item_id#11], [i_item_id#11] + +(20) ColumnarToRow [codegen id : 3] +Input [1]: [i_item_id#11] + +(21) BroadcastExchange +Input [1]: [i_item_id#11] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=2] + +(22) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [i_item_id#10] +Right keys [1]: [i_item_id#11] +Join type: LeftSemi +Join condition: None + +(23) BroadcastExchange +Input [2]: [i_item_sk#9, i_item_id#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#9] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 5] +Output [2]: [ss_ext_sales_price#3, i_item_id#10] +Input [4]: [ss_item_sk#1, ss_ext_sales_price#3, i_item_sk#9, i_item_id#10] + +(26) HashAggregate [codegen id : 5] +Input [2]: [ss_ext_sales_price#3, i_item_id#10] +Keys [1]: [i_item_id#10] +Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#3))] +Aggregate Attributes [1]: [sum#13] +Results [2]: [i_item_id#10, sum#14] + +(27) Exchange +Input [2]: [i_item_id#10, sum#14] +Arguments: hashpartitioning(i_item_id#10, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(28) HashAggregate [codegen id : 6] +Input [2]: [i_item_id#10, sum#14] +Keys [1]: [i_item_id#10] +Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#3))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#3))#15] +Results [2]: [i_item_id#10, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#3))#15,17,2) AS total_sales#16] + +(29) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, cs_sold_date_sk#20] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#20), dynamicpruningexpression(cs_sold_date_sk#20 IN dynamicpruning#21)] +PushedFilters: [IsNotNull(cs_bill_addr_sk), IsNotNull(cs_item_sk)] +ReadSchema: struct + +(30) CometFilter +Input [4]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, cs_sold_date_sk#20] +Condition : (isnotnull(cs_bill_addr_sk#17) AND isnotnull(cs_item_sk#18)) + +(31) ColumnarToRow [codegen id : 11] +Input [4]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, cs_sold_date_sk#20] + +(32) ReusedExchange [Reuses operator id: 68] +Output [1]: [d_date_sk#22] + +(33) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [cs_sold_date_sk#20] +Right keys [1]: [d_date_sk#22] +Join type: Inner +Join condition: None + +(34) Project [codegen id : 11] +Output [3]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19] +Input [5]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, cs_sold_date_sk#20, d_date_sk#22] + +(35) ReusedExchange [Reuses operator id: 11] +Output [1]: [ca_address_sk#23] + +(36) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [cs_bill_addr_sk#17] +Right keys [1]: [ca_address_sk#23] +Join type: Inner +Join condition: None + +(37) Project [codegen id : 11] +Output [2]: [cs_item_sk#18, cs_ext_sales_price#19] +Input [4]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, ca_address_sk#23] + +(38) ReusedExchange [Reuses operator id: 23] +Output [2]: [i_item_sk#24, i_item_id#25] + +(39) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [cs_item_sk#18] +Right keys [1]: [i_item_sk#24] +Join type: Inner +Join condition: None + +(40) Project [codegen id : 11] +Output [2]: [cs_ext_sales_price#19, i_item_id#25] +Input [4]: [cs_item_sk#18, cs_ext_sales_price#19, i_item_sk#24, i_item_id#25] + +(41) HashAggregate [codegen id : 11] +Input [2]: [cs_ext_sales_price#19, i_item_id#25] +Keys [1]: [i_item_id#25] +Functions [1]: [partial_sum(UnscaledValue(cs_ext_sales_price#19))] +Aggregate Attributes [1]: [sum#26] +Results [2]: [i_item_id#25, sum#27] + +(42) Exchange +Input [2]: [i_item_id#25, sum#27] +Arguments: hashpartitioning(i_item_id#25, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(43) HashAggregate [codegen id : 12] +Input [2]: [i_item_id#25, sum#27] +Keys [1]: [i_item_id#25] +Functions [1]: [sum(UnscaledValue(cs_ext_sales_price#19))] +Aggregate Attributes [1]: [sum(UnscaledValue(cs_ext_sales_price#19))#28] +Results [2]: [i_item_id#25, MakeDecimal(sum(UnscaledValue(cs_ext_sales_price#19))#28,17,2) AS total_sales#29] + +(44) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ws_sold_date_sk#33] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#33), dynamicpruningexpression(ws_sold_date_sk#33 IN dynamicpruning#34)] +PushedFilters: [IsNotNull(ws_bill_addr_sk), IsNotNull(ws_item_sk)] +ReadSchema: struct + +(45) CometFilter +Input [4]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ws_sold_date_sk#33] +Condition : (isnotnull(ws_bill_addr_sk#31) AND isnotnull(ws_item_sk#30)) + +(46) ColumnarToRow [codegen id : 17] +Input [4]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ws_sold_date_sk#33] + +(47) ReusedExchange [Reuses operator id: 68] +Output [1]: [d_date_sk#35] + +(48) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ws_sold_date_sk#33] +Right keys [1]: [d_date_sk#35] +Join type: Inner +Join condition: None + +(49) Project [codegen id : 17] +Output [3]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32] +Input [5]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ws_sold_date_sk#33, d_date_sk#35] + +(50) ReusedExchange [Reuses operator id: 11] +Output [1]: [ca_address_sk#36] + +(51) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ws_bill_addr_sk#31] +Right keys [1]: [ca_address_sk#36] +Join type: Inner +Join condition: None + +(52) Project [codegen id : 17] +Output [2]: [ws_item_sk#30, ws_ext_sales_price#32] +Input [4]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ca_address_sk#36] + +(53) ReusedExchange [Reuses operator id: 23] +Output [2]: [i_item_sk#37, i_item_id#38] + +(54) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ws_item_sk#30] +Right keys [1]: [i_item_sk#37] +Join type: Inner +Join condition: None + +(55) Project [codegen id : 17] +Output [2]: [ws_ext_sales_price#32, i_item_id#38] +Input [4]: [ws_item_sk#30, ws_ext_sales_price#32, i_item_sk#37, i_item_id#38] + +(56) HashAggregate [codegen id : 17] +Input [2]: [ws_ext_sales_price#32, i_item_id#38] +Keys [1]: [i_item_id#38] +Functions [1]: [partial_sum(UnscaledValue(ws_ext_sales_price#32))] +Aggregate Attributes [1]: [sum#39] +Results [2]: [i_item_id#38, sum#40] + +(57) Exchange +Input [2]: [i_item_id#38, sum#40] +Arguments: hashpartitioning(i_item_id#38, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(58) HashAggregate [codegen id : 18] +Input [2]: [i_item_id#38, sum#40] +Keys [1]: [i_item_id#38] +Functions [1]: [sum(UnscaledValue(ws_ext_sales_price#32))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_ext_sales_price#32))#41] +Results [2]: [i_item_id#38, MakeDecimal(sum(UnscaledValue(ws_ext_sales_price#32))#41,17,2) AS total_sales#42] + +(59) Union + +(60) HashAggregate [codegen id : 19] +Input [2]: [i_item_id#10, total_sales#16] +Keys [1]: [i_item_id#10] +Functions [1]: [partial_sum(total_sales#16)] +Aggregate Attributes [2]: [sum#43, isEmpty#44] +Results [3]: [i_item_id#10, sum#45, isEmpty#46] + +(61) Exchange +Input [3]: [i_item_id#10, sum#45, isEmpty#46] +Arguments: hashpartitioning(i_item_id#10, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(62) HashAggregate [codegen id : 20] +Input [3]: [i_item_id#10, sum#45, isEmpty#46] +Keys [1]: [i_item_id#10] +Functions [1]: [sum(total_sales#16)] +Aggregate Attributes [1]: [sum(total_sales#16)#47] +Results [2]: [i_item_id#10, sum(total_sales#16)#47 AS total_sales#48] + +(63) TakeOrderedAndProject +Input [2]: [i_item_id#10, total_sales#48] +Arguments: 100, [total_sales#48 ASC NULLS FIRST], [i_item_id#10, total_sales#48] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (68) ++- * ColumnarToRow (67) + +- CometProject (66) + +- CometFilter (65) + +- CometScan parquet spark_catalog.default.date_dim (64) + + +(64) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#6, d_year#49, d_moy#50] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2001), EqualTo(d_moy,2), IsNotNull(d_date_sk)] +ReadSchema: struct + +(65) CometFilter +Input [3]: [d_date_sk#6, d_year#49, d_moy#50] +Condition : ((((isnotnull(d_year#49) AND isnotnull(d_moy#50)) AND (d_year#49 = 2001)) AND (d_moy#50 = 2)) AND isnotnull(d_date_sk#6)) + +(66) CometProject +Input [3]: [d_date_sk#6, d_year#49, d_moy#50] +Arguments: [d_date_sk#6], [d_date_sk#6] + +(67) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#6] + +(68) BroadcastExchange +Input [1]: [d_date_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + +Subquery:2 Hosting operator id = 29 Hosting Expression = cs_sold_date_sk#20 IN dynamicpruning#5 + +Subquery:3 Hosting operator id = 44 Hosting Expression = ws_sold_date_sk#33 IN dynamicpruning#5 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q56/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q56/simplified.txt new file mode 100644 index 0000000000..f781ed1f7b --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q56/simplified.txt @@ -0,0 +1,105 @@ +TakeOrderedAndProject [total_sales,i_item_id] + WholeStageCodegen (20) + HashAggregate [i_item_id,sum,isEmpty] [sum(total_sales),total_sales,sum,isEmpty] + InputAdapter + Exchange [i_item_id] #1 + WholeStageCodegen (19) + HashAggregate [i_item_id,total_sales] [sum,isEmpty,sum,isEmpty] + InputAdapter + Union + WholeStageCodegen (6) + HashAggregate [i_item_id,sum] [sum(UnscaledValue(ss_ext_sales_price)),total_sales,sum] + InputAdapter + Exchange [i_item_id] #2 + WholeStageCodegen (5) + HashAggregate [i_item_id,ss_ext_sales_price] [sum,sum] + Project [ss_ext_sales_price,i_item_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_ext_sales_price] + BroadcastHashJoin [ss_addr_sk,ca_address_sk] + Project [ss_item_sk,ss_addr_sk,ss_ext_sales_price] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_addr_sk,ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_addr_sk,ss_ext_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_moy,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometProject [ca_address_sk] + CometFilter [ca_gmt_offset,ca_address_sk] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_gmt_offset] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (4) + BroadcastHashJoin [i_item_id,i_item_id] + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometProject [i_item_id] + CometFilter [i_color] + CometScan parquet spark_catalog.default.item [i_item_id,i_color] + WholeStageCodegen (12) + HashAggregate [i_item_id,sum] [sum(UnscaledValue(cs_ext_sales_price)),total_sales,sum] + InputAdapter + Exchange [i_item_id] #7 + WholeStageCodegen (11) + HashAggregate [i_item_id,cs_ext_sales_price] [sum,sum] + Project [cs_ext_sales_price,i_item_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Project [cs_item_sk,cs_ext_sales_price] + BroadcastHashJoin [cs_bill_addr_sk,ca_address_sk] + Project [cs_bill_addr_sk,cs_item_sk,cs_ext_sales_price] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [cs_bill_addr_sk,cs_item_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_addr_sk,cs_item_sk,cs_ext_sales_price,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + ReusedExchange [ca_address_sk] #4 + InputAdapter + ReusedExchange [i_item_sk,i_item_id] #5 + WholeStageCodegen (18) + HashAggregate [i_item_id,sum] [sum(UnscaledValue(ws_ext_sales_price)),total_sales,sum] + InputAdapter + Exchange [i_item_id] #8 + WholeStageCodegen (17) + HashAggregate [i_item_id,ws_ext_sales_price] [sum,sum] + Project [ws_ext_sales_price,i_item_id] + BroadcastHashJoin [ws_item_sk,i_item_sk] + Project [ws_item_sk,ws_ext_sales_price] + BroadcastHashJoin [ws_bill_addr_sk,ca_address_sk] + Project [ws_item_sk,ws_bill_addr_sk,ws_ext_sales_price] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ws_bill_addr_sk,ws_item_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_bill_addr_sk,ws_ext_sales_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + ReusedExchange [ca_address_sk] #4 + InputAdapter + ReusedExchange [i_item_sk,i_item_id] #5 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q57/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q57/explain.txt new file mode 100644 index 0000000000..8746c36d68 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q57/explain.txt @@ -0,0 +1,279 @@ +== Physical Plan == +TakeOrderedAndProject (45) ++- * Project (44) + +- * BroadcastHashJoin Inner BuildRight (43) + :- * Project (37) + : +- * BroadcastHashJoin Inner BuildRight (36) + : :- * Project (28) + : : +- * Filter (27) + : : +- Window (26) + : : +- * Filter (25) + : : +- Window (24) + : : +- * Sort (23) + : : +- Exchange (22) + : : +- * HashAggregate (21) + : : +- Exchange (20) + : : +- * HashAggregate (19) + : : +- * Project (18) + : : +- * BroadcastHashJoin Inner BuildRight (17) + : : :- * Project (12) + : : : +- * BroadcastHashJoin Inner BuildRight (11) + : : : :- * Project (9) + : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) + : : : : : +- CometScan parquet spark_catalog.default.item (1) + : : : : +- BroadcastExchange (7) + : : : : +- * ColumnarToRow (6) + : : : : +- CometFilter (5) + : : : : +- CometScan parquet spark_catalog.default.catalog_sales (4) + : : : +- ReusedExchange (10) + : : +- BroadcastExchange (16) + : : +- * ColumnarToRow (15) + : : +- CometFilter (14) + : : +- CometScan parquet spark_catalog.default.call_center (13) + : +- BroadcastExchange (35) + : +- * Project (34) + : +- Window (33) + : +- * Sort (32) + : +- Exchange (31) + : +- * HashAggregate (30) + : +- ReusedExchange (29) + +- BroadcastExchange (42) + +- * Project (41) + +- Window (40) + +- * Sort (39) + +- ReusedExchange (38) + + +(1) Scan parquet spark_catalog.default.item +Output [3]: [i_item_sk#1, i_brand#2, i_category#3] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_category), IsNotNull(i_brand)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [i_item_sk#1, i_brand#2, i_category#3] +Condition : ((isnotnull(i_item_sk#1) AND isnotnull(i_category#3)) AND isnotnull(i_brand#2)) + +(3) ColumnarToRow [codegen id : 4] +Input [3]: [i_item_sk#1, i_brand#2, i_category#3] + +(4) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_call_center_sk#4, cs_item_sk#5, cs_sales_price#6, cs_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#7), dynamicpruningexpression(cs_sold_date_sk#7 IN dynamicpruning#8)] +PushedFilters: [IsNotNull(cs_item_sk), IsNotNull(cs_call_center_sk)] +ReadSchema: struct + +(5) CometFilter +Input [4]: [cs_call_center_sk#4, cs_item_sk#5, cs_sales_price#6, cs_sold_date_sk#7] +Condition : (isnotnull(cs_item_sk#5) AND isnotnull(cs_call_center_sk#4)) + +(6) ColumnarToRow [codegen id : 1] +Input [4]: [cs_call_center_sk#4, cs_item_sk#5, cs_sales_price#6, cs_sold_date_sk#7] + +(7) BroadcastExchange +Input [4]: [cs_call_center_sk#4, cs_item_sk#5, cs_sales_price#6, cs_sold_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[1, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [i_item_sk#1] +Right keys [1]: [cs_item_sk#5] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 4] +Output [5]: [i_brand#2, i_category#3, cs_call_center_sk#4, cs_sales_price#6, cs_sold_date_sk#7] +Input [7]: [i_item_sk#1, i_brand#2, i_category#3, cs_call_center_sk#4, cs_item_sk#5, cs_sales_price#6, cs_sold_date_sk#7] + +(10) ReusedExchange [Reuses operator id: 49] +Output [3]: [d_date_sk#9, d_year#10, d_moy#11] + +(11) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [cs_sold_date_sk#7] +Right keys [1]: [d_date_sk#9] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 4] +Output [6]: [i_brand#2, i_category#3, cs_call_center_sk#4, cs_sales_price#6, d_year#10, d_moy#11] +Input [8]: [i_brand#2, i_category#3, cs_call_center_sk#4, cs_sales_price#6, cs_sold_date_sk#7, d_date_sk#9, d_year#10, d_moy#11] + +(13) Scan parquet spark_catalog.default.call_center +Output [2]: [cc_call_center_sk#12, cc_name#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/call_center] +PushedFilters: [IsNotNull(cc_call_center_sk), IsNotNull(cc_name)] +ReadSchema: struct + +(14) CometFilter +Input [2]: [cc_call_center_sk#12, cc_name#13] +Condition : (isnotnull(cc_call_center_sk#12) AND isnotnull(cc_name#13)) + +(15) ColumnarToRow [codegen id : 3] +Input [2]: [cc_call_center_sk#12, cc_name#13] + +(16) BroadcastExchange +Input [2]: [cc_call_center_sk#12, cc_name#13] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(17) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [cs_call_center_sk#4] +Right keys [1]: [cc_call_center_sk#12] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 4] +Output [6]: [i_brand#2, i_category#3, cs_sales_price#6, d_year#10, d_moy#11, cc_name#13] +Input [8]: [i_brand#2, i_category#3, cs_call_center_sk#4, cs_sales_price#6, d_year#10, d_moy#11, cc_call_center_sk#12, cc_name#13] + +(19) HashAggregate [codegen id : 4] +Input [6]: [i_brand#2, i_category#3, cs_sales_price#6, d_year#10, d_moy#11, cc_name#13] +Keys [5]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11] +Functions [1]: [partial_sum(UnscaledValue(cs_sales_price#6))] +Aggregate Attributes [1]: [sum#14] +Results [6]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum#15] + +(20) Exchange +Input [6]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum#15] +Arguments: hashpartitioning(i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(21) HashAggregate [codegen id : 5] +Input [6]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum#15] +Keys [5]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11] +Functions [1]: [sum(UnscaledValue(cs_sales_price#6))] +Aggregate Attributes [1]: [sum(UnscaledValue(cs_sales_price#6))#16] +Results [7]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, MakeDecimal(sum(UnscaledValue(cs_sales_price#6))#16,17,2) AS sum_sales#17, MakeDecimal(sum(UnscaledValue(cs_sales_price#6))#16,17,2) AS _w0#18] + +(22) Exchange +Input [7]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, _w0#18] +Arguments: hashpartitioning(i_category#3, i_brand#2, cc_name#13, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(23) Sort [codegen id : 6] +Input [7]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, _w0#18] +Arguments: [i_category#3 ASC NULLS FIRST, i_brand#2 ASC NULLS FIRST, cc_name#13 ASC NULLS FIRST, d_year#10 ASC NULLS FIRST, d_moy#11 ASC NULLS FIRST], false, 0 + +(24) Window +Input [7]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, _w0#18] +Arguments: [rank(d_year#10, d_moy#11) windowspecdefinition(i_category#3, i_brand#2, cc_name#13, d_year#10 ASC NULLS FIRST, d_moy#11 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rn#19], [i_category#3, i_brand#2, cc_name#13], [d_year#10 ASC NULLS FIRST, d_moy#11 ASC NULLS FIRST] + +(25) Filter [codegen id : 7] +Input [8]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, _w0#18, rn#19] +Condition : (isnotnull(d_year#10) AND (d_year#10 = 1999)) + +(26) Window +Input [8]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, _w0#18, rn#19] +Arguments: [avg(_w0#18) windowspecdefinition(i_category#3, i_brand#2, cc_name#13, d_year#10, specifiedwindowframe(RowFrame, unboundedpreceding$(), unboundedfollowing$())) AS avg_monthly_sales#20], [i_category#3, i_brand#2, cc_name#13, d_year#10] + +(27) Filter [codegen id : 22] +Input [9]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, _w0#18, rn#19, avg_monthly_sales#20] +Condition : ((isnotnull(avg_monthly_sales#20) AND (avg_monthly_sales#20 > 0.000000)) AND CASE WHEN (avg_monthly_sales#20 > 0.000000) THEN ((abs((sum_sales#17 - avg_monthly_sales#20)) / avg_monthly_sales#20) > 0.1000000000000000) END) + +(28) Project [codegen id : 22] +Output [8]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, avg_monthly_sales#20, rn#19] +Input [9]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, _w0#18, rn#19, avg_monthly_sales#20] + +(29) ReusedExchange [Reuses operator id: 20] +Output [6]: [i_category#21, i_brand#22, cc_name#23, d_year#24, d_moy#25, sum#26] + +(30) HashAggregate [codegen id : 12] +Input [6]: [i_category#21, i_brand#22, cc_name#23, d_year#24, d_moy#25, sum#26] +Keys [5]: [i_category#21, i_brand#22, cc_name#23, d_year#24, d_moy#25] +Functions [1]: [sum(UnscaledValue(cs_sales_price#27))] +Aggregate Attributes [1]: [sum(UnscaledValue(cs_sales_price#27))#16] +Results [6]: [i_category#21, i_brand#22, cc_name#23, d_year#24, d_moy#25, MakeDecimal(sum(UnscaledValue(cs_sales_price#27))#16,17,2) AS sum_sales#28] + +(31) Exchange +Input [6]: [i_category#21, i_brand#22, cc_name#23, d_year#24, d_moy#25, sum_sales#28] +Arguments: hashpartitioning(i_category#21, i_brand#22, cc_name#23, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(32) Sort [codegen id : 13] +Input [6]: [i_category#21, i_brand#22, cc_name#23, d_year#24, d_moy#25, sum_sales#28] +Arguments: [i_category#21 ASC NULLS FIRST, i_brand#22 ASC NULLS FIRST, cc_name#23 ASC NULLS FIRST, d_year#24 ASC NULLS FIRST, d_moy#25 ASC NULLS FIRST], false, 0 + +(33) Window +Input [6]: [i_category#21, i_brand#22, cc_name#23, d_year#24, d_moy#25, sum_sales#28] +Arguments: [rank(d_year#24, d_moy#25) windowspecdefinition(i_category#21, i_brand#22, cc_name#23, d_year#24 ASC NULLS FIRST, d_moy#25 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rn#29], [i_category#21, i_brand#22, cc_name#23], [d_year#24 ASC NULLS FIRST, d_moy#25 ASC NULLS FIRST] + +(34) Project [codegen id : 14] +Output [5]: [i_category#21, i_brand#22, cc_name#23, sum_sales#28, rn#29] +Input [7]: [i_category#21, i_brand#22, cc_name#23, d_year#24, d_moy#25, sum_sales#28, rn#29] + +(35) BroadcastExchange +Input [5]: [i_category#21, i_brand#22, cc_name#23, sum_sales#28, rn#29] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true], input[1, string, true], input[2, string, true], (input[4, int, false] + 1)),false), [plan_id=6] + +(36) BroadcastHashJoin [codegen id : 22] +Left keys [4]: [i_category#3, i_brand#2, cc_name#13, rn#19] +Right keys [4]: [i_category#21, i_brand#22, cc_name#23, (rn#29 + 1)] +Join type: Inner +Join condition: None + +(37) Project [codegen id : 22] +Output [9]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, avg_monthly_sales#20, rn#19, sum_sales#28] +Input [13]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, avg_monthly_sales#20, rn#19, i_category#21, i_brand#22, cc_name#23, sum_sales#28, rn#29] + +(38) ReusedExchange [Reuses operator id: 31] +Output [6]: [i_category#30, i_brand#31, cc_name#32, d_year#33, d_moy#34, sum_sales#35] + +(39) Sort [codegen id : 20] +Input [6]: [i_category#30, i_brand#31, cc_name#32, d_year#33, d_moy#34, sum_sales#35] +Arguments: [i_category#30 ASC NULLS FIRST, i_brand#31 ASC NULLS FIRST, cc_name#32 ASC NULLS FIRST, d_year#33 ASC NULLS FIRST, d_moy#34 ASC NULLS FIRST], false, 0 + +(40) Window +Input [6]: [i_category#30, i_brand#31, cc_name#32, d_year#33, d_moy#34, sum_sales#35] +Arguments: [rank(d_year#33, d_moy#34) windowspecdefinition(i_category#30, i_brand#31, cc_name#32, d_year#33 ASC NULLS FIRST, d_moy#34 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rn#36], [i_category#30, i_brand#31, cc_name#32], [d_year#33 ASC NULLS FIRST, d_moy#34 ASC NULLS FIRST] + +(41) Project [codegen id : 21] +Output [5]: [i_category#30, i_brand#31, cc_name#32, sum_sales#35, rn#36] +Input [7]: [i_category#30, i_brand#31, cc_name#32, d_year#33, d_moy#34, sum_sales#35, rn#36] + +(42) BroadcastExchange +Input [5]: [i_category#30, i_brand#31, cc_name#32, sum_sales#35, rn#36] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true], input[1, string, true], input[2, string, true], (input[4, int, false] - 1)),false), [plan_id=7] + +(43) BroadcastHashJoin [codegen id : 22] +Left keys [4]: [i_category#3, i_brand#2, cc_name#13, rn#19] +Right keys [4]: [i_category#30, i_brand#31, cc_name#32, (rn#36 - 1)] +Join type: Inner +Join condition: None + +(44) Project [codegen id : 22] +Output [9]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, avg_monthly_sales#20, sum_sales#17, sum_sales#28 AS psum#37, sum_sales#35 AS nsum#38] +Input [14]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, avg_monthly_sales#20, rn#19, sum_sales#28, i_category#30, i_brand#31, cc_name#32, sum_sales#35, rn#36] + +(45) TakeOrderedAndProject +Input [9]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, avg_monthly_sales#20, sum_sales#17, psum#37, nsum#38] +Arguments: 100, [(sum_sales#17 - avg_monthly_sales#20) ASC NULLS FIRST, cc_name#13 ASC NULLS FIRST], [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, avg_monthly_sales#20, sum_sales#17, psum#37, nsum#38] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = cs_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (49) ++- * ColumnarToRow (48) + +- CometFilter (47) + +- CometScan parquet spark_catalog.default.date_dim (46) + + +(46) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#9, d_year#10, d_moy#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [Or(Or(EqualTo(d_year,1999),And(EqualTo(d_year,1998),EqualTo(d_moy,12))),And(EqualTo(d_year,2000),EqualTo(d_moy,1))), IsNotNull(d_date_sk)] +ReadSchema: struct + +(47) CometFilter +Input [3]: [d_date_sk#9, d_year#10, d_moy#11] +Condition : ((((d_year#10 = 1999) OR ((d_year#10 = 1998) AND (d_moy#11 = 12))) OR ((d_year#10 = 2000) AND (d_moy#11 = 1))) AND isnotnull(d_date_sk#9)) + +(48) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#9, d_year#10, d_moy#11] + +(49) BroadcastExchange +Input [3]: [d_date_sk#9, d_year#10, d_moy#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q57/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q57/simplified.txt new file mode 100644 index 0000000000..3bc01343ae --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q57/simplified.txt @@ -0,0 +1,81 @@ +TakeOrderedAndProject [sum_sales,avg_monthly_sales,cc_name,i_category,i_brand,d_year,d_moy,psum,nsum] + WholeStageCodegen (22) + Project [i_category,i_brand,cc_name,d_year,d_moy,avg_monthly_sales,sum_sales,sum_sales,sum_sales] + BroadcastHashJoin [i_category,i_brand,cc_name,rn,i_category,i_brand,cc_name,rn] + Project [i_category,i_brand,cc_name,d_year,d_moy,sum_sales,avg_monthly_sales,rn,sum_sales] + BroadcastHashJoin [i_category,i_brand,cc_name,rn,i_category,i_brand,cc_name,rn] + Project [i_category,i_brand,cc_name,d_year,d_moy,sum_sales,avg_monthly_sales,rn] + Filter [avg_monthly_sales,sum_sales] + InputAdapter + Window [_w0,i_category,i_brand,cc_name,d_year] + WholeStageCodegen (7) + Filter [d_year] + InputAdapter + Window [d_year,d_moy,i_category,i_brand,cc_name] + WholeStageCodegen (6) + Sort [i_category,i_brand,cc_name,d_year,d_moy] + InputAdapter + Exchange [i_category,i_brand,cc_name] #1 + WholeStageCodegen (5) + HashAggregate [i_category,i_brand,cc_name,d_year,d_moy,sum] [sum(UnscaledValue(cs_sales_price)),sum_sales,_w0,sum] + InputAdapter + Exchange [i_category,i_brand,cc_name,d_year,d_moy] #2 + WholeStageCodegen (4) + HashAggregate [i_category,i_brand,cc_name,d_year,d_moy,cs_sales_price] [sum,sum] + Project [i_brand,i_category,cs_sales_price,d_year,d_moy,cc_name] + BroadcastHashJoin [cs_call_center_sk,cc_call_center_sk] + Project [i_brand,i_category,cs_call_center_sk,cs_sales_price,d_year,d_moy] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [i_brand,i_category,cs_call_center_sk,cs_sales_price,cs_sold_date_sk] + BroadcastHashJoin [i_item_sk,cs_item_sk] + ColumnarToRow + InputAdapter + CometFilter [i_item_sk,i_category,i_brand] + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_category] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk,cs_call_center_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_call_center_sk,cs_item_sk,cs_sales_price,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_year,d_moy,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + ReusedExchange [d_date_sk,d_year,d_moy] #4 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometFilter [cc_call_center_sk,cc_name] + CometScan parquet spark_catalog.default.call_center [cc_call_center_sk,cc_name] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (14) + Project [i_category,i_brand,cc_name,sum_sales,rn] + InputAdapter + Window [d_year,d_moy,i_category,i_brand,cc_name] + WholeStageCodegen (13) + Sort [i_category,i_brand,cc_name,d_year,d_moy] + InputAdapter + Exchange [i_category,i_brand,cc_name] #7 + WholeStageCodegen (12) + HashAggregate [i_category,i_brand,cc_name,d_year,d_moy,sum] [sum(UnscaledValue(cs_sales_price)),sum_sales,sum] + InputAdapter + ReusedExchange [i_category,i_brand,cc_name,d_year,d_moy,sum] #2 + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (21) + Project [i_category,i_brand,cc_name,sum_sales,rn] + InputAdapter + Window [d_year,d_moy,i_category,i_brand,cc_name] + WholeStageCodegen (20) + Sort [i_category,i_brand,cc_name,d_year,d_moy] + InputAdapter + ReusedExchange [i_category,i_brand,cc_name,d_year,d_moy,sum_sales] #7 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q58/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q58/explain.txt new file mode 100644 index 0000000000..35fedb6d37 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q58/explain.txt @@ -0,0 +1,386 @@ +== Physical Plan == +TakeOrderedAndProject (49) ++- * Project (48) + +- * BroadcastHashJoin Inner BuildRight (47) + :- * Project (32) + : +- * BroadcastHashJoin Inner BuildRight (31) + : :- * Filter (16) + : : +- * HashAggregate (15) + : : +- Exchange (14) + : : +- * HashAggregate (13) + : : +- * Project (12) + : : +- * BroadcastHashJoin Inner BuildRight (11) + : : :- * Project (9) + : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- BroadcastExchange (7) + : : : +- * ColumnarToRow (6) + : : : +- CometFilter (5) + : : : +- CometScan parquet spark_catalog.default.item (4) + : : +- ReusedExchange (10) + : +- BroadcastExchange (30) + : +- * Filter (29) + : +- * HashAggregate (28) + : +- Exchange (27) + : +- * HashAggregate (26) + : +- * Project (25) + : +- * BroadcastHashJoin Inner BuildRight (24) + : :- * Project (22) + : : +- * BroadcastHashJoin Inner BuildRight (21) + : : :- * ColumnarToRow (19) + : : : +- CometFilter (18) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (17) + : : +- ReusedExchange (20) + : +- ReusedExchange (23) + +- BroadcastExchange (46) + +- * Filter (45) + +- * HashAggregate (44) + +- Exchange (43) + +- * HashAggregate (42) + +- * Project (41) + +- * BroadcastHashJoin Inner BuildRight (40) + :- * Project (38) + : +- * BroadcastHashJoin Inner BuildRight (37) + : :- * ColumnarToRow (35) + : : +- CometFilter (34) + : : +- CometScan parquet spark_catalog.default.web_sales (33) + : +- ReusedExchange (36) + +- ReusedExchange (39) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_item_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#3), dynamicpruningexpression(ss_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [ss_item_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3] +Condition : isnotnull(ss_item_sk#1) + +(3) ColumnarToRow [codegen id : 4] +Input [3]: [ss_item_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3] + +(4) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#5, i_item_id#6] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_item_id)] +ReadSchema: struct + +(5) CometFilter +Input [2]: [i_item_sk#5, i_item_id#6] +Condition : (isnotnull(i_item_sk#5) AND isnotnull(i_item_id#6)) + +(6) ColumnarToRow [codegen id : 1] +Input [2]: [i_item_sk#5, i_item_id#6] + +(7) BroadcastExchange +Input [2]: [i_item_sk#5, i_item_id#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#5] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 4] +Output [3]: [ss_ext_sales_price#2, ss_sold_date_sk#3, i_item_id#6] +Input [5]: [ss_item_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3, i_item_sk#5, i_item_id#6] + +(10) ReusedExchange [Reuses operator id: 60] +Output [1]: [d_date_sk#7] + +(11) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_date_sk#3] +Right keys [1]: [d_date_sk#7] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 4] +Output [2]: [ss_ext_sales_price#2, i_item_id#6] +Input [4]: [ss_ext_sales_price#2, ss_sold_date_sk#3, i_item_id#6, d_date_sk#7] + +(13) HashAggregate [codegen id : 4] +Input [2]: [ss_ext_sales_price#2, i_item_id#6] +Keys [1]: [i_item_id#6] +Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#2))] +Aggregate Attributes [1]: [sum#8] +Results [2]: [i_item_id#6, sum#9] + +(14) Exchange +Input [2]: [i_item_id#6, sum#9] +Arguments: hashpartitioning(i_item_id#6, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 15] +Input [2]: [i_item_id#6, sum#9] +Keys [1]: [i_item_id#6] +Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#2))#10] +Results [2]: [i_item_id#6 AS item_id#11, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#2))#10,17,2) AS ss_item_rev#12] + +(16) Filter [codegen id : 15] +Input [2]: [item_id#11, ss_item_rev#12] +Condition : isnotnull(ss_item_rev#12) + +(17) Scan parquet spark_catalog.default.catalog_sales +Output [3]: [cs_item_sk#13, cs_ext_sales_price#14, cs_sold_date_sk#15] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#15), dynamicpruningexpression(cs_sold_date_sk#15 IN dynamicpruning#16)] +PushedFilters: [IsNotNull(cs_item_sk)] +ReadSchema: struct + +(18) CometFilter +Input [3]: [cs_item_sk#13, cs_ext_sales_price#14, cs_sold_date_sk#15] +Condition : isnotnull(cs_item_sk#13) + +(19) ColumnarToRow [codegen id : 8] +Input [3]: [cs_item_sk#13, cs_ext_sales_price#14, cs_sold_date_sk#15] + +(20) ReusedExchange [Reuses operator id: 7] +Output [2]: [i_item_sk#17, i_item_id#18] + +(21) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [cs_item_sk#13] +Right keys [1]: [i_item_sk#17] +Join type: Inner +Join condition: None + +(22) Project [codegen id : 8] +Output [3]: [cs_ext_sales_price#14, cs_sold_date_sk#15, i_item_id#18] +Input [5]: [cs_item_sk#13, cs_ext_sales_price#14, cs_sold_date_sk#15, i_item_sk#17, i_item_id#18] + +(23) ReusedExchange [Reuses operator id: 60] +Output [1]: [d_date_sk#19] + +(24) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [cs_sold_date_sk#15] +Right keys [1]: [d_date_sk#19] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 8] +Output [2]: [cs_ext_sales_price#14, i_item_id#18] +Input [4]: [cs_ext_sales_price#14, cs_sold_date_sk#15, i_item_id#18, d_date_sk#19] + +(26) HashAggregate [codegen id : 8] +Input [2]: [cs_ext_sales_price#14, i_item_id#18] +Keys [1]: [i_item_id#18] +Functions [1]: [partial_sum(UnscaledValue(cs_ext_sales_price#14))] +Aggregate Attributes [1]: [sum#20] +Results [2]: [i_item_id#18, sum#21] + +(27) Exchange +Input [2]: [i_item_id#18, sum#21] +Arguments: hashpartitioning(i_item_id#18, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(28) HashAggregate [codegen id : 9] +Input [2]: [i_item_id#18, sum#21] +Keys [1]: [i_item_id#18] +Functions [1]: [sum(UnscaledValue(cs_ext_sales_price#14))] +Aggregate Attributes [1]: [sum(UnscaledValue(cs_ext_sales_price#14))#22] +Results [2]: [i_item_id#18 AS item_id#23, MakeDecimal(sum(UnscaledValue(cs_ext_sales_price#14))#22,17,2) AS cs_item_rev#24] + +(29) Filter [codegen id : 9] +Input [2]: [item_id#23, cs_item_rev#24] +Condition : isnotnull(cs_item_rev#24) + +(30) BroadcastExchange +Input [2]: [item_id#23, cs_item_rev#24] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=4] + +(31) BroadcastHashJoin [codegen id : 15] +Left keys [1]: [item_id#11] +Right keys [1]: [item_id#23] +Join type: Inner +Join condition: ((((cast(ss_item_rev#12 as decimal(19,3)) >= (0.9 * cs_item_rev#24)) AND (cast(ss_item_rev#12 as decimal(20,3)) <= (1.1 * cs_item_rev#24))) AND (cast(cs_item_rev#24 as decimal(19,3)) >= (0.9 * ss_item_rev#12))) AND (cast(cs_item_rev#24 as decimal(20,3)) <= (1.1 * ss_item_rev#12))) + +(32) Project [codegen id : 15] +Output [3]: [item_id#11, ss_item_rev#12, cs_item_rev#24] +Input [4]: [item_id#11, ss_item_rev#12, item_id#23, cs_item_rev#24] + +(33) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_item_sk#25, ws_ext_sales_price#26, ws_sold_date_sk#27] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#27), dynamicpruningexpression(ws_sold_date_sk#27 IN dynamicpruning#28)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(34) CometFilter +Input [3]: [ws_item_sk#25, ws_ext_sales_price#26, ws_sold_date_sk#27] +Condition : isnotnull(ws_item_sk#25) + +(35) ColumnarToRow [codegen id : 13] +Input [3]: [ws_item_sk#25, ws_ext_sales_price#26, ws_sold_date_sk#27] + +(36) ReusedExchange [Reuses operator id: 7] +Output [2]: [i_item_sk#29, i_item_id#30] + +(37) BroadcastHashJoin [codegen id : 13] +Left keys [1]: [ws_item_sk#25] +Right keys [1]: [i_item_sk#29] +Join type: Inner +Join condition: None + +(38) Project [codegen id : 13] +Output [3]: [ws_ext_sales_price#26, ws_sold_date_sk#27, i_item_id#30] +Input [5]: [ws_item_sk#25, ws_ext_sales_price#26, ws_sold_date_sk#27, i_item_sk#29, i_item_id#30] + +(39) ReusedExchange [Reuses operator id: 60] +Output [1]: [d_date_sk#31] + +(40) BroadcastHashJoin [codegen id : 13] +Left keys [1]: [ws_sold_date_sk#27] +Right keys [1]: [d_date_sk#31] +Join type: Inner +Join condition: None + +(41) Project [codegen id : 13] +Output [2]: [ws_ext_sales_price#26, i_item_id#30] +Input [4]: [ws_ext_sales_price#26, ws_sold_date_sk#27, i_item_id#30, d_date_sk#31] + +(42) HashAggregate [codegen id : 13] +Input [2]: [ws_ext_sales_price#26, i_item_id#30] +Keys [1]: [i_item_id#30] +Functions [1]: [partial_sum(UnscaledValue(ws_ext_sales_price#26))] +Aggregate Attributes [1]: [sum#32] +Results [2]: [i_item_id#30, sum#33] + +(43) Exchange +Input [2]: [i_item_id#30, sum#33] +Arguments: hashpartitioning(i_item_id#30, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(44) HashAggregate [codegen id : 14] +Input [2]: [i_item_id#30, sum#33] +Keys [1]: [i_item_id#30] +Functions [1]: [sum(UnscaledValue(ws_ext_sales_price#26))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_ext_sales_price#26))#34] +Results [2]: [i_item_id#30 AS item_id#35, MakeDecimal(sum(UnscaledValue(ws_ext_sales_price#26))#34,17,2) AS ws_item_rev#36] + +(45) Filter [codegen id : 14] +Input [2]: [item_id#35, ws_item_rev#36] +Condition : isnotnull(ws_item_rev#36) + +(46) BroadcastExchange +Input [2]: [item_id#35, ws_item_rev#36] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=6] + +(47) BroadcastHashJoin [codegen id : 15] +Left keys [1]: [item_id#11] +Right keys [1]: [item_id#35] +Join type: Inner +Join condition: ((((((((cast(ss_item_rev#12 as decimal(19,3)) >= (0.9 * ws_item_rev#36)) AND (cast(ss_item_rev#12 as decimal(20,3)) <= (1.1 * ws_item_rev#36))) AND (cast(cs_item_rev#24 as decimal(19,3)) >= (0.9 * ws_item_rev#36))) AND (cast(cs_item_rev#24 as decimal(20,3)) <= (1.1 * ws_item_rev#36))) AND (cast(ws_item_rev#36 as decimal(19,3)) >= (0.9 * ss_item_rev#12))) AND (cast(ws_item_rev#36 as decimal(20,3)) <= (1.1 * ss_item_rev#12))) AND (cast(ws_item_rev#36 as decimal(19,3)) >= (0.9 * cs_item_rev#24))) AND (cast(ws_item_rev#36 as decimal(20,3)) <= (1.1 * cs_item_rev#24))) + +(48) Project [codegen id : 15] +Output [8]: [item_id#11, ss_item_rev#12, (((ss_item_rev#12 / ((ss_item_rev#12 + cs_item_rev#24) + ws_item_rev#36)) / 3) * 100) AS ss_dev#37, cs_item_rev#24, (((cs_item_rev#24 / ((ss_item_rev#12 + cs_item_rev#24) + ws_item_rev#36)) / 3) * 100) AS cs_dev#38, ws_item_rev#36, (((ws_item_rev#36 / ((ss_item_rev#12 + cs_item_rev#24) + ws_item_rev#36)) / 3) * 100) AS ws_dev#39, (((ss_item_rev#12 + cs_item_rev#24) + ws_item_rev#36) / 3) AS average#40] +Input [5]: [item_id#11, ss_item_rev#12, cs_item_rev#24, item_id#35, ws_item_rev#36] + +(49) TakeOrderedAndProject +Input [8]: [item_id#11, ss_item_rev#12, ss_dev#37, cs_item_rev#24, cs_dev#38, ws_item_rev#36, ws_dev#39, average#40] +Arguments: 100, [item_id#11 ASC NULLS FIRST, ss_item_rev#12 ASC NULLS FIRST], [item_id#11, ss_item_rev#12, ss_dev#37, cs_item_rev#24, cs_dev#38, ws_item_rev#36, ws_dev#39, average#40] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (60) ++- * Project (59) + +- * BroadcastHashJoin LeftSemi BuildRight (58) + :- * ColumnarToRow (52) + : +- CometFilter (51) + : +- CometScan parquet spark_catalog.default.date_dim (50) + +- BroadcastExchange (57) + +- * ColumnarToRow (56) + +- CometProject (55) + +- CometFilter (54) + +- CometScan parquet spark_catalog.default.date_dim (53) + + +(50) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#7, d_date#41] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date_sk)] +ReadSchema: struct + +(51) CometFilter +Input [2]: [d_date_sk#7, d_date#41] +Condition : isnotnull(d_date_sk#7) + +(52) ColumnarToRow [codegen id : 2] +Input [2]: [d_date_sk#7, d_date#41] + +(53) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date#42, d_week_seq#43] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_week_seq), EqualTo(d_week_seq,ScalarSubquery#44)] +ReadSchema: struct + +(54) CometFilter +Input [2]: [d_date#42, d_week_seq#43] +Condition : (isnotnull(d_week_seq#43) AND (d_week_seq#43 = ReusedSubquery Subquery scalar-subquery#44, [id=#45])) + +(55) CometProject +Input [2]: [d_date#42, d_week_seq#43] +Arguments: [d_date#42], [d_date#42] + +(56) ColumnarToRow [codegen id : 1] +Input [1]: [d_date#42] + +(57) BroadcastExchange +Input [1]: [d_date#42] +Arguments: HashedRelationBroadcastMode(List(input[0, date, true]),false), [plan_id=7] + +(58) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [d_date#41] +Right keys [1]: [d_date#42] +Join type: LeftSemi +Join condition: None + +(59) Project [codegen id : 2] +Output [1]: [d_date_sk#7] +Input [2]: [d_date_sk#7, d_date#41] + +(60) BroadcastExchange +Input [1]: [d_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + +Subquery:2 Hosting operator id = 54 Hosting Expression = ReusedSubquery Subquery scalar-subquery#44, [id=#45] + +Subquery:3 Hosting operator id = 53 Hosting Expression = Subquery scalar-subquery#44, [id=#45] +* ColumnarToRow (64) ++- CometProject (63) + +- CometFilter (62) + +- CometScan parquet spark_catalog.default.date_dim (61) + + +(61) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date#46, d_week_seq#47] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), EqualTo(d_date,2000-01-03)] +ReadSchema: struct + +(62) CometFilter +Input [2]: [d_date#46, d_week_seq#47] +Condition : (isnotnull(d_date#46) AND (d_date#46 = 2000-01-03)) + +(63) CometProject +Input [2]: [d_date#46, d_week_seq#47] +Arguments: [d_week_seq#47], [d_week_seq#47] + +(64) ColumnarToRow [codegen id : 1] +Input [1]: [d_week_seq#47] + +Subquery:4 Hosting operator id = 17 Hosting Expression = cs_sold_date_sk#15 IN dynamicpruning#4 + +Subquery:5 Hosting operator id = 33 Hosting Expression = ws_sold_date_sk#27 IN dynamicpruning#4 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q58/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q58/simplified.txt new file mode 100644 index 0000000000..c7ed479add --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q58/simplified.txt @@ -0,0 +1,98 @@ +TakeOrderedAndProject [item_id,ss_item_rev,ss_dev,cs_item_rev,cs_dev,ws_item_rev,ws_dev,average] + WholeStageCodegen (15) + Project [item_id,ss_item_rev,cs_item_rev,ws_item_rev] + BroadcastHashJoin [item_id,item_id,ss_item_rev,ws_item_rev,cs_item_rev] + Project [item_id,ss_item_rev,cs_item_rev] + BroadcastHashJoin [item_id,item_id,ss_item_rev,cs_item_rev] + Filter [ss_item_rev] + HashAggregate [i_item_id,sum] [sum(UnscaledValue(ss_ext_sales_price)),item_id,ss_item_rev,sum] + InputAdapter + Exchange [i_item_id] #1 + WholeStageCodegen (4) + HashAggregate [i_item_id,ss_ext_sales_price] [sum,sum] + Project [ss_ext_sales_price,i_item_id] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_ext_sales_price,ss_sold_date_sk,i_item_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ext_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (2) + Project [d_date_sk] + BroadcastHashJoin [d_date,d_date] + ColumnarToRow + InputAdapter + CometFilter [d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date] + CometFilter [d_week_seq] + ReusedSubquery [d_week_seq] #2 + CometScan parquet spark_catalog.default.date_dim [d_date,d_week_seq] + Subquery #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_week_seq] + CometFilter [d_date] + CometScan parquet spark_catalog.default.date_dim [d_date,d_week_seq] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk,i_item_id] + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (9) + Filter [cs_item_rev] + HashAggregate [i_item_id,sum] [sum(UnscaledValue(cs_ext_sales_price)),item_id,cs_item_rev,sum] + InputAdapter + Exchange [i_item_id] #6 + WholeStageCodegen (8) + HashAggregate [i_item_id,cs_ext_sales_price] [sum,sum] + Project [cs_ext_sales_price,i_item_id] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_ext_sales_price,cs_sold_date_sk,i_item_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_ext_sales_price,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [i_item_sk,i_item_id] #4 + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (14) + Filter [ws_item_rev] + HashAggregate [i_item_id,sum] [sum(UnscaledValue(ws_ext_sales_price)),item_id,ws_item_rev,sum] + InputAdapter + Exchange [i_item_id] #8 + WholeStageCodegen (13) + HashAggregate [i_item_id,ws_ext_sales_price] [sum,sum] + Project [ws_ext_sales_price,i_item_id] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_ext_sales_price,ws_sold_date_sk,i_item_id] + BroadcastHashJoin [ws_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_ext_sales_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [i_item_sk,i_item_id] #4 + InputAdapter + ReusedExchange [d_date_sk] #2 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q59/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q59/explain.txt new file mode 100644 index 0000000000..023c54bdd3 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q59/explain.txt @@ -0,0 +1,256 @@ +== Physical Plan == +TakeOrderedAndProject (44) ++- * Project (43) + +- * BroadcastHashJoin Inner BuildRight (42) + :- * Project (25) + : +- * BroadcastHashJoin Inner BuildRight (24) + : :- * Project (18) + : : +- * BroadcastHashJoin Inner BuildRight (17) + : : :- * HashAggregate (12) + : : : +- Exchange (11) + : : : +- * HashAggregate (10) + : : : +- * Project (9) + : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- BroadcastExchange (7) + : : : +- * ColumnarToRow (6) + : : : +- CometFilter (5) + : : : +- CometScan parquet spark_catalog.default.date_dim (4) + : : +- BroadcastExchange (16) + : : +- * ColumnarToRow (15) + : : +- CometFilter (14) + : : +- CometScan parquet spark_catalog.default.store (13) + : +- BroadcastExchange (23) + : +- * ColumnarToRow (22) + : +- CometProject (21) + : +- CometFilter (20) + : +- CometScan parquet spark_catalog.default.date_dim (19) + +- BroadcastExchange (41) + +- * Project (40) + +- * BroadcastHashJoin Inner BuildRight (39) + :- * Project (33) + : +- * BroadcastHashJoin Inner BuildRight (32) + : :- * HashAggregate (27) + : : +- ReusedExchange (26) + : +- BroadcastExchange (31) + : +- * ColumnarToRow (30) + : +- CometFilter (29) + : +- CometScan parquet spark_catalog.default.store (28) + +- BroadcastExchange (38) + +- * ColumnarToRow (37) + +- CometProject (36) + +- CometFilter (35) + +- CometScan parquet spark_catalog.default.date_dim (34) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_store_sk#1, ss_sales_price#2, ss_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#3)] +PushedFilters: [IsNotNull(ss_store_sk)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [ss_store_sk#1, ss_sales_price#2, ss_sold_date_sk#3] +Condition : isnotnull(ss_store_sk#1) + +(3) ColumnarToRow [codegen id : 2] +Input [3]: [ss_store_sk#1, ss_sales_price#2, ss_sold_date_sk#3] + +(4) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#4, d_week_seq#5, d_day_name#6] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date_sk), IsNotNull(d_week_seq)] +ReadSchema: struct + +(5) CometFilter +Input [3]: [d_date_sk#4, d_week_seq#5, d_day_name#6] +Condition : (isnotnull(d_date_sk#4) AND isnotnull(d_week_seq#5)) + +(6) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#4, d_week_seq#5, d_day_name#6] + +(7) BroadcastExchange +Input [3]: [d_date_sk#4, d_week_seq#5, d_day_name#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [ss_sold_date_sk#3] +Right keys [1]: [d_date_sk#4] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 2] +Output [4]: [ss_store_sk#1, ss_sales_price#2, d_week_seq#5, d_day_name#6] +Input [6]: [ss_store_sk#1, ss_sales_price#2, ss_sold_date_sk#3, d_date_sk#4, d_week_seq#5, d_day_name#6] + +(10) HashAggregate [codegen id : 2] +Input [4]: [ss_store_sk#1, ss_sales_price#2, d_week_seq#5, d_day_name#6] +Keys [2]: [d_week_seq#5, ss_store_sk#1] +Functions [7]: [partial_sum(UnscaledValue(CASE WHEN (d_day_name#6 = Sunday ) THEN ss_sales_price#2 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#6 = Monday ) THEN ss_sales_price#2 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#6 = Tuesday ) THEN ss_sales_price#2 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#6 = Wednesday) THEN ss_sales_price#2 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#6 = Thursday ) THEN ss_sales_price#2 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#6 = Friday ) THEN ss_sales_price#2 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#6 = Saturday ) THEN ss_sales_price#2 END))] +Aggregate Attributes [7]: [sum#7, sum#8, sum#9, sum#10, sum#11, sum#12, sum#13] +Results [9]: [d_week_seq#5, ss_store_sk#1, sum#14, sum#15, sum#16, sum#17, sum#18, sum#19, sum#20] + +(11) Exchange +Input [9]: [d_week_seq#5, ss_store_sk#1, sum#14, sum#15, sum#16, sum#17, sum#18, sum#19, sum#20] +Arguments: hashpartitioning(d_week_seq#5, ss_store_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(12) HashAggregate [codegen id : 10] +Input [9]: [d_week_seq#5, ss_store_sk#1, sum#14, sum#15, sum#16, sum#17, sum#18, sum#19, sum#20] +Keys [2]: [d_week_seq#5, ss_store_sk#1] +Functions [7]: [sum(UnscaledValue(CASE WHEN (d_day_name#6 = Sunday ) THEN ss_sales_price#2 END)), sum(UnscaledValue(CASE WHEN (d_day_name#6 = Monday ) THEN ss_sales_price#2 END)), sum(UnscaledValue(CASE WHEN (d_day_name#6 = Tuesday ) THEN ss_sales_price#2 END)), sum(UnscaledValue(CASE WHEN (d_day_name#6 = Wednesday) THEN ss_sales_price#2 END)), sum(UnscaledValue(CASE WHEN (d_day_name#6 = Thursday ) THEN ss_sales_price#2 END)), sum(UnscaledValue(CASE WHEN (d_day_name#6 = Friday ) THEN ss_sales_price#2 END)), sum(UnscaledValue(CASE WHEN (d_day_name#6 = Saturday ) THEN ss_sales_price#2 END))] +Aggregate Attributes [7]: [sum(UnscaledValue(CASE WHEN (d_day_name#6 = Sunday ) THEN ss_sales_price#2 END))#21, sum(UnscaledValue(CASE WHEN (d_day_name#6 = Monday ) THEN ss_sales_price#2 END))#22, sum(UnscaledValue(CASE WHEN (d_day_name#6 = Tuesday ) THEN ss_sales_price#2 END))#23, sum(UnscaledValue(CASE WHEN (d_day_name#6 = Wednesday) THEN ss_sales_price#2 END))#24, sum(UnscaledValue(CASE WHEN (d_day_name#6 = Thursday ) THEN ss_sales_price#2 END))#25, sum(UnscaledValue(CASE WHEN (d_day_name#6 = Friday ) THEN ss_sales_price#2 END))#26, sum(UnscaledValue(CASE WHEN (d_day_name#6 = Saturday ) THEN ss_sales_price#2 END))#27] +Results [9]: [d_week_seq#5, ss_store_sk#1, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#6 = Sunday ) THEN ss_sales_price#2 END))#21,17,2) AS sun_sales#28, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#6 = Monday ) THEN ss_sales_price#2 END))#22,17,2) AS mon_sales#29, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#6 = Tuesday ) THEN ss_sales_price#2 END))#23,17,2) AS tue_sales#30, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#6 = Wednesday) THEN ss_sales_price#2 END))#24,17,2) AS wed_sales#31, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#6 = Thursday ) THEN ss_sales_price#2 END))#25,17,2) AS thu_sales#32, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#6 = Friday ) THEN ss_sales_price#2 END))#26,17,2) AS fri_sales#33, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#6 = Saturday ) THEN ss_sales_price#2 END))#27,17,2) AS sat_sales#34] + +(13) Scan parquet spark_catalog.default.store +Output [3]: [s_store_sk#35, s_store_id#36, s_store_name#37] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk), IsNotNull(s_store_id)] +ReadSchema: struct + +(14) CometFilter +Input [3]: [s_store_sk#35, s_store_id#36, s_store_name#37] +Condition : (isnotnull(s_store_sk#35) AND isnotnull(s_store_id#36)) + +(15) ColumnarToRow [codegen id : 3] +Input [3]: [s_store_sk#35, s_store_id#36, s_store_name#37] + +(16) BroadcastExchange +Input [3]: [s_store_sk#35, s_store_id#36, s_store_name#37] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(17) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [ss_store_sk#1] +Right keys [1]: [s_store_sk#35] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 10] +Output [10]: [d_week_seq#5, sun_sales#28, mon_sales#29, tue_sales#30, wed_sales#31, thu_sales#32, fri_sales#33, sat_sales#34, s_store_id#36, s_store_name#37] +Input [12]: [d_week_seq#5, ss_store_sk#1, sun_sales#28, mon_sales#29, tue_sales#30, wed_sales#31, thu_sales#32, fri_sales#33, sat_sales#34, s_store_sk#35, s_store_id#36, s_store_name#37] + +(19) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_month_seq#38, d_week_seq#39] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1212), LessThanOrEqual(d_month_seq,1223), IsNotNull(d_week_seq)] +ReadSchema: struct + +(20) CometFilter +Input [2]: [d_month_seq#38, d_week_seq#39] +Condition : (((isnotnull(d_month_seq#38) AND (d_month_seq#38 >= 1212)) AND (d_month_seq#38 <= 1223)) AND isnotnull(d_week_seq#39)) + +(21) CometProject +Input [2]: [d_month_seq#38, d_week_seq#39] +Arguments: [d_week_seq#39], [d_week_seq#39] + +(22) ColumnarToRow [codegen id : 4] +Input [1]: [d_week_seq#39] + +(23) BroadcastExchange +Input [1]: [d_week_seq#39] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(24) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [d_week_seq#5] +Right keys [1]: [d_week_seq#39] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 10] +Output [10]: [s_store_name#37 AS s_store_name1#40, d_week_seq#5 AS d_week_seq1#41, s_store_id#36 AS s_store_id1#42, sun_sales#28 AS sun_sales1#43, mon_sales#29 AS mon_sales1#44, tue_sales#30 AS tue_sales1#45, wed_sales#31 AS wed_sales1#46, thu_sales#32 AS thu_sales1#47, fri_sales#33 AS fri_sales1#48, sat_sales#34 AS sat_sales1#49] +Input [11]: [d_week_seq#5, sun_sales#28, mon_sales#29, tue_sales#30, wed_sales#31, thu_sales#32, fri_sales#33, sat_sales#34, s_store_id#36, s_store_name#37, d_week_seq#39] + +(26) ReusedExchange [Reuses operator id: 11] +Output [9]: [d_week_seq#50, ss_store_sk#51, sum#52, sum#53, sum#54, sum#55, sum#56, sum#57, sum#58] + +(27) HashAggregate [codegen id : 9] +Input [9]: [d_week_seq#50, ss_store_sk#51, sum#52, sum#53, sum#54, sum#55, sum#56, sum#57, sum#58] +Keys [2]: [d_week_seq#50, ss_store_sk#51] +Functions [7]: [sum(UnscaledValue(CASE WHEN (d_day_name#59 = Sunday ) THEN ss_sales_price#60 END)), sum(UnscaledValue(CASE WHEN (d_day_name#59 = Monday ) THEN ss_sales_price#60 END)), sum(UnscaledValue(CASE WHEN (d_day_name#59 = Tuesday ) THEN ss_sales_price#60 END)), sum(UnscaledValue(CASE WHEN (d_day_name#59 = Wednesday) THEN ss_sales_price#60 END)), sum(UnscaledValue(CASE WHEN (d_day_name#59 = Thursday ) THEN ss_sales_price#60 END)), sum(UnscaledValue(CASE WHEN (d_day_name#59 = Friday ) THEN ss_sales_price#60 END)), sum(UnscaledValue(CASE WHEN (d_day_name#59 = Saturday ) THEN ss_sales_price#60 END))] +Aggregate Attributes [7]: [sum(UnscaledValue(CASE WHEN (d_day_name#59 = Sunday ) THEN ss_sales_price#60 END))#21, sum(UnscaledValue(CASE WHEN (d_day_name#59 = Monday ) THEN ss_sales_price#60 END))#22, sum(UnscaledValue(CASE WHEN (d_day_name#59 = Tuesday ) THEN ss_sales_price#60 END))#23, sum(UnscaledValue(CASE WHEN (d_day_name#59 = Wednesday) THEN ss_sales_price#60 END))#24, sum(UnscaledValue(CASE WHEN (d_day_name#59 = Thursday ) THEN ss_sales_price#60 END))#25, sum(UnscaledValue(CASE WHEN (d_day_name#59 = Friday ) THEN ss_sales_price#60 END))#26, sum(UnscaledValue(CASE WHEN (d_day_name#59 = Saturday ) THEN ss_sales_price#60 END))#27] +Results [9]: [d_week_seq#50, ss_store_sk#51, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#59 = Sunday ) THEN ss_sales_price#60 END))#21,17,2) AS sun_sales#61, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#59 = Monday ) THEN ss_sales_price#60 END))#22,17,2) AS mon_sales#62, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#59 = Tuesday ) THEN ss_sales_price#60 END))#23,17,2) AS tue_sales#63, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#59 = Wednesday) THEN ss_sales_price#60 END))#24,17,2) AS wed_sales#64, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#59 = Thursday ) THEN ss_sales_price#60 END))#25,17,2) AS thu_sales#65, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#59 = Friday ) THEN ss_sales_price#60 END))#26,17,2) AS fri_sales#66, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#59 = Saturday ) THEN ss_sales_price#60 END))#27,17,2) AS sat_sales#67] + +(28) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#68, s_store_id#69] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk), IsNotNull(s_store_id)] +ReadSchema: struct + +(29) CometFilter +Input [2]: [s_store_sk#68, s_store_id#69] +Condition : (isnotnull(s_store_sk#68) AND isnotnull(s_store_id#69)) + +(30) ColumnarToRow [codegen id : 7] +Input [2]: [s_store_sk#68, s_store_id#69] + +(31) BroadcastExchange +Input [2]: [s_store_sk#68, s_store_id#69] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(32) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_store_sk#51] +Right keys [1]: [s_store_sk#68] +Join type: Inner +Join condition: None + +(33) Project [codegen id : 9] +Output [9]: [d_week_seq#50, sun_sales#61, mon_sales#62, tue_sales#63, wed_sales#64, thu_sales#65, fri_sales#66, sat_sales#67, s_store_id#69] +Input [11]: [d_week_seq#50, ss_store_sk#51, sun_sales#61, mon_sales#62, tue_sales#63, wed_sales#64, thu_sales#65, fri_sales#66, sat_sales#67, s_store_sk#68, s_store_id#69] + +(34) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_month_seq#70, d_week_seq#71] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1224), LessThanOrEqual(d_month_seq,1235), IsNotNull(d_week_seq)] +ReadSchema: struct + +(35) CometFilter +Input [2]: [d_month_seq#70, d_week_seq#71] +Condition : (((isnotnull(d_month_seq#70) AND (d_month_seq#70 >= 1224)) AND (d_month_seq#70 <= 1235)) AND isnotnull(d_week_seq#71)) + +(36) CometProject +Input [2]: [d_month_seq#70, d_week_seq#71] +Arguments: [d_week_seq#71], [d_week_seq#71] + +(37) ColumnarToRow [codegen id : 8] +Input [1]: [d_week_seq#71] + +(38) BroadcastExchange +Input [1]: [d_week_seq#71] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6] + +(39) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [d_week_seq#50] +Right keys [1]: [d_week_seq#71] +Join type: Inner +Join condition: None + +(40) Project [codegen id : 9] +Output [9]: [d_week_seq#50 AS d_week_seq2#72, s_store_id#69 AS s_store_id2#73, sun_sales#61 AS sun_sales2#74, mon_sales#62 AS mon_sales2#75, tue_sales#63 AS tue_sales2#76, wed_sales#64 AS wed_sales2#77, thu_sales#65 AS thu_sales2#78, fri_sales#66 AS fri_sales2#79, sat_sales#67 AS sat_sales2#80] +Input [10]: [d_week_seq#50, sun_sales#61, mon_sales#62, tue_sales#63, wed_sales#64, thu_sales#65, fri_sales#66, sat_sales#67, s_store_id#69, d_week_seq#71] + +(41) BroadcastExchange +Input [9]: [d_week_seq2#72, s_store_id2#73, sun_sales2#74, mon_sales2#75, tue_sales2#76, wed_sales2#77, thu_sales2#78, fri_sales2#79, sat_sales2#80] +Arguments: HashedRelationBroadcastMode(List(input[1, string, true], (input[0, int, true] - 52)),false), [plan_id=7] + +(42) BroadcastHashJoin [codegen id : 10] +Left keys [2]: [s_store_id1#42, d_week_seq1#41] +Right keys [2]: [s_store_id2#73, (d_week_seq2#72 - 52)] +Join type: Inner +Join condition: None + +(43) Project [codegen id : 10] +Output [10]: [s_store_name1#40, s_store_id1#42, d_week_seq1#41, (sun_sales1#43 / sun_sales2#74) AS (sun_sales1 / sun_sales2)#81, (mon_sales1#44 / mon_sales2#75) AS (mon_sales1 / mon_sales2)#82, (tue_sales1#45 / tue_sales2#76) AS (tue_sales1 / tue_sales2)#83, (wed_sales1#46 / wed_sales2#77) AS (wed_sales1 / wed_sales2)#84, (thu_sales1#47 / thu_sales2#78) AS (thu_sales1 / thu_sales2)#85, (fri_sales1#48 / fri_sales2#79) AS (fri_sales1 / fri_sales2)#86, (sat_sales1#49 / sat_sales2#80) AS (sat_sales1 / sat_sales2)#87] +Input [19]: [s_store_name1#40, d_week_seq1#41, s_store_id1#42, sun_sales1#43, mon_sales1#44, tue_sales1#45, wed_sales1#46, thu_sales1#47, fri_sales1#48, sat_sales1#49, d_week_seq2#72, s_store_id2#73, sun_sales2#74, mon_sales2#75, tue_sales2#76, wed_sales2#77, thu_sales2#78, fri_sales2#79, sat_sales2#80] + +(44) TakeOrderedAndProject +Input [10]: [s_store_name1#40, s_store_id1#42, d_week_seq1#41, (sun_sales1 / sun_sales2)#81, (mon_sales1 / mon_sales2)#82, (tue_sales1 / tue_sales2)#83, (wed_sales1 / wed_sales2)#84, (thu_sales1 / thu_sales2)#85, (fri_sales1 / fri_sales2)#86, (sat_sales1 / sat_sales2)#87] +Arguments: 100, [s_store_name1#40 ASC NULLS FIRST, s_store_id1#42 ASC NULLS FIRST, d_week_seq1#41 ASC NULLS FIRST], [s_store_name1#40, s_store_id1#42, d_week_seq1#41, (sun_sales1 / sun_sales2)#81, (mon_sales1 / mon_sales2)#82, (tue_sales1 / tue_sales2)#83, (wed_sales1 / wed_sales2)#84, (thu_sales1 / thu_sales2)#85, (fri_sales1 / fri_sales2)#86, (sat_sales1 / sat_sales2)#87] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q59/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q59/simplified.txt new file mode 100644 index 0000000000..9ad61e946e --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q59/simplified.txt @@ -0,0 +1,66 @@ +TakeOrderedAndProject [s_store_name1,s_store_id1,d_week_seq1,(sun_sales1 / sun_sales2),(mon_sales1 / mon_sales2),(tue_sales1 / tue_sales2),(wed_sales1 / wed_sales2),(thu_sales1 / thu_sales2),(fri_sales1 / fri_sales2),(sat_sales1 / sat_sales2)] + WholeStageCodegen (10) + Project [s_store_name1,s_store_id1,d_week_seq1,sun_sales1,sun_sales2,mon_sales1,mon_sales2,tue_sales1,tue_sales2,wed_sales1,wed_sales2,thu_sales1,thu_sales2,fri_sales1,fri_sales2,sat_sales1,sat_sales2] + BroadcastHashJoin [s_store_id1,d_week_seq1,s_store_id2,d_week_seq2] + Project [s_store_name,d_week_seq,s_store_id,sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales] + BroadcastHashJoin [d_week_seq,d_week_seq] + Project [d_week_seq,sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales,s_store_id,s_store_name] + BroadcastHashJoin [ss_store_sk,s_store_sk] + HashAggregate [d_week_seq,ss_store_sk,sum,sum,sum,sum,sum,sum,sum] [sum(UnscaledValue(CASE WHEN (d_day_name = Sunday ) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Monday ) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Tuesday ) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Wednesday) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Thursday ) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Friday ) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Saturday ) THEN ss_sales_price END)),sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales,sum,sum,sum,sum,sum,sum,sum] + InputAdapter + Exchange [d_week_seq,ss_store_sk] #1 + WholeStageCodegen (2) + HashAggregate [d_week_seq,ss_store_sk,d_day_name,ss_sales_price] [sum,sum,sum,sum,sum,sum,sum,sum,sum,sum,sum,sum,sum,sum] + Project [ss_store_sk,ss_sales_price,d_week_seq,d_day_name] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_store_sk,ss_sales_price,ss_sold_date_sk] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_date_sk,d_week_seq] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_week_seq,d_day_name] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometFilter [s_store_sk,s_store_id] + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_id,s_store_name] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (4) + ColumnarToRow + InputAdapter + CometProject [d_week_seq] + CometFilter [d_month_seq,d_week_seq] + CometScan parquet spark_catalog.default.date_dim [d_month_seq,d_week_seq] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (9) + Project [d_week_seq,s_store_id,sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales] + BroadcastHashJoin [d_week_seq,d_week_seq] + Project [d_week_seq,sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales,s_store_id] + BroadcastHashJoin [ss_store_sk,s_store_sk] + HashAggregate [d_week_seq,ss_store_sk,sum,sum,sum,sum,sum,sum,sum] [sum(UnscaledValue(CASE WHEN (d_day_name = Sunday ) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Monday ) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Tuesday ) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Wednesday) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Thursday ) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Friday ) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Saturday ) THEN ss_sales_price END)),sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales,sum,sum,sum,sum,sum,sum,sum] + InputAdapter + ReusedExchange [d_week_seq,ss_store_sk,sum,sum,sum,sum,sum,sum,sum] #1 + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (7) + ColumnarToRow + InputAdapter + CometFilter [s_store_sk,s_store_id] + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_id] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (8) + ColumnarToRow + InputAdapter + CometProject [d_week_seq] + CometFilter [d_month_seq,d_week_seq] + CometScan parquet spark_catalog.default.date_dim [d_month_seq,d_week_seq] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q6/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q6/explain.txt new file mode 100644 index 0000000000..f8ae10ebef --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q6/explain.txt @@ -0,0 +1,309 @@ +== Physical Plan == +TakeOrderedAndProject (39) ++- * Filter (38) + +- * HashAggregate (37) + +- Exchange (36) + +- * HashAggregate (35) + +- * Project (34) + +- * BroadcastHashJoin Inner BuildRight (33) + :- * Project (18) + : +- * BroadcastHashJoin Inner BuildRight (17) + : :- * Project (15) + : : +- * BroadcastHashJoin Inner BuildRight (14) + : : :- * Project (9) + : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.customer_address (1) + : : : +- BroadcastExchange (7) + : : : +- * ColumnarToRow (6) + : : : +- CometFilter (5) + : : : +- CometScan parquet spark_catalog.default.customer (4) + : : +- BroadcastExchange (13) + : : +- * ColumnarToRow (12) + : : +- CometFilter (11) + : : +- CometScan parquet spark_catalog.default.store_sales (10) + : +- ReusedExchange (16) + +- BroadcastExchange (32) + +- * Project (31) + +- * BroadcastHashJoin Inner BuildRight (30) + :- * ColumnarToRow (21) + : +- CometFilter (20) + : +- CometScan parquet spark_catalog.default.item (19) + +- BroadcastExchange (29) + +- * Filter (28) + +- * HashAggregate (27) + +- Exchange (26) + +- * HashAggregate (25) + +- * ColumnarToRow (24) + +- CometFilter (23) + +- CometScan parquet spark_catalog.default.item (22) + + +(1) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#1, ca_state#2] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk)] +ReadSchema: struct + +(2) CometFilter +Input [2]: [ca_address_sk#1, ca_state#2] +Condition : isnotnull(ca_address_sk#1) + +(3) ColumnarToRow [codegen id : 7] +Input [2]: [ca_address_sk#1, ca_state#2] + +(4) Scan parquet spark_catalog.default.customer +Output [2]: [c_customer_sk#3, c_current_addr_sk#4] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_current_addr_sk), IsNotNull(c_customer_sk)] +ReadSchema: struct + +(5) CometFilter +Input [2]: [c_customer_sk#3, c_current_addr_sk#4] +Condition : (isnotnull(c_current_addr_sk#4) AND isnotnull(c_customer_sk#3)) + +(6) ColumnarToRow [codegen id : 1] +Input [2]: [c_customer_sk#3, c_current_addr_sk#4] + +(7) BroadcastExchange +Input [2]: [c_customer_sk#3, c_current_addr_sk#4] +Arguments: HashedRelationBroadcastMode(List(cast(input[1, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [ca_address_sk#1] +Right keys [1]: [c_current_addr_sk#4] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 7] +Output [2]: [ca_state#2, c_customer_sk#3] +Input [4]: [ca_address_sk#1, ca_state#2, c_customer_sk#3, c_current_addr_sk#4] + +(10) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_item_sk#5, ss_customer_sk#6, ss_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sold_date_sk#7 IN dynamicpruning#8)] +PushedFilters: [IsNotNull(ss_customer_sk), IsNotNull(ss_item_sk)] +ReadSchema: struct + +(11) CometFilter +Input [3]: [ss_item_sk#5, ss_customer_sk#6, ss_sold_date_sk#7] +Condition : (isnotnull(ss_customer_sk#6) AND isnotnull(ss_item_sk#5)) + +(12) ColumnarToRow [codegen id : 2] +Input [3]: [ss_item_sk#5, ss_customer_sk#6, ss_sold_date_sk#7] + +(13) BroadcastExchange +Input [3]: [ss_item_sk#5, ss_customer_sk#6, ss_sold_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[1, int, false] as bigint)),false), [plan_id=2] + +(14) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [c_customer_sk#3] +Right keys [1]: [ss_customer_sk#6] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 7] +Output [3]: [ca_state#2, ss_item_sk#5, ss_sold_date_sk#7] +Input [5]: [ca_state#2, c_customer_sk#3, ss_item_sk#5, ss_customer_sk#6, ss_sold_date_sk#7] + +(16) ReusedExchange [Reuses operator id: 44] +Output [1]: [d_date_sk#9] + +(17) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [ss_sold_date_sk#7] +Right keys [1]: [d_date_sk#9] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 7] +Output [2]: [ca_state#2, ss_item_sk#5] +Input [4]: [ca_state#2, ss_item_sk#5, ss_sold_date_sk#7, d_date_sk#9] + +(19) Scan parquet spark_catalog.default.item +Output [3]: [i_item_sk#10, i_current_price#11, i_category#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_current_price), IsNotNull(i_category), IsNotNull(i_item_sk)] +ReadSchema: struct + +(20) CometFilter +Input [3]: [i_item_sk#10, i_current_price#11, i_category#12] +Condition : ((isnotnull(i_current_price#11) AND isnotnull(i_category#12)) AND isnotnull(i_item_sk#10)) + +(21) ColumnarToRow [codegen id : 6] +Input [3]: [i_item_sk#10, i_current_price#11, i_category#12] + +(22) Scan parquet spark_catalog.default.item +Output [2]: [i_current_price#13, i_category#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_category)] +ReadSchema: struct + +(23) CometFilter +Input [2]: [i_current_price#13, i_category#14] +Condition : isnotnull(i_category#14) + +(24) ColumnarToRow [codegen id : 4] +Input [2]: [i_current_price#13, i_category#14] + +(25) HashAggregate [codegen id : 4] +Input [2]: [i_current_price#13, i_category#14] +Keys [1]: [i_category#14] +Functions [1]: [partial_avg(UnscaledValue(i_current_price#13))] +Aggregate Attributes [2]: [sum#15, count#16] +Results [3]: [i_category#14, sum#17, count#18] + +(26) Exchange +Input [3]: [i_category#14, sum#17, count#18] +Arguments: hashpartitioning(i_category#14, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(27) HashAggregate [codegen id : 5] +Input [3]: [i_category#14, sum#17, count#18] +Keys [1]: [i_category#14] +Functions [1]: [avg(UnscaledValue(i_current_price#13))] +Aggregate Attributes [1]: [avg(UnscaledValue(i_current_price#13))#19] +Results [2]: [cast((avg(UnscaledValue(i_current_price#13))#19 / 100.0) as decimal(11,6)) AS avg(i_current_price)#20, i_category#14] + +(28) Filter [codegen id : 5] +Input [2]: [avg(i_current_price)#20, i_category#14] +Condition : isnotnull(avg(i_current_price)#20) + +(29) BroadcastExchange +Input [2]: [avg(i_current_price)#20, i_category#14] +Arguments: HashedRelationBroadcastMode(List(input[1, string, true]),false), [plan_id=4] + +(30) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [i_category#12] +Right keys [1]: [i_category#14] +Join type: Inner +Join condition: (cast(i_current_price#11 as decimal(14,7)) > (1.2 * avg(i_current_price)#20)) + +(31) Project [codegen id : 6] +Output [1]: [i_item_sk#10] +Input [5]: [i_item_sk#10, i_current_price#11, i_category#12, avg(i_current_price)#20, i_category#14] + +(32) BroadcastExchange +Input [1]: [i_item_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +(33) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [ss_item_sk#5] +Right keys [1]: [i_item_sk#10] +Join type: Inner +Join condition: None + +(34) Project [codegen id : 7] +Output [1]: [ca_state#2] +Input [3]: [ca_state#2, ss_item_sk#5, i_item_sk#10] + +(35) HashAggregate [codegen id : 7] +Input [1]: [ca_state#2] +Keys [1]: [ca_state#2] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#21] +Results [2]: [ca_state#2, count#22] + +(36) Exchange +Input [2]: [ca_state#2, count#22] +Arguments: hashpartitioning(ca_state#2, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(37) HashAggregate [codegen id : 8] +Input [2]: [ca_state#2, count#22] +Keys [1]: [ca_state#2] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#23] +Results [2]: [ca_state#2 AS state#24, count(1)#23 AS cnt#25] + +(38) Filter [codegen id : 8] +Input [2]: [state#24, cnt#25] +Condition : (cnt#25 >= 10) + +(39) TakeOrderedAndProject +Input [2]: [state#24, cnt#25] +Arguments: 100, [cnt#25 ASC NULLS FIRST], [state#24, cnt#25] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 10 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (44) ++- * ColumnarToRow (43) + +- CometProject (42) + +- CometFilter (41) + +- CometScan parquet spark_catalog.default.date_dim (40) + + +(40) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#9, d_month_seq#26] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), EqualTo(d_month_seq,ScalarSubquery#27), IsNotNull(d_date_sk)] +ReadSchema: struct + +(41) CometFilter +Input [2]: [d_date_sk#9, d_month_seq#26] +Condition : ((isnotnull(d_month_seq#26) AND (d_month_seq#26 = ReusedSubquery Subquery scalar-subquery#27, [id=#28])) AND isnotnull(d_date_sk#9)) + +(42) CometProject +Input [2]: [d_date_sk#9, d_month_seq#26] +Arguments: [d_date_sk#9], [d_date_sk#9] + +(43) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#9] + +(44) BroadcastExchange +Input [1]: [d_date_sk#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +Subquery:2 Hosting operator id = 41 Hosting Expression = ReusedSubquery Subquery scalar-subquery#27, [id=#28] + +Subquery:3 Hosting operator id = 40 Hosting Expression = Subquery scalar-subquery#27, [id=#28] +* HashAggregate (51) ++- Exchange (50) + +- * ColumnarToRow (49) + +- CometHashAggregate (48) + +- CometProject (47) + +- CometFilter (46) + +- CometScan parquet spark_catalog.default.date_dim (45) + + +(45) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_month_seq#29, d_year#30, d_moy#31] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2000), EqualTo(d_moy,1)] +ReadSchema: struct + +(46) CometFilter +Input [3]: [d_month_seq#29, d_year#30, d_moy#31] +Condition : (((isnotnull(d_year#30) AND isnotnull(d_moy#31)) AND (d_year#30 = 2000)) AND (d_moy#31 = 1)) + +(47) CometProject +Input [3]: [d_month_seq#29, d_year#30, d_moy#31] +Arguments: [d_month_seq#29], [d_month_seq#29] + +(48) CometHashAggregate +Input [1]: [d_month_seq#29] +Keys [1]: [d_month_seq#29] +Functions: [] + +(49) ColumnarToRow [codegen id : 1] +Input [1]: [d_month_seq#29] + +(50) Exchange +Input [1]: [d_month_seq#29] +Arguments: hashpartitioning(d_month_seq#29, 5), ENSURE_REQUIREMENTS, [plan_id=8] + +(51) HashAggregate [codegen id : 2] +Input [1]: [d_month_seq#29] +Keys [1]: [d_month_seq#29] +Functions: [] +Aggregate Attributes: [] +Results [1]: [d_month_seq#29] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q6/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q6/simplified.txt new file mode 100644 index 0000000000..c2d5a6ce83 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q6/simplified.txt @@ -0,0 +1,79 @@ +TakeOrderedAndProject [cnt,state] + WholeStageCodegen (8) + Filter [cnt] + HashAggregate [ca_state,count] [count(1),state,cnt,count] + InputAdapter + Exchange [ca_state] #1 + WholeStageCodegen (7) + HashAggregate [ca_state] [count,count] + Project [ca_state] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ca_state,ss_item_sk] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ca_state,ss_item_sk,ss_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + Project [ca_state,c_customer_sk] + BroadcastHashJoin [ca_address_sk,c_current_addr_sk] + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [c_current_addr_sk,c_customer_sk] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_addr_sk] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk,ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_month_seq,d_date_sk] + ReusedSubquery [d_month_seq] #2 + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] + Subquery #2 + WholeStageCodegen (2) + HashAggregate [d_month_seq] + InputAdapter + Exchange [d_month_seq] #5 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometHashAggregate [d_month_seq] + CometProject [d_month_seq] + CometFilter [d_year,d_moy] + CometScan parquet spark_catalog.default.date_dim [d_month_seq,d_year,d_moy] + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (6) + Project [i_item_sk] + BroadcastHashJoin [i_category,i_category,i_current_price,avg(i_current_price)] + ColumnarToRow + InputAdapter + CometFilter [i_current_price,i_category,i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price,i_category] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (5) + Filter [avg(i_current_price)] + HashAggregate [i_category,sum,count] [avg(UnscaledValue(i_current_price)),avg(i_current_price),sum,count] + InputAdapter + Exchange [i_category] #8 + WholeStageCodegen (4) + HashAggregate [i_category,i_current_price] [sum,count,sum,count] + ColumnarToRow + InputAdapter + CometFilter [i_category] + CometScan parquet spark_catalog.default.item [i_current_price,i_category] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q60/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q60/explain.txt new file mode 100644 index 0000000000..78f4b27ac9 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q60/explain.txt @@ -0,0 +1,405 @@ +== Physical Plan == +TakeOrderedAndProject (63) ++- * HashAggregate (62) + +- Exchange (61) + +- * HashAggregate (60) + +- Union (59) + :- * HashAggregate (28) + : +- Exchange (27) + : +- * HashAggregate (26) + : +- * Project (25) + : +- * BroadcastHashJoin Inner BuildRight (24) + : :- * Project (13) + : : +- * BroadcastHashJoin Inner BuildRight (12) + : : :- * Project (6) + : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- ReusedExchange (4) + : : +- BroadcastExchange (11) + : : +- * ColumnarToRow (10) + : : +- CometProject (9) + : : +- CometFilter (8) + : : +- CometScan parquet spark_catalog.default.customer_address (7) + : +- BroadcastExchange (23) + : +- * BroadcastHashJoin LeftSemi BuildRight (22) + : :- * ColumnarToRow (16) + : : +- CometFilter (15) + : : +- CometScan parquet spark_catalog.default.item (14) + : +- BroadcastExchange (21) + : +- * ColumnarToRow (20) + : +- CometProject (19) + : +- CometFilter (18) + : +- CometScan parquet spark_catalog.default.item (17) + :- * HashAggregate (43) + : +- Exchange (42) + : +- * HashAggregate (41) + : +- * Project (40) + : +- * BroadcastHashJoin Inner BuildRight (39) + : :- * Project (37) + : : +- * BroadcastHashJoin Inner BuildRight (36) + : : :- * Project (34) + : : : +- * BroadcastHashJoin Inner BuildRight (33) + : : : :- * ColumnarToRow (31) + : : : : +- CometFilter (30) + : : : : +- CometScan parquet spark_catalog.default.catalog_sales (29) + : : : +- ReusedExchange (32) + : : +- ReusedExchange (35) + : +- ReusedExchange (38) + +- * HashAggregate (58) + +- Exchange (57) + +- * HashAggregate (56) + +- * Project (55) + +- * BroadcastHashJoin Inner BuildRight (54) + :- * Project (52) + : +- * BroadcastHashJoin Inner BuildRight (51) + : :- * Project (49) + : : +- * BroadcastHashJoin Inner BuildRight (48) + : : :- * ColumnarToRow (46) + : : : +- CometFilter (45) + : : : +- CometScan parquet spark_catalog.default.web_sales (44) + : : +- ReusedExchange (47) + : +- ReusedExchange (50) + +- ReusedExchange (53) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#4), dynamicpruningexpression(ss_sold_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(ss_addr_sk), IsNotNull(ss_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [4]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4] +Condition : (isnotnull(ss_addr_sk#2) AND isnotnull(ss_item_sk#1)) + +(3) ColumnarToRow [codegen id : 5] +Input [4]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4] + +(4) ReusedExchange [Reuses operator id: 68] +Output [1]: [d_date_sk#6] + +(5) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_sold_date_sk#4] +Right keys [1]: [d_date_sk#6] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 5] +Output [3]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3] +Input [5]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4, d_date_sk#6] + +(7) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#7, ca_gmt_offset#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_gmt_offset), EqualTo(ca_gmt_offset,-5.00), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(8) CometFilter +Input [2]: [ca_address_sk#7, ca_gmt_offset#8] +Condition : ((isnotnull(ca_gmt_offset#8) AND (ca_gmt_offset#8 = -5.00)) AND isnotnull(ca_address_sk#7)) + +(9) CometProject +Input [2]: [ca_address_sk#7, ca_gmt_offset#8] +Arguments: [ca_address_sk#7], [ca_address_sk#7] + +(10) ColumnarToRow [codegen id : 2] +Input [1]: [ca_address_sk#7] + +(11) BroadcastExchange +Input [1]: [ca_address_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(12) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_addr_sk#2] +Right keys [1]: [ca_address_sk#7] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 5] +Output [2]: [ss_item_sk#1, ss_ext_sales_price#3] +Input [4]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ca_address_sk#7] + +(14) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#9, i_item_id#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(15) CometFilter +Input [2]: [i_item_sk#9, i_item_id#10] +Condition : isnotnull(i_item_sk#9) + +(16) ColumnarToRow [codegen id : 4] +Input [2]: [i_item_sk#9, i_item_id#10] + +(17) Scan parquet spark_catalog.default.item +Output [2]: [i_item_id#11, i_category#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_category), EqualTo(i_category,Music )] +ReadSchema: struct + +(18) CometFilter +Input [2]: [i_item_id#11, i_category#12] +Condition : (isnotnull(i_category#12) AND (i_category#12 = Music )) + +(19) CometProject +Input [2]: [i_item_id#11, i_category#12] +Arguments: [i_item_id#11], [i_item_id#11] + +(20) ColumnarToRow [codegen id : 3] +Input [1]: [i_item_id#11] + +(21) BroadcastExchange +Input [1]: [i_item_id#11] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=2] + +(22) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [i_item_id#10] +Right keys [1]: [i_item_id#11] +Join type: LeftSemi +Join condition: None + +(23) BroadcastExchange +Input [2]: [i_item_sk#9, i_item_id#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#9] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 5] +Output [2]: [ss_ext_sales_price#3, i_item_id#10] +Input [4]: [ss_item_sk#1, ss_ext_sales_price#3, i_item_sk#9, i_item_id#10] + +(26) HashAggregate [codegen id : 5] +Input [2]: [ss_ext_sales_price#3, i_item_id#10] +Keys [1]: [i_item_id#10] +Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#3))] +Aggregate Attributes [1]: [sum#13] +Results [2]: [i_item_id#10, sum#14] + +(27) Exchange +Input [2]: [i_item_id#10, sum#14] +Arguments: hashpartitioning(i_item_id#10, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(28) HashAggregate [codegen id : 6] +Input [2]: [i_item_id#10, sum#14] +Keys [1]: [i_item_id#10] +Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#3))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#3))#15] +Results [2]: [i_item_id#10, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#3))#15,17,2) AS total_sales#16] + +(29) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, cs_sold_date_sk#20] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#20), dynamicpruningexpression(cs_sold_date_sk#20 IN dynamicpruning#21)] +PushedFilters: [IsNotNull(cs_bill_addr_sk), IsNotNull(cs_item_sk)] +ReadSchema: struct + +(30) CometFilter +Input [4]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, cs_sold_date_sk#20] +Condition : (isnotnull(cs_bill_addr_sk#17) AND isnotnull(cs_item_sk#18)) + +(31) ColumnarToRow [codegen id : 11] +Input [4]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, cs_sold_date_sk#20] + +(32) ReusedExchange [Reuses operator id: 68] +Output [1]: [d_date_sk#22] + +(33) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [cs_sold_date_sk#20] +Right keys [1]: [d_date_sk#22] +Join type: Inner +Join condition: None + +(34) Project [codegen id : 11] +Output [3]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19] +Input [5]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, cs_sold_date_sk#20, d_date_sk#22] + +(35) ReusedExchange [Reuses operator id: 11] +Output [1]: [ca_address_sk#23] + +(36) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [cs_bill_addr_sk#17] +Right keys [1]: [ca_address_sk#23] +Join type: Inner +Join condition: None + +(37) Project [codegen id : 11] +Output [2]: [cs_item_sk#18, cs_ext_sales_price#19] +Input [4]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, ca_address_sk#23] + +(38) ReusedExchange [Reuses operator id: 23] +Output [2]: [i_item_sk#24, i_item_id#25] + +(39) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [cs_item_sk#18] +Right keys [1]: [i_item_sk#24] +Join type: Inner +Join condition: None + +(40) Project [codegen id : 11] +Output [2]: [cs_ext_sales_price#19, i_item_id#25] +Input [4]: [cs_item_sk#18, cs_ext_sales_price#19, i_item_sk#24, i_item_id#25] + +(41) HashAggregate [codegen id : 11] +Input [2]: [cs_ext_sales_price#19, i_item_id#25] +Keys [1]: [i_item_id#25] +Functions [1]: [partial_sum(UnscaledValue(cs_ext_sales_price#19))] +Aggregate Attributes [1]: [sum#26] +Results [2]: [i_item_id#25, sum#27] + +(42) Exchange +Input [2]: [i_item_id#25, sum#27] +Arguments: hashpartitioning(i_item_id#25, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(43) HashAggregate [codegen id : 12] +Input [2]: [i_item_id#25, sum#27] +Keys [1]: [i_item_id#25] +Functions [1]: [sum(UnscaledValue(cs_ext_sales_price#19))] +Aggregate Attributes [1]: [sum(UnscaledValue(cs_ext_sales_price#19))#28] +Results [2]: [i_item_id#25, MakeDecimal(sum(UnscaledValue(cs_ext_sales_price#19))#28,17,2) AS total_sales#29] + +(44) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ws_sold_date_sk#33] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#33), dynamicpruningexpression(ws_sold_date_sk#33 IN dynamicpruning#34)] +PushedFilters: [IsNotNull(ws_bill_addr_sk), IsNotNull(ws_item_sk)] +ReadSchema: struct + +(45) CometFilter +Input [4]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ws_sold_date_sk#33] +Condition : (isnotnull(ws_bill_addr_sk#31) AND isnotnull(ws_item_sk#30)) + +(46) ColumnarToRow [codegen id : 17] +Input [4]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ws_sold_date_sk#33] + +(47) ReusedExchange [Reuses operator id: 68] +Output [1]: [d_date_sk#35] + +(48) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ws_sold_date_sk#33] +Right keys [1]: [d_date_sk#35] +Join type: Inner +Join condition: None + +(49) Project [codegen id : 17] +Output [3]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32] +Input [5]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ws_sold_date_sk#33, d_date_sk#35] + +(50) ReusedExchange [Reuses operator id: 11] +Output [1]: [ca_address_sk#36] + +(51) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ws_bill_addr_sk#31] +Right keys [1]: [ca_address_sk#36] +Join type: Inner +Join condition: None + +(52) Project [codegen id : 17] +Output [2]: [ws_item_sk#30, ws_ext_sales_price#32] +Input [4]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ca_address_sk#36] + +(53) ReusedExchange [Reuses operator id: 23] +Output [2]: [i_item_sk#37, i_item_id#38] + +(54) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ws_item_sk#30] +Right keys [1]: [i_item_sk#37] +Join type: Inner +Join condition: None + +(55) Project [codegen id : 17] +Output [2]: [ws_ext_sales_price#32, i_item_id#38] +Input [4]: [ws_item_sk#30, ws_ext_sales_price#32, i_item_sk#37, i_item_id#38] + +(56) HashAggregate [codegen id : 17] +Input [2]: [ws_ext_sales_price#32, i_item_id#38] +Keys [1]: [i_item_id#38] +Functions [1]: [partial_sum(UnscaledValue(ws_ext_sales_price#32))] +Aggregate Attributes [1]: [sum#39] +Results [2]: [i_item_id#38, sum#40] + +(57) Exchange +Input [2]: [i_item_id#38, sum#40] +Arguments: hashpartitioning(i_item_id#38, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(58) HashAggregate [codegen id : 18] +Input [2]: [i_item_id#38, sum#40] +Keys [1]: [i_item_id#38] +Functions [1]: [sum(UnscaledValue(ws_ext_sales_price#32))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_ext_sales_price#32))#41] +Results [2]: [i_item_id#38, MakeDecimal(sum(UnscaledValue(ws_ext_sales_price#32))#41,17,2) AS total_sales#42] + +(59) Union + +(60) HashAggregate [codegen id : 19] +Input [2]: [i_item_id#10, total_sales#16] +Keys [1]: [i_item_id#10] +Functions [1]: [partial_sum(total_sales#16)] +Aggregate Attributes [2]: [sum#43, isEmpty#44] +Results [3]: [i_item_id#10, sum#45, isEmpty#46] + +(61) Exchange +Input [3]: [i_item_id#10, sum#45, isEmpty#46] +Arguments: hashpartitioning(i_item_id#10, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(62) HashAggregate [codegen id : 20] +Input [3]: [i_item_id#10, sum#45, isEmpty#46] +Keys [1]: [i_item_id#10] +Functions [1]: [sum(total_sales#16)] +Aggregate Attributes [1]: [sum(total_sales#16)#47] +Results [2]: [i_item_id#10, sum(total_sales#16)#47 AS total_sales#48] + +(63) TakeOrderedAndProject +Input [2]: [i_item_id#10, total_sales#48] +Arguments: 100, [i_item_id#10 ASC NULLS FIRST, total_sales#48 ASC NULLS FIRST], [i_item_id#10, total_sales#48] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (68) ++- * ColumnarToRow (67) + +- CometProject (66) + +- CometFilter (65) + +- CometScan parquet spark_catalog.default.date_dim (64) + + +(64) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#6, d_year#49, d_moy#50] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,1998), EqualTo(d_moy,9), IsNotNull(d_date_sk)] +ReadSchema: struct + +(65) CometFilter +Input [3]: [d_date_sk#6, d_year#49, d_moy#50] +Condition : ((((isnotnull(d_year#49) AND isnotnull(d_moy#50)) AND (d_year#49 = 1998)) AND (d_moy#50 = 9)) AND isnotnull(d_date_sk#6)) + +(66) CometProject +Input [3]: [d_date_sk#6, d_year#49, d_moy#50] +Arguments: [d_date_sk#6], [d_date_sk#6] + +(67) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#6] + +(68) BroadcastExchange +Input [1]: [d_date_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + +Subquery:2 Hosting operator id = 29 Hosting Expression = cs_sold_date_sk#20 IN dynamicpruning#5 + +Subquery:3 Hosting operator id = 44 Hosting Expression = ws_sold_date_sk#33 IN dynamicpruning#5 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q60/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q60/simplified.txt new file mode 100644 index 0000000000..b010414a86 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q60/simplified.txt @@ -0,0 +1,105 @@ +TakeOrderedAndProject [i_item_id,total_sales] + WholeStageCodegen (20) + HashAggregate [i_item_id,sum,isEmpty] [sum(total_sales),total_sales,sum,isEmpty] + InputAdapter + Exchange [i_item_id] #1 + WholeStageCodegen (19) + HashAggregate [i_item_id,total_sales] [sum,isEmpty,sum,isEmpty] + InputAdapter + Union + WholeStageCodegen (6) + HashAggregate [i_item_id,sum] [sum(UnscaledValue(ss_ext_sales_price)),total_sales,sum] + InputAdapter + Exchange [i_item_id] #2 + WholeStageCodegen (5) + HashAggregate [i_item_id,ss_ext_sales_price] [sum,sum] + Project [ss_ext_sales_price,i_item_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_ext_sales_price] + BroadcastHashJoin [ss_addr_sk,ca_address_sk] + Project [ss_item_sk,ss_addr_sk,ss_ext_sales_price] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_addr_sk,ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_addr_sk,ss_ext_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_moy,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometProject [ca_address_sk] + CometFilter [ca_gmt_offset,ca_address_sk] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_gmt_offset] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (4) + BroadcastHashJoin [i_item_id,i_item_id] + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometProject [i_item_id] + CometFilter [i_category] + CometScan parquet spark_catalog.default.item [i_item_id,i_category] + WholeStageCodegen (12) + HashAggregate [i_item_id,sum] [sum(UnscaledValue(cs_ext_sales_price)),total_sales,sum] + InputAdapter + Exchange [i_item_id] #7 + WholeStageCodegen (11) + HashAggregate [i_item_id,cs_ext_sales_price] [sum,sum] + Project [cs_ext_sales_price,i_item_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Project [cs_item_sk,cs_ext_sales_price] + BroadcastHashJoin [cs_bill_addr_sk,ca_address_sk] + Project [cs_bill_addr_sk,cs_item_sk,cs_ext_sales_price] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [cs_bill_addr_sk,cs_item_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_addr_sk,cs_item_sk,cs_ext_sales_price,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + ReusedExchange [ca_address_sk] #4 + InputAdapter + ReusedExchange [i_item_sk,i_item_id] #5 + WholeStageCodegen (18) + HashAggregate [i_item_id,sum] [sum(UnscaledValue(ws_ext_sales_price)),total_sales,sum] + InputAdapter + Exchange [i_item_id] #8 + WholeStageCodegen (17) + HashAggregate [i_item_id,ws_ext_sales_price] [sum,sum] + Project [ws_ext_sales_price,i_item_id] + BroadcastHashJoin [ws_item_sk,i_item_sk] + Project [ws_item_sk,ws_ext_sales_price] + BroadcastHashJoin [ws_bill_addr_sk,ca_address_sk] + Project [ws_item_sk,ws_bill_addr_sk,ws_ext_sales_price] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ws_bill_addr_sk,ws_item_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_bill_addr_sk,ws_ext_sales_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + ReusedExchange [ca_address_sk] #4 + InputAdapter + ReusedExchange [i_item_sk,i_item_id] #5 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q61/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q61/explain.txt new file mode 100644 index 0000000000..766362167e --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q61/explain.txt @@ -0,0 +1,417 @@ +== Physical Plan == +* Project (67) ++- * BroadcastNestedLoopJoin Inner BuildRight (66) + :- * HashAggregate (43) + : +- Exchange (42) + : +- * HashAggregate (41) + : +- * Project (40) + : +- * BroadcastHashJoin Inner BuildRight (39) + : :- * Project (33) + : : +- * BroadcastHashJoin Inner BuildRight (32) + : : :- * Project (26) + : : : +- * BroadcastHashJoin Inner BuildRight (25) + : : : :- * Project (20) + : : : : +- * BroadcastHashJoin Inner BuildRight (19) + : : : : :- * Project (17) + : : : : : +- * BroadcastHashJoin Inner BuildRight (16) + : : : : : :- * Project (10) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (9) + : : : : : : :- * ColumnarToRow (3) + : : : : : : : +- CometFilter (2) + : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : : : +- BroadcastExchange (8) + : : : : : : +- * ColumnarToRow (7) + : : : : : : +- CometProject (6) + : : : : : : +- CometFilter (5) + : : : : : : +- CometScan parquet spark_catalog.default.store (4) + : : : : : +- BroadcastExchange (15) + : : : : : +- * ColumnarToRow (14) + : : : : : +- CometProject (13) + : : : : : +- CometFilter (12) + : : : : : +- CometScan parquet spark_catalog.default.promotion (11) + : : : : +- ReusedExchange (18) + : : : +- BroadcastExchange (24) + : : : +- * ColumnarToRow (23) + : : : +- CometFilter (22) + : : : +- CometScan parquet spark_catalog.default.customer (21) + : : +- BroadcastExchange (31) + : : +- * ColumnarToRow (30) + : : +- CometProject (29) + : : +- CometFilter (28) + : : +- CometScan parquet spark_catalog.default.customer_address (27) + : +- BroadcastExchange (38) + : +- * ColumnarToRow (37) + : +- CometProject (36) + : +- CometFilter (35) + : +- CometScan parquet spark_catalog.default.item (34) + +- BroadcastExchange (65) + +- * HashAggregate (64) + +- Exchange (63) + +- * HashAggregate (62) + +- * Project (61) + +- * BroadcastHashJoin Inner BuildRight (60) + :- * Project (58) + : +- * BroadcastHashJoin Inner BuildRight (57) + : :- * Project (55) + : : +- * BroadcastHashJoin Inner BuildRight (54) + : : :- * Project (52) + : : : +- * BroadcastHashJoin Inner BuildRight (51) + : : : :- * Project (49) + : : : : +- * BroadcastHashJoin Inner BuildRight (48) + : : : : :- * ColumnarToRow (46) + : : : : : +- CometFilter (45) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (44) + : : : : +- ReusedExchange (47) + : : : +- ReusedExchange (50) + : : +- ReusedExchange (53) + : +- ReusedExchange (56) + +- ReusedExchange (59) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_promo_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#6), dynamicpruningexpression(ss_sold_date_sk#6 IN dynamicpruning#7)] +PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_promo_sk), IsNotNull(ss_customer_sk), IsNotNull(ss_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_promo_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] +Condition : (((isnotnull(ss_store_sk#3) AND isnotnull(ss_promo_sk#4)) AND isnotnull(ss_customer_sk#2)) AND isnotnull(ss_item_sk#1)) + +(3) ColumnarToRow [codegen id : 7] +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_promo_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] + +(4) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#8, s_gmt_offset#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_gmt_offset), EqualTo(s_gmt_offset,-5.00), IsNotNull(s_store_sk)] +ReadSchema: struct + +(5) CometFilter +Input [2]: [s_store_sk#8, s_gmt_offset#9] +Condition : ((isnotnull(s_gmt_offset#9) AND (s_gmt_offset#9 = -5.00)) AND isnotnull(s_store_sk#8)) + +(6) CometProject +Input [2]: [s_store_sk#8, s_gmt_offset#9] +Arguments: [s_store_sk#8], [s_store_sk#8] + +(7) ColumnarToRow [codegen id : 1] +Input [1]: [s_store_sk#8] + +(8) BroadcastExchange +Input [1]: [s_store_sk#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [ss_store_sk#3] +Right keys [1]: [s_store_sk#8] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 7] +Output [5]: [ss_item_sk#1, ss_customer_sk#2, ss_promo_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] +Input [7]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_promo_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6, s_store_sk#8] + +(11) Scan parquet spark_catalog.default.promotion +Output [4]: [p_promo_sk#10, p_channel_dmail#11, p_channel_email#12, p_channel_tv#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/promotion] +PushedFilters: [Or(Or(EqualTo(p_channel_dmail,Y),EqualTo(p_channel_email,Y)),EqualTo(p_channel_tv,Y)), IsNotNull(p_promo_sk)] +ReadSchema: struct + +(12) CometFilter +Input [4]: [p_promo_sk#10, p_channel_dmail#11, p_channel_email#12, p_channel_tv#13] +Condition : ((((p_channel_dmail#11 = Y) OR (p_channel_email#12 = Y)) OR (p_channel_tv#13 = Y)) AND isnotnull(p_promo_sk#10)) + +(13) CometProject +Input [4]: [p_promo_sk#10, p_channel_dmail#11, p_channel_email#12, p_channel_tv#13] +Arguments: [p_promo_sk#10], [p_promo_sk#10] + +(14) ColumnarToRow [codegen id : 2] +Input [1]: [p_promo_sk#10] + +(15) BroadcastExchange +Input [1]: [p_promo_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(16) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [ss_promo_sk#4] +Right keys [1]: [p_promo_sk#10] +Join type: Inner +Join condition: None + +(17) Project [codegen id : 7] +Output [4]: [ss_item_sk#1, ss_customer_sk#2, ss_ext_sales_price#5, ss_sold_date_sk#6] +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_promo_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6, p_promo_sk#10] + +(18) ReusedExchange [Reuses operator id: 72] +Output [1]: [d_date_sk#14] + +(19) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [ss_sold_date_sk#6] +Right keys [1]: [d_date_sk#14] +Join type: Inner +Join condition: None + +(20) Project [codegen id : 7] +Output [3]: [ss_item_sk#1, ss_customer_sk#2, ss_ext_sales_price#5] +Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_ext_sales_price#5, ss_sold_date_sk#6, d_date_sk#14] + +(21) Scan parquet spark_catalog.default.customer +Output [2]: [c_customer_sk#15, c_current_addr_sk#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_current_addr_sk)] +ReadSchema: struct + +(22) CometFilter +Input [2]: [c_customer_sk#15, c_current_addr_sk#16] +Condition : (isnotnull(c_customer_sk#15) AND isnotnull(c_current_addr_sk#16)) + +(23) ColumnarToRow [codegen id : 4] +Input [2]: [c_customer_sk#15, c_current_addr_sk#16] + +(24) BroadcastExchange +Input [2]: [c_customer_sk#15, c_current_addr_sk#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(25) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [ss_customer_sk#2] +Right keys [1]: [c_customer_sk#15] +Join type: Inner +Join condition: None + +(26) Project [codegen id : 7] +Output [3]: [ss_item_sk#1, ss_ext_sales_price#5, c_current_addr_sk#16] +Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_ext_sales_price#5, c_customer_sk#15, c_current_addr_sk#16] + +(27) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#17, ca_gmt_offset#18] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_gmt_offset), EqualTo(ca_gmt_offset,-5.00), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(28) CometFilter +Input [2]: [ca_address_sk#17, ca_gmt_offset#18] +Condition : ((isnotnull(ca_gmt_offset#18) AND (ca_gmt_offset#18 = -5.00)) AND isnotnull(ca_address_sk#17)) + +(29) CometProject +Input [2]: [ca_address_sk#17, ca_gmt_offset#18] +Arguments: [ca_address_sk#17], [ca_address_sk#17] + +(30) ColumnarToRow [codegen id : 5] +Input [1]: [ca_address_sk#17] + +(31) BroadcastExchange +Input [1]: [ca_address_sk#17] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(32) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [c_current_addr_sk#16] +Right keys [1]: [ca_address_sk#17] +Join type: Inner +Join condition: None + +(33) Project [codegen id : 7] +Output [2]: [ss_item_sk#1, ss_ext_sales_price#5] +Input [4]: [ss_item_sk#1, ss_ext_sales_price#5, c_current_addr_sk#16, ca_address_sk#17] + +(34) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#19, i_category#20] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_category), EqualTo(i_category,Jewelry ), IsNotNull(i_item_sk)] +ReadSchema: struct + +(35) CometFilter +Input [2]: [i_item_sk#19, i_category#20] +Condition : ((isnotnull(i_category#20) AND (i_category#20 = Jewelry )) AND isnotnull(i_item_sk#19)) + +(36) CometProject +Input [2]: [i_item_sk#19, i_category#20] +Arguments: [i_item_sk#19], [i_item_sk#19] + +(37) ColumnarToRow [codegen id : 6] +Input [1]: [i_item_sk#19] + +(38) BroadcastExchange +Input [1]: [i_item_sk#19] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +(39) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#19] +Join type: Inner +Join condition: None + +(40) Project [codegen id : 7] +Output [1]: [ss_ext_sales_price#5] +Input [3]: [ss_item_sk#1, ss_ext_sales_price#5, i_item_sk#19] + +(41) HashAggregate [codegen id : 7] +Input [1]: [ss_ext_sales_price#5] +Keys: [] +Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#5))] +Aggregate Attributes [1]: [sum#21] +Results [1]: [sum#22] + +(42) Exchange +Input [1]: [sum#22] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=6] + +(43) HashAggregate [codegen id : 15] +Input [1]: [sum#22] +Keys: [] +Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#5))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#5))#23] +Results [1]: [MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#5))#23,17,2) AS promotions#24] + +(44) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_item_sk#25, ss_customer_sk#26, ss_store_sk#27, ss_ext_sales_price#28, ss_sold_date_sk#29] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#29), dynamicpruningexpression(ss_sold_date_sk#29 IN dynamicpruning#30)] +PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_customer_sk), IsNotNull(ss_item_sk)] +ReadSchema: struct + +(45) CometFilter +Input [5]: [ss_item_sk#25, ss_customer_sk#26, ss_store_sk#27, ss_ext_sales_price#28, ss_sold_date_sk#29] +Condition : ((isnotnull(ss_store_sk#27) AND isnotnull(ss_customer_sk#26)) AND isnotnull(ss_item_sk#25)) + +(46) ColumnarToRow [codegen id : 13] +Input [5]: [ss_item_sk#25, ss_customer_sk#26, ss_store_sk#27, ss_ext_sales_price#28, ss_sold_date_sk#29] + +(47) ReusedExchange [Reuses operator id: 8] +Output [1]: [s_store_sk#31] + +(48) BroadcastHashJoin [codegen id : 13] +Left keys [1]: [ss_store_sk#27] +Right keys [1]: [s_store_sk#31] +Join type: Inner +Join condition: None + +(49) Project [codegen id : 13] +Output [4]: [ss_item_sk#25, ss_customer_sk#26, ss_ext_sales_price#28, ss_sold_date_sk#29] +Input [6]: [ss_item_sk#25, ss_customer_sk#26, ss_store_sk#27, ss_ext_sales_price#28, ss_sold_date_sk#29, s_store_sk#31] + +(50) ReusedExchange [Reuses operator id: 72] +Output [1]: [d_date_sk#32] + +(51) BroadcastHashJoin [codegen id : 13] +Left keys [1]: [ss_sold_date_sk#29] +Right keys [1]: [d_date_sk#32] +Join type: Inner +Join condition: None + +(52) Project [codegen id : 13] +Output [3]: [ss_item_sk#25, ss_customer_sk#26, ss_ext_sales_price#28] +Input [5]: [ss_item_sk#25, ss_customer_sk#26, ss_ext_sales_price#28, ss_sold_date_sk#29, d_date_sk#32] + +(53) ReusedExchange [Reuses operator id: 24] +Output [2]: [c_customer_sk#33, c_current_addr_sk#34] + +(54) BroadcastHashJoin [codegen id : 13] +Left keys [1]: [ss_customer_sk#26] +Right keys [1]: [c_customer_sk#33] +Join type: Inner +Join condition: None + +(55) Project [codegen id : 13] +Output [3]: [ss_item_sk#25, ss_ext_sales_price#28, c_current_addr_sk#34] +Input [5]: [ss_item_sk#25, ss_customer_sk#26, ss_ext_sales_price#28, c_customer_sk#33, c_current_addr_sk#34] + +(56) ReusedExchange [Reuses operator id: 31] +Output [1]: [ca_address_sk#35] + +(57) BroadcastHashJoin [codegen id : 13] +Left keys [1]: [c_current_addr_sk#34] +Right keys [1]: [ca_address_sk#35] +Join type: Inner +Join condition: None + +(58) Project [codegen id : 13] +Output [2]: [ss_item_sk#25, ss_ext_sales_price#28] +Input [4]: [ss_item_sk#25, ss_ext_sales_price#28, c_current_addr_sk#34, ca_address_sk#35] + +(59) ReusedExchange [Reuses operator id: 38] +Output [1]: [i_item_sk#36] + +(60) BroadcastHashJoin [codegen id : 13] +Left keys [1]: [ss_item_sk#25] +Right keys [1]: [i_item_sk#36] +Join type: Inner +Join condition: None + +(61) Project [codegen id : 13] +Output [1]: [ss_ext_sales_price#28] +Input [3]: [ss_item_sk#25, ss_ext_sales_price#28, i_item_sk#36] + +(62) HashAggregate [codegen id : 13] +Input [1]: [ss_ext_sales_price#28] +Keys: [] +Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#28))] +Aggregate Attributes [1]: [sum#37] +Results [1]: [sum#38] + +(63) Exchange +Input [1]: [sum#38] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=7] + +(64) HashAggregate [codegen id : 14] +Input [1]: [sum#38] +Keys: [] +Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#28))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#28))#39] +Results [1]: [MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#28))#39,17,2) AS total#40] + +(65) BroadcastExchange +Input [1]: [total#40] +Arguments: IdentityBroadcastMode, [plan_id=8] + +(66) BroadcastNestedLoopJoin [codegen id : 15] +Join type: Inner +Join condition: None + +(67) Project [codegen id : 15] +Output [3]: [promotions#24, total#40, ((cast(promotions#24 as decimal(15,4)) / cast(total#40 as decimal(15,4))) * 100) AS ((CAST(promotions AS DECIMAL(15,4)) / CAST(total AS DECIMAL(15,4))) * 100)#41] +Input [2]: [promotions#24, total#40] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#6 IN dynamicpruning#7 +BroadcastExchange (72) ++- * ColumnarToRow (71) + +- CometProject (70) + +- CometFilter (69) + +- CometScan parquet spark_catalog.default.date_dim (68) + + +(68) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#14, d_year#42, d_moy#43] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,1998), EqualTo(d_moy,11), IsNotNull(d_date_sk)] +ReadSchema: struct + +(69) CometFilter +Input [3]: [d_date_sk#14, d_year#42, d_moy#43] +Condition : ((((isnotnull(d_year#42) AND isnotnull(d_moy#43)) AND (d_year#42 = 1998)) AND (d_moy#43 = 11)) AND isnotnull(d_date_sk#14)) + +(70) CometProject +Input [3]: [d_date_sk#14, d_year#42, d_moy#43] +Arguments: [d_date_sk#14], [d_date_sk#14] + +(71) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#14] + +(72) BroadcastExchange +Input [1]: [d_date_sk#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=9] + +Subquery:2 Hosting operator id = 44 Hosting Expression = ss_sold_date_sk#29 IN dynamicpruning#7 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q61/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q61/simplified.txt new file mode 100644 index 0000000000..2c3d07ac64 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q61/simplified.txt @@ -0,0 +1,106 @@ +WholeStageCodegen (15) + Project [promotions,total] + BroadcastNestedLoopJoin + HashAggregate [sum] [sum(UnscaledValue(ss_ext_sales_price)),promotions,sum] + InputAdapter + Exchange #1 + WholeStageCodegen (7) + HashAggregate [ss_ext_sales_price] [sum,sum] + Project [ss_ext_sales_price] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_ext_sales_price] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [ss_item_sk,ss_ext_sales_price,c_current_addr_sk] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Project [ss_item_sk,ss_customer_sk,ss_ext_sales_price] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_customer_sk,ss_ext_sales_price,ss_sold_date_sk] + BroadcastHashJoin [ss_promo_sk,p_promo_sk] + Project [ss_item_sk,ss_customer_sk,ss_promo_sk,ss_ext_sales_price,ss_sold_date_sk] + BroadcastHashJoin [ss_store_sk,s_store_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk,ss_promo_sk,ss_customer_sk,ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_store_sk,ss_promo_sk,ss_ext_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_moy,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [s_store_sk] + CometFilter [s_gmt_offset,s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk,s_gmt_offset] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometProject [p_promo_sk] + CometFilter [p_channel_dmail,p_channel_email,p_channel_tv,p_promo_sk] + CometScan parquet spark_catalog.default.promotion [p_promo_sk,p_channel_dmail,p_channel_email,p_channel_tv] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (4) + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_current_addr_sk] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_addr_sk] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (5) + ColumnarToRow + InputAdapter + CometProject [ca_address_sk] + CometFilter [ca_gmt_offset,ca_address_sk] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_gmt_offset] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (6) + ColumnarToRow + InputAdapter + CometProject [i_item_sk] + CometFilter [i_category,i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_category] + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (14) + HashAggregate [sum] [sum(UnscaledValue(ss_ext_sales_price)),total,sum] + InputAdapter + Exchange #9 + WholeStageCodegen (13) + HashAggregate [ss_ext_sales_price] [sum,sum] + Project [ss_ext_sales_price] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_ext_sales_price] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [ss_item_sk,ss_ext_sales_price,c_current_addr_sk] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Project [ss_item_sk,ss_customer_sk,ss_ext_sales_price] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_customer_sk,ss_ext_sales_price,ss_sold_date_sk] + BroadcastHashJoin [ss_store_sk,s_store_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk,ss_customer_sk,ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ext_sales_price,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [s_store_sk] #3 + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + ReusedExchange [c_customer_sk,c_current_addr_sk] #5 + InputAdapter + ReusedExchange [ca_address_sk] #6 + InputAdapter + ReusedExchange [i_item_sk] #7 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q62/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q62/explain.txt new file mode 100644 index 0000000000..0607d80770 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q62/explain.txt @@ -0,0 +1,187 @@ +== Physical Plan == +TakeOrderedAndProject (32) ++- * HashAggregate (31) + +- Exchange (30) + +- * HashAggregate (29) + +- * Project (28) + +- * BroadcastHashJoin Inner BuildRight (27) + :- * Project (21) + : +- * BroadcastHashJoin Inner BuildRight (20) + : :- * Project (15) + : : +- * BroadcastHashJoin Inner BuildRight (14) + : : :- * Project (9) + : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.web_sales (1) + : : : +- BroadcastExchange (7) + : : : +- * ColumnarToRow (6) + : : : +- CometFilter (5) + : : : +- CometScan parquet spark_catalog.default.warehouse (4) + : : +- BroadcastExchange (13) + : : +- * ColumnarToRow (12) + : : +- CometFilter (11) + : : +- CometScan parquet spark_catalog.default.ship_mode (10) + : +- BroadcastExchange (19) + : +- * ColumnarToRow (18) + : +- CometFilter (17) + : +- CometScan parquet spark_catalog.default.web_site (16) + +- BroadcastExchange (26) + +- * ColumnarToRow (25) + +- CometProject (24) + +- CometFilter (23) + +- CometScan parquet spark_catalog.default.date_dim (22) + + +(1) Scan parquet spark_catalog.default.web_sales +Output [5]: [ws_ship_date_sk#1, ws_web_site_sk#2, ws_ship_mode_sk#3, ws_warehouse_sk#4, ws_sold_date_sk#5] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_sales] +PushedFilters: [IsNotNull(ws_warehouse_sk), IsNotNull(ws_ship_mode_sk), IsNotNull(ws_web_site_sk), IsNotNull(ws_ship_date_sk)] +ReadSchema: struct + +(2) CometFilter +Input [5]: [ws_ship_date_sk#1, ws_web_site_sk#2, ws_ship_mode_sk#3, ws_warehouse_sk#4, ws_sold_date_sk#5] +Condition : (((isnotnull(ws_warehouse_sk#4) AND isnotnull(ws_ship_mode_sk#3)) AND isnotnull(ws_web_site_sk#2)) AND isnotnull(ws_ship_date_sk#1)) + +(3) ColumnarToRow [codegen id : 5] +Input [5]: [ws_ship_date_sk#1, ws_web_site_sk#2, ws_ship_mode_sk#3, ws_warehouse_sk#4, ws_sold_date_sk#5] + +(4) Scan parquet spark_catalog.default.warehouse +Output [2]: [w_warehouse_sk#6, w_warehouse_name#7] +Batched: true +Location [not included in comparison]/{warehouse_dir}/warehouse] +PushedFilters: [IsNotNull(w_warehouse_sk)] +ReadSchema: struct + +(5) CometFilter +Input [2]: [w_warehouse_sk#6, w_warehouse_name#7] +Condition : isnotnull(w_warehouse_sk#6) + +(6) ColumnarToRow [codegen id : 1] +Input [2]: [w_warehouse_sk#6, w_warehouse_name#7] + +(7) BroadcastExchange +Input [2]: [w_warehouse_sk#6, w_warehouse_name#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ws_warehouse_sk#4] +Right keys [1]: [w_warehouse_sk#6] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 5] +Output [5]: [ws_ship_date_sk#1, ws_web_site_sk#2, ws_ship_mode_sk#3, ws_sold_date_sk#5, w_warehouse_name#7] +Input [7]: [ws_ship_date_sk#1, ws_web_site_sk#2, ws_ship_mode_sk#3, ws_warehouse_sk#4, ws_sold_date_sk#5, w_warehouse_sk#6, w_warehouse_name#7] + +(10) Scan parquet spark_catalog.default.ship_mode +Output [2]: [sm_ship_mode_sk#8, sm_type#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/ship_mode] +PushedFilters: [IsNotNull(sm_ship_mode_sk)] +ReadSchema: struct + +(11) CometFilter +Input [2]: [sm_ship_mode_sk#8, sm_type#9] +Condition : isnotnull(sm_ship_mode_sk#8) + +(12) ColumnarToRow [codegen id : 2] +Input [2]: [sm_ship_mode_sk#8, sm_type#9] + +(13) BroadcastExchange +Input [2]: [sm_ship_mode_sk#8, sm_type#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(14) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ws_ship_mode_sk#3] +Right keys [1]: [sm_ship_mode_sk#8] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 5] +Output [5]: [ws_ship_date_sk#1, ws_web_site_sk#2, ws_sold_date_sk#5, w_warehouse_name#7, sm_type#9] +Input [7]: [ws_ship_date_sk#1, ws_web_site_sk#2, ws_ship_mode_sk#3, ws_sold_date_sk#5, w_warehouse_name#7, sm_ship_mode_sk#8, sm_type#9] + +(16) Scan parquet spark_catalog.default.web_site +Output [2]: [web_site_sk#10, web_name#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_site] +PushedFilters: [IsNotNull(web_site_sk)] +ReadSchema: struct + +(17) CometFilter +Input [2]: [web_site_sk#10, web_name#11] +Condition : isnotnull(web_site_sk#10) + +(18) ColumnarToRow [codegen id : 3] +Input [2]: [web_site_sk#10, web_name#11] + +(19) BroadcastExchange +Input [2]: [web_site_sk#10, web_name#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(20) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ws_web_site_sk#2] +Right keys [1]: [web_site_sk#10] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 5] +Output [5]: [ws_ship_date_sk#1, ws_sold_date_sk#5, w_warehouse_name#7, sm_type#9, web_name#11] +Input [7]: [ws_ship_date_sk#1, ws_web_site_sk#2, ws_sold_date_sk#5, w_warehouse_name#7, sm_type#9, web_site_sk#10, web_name#11] + +(22) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#12, d_month_seq#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)] +ReadSchema: struct + +(23) CometFilter +Input [2]: [d_date_sk#12, d_month_seq#13] +Condition : (((isnotnull(d_month_seq#13) AND (d_month_seq#13 >= 1200)) AND (d_month_seq#13 <= 1211)) AND isnotnull(d_date_sk#12)) + +(24) CometProject +Input [2]: [d_date_sk#12, d_month_seq#13] +Arguments: [d_date_sk#12], [d_date_sk#12] + +(25) ColumnarToRow [codegen id : 4] +Input [1]: [d_date_sk#12] + +(26) BroadcastExchange +Input [1]: [d_date_sk#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(27) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ws_ship_date_sk#1] +Right keys [1]: [d_date_sk#12] +Join type: Inner +Join condition: None + +(28) Project [codegen id : 5] +Output [5]: [ws_ship_date_sk#1, ws_sold_date_sk#5, sm_type#9, web_name#11, substr(w_warehouse_name#7, 1, 20) AS _groupingexpression#14] +Input [6]: [ws_ship_date_sk#1, ws_sold_date_sk#5, w_warehouse_name#7, sm_type#9, web_name#11, d_date_sk#12] + +(29) HashAggregate [codegen id : 5] +Input [5]: [ws_ship_date_sk#1, ws_sold_date_sk#5, sm_type#9, web_name#11, _groupingexpression#14] +Keys [3]: [_groupingexpression#14, sm_type#9, web_name#11] +Functions [5]: [partial_sum(CASE WHEN ((ws_ship_date_sk#1 - ws_sold_date_sk#5) <= 30) THEN 1 ELSE 0 END), partial_sum(CASE WHEN (((ws_ship_date_sk#1 - ws_sold_date_sk#5) > 30) AND ((ws_ship_date_sk#1 - ws_sold_date_sk#5) <= 60)) THEN 1 ELSE 0 END), partial_sum(CASE WHEN (((ws_ship_date_sk#1 - ws_sold_date_sk#5) > 60) AND ((ws_ship_date_sk#1 - ws_sold_date_sk#5) <= 90)) THEN 1 ELSE 0 END), partial_sum(CASE WHEN (((ws_ship_date_sk#1 - ws_sold_date_sk#5) > 90) AND ((ws_ship_date_sk#1 - ws_sold_date_sk#5) <= 120)) THEN 1 ELSE 0 END), partial_sum(CASE WHEN ((ws_ship_date_sk#1 - ws_sold_date_sk#5) > 120) THEN 1 ELSE 0 END)] +Aggregate Attributes [5]: [sum#15, sum#16, sum#17, sum#18, sum#19] +Results [8]: [_groupingexpression#14, sm_type#9, web_name#11, sum#20, sum#21, sum#22, sum#23, sum#24] + +(30) Exchange +Input [8]: [_groupingexpression#14, sm_type#9, web_name#11, sum#20, sum#21, sum#22, sum#23, sum#24] +Arguments: hashpartitioning(_groupingexpression#14, sm_type#9, web_name#11, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(31) HashAggregate [codegen id : 6] +Input [8]: [_groupingexpression#14, sm_type#9, web_name#11, sum#20, sum#21, sum#22, sum#23, sum#24] +Keys [3]: [_groupingexpression#14, sm_type#9, web_name#11] +Functions [5]: [sum(CASE WHEN ((ws_ship_date_sk#1 - ws_sold_date_sk#5) <= 30) THEN 1 ELSE 0 END), sum(CASE WHEN (((ws_ship_date_sk#1 - ws_sold_date_sk#5) > 30) AND ((ws_ship_date_sk#1 - ws_sold_date_sk#5) <= 60)) THEN 1 ELSE 0 END), sum(CASE WHEN (((ws_ship_date_sk#1 - ws_sold_date_sk#5) > 60) AND ((ws_ship_date_sk#1 - ws_sold_date_sk#5) <= 90)) THEN 1 ELSE 0 END), sum(CASE WHEN (((ws_ship_date_sk#1 - ws_sold_date_sk#5) > 90) AND ((ws_ship_date_sk#1 - ws_sold_date_sk#5) <= 120)) THEN 1 ELSE 0 END), sum(CASE WHEN ((ws_ship_date_sk#1 - ws_sold_date_sk#5) > 120) THEN 1 ELSE 0 END)] +Aggregate Attributes [5]: [sum(CASE WHEN ((ws_ship_date_sk#1 - ws_sold_date_sk#5) <= 30) THEN 1 ELSE 0 END)#25, sum(CASE WHEN (((ws_ship_date_sk#1 - ws_sold_date_sk#5) > 30) AND ((ws_ship_date_sk#1 - ws_sold_date_sk#5) <= 60)) THEN 1 ELSE 0 END)#26, sum(CASE WHEN (((ws_ship_date_sk#1 - ws_sold_date_sk#5) > 60) AND ((ws_ship_date_sk#1 - ws_sold_date_sk#5) <= 90)) THEN 1 ELSE 0 END)#27, sum(CASE WHEN (((ws_ship_date_sk#1 - ws_sold_date_sk#5) > 90) AND ((ws_ship_date_sk#1 - ws_sold_date_sk#5) <= 120)) THEN 1 ELSE 0 END)#28, sum(CASE WHEN ((ws_ship_date_sk#1 - ws_sold_date_sk#5) > 120) THEN 1 ELSE 0 END)#29] +Results [8]: [_groupingexpression#14 AS substr(w_warehouse_name, 1, 20)#30, sm_type#9, web_name#11, sum(CASE WHEN ((ws_ship_date_sk#1 - ws_sold_date_sk#5) <= 30) THEN 1 ELSE 0 END)#25 AS 30 days #31, sum(CASE WHEN (((ws_ship_date_sk#1 - ws_sold_date_sk#5) > 30) AND ((ws_ship_date_sk#1 - ws_sold_date_sk#5) <= 60)) THEN 1 ELSE 0 END)#26 AS 31 - 60 days #32, sum(CASE WHEN (((ws_ship_date_sk#1 - ws_sold_date_sk#5) > 60) AND ((ws_ship_date_sk#1 - ws_sold_date_sk#5) <= 90)) THEN 1 ELSE 0 END)#27 AS 61 - 90 days #33, sum(CASE WHEN (((ws_ship_date_sk#1 - ws_sold_date_sk#5) > 90) AND ((ws_ship_date_sk#1 - ws_sold_date_sk#5) <= 120)) THEN 1 ELSE 0 END)#28 AS 91 - 120 days #34, sum(CASE WHEN ((ws_ship_date_sk#1 - ws_sold_date_sk#5) > 120) THEN 1 ELSE 0 END)#29 AS >120 days #35] + +(32) TakeOrderedAndProject +Input [8]: [substr(w_warehouse_name, 1, 20)#30, sm_type#9, web_name#11, 30 days #31, 31 - 60 days #32, 61 - 90 days #33, 91 - 120 days #34, >120 days #35] +Arguments: 100, [substr(w_warehouse_name, 1, 20)#30 ASC NULLS FIRST, sm_type#9 ASC NULLS FIRST, web_name#11 ASC NULLS FIRST], [substr(w_warehouse_name, 1, 20)#30, sm_type#9, web_name#11, 30 days #31, 31 - 60 days #32, 61 - 90 days #33, 91 - 120 days #34, >120 days #35] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q62/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q62/simplified.txt new file mode 100644 index 0000000000..5ae522ce1c --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q62/simplified.txt @@ -0,0 +1,48 @@ +TakeOrderedAndProject [substr(w_warehouse_name, 1, 20),sm_type,web_name,30 days ,31 - 60 days ,61 - 90 days ,91 - 120 days ,>120 days ] + WholeStageCodegen (6) + HashAggregate [_groupingexpression,sm_type,web_name,sum,sum,sum,sum,sum] [sum(CASE WHEN ((ws_ship_date_sk - ws_sold_date_sk) <= 30) THEN 1 ELSE 0 END),sum(CASE WHEN (((ws_ship_date_sk - ws_sold_date_sk) > 30) AND ((ws_ship_date_sk - ws_sold_date_sk) <= 60)) THEN 1 ELSE 0 END),sum(CASE WHEN (((ws_ship_date_sk - ws_sold_date_sk) > 60) AND ((ws_ship_date_sk - ws_sold_date_sk) <= 90)) THEN 1 ELSE 0 END),sum(CASE WHEN (((ws_ship_date_sk - ws_sold_date_sk) > 90) AND ((ws_ship_date_sk - ws_sold_date_sk) <= 120)) THEN 1 ELSE 0 END),sum(CASE WHEN ((ws_ship_date_sk - ws_sold_date_sk) > 120) THEN 1 ELSE 0 END),substr(w_warehouse_name, 1, 20),30 days ,31 - 60 days ,61 - 90 days ,91 - 120 days ,>120 days ,sum,sum,sum,sum,sum] + InputAdapter + Exchange [_groupingexpression,sm_type,web_name] #1 + WholeStageCodegen (5) + HashAggregate [_groupingexpression,sm_type,web_name,ws_ship_date_sk,ws_sold_date_sk] [sum,sum,sum,sum,sum,sum,sum,sum,sum,sum] + Project [ws_ship_date_sk,ws_sold_date_sk,sm_type,web_name,w_warehouse_name] + BroadcastHashJoin [ws_ship_date_sk,d_date_sk] + Project [ws_ship_date_sk,ws_sold_date_sk,w_warehouse_name,sm_type,web_name] + BroadcastHashJoin [ws_web_site_sk,web_site_sk] + Project [ws_ship_date_sk,ws_web_site_sk,ws_sold_date_sk,w_warehouse_name,sm_type] + BroadcastHashJoin [ws_ship_mode_sk,sm_ship_mode_sk] + Project [ws_ship_date_sk,ws_web_site_sk,ws_ship_mode_sk,ws_sold_date_sk,w_warehouse_name] + BroadcastHashJoin [ws_warehouse_sk,w_warehouse_sk] + ColumnarToRow + InputAdapter + CometFilter [ws_warehouse_sk,ws_ship_mode_sk,ws_web_site_sk,ws_ship_date_sk] + CometScan parquet spark_catalog.default.web_sales [ws_ship_date_sk,ws_web_site_sk,ws_ship_mode_sk,ws_warehouse_sk,ws_sold_date_sk] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [w_warehouse_sk] + CometScan parquet spark_catalog.default.warehouse [w_warehouse_sk,w_warehouse_name] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [sm_ship_mode_sk] + CometScan parquet spark_catalog.default.ship_mode [sm_ship_mode_sk,sm_type] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometFilter [web_site_sk] + CometScan parquet spark_catalog.default.web_site [web_site_sk,web_name] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (4) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_month_seq,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q63/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q63/explain.txt new file mode 100644 index 0000000000..990bc31957 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q63/explain.txt @@ -0,0 +1,194 @@ +== Physical Plan == +TakeOrderedAndProject (28) ++- * Project (27) + +- * Filter (26) + +- Window (25) + +- * Sort (24) + +- Exchange (23) + +- * HashAggregate (22) + +- Exchange (21) + +- * HashAggregate (20) + +- * Project (19) + +- * BroadcastHashJoin Inner BuildRight (18) + :- * Project (13) + : +- * BroadcastHashJoin Inner BuildRight (12) + : :- * Project (10) + : : +- * BroadcastHashJoin Inner BuildRight (9) + : : :- * ColumnarToRow (4) + : : : +- CometProject (3) + : : : +- CometFilter (2) + : : : +- CometScan parquet spark_catalog.default.item (1) + : : +- BroadcastExchange (8) + : : +- * ColumnarToRow (7) + : : +- CometFilter (6) + : : +- CometScan parquet spark_catalog.default.store_sales (5) + : +- ReusedExchange (11) + +- BroadcastExchange (17) + +- * ColumnarToRow (16) + +- CometFilter (15) + +- CometScan parquet spark_catalog.default.store (14) + + +(1) Scan parquet spark_catalog.default.item +Output [5]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4, i_manager_id#5] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [Or(And(And(In(i_category, [Books ,Children ,Electronics ]),In(i_class, [personal ,portable ,refernece ,self-help ])),In(i_brand, [exportiunivamalg #6 ,scholaramalgamalg #7 ,scholaramalgamalg #8 ,scholaramalgamalg #6 ])),And(And(In(i_category, [Men ,Music ,Women ]),In(i_class, [accessories ,classical ,fragrances ,pants ])),In(i_brand, [amalgimporto #9 ,edu packscholar #9 ,exportiimporto #9 ,importoamalg #9 ]))), IsNotNull(i_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [5]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4, i_manager_id#5] +Condition : ((((i_category#4 IN (Books ,Children ,Electronics ) AND i_class#3 IN (personal ,portable ,refernece ,self-help )) AND i_brand#2 IN (scholaramalgamalg #7 ,scholaramalgamalg #8 ,exportiunivamalg #6 ,scholaramalgamalg #6 )) OR ((i_category#4 IN (Women ,Music ,Men ) AND i_class#3 IN (accessories ,classical ,fragrances ,pants )) AND i_brand#2 IN (amalgimporto #9 ,edu packscholar #9 ,exportiimporto #9 ,importoamalg #9 ))) AND isnotnull(i_item_sk#1)) + +(3) CometProject +Input [5]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4, i_manager_id#5] +Arguments: [i_item_sk#1, i_manager_id#5], [i_item_sk#1, i_manager_id#5] + +(4) ColumnarToRow [codegen id : 4] +Input [2]: [i_item_sk#1, i_manager_id#5] + +(5) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#10, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#13), dynamicpruningexpression(ss_sold_date_sk#13 IN dynamicpruning#14)] +PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(6) CometFilter +Input [4]: [ss_item_sk#10, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13] +Condition : (isnotnull(ss_item_sk#10) AND isnotnull(ss_store_sk#11)) + +(7) ColumnarToRow [codegen id : 1] +Input [4]: [ss_item_sk#10, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13] + +(8) BroadcastExchange +Input [4]: [ss_item_sk#10, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [i_item_sk#1] +Right keys [1]: [ss_item_sk#10] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 4] +Output [4]: [i_manager_id#5, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13] +Input [6]: [i_item_sk#1, i_manager_id#5, ss_item_sk#10, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13] + +(11) ReusedExchange [Reuses operator id: 33] +Output [2]: [d_date_sk#15, d_moy#16] + +(12) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_date_sk#13] +Right keys [1]: [d_date_sk#15] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 4] +Output [4]: [i_manager_id#5, ss_store_sk#11, ss_sales_price#12, d_moy#16] +Input [6]: [i_manager_id#5, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13, d_date_sk#15, d_moy#16] + +(14) Scan parquet spark_catalog.default.store +Output [1]: [s_store_sk#17] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(15) CometFilter +Input [1]: [s_store_sk#17] +Condition : isnotnull(s_store_sk#17) + +(16) ColumnarToRow [codegen id : 3] +Input [1]: [s_store_sk#17] + +(17) BroadcastExchange +Input [1]: [s_store_sk#17] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(18) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_store_sk#11] +Right keys [1]: [s_store_sk#17] +Join type: Inner +Join condition: None + +(19) Project [codegen id : 4] +Output [3]: [i_manager_id#5, ss_sales_price#12, d_moy#16] +Input [5]: [i_manager_id#5, ss_store_sk#11, ss_sales_price#12, d_moy#16, s_store_sk#17] + +(20) HashAggregate [codegen id : 4] +Input [3]: [i_manager_id#5, ss_sales_price#12, d_moy#16] +Keys [2]: [i_manager_id#5, d_moy#16] +Functions [1]: [partial_sum(UnscaledValue(ss_sales_price#12))] +Aggregate Attributes [1]: [sum#18] +Results [3]: [i_manager_id#5, d_moy#16, sum#19] + +(21) Exchange +Input [3]: [i_manager_id#5, d_moy#16, sum#19] +Arguments: hashpartitioning(i_manager_id#5, d_moy#16, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(22) HashAggregate [codegen id : 5] +Input [3]: [i_manager_id#5, d_moy#16, sum#19] +Keys [2]: [i_manager_id#5, d_moy#16] +Functions [1]: [sum(UnscaledValue(ss_sales_price#12))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_sales_price#12))#20] +Results [3]: [i_manager_id#5, MakeDecimal(sum(UnscaledValue(ss_sales_price#12))#20,17,2) AS sum_sales#21, MakeDecimal(sum(UnscaledValue(ss_sales_price#12))#20,17,2) AS _w0#22] + +(23) Exchange +Input [3]: [i_manager_id#5, sum_sales#21, _w0#22] +Arguments: hashpartitioning(i_manager_id#5, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(24) Sort [codegen id : 6] +Input [3]: [i_manager_id#5, sum_sales#21, _w0#22] +Arguments: [i_manager_id#5 ASC NULLS FIRST], false, 0 + +(25) Window +Input [3]: [i_manager_id#5, sum_sales#21, _w0#22] +Arguments: [avg(_w0#22) windowspecdefinition(i_manager_id#5, specifiedwindowframe(RowFrame, unboundedpreceding$(), unboundedfollowing$())) AS avg_monthly_sales#23], [i_manager_id#5] + +(26) Filter [codegen id : 7] +Input [4]: [i_manager_id#5, sum_sales#21, _w0#22, avg_monthly_sales#23] +Condition : CASE WHEN (avg_monthly_sales#23 > 0.000000) THEN ((abs((sum_sales#21 - avg_monthly_sales#23)) / avg_monthly_sales#23) > 0.1000000000000000) ELSE false END + +(27) Project [codegen id : 7] +Output [3]: [i_manager_id#5, sum_sales#21, avg_monthly_sales#23] +Input [4]: [i_manager_id#5, sum_sales#21, _w0#22, avg_monthly_sales#23] + +(28) TakeOrderedAndProject +Input [3]: [i_manager_id#5, sum_sales#21, avg_monthly_sales#23] +Arguments: 100, [i_manager_id#5 ASC NULLS FIRST, avg_monthly_sales#23 ASC NULLS FIRST, sum_sales#21 ASC NULLS FIRST], [i_manager_id#5, sum_sales#21, avg_monthly_sales#23] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 5 Hosting Expression = ss_sold_date_sk#13 IN dynamicpruning#14 +BroadcastExchange (33) ++- * ColumnarToRow (32) + +- CometProject (31) + +- CometFilter (30) + +- CometScan parquet spark_catalog.default.date_dim (29) + + +(29) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#15, d_month_seq#24, d_moy#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [In(d_month_seq, [1200,1201,1202,1203,1204,1205,1206,1207,1208,1209,1210,1211]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(30) CometFilter +Input [3]: [d_date_sk#15, d_month_seq#24, d_moy#16] +Condition : (d_month_seq#24 INSET 1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211 AND isnotnull(d_date_sk#15)) + +(31) CometProject +Input [3]: [d_date_sk#15, d_month_seq#24, d_moy#16] +Arguments: [d_date_sk#15, d_moy#16], [d_date_sk#15, d_moy#16] + +(32) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#15, d_moy#16] + +(33) BroadcastExchange +Input [2]: [d_date_sk#15, d_moy#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q63/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q63/simplified.txt new file mode 100644 index 0000000000..7f6f8c1370 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q63/simplified.txt @@ -0,0 +1,51 @@ +TakeOrderedAndProject [i_manager_id,avg_monthly_sales,sum_sales] + WholeStageCodegen (7) + Project [i_manager_id,sum_sales,avg_monthly_sales] + Filter [avg_monthly_sales,sum_sales] + InputAdapter + Window [_w0,i_manager_id] + WholeStageCodegen (6) + Sort [i_manager_id] + InputAdapter + Exchange [i_manager_id] #1 + WholeStageCodegen (5) + HashAggregate [i_manager_id,d_moy,sum] [sum(UnscaledValue(ss_sales_price)),sum_sales,_w0,sum] + InputAdapter + Exchange [i_manager_id,d_moy] #2 + WholeStageCodegen (4) + HashAggregate [i_manager_id,d_moy,ss_sales_price] [sum,sum] + Project [i_manager_id,ss_sales_price,d_moy] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [i_manager_id,ss_store_sk,ss_sales_price,d_moy] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [i_manager_id,ss_store_sk,ss_sales_price,ss_sold_date_sk] + BroadcastHashJoin [i_item_sk,ss_item_sk] + ColumnarToRow + InputAdapter + CometProject [i_item_sk,i_manager_id] + CometFilter [i_category,i_class,i_brand,i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_class,i_category,i_manager_id] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk,ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_moy] + CometFilter [d_month_seq,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq,d_moy] + InputAdapter + ReusedExchange [d_date_sk,d_moy] #4 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q64/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q64/explain.txt new file mode 100644 index 0000000000..667362aa3c --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q64/explain.txt @@ -0,0 +1,1064 @@ +== Physical Plan == +* Sort (181) ++- Exchange (180) + +- * Project (179) + +- * SortMergeJoin Inner (178) + :- * Sort (110) + : +- Exchange (109) + : +- * HashAggregate (108) + : +- * HashAggregate (107) + : +- * Project (106) + : +- * BroadcastHashJoin Inner BuildRight (105) + : :- * Project (99) + : : +- * BroadcastHashJoin Inner BuildRight (98) + : : :- * Project (96) + : : : +- * BroadcastHashJoin Inner BuildRight (95) + : : : :- * Project (90) + : : : : +- * BroadcastHashJoin Inner BuildRight (89) + : : : : :- * Project (87) + : : : : : +- * BroadcastHashJoin Inner BuildRight (86) + : : : : : :- * Project (81) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (80) + : : : : : : :- * Project (78) + : : : : : : : +- * BroadcastHashJoin Inner BuildRight (77) + : : : : : : : :- * Project (72) + : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (71) + : : : : : : : : :- * Project (66) + : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (65) + : : : : : : : : : :- * Project (63) + : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (62) + : : : : : : : : : : :- * Project (57) + : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (56) + : : : : : : : : : : : :- * Project (54) + : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (53) + : : : : : : : : : : : : :- * Project (48) + : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (47) + : : : : : : : : : : : : : :- * Project (42) + : : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (41) + : : : : : : : : : : : : : : :- * Project (36) + : : : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (35) + : : : : : : : : : : : : : : : :- * Project (33) + : : : : : : : : : : : : : : : : +- * SortMergeJoin Inner (32) + : : : : : : : : : : : : : : : : :- * Sort (11) + : : : : : : : : : : : : : : : : : +- Exchange (10) + : : : : : : : : : : : : : : : : : +- * ColumnarToRow (9) + : : : : : : : : : : : : : : : : : +- CometProject (8) + : : : : : : : : : : : : : : : : : +- CometBroadcastHashJoin (7) + : : : : : : : : : : : : : : : : : :- CometBroadcastExchange (3) + : : : : : : : : : : : : : : : : : : +- CometFilter (2) + : : : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : : : : : : : : : : : : : : +- CometProject (6) + : : : : : : : : : : : : : : : : : +- CometFilter (5) + : : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store_returns (4) + : : : : : : : : : : : : : : : : +- * Sort (31) + : : : : : : : : : : : : : : : : +- * Project (30) + : : : : : : : : : : : : : : : : +- * Filter (29) + : : : : : : : : : : : : : : : : +- * HashAggregate (28) + : : : : : : : : : : : : : : : : +- Exchange (27) + : : : : : : : : : : : : : : : : +- * HashAggregate (26) + : : : : : : : : : : : : : : : : +- * Project (25) + : : : : : : : : : : : : : : : : +- * SortMergeJoin Inner (24) + : : : : : : : : : : : : : : : : :- * Sort (17) + : : : : : : : : : : : : : : : : : +- Exchange (16) + : : : : : : : : : : : : : : : : : +- * ColumnarToRow (15) + : : : : : : : : : : : : : : : : : +- CometProject (14) + : : : : : : : : : : : : : : : : : +- CometFilter (13) + : : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (12) + : : : : : : : : : : : : : : : : +- * Sort (23) + : : : : : : : : : : : : : : : : +- Exchange (22) + : : : : : : : : : : : : : : : : +- * ColumnarToRow (21) + : : : : : : : : : : : : : : : : +- CometProject (20) + : : : : : : : : : : : : : : : : +- CometFilter (19) + : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.catalog_returns (18) + : : : : : : : : : : : : : : : +- ReusedExchange (34) + : : : : : : : : : : : : : : +- BroadcastExchange (40) + : : : : : : : : : : : : : : +- * ColumnarToRow (39) + : : : : : : : : : : : : : : +- CometFilter (38) + : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store (37) + : : : : : : : : : : : : : +- BroadcastExchange (46) + : : : : : : : : : : : : : +- * ColumnarToRow (45) + : : : : : : : : : : : : : +- CometFilter (44) + : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.customer (43) + : : : : : : : : : : : : +- BroadcastExchange (52) + : : : : : : : : : : : : +- * ColumnarToRow (51) + : : : : : : : : : : : : +- CometFilter (50) + : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.date_dim (49) + : : : : : : : : : : : +- ReusedExchange (55) + : : : : : : : : : : +- BroadcastExchange (61) + : : : : : : : : : : +- * ColumnarToRow (60) + : : : : : : : : : : +- CometFilter (59) + : : : : : : : : : : +- CometScan parquet spark_catalog.default.customer_demographics (58) + : : : : : : : : : +- ReusedExchange (64) + : : : : : : : : +- BroadcastExchange (70) + : : : : : : : : +- * ColumnarToRow (69) + : : : : : : : : +- CometFilter (68) + : : : : : : : : +- CometScan parquet spark_catalog.default.promotion (67) + : : : : : : : +- BroadcastExchange (76) + : : : : : : : +- * ColumnarToRow (75) + : : : : : : : +- CometFilter (74) + : : : : : : : +- CometScan parquet spark_catalog.default.household_demographics (73) + : : : : : : +- ReusedExchange (79) + : : : : : +- BroadcastExchange (85) + : : : : : +- * ColumnarToRow (84) + : : : : : +- CometFilter (83) + : : : : : +- CometScan parquet spark_catalog.default.customer_address (82) + : : : : +- ReusedExchange (88) + : : : +- BroadcastExchange (94) + : : : +- * ColumnarToRow (93) + : : : +- CometFilter (92) + : : : +- CometScan parquet spark_catalog.default.income_band (91) + : : +- ReusedExchange (97) + : +- BroadcastExchange (104) + : +- * ColumnarToRow (103) + : +- CometProject (102) + : +- CometFilter (101) + : +- CometScan parquet spark_catalog.default.item (100) + +- * Sort (177) + +- Exchange (176) + +- * HashAggregate (175) + +- * HashAggregate (174) + +- * Project (173) + +- * BroadcastHashJoin Inner BuildRight (172) + :- * Project (170) + : +- * BroadcastHashJoin Inner BuildRight (169) + : :- * Project (167) + : : +- * BroadcastHashJoin Inner BuildRight (166) + : : :- * Project (164) + : : : +- * BroadcastHashJoin Inner BuildRight (163) + : : : :- * Project (161) + : : : : +- * BroadcastHashJoin Inner BuildRight (160) + : : : : :- * Project (158) + : : : : : +- * BroadcastHashJoin Inner BuildRight (157) + : : : : : :- * Project (155) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (154) + : : : : : : :- * Project (152) + : : : : : : : +- * BroadcastHashJoin Inner BuildRight (151) + : : : : : : : :- * Project (149) + : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (148) + : : : : : : : : :- * Project (146) + : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (145) + : : : : : : : : : :- * Project (143) + : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (142) + : : : : : : : : : : :- * Project (140) + : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (139) + : : : : : : : : : : : :- * Project (137) + : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (136) + : : : : : : : : : : : : :- * Project (134) + : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (133) + : : : : : : : : : : : : : :- * Project (131) + : : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (130) + : : : : : : : : : : : : : : :- * Project (128) + : : : : : : : : : : : : : : : +- * SortMergeJoin Inner (127) + : : : : : : : : : : : : : : : :- * Sort (121) + : : : : : : : : : : : : : : : : +- Exchange (120) + : : : : : : : : : : : : : : : : +- * ColumnarToRow (119) + : : : : : : : : : : : : : : : : +- CometProject (118) + : : : : : : : : : : : : : : : : +- CometBroadcastHashJoin (117) + : : : : : : : : : : : : : : : : :- CometBroadcastExchange (113) + : : : : : : : : : : : : : : : : : +- CometFilter (112) + : : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (111) + : : : : : : : : : : : : : : : : +- CometProject (116) + : : : : : : : : : : : : : : : : +- CometFilter (115) + : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store_returns (114) + : : : : : : : : : : : : : : : +- * Sort (126) + : : : : : : : : : : : : : : : +- * Project (125) + : : : : : : : : : : : : : : : +- * Filter (124) + : : : : : : : : : : : : : : : +- * HashAggregate (123) + : : : : : : : : : : : : : : : +- ReusedExchange (122) + : : : : : : : : : : : : : : +- ReusedExchange (129) + : : : : : : : : : : : : : +- ReusedExchange (132) + : : : : : : : : : : : : +- ReusedExchange (135) + : : : : : : : : : : : +- ReusedExchange (138) + : : : : : : : : : : +- ReusedExchange (141) + : : : : : : : : : +- ReusedExchange (144) + : : : : : : : : +- ReusedExchange (147) + : : : : : : : +- ReusedExchange (150) + : : : : : : +- ReusedExchange (153) + : : : : : +- ReusedExchange (156) + : : : : +- ReusedExchange (159) + : : : +- ReusedExchange (162) + : : +- ReusedExchange (165) + : +- ReusedExchange (168) + +- ReusedExchange (171) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_ticket_number#8, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#12), dynamicpruningexpression(ss_sold_date_sk#12 IN dynamicpruning#13)] +PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_ticket_number), IsNotNull(ss_store_sk), IsNotNull(ss_customer_sk), IsNotNull(ss_cdemo_sk), IsNotNull(ss_promo_sk), IsNotNull(ss_hdemo_sk), IsNotNull(ss_addr_sk)] +ReadSchema: struct + +(2) CometFilter +Input [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_ticket_number#8, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] +Condition : (((((((isnotnull(ss_item_sk#1) AND isnotnull(ss_ticket_number#8)) AND isnotnull(ss_store_sk#6)) AND isnotnull(ss_customer_sk#2)) AND isnotnull(ss_cdemo_sk#3)) AND isnotnull(ss_promo_sk#7)) AND isnotnull(ss_hdemo_sk#4)) AND isnotnull(ss_addr_sk#5)) + +(3) CometBroadcastExchange +Input [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_ticket_number#8, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] +Arguments: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_ticket_number#8, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] + +(4) Scan parquet spark_catalog.default.store_returns +Output [3]: [sr_item_sk#14, sr_ticket_number#15, sr_returned_date_sk#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_returns] +PushedFilters: [IsNotNull(sr_item_sk), IsNotNull(sr_ticket_number)] +ReadSchema: struct + +(5) CometFilter +Input [3]: [sr_item_sk#14, sr_ticket_number#15, sr_returned_date_sk#16] +Condition : (isnotnull(sr_item_sk#14) AND isnotnull(sr_ticket_number#15)) + +(6) CometProject +Input [3]: [sr_item_sk#14, sr_ticket_number#15, sr_returned_date_sk#16] +Arguments: [sr_item_sk#14, sr_ticket_number#15], [sr_item_sk#14, sr_ticket_number#15] + +(7) CometBroadcastHashJoin +Left output [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_ticket_number#8, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] +Right output [2]: [sr_item_sk#14, sr_ticket_number#15] +Arguments: [ss_item_sk#1, ss_ticket_number#8], [sr_item_sk#14, sr_ticket_number#15], Inner + +(8) CometProject +Input [14]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_ticket_number#8, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12, sr_item_sk#14, sr_ticket_number#15] +Arguments: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12], [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] + +(9) ColumnarToRow [codegen id : 1] +Input [11]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] + +(10) Exchange +Input [11]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] +Arguments: hashpartitioning(ss_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(11) Sort [codegen id : 2] +Input [11]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] +Arguments: [ss_item_sk#1 ASC NULLS FIRST], false, 0 + +(12) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19, cs_sold_date_sk#20] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_sales] +PushedFilters: [IsNotNull(cs_item_sk), IsNotNull(cs_order_number)] +ReadSchema: struct + +(13) CometFilter +Input [4]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19, cs_sold_date_sk#20] +Condition : (isnotnull(cs_item_sk#17) AND isnotnull(cs_order_number#18)) + +(14) CometProject +Input [4]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19, cs_sold_date_sk#20] +Arguments: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19], [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19] + +(15) ColumnarToRow [codegen id : 3] +Input [3]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19] + +(16) Exchange +Input [3]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19] +Arguments: hashpartitioning(cs_item_sk#17, cs_order_number#18, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(17) Sort [codegen id : 4] +Input [3]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19] +Arguments: [cs_item_sk#17 ASC NULLS FIRST, cs_order_number#18 ASC NULLS FIRST], false, 0 + +(18) Scan parquet spark_catalog.default.catalog_returns +Output [6]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25, cr_returned_date_sk#26] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_returns] +PushedFilters: [IsNotNull(cr_item_sk), IsNotNull(cr_order_number)] +ReadSchema: struct + +(19) CometFilter +Input [6]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25, cr_returned_date_sk#26] +Condition : (isnotnull(cr_item_sk#21) AND isnotnull(cr_order_number#22)) + +(20) CometProject +Input [6]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25, cr_returned_date_sk#26] +Arguments: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25], [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] + +(21) ColumnarToRow [codegen id : 5] +Input [5]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] + +(22) Exchange +Input [5]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] +Arguments: hashpartitioning(cr_item_sk#21, cr_order_number#22, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(23) Sort [codegen id : 6] +Input [5]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] +Arguments: [cr_item_sk#21 ASC NULLS FIRST, cr_order_number#22 ASC NULLS FIRST], false, 0 + +(24) SortMergeJoin [codegen id : 7] +Left keys [2]: [cs_item_sk#17, cs_order_number#18] +Right keys [2]: [cr_item_sk#21, cr_order_number#22] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 7] +Output [5]: [cs_item_sk#17, cs_ext_list_price#19, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] +Input [8]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19, cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] + +(26) HashAggregate [codegen id : 7] +Input [5]: [cs_item_sk#17, cs_ext_list_price#19, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] +Keys [1]: [cs_item_sk#17] +Functions [2]: [partial_sum(UnscaledValue(cs_ext_list_price#19)), partial_sum(((cr_refunded_cash#23 + cr_reversed_charge#24) + cr_store_credit#25))] +Aggregate Attributes [3]: [sum#27, sum#28, isEmpty#29] +Results [4]: [cs_item_sk#17, sum#30, sum#31, isEmpty#32] + +(27) Exchange +Input [4]: [cs_item_sk#17, sum#30, sum#31, isEmpty#32] +Arguments: hashpartitioning(cs_item_sk#17, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(28) HashAggregate [codegen id : 8] +Input [4]: [cs_item_sk#17, sum#30, sum#31, isEmpty#32] +Keys [1]: [cs_item_sk#17] +Functions [2]: [sum(UnscaledValue(cs_ext_list_price#19)), sum(((cr_refunded_cash#23 + cr_reversed_charge#24) + cr_store_credit#25))] +Aggregate Attributes [2]: [sum(UnscaledValue(cs_ext_list_price#19))#33, sum(((cr_refunded_cash#23 + cr_reversed_charge#24) + cr_store_credit#25))#34] +Results [3]: [cs_item_sk#17, MakeDecimal(sum(UnscaledValue(cs_ext_list_price#19))#33,17,2) AS sale#35, sum(((cr_refunded_cash#23 + cr_reversed_charge#24) + cr_store_credit#25))#34 AS refund#36] + +(29) Filter [codegen id : 8] +Input [3]: [cs_item_sk#17, sale#35, refund#36] +Condition : ((isnotnull(sale#35) AND isnotnull(refund#36)) AND (cast(sale#35 as decimal(21,2)) > (2 * refund#36))) + +(30) Project [codegen id : 8] +Output [1]: [cs_item_sk#17] +Input [3]: [cs_item_sk#17, sale#35, refund#36] + +(31) Sort [codegen id : 8] +Input [1]: [cs_item_sk#17] +Arguments: [cs_item_sk#17 ASC NULLS FIRST], false, 0 + +(32) SortMergeJoin [codegen id : 24] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [cs_item_sk#17] +Join type: Inner +Join condition: None + +(33) Project [codegen id : 24] +Output [11]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] +Input [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12, cs_item_sk#17] + +(34) ReusedExchange [Reuses operator id: 185] +Output [2]: [d_date_sk#37, d_year#38] + +(35) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [ss_sold_date_sk#12] +Right keys [1]: [d_date_sk#37] +Join type: Inner +Join condition: None + +(36) Project [codegen id : 24] +Output [11]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38] +Input [13]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12, d_date_sk#37, d_year#38] + +(37) Scan parquet spark_catalog.default.store +Output [3]: [s_store_sk#39, s_store_name#40, s_zip#41] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk), IsNotNull(s_store_name), IsNotNull(s_zip)] +ReadSchema: struct + +(38) CometFilter +Input [3]: [s_store_sk#39, s_store_name#40, s_zip#41] +Condition : ((isnotnull(s_store_sk#39) AND isnotnull(s_store_name#40)) AND isnotnull(s_zip#41)) + +(39) ColumnarToRow [codegen id : 10] +Input [3]: [s_store_sk#39, s_store_name#40, s_zip#41] + +(40) BroadcastExchange +Input [3]: [s_store_sk#39, s_store_name#40, s_zip#41] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(41) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [ss_store_sk#6] +Right keys [1]: [s_store_sk#39] +Join type: Inner +Join condition: None + +(42) Project [codegen id : 24] +Output [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41] +Input [14]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_sk#39, s_store_name#40, s_zip#41] + +(43) Scan parquet spark_catalog.default.customer +Output [6]: [c_customer_sk#42, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_first_sales_date_sk), IsNotNull(c_first_shipto_date_sk), IsNotNull(c_current_cdemo_sk), IsNotNull(c_current_hdemo_sk), IsNotNull(c_current_addr_sk)] +ReadSchema: struct + +(44) CometFilter +Input [6]: [c_customer_sk#42, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] +Condition : (((((isnotnull(c_customer_sk#42) AND isnotnull(c_first_sales_date_sk#47)) AND isnotnull(c_first_shipto_date_sk#46)) AND isnotnull(c_current_cdemo_sk#43)) AND isnotnull(c_current_hdemo_sk#44)) AND isnotnull(c_current_addr_sk#45)) + +(45) ColumnarToRow [codegen id : 11] +Input [6]: [c_customer_sk#42, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] + +(46) BroadcastExchange +Input [6]: [c_customer_sk#42, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6] + +(47) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [ss_customer_sk#2] +Right keys [1]: [c_customer_sk#42] +Join type: Inner +Join condition: None + +(48) Project [codegen id : 24] +Output [16]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] +Input [18]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_customer_sk#42, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] + +(49) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#48, d_year#49] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date_sk)] +ReadSchema: struct + +(50) CometFilter +Input [2]: [d_date_sk#48, d_year#49] +Condition : isnotnull(d_date_sk#48) + +(51) ColumnarToRow [codegen id : 12] +Input [2]: [d_date_sk#48, d_year#49] + +(52) BroadcastExchange +Input [2]: [d_date_sk#48, d_year#49] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=7] + +(53) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [c_first_sales_date_sk#47] +Right keys [1]: [d_date_sk#48] +Join type: Inner +Join condition: None + +(54) Project [codegen id : 24] +Output [16]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, d_year#49] +Input [18]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47, d_date_sk#48, d_year#49] + +(55) ReusedExchange [Reuses operator id: 52] +Output [2]: [d_date_sk#50, d_year#51] + +(56) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [c_first_shipto_date_sk#46] +Right keys [1]: [d_date_sk#50] +Join type: Inner +Join condition: None + +(57) Project [codegen id : 24] +Output [16]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51] +Input [18]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, d_year#49, d_date_sk#50, d_year#51] + +(58) Scan parquet spark_catalog.default.customer_demographics +Output [2]: [cd_demo_sk#52, cd_marital_status#53] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_demo_sk), IsNotNull(cd_marital_status)] +ReadSchema: struct + +(59) CometFilter +Input [2]: [cd_demo_sk#52, cd_marital_status#53] +Condition : (isnotnull(cd_demo_sk#52) AND isnotnull(cd_marital_status#53)) + +(60) ColumnarToRow [codegen id : 14] +Input [2]: [cd_demo_sk#52, cd_marital_status#53] + +(61) BroadcastExchange +Input [2]: [cd_demo_sk#52, cd_marital_status#53] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8] + +(62) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [ss_cdemo_sk#3] +Right keys [1]: [cd_demo_sk#52] +Join type: Inner +Join condition: None + +(63) Project [codegen id : 24] +Output [16]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, cd_marital_status#53] +Input [18]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, cd_demo_sk#52, cd_marital_status#53] + +(64) ReusedExchange [Reuses operator id: 61] +Output [2]: [cd_demo_sk#54, cd_marital_status#55] + +(65) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [c_current_cdemo_sk#43] +Right keys [1]: [cd_demo_sk#54] +Join type: Inner +Join condition: NOT (cd_marital_status#53 = cd_marital_status#55) + +(66) Project [codegen id : 24] +Output [14]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51] +Input [18]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, cd_marital_status#53, cd_demo_sk#54, cd_marital_status#55] + +(67) Scan parquet spark_catalog.default.promotion +Output [1]: [p_promo_sk#56] +Batched: true +Location [not included in comparison]/{warehouse_dir}/promotion] +PushedFilters: [IsNotNull(p_promo_sk)] +ReadSchema: struct + +(68) CometFilter +Input [1]: [p_promo_sk#56] +Condition : isnotnull(p_promo_sk#56) + +(69) ColumnarToRow [codegen id : 16] +Input [1]: [p_promo_sk#56] + +(70) BroadcastExchange +Input [1]: [p_promo_sk#56] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=9] + +(71) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [ss_promo_sk#7] +Right keys [1]: [p_promo_sk#56] +Join type: Inner +Join condition: None + +(72) Project [codegen id : 24] +Output [13]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51] +Input [15]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, p_promo_sk#56] + +(73) Scan parquet spark_catalog.default.household_demographics +Output [2]: [hd_demo_sk#57, hd_income_band_sk#58] +Batched: true +Location [not included in comparison]/{warehouse_dir}/household_demographics] +PushedFilters: [IsNotNull(hd_demo_sk), IsNotNull(hd_income_band_sk)] +ReadSchema: struct + +(74) CometFilter +Input [2]: [hd_demo_sk#57, hd_income_band_sk#58] +Condition : (isnotnull(hd_demo_sk#57) AND isnotnull(hd_income_band_sk#58)) + +(75) ColumnarToRow [codegen id : 17] +Input [2]: [hd_demo_sk#57, hd_income_band_sk#58] + +(76) BroadcastExchange +Input [2]: [hd_demo_sk#57, hd_income_band_sk#58] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=10] + +(77) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [ss_hdemo_sk#4] +Right keys [1]: [hd_demo_sk#57] +Join type: Inner +Join condition: None + +(78) Project [codegen id : 24] +Output [13]: [ss_item_sk#1, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58] +Input [15]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, hd_demo_sk#57, hd_income_band_sk#58] + +(79) ReusedExchange [Reuses operator id: 76] +Output [2]: [hd_demo_sk#59, hd_income_band_sk#60] + +(80) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [c_current_hdemo_sk#44] +Right keys [1]: [hd_demo_sk#59] +Join type: Inner +Join condition: None + +(81) Project [codegen id : 24] +Output [13]: [ss_item_sk#1, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60] +Input [15]: [ss_item_sk#1, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58, hd_demo_sk#59, hd_income_band_sk#60] + +(82) Scan parquet spark_catalog.default.customer_address +Output [5]: [ca_address_sk#61, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk)] +ReadSchema: struct + +(83) CometFilter +Input [5]: [ca_address_sk#61, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] +Condition : isnotnull(ca_address_sk#61) + +(84) ColumnarToRow [codegen id : 19] +Input [5]: [ca_address_sk#61, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] + +(85) BroadcastExchange +Input [5]: [ca_address_sk#61, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=11] + +(86) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [ss_addr_sk#5] +Right keys [1]: [ca_address_sk#61] +Join type: Inner +Join condition: None + +(87) Project [codegen id : 24] +Output [16]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] +Input [18]: [ss_item_sk#1, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60, ca_address_sk#61, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] + +(88) ReusedExchange [Reuses operator id: 85] +Output [5]: [ca_address_sk#66, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70] + +(89) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [c_current_addr_sk#45] +Right keys [1]: [ca_address_sk#66] +Join type: Inner +Join condition: None + +(90) Project [codegen id : 24] +Output [19]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70] +Input [21]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_address_sk#66, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70] + +(91) Scan parquet spark_catalog.default.income_band +Output [1]: [ib_income_band_sk#71] +Batched: true +Location [not included in comparison]/{warehouse_dir}/income_band] +PushedFilters: [IsNotNull(ib_income_band_sk)] +ReadSchema: struct + +(92) CometFilter +Input [1]: [ib_income_band_sk#71] +Condition : isnotnull(ib_income_band_sk#71) + +(93) ColumnarToRow [codegen id : 21] +Input [1]: [ib_income_band_sk#71] + +(94) BroadcastExchange +Input [1]: [ib_income_band_sk#71] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=12] + +(95) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [hd_income_band_sk#58] +Right keys [1]: [ib_income_band_sk#71] +Join type: Inner +Join condition: None + +(96) Project [codegen id : 24] +Output [18]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70] +Input [20]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, ib_income_band_sk#71] + +(97) ReusedExchange [Reuses operator id: 94] +Output [1]: [ib_income_band_sk#72] + +(98) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [hd_income_band_sk#60] +Right keys [1]: [ib_income_band_sk#72] +Join type: Inner +Join condition: None + +(99) Project [codegen id : 24] +Output [17]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70] +Input [19]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, ib_income_band_sk#72] + +(100) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#73, i_current_price#74, i_color#75, i_product_name#76] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_current_price), In(i_color, [burlywood ,floral ,indian ,medium ,purple ,spring ]), GreaterThanOrEqual(i_current_price,64.00), LessThanOrEqual(i_current_price,74.00), GreaterThanOrEqual(i_current_price,65.00), LessThanOrEqual(i_current_price,79.00), IsNotNull(i_item_sk)] +ReadSchema: struct + +(101) CometFilter +Input [4]: [i_item_sk#73, i_current_price#74, i_color#75, i_product_name#76] +Condition : ((((((isnotnull(i_current_price#74) AND i_color#75 IN (purple ,burlywood ,indian ,spring ,floral ,medium )) AND (i_current_price#74 >= 64.00)) AND (i_current_price#74 <= 74.00)) AND (i_current_price#74 >= 65.00)) AND (i_current_price#74 <= 79.00)) AND isnotnull(i_item_sk#73)) + +(102) CometProject +Input [4]: [i_item_sk#73, i_current_price#74, i_color#75, i_product_name#76] +Arguments: [i_item_sk#73, i_product_name#76], [i_item_sk#73, i_product_name#76] + +(103) ColumnarToRow [codegen id : 23] +Input [2]: [i_item_sk#73, i_product_name#76] + +(104) BroadcastExchange +Input [2]: [i_item_sk#73, i_product_name#76] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=13] + +(105) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#73] +Join type: Inner +Join condition: None + +(106) Project [codegen id : 24] +Output [18]: [ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, d_year#49, d_year#51, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, i_item_sk#73, i_product_name#76] +Input [19]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, i_item_sk#73, i_product_name#76] + +(107) HashAggregate [codegen id : 24] +Input [18]: [ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, d_year#49, d_year#51, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, i_item_sk#73, i_product_name#76] +Keys [15]: [i_product_name#76, i_item_sk#73, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, d_year#38, d_year#49, d_year#51] +Functions [4]: [partial_count(1), partial_sum(UnscaledValue(ss_wholesale_cost#9)), partial_sum(UnscaledValue(ss_list_price#10)), partial_sum(UnscaledValue(ss_coupon_amt#11))] +Aggregate Attributes [4]: [count#77, sum#78, sum#79, sum#80] +Results [19]: [i_product_name#76, i_item_sk#73, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, d_year#38, d_year#49, d_year#51, count#81, sum#82, sum#83, sum#84] + +(108) HashAggregate [codegen id : 24] +Input [19]: [i_product_name#76, i_item_sk#73, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, d_year#38, d_year#49, d_year#51, count#81, sum#82, sum#83, sum#84] +Keys [15]: [i_product_name#76, i_item_sk#73, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, d_year#38, d_year#49, d_year#51] +Functions [4]: [count(1), sum(UnscaledValue(ss_wholesale_cost#9)), sum(UnscaledValue(ss_list_price#10)), sum(UnscaledValue(ss_coupon_amt#11))] +Aggregate Attributes [4]: [count(1)#85, sum(UnscaledValue(ss_wholesale_cost#9))#86, sum(UnscaledValue(ss_list_price#10))#87, sum(UnscaledValue(ss_coupon_amt#11))#88] +Results [17]: [i_product_name#76 AS product_name#89, i_item_sk#73 AS item_sk#90, s_store_name#40 AS store_name#91, s_zip#41 AS store_zip#92, ca_street_number#62 AS b_street_number#93, ca_street_name#63 AS b_streen_name#94, ca_city#64 AS b_city#95, ca_zip#65 AS b_zip#96, ca_street_number#67 AS c_street_number#97, ca_street_name#68 AS c_street_name#98, ca_city#69 AS c_city#99, ca_zip#70 AS c_zip#100, d_year#38 AS syear#101, count(1)#85 AS cnt#102, MakeDecimal(sum(UnscaledValue(ss_wholesale_cost#9))#86,17,2) AS s1#103, MakeDecimal(sum(UnscaledValue(ss_list_price#10))#87,17,2) AS s2#104, MakeDecimal(sum(UnscaledValue(ss_coupon_amt#11))#88,17,2) AS s3#105] + +(109) Exchange +Input [17]: [product_name#89, item_sk#90, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105] +Arguments: hashpartitioning(item_sk#90, store_name#91, store_zip#92, 5), ENSURE_REQUIREMENTS, [plan_id=14] + +(110) Sort [codegen id : 25] +Input [17]: [product_name#89, item_sk#90, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105] +Arguments: [item_sk#90 ASC NULLS FIRST, store_name#91 ASC NULLS FIRST, store_zip#92 ASC NULLS FIRST], false, 0 + +(111) Scan parquet spark_catalog.default.store_sales +Output [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#117), dynamicpruningexpression(ss_sold_date_sk#117 IN dynamicpruning#118)] +PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_ticket_number), IsNotNull(ss_store_sk), IsNotNull(ss_customer_sk), IsNotNull(ss_cdemo_sk), IsNotNull(ss_promo_sk), IsNotNull(ss_hdemo_sk), IsNotNull(ss_addr_sk)] +ReadSchema: struct + +(112) CometFilter +Input [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] +Condition : (((((((isnotnull(ss_item_sk#106) AND isnotnull(ss_ticket_number#113)) AND isnotnull(ss_store_sk#111)) AND isnotnull(ss_customer_sk#107)) AND isnotnull(ss_cdemo_sk#108)) AND isnotnull(ss_promo_sk#112)) AND isnotnull(ss_hdemo_sk#109)) AND isnotnull(ss_addr_sk#110)) + +(113) CometBroadcastExchange +Input [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] +Arguments: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] + +(114) Scan parquet spark_catalog.default.store_returns +Output [3]: [sr_item_sk#119, sr_ticket_number#120, sr_returned_date_sk#121] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_returns] +PushedFilters: [IsNotNull(sr_item_sk), IsNotNull(sr_ticket_number)] +ReadSchema: struct + +(115) CometFilter +Input [3]: [sr_item_sk#119, sr_ticket_number#120, sr_returned_date_sk#121] +Condition : (isnotnull(sr_item_sk#119) AND isnotnull(sr_ticket_number#120)) + +(116) CometProject +Input [3]: [sr_item_sk#119, sr_ticket_number#120, sr_returned_date_sk#121] +Arguments: [sr_item_sk#119, sr_ticket_number#120], [sr_item_sk#119, sr_ticket_number#120] + +(117) CometBroadcastHashJoin +Left output [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] +Right output [2]: [sr_item_sk#119, sr_ticket_number#120] +Arguments: [ss_item_sk#106, ss_ticket_number#113], [sr_item_sk#119, sr_ticket_number#120], Inner + +(118) CometProject +Input [14]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117, sr_item_sk#119, sr_ticket_number#120] +Arguments: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117], [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] + +(119) ColumnarToRow [codegen id : 26] +Input [11]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] + +(120) Exchange +Input [11]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] +Arguments: hashpartitioning(ss_item_sk#106, 5), ENSURE_REQUIREMENTS, [plan_id=15] + +(121) Sort [codegen id : 27] +Input [11]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] +Arguments: [ss_item_sk#106 ASC NULLS FIRST], false, 0 + +(122) ReusedExchange [Reuses operator id: 27] +Output [4]: [cs_item_sk#122, sum#123, sum#124, isEmpty#125] + +(123) HashAggregate [codegen id : 33] +Input [4]: [cs_item_sk#122, sum#123, sum#124, isEmpty#125] +Keys [1]: [cs_item_sk#122] +Functions [2]: [sum(UnscaledValue(cs_ext_list_price#126)), sum(((cr_refunded_cash#127 + cr_reversed_charge#128) + cr_store_credit#129))] +Aggregate Attributes [2]: [sum(UnscaledValue(cs_ext_list_price#126))#33, sum(((cr_refunded_cash#127 + cr_reversed_charge#128) + cr_store_credit#129))#34] +Results [3]: [cs_item_sk#122, MakeDecimal(sum(UnscaledValue(cs_ext_list_price#126))#33,17,2) AS sale#130, sum(((cr_refunded_cash#127 + cr_reversed_charge#128) + cr_store_credit#129))#34 AS refund#131] + +(124) Filter [codegen id : 33] +Input [3]: [cs_item_sk#122, sale#130, refund#131] +Condition : ((isnotnull(sale#130) AND isnotnull(refund#131)) AND (cast(sale#130 as decimal(21,2)) > (2 * refund#131))) + +(125) Project [codegen id : 33] +Output [1]: [cs_item_sk#122] +Input [3]: [cs_item_sk#122, sale#130, refund#131] + +(126) Sort [codegen id : 33] +Input [1]: [cs_item_sk#122] +Arguments: [cs_item_sk#122 ASC NULLS FIRST], false, 0 + +(127) SortMergeJoin [codegen id : 49] +Left keys [1]: [ss_item_sk#106] +Right keys [1]: [cs_item_sk#122] +Join type: Inner +Join condition: None + +(128) Project [codegen id : 49] +Output [11]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] +Input [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117, cs_item_sk#122] + +(129) ReusedExchange [Reuses operator id: 189] +Output [2]: [d_date_sk#132, d_year#133] + +(130) BroadcastHashJoin [codegen id : 49] +Left keys [1]: [ss_sold_date_sk#117] +Right keys [1]: [d_date_sk#132] +Join type: Inner +Join condition: None + +(131) Project [codegen id : 49] +Output [11]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133] +Input [13]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117, d_date_sk#132, d_year#133] + +(132) ReusedExchange [Reuses operator id: 40] +Output [3]: [s_store_sk#134, s_store_name#135, s_zip#136] + +(133) BroadcastHashJoin [codegen id : 49] +Left keys [1]: [ss_store_sk#111] +Right keys [1]: [s_store_sk#134] +Join type: Inner +Join condition: None + +(134) Project [codegen id : 49] +Output [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136] +Input [14]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_sk#134, s_store_name#135, s_zip#136] + +(135) ReusedExchange [Reuses operator id: 46] +Output [6]: [c_customer_sk#137, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, c_first_sales_date_sk#142] + +(136) BroadcastHashJoin [codegen id : 49] +Left keys [1]: [ss_customer_sk#107] +Right keys [1]: [c_customer_sk#137] +Join type: Inner +Join condition: None + +(137) Project [codegen id : 49] +Output [16]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, c_first_sales_date_sk#142] +Input [18]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_customer_sk#137, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, c_first_sales_date_sk#142] + +(138) ReusedExchange [Reuses operator id: 52] +Output [2]: [d_date_sk#143, d_year#144] + +(139) BroadcastHashJoin [codegen id : 49] +Left keys [1]: [c_first_sales_date_sk#142] +Right keys [1]: [d_date_sk#143] +Join type: Inner +Join condition: None + +(140) Project [codegen id : 49] +Output [16]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, d_year#144] +Input [18]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, c_first_sales_date_sk#142, d_date_sk#143, d_year#144] + +(141) ReusedExchange [Reuses operator id: 52] +Output [2]: [d_date_sk#145, d_year#146] + +(142) BroadcastHashJoin [codegen id : 49] +Left keys [1]: [c_first_shipto_date_sk#141] +Right keys [1]: [d_date_sk#145] +Join type: Inner +Join condition: None + +(143) Project [codegen id : 49] +Output [16]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146] +Input [18]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, d_year#144, d_date_sk#145, d_year#146] + +(144) ReusedExchange [Reuses operator id: 61] +Output [2]: [cd_demo_sk#147, cd_marital_status#148] + +(145) BroadcastHashJoin [codegen id : 49] +Left keys [1]: [ss_cdemo_sk#108] +Right keys [1]: [cd_demo_sk#147] +Join type: Inner +Join condition: None + +(146) Project [codegen id : 49] +Output [16]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, cd_marital_status#148] +Input [18]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, cd_demo_sk#147, cd_marital_status#148] + +(147) ReusedExchange [Reuses operator id: 61] +Output [2]: [cd_demo_sk#149, cd_marital_status#150] + +(148) BroadcastHashJoin [codegen id : 49] +Left keys [1]: [c_current_cdemo_sk#138] +Right keys [1]: [cd_demo_sk#149] +Join type: Inner +Join condition: NOT (cd_marital_status#148 = cd_marital_status#150) + +(149) Project [codegen id : 49] +Output [14]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146] +Input [18]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, cd_marital_status#148, cd_demo_sk#149, cd_marital_status#150] + +(150) ReusedExchange [Reuses operator id: 70] +Output [1]: [p_promo_sk#151] + +(151) BroadcastHashJoin [codegen id : 49] +Left keys [1]: [ss_promo_sk#112] +Right keys [1]: [p_promo_sk#151] +Join type: Inner +Join condition: None + +(152) Project [codegen id : 49] +Output [13]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146] +Input [15]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, p_promo_sk#151] + +(153) ReusedExchange [Reuses operator id: 76] +Output [2]: [hd_demo_sk#152, hd_income_band_sk#153] + +(154) BroadcastHashJoin [codegen id : 49] +Left keys [1]: [ss_hdemo_sk#109] +Right keys [1]: [hd_demo_sk#152] +Join type: Inner +Join condition: None + +(155) Project [codegen id : 49] +Output [13]: [ss_item_sk#106, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153] +Input [15]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, hd_demo_sk#152, hd_income_band_sk#153] + +(156) ReusedExchange [Reuses operator id: 76] +Output [2]: [hd_demo_sk#154, hd_income_band_sk#155] + +(157) BroadcastHashJoin [codegen id : 49] +Left keys [1]: [c_current_hdemo_sk#139] +Right keys [1]: [hd_demo_sk#154] +Join type: Inner +Join condition: None + +(158) Project [codegen id : 49] +Output [13]: [ss_item_sk#106, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155] +Input [15]: [ss_item_sk#106, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153, hd_demo_sk#154, hd_income_band_sk#155] + +(159) ReusedExchange [Reuses operator id: 85] +Output [5]: [ca_address_sk#156, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160] + +(160) BroadcastHashJoin [codegen id : 49] +Left keys [1]: [ss_addr_sk#110] +Right keys [1]: [ca_address_sk#156] +Join type: Inner +Join condition: None + +(161) Project [codegen id : 49] +Output [16]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160] +Input [18]: [ss_item_sk#106, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155, ca_address_sk#156, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160] + +(162) ReusedExchange [Reuses operator id: 85] +Output [5]: [ca_address_sk#161, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165] + +(163) BroadcastHashJoin [codegen id : 49] +Left keys [1]: [c_current_addr_sk#140] +Right keys [1]: [ca_address_sk#161] +Join type: Inner +Join condition: None + +(164) Project [codegen id : 49] +Output [19]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165] +Input [21]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_address_sk#161, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165] + +(165) ReusedExchange [Reuses operator id: 94] +Output [1]: [ib_income_band_sk#166] + +(166) BroadcastHashJoin [codegen id : 49] +Left keys [1]: [hd_income_band_sk#153] +Right keys [1]: [ib_income_band_sk#166] +Join type: Inner +Join condition: None + +(167) Project [codegen id : 49] +Output [18]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165] +Input [20]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, ib_income_band_sk#166] + +(168) ReusedExchange [Reuses operator id: 94] +Output [1]: [ib_income_band_sk#167] + +(169) BroadcastHashJoin [codegen id : 49] +Left keys [1]: [hd_income_band_sk#155] +Right keys [1]: [ib_income_band_sk#167] +Join type: Inner +Join condition: None + +(170) Project [codegen id : 49] +Output [17]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165] +Input [19]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, ib_income_band_sk#167] + +(171) ReusedExchange [Reuses operator id: 104] +Output [2]: [i_item_sk#168, i_product_name#169] + +(172) BroadcastHashJoin [codegen id : 49] +Left keys [1]: [ss_item_sk#106] +Right keys [1]: [i_item_sk#168] +Join type: Inner +Join condition: None + +(173) Project [codegen id : 49] +Output [18]: [ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, d_year#144, d_year#146, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, i_item_sk#168, i_product_name#169] +Input [19]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, i_item_sk#168, i_product_name#169] + +(174) HashAggregate [codegen id : 49] +Input [18]: [ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, d_year#144, d_year#146, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, i_item_sk#168, i_product_name#169] +Keys [15]: [i_product_name#169, i_item_sk#168, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, d_year#133, d_year#144, d_year#146] +Functions [4]: [partial_count(1), partial_sum(UnscaledValue(ss_wholesale_cost#114)), partial_sum(UnscaledValue(ss_list_price#115)), partial_sum(UnscaledValue(ss_coupon_amt#116))] +Aggregate Attributes [4]: [count#77, sum#170, sum#171, sum#172] +Results [19]: [i_product_name#169, i_item_sk#168, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, d_year#133, d_year#144, d_year#146, count#81, sum#173, sum#174, sum#175] + +(175) HashAggregate [codegen id : 49] +Input [19]: [i_product_name#169, i_item_sk#168, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, d_year#133, d_year#144, d_year#146, count#81, sum#173, sum#174, sum#175] +Keys [15]: [i_product_name#169, i_item_sk#168, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, d_year#133, d_year#144, d_year#146] +Functions [4]: [count(1), sum(UnscaledValue(ss_wholesale_cost#114)), sum(UnscaledValue(ss_list_price#115)), sum(UnscaledValue(ss_coupon_amt#116))] +Aggregate Attributes [4]: [count(1)#85, sum(UnscaledValue(ss_wholesale_cost#114))#86, sum(UnscaledValue(ss_list_price#115))#87, sum(UnscaledValue(ss_coupon_amt#116))#88] +Results [8]: [i_item_sk#168 AS item_sk#176, s_store_name#135 AS store_name#177, s_zip#136 AS store_zip#178, d_year#133 AS syear#179, count(1)#85 AS cnt#180, MakeDecimal(sum(UnscaledValue(ss_wholesale_cost#114))#86,17,2) AS s1#181, MakeDecimal(sum(UnscaledValue(ss_list_price#115))#87,17,2) AS s2#182, MakeDecimal(sum(UnscaledValue(ss_coupon_amt#116))#88,17,2) AS s3#183] + +(176) Exchange +Input [8]: [item_sk#176, store_name#177, store_zip#178, syear#179, cnt#180, s1#181, s2#182, s3#183] +Arguments: hashpartitioning(item_sk#176, store_name#177, store_zip#178, 5), ENSURE_REQUIREMENTS, [plan_id=16] + +(177) Sort [codegen id : 50] +Input [8]: [item_sk#176, store_name#177, store_zip#178, syear#179, cnt#180, s1#181, s2#182, s3#183] +Arguments: [item_sk#176 ASC NULLS FIRST, store_name#177 ASC NULLS FIRST, store_zip#178 ASC NULLS FIRST], false, 0 + +(178) SortMergeJoin [codegen id : 51] +Left keys [3]: [item_sk#90, store_name#91, store_zip#92] +Right keys [3]: [item_sk#176, store_name#177, store_zip#178] +Join type: Inner +Join condition: (cnt#180 <= cnt#102) + +(179) Project [codegen id : 51] +Output [21]: [product_name#89, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105, s1#181, s2#182, s3#183, syear#179, cnt#180] +Input [25]: [product_name#89, item_sk#90, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105, item_sk#176, store_name#177, store_zip#178, syear#179, cnt#180, s1#181, s2#182, s3#183] + +(180) Exchange +Input [21]: [product_name#89, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105, s1#181, s2#182, s3#183, syear#179, cnt#180] +Arguments: rangepartitioning(product_name#89 ASC NULLS FIRST, store_name#91 ASC NULLS FIRST, cnt#180 ASC NULLS FIRST, 5), ENSURE_REQUIREMENTS, [plan_id=17] + +(181) Sort [codegen id : 52] +Input [21]: [product_name#89, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105, s1#181, s2#182, s3#183, syear#179, cnt#180] +Arguments: [product_name#89 ASC NULLS FIRST, store_name#91 ASC NULLS FIRST, cnt#180 ASC NULLS FIRST], true, 0 + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#12 IN dynamicpruning#13 +BroadcastExchange (185) ++- * ColumnarToRow (184) + +- CometFilter (183) + +- CometScan parquet spark_catalog.default.date_dim (182) + + +(182) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#37, d_year#38] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,1999), IsNotNull(d_date_sk)] +ReadSchema: struct + +(183) CometFilter +Input [2]: [d_date_sk#37, d_year#38] +Condition : ((isnotnull(d_year#38) AND (d_year#38 = 1999)) AND isnotnull(d_date_sk#37)) + +(184) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#37, d_year#38] + +(185) BroadcastExchange +Input [2]: [d_date_sk#37, d_year#38] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=18] + +Subquery:2 Hosting operator id = 111 Hosting Expression = ss_sold_date_sk#117 IN dynamicpruning#118 +BroadcastExchange (189) ++- * ColumnarToRow (188) + +- CometFilter (187) + +- CometScan parquet spark_catalog.default.date_dim (186) + + +(186) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#132, d_year#133] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2000), IsNotNull(d_date_sk)] +ReadSchema: struct + +(187) CometFilter +Input [2]: [d_date_sk#132, d_year#133] +Condition : ((isnotnull(d_year#133) AND (d_year#133 = 2000)) AND isnotnull(d_date_sk#132)) + +(188) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#132, d_year#133] + +(189) BroadcastExchange +Input [2]: [d_date_sk#132, d_year#133] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=19] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q64/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q64/simplified.txt new file mode 100644 index 0000000000..d972e0082c --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q64/simplified.txt @@ -0,0 +1,281 @@ +WholeStageCodegen (52) + Sort [product_name,store_name,cnt] + InputAdapter + Exchange [product_name,store_name,cnt] #1 + WholeStageCodegen (51) + Project [product_name,store_name,store_zip,b_street_number,b_streen_name,b_city,b_zip,c_street_number,c_street_name,c_city,c_zip,syear,cnt,s1,s2,s3,s1,s2,s3,syear,cnt] + SortMergeJoin [item_sk,store_name,store_zip,item_sk,store_name,store_zip,cnt,cnt] + InputAdapter + WholeStageCodegen (25) + Sort [item_sk,store_name,store_zip] + InputAdapter + Exchange [item_sk,store_name,store_zip] #2 + WholeStageCodegen (24) + HashAggregate [i_product_name,i_item_sk,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,d_year,d_year,d_year,count,sum,sum,sum] [count(1),sum(UnscaledValue(ss_wholesale_cost)),sum(UnscaledValue(ss_list_price)),sum(UnscaledValue(ss_coupon_amt)),product_name,item_sk,store_name,store_zip,b_street_number,b_streen_name,b_city,b_zip,c_street_number,c_street_name,c_city,c_zip,syear,cnt,s1,s2,s3,count,sum,sum,sum] + HashAggregate [i_product_name,i_item_sk,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,d_year,d_year,d_year,ss_wholesale_cost,ss_list_price,ss_coupon_amt] [count,sum,sum,sum,count,sum,sum,sum] + Project [ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,d_year,d_year,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,i_item_sk,i_product_name] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,d_year,d_year,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip] + BroadcastHashJoin [hd_income_band_sk,ib_income_band_sk] + Project [ss_item_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,d_year,d_year,hd_income_band_sk,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip] + BroadcastHashJoin [hd_income_band_sk,ib_income_band_sk] + Project [ss_item_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,d_year,d_year,hd_income_band_sk,hd_income_band_sk,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [ss_item_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_addr_sk,d_year,d_year,hd_income_band_sk,hd_income_band_sk,ca_street_number,ca_street_name,ca_city,ca_zip] + BroadcastHashJoin [ss_addr_sk,ca_address_sk] + Project [ss_item_sk,ss_addr_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_addr_sk,d_year,d_year,hd_income_band_sk,hd_income_band_sk] + BroadcastHashJoin [c_current_hdemo_sk,hd_demo_sk] + Project [ss_item_sk,ss_addr_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year,hd_income_band_sk] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + Project [ss_item_sk,ss_hdemo_sk,ss_addr_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year] + BroadcastHashJoin [ss_promo_sk,p_promo_sk] + Project [ss_item_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk,cd_marital_status,cd_marital_status] + Project [ss_item_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year,cd_marital_status] + BroadcastHashJoin [ss_cdemo_sk,cd_demo_sk] + Project [ss_item_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year] + BroadcastHashJoin [c_first_shipto_date_sk,d_date_sk] + Project [ss_item_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,c_first_shipto_date_sk,d_year] + BroadcastHashJoin [c_first_sales_date_sk,d_date_sk] + Project [ss_item_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,c_first_shipto_date_sk,c_first_sales_date_sk] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + SortMergeJoin [ss_item_sk,cs_item_sk] + InputAdapter + WholeStageCodegen (2) + Sort [ss_item_sk] + InputAdapter + Exchange [ss_item_sk] #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + CometBroadcastHashJoin [ss_item_sk,ss_ticket_number,sr_item_sk,sr_ticket_number] + CometBroadcastExchange #4 + CometFilter [ss_item_sk,ss_ticket_number,ss_store_sk,ss_customer_sk,ss_cdemo_sk,ss_promo_sk,ss_hdemo_sk,ss_addr_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_ticket_number,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #5 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + CometProject [sr_item_sk,sr_ticket_number] + CometFilter [sr_item_sk,sr_ticket_number] + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_returned_date_sk] + InputAdapter + WholeStageCodegen (8) + Sort [cs_item_sk] + Project [cs_item_sk] + Filter [sale,refund] + HashAggregate [cs_item_sk,sum,sum,isEmpty] [sum(UnscaledValue(cs_ext_list_price)),sum(((cr_refunded_cash + cr_reversed_charge) + cr_store_credit)),sale,refund,sum,sum,isEmpty] + InputAdapter + Exchange [cs_item_sk] #6 + WholeStageCodegen (7) + HashAggregate [cs_item_sk,cs_ext_list_price,cr_refunded_cash,cr_reversed_charge,cr_store_credit] [sum,sum,isEmpty,sum,sum,isEmpty] + Project [cs_item_sk,cs_ext_list_price,cr_refunded_cash,cr_reversed_charge,cr_store_credit] + SortMergeJoin [cs_item_sk,cs_order_number,cr_item_sk,cr_order_number] + InputAdapter + WholeStageCodegen (4) + Sort [cs_item_sk,cs_order_number] + InputAdapter + Exchange [cs_item_sk,cs_order_number] #7 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometProject [cs_item_sk,cs_order_number,cs_ext_list_price] + CometFilter [cs_item_sk,cs_order_number] + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_order_number,cs_ext_list_price,cs_sold_date_sk] + InputAdapter + WholeStageCodegen (6) + Sort [cr_item_sk,cr_order_number] + InputAdapter + Exchange [cr_item_sk,cr_order_number] #8 + WholeStageCodegen (5) + ColumnarToRow + InputAdapter + CometProject [cr_item_sk,cr_order_number,cr_refunded_cash,cr_reversed_charge,cr_store_credit] + CometFilter [cr_item_sk,cr_order_number] + CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_refunded_cash,cr_reversed_charge,cr_store_credit,cr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk,d_year] #5 + InputAdapter + BroadcastExchange #9 + WholeStageCodegen (10) + ColumnarToRow + InputAdapter + CometFilter [s_store_sk,s_store_name,s_zip] + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name,s_zip] + InputAdapter + BroadcastExchange #10 + WholeStageCodegen (11) + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_first_sales_date_sk,c_first_shipto_date_sk,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,c_first_shipto_date_sk,c_first_sales_date_sk] + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (12) + ColumnarToRow + InputAdapter + CometFilter [d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk,d_year] #11 + InputAdapter + BroadcastExchange #12 + WholeStageCodegen (14) + ColumnarToRow + InputAdapter + CometFilter [cd_demo_sk,cd_marital_status] + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_marital_status] + InputAdapter + ReusedExchange [cd_demo_sk,cd_marital_status] #12 + InputAdapter + BroadcastExchange #13 + WholeStageCodegen (16) + ColumnarToRow + InputAdapter + CometFilter [p_promo_sk] + CometScan parquet spark_catalog.default.promotion [p_promo_sk] + InputAdapter + BroadcastExchange #14 + WholeStageCodegen (17) + ColumnarToRow + InputAdapter + CometFilter [hd_demo_sk,hd_income_band_sk] + CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_income_band_sk] + InputAdapter + ReusedExchange [hd_demo_sk,hd_income_band_sk] #14 + InputAdapter + BroadcastExchange #15 + WholeStageCodegen (19) + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_street_number,ca_street_name,ca_city,ca_zip] + InputAdapter + ReusedExchange [ca_address_sk,ca_street_number,ca_street_name,ca_city,ca_zip] #15 + InputAdapter + BroadcastExchange #16 + WholeStageCodegen (21) + ColumnarToRow + InputAdapter + CometFilter [ib_income_band_sk] + CometScan parquet spark_catalog.default.income_band [ib_income_band_sk] + InputAdapter + ReusedExchange [ib_income_band_sk] #16 + InputAdapter + BroadcastExchange #17 + WholeStageCodegen (23) + ColumnarToRow + InputAdapter + CometProject [i_item_sk,i_product_name] + CometFilter [i_current_price,i_color,i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price,i_color,i_product_name] + InputAdapter + WholeStageCodegen (50) + Sort [item_sk,store_name,store_zip] + InputAdapter + Exchange [item_sk,store_name,store_zip] #18 + WholeStageCodegen (49) + HashAggregate [i_product_name,i_item_sk,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,d_year,d_year,d_year,count,sum,sum,sum] [count(1),sum(UnscaledValue(ss_wholesale_cost)),sum(UnscaledValue(ss_list_price)),sum(UnscaledValue(ss_coupon_amt)),item_sk,store_name,store_zip,syear,cnt,s1,s2,s3,count,sum,sum,sum] + HashAggregate [i_product_name,i_item_sk,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,d_year,d_year,d_year,ss_wholesale_cost,ss_list_price,ss_coupon_amt] [count,sum,sum,sum,count,sum,sum,sum] + Project [ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,d_year,d_year,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,i_item_sk,i_product_name] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,d_year,d_year,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip] + BroadcastHashJoin [hd_income_band_sk,ib_income_band_sk] + Project [ss_item_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,d_year,d_year,hd_income_band_sk,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip] + BroadcastHashJoin [hd_income_band_sk,ib_income_band_sk] + Project [ss_item_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,d_year,d_year,hd_income_band_sk,hd_income_band_sk,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [ss_item_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_addr_sk,d_year,d_year,hd_income_band_sk,hd_income_band_sk,ca_street_number,ca_street_name,ca_city,ca_zip] + BroadcastHashJoin [ss_addr_sk,ca_address_sk] + Project [ss_item_sk,ss_addr_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_addr_sk,d_year,d_year,hd_income_band_sk,hd_income_band_sk] + BroadcastHashJoin [c_current_hdemo_sk,hd_demo_sk] + Project [ss_item_sk,ss_addr_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year,hd_income_band_sk] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + Project [ss_item_sk,ss_hdemo_sk,ss_addr_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year] + BroadcastHashJoin [ss_promo_sk,p_promo_sk] + Project [ss_item_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk,cd_marital_status,cd_marital_status] + Project [ss_item_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year,cd_marital_status] + BroadcastHashJoin [ss_cdemo_sk,cd_demo_sk] + Project [ss_item_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year] + BroadcastHashJoin [c_first_shipto_date_sk,d_date_sk] + Project [ss_item_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,c_first_shipto_date_sk,d_year] + BroadcastHashJoin [c_first_sales_date_sk,d_date_sk] + Project [ss_item_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,c_first_shipto_date_sk,c_first_sales_date_sk] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + SortMergeJoin [ss_item_sk,cs_item_sk] + InputAdapter + WholeStageCodegen (27) + Sort [ss_item_sk] + InputAdapter + Exchange [ss_item_sk] #19 + WholeStageCodegen (26) + ColumnarToRow + InputAdapter + CometProject [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + CometBroadcastHashJoin [ss_item_sk,ss_ticket_number,sr_item_sk,sr_ticket_number] + CometBroadcastExchange #20 + CometFilter [ss_item_sk,ss_ticket_number,ss_store_sk,ss_customer_sk,ss_cdemo_sk,ss_promo_sk,ss_hdemo_sk,ss_addr_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_ticket_number,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #21 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + CometProject [sr_item_sk,sr_ticket_number] + CometFilter [sr_item_sk,sr_ticket_number] + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_returned_date_sk] + InputAdapter + WholeStageCodegen (33) + Sort [cs_item_sk] + Project [cs_item_sk] + Filter [sale,refund] + HashAggregate [cs_item_sk,sum,sum,isEmpty] [sum(UnscaledValue(cs_ext_list_price)),sum(((cr_refunded_cash + cr_reversed_charge) + cr_store_credit)),sale,refund,sum,sum,isEmpty] + InputAdapter + ReusedExchange [cs_item_sk,sum,sum,isEmpty] #6 + InputAdapter + ReusedExchange [d_date_sk,d_year] #21 + InputAdapter + ReusedExchange [s_store_sk,s_store_name,s_zip] #9 + InputAdapter + ReusedExchange [c_customer_sk,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,c_first_shipto_date_sk,c_first_sales_date_sk] #10 + InputAdapter + ReusedExchange [d_date_sk,d_year] #11 + InputAdapter + ReusedExchange [d_date_sk,d_year] #11 + InputAdapter + ReusedExchange [cd_demo_sk,cd_marital_status] #12 + InputAdapter + ReusedExchange [cd_demo_sk,cd_marital_status] #12 + InputAdapter + ReusedExchange [p_promo_sk] #13 + InputAdapter + ReusedExchange [hd_demo_sk,hd_income_band_sk] #14 + InputAdapter + ReusedExchange [hd_demo_sk,hd_income_band_sk] #14 + InputAdapter + ReusedExchange [ca_address_sk,ca_street_number,ca_street_name,ca_city,ca_zip] #15 + InputAdapter + ReusedExchange [ca_address_sk,ca_street_number,ca_street_name,ca_city,ca_zip] #15 + InputAdapter + ReusedExchange [ib_income_band_sk] #16 + InputAdapter + ReusedExchange [ib_income_band_sk] #16 + InputAdapter + ReusedExchange [i_item_sk,i_product_name] #17 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q65/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q65/explain.txt new file mode 100644 index 0000000000..eda84bb525 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q65/explain.txt @@ -0,0 +1,269 @@ +== Physical Plan == +TakeOrderedAndProject (39) ++- * Project (38) + +- * BroadcastHashJoin Inner BuildRight (37) + :- * Project (22) + : +- * BroadcastHashJoin Inner BuildRight (21) + : :- * Project (16) + : : +- * BroadcastHashJoin Inner BuildRight (15) + : : :- * ColumnarToRow (3) + : : : +- CometFilter (2) + : : : +- CometScan parquet spark_catalog.default.store (1) + : : +- BroadcastExchange (14) + : : +- * Filter (13) + : : +- * HashAggregate (12) + : : +- Exchange (11) + : : +- * HashAggregate (10) + : : +- * Project (9) + : : +- * BroadcastHashJoin Inner BuildRight (8) + : : :- * ColumnarToRow (6) + : : : +- CometFilter (5) + : : : +- CometScan parquet spark_catalog.default.store_sales (4) + : : +- ReusedExchange (7) + : +- BroadcastExchange (20) + : +- * ColumnarToRow (19) + : +- CometFilter (18) + : +- CometScan parquet spark_catalog.default.item (17) + +- BroadcastExchange (36) + +- * Filter (35) + +- * HashAggregate (34) + +- Exchange (33) + +- * HashAggregate (32) + +- * HashAggregate (31) + +- Exchange (30) + +- * HashAggregate (29) + +- * Project (28) + +- * BroadcastHashJoin Inner BuildRight (27) + :- * ColumnarToRow (25) + : +- CometFilter (24) + : +- CometScan parquet spark_catalog.default.store_sales (23) + +- ReusedExchange (26) + + +(1) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#1, s_store_name#2] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(2) CometFilter +Input [2]: [s_store_sk#1, s_store_name#2] +Condition : isnotnull(s_store_sk#1) + +(3) ColumnarToRow [codegen id : 9] +Input [2]: [s_store_sk#1, s_store_name#2] + +(4) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#3, ss_store_sk#4, ss_sales_price#5, ss_sold_date_sk#6] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#6), dynamicpruningexpression(ss_sold_date_sk#6 IN dynamicpruning#7)] +PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_item_sk)] +ReadSchema: struct + +(5) CometFilter +Input [4]: [ss_item_sk#3, ss_store_sk#4, ss_sales_price#5, ss_sold_date_sk#6] +Condition : (isnotnull(ss_store_sk#4) AND isnotnull(ss_item_sk#3)) + +(6) ColumnarToRow [codegen id : 2] +Input [4]: [ss_item_sk#3, ss_store_sk#4, ss_sales_price#5, ss_sold_date_sk#6] + +(7) ReusedExchange [Reuses operator id: 44] +Output [1]: [d_date_sk#8] + +(8) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [ss_sold_date_sk#6] +Right keys [1]: [d_date_sk#8] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 2] +Output [3]: [ss_item_sk#3, ss_store_sk#4, ss_sales_price#5] +Input [5]: [ss_item_sk#3, ss_store_sk#4, ss_sales_price#5, ss_sold_date_sk#6, d_date_sk#8] + +(10) HashAggregate [codegen id : 2] +Input [3]: [ss_item_sk#3, ss_store_sk#4, ss_sales_price#5] +Keys [2]: [ss_store_sk#4, ss_item_sk#3] +Functions [1]: [partial_sum(UnscaledValue(ss_sales_price#5))] +Aggregate Attributes [1]: [sum#9] +Results [3]: [ss_store_sk#4, ss_item_sk#3, sum#10] + +(11) Exchange +Input [3]: [ss_store_sk#4, ss_item_sk#3, sum#10] +Arguments: hashpartitioning(ss_store_sk#4, ss_item_sk#3, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(12) HashAggregate [codegen id : 3] +Input [3]: [ss_store_sk#4, ss_item_sk#3, sum#10] +Keys [2]: [ss_store_sk#4, ss_item_sk#3] +Functions [1]: [sum(UnscaledValue(ss_sales_price#5))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_sales_price#5))#11] +Results [3]: [ss_store_sk#4, ss_item_sk#3, MakeDecimal(sum(UnscaledValue(ss_sales_price#5))#11,17,2) AS revenue#12] + +(13) Filter [codegen id : 3] +Input [3]: [ss_store_sk#4, ss_item_sk#3, revenue#12] +Condition : isnotnull(revenue#12) + +(14) BroadcastExchange +Input [3]: [ss_store_sk#4, ss_item_sk#3, revenue#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(15) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [s_store_sk#1] +Right keys [1]: [ss_store_sk#4] +Join type: Inner +Join condition: None + +(16) Project [codegen id : 9] +Output [4]: [s_store_name#2, ss_store_sk#4, ss_item_sk#3, revenue#12] +Input [5]: [s_store_sk#1, s_store_name#2, ss_store_sk#4, ss_item_sk#3, revenue#12] + +(17) Scan parquet spark_catalog.default.item +Output [5]: [i_item_sk#13, i_item_desc#14, i_current_price#15, i_wholesale_cost#16, i_brand#17] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(18) CometFilter +Input [5]: [i_item_sk#13, i_item_desc#14, i_current_price#15, i_wholesale_cost#16, i_brand#17] +Condition : isnotnull(i_item_sk#13) + +(19) ColumnarToRow [codegen id : 4] +Input [5]: [i_item_sk#13, i_item_desc#14, i_current_price#15, i_wholesale_cost#16, i_brand#17] + +(20) BroadcastExchange +Input [5]: [i_item_sk#13, i_item_desc#14, i_current_price#15, i_wholesale_cost#16, i_brand#17] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(21) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_item_sk#3] +Right keys [1]: [i_item_sk#13] +Join type: Inner +Join condition: None + +(22) Project [codegen id : 9] +Output [7]: [s_store_name#2, ss_store_sk#4, revenue#12, i_item_desc#14, i_current_price#15, i_wholesale_cost#16, i_brand#17] +Input [9]: [s_store_name#2, ss_store_sk#4, ss_item_sk#3, revenue#12, i_item_sk#13, i_item_desc#14, i_current_price#15, i_wholesale_cost#16, i_brand#17] + +(23) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#18, ss_store_sk#19, ss_sales_price#20, ss_sold_date_sk#21] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#21), dynamicpruningexpression(ss_sold_date_sk#21 IN dynamicpruning#22)] +PushedFilters: [IsNotNull(ss_store_sk)] +ReadSchema: struct + +(24) CometFilter +Input [4]: [ss_item_sk#18, ss_store_sk#19, ss_sales_price#20, ss_sold_date_sk#21] +Condition : isnotnull(ss_store_sk#19) + +(25) ColumnarToRow [codegen id : 6] +Input [4]: [ss_item_sk#18, ss_store_sk#19, ss_sales_price#20, ss_sold_date_sk#21] + +(26) ReusedExchange [Reuses operator id: 44] +Output [1]: [d_date_sk#23] + +(27) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_sold_date_sk#21] +Right keys [1]: [d_date_sk#23] +Join type: Inner +Join condition: None + +(28) Project [codegen id : 6] +Output [3]: [ss_item_sk#18, ss_store_sk#19, ss_sales_price#20] +Input [5]: [ss_item_sk#18, ss_store_sk#19, ss_sales_price#20, ss_sold_date_sk#21, d_date_sk#23] + +(29) HashAggregate [codegen id : 6] +Input [3]: [ss_item_sk#18, ss_store_sk#19, ss_sales_price#20] +Keys [2]: [ss_store_sk#19, ss_item_sk#18] +Functions [1]: [partial_sum(UnscaledValue(ss_sales_price#20))] +Aggregate Attributes [1]: [sum#24] +Results [3]: [ss_store_sk#19, ss_item_sk#18, sum#25] + +(30) Exchange +Input [3]: [ss_store_sk#19, ss_item_sk#18, sum#25] +Arguments: hashpartitioning(ss_store_sk#19, ss_item_sk#18, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(31) HashAggregate [codegen id : 7] +Input [3]: [ss_store_sk#19, ss_item_sk#18, sum#25] +Keys [2]: [ss_store_sk#19, ss_item_sk#18] +Functions [1]: [sum(UnscaledValue(ss_sales_price#20))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_sales_price#20))#26] +Results [2]: [ss_store_sk#19, MakeDecimal(sum(UnscaledValue(ss_sales_price#20))#26,17,2) AS revenue#27] + +(32) HashAggregate [codegen id : 7] +Input [2]: [ss_store_sk#19, revenue#27] +Keys [1]: [ss_store_sk#19] +Functions [1]: [partial_avg(revenue#27)] +Aggregate Attributes [2]: [sum#28, count#29] +Results [3]: [ss_store_sk#19, sum#30, count#31] + +(33) Exchange +Input [3]: [ss_store_sk#19, sum#30, count#31] +Arguments: hashpartitioning(ss_store_sk#19, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(34) HashAggregate [codegen id : 8] +Input [3]: [ss_store_sk#19, sum#30, count#31] +Keys [1]: [ss_store_sk#19] +Functions [1]: [avg(revenue#27)] +Aggregate Attributes [1]: [avg(revenue#27)#32] +Results [2]: [ss_store_sk#19, avg(revenue#27)#32 AS ave#33] + +(35) Filter [codegen id : 8] +Input [2]: [ss_store_sk#19, ave#33] +Condition : isnotnull(ave#33) + +(36) BroadcastExchange +Input [2]: [ss_store_sk#19, ave#33] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6] + +(37) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_store_sk#4] +Right keys [1]: [ss_store_sk#19] +Join type: Inner +Join condition: (cast(revenue#12 as decimal(23,7)) <= (0.1 * ave#33)) + +(38) Project [codegen id : 9] +Output [6]: [s_store_name#2, i_item_desc#14, revenue#12, i_current_price#15, i_wholesale_cost#16, i_brand#17] +Input [9]: [s_store_name#2, ss_store_sk#4, revenue#12, i_item_desc#14, i_current_price#15, i_wholesale_cost#16, i_brand#17, ss_store_sk#19, ave#33] + +(39) TakeOrderedAndProject +Input [6]: [s_store_name#2, i_item_desc#14, revenue#12, i_current_price#15, i_wholesale_cost#16, i_brand#17] +Arguments: 100, [s_store_name#2 ASC NULLS FIRST, i_item_desc#14 ASC NULLS FIRST], [s_store_name#2, i_item_desc#14, revenue#12, i_current_price#15, i_wholesale_cost#16, i_brand#17] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#6 IN dynamicpruning#7 +BroadcastExchange (44) ++- * ColumnarToRow (43) + +- CometProject (42) + +- CometFilter (41) + +- CometScan parquet spark_catalog.default.date_dim (40) + + +(40) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#8, d_month_seq#34] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1176), LessThanOrEqual(d_month_seq,1187), IsNotNull(d_date_sk)] +ReadSchema: struct + +(41) CometFilter +Input [2]: [d_date_sk#8, d_month_seq#34] +Condition : (((isnotnull(d_month_seq#34) AND (d_month_seq#34 >= 1176)) AND (d_month_seq#34 <= 1187)) AND isnotnull(d_date_sk#8)) + +(42) CometProject +Input [2]: [d_date_sk#8, d_month_seq#34] +Arguments: [d_date_sk#8], [d_date_sk#8] + +(43) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#8] + +(44) BroadcastExchange +Input [1]: [d_date_sk#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +Subquery:2 Hosting operator id = 23 Hosting Expression = ss_sold_date_sk#21 IN dynamicpruning#7 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q65/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q65/simplified.txt new file mode 100644 index 0000000000..33b695e811 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q65/simplified.txt @@ -0,0 +1,67 @@ +TakeOrderedAndProject [s_store_name,i_item_desc,revenue,i_current_price,i_wholesale_cost,i_brand] + WholeStageCodegen (9) + Project [s_store_name,i_item_desc,revenue,i_current_price,i_wholesale_cost,i_brand] + BroadcastHashJoin [ss_store_sk,ss_store_sk,revenue,ave] + Project [s_store_name,ss_store_sk,revenue,i_item_desc,i_current_price,i_wholesale_cost,i_brand] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [s_store_name,ss_store_sk,ss_item_sk,revenue] + BroadcastHashJoin [s_store_sk,ss_store_sk] + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name] + InputAdapter + BroadcastExchange #1 + WholeStageCodegen (3) + Filter [revenue] + HashAggregate [ss_store_sk,ss_item_sk,sum] [sum(UnscaledValue(ss_sales_price)),revenue,sum] + InputAdapter + Exchange [ss_store_sk,ss_item_sk] #2 + WholeStageCodegen (2) + HashAggregate [ss_store_sk,ss_item_sk,ss_sales_price] [sum,sum] + Project [ss_item_sk,ss_store_sk,ss_sales_price] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk,ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_month_seq,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (4) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_desc,i_current_price,i_wholesale_cost,i_brand] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (8) + Filter [ave] + HashAggregate [ss_store_sk,sum,count] [avg(revenue),ave,sum,count] + InputAdapter + Exchange [ss_store_sk] #6 + WholeStageCodegen (7) + HashAggregate [ss_store_sk,revenue] [sum,count,sum,count] + HashAggregate [ss_store_sk,ss_item_sk,sum] [sum(UnscaledValue(ss_sales_price)),revenue,sum] + InputAdapter + Exchange [ss_store_sk,ss_item_sk] #7 + WholeStageCodegen (6) + HashAggregate [ss_store_sk,ss_item_sk,ss_sales_price] [sum,sum] + Project [ss_item_sk,ss_store_sk,ss_sales_price] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_sales_price,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q66/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q66/explain.txt new file mode 100644 index 0000000000..a26c457aa4 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q66/explain.txt @@ -0,0 +1,332 @@ +== Physical Plan == +TakeOrderedAndProject (52) ++- * HashAggregate (51) + +- Exchange (50) + +- * HashAggregate (49) + +- Union (48) + :- * HashAggregate (29) + : +- Exchange (28) + : +- * HashAggregate (27) + : +- * Project (26) + : +- * BroadcastHashJoin Inner BuildRight (25) + : :- * Project (19) + : : +- * BroadcastHashJoin Inner BuildRight (18) + : : :- * Project (12) + : : : +- * BroadcastHashJoin Inner BuildRight (11) + : : : :- * Project (9) + : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) + : : : : : +- CometScan parquet spark_catalog.default.web_sales (1) + : : : : +- BroadcastExchange (7) + : : : : +- * ColumnarToRow (6) + : : : : +- CometFilter (5) + : : : : +- CometScan parquet spark_catalog.default.warehouse (4) + : : : +- ReusedExchange (10) + : : +- BroadcastExchange (17) + : : +- * ColumnarToRow (16) + : : +- CometProject (15) + : : +- CometFilter (14) + : : +- CometScan parquet spark_catalog.default.time_dim (13) + : +- BroadcastExchange (24) + : +- * ColumnarToRow (23) + : +- CometProject (22) + : +- CometFilter (21) + : +- CometScan parquet spark_catalog.default.ship_mode (20) + +- * HashAggregate (47) + +- Exchange (46) + +- * HashAggregate (45) + +- * Project (44) + +- * BroadcastHashJoin Inner BuildRight (43) + :- * Project (41) + : +- * BroadcastHashJoin Inner BuildRight (40) + : :- * Project (38) + : : +- * BroadcastHashJoin Inner BuildRight (37) + : : :- * Project (35) + : : : +- * BroadcastHashJoin Inner BuildRight (34) + : : : :- * ColumnarToRow (32) + : : : : +- CometFilter (31) + : : : : +- CometScan parquet spark_catalog.default.catalog_sales (30) + : : : +- ReusedExchange (33) + : : +- ReusedExchange (36) + : +- ReusedExchange (39) + +- ReusedExchange (42) + + +(1) Scan parquet spark_catalog.default.web_sales +Output [7]: [ws_sold_time_sk#1, ws_ship_mode_sk#2, ws_warehouse_sk#3, ws_quantity#4, ws_ext_sales_price#5, ws_net_paid#6, ws_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#7), dynamicpruningexpression(ws_sold_date_sk#7 IN dynamicpruning#8)] +PushedFilters: [IsNotNull(ws_warehouse_sk), IsNotNull(ws_sold_time_sk), IsNotNull(ws_ship_mode_sk)] +ReadSchema: struct + +(2) CometFilter +Input [7]: [ws_sold_time_sk#1, ws_ship_mode_sk#2, ws_warehouse_sk#3, ws_quantity#4, ws_ext_sales_price#5, ws_net_paid#6, ws_sold_date_sk#7] +Condition : ((isnotnull(ws_warehouse_sk#3) AND isnotnull(ws_sold_time_sk#1)) AND isnotnull(ws_ship_mode_sk#2)) + +(3) ColumnarToRow [codegen id : 5] +Input [7]: [ws_sold_time_sk#1, ws_ship_mode_sk#2, ws_warehouse_sk#3, ws_quantity#4, ws_ext_sales_price#5, ws_net_paid#6, ws_sold_date_sk#7] + +(4) Scan parquet spark_catalog.default.warehouse +Output [7]: [w_warehouse_sk#9, w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15] +Batched: true +Location [not included in comparison]/{warehouse_dir}/warehouse] +PushedFilters: [IsNotNull(w_warehouse_sk)] +ReadSchema: struct + +(5) CometFilter +Input [7]: [w_warehouse_sk#9, w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15] +Condition : isnotnull(w_warehouse_sk#9) + +(6) ColumnarToRow [codegen id : 1] +Input [7]: [w_warehouse_sk#9, w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15] + +(7) BroadcastExchange +Input [7]: [w_warehouse_sk#9, w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ws_warehouse_sk#3] +Right keys [1]: [w_warehouse_sk#9] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 5] +Output [12]: [ws_sold_time_sk#1, ws_ship_mode_sk#2, ws_quantity#4, ws_ext_sales_price#5, ws_net_paid#6, ws_sold_date_sk#7, w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15] +Input [14]: [ws_sold_time_sk#1, ws_ship_mode_sk#2, ws_warehouse_sk#3, ws_quantity#4, ws_ext_sales_price#5, ws_net_paid#6, ws_sold_date_sk#7, w_warehouse_sk#9, w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15] + +(10) ReusedExchange [Reuses operator id: 56] +Output [3]: [d_date_sk#16, d_year#17, d_moy#18] + +(11) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ws_sold_date_sk#7] +Right keys [1]: [d_date_sk#16] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 5] +Output [13]: [ws_sold_time_sk#1, ws_ship_mode_sk#2, ws_quantity#4, ws_ext_sales_price#5, ws_net_paid#6, w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, d_year#17, d_moy#18] +Input [15]: [ws_sold_time_sk#1, ws_ship_mode_sk#2, ws_quantity#4, ws_ext_sales_price#5, ws_net_paid#6, ws_sold_date_sk#7, w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, d_date_sk#16, d_year#17, d_moy#18] + +(13) Scan parquet spark_catalog.default.time_dim +Output [2]: [t_time_sk#19, t_time#20] +Batched: true +Location [not included in comparison]/{warehouse_dir}/time_dim] +PushedFilters: [IsNotNull(t_time), GreaterThanOrEqual(t_time,30838), LessThanOrEqual(t_time,59638), IsNotNull(t_time_sk)] +ReadSchema: struct + +(14) CometFilter +Input [2]: [t_time_sk#19, t_time#20] +Condition : (((isnotnull(t_time#20) AND (t_time#20 >= 30838)) AND (t_time#20 <= 59638)) AND isnotnull(t_time_sk#19)) + +(15) CometProject +Input [2]: [t_time_sk#19, t_time#20] +Arguments: [t_time_sk#19], [t_time_sk#19] + +(16) ColumnarToRow [codegen id : 3] +Input [1]: [t_time_sk#19] + +(17) BroadcastExchange +Input [1]: [t_time_sk#19] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(18) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ws_sold_time_sk#1] +Right keys [1]: [t_time_sk#19] +Join type: Inner +Join condition: None + +(19) Project [codegen id : 5] +Output [12]: [ws_ship_mode_sk#2, ws_quantity#4, ws_ext_sales_price#5, ws_net_paid#6, w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, d_year#17, d_moy#18] +Input [14]: [ws_sold_time_sk#1, ws_ship_mode_sk#2, ws_quantity#4, ws_ext_sales_price#5, ws_net_paid#6, w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, d_year#17, d_moy#18, t_time_sk#19] + +(20) Scan parquet spark_catalog.default.ship_mode +Output [2]: [sm_ship_mode_sk#21, sm_carrier#22] +Batched: true +Location [not included in comparison]/{warehouse_dir}/ship_mode] +PushedFilters: [In(sm_carrier, [BARIAN ,DHL ]), IsNotNull(sm_ship_mode_sk)] +ReadSchema: struct + +(21) CometFilter +Input [2]: [sm_ship_mode_sk#21, sm_carrier#22] +Condition : (sm_carrier#22 IN (DHL ,BARIAN ) AND isnotnull(sm_ship_mode_sk#21)) + +(22) CometProject +Input [2]: [sm_ship_mode_sk#21, sm_carrier#22] +Arguments: [sm_ship_mode_sk#21], [sm_ship_mode_sk#21] + +(23) ColumnarToRow [codegen id : 4] +Input [1]: [sm_ship_mode_sk#21] + +(24) BroadcastExchange +Input [1]: [sm_ship_mode_sk#21] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(25) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ws_ship_mode_sk#2] +Right keys [1]: [sm_ship_mode_sk#21] +Join type: Inner +Join condition: None + +(26) Project [codegen id : 5] +Output [11]: [ws_quantity#4, ws_ext_sales_price#5, ws_net_paid#6, w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, d_year#17, d_moy#18] +Input [13]: [ws_ship_mode_sk#2, ws_quantity#4, ws_ext_sales_price#5, ws_net_paid#6, w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, d_year#17, d_moy#18, sm_ship_mode_sk#21] + +(27) HashAggregate [codegen id : 5] +Input [11]: [ws_quantity#4, ws_ext_sales_price#5, ws_net_paid#6, w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, d_year#17, d_moy#18] +Keys [7]: [w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, d_year#17] +Functions [24]: [partial_sum(CASE WHEN (d_moy#18 = 1) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 2) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 3) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 4) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 5) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 6) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 7) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 8) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 9) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 10) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 11) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 12) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 1) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 2) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 3) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 4) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 5) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 6) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 7) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 8) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 9) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 10) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 11) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 12) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)] +Aggregate Attributes [48]: [sum#23, isEmpty#24, sum#25, isEmpty#26, sum#27, isEmpty#28, sum#29, isEmpty#30, sum#31, isEmpty#32, sum#33, isEmpty#34, sum#35, isEmpty#36, sum#37, isEmpty#38, sum#39, isEmpty#40, sum#41, isEmpty#42, sum#43, isEmpty#44, sum#45, isEmpty#46, sum#47, isEmpty#48, sum#49, isEmpty#50, sum#51, isEmpty#52, sum#53, isEmpty#54, sum#55, isEmpty#56, sum#57, isEmpty#58, sum#59, isEmpty#60, sum#61, isEmpty#62, sum#63, isEmpty#64, sum#65, isEmpty#66, sum#67, isEmpty#68, sum#69, isEmpty#70] +Results [55]: [w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, d_year#17, sum#71, isEmpty#72, sum#73, isEmpty#74, sum#75, isEmpty#76, sum#77, isEmpty#78, sum#79, isEmpty#80, sum#81, isEmpty#82, sum#83, isEmpty#84, sum#85, isEmpty#86, sum#87, isEmpty#88, sum#89, isEmpty#90, sum#91, isEmpty#92, sum#93, isEmpty#94, sum#95, isEmpty#96, sum#97, isEmpty#98, sum#99, isEmpty#100, sum#101, isEmpty#102, sum#103, isEmpty#104, sum#105, isEmpty#106, sum#107, isEmpty#108, sum#109, isEmpty#110, sum#111, isEmpty#112, sum#113, isEmpty#114, sum#115, isEmpty#116, sum#117, isEmpty#118] + +(28) Exchange +Input [55]: [w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, d_year#17, sum#71, isEmpty#72, sum#73, isEmpty#74, sum#75, isEmpty#76, sum#77, isEmpty#78, sum#79, isEmpty#80, sum#81, isEmpty#82, sum#83, isEmpty#84, sum#85, isEmpty#86, sum#87, isEmpty#88, sum#89, isEmpty#90, sum#91, isEmpty#92, sum#93, isEmpty#94, sum#95, isEmpty#96, sum#97, isEmpty#98, sum#99, isEmpty#100, sum#101, isEmpty#102, sum#103, isEmpty#104, sum#105, isEmpty#106, sum#107, isEmpty#108, sum#109, isEmpty#110, sum#111, isEmpty#112, sum#113, isEmpty#114, sum#115, isEmpty#116, sum#117, isEmpty#118] +Arguments: hashpartitioning(w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, d_year#17, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(29) HashAggregate [codegen id : 6] +Input [55]: [w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, d_year#17, sum#71, isEmpty#72, sum#73, isEmpty#74, sum#75, isEmpty#76, sum#77, isEmpty#78, sum#79, isEmpty#80, sum#81, isEmpty#82, sum#83, isEmpty#84, sum#85, isEmpty#86, sum#87, isEmpty#88, sum#89, isEmpty#90, sum#91, isEmpty#92, sum#93, isEmpty#94, sum#95, isEmpty#96, sum#97, isEmpty#98, sum#99, isEmpty#100, sum#101, isEmpty#102, sum#103, isEmpty#104, sum#105, isEmpty#106, sum#107, isEmpty#108, sum#109, isEmpty#110, sum#111, isEmpty#112, sum#113, isEmpty#114, sum#115, isEmpty#116, sum#117, isEmpty#118] +Keys [7]: [w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, d_year#17] +Functions [24]: [sum(CASE WHEN (d_moy#18 = 1) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 2) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 3) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 4) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 5) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 6) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 7) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 8) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 9) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 10) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 11) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 12) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 1) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 2) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 3) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 4) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 5) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 6) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 7) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 8) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 9) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 10) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 11) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 12) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)] +Aggregate Attributes [24]: [sum(CASE WHEN (d_moy#18 = 1) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#119, sum(CASE WHEN (d_moy#18 = 2) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#120, sum(CASE WHEN (d_moy#18 = 3) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#121, sum(CASE WHEN (d_moy#18 = 4) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#122, sum(CASE WHEN (d_moy#18 = 5) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#123, sum(CASE WHEN (d_moy#18 = 6) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#124, sum(CASE WHEN (d_moy#18 = 7) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#125, sum(CASE WHEN (d_moy#18 = 8) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#126, sum(CASE WHEN (d_moy#18 = 9) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#127, sum(CASE WHEN (d_moy#18 = 10) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#128, sum(CASE WHEN (d_moy#18 = 11) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#129, sum(CASE WHEN (d_moy#18 = 12) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#130, sum(CASE WHEN (d_moy#18 = 1) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#131, sum(CASE WHEN (d_moy#18 = 2) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#132, sum(CASE WHEN (d_moy#18 = 3) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#133, sum(CASE WHEN (d_moy#18 = 4) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#134, sum(CASE WHEN (d_moy#18 = 5) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#135, sum(CASE WHEN (d_moy#18 = 6) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#136, sum(CASE WHEN (d_moy#18 = 7) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#137, sum(CASE WHEN (d_moy#18 = 8) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#138, sum(CASE WHEN (d_moy#18 = 9) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#139, sum(CASE WHEN (d_moy#18 = 10) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#140, sum(CASE WHEN (d_moy#18 = 11) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#141, sum(CASE WHEN (d_moy#18 = 12) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#142] +Results [32]: [w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, DHL,BARIAN AS ship_carriers#143, d_year#17 AS year#144, sum(CASE WHEN (d_moy#18 = 1) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#119 AS jan_sales#145, sum(CASE WHEN (d_moy#18 = 2) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#120 AS feb_sales#146, sum(CASE WHEN (d_moy#18 = 3) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#121 AS mar_sales#147, sum(CASE WHEN (d_moy#18 = 4) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#122 AS apr_sales#148, sum(CASE WHEN (d_moy#18 = 5) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#123 AS may_sales#149, sum(CASE WHEN (d_moy#18 = 6) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#124 AS jun_sales#150, sum(CASE WHEN (d_moy#18 = 7) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#125 AS jul_sales#151, sum(CASE WHEN (d_moy#18 = 8) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#126 AS aug_sales#152, sum(CASE WHEN (d_moy#18 = 9) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#127 AS sep_sales#153, sum(CASE WHEN (d_moy#18 = 10) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#128 AS oct_sales#154, sum(CASE WHEN (d_moy#18 = 11) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#129 AS nov_sales#155, sum(CASE WHEN (d_moy#18 = 12) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#130 AS dec_sales#156, sum(CASE WHEN (d_moy#18 = 1) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#131 AS jan_net#157, sum(CASE WHEN (d_moy#18 = 2) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#132 AS feb_net#158, sum(CASE WHEN (d_moy#18 = 3) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#133 AS mar_net#159, sum(CASE WHEN (d_moy#18 = 4) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#134 AS apr_net#160, sum(CASE WHEN (d_moy#18 = 5) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#135 AS may_net#161, sum(CASE WHEN (d_moy#18 = 6) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#136 AS jun_net#162, sum(CASE WHEN (d_moy#18 = 7) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#137 AS jul_net#163, sum(CASE WHEN (d_moy#18 = 8) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#138 AS aug_net#164, sum(CASE WHEN (d_moy#18 = 9) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#139 AS sep_net#165, sum(CASE WHEN (d_moy#18 = 10) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#140 AS oct_net#166, sum(CASE WHEN (d_moy#18 = 11) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#141 AS nov_net#167, sum(CASE WHEN (d_moy#18 = 12) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#142 AS dec_net#168] + +(30) Scan parquet spark_catalog.default.catalog_sales +Output [7]: [cs_sold_time_sk#169, cs_ship_mode_sk#170, cs_warehouse_sk#171, cs_quantity#172, cs_sales_price#173, cs_net_paid_inc_tax#174, cs_sold_date_sk#175] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#175), dynamicpruningexpression(cs_sold_date_sk#175 IN dynamicpruning#176)] +PushedFilters: [IsNotNull(cs_warehouse_sk), IsNotNull(cs_sold_time_sk), IsNotNull(cs_ship_mode_sk)] +ReadSchema: struct + +(31) CometFilter +Input [7]: [cs_sold_time_sk#169, cs_ship_mode_sk#170, cs_warehouse_sk#171, cs_quantity#172, cs_sales_price#173, cs_net_paid_inc_tax#174, cs_sold_date_sk#175] +Condition : ((isnotnull(cs_warehouse_sk#171) AND isnotnull(cs_sold_time_sk#169)) AND isnotnull(cs_ship_mode_sk#170)) + +(32) ColumnarToRow [codegen id : 11] +Input [7]: [cs_sold_time_sk#169, cs_ship_mode_sk#170, cs_warehouse_sk#171, cs_quantity#172, cs_sales_price#173, cs_net_paid_inc_tax#174, cs_sold_date_sk#175] + +(33) ReusedExchange [Reuses operator id: 7] +Output [7]: [w_warehouse_sk#177, w_warehouse_name#178, w_warehouse_sq_ft#179, w_city#180, w_county#181, w_state#182, w_country#183] + +(34) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [cs_warehouse_sk#171] +Right keys [1]: [w_warehouse_sk#177] +Join type: Inner +Join condition: None + +(35) Project [codegen id : 11] +Output [12]: [cs_sold_time_sk#169, cs_ship_mode_sk#170, cs_quantity#172, cs_sales_price#173, cs_net_paid_inc_tax#174, cs_sold_date_sk#175, w_warehouse_name#178, w_warehouse_sq_ft#179, w_city#180, w_county#181, w_state#182, w_country#183] +Input [14]: [cs_sold_time_sk#169, cs_ship_mode_sk#170, cs_warehouse_sk#171, cs_quantity#172, cs_sales_price#173, cs_net_paid_inc_tax#174, cs_sold_date_sk#175, w_warehouse_sk#177, w_warehouse_name#178, w_warehouse_sq_ft#179, w_city#180, w_county#181, w_state#182, w_country#183] + +(36) ReusedExchange [Reuses operator id: 56] +Output [3]: [d_date_sk#184, d_year#185, d_moy#186] + +(37) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [cs_sold_date_sk#175] +Right keys [1]: [d_date_sk#184] +Join type: Inner +Join condition: None + +(38) Project [codegen id : 11] +Output [13]: [cs_sold_time_sk#169, cs_ship_mode_sk#170, cs_quantity#172, cs_sales_price#173, cs_net_paid_inc_tax#174, w_warehouse_name#178, w_warehouse_sq_ft#179, w_city#180, w_county#181, w_state#182, w_country#183, d_year#185, d_moy#186] +Input [15]: [cs_sold_time_sk#169, cs_ship_mode_sk#170, cs_quantity#172, cs_sales_price#173, cs_net_paid_inc_tax#174, cs_sold_date_sk#175, w_warehouse_name#178, w_warehouse_sq_ft#179, w_city#180, w_county#181, w_state#182, w_country#183, d_date_sk#184, d_year#185, d_moy#186] + +(39) ReusedExchange [Reuses operator id: 17] +Output [1]: [t_time_sk#187] + +(40) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [cs_sold_time_sk#169] +Right keys [1]: [t_time_sk#187] +Join type: Inner +Join condition: None + +(41) Project [codegen id : 11] +Output [12]: [cs_ship_mode_sk#170, cs_quantity#172, cs_sales_price#173, cs_net_paid_inc_tax#174, w_warehouse_name#178, w_warehouse_sq_ft#179, w_city#180, w_county#181, w_state#182, w_country#183, d_year#185, d_moy#186] +Input [14]: [cs_sold_time_sk#169, cs_ship_mode_sk#170, cs_quantity#172, cs_sales_price#173, cs_net_paid_inc_tax#174, w_warehouse_name#178, w_warehouse_sq_ft#179, w_city#180, w_county#181, w_state#182, w_country#183, d_year#185, d_moy#186, t_time_sk#187] + +(42) ReusedExchange [Reuses operator id: 24] +Output [1]: [sm_ship_mode_sk#188] + +(43) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [cs_ship_mode_sk#170] +Right keys [1]: [sm_ship_mode_sk#188] +Join type: Inner +Join condition: None + +(44) Project [codegen id : 11] +Output [11]: [cs_quantity#172, cs_sales_price#173, cs_net_paid_inc_tax#174, w_warehouse_name#178, w_warehouse_sq_ft#179, w_city#180, w_county#181, w_state#182, w_country#183, d_year#185, d_moy#186] +Input [13]: [cs_ship_mode_sk#170, cs_quantity#172, cs_sales_price#173, cs_net_paid_inc_tax#174, w_warehouse_name#178, w_warehouse_sq_ft#179, w_city#180, w_county#181, w_state#182, w_country#183, d_year#185, d_moy#186, sm_ship_mode_sk#188] + +(45) HashAggregate [codegen id : 11] +Input [11]: [cs_quantity#172, cs_sales_price#173, cs_net_paid_inc_tax#174, w_warehouse_name#178, w_warehouse_sq_ft#179, w_city#180, w_county#181, w_state#182, w_country#183, d_year#185, d_moy#186] +Keys [7]: [w_warehouse_name#178, w_warehouse_sq_ft#179, w_city#180, w_county#181, w_state#182, w_country#183, d_year#185] +Functions [24]: [partial_sum(CASE WHEN (d_moy#186 = 1) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 2) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 3) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 4) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 5) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 6) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 7) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 8) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 9) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 10) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 11) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 12) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 1) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 2) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 3) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 4) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 5) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 6) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 7) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 8) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 9) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 10) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 11) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 12) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)] +Aggregate Attributes [48]: [sum#189, isEmpty#190, sum#191, isEmpty#192, sum#193, isEmpty#194, sum#195, isEmpty#196, sum#197, isEmpty#198, sum#199, isEmpty#200, sum#201, isEmpty#202, sum#203, isEmpty#204, sum#205, isEmpty#206, sum#207, isEmpty#208, sum#209, isEmpty#210, sum#211, isEmpty#212, sum#213, isEmpty#214, sum#215, isEmpty#216, sum#217, isEmpty#218, sum#219, isEmpty#220, sum#221, isEmpty#222, sum#223, isEmpty#224, sum#225, isEmpty#226, sum#227, isEmpty#228, sum#229, isEmpty#230, sum#231, isEmpty#232, sum#233, isEmpty#234, sum#235, isEmpty#236] +Results [55]: [w_warehouse_name#178, w_warehouse_sq_ft#179, w_city#180, w_county#181, w_state#182, w_country#183, d_year#185, sum#237, isEmpty#238, sum#239, isEmpty#240, sum#241, isEmpty#242, sum#243, isEmpty#244, sum#245, isEmpty#246, sum#247, isEmpty#248, sum#249, isEmpty#250, sum#251, isEmpty#252, sum#253, isEmpty#254, sum#255, isEmpty#256, sum#257, isEmpty#258, sum#259, isEmpty#260, sum#261, isEmpty#262, sum#263, isEmpty#264, sum#265, isEmpty#266, sum#267, isEmpty#268, sum#269, isEmpty#270, sum#271, isEmpty#272, sum#273, isEmpty#274, sum#275, isEmpty#276, sum#277, isEmpty#278, sum#279, isEmpty#280, sum#281, isEmpty#282, sum#283, isEmpty#284] + +(46) Exchange +Input [55]: [w_warehouse_name#178, w_warehouse_sq_ft#179, w_city#180, w_county#181, w_state#182, w_country#183, d_year#185, sum#237, isEmpty#238, sum#239, isEmpty#240, sum#241, isEmpty#242, sum#243, isEmpty#244, sum#245, isEmpty#246, sum#247, isEmpty#248, sum#249, isEmpty#250, sum#251, isEmpty#252, sum#253, isEmpty#254, sum#255, isEmpty#256, sum#257, isEmpty#258, sum#259, isEmpty#260, sum#261, isEmpty#262, sum#263, isEmpty#264, sum#265, isEmpty#266, sum#267, isEmpty#268, sum#269, isEmpty#270, sum#271, isEmpty#272, sum#273, isEmpty#274, sum#275, isEmpty#276, sum#277, isEmpty#278, sum#279, isEmpty#280, sum#281, isEmpty#282, sum#283, isEmpty#284] +Arguments: hashpartitioning(w_warehouse_name#178, w_warehouse_sq_ft#179, w_city#180, w_county#181, w_state#182, w_country#183, d_year#185, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(47) HashAggregate [codegen id : 12] +Input [55]: [w_warehouse_name#178, w_warehouse_sq_ft#179, w_city#180, w_county#181, w_state#182, w_country#183, d_year#185, sum#237, isEmpty#238, sum#239, isEmpty#240, sum#241, isEmpty#242, sum#243, isEmpty#244, sum#245, isEmpty#246, sum#247, isEmpty#248, sum#249, isEmpty#250, sum#251, isEmpty#252, sum#253, isEmpty#254, sum#255, isEmpty#256, sum#257, isEmpty#258, sum#259, isEmpty#260, sum#261, isEmpty#262, sum#263, isEmpty#264, sum#265, isEmpty#266, sum#267, isEmpty#268, sum#269, isEmpty#270, sum#271, isEmpty#272, sum#273, isEmpty#274, sum#275, isEmpty#276, sum#277, isEmpty#278, sum#279, isEmpty#280, sum#281, isEmpty#282, sum#283, isEmpty#284] +Keys [7]: [w_warehouse_name#178, w_warehouse_sq_ft#179, w_city#180, w_county#181, w_state#182, w_country#183, d_year#185] +Functions [24]: [sum(CASE WHEN (d_moy#186 = 1) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 2) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 3) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 4) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 5) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 6) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 7) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 8) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 9) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 10) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 11) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 12) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 1) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 2) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 3) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 4) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 5) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 6) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 7) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 8) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 9) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 10) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 11) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 12) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)] +Aggregate Attributes [24]: [sum(CASE WHEN (d_moy#186 = 1) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#285, sum(CASE WHEN (d_moy#186 = 2) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#286, sum(CASE WHEN (d_moy#186 = 3) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#287, sum(CASE WHEN (d_moy#186 = 4) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#288, sum(CASE WHEN (d_moy#186 = 5) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#289, sum(CASE WHEN (d_moy#186 = 6) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#290, sum(CASE WHEN (d_moy#186 = 7) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#291, sum(CASE WHEN (d_moy#186 = 8) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#292, sum(CASE WHEN (d_moy#186 = 9) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#293, sum(CASE WHEN (d_moy#186 = 10) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#294, sum(CASE WHEN (d_moy#186 = 11) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#295, sum(CASE WHEN (d_moy#186 = 12) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#296, sum(CASE WHEN (d_moy#186 = 1) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#297, sum(CASE WHEN (d_moy#186 = 2) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#298, sum(CASE WHEN (d_moy#186 = 3) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#299, sum(CASE WHEN (d_moy#186 = 4) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#300, sum(CASE WHEN (d_moy#186 = 5) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#301, sum(CASE WHEN (d_moy#186 = 6) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#302, sum(CASE WHEN (d_moy#186 = 7) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#303, sum(CASE WHEN (d_moy#186 = 8) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#304, sum(CASE WHEN (d_moy#186 = 9) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#305, sum(CASE WHEN (d_moy#186 = 10) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#306, sum(CASE WHEN (d_moy#186 = 11) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#307, sum(CASE WHEN (d_moy#186 = 12) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#308] +Results [32]: [w_warehouse_name#178, w_warehouse_sq_ft#179, w_city#180, w_county#181, w_state#182, w_country#183, DHL,BARIAN AS ship_carriers#309, d_year#185 AS year#310, sum(CASE WHEN (d_moy#186 = 1) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#285 AS jan_sales#311, sum(CASE WHEN (d_moy#186 = 2) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#286 AS feb_sales#312, sum(CASE WHEN (d_moy#186 = 3) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#287 AS mar_sales#313, sum(CASE WHEN (d_moy#186 = 4) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#288 AS apr_sales#314, sum(CASE WHEN (d_moy#186 = 5) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#289 AS may_sales#315, sum(CASE WHEN (d_moy#186 = 6) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#290 AS jun_sales#316, sum(CASE WHEN (d_moy#186 = 7) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#291 AS jul_sales#317, sum(CASE WHEN (d_moy#186 = 8) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#292 AS aug_sales#318, sum(CASE WHEN (d_moy#186 = 9) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#293 AS sep_sales#319, sum(CASE WHEN (d_moy#186 = 10) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#294 AS oct_sales#320, sum(CASE WHEN (d_moy#186 = 11) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#295 AS nov_sales#321, sum(CASE WHEN (d_moy#186 = 12) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#296 AS dec_sales#322, sum(CASE WHEN (d_moy#186 = 1) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#297 AS jan_net#323, sum(CASE WHEN (d_moy#186 = 2) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#298 AS feb_net#324, sum(CASE WHEN (d_moy#186 = 3) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#299 AS mar_net#325, sum(CASE WHEN (d_moy#186 = 4) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#300 AS apr_net#326, sum(CASE WHEN (d_moy#186 = 5) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#301 AS may_net#327, sum(CASE WHEN (d_moy#186 = 6) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#302 AS jun_net#328, sum(CASE WHEN (d_moy#186 = 7) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#303 AS jul_net#329, sum(CASE WHEN (d_moy#186 = 8) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#304 AS aug_net#330, sum(CASE WHEN (d_moy#186 = 9) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#305 AS sep_net#331, sum(CASE WHEN (d_moy#186 = 10) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#306 AS oct_net#332, sum(CASE WHEN (d_moy#186 = 11) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#307 AS nov_net#333, sum(CASE WHEN (d_moy#186 = 12) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#308 AS dec_net#334] + +(48) Union + +(49) HashAggregate [codegen id : 13] +Input [32]: [w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, ship_carriers#143, year#144, jan_sales#145, feb_sales#146, mar_sales#147, apr_sales#148, may_sales#149, jun_sales#150, jul_sales#151, aug_sales#152, sep_sales#153, oct_sales#154, nov_sales#155, dec_sales#156, jan_net#157, feb_net#158, mar_net#159, apr_net#160, may_net#161, jun_net#162, jul_net#163, aug_net#164, sep_net#165, oct_net#166, nov_net#167, dec_net#168] +Keys [8]: [w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, ship_carriers#143, year#144] +Functions [36]: [partial_sum(jan_sales#145), partial_sum(feb_sales#146), partial_sum(mar_sales#147), partial_sum(apr_sales#148), partial_sum(may_sales#149), partial_sum(jun_sales#150), partial_sum(jul_sales#151), partial_sum(aug_sales#152), partial_sum(sep_sales#153), partial_sum(oct_sales#154), partial_sum(nov_sales#155), partial_sum(dec_sales#156), partial_sum((jan_sales#145 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), partial_sum((feb_sales#146 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), partial_sum((mar_sales#147 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), partial_sum((apr_sales#148 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), partial_sum((may_sales#149 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), partial_sum((jun_sales#150 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), partial_sum((jul_sales#151 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), partial_sum((aug_sales#152 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), partial_sum((sep_sales#153 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), partial_sum((oct_sales#154 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), partial_sum((nov_sales#155 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), partial_sum((dec_sales#156 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), partial_sum(jan_net#157), partial_sum(feb_net#158), partial_sum(mar_net#159), partial_sum(apr_net#160), partial_sum(may_net#161), partial_sum(jun_net#162), partial_sum(jul_net#163), partial_sum(aug_net#164), partial_sum(sep_net#165), partial_sum(oct_net#166), partial_sum(nov_net#167), partial_sum(dec_net#168)] +Aggregate Attributes [72]: [sum#335, isEmpty#336, sum#337, isEmpty#338, sum#339, isEmpty#340, sum#341, isEmpty#342, sum#343, isEmpty#344, sum#345, isEmpty#346, sum#347, isEmpty#348, sum#349, isEmpty#350, sum#351, isEmpty#352, sum#353, isEmpty#354, sum#355, isEmpty#356, sum#357, isEmpty#358, sum#359, isEmpty#360, sum#361, isEmpty#362, sum#363, isEmpty#364, sum#365, isEmpty#366, sum#367, isEmpty#368, sum#369, isEmpty#370, sum#371, isEmpty#372, sum#373, isEmpty#374, sum#375, isEmpty#376, sum#377, isEmpty#378, sum#379, isEmpty#380, sum#381, isEmpty#382, sum#383, isEmpty#384, sum#385, isEmpty#386, sum#387, isEmpty#388, sum#389, isEmpty#390, sum#391, isEmpty#392, sum#393, isEmpty#394, sum#395, isEmpty#396, sum#397, isEmpty#398, sum#399, isEmpty#400, sum#401, isEmpty#402, sum#403, isEmpty#404, sum#405, isEmpty#406] +Results [80]: [w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, ship_carriers#143, year#144, sum#407, isEmpty#408, sum#409, isEmpty#410, sum#411, isEmpty#412, sum#413, isEmpty#414, sum#415, isEmpty#416, sum#417, isEmpty#418, sum#419, isEmpty#420, sum#421, isEmpty#422, sum#423, isEmpty#424, sum#425, isEmpty#426, sum#427, isEmpty#428, sum#429, isEmpty#430, sum#431, isEmpty#432, sum#433, isEmpty#434, sum#435, isEmpty#436, sum#437, isEmpty#438, sum#439, isEmpty#440, sum#441, isEmpty#442, sum#443, isEmpty#444, sum#445, isEmpty#446, sum#447, isEmpty#448, sum#449, isEmpty#450, sum#451, isEmpty#452, sum#453, isEmpty#454, sum#455, isEmpty#456, sum#457, isEmpty#458, sum#459, isEmpty#460, sum#461, isEmpty#462, sum#463, isEmpty#464, sum#465, isEmpty#466, sum#467, isEmpty#468, sum#469, isEmpty#470, sum#471, isEmpty#472, sum#473, isEmpty#474, sum#475, isEmpty#476, sum#477, isEmpty#478] + +(50) Exchange +Input [80]: [w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, ship_carriers#143, year#144, sum#407, isEmpty#408, sum#409, isEmpty#410, sum#411, isEmpty#412, sum#413, isEmpty#414, sum#415, isEmpty#416, sum#417, isEmpty#418, sum#419, isEmpty#420, sum#421, isEmpty#422, sum#423, isEmpty#424, sum#425, isEmpty#426, sum#427, isEmpty#428, sum#429, isEmpty#430, sum#431, isEmpty#432, sum#433, isEmpty#434, sum#435, isEmpty#436, sum#437, isEmpty#438, sum#439, isEmpty#440, sum#441, isEmpty#442, sum#443, isEmpty#444, sum#445, isEmpty#446, sum#447, isEmpty#448, sum#449, isEmpty#450, sum#451, isEmpty#452, sum#453, isEmpty#454, sum#455, isEmpty#456, sum#457, isEmpty#458, sum#459, isEmpty#460, sum#461, isEmpty#462, sum#463, isEmpty#464, sum#465, isEmpty#466, sum#467, isEmpty#468, sum#469, isEmpty#470, sum#471, isEmpty#472, sum#473, isEmpty#474, sum#475, isEmpty#476, sum#477, isEmpty#478] +Arguments: hashpartitioning(w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, ship_carriers#143, year#144, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(51) HashAggregate [codegen id : 14] +Input [80]: [w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, ship_carriers#143, year#144, sum#407, isEmpty#408, sum#409, isEmpty#410, sum#411, isEmpty#412, sum#413, isEmpty#414, sum#415, isEmpty#416, sum#417, isEmpty#418, sum#419, isEmpty#420, sum#421, isEmpty#422, sum#423, isEmpty#424, sum#425, isEmpty#426, sum#427, isEmpty#428, sum#429, isEmpty#430, sum#431, isEmpty#432, sum#433, isEmpty#434, sum#435, isEmpty#436, sum#437, isEmpty#438, sum#439, isEmpty#440, sum#441, isEmpty#442, sum#443, isEmpty#444, sum#445, isEmpty#446, sum#447, isEmpty#448, sum#449, isEmpty#450, sum#451, isEmpty#452, sum#453, isEmpty#454, sum#455, isEmpty#456, sum#457, isEmpty#458, sum#459, isEmpty#460, sum#461, isEmpty#462, sum#463, isEmpty#464, sum#465, isEmpty#466, sum#467, isEmpty#468, sum#469, isEmpty#470, sum#471, isEmpty#472, sum#473, isEmpty#474, sum#475, isEmpty#476, sum#477, isEmpty#478] +Keys [8]: [w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, ship_carriers#143, year#144] +Functions [36]: [sum(jan_sales#145), sum(feb_sales#146), sum(mar_sales#147), sum(apr_sales#148), sum(may_sales#149), sum(jun_sales#150), sum(jul_sales#151), sum(aug_sales#152), sum(sep_sales#153), sum(oct_sales#154), sum(nov_sales#155), sum(dec_sales#156), sum((jan_sales#145 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), sum((feb_sales#146 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), sum((mar_sales#147 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), sum((apr_sales#148 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), sum((may_sales#149 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), sum((jun_sales#150 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), sum((jul_sales#151 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), sum((aug_sales#152 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), sum((sep_sales#153 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), sum((oct_sales#154 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), sum((nov_sales#155 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), sum((dec_sales#156 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), sum(jan_net#157), sum(feb_net#158), sum(mar_net#159), sum(apr_net#160), sum(may_net#161), sum(jun_net#162), sum(jul_net#163), sum(aug_net#164), sum(sep_net#165), sum(oct_net#166), sum(nov_net#167), sum(dec_net#168)] +Aggregate Attributes [36]: [sum(jan_sales#145)#479, sum(feb_sales#146)#480, sum(mar_sales#147)#481, sum(apr_sales#148)#482, sum(may_sales#149)#483, sum(jun_sales#150)#484, sum(jul_sales#151)#485, sum(aug_sales#152)#486, sum(sep_sales#153)#487, sum(oct_sales#154)#488, sum(nov_sales#155)#489, sum(dec_sales#156)#490, sum((jan_sales#145 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#491, sum((feb_sales#146 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#492, sum((mar_sales#147 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#493, sum((apr_sales#148 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#494, sum((may_sales#149 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#495, sum((jun_sales#150 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#496, sum((jul_sales#151 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#497, sum((aug_sales#152 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#498, sum((sep_sales#153 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#499, sum((oct_sales#154 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#500, sum((nov_sales#155 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#501, sum((dec_sales#156 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#502, sum(jan_net#157)#503, sum(feb_net#158)#504, sum(mar_net#159)#505, sum(apr_net#160)#506, sum(may_net#161)#507, sum(jun_net#162)#508, sum(jul_net#163)#509, sum(aug_net#164)#510, sum(sep_net#165)#511, sum(oct_net#166)#512, sum(nov_net#167)#513, sum(dec_net#168)#514] +Results [44]: [w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, ship_carriers#143, year#144, sum(jan_sales#145)#479 AS jan_sales#515, sum(feb_sales#146)#480 AS feb_sales#516, sum(mar_sales#147)#481 AS mar_sales#517, sum(apr_sales#148)#482 AS apr_sales#518, sum(may_sales#149)#483 AS may_sales#519, sum(jun_sales#150)#484 AS jun_sales#520, sum(jul_sales#151)#485 AS jul_sales#521, sum(aug_sales#152)#486 AS aug_sales#522, sum(sep_sales#153)#487 AS sep_sales#523, sum(oct_sales#154)#488 AS oct_sales#524, sum(nov_sales#155)#489 AS nov_sales#525, sum(dec_sales#156)#490 AS dec_sales#526, sum((jan_sales#145 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#491 AS jan_sales_per_sq_foot#527, sum((feb_sales#146 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#492 AS feb_sales_per_sq_foot#528, sum((mar_sales#147 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#493 AS mar_sales_per_sq_foot#529, sum((apr_sales#148 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#494 AS apr_sales_per_sq_foot#530, sum((may_sales#149 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#495 AS may_sales_per_sq_foot#531, sum((jun_sales#150 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#496 AS jun_sales_per_sq_foot#532, sum((jul_sales#151 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#497 AS jul_sales_per_sq_foot#533, sum((aug_sales#152 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#498 AS aug_sales_per_sq_foot#534, sum((sep_sales#153 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#499 AS sep_sales_per_sq_foot#535, sum((oct_sales#154 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#500 AS oct_sales_per_sq_foot#536, sum((nov_sales#155 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#501 AS nov_sales_per_sq_foot#537, sum((dec_sales#156 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#502 AS dec_sales_per_sq_foot#538, sum(jan_net#157)#503 AS jan_net#539, sum(feb_net#158)#504 AS feb_net#540, sum(mar_net#159)#505 AS mar_net#541, sum(apr_net#160)#506 AS apr_net#542, sum(may_net#161)#507 AS may_net#543, sum(jun_net#162)#508 AS jun_net#544, sum(jul_net#163)#509 AS jul_net#545, sum(aug_net#164)#510 AS aug_net#546, sum(sep_net#165)#511 AS sep_net#547, sum(oct_net#166)#512 AS oct_net#548, sum(nov_net#167)#513 AS nov_net#549, sum(dec_net#168)#514 AS dec_net#550] + +(52) TakeOrderedAndProject +Input [44]: [w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, ship_carriers#143, year#144, jan_sales#515, feb_sales#516, mar_sales#517, apr_sales#518, may_sales#519, jun_sales#520, jul_sales#521, aug_sales#522, sep_sales#523, oct_sales#524, nov_sales#525, dec_sales#526, jan_sales_per_sq_foot#527, feb_sales_per_sq_foot#528, mar_sales_per_sq_foot#529, apr_sales_per_sq_foot#530, may_sales_per_sq_foot#531, jun_sales_per_sq_foot#532, jul_sales_per_sq_foot#533, aug_sales_per_sq_foot#534, sep_sales_per_sq_foot#535, oct_sales_per_sq_foot#536, nov_sales_per_sq_foot#537, dec_sales_per_sq_foot#538, jan_net#539, feb_net#540, mar_net#541, apr_net#542, may_net#543, jun_net#544, jul_net#545, aug_net#546, sep_net#547, oct_net#548, nov_net#549, dec_net#550] +Arguments: 100, [w_warehouse_name#10 ASC NULLS FIRST], [w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, ship_carriers#143, year#144, jan_sales#515, feb_sales#516, mar_sales#517, apr_sales#518, may_sales#519, jun_sales#520, jul_sales#521, aug_sales#522, sep_sales#523, oct_sales#524, nov_sales#525, dec_sales#526, jan_sales_per_sq_foot#527, feb_sales_per_sq_foot#528, mar_sales_per_sq_foot#529, apr_sales_per_sq_foot#530, may_sales_per_sq_foot#531, jun_sales_per_sq_foot#532, jul_sales_per_sq_foot#533, aug_sales_per_sq_foot#534, sep_sales_per_sq_foot#535, oct_sales_per_sq_foot#536, nov_sales_per_sq_foot#537, dec_sales_per_sq_foot#538, jan_net#539, feb_net#540, mar_net#541, apr_net#542, may_net#543, jun_net#544, jul_net#545, aug_net#546, sep_net#547, oct_net#548, nov_net#549, dec_net#550] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (56) ++- * ColumnarToRow (55) + +- CometFilter (54) + +- CometScan parquet spark_catalog.default.date_dim (53) + + +(53) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#16, d_year#17, d_moy#18] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(54) CometFilter +Input [3]: [d_date_sk#16, d_year#17, d_moy#18] +Condition : ((isnotnull(d_year#17) AND (d_year#17 = 2001)) AND isnotnull(d_date_sk#16)) + +(55) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#16, d_year#17, d_moy#18] + +(56) BroadcastExchange +Input [3]: [d_date_sk#16, d_year#17, d_moy#18] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=7] + +Subquery:2 Hosting operator id = 30 Hosting Expression = cs_sold_date_sk#175 IN dynamicpruning#8 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q66/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q66/simplified.txt new file mode 100644 index 0000000000..8ed74582f0 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q66/simplified.txt @@ -0,0 +1,86 @@ +TakeOrderedAndProject [w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country,ship_carriers,year,jan_sales,feb_sales,mar_sales,apr_sales,may_sales,jun_sales,jul_sales,aug_sales,sep_sales,oct_sales,nov_sales,dec_sales,jan_sales_per_sq_foot,feb_sales_per_sq_foot,mar_sales_per_sq_foot,apr_sales_per_sq_foot,may_sales_per_sq_foot,jun_sales_per_sq_foot,jul_sales_per_sq_foot,aug_sales_per_sq_foot,sep_sales_per_sq_foot,oct_sales_per_sq_foot,nov_sales_per_sq_foot,dec_sales_per_sq_foot,jan_net,feb_net,mar_net,apr_net,may_net,jun_net,jul_net,aug_net,sep_net,oct_net,nov_net,dec_net] + WholeStageCodegen (14) + HashAggregate [w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country,ship_carriers,year,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(jan_sales),sum(feb_sales),sum(mar_sales),sum(apr_sales),sum(may_sales),sum(jun_sales),sum(jul_sales),sum(aug_sales),sum(sep_sales),sum(oct_sales),sum(nov_sales),sum(dec_sales),sum((jan_sales / cast(w_warehouse_sq_ft as decimal(10,0)))),sum((feb_sales / cast(w_warehouse_sq_ft as decimal(10,0)))),sum((mar_sales / cast(w_warehouse_sq_ft as decimal(10,0)))),sum((apr_sales / cast(w_warehouse_sq_ft as decimal(10,0)))),sum((may_sales / cast(w_warehouse_sq_ft as decimal(10,0)))),sum((jun_sales / cast(w_warehouse_sq_ft as decimal(10,0)))),sum((jul_sales / cast(w_warehouse_sq_ft as decimal(10,0)))),sum((aug_sales / cast(w_warehouse_sq_ft as decimal(10,0)))),sum((sep_sales / cast(w_warehouse_sq_ft as decimal(10,0)))),sum((oct_sales / cast(w_warehouse_sq_ft as decimal(10,0)))),sum((nov_sales / cast(w_warehouse_sq_ft as decimal(10,0)))),sum((dec_sales / cast(w_warehouse_sq_ft as decimal(10,0)))),sum(jan_net),sum(feb_net),sum(mar_net),sum(apr_net),sum(may_net),sum(jun_net),sum(jul_net),sum(aug_net),sum(sep_net),sum(oct_net),sum(nov_net),sum(dec_net),jan_sales,feb_sales,mar_sales,apr_sales,may_sales,jun_sales,jul_sales,aug_sales,sep_sales,oct_sales,nov_sales,dec_sales,jan_sales_per_sq_foot,feb_sales_per_sq_foot,mar_sales_per_sq_foot,apr_sales_per_sq_foot,may_sales_per_sq_foot,jun_sales_per_sq_foot,jul_sales_per_sq_foot,aug_sales_per_sq_foot,sep_sales_per_sq_foot,oct_sales_per_sq_foot,nov_sales_per_sq_foot,dec_sales_per_sq_foot,jan_net,feb_net,mar_net,apr_net,may_net,jun_net,jul_net,aug_net,sep_net,oct_net,nov_net,dec_net,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country,ship_carriers,year] #1 + WholeStageCodegen (13) + HashAggregate [w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country,ship_carriers,year,jan_sales,feb_sales,mar_sales,apr_sales,may_sales,jun_sales,jul_sales,aug_sales,sep_sales,oct_sales,nov_sales,dec_sales,jan_net,feb_net,mar_net,apr_net,may_net,jun_net,jul_net,aug_net,sep_net,oct_net,nov_net,dec_net] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Union + WholeStageCodegen (6) + HashAggregate [w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country,d_year,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(CASE WHEN (d_moy = 1) THEN (ws_ext_sales_price * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 2) THEN (ws_ext_sales_price * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 3) THEN (ws_ext_sales_price * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 4) THEN (ws_ext_sales_price * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 5) THEN (ws_ext_sales_price * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 6) THEN (ws_ext_sales_price * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 7) THEN (ws_ext_sales_price * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 8) THEN (ws_ext_sales_price * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 9) THEN (ws_ext_sales_price * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 10) THEN (ws_ext_sales_price * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 11) THEN (ws_ext_sales_price * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 12) THEN (ws_ext_sales_price * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 1) THEN (ws_net_paid * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 2) THEN (ws_net_paid * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 3) THEN (ws_net_paid * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 4) THEN (ws_net_paid * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 5) THEN (ws_net_paid * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 6) THEN (ws_net_paid * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 7) THEN (ws_net_paid * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 8) THEN (ws_net_paid * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 9) THEN (ws_net_paid * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 10) THEN (ws_net_paid * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 11) THEN (ws_net_paid * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 12) THEN (ws_net_paid * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),ship_carriers,year,jan_sales,feb_sales,mar_sales,apr_sales,may_sales,jun_sales,jul_sales,aug_sales,sep_sales,oct_sales,nov_sales,dec_sales,jan_net,feb_net,mar_net,apr_net,may_net,jun_net,jul_net,aug_net,sep_net,oct_net,nov_net,dec_net,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country,d_year] #2 + WholeStageCodegen (5) + HashAggregate [w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country,d_year,d_moy,ws_ext_sales_price,ws_quantity,ws_net_paid] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + Project [ws_quantity,ws_ext_sales_price,ws_net_paid,w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country,d_year,d_moy] + BroadcastHashJoin [ws_ship_mode_sk,sm_ship_mode_sk] + Project [ws_ship_mode_sk,ws_quantity,ws_ext_sales_price,ws_net_paid,w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country,d_year,d_moy] + BroadcastHashJoin [ws_sold_time_sk,t_time_sk] + Project [ws_sold_time_sk,ws_ship_mode_sk,ws_quantity,ws_ext_sales_price,ws_net_paid,w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country,d_year,d_moy] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_sold_time_sk,ws_ship_mode_sk,ws_quantity,ws_ext_sales_price,ws_net_paid,ws_sold_date_sk,w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country] + BroadcastHashJoin [ws_warehouse_sk,w_warehouse_sk] + ColumnarToRow + InputAdapter + CometFilter [ws_warehouse_sk,ws_sold_time_sk,ws_ship_mode_sk] + CometScan parquet spark_catalog.default.web_sales [ws_sold_time_sk,ws_ship_mode_sk,ws_warehouse_sk,ws_quantity,ws_ext_sales_price,ws_net_paid,ws_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [w_warehouse_sk] + CometScan parquet spark_catalog.default.warehouse [w_warehouse_sk,w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country] + InputAdapter + ReusedExchange [d_date_sk,d_year,d_moy] #3 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometProject [t_time_sk] + CometFilter [t_time,t_time_sk] + CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_time] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (4) + ColumnarToRow + InputAdapter + CometProject [sm_ship_mode_sk] + CometFilter [sm_carrier,sm_ship_mode_sk] + CometScan parquet spark_catalog.default.ship_mode [sm_ship_mode_sk,sm_carrier] + WholeStageCodegen (12) + HashAggregate [w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country,d_year,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(CASE WHEN (d_moy = 1) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 2) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 3) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 4) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 5) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 6) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 7) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 8) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 9) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 10) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 11) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 12) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 1) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 2) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 3) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 4) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 5) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 6) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 7) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 8) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 9) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 10) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 11) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 12) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),ship_carriers,year,jan_sales,feb_sales,mar_sales,apr_sales,may_sales,jun_sales,jul_sales,aug_sales,sep_sales,oct_sales,nov_sales,dec_sales,jan_net,feb_net,mar_net,apr_net,may_net,jun_net,jul_net,aug_net,sep_net,oct_net,nov_net,dec_net,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country,d_year] #7 + WholeStageCodegen (11) + HashAggregate [w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country,d_year,d_moy,cs_sales_price,cs_quantity,cs_net_paid_inc_tax] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + Project [cs_quantity,cs_sales_price,cs_net_paid_inc_tax,w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country,d_year,d_moy] + BroadcastHashJoin [cs_ship_mode_sk,sm_ship_mode_sk] + Project [cs_ship_mode_sk,cs_quantity,cs_sales_price,cs_net_paid_inc_tax,w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country,d_year,d_moy] + BroadcastHashJoin [cs_sold_time_sk,t_time_sk] + Project [cs_sold_time_sk,cs_ship_mode_sk,cs_quantity,cs_sales_price,cs_net_paid_inc_tax,w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country,d_year,d_moy] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_sold_time_sk,cs_ship_mode_sk,cs_quantity,cs_sales_price,cs_net_paid_inc_tax,cs_sold_date_sk,w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country] + BroadcastHashJoin [cs_warehouse_sk,w_warehouse_sk] + ColumnarToRow + InputAdapter + CometFilter [cs_warehouse_sk,cs_sold_time_sk,cs_ship_mode_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_sold_time_sk,cs_ship_mode_sk,cs_warehouse_sk,cs_quantity,cs_sales_price,cs_net_paid_inc_tax,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [w_warehouse_sk,w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country] #4 + InputAdapter + ReusedExchange [d_date_sk,d_year,d_moy] #3 + InputAdapter + ReusedExchange [t_time_sk] #5 + InputAdapter + ReusedExchange [sm_ship_mode_sk] #6 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q67/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q67/explain.txt new file mode 100644 index 0000000000..d1a6a4f471 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q67/explain.txt @@ -0,0 +1,204 @@ +== Physical Plan == +TakeOrderedAndProject (30) ++- * Filter (29) + +- Window (28) + +- WindowGroupLimit (27) + +- * Sort (26) + +- Exchange (25) + +- WindowGroupLimit (24) + +- * Sort (23) + +- * HashAggregate (22) + +- Exchange (21) + +- * HashAggregate (20) + +- * Expand (19) + +- * Project (18) + +- * BroadcastHashJoin Inner BuildRight (17) + :- * Project (12) + : +- * BroadcastHashJoin Inner BuildRight (11) + : :- * Project (6) + : : +- * BroadcastHashJoin Inner BuildRight (5) + : : :- * ColumnarToRow (3) + : : : +- CometFilter (2) + : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : +- ReusedExchange (4) + : +- BroadcastExchange (10) + : +- * ColumnarToRow (9) + : +- CometFilter (8) + : +- CometScan parquet spark_catalog.default.store (7) + +- BroadcastExchange (16) + +- * ColumnarToRow (15) + +- CometFilter (14) + +- CometScan parquet spark_catalog.default.item (13) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, ss_sold_date_sk#5] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#5), dynamicpruningexpression(ss_sold_date_sk#5 IN dynamicpruning#6)] +PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [5]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, ss_sold_date_sk#5] +Condition : (isnotnull(ss_store_sk#2) AND isnotnull(ss_item_sk#1)) + +(3) ColumnarToRow [codegen id : 4] +Input [5]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, ss_sold_date_sk#5] + +(4) ReusedExchange [Reuses operator id: 35] +Output [4]: [d_date_sk#7, d_year#8, d_moy#9, d_qoy#10] + +(5) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_date_sk#5] +Right keys [1]: [d_date_sk#7] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 4] +Output [7]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, d_year#8, d_moy#9, d_qoy#10] +Input [9]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, ss_sold_date_sk#5, d_date_sk#7, d_year#8, d_moy#9, d_qoy#10] + +(7) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#11, s_store_id#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(8) CometFilter +Input [2]: [s_store_sk#11, s_store_id#12] +Condition : isnotnull(s_store_sk#11) + +(9) ColumnarToRow [codegen id : 2] +Input [2]: [s_store_sk#11, s_store_id#12] + +(10) BroadcastExchange +Input [2]: [s_store_sk#11, s_store_id#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(11) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_store_sk#2] +Right keys [1]: [s_store_sk#11] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 4] +Output [7]: [ss_item_sk#1, ss_quantity#3, ss_sales_price#4, d_year#8, d_moy#9, d_qoy#10, s_store_id#12] +Input [9]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, d_year#8, d_moy#9, d_qoy#10, s_store_sk#11, s_store_id#12] + +(13) Scan parquet spark_catalog.default.item +Output [5]: [i_item_sk#13, i_brand#14, i_class#15, i_category#16, i_product_name#17] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(14) CometFilter +Input [5]: [i_item_sk#13, i_brand#14, i_class#15, i_category#16, i_product_name#17] +Condition : isnotnull(i_item_sk#13) + +(15) ColumnarToRow [codegen id : 3] +Input [5]: [i_item_sk#13, i_brand#14, i_class#15, i_category#16, i_product_name#17] + +(16) BroadcastExchange +Input [5]: [i_item_sk#13, i_brand#14, i_class#15, i_category#16, i_product_name#17] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(17) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#13] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 4] +Output [10]: [ss_quantity#3, ss_sales_price#4, i_category#16, i_class#15, i_brand#14, i_product_name#17, d_year#8, d_qoy#10, d_moy#9, s_store_id#12] +Input [12]: [ss_item_sk#1, ss_quantity#3, ss_sales_price#4, d_year#8, d_moy#9, d_qoy#10, s_store_id#12, i_item_sk#13, i_brand#14, i_class#15, i_category#16, i_product_name#17] + +(19) Expand [codegen id : 4] +Input [10]: [ss_quantity#3, ss_sales_price#4, i_category#16, i_class#15, i_brand#14, i_product_name#17, d_year#8, d_qoy#10, d_moy#9, s_store_id#12] +Arguments: [[ss_quantity#3, ss_sales_price#4, i_category#16, i_class#15, i_brand#14, i_product_name#17, d_year#8, d_qoy#10, d_moy#9, s_store_id#12, 0], [ss_quantity#3, ss_sales_price#4, i_category#16, i_class#15, i_brand#14, i_product_name#17, d_year#8, d_qoy#10, d_moy#9, null, 1], [ss_quantity#3, ss_sales_price#4, i_category#16, i_class#15, i_brand#14, i_product_name#17, d_year#8, d_qoy#10, null, null, 3], [ss_quantity#3, ss_sales_price#4, i_category#16, i_class#15, i_brand#14, i_product_name#17, d_year#8, null, null, null, 7], [ss_quantity#3, ss_sales_price#4, i_category#16, i_class#15, i_brand#14, i_product_name#17, null, null, null, null, 15], [ss_quantity#3, ss_sales_price#4, i_category#16, i_class#15, i_brand#14, null, null, null, null, null, 31], [ss_quantity#3, ss_sales_price#4, i_category#16, i_class#15, null, null, null, null, null, null, 63], [ss_quantity#3, ss_sales_price#4, i_category#16, null, null, null, null, null, null, null, 127], [ss_quantity#3, ss_sales_price#4, null, null, null, null, null, null, null, null, 255]], [ss_quantity#3, ss_sales_price#4, i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, spark_grouping_id#26] + +(20) HashAggregate [codegen id : 4] +Input [11]: [ss_quantity#3, ss_sales_price#4, i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, spark_grouping_id#26] +Keys [9]: [i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, spark_grouping_id#26] +Functions [1]: [partial_sum(coalesce((ss_sales_price#4 * cast(ss_quantity#3 as decimal(10,0))), 0.00))] +Aggregate Attributes [2]: [sum#27, isEmpty#28] +Results [11]: [i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, spark_grouping_id#26, sum#29, isEmpty#30] + +(21) Exchange +Input [11]: [i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, spark_grouping_id#26, sum#29, isEmpty#30] +Arguments: hashpartitioning(i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, spark_grouping_id#26, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(22) HashAggregate [codegen id : 5] +Input [11]: [i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, spark_grouping_id#26, sum#29, isEmpty#30] +Keys [9]: [i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, spark_grouping_id#26] +Functions [1]: [sum(coalesce((ss_sales_price#4 * cast(ss_quantity#3 as decimal(10,0))), 0.00))] +Aggregate Attributes [1]: [sum(coalesce((ss_sales_price#4 * cast(ss_quantity#3 as decimal(10,0))), 0.00))#31] +Results [9]: [i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, sum(coalesce((ss_sales_price#4 * cast(ss_quantity#3 as decimal(10,0))), 0.00))#31 AS sumsales#32] + +(23) Sort [codegen id : 5] +Input [9]: [i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, sumsales#32] +Arguments: [i_category#18 ASC NULLS FIRST, sumsales#32 DESC NULLS LAST], false, 0 + +(24) WindowGroupLimit +Input [9]: [i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, sumsales#32] +Arguments: [i_category#18], [sumsales#32 DESC NULLS LAST], rank(sumsales#32), 100, Partial + +(25) Exchange +Input [9]: [i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, sumsales#32] +Arguments: hashpartitioning(i_category#18, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(26) Sort [codegen id : 6] +Input [9]: [i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, sumsales#32] +Arguments: [i_category#18 ASC NULLS FIRST, sumsales#32 DESC NULLS LAST], false, 0 + +(27) WindowGroupLimit +Input [9]: [i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, sumsales#32] +Arguments: [i_category#18], [sumsales#32 DESC NULLS LAST], rank(sumsales#32), 100, Final + +(28) Window +Input [9]: [i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, sumsales#32] +Arguments: [rank(sumsales#32) windowspecdefinition(i_category#18, sumsales#32 DESC NULLS LAST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rk#33], [i_category#18], [sumsales#32 DESC NULLS LAST] + +(29) Filter [codegen id : 7] +Input [10]: [i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, sumsales#32, rk#33] +Condition : (rk#33 <= 100) + +(30) TakeOrderedAndProject +Input [10]: [i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, sumsales#32, rk#33] +Arguments: 100, [i_category#18 ASC NULLS FIRST, i_class#19 ASC NULLS FIRST, i_brand#20 ASC NULLS FIRST, i_product_name#21 ASC NULLS FIRST, d_year#22 ASC NULLS FIRST, d_qoy#23 ASC NULLS FIRST, d_moy#24 ASC NULLS FIRST, s_store_id#25 ASC NULLS FIRST, sumsales#32 ASC NULLS FIRST, rk#33 ASC NULLS FIRST], [i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, sumsales#32, rk#33] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6 +BroadcastExchange (35) ++- * ColumnarToRow (34) + +- CometProject (33) + +- CometFilter (32) + +- CometScan parquet spark_catalog.default.date_dim (31) + + +(31) Scan parquet spark_catalog.default.date_dim +Output [5]: [d_date_sk#7, d_month_seq#34, d_year#8, d_moy#9, d_qoy#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)] +ReadSchema: struct + +(32) CometFilter +Input [5]: [d_date_sk#7, d_month_seq#34, d_year#8, d_moy#9, d_qoy#10] +Condition : (((isnotnull(d_month_seq#34) AND (d_month_seq#34 >= 1200)) AND (d_month_seq#34 <= 1211)) AND isnotnull(d_date_sk#7)) + +(33) CometProject +Input [5]: [d_date_sk#7, d_month_seq#34, d_year#8, d_moy#9, d_qoy#10] +Arguments: [d_date_sk#7, d_year#8, d_moy#9, d_qoy#10], [d_date_sk#7, d_year#8, d_moy#9, d_qoy#10] + +(34) ColumnarToRow [codegen id : 1] +Input [4]: [d_date_sk#7, d_year#8, d_moy#9, d_qoy#10] + +(35) BroadcastExchange +Input [4]: [d_date_sk#7, d_year#8, d_moy#9, d_qoy#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q67/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q67/simplified.txt new file mode 100644 index 0000000000..e10def3975 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q67/simplified.txt @@ -0,0 +1,53 @@ +TakeOrderedAndProject [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sumsales,rk] + WholeStageCodegen (7) + Filter [rk] + InputAdapter + Window [sumsales,i_category] + WindowGroupLimit [i_category,sumsales] + WholeStageCodegen (6) + Sort [i_category,sumsales] + InputAdapter + Exchange [i_category] #1 + WindowGroupLimit [i_category,sumsales] + WholeStageCodegen (5) + Sort [i_category,sumsales] + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,spark_grouping_id,sum,isEmpty] [sum(coalesce((ss_sales_price * cast(ss_quantity as decimal(10,0))), 0.00)),sumsales,sum,isEmpty] + InputAdapter + Exchange [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,spark_grouping_id] #2 + WholeStageCodegen (4) + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,spark_grouping_id,ss_sales_price,ss_quantity] [sum,isEmpty,sum,isEmpty] + Expand [ss_quantity,ss_sales_price,i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id] + Project [ss_quantity,ss_sales_price,i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_quantity,ss_sales_price,d_year,d_moy,d_qoy,s_store_id] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,ss_sales_price,d_year,d_moy,d_qoy] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk,ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_quantity,ss_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_year,d_moy,d_qoy] + CometFilter [d_month_seq,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq,d_year,d_moy,d_qoy] + InputAdapter + ReusedExchange [d_date_sk,d_year,d_moy,d_qoy] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_id] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_class,i_category,i_product_name] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q68/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q68/explain.txt new file mode 100644 index 0000000000..734b6c11c6 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q68/explain.txt @@ -0,0 +1,258 @@ +== Physical Plan == +TakeOrderedAndProject (39) ++- * Project (38) + +- * BroadcastHashJoin Inner BuildRight (37) + :- * Project (35) + : +- * BroadcastHashJoin Inner BuildRight (34) + : :- * HashAggregate (29) + : : +- Exchange (28) + : : +- * HashAggregate (27) + : : +- * Project (26) + : : +- * BroadcastHashJoin Inner BuildRight (25) + : : :- * Project (20) + : : : +- * BroadcastHashJoin Inner BuildRight (19) + : : : :- * Project (13) + : : : : +- * BroadcastHashJoin Inner BuildRight (12) + : : : : :- * Project (6) + : : : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : : : :- * ColumnarToRow (3) + : : : : : : +- CometFilter (2) + : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : : +- ReusedExchange (4) + : : : : +- BroadcastExchange (11) + : : : : +- * ColumnarToRow (10) + : : : : +- CometProject (9) + : : : : +- CometFilter (8) + : : : : +- CometScan parquet spark_catalog.default.store (7) + : : : +- BroadcastExchange (18) + : : : +- * ColumnarToRow (17) + : : : +- CometProject (16) + : : : +- CometFilter (15) + : : : +- CometScan parquet spark_catalog.default.household_demographics (14) + : : +- BroadcastExchange (24) + : : +- * ColumnarToRow (23) + : : +- CometFilter (22) + : : +- CometScan parquet spark_catalog.default.customer_address (21) + : +- BroadcastExchange (33) + : +- * ColumnarToRow (32) + : +- CometFilter (31) + : +- CometScan parquet spark_catalog.default.customer (30) + +- ReusedExchange (36) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [9]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_ext_sales_price#6, ss_ext_list_price#7, ss_ext_tax#8, ss_sold_date_sk#9] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#9), dynamicpruningexpression(ss_sold_date_sk#9 IN dynamicpruning#10)] +PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_hdemo_sk), IsNotNull(ss_addr_sk), IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(2) CometFilter +Input [9]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_ext_sales_price#6, ss_ext_list_price#7, ss_ext_tax#8, ss_sold_date_sk#9] +Condition : (((isnotnull(ss_store_sk#4) AND isnotnull(ss_hdemo_sk#2)) AND isnotnull(ss_addr_sk#3)) AND isnotnull(ss_customer_sk#1)) + +(3) ColumnarToRow [codegen id : 5] +Input [9]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_ext_sales_price#6, ss_ext_list_price#7, ss_ext_tax#8, ss_sold_date_sk#9] + +(4) ReusedExchange [Reuses operator id: 44] +Output [1]: [d_date_sk#11] + +(5) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_sold_date_sk#9] +Right keys [1]: [d_date_sk#11] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 5] +Output [8]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_ext_sales_price#6, ss_ext_list_price#7, ss_ext_tax#8] +Input [10]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_ext_sales_price#6, ss_ext_list_price#7, ss_ext_tax#8, ss_sold_date_sk#9, d_date_sk#11] + +(7) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#12, s_city#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [In(s_city, [Fairview,Midway]), IsNotNull(s_store_sk)] +ReadSchema: struct + +(8) CometFilter +Input [2]: [s_store_sk#12, s_city#13] +Condition : (s_city#13 IN (Midway,Fairview) AND isnotnull(s_store_sk#12)) + +(9) CometProject +Input [2]: [s_store_sk#12, s_city#13] +Arguments: [s_store_sk#12], [s_store_sk#12] + +(10) ColumnarToRow [codegen id : 2] +Input [1]: [s_store_sk#12] + +(11) BroadcastExchange +Input [1]: [s_store_sk#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(12) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_store_sk#4] +Right keys [1]: [s_store_sk#12] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 5] +Output [7]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_ticket_number#5, ss_ext_sales_price#6, ss_ext_list_price#7, ss_ext_tax#8] +Input [9]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_ext_sales_price#6, ss_ext_list_price#7, ss_ext_tax#8, s_store_sk#12] + +(14) Scan parquet spark_catalog.default.household_demographics +Output [3]: [hd_demo_sk#14, hd_dep_count#15, hd_vehicle_count#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/household_demographics] +PushedFilters: [Or(EqualTo(hd_dep_count,4),EqualTo(hd_vehicle_count,3)), IsNotNull(hd_demo_sk)] +ReadSchema: struct + +(15) CometFilter +Input [3]: [hd_demo_sk#14, hd_dep_count#15, hd_vehicle_count#16] +Condition : (((hd_dep_count#15 = 4) OR (hd_vehicle_count#16 = 3)) AND isnotnull(hd_demo_sk#14)) + +(16) CometProject +Input [3]: [hd_demo_sk#14, hd_dep_count#15, hd_vehicle_count#16] +Arguments: [hd_demo_sk#14], [hd_demo_sk#14] + +(17) ColumnarToRow [codegen id : 3] +Input [1]: [hd_demo_sk#14] + +(18) BroadcastExchange +Input [1]: [hd_demo_sk#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(19) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_hdemo_sk#2] +Right keys [1]: [hd_demo_sk#14] +Join type: Inner +Join condition: None + +(20) Project [codegen id : 5] +Output [6]: [ss_customer_sk#1, ss_addr_sk#3, ss_ticket_number#5, ss_ext_sales_price#6, ss_ext_list_price#7, ss_ext_tax#8] +Input [8]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_ticket_number#5, ss_ext_sales_price#6, ss_ext_list_price#7, ss_ext_tax#8, hd_demo_sk#14] + +(21) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#17, ca_city#18] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk), IsNotNull(ca_city)] +ReadSchema: struct + +(22) CometFilter +Input [2]: [ca_address_sk#17, ca_city#18] +Condition : (isnotnull(ca_address_sk#17) AND isnotnull(ca_city#18)) + +(23) ColumnarToRow [codegen id : 4] +Input [2]: [ca_address_sk#17, ca_city#18] + +(24) BroadcastExchange +Input [2]: [ca_address_sk#17, ca_city#18] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(25) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_addr_sk#3] +Right keys [1]: [ca_address_sk#17] +Join type: Inner +Join condition: None + +(26) Project [codegen id : 5] +Output [7]: [ss_customer_sk#1, ss_addr_sk#3, ss_ticket_number#5, ss_ext_sales_price#6, ss_ext_list_price#7, ss_ext_tax#8, ca_city#18] +Input [8]: [ss_customer_sk#1, ss_addr_sk#3, ss_ticket_number#5, ss_ext_sales_price#6, ss_ext_list_price#7, ss_ext_tax#8, ca_address_sk#17, ca_city#18] + +(27) HashAggregate [codegen id : 5] +Input [7]: [ss_customer_sk#1, ss_addr_sk#3, ss_ticket_number#5, ss_ext_sales_price#6, ss_ext_list_price#7, ss_ext_tax#8, ca_city#18] +Keys [4]: [ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, ca_city#18] +Functions [3]: [partial_sum(UnscaledValue(ss_ext_sales_price#6)), partial_sum(UnscaledValue(ss_ext_list_price#7)), partial_sum(UnscaledValue(ss_ext_tax#8))] +Aggregate Attributes [3]: [sum#19, sum#20, sum#21] +Results [7]: [ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, ca_city#18, sum#22, sum#23, sum#24] + +(28) Exchange +Input [7]: [ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, ca_city#18, sum#22, sum#23, sum#24] +Arguments: hashpartitioning(ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, ca_city#18, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(29) HashAggregate [codegen id : 8] +Input [7]: [ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, ca_city#18, sum#22, sum#23, sum#24] +Keys [4]: [ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, ca_city#18] +Functions [3]: [sum(UnscaledValue(ss_ext_sales_price#6)), sum(UnscaledValue(ss_ext_list_price#7)), sum(UnscaledValue(ss_ext_tax#8))] +Aggregate Attributes [3]: [sum(UnscaledValue(ss_ext_sales_price#6))#25, sum(UnscaledValue(ss_ext_list_price#7))#26, sum(UnscaledValue(ss_ext_tax#8))#27] +Results [6]: [ss_ticket_number#5, ss_customer_sk#1, ca_city#18 AS bought_city#28, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#6))#25,17,2) AS extended_price#29, MakeDecimal(sum(UnscaledValue(ss_ext_list_price#7))#26,17,2) AS list_price#30, MakeDecimal(sum(UnscaledValue(ss_ext_tax#8))#27,17,2) AS extended_tax#31] + +(30) Scan parquet spark_catalog.default.customer +Output [4]: [c_customer_sk#32, c_current_addr_sk#33, c_first_name#34, c_last_name#35] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_current_addr_sk)] +ReadSchema: struct + +(31) CometFilter +Input [4]: [c_customer_sk#32, c_current_addr_sk#33, c_first_name#34, c_last_name#35] +Condition : (isnotnull(c_customer_sk#32) AND isnotnull(c_current_addr_sk#33)) + +(32) ColumnarToRow [codegen id : 6] +Input [4]: [c_customer_sk#32, c_current_addr_sk#33, c_first_name#34, c_last_name#35] + +(33) BroadcastExchange +Input [4]: [c_customer_sk#32, c_current_addr_sk#33, c_first_name#34, c_last_name#35] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(34) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_customer_sk#1] +Right keys [1]: [c_customer_sk#32] +Join type: Inner +Join condition: None + +(35) Project [codegen id : 8] +Output [8]: [ss_ticket_number#5, bought_city#28, extended_price#29, list_price#30, extended_tax#31, c_current_addr_sk#33, c_first_name#34, c_last_name#35] +Input [10]: [ss_ticket_number#5, ss_customer_sk#1, bought_city#28, extended_price#29, list_price#30, extended_tax#31, c_customer_sk#32, c_current_addr_sk#33, c_first_name#34, c_last_name#35] + +(36) ReusedExchange [Reuses operator id: 24] +Output [2]: [ca_address_sk#36, ca_city#37] + +(37) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [c_current_addr_sk#33] +Right keys [1]: [ca_address_sk#36] +Join type: Inner +Join condition: NOT (ca_city#37 = bought_city#28) + +(38) Project [codegen id : 8] +Output [8]: [c_last_name#35, c_first_name#34, ca_city#37, bought_city#28, ss_ticket_number#5, extended_price#29, extended_tax#31, list_price#30] +Input [10]: [ss_ticket_number#5, bought_city#28, extended_price#29, list_price#30, extended_tax#31, c_current_addr_sk#33, c_first_name#34, c_last_name#35, ca_address_sk#36, ca_city#37] + +(39) TakeOrderedAndProject +Input [8]: [c_last_name#35, c_first_name#34, ca_city#37, bought_city#28, ss_ticket_number#5, extended_price#29, extended_tax#31, list_price#30] +Arguments: 100, [c_last_name#35 ASC NULLS FIRST, ss_ticket_number#5 ASC NULLS FIRST], [c_last_name#35, c_first_name#34, ca_city#37, bought_city#28, ss_ticket_number#5, extended_price#29, extended_tax#31, list_price#30] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#9 IN dynamicpruning#10 +BroadcastExchange (44) ++- * ColumnarToRow (43) + +- CometProject (42) + +- CometFilter (41) + +- CometScan parquet spark_catalog.default.date_dim (40) + + +(40) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#11, d_year#38, d_dom#39] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_dom), GreaterThanOrEqual(d_dom,1), LessThanOrEqual(d_dom,2), In(d_year, [1999,2000,2001]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(41) CometFilter +Input [3]: [d_date_sk#11, d_year#38, d_dom#39] +Condition : ((((isnotnull(d_dom#39) AND (d_dom#39 >= 1)) AND (d_dom#39 <= 2)) AND d_year#38 IN (1999,2000,2001)) AND isnotnull(d_date_sk#11)) + +(42) CometProject +Input [3]: [d_date_sk#11, d_year#38, d_dom#39] +Arguments: [d_date_sk#11], [d_date_sk#11] + +(43) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#11] + +(44) BroadcastExchange +Input [1]: [d_date_sk#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q68/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q68/simplified.txt new file mode 100644 index 0000000000..f2680bebb0 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q68/simplified.txt @@ -0,0 +1,65 @@ +TakeOrderedAndProject [c_last_name,ss_ticket_number,c_first_name,ca_city,bought_city,extended_price,extended_tax,list_price] + WholeStageCodegen (8) + Project [c_last_name,c_first_name,ca_city,bought_city,ss_ticket_number,extended_price,extended_tax,list_price] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk,ca_city,bought_city] + Project [ss_ticket_number,bought_city,extended_price,list_price,extended_tax,c_current_addr_sk,c_first_name,c_last_name] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + HashAggregate [ss_ticket_number,ss_customer_sk,ss_addr_sk,ca_city,sum,sum,sum] [sum(UnscaledValue(ss_ext_sales_price)),sum(UnscaledValue(ss_ext_list_price)),sum(UnscaledValue(ss_ext_tax)),bought_city,extended_price,list_price,extended_tax,sum,sum,sum] + InputAdapter + Exchange [ss_ticket_number,ss_customer_sk,ss_addr_sk,ca_city] #1 + WholeStageCodegen (5) + HashAggregate [ss_ticket_number,ss_customer_sk,ss_addr_sk,ca_city,ss_ext_sales_price,ss_ext_list_price,ss_ext_tax] [sum,sum,sum,sum,sum,sum] + Project [ss_customer_sk,ss_addr_sk,ss_ticket_number,ss_ext_sales_price,ss_ext_list_price,ss_ext_tax,ca_city] + BroadcastHashJoin [ss_addr_sk,ca_address_sk] + Project [ss_customer_sk,ss_addr_sk,ss_ticket_number,ss_ext_sales_price,ss_ext_list_price,ss_ext_tax] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + Project [ss_customer_sk,ss_hdemo_sk,ss_addr_sk,ss_ticket_number,ss_ext_sales_price,ss_ext_list_price,ss_ext_tax] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_customer_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_ticket_number,ss_ext_sales_price,ss_ext_list_price,ss_ext_tax] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk,ss_hdemo_sk,ss_addr_sk,ss_customer_sk] + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_ticket_number,ss_ext_sales_price,ss_ext_list_price,ss_ext_tax,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_dom,d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_dom] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometProject [s_store_sk] + CometFilter [s_city,s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk,s_city] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometProject [hd_demo_sk] + CometFilter [hd_dep_count,hd_vehicle_count,hd_demo_sk] + CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_dep_count,hd_vehicle_count] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (4) + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk,ca_city] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_city] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (6) + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_current_addr_sk] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_addr_sk,c_first_name,c_last_name] + InputAdapter + ReusedExchange [ca_address_sk,ca_city] #5 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q69/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q69/explain.txt new file mode 100644 index 0000000000..d56b01d737 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q69/explain.txt @@ -0,0 +1,281 @@ +== Physical Plan == +TakeOrderedAndProject (42) ++- * HashAggregate (41) + +- Exchange (40) + +- * HashAggregate (39) + +- * Project (38) + +- * BroadcastHashJoin Inner BuildRight (37) + :- * Project (32) + : +- * BroadcastHashJoin Inner BuildRight (31) + : :- * Project (25) + : : +- * BroadcastHashJoin LeftAnti BuildRight (24) + : : :- * BroadcastHashJoin LeftAnti BuildRight (17) + : : : :- * BroadcastHashJoin LeftSemi BuildRight (10) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) + : : : : : +- CometScan parquet spark_catalog.default.customer (1) + : : : : +- BroadcastExchange (9) + : : : : +- * Project (8) + : : : : +- * BroadcastHashJoin Inner BuildRight (7) + : : : : :- * ColumnarToRow (5) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (4) + : : : : +- ReusedExchange (6) + : : : +- BroadcastExchange (16) + : : : +- * Project (15) + : : : +- * BroadcastHashJoin Inner BuildRight (14) + : : : :- * ColumnarToRow (12) + : : : : +- CometScan parquet spark_catalog.default.web_sales (11) + : : : +- ReusedExchange (13) + : : +- BroadcastExchange (23) + : : +- * Project (22) + : : +- * BroadcastHashJoin Inner BuildRight (21) + : : :- * ColumnarToRow (19) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (18) + : : +- ReusedExchange (20) + : +- BroadcastExchange (30) + : +- * ColumnarToRow (29) + : +- CometProject (28) + : +- CometFilter (27) + : +- CometScan parquet spark_catalog.default.customer_address (26) + +- BroadcastExchange (36) + +- * ColumnarToRow (35) + +- CometFilter (34) + +- CometScan parquet spark_catalog.default.customer_demographics (33) + + +(1) Scan parquet spark_catalog.default.customer +Output [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_current_addr_sk), IsNotNull(c_current_cdemo_sk)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3] +Condition : (isnotnull(c_current_addr_sk#3) AND isnotnull(c_current_cdemo_sk#2)) + +(3) ColumnarToRow [codegen id : 9] +Input [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3] + +(4) Scan parquet spark_catalog.default.store_sales +Output [2]: [ss_customer_sk#4, ss_sold_date_sk#5] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#5), dynamicpruningexpression(ss_sold_date_sk#5 IN dynamicpruning#6)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 2] +Input [2]: [ss_customer_sk#4, ss_sold_date_sk#5] + +(6) ReusedExchange [Reuses operator id: 47] +Output [1]: [d_date_sk#7] + +(7) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [ss_sold_date_sk#5] +Right keys [1]: [d_date_sk#7] +Join type: Inner +Join condition: None + +(8) Project [codegen id : 2] +Output [1]: [ss_customer_sk#4] +Input [3]: [ss_customer_sk#4, ss_sold_date_sk#5, d_date_sk#7] + +(9) BroadcastExchange +Input [1]: [ss_customer_sk#4] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(10) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_customer_sk#1] +Right keys [1]: [ss_customer_sk#4] +Join type: LeftSemi +Join condition: None + +(11) Scan parquet spark_catalog.default.web_sales +Output [2]: [ws_bill_customer_sk#8, ws_sold_date_sk#9] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#9), dynamicpruningexpression(ws_sold_date_sk#9 IN dynamicpruning#10)] +ReadSchema: struct + +(12) ColumnarToRow [codegen id : 4] +Input [2]: [ws_bill_customer_sk#8, ws_sold_date_sk#9] + +(13) ReusedExchange [Reuses operator id: 47] +Output [1]: [d_date_sk#11] + +(14) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ws_sold_date_sk#9] +Right keys [1]: [d_date_sk#11] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 4] +Output [1]: [ws_bill_customer_sk#8] +Input [3]: [ws_bill_customer_sk#8, ws_sold_date_sk#9, d_date_sk#11] + +(16) BroadcastExchange +Input [1]: [ws_bill_customer_sk#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(17) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_customer_sk#1] +Right keys [1]: [ws_bill_customer_sk#8] +Join type: LeftAnti +Join condition: None + +(18) Scan parquet spark_catalog.default.catalog_sales +Output [2]: [cs_ship_customer_sk#12, cs_sold_date_sk#13] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#13), dynamicpruningexpression(cs_sold_date_sk#13 IN dynamicpruning#14)] +ReadSchema: struct + +(19) ColumnarToRow [codegen id : 6] +Input [2]: [cs_ship_customer_sk#12, cs_sold_date_sk#13] + +(20) ReusedExchange [Reuses operator id: 47] +Output [1]: [d_date_sk#15] + +(21) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [cs_sold_date_sk#13] +Right keys [1]: [d_date_sk#15] +Join type: Inner +Join condition: None + +(22) Project [codegen id : 6] +Output [1]: [cs_ship_customer_sk#12] +Input [3]: [cs_ship_customer_sk#12, cs_sold_date_sk#13, d_date_sk#15] + +(23) BroadcastExchange +Input [1]: [cs_ship_customer_sk#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_customer_sk#1] +Right keys [1]: [cs_ship_customer_sk#12] +Join type: LeftAnti +Join condition: None + +(25) Project [codegen id : 9] +Output [2]: [c_current_cdemo_sk#2, c_current_addr_sk#3] +Input [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3] + +(26) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#16, ca_state#17] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [In(ca_state, [GA,KY,NM]), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(27) CometFilter +Input [2]: [ca_address_sk#16, ca_state#17] +Condition : (ca_state#17 IN (KY,GA,NM) AND isnotnull(ca_address_sk#16)) + +(28) CometProject +Input [2]: [ca_address_sk#16, ca_state#17] +Arguments: [ca_address_sk#16], [ca_address_sk#16] + +(29) ColumnarToRow [codegen id : 7] +Input [1]: [ca_address_sk#16] + +(30) BroadcastExchange +Input [1]: [ca_address_sk#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(31) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_current_addr_sk#3] +Right keys [1]: [ca_address_sk#16] +Join type: Inner +Join condition: None + +(32) Project [codegen id : 9] +Output [1]: [c_current_cdemo_sk#2] +Input [3]: [c_current_cdemo_sk#2, c_current_addr_sk#3, ca_address_sk#16] + +(33) Scan parquet spark_catalog.default.customer_demographics +Output [6]: [cd_demo_sk#18, cd_gender#19, cd_marital_status#20, cd_education_status#21, cd_purchase_estimate#22, cd_credit_rating#23] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(34) CometFilter +Input [6]: [cd_demo_sk#18, cd_gender#19, cd_marital_status#20, cd_education_status#21, cd_purchase_estimate#22, cd_credit_rating#23] +Condition : isnotnull(cd_demo_sk#18) + +(35) ColumnarToRow [codegen id : 8] +Input [6]: [cd_demo_sk#18, cd_gender#19, cd_marital_status#20, cd_education_status#21, cd_purchase_estimate#22, cd_credit_rating#23] + +(36) BroadcastExchange +Input [6]: [cd_demo_sk#18, cd_gender#19, cd_marital_status#20, cd_education_status#21, cd_purchase_estimate#22, cd_credit_rating#23] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(37) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_current_cdemo_sk#2] +Right keys [1]: [cd_demo_sk#18] +Join type: Inner +Join condition: None + +(38) Project [codegen id : 9] +Output [5]: [cd_gender#19, cd_marital_status#20, cd_education_status#21, cd_purchase_estimate#22, cd_credit_rating#23] +Input [7]: [c_current_cdemo_sk#2, cd_demo_sk#18, cd_gender#19, cd_marital_status#20, cd_education_status#21, cd_purchase_estimate#22, cd_credit_rating#23] + +(39) HashAggregate [codegen id : 9] +Input [5]: [cd_gender#19, cd_marital_status#20, cd_education_status#21, cd_purchase_estimate#22, cd_credit_rating#23] +Keys [5]: [cd_gender#19, cd_marital_status#20, cd_education_status#21, cd_purchase_estimate#22, cd_credit_rating#23] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#24] +Results [6]: [cd_gender#19, cd_marital_status#20, cd_education_status#21, cd_purchase_estimate#22, cd_credit_rating#23, count#25] + +(40) Exchange +Input [6]: [cd_gender#19, cd_marital_status#20, cd_education_status#21, cd_purchase_estimate#22, cd_credit_rating#23, count#25] +Arguments: hashpartitioning(cd_gender#19, cd_marital_status#20, cd_education_status#21, cd_purchase_estimate#22, cd_credit_rating#23, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(41) HashAggregate [codegen id : 10] +Input [6]: [cd_gender#19, cd_marital_status#20, cd_education_status#21, cd_purchase_estimate#22, cd_credit_rating#23, count#25] +Keys [5]: [cd_gender#19, cd_marital_status#20, cd_education_status#21, cd_purchase_estimate#22, cd_credit_rating#23] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#26] +Results [8]: [cd_gender#19, cd_marital_status#20, cd_education_status#21, count(1)#26 AS cnt1#27, cd_purchase_estimate#22, count(1)#26 AS cnt2#28, cd_credit_rating#23, count(1)#26 AS cnt3#29] + +(42) TakeOrderedAndProject +Input [8]: [cd_gender#19, cd_marital_status#20, cd_education_status#21, cnt1#27, cd_purchase_estimate#22, cnt2#28, cd_credit_rating#23, cnt3#29] +Arguments: 100, [cd_gender#19 ASC NULLS FIRST, cd_marital_status#20 ASC NULLS FIRST, cd_education_status#21 ASC NULLS FIRST, cd_purchase_estimate#22 ASC NULLS FIRST, cd_credit_rating#23 ASC NULLS FIRST], [cd_gender#19, cd_marital_status#20, cd_education_status#21, cnt1#27, cd_purchase_estimate#22, cnt2#28, cd_credit_rating#23, cnt3#29] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6 +BroadcastExchange (47) ++- * ColumnarToRow (46) + +- CometProject (45) + +- CometFilter (44) + +- CometScan parquet spark_catalog.default.date_dim (43) + + +(43) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#7, d_year#30, d_moy#31] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2001), GreaterThanOrEqual(d_moy,4), LessThanOrEqual(d_moy,6), IsNotNull(d_date_sk)] +ReadSchema: struct + +(44) CometFilter +Input [3]: [d_date_sk#7, d_year#30, d_moy#31] +Condition : (((((isnotnull(d_year#30) AND isnotnull(d_moy#31)) AND (d_year#30 = 2001)) AND (d_moy#31 >= 4)) AND (d_moy#31 <= 6)) AND isnotnull(d_date_sk#7)) + +(45) CometProject +Input [3]: [d_date_sk#7, d_year#30, d_moy#31] +Arguments: [d_date_sk#7], [d_date_sk#7] + +(46) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#7] + +(47) BroadcastExchange +Input [1]: [d_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +Subquery:2 Hosting operator id = 11 Hosting Expression = ws_sold_date_sk#9 IN dynamicpruning#6 + +Subquery:3 Hosting operator id = 18 Hosting Expression = cs_sold_date_sk#13 IN dynamicpruning#6 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q69/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q69/simplified.txt new file mode 100644 index 0000000000..f5b4eccfbe --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q69/simplified.txt @@ -0,0 +1,74 @@ +TakeOrderedAndProject [cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating,cnt1,cnt2,cnt3] + WholeStageCodegen (10) + HashAggregate [cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating,count] [count(1),cnt1,cnt2,cnt3,count] + InputAdapter + Exchange [cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating] #1 + WholeStageCodegen (9) + HashAggregate [cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating] [count,count] + Project [cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk] + Project [c_current_cdemo_sk] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [c_current_cdemo_sk,c_current_addr_sk] + BroadcastHashJoin [c_customer_sk,cs_ship_customer_sk] + BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + ColumnarToRow + InputAdapter + CometFilter [c_current_addr_sk,c_current_cdemo_sk] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (2) + Project [ss_customer_sk] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_moy,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (4) + Project [ws_bill_customer_sk] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (6) + Project [cs_ship_customer_sk] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_ship_customer_sk,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (7) + ColumnarToRow + InputAdapter + CometProject [ca_address_sk] + CometFilter [ca_state,ca_address_sk] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (8) + ColumnarToRow + InputAdapter + CometFilter [cd_demo_sk] + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q7/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q7/explain.txt new file mode 100644 index 0000000000..790a917e38 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q7/explain.txt @@ -0,0 +1,208 @@ +== Physical Plan == +TakeOrderedAndProject (30) ++- * HashAggregate (29) + +- Exchange (28) + +- * HashAggregate (27) + +- * Project (26) + +- * BroadcastHashJoin Inner BuildRight (25) + :- * Project (19) + : +- * BroadcastHashJoin Inner BuildRight (18) + : :- * Project (13) + : : +- * BroadcastHashJoin Inner BuildRight (12) + : : :- * Project (10) + : : : +- * BroadcastHashJoin Inner BuildRight (9) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- BroadcastExchange (8) + : : : +- * ColumnarToRow (7) + : : : +- CometProject (6) + : : : +- CometFilter (5) + : : : +- CometScan parquet spark_catalog.default.customer_demographics (4) + : : +- ReusedExchange (11) + : +- BroadcastExchange (17) + : +- * ColumnarToRow (16) + : +- CometFilter (15) + : +- CometScan parquet spark_catalog.default.item (14) + +- BroadcastExchange (24) + +- * ColumnarToRow (23) + +- CometProject (22) + +- CometFilter (21) + +- CometScan parquet spark_catalog.default.promotion (20) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [8]: [ss_item_sk#1, ss_cdemo_sk#2, ss_promo_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#8), dynamicpruningexpression(ss_sold_date_sk#8 IN dynamicpruning#9)] +PushedFilters: [IsNotNull(ss_cdemo_sk), IsNotNull(ss_item_sk), IsNotNull(ss_promo_sk)] +ReadSchema: struct + +(2) CometFilter +Input [8]: [ss_item_sk#1, ss_cdemo_sk#2, ss_promo_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8] +Condition : ((isnotnull(ss_cdemo_sk#2) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_promo_sk#3)) + +(3) ColumnarToRow [codegen id : 5] +Input [8]: [ss_item_sk#1, ss_cdemo_sk#2, ss_promo_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8] + +(4) Scan parquet spark_catalog.default.customer_demographics +Output [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_gender), IsNotNull(cd_marital_status), IsNotNull(cd_education_status), EqualTo(cd_gender,M), EqualTo(cd_marital_status,S), EqualTo(cd_education_status,College ), IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(5) CometFilter +Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] +Condition : ((((((isnotnull(cd_gender#11) AND isnotnull(cd_marital_status#12)) AND isnotnull(cd_education_status#13)) AND (cd_gender#11 = M)) AND (cd_marital_status#12 = S)) AND (cd_education_status#13 = College )) AND isnotnull(cd_demo_sk#10)) + +(6) CometProject +Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] +Arguments: [cd_demo_sk#10], [cd_demo_sk#10] + +(7) ColumnarToRow [codegen id : 1] +Input [1]: [cd_demo_sk#10] + +(8) BroadcastExchange +Input [1]: [cd_demo_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_cdemo_sk#2] +Right keys [1]: [cd_demo_sk#10] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 5] +Output [7]: [ss_item_sk#1, ss_promo_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8] +Input [9]: [ss_item_sk#1, ss_cdemo_sk#2, ss_promo_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8, cd_demo_sk#10] + +(11) ReusedExchange [Reuses operator id: 35] +Output [1]: [d_date_sk#14] + +(12) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_sold_date_sk#8] +Right keys [1]: [d_date_sk#14] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 5] +Output [6]: [ss_item_sk#1, ss_promo_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7] +Input [8]: [ss_item_sk#1, ss_promo_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8, d_date_sk#14] + +(14) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#15, i_item_id#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(15) CometFilter +Input [2]: [i_item_sk#15, i_item_id#16] +Condition : isnotnull(i_item_sk#15) + +(16) ColumnarToRow [codegen id : 3] +Input [2]: [i_item_sk#15, i_item_id#16] + +(17) BroadcastExchange +Input [2]: [i_item_sk#15, i_item_id#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(18) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#15] +Join type: Inner +Join condition: None + +(19) Project [codegen id : 5] +Output [6]: [ss_promo_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#16] +Input [8]: [ss_item_sk#1, ss_promo_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_sk#15, i_item_id#16] + +(20) Scan parquet spark_catalog.default.promotion +Output [3]: [p_promo_sk#17, p_channel_email#18, p_channel_event#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/promotion] +PushedFilters: [Or(EqualTo(p_channel_email,N),EqualTo(p_channel_event,N)), IsNotNull(p_promo_sk)] +ReadSchema: struct + +(21) CometFilter +Input [3]: [p_promo_sk#17, p_channel_email#18, p_channel_event#19] +Condition : (((p_channel_email#18 = N) OR (p_channel_event#19 = N)) AND isnotnull(p_promo_sk#17)) + +(22) CometProject +Input [3]: [p_promo_sk#17, p_channel_email#18, p_channel_event#19] +Arguments: [p_promo_sk#17], [p_promo_sk#17] + +(23) ColumnarToRow [codegen id : 4] +Input [1]: [p_promo_sk#17] + +(24) BroadcastExchange +Input [1]: [p_promo_sk#17] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(25) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_promo_sk#3] +Right keys [1]: [p_promo_sk#17] +Join type: Inner +Join condition: None + +(26) Project [codegen id : 5] +Output [5]: [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#16] +Input [7]: [ss_promo_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#16, p_promo_sk#17] + +(27) HashAggregate [codegen id : 5] +Input [5]: [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#16] +Keys [1]: [i_item_id#16] +Functions [4]: [partial_avg(ss_quantity#4), partial_avg(UnscaledValue(ss_list_price#5)), partial_avg(UnscaledValue(ss_coupon_amt#7)), partial_avg(UnscaledValue(ss_sales_price#6))] +Aggregate Attributes [8]: [sum#20, count#21, sum#22, count#23, sum#24, count#25, sum#26, count#27] +Results [9]: [i_item_id#16, sum#28, count#29, sum#30, count#31, sum#32, count#33, sum#34, count#35] + +(28) Exchange +Input [9]: [i_item_id#16, sum#28, count#29, sum#30, count#31, sum#32, count#33, sum#34, count#35] +Arguments: hashpartitioning(i_item_id#16, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(29) HashAggregate [codegen id : 6] +Input [9]: [i_item_id#16, sum#28, count#29, sum#30, count#31, sum#32, count#33, sum#34, count#35] +Keys [1]: [i_item_id#16] +Functions [4]: [avg(ss_quantity#4), avg(UnscaledValue(ss_list_price#5)), avg(UnscaledValue(ss_coupon_amt#7)), avg(UnscaledValue(ss_sales_price#6))] +Aggregate Attributes [4]: [avg(ss_quantity#4)#36, avg(UnscaledValue(ss_list_price#5))#37, avg(UnscaledValue(ss_coupon_amt#7))#38, avg(UnscaledValue(ss_sales_price#6))#39] +Results [5]: [i_item_id#16, avg(ss_quantity#4)#36 AS agg1#40, cast((avg(UnscaledValue(ss_list_price#5))#37 / 100.0) as decimal(11,6)) AS agg2#41, cast((avg(UnscaledValue(ss_coupon_amt#7))#38 / 100.0) as decimal(11,6)) AS agg3#42, cast((avg(UnscaledValue(ss_sales_price#6))#39 / 100.0) as decimal(11,6)) AS agg4#43] + +(30) TakeOrderedAndProject +Input [5]: [i_item_id#16, agg1#40, agg2#41, agg3#42, agg4#43] +Arguments: 100, [i_item_id#16 ASC NULLS FIRST], [i_item_id#16, agg1#40, agg2#41, agg3#42, agg4#43] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#8 IN dynamicpruning#9 +BroadcastExchange (35) ++- * ColumnarToRow (34) + +- CometProject (33) + +- CometFilter (32) + +- CometScan parquet spark_catalog.default.date_dim (31) + + +(31) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#14, d_year#44] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2000), IsNotNull(d_date_sk)] +ReadSchema: struct + +(32) CometFilter +Input [2]: [d_date_sk#14, d_year#44] +Condition : ((isnotnull(d_year#44) AND (d_year#44 = 2000)) AND isnotnull(d_date_sk#14)) + +(33) CometProject +Input [2]: [d_date_sk#14, d_year#44] +Arguments: [d_date_sk#14], [d_date_sk#14] + +(34) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#14] + +(35) BroadcastExchange +Input [1]: [d_date_sk#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q7/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q7/simplified.txt new file mode 100644 index 0000000000..2471de20a3 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q7/simplified.txt @@ -0,0 +1,52 @@ +TakeOrderedAndProject [i_item_id,agg1,agg2,agg3,agg4] + WholeStageCodegen (6) + HashAggregate [i_item_id,sum,count,sum,count,sum,count,sum,count] [avg(ss_quantity),avg(UnscaledValue(ss_list_price)),avg(UnscaledValue(ss_coupon_amt)),avg(UnscaledValue(ss_sales_price)),agg1,agg2,agg3,agg4,sum,count,sum,count,sum,count,sum,count] + InputAdapter + Exchange [i_item_id] #1 + WholeStageCodegen (5) + HashAggregate [i_item_id,ss_quantity,ss_list_price,ss_coupon_amt,ss_sales_price] [sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + Project [ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,i_item_id] + BroadcastHashJoin [ss_promo_sk,p_promo_sk] + Project [ss_promo_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,i_item_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_promo_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_promo_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,ss_sold_date_sk] + BroadcastHashJoin [ss_cdemo_sk,cd_demo_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_cdemo_sk,ss_item_sk,ss_promo_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_cdemo_sk,ss_promo_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [cd_demo_sk] + CometFilter [cd_gender,cd_marital_status,cd_education_status,cd_demo_sk] + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_marital_status,cd_education_status] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (4) + ColumnarToRow + InputAdapter + CometProject [p_promo_sk] + CometFilter [p_channel_email,p_channel_event,p_promo_sk] + CometScan parquet spark_catalog.default.promotion [p_promo_sk,p_channel_email,p_channel_event] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q70/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q70/explain.txt new file mode 100644 index 0000000000..c3acf0a8de --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q70/explain.txt @@ -0,0 +1,283 @@ +== Physical Plan == +TakeOrderedAndProject (43) ++- * Project (42) + +- Window (41) + +- * Sort (40) + +- Exchange (39) + +- * HashAggregate (38) + +- Exchange (37) + +- * HashAggregate (36) + +- * Expand (35) + +- * Project (34) + +- * BroadcastHashJoin Inner BuildRight (33) + :- * Project (6) + : +- * BroadcastHashJoin Inner BuildRight (5) + : :- * ColumnarToRow (3) + : : +- CometFilter (2) + : : +- CometScan parquet spark_catalog.default.store_sales (1) + : +- ReusedExchange (4) + +- BroadcastExchange (32) + +- * BroadcastHashJoin LeftSemi BuildRight (31) + :- * ColumnarToRow (9) + : +- CometFilter (8) + : +- CometScan parquet spark_catalog.default.store (7) + +- BroadcastExchange (30) + +- * Project (29) + +- * Filter (28) + +- Window (27) + +- WindowGroupLimit (26) + +- * Sort (25) + +- * HashAggregate (24) + +- Exchange (23) + +- * HashAggregate (22) + +- * Project (21) + +- * BroadcastHashJoin Inner BuildRight (20) + :- * Project (18) + : +- * BroadcastHashJoin Inner BuildRight (17) + : :- * ColumnarToRow (12) + : : +- CometFilter (11) + : : +- CometScan parquet spark_catalog.default.store_sales (10) + : +- BroadcastExchange (16) + : +- * ColumnarToRow (15) + : +- CometFilter (14) + : +- CometScan parquet spark_catalog.default.store (13) + +- ReusedExchange (19) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_store_sk#1, ss_net_profit#2, ss_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#3), dynamicpruningexpression(ss_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(ss_store_sk)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [ss_store_sk#1, ss_net_profit#2, ss_sold_date_sk#3] +Condition : isnotnull(ss_store_sk#1) + +(3) ColumnarToRow [codegen id : 8] +Input [3]: [ss_store_sk#1, ss_net_profit#2, ss_sold_date_sk#3] + +(4) ReusedExchange [Reuses operator id: 48] +Output [1]: [d_date_sk#5] + +(5) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_sold_date_sk#3] +Right keys [1]: [d_date_sk#5] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 8] +Output [2]: [ss_store_sk#1, ss_net_profit#2] +Input [4]: [ss_store_sk#1, ss_net_profit#2, ss_sold_date_sk#3, d_date_sk#5] + +(7) Scan parquet spark_catalog.default.store +Output [3]: [s_store_sk#6, s_county#7, s_state#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(8) CometFilter +Input [3]: [s_store_sk#6, s_county#7, s_state#8] +Condition : isnotnull(s_store_sk#6) + +(9) ColumnarToRow [codegen id : 7] +Input [3]: [s_store_sk#6, s_county#7, s_state#8] + +(10) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_store_sk#9, ss_net_profit#10, ss_sold_date_sk#11] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#11), dynamicpruningexpression(ss_sold_date_sk#11 IN dynamicpruning#12)] +PushedFilters: [IsNotNull(ss_store_sk)] +ReadSchema: struct + +(11) CometFilter +Input [3]: [ss_store_sk#9, ss_net_profit#10, ss_sold_date_sk#11] +Condition : isnotnull(ss_store_sk#9) + +(12) ColumnarToRow [codegen id : 4] +Input [3]: [ss_store_sk#9, ss_net_profit#10, ss_sold_date_sk#11] + +(13) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#13, s_state#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(14) CometFilter +Input [2]: [s_store_sk#13, s_state#14] +Condition : isnotnull(s_store_sk#13) + +(15) ColumnarToRow [codegen id : 2] +Input [2]: [s_store_sk#13, s_state#14] + +(16) BroadcastExchange +Input [2]: [s_store_sk#13, s_state#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(17) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_store_sk#9] +Right keys [1]: [s_store_sk#13] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 4] +Output [3]: [ss_net_profit#10, ss_sold_date_sk#11, s_state#14] +Input [5]: [ss_store_sk#9, ss_net_profit#10, ss_sold_date_sk#11, s_store_sk#13, s_state#14] + +(19) ReusedExchange [Reuses operator id: 48] +Output [1]: [d_date_sk#15] + +(20) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_date_sk#11] +Right keys [1]: [d_date_sk#15] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 4] +Output [2]: [ss_net_profit#10, s_state#14] +Input [4]: [ss_net_profit#10, ss_sold_date_sk#11, s_state#14, d_date_sk#15] + +(22) HashAggregate [codegen id : 4] +Input [2]: [ss_net_profit#10, s_state#14] +Keys [1]: [s_state#14] +Functions [1]: [partial_sum(UnscaledValue(ss_net_profit#10))] +Aggregate Attributes [1]: [sum#16] +Results [2]: [s_state#14, sum#17] + +(23) Exchange +Input [2]: [s_state#14, sum#17] +Arguments: hashpartitioning(s_state#14, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(24) HashAggregate [codegen id : 5] +Input [2]: [s_state#14, sum#17] +Keys [1]: [s_state#14] +Functions [1]: [sum(UnscaledValue(ss_net_profit#10))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_profit#10))#18] +Results [3]: [s_state#14, MakeDecimal(sum(UnscaledValue(ss_net_profit#10))#18,17,2) AS _w0#19, s_state#14] + +(25) Sort [codegen id : 5] +Input [3]: [s_state#14, _w0#19, s_state#14] +Arguments: [s_state#14 ASC NULLS FIRST, _w0#19 DESC NULLS LAST], false, 0 + +(26) WindowGroupLimit +Input [3]: [s_state#14, _w0#19, s_state#14] +Arguments: [s_state#14], [_w0#19 DESC NULLS LAST], rank(_w0#19), 5, Final + +(27) Window +Input [3]: [s_state#14, _w0#19, s_state#14] +Arguments: [rank(_w0#19) windowspecdefinition(s_state#14, _w0#19 DESC NULLS LAST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS ranking#20], [s_state#14], [_w0#19 DESC NULLS LAST] + +(28) Filter [codegen id : 6] +Input [4]: [s_state#14, _w0#19, s_state#14, ranking#20] +Condition : (ranking#20 <= 5) + +(29) Project [codegen id : 6] +Output [1]: [s_state#14] +Input [4]: [s_state#14, _w0#19, s_state#14, ranking#20] + +(30) BroadcastExchange +Input [1]: [s_state#14] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=3] + +(31) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [s_state#8] +Right keys [1]: [s_state#14] +Join type: LeftSemi +Join condition: None + +(32) BroadcastExchange +Input [3]: [s_store_sk#6, s_county#7, s_state#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(33) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_store_sk#1] +Right keys [1]: [s_store_sk#6] +Join type: Inner +Join condition: None + +(34) Project [codegen id : 8] +Output [3]: [ss_net_profit#2, s_state#8, s_county#7] +Input [5]: [ss_store_sk#1, ss_net_profit#2, s_store_sk#6, s_county#7, s_state#8] + +(35) Expand [codegen id : 8] +Input [3]: [ss_net_profit#2, s_state#8, s_county#7] +Arguments: [[ss_net_profit#2, s_state#8, s_county#7, 0], [ss_net_profit#2, s_state#8, null, 1], [ss_net_profit#2, null, null, 3]], [ss_net_profit#2, s_state#21, s_county#22, spark_grouping_id#23] + +(36) HashAggregate [codegen id : 8] +Input [4]: [ss_net_profit#2, s_state#21, s_county#22, spark_grouping_id#23] +Keys [3]: [s_state#21, s_county#22, spark_grouping_id#23] +Functions [1]: [partial_sum(UnscaledValue(ss_net_profit#2))] +Aggregate Attributes [1]: [sum#24] +Results [4]: [s_state#21, s_county#22, spark_grouping_id#23, sum#25] + +(37) Exchange +Input [4]: [s_state#21, s_county#22, spark_grouping_id#23, sum#25] +Arguments: hashpartitioning(s_state#21, s_county#22, spark_grouping_id#23, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(38) HashAggregate [codegen id : 9] +Input [4]: [s_state#21, s_county#22, spark_grouping_id#23, sum#25] +Keys [3]: [s_state#21, s_county#22, spark_grouping_id#23] +Functions [1]: [sum(UnscaledValue(ss_net_profit#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_profit#2))#26] +Results [7]: [MakeDecimal(sum(UnscaledValue(ss_net_profit#2))#26,17,2) AS total_sum#27, s_state#21, s_county#22, (cast((shiftright(spark_grouping_id#23, 1) & 1) as tinyint) + cast((shiftright(spark_grouping_id#23, 0) & 1) as tinyint)) AS lochierarchy#28, MakeDecimal(sum(UnscaledValue(ss_net_profit#2))#26,17,2) AS _w0#29, (cast((shiftright(spark_grouping_id#23, 1) & 1) as tinyint) + cast((shiftright(spark_grouping_id#23, 0) & 1) as tinyint)) AS _w1#30, CASE WHEN (cast((shiftright(spark_grouping_id#23, 0) & 1) as tinyint) = 0) THEN s_state#21 END AS _w2#31] + +(39) Exchange +Input [7]: [total_sum#27, s_state#21, s_county#22, lochierarchy#28, _w0#29, _w1#30, _w2#31] +Arguments: hashpartitioning(_w1#30, _w2#31, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(40) Sort [codegen id : 10] +Input [7]: [total_sum#27, s_state#21, s_county#22, lochierarchy#28, _w0#29, _w1#30, _w2#31] +Arguments: [_w1#30 ASC NULLS FIRST, _w2#31 ASC NULLS FIRST, _w0#29 DESC NULLS LAST], false, 0 + +(41) Window +Input [7]: [total_sum#27, s_state#21, s_county#22, lochierarchy#28, _w0#29, _w1#30, _w2#31] +Arguments: [rank(_w0#29) windowspecdefinition(_w1#30, _w2#31, _w0#29 DESC NULLS LAST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rank_within_parent#32], [_w1#30, _w2#31], [_w0#29 DESC NULLS LAST] + +(42) Project [codegen id : 11] +Output [5]: [total_sum#27, s_state#21, s_county#22, lochierarchy#28, rank_within_parent#32] +Input [8]: [total_sum#27, s_state#21, s_county#22, lochierarchy#28, _w0#29, _w1#30, _w2#31, rank_within_parent#32] + +(43) TakeOrderedAndProject +Input [5]: [total_sum#27, s_state#21, s_county#22, lochierarchy#28, rank_within_parent#32] +Arguments: 100, [lochierarchy#28 DESC NULLS LAST, CASE WHEN (lochierarchy#28 = 0) THEN s_state#21 END ASC NULLS FIRST, rank_within_parent#32 ASC NULLS FIRST], [total_sum#27, s_state#21, s_county#22, lochierarchy#28, rank_within_parent#32] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (48) ++- * ColumnarToRow (47) + +- CometProject (46) + +- CometFilter (45) + +- CometScan parquet spark_catalog.default.date_dim (44) + + +(44) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#5, d_month_seq#33] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)] +ReadSchema: struct + +(45) CometFilter +Input [2]: [d_date_sk#5, d_month_seq#33] +Condition : (((isnotnull(d_month_seq#33) AND (d_month_seq#33 >= 1200)) AND (d_month_seq#33 <= 1211)) AND isnotnull(d_date_sk#5)) + +(46) CometProject +Input [2]: [d_date_sk#5, d_month_seq#33] +Arguments: [d_date_sk#5], [d_date_sk#5] + +(47) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#5] + +(48) BroadcastExchange +Input [1]: [d_date_sk#5] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +Subquery:2 Hosting operator id = 10 Hosting Expression = ss_sold_date_sk#11 IN dynamicpruning#4 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q70/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q70/simplified.txt new file mode 100644 index 0000000000..268af2e2f3 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q70/simplified.txt @@ -0,0 +1,75 @@ +TakeOrderedAndProject [lochierarchy,s_state,rank_within_parent,total_sum,s_county] + WholeStageCodegen (11) + Project [total_sum,s_state,s_county,lochierarchy,rank_within_parent] + InputAdapter + Window [_w0,_w1,_w2] + WholeStageCodegen (10) + Sort [_w1,_w2,_w0] + InputAdapter + Exchange [_w1,_w2] #1 + WholeStageCodegen (9) + HashAggregate [s_state,s_county,spark_grouping_id,sum] [sum(UnscaledValue(ss_net_profit)),total_sum,lochierarchy,_w0,_w1,_w2,sum] + InputAdapter + Exchange [s_state,s_county,spark_grouping_id] #2 + WholeStageCodegen (8) + HashAggregate [s_state,s_county,spark_grouping_id,ss_net_profit] [sum,sum] + Expand [ss_net_profit,s_state,s_county] + Project [ss_net_profit,s_state,s_county] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_store_sk,ss_net_profit] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_store_sk,ss_net_profit,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_month_seq,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (7) + BroadcastHashJoin [s_state,s_state] + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk,s_county,s_state] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (6) + Project [s_state] + Filter [ranking] + InputAdapter + Window [_w0,s_state] + WindowGroupLimit [s_state,_w0] + WholeStageCodegen (5) + Sort [s_state,_w0] + HashAggregate [sum] [sum(UnscaledValue(ss_net_profit)),_w0,s_state,sum] + InputAdapter + Exchange [s_state] #6 + WholeStageCodegen (4) + HashAggregate [s_state,ss_net_profit] [sum,sum] + Project [ss_net_profit,s_state] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_net_profit,ss_sold_date_sk,s_state] + BroadcastHashJoin [ss_store_sk,s_store_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_store_sk,ss_net_profit,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk,s_state] + InputAdapter + ReusedExchange [d_date_sk] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q71/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q71/explain.txt new file mode 100644 index 0000000000..624103b664 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q71/explain.txt @@ -0,0 +1,254 @@ +== Physical Plan == +* Sort (38) ++- Exchange (37) + +- * HashAggregate (36) + +- Exchange (35) + +- * HashAggregate (34) + +- * Project (33) + +- * BroadcastHashJoin Inner BuildRight (32) + :- * Project (26) + : +- * BroadcastHashJoin Inner BuildLeft (25) + : :- BroadcastExchange (5) + : : +- * ColumnarToRow (4) + : : +- CometProject (3) + : : +- CometFilter (2) + : : +- CometScan parquet spark_catalog.default.item (1) + : +- Union (24) + : :- * Project (11) + : : +- * BroadcastHashJoin Inner BuildRight (10) + : : :- * ColumnarToRow (8) + : : : +- CometFilter (7) + : : : +- CometScan parquet spark_catalog.default.web_sales (6) + : : +- ReusedExchange (9) + : :- * Project (17) + : : +- * BroadcastHashJoin Inner BuildRight (16) + : : :- * ColumnarToRow (14) + : : : +- CometFilter (13) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (12) + : : +- ReusedExchange (15) + : +- * Project (23) + : +- * BroadcastHashJoin Inner BuildRight (22) + : :- * ColumnarToRow (20) + : : +- CometFilter (19) + : : +- CometScan parquet spark_catalog.default.store_sales (18) + : +- ReusedExchange (21) + +- BroadcastExchange (31) + +- * ColumnarToRow (30) + +- CometProject (29) + +- CometFilter (28) + +- CometScan parquet spark_catalog.default.time_dim (27) + + +(1) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#1, i_brand_id#2, i_brand#3, i_manager_id#4] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_manager_id), EqualTo(i_manager_id,1), IsNotNull(i_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [4]: [i_item_sk#1, i_brand_id#2, i_brand#3, i_manager_id#4] +Condition : ((isnotnull(i_manager_id#4) AND (i_manager_id#4 = 1)) AND isnotnull(i_item_sk#1)) + +(3) CometProject +Input [4]: [i_item_sk#1, i_brand_id#2, i_brand#3, i_manager_id#4] +Arguments: [i_item_sk#1, i_brand_id#2, i_brand#3], [i_item_sk#1, i_brand_id#2, i_brand#3] + +(4) ColumnarToRow [codegen id : 1] +Input [3]: [i_item_sk#1, i_brand_id#2, i_brand#3] + +(5) BroadcastExchange +Input [3]: [i_item_sk#1, i_brand_id#2, i_brand#3] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(6) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_sold_time_sk#5, ws_item_sk#6, ws_ext_sales_price#7, ws_sold_date_sk#8] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#8), dynamicpruningexpression(ws_sold_date_sk#8 IN dynamicpruning#9)] +PushedFilters: [IsNotNull(ws_item_sk), IsNotNull(ws_sold_time_sk)] +ReadSchema: struct + +(7) CometFilter +Input [4]: [ws_sold_time_sk#5, ws_item_sk#6, ws_ext_sales_price#7, ws_sold_date_sk#8] +Condition : (isnotnull(ws_item_sk#6) AND isnotnull(ws_sold_time_sk#5)) + +(8) ColumnarToRow [codegen id : 3] +Input [4]: [ws_sold_time_sk#5, ws_item_sk#6, ws_ext_sales_price#7, ws_sold_date_sk#8] + +(9) ReusedExchange [Reuses operator id: 43] +Output [1]: [d_date_sk#10] + +(10) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ws_sold_date_sk#8] +Right keys [1]: [d_date_sk#10] +Join type: Inner +Join condition: None + +(11) Project [codegen id : 3] +Output [3]: [ws_ext_sales_price#7 AS ext_price#11, ws_item_sk#6 AS sold_item_sk#12, ws_sold_time_sk#5 AS time_sk#13] +Input [5]: [ws_sold_time_sk#5, ws_item_sk#6, ws_ext_sales_price#7, ws_sold_date_sk#8, d_date_sk#10] + +(12) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_sold_time_sk#14, cs_item_sk#15, cs_ext_sales_price#16, cs_sold_date_sk#17] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#17), dynamicpruningexpression(cs_sold_date_sk#17 IN dynamicpruning#18)] +PushedFilters: [IsNotNull(cs_item_sk), IsNotNull(cs_sold_time_sk)] +ReadSchema: struct + +(13) CometFilter +Input [4]: [cs_sold_time_sk#14, cs_item_sk#15, cs_ext_sales_price#16, cs_sold_date_sk#17] +Condition : (isnotnull(cs_item_sk#15) AND isnotnull(cs_sold_time_sk#14)) + +(14) ColumnarToRow [codegen id : 5] +Input [4]: [cs_sold_time_sk#14, cs_item_sk#15, cs_ext_sales_price#16, cs_sold_date_sk#17] + +(15) ReusedExchange [Reuses operator id: 43] +Output [1]: [d_date_sk#19] + +(16) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [cs_sold_date_sk#17] +Right keys [1]: [d_date_sk#19] +Join type: Inner +Join condition: None + +(17) Project [codegen id : 5] +Output [3]: [cs_ext_sales_price#16 AS ext_price#20, cs_item_sk#15 AS sold_item_sk#21, cs_sold_time_sk#14 AS time_sk#22] +Input [5]: [cs_sold_time_sk#14, cs_item_sk#15, cs_ext_sales_price#16, cs_sold_date_sk#17, d_date_sk#19] + +(18) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_sold_time_sk#23, ss_item_sk#24, ss_ext_sales_price#25, ss_sold_date_sk#26] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#26), dynamicpruningexpression(ss_sold_date_sk#26 IN dynamicpruning#27)] +PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_sold_time_sk)] +ReadSchema: struct + +(19) CometFilter +Input [4]: [ss_sold_time_sk#23, ss_item_sk#24, ss_ext_sales_price#25, ss_sold_date_sk#26] +Condition : (isnotnull(ss_item_sk#24) AND isnotnull(ss_sold_time_sk#23)) + +(20) ColumnarToRow [codegen id : 7] +Input [4]: [ss_sold_time_sk#23, ss_item_sk#24, ss_ext_sales_price#25, ss_sold_date_sk#26] + +(21) ReusedExchange [Reuses operator id: 43] +Output [1]: [d_date_sk#28] + +(22) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [ss_sold_date_sk#26] +Right keys [1]: [d_date_sk#28] +Join type: Inner +Join condition: None + +(23) Project [codegen id : 7] +Output [3]: [ss_ext_sales_price#25 AS ext_price#29, ss_item_sk#24 AS sold_item_sk#30, ss_sold_time_sk#23 AS time_sk#31] +Input [5]: [ss_sold_time_sk#23, ss_item_sk#24, ss_ext_sales_price#25, ss_sold_date_sk#26, d_date_sk#28] + +(24) Union + +(25) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [i_item_sk#1] +Right keys [1]: [sold_item_sk#12] +Join type: Inner +Join condition: None + +(26) Project [codegen id : 9] +Output [4]: [i_brand_id#2, i_brand#3, ext_price#11, time_sk#13] +Input [6]: [i_item_sk#1, i_brand_id#2, i_brand#3, ext_price#11, sold_item_sk#12, time_sk#13] + +(27) Scan parquet spark_catalog.default.time_dim +Output [4]: [t_time_sk#32, t_hour#33, t_minute#34, t_meal_time#35] +Batched: true +Location [not included in comparison]/{warehouse_dir}/time_dim] +PushedFilters: [Or(EqualTo(t_meal_time,breakfast ),EqualTo(t_meal_time,dinner )), IsNotNull(t_time_sk)] +ReadSchema: struct + +(28) CometFilter +Input [4]: [t_time_sk#32, t_hour#33, t_minute#34, t_meal_time#35] +Condition : (((t_meal_time#35 = breakfast ) OR (t_meal_time#35 = dinner )) AND isnotnull(t_time_sk#32)) + +(29) CometProject +Input [4]: [t_time_sk#32, t_hour#33, t_minute#34, t_meal_time#35] +Arguments: [t_time_sk#32, t_hour#33, t_minute#34], [t_time_sk#32, t_hour#33, t_minute#34] + +(30) ColumnarToRow [codegen id : 8] +Input [3]: [t_time_sk#32, t_hour#33, t_minute#34] + +(31) BroadcastExchange +Input [3]: [t_time_sk#32, t_hour#33, t_minute#34] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(32) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [time_sk#13] +Right keys [1]: [t_time_sk#32] +Join type: Inner +Join condition: None + +(33) Project [codegen id : 9] +Output [5]: [i_brand_id#2, i_brand#3, ext_price#11, t_hour#33, t_minute#34] +Input [7]: [i_brand_id#2, i_brand#3, ext_price#11, time_sk#13, t_time_sk#32, t_hour#33, t_minute#34] + +(34) HashAggregate [codegen id : 9] +Input [5]: [i_brand_id#2, i_brand#3, ext_price#11, t_hour#33, t_minute#34] +Keys [4]: [i_brand#3, i_brand_id#2, t_hour#33, t_minute#34] +Functions [1]: [partial_sum(UnscaledValue(ext_price#11))] +Aggregate Attributes [1]: [sum#36] +Results [5]: [i_brand#3, i_brand_id#2, t_hour#33, t_minute#34, sum#37] + +(35) Exchange +Input [5]: [i_brand#3, i_brand_id#2, t_hour#33, t_minute#34, sum#37] +Arguments: hashpartitioning(i_brand#3, i_brand_id#2, t_hour#33, t_minute#34, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(36) HashAggregate [codegen id : 10] +Input [5]: [i_brand#3, i_brand_id#2, t_hour#33, t_minute#34, sum#37] +Keys [4]: [i_brand#3, i_brand_id#2, t_hour#33, t_minute#34] +Functions [1]: [sum(UnscaledValue(ext_price#11))] +Aggregate Attributes [1]: [sum(UnscaledValue(ext_price#11))#38] +Results [5]: [i_brand_id#2 AS brand_id#39, i_brand#3 AS brand#40, t_hour#33, t_minute#34, MakeDecimal(sum(UnscaledValue(ext_price#11))#38,17,2) AS ext_price#41] + +(37) Exchange +Input [5]: [brand_id#39, brand#40, t_hour#33, t_minute#34, ext_price#41] +Arguments: rangepartitioning(ext_price#41 DESC NULLS LAST, brand_id#39 ASC NULLS FIRST, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(38) Sort [codegen id : 11] +Input [5]: [brand_id#39, brand#40, t_hour#33, t_minute#34, ext_price#41] +Arguments: [ext_price#41 DESC NULLS LAST, brand_id#39 ASC NULLS FIRST], true, 0 + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 6 Hosting Expression = ws_sold_date_sk#8 IN dynamicpruning#9 +BroadcastExchange (43) ++- * ColumnarToRow (42) + +- CometProject (41) + +- CometFilter (40) + +- CometScan parquet spark_catalog.default.date_dim (39) + + +(39) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#10, d_year#42, d_moy#43] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), EqualTo(d_moy,11), EqualTo(d_year,1999), IsNotNull(d_date_sk)] +ReadSchema: struct + +(40) CometFilter +Input [3]: [d_date_sk#10, d_year#42, d_moy#43] +Condition : ((((isnotnull(d_moy#43) AND isnotnull(d_year#42)) AND (d_moy#43 = 11)) AND (d_year#42 = 1999)) AND isnotnull(d_date_sk#10)) + +(41) CometProject +Input [3]: [d_date_sk#10, d_year#42, d_moy#43] +Arguments: [d_date_sk#10], [d_date_sk#10] + +(42) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#10] + +(43) BroadcastExchange +Input [1]: [d_date_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +Subquery:2 Hosting operator id = 12 Hosting Expression = cs_sold_date_sk#17 IN dynamicpruning#9 + +Subquery:3 Hosting operator id = 18 Hosting Expression = ss_sold_date_sk#26 IN dynamicpruning#9 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q71/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q71/simplified.txt new file mode 100644 index 0000000000..bea5376a00 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q71/simplified.txt @@ -0,0 +1,69 @@ +WholeStageCodegen (11) + Sort [ext_price,brand_id] + InputAdapter + Exchange [ext_price,brand_id] #1 + WholeStageCodegen (10) + HashAggregate [i_brand,i_brand_id,t_hour,t_minute,sum] [sum(UnscaledValue(ext_price)),brand_id,brand,ext_price,sum] + InputAdapter + Exchange [i_brand,i_brand_id,t_hour,t_minute] #2 + WholeStageCodegen (9) + HashAggregate [i_brand,i_brand_id,t_hour,t_minute,ext_price] [sum,sum] + Project [i_brand_id,i_brand,ext_price,t_hour,t_minute] + BroadcastHashJoin [time_sk,t_time_sk] + Project [i_brand_id,i_brand,ext_price,time_sk] + BroadcastHashJoin [i_item_sk,sold_item_sk] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [i_item_sk,i_brand_id,i_brand] + CometFilter [i_manager_id,i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_brand,i_manager_id] + InputAdapter + Union + WholeStageCodegen (3) + Project [ws_ext_sales_price,ws_item_sk,ws_sold_time_sk] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk,ws_sold_time_sk] + CometScan parquet spark_catalog.default.web_sales [ws_sold_time_sk,ws_item_sk,ws_ext_sales_price,ws_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_moy,d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + ReusedExchange [d_date_sk] #4 + WholeStageCodegen (5) + Project [cs_ext_sales_price,cs_item_sk,cs_sold_time_sk] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk,cs_sold_time_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_sold_time_sk,cs_item_sk,cs_ext_sales_price,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #4 + WholeStageCodegen (7) + Project [ss_ext_sales_price,ss_item_sk,ss_sold_time_sk] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk,ss_sold_time_sk] + CometScan parquet spark_catalog.default.store_sales [ss_sold_time_sk,ss_item_sk,ss_ext_sales_price,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (8) + ColumnarToRow + InputAdapter + CometProject [t_time_sk,t_hour,t_minute] + CometFilter [t_meal_time,t_time_sk] + CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour,t_minute,t_meal_time] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q72/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q72/explain.txt new file mode 100644 index 0000000000..4e5d9e9f60 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q72/explain.txt @@ -0,0 +1,433 @@ +== Physical Plan == +TakeOrderedAndProject (70) ++- * HashAggregate (69) + +- Exchange (68) + +- * HashAggregate (67) + +- * Project (66) + +- * SortMergeJoin LeftOuter (65) + :- * Sort (58) + : +- Exchange (57) + : +- * Project (56) + : +- * BroadcastHashJoin LeftOuter BuildRight (55) + : :- * Project (50) + : : +- * BroadcastHashJoin Inner BuildRight (49) + : : :- * Project (44) + : : : +- * BroadcastHashJoin Inner BuildRight (43) + : : : :- * Project (38) + : : : : +- * BroadcastHashJoin Inner BuildRight (37) + : : : : :- * Project (35) + : : : : : +- * BroadcastHashJoin Inner BuildRight (34) + : : : : : :- * Project (28) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (27) + : : : : : : :- * Project (21) + : : : : : : : +- * BroadcastHashJoin Inner BuildRight (20) + : : : : : : : :- * Project (15) + : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (14) + : : : : : : : : :- * Project (9) + : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : : : : : : :- * ColumnarToRow (3) + : : : : : : : : : : +- CometFilter (2) + : : : : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) + : : : : : : : : : +- BroadcastExchange (7) + : : : : : : : : : +- * ColumnarToRow (6) + : : : : : : : : : +- CometFilter (5) + : : : : : : : : : +- CometScan parquet spark_catalog.default.inventory (4) + : : : : : : : : +- BroadcastExchange (13) + : : : : : : : : +- * ColumnarToRow (12) + : : : : : : : : +- CometFilter (11) + : : : : : : : : +- CometScan parquet spark_catalog.default.warehouse (10) + : : : : : : : +- BroadcastExchange (19) + : : : : : : : +- * ColumnarToRow (18) + : : : : : : : +- CometFilter (17) + : : : : : : : +- CometScan parquet spark_catalog.default.item (16) + : : : : : : +- BroadcastExchange (26) + : : : : : : +- * ColumnarToRow (25) + : : : : : : +- CometProject (24) + : : : : : : +- CometFilter (23) + : : : : : : +- CometScan parquet spark_catalog.default.customer_demographics (22) + : : : : : +- BroadcastExchange (33) + : : : : : +- * ColumnarToRow (32) + : : : : : +- CometProject (31) + : : : : : +- CometFilter (30) + : : : : : +- CometScan parquet spark_catalog.default.household_demographics (29) + : : : : +- ReusedExchange (36) + : : : +- BroadcastExchange (42) + : : : +- * ColumnarToRow (41) + : : : +- CometFilter (40) + : : : +- CometScan parquet spark_catalog.default.date_dim (39) + : : +- BroadcastExchange (48) + : : +- * ColumnarToRow (47) + : : +- CometFilter (46) + : : +- CometScan parquet spark_catalog.default.date_dim (45) + : +- BroadcastExchange (54) + : +- * ColumnarToRow (53) + : +- CometFilter (52) + : +- CometScan parquet spark_catalog.default.promotion (51) + +- * Sort (64) + +- Exchange (63) + +- * ColumnarToRow (62) + +- CometProject (61) + +- CometFilter (60) + +- CometScan parquet spark_catalog.default.catalog_returns (59) + + +(1) Scan parquet spark_catalog.default.catalog_sales +Output [8]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_quantity#7, cs_sold_date_sk#8] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#8), dynamicpruningexpression(cs_sold_date_sk#8 IN dynamicpruning#9)] +PushedFilters: [IsNotNull(cs_quantity), IsNotNull(cs_item_sk), IsNotNull(cs_bill_cdemo_sk), IsNotNull(cs_bill_hdemo_sk), IsNotNull(cs_ship_date_sk)] +ReadSchema: struct + +(2) CometFilter +Input [8]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_quantity#7, cs_sold_date_sk#8] +Condition : ((((isnotnull(cs_quantity#7) AND isnotnull(cs_item_sk#4)) AND isnotnull(cs_bill_cdemo_sk#2)) AND isnotnull(cs_bill_hdemo_sk#3)) AND isnotnull(cs_ship_date_sk#1)) + +(3) ColumnarToRow [codegen id : 10] +Input [8]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_quantity#7, cs_sold_date_sk#8] + +(4) Scan parquet spark_catalog.default.inventory +Output [4]: [inv_item_sk#10, inv_warehouse_sk#11, inv_quantity_on_hand#12, inv_date_sk#13] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(inv_date_sk#13)] +PushedFilters: [IsNotNull(inv_quantity_on_hand), IsNotNull(inv_item_sk), IsNotNull(inv_warehouse_sk)] +ReadSchema: struct + +(5) CometFilter +Input [4]: [inv_item_sk#10, inv_warehouse_sk#11, inv_quantity_on_hand#12, inv_date_sk#13] +Condition : ((isnotnull(inv_quantity_on_hand#12) AND isnotnull(inv_item_sk#10)) AND isnotnull(inv_warehouse_sk#11)) + +(6) ColumnarToRow [codegen id : 1] +Input [4]: [inv_item_sk#10, inv_warehouse_sk#11, inv_quantity_on_hand#12, inv_date_sk#13] + +(7) BroadcastExchange +Input [4]: [inv_item_sk#10, inv_warehouse_sk#11, inv_quantity_on_hand#12, inv_date_sk#13] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_item_sk#4] +Right keys [1]: [inv_item_sk#10] +Join type: Inner +Join condition: (inv_quantity_on_hand#12 < cs_quantity#7) + +(9) Project [codegen id : 10] +Output [9]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_warehouse_sk#11, inv_date_sk#13] +Input [12]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_quantity#7, cs_sold_date_sk#8, inv_item_sk#10, inv_warehouse_sk#11, inv_quantity_on_hand#12, inv_date_sk#13] + +(10) Scan parquet spark_catalog.default.warehouse +Output [2]: [w_warehouse_sk#14, w_warehouse_name#15] +Batched: true +Location [not included in comparison]/{warehouse_dir}/warehouse] +PushedFilters: [IsNotNull(w_warehouse_sk)] +ReadSchema: struct + +(11) CometFilter +Input [2]: [w_warehouse_sk#14, w_warehouse_name#15] +Condition : isnotnull(w_warehouse_sk#14) + +(12) ColumnarToRow [codegen id : 2] +Input [2]: [w_warehouse_sk#14, w_warehouse_name#15] + +(13) BroadcastExchange +Input [2]: [w_warehouse_sk#14, w_warehouse_name#15] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(14) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [inv_warehouse_sk#11] +Right keys [1]: [w_warehouse_sk#14] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 10] +Output [9]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15] +Input [11]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_warehouse_sk#11, inv_date_sk#13, w_warehouse_sk#14, w_warehouse_name#15] + +(16) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#16, i_item_desc#17] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(17) CometFilter +Input [2]: [i_item_sk#16, i_item_desc#17] +Condition : isnotnull(i_item_sk#16) + +(18) ColumnarToRow [codegen id : 3] +Input [2]: [i_item_sk#16, i_item_desc#17] + +(19) BroadcastExchange +Input [2]: [i_item_sk#16, i_item_desc#17] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(20) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_item_sk#4] +Right keys [1]: [i_item_sk#16] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 10] +Output [10]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17] +Input [11]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15, i_item_sk#16, i_item_desc#17] + +(22) Scan parquet spark_catalog.default.customer_demographics +Output [2]: [cd_demo_sk#18, cd_marital_status#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_marital_status), EqualTo(cd_marital_status,D), IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(23) CometFilter +Input [2]: [cd_demo_sk#18, cd_marital_status#19] +Condition : ((isnotnull(cd_marital_status#19) AND (cd_marital_status#19 = D)) AND isnotnull(cd_demo_sk#18)) + +(24) CometProject +Input [2]: [cd_demo_sk#18, cd_marital_status#19] +Arguments: [cd_demo_sk#18], [cd_demo_sk#18] + +(25) ColumnarToRow [codegen id : 4] +Input [1]: [cd_demo_sk#18] + +(26) BroadcastExchange +Input [1]: [cd_demo_sk#18] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(27) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_bill_cdemo_sk#2] +Right keys [1]: [cd_demo_sk#18] +Join type: Inner +Join condition: None + +(28) Project [codegen id : 10] +Output [9]: [cs_ship_date_sk#1, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17] +Input [11]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17, cd_demo_sk#18] + +(29) Scan parquet spark_catalog.default.household_demographics +Output [2]: [hd_demo_sk#20, hd_buy_potential#21] +Batched: true +Location [not included in comparison]/{warehouse_dir}/household_demographics] +PushedFilters: [IsNotNull(hd_buy_potential), EqualTo(hd_buy_potential,>10000 ), IsNotNull(hd_demo_sk)] +ReadSchema: struct + +(30) CometFilter +Input [2]: [hd_demo_sk#20, hd_buy_potential#21] +Condition : ((isnotnull(hd_buy_potential#21) AND (hd_buy_potential#21 = >10000 )) AND isnotnull(hd_demo_sk#20)) + +(31) CometProject +Input [2]: [hd_demo_sk#20, hd_buy_potential#21] +Arguments: [hd_demo_sk#20], [hd_demo_sk#20] + +(32) ColumnarToRow [codegen id : 5] +Input [1]: [hd_demo_sk#20] + +(33) BroadcastExchange +Input [1]: [hd_demo_sk#20] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +(34) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_bill_hdemo_sk#3] +Right keys [1]: [hd_demo_sk#20] +Join type: Inner +Join condition: None + +(35) Project [codegen id : 10] +Output [8]: [cs_ship_date_sk#1, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17] +Input [10]: [cs_ship_date_sk#1, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17, hd_demo_sk#20] + +(36) ReusedExchange [Reuses operator id: 75] +Output [3]: [d_date_sk#22, d_date#23, d_week_seq#24] + +(37) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_sold_date_sk#8] +Right keys [1]: [d_date_sk#22] +Join type: Inner +Join condition: None + +(38) Project [codegen id : 10] +Output [9]: [cs_ship_date_sk#1, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17, d_date#23, d_week_seq#24] +Input [11]: [cs_ship_date_sk#1, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17, d_date_sk#22, d_date#23, d_week_seq#24] + +(39) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#25, d_week_seq#26] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_week_seq), IsNotNull(d_date_sk)] +ReadSchema: struct + +(40) CometFilter +Input [2]: [d_date_sk#25, d_week_seq#26] +Condition : (isnotnull(d_week_seq#26) AND isnotnull(d_date_sk#25)) + +(41) ColumnarToRow [codegen id : 7] +Input [2]: [d_date_sk#25, d_week_seq#26] + +(42) BroadcastExchange +Input [2]: [d_date_sk#25, d_week_seq#26] +Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[1, int, false] as bigint), 32) | (cast(input[0, int, false] as bigint) & 4294967295))),false), [plan_id=6] + +(43) BroadcastHashJoin [codegen id : 10] +Left keys [2]: [d_week_seq#24, inv_date_sk#13] +Right keys [2]: [d_week_seq#26, d_date_sk#25] +Join type: Inner +Join condition: None + +(44) Project [codegen id : 10] +Output [8]: [cs_ship_date_sk#1, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_date#23, d_week_seq#24] +Input [11]: [cs_ship_date_sk#1, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17, d_date#23, d_week_seq#24, d_date_sk#25, d_week_seq#26] + +(45) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#27, d_date#28] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), IsNotNull(d_date_sk)] +ReadSchema: struct + +(46) CometFilter +Input [2]: [d_date_sk#27, d_date#28] +Condition : (isnotnull(d_date#28) AND isnotnull(d_date_sk#27)) + +(47) ColumnarToRow [codegen id : 8] +Input [2]: [d_date_sk#27, d_date#28] + +(48) BroadcastExchange +Input [2]: [d_date_sk#27, d_date#28] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=7] + +(49) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_ship_date_sk#1] +Right keys [1]: [d_date_sk#27] +Join type: Inner +Join condition: (d_date#28 > date_add(d_date#23, 5)) + +(50) Project [codegen id : 10] +Output [6]: [cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_week_seq#24] +Input [10]: [cs_ship_date_sk#1, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_date#23, d_week_seq#24, d_date_sk#27, d_date#28] + +(51) Scan parquet spark_catalog.default.promotion +Output [1]: [p_promo_sk#29] +Batched: true +Location [not included in comparison]/{warehouse_dir}/promotion] +PushedFilters: [IsNotNull(p_promo_sk)] +ReadSchema: struct + +(52) CometFilter +Input [1]: [p_promo_sk#29] +Condition : isnotnull(p_promo_sk#29) + +(53) ColumnarToRow [codegen id : 9] +Input [1]: [p_promo_sk#29] + +(54) BroadcastExchange +Input [1]: [p_promo_sk#29] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8] + +(55) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_promo_sk#5] +Right keys [1]: [p_promo_sk#29] +Join type: LeftOuter +Join condition: None + +(56) Project [codegen id : 10] +Output [5]: [cs_item_sk#4, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_week_seq#24] +Input [7]: [cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_week_seq#24, p_promo_sk#29] + +(57) Exchange +Input [5]: [cs_item_sk#4, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_week_seq#24] +Arguments: hashpartitioning(cs_item_sk#4, cs_order_number#6, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(58) Sort [codegen id : 11] +Input [5]: [cs_item_sk#4, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_week_seq#24] +Arguments: [cs_item_sk#4 ASC NULLS FIRST, cs_order_number#6 ASC NULLS FIRST], false, 0 + +(59) Scan parquet spark_catalog.default.catalog_returns +Output [3]: [cr_item_sk#30, cr_order_number#31, cr_returned_date_sk#32] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_returns] +PushedFilters: [IsNotNull(cr_item_sk), IsNotNull(cr_order_number)] +ReadSchema: struct + +(60) CometFilter +Input [3]: [cr_item_sk#30, cr_order_number#31, cr_returned_date_sk#32] +Condition : (isnotnull(cr_item_sk#30) AND isnotnull(cr_order_number#31)) + +(61) CometProject +Input [3]: [cr_item_sk#30, cr_order_number#31, cr_returned_date_sk#32] +Arguments: [cr_item_sk#30, cr_order_number#31], [cr_item_sk#30, cr_order_number#31] + +(62) ColumnarToRow [codegen id : 12] +Input [2]: [cr_item_sk#30, cr_order_number#31] + +(63) Exchange +Input [2]: [cr_item_sk#30, cr_order_number#31] +Arguments: hashpartitioning(cr_item_sk#30, cr_order_number#31, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(64) Sort [codegen id : 13] +Input [2]: [cr_item_sk#30, cr_order_number#31] +Arguments: [cr_item_sk#30 ASC NULLS FIRST, cr_order_number#31 ASC NULLS FIRST], false, 0 + +(65) SortMergeJoin [codegen id : 14] +Left keys [2]: [cs_item_sk#4, cs_order_number#6] +Right keys [2]: [cr_item_sk#30, cr_order_number#31] +Join type: LeftOuter +Join condition: None + +(66) Project [codegen id : 14] +Output [3]: [w_warehouse_name#15, i_item_desc#17, d_week_seq#24] +Input [7]: [cs_item_sk#4, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_week_seq#24, cr_item_sk#30, cr_order_number#31] + +(67) HashAggregate [codegen id : 14] +Input [3]: [w_warehouse_name#15, i_item_desc#17, d_week_seq#24] +Keys [3]: [i_item_desc#17, w_warehouse_name#15, d_week_seq#24] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#33] +Results [4]: [i_item_desc#17, w_warehouse_name#15, d_week_seq#24, count#34] + +(68) Exchange +Input [4]: [i_item_desc#17, w_warehouse_name#15, d_week_seq#24, count#34] +Arguments: hashpartitioning(i_item_desc#17, w_warehouse_name#15, d_week_seq#24, 5), ENSURE_REQUIREMENTS, [plan_id=11] + +(69) HashAggregate [codegen id : 15] +Input [4]: [i_item_desc#17, w_warehouse_name#15, d_week_seq#24, count#34] +Keys [3]: [i_item_desc#17, w_warehouse_name#15, d_week_seq#24] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#35] +Results [6]: [i_item_desc#17, w_warehouse_name#15, d_week_seq#24, count(1)#35 AS no_promo#36, count(1)#35 AS promo#37, count(1)#35 AS total_cnt#38] + +(70) TakeOrderedAndProject +Input [6]: [i_item_desc#17, w_warehouse_name#15, d_week_seq#24, no_promo#36, promo#37, total_cnt#38] +Arguments: 100, [total_cnt#38 DESC NULLS LAST, i_item_desc#17 ASC NULLS FIRST, w_warehouse_name#15 ASC NULLS FIRST, d_week_seq#24 ASC NULLS FIRST], [i_item_desc#17, w_warehouse_name#15, d_week_seq#24, no_promo#36, promo#37, total_cnt#38] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#8 IN dynamicpruning#9 +BroadcastExchange (75) ++- * ColumnarToRow (74) + +- CometProject (73) + +- CometFilter (72) + +- CometScan parquet spark_catalog.default.date_dim (71) + + +(71) Scan parquet spark_catalog.default.date_dim +Output [4]: [d_date_sk#22, d_date#23, d_week_seq#24, d_year#39] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,1999), IsNotNull(d_date_sk), IsNotNull(d_week_seq), IsNotNull(d_date)] +ReadSchema: struct + +(72) CometFilter +Input [4]: [d_date_sk#22, d_date#23, d_week_seq#24, d_year#39] +Condition : ((((isnotnull(d_year#39) AND (d_year#39 = 1999)) AND isnotnull(d_date_sk#22)) AND isnotnull(d_week_seq#24)) AND isnotnull(d_date#23)) + +(73) CometProject +Input [4]: [d_date_sk#22, d_date#23, d_week_seq#24, d_year#39] +Arguments: [d_date_sk#22, d_date#23, d_week_seq#24], [d_date_sk#22, d_date#23, d_week_seq#24] + +(74) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#22, d_date#23, d_week_seq#24] + +(75) BroadcastExchange +Input [3]: [d_date_sk#22, d_date#23, d_week_seq#24] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=12] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q72/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q72/simplified.txt new file mode 100644 index 0000000000..17fc9dee7e --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q72/simplified.txt @@ -0,0 +1,116 @@ +TakeOrderedAndProject [total_cnt,i_item_desc,w_warehouse_name,d_week_seq,no_promo,promo] + WholeStageCodegen (15) + HashAggregate [i_item_desc,w_warehouse_name,d_week_seq,count] [count(1),no_promo,promo,total_cnt,count] + InputAdapter + Exchange [i_item_desc,w_warehouse_name,d_week_seq] #1 + WholeStageCodegen (14) + HashAggregate [i_item_desc,w_warehouse_name,d_week_seq] [count,count] + Project [w_warehouse_name,i_item_desc,d_week_seq] + SortMergeJoin [cs_item_sk,cs_order_number,cr_item_sk,cr_order_number] + InputAdapter + WholeStageCodegen (11) + Sort [cs_item_sk,cs_order_number] + InputAdapter + Exchange [cs_item_sk,cs_order_number] #2 + WholeStageCodegen (10) + Project [cs_item_sk,cs_order_number,w_warehouse_name,i_item_desc,d_week_seq] + BroadcastHashJoin [cs_promo_sk,p_promo_sk] + Project [cs_item_sk,cs_promo_sk,cs_order_number,w_warehouse_name,i_item_desc,d_week_seq] + BroadcastHashJoin [cs_ship_date_sk,d_date_sk,d_date,d_date] + Project [cs_ship_date_sk,cs_item_sk,cs_promo_sk,cs_order_number,w_warehouse_name,i_item_desc,d_date,d_week_seq] + BroadcastHashJoin [d_week_seq,inv_date_sk,d_week_seq,d_date_sk] + Project [cs_ship_date_sk,cs_item_sk,cs_promo_sk,cs_order_number,inv_date_sk,w_warehouse_name,i_item_desc,d_date,d_week_seq] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_ship_date_sk,cs_item_sk,cs_promo_sk,cs_order_number,cs_sold_date_sk,inv_date_sk,w_warehouse_name,i_item_desc] + BroadcastHashJoin [cs_bill_hdemo_sk,hd_demo_sk] + Project [cs_ship_date_sk,cs_bill_hdemo_sk,cs_item_sk,cs_promo_sk,cs_order_number,cs_sold_date_sk,inv_date_sk,w_warehouse_name,i_item_desc] + BroadcastHashJoin [cs_bill_cdemo_sk,cd_demo_sk] + Project [cs_ship_date_sk,cs_bill_cdemo_sk,cs_bill_hdemo_sk,cs_item_sk,cs_promo_sk,cs_order_number,cs_sold_date_sk,inv_date_sk,w_warehouse_name,i_item_desc] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Project [cs_ship_date_sk,cs_bill_cdemo_sk,cs_bill_hdemo_sk,cs_item_sk,cs_promo_sk,cs_order_number,cs_sold_date_sk,inv_date_sk,w_warehouse_name] + BroadcastHashJoin [inv_warehouse_sk,w_warehouse_sk] + Project [cs_ship_date_sk,cs_bill_cdemo_sk,cs_bill_hdemo_sk,cs_item_sk,cs_promo_sk,cs_order_number,cs_sold_date_sk,inv_warehouse_sk,inv_date_sk] + BroadcastHashJoin [cs_item_sk,inv_item_sk,inv_quantity_on_hand,cs_quantity] + ColumnarToRow + InputAdapter + CometFilter [cs_quantity,cs_item_sk,cs_bill_cdemo_sk,cs_bill_hdemo_sk,cs_ship_date_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_ship_date_sk,cs_bill_cdemo_sk,cs_bill_hdemo_sk,cs_item_sk,cs_promo_sk,cs_order_number,cs_quantity,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_date,d_week_seq] + CometFilter [d_year,d_date_sk,d_week_seq,d_date] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date,d_week_seq,d_year] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [inv_quantity_on_hand,inv_item_sk,inv_warehouse_sk] + CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [w_warehouse_sk] + CometScan parquet spark_catalog.default.warehouse [w_warehouse_sk,w_warehouse_name] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_desc] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (4) + ColumnarToRow + InputAdapter + CometProject [cd_demo_sk] + CometFilter [cd_marital_status,cd_demo_sk] + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_marital_status] + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (5) + ColumnarToRow + InputAdapter + CometProject [hd_demo_sk] + CometFilter [hd_buy_potential,hd_demo_sk] + CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_buy_potential] + InputAdapter + ReusedExchange [d_date_sk,d_date,d_week_seq] #3 + InputAdapter + BroadcastExchange #9 + WholeStageCodegen (7) + ColumnarToRow + InputAdapter + CometFilter [d_week_seq,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_week_seq] + InputAdapter + BroadcastExchange #10 + WholeStageCodegen (8) + ColumnarToRow + InputAdapter + CometFilter [d_date,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (9) + ColumnarToRow + InputAdapter + CometFilter [p_promo_sk] + CometScan parquet spark_catalog.default.promotion [p_promo_sk] + InputAdapter + WholeStageCodegen (13) + Sort [cr_item_sk,cr_order_number] + InputAdapter + Exchange [cr_item_sk,cr_order_number] #12 + WholeStageCodegen (12) + ColumnarToRow + InputAdapter + CometProject [cr_item_sk,cr_order_number] + CometFilter [cr_item_sk,cr_order_number] + CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_returned_date_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q73/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q73/explain.txt new file mode 100644 index 0000000000..ef2c38aea4 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q73/explain.txt @@ -0,0 +1,218 @@ +== Physical Plan == +* Sort (32) ++- Exchange (31) + +- * Project (30) + +- * BroadcastHashJoin Inner BuildRight (29) + :- * Filter (24) + : +- * HashAggregate (23) + : +- Exchange (22) + : +- * HashAggregate (21) + : +- * Project (20) + : +- * BroadcastHashJoin Inner BuildRight (19) + : :- * Project (13) + : : +- * BroadcastHashJoin Inner BuildRight (12) + : : :- * Project (6) + : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- ReusedExchange (4) + : : +- BroadcastExchange (11) + : : +- * ColumnarToRow (10) + : : +- CometProject (9) + : : +- CometFilter (8) + : : +- CometScan parquet spark_catalog.default.store (7) + : +- BroadcastExchange (18) + : +- * ColumnarToRow (17) + : +- CometProject (16) + : +- CometFilter (15) + : +- CometScan parquet spark_catalog.default.household_demographics (14) + +- BroadcastExchange (28) + +- * ColumnarToRow (27) + +- CometFilter (26) + +- CometScan parquet spark_catalog.default.customer (25) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#5), dynamicpruningexpression(ss_sold_date_sk#5 IN dynamicpruning#6)] +PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_hdemo_sk), IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(2) CometFilter +Input [5]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5] +Condition : ((isnotnull(ss_store_sk#3) AND isnotnull(ss_hdemo_sk#2)) AND isnotnull(ss_customer_sk#1)) + +(3) ColumnarToRow [codegen id : 4] +Input [5]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5] + +(4) ReusedExchange [Reuses operator id: 37] +Output [1]: [d_date_sk#7] + +(5) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_date_sk#5] +Right keys [1]: [d_date_sk#7] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 4] +Output [4]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4] +Input [6]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5, d_date_sk#7] + +(7) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#8, s_county#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [In(s_county, [Bronx County,Franklin Parish,Orange County,Williamson County]), IsNotNull(s_store_sk)] +ReadSchema: struct + +(8) CometFilter +Input [2]: [s_store_sk#8, s_county#9] +Condition : (s_county#9 IN (Williamson County,Franklin Parish,Bronx County,Orange County) AND isnotnull(s_store_sk#8)) + +(9) CometProject +Input [2]: [s_store_sk#8, s_county#9] +Arguments: [s_store_sk#8], [s_store_sk#8] + +(10) ColumnarToRow [codegen id : 2] +Input [1]: [s_store_sk#8] + +(11) BroadcastExchange +Input [1]: [s_store_sk#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(12) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_store_sk#3] +Right keys [1]: [s_store_sk#8] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 4] +Output [3]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_ticket_number#4] +Input [5]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, s_store_sk#8] + +(14) Scan parquet spark_catalog.default.household_demographics +Output [4]: [hd_demo_sk#10, hd_buy_potential#11, hd_dep_count#12, hd_vehicle_count#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/household_demographics] +PushedFilters: [IsNotNull(hd_vehicle_count), Or(EqualTo(hd_buy_potential,>10000 ),EqualTo(hd_buy_potential,unknown )), GreaterThan(hd_vehicle_count,0), IsNotNull(hd_demo_sk)] +ReadSchema: struct + +(15) CometFilter +Input [4]: [hd_demo_sk#10, hd_buy_potential#11, hd_dep_count#12, hd_vehicle_count#13] +Condition : ((((isnotnull(hd_vehicle_count#13) AND ((hd_buy_potential#11 = >10000 ) OR (hd_buy_potential#11 = unknown ))) AND (hd_vehicle_count#13 > 0)) AND CASE WHEN (hd_vehicle_count#13 > 0) THEN ((cast(hd_dep_count#12 as double) / cast(hd_vehicle_count#13 as double)) > 1.0) END) AND isnotnull(hd_demo_sk#10)) + +(16) CometProject +Input [4]: [hd_demo_sk#10, hd_buy_potential#11, hd_dep_count#12, hd_vehicle_count#13] +Arguments: [hd_demo_sk#10], [hd_demo_sk#10] + +(17) ColumnarToRow [codegen id : 3] +Input [1]: [hd_demo_sk#10] + +(18) BroadcastExchange +Input [1]: [hd_demo_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(19) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_hdemo_sk#2] +Right keys [1]: [hd_demo_sk#10] +Join type: Inner +Join condition: None + +(20) Project [codegen id : 4] +Output [2]: [ss_customer_sk#1, ss_ticket_number#4] +Input [4]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_ticket_number#4, hd_demo_sk#10] + +(21) HashAggregate [codegen id : 4] +Input [2]: [ss_customer_sk#1, ss_ticket_number#4] +Keys [2]: [ss_ticket_number#4, ss_customer_sk#1] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#14] +Results [3]: [ss_ticket_number#4, ss_customer_sk#1, count#15] + +(22) Exchange +Input [3]: [ss_ticket_number#4, ss_customer_sk#1, count#15] +Arguments: hashpartitioning(ss_ticket_number#4, ss_customer_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(23) HashAggregate [codegen id : 6] +Input [3]: [ss_ticket_number#4, ss_customer_sk#1, count#15] +Keys [2]: [ss_ticket_number#4, ss_customer_sk#1] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#16] +Results [3]: [ss_ticket_number#4, ss_customer_sk#1, count(1)#16 AS cnt#17] + +(24) Filter [codegen id : 6] +Input [3]: [ss_ticket_number#4, ss_customer_sk#1, cnt#17] +Condition : ((cnt#17 >= 1) AND (cnt#17 <= 5)) + +(25) Scan parquet spark_catalog.default.customer +Output [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk)] +ReadSchema: struct + +(26) CometFilter +Input [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] +Condition : isnotnull(c_customer_sk#18) + +(27) ColumnarToRow [codegen id : 5] +Input [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] + +(28) BroadcastExchange +Input [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(29) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_customer_sk#1] +Right keys [1]: [c_customer_sk#18] +Join type: Inner +Join condition: None + +(30) Project [codegen id : 6] +Output [6]: [c_last_name#21, c_first_name#20, c_salutation#19, c_preferred_cust_flag#22, ss_ticket_number#4, cnt#17] +Input [8]: [ss_ticket_number#4, ss_customer_sk#1, cnt#17, c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] + +(31) Exchange +Input [6]: [c_last_name#21, c_first_name#20, c_salutation#19, c_preferred_cust_flag#22, ss_ticket_number#4, cnt#17] +Arguments: rangepartitioning(cnt#17 DESC NULLS LAST, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(32) Sort [codegen id : 7] +Input [6]: [c_last_name#21, c_first_name#20, c_salutation#19, c_preferred_cust_flag#22, ss_ticket_number#4, cnt#17] +Arguments: [cnt#17 DESC NULLS LAST], true, 0 + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6 +BroadcastExchange (37) ++- * ColumnarToRow (36) + +- CometProject (35) + +- CometFilter (34) + +- CometScan parquet spark_catalog.default.date_dim (33) + + +(33) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#7, d_year#23, d_dom#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_dom), GreaterThanOrEqual(d_dom,1), LessThanOrEqual(d_dom,2), In(d_year, [1999,2000,2001]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(34) CometFilter +Input [3]: [d_date_sk#7, d_year#23, d_dom#24] +Condition : ((((isnotnull(d_dom#24) AND (d_dom#24 >= 1)) AND (d_dom#24 <= 2)) AND d_year#23 IN (1999,2000,2001)) AND isnotnull(d_date_sk#7)) + +(35) CometProject +Input [3]: [d_date_sk#7, d_year#23, d_dom#24] +Arguments: [d_date_sk#7], [d_date_sk#7] + +(36) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#7] + +(37) BroadcastExchange +Input [1]: [d_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q73/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q73/simplified.txt new file mode 100644 index 0000000000..7c5ee1ef5a --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q73/simplified.txt @@ -0,0 +1,56 @@ +WholeStageCodegen (7) + Sort [cnt] + InputAdapter + Exchange [cnt] #1 + WholeStageCodegen (6) + Project [c_last_name,c_first_name,c_salutation,c_preferred_cust_flag,ss_ticket_number,cnt] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Filter [cnt] + HashAggregate [ss_ticket_number,ss_customer_sk,count] [count(1),cnt,count] + InputAdapter + Exchange [ss_ticket_number,ss_customer_sk] #2 + WholeStageCodegen (4) + HashAggregate [ss_ticket_number,ss_customer_sk] [count,count] + Project [ss_customer_sk,ss_ticket_number] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + Project [ss_customer_sk,ss_hdemo_sk,ss_ticket_number] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_customer_sk,ss_hdemo_sk,ss_store_sk,ss_ticket_number] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk,ss_hdemo_sk,ss_customer_sk] + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_hdemo_sk,ss_store_sk,ss_ticket_number,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_dom,d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_dom] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometProject [s_store_sk] + CometFilter [s_county,s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk,s_county] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometProject [hd_demo_sk] + CometFilter [hd_vehicle_count,hd_buy_potential,hd_dep_count,hd_demo_sk] + CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_buy_potential,hd_dep_count,hd_vehicle_count] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (5) + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_salutation,c_first_name,c_last_name,c_preferred_cust_flag] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q74/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q74/explain.txt new file mode 100644 index 0000000000..dad94eb2cd --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q74/explain.txt @@ -0,0 +1,477 @@ +== Physical Plan == +TakeOrderedAndProject (71) ++- * Project (70) + +- * BroadcastHashJoin Inner BuildRight (69) + :- * Project (52) + : +- * BroadcastHashJoin Inner BuildRight (51) + : :- * BroadcastHashJoin Inner BuildRight (33) + : : :- * Filter (16) + : : : +- * HashAggregate (15) + : : : +- Exchange (14) + : : : +- * HashAggregate (13) + : : : +- * Project (12) + : : : +- * BroadcastHashJoin Inner BuildRight (11) + : : : :- * Project (9) + : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) + : : : : : +- CometScan parquet spark_catalog.default.customer (1) + : : : : +- BroadcastExchange (7) + : : : : +- * ColumnarToRow (6) + : : : : +- CometFilter (5) + : : : : +- CometScan parquet spark_catalog.default.store_sales (4) + : : : +- ReusedExchange (10) + : : +- BroadcastExchange (32) + : : +- * HashAggregate (31) + : : +- Exchange (30) + : : +- * HashAggregate (29) + : : +- * Project (28) + : : +- * BroadcastHashJoin Inner BuildRight (27) + : : :- * Project (25) + : : : +- * BroadcastHashJoin Inner BuildRight (24) + : : : :- * ColumnarToRow (19) + : : : : +- CometFilter (18) + : : : : +- CometScan parquet spark_catalog.default.customer (17) + : : : +- BroadcastExchange (23) + : : : +- * ColumnarToRow (22) + : : : +- CometFilter (21) + : : : +- CometScan parquet spark_catalog.default.store_sales (20) + : : +- ReusedExchange (26) + : +- BroadcastExchange (50) + : +- * Filter (49) + : +- * HashAggregate (48) + : +- Exchange (47) + : +- * HashAggregate (46) + : +- * Project (45) + : +- * BroadcastHashJoin Inner BuildRight (44) + : :- * Project (42) + : : +- * BroadcastHashJoin Inner BuildRight (41) + : : :- * ColumnarToRow (36) + : : : +- CometFilter (35) + : : : +- CometScan parquet spark_catalog.default.customer (34) + : : +- BroadcastExchange (40) + : : +- * ColumnarToRow (39) + : : +- CometFilter (38) + : : +- CometScan parquet spark_catalog.default.web_sales (37) + : +- ReusedExchange (43) + +- BroadcastExchange (68) + +- * HashAggregate (67) + +- Exchange (66) + +- * HashAggregate (65) + +- * Project (64) + +- * BroadcastHashJoin Inner BuildRight (63) + :- * Project (61) + : +- * BroadcastHashJoin Inner BuildRight (60) + : :- * ColumnarToRow (55) + : : +- CometFilter (54) + : : +- CometScan parquet spark_catalog.default.customer (53) + : +- BroadcastExchange (59) + : +- * ColumnarToRow (58) + : +- CometFilter (57) + : +- CometScan parquet spark_catalog.default.web_sales (56) + +- ReusedExchange (62) + + +(1) Scan parquet spark_catalog.default.customer +Output [4]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(2) CometFilter +Input [4]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4] +Condition : (isnotnull(c_customer_sk#1) AND isnotnull(c_customer_id#2)) + +(3) ColumnarToRow [codegen id : 3] +Input [4]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4] + +(4) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_customer_sk#5, ss_net_paid#6, ss_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sold_date_sk#7 IN dynamicpruning#8)] +PushedFilters: [IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(5) CometFilter +Input [3]: [ss_customer_sk#5, ss_net_paid#6, ss_sold_date_sk#7] +Condition : isnotnull(ss_customer_sk#5) + +(6) ColumnarToRow [codegen id : 1] +Input [3]: [ss_customer_sk#5, ss_net_paid#6, ss_sold_date_sk#7] + +(7) BroadcastExchange +Input [3]: [ss_customer_sk#5, ss_net_paid#6, ss_sold_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [c_customer_sk#1] +Right keys [1]: [ss_customer_sk#5] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 3] +Output [5]: [c_customer_id#2, c_first_name#3, c_last_name#4, ss_net_paid#6, ss_sold_date_sk#7] +Input [7]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4, ss_customer_sk#5, ss_net_paid#6, ss_sold_date_sk#7] + +(10) ReusedExchange [Reuses operator id: 75] +Output [2]: [d_date_sk#9, d_year#10] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_sold_date_sk#7] +Right keys [1]: [d_date_sk#9] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [5]: [c_customer_id#2, c_first_name#3, c_last_name#4, ss_net_paid#6, d_year#10] +Input [7]: [c_customer_id#2, c_first_name#3, c_last_name#4, ss_net_paid#6, ss_sold_date_sk#7, d_date_sk#9, d_year#10] + +(13) HashAggregate [codegen id : 3] +Input [5]: [c_customer_id#2, c_first_name#3, c_last_name#4, ss_net_paid#6, d_year#10] +Keys [4]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#10] +Functions [1]: [partial_sum(UnscaledValue(ss_net_paid#6))] +Aggregate Attributes [1]: [sum#11] +Results [5]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#10, sum#12] + +(14) Exchange +Input [5]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#10, sum#12] +Arguments: hashpartitioning(c_customer_id#2, c_first_name#3, c_last_name#4, d_year#10, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 16] +Input [5]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#10, sum#12] +Keys [4]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#10] +Functions [1]: [sum(UnscaledValue(ss_net_paid#6))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_paid#6))#13] +Results [2]: [c_customer_id#2 AS customer_id#14, MakeDecimal(sum(UnscaledValue(ss_net_paid#6))#13,17,2) AS year_total#15] + +(16) Filter [codegen id : 16] +Input [2]: [customer_id#14, year_total#15] +Condition : (isnotnull(year_total#15) AND (year_total#15 > 0.00)) + +(17) Scan parquet spark_catalog.default.customer +Output [4]: [c_customer_sk#16, c_customer_id#17, c_first_name#18, c_last_name#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(18) CometFilter +Input [4]: [c_customer_sk#16, c_customer_id#17, c_first_name#18, c_last_name#19] +Condition : (isnotnull(c_customer_sk#16) AND isnotnull(c_customer_id#17)) + +(19) ColumnarToRow [codegen id : 6] +Input [4]: [c_customer_sk#16, c_customer_id#17, c_first_name#18, c_last_name#19] + +(20) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_customer_sk#20, ss_net_paid#21, ss_sold_date_sk#22] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#22), dynamicpruningexpression(ss_sold_date_sk#22 IN dynamicpruning#23)] +PushedFilters: [IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(21) CometFilter +Input [3]: [ss_customer_sk#20, ss_net_paid#21, ss_sold_date_sk#22] +Condition : isnotnull(ss_customer_sk#20) + +(22) ColumnarToRow [codegen id : 4] +Input [3]: [ss_customer_sk#20, ss_net_paid#21, ss_sold_date_sk#22] + +(23) BroadcastExchange +Input [3]: [ss_customer_sk#20, ss_net_paid#21, ss_sold_date_sk#22] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [c_customer_sk#16] +Right keys [1]: [ss_customer_sk#20] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 6] +Output [5]: [c_customer_id#17, c_first_name#18, c_last_name#19, ss_net_paid#21, ss_sold_date_sk#22] +Input [7]: [c_customer_sk#16, c_customer_id#17, c_first_name#18, c_last_name#19, ss_customer_sk#20, ss_net_paid#21, ss_sold_date_sk#22] + +(26) ReusedExchange [Reuses operator id: 79] +Output [2]: [d_date_sk#24, d_year#25] + +(27) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_sold_date_sk#22] +Right keys [1]: [d_date_sk#24] +Join type: Inner +Join condition: None + +(28) Project [codegen id : 6] +Output [5]: [c_customer_id#17, c_first_name#18, c_last_name#19, ss_net_paid#21, d_year#25] +Input [7]: [c_customer_id#17, c_first_name#18, c_last_name#19, ss_net_paid#21, ss_sold_date_sk#22, d_date_sk#24, d_year#25] + +(29) HashAggregate [codegen id : 6] +Input [5]: [c_customer_id#17, c_first_name#18, c_last_name#19, ss_net_paid#21, d_year#25] +Keys [4]: [c_customer_id#17, c_first_name#18, c_last_name#19, d_year#25] +Functions [1]: [partial_sum(UnscaledValue(ss_net_paid#21))] +Aggregate Attributes [1]: [sum#26] +Results [5]: [c_customer_id#17, c_first_name#18, c_last_name#19, d_year#25, sum#27] + +(30) Exchange +Input [5]: [c_customer_id#17, c_first_name#18, c_last_name#19, d_year#25, sum#27] +Arguments: hashpartitioning(c_customer_id#17, c_first_name#18, c_last_name#19, d_year#25, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(31) HashAggregate [codegen id : 7] +Input [5]: [c_customer_id#17, c_first_name#18, c_last_name#19, d_year#25, sum#27] +Keys [4]: [c_customer_id#17, c_first_name#18, c_last_name#19, d_year#25] +Functions [1]: [sum(UnscaledValue(ss_net_paid#21))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_paid#21))#13] +Results [4]: [c_customer_id#17 AS customer_id#28, c_first_name#18 AS customer_first_name#29, c_last_name#19 AS customer_last_name#30, MakeDecimal(sum(UnscaledValue(ss_net_paid#21))#13,17,2) AS year_total#31] + +(32) BroadcastExchange +Input [4]: [customer_id#28, customer_first_name#29, customer_last_name#30, year_total#31] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=5] + +(33) BroadcastHashJoin [codegen id : 16] +Left keys [1]: [customer_id#14] +Right keys [1]: [customer_id#28] +Join type: Inner +Join condition: None + +(34) Scan parquet spark_catalog.default.customer +Output [4]: [c_customer_sk#32, c_customer_id#33, c_first_name#34, c_last_name#35] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(35) CometFilter +Input [4]: [c_customer_sk#32, c_customer_id#33, c_first_name#34, c_last_name#35] +Condition : (isnotnull(c_customer_sk#32) AND isnotnull(c_customer_id#33)) + +(36) ColumnarToRow [codegen id : 10] +Input [4]: [c_customer_sk#32, c_customer_id#33, c_first_name#34, c_last_name#35] + +(37) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_bill_customer_sk#36, ws_net_paid#37, ws_sold_date_sk#38] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#38), dynamicpruningexpression(ws_sold_date_sk#38 IN dynamicpruning#39)] +PushedFilters: [IsNotNull(ws_bill_customer_sk)] +ReadSchema: struct + +(38) CometFilter +Input [3]: [ws_bill_customer_sk#36, ws_net_paid#37, ws_sold_date_sk#38] +Condition : isnotnull(ws_bill_customer_sk#36) + +(39) ColumnarToRow [codegen id : 8] +Input [3]: [ws_bill_customer_sk#36, ws_net_paid#37, ws_sold_date_sk#38] + +(40) BroadcastExchange +Input [3]: [ws_bill_customer_sk#36, ws_net_paid#37, ws_sold_date_sk#38] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6] + +(41) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [c_customer_sk#32] +Right keys [1]: [ws_bill_customer_sk#36] +Join type: Inner +Join condition: None + +(42) Project [codegen id : 10] +Output [5]: [c_customer_id#33, c_first_name#34, c_last_name#35, ws_net_paid#37, ws_sold_date_sk#38] +Input [7]: [c_customer_sk#32, c_customer_id#33, c_first_name#34, c_last_name#35, ws_bill_customer_sk#36, ws_net_paid#37, ws_sold_date_sk#38] + +(43) ReusedExchange [Reuses operator id: 75] +Output [2]: [d_date_sk#40, d_year#41] + +(44) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [ws_sold_date_sk#38] +Right keys [1]: [d_date_sk#40] +Join type: Inner +Join condition: None + +(45) Project [codegen id : 10] +Output [5]: [c_customer_id#33, c_first_name#34, c_last_name#35, ws_net_paid#37, d_year#41] +Input [7]: [c_customer_id#33, c_first_name#34, c_last_name#35, ws_net_paid#37, ws_sold_date_sk#38, d_date_sk#40, d_year#41] + +(46) HashAggregate [codegen id : 10] +Input [5]: [c_customer_id#33, c_first_name#34, c_last_name#35, ws_net_paid#37, d_year#41] +Keys [4]: [c_customer_id#33, c_first_name#34, c_last_name#35, d_year#41] +Functions [1]: [partial_sum(UnscaledValue(ws_net_paid#37))] +Aggregate Attributes [1]: [sum#42] +Results [5]: [c_customer_id#33, c_first_name#34, c_last_name#35, d_year#41, sum#43] + +(47) Exchange +Input [5]: [c_customer_id#33, c_first_name#34, c_last_name#35, d_year#41, sum#43] +Arguments: hashpartitioning(c_customer_id#33, c_first_name#34, c_last_name#35, d_year#41, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(48) HashAggregate [codegen id : 11] +Input [5]: [c_customer_id#33, c_first_name#34, c_last_name#35, d_year#41, sum#43] +Keys [4]: [c_customer_id#33, c_first_name#34, c_last_name#35, d_year#41] +Functions [1]: [sum(UnscaledValue(ws_net_paid#37))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_net_paid#37))#44] +Results [2]: [c_customer_id#33 AS customer_id#45, MakeDecimal(sum(UnscaledValue(ws_net_paid#37))#44,17,2) AS year_total#46] + +(49) Filter [codegen id : 11] +Input [2]: [customer_id#45, year_total#46] +Condition : (isnotnull(year_total#46) AND (year_total#46 > 0.00)) + +(50) BroadcastExchange +Input [2]: [customer_id#45, year_total#46] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=8] + +(51) BroadcastHashJoin [codegen id : 16] +Left keys [1]: [customer_id#14] +Right keys [1]: [customer_id#45] +Join type: Inner +Join condition: None + +(52) Project [codegen id : 16] +Output [7]: [customer_id#14, year_total#15, customer_id#28, customer_first_name#29, customer_last_name#30, year_total#31, year_total#46] +Input [8]: [customer_id#14, year_total#15, customer_id#28, customer_first_name#29, customer_last_name#30, year_total#31, customer_id#45, year_total#46] + +(53) Scan parquet spark_catalog.default.customer +Output [4]: [c_customer_sk#47, c_customer_id#48, c_first_name#49, c_last_name#50] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(54) CometFilter +Input [4]: [c_customer_sk#47, c_customer_id#48, c_first_name#49, c_last_name#50] +Condition : (isnotnull(c_customer_sk#47) AND isnotnull(c_customer_id#48)) + +(55) ColumnarToRow [codegen id : 14] +Input [4]: [c_customer_sk#47, c_customer_id#48, c_first_name#49, c_last_name#50] + +(56) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_bill_customer_sk#51, ws_net_paid#52, ws_sold_date_sk#53] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#53), dynamicpruningexpression(ws_sold_date_sk#53 IN dynamicpruning#54)] +PushedFilters: [IsNotNull(ws_bill_customer_sk)] +ReadSchema: struct + +(57) CometFilter +Input [3]: [ws_bill_customer_sk#51, ws_net_paid#52, ws_sold_date_sk#53] +Condition : isnotnull(ws_bill_customer_sk#51) + +(58) ColumnarToRow [codegen id : 12] +Input [3]: [ws_bill_customer_sk#51, ws_net_paid#52, ws_sold_date_sk#53] + +(59) BroadcastExchange +Input [3]: [ws_bill_customer_sk#51, ws_net_paid#52, ws_sold_date_sk#53] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=9] + +(60) BroadcastHashJoin [codegen id : 14] +Left keys [1]: [c_customer_sk#47] +Right keys [1]: [ws_bill_customer_sk#51] +Join type: Inner +Join condition: None + +(61) Project [codegen id : 14] +Output [5]: [c_customer_id#48, c_first_name#49, c_last_name#50, ws_net_paid#52, ws_sold_date_sk#53] +Input [7]: [c_customer_sk#47, c_customer_id#48, c_first_name#49, c_last_name#50, ws_bill_customer_sk#51, ws_net_paid#52, ws_sold_date_sk#53] + +(62) ReusedExchange [Reuses operator id: 79] +Output [2]: [d_date_sk#55, d_year#56] + +(63) BroadcastHashJoin [codegen id : 14] +Left keys [1]: [ws_sold_date_sk#53] +Right keys [1]: [d_date_sk#55] +Join type: Inner +Join condition: None + +(64) Project [codegen id : 14] +Output [5]: [c_customer_id#48, c_first_name#49, c_last_name#50, ws_net_paid#52, d_year#56] +Input [7]: [c_customer_id#48, c_first_name#49, c_last_name#50, ws_net_paid#52, ws_sold_date_sk#53, d_date_sk#55, d_year#56] + +(65) HashAggregate [codegen id : 14] +Input [5]: [c_customer_id#48, c_first_name#49, c_last_name#50, ws_net_paid#52, d_year#56] +Keys [4]: [c_customer_id#48, c_first_name#49, c_last_name#50, d_year#56] +Functions [1]: [partial_sum(UnscaledValue(ws_net_paid#52))] +Aggregate Attributes [1]: [sum#57] +Results [5]: [c_customer_id#48, c_first_name#49, c_last_name#50, d_year#56, sum#58] + +(66) Exchange +Input [5]: [c_customer_id#48, c_first_name#49, c_last_name#50, d_year#56, sum#58] +Arguments: hashpartitioning(c_customer_id#48, c_first_name#49, c_last_name#50, d_year#56, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(67) HashAggregate [codegen id : 15] +Input [5]: [c_customer_id#48, c_first_name#49, c_last_name#50, d_year#56, sum#58] +Keys [4]: [c_customer_id#48, c_first_name#49, c_last_name#50, d_year#56] +Functions [1]: [sum(UnscaledValue(ws_net_paid#52))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_net_paid#52))#44] +Results [2]: [c_customer_id#48 AS customer_id#59, MakeDecimal(sum(UnscaledValue(ws_net_paid#52))#44,17,2) AS year_total#60] + +(68) BroadcastExchange +Input [2]: [customer_id#59, year_total#60] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=11] + +(69) BroadcastHashJoin [codegen id : 16] +Left keys [1]: [customer_id#14] +Right keys [1]: [customer_id#59] +Join type: Inner +Join condition: (CASE WHEN (year_total#46 > 0.00) THEN (year_total#60 / year_total#46) END > CASE WHEN (year_total#15 > 0.00) THEN (year_total#31 / year_total#15) END) + +(70) Project [codegen id : 16] +Output [3]: [customer_id#28, customer_first_name#29, customer_last_name#30] +Input [9]: [customer_id#14, year_total#15, customer_id#28, customer_first_name#29, customer_last_name#30, year_total#31, year_total#46, customer_id#59, year_total#60] + +(71) TakeOrderedAndProject +Input [3]: [customer_id#28, customer_first_name#29, customer_last_name#30] +Arguments: 100, [customer_id#28 ASC NULLS FIRST, customer_id#28 ASC NULLS FIRST, customer_id#28 ASC NULLS FIRST], [customer_id#28, customer_first_name#29, customer_last_name#30] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (75) ++- * ColumnarToRow (74) + +- CometFilter (73) + +- CometScan parquet spark_catalog.default.date_dim (72) + + +(72) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#9, d_year#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), In(d_year, [2001,2002]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(73) CometFilter +Input [2]: [d_date_sk#9, d_year#10] +Condition : (((isnotnull(d_year#10) AND (d_year#10 = 2001)) AND d_year#10 IN (2001,2002)) AND isnotnull(d_date_sk#9)) + +(74) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#9, d_year#10] + +(75) BroadcastExchange +Input [2]: [d_date_sk#9, d_year#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=12] + +Subquery:2 Hosting operator id = 20 Hosting Expression = ss_sold_date_sk#22 IN dynamicpruning#23 +BroadcastExchange (79) ++- * ColumnarToRow (78) + +- CometFilter (77) + +- CometScan parquet spark_catalog.default.date_dim (76) + + +(76) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#24, d_year#25] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2002), In(d_year, [2001,2002]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(77) CometFilter +Input [2]: [d_date_sk#24, d_year#25] +Condition : (((isnotnull(d_year#25) AND (d_year#25 = 2002)) AND d_year#25 IN (2001,2002)) AND isnotnull(d_date_sk#24)) + +(78) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#24, d_year#25] + +(79) BroadcastExchange +Input [2]: [d_date_sk#24, d_year#25] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=13] + +Subquery:3 Hosting operator id = 37 Hosting Expression = ws_sold_date_sk#38 IN dynamicpruning#8 + +Subquery:4 Hosting operator id = 56 Hosting Expression = ws_sold_date_sk#53 IN dynamicpruning#23 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q74/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q74/simplified.txt new file mode 100644 index 0000000000..9d3ae8fbee --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q74/simplified.txt @@ -0,0 +1,122 @@ +TakeOrderedAndProject [customer_id,customer_first_name,customer_last_name] + WholeStageCodegen (16) + Project [customer_id,customer_first_name,customer_last_name] + BroadcastHashJoin [customer_id,customer_id,year_total,year_total,year_total,year_total] + Project [customer_id,year_total,customer_id,customer_first_name,customer_last_name,year_total,year_total] + BroadcastHashJoin [customer_id,customer_id] + BroadcastHashJoin [customer_id,customer_id] + Filter [year_total] + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,sum] [sum(UnscaledValue(ss_net_paid)),customer_id,year_total,sum] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,d_year] #1 + WholeStageCodegen (3) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,ss_net_paid] [sum,sum] + Project [c_customer_id,c_first_name,c_last_name,ss_net_paid,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,ss_net_paid,ss_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk] + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_net_paid,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk,d_year] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (7) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,sum] [sum(UnscaledValue(ss_net_paid)),customer_id,customer_first_name,customer_last_name,year_total,sum] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,d_year] #5 + WholeStageCodegen (6) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,ss_net_paid] [sum,sum] + Project [c_customer_id,c_first_name,c_last_name,ss_net_paid,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,ss_net_paid,ss_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (4) + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk] + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_net_paid,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #7 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk,d_year] #7 + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (11) + Filter [year_total] + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,sum] [sum(UnscaledValue(ws_net_paid)),customer_id,year_total,sum] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,d_year] #9 + WholeStageCodegen (10) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,ws_net_paid] [sum,sum] + Project [c_customer_id,c_first_name,c_last_name,ws_net_paid,d_year] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,ws_net_paid,ws_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name] + InputAdapter + BroadcastExchange #10 + WholeStageCodegen (8) + ColumnarToRow + InputAdapter + CometFilter [ws_bill_customer_sk] + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_net_paid,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk,d_year] #3 + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (15) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,sum] [sum(UnscaledValue(ws_net_paid)),customer_id,year_total,sum] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,d_year] #12 + WholeStageCodegen (14) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,ws_net_paid] [sum,sum] + Project [c_customer_id,c_first_name,c_last_name,ws_net_paid,d_year] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,ws_net_paid,ws_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name] + InputAdapter + BroadcastExchange #13 + WholeStageCodegen (12) + ColumnarToRow + InputAdapter + CometFilter [ws_bill_customer_sk] + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_net_paid,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk,d_year] #7 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q75/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q75/explain.txt new file mode 100644 index 0000000000..a3d12a1d47 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q75/explain.txt @@ -0,0 +1,779 @@ +== Physical Plan == +TakeOrderedAndProject (129) ++- * Project (128) + +- * SortMergeJoin Inner (127) + :- * Sort (71) + : +- Exchange (70) + : +- * Filter (69) + : +- * HashAggregate (68) + : +- Exchange (67) + : +- * HashAggregate (66) + : +- * HashAggregate (65) + : +- Exchange (64) + : +- * HashAggregate (63) + : +- Union (62) + : :- * Project (23) + : : +- * SortMergeJoin LeftOuter (22) + : : :- * Sort (15) + : : : +- Exchange (14) + : : : +- * Project (13) + : : : +- * BroadcastHashJoin Inner BuildRight (12) + : : : :- * Project (10) + : : : : +- * BroadcastHashJoin Inner BuildRight (9) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) + : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) + : : : : +- BroadcastExchange (8) + : : : : +- * ColumnarToRow (7) + : : : : +- CometProject (6) + : : : : +- CometFilter (5) + : : : : +- CometScan parquet spark_catalog.default.item (4) + : : : +- ReusedExchange (11) + : : +- * Sort (21) + : : +- Exchange (20) + : : +- * ColumnarToRow (19) + : : +- CometProject (18) + : : +- CometFilter (17) + : : +- CometScan parquet spark_catalog.default.catalog_returns (16) + : :- * Project (42) + : : +- * SortMergeJoin LeftOuter (41) + : : :- * Sort (34) + : : : +- Exchange (33) + : : : +- * Project (32) + : : : +- * BroadcastHashJoin Inner BuildRight (31) + : : : :- * Project (29) + : : : : +- * BroadcastHashJoin Inner BuildRight (28) + : : : : :- * ColumnarToRow (26) + : : : : : +- CometFilter (25) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (24) + : : : : +- ReusedExchange (27) + : : : +- ReusedExchange (30) + : : +- * Sort (40) + : : +- Exchange (39) + : : +- * ColumnarToRow (38) + : : +- CometProject (37) + : : +- CometFilter (36) + : : +- CometScan parquet spark_catalog.default.store_returns (35) + : +- * Project (61) + : +- * SortMergeJoin LeftOuter (60) + : :- * Sort (53) + : : +- Exchange (52) + : : +- * Project (51) + : : +- * BroadcastHashJoin Inner BuildRight (50) + : : :- * Project (48) + : : : +- * BroadcastHashJoin Inner BuildRight (47) + : : : :- * ColumnarToRow (45) + : : : : +- CometFilter (44) + : : : : +- CometScan parquet spark_catalog.default.web_sales (43) + : : : +- ReusedExchange (46) + : : +- ReusedExchange (49) + : +- * Sort (59) + : +- Exchange (58) + : +- * ColumnarToRow (57) + : +- CometProject (56) + : +- CometFilter (55) + : +- CometScan parquet spark_catalog.default.web_returns (54) + +- * Sort (126) + +- Exchange (125) + +- * Filter (124) + +- * HashAggregate (123) + +- Exchange (122) + +- * HashAggregate (121) + +- * HashAggregate (120) + +- Exchange (119) + +- * HashAggregate (118) + +- Union (117) + :- * Project (86) + : +- * SortMergeJoin LeftOuter (85) + : :- * Sort (82) + : : +- Exchange (81) + : : +- * Project (80) + : : +- * BroadcastHashJoin Inner BuildRight (79) + : : :- * Project (77) + : : : +- * BroadcastHashJoin Inner BuildRight (76) + : : : :- * ColumnarToRow (74) + : : : : +- CometFilter (73) + : : : : +- CometScan parquet spark_catalog.default.catalog_sales (72) + : : : +- ReusedExchange (75) + : : +- ReusedExchange (78) + : +- * Sort (84) + : +- ReusedExchange (83) + :- * Project (101) + : +- * SortMergeJoin LeftOuter (100) + : :- * Sort (97) + : : +- Exchange (96) + : : +- * Project (95) + : : +- * BroadcastHashJoin Inner BuildRight (94) + : : :- * Project (92) + : : : +- * BroadcastHashJoin Inner BuildRight (91) + : : : :- * ColumnarToRow (89) + : : : : +- CometFilter (88) + : : : : +- CometScan parquet spark_catalog.default.store_sales (87) + : : : +- ReusedExchange (90) + : : +- ReusedExchange (93) + : +- * Sort (99) + : +- ReusedExchange (98) + +- * Project (116) + +- * SortMergeJoin LeftOuter (115) + :- * Sort (112) + : +- Exchange (111) + : +- * Project (110) + : +- * BroadcastHashJoin Inner BuildRight (109) + : :- * Project (107) + : : +- * BroadcastHashJoin Inner BuildRight (106) + : : :- * ColumnarToRow (104) + : : : +- CometFilter (103) + : : : +- CometScan parquet spark_catalog.default.web_sales (102) + : : +- ReusedExchange (105) + : +- ReusedExchange (108) + +- * Sort (114) + +- ReusedExchange (113) + + +(1) Scan parquet spark_catalog.default.catalog_sales +Output [5]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, cs_sold_date_sk#5] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#5), dynamicpruningexpression(cs_sold_date_sk#5 IN dynamicpruning#6)] +PushedFilters: [IsNotNull(cs_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [5]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, cs_sold_date_sk#5] +Condition : isnotnull(cs_item_sk#1) + +(3) ColumnarToRow [codegen id : 3] +Input [5]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, cs_sold_date_sk#5] + +(4) Scan parquet spark_catalog.default.item +Output [6]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_category#11, i_manufact_id#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_category), EqualTo(i_category,Books ), IsNotNull(i_item_sk), IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id), IsNotNull(i_manufact_id)] +ReadSchema: struct + +(5) CometFilter +Input [6]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_category#11, i_manufact_id#12] +Condition : ((((((isnotnull(i_category#11) AND (i_category#11 = Books )) AND isnotnull(i_item_sk#7)) AND isnotnull(i_brand_id#8)) AND isnotnull(i_class_id#9)) AND isnotnull(i_category_id#10)) AND isnotnull(i_manufact_id#12)) + +(6) CometProject +Input [6]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_category#11, i_manufact_id#12] +Arguments: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12], [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] + +(7) ColumnarToRow [codegen id : 1] +Input [5]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] + +(8) BroadcastExchange +Input [5]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cs_item_sk#1] +Right keys [1]: [i_item_sk#7] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 3] +Output [9]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, cs_sold_date_sk#5, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] +Input [10]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, cs_sold_date_sk#5, i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] + +(11) ReusedExchange [Reuses operator id: 133] +Output [2]: [d_date_sk#13, d_year#14] + +(12) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cs_sold_date_sk#5] +Right keys [1]: [d_date_sk#13] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 3] +Output [9]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, d_year#14] +Input [11]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, cs_sold_date_sk#5, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, d_date_sk#13, d_year#14] + +(14) Exchange +Input [9]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, d_year#14] +Arguments: hashpartitioning(cs_order_number#2, cs_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) Sort [codegen id : 4] +Input [9]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, d_year#14] +Arguments: [cs_order_number#2 ASC NULLS FIRST, cs_item_sk#1 ASC NULLS FIRST], false, 0 + +(16) Scan parquet spark_catalog.default.catalog_returns +Output [5]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18, cr_returned_date_sk#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_returns] +PushedFilters: [IsNotNull(cr_order_number), IsNotNull(cr_item_sk)] +ReadSchema: struct + +(17) CometFilter +Input [5]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18, cr_returned_date_sk#19] +Condition : (isnotnull(cr_order_number#16) AND isnotnull(cr_item_sk#15)) + +(18) CometProject +Input [5]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18, cr_returned_date_sk#19] +Arguments: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18], [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18] + +(19) ColumnarToRow [codegen id : 5] +Input [4]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18] + +(20) Exchange +Input [4]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18] +Arguments: hashpartitioning(cr_order_number#16, cr_item_sk#15, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(21) Sort [codegen id : 6] +Input [4]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18] +Arguments: [cr_order_number#16 ASC NULLS FIRST, cr_item_sk#15 ASC NULLS FIRST], false, 0 + +(22) SortMergeJoin [codegen id : 7] +Left keys [2]: [cs_order_number#2, cs_item_sk#1] +Right keys [2]: [cr_order_number#16, cr_item_sk#15] +Join type: LeftOuter +Join condition: None + +(23) Project [codegen id : 7] +Output [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, (cs_quantity#3 - coalesce(cr_return_quantity#17, 0)) AS sales_cnt#20, (cs_ext_sales_price#4 - coalesce(cr_return_amount#18, 0.00)) AS sales_amt#21] +Input [13]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, d_year#14, cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18] + +(24) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, ss_sold_date_sk#26] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#26), dynamicpruningexpression(ss_sold_date_sk#26 IN dynamicpruning#27)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(25) CometFilter +Input [5]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, ss_sold_date_sk#26] +Condition : isnotnull(ss_item_sk#22) + +(26) ColumnarToRow [codegen id : 10] +Input [5]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, ss_sold_date_sk#26] + +(27) ReusedExchange [Reuses operator id: 8] +Output [5]: [i_item_sk#28, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32] + +(28) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [ss_item_sk#22] +Right keys [1]: [i_item_sk#28] +Join type: Inner +Join condition: None + +(29) Project [codegen id : 10] +Output [9]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, ss_sold_date_sk#26, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32] +Input [10]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, ss_sold_date_sk#26, i_item_sk#28, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32] + +(30) ReusedExchange [Reuses operator id: 133] +Output [2]: [d_date_sk#33, d_year#34] + +(31) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [ss_sold_date_sk#26] +Right keys [1]: [d_date_sk#33] +Join type: Inner +Join condition: None + +(32) Project [codegen id : 10] +Output [9]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32, d_year#34] +Input [11]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, ss_sold_date_sk#26, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32, d_date_sk#33, d_year#34] + +(33) Exchange +Input [9]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32, d_year#34] +Arguments: hashpartitioning(ss_ticket_number#23, ss_item_sk#22, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(34) Sort [codegen id : 11] +Input [9]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32, d_year#34] +Arguments: [ss_ticket_number#23 ASC NULLS FIRST, ss_item_sk#22 ASC NULLS FIRST], false, 0 + +(35) Scan parquet spark_catalog.default.store_returns +Output [5]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38, sr_returned_date_sk#39] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_returns] +PushedFilters: [IsNotNull(sr_ticket_number), IsNotNull(sr_item_sk)] +ReadSchema: struct + +(36) CometFilter +Input [5]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38, sr_returned_date_sk#39] +Condition : (isnotnull(sr_ticket_number#36) AND isnotnull(sr_item_sk#35)) + +(37) CometProject +Input [5]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38, sr_returned_date_sk#39] +Arguments: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38], [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38] + +(38) ColumnarToRow [codegen id : 12] +Input [4]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38] + +(39) Exchange +Input [4]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38] +Arguments: hashpartitioning(sr_ticket_number#36, sr_item_sk#35, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(40) Sort [codegen id : 13] +Input [4]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38] +Arguments: [sr_ticket_number#36 ASC NULLS FIRST, sr_item_sk#35 ASC NULLS FIRST], false, 0 + +(41) SortMergeJoin [codegen id : 14] +Left keys [2]: [ss_ticket_number#23, ss_item_sk#22] +Right keys [2]: [sr_ticket_number#36, sr_item_sk#35] +Join type: LeftOuter +Join condition: None + +(42) Project [codegen id : 14] +Output [7]: [d_year#34, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32, (ss_quantity#24 - coalesce(sr_return_quantity#37, 0)) AS sales_cnt#40, (ss_ext_sales_price#25 - coalesce(sr_return_amt#38, 0.00)) AS sales_amt#41] +Input [13]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32, d_year#34, sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38] + +(43) Scan parquet spark_catalog.default.web_sales +Output [5]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, ws_sold_date_sk#46] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#46), dynamicpruningexpression(ws_sold_date_sk#46 IN dynamicpruning#47)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(44) CometFilter +Input [5]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, ws_sold_date_sk#46] +Condition : isnotnull(ws_item_sk#42) + +(45) ColumnarToRow [codegen id : 17] +Input [5]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, ws_sold_date_sk#46] + +(46) ReusedExchange [Reuses operator id: 8] +Output [5]: [i_item_sk#48, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52] + +(47) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ws_item_sk#42] +Right keys [1]: [i_item_sk#48] +Join type: Inner +Join condition: None + +(48) Project [codegen id : 17] +Output [9]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, ws_sold_date_sk#46, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52] +Input [10]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, ws_sold_date_sk#46, i_item_sk#48, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52] + +(49) ReusedExchange [Reuses operator id: 133] +Output [2]: [d_date_sk#53, d_year#54] + +(50) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ws_sold_date_sk#46] +Right keys [1]: [d_date_sk#53] +Join type: Inner +Join condition: None + +(51) Project [codegen id : 17] +Output [9]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52, d_year#54] +Input [11]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, ws_sold_date_sk#46, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52, d_date_sk#53, d_year#54] + +(52) Exchange +Input [9]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52, d_year#54] +Arguments: hashpartitioning(ws_order_number#43, ws_item_sk#42, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(53) Sort [codegen id : 18] +Input [9]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52, d_year#54] +Arguments: [ws_order_number#43 ASC NULLS FIRST, ws_item_sk#42 ASC NULLS FIRST], false, 0 + +(54) Scan parquet spark_catalog.default.web_returns +Output [5]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58, wr_returned_date_sk#59] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_returns] +PushedFilters: [IsNotNull(wr_order_number), IsNotNull(wr_item_sk)] +ReadSchema: struct + +(55) CometFilter +Input [5]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58, wr_returned_date_sk#59] +Condition : (isnotnull(wr_order_number#56) AND isnotnull(wr_item_sk#55)) + +(56) CometProject +Input [5]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58, wr_returned_date_sk#59] +Arguments: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58], [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58] + +(57) ColumnarToRow [codegen id : 19] +Input [4]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58] + +(58) Exchange +Input [4]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58] +Arguments: hashpartitioning(wr_order_number#56, wr_item_sk#55, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(59) Sort [codegen id : 20] +Input [4]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58] +Arguments: [wr_order_number#56 ASC NULLS FIRST, wr_item_sk#55 ASC NULLS FIRST], false, 0 + +(60) SortMergeJoin [codegen id : 21] +Left keys [2]: [ws_order_number#43, ws_item_sk#42] +Right keys [2]: [wr_order_number#56, wr_item_sk#55] +Join type: LeftOuter +Join condition: None + +(61) Project [codegen id : 21] +Output [7]: [d_year#54, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52, (ws_quantity#44 - coalesce(wr_return_quantity#57, 0)) AS sales_cnt#60, (ws_ext_sales_price#45 - coalesce(wr_return_amt#58, 0.00)) AS sales_amt#61] +Input [13]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52, d_year#54, wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58] + +(62) Union + +(63) HashAggregate [codegen id : 22] +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21] +Keys [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21] +Functions: [] +Aggregate Attributes: [] +Results [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21] + +(64) Exchange +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21] +Arguments: hashpartitioning(d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21, 5), ENSURE_REQUIREMENTS, [plan_id=8] + +(65) HashAggregate [codegen id : 23] +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21] +Keys [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21] +Functions: [] +Aggregate Attributes: [] +Results [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21] + +(66) HashAggregate [codegen id : 23] +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21] +Keys [5]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] +Functions [2]: [partial_sum(sales_cnt#20), partial_sum(UnscaledValue(sales_amt#21))] +Aggregate Attributes [2]: [sum#62, sum#63] +Results [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sum#64, sum#65] + +(67) Exchange +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sum#64, sum#65] +Arguments: hashpartitioning(d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(68) HashAggregate [codegen id : 24] +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sum#64, sum#65] +Keys [5]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] +Functions [2]: [sum(sales_cnt#20), sum(UnscaledValue(sales_amt#21))] +Aggregate Attributes [2]: [sum(sales_cnt#20)#66, sum(UnscaledValue(sales_amt#21))#67] +Results [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sum(sales_cnt#20)#66 AS sales_cnt#68, MakeDecimal(sum(UnscaledValue(sales_amt#21))#67,18,2) AS sales_amt#69] + +(69) Filter [codegen id : 24] +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#68, sales_amt#69] +Condition : isnotnull(sales_cnt#68) + +(70) Exchange +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#68, sales_amt#69] +Arguments: hashpartitioning(i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(71) Sort [codegen id : 25] +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#68, sales_amt#69] +Arguments: [i_brand_id#8 ASC NULLS FIRST, i_class_id#9 ASC NULLS FIRST, i_category_id#10 ASC NULLS FIRST, i_manufact_id#12 ASC NULLS FIRST], false, 0 + +(72) Scan parquet spark_catalog.default.catalog_sales +Output [5]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, cs_sold_date_sk#74] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#74), dynamicpruningexpression(cs_sold_date_sk#74 IN dynamicpruning#75)] +PushedFilters: [IsNotNull(cs_item_sk)] +ReadSchema: struct + +(73) CometFilter +Input [5]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, cs_sold_date_sk#74] +Condition : isnotnull(cs_item_sk#70) + +(74) ColumnarToRow [codegen id : 28] +Input [5]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, cs_sold_date_sk#74] + +(75) ReusedExchange [Reuses operator id: 8] +Output [5]: [i_item_sk#76, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80] + +(76) BroadcastHashJoin [codegen id : 28] +Left keys [1]: [cs_item_sk#70] +Right keys [1]: [i_item_sk#76] +Join type: Inner +Join condition: None + +(77) Project [codegen id : 28] +Output [9]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, cs_sold_date_sk#74, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80] +Input [10]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, cs_sold_date_sk#74, i_item_sk#76, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80] + +(78) ReusedExchange [Reuses operator id: 137] +Output [2]: [d_date_sk#81, d_year#82] + +(79) BroadcastHashJoin [codegen id : 28] +Left keys [1]: [cs_sold_date_sk#74] +Right keys [1]: [d_date_sk#81] +Join type: Inner +Join condition: None + +(80) Project [codegen id : 28] +Output [9]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, d_year#82] +Input [11]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, cs_sold_date_sk#74, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, d_date_sk#81, d_year#82] + +(81) Exchange +Input [9]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, d_year#82] +Arguments: hashpartitioning(cs_order_number#71, cs_item_sk#70, 5), ENSURE_REQUIREMENTS, [plan_id=11] + +(82) Sort [codegen id : 29] +Input [9]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, d_year#82] +Arguments: [cs_order_number#71 ASC NULLS FIRST, cs_item_sk#70 ASC NULLS FIRST], false, 0 + +(83) ReusedExchange [Reuses operator id: 20] +Output [4]: [cr_item_sk#83, cr_order_number#84, cr_return_quantity#85, cr_return_amount#86] + +(84) Sort [codegen id : 31] +Input [4]: [cr_item_sk#83, cr_order_number#84, cr_return_quantity#85, cr_return_amount#86] +Arguments: [cr_order_number#84 ASC NULLS FIRST, cr_item_sk#83 ASC NULLS FIRST], false, 0 + +(85) SortMergeJoin [codegen id : 32] +Left keys [2]: [cs_order_number#71, cs_item_sk#70] +Right keys [2]: [cr_order_number#84, cr_item_sk#83] +Join type: LeftOuter +Join condition: None + +(86) Project [codegen id : 32] +Output [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, (cs_quantity#72 - coalesce(cr_return_quantity#85, 0)) AS sales_cnt#87, (cs_ext_sales_price#73 - coalesce(cr_return_amount#86, 0.00)) AS sales_amt#88] +Input [13]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, d_year#82, cr_item_sk#83, cr_order_number#84, cr_return_quantity#85, cr_return_amount#86] + +(87) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, ss_sold_date_sk#93] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#93), dynamicpruningexpression(ss_sold_date_sk#93 IN dynamicpruning#94)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(88) CometFilter +Input [5]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, ss_sold_date_sk#93] +Condition : isnotnull(ss_item_sk#89) + +(89) ColumnarToRow [codegen id : 35] +Input [5]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, ss_sold_date_sk#93] + +(90) ReusedExchange [Reuses operator id: 8] +Output [5]: [i_item_sk#95, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99] + +(91) BroadcastHashJoin [codegen id : 35] +Left keys [1]: [ss_item_sk#89] +Right keys [1]: [i_item_sk#95] +Join type: Inner +Join condition: None + +(92) Project [codegen id : 35] +Output [9]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, ss_sold_date_sk#93, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99] +Input [10]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, ss_sold_date_sk#93, i_item_sk#95, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99] + +(93) ReusedExchange [Reuses operator id: 137] +Output [2]: [d_date_sk#100, d_year#101] + +(94) BroadcastHashJoin [codegen id : 35] +Left keys [1]: [ss_sold_date_sk#93] +Right keys [1]: [d_date_sk#100] +Join type: Inner +Join condition: None + +(95) Project [codegen id : 35] +Output [9]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99, d_year#101] +Input [11]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, ss_sold_date_sk#93, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99, d_date_sk#100, d_year#101] + +(96) Exchange +Input [9]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99, d_year#101] +Arguments: hashpartitioning(ss_ticket_number#90, ss_item_sk#89, 5), ENSURE_REQUIREMENTS, [plan_id=12] + +(97) Sort [codegen id : 36] +Input [9]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99, d_year#101] +Arguments: [ss_ticket_number#90 ASC NULLS FIRST, ss_item_sk#89 ASC NULLS FIRST], false, 0 + +(98) ReusedExchange [Reuses operator id: 39] +Output [4]: [sr_item_sk#102, sr_ticket_number#103, sr_return_quantity#104, sr_return_amt#105] + +(99) Sort [codegen id : 38] +Input [4]: [sr_item_sk#102, sr_ticket_number#103, sr_return_quantity#104, sr_return_amt#105] +Arguments: [sr_ticket_number#103 ASC NULLS FIRST, sr_item_sk#102 ASC NULLS FIRST], false, 0 + +(100) SortMergeJoin [codegen id : 39] +Left keys [2]: [ss_ticket_number#90, ss_item_sk#89] +Right keys [2]: [sr_ticket_number#103, sr_item_sk#102] +Join type: LeftOuter +Join condition: None + +(101) Project [codegen id : 39] +Output [7]: [d_year#101, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99, (ss_quantity#91 - coalesce(sr_return_quantity#104, 0)) AS sales_cnt#106, (ss_ext_sales_price#92 - coalesce(sr_return_amt#105, 0.00)) AS sales_amt#107] +Input [13]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99, d_year#101, sr_item_sk#102, sr_ticket_number#103, sr_return_quantity#104, sr_return_amt#105] + +(102) Scan parquet spark_catalog.default.web_sales +Output [5]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, ws_sold_date_sk#112] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#112), dynamicpruningexpression(ws_sold_date_sk#112 IN dynamicpruning#113)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(103) CometFilter +Input [5]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, ws_sold_date_sk#112] +Condition : isnotnull(ws_item_sk#108) + +(104) ColumnarToRow [codegen id : 42] +Input [5]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, ws_sold_date_sk#112] + +(105) ReusedExchange [Reuses operator id: 8] +Output [5]: [i_item_sk#114, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118] + +(106) BroadcastHashJoin [codegen id : 42] +Left keys [1]: [ws_item_sk#108] +Right keys [1]: [i_item_sk#114] +Join type: Inner +Join condition: None + +(107) Project [codegen id : 42] +Output [9]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, ws_sold_date_sk#112, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118] +Input [10]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, ws_sold_date_sk#112, i_item_sk#114, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118] + +(108) ReusedExchange [Reuses operator id: 137] +Output [2]: [d_date_sk#119, d_year#120] + +(109) BroadcastHashJoin [codegen id : 42] +Left keys [1]: [ws_sold_date_sk#112] +Right keys [1]: [d_date_sk#119] +Join type: Inner +Join condition: None + +(110) Project [codegen id : 42] +Output [9]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118, d_year#120] +Input [11]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, ws_sold_date_sk#112, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118, d_date_sk#119, d_year#120] + +(111) Exchange +Input [9]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118, d_year#120] +Arguments: hashpartitioning(ws_order_number#109, ws_item_sk#108, 5), ENSURE_REQUIREMENTS, [plan_id=13] + +(112) Sort [codegen id : 43] +Input [9]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118, d_year#120] +Arguments: [ws_order_number#109 ASC NULLS FIRST, ws_item_sk#108 ASC NULLS FIRST], false, 0 + +(113) ReusedExchange [Reuses operator id: 58] +Output [4]: [wr_item_sk#121, wr_order_number#122, wr_return_quantity#123, wr_return_amt#124] + +(114) Sort [codegen id : 45] +Input [4]: [wr_item_sk#121, wr_order_number#122, wr_return_quantity#123, wr_return_amt#124] +Arguments: [wr_order_number#122 ASC NULLS FIRST, wr_item_sk#121 ASC NULLS FIRST], false, 0 + +(115) SortMergeJoin [codegen id : 46] +Left keys [2]: [ws_order_number#109, ws_item_sk#108] +Right keys [2]: [wr_order_number#122, wr_item_sk#121] +Join type: LeftOuter +Join condition: None + +(116) Project [codegen id : 46] +Output [7]: [d_year#120, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118, (ws_quantity#110 - coalesce(wr_return_quantity#123, 0)) AS sales_cnt#125, (ws_ext_sales_price#111 - coalesce(wr_return_amt#124, 0.00)) AS sales_amt#126] +Input [13]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118, d_year#120, wr_item_sk#121, wr_order_number#122, wr_return_quantity#123, wr_return_amt#124] + +(117) Union + +(118) HashAggregate [codegen id : 47] +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88] +Keys [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88] +Functions: [] +Aggregate Attributes: [] +Results [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88] + +(119) Exchange +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88] +Arguments: hashpartitioning(d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88, 5), ENSURE_REQUIREMENTS, [plan_id=14] + +(120) HashAggregate [codegen id : 48] +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88] +Keys [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88] +Functions: [] +Aggregate Attributes: [] +Results [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88] + +(121) HashAggregate [codegen id : 48] +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88] +Keys [5]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80] +Functions [2]: [partial_sum(sales_cnt#87), partial_sum(UnscaledValue(sales_amt#88))] +Aggregate Attributes [2]: [sum#127, sum#128] +Results [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sum#129, sum#130] + +(122) Exchange +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sum#129, sum#130] +Arguments: hashpartitioning(d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, 5), ENSURE_REQUIREMENTS, [plan_id=15] + +(123) HashAggregate [codegen id : 49] +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sum#129, sum#130] +Keys [5]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80] +Functions [2]: [sum(sales_cnt#87), sum(UnscaledValue(sales_amt#88))] +Aggregate Attributes [2]: [sum(sales_cnt#87)#66, sum(UnscaledValue(sales_amt#88))#67] +Results [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sum(sales_cnt#87)#66 AS sales_cnt#131, MakeDecimal(sum(UnscaledValue(sales_amt#88))#67,18,2) AS sales_amt#132] + +(124) Filter [codegen id : 49] +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#131, sales_amt#132] +Condition : isnotnull(sales_cnt#131) + +(125) Exchange +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#131, sales_amt#132] +Arguments: hashpartitioning(i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, 5), ENSURE_REQUIREMENTS, [plan_id=16] + +(126) Sort [codegen id : 50] +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#131, sales_amt#132] +Arguments: [i_brand_id#77 ASC NULLS FIRST, i_class_id#78 ASC NULLS FIRST, i_category_id#79 ASC NULLS FIRST, i_manufact_id#80 ASC NULLS FIRST], false, 0 + +(127) SortMergeJoin [codegen id : 51] +Left keys [4]: [i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] +Right keys [4]: [i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80] +Join type: Inner +Join condition: ((cast(sales_cnt#68 as decimal(17,2)) / cast(sales_cnt#131 as decimal(17,2))) < 0.90000000000000000000) + +(128) Project [codegen id : 51] +Output [10]: [d_year#82 AS prev_year#133, d_year#14 AS year#134, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#131 AS prev_yr_cnt#135, sales_cnt#68 AS curr_yr_cnt#136, (sales_cnt#68 - sales_cnt#131) AS sales_cnt_diff#137, (sales_amt#69 - sales_amt#132) AS sales_amt_diff#138] +Input [14]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#68, sales_amt#69, d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#131, sales_amt#132] + +(129) TakeOrderedAndProject +Input [10]: [prev_year#133, year#134, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, prev_yr_cnt#135, curr_yr_cnt#136, sales_cnt_diff#137, sales_amt_diff#138] +Arguments: 100, [sales_cnt_diff#137 ASC NULLS FIRST], [prev_year#133, year#134, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, prev_yr_cnt#135, curr_yr_cnt#136, sales_cnt_diff#137, sales_amt_diff#138] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#5 IN dynamicpruning#6 +BroadcastExchange (133) ++- * ColumnarToRow (132) + +- CometFilter (131) + +- CometScan parquet spark_catalog.default.date_dim (130) + + +(130) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#13, d_year#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2002), IsNotNull(d_date_sk)] +ReadSchema: struct + +(131) CometFilter +Input [2]: [d_date_sk#13, d_year#14] +Condition : ((isnotnull(d_year#14) AND (d_year#14 = 2002)) AND isnotnull(d_date_sk#13)) + +(132) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#13, d_year#14] + +(133) BroadcastExchange +Input [2]: [d_date_sk#13, d_year#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=17] + +Subquery:2 Hosting operator id = 24 Hosting Expression = ss_sold_date_sk#26 IN dynamicpruning#6 + +Subquery:3 Hosting operator id = 43 Hosting Expression = ws_sold_date_sk#46 IN dynamicpruning#6 + +Subquery:4 Hosting operator id = 72 Hosting Expression = cs_sold_date_sk#74 IN dynamicpruning#75 +BroadcastExchange (137) ++- * ColumnarToRow (136) + +- CometFilter (135) + +- CometScan parquet spark_catalog.default.date_dim (134) + + +(134) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#81, d_year#82] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(135) CometFilter +Input [2]: [d_date_sk#81, d_year#82] +Condition : ((isnotnull(d_year#82) AND (d_year#82 = 2001)) AND isnotnull(d_date_sk#81)) + +(136) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#81, d_year#82] + +(137) BroadcastExchange +Input [2]: [d_date_sk#81, d_year#82] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=18] + +Subquery:5 Hosting operator id = 87 Hosting Expression = ss_sold_date_sk#93 IN dynamicpruning#75 + +Subquery:6 Hosting operator id = 102 Hosting Expression = ws_sold_date_sk#112 IN dynamicpruning#75 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q75/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q75/simplified.txt new file mode 100644 index 0000000000..44bcabcdb1 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q75/simplified.txt @@ -0,0 +1,240 @@ +TakeOrderedAndProject [sales_cnt_diff,prev_year,year,i_brand_id,i_class_id,i_category_id,i_manufact_id,prev_yr_cnt,curr_yr_cnt,sales_amt_diff] + WholeStageCodegen (51) + Project [d_year,d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_cnt,sales_amt,sales_amt] + SortMergeJoin [i_brand_id,i_class_id,i_category_id,i_manufact_id,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_cnt] + InputAdapter + WholeStageCodegen (25) + Sort [i_brand_id,i_class_id,i_category_id,i_manufact_id] + InputAdapter + Exchange [i_brand_id,i_class_id,i_category_id,i_manufact_id] #1 + WholeStageCodegen (24) + Filter [sales_cnt] + HashAggregate [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sum,sum] [sum(sales_cnt),sum(UnscaledValue(sales_amt)),sales_cnt,sales_amt,sum,sum] + InputAdapter + Exchange [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id] #2 + WholeStageCodegen (23) + HashAggregate [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_amt] [sum,sum,sum,sum] + HashAggregate [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_amt] + InputAdapter + Exchange [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_amt] #3 + WholeStageCodegen (22) + HashAggregate [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_amt] + InputAdapter + Union + WholeStageCodegen (7) + Project [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,cs_quantity,cr_return_quantity,cs_ext_sales_price,cr_return_amount] + SortMergeJoin [cs_order_number,cs_item_sk,cr_order_number,cr_item_sk] + InputAdapter + WholeStageCodegen (4) + Sort [cs_order_number,cs_item_sk] + InputAdapter + Exchange [cs_order_number,cs_item_sk] #4 + WholeStageCodegen (3) + Project [cs_item_sk,cs_order_number,cs_quantity,cs_ext_sales_price,i_brand_id,i_class_id,i_category_id,i_manufact_id,d_year] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_item_sk,cs_order_number,cs_quantity,cs_ext_sales_price,cs_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_order_number,cs_quantity,cs_ext_sales_price,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #5 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] + CometFilter [i_category,i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id,i_category,i_manufact_id] + InputAdapter + ReusedExchange [d_date_sk,d_year] #5 + InputAdapter + WholeStageCodegen (6) + Sort [cr_order_number,cr_item_sk] + InputAdapter + Exchange [cr_order_number,cr_item_sk] #7 + WholeStageCodegen (5) + ColumnarToRow + InputAdapter + CometProject [cr_item_sk,cr_order_number,cr_return_quantity,cr_return_amount] + CometFilter [cr_order_number,cr_item_sk] + CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_return_quantity,cr_return_amount,cr_returned_date_sk] + WholeStageCodegen (14) + Project [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,ss_quantity,sr_return_quantity,ss_ext_sales_price,sr_return_amt] + SortMergeJoin [ss_ticket_number,ss_item_sk,sr_ticket_number,sr_item_sk] + InputAdapter + WholeStageCodegen (11) + Sort [ss_ticket_number,ss_item_sk] + InputAdapter + Exchange [ss_ticket_number,ss_item_sk] #8 + WholeStageCodegen (10) + Project [ss_item_sk,ss_ticket_number,ss_quantity,ss_ext_sales_price,i_brand_id,i_class_id,i_category_id,i_manufact_id,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_ticket_number,ss_quantity,ss_ext_sales_price,ss_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ticket_number,ss_quantity,ss_ext_sales_price,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] #6 + InputAdapter + ReusedExchange [d_date_sk,d_year] #5 + InputAdapter + WholeStageCodegen (13) + Sort [sr_ticket_number,sr_item_sk] + InputAdapter + Exchange [sr_ticket_number,sr_item_sk] #9 + WholeStageCodegen (12) + ColumnarToRow + InputAdapter + CometProject [sr_item_sk,sr_ticket_number,sr_return_quantity,sr_return_amt] + CometFilter [sr_ticket_number,sr_item_sk] + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_return_quantity,sr_return_amt,sr_returned_date_sk] + WholeStageCodegen (21) + Project [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,ws_quantity,wr_return_quantity,ws_ext_sales_price,wr_return_amt] + SortMergeJoin [ws_order_number,ws_item_sk,wr_order_number,wr_item_sk] + InputAdapter + WholeStageCodegen (18) + Sort [ws_order_number,ws_item_sk] + InputAdapter + Exchange [ws_order_number,ws_item_sk] #10 + WholeStageCodegen (17) + Project [ws_item_sk,ws_order_number,ws_quantity,ws_ext_sales_price,i_brand_id,i_class_id,i_category_id,i_manufact_id,d_year] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_item_sk,ws_order_number,ws_quantity,ws_ext_sales_price,ws_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] + BroadcastHashJoin [ws_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_order_number,ws_quantity,ws_ext_sales_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] #6 + InputAdapter + ReusedExchange [d_date_sk,d_year] #5 + InputAdapter + WholeStageCodegen (20) + Sort [wr_order_number,wr_item_sk] + InputAdapter + Exchange [wr_order_number,wr_item_sk] #11 + WholeStageCodegen (19) + ColumnarToRow + InputAdapter + CometProject [wr_item_sk,wr_order_number,wr_return_quantity,wr_return_amt] + CometFilter [wr_order_number,wr_item_sk] + CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_order_number,wr_return_quantity,wr_return_amt,wr_returned_date_sk] + InputAdapter + WholeStageCodegen (50) + Sort [i_brand_id,i_class_id,i_category_id,i_manufact_id] + InputAdapter + Exchange [i_brand_id,i_class_id,i_category_id,i_manufact_id] #12 + WholeStageCodegen (49) + Filter [sales_cnt] + HashAggregate [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sum,sum] [sum(sales_cnt),sum(UnscaledValue(sales_amt)),sales_cnt,sales_amt,sum,sum] + InputAdapter + Exchange [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id] #13 + WholeStageCodegen (48) + HashAggregate [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_amt] [sum,sum,sum,sum] + HashAggregate [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_amt] + InputAdapter + Exchange [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_amt] #14 + WholeStageCodegen (47) + HashAggregate [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_amt] + InputAdapter + Union + WholeStageCodegen (32) + Project [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,cs_quantity,cr_return_quantity,cs_ext_sales_price,cr_return_amount] + SortMergeJoin [cs_order_number,cs_item_sk,cr_order_number,cr_item_sk] + InputAdapter + WholeStageCodegen (29) + Sort [cs_order_number,cs_item_sk] + InputAdapter + Exchange [cs_order_number,cs_item_sk] #15 + WholeStageCodegen (28) + Project [cs_item_sk,cs_order_number,cs_quantity,cs_ext_sales_price,i_brand_id,i_class_id,i_category_id,i_manufact_id,d_year] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_item_sk,cs_order_number,cs_quantity,cs_ext_sales_price,cs_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_order_number,cs_quantity,cs_ext_sales_price,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #16 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] #6 + InputAdapter + ReusedExchange [d_date_sk,d_year] #16 + InputAdapter + WholeStageCodegen (31) + Sort [cr_order_number,cr_item_sk] + InputAdapter + ReusedExchange [cr_item_sk,cr_order_number,cr_return_quantity,cr_return_amount] #7 + WholeStageCodegen (39) + Project [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,ss_quantity,sr_return_quantity,ss_ext_sales_price,sr_return_amt] + SortMergeJoin [ss_ticket_number,ss_item_sk,sr_ticket_number,sr_item_sk] + InputAdapter + WholeStageCodegen (36) + Sort [ss_ticket_number,ss_item_sk] + InputAdapter + Exchange [ss_ticket_number,ss_item_sk] #17 + WholeStageCodegen (35) + Project [ss_item_sk,ss_ticket_number,ss_quantity,ss_ext_sales_price,i_brand_id,i_class_id,i_category_id,i_manufact_id,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_ticket_number,ss_quantity,ss_ext_sales_price,ss_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ticket_number,ss_quantity,ss_ext_sales_price,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] #6 + InputAdapter + ReusedExchange [d_date_sk,d_year] #16 + InputAdapter + WholeStageCodegen (38) + Sort [sr_ticket_number,sr_item_sk] + InputAdapter + ReusedExchange [sr_item_sk,sr_ticket_number,sr_return_quantity,sr_return_amt] #9 + WholeStageCodegen (46) + Project [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,ws_quantity,wr_return_quantity,ws_ext_sales_price,wr_return_amt] + SortMergeJoin [ws_order_number,ws_item_sk,wr_order_number,wr_item_sk] + InputAdapter + WholeStageCodegen (43) + Sort [ws_order_number,ws_item_sk] + InputAdapter + Exchange [ws_order_number,ws_item_sk] #18 + WholeStageCodegen (42) + Project [ws_item_sk,ws_order_number,ws_quantity,ws_ext_sales_price,i_brand_id,i_class_id,i_category_id,i_manufact_id,d_year] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_item_sk,ws_order_number,ws_quantity,ws_ext_sales_price,ws_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] + BroadcastHashJoin [ws_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_order_number,ws_quantity,ws_ext_sales_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] #6 + InputAdapter + ReusedExchange [d_date_sk,d_year] #16 + InputAdapter + WholeStageCodegen (45) + Sort [wr_order_number,wr_item_sk] + InputAdapter + ReusedExchange [wr_item_sk,wr_order_number,wr_return_quantity,wr_return_amt] #11 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q76/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q76/explain.txt new file mode 100644 index 0000000000..f3b80d8bdf --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q76/explain.txt @@ -0,0 +1,218 @@ +== Physical Plan == +TakeOrderedAndProject (38) ++- * HashAggregate (37) + +- Exchange (36) + +- * HashAggregate (35) + +- Union (34) + :- * Project (15) + : +- * BroadcastHashJoin Inner BuildRight (14) + : :- * Project (9) + : : +- * BroadcastHashJoin Inner BuildRight (8) + : : :- * ColumnarToRow (3) + : : : +- CometFilter (2) + : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : +- BroadcastExchange (7) + : : +- * ColumnarToRow (6) + : : +- CometFilter (5) + : : +- CometScan parquet spark_catalog.default.item (4) + : +- BroadcastExchange (13) + : +- * ColumnarToRow (12) + : +- CometFilter (11) + : +- CometScan parquet spark_catalog.default.date_dim (10) + :- * Project (24) + : +- * BroadcastHashJoin Inner BuildRight (23) + : :- * Project (21) + : : +- * BroadcastHashJoin Inner BuildRight (20) + : : :- * ColumnarToRow (18) + : : : +- CometFilter (17) + : : : +- CometScan parquet spark_catalog.default.web_sales (16) + : : +- ReusedExchange (19) + : +- ReusedExchange (22) + +- * Project (33) + +- * BroadcastHashJoin Inner BuildRight (32) + :- * Project (30) + : +- * BroadcastHashJoin Inner BuildRight (29) + : :- * ColumnarToRow (27) + : : +- CometFilter (26) + : : +- CometScan parquet spark_catalog.default.catalog_sales (25) + : +- ReusedExchange (28) + +- ReusedExchange (31) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#4)] +PushedFilters: [IsNull(ss_store_sk), IsNotNull(ss_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [4]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4] +Condition : (isnull(ss_store_sk#2) AND isnotnull(ss_item_sk#1)) + +(3) ColumnarToRow [codegen id : 3] +Input [4]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4] + +(4) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#5, i_category#6] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(5) CometFilter +Input [2]: [i_item_sk#5, i_category#6] +Condition : isnotnull(i_item_sk#5) + +(6) ColumnarToRow [codegen id : 1] +Input [2]: [i_item_sk#5, i_category#6] + +(7) BroadcastExchange +Input [2]: [i_item_sk#5, i_category#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#5] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 3] +Output [4]: [ss_store_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4, i_category#6] +Input [6]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4, i_item_sk#5, i_category#6] + +(10) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#7, d_year#8, d_qoy#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date_sk)] +ReadSchema: struct + +(11) CometFilter +Input [3]: [d_date_sk#7, d_year#8, d_qoy#9] +Condition : isnotnull(d_date_sk#7) + +(12) ColumnarToRow [codegen id : 2] +Input [3]: [d_date_sk#7, d_year#8, d_qoy#9] + +(13) BroadcastExchange +Input [3]: [d_date_sk#7, d_year#8, d_qoy#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(14) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_sold_date_sk#4] +Right keys [1]: [d_date_sk#7] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 3] +Output [6]: [store AS channel#10, ss_store_sk#2 AS col_name#11, d_year#8, d_qoy#9, i_category#6, ss_ext_sales_price#3 AS ext_sales_price#12] +Input [7]: [ss_store_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4, i_category#6, d_date_sk#7, d_year#8, d_qoy#9] + +(16) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_item_sk#13, ws_ship_customer_sk#14, ws_ext_sales_price#15, ws_sold_date_sk#16] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#16)] +PushedFilters: [IsNull(ws_ship_customer_sk), IsNotNull(ws_item_sk)] +ReadSchema: struct + +(17) CometFilter +Input [4]: [ws_item_sk#13, ws_ship_customer_sk#14, ws_ext_sales_price#15, ws_sold_date_sk#16] +Condition : (isnull(ws_ship_customer_sk#14) AND isnotnull(ws_item_sk#13)) + +(18) ColumnarToRow [codegen id : 6] +Input [4]: [ws_item_sk#13, ws_ship_customer_sk#14, ws_ext_sales_price#15, ws_sold_date_sk#16] + +(19) ReusedExchange [Reuses operator id: 7] +Output [2]: [i_item_sk#17, i_category#18] + +(20) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ws_item_sk#13] +Right keys [1]: [i_item_sk#17] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 6] +Output [4]: [ws_ship_customer_sk#14, ws_ext_sales_price#15, ws_sold_date_sk#16, i_category#18] +Input [6]: [ws_item_sk#13, ws_ship_customer_sk#14, ws_ext_sales_price#15, ws_sold_date_sk#16, i_item_sk#17, i_category#18] + +(22) ReusedExchange [Reuses operator id: 13] +Output [3]: [d_date_sk#19, d_year#20, d_qoy#21] + +(23) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ws_sold_date_sk#16] +Right keys [1]: [d_date_sk#19] +Join type: Inner +Join condition: None + +(24) Project [codegen id : 6] +Output [6]: [web AS channel#22, ws_ship_customer_sk#14 AS col_name#23, d_year#20, d_qoy#21, i_category#18, ws_ext_sales_price#15 AS ext_sales_price#24] +Input [7]: [ws_ship_customer_sk#14, ws_ext_sales_price#15, ws_sold_date_sk#16, i_category#18, d_date_sk#19, d_year#20, d_qoy#21] + +(25) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_ship_addr_sk#25, cs_item_sk#26, cs_ext_sales_price#27, cs_sold_date_sk#28] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#28)] +PushedFilters: [IsNull(cs_ship_addr_sk), IsNotNull(cs_item_sk)] +ReadSchema: struct + +(26) CometFilter +Input [4]: [cs_ship_addr_sk#25, cs_item_sk#26, cs_ext_sales_price#27, cs_sold_date_sk#28] +Condition : (isnull(cs_ship_addr_sk#25) AND isnotnull(cs_item_sk#26)) + +(27) ColumnarToRow [codegen id : 9] +Input [4]: [cs_ship_addr_sk#25, cs_item_sk#26, cs_ext_sales_price#27, cs_sold_date_sk#28] + +(28) ReusedExchange [Reuses operator id: 7] +Output [2]: [i_item_sk#29, i_category#30] + +(29) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [cs_item_sk#26] +Right keys [1]: [i_item_sk#29] +Join type: Inner +Join condition: None + +(30) Project [codegen id : 9] +Output [4]: [cs_ship_addr_sk#25, cs_ext_sales_price#27, cs_sold_date_sk#28, i_category#30] +Input [6]: [cs_ship_addr_sk#25, cs_item_sk#26, cs_ext_sales_price#27, cs_sold_date_sk#28, i_item_sk#29, i_category#30] + +(31) ReusedExchange [Reuses operator id: 13] +Output [3]: [d_date_sk#31, d_year#32, d_qoy#33] + +(32) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [cs_sold_date_sk#28] +Right keys [1]: [d_date_sk#31] +Join type: Inner +Join condition: None + +(33) Project [codegen id : 9] +Output [6]: [catalog AS channel#34, cs_ship_addr_sk#25 AS col_name#35, d_year#32, d_qoy#33, i_category#30, cs_ext_sales_price#27 AS ext_sales_price#36] +Input [7]: [cs_ship_addr_sk#25, cs_ext_sales_price#27, cs_sold_date_sk#28, i_category#30, d_date_sk#31, d_year#32, d_qoy#33] + +(34) Union + +(35) HashAggregate [codegen id : 10] +Input [6]: [channel#10, col_name#11, d_year#8, d_qoy#9, i_category#6, ext_sales_price#12] +Keys [5]: [channel#10, col_name#11, d_year#8, d_qoy#9, i_category#6] +Functions [2]: [partial_count(1), partial_sum(UnscaledValue(ext_sales_price#12))] +Aggregate Attributes [2]: [count#37, sum#38] +Results [7]: [channel#10, col_name#11, d_year#8, d_qoy#9, i_category#6, count#39, sum#40] + +(36) Exchange +Input [7]: [channel#10, col_name#11, d_year#8, d_qoy#9, i_category#6, count#39, sum#40] +Arguments: hashpartitioning(channel#10, col_name#11, d_year#8, d_qoy#9, i_category#6, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(37) HashAggregate [codegen id : 11] +Input [7]: [channel#10, col_name#11, d_year#8, d_qoy#9, i_category#6, count#39, sum#40] +Keys [5]: [channel#10, col_name#11, d_year#8, d_qoy#9, i_category#6] +Functions [2]: [count(1), sum(UnscaledValue(ext_sales_price#12))] +Aggregate Attributes [2]: [count(1)#41, sum(UnscaledValue(ext_sales_price#12))#42] +Results [7]: [channel#10, col_name#11, d_year#8, d_qoy#9, i_category#6, count(1)#41 AS sales_cnt#43, MakeDecimal(sum(UnscaledValue(ext_sales_price#12))#42,17,2) AS sales_amt#44] + +(38) TakeOrderedAndProject +Input [7]: [channel#10, col_name#11, d_year#8, d_qoy#9, i_category#6, sales_cnt#43, sales_amt#44] +Arguments: 100, [channel#10 ASC NULLS FIRST, col_name#11 ASC NULLS FIRST, d_year#8 ASC NULLS FIRST, d_qoy#9 ASC NULLS FIRST, i_category#6 ASC NULLS FIRST], [channel#10, col_name#11, d_year#8, d_qoy#9, i_category#6, sales_cnt#43, sales_amt#44] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q76/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q76/simplified.txt new file mode 100644 index 0000000000..73e6b09afe --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q76/simplified.txt @@ -0,0 +1,58 @@ +TakeOrderedAndProject [channel,col_name,d_year,d_qoy,i_category,sales_cnt,sales_amt] + WholeStageCodegen (11) + HashAggregate [channel,col_name,d_year,d_qoy,i_category,count,sum] [count(1),sum(UnscaledValue(ext_sales_price)),sales_cnt,sales_amt,count,sum] + InputAdapter + Exchange [channel,col_name,d_year,d_qoy,i_category] #1 + WholeStageCodegen (10) + HashAggregate [channel,col_name,d_year,d_qoy,i_category,ext_sales_price] [count,sum,count,sum] + InputAdapter + Union + WholeStageCodegen (3) + Project [ss_store_sk,d_year,d_qoy,i_category,ss_ext_sales_price] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_store_sk,ss_ext_sales_price,ss_sold_date_sk,i_category] + BroadcastHashJoin [ss_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk,ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_ext_sales_price,ss_sold_date_sk] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_category] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_qoy] + WholeStageCodegen (6) + Project [ws_ship_customer_sk,d_year,d_qoy,i_category,ws_ext_sales_price] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_ship_customer_sk,ws_ext_sales_price,ws_sold_date_sk,i_category] + BroadcastHashJoin [ws_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [ws_ship_customer_sk,ws_item_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_ship_customer_sk,ws_ext_sales_price,ws_sold_date_sk] + InputAdapter + ReusedExchange [i_item_sk,i_category] #2 + InputAdapter + ReusedExchange [d_date_sk,d_year,d_qoy] #3 + WholeStageCodegen (9) + Project [cs_ship_addr_sk,d_year,d_qoy,i_category,cs_ext_sales_price] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_ship_addr_sk,cs_ext_sales_price,cs_sold_date_sk,i_category] + BroadcastHashJoin [cs_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [cs_ship_addr_sk,cs_item_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_ship_addr_sk,cs_item_sk,cs_ext_sales_price,cs_sold_date_sk] + InputAdapter + ReusedExchange [i_item_sk,i_category] #2 + InputAdapter + ReusedExchange [d_date_sk,d_year,d_qoy] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q77/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q77/explain.txt new file mode 100644 index 0000000000..bbfa6a4c4a --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q77/explain.txt @@ -0,0 +1,547 @@ +== Physical Plan == +TakeOrderedAndProject (85) ++- * HashAggregate (84) + +- Exchange (83) + +- * HashAggregate (82) + +- * Expand (81) + +- Union (80) + :- * Project (30) + : +- * BroadcastHashJoin LeftOuter BuildRight (29) + : :- * HashAggregate (15) + : : +- Exchange (14) + : : +- * HashAggregate (13) + : : +- * Project (12) + : : +- * BroadcastHashJoin Inner BuildRight (11) + : : :- * Project (6) + : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- ReusedExchange (4) + : : +- BroadcastExchange (10) + : : +- * ColumnarToRow (9) + : : +- CometFilter (8) + : : +- CometScan parquet spark_catalog.default.store (7) + : +- BroadcastExchange (28) + : +- * HashAggregate (27) + : +- Exchange (26) + : +- * HashAggregate (25) + : +- * Project (24) + : +- * BroadcastHashJoin Inner BuildRight (23) + : :- * Project (21) + : : +- * BroadcastHashJoin Inner BuildRight (20) + : : :- * ColumnarToRow (18) + : : : +- CometFilter (17) + : : : +- CometScan parquet spark_catalog.default.store_returns (16) + : : +- ReusedExchange (19) + : +- ReusedExchange (22) + :- * Project (49) + : +- * BroadcastNestedLoopJoin Inner BuildLeft (48) + : :- BroadcastExchange (39) + : : +- * HashAggregate (38) + : : +- Exchange (37) + : : +- * HashAggregate (36) + : : +- * Project (35) + : : +- * BroadcastHashJoin Inner BuildRight (34) + : : :- * ColumnarToRow (32) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (31) + : : +- ReusedExchange (33) + : +- * HashAggregate (47) + : +- Exchange (46) + : +- * HashAggregate (45) + : +- * Project (44) + : +- * BroadcastHashJoin Inner BuildRight (43) + : :- * ColumnarToRow (41) + : : +- CometScan parquet spark_catalog.default.catalog_returns (40) + : +- ReusedExchange (42) + +- * Project (79) + +- * BroadcastHashJoin LeftOuter BuildRight (78) + :- * HashAggregate (64) + : +- Exchange (63) + : +- * HashAggregate (62) + : +- * Project (61) + : +- * BroadcastHashJoin Inner BuildRight (60) + : :- * Project (55) + : : +- * BroadcastHashJoin Inner BuildRight (54) + : : :- * ColumnarToRow (52) + : : : +- CometFilter (51) + : : : +- CometScan parquet spark_catalog.default.web_sales (50) + : : +- ReusedExchange (53) + : +- BroadcastExchange (59) + : +- * ColumnarToRow (58) + : +- CometFilter (57) + : +- CometScan parquet spark_catalog.default.web_page (56) + +- BroadcastExchange (77) + +- * HashAggregate (76) + +- Exchange (75) + +- * HashAggregate (74) + +- * Project (73) + +- * BroadcastHashJoin Inner BuildRight (72) + :- * Project (70) + : +- * BroadcastHashJoin Inner BuildRight (69) + : :- * ColumnarToRow (67) + : : +- CometFilter (66) + : : +- CometScan parquet spark_catalog.default.web_returns (65) + : +- ReusedExchange (68) + +- ReusedExchange (71) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#4), dynamicpruningexpression(ss_sold_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(ss_store_sk)] +ReadSchema: struct + +(2) CometFilter +Input [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] +Condition : isnotnull(ss_store_sk#1) + +(3) ColumnarToRow [codegen id : 3] +Input [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] + +(4) ReusedExchange [Reuses operator id: 90] +Output [1]: [d_date_sk#6] + +(5) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_sold_date_sk#4] +Right keys [1]: [d_date_sk#6] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 3] +Output [3]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3] +Input [5]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4, d_date_sk#6] + +(7) Scan parquet spark_catalog.default.store +Output [1]: [s_store_sk#7] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(8) CometFilter +Input [1]: [s_store_sk#7] +Condition : isnotnull(s_store_sk#7) + +(9) ColumnarToRow [codegen id : 2] +Input [1]: [s_store_sk#7] + +(10) BroadcastExchange +Input [1]: [s_store_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_store_sk#1] +Right keys [1]: [s_store_sk#7] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [3]: [ss_ext_sales_price#2, ss_net_profit#3, s_store_sk#7] +Input [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, s_store_sk#7] + +(13) HashAggregate [codegen id : 3] +Input [3]: [ss_ext_sales_price#2, ss_net_profit#3, s_store_sk#7] +Keys [1]: [s_store_sk#7] +Functions [2]: [partial_sum(UnscaledValue(ss_ext_sales_price#2)), partial_sum(UnscaledValue(ss_net_profit#3))] +Aggregate Attributes [2]: [sum#8, sum#9] +Results [3]: [s_store_sk#7, sum#10, sum#11] + +(14) Exchange +Input [3]: [s_store_sk#7, sum#10, sum#11] +Arguments: hashpartitioning(s_store_sk#7, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 8] +Input [3]: [s_store_sk#7, sum#10, sum#11] +Keys [1]: [s_store_sk#7] +Functions [2]: [sum(UnscaledValue(ss_ext_sales_price#2)), sum(UnscaledValue(ss_net_profit#3))] +Aggregate Attributes [2]: [sum(UnscaledValue(ss_ext_sales_price#2))#12, sum(UnscaledValue(ss_net_profit#3))#13] +Results [3]: [s_store_sk#7, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#2))#12,17,2) AS sales#14, MakeDecimal(sum(UnscaledValue(ss_net_profit#3))#13,17,2) AS profit#15] + +(16) Scan parquet spark_catalog.default.store_returns +Output [4]: [sr_store_sk#16, sr_return_amt#17, sr_net_loss#18, sr_returned_date_sk#19] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(sr_returned_date_sk#19), dynamicpruningexpression(sr_returned_date_sk#19 IN dynamicpruning#20)] +PushedFilters: [IsNotNull(sr_store_sk)] +ReadSchema: struct + +(17) CometFilter +Input [4]: [sr_store_sk#16, sr_return_amt#17, sr_net_loss#18, sr_returned_date_sk#19] +Condition : isnotnull(sr_store_sk#16) + +(18) ColumnarToRow [codegen id : 6] +Input [4]: [sr_store_sk#16, sr_return_amt#17, sr_net_loss#18, sr_returned_date_sk#19] + +(19) ReusedExchange [Reuses operator id: 90] +Output [1]: [d_date_sk#21] + +(20) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [sr_returned_date_sk#19] +Right keys [1]: [d_date_sk#21] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 6] +Output [3]: [sr_store_sk#16, sr_return_amt#17, sr_net_loss#18] +Input [5]: [sr_store_sk#16, sr_return_amt#17, sr_net_loss#18, sr_returned_date_sk#19, d_date_sk#21] + +(22) ReusedExchange [Reuses operator id: 10] +Output [1]: [s_store_sk#22] + +(23) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [sr_store_sk#16] +Right keys [1]: [s_store_sk#22] +Join type: Inner +Join condition: None + +(24) Project [codegen id : 6] +Output [3]: [sr_return_amt#17, sr_net_loss#18, s_store_sk#22] +Input [4]: [sr_store_sk#16, sr_return_amt#17, sr_net_loss#18, s_store_sk#22] + +(25) HashAggregate [codegen id : 6] +Input [3]: [sr_return_amt#17, sr_net_loss#18, s_store_sk#22] +Keys [1]: [s_store_sk#22] +Functions [2]: [partial_sum(UnscaledValue(sr_return_amt#17)), partial_sum(UnscaledValue(sr_net_loss#18))] +Aggregate Attributes [2]: [sum#23, sum#24] +Results [3]: [s_store_sk#22, sum#25, sum#26] + +(26) Exchange +Input [3]: [s_store_sk#22, sum#25, sum#26] +Arguments: hashpartitioning(s_store_sk#22, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(27) HashAggregate [codegen id : 7] +Input [3]: [s_store_sk#22, sum#25, sum#26] +Keys [1]: [s_store_sk#22] +Functions [2]: [sum(UnscaledValue(sr_return_amt#17)), sum(UnscaledValue(sr_net_loss#18))] +Aggregate Attributes [2]: [sum(UnscaledValue(sr_return_amt#17))#27, sum(UnscaledValue(sr_net_loss#18))#28] +Results [3]: [s_store_sk#22, MakeDecimal(sum(UnscaledValue(sr_return_amt#17))#27,17,2) AS returns#29, MakeDecimal(sum(UnscaledValue(sr_net_loss#18))#28,17,2) AS profit_loss#30] + +(28) BroadcastExchange +Input [3]: [s_store_sk#22, returns#29, profit_loss#30] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(29) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [s_store_sk#7] +Right keys [1]: [s_store_sk#22] +Join type: LeftOuter +Join condition: None + +(30) Project [codegen id : 8] +Output [5]: [sales#14, coalesce(returns#29, 0.00) AS returns#31, (profit#15 - coalesce(profit_loss#30, 0.00)) AS profit#32, store channel AS channel#33, s_store_sk#7 AS id#34] +Input [6]: [s_store_sk#7, sales#14, profit#15, s_store_sk#22, returns#29, profit_loss#30] + +(31) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_call_center_sk#35, cs_ext_sales_price#36, cs_net_profit#37, cs_sold_date_sk#38] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#38), dynamicpruningexpression(cs_sold_date_sk#38 IN dynamicpruning#39)] +ReadSchema: struct + +(32) ColumnarToRow [codegen id : 10] +Input [4]: [cs_call_center_sk#35, cs_ext_sales_price#36, cs_net_profit#37, cs_sold_date_sk#38] + +(33) ReusedExchange [Reuses operator id: 90] +Output [1]: [d_date_sk#40] + +(34) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_sold_date_sk#38] +Right keys [1]: [d_date_sk#40] +Join type: Inner +Join condition: None + +(35) Project [codegen id : 10] +Output [3]: [cs_call_center_sk#35, cs_ext_sales_price#36, cs_net_profit#37] +Input [5]: [cs_call_center_sk#35, cs_ext_sales_price#36, cs_net_profit#37, cs_sold_date_sk#38, d_date_sk#40] + +(36) HashAggregate [codegen id : 10] +Input [3]: [cs_call_center_sk#35, cs_ext_sales_price#36, cs_net_profit#37] +Keys [1]: [cs_call_center_sk#35] +Functions [2]: [partial_sum(UnscaledValue(cs_ext_sales_price#36)), partial_sum(UnscaledValue(cs_net_profit#37))] +Aggregate Attributes [2]: [sum#41, sum#42] +Results [3]: [cs_call_center_sk#35, sum#43, sum#44] + +(37) Exchange +Input [3]: [cs_call_center_sk#35, sum#43, sum#44] +Arguments: hashpartitioning(cs_call_center_sk#35, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(38) HashAggregate [codegen id : 11] +Input [3]: [cs_call_center_sk#35, sum#43, sum#44] +Keys [1]: [cs_call_center_sk#35] +Functions [2]: [sum(UnscaledValue(cs_ext_sales_price#36)), sum(UnscaledValue(cs_net_profit#37))] +Aggregate Attributes [2]: [sum(UnscaledValue(cs_ext_sales_price#36))#45, sum(UnscaledValue(cs_net_profit#37))#46] +Results [3]: [cs_call_center_sk#35, MakeDecimal(sum(UnscaledValue(cs_ext_sales_price#36))#45,17,2) AS sales#47, MakeDecimal(sum(UnscaledValue(cs_net_profit#37))#46,17,2) AS profit#48] + +(39) BroadcastExchange +Input [3]: [cs_call_center_sk#35, sales#47, profit#48] +Arguments: IdentityBroadcastMode, [plan_id=6] + +(40) Scan parquet spark_catalog.default.catalog_returns +Output [3]: [cr_return_amount#49, cr_net_loss#50, cr_returned_date_sk#51] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cr_returned_date_sk#51), dynamicpruningexpression(cr_returned_date_sk#51 IN dynamicpruning#52)] +ReadSchema: struct + +(41) ColumnarToRow [codegen id : 13] +Input [3]: [cr_return_amount#49, cr_net_loss#50, cr_returned_date_sk#51] + +(42) ReusedExchange [Reuses operator id: 90] +Output [1]: [d_date_sk#53] + +(43) BroadcastHashJoin [codegen id : 13] +Left keys [1]: [cr_returned_date_sk#51] +Right keys [1]: [d_date_sk#53] +Join type: Inner +Join condition: None + +(44) Project [codegen id : 13] +Output [2]: [cr_return_amount#49, cr_net_loss#50] +Input [4]: [cr_return_amount#49, cr_net_loss#50, cr_returned_date_sk#51, d_date_sk#53] + +(45) HashAggregate [codegen id : 13] +Input [2]: [cr_return_amount#49, cr_net_loss#50] +Keys: [] +Functions [2]: [partial_sum(UnscaledValue(cr_return_amount#49)), partial_sum(UnscaledValue(cr_net_loss#50))] +Aggregate Attributes [2]: [sum#54, sum#55] +Results [2]: [sum#56, sum#57] + +(46) Exchange +Input [2]: [sum#56, sum#57] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=7] + +(47) HashAggregate +Input [2]: [sum#56, sum#57] +Keys: [] +Functions [2]: [sum(UnscaledValue(cr_return_amount#49)), sum(UnscaledValue(cr_net_loss#50))] +Aggregate Attributes [2]: [sum(UnscaledValue(cr_return_amount#49))#58, sum(UnscaledValue(cr_net_loss#50))#59] +Results [2]: [MakeDecimal(sum(UnscaledValue(cr_return_amount#49))#58,17,2) AS returns#60, MakeDecimal(sum(UnscaledValue(cr_net_loss#50))#59,17,2) AS profit_loss#61] + +(48) BroadcastNestedLoopJoin [codegen id : 14] +Join type: Inner +Join condition: None + +(49) Project [codegen id : 14] +Output [5]: [sales#47, returns#60, (profit#48 - profit_loss#61) AS profit#62, catalog channel AS channel#63, cs_call_center_sk#35 AS id#64] +Input [5]: [cs_call_center_sk#35, sales#47, profit#48, returns#60, profit_loss#61] + +(50) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_web_page_sk#65, ws_ext_sales_price#66, ws_net_profit#67, ws_sold_date_sk#68] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#68), dynamicpruningexpression(ws_sold_date_sk#68 IN dynamicpruning#69)] +PushedFilters: [IsNotNull(ws_web_page_sk)] +ReadSchema: struct + +(51) CometFilter +Input [4]: [ws_web_page_sk#65, ws_ext_sales_price#66, ws_net_profit#67, ws_sold_date_sk#68] +Condition : isnotnull(ws_web_page_sk#65) + +(52) ColumnarToRow [codegen id : 17] +Input [4]: [ws_web_page_sk#65, ws_ext_sales_price#66, ws_net_profit#67, ws_sold_date_sk#68] + +(53) ReusedExchange [Reuses operator id: 90] +Output [1]: [d_date_sk#70] + +(54) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ws_sold_date_sk#68] +Right keys [1]: [d_date_sk#70] +Join type: Inner +Join condition: None + +(55) Project [codegen id : 17] +Output [3]: [ws_web_page_sk#65, ws_ext_sales_price#66, ws_net_profit#67] +Input [5]: [ws_web_page_sk#65, ws_ext_sales_price#66, ws_net_profit#67, ws_sold_date_sk#68, d_date_sk#70] + +(56) Scan parquet spark_catalog.default.web_page +Output [1]: [wp_web_page_sk#71] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_page] +PushedFilters: [IsNotNull(wp_web_page_sk)] +ReadSchema: struct + +(57) CometFilter +Input [1]: [wp_web_page_sk#71] +Condition : isnotnull(wp_web_page_sk#71) + +(58) ColumnarToRow [codegen id : 16] +Input [1]: [wp_web_page_sk#71] + +(59) BroadcastExchange +Input [1]: [wp_web_page_sk#71] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8] + +(60) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ws_web_page_sk#65] +Right keys [1]: [wp_web_page_sk#71] +Join type: Inner +Join condition: None + +(61) Project [codegen id : 17] +Output [3]: [ws_ext_sales_price#66, ws_net_profit#67, wp_web_page_sk#71] +Input [4]: [ws_web_page_sk#65, ws_ext_sales_price#66, ws_net_profit#67, wp_web_page_sk#71] + +(62) HashAggregate [codegen id : 17] +Input [3]: [ws_ext_sales_price#66, ws_net_profit#67, wp_web_page_sk#71] +Keys [1]: [wp_web_page_sk#71] +Functions [2]: [partial_sum(UnscaledValue(ws_ext_sales_price#66)), partial_sum(UnscaledValue(ws_net_profit#67))] +Aggregate Attributes [2]: [sum#72, sum#73] +Results [3]: [wp_web_page_sk#71, sum#74, sum#75] + +(63) Exchange +Input [3]: [wp_web_page_sk#71, sum#74, sum#75] +Arguments: hashpartitioning(wp_web_page_sk#71, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(64) HashAggregate [codegen id : 22] +Input [3]: [wp_web_page_sk#71, sum#74, sum#75] +Keys [1]: [wp_web_page_sk#71] +Functions [2]: [sum(UnscaledValue(ws_ext_sales_price#66)), sum(UnscaledValue(ws_net_profit#67))] +Aggregate Attributes [2]: [sum(UnscaledValue(ws_ext_sales_price#66))#76, sum(UnscaledValue(ws_net_profit#67))#77] +Results [3]: [wp_web_page_sk#71, MakeDecimal(sum(UnscaledValue(ws_ext_sales_price#66))#76,17,2) AS sales#78, MakeDecimal(sum(UnscaledValue(ws_net_profit#67))#77,17,2) AS profit#79] + +(65) Scan parquet spark_catalog.default.web_returns +Output [4]: [wr_web_page_sk#80, wr_return_amt#81, wr_net_loss#82, wr_returned_date_sk#83] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(wr_returned_date_sk#83), dynamicpruningexpression(wr_returned_date_sk#83 IN dynamicpruning#84)] +PushedFilters: [IsNotNull(wr_web_page_sk)] +ReadSchema: struct + +(66) CometFilter +Input [4]: [wr_web_page_sk#80, wr_return_amt#81, wr_net_loss#82, wr_returned_date_sk#83] +Condition : isnotnull(wr_web_page_sk#80) + +(67) ColumnarToRow [codegen id : 20] +Input [4]: [wr_web_page_sk#80, wr_return_amt#81, wr_net_loss#82, wr_returned_date_sk#83] + +(68) ReusedExchange [Reuses operator id: 90] +Output [1]: [d_date_sk#85] + +(69) BroadcastHashJoin [codegen id : 20] +Left keys [1]: [wr_returned_date_sk#83] +Right keys [1]: [d_date_sk#85] +Join type: Inner +Join condition: None + +(70) Project [codegen id : 20] +Output [3]: [wr_web_page_sk#80, wr_return_amt#81, wr_net_loss#82] +Input [5]: [wr_web_page_sk#80, wr_return_amt#81, wr_net_loss#82, wr_returned_date_sk#83, d_date_sk#85] + +(71) ReusedExchange [Reuses operator id: 59] +Output [1]: [wp_web_page_sk#86] + +(72) BroadcastHashJoin [codegen id : 20] +Left keys [1]: [wr_web_page_sk#80] +Right keys [1]: [wp_web_page_sk#86] +Join type: Inner +Join condition: None + +(73) Project [codegen id : 20] +Output [3]: [wr_return_amt#81, wr_net_loss#82, wp_web_page_sk#86] +Input [4]: [wr_web_page_sk#80, wr_return_amt#81, wr_net_loss#82, wp_web_page_sk#86] + +(74) HashAggregate [codegen id : 20] +Input [3]: [wr_return_amt#81, wr_net_loss#82, wp_web_page_sk#86] +Keys [1]: [wp_web_page_sk#86] +Functions [2]: [partial_sum(UnscaledValue(wr_return_amt#81)), partial_sum(UnscaledValue(wr_net_loss#82))] +Aggregate Attributes [2]: [sum#87, sum#88] +Results [3]: [wp_web_page_sk#86, sum#89, sum#90] + +(75) Exchange +Input [3]: [wp_web_page_sk#86, sum#89, sum#90] +Arguments: hashpartitioning(wp_web_page_sk#86, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(76) HashAggregate [codegen id : 21] +Input [3]: [wp_web_page_sk#86, sum#89, sum#90] +Keys [1]: [wp_web_page_sk#86] +Functions [2]: [sum(UnscaledValue(wr_return_amt#81)), sum(UnscaledValue(wr_net_loss#82))] +Aggregate Attributes [2]: [sum(UnscaledValue(wr_return_amt#81))#91, sum(UnscaledValue(wr_net_loss#82))#92] +Results [3]: [wp_web_page_sk#86, MakeDecimal(sum(UnscaledValue(wr_return_amt#81))#91,17,2) AS returns#93, MakeDecimal(sum(UnscaledValue(wr_net_loss#82))#92,17,2) AS profit_loss#94] + +(77) BroadcastExchange +Input [3]: [wp_web_page_sk#86, returns#93, profit_loss#94] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=11] + +(78) BroadcastHashJoin [codegen id : 22] +Left keys [1]: [wp_web_page_sk#71] +Right keys [1]: [wp_web_page_sk#86] +Join type: LeftOuter +Join condition: None + +(79) Project [codegen id : 22] +Output [5]: [sales#78, coalesce(returns#93, 0.00) AS returns#95, (profit#79 - coalesce(profit_loss#94, 0.00)) AS profit#96, web channel AS channel#97, wp_web_page_sk#71 AS id#98] +Input [6]: [wp_web_page_sk#71, sales#78, profit#79, wp_web_page_sk#86, returns#93, profit_loss#94] + +(80) Union + +(81) Expand [codegen id : 23] +Input [5]: [sales#14, returns#31, profit#32, channel#33, id#34] +Arguments: [[sales#14, returns#31, profit#32, channel#33, id#34, 0], [sales#14, returns#31, profit#32, channel#33, null, 1], [sales#14, returns#31, profit#32, null, null, 3]], [sales#14, returns#31, profit#32, channel#99, id#100, spark_grouping_id#101] + +(82) HashAggregate [codegen id : 23] +Input [6]: [sales#14, returns#31, profit#32, channel#99, id#100, spark_grouping_id#101] +Keys [3]: [channel#99, id#100, spark_grouping_id#101] +Functions [3]: [partial_sum(sales#14), partial_sum(returns#31), partial_sum(profit#32)] +Aggregate Attributes [6]: [sum#102, isEmpty#103, sum#104, isEmpty#105, sum#106, isEmpty#107] +Results [9]: [channel#99, id#100, spark_grouping_id#101, sum#108, isEmpty#109, sum#110, isEmpty#111, sum#112, isEmpty#113] + +(83) Exchange +Input [9]: [channel#99, id#100, spark_grouping_id#101, sum#108, isEmpty#109, sum#110, isEmpty#111, sum#112, isEmpty#113] +Arguments: hashpartitioning(channel#99, id#100, spark_grouping_id#101, 5), ENSURE_REQUIREMENTS, [plan_id=12] + +(84) HashAggregate [codegen id : 24] +Input [9]: [channel#99, id#100, spark_grouping_id#101, sum#108, isEmpty#109, sum#110, isEmpty#111, sum#112, isEmpty#113] +Keys [3]: [channel#99, id#100, spark_grouping_id#101] +Functions [3]: [sum(sales#14), sum(returns#31), sum(profit#32)] +Aggregate Attributes [3]: [sum(sales#14)#114, sum(returns#31)#115, sum(profit#32)#116] +Results [5]: [channel#99, id#100, sum(sales#14)#114 AS sales#117, sum(returns#31)#115 AS returns#118, sum(profit#32)#116 AS profit#119] + +(85) TakeOrderedAndProject +Input [5]: [channel#99, id#100, sales#117, returns#118, profit#119] +Arguments: 100, [channel#99 ASC NULLS FIRST, id#100 ASC NULLS FIRST], [channel#99, id#100, sales#117, returns#118, profit#119] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (90) ++- * ColumnarToRow (89) + +- CometProject (88) + +- CometFilter (87) + +- CometScan parquet spark_catalog.default.date_dim (86) + + +(86) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#6, d_date#120] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,2000-08-03), LessThanOrEqual(d_date,2000-09-02), IsNotNull(d_date_sk)] +ReadSchema: struct + +(87) CometFilter +Input [2]: [d_date_sk#6, d_date#120] +Condition : (((isnotnull(d_date#120) AND (d_date#120 >= 2000-08-03)) AND (d_date#120 <= 2000-09-02)) AND isnotnull(d_date_sk#6)) + +(88) CometProject +Input [2]: [d_date_sk#6, d_date#120] +Arguments: [d_date_sk#6], [d_date_sk#6] + +(89) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#6] + +(90) BroadcastExchange +Input [1]: [d_date_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=13] + +Subquery:2 Hosting operator id = 16 Hosting Expression = sr_returned_date_sk#19 IN dynamicpruning#5 + +Subquery:3 Hosting operator id = 31 Hosting Expression = cs_sold_date_sk#38 IN dynamicpruning#5 + +Subquery:4 Hosting operator id = 40 Hosting Expression = cr_returned_date_sk#51 IN dynamicpruning#5 + +Subquery:5 Hosting operator id = 50 Hosting Expression = ws_sold_date_sk#68 IN dynamicpruning#5 + +Subquery:6 Hosting operator id = 65 Hosting Expression = wr_returned_date_sk#83 IN dynamicpruning#5 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q77/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q77/simplified.txt new file mode 100644 index 0000000000..d6693067f0 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q77/simplified.txt @@ -0,0 +1,143 @@ +TakeOrderedAndProject [channel,id,sales,returns,profit] + WholeStageCodegen (24) + HashAggregate [channel,id,spark_grouping_id,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [channel,id,spark_grouping_id] #1 + WholeStageCodegen (23) + HashAggregate [channel,id,spark_grouping_id,sales,returns,profit] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + Expand [sales,returns,profit,channel,id] + InputAdapter + Union + WholeStageCodegen (8) + Project [sales,returns,profit,profit_loss,s_store_sk] + BroadcastHashJoin [s_store_sk,s_store_sk] + HashAggregate [s_store_sk,sum,sum] [sum(UnscaledValue(ss_ext_sales_price)),sum(UnscaledValue(ss_net_profit)),sales,profit,sum,sum] + InputAdapter + Exchange [s_store_sk] #2 + WholeStageCodegen (3) + HashAggregate [s_store_sk,ss_ext_sales_price,ss_net_profit] [sum,sum,sum,sum] + Project [ss_ext_sales_price,ss_net_profit,s_store_sk] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_store_sk,ss_ext_sales_price,ss_net_profit] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_store_sk,ss_ext_sales_price,ss_net_profit,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (7) + HashAggregate [s_store_sk,sum,sum] [sum(UnscaledValue(sr_return_amt)),sum(UnscaledValue(sr_net_loss)),returns,profit_loss,sum,sum] + InputAdapter + Exchange [s_store_sk] #6 + WholeStageCodegen (6) + HashAggregate [s_store_sk,sr_return_amt,sr_net_loss] [sum,sum,sum,sum] + Project [sr_return_amt,sr_net_loss,s_store_sk] + BroadcastHashJoin [sr_store_sk,s_store_sk] + Project [sr_store_sk,sr_return_amt,sr_net_loss] + BroadcastHashJoin [sr_returned_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [sr_store_sk] + CometScan parquet spark_catalog.default.store_returns [sr_store_sk,sr_return_amt,sr_net_loss,sr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + ReusedExchange [s_store_sk] #4 + WholeStageCodegen (14) + Project [sales,returns,profit,profit_loss,cs_call_center_sk] + BroadcastNestedLoopJoin + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (11) + HashAggregate [cs_call_center_sk,sum,sum] [sum(UnscaledValue(cs_ext_sales_price)),sum(UnscaledValue(cs_net_profit)),sales,profit,sum,sum] + InputAdapter + Exchange [cs_call_center_sk] #8 + WholeStageCodegen (10) + HashAggregate [cs_call_center_sk,cs_ext_sales_price,cs_net_profit] [sum,sum,sum,sum] + Project [cs_call_center_sk,cs_ext_sales_price,cs_net_profit] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_call_center_sk,cs_ext_sales_price,cs_net_profit,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + HashAggregate [sum,sum] [sum(UnscaledValue(cr_return_amount)),sum(UnscaledValue(cr_net_loss)),returns,profit_loss,sum,sum] + InputAdapter + Exchange #9 + WholeStageCodegen (13) + HashAggregate [cr_return_amount,cr_net_loss] [sum,sum,sum,sum] + Project [cr_return_amount,cr_net_loss] + BroadcastHashJoin [cr_returned_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_returns [cr_return_amount,cr_net_loss,cr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + WholeStageCodegen (22) + Project [sales,returns,profit,profit_loss,wp_web_page_sk] + BroadcastHashJoin [wp_web_page_sk,wp_web_page_sk] + HashAggregate [wp_web_page_sk,sum,sum] [sum(UnscaledValue(ws_ext_sales_price)),sum(UnscaledValue(ws_net_profit)),sales,profit,sum,sum] + InputAdapter + Exchange [wp_web_page_sk] #10 + WholeStageCodegen (17) + HashAggregate [wp_web_page_sk,ws_ext_sales_price,ws_net_profit] [sum,sum,sum,sum] + Project [ws_ext_sales_price,ws_net_profit,wp_web_page_sk] + BroadcastHashJoin [ws_web_page_sk,wp_web_page_sk] + Project [ws_web_page_sk,ws_ext_sales_price,ws_net_profit] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ws_web_page_sk] + CometScan parquet spark_catalog.default.web_sales [ws_web_page_sk,ws_ext_sales_price,ws_net_profit,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (16) + ColumnarToRow + InputAdapter + CometFilter [wp_web_page_sk] + CometScan parquet spark_catalog.default.web_page [wp_web_page_sk] + InputAdapter + BroadcastExchange #12 + WholeStageCodegen (21) + HashAggregate [wp_web_page_sk,sum,sum] [sum(UnscaledValue(wr_return_amt)),sum(UnscaledValue(wr_net_loss)),returns,profit_loss,sum,sum] + InputAdapter + Exchange [wp_web_page_sk] #13 + WholeStageCodegen (20) + HashAggregate [wp_web_page_sk,wr_return_amt,wr_net_loss] [sum,sum,sum,sum] + Project [wr_return_amt,wr_net_loss,wp_web_page_sk] + BroadcastHashJoin [wr_web_page_sk,wp_web_page_sk] + Project [wr_web_page_sk,wr_return_amt,wr_net_loss] + BroadcastHashJoin [wr_returned_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [wr_web_page_sk] + CometScan parquet spark_catalog.default.web_returns [wr_web_page_sk,wr_return_amt,wr_net_loss,wr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + ReusedExchange [wp_web_page_sk] #11 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q78/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q78/explain.txt new file mode 100644 index 0000000000..7f26881123 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q78/explain.txt @@ -0,0 +1,431 @@ +== Physical Plan == +TakeOrderedAndProject (70) ++- * Project (69) + +- * SortMergeJoin Inner (68) + :- * Project (45) + : +- * SortMergeJoin Inner (44) + : :- * Sort (21) + : : +- * HashAggregate (20) + : : +- Exchange (19) + : : +- * HashAggregate (18) + : : +- * Project (17) + : : +- * BroadcastHashJoin Inner BuildRight (16) + : : :- * Project (14) + : : : +- * Filter (13) + : : : +- * SortMergeJoin LeftOuter (12) + : : : :- * Sort (5) + : : : : +- Exchange (4) + : : : : +- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- * Sort (11) + : : : +- Exchange (10) + : : : +- * ColumnarToRow (9) + : : : +- CometProject (8) + : : : +- CometFilter (7) + : : : +- CometScan parquet spark_catalog.default.store_returns (6) + : : +- ReusedExchange (15) + : +- * Sort (43) + : +- * Filter (42) + : +- * HashAggregate (41) + : +- Exchange (40) + : +- * HashAggregate (39) + : +- * Project (38) + : +- * BroadcastHashJoin Inner BuildRight (37) + : :- * Project (35) + : : +- * Filter (34) + : : +- * SortMergeJoin LeftOuter (33) + : : :- * Sort (26) + : : : +- Exchange (25) + : : : +- * ColumnarToRow (24) + : : : +- CometFilter (23) + : : : +- CometScan parquet spark_catalog.default.web_sales (22) + : : +- * Sort (32) + : : +- Exchange (31) + : : +- * ColumnarToRow (30) + : : +- CometProject (29) + : : +- CometFilter (28) + : : +- CometScan parquet spark_catalog.default.web_returns (27) + : +- ReusedExchange (36) + +- * Sort (67) + +- * Filter (66) + +- * HashAggregate (65) + +- Exchange (64) + +- * HashAggregate (63) + +- * Project (62) + +- * BroadcastHashJoin Inner BuildRight (61) + :- * Project (59) + : +- * Filter (58) + : +- * SortMergeJoin LeftOuter (57) + : :- * Sort (50) + : : +- Exchange (49) + : : +- * ColumnarToRow (48) + : : +- CometFilter (47) + : : +- CometScan parquet spark_catalog.default.catalog_sales (46) + : +- * Sort (56) + : +- Exchange (55) + : +- * ColumnarToRow (54) + : +- CometProject (53) + : +- CometFilter (52) + : +- CometScan parquet spark_catalog.default.catalog_returns (51) + +- ReusedExchange (60) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [7]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sold_date_sk#7 IN dynamicpruning#8)] +PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(2) CometFilter +Input [7]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7] +Condition : (isnotnull(ss_item_sk#1) AND isnotnull(ss_customer_sk#2)) + +(3) ColumnarToRow [codegen id : 1] +Input [7]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7] + +(4) Exchange +Input [7]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7] +Arguments: hashpartitioning(ss_ticket_number#3, ss_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(5) Sort [codegen id : 2] +Input [7]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7] +Arguments: [ss_ticket_number#3 ASC NULLS FIRST, ss_item_sk#1 ASC NULLS FIRST], false, 0 + +(6) Scan parquet spark_catalog.default.store_returns +Output [3]: [sr_item_sk#9, sr_ticket_number#10, sr_returned_date_sk#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_returns] +PushedFilters: [IsNotNull(sr_ticket_number), IsNotNull(sr_item_sk)] +ReadSchema: struct + +(7) CometFilter +Input [3]: [sr_item_sk#9, sr_ticket_number#10, sr_returned_date_sk#11] +Condition : (isnotnull(sr_ticket_number#10) AND isnotnull(sr_item_sk#9)) + +(8) CometProject +Input [3]: [sr_item_sk#9, sr_ticket_number#10, sr_returned_date_sk#11] +Arguments: [sr_item_sk#9, sr_ticket_number#10], [sr_item_sk#9, sr_ticket_number#10] + +(9) ColumnarToRow [codegen id : 3] +Input [2]: [sr_item_sk#9, sr_ticket_number#10] + +(10) Exchange +Input [2]: [sr_item_sk#9, sr_ticket_number#10] +Arguments: hashpartitioning(sr_ticket_number#10, sr_item_sk#9, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(11) Sort [codegen id : 4] +Input [2]: [sr_item_sk#9, sr_ticket_number#10] +Arguments: [sr_ticket_number#10 ASC NULLS FIRST, sr_item_sk#9 ASC NULLS FIRST], false, 0 + +(12) SortMergeJoin [codegen id : 6] +Left keys [2]: [ss_ticket_number#3, ss_item_sk#1] +Right keys [2]: [sr_ticket_number#10, sr_item_sk#9] +Join type: LeftOuter +Join condition: None + +(13) Filter [codegen id : 6] +Input [9]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7, sr_item_sk#9, sr_ticket_number#10] +Condition : isnull(sr_ticket_number#10) + +(14) Project [codegen id : 6] +Output [6]: [ss_item_sk#1, ss_customer_sk#2, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7] +Input [9]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7, sr_item_sk#9, sr_ticket_number#10] + +(15) ReusedExchange [Reuses operator id: 74] +Output [2]: [d_date_sk#12, d_year#13] + +(16) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_sold_date_sk#7] +Right keys [1]: [d_date_sk#12] +Join type: Inner +Join condition: None + +(17) Project [codegen id : 6] +Output [6]: [ss_item_sk#1, ss_customer_sk#2, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, d_year#13] +Input [8]: [ss_item_sk#1, ss_customer_sk#2, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7, d_date_sk#12, d_year#13] + +(18) HashAggregate [codegen id : 6] +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, d_year#13] +Keys [3]: [d_year#13, ss_item_sk#1, ss_customer_sk#2] +Functions [3]: [partial_sum(ss_quantity#4), partial_sum(UnscaledValue(ss_wholesale_cost#5)), partial_sum(UnscaledValue(ss_sales_price#6))] +Aggregate Attributes [3]: [sum#14, sum#15, sum#16] +Results [6]: [d_year#13, ss_item_sk#1, ss_customer_sk#2, sum#17, sum#18, sum#19] + +(19) Exchange +Input [6]: [d_year#13, ss_item_sk#1, ss_customer_sk#2, sum#17, sum#18, sum#19] +Arguments: hashpartitioning(d_year#13, ss_item_sk#1, ss_customer_sk#2, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(20) HashAggregate [codegen id : 7] +Input [6]: [d_year#13, ss_item_sk#1, ss_customer_sk#2, sum#17, sum#18, sum#19] +Keys [3]: [d_year#13, ss_item_sk#1, ss_customer_sk#2] +Functions [3]: [sum(ss_quantity#4), sum(UnscaledValue(ss_wholesale_cost#5)), sum(UnscaledValue(ss_sales_price#6))] +Aggregate Attributes [3]: [sum(ss_quantity#4)#20, sum(UnscaledValue(ss_wholesale_cost#5))#21, sum(UnscaledValue(ss_sales_price#6))#22] +Results [6]: [d_year#13 AS ss_sold_year#23, ss_item_sk#1, ss_customer_sk#2, sum(ss_quantity#4)#20 AS ss_qty#24, MakeDecimal(sum(UnscaledValue(ss_wholesale_cost#5))#21,17,2) AS ss_wc#25, MakeDecimal(sum(UnscaledValue(ss_sales_price#6))#22,17,2) AS ss_sp#26] + +(21) Sort [codegen id : 7] +Input [6]: [ss_sold_year#23, ss_item_sk#1, ss_customer_sk#2, ss_qty#24, ss_wc#25, ss_sp#26] +Arguments: [ss_sold_year#23 ASC NULLS FIRST, ss_item_sk#1 ASC NULLS FIRST, ss_customer_sk#2 ASC NULLS FIRST], false, 0 + +(22) Scan parquet spark_catalog.default.web_sales +Output [7]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_order_number#29, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#33), dynamicpruningexpression(ws_sold_date_sk#33 IN dynamicpruning#34)] +PushedFilters: [IsNotNull(ws_item_sk), IsNotNull(ws_bill_customer_sk)] +ReadSchema: struct + +(23) CometFilter +Input [7]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_order_number#29, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33] +Condition : (isnotnull(ws_item_sk#27) AND isnotnull(ws_bill_customer_sk#28)) + +(24) ColumnarToRow [codegen id : 8] +Input [7]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_order_number#29, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33] + +(25) Exchange +Input [7]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_order_number#29, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33] +Arguments: hashpartitioning(ws_order_number#29, ws_item_sk#27, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(26) Sort [codegen id : 9] +Input [7]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_order_number#29, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33] +Arguments: [ws_order_number#29 ASC NULLS FIRST, ws_item_sk#27 ASC NULLS FIRST], false, 0 + +(27) Scan parquet spark_catalog.default.web_returns +Output [3]: [wr_item_sk#35, wr_order_number#36, wr_returned_date_sk#37] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_returns] +PushedFilters: [IsNotNull(wr_order_number), IsNotNull(wr_item_sk)] +ReadSchema: struct + +(28) CometFilter +Input [3]: [wr_item_sk#35, wr_order_number#36, wr_returned_date_sk#37] +Condition : (isnotnull(wr_order_number#36) AND isnotnull(wr_item_sk#35)) + +(29) CometProject +Input [3]: [wr_item_sk#35, wr_order_number#36, wr_returned_date_sk#37] +Arguments: [wr_item_sk#35, wr_order_number#36], [wr_item_sk#35, wr_order_number#36] + +(30) ColumnarToRow [codegen id : 10] +Input [2]: [wr_item_sk#35, wr_order_number#36] + +(31) Exchange +Input [2]: [wr_item_sk#35, wr_order_number#36] +Arguments: hashpartitioning(wr_order_number#36, wr_item_sk#35, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(32) Sort [codegen id : 11] +Input [2]: [wr_item_sk#35, wr_order_number#36] +Arguments: [wr_order_number#36 ASC NULLS FIRST, wr_item_sk#35 ASC NULLS FIRST], false, 0 + +(33) SortMergeJoin [codegen id : 13] +Left keys [2]: [ws_order_number#29, ws_item_sk#27] +Right keys [2]: [wr_order_number#36, wr_item_sk#35] +Join type: LeftOuter +Join condition: None + +(34) Filter [codegen id : 13] +Input [9]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_order_number#29, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33, wr_item_sk#35, wr_order_number#36] +Condition : isnull(wr_order_number#36) + +(35) Project [codegen id : 13] +Output [6]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33] +Input [9]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_order_number#29, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33, wr_item_sk#35, wr_order_number#36] + +(36) ReusedExchange [Reuses operator id: 74] +Output [2]: [d_date_sk#38, d_year#39] + +(37) BroadcastHashJoin [codegen id : 13] +Left keys [1]: [ws_sold_date_sk#33] +Right keys [1]: [d_date_sk#38] +Join type: Inner +Join condition: None + +(38) Project [codegen id : 13] +Output [6]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, d_year#39] +Input [8]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33, d_date_sk#38, d_year#39] + +(39) HashAggregate [codegen id : 13] +Input [6]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, d_year#39] +Keys [3]: [d_year#39, ws_item_sk#27, ws_bill_customer_sk#28] +Functions [3]: [partial_sum(ws_quantity#30), partial_sum(UnscaledValue(ws_wholesale_cost#31)), partial_sum(UnscaledValue(ws_sales_price#32))] +Aggregate Attributes [3]: [sum#40, sum#41, sum#42] +Results [6]: [d_year#39, ws_item_sk#27, ws_bill_customer_sk#28, sum#43, sum#44, sum#45] + +(40) Exchange +Input [6]: [d_year#39, ws_item_sk#27, ws_bill_customer_sk#28, sum#43, sum#44, sum#45] +Arguments: hashpartitioning(d_year#39, ws_item_sk#27, ws_bill_customer_sk#28, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(41) HashAggregate [codegen id : 14] +Input [6]: [d_year#39, ws_item_sk#27, ws_bill_customer_sk#28, sum#43, sum#44, sum#45] +Keys [3]: [d_year#39, ws_item_sk#27, ws_bill_customer_sk#28] +Functions [3]: [sum(ws_quantity#30), sum(UnscaledValue(ws_wholesale_cost#31)), sum(UnscaledValue(ws_sales_price#32))] +Aggregate Attributes [3]: [sum(ws_quantity#30)#46, sum(UnscaledValue(ws_wholesale_cost#31))#47, sum(UnscaledValue(ws_sales_price#32))#48] +Results [6]: [d_year#39 AS ws_sold_year#49, ws_item_sk#27, ws_bill_customer_sk#28 AS ws_customer_sk#50, sum(ws_quantity#30)#46 AS ws_qty#51, MakeDecimal(sum(UnscaledValue(ws_wholesale_cost#31))#47,17,2) AS ws_wc#52, MakeDecimal(sum(UnscaledValue(ws_sales_price#32))#48,17,2) AS ws_sp#53] + +(42) Filter [codegen id : 14] +Input [6]: [ws_sold_year#49, ws_item_sk#27, ws_customer_sk#50, ws_qty#51, ws_wc#52, ws_sp#53] +Condition : (coalesce(ws_qty#51, 0) > 0) + +(43) Sort [codegen id : 14] +Input [6]: [ws_sold_year#49, ws_item_sk#27, ws_customer_sk#50, ws_qty#51, ws_wc#52, ws_sp#53] +Arguments: [ws_sold_year#49 ASC NULLS FIRST, ws_item_sk#27 ASC NULLS FIRST, ws_customer_sk#50 ASC NULLS FIRST], false, 0 + +(44) SortMergeJoin [codegen id : 15] +Left keys [3]: [ss_sold_year#23, ss_item_sk#1, ss_customer_sk#2] +Right keys [3]: [ws_sold_year#49, ws_item_sk#27, ws_customer_sk#50] +Join type: Inner +Join condition: None + +(45) Project [codegen id : 15] +Output [9]: [ss_sold_year#23, ss_item_sk#1, ss_customer_sk#2, ss_qty#24, ss_wc#25, ss_sp#26, ws_qty#51, ws_wc#52, ws_sp#53] +Input [12]: [ss_sold_year#23, ss_item_sk#1, ss_customer_sk#2, ss_qty#24, ss_wc#25, ss_sp#26, ws_sold_year#49, ws_item_sk#27, ws_customer_sk#50, ws_qty#51, ws_wc#52, ws_sp#53] + +(46) Scan parquet spark_catalog.default.catalog_sales +Output [7]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_order_number#56, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#60), dynamicpruningexpression(cs_sold_date_sk#60 IN dynamicpruning#61)] +PushedFilters: [IsNotNull(cs_item_sk), IsNotNull(cs_bill_customer_sk)] +ReadSchema: struct + +(47) CometFilter +Input [7]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_order_number#56, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60] +Condition : (isnotnull(cs_item_sk#55) AND isnotnull(cs_bill_customer_sk#54)) + +(48) ColumnarToRow [codegen id : 16] +Input [7]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_order_number#56, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60] + +(49) Exchange +Input [7]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_order_number#56, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60] +Arguments: hashpartitioning(cs_order_number#56, cs_item_sk#55, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(50) Sort [codegen id : 17] +Input [7]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_order_number#56, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60] +Arguments: [cs_order_number#56 ASC NULLS FIRST, cs_item_sk#55 ASC NULLS FIRST], false, 0 + +(51) Scan parquet spark_catalog.default.catalog_returns +Output [3]: [cr_item_sk#62, cr_order_number#63, cr_returned_date_sk#64] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_returns] +PushedFilters: [IsNotNull(cr_order_number), IsNotNull(cr_item_sk)] +ReadSchema: struct + +(52) CometFilter +Input [3]: [cr_item_sk#62, cr_order_number#63, cr_returned_date_sk#64] +Condition : (isnotnull(cr_order_number#63) AND isnotnull(cr_item_sk#62)) + +(53) CometProject +Input [3]: [cr_item_sk#62, cr_order_number#63, cr_returned_date_sk#64] +Arguments: [cr_item_sk#62, cr_order_number#63], [cr_item_sk#62, cr_order_number#63] + +(54) ColumnarToRow [codegen id : 18] +Input [2]: [cr_item_sk#62, cr_order_number#63] + +(55) Exchange +Input [2]: [cr_item_sk#62, cr_order_number#63] +Arguments: hashpartitioning(cr_order_number#63, cr_item_sk#62, 5), ENSURE_REQUIREMENTS, [plan_id=8] + +(56) Sort [codegen id : 19] +Input [2]: [cr_item_sk#62, cr_order_number#63] +Arguments: [cr_order_number#63 ASC NULLS FIRST, cr_item_sk#62 ASC NULLS FIRST], false, 0 + +(57) SortMergeJoin [codegen id : 21] +Left keys [2]: [cs_order_number#56, cs_item_sk#55] +Right keys [2]: [cr_order_number#63, cr_item_sk#62] +Join type: LeftOuter +Join condition: None + +(58) Filter [codegen id : 21] +Input [9]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_order_number#56, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60, cr_item_sk#62, cr_order_number#63] +Condition : isnull(cr_order_number#63) + +(59) Project [codegen id : 21] +Output [6]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60] +Input [9]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_order_number#56, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60, cr_item_sk#62, cr_order_number#63] + +(60) ReusedExchange [Reuses operator id: 74] +Output [2]: [d_date_sk#65, d_year#66] + +(61) BroadcastHashJoin [codegen id : 21] +Left keys [1]: [cs_sold_date_sk#60] +Right keys [1]: [d_date_sk#65] +Join type: Inner +Join condition: None + +(62) Project [codegen id : 21] +Output [6]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, d_year#66] +Input [8]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60, d_date_sk#65, d_year#66] + +(63) HashAggregate [codegen id : 21] +Input [6]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, d_year#66] +Keys [3]: [d_year#66, cs_item_sk#55, cs_bill_customer_sk#54] +Functions [3]: [partial_sum(cs_quantity#57), partial_sum(UnscaledValue(cs_wholesale_cost#58)), partial_sum(UnscaledValue(cs_sales_price#59))] +Aggregate Attributes [3]: [sum#67, sum#68, sum#69] +Results [6]: [d_year#66, cs_item_sk#55, cs_bill_customer_sk#54, sum#70, sum#71, sum#72] + +(64) Exchange +Input [6]: [d_year#66, cs_item_sk#55, cs_bill_customer_sk#54, sum#70, sum#71, sum#72] +Arguments: hashpartitioning(d_year#66, cs_item_sk#55, cs_bill_customer_sk#54, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(65) HashAggregate [codegen id : 22] +Input [6]: [d_year#66, cs_item_sk#55, cs_bill_customer_sk#54, sum#70, sum#71, sum#72] +Keys [3]: [d_year#66, cs_item_sk#55, cs_bill_customer_sk#54] +Functions [3]: [sum(cs_quantity#57), sum(UnscaledValue(cs_wholesale_cost#58)), sum(UnscaledValue(cs_sales_price#59))] +Aggregate Attributes [3]: [sum(cs_quantity#57)#73, sum(UnscaledValue(cs_wholesale_cost#58))#74, sum(UnscaledValue(cs_sales_price#59))#75] +Results [6]: [d_year#66 AS cs_sold_year#76, cs_item_sk#55, cs_bill_customer_sk#54 AS cs_customer_sk#77, sum(cs_quantity#57)#73 AS cs_qty#78, MakeDecimal(sum(UnscaledValue(cs_wholesale_cost#58))#74,17,2) AS cs_wc#79, MakeDecimal(sum(UnscaledValue(cs_sales_price#59))#75,17,2) AS cs_sp#80] + +(66) Filter [codegen id : 22] +Input [6]: [cs_sold_year#76, cs_item_sk#55, cs_customer_sk#77, cs_qty#78, cs_wc#79, cs_sp#80] +Condition : (coalesce(cs_qty#78, 0) > 0) + +(67) Sort [codegen id : 22] +Input [6]: [cs_sold_year#76, cs_item_sk#55, cs_customer_sk#77, cs_qty#78, cs_wc#79, cs_sp#80] +Arguments: [cs_sold_year#76 ASC NULLS FIRST, cs_item_sk#55 ASC NULLS FIRST, cs_customer_sk#77 ASC NULLS FIRST], false, 0 + +(68) SortMergeJoin [codegen id : 23] +Left keys [3]: [ss_sold_year#23, ss_item_sk#1, ss_customer_sk#2] +Right keys [3]: [cs_sold_year#76, cs_item_sk#55, cs_customer_sk#77] +Join type: Inner +Join condition: None + +(69) Project [codegen id : 23] +Output [12]: [round((cast(ss_qty#24 as double) / cast(coalesce((ws_qty#51 + cs_qty#78), 1) as double)), 2) AS ratio#81, ss_qty#24 AS store_qty#82, ss_wc#25 AS store_wholesale_cost#83, ss_sp#26 AS store_sales_price#84, (coalesce(ws_qty#51, 0) + coalesce(cs_qty#78, 0)) AS other_chan_qty#85, (coalesce(ws_wc#52, 0.00) + coalesce(cs_wc#79, 0.00)) AS other_chan_wholesale_cost#86, (coalesce(ws_sp#53, 0.00) + coalesce(cs_sp#80, 0.00)) AS other_chan_sales_price#87, ss_qty#24, ss_wc#25, ss_sp#26, ws_qty#51, cs_qty#78] +Input [15]: [ss_sold_year#23, ss_item_sk#1, ss_customer_sk#2, ss_qty#24, ss_wc#25, ss_sp#26, ws_qty#51, ws_wc#52, ws_sp#53, cs_sold_year#76, cs_item_sk#55, cs_customer_sk#77, cs_qty#78, cs_wc#79, cs_sp#80] + +(70) TakeOrderedAndProject +Input [12]: [ratio#81, store_qty#82, store_wholesale_cost#83, store_sales_price#84, other_chan_qty#85, other_chan_wholesale_cost#86, other_chan_sales_price#87, ss_qty#24, ss_wc#25, ss_sp#26, ws_qty#51, cs_qty#78] +Arguments: 100, [ratio#81 ASC NULLS FIRST, ss_qty#24 DESC NULLS LAST, ss_wc#25 DESC NULLS LAST, ss_sp#26 DESC NULLS LAST, other_chan_qty#85 ASC NULLS FIRST, other_chan_wholesale_cost#86 ASC NULLS FIRST, other_chan_sales_price#87 ASC NULLS FIRST, round((cast(ss_qty#24 as double) / cast(coalesce((ws_qty#51 + cs_qty#78), 1) as double)), 2) ASC NULLS FIRST], [ratio#81, store_qty#82, store_wholesale_cost#83, store_sales_price#84, other_chan_qty#85, other_chan_wholesale_cost#86, other_chan_sales_price#87] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (74) ++- * ColumnarToRow (73) + +- CometFilter (72) + +- CometScan parquet spark_catalog.default.date_dim (71) + + +(71) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#12, d_year#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2000), IsNotNull(d_date_sk)] +ReadSchema: struct + +(72) CometFilter +Input [2]: [d_date_sk#12, d_year#13] +Condition : ((isnotnull(d_year#13) AND (d_year#13 = 2000)) AND isnotnull(d_date_sk#12)) + +(73) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#12, d_year#13] + +(74) BroadcastExchange +Input [2]: [d_date_sk#12, d_year#13] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=10] + +Subquery:2 Hosting operator id = 22 Hosting Expression = ws_sold_date_sk#33 IN dynamicpruning#8 + +Subquery:3 Hosting operator id = 46 Hosting Expression = cs_sold_date_sk#60 IN dynamicpruning#8 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q78/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q78/simplified.txt new file mode 100644 index 0000000000..280687e301 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q78/simplified.txt @@ -0,0 +1,127 @@ +TakeOrderedAndProject [ratio,ss_qty,ss_wc,ss_sp,other_chan_qty,other_chan_wholesale_cost,other_chan_sales_price,ws_qty,cs_qty,store_qty,store_wholesale_cost,store_sales_price] + WholeStageCodegen (23) + Project [ss_qty,ws_qty,cs_qty,ss_wc,ss_sp,ws_wc,cs_wc,ws_sp,cs_sp] + SortMergeJoin [ss_sold_year,ss_item_sk,ss_customer_sk,cs_sold_year,cs_item_sk,cs_customer_sk] + InputAdapter + WholeStageCodegen (15) + Project [ss_sold_year,ss_item_sk,ss_customer_sk,ss_qty,ss_wc,ss_sp,ws_qty,ws_wc,ws_sp] + SortMergeJoin [ss_sold_year,ss_item_sk,ss_customer_sk,ws_sold_year,ws_item_sk,ws_customer_sk] + InputAdapter + WholeStageCodegen (7) + Sort [ss_sold_year,ss_item_sk,ss_customer_sk] + HashAggregate [d_year,ss_item_sk,ss_customer_sk,sum,sum,sum] [sum(ss_quantity),sum(UnscaledValue(ss_wholesale_cost)),sum(UnscaledValue(ss_sales_price)),ss_sold_year,ss_qty,ss_wc,ss_sp,sum,sum,sum] + InputAdapter + Exchange [d_year,ss_item_sk,ss_customer_sk] #1 + WholeStageCodegen (6) + HashAggregate [d_year,ss_item_sk,ss_customer_sk,ss_quantity,ss_wholesale_cost,ss_sales_price] [sum,sum,sum,sum,sum,sum] + Project [ss_item_sk,ss_customer_sk,ss_quantity,ss_wholesale_cost,ss_sales_price,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_customer_sk,ss_quantity,ss_wholesale_cost,ss_sales_price,ss_sold_date_sk] + Filter [sr_ticket_number] + SortMergeJoin [ss_ticket_number,ss_item_sk,sr_ticket_number,sr_item_sk] + InputAdapter + WholeStageCodegen (2) + Sort [ss_ticket_number,ss_item_sk] + InputAdapter + Exchange [ss_ticket_number,ss_item_sk] #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk,ss_customer_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_ticket_number,ss_quantity,ss_wholesale_cost,ss_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + WholeStageCodegen (4) + Sort [sr_ticket_number,sr_item_sk] + InputAdapter + Exchange [sr_ticket_number,sr_item_sk] #4 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometProject [sr_item_sk,sr_ticket_number] + CometFilter [sr_ticket_number,sr_item_sk] + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk,d_year] #3 + InputAdapter + WholeStageCodegen (14) + Sort [ws_sold_year,ws_item_sk,ws_customer_sk] + Filter [ws_qty] + HashAggregate [d_year,ws_item_sk,ws_bill_customer_sk,sum,sum,sum] [sum(ws_quantity),sum(UnscaledValue(ws_wholesale_cost)),sum(UnscaledValue(ws_sales_price)),ws_sold_year,ws_customer_sk,ws_qty,ws_wc,ws_sp,sum,sum,sum] + InputAdapter + Exchange [d_year,ws_item_sk,ws_bill_customer_sk] #5 + WholeStageCodegen (13) + HashAggregate [d_year,ws_item_sk,ws_bill_customer_sk,ws_quantity,ws_wholesale_cost,ws_sales_price] [sum,sum,sum,sum,sum,sum] + Project [ws_item_sk,ws_bill_customer_sk,ws_quantity,ws_wholesale_cost,ws_sales_price,d_year] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_item_sk,ws_bill_customer_sk,ws_quantity,ws_wholesale_cost,ws_sales_price,ws_sold_date_sk] + Filter [wr_order_number] + SortMergeJoin [ws_order_number,ws_item_sk,wr_order_number,wr_item_sk] + InputAdapter + WholeStageCodegen (9) + Sort [ws_order_number,ws_item_sk] + InputAdapter + Exchange [ws_order_number,ws_item_sk] #6 + WholeStageCodegen (8) + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk,ws_bill_customer_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_bill_customer_sk,ws_order_number,ws_quantity,ws_wholesale_cost,ws_sales_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + WholeStageCodegen (11) + Sort [wr_order_number,wr_item_sk] + InputAdapter + Exchange [wr_order_number,wr_item_sk] #7 + WholeStageCodegen (10) + ColumnarToRow + InputAdapter + CometProject [wr_item_sk,wr_order_number] + CometFilter [wr_order_number,wr_item_sk] + CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_order_number,wr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk,d_year] #3 + InputAdapter + WholeStageCodegen (22) + Sort [cs_sold_year,cs_item_sk,cs_customer_sk] + Filter [cs_qty] + HashAggregate [d_year,cs_item_sk,cs_bill_customer_sk,sum,sum,sum] [sum(cs_quantity),sum(UnscaledValue(cs_wholesale_cost)),sum(UnscaledValue(cs_sales_price)),cs_sold_year,cs_customer_sk,cs_qty,cs_wc,cs_sp,sum,sum,sum] + InputAdapter + Exchange [d_year,cs_item_sk,cs_bill_customer_sk] #8 + WholeStageCodegen (21) + HashAggregate [d_year,cs_item_sk,cs_bill_customer_sk,cs_quantity,cs_wholesale_cost,cs_sales_price] [sum,sum,sum,sum,sum,sum] + Project [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_wholesale_cost,cs_sales_price,d_year] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_wholesale_cost,cs_sales_price,cs_sold_date_sk] + Filter [cr_order_number] + SortMergeJoin [cs_order_number,cs_item_sk,cr_order_number,cr_item_sk] + InputAdapter + WholeStageCodegen (17) + Sort [cs_order_number,cs_item_sk] + InputAdapter + Exchange [cs_order_number,cs_item_sk] #9 + WholeStageCodegen (16) + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk,cs_bill_customer_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_item_sk,cs_order_number,cs_quantity,cs_wholesale_cost,cs_sales_price,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + WholeStageCodegen (19) + Sort [cr_order_number,cr_item_sk] + InputAdapter + Exchange [cr_order_number,cr_item_sk] #10 + WholeStageCodegen (18) + ColumnarToRow + InputAdapter + CometProject [cr_item_sk,cr_order_number] + CometFilter [cr_order_number,cr_item_sk] + CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk,d_year] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q79/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q79/explain.txt new file mode 100644 index 0000000000..c89bad2201 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q79/explain.txt @@ -0,0 +1,208 @@ +== Physical Plan == +TakeOrderedAndProject (30) ++- * Project (29) + +- * BroadcastHashJoin Inner BuildRight (28) + :- * HashAggregate (23) + : +- Exchange (22) + : +- * HashAggregate (21) + : +- * Project (20) + : +- * BroadcastHashJoin Inner BuildRight (19) + : :- * Project (13) + : : +- * BroadcastHashJoin Inner BuildRight (12) + : : :- * Project (6) + : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- ReusedExchange (4) + : : +- BroadcastExchange (11) + : : +- * ColumnarToRow (10) + : : +- CometProject (9) + : : +- CometFilter (8) + : : +- CometScan parquet spark_catalog.default.store (7) + : +- BroadcastExchange (18) + : +- * ColumnarToRow (17) + : +- CometProject (16) + : +- CometFilter (15) + : +- CometScan parquet spark_catalog.default.household_demographics (14) + +- BroadcastExchange (27) + +- * ColumnarToRow (26) + +- CometFilter (25) + +- CometScan parquet spark_catalog.default.customer (24) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [8]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, ss_sold_date_sk#8] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#8), dynamicpruningexpression(ss_sold_date_sk#8 IN dynamicpruning#9)] +PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_hdemo_sk), IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(2) CometFilter +Input [8]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, ss_sold_date_sk#8] +Condition : ((isnotnull(ss_store_sk#4) AND isnotnull(ss_hdemo_sk#2)) AND isnotnull(ss_customer_sk#1)) + +(3) ColumnarToRow [codegen id : 4] +Input [8]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, ss_sold_date_sk#8] + +(4) ReusedExchange [Reuses operator id: 35] +Output [1]: [d_date_sk#10] + +(5) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_date_sk#8] +Right keys [1]: [d_date_sk#10] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 4] +Output [7]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7] +Input [9]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, ss_sold_date_sk#8, d_date_sk#10] + +(7) Scan parquet spark_catalog.default.store +Output [3]: [s_store_sk#11, s_number_employees#12, s_city#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_number_employees), GreaterThanOrEqual(s_number_employees,200), LessThanOrEqual(s_number_employees,295), IsNotNull(s_store_sk)] +ReadSchema: struct + +(8) CometFilter +Input [3]: [s_store_sk#11, s_number_employees#12, s_city#13] +Condition : (((isnotnull(s_number_employees#12) AND (s_number_employees#12 >= 200)) AND (s_number_employees#12 <= 295)) AND isnotnull(s_store_sk#11)) + +(9) CometProject +Input [3]: [s_store_sk#11, s_number_employees#12, s_city#13] +Arguments: [s_store_sk#11, s_city#13], [s_store_sk#11, s_city#13] + +(10) ColumnarToRow [codegen id : 2] +Input [2]: [s_store_sk#11, s_city#13] + +(11) BroadcastExchange +Input [2]: [s_store_sk#11, s_city#13] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(12) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_store_sk#4] +Right keys [1]: [s_store_sk#11] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 4] +Output [7]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, s_city#13] +Input [9]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, s_store_sk#11, s_city#13] + +(14) Scan parquet spark_catalog.default.household_demographics +Output [3]: [hd_demo_sk#14, hd_dep_count#15, hd_vehicle_count#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/household_demographics] +PushedFilters: [Or(EqualTo(hd_dep_count,6),GreaterThan(hd_vehicle_count,2)), IsNotNull(hd_demo_sk)] +ReadSchema: struct + +(15) CometFilter +Input [3]: [hd_demo_sk#14, hd_dep_count#15, hd_vehicle_count#16] +Condition : (((hd_dep_count#15 = 6) OR (hd_vehicle_count#16 > 2)) AND isnotnull(hd_demo_sk#14)) + +(16) CometProject +Input [3]: [hd_demo_sk#14, hd_dep_count#15, hd_vehicle_count#16] +Arguments: [hd_demo_sk#14], [hd_demo_sk#14] + +(17) ColumnarToRow [codegen id : 3] +Input [1]: [hd_demo_sk#14] + +(18) BroadcastExchange +Input [1]: [hd_demo_sk#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(19) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_hdemo_sk#2] +Right keys [1]: [hd_demo_sk#14] +Join type: Inner +Join condition: None + +(20) Project [codegen id : 4] +Output [6]: [ss_customer_sk#1, ss_addr_sk#3, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, s_city#13] +Input [8]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, s_city#13, hd_demo_sk#14] + +(21) HashAggregate [codegen id : 4] +Input [6]: [ss_customer_sk#1, ss_addr_sk#3, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, s_city#13] +Keys [4]: [ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, s_city#13] +Functions [2]: [partial_sum(UnscaledValue(ss_coupon_amt#6)), partial_sum(UnscaledValue(ss_net_profit#7))] +Aggregate Attributes [2]: [sum#17, sum#18] +Results [6]: [ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, s_city#13, sum#19, sum#20] + +(22) Exchange +Input [6]: [ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, s_city#13, sum#19, sum#20] +Arguments: hashpartitioning(ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, s_city#13, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(23) HashAggregate [codegen id : 6] +Input [6]: [ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, s_city#13, sum#19, sum#20] +Keys [4]: [ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, s_city#13] +Functions [2]: [sum(UnscaledValue(ss_coupon_amt#6)), sum(UnscaledValue(ss_net_profit#7))] +Aggregate Attributes [2]: [sum(UnscaledValue(ss_coupon_amt#6))#21, sum(UnscaledValue(ss_net_profit#7))#22] +Results [5]: [ss_ticket_number#5, ss_customer_sk#1, s_city#13, MakeDecimal(sum(UnscaledValue(ss_coupon_amt#6))#21,17,2) AS amt#23, MakeDecimal(sum(UnscaledValue(ss_net_profit#7))#22,17,2) AS profit#24] + +(24) Scan parquet spark_catalog.default.customer +Output [3]: [c_customer_sk#25, c_first_name#26, c_last_name#27] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk)] +ReadSchema: struct + +(25) CometFilter +Input [3]: [c_customer_sk#25, c_first_name#26, c_last_name#27] +Condition : isnotnull(c_customer_sk#25) + +(26) ColumnarToRow [codegen id : 5] +Input [3]: [c_customer_sk#25, c_first_name#26, c_last_name#27] + +(27) BroadcastExchange +Input [3]: [c_customer_sk#25, c_first_name#26, c_last_name#27] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(28) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_customer_sk#1] +Right keys [1]: [c_customer_sk#25] +Join type: Inner +Join condition: None + +(29) Project [codegen id : 6] +Output [7]: [c_last_name#27, c_first_name#26, substr(s_city#13, 1, 30) AS substr(s_city, 1, 30)#28, ss_ticket_number#5, amt#23, profit#24, s_city#13] +Input [8]: [ss_ticket_number#5, ss_customer_sk#1, s_city#13, amt#23, profit#24, c_customer_sk#25, c_first_name#26, c_last_name#27] + +(30) TakeOrderedAndProject +Input [7]: [c_last_name#27, c_first_name#26, substr(s_city, 1, 30)#28, ss_ticket_number#5, amt#23, profit#24, s_city#13] +Arguments: 100, [c_last_name#27 ASC NULLS FIRST, c_first_name#26 ASC NULLS FIRST, substr(s_city#13, 1, 30) ASC NULLS FIRST, profit#24 ASC NULLS FIRST], [c_last_name#27, c_first_name#26, substr(s_city, 1, 30)#28, ss_ticket_number#5, amt#23, profit#24] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#8 IN dynamicpruning#9 +BroadcastExchange (35) ++- * ColumnarToRow (34) + +- CometProject (33) + +- CometFilter (32) + +- CometScan parquet spark_catalog.default.date_dim (31) + + +(31) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#10, d_year#29, d_dow#30] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_dow), EqualTo(d_dow,1), In(d_year, [1999,2000,2001]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(32) CometFilter +Input [3]: [d_date_sk#10, d_year#29, d_dow#30] +Condition : (((isnotnull(d_dow#30) AND (d_dow#30 = 1)) AND d_year#29 IN (1999,2000,2001)) AND isnotnull(d_date_sk#10)) + +(33) CometProject +Input [3]: [d_date_sk#10, d_year#29, d_dow#30] +Arguments: [d_date_sk#10], [d_date_sk#10] + +(34) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#10] + +(35) BroadcastExchange +Input [1]: [d_date_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q79/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q79/simplified.txt new file mode 100644 index 0000000000..4c05c449c5 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q79/simplified.txt @@ -0,0 +1,52 @@ +TakeOrderedAndProject [c_last_name,c_first_name,s_city,profit,substr(s_city, 1, 30),ss_ticket_number,amt] + WholeStageCodegen (6) + Project [c_last_name,c_first_name,s_city,ss_ticket_number,amt,profit] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + HashAggregate [ss_ticket_number,ss_customer_sk,ss_addr_sk,s_city,sum,sum] [sum(UnscaledValue(ss_coupon_amt)),sum(UnscaledValue(ss_net_profit)),amt,profit,sum,sum] + InputAdapter + Exchange [ss_ticket_number,ss_customer_sk,ss_addr_sk,s_city] #1 + WholeStageCodegen (4) + HashAggregate [ss_ticket_number,ss_customer_sk,ss_addr_sk,s_city,ss_coupon_amt,ss_net_profit] [sum,sum,sum,sum] + Project [ss_customer_sk,ss_addr_sk,ss_ticket_number,ss_coupon_amt,ss_net_profit,s_city] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + Project [ss_customer_sk,ss_hdemo_sk,ss_addr_sk,ss_ticket_number,ss_coupon_amt,ss_net_profit,s_city] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_customer_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_ticket_number,ss_coupon_amt,ss_net_profit] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk,ss_hdemo_sk,ss_customer_sk] + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_ticket_number,ss_coupon_amt,ss_net_profit,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_dow,d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_dow] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometProject [s_store_sk,s_city] + CometFilter [s_number_employees,s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk,s_number_employees,s_city] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometProject [hd_demo_sk] + CometFilter [hd_dep_count,hd_vehicle_count,hd_demo_sk] + CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_dep_count,hd_vehicle_count] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (5) + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_first_name,c_last_name] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q8/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q8/explain.txt new file mode 100644 index 0000000000..7d6d717c1b --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q8/explain.txt @@ -0,0 +1,288 @@ +== Physical Plan == +TakeOrderedAndProject (43) ++- * HashAggregate (42) + +- Exchange (41) + +- * HashAggregate (40) + +- * Project (39) + +- * BroadcastHashJoin Inner BuildRight (38) + :- * Project (12) + : +- * BroadcastHashJoin Inner BuildRight (11) + : :- * Project (6) + : : +- * BroadcastHashJoin Inner BuildRight (5) + : : :- * ColumnarToRow (3) + : : : +- CometFilter (2) + : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : +- ReusedExchange (4) + : +- BroadcastExchange (10) + : +- * ColumnarToRow (9) + : +- CometFilter (8) + : +- CometScan parquet spark_catalog.default.store (7) + +- BroadcastExchange (37) + +- * HashAggregate (36) + +- Exchange (35) + +- * HashAggregate (34) + +- * BroadcastHashJoin LeftSemi BuildRight (33) + :- * ColumnarToRow (16) + : +- CometProject (15) + : +- CometFilter (14) + : +- CometScan parquet spark_catalog.default.customer_address (13) + +- BroadcastExchange (32) + +- * Project (31) + +- * Filter (30) + +- * HashAggregate (29) + +- Exchange (28) + +- * HashAggregate (27) + +- * Project (26) + +- * BroadcastHashJoin Inner BuildRight (25) + :- * ColumnarToRow (19) + : +- CometFilter (18) + : +- CometScan parquet spark_catalog.default.customer_address (17) + +- BroadcastExchange (24) + +- * ColumnarToRow (23) + +- CometProject (22) + +- CometFilter (21) + +- CometScan parquet spark_catalog.default.customer (20) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_store_sk#1, ss_net_profit#2, ss_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#3), dynamicpruningexpression(ss_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(ss_store_sk)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [ss_store_sk#1, ss_net_profit#2, ss_sold_date_sk#3] +Condition : isnotnull(ss_store_sk#1) + +(3) ColumnarToRow [codegen id : 8] +Input [3]: [ss_store_sk#1, ss_net_profit#2, ss_sold_date_sk#3] + +(4) ReusedExchange [Reuses operator id: 48] +Output [1]: [d_date_sk#5] + +(5) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_sold_date_sk#3] +Right keys [1]: [d_date_sk#5] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 8] +Output [2]: [ss_store_sk#1, ss_net_profit#2] +Input [4]: [ss_store_sk#1, ss_net_profit#2, ss_sold_date_sk#3, d_date_sk#5] + +(7) Scan parquet spark_catalog.default.store +Output [3]: [s_store_sk#6, s_store_name#7, s_zip#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk), IsNotNull(s_zip)] +ReadSchema: struct + +(8) CometFilter +Input [3]: [s_store_sk#6, s_store_name#7, s_zip#8] +Condition : (isnotnull(s_store_sk#6) AND isnotnull(s_zip#8)) + +(9) ColumnarToRow [codegen id : 2] +Input [3]: [s_store_sk#6, s_store_name#7, s_zip#8] + +(10) BroadcastExchange +Input [3]: [s_store_sk#6, s_store_name#7, s_zip#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(11) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_store_sk#1] +Right keys [1]: [s_store_sk#6] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 8] +Output [3]: [ss_net_profit#2, s_store_name#7, s_zip#8] +Input [5]: [ss_store_sk#1, ss_net_profit#2, s_store_sk#6, s_store_name#7, s_zip#8] + +(13) Scan parquet spark_catalog.default.customer_address +Output [1]: [ca_zip#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +ReadSchema: struct + +(14) CometFilter +Input [1]: [ca_zip#9] +Condition : (substr(ca_zip#9, 1, 5) INSET 10144, 10336, 10390, 10445, 10516, 10567, 11101, 11356, 11376, 11489, 11634, 11928, 12305, 13354, 13375, 13376, 13394, 13595, 13695, 13955, 14060, 14089, 14171, 14328, 14663, 14867, 14922, 15126, 15146, 15371, 15455, 15559, 15723, 15734, 15765, 15798, 15882, 16021, 16725, 16807, 17043, 17183, 17871, 17879, 17920, 18119, 18270, 18376, 18383, 18426, 18652, 18767, 18799, 18840, 18842, 18845, 18906, 19430, 19505, 19512, 19515, 19736, 19769, 19849, 20004, 20260, 20548, 21076, 21195, 21286, 21309, 21337, 21756, 22152, 22245, 22246, 22351, 22437, 22461, 22685, 22744, 22752, 22927, 23006, 23470, 23932, 23968, 24128, 24206, 24317, 24610, 24671, 24676, 24996, 25003, 25103, 25280, 25486, 25631, 25733, 25782, 25858, 25989, 26065, 26105, 26231, 26233, 26653, 26689, 26859, 27068, 27156, 27385, 27700, 28286, 28488, 28545, 28577, 28587, 28709, 28810, 28898, 28915, 29178, 29741, 29839, 30010, 30122, 30431, 30450, 30469, 30625, 30903, 31016, 31029, 31387, 31671, 31880, 32213, 32754, 33123, 33282, 33515, 33786, 34102, 34322, 34425, 35258, 35458, 35474, 35576, 35850, 35942, 36233, 36420, 36446, 36495, 36634, 37125, 37126, 37930, 38122, 38193, 38415, 38607, 38935, 39127, 39192, 39371, 39516, 39736, 39861, 39972, 40081, 40162, 40558, 40604, 41248, 41367, 41368, 41766, 41918, 42029, 42666, 42961, 43285, 43848, 43933, 44165, 44438, 45200, 45266, 45375, 45549, 45692, 45721, 45748, 46081, 46136, 46820, 47305, 47537, 47770, 48033, 48425, 48583, 49130, 49156, 49448, 50016, 50298, 50308, 50412, 51061, 51103, 51200, 51211, 51622, 51649, 51650, 51798, 51949, 52867, 53179, 53268, 53535, 53672, 54364, 54601, 54917, 55253, 55307, 55565, 56240, 56458, 56529, 56571, 56575, 56616, 56691, 56910, 57047, 57647, 57665, 57834, 57855, 58048, 58058, 58078, 58263, 58470, 58943, 59166, 59402, 60099, 60279, 60576, 61265, 61547, 61810, 61860, 62377, 62496, 62878, 62971, 63089, 63193, 63435, 63792, 63837, 63981, 64034, 64147, 64457, 64528, 64544, 65084, 65164, 66162, 66708, 66864, 67030, 67301, 67467, 67473, 67853, 67875, 67897, 68014, 68100, 68101, 68309, 68341, 68621, 68786, 68806, 68880, 68893, 68908, 69035, 69399, 69913, 69952, 70372, 70466, 70738, 71256, 71286, 71791, 71954, 72013, 72151, 72175, 72305, 72325, 72425, 72550, 72823, 73134, 73171, 73241, 73273, 73520, 73650, 74351, 75691, 76107, 76231, 76232, 76614, 76638, 76698, 77191, 77556, 77610, 77721, 78451, 78567, 78668, 78890, 79077, 79777, 79994, 81019, 81096, 81312, 81426, 82136, 82276, 82636, 83041, 83144, 83444, 83849, 83921, 83926, 83933, 84093, 84935, 85816, 86057, 86198, 86284, 86379, 87343, 87501, 87816, 88086, 88190, 88424, 88885, 89091, 89360, 90225, 90257, 90578, 91068, 91110, 91137, 91393, 92712, 94167, 94627, 94898, 94945, 94983, 96451, 96576, 96765, 96888, 96976, 97189, 97789, 98025, 98235, 98294, 98359, 98569, 99076, 99543 AND isnotnull(substr(ca_zip#9, 1, 5))) + +(15) CometProject +Input [1]: [ca_zip#9] +Arguments: [ca_zip#10], [substr(ca_zip#9, 1, 5) AS ca_zip#10] + +(16) ColumnarToRow [codegen id : 6] +Input [1]: [ca_zip#10] + +(17) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#11, ca_zip#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk)] +ReadSchema: struct + +(18) CometFilter +Input [2]: [ca_address_sk#11, ca_zip#12] +Condition : isnotnull(ca_address_sk#11) + +(19) ColumnarToRow [codegen id : 4] +Input [2]: [ca_address_sk#11, ca_zip#12] + +(20) Scan parquet spark_catalog.default.customer +Output [2]: [c_current_addr_sk#13, c_preferred_cust_flag#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_preferred_cust_flag), EqualTo(c_preferred_cust_flag,Y), IsNotNull(c_current_addr_sk)] +ReadSchema: struct + +(21) CometFilter +Input [2]: [c_current_addr_sk#13, c_preferred_cust_flag#14] +Condition : ((isnotnull(c_preferred_cust_flag#14) AND (c_preferred_cust_flag#14 = Y)) AND isnotnull(c_current_addr_sk#13)) + +(22) CometProject +Input [2]: [c_current_addr_sk#13, c_preferred_cust_flag#14] +Arguments: [c_current_addr_sk#13], [c_current_addr_sk#13] + +(23) ColumnarToRow [codegen id : 3] +Input [1]: [c_current_addr_sk#13] + +(24) BroadcastExchange +Input [1]: [c_current_addr_sk#13] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(25) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ca_address_sk#11] +Right keys [1]: [c_current_addr_sk#13] +Join type: Inner +Join condition: None + +(26) Project [codegen id : 4] +Output [1]: [ca_zip#12] +Input [3]: [ca_address_sk#11, ca_zip#12, c_current_addr_sk#13] + +(27) HashAggregate [codegen id : 4] +Input [1]: [ca_zip#12] +Keys [1]: [ca_zip#12] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#15] +Results [2]: [ca_zip#12, count#16] + +(28) Exchange +Input [2]: [ca_zip#12, count#16] +Arguments: hashpartitioning(ca_zip#12, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(29) HashAggregate [codegen id : 5] +Input [2]: [ca_zip#12, count#16] +Keys [1]: [ca_zip#12] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#17] +Results [2]: [substr(ca_zip#12, 1, 5) AS ca_zip#18, count(1)#17 AS cnt#19] + +(30) Filter [codegen id : 5] +Input [2]: [ca_zip#18, cnt#19] +Condition : (cnt#19 > 10) + +(31) Project [codegen id : 5] +Output [1]: [ca_zip#18] +Input [2]: [ca_zip#18, cnt#19] + +(32) BroadcastExchange +Input [1]: [ca_zip#18] +Arguments: HashedRelationBroadcastMode(List(coalesce(input[0, string, true], ), isnull(input[0, string, true])),false), [plan_id=4] + +(33) BroadcastHashJoin [codegen id : 6] +Left keys [2]: [coalesce(ca_zip#10, ), isnull(ca_zip#10)] +Right keys [2]: [coalesce(ca_zip#18, ), isnull(ca_zip#18)] +Join type: LeftSemi +Join condition: None + +(34) HashAggregate [codegen id : 6] +Input [1]: [ca_zip#10] +Keys [1]: [ca_zip#10] +Functions: [] +Aggregate Attributes: [] +Results [1]: [ca_zip#10] + +(35) Exchange +Input [1]: [ca_zip#10] +Arguments: hashpartitioning(ca_zip#10, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(36) HashAggregate [codegen id : 7] +Input [1]: [ca_zip#10] +Keys [1]: [ca_zip#10] +Functions: [] +Aggregate Attributes: [] +Results [1]: [ca_zip#10] + +(37) BroadcastExchange +Input [1]: [ca_zip#10] +Arguments: HashedRelationBroadcastMode(List(substr(input[0, string, true], 1, 2)),false), [plan_id=6] + +(38) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [substr(s_zip#8, 1, 2)] +Right keys [1]: [substr(ca_zip#10, 1, 2)] +Join type: Inner +Join condition: None + +(39) Project [codegen id : 8] +Output [2]: [ss_net_profit#2, s_store_name#7] +Input [4]: [ss_net_profit#2, s_store_name#7, s_zip#8, ca_zip#10] + +(40) HashAggregate [codegen id : 8] +Input [2]: [ss_net_profit#2, s_store_name#7] +Keys [1]: [s_store_name#7] +Functions [1]: [partial_sum(UnscaledValue(ss_net_profit#2))] +Aggregate Attributes [1]: [sum#20] +Results [2]: [s_store_name#7, sum#21] + +(41) Exchange +Input [2]: [s_store_name#7, sum#21] +Arguments: hashpartitioning(s_store_name#7, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(42) HashAggregate [codegen id : 9] +Input [2]: [s_store_name#7, sum#21] +Keys [1]: [s_store_name#7] +Functions [1]: [sum(UnscaledValue(ss_net_profit#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_profit#2))#22] +Results [2]: [s_store_name#7, MakeDecimal(sum(UnscaledValue(ss_net_profit#2))#22,17,2) AS sum(ss_net_profit)#23] + +(43) TakeOrderedAndProject +Input [2]: [s_store_name#7, sum(ss_net_profit)#23] +Arguments: 100, [s_store_name#7 ASC NULLS FIRST], [s_store_name#7, sum(ss_net_profit)#23] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (48) ++- * ColumnarToRow (47) + +- CometProject (46) + +- CometFilter (45) + +- CometScan parquet spark_catalog.default.date_dim (44) + + +(44) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#5, d_year#24, d_qoy#25] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_qoy), IsNotNull(d_year), EqualTo(d_qoy,2), EqualTo(d_year,1998), IsNotNull(d_date_sk)] +ReadSchema: struct + +(45) CometFilter +Input [3]: [d_date_sk#5, d_year#24, d_qoy#25] +Condition : ((((isnotnull(d_qoy#25) AND isnotnull(d_year#24)) AND (d_qoy#25 = 2)) AND (d_year#24 = 1998)) AND isnotnull(d_date_sk#5)) + +(46) CometProject +Input [3]: [d_date_sk#5, d_year#24, d_qoy#25] +Arguments: [d_date_sk#5], [d_date_sk#5] + +(47) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#5] + +(48) BroadcastExchange +Input [1]: [d_date_sk#5] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q8/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q8/simplified.txt new file mode 100644 index 0000000000..76fa276931 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q8/simplified.txt @@ -0,0 +1,72 @@ +TakeOrderedAndProject [s_store_name,sum(ss_net_profit)] + WholeStageCodegen (9) + HashAggregate [s_store_name,sum] [sum(UnscaledValue(ss_net_profit)),sum(ss_net_profit),sum] + InputAdapter + Exchange [s_store_name] #1 + WholeStageCodegen (8) + HashAggregate [s_store_name,ss_net_profit] [sum,sum] + Project [ss_net_profit,s_store_name] + BroadcastHashJoin [s_zip,ca_zip] + Project [ss_net_profit,s_store_name,s_zip] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_store_sk,ss_net_profit] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_store_sk,ss_net_profit,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_qoy,d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_qoy] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [s_store_sk,s_zip] + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name,s_zip] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (7) + HashAggregate [ca_zip] + InputAdapter + Exchange [ca_zip] #5 + WholeStageCodegen (6) + HashAggregate [ca_zip] + BroadcastHashJoin [ca_zip,ca_zip] + ColumnarToRow + InputAdapter + CometProject [ca_zip] [ca_zip] + CometFilter [ca_zip] + CometScan parquet spark_catalog.default.customer_address [ca_zip] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (5) + Project [ca_zip] + Filter [cnt] + HashAggregate [ca_zip,count] [count(1),ca_zip,cnt,count] + InputAdapter + Exchange [ca_zip] #7 + WholeStageCodegen (4) + HashAggregate [ca_zip] [count,count] + Project [ca_zip] + BroadcastHashJoin [ca_address_sk,c_current_addr_sk] + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_zip] + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometProject [c_current_addr_sk] + CometFilter [c_preferred_cust_flag,c_current_addr_sk] + CometScan parquet spark_catalog.default.customer [c_current_addr_sk,c_preferred_cust_flag] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q80/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q80/explain.txt new file mode 100644 index 0000000000..db2d015db2 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q80/explain.txt @@ -0,0 +1,645 @@ +== Physical Plan == +TakeOrderedAndProject (107) ++- * HashAggregate (106) + +- Exchange (105) + +- * HashAggregate (104) + +- * Expand (103) + +- Union (102) + :- * HashAggregate (39) + : +- Exchange (38) + : +- * HashAggregate (37) + : +- * Project (36) + : +- * BroadcastHashJoin Inner BuildRight (35) + : :- * Project (29) + : : +- * BroadcastHashJoin Inner BuildRight (28) + : : :- * Project (22) + : : : +- * BroadcastHashJoin Inner BuildRight (21) + : : : :- * Project (16) + : : : : +- * BroadcastHashJoin Inner BuildRight (15) + : : : : :- * Project (13) + : : : : : +- * SortMergeJoin LeftOuter (12) + : : : : : :- * Sort (5) + : : : : : : +- Exchange (4) + : : : : : : +- * ColumnarToRow (3) + : : : : : : +- CometFilter (2) + : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : : +- * Sort (11) + : : : : : +- Exchange (10) + : : : : : +- * ColumnarToRow (9) + : : : : : +- CometProject (8) + : : : : : +- CometFilter (7) + : : : : : +- CometScan parquet spark_catalog.default.store_returns (6) + : : : : +- ReusedExchange (14) + : : : +- BroadcastExchange (20) + : : : +- * ColumnarToRow (19) + : : : +- CometFilter (18) + : : : +- CometScan parquet spark_catalog.default.store (17) + : : +- BroadcastExchange (27) + : : +- * ColumnarToRow (26) + : : +- CometProject (25) + : : +- CometFilter (24) + : : +- CometScan parquet spark_catalog.default.item (23) + : +- BroadcastExchange (34) + : +- * ColumnarToRow (33) + : +- CometProject (32) + : +- CometFilter (31) + : +- CometScan parquet spark_catalog.default.promotion (30) + :- * HashAggregate (70) + : +- Exchange (69) + : +- * HashAggregate (68) + : +- * Project (67) + : +- * BroadcastHashJoin Inner BuildRight (66) + : :- * Project (64) + : : +- * BroadcastHashJoin Inner BuildRight (63) + : : :- * Project (61) + : : : +- * BroadcastHashJoin Inner BuildRight (60) + : : : :- * Project (55) + : : : : +- * BroadcastHashJoin Inner BuildRight (54) + : : : : :- * Project (52) + : : : : : +- * SortMergeJoin LeftOuter (51) + : : : : : :- * Sort (44) + : : : : : : +- Exchange (43) + : : : : : : +- * ColumnarToRow (42) + : : : : : : +- CometFilter (41) + : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (40) + : : : : : +- * Sort (50) + : : : : : +- Exchange (49) + : : : : : +- * ColumnarToRow (48) + : : : : : +- CometProject (47) + : : : : : +- CometFilter (46) + : : : : : +- CometScan parquet spark_catalog.default.catalog_returns (45) + : : : : +- ReusedExchange (53) + : : : +- BroadcastExchange (59) + : : : +- * ColumnarToRow (58) + : : : +- CometFilter (57) + : : : +- CometScan parquet spark_catalog.default.catalog_page (56) + : : +- ReusedExchange (62) + : +- ReusedExchange (65) + +- * HashAggregate (101) + +- Exchange (100) + +- * HashAggregate (99) + +- * Project (98) + +- * BroadcastHashJoin Inner BuildRight (97) + :- * Project (95) + : +- * BroadcastHashJoin Inner BuildRight (94) + : :- * Project (92) + : : +- * BroadcastHashJoin Inner BuildRight (91) + : : :- * Project (86) + : : : +- * BroadcastHashJoin Inner BuildRight (85) + : : : :- * Project (83) + : : : : +- * SortMergeJoin LeftOuter (82) + : : : : :- * Sort (75) + : : : : : +- Exchange (74) + : : : : : +- * ColumnarToRow (73) + : : : : : +- CometFilter (72) + : : : : : +- CometScan parquet spark_catalog.default.web_sales (71) + : : : : +- * Sort (81) + : : : : +- Exchange (80) + : : : : +- * ColumnarToRow (79) + : : : : +- CometProject (78) + : : : : +- CometFilter (77) + : : : : +- CometScan parquet spark_catalog.default.web_returns (76) + : : : +- ReusedExchange (84) + : : +- BroadcastExchange (90) + : : +- * ColumnarToRow (89) + : : +- CometFilter (88) + : : +- CometScan parquet spark_catalog.default.web_site (87) + : +- ReusedExchange (93) + +- ReusedExchange (96) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [7]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ticket_number#4, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sold_date_sk#7 IN dynamicpruning#8)] +PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_item_sk), IsNotNull(ss_promo_sk)] +ReadSchema: struct + +(2) CometFilter +Input [7]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ticket_number#4, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] +Condition : ((isnotnull(ss_store_sk#2) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_promo_sk#3)) + +(3) ColumnarToRow [codegen id : 1] +Input [7]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ticket_number#4, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] + +(4) Exchange +Input [7]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ticket_number#4, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] +Arguments: hashpartitioning(ss_item_sk#1, ss_ticket_number#4, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(5) Sort [codegen id : 2] +Input [7]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ticket_number#4, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] +Arguments: [ss_item_sk#1 ASC NULLS FIRST, ss_ticket_number#4 ASC NULLS FIRST], false, 0 + +(6) Scan parquet spark_catalog.default.store_returns +Output [5]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12, sr_returned_date_sk#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_returns] +PushedFilters: [IsNotNull(sr_item_sk), IsNotNull(sr_ticket_number)] +ReadSchema: struct + +(7) CometFilter +Input [5]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12, sr_returned_date_sk#13] +Condition : (isnotnull(sr_item_sk#9) AND isnotnull(sr_ticket_number#10)) + +(8) CometProject +Input [5]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12, sr_returned_date_sk#13] +Arguments: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12], [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12] + +(9) ColumnarToRow [codegen id : 3] +Input [4]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12] + +(10) Exchange +Input [4]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12] +Arguments: hashpartitioning(sr_item_sk#9, sr_ticket_number#10, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(11) Sort [codegen id : 4] +Input [4]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12] +Arguments: [sr_item_sk#9 ASC NULLS FIRST, sr_ticket_number#10 ASC NULLS FIRST], false, 0 + +(12) SortMergeJoin [codegen id : 9] +Left keys [2]: [ss_item_sk#1, ss_ticket_number#4] +Right keys [2]: [sr_item_sk#9, sr_ticket_number#10] +Join type: LeftOuter +Join condition: None + +(13) Project [codegen id : 9] +Output [8]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7, sr_return_amt#11, sr_net_loss#12] +Input [11]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ticket_number#4, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7, sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12] + +(14) ReusedExchange [Reuses operator id: 112] +Output [1]: [d_date_sk#14] + +(15) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_sold_date_sk#7] +Right keys [1]: [d_date_sk#14] +Join type: Inner +Join condition: None + +(16) Project [codegen id : 9] +Output [7]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ext_sales_price#5, ss_net_profit#6, sr_return_amt#11, sr_net_loss#12] +Input [9]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7, sr_return_amt#11, sr_net_loss#12, d_date_sk#14] + +(17) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#15, s_store_id#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(18) CometFilter +Input [2]: [s_store_sk#15, s_store_id#16] +Condition : isnotnull(s_store_sk#15) + +(19) ColumnarToRow [codegen id : 6] +Input [2]: [s_store_sk#15, s_store_id#16] + +(20) BroadcastExchange +Input [2]: [s_store_sk#15, s_store_id#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(21) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_store_sk#2] +Right keys [1]: [s_store_sk#15] +Join type: Inner +Join condition: None + +(22) Project [codegen id : 9] +Output [7]: [ss_item_sk#1, ss_promo_sk#3, ss_ext_sales_price#5, ss_net_profit#6, sr_return_amt#11, sr_net_loss#12, s_store_id#16] +Input [9]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ext_sales_price#5, ss_net_profit#6, sr_return_amt#11, sr_net_loss#12, s_store_sk#15, s_store_id#16] + +(23) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#17, i_current_price#18] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_current_price), GreaterThan(i_current_price,50.00), IsNotNull(i_item_sk)] +ReadSchema: struct + +(24) CometFilter +Input [2]: [i_item_sk#17, i_current_price#18] +Condition : ((isnotnull(i_current_price#18) AND (i_current_price#18 > 50.00)) AND isnotnull(i_item_sk#17)) + +(25) CometProject +Input [2]: [i_item_sk#17, i_current_price#18] +Arguments: [i_item_sk#17], [i_item_sk#17] + +(26) ColumnarToRow [codegen id : 7] +Input [1]: [i_item_sk#17] + +(27) BroadcastExchange +Input [1]: [i_item_sk#17] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(28) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#17] +Join type: Inner +Join condition: None + +(29) Project [codegen id : 9] +Output [6]: [ss_promo_sk#3, ss_ext_sales_price#5, ss_net_profit#6, sr_return_amt#11, sr_net_loss#12, s_store_id#16] +Input [8]: [ss_item_sk#1, ss_promo_sk#3, ss_ext_sales_price#5, ss_net_profit#6, sr_return_amt#11, sr_net_loss#12, s_store_id#16, i_item_sk#17] + +(30) Scan parquet spark_catalog.default.promotion +Output [2]: [p_promo_sk#19, p_channel_tv#20] +Batched: true +Location [not included in comparison]/{warehouse_dir}/promotion] +PushedFilters: [IsNotNull(p_channel_tv), EqualTo(p_channel_tv,N), IsNotNull(p_promo_sk)] +ReadSchema: struct + +(31) CometFilter +Input [2]: [p_promo_sk#19, p_channel_tv#20] +Condition : ((isnotnull(p_channel_tv#20) AND (p_channel_tv#20 = N)) AND isnotnull(p_promo_sk#19)) + +(32) CometProject +Input [2]: [p_promo_sk#19, p_channel_tv#20] +Arguments: [p_promo_sk#19], [p_promo_sk#19] + +(33) ColumnarToRow [codegen id : 8] +Input [1]: [p_promo_sk#19] + +(34) BroadcastExchange +Input [1]: [p_promo_sk#19] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +(35) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_promo_sk#3] +Right keys [1]: [p_promo_sk#19] +Join type: Inner +Join condition: None + +(36) Project [codegen id : 9] +Output [5]: [ss_ext_sales_price#5, ss_net_profit#6, sr_return_amt#11, sr_net_loss#12, s_store_id#16] +Input [7]: [ss_promo_sk#3, ss_ext_sales_price#5, ss_net_profit#6, sr_return_amt#11, sr_net_loss#12, s_store_id#16, p_promo_sk#19] + +(37) HashAggregate [codegen id : 9] +Input [5]: [ss_ext_sales_price#5, ss_net_profit#6, sr_return_amt#11, sr_net_loss#12, s_store_id#16] +Keys [1]: [s_store_id#16] +Functions [3]: [partial_sum(UnscaledValue(ss_ext_sales_price#5)), partial_sum(coalesce(cast(sr_return_amt#11 as decimal(12,2)), 0.00)), partial_sum((ss_net_profit#6 - coalesce(cast(sr_net_loss#12 as decimal(12,2)), 0.00)))] +Aggregate Attributes [5]: [sum#21, sum#22, isEmpty#23, sum#24, isEmpty#25] +Results [6]: [s_store_id#16, sum#26, sum#27, isEmpty#28, sum#29, isEmpty#30] + +(38) Exchange +Input [6]: [s_store_id#16, sum#26, sum#27, isEmpty#28, sum#29, isEmpty#30] +Arguments: hashpartitioning(s_store_id#16, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(39) HashAggregate [codegen id : 10] +Input [6]: [s_store_id#16, sum#26, sum#27, isEmpty#28, sum#29, isEmpty#30] +Keys [1]: [s_store_id#16] +Functions [3]: [sum(UnscaledValue(ss_ext_sales_price#5)), sum(coalesce(cast(sr_return_amt#11 as decimal(12,2)), 0.00)), sum((ss_net_profit#6 - coalesce(cast(sr_net_loss#12 as decimal(12,2)), 0.00)))] +Aggregate Attributes [3]: [sum(UnscaledValue(ss_ext_sales_price#5))#31, sum(coalesce(cast(sr_return_amt#11 as decimal(12,2)), 0.00))#32, sum((ss_net_profit#6 - coalesce(cast(sr_net_loss#12 as decimal(12,2)), 0.00)))#33] +Results [5]: [MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#5))#31,17,2) AS sales#34, sum(coalesce(cast(sr_return_amt#11 as decimal(12,2)), 0.00))#32 AS returns#35, sum((ss_net_profit#6 - coalesce(cast(sr_net_loss#12 as decimal(12,2)), 0.00)))#33 AS profit#36, store channel AS channel#37, concat(store, s_store_id#16) AS id#38] + +(40) Scan parquet spark_catalog.default.catalog_sales +Output [7]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_order_number#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#45), dynamicpruningexpression(cs_sold_date_sk#45 IN dynamicpruning#46)] +PushedFilters: [IsNotNull(cs_catalog_page_sk), IsNotNull(cs_item_sk), IsNotNull(cs_promo_sk)] +ReadSchema: struct + +(41) CometFilter +Input [7]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_order_number#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] +Condition : ((isnotnull(cs_catalog_page_sk#39) AND isnotnull(cs_item_sk#40)) AND isnotnull(cs_promo_sk#41)) + +(42) ColumnarToRow [codegen id : 11] +Input [7]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_order_number#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] + +(43) Exchange +Input [7]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_order_number#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] +Arguments: hashpartitioning(cs_item_sk#40, cs_order_number#42, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(44) Sort [codegen id : 12] +Input [7]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_order_number#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] +Arguments: [cs_item_sk#40 ASC NULLS FIRST, cs_order_number#42 ASC NULLS FIRST], false, 0 + +(45) Scan parquet spark_catalog.default.catalog_returns +Output [5]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50, cr_returned_date_sk#51] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_returns] +PushedFilters: [IsNotNull(cr_item_sk), IsNotNull(cr_order_number)] +ReadSchema: struct + +(46) CometFilter +Input [5]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50, cr_returned_date_sk#51] +Condition : (isnotnull(cr_item_sk#47) AND isnotnull(cr_order_number#48)) + +(47) CometProject +Input [5]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50, cr_returned_date_sk#51] +Arguments: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50], [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50] + +(48) ColumnarToRow [codegen id : 13] +Input [4]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50] + +(49) Exchange +Input [4]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50] +Arguments: hashpartitioning(cr_item_sk#47, cr_order_number#48, 5), ENSURE_REQUIREMENTS, [plan_id=8] + +(50) Sort [codegen id : 14] +Input [4]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50] +Arguments: [cr_item_sk#47 ASC NULLS FIRST, cr_order_number#48 ASC NULLS FIRST], false, 0 + +(51) SortMergeJoin [codegen id : 19] +Left keys [2]: [cs_item_sk#40, cs_order_number#42] +Right keys [2]: [cr_item_sk#47, cr_order_number#48] +Join type: LeftOuter +Join condition: None + +(52) Project [codegen id : 19] +Output [8]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45, cr_return_amount#49, cr_net_loss#50] +Input [11]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_order_number#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45, cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50] + +(53) ReusedExchange [Reuses operator id: 112] +Output [1]: [d_date_sk#52] + +(54) BroadcastHashJoin [codegen id : 19] +Left keys [1]: [cs_sold_date_sk#45] +Right keys [1]: [d_date_sk#52] +Join type: Inner +Join condition: None + +(55) Project [codegen id : 19] +Output [7]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_ext_sales_price#43, cs_net_profit#44, cr_return_amount#49, cr_net_loss#50] +Input [9]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45, cr_return_amount#49, cr_net_loss#50, d_date_sk#52] + +(56) Scan parquet spark_catalog.default.catalog_page +Output [2]: [cp_catalog_page_sk#53, cp_catalog_page_id#54] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_page] +PushedFilters: [IsNotNull(cp_catalog_page_sk)] +ReadSchema: struct + +(57) CometFilter +Input [2]: [cp_catalog_page_sk#53, cp_catalog_page_id#54] +Condition : isnotnull(cp_catalog_page_sk#53) + +(58) ColumnarToRow [codegen id : 16] +Input [2]: [cp_catalog_page_sk#53, cp_catalog_page_id#54] + +(59) BroadcastExchange +Input [2]: [cp_catalog_page_sk#53, cp_catalog_page_id#54] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=9] + +(60) BroadcastHashJoin [codegen id : 19] +Left keys [1]: [cs_catalog_page_sk#39] +Right keys [1]: [cp_catalog_page_sk#53] +Join type: Inner +Join condition: None + +(61) Project [codegen id : 19] +Output [7]: [cs_item_sk#40, cs_promo_sk#41, cs_ext_sales_price#43, cs_net_profit#44, cr_return_amount#49, cr_net_loss#50, cp_catalog_page_id#54] +Input [9]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_ext_sales_price#43, cs_net_profit#44, cr_return_amount#49, cr_net_loss#50, cp_catalog_page_sk#53, cp_catalog_page_id#54] + +(62) ReusedExchange [Reuses operator id: 27] +Output [1]: [i_item_sk#55] + +(63) BroadcastHashJoin [codegen id : 19] +Left keys [1]: [cs_item_sk#40] +Right keys [1]: [i_item_sk#55] +Join type: Inner +Join condition: None + +(64) Project [codegen id : 19] +Output [6]: [cs_promo_sk#41, cs_ext_sales_price#43, cs_net_profit#44, cr_return_amount#49, cr_net_loss#50, cp_catalog_page_id#54] +Input [8]: [cs_item_sk#40, cs_promo_sk#41, cs_ext_sales_price#43, cs_net_profit#44, cr_return_amount#49, cr_net_loss#50, cp_catalog_page_id#54, i_item_sk#55] + +(65) ReusedExchange [Reuses operator id: 34] +Output [1]: [p_promo_sk#56] + +(66) BroadcastHashJoin [codegen id : 19] +Left keys [1]: [cs_promo_sk#41] +Right keys [1]: [p_promo_sk#56] +Join type: Inner +Join condition: None + +(67) Project [codegen id : 19] +Output [5]: [cs_ext_sales_price#43, cs_net_profit#44, cr_return_amount#49, cr_net_loss#50, cp_catalog_page_id#54] +Input [7]: [cs_promo_sk#41, cs_ext_sales_price#43, cs_net_profit#44, cr_return_amount#49, cr_net_loss#50, cp_catalog_page_id#54, p_promo_sk#56] + +(68) HashAggregate [codegen id : 19] +Input [5]: [cs_ext_sales_price#43, cs_net_profit#44, cr_return_amount#49, cr_net_loss#50, cp_catalog_page_id#54] +Keys [1]: [cp_catalog_page_id#54] +Functions [3]: [partial_sum(UnscaledValue(cs_ext_sales_price#43)), partial_sum(coalesce(cast(cr_return_amount#49 as decimal(12,2)), 0.00)), partial_sum((cs_net_profit#44 - coalesce(cast(cr_net_loss#50 as decimal(12,2)), 0.00)))] +Aggregate Attributes [5]: [sum#57, sum#58, isEmpty#59, sum#60, isEmpty#61] +Results [6]: [cp_catalog_page_id#54, sum#62, sum#63, isEmpty#64, sum#65, isEmpty#66] + +(69) Exchange +Input [6]: [cp_catalog_page_id#54, sum#62, sum#63, isEmpty#64, sum#65, isEmpty#66] +Arguments: hashpartitioning(cp_catalog_page_id#54, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(70) HashAggregate [codegen id : 20] +Input [6]: [cp_catalog_page_id#54, sum#62, sum#63, isEmpty#64, sum#65, isEmpty#66] +Keys [1]: [cp_catalog_page_id#54] +Functions [3]: [sum(UnscaledValue(cs_ext_sales_price#43)), sum(coalesce(cast(cr_return_amount#49 as decimal(12,2)), 0.00)), sum((cs_net_profit#44 - coalesce(cast(cr_net_loss#50 as decimal(12,2)), 0.00)))] +Aggregate Attributes [3]: [sum(UnscaledValue(cs_ext_sales_price#43))#67, sum(coalesce(cast(cr_return_amount#49 as decimal(12,2)), 0.00))#68, sum((cs_net_profit#44 - coalesce(cast(cr_net_loss#50 as decimal(12,2)), 0.00)))#69] +Results [5]: [MakeDecimal(sum(UnscaledValue(cs_ext_sales_price#43))#67,17,2) AS sales#70, sum(coalesce(cast(cr_return_amount#49 as decimal(12,2)), 0.00))#68 AS returns#71, sum((cs_net_profit#44 - coalesce(cast(cr_net_loss#50 as decimal(12,2)), 0.00)))#69 AS profit#72, catalog channel AS channel#73, concat(catalog_page, cp_catalog_page_id#54) AS id#74] + +(71) Scan parquet spark_catalog.default.web_sales +Output [7]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_order_number#78, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#81), dynamicpruningexpression(ws_sold_date_sk#81 IN dynamicpruning#82)] +PushedFilters: [IsNotNull(ws_web_site_sk), IsNotNull(ws_item_sk), IsNotNull(ws_promo_sk)] +ReadSchema: struct + +(72) CometFilter +Input [7]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_order_number#78, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81] +Condition : ((isnotnull(ws_web_site_sk#76) AND isnotnull(ws_item_sk#75)) AND isnotnull(ws_promo_sk#77)) + +(73) ColumnarToRow [codegen id : 21] +Input [7]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_order_number#78, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81] + +(74) Exchange +Input [7]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_order_number#78, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81] +Arguments: hashpartitioning(ws_item_sk#75, ws_order_number#78, 5), ENSURE_REQUIREMENTS, [plan_id=11] + +(75) Sort [codegen id : 22] +Input [7]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_order_number#78, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81] +Arguments: [ws_item_sk#75 ASC NULLS FIRST, ws_order_number#78 ASC NULLS FIRST], false, 0 + +(76) Scan parquet spark_catalog.default.web_returns +Output [5]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86, wr_returned_date_sk#87] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_returns] +PushedFilters: [IsNotNull(wr_item_sk), IsNotNull(wr_order_number)] +ReadSchema: struct + +(77) CometFilter +Input [5]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86, wr_returned_date_sk#87] +Condition : (isnotnull(wr_item_sk#83) AND isnotnull(wr_order_number#84)) + +(78) CometProject +Input [5]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86, wr_returned_date_sk#87] +Arguments: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86], [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86] + +(79) ColumnarToRow [codegen id : 23] +Input [4]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86] + +(80) Exchange +Input [4]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86] +Arguments: hashpartitioning(wr_item_sk#83, wr_order_number#84, 5), ENSURE_REQUIREMENTS, [plan_id=12] + +(81) Sort [codegen id : 24] +Input [4]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86] +Arguments: [wr_item_sk#83 ASC NULLS FIRST, wr_order_number#84 ASC NULLS FIRST], false, 0 + +(82) SortMergeJoin [codegen id : 29] +Left keys [2]: [ws_item_sk#75, ws_order_number#78] +Right keys [2]: [wr_item_sk#83, wr_order_number#84] +Join type: LeftOuter +Join condition: None + +(83) Project [codegen id : 29] +Output [8]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81, wr_return_amt#85, wr_net_loss#86] +Input [11]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_order_number#78, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81, wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86] + +(84) ReusedExchange [Reuses operator id: 112] +Output [1]: [d_date_sk#88] + +(85) BroadcastHashJoin [codegen id : 29] +Left keys [1]: [ws_sold_date_sk#81] +Right keys [1]: [d_date_sk#88] +Join type: Inner +Join condition: None + +(86) Project [codegen id : 29] +Output [7]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_ext_sales_price#79, ws_net_profit#80, wr_return_amt#85, wr_net_loss#86] +Input [9]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81, wr_return_amt#85, wr_net_loss#86, d_date_sk#88] + +(87) Scan parquet spark_catalog.default.web_site +Output [2]: [web_site_sk#89, web_site_id#90] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_site] +PushedFilters: [IsNotNull(web_site_sk)] +ReadSchema: struct + +(88) CometFilter +Input [2]: [web_site_sk#89, web_site_id#90] +Condition : isnotnull(web_site_sk#89) + +(89) ColumnarToRow [codegen id : 26] +Input [2]: [web_site_sk#89, web_site_id#90] + +(90) BroadcastExchange +Input [2]: [web_site_sk#89, web_site_id#90] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=13] + +(91) BroadcastHashJoin [codegen id : 29] +Left keys [1]: [ws_web_site_sk#76] +Right keys [1]: [web_site_sk#89] +Join type: Inner +Join condition: None + +(92) Project [codegen id : 29] +Output [7]: [ws_item_sk#75, ws_promo_sk#77, ws_ext_sales_price#79, ws_net_profit#80, wr_return_amt#85, wr_net_loss#86, web_site_id#90] +Input [9]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_ext_sales_price#79, ws_net_profit#80, wr_return_amt#85, wr_net_loss#86, web_site_sk#89, web_site_id#90] + +(93) ReusedExchange [Reuses operator id: 27] +Output [1]: [i_item_sk#91] + +(94) BroadcastHashJoin [codegen id : 29] +Left keys [1]: [ws_item_sk#75] +Right keys [1]: [i_item_sk#91] +Join type: Inner +Join condition: None + +(95) Project [codegen id : 29] +Output [6]: [ws_promo_sk#77, ws_ext_sales_price#79, ws_net_profit#80, wr_return_amt#85, wr_net_loss#86, web_site_id#90] +Input [8]: [ws_item_sk#75, ws_promo_sk#77, ws_ext_sales_price#79, ws_net_profit#80, wr_return_amt#85, wr_net_loss#86, web_site_id#90, i_item_sk#91] + +(96) ReusedExchange [Reuses operator id: 34] +Output [1]: [p_promo_sk#92] + +(97) BroadcastHashJoin [codegen id : 29] +Left keys [1]: [ws_promo_sk#77] +Right keys [1]: [p_promo_sk#92] +Join type: Inner +Join condition: None + +(98) Project [codegen id : 29] +Output [5]: [ws_ext_sales_price#79, ws_net_profit#80, wr_return_amt#85, wr_net_loss#86, web_site_id#90] +Input [7]: [ws_promo_sk#77, ws_ext_sales_price#79, ws_net_profit#80, wr_return_amt#85, wr_net_loss#86, web_site_id#90, p_promo_sk#92] + +(99) HashAggregate [codegen id : 29] +Input [5]: [ws_ext_sales_price#79, ws_net_profit#80, wr_return_amt#85, wr_net_loss#86, web_site_id#90] +Keys [1]: [web_site_id#90] +Functions [3]: [partial_sum(UnscaledValue(ws_ext_sales_price#79)), partial_sum(coalesce(cast(wr_return_amt#85 as decimal(12,2)), 0.00)), partial_sum((ws_net_profit#80 - coalesce(cast(wr_net_loss#86 as decimal(12,2)), 0.00)))] +Aggregate Attributes [5]: [sum#93, sum#94, isEmpty#95, sum#96, isEmpty#97] +Results [6]: [web_site_id#90, sum#98, sum#99, isEmpty#100, sum#101, isEmpty#102] + +(100) Exchange +Input [6]: [web_site_id#90, sum#98, sum#99, isEmpty#100, sum#101, isEmpty#102] +Arguments: hashpartitioning(web_site_id#90, 5), ENSURE_REQUIREMENTS, [plan_id=14] + +(101) HashAggregate [codegen id : 30] +Input [6]: [web_site_id#90, sum#98, sum#99, isEmpty#100, sum#101, isEmpty#102] +Keys [1]: [web_site_id#90] +Functions [3]: [sum(UnscaledValue(ws_ext_sales_price#79)), sum(coalesce(cast(wr_return_amt#85 as decimal(12,2)), 0.00)), sum((ws_net_profit#80 - coalesce(cast(wr_net_loss#86 as decimal(12,2)), 0.00)))] +Aggregate Attributes [3]: [sum(UnscaledValue(ws_ext_sales_price#79))#103, sum(coalesce(cast(wr_return_amt#85 as decimal(12,2)), 0.00))#104, sum((ws_net_profit#80 - coalesce(cast(wr_net_loss#86 as decimal(12,2)), 0.00)))#105] +Results [5]: [MakeDecimal(sum(UnscaledValue(ws_ext_sales_price#79))#103,17,2) AS sales#106, sum(coalesce(cast(wr_return_amt#85 as decimal(12,2)), 0.00))#104 AS returns#107, sum((ws_net_profit#80 - coalesce(cast(wr_net_loss#86 as decimal(12,2)), 0.00)))#105 AS profit#108, web channel AS channel#109, concat(web_site, web_site_id#90) AS id#110] + +(102) Union + +(103) Expand [codegen id : 31] +Input [5]: [sales#34, returns#35, profit#36, channel#37, id#38] +Arguments: [[sales#34, returns#35, profit#36, channel#37, id#38, 0], [sales#34, returns#35, profit#36, channel#37, null, 1], [sales#34, returns#35, profit#36, null, null, 3]], [sales#34, returns#35, profit#36, channel#111, id#112, spark_grouping_id#113] + +(104) HashAggregate [codegen id : 31] +Input [6]: [sales#34, returns#35, profit#36, channel#111, id#112, spark_grouping_id#113] +Keys [3]: [channel#111, id#112, spark_grouping_id#113] +Functions [3]: [partial_sum(sales#34), partial_sum(returns#35), partial_sum(profit#36)] +Aggregate Attributes [6]: [sum#114, isEmpty#115, sum#116, isEmpty#117, sum#118, isEmpty#119] +Results [9]: [channel#111, id#112, spark_grouping_id#113, sum#120, isEmpty#121, sum#122, isEmpty#123, sum#124, isEmpty#125] + +(105) Exchange +Input [9]: [channel#111, id#112, spark_grouping_id#113, sum#120, isEmpty#121, sum#122, isEmpty#123, sum#124, isEmpty#125] +Arguments: hashpartitioning(channel#111, id#112, spark_grouping_id#113, 5), ENSURE_REQUIREMENTS, [plan_id=15] + +(106) HashAggregate [codegen id : 32] +Input [9]: [channel#111, id#112, spark_grouping_id#113, sum#120, isEmpty#121, sum#122, isEmpty#123, sum#124, isEmpty#125] +Keys [3]: [channel#111, id#112, spark_grouping_id#113] +Functions [3]: [sum(sales#34), sum(returns#35), sum(profit#36)] +Aggregate Attributes [3]: [sum(sales#34)#126, sum(returns#35)#127, sum(profit#36)#128] +Results [5]: [channel#111, id#112, sum(sales#34)#126 AS sales#129, sum(returns#35)#127 AS returns#130, sum(profit#36)#128 AS profit#131] + +(107) TakeOrderedAndProject +Input [5]: [channel#111, id#112, sales#129, returns#130, profit#131] +Arguments: 100, [channel#111 ASC NULLS FIRST, id#112 ASC NULLS FIRST], [channel#111, id#112, sales#129, returns#130, profit#131] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (112) ++- * ColumnarToRow (111) + +- CometProject (110) + +- CometFilter (109) + +- CometScan parquet spark_catalog.default.date_dim (108) + + +(108) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#14, d_date#132] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,2000-08-23), LessThanOrEqual(d_date,2000-09-22), IsNotNull(d_date_sk)] +ReadSchema: struct + +(109) CometFilter +Input [2]: [d_date_sk#14, d_date#132] +Condition : (((isnotnull(d_date#132) AND (d_date#132 >= 2000-08-23)) AND (d_date#132 <= 2000-09-22)) AND isnotnull(d_date_sk#14)) + +(110) CometProject +Input [2]: [d_date_sk#14, d_date#132] +Arguments: [d_date_sk#14], [d_date_sk#14] + +(111) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#14] + +(112) BroadcastExchange +Input [1]: [d_date_sk#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=16] + +Subquery:2 Hosting operator id = 40 Hosting Expression = cs_sold_date_sk#45 IN dynamicpruning#8 + +Subquery:3 Hosting operator id = 71 Hosting Expression = ws_sold_date_sk#81 IN dynamicpruning#8 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q80/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q80/simplified.txt new file mode 100644 index 0000000000..7e257bdc64 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q80/simplified.txt @@ -0,0 +1,182 @@ +TakeOrderedAndProject [channel,id,sales,returns,profit] + WholeStageCodegen (32) + HashAggregate [channel,id,spark_grouping_id,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [channel,id,spark_grouping_id] #1 + WholeStageCodegen (31) + HashAggregate [channel,id,spark_grouping_id,sales,returns,profit] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + Expand [sales,returns,profit,channel,id] + InputAdapter + Union + WholeStageCodegen (10) + HashAggregate [s_store_id,sum,sum,isEmpty,sum,isEmpty] [sum(UnscaledValue(ss_ext_sales_price)),sum(coalesce(cast(sr_return_amt as decimal(12,2)), 0.00)),sum((ss_net_profit - coalesce(cast(sr_net_loss as decimal(12,2)), 0.00))),sales,returns,profit,channel,id,sum,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [s_store_id] #2 + WholeStageCodegen (9) + HashAggregate [s_store_id,ss_ext_sales_price,sr_return_amt,ss_net_profit,sr_net_loss] [sum,sum,isEmpty,sum,isEmpty,sum,sum,isEmpty,sum,isEmpty] + Project [ss_ext_sales_price,ss_net_profit,sr_return_amt,sr_net_loss,s_store_id] + BroadcastHashJoin [ss_promo_sk,p_promo_sk] + Project [ss_promo_sk,ss_ext_sales_price,ss_net_profit,sr_return_amt,sr_net_loss,s_store_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_promo_sk,ss_ext_sales_price,ss_net_profit,sr_return_amt,sr_net_loss,s_store_id] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_store_sk,ss_promo_sk,ss_ext_sales_price,ss_net_profit,sr_return_amt,sr_net_loss] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_store_sk,ss_promo_sk,ss_ext_sales_price,ss_net_profit,ss_sold_date_sk,sr_return_amt,sr_net_loss] + SortMergeJoin [ss_item_sk,ss_ticket_number,sr_item_sk,sr_ticket_number] + InputAdapter + WholeStageCodegen (2) + Sort [ss_item_sk,ss_ticket_number] + InputAdapter + Exchange [ss_item_sk,ss_ticket_number] #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk,ss_item_sk,ss_promo_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_promo_sk,ss_ticket_number,ss_ext_sales_price,ss_net_profit,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + WholeStageCodegen (4) + Sort [sr_item_sk,sr_ticket_number] + InputAdapter + Exchange [sr_item_sk,sr_ticket_number] #5 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometProject [sr_item_sk,sr_ticket_number,sr_return_amt,sr_net_loss] + CometFilter [sr_item_sk,sr_ticket_number] + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_return_amt,sr_net_loss,sr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (6) + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_id] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (7) + ColumnarToRow + InputAdapter + CometProject [i_item_sk] + CometFilter [i_current_price,i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price] + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (8) + ColumnarToRow + InputAdapter + CometProject [p_promo_sk] + CometFilter [p_channel_tv,p_promo_sk] + CometScan parquet spark_catalog.default.promotion [p_promo_sk,p_channel_tv] + WholeStageCodegen (20) + HashAggregate [cp_catalog_page_id,sum,sum,isEmpty,sum,isEmpty] [sum(UnscaledValue(cs_ext_sales_price)),sum(coalesce(cast(cr_return_amount as decimal(12,2)), 0.00)),sum((cs_net_profit - coalesce(cast(cr_net_loss as decimal(12,2)), 0.00))),sales,returns,profit,channel,id,sum,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [cp_catalog_page_id] #9 + WholeStageCodegen (19) + HashAggregate [cp_catalog_page_id,cs_ext_sales_price,cr_return_amount,cs_net_profit,cr_net_loss] [sum,sum,isEmpty,sum,isEmpty,sum,sum,isEmpty,sum,isEmpty] + Project [cs_ext_sales_price,cs_net_profit,cr_return_amount,cr_net_loss,cp_catalog_page_id] + BroadcastHashJoin [cs_promo_sk,p_promo_sk] + Project [cs_promo_sk,cs_ext_sales_price,cs_net_profit,cr_return_amount,cr_net_loss,cp_catalog_page_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Project [cs_item_sk,cs_promo_sk,cs_ext_sales_price,cs_net_profit,cr_return_amount,cr_net_loss,cp_catalog_page_id] + BroadcastHashJoin [cs_catalog_page_sk,cp_catalog_page_sk] + Project [cs_catalog_page_sk,cs_item_sk,cs_promo_sk,cs_ext_sales_price,cs_net_profit,cr_return_amount,cr_net_loss] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_catalog_page_sk,cs_item_sk,cs_promo_sk,cs_ext_sales_price,cs_net_profit,cs_sold_date_sk,cr_return_amount,cr_net_loss] + SortMergeJoin [cs_item_sk,cs_order_number,cr_item_sk,cr_order_number] + InputAdapter + WholeStageCodegen (12) + Sort [cs_item_sk,cs_order_number] + InputAdapter + Exchange [cs_item_sk,cs_order_number] #10 + WholeStageCodegen (11) + ColumnarToRow + InputAdapter + CometFilter [cs_catalog_page_sk,cs_item_sk,cs_promo_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_catalog_page_sk,cs_item_sk,cs_promo_sk,cs_order_number,cs_ext_sales_price,cs_net_profit,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + WholeStageCodegen (14) + Sort [cr_item_sk,cr_order_number] + InputAdapter + Exchange [cr_item_sk,cr_order_number] #11 + WholeStageCodegen (13) + ColumnarToRow + InputAdapter + CometProject [cr_item_sk,cr_order_number,cr_return_amount,cr_net_loss] + CometFilter [cr_item_sk,cr_order_number] + CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_return_amount,cr_net_loss,cr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #12 + WholeStageCodegen (16) + ColumnarToRow + InputAdapter + CometFilter [cp_catalog_page_sk] + CometScan parquet spark_catalog.default.catalog_page [cp_catalog_page_sk,cp_catalog_page_id] + InputAdapter + ReusedExchange [i_item_sk] #7 + InputAdapter + ReusedExchange [p_promo_sk] #8 + WholeStageCodegen (30) + HashAggregate [web_site_id,sum,sum,isEmpty,sum,isEmpty] [sum(UnscaledValue(ws_ext_sales_price)),sum(coalesce(cast(wr_return_amt as decimal(12,2)), 0.00)),sum((ws_net_profit - coalesce(cast(wr_net_loss as decimal(12,2)), 0.00))),sales,returns,profit,channel,id,sum,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [web_site_id] #13 + WholeStageCodegen (29) + HashAggregate [web_site_id,ws_ext_sales_price,wr_return_amt,ws_net_profit,wr_net_loss] [sum,sum,isEmpty,sum,isEmpty,sum,sum,isEmpty,sum,isEmpty] + Project [ws_ext_sales_price,ws_net_profit,wr_return_amt,wr_net_loss,web_site_id] + BroadcastHashJoin [ws_promo_sk,p_promo_sk] + Project [ws_promo_sk,ws_ext_sales_price,ws_net_profit,wr_return_amt,wr_net_loss,web_site_id] + BroadcastHashJoin [ws_item_sk,i_item_sk] + Project [ws_item_sk,ws_promo_sk,ws_ext_sales_price,ws_net_profit,wr_return_amt,wr_net_loss,web_site_id] + BroadcastHashJoin [ws_web_site_sk,web_site_sk] + Project [ws_item_sk,ws_web_site_sk,ws_promo_sk,ws_ext_sales_price,ws_net_profit,wr_return_amt,wr_net_loss] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_item_sk,ws_web_site_sk,ws_promo_sk,ws_ext_sales_price,ws_net_profit,ws_sold_date_sk,wr_return_amt,wr_net_loss] + SortMergeJoin [ws_item_sk,ws_order_number,wr_item_sk,wr_order_number] + InputAdapter + WholeStageCodegen (22) + Sort [ws_item_sk,ws_order_number] + InputAdapter + Exchange [ws_item_sk,ws_order_number] #14 + WholeStageCodegen (21) + ColumnarToRow + InputAdapter + CometFilter [ws_web_site_sk,ws_item_sk,ws_promo_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_web_site_sk,ws_promo_sk,ws_order_number,ws_ext_sales_price,ws_net_profit,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + WholeStageCodegen (24) + Sort [wr_item_sk,wr_order_number] + InputAdapter + Exchange [wr_item_sk,wr_order_number] #15 + WholeStageCodegen (23) + ColumnarToRow + InputAdapter + CometProject [wr_item_sk,wr_order_number,wr_return_amt,wr_net_loss] + CometFilter [wr_item_sk,wr_order_number] + CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_order_number,wr_return_amt,wr_net_loss,wr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #16 + WholeStageCodegen (26) + ColumnarToRow + InputAdapter + CometFilter [web_site_sk] + CometScan parquet spark_catalog.default.web_site [web_site_sk,web_site_id] + InputAdapter + ReusedExchange [i_item_sk] #7 + InputAdapter + ReusedExchange [p_promo_sk] #8 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q81/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q81/explain.txt new file mode 100644 index 0000000000..431d1453dd --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q81/explain.txt @@ -0,0 +1,319 @@ +== Physical Plan == +TakeOrderedAndProject (48) ++- * Project (47) + +- * BroadcastHashJoin Inner BuildRight (46) + :- * Project (41) + : +- * BroadcastHashJoin Inner BuildRight (40) + : :- * Project (35) + : : +- * BroadcastHashJoin Inner BuildRight (34) + : : :- * Filter (16) + : : : +- * HashAggregate (15) + : : : +- Exchange (14) + : : : +- * HashAggregate (13) + : : : +- * Project (12) + : : : +- * BroadcastHashJoin Inner BuildRight (11) + : : : :- * Project (6) + : : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) + : : : : : +- CometScan parquet spark_catalog.default.catalog_returns (1) + : : : : +- ReusedExchange (4) + : : : +- BroadcastExchange (10) + : : : +- * ColumnarToRow (9) + : : : +- CometFilter (8) + : : : +- CometScan parquet spark_catalog.default.customer_address (7) + : : +- BroadcastExchange (33) + : : +- * Filter (32) + : : +- * HashAggregate (31) + : : +- Exchange (30) + : : +- * HashAggregate (29) + : : +- * HashAggregate (28) + : : +- Exchange (27) + : : +- * HashAggregate (26) + : : +- * Project (25) + : : +- * BroadcastHashJoin Inner BuildRight (24) + : : :- * Project (22) + : : : +- * BroadcastHashJoin Inner BuildRight (21) + : : : :- * ColumnarToRow (19) + : : : : +- CometFilter (18) + : : : : +- CometScan parquet spark_catalog.default.catalog_returns (17) + : : : +- ReusedExchange (20) + : : +- ReusedExchange (23) + : +- BroadcastExchange (39) + : +- * ColumnarToRow (38) + : +- CometFilter (37) + : +- CometScan parquet spark_catalog.default.customer (36) + +- BroadcastExchange (45) + +- * ColumnarToRow (44) + +- CometFilter (43) + +- CometScan parquet spark_catalog.default.customer_address (42) + + +(1) Scan parquet spark_catalog.default.catalog_returns +Output [4]: [cr_returning_customer_sk#1, cr_returning_addr_sk#2, cr_return_amt_inc_tax#3, cr_returned_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cr_returned_date_sk#4), dynamicpruningexpression(cr_returned_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(cr_returning_addr_sk), IsNotNull(cr_returning_customer_sk)] +ReadSchema: struct + +(2) CometFilter +Input [4]: [cr_returning_customer_sk#1, cr_returning_addr_sk#2, cr_return_amt_inc_tax#3, cr_returned_date_sk#4] +Condition : (isnotnull(cr_returning_addr_sk#2) AND isnotnull(cr_returning_customer_sk#1)) + +(3) ColumnarToRow [codegen id : 3] +Input [4]: [cr_returning_customer_sk#1, cr_returning_addr_sk#2, cr_return_amt_inc_tax#3, cr_returned_date_sk#4] + +(4) ReusedExchange [Reuses operator id: 53] +Output [1]: [d_date_sk#6] + +(5) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cr_returned_date_sk#4] +Right keys [1]: [d_date_sk#6] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 3] +Output [3]: [cr_returning_customer_sk#1, cr_returning_addr_sk#2, cr_return_amt_inc_tax#3] +Input [5]: [cr_returning_customer_sk#1, cr_returning_addr_sk#2, cr_return_amt_inc_tax#3, cr_returned_date_sk#4, d_date_sk#6] + +(7) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#7, ca_state#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk), IsNotNull(ca_state)] +ReadSchema: struct + +(8) CometFilter +Input [2]: [ca_address_sk#7, ca_state#8] +Condition : (isnotnull(ca_address_sk#7) AND isnotnull(ca_state#8)) + +(9) ColumnarToRow [codegen id : 2] +Input [2]: [ca_address_sk#7, ca_state#8] + +(10) BroadcastExchange +Input [2]: [ca_address_sk#7, ca_state#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cr_returning_addr_sk#2] +Right keys [1]: [ca_address_sk#7] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [3]: [cr_returning_customer_sk#1, cr_return_amt_inc_tax#3, ca_state#8] +Input [5]: [cr_returning_customer_sk#1, cr_returning_addr_sk#2, cr_return_amt_inc_tax#3, ca_address_sk#7, ca_state#8] + +(13) HashAggregate [codegen id : 3] +Input [3]: [cr_returning_customer_sk#1, cr_return_amt_inc_tax#3, ca_state#8] +Keys [2]: [cr_returning_customer_sk#1, ca_state#8] +Functions [1]: [partial_sum(UnscaledValue(cr_return_amt_inc_tax#3))] +Aggregate Attributes [1]: [sum#9] +Results [3]: [cr_returning_customer_sk#1, ca_state#8, sum#10] + +(14) Exchange +Input [3]: [cr_returning_customer_sk#1, ca_state#8, sum#10] +Arguments: hashpartitioning(cr_returning_customer_sk#1, ca_state#8, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 11] +Input [3]: [cr_returning_customer_sk#1, ca_state#8, sum#10] +Keys [2]: [cr_returning_customer_sk#1, ca_state#8] +Functions [1]: [sum(UnscaledValue(cr_return_amt_inc_tax#3))] +Aggregate Attributes [1]: [sum(UnscaledValue(cr_return_amt_inc_tax#3))#11] +Results [3]: [cr_returning_customer_sk#1 AS ctr_customer_sk#12, ca_state#8 AS ctr_state#13, MakeDecimal(sum(UnscaledValue(cr_return_amt_inc_tax#3))#11,17,2) AS ctr_total_return#14] + +(16) Filter [codegen id : 11] +Input [3]: [ctr_customer_sk#12, ctr_state#13, ctr_total_return#14] +Condition : isnotnull(ctr_total_return#14) + +(17) Scan parquet spark_catalog.default.catalog_returns +Output [4]: [cr_returning_customer_sk#15, cr_returning_addr_sk#16, cr_return_amt_inc_tax#17, cr_returned_date_sk#18] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cr_returned_date_sk#18), dynamicpruningexpression(cr_returned_date_sk#18 IN dynamicpruning#19)] +PushedFilters: [IsNotNull(cr_returning_addr_sk)] +ReadSchema: struct + +(18) CometFilter +Input [4]: [cr_returning_customer_sk#15, cr_returning_addr_sk#16, cr_return_amt_inc_tax#17, cr_returned_date_sk#18] +Condition : isnotnull(cr_returning_addr_sk#16) + +(19) ColumnarToRow [codegen id : 6] +Input [4]: [cr_returning_customer_sk#15, cr_returning_addr_sk#16, cr_return_amt_inc_tax#17, cr_returned_date_sk#18] + +(20) ReusedExchange [Reuses operator id: 53] +Output [1]: [d_date_sk#20] + +(21) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [cr_returned_date_sk#18] +Right keys [1]: [d_date_sk#20] +Join type: Inner +Join condition: None + +(22) Project [codegen id : 6] +Output [3]: [cr_returning_customer_sk#15, cr_returning_addr_sk#16, cr_return_amt_inc_tax#17] +Input [5]: [cr_returning_customer_sk#15, cr_returning_addr_sk#16, cr_return_amt_inc_tax#17, cr_returned_date_sk#18, d_date_sk#20] + +(23) ReusedExchange [Reuses operator id: 10] +Output [2]: [ca_address_sk#21, ca_state#22] + +(24) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [cr_returning_addr_sk#16] +Right keys [1]: [ca_address_sk#21] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 6] +Output [3]: [cr_returning_customer_sk#15, cr_return_amt_inc_tax#17, ca_state#22] +Input [5]: [cr_returning_customer_sk#15, cr_returning_addr_sk#16, cr_return_amt_inc_tax#17, ca_address_sk#21, ca_state#22] + +(26) HashAggregate [codegen id : 6] +Input [3]: [cr_returning_customer_sk#15, cr_return_amt_inc_tax#17, ca_state#22] +Keys [2]: [cr_returning_customer_sk#15, ca_state#22] +Functions [1]: [partial_sum(UnscaledValue(cr_return_amt_inc_tax#17))] +Aggregate Attributes [1]: [sum#23] +Results [3]: [cr_returning_customer_sk#15, ca_state#22, sum#24] + +(27) Exchange +Input [3]: [cr_returning_customer_sk#15, ca_state#22, sum#24] +Arguments: hashpartitioning(cr_returning_customer_sk#15, ca_state#22, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(28) HashAggregate [codegen id : 7] +Input [3]: [cr_returning_customer_sk#15, ca_state#22, sum#24] +Keys [2]: [cr_returning_customer_sk#15, ca_state#22] +Functions [1]: [sum(UnscaledValue(cr_return_amt_inc_tax#17))] +Aggregate Attributes [1]: [sum(UnscaledValue(cr_return_amt_inc_tax#17))#11] +Results [2]: [ca_state#22 AS ctr_state#25, MakeDecimal(sum(UnscaledValue(cr_return_amt_inc_tax#17))#11,17,2) AS ctr_total_return#26] + +(29) HashAggregate [codegen id : 7] +Input [2]: [ctr_state#25, ctr_total_return#26] +Keys [1]: [ctr_state#25] +Functions [1]: [partial_avg(ctr_total_return#26)] +Aggregate Attributes [2]: [sum#27, count#28] +Results [3]: [ctr_state#25, sum#29, count#30] + +(30) Exchange +Input [3]: [ctr_state#25, sum#29, count#30] +Arguments: hashpartitioning(ctr_state#25, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(31) HashAggregate [codegen id : 8] +Input [3]: [ctr_state#25, sum#29, count#30] +Keys [1]: [ctr_state#25] +Functions [1]: [avg(ctr_total_return#26)] +Aggregate Attributes [1]: [avg(ctr_total_return#26)#31] +Results [2]: [(avg(ctr_total_return#26)#31 * 1.2) AS (avg(ctr_total_return) * 1.2)#32, ctr_state#25] + +(32) Filter [codegen id : 8] +Input [2]: [(avg(ctr_total_return) * 1.2)#32, ctr_state#25] +Condition : isnotnull((avg(ctr_total_return) * 1.2)#32) + +(33) BroadcastExchange +Input [2]: [(avg(ctr_total_return) * 1.2)#32, ctr_state#25] +Arguments: HashedRelationBroadcastMode(List(input[1, string, true]),false), [plan_id=5] + +(34) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [ctr_state#13] +Right keys [1]: [ctr_state#25] +Join type: Inner +Join condition: (cast(ctr_total_return#14 as decimal(24,7)) > (avg(ctr_total_return) * 1.2)#32) + +(35) Project [codegen id : 11] +Output [2]: [ctr_customer_sk#12, ctr_total_return#14] +Input [5]: [ctr_customer_sk#12, ctr_state#13, ctr_total_return#14, (avg(ctr_total_return) * 1.2)#32, ctr_state#25] + +(36) Scan parquet spark_catalog.default.customer +Output [6]: [c_customer_sk#33, c_customer_id#34, c_current_addr_sk#35, c_salutation#36, c_first_name#37, c_last_name#38] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_current_addr_sk)] +ReadSchema: struct + +(37) CometFilter +Input [6]: [c_customer_sk#33, c_customer_id#34, c_current_addr_sk#35, c_salutation#36, c_first_name#37, c_last_name#38] +Condition : (isnotnull(c_customer_sk#33) AND isnotnull(c_current_addr_sk#35)) + +(38) ColumnarToRow [codegen id : 9] +Input [6]: [c_customer_sk#33, c_customer_id#34, c_current_addr_sk#35, c_salutation#36, c_first_name#37, c_last_name#38] + +(39) BroadcastExchange +Input [6]: [c_customer_sk#33, c_customer_id#34, c_current_addr_sk#35, c_salutation#36, c_first_name#37, c_last_name#38] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6] + +(40) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [ctr_customer_sk#12] +Right keys [1]: [c_customer_sk#33] +Join type: Inner +Join condition: None + +(41) Project [codegen id : 11] +Output [6]: [ctr_total_return#14, c_customer_id#34, c_current_addr_sk#35, c_salutation#36, c_first_name#37, c_last_name#38] +Input [8]: [ctr_customer_sk#12, ctr_total_return#14, c_customer_sk#33, c_customer_id#34, c_current_addr_sk#35, c_salutation#36, c_first_name#37, c_last_name#38] + +(42) Scan parquet spark_catalog.default.customer_address +Output [12]: [ca_address_sk#39, ca_street_number#40, ca_street_name#41, ca_street_type#42, ca_suite_number#43, ca_city#44, ca_county#45, ca_state#46, ca_zip#47, ca_country#48, ca_gmt_offset#49, ca_location_type#50] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_state), EqualTo(ca_state,GA), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(43) CometFilter +Input [12]: [ca_address_sk#39, ca_street_number#40, ca_street_name#41, ca_street_type#42, ca_suite_number#43, ca_city#44, ca_county#45, ca_state#46, ca_zip#47, ca_country#48, ca_gmt_offset#49, ca_location_type#50] +Condition : ((isnotnull(ca_state#46) AND (ca_state#46 = GA)) AND isnotnull(ca_address_sk#39)) + +(44) ColumnarToRow [codegen id : 10] +Input [12]: [ca_address_sk#39, ca_street_number#40, ca_street_name#41, ca_street_type#42, ca_suite_number#43, ca_city#44, ca_county#45, ca_state#46, ca_zip#47, ca_country#48, ca_gmt_offset#49, ca_location_type#50] + +(45) BroadcastExchange +Input [12]: [ca_address_sk#39, ca_street_number#40, ca_street_name#41, ca_street_type#42, ca_suite_number#43, ca_city#44, ca_county#45, ca_state#46, ca_zip#47, ca_country#48, ca_gmt_offset#49, ca_location_type#50] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=7] + +(46) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [c_current_addr_sk#35] +Right keys [1]: [ca_address_sk#39] +Join type: Inner +Join condition: None + +(47) Project [codegen id : 11] +Output [16]: [c_customer_id#34, c_salutation#36, c_first_name#37, c_last_name#38, ca_street_number#40, ca_street_name#41, ca_street_type#42, ca_suite_number#43, ca_city#44, ca_county#45, ca_state#46, ca_zip#47, ca_country#48, ca_gmt_offset#49, ca_location_type#50, ctr_total_return#14] +Input [18]: [ctr_total_return#14, c_customer_id#34, c_current_addr_sk#35, c_salutation#36, c_first_name#37, c_last_name#38, ca_address_sk#39, ca_street_number#40, ca_street_name#41, ca_street_type#42, ca_suite_number#43, ca_city#44, ca_county#45, ca_state#46, ca_zip#47, ca_country#48, ca_gmt_offset#49, ca_location_type#50] + +(48) TakeOrderedAndProject +Input [16]: [c_customer_id#34, c_salutation#36, c_first_name#37, c_last_name#38, ca_street_number#40, ca_street_name#41, ca_street_type#42, ca_suite_number#43, ca_city#44, ca_county#45, ca_state#46, ca_zip#47, ca_country#48, ca_gmt_offset#49, ca_location_type#50, ctr_total_return#14] +Arguments: 100, [c_customer_id#34 ASC NULLS FIRST, c_salutation#36 ASC NULLS FIRST, c_first_name#37 ASC NULLS FIRST, c_last_name#38 ASC NULLS FIRST, ca_street_number#40 ASC NULLS FIRST, ca_street_name#41 ASC NULLS FIRST, ca_street_type#42 ASC NULLS FIRST, ca_suite_number#43 ASC NULLS FIRST, ca_city#44 ASC NULLS FIRST, ca_county#45 ASC NULLS FIRST, ca_state#46 ASC NULLS FIRST, ca_zip#47 ASC NULLS FIRST, ca_country#48 ASC NULLS FIRST, ca_gmt_offset#49 ASC NULLS FIRST, ca_location_type#50 ASC NULLS FIRST, ctr_total_return#14 ASC NULLS FIRST], [c_customer_id#34, c_salutation#36, c_first_name#37, c_last_name#38, ca_street_number#40, ca_street_name#41, ca_street_type#42, ca_suite_number#43, ca_city#44, ca_county#45, ca_state#46, ca_zip#47, ca_country#48, ca_gmt_offset#49, ca_location_type#50, ctr_total_return#14] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = cr_returned_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (53) ++- * ColumnarToRow (52) + +- CometProject (51) + +- CometFilter (50) + +- CometScan parquet spark_catalog.default.date_dim (49) + + +(49) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#6, d_year#51] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2000), IsNotNull(d_date_sk)] +ReadSchema: struct + +(50) CometFilter +Input [2]: [d_date_sk#6, d_year#51] +Condition : ((isnotnull(d_year#51) AND (d_year#51 = 2000)) AND isnotnull(d_date_sk#6)) + +(51) CometProject +Input [2]: [d_date_sk#6, d_year#51] +Arguments: [d_date_sk#6], [d_date_sk#6] + +(52) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#6] + +(53) BroadcastExchange +Input [1]: [d_date_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + +Subquery:2 Hosting operator id = 17 Hosting Expression = cr_returned_date_sk#18 IN dynamicpruning#5 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q81/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q81/simplified.txt new file mode 100644 index 0000000000..6f042847ca --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q81/simplified.txt @@ -0,0 +1,80 @@ +TakeOrderedAndProject [c_customer_id,c_salutation,c_first_name,c_last_name,ca_street_number,ca_street_name,ca_street_type,ca_suite_number,ca_city,ca_county,ca_state,ca_zip,ca_country,ca_gmt_offset,ca_location_type,ctr_total_return] + WholeStageCodegen (11) + Project [c_customer_id,c_salutation,c_first_name,c_last_name,ca_street_number,ca_street_name,ca_street_type,ca_suite_number,ca_city,ca_county,ca_state,ca_zip,ca_country,ca_gmt_offset,ca_location_type,ctr_total_return] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [ctr_total_return,c_customer_id,c_current_addr_sk,c_salutation,c_first_name,c_last_name] + BroadcastHashJoin [ctr_customer_sk,c_customer_sk] + Project [ctr_customer_sk,ctr_total_return] + BroadcastHashJoin [ctr_state,ctr_state,ctr_total_return,(avg(ctr_total_return) * 1.2)] + Filter [ctr_total_return] + HashAggregate [cr_returning_customer_sk,ca_state,sum] [sum(UnscaledValue(cr_return_amt_inc_tax)),ctr_customer_sk,ctr_state,ctr_total_return,sum] + InputAdapter + Exchange [cr_returning_customer_sk,ca_state] #1 + WholeStageCodegen (3) + HashAggregate [cr_returning_customer_sk,ca_state,cr_return_amt_inc_tax] [sum,sum] + Project [cr_returning_customer_sk,cr_return_amt_inc_tax,ca_state] + BroadcastHashJoin [cr_returning_addr_sk,ca_address_sk] + Project [cr_returning_customer_sk,cr_returning_addr_sk,cr_return_amt_inc_tax] + BroadcastHashJoin [cr_returned_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [cr_returning_addr_sk,cr_returning_customer_sk] + CometScan parquet spark_catalog.default.catalog_returns [cr_returning_customer_sk,cr_returning_addr_sk,cr_return_amt_inc_tax,cr_returned_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk,ca_state] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (8) + Filter [(avg(ctr_total_return) * 1.2)] + HashAggregate [ctr_state,sum,count] [avg(ctr_total_return),(avg(ctr_total_return) * 1.2),sum,count] + InputAdapter + Exchange [ctr_state] #5 + WholeStageCodegen (7) + HashAggregate [ctr_state,ctr_total_return] [sum,count,sum,count] + HashAggregate [cr_returning_customer_sk,ca_state,sum] [sum(UnscaledValue(cr_return_amt_inc_tax)),ctr_state,ctr_total_return,sum] + InputAdapter + Exchange [cr_returning_customer_sk,ca_state] #6 + WholeStageCodegen (6) + HashAggregate [cr_returning_customer_sk,ca_state,cr_return_amt_inc_tax] [sum,sum] + Project [cr_returning_customer_sk,cr_return_amt_inc_tax,ca_state] + BroadcastHashJoin [cr_returning_addr_sk,ca_address_sk] + Project [cr_returning_customer_sk,cr_returning_addr_sk,cr_return_amt_inc_tax] + BroadcastHashJoin [cr_returned_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [cr_returning_addr_sk] + CometScan parquet spark_catalog.default.catalog_returns [cr_returning_customer_sk,cr_returning_addr_sk,cr_return_amt_inc_tax,cr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + ReusedExchange [ca_address_sk,ca_state] #3 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (9) + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_current_addr_sk] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_current_addr_sk,c_salutation,c_first_name,c_last_name] + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (10) + ColumnarToRow + InputAdapter + CometFilter [ca_state,ca_address_sk] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_street_number,ca_street_name,ca_street_type,ca_suite_number,ca_city,ca_county,ca_state,ca_zip,ca_country,ca_gmt_offset,ca_location_type] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q82/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q82/explain.txt new file mode 100644 index 0000000000..7609fa5208 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q82/explain.txt @@ -0,0 +1,179 @@ +== Physical Plan == +TakeOrderedAndProject (25) ++- * HashAggregate (24) + +- Exchange (23) + +- * HashAggregate (22) + +- * Project (21) + +- * BroadcastHashJoin Inner BuildLeft (20) + :- BroadcastExchange (15) + : +- * Project (14) + : +- * BroadcastHashJoin Inner BuildRight (13) + : :- * Project (11) + : : +- * BroadcastHashJoin Inner BuildRight (10) + : : :- * ColumnarToRow (4) + : : : +- CometProject (3) + : : : +- CometFilter (2) + : : : +- CometScan parquet spark_catalog.default.item (1) + : : +- BroadcastExchange (9) + : : +- * ColumnarToRow (8) + : : +- CometProject (7) + : : +- CometFilter (6) + : : +- CometScan parquet spark_catalog.default.inventory (5) + : +- ReusedExchange (12) + +- * ColumnarToRow (19) + +- CometProject (18) + +- CometFilter (17) + +- CometScan parquet spark_catalog.default.store_sales (16) + + +(1) Scan parquet spark_catalog.default.item +Output [5]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, i_manufact_id#5] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_current_price), GreaterThanOrEqual(i_current_price,62.00), LessThanOrEqual(i_current_price,92.00), In(i_manufact_id, [129,270,423,821]), IsNotNull(i_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [5]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, i_manufact_id#5] +Condition : ((((isnotnull(i_current_price#4) AND (i_current_price#4 >= 62.00)) AND (i_current_price#4 <= 92.00)) AND i_manufact_id#5 IN (129,270,821,423)) AND isnotnull(i_item_sk#1)) + +(3) CometProject +Input [5]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, i_manufact_id#5] +Arguments: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4], [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4] + +(4) ColumnarToRow [codegen id : 3] +Input [4]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4] + +(5) Scan parquet spark_catalog.default.inventory +Output [3]: [inv_item_sk#6, inv_quantity_on_hand#7, inv_date_sk#8] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(inv_date_sk#8), dynamicpruningexpression(inv_date_sk#8 IN dynamicpruning#9)] +PushedFilters: [IsNotNull(inv_quantity_on_hand), GreaterThanOrEqual(inv_quantity_on_hand,100), LessThanOrEqual(inv_quantity_on_hand,500), IsNotNull(inv_item_sk)] +ReadSchema: struct + +(6) CometFilter +Input [3]: [inv_item_sk#6, inv_quantity_on_hand#7, inv_date_sk#8] +Condition : (((isnotnull(inv_quantity_on_hand#7) AND (inv_quantity_on_hand#7 >= 100)) AND (inv_quantity_on_hand#7 <= 500)) AND isnotnull(inv_item_sk#6)) + +(7) CometProject +Input [3]: [inv_item_sk#6, inv_quantity_on_hand#7, inv_date_sk#8] +Arguments: [inv_item_sk#6, inv_date_sk#8], [inv_item_sk#6, inv_date_sk#8] + +(8) ColumnarToRow [codegen id : 1] +Input [2]: [inv_item_sk#6, inv_date_sk#8] + +(9) BroadcastExchange +Input [2]: [inv_item_sk#6, inv_date_sk#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(10) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [i_item_sk#1] +Right keys [1]: [inv_item_sk#6] +Join type: Inner +Join condition: None + +(11) Project [codegen id : 3] +Output [5]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, inv_date_sk#8] +Input [6]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, inv_item_sk#6, inv_date_sk#8] + +(12) ReusedExchange [Reuses operator id: 30] +Output [1]: [d_date_sk#10] + +(13) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [inv_date_sk#8] +Right keys [1]: [d_date_sk#10] +Join type: Inner +Join condition: None + +(14) Project [codegen id : 3] +Output [4]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4] +Input [6]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, inv_date_sk#8, d_date_sk#10] + +(15) BroadcastExchange +Input [4]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(16) Scan parquet spark_catalog.default.store_sales +Output [2]: [ss_item_sk#11, ss_sold_date_sk#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(17) CometFilter +Input [2]: [ss_item_sk#11, ss_sold_date_sk#12] +Condition : isnotnull(ss_item_sk#11) + +(18) CometProject +Input [2]: [ss_item_sk#11, ss_sold_date_sk#12] +Arguments: [ss_item_sk#11], [ss_item_sk#11] + +(19) ColumnarToRow +Input [1]: [ss_item_sk#11] + +(20) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [i_item_sk#1] +Right keys [1]: [ss_item_sk#11] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 4] +Output [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] +Input [5]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, ss_item_sk#11] + +(22) HashAggregate [codegen id : 4] +Input [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] +Keys [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] +Functions: [] +Aggregate Attributes: [] +Results [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] + +(23) Exchange +Input [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] +Arguments: hashpartitioning(i_item_id#2, i_item_desc#3, i_current_price#4, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(24) HashAggregate [codegen id : 5] +Input [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] +Keys [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] +Functions: [] +Aggregate Attributes: [] +Results [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] + +(25) TakeOrderedAndProject +Input [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] +Arguments: 100, [i_item_id#2 ASC NULLS FIRST], [i_item_id#2, i_item_desc#3, i_current_price#4] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 5 Hosting Expression = inv_date_sk#8 IN dynamicpruning#9 +BroadcastExchange (30) ++- * ColumnarToRow (29) + +- CometProject (28) + +- CometFilter (27) + +- CometScan parquet spark_catalog.default.date_dim (26) + + +(26) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#10, d_date#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,2000-05-25), LessThanOrEqual(d_date,2000-07-24), IsNotNull(d_date_sk)] +ReadSchema: struct + +(27) CometFilter +Input [2]: [d_date_sk#10, d_date#13] +Condition : (((isnotnull(d_date#13) AND (d_date#13 >= 2000-05-25)) AND (d_date#13 <= 2000-07-24)) AND isnotnull(d_date_sk#10)) + +(28) CometProject +Input [2]: [d_date_sk#10, d_date#13] +Arguments: [d_date_sk#10], [d_date_sk#10] + +(29) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#10] + +(30) BroadcastExchange +Input [1]: [d_date_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q82/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q82/simplified.txt new file mode 100644 index 0000000000..0252eb575f --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q82/simplified.txt @@ -0,0 +1,44 @@ +TakeOrderedAndProject [i_item_id,i_item_desc,i_current_price] + WholeStageCodegen (5) + HashAggregate [i_item_id,i_item_desc,i_current_price] + InputAdapter + Exchange [i_item_id,i_item_desc,i_current_price] #1 + WholeStageCodegen (4) + HashAggregate [i_item_id,i_item_desc,i_current_price] + Project [i_item_id,i_item_desc,i_current_price] + BroadcastHashJoin [i_item_sk,ss_item_sk] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (3) + Project [i_item_sk,i_item_id,i_item_desc,i_current_price] + BroadcastHashJoin [inv_date_sk,d_date_sk] + Project [i_item_sk,i_item_id,i_item_desc,i_current_price,inv_date_sk] + BroadcastHashJoin [i_item_sk,inv_item_sk] + ColumnarToRow + InputAdapter + CometProject [i_item_sk,i_item_id,i_item_desc,i_current_price] + CometFilter [i_current_price,i_manufact_id,i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_item_desc,i_current_price,i_manufact_id] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [inv_item_sk,inv_date_sk] + CometFilter [inv_quantity_on_hand,inv_item_sk] + CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_quantity_on_hand,inv_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + ReusedExchange [d_date_sk] #4 + ColumnarToRow + InputAdapter + CometProject [ss_item_sk] + CometFilter [ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_sold_date_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q83.ansi/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q83.ansi/explain.txt new file mode 100644 index 0000000000..5183e02755 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q83.ansi/explain.txt @@ -0,0 +1,372 @@ +== Physical Plan == +TakeOrderedAndProject (46) ++- * Project (45) + +- * BroadcastHashJoin Inner BuildRight (44) + :- * Project (30) + : +- * BroadcastHashJoin Inner BuildRight (29) + : :- * HashAggregate (15) + : : +- Exchange (14) + : : +- * HashAggregate (13) + : : +- * Project (12) + : : +- * BroadcastHashJoin Inner BuildRight (11) + : : :- * Project (9) + : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.store_returns (1) + : : : +- BroadcastExchange (7) + : : : +- * ColumnarToRow (6) + : : : +- CometFilter (5) + : : : +- CometScan parquet spark_catalog.default.item (4) + : : +- ReusedExchange (10) + : +- BroadcastExchange (28) + : +- * HashAggregate (27) + : +- Exchange (26) + : +- * HashAggregate (25) + : +- * Project (24) + : +- * BroadcastHashJoin Inner BuildRight (23) + : :- * Project (21) + : : +- * BroadcastHashJoin Inner BuildRight (20) + : : :- * ColumnarToRow (18) + : : : +- CometFilter (17) + : : : +- CometScan parquet spark_catalog.default.catalog_returns (16) + : : +- ReusedExchange (19) + : +- ReusedExchange (22) + +- BroadcastExchange (43) + +- * HashAggregate (42) + +- Exchange (41) + +- * HashAggregate (40) + +- * Project (39) + +- * BroadcastHashJoin Inner BuildRight (38) + :- * Project (36) + : +- * BroadcastHashJoin Inner BuildRight (35) + : :- * ColumnarToRow (33) + : : +- CometFilter (32) + : : +- CometScan parquet spark_catalog.default.web_returns (31) + : +- ReusedExchange (34) + +- ReusedExchange (37) + + +(1) Scan parquet spark_catalog.default.store_returns +Output [3]: [sr_item_sk#1, sr_return_quantity#2, sr_returned_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(sr_returned_date_sk#3), dynamicpruningexpression(sr_returned_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(sr_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [sr_item_sk#1, sr_return_quantity#2, sr_returned_date_sk#3] +Condition : isnotnull(sr_item_sk#1) + +(3) ColumnarToRow [codegen id : 5] +Input [3]: [sr_item_sk#1, sr_return_quantity#2, sr_returned_date_sk#3] + +(4) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#5, i_item_id#6] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_item_id)] +ReadSchema: struct + +(5) CometFilter +Input [2]: [i_item_sk#5, i_item_id#6] +Condition : (isnotnull(i_item_sk#5) AND isnotnull(i_item_id#6)) + +(6) ColumnarToRow [codegen id : 1] +Input [2]: [i_item_sk#5, i_item_id#6] + +(7) BroadcastExchange +Input [2]: [i_item_sk#5, i_item_id#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [sr_item_sk#1] +Right keys [1]: [i_item_sk#5] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 5] +Output [3]: [sr_return_quantity#2, sr_returned_date_sk#3, i_item_id#6] +Input [5]: [sr_item_sk#1, sr_return_quantity#2, sr_returned_date_sk#3, i_item_sk#5, i_item_id#6] + +(10) ReusedExchange [Reuses operator id: 62] +Output [1]: [d_date_sk#7] + +(11) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [sr_returned_date_sk#3] +Right keys [1]: [d_date_sk#7] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 5] +Output [2]: [sr_return_quantity#2, i_item_id#6] +Input [4]: [sr_return_quantity#2, sr_returned_date_sk#3, i_item_id#6, d_date_sk#7] + +(13) HashAggregate [codegen id : 5] +Input [2]: [sr_return_quantity#2, i_item_id#6] +Keys [1]: [i_item_id#6] +Functions [1]: [partial_sum(sr_return_quantity#2)] +Aggregate Attributes [1]: [sum#8] +Results [2]: [i_item_id#6, sum#9] + +(14) Exchange +Input [2]: [i_item_id#6, sum#9] +Arguments: hashpartitioning(i_item_id#6, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 18] +Input [2]: [i_item_id#6, sum#9] +Keys [1]: [i_item_id#6] +Functions [1]: [sum(sr_return_quantity#2)] +Aggregate Attributes [1]: [sum(sr_return_quantity#2)#10] +Results [2]: [i_item_id#6 AS item_id#11, sum(sr_return_quantity#2)#10 AS sr_item_qty#12] + +(16) Scan parquet spark_catalog.default.catalog_returns +Output [3]: [cr_item_sk#13, cr_return_quantity#14, cr_returned_date_sk#15] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cr_returned_date_sk#15), dynamicpruningexpression(cr_returned_date_sk#15 IN dynamicpruning#16)] +PushedFilters: [IsNotNull(cr_item_sk)] +ReadSchema: struct + +(17) CometFilter +Input [3]: [cr_item_sk#13, cr_return_quantity#14, cr_returned_date_sk#15] +Condition : isnotnull(cr_item_sk#13) + +(18) ColumnarToRow [codegen id : 10] +Input [3]: [cr_item_sk#13, cr_return_quantity#14, cr_returned_date_sk#15] + +(19) ReusedExchange [Reuses operator id: 7] +Output [2]: [i_item_sk#17, i_item_id#18] + +(20) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cr_item_sk#13] +Right keys [1]: [i_item_sk#17] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 10] +Output [3]: [cr_return_quantity#14, cr_returned_date_sk#15, i_item_id#18] +Input [5]: [cr_item_sk#13, cr_return_quantity#14, cr_returned_date_sk#15, i_item_sk#17, i_item_id#18] + +(22) ReusedExchange [Reuses operator id: 62] +Output [1]: [d_date_sk#19] + +(23) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cr_returned_date_sk#15] +Right keys [1]: [d_date_sk#19] +Join type: Inner +Join condition: None + +(24) Project [codegen id : 10] +Output [2]: [cr_return_quantity#14, i_item_id#18] +Input [4]: [cr_return_quantity#14, cr_returned_date_sk#15, i_item_id#18, d_date_sk#19] + +(25) HashAggregate [codegen id : 10] +Input [2]: [cr_return_quantity#14, i_item_id#18] +Keys [1]: [i_item_id#18] +Functions [1]: [partial_sum(cr_return_quantity#14)] +Aggregate Attributes [1]: [sum#20] +Results [2]: [i_item_id#18, sum#21] + +(26) Exchange +Input [2]: [i_item_id#18, sum#21] +Arguments: hashpartitioning(i_item_id#18, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(27) HashAggregate [codegen id : 11] +Input [2]: [i_item_id#18, sum#21] +Keys [1]: [i_item_id#18] +Functions [1]: [sum(cr_return_quantity#14)] +Aggregate Attributes [1]: [sum(cr_return_quantity#14)#22] +Results [2]: [i_item_id#18 AS item_id#23, sum(cr_return_quantity#14)#22 AS cr_item_qty#24] + +(28) BroadcastExchange +Input [2]: [item_id#23, cr_item_qty#24] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=4] + +(29) BroadcastHashJoin [codegen id : 18] +Left keys [1]: [item_id#11] +Right keys [1]: [item_id#23] +Join type: Inner +Join condition: None + +(30) Project [codegen id : 18] +Output [3]: [item_id#11, sr_item_qty#12, cr_item_qty#24] +Input [4]: [item_id#11, sr_item_qty#12, item_id#23, cr_item_qty#24] + +(31) Scan parquet spark_catalog.default.web_returns +Output [3]: [wr_item_sk#25, wr_return_quantity#26, wr_returned_date_sk#27] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(wr_returned_date_sk#27), dynamicpruningexpression(wr_returned_date_sk#27 IN dynamicpruning#28)] +PushedFilters: [IsNotNull(wr_item_sk)] +ReadSchema: struct + +(32) CometFilter +Input [3]: [wr_item_sk#25, wr_return_quantity#26, wr_returned_date_sk#27] +Condition : isnotnull(wr_item_sk#25) + +(33) ColumnarToRow [codegen id : 16] +Input [3]: [wr_item_sk#25, wr_return_quantity#26, wr_returned_date_sk#27] + +(34) ReusedExchange [Reuses operator id: 7] +Output [2]: [i_item_sk#29, i_item_id#30] + +(35) BroadcastHashJoin [codegen id : 16] +Left keys [1]: [wr_item_sk#25] +Right keys [1]: [i_item_sk#29] +Join type: Inner +Join condition: None + +(36) Project [codegen id : 16] +Output [3]: [wr_return_quantity#26, wr_returned_date_sk#27, i_item_id#30] +Input [5]: [wr_item_sk#25, wr_return_quantity#26, wr_returned_date_sk#27, i_item_sk#29, i_item_id#30] + +(37) ReusedExchange [Reuses operator id: 62] +Output [1]: [d_date_sk#31] + +(38) BroadcastHashJoin [codegen id : 16] +Left keys [1]: [wr_returned_date_sk#27] +Right keys [1]: [d_date_sk#31] +Join type: Inner +Join condition: None + +(39) Project [codegen id : 16] +Output [2]: [wr_return_quantity#26, i_item_id#30] +Input [4]: [wr_return_quantity#26, wr_returned_date_sk#27, i_item_id#30, d_date_sk#31] + +(40) HashAggregate [codegen id : 16] +Input [2]: [wr_return_quantity#26, i_item_id#30] +Keys [1]: [i_item_id#30] +Functions [1]: [partial_sum(wr_return_quantity#26)] +Aggregate Attributes [1]: [sum#32] +Results [2]: [i_item_id#30, sum#33] + +(41) Exchange +Input [2]: [i_item_id#30, sum#33] +Arguments: hashpartitioning(i_item_id#30, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(42) HashAggregate [codegen id : 17] +Input [2]: [i_item_id#30, sum#33] +Keys [1]: [i_item_id#30] +Functions [1]: [sum(wr_return_quantity#26)] +Aggregate Attributes [1]: [sum(wr_return_quantity#26)#34] +Results [2]: [i_item_id#30 AS item_id#35, sum(wr_return_quantity#26)#34 AS wr_item_qty#36] + +(43) BroadcastExchange +Input [2]: [item_id#35, wr_item_qty#36] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=6] + +(44) BroadcastHashJoin [codegen id : 18] +Left keys [1]: [item_id#11] +Right keys [1]: [item_id#35] +Join type: Inner +Join condition: None + +(45) Project [codegen id : 18] +Output [8]: [item_id#11, sr_item_qty#12, (((cast(sr_item_qty#12 as double) / cast(((sr_item_qty#12 + cr_item_qty#24) + wr_item_qty#36) as double)) / 3.0) * 100.0) AS sr_dev#37, cr_item_qty#24, (((cast(cr_item_qty#24 as double) / cast(((sr_item_qty#12 + cr_item_qty#24) + wr_item_qty#36) as double)) / 3.0) * 100.0) AS cr_dev#38, wr_item_qty#36, (((cast(wr_item_qty#36 as double) / cast(((sr_item_qty#12 + cr_item_qty#24) + wr_item_qty#36) as double)) / 3.0) * 100.0) AS wr_dev#39, (cast(((sr_item_qty#12 + cr_item_qty#24) + wr_item_qty#36) as decimal(20,0)) / 3.0) AS average#40] +Input [5]: [item_id#11, sr_item_qty#12, cr_item_qty#24, item_id#35, wr_item_qty#36] + +(46) TakeOrderedAndProject +Input [8]: [item_id#11, sr_item_qty#12, sr_dev#37, cr_item_qty#24, cr_dev#38, wr_item_qty#36, wr_dev#39, average#40] +Arguments: 100, [item_id#11 ASC NULLS FIRST, sr_item_qty#12 ASC NULLS FIRST], [item_id#11, sr_item_qty#12, sr_dev#37, cr_item_qty#24, cr_dev#38, wr_item_qty#36, wr_dev#39, average#40] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = sr_returned_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (62) ++- * Project (61) + +- * BroadcastHashJoin LeftSemi BuildRight (60) + :- * ColumnarToRow (49) + : +- CometFilter (48) + : +- CometScan parquet spark_catalog.default.date_dim (47) + +- BroadcastExchange (59) + +- * Project (58) + +- * BroadcastHashJoin LeftSemi BuildRight (57) + :- * ColumnarToRow (51) + : +- CometScan parquet spark_catalog.default.date_dim (50) + +- BroadcastExchange (56) + +- * ColumnarToRow (55) + +- CometProject (54) + +- CometFilter (53) + +- CometScan parquet spark_catalog.default.date_dim (52) + + +(47) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#7, d_date#41] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date_sk)] +ReadSchema: struct + +(48) CometFilter +Input [2]: [d_date_sk#7, d_date#41] +Condition : isnotnull(d_date_sk#7) + +(49) ColumnarToRow [codegen id : 3] +Input [2]: [d_date_sk#7, d_date#41] + +(50) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date#42, d_week_seq#43] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +ReadSchema: struct + +(51) ColumnarToRow [codegen id : 2] +Input [2]: [d_date#42, d_week_seq#43] + +(52) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date#44, d_week_seq#45] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [In(d_date, [2000-06-30,2000-09-27,2000-11-17])] +ReadSchema: struct + +(53) CometFilter +Input [2]: [d_date#44, d_week_seq#45] +Condition : d_date#44 IN (2000-06-30,2000-09-27,2000-11-17) + +(54) CometProject +Input [2]: [d_date#44, d_week_seq#45] +Arguments: [d_week_seq#45], [d_week_seq#45] + +(55) ColumnarToRow [codegen id : 1] +Input [1]: [d_week_seq#45] + +(56) BroadcastExchange +Input [1]: [d_week_seq#45] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +(57) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [d_week_seq#43] +Right keys [1]: [d_week_seq#45] +Join type: LeftSemi +Join condition: None + +(58) Project [codegen id : 2] +Output [1]: [d_date#42] +Input [2]: [d_date#42, d_week_seq#43] + +(59) BroadcastExchange +Input [1]: [d_date#42] +Arguments: HashedRelationBroadcastMode(List(input[0, date, true]),false), [plan_id=8] + +(60) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [d_date#41] +Right keys [1]: [d_date#42] +Join type: LeftSemi +Join condition: None + +(61) Project [codegen id : 3] +Output [1]: [d_date_sk#7] +Input [2]: [d_date_sk#7, d_date#41] + +(62) BroadcastExchange +Input [1]: [d_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=9] + +Subquery:2 Hosting operator id = 16 Hosting Expression = cr_returned_date_sk#15 IN dynamicpruning#4 + +Subquery:3 Hosting operator id = 31 Hosting Expression = wr_returned_date_sk#27 IN dynamicpruning#4 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q83.ansi/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q83.ansi/simplified.txt new file mode 100644 index 0000000000..a8f1ba3f10 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q83.ansi/simplified.txt @@ -0,0 +1,95 @@ +TakeOrderedAndProject [item_id,sr_item_qty,sr_dev,cr_item_qty,cr_dev,wr_item_qty,wr_dev,average] + WholeStageCodegen (18) + Project [item_id,sr_item_qty,cr_item_qty,wr_item_qty] + BroadcastHashJoin [item_id,item_id] + Project [item_id,sr_item_qty,cr_item_qty] + BroadcastHashJoin [item_id,item_id] + HashAggregate [i_item_id,sum] [sum(sr_return_quantity),item_id,sr_item_qty,sum] + InputAdapter + Exchange [i_item_id] #1 + WholeStageCodegen (5) + HashAggregate [i_item_id,sr_return_quantity] [sum,sum] + Project [sr_return_quantity,i_item_id] + BroadcastHashJoin [sr_returned_date_sk,d_date_sk] + Project [sr_return_quantity,sr_returned_date_sk,i_item_id] + BroadcastHashJoin [sr_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [sr_item_sk] + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_return_quantity,sr_returned_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (3) + Project [d_date_sk] + BroadcastHashJoin [d_date,d_date] + ColumnarToRow + InputAdapter + CometFilter [d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + Project [d_date] + BroadcastHashJoin [d_week_seq,d_week_seq] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date,d_week_seq] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_week_seq] + CometFilter [d_date] + CometScan parquet spark_catalog.default.date_dim [d_date,d_week_seq] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk,i_item_id] + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (11) + HashAggregate [i_item_id,sum] [sum(cr_return_quantity),item_id,cr_item_qty,sum] + InputAdapter + Exchange [i_item_id] #7 + WholeStageCodegen (10) + HashAggregate [i_item_id,cr_return_quantity] [sum,sum] + Project [cr_return_quantity,i_item_id] + BroadcastHashJoin [cr_returned_date_sk,d_date_sk] + Project [cr_return_quantity,cr_returned_date_sk,i_item_id] + BroadcastHashJoin [cr_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [cr_item_sk] + CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_return_quantity,cr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [i_item_sk,i_item_id] #5 + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (17) + HashAggregate [i_item_id,sum] [sum(wr_return_quantity),item_id,wr_item_qty,sum] + InputAdapter + Exchange [i_item_id] #9 + WholeStageCodegen (16) + HashAggregate [i_item_id,wr_return_quantity] [sum,sum] + Project [wr_return_quantity,i_item_id] + BroadcastHashJoin [wr_returned_date_sk,d_date_sk] + Project [wr_return_quantity,wr_returned_date_sk,i_item_id] + BroadcastHashJoin [wr_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [wr_item_sk] + CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_return_quantity,wr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [i_item_sk,i_item_id] #5 + InputAdapter + ReusedExchange [d_date_sk] #2 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q84/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q84/explain.txt new file mode 100644 index 0000000000..8dc935d1da --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q84/explain.txt @@ -0,0 +1,210 @@ +== Physical Plan == +TakeOrderedAndProject (37) ++- * Project (36) + +- * BroadcastHashJoin Inner BuildLeft (35) + :- BroadcastExchange (30) + : +- * Project (29) + : +- * BroadcastHashJoin Inner BuildRight (28) + : :- * Project (22) + : : +- * BroadcastHashJoin Inner BuildRight (21) + : : :- * Project (16) + : : : +- * BroadcastHashJoin Inner BuildRight (15) + : : : :- * Project (10) + : : : : +- * BroadcastHashJoin Inner BuildRight (9) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) + : : : : : +- CometScan parquet spark_catalog.default.customer (1) + : : : : +- BroadcastExchange (8) + : : : : +- * ColumnarToRow (7) + : : : : +- CometProject (6) + : : : : +- CometFilter (5) + : : : : +- CometScan parquet spark_catalog.default.customer_address (4) + : : : +- BroadcastExchange (14) + : : : +- * ColumnarToRow (13) + : : : +- CometFilter (12) + : : : +- CometScan parquet spark_catalog.default.customer_demographics (11) + : : +- BroadcastExchange (20) + : : +- * ColumnarToRow (19) + : : +- CometFilter (18) + : : +- CometScan parquet spark_catalog.default.household_demographics (17) + : +- BroadcastExchange (27) + : +- * ColumnarToRow (26) + : +- CometProject (25) + : +- CometFilter (24) + : +- CometScan parquet spark_catalog.default.income_band (23) + +- * ColumnarToRow (34) + +- CometProject (33) + +- CometFilter (32) + +- CometScan parquet spark_catalog.default.store_returns (31) + + +(1) Scan parquet spark_catalog.default.customer +Output [6]: [c_customer_id#1, c_current_cdemo_sk#2, c_current_hdemo_sk#3, c_current_addr_sk#4, c_first_name#5, c_last_name#6] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_current_addr_sk), IsNotNull(c_current_cdemo_sk), IsNotNull(c_current_hdemo_sk)] +ReadSchema: struct + +(2) CometFilter +Input [6]: [c_customer_id#1, c_current_cdemo_sk#2, c_current_hdemo_sk#3, c_current_addr_sk#4, c_first_name#5, c_last_name#6] +Condition : ((isnotnull(c_current_addr_sk#4) AND isnotnull(c_current_cdemo_sk#2)) AND isnotnull(c_current_hdemo_sk#3)) + +(3) ColumnarToRow [codegen id : 5] +Input [6]: [c_customer_id#1, c_current_cdemo_sk#2, c_current_hdemo_sk#3, c_current_addr_sk#4, c_first_name#5, c_last_name#6] + +(4) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#7, ca_city#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_city), EqualTo(ca_city,Edgewood), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(5) CometFilter +Input [2]: [ca_address_sk#7, ca_city#8] +Condition : ((isnotnull(ca_city#8) AND (ca_city#8 = Edgewood)) AND isnotnull(ca_address_sk#7)) + +(6) CometProject +Input [2]: [ca_address_sk#7, ca_city#8] +Arguments: [ca_address_sk#7], [ca_address_sk#7] + +(7) ColumnarToRow [codegen id : 1] +Input [1]: [ca_address_sk#7] + +(8) BroadcastExchange +Input [1]: [ca_address_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [c_current_addr_sk#4] +Right keys [1]: [ca_address_sk#7] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 5] +Output [5]: [c_customer_id#1, c_current_cdemo_sk#2, c_current_hdemo_sk#3, c_first_name#5, c_last_name#6] +Input [7]: [c_customer_id#1, c_current_cdemo_sk#2, c_current_hdemo_sk#3, c_current_addr_sk#4, c_first_name#5, c_last_name#6, ca_address_sk#7] + +(11) Scan parquet spark_catalog.default.customer_demographics +Output [1]: [cd_demo_sk#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(12) CometFilter +Input [1]: [cd_demo_sk#9] +Condition : isnotnull(cd_demo_sk#9) + +(13) ColumnarToRow [codegen id : 2] +Input [1]: [cd_demo_sk#9] + +(14) BroadcastExchange +Input [1]: [cd_demo_sk#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(15) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [c_current_cdemo_sk#2] +Right keys [1]: [cd_demo_sk#9] +Join type: Inner +Join condition: None + +(16) Project [codegen id : 5] +Output [5]: [c_customer_id#1, c_current_hdemo_sk#3, c_first_name#5, c_last_name#6, cd_demo_sk#9] +Input [6]: [c_customer_id#1, c_current_cdemo_sk#2, c_current_hdemo_sk#3, c_first_name#5, c_last_name#6, cd_demo_sk#9] + +(17) Scan parquet spark_catalog.default.household_demographics +Output [2]: [hd_demo_sk#10, hd_income_band_sk#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/household_demographics] +PushedFilters: [IsNotNull(hd_demo_sk), IsNotNull(hd_income_band_sk)] +ReadSchema: struct + +(18) CometFilter +Input [2]: [hd_demo_sk#10, hd_income_band_sk#11] +Condition : (isnotnull(hd_demo_sk#10) AND isnotnull(hd_income_band_sk#11)) + +(19) ColumnarToRow [codegen id : 3] +Input [2]: [hd_demo_sk#10, hd_income_band_sk#11] + +(20) BroadcastExchange +Input [2]: [hd_demo_sk#10, hd_income_band_sk#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(21) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [c_current_hdemo_sk#3] +Right keys [1]: [hd_demo_sk#10] +Join type: Inner +Join condition: None + +(22) Project [codegen id : 5] +Output [5]: [c_customer_id#1, c_first_name#5, c_last_name#6, cd_demo_sk#9, hd_income_band_sk#11] +Input [7]: [c_customer_id#1, c_current_hdemo_sk#3, c_first_name#5, c_last_name#6, cd_demo_sk#9, hd_demo_sk#10, hd_income_band_sk#11] + +(23) Scan parquet spark_catalog.default.income_band +Output [3]: [ib_income_band_sk#12, ib_lower_bound#13, ib_upper_bound#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/income_band] +PushedFilters: [IsNotNull(ib_lower_bound), IsNotNull(ib_upper_bound), GreaterThanOrEqual(ib_lower_bound,38128), LessThanOrEqual(ib_upper_bound,88128), IsNotNull(ib_income_band_sk)] +ReadSchema: struct + +(24) CometFilter +Input [3]: [ib_income_band_sk#12, ib_lower_bound#13, ib_upper_bound#14] +Condition : ((((isnotnull(ib_lower_bound#13) AND isnotnull(ib_upper_bound#14)) AND (ib_lower_bound#13 >= 38128)) AND (ib_upper_bound#14 <= 88128)) AND isnotnull(ib_income_band_sk#12)) + +(25) CometProject +Input [3]: [ib_income_band_sk#12, ib_lower_bound#13, ib_upper_bound#14] +Arguments: [ib_income_band_sk#12], [ib_income_band_sk#12] + +(26) ColumnarToRow [codegen id : 4] +Input [1]: [ib_income_band_sk#12] + +(27) BroadcastExchange +Input [1]: [ib_income_band_sk#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(28) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [hd_income_band_sk#11] +Right keys [1]: [ib_income_band_sk#12] +Join type: Inner +Join condition: None + +(29) Project [codegen id : 5] +Output [4]: [c_customer_id#1, c_first_name#5, c_last_name#6, cd_demo_sk#9] +Input [6]: [c_customer_id#1, c_first_name#5, c_last_name#6, cd_demo_sk#9, hd_income_band_sk#11, ib_income_band_sk#12] + +(30) BroadcastExchange +Input [4]: [c_customer_id#1, c_first_name#5, c_last_name#6, cd_demo_sk#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[3, int, true] as bigint)),false), [plan_id=5] + +(31) Scan parquet spark_catalog.default.store_returns +Output [2]: [sr_cdemo_sk#15, sr_returned_date_sk#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_returns] +PushedFilters: [IsNotNull(sr_cdemo_sk)] +ReadSchema: struct + +(32) CometFilter +Input [2]: [sr_cdemo_sk#15, sr_returned_date_sk#16] +Condition : isnotnull(sr_cdemo_sk#15) + +(33) CometProject +Input [2]: [sr_cdemo_sk#15, sr_returned_date_sk#16] +Arguments: [sr_cdemo_sk#15], [sr_cdemo_sk#15] + +(34) ColumnarToRow +Input [1]: [sr_cdemo_sk#15] + +(35) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [cd_demo_sk#9] +Right keys [1]: [sr_cdemo_sk#15] +Join type: Inner +Join condition: None + +(36) Project [codegen id : 6] +Output [3]: [c_customer_id#1 AS customer_id#17, concat(c_last_name#6, , , c_first_name#5) AS customername#18, c_customer_id#1] +Input [5]: [c_customer_id#1, c_first_name#5, c_last_name#6, cd_demo_sk#9, sr_cdemo_sk#15] + +(37) TakeOrderedAndProject +Input [3]: [customer_id#17, customername#18, c_customer_id#1] +Arguments: 100, [c_customer_id#1 ASC NULLS FIRST], [customer_id#17, customername#18] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q84/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q84/simplified.txt new file mode 100644 index 0000000000..be3451d29c --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q84/simplified.txt @@ -0,0 +1,54 @@ +TakeOrderedAndProject [c_customer_id,customer_id,customername] + WholeStageCodegen (6) + Project [c_customer_id,c_last_name,c_first_name] + BroadcastHashJoin [cd_demo_sk,sr_cdemo_sk] + InputAdapter + BroadcastExchange #1 + WholeStageCodegen (5) + Project [c_customer_id,c_first_name,c_last_name,cd_demo_sk] + BroadcastHashJoin [hd_income_band_sk,ib_income_band_sk] + Project [c_customer_id,c_first_name,c_last_name,cd_demo_sk,hd_income_band_sk] + BroadcastHashJoin [c_current_hdemo_sk,hd_demo_sk] + Project [c_customer_id,c_current_hdemo_sk,c_first_name,c_last_name,cd_demo_sk] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk] + Project [c_customer_id,c_current_cdemo_sk,c_current_hdemo_sk,c_first_name,c_last_name] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + ColumnarToRow + InputAdapter + CometFilter [c_current_addr_sk,c_current_cdemo_sk,c_current_hdemo_sk] + CometScan parquet spark_catalog.default.customer [c_customer_id,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,c_first_name,c_last_name] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [ca_address_sk] + CometFilter [ca_city,ca_address_sk] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_city] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [cd_demo_sk] + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometFilter [hd_demo_sk,hd_income_band_sk] + CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_income_band_sk] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (4) + ColumnarToRow + InputAdapter + CometProject [ib_income_band_sk] + CometFilter [ib_lower_bound,ib_upper_bound,ib_income_band_sk] + CometScan parquet spark_catalog.default.income_band [ib_income_band_sk,ib_lower_bound,ib_upper_bound] + ColumnarToRow + InputAdapter + CometProject [sr_cdemo_sk] + CometFilter [sr_cdemo_sk] + CometScan parquet spark_catalog.default.store_returns [sr_cdemo_sk,sr_returned_date_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q85/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q85/explain.txt new file mode 100644 index 0000000000..ce1cc22629 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q85/explain.txt @@ -0,0 +1,305 @@ +== Physical Plan == +TakeOrderedAndProject (47) ++- * HashAggregate (46) + +- Exchange (45) + +- * HashAggregate (44) + +- * Project (43) + +- * BroadcastHashJoin Inner BuildRight (42) + :- * Project (37) + : +- * BroadcastHashJoin Inner BuildRight (36) + : :- * Project (34) + : : +- * BroadcastHashJoin Inner BuildRight (33) + : : :- * Project (27) + : : : +- * BroadcastHashJoin Inner BuildRight (26) + : : : :- * Project (21) + : : : : +- * BroadcastHashJoin Inner BuildRight (20) + : : : : :- * Project (15) + : : : : : +- * BroadcastHashJoin Inner BuildRight (14) + : : : : : :- * ColumnarToRow (9) + : : : : : : +- CometProject (8) + : : : : : : +- CometBroadcastHashJoin (7) + : : : : : : :- CometBroadcastExchange (3) + : : : : : : : +- CometFilter (2) + : : : : : : : +- CometScan parquet spark_catalog.default.web_sales (1) + : : : : : : +- CometProject (6) + : : : : : : +- CometFilter (5) + : : : : : : +- CometScan parquet spark_catalog.default.web_returns (4) + : : : : : +- BroadcastExchange (13) + : : : : : +- * ColumnarToRow (12) + : : : : : +- CometFilter (11) + : : : : : +- CometScan parquet spark_catalog.default.web_page (10) + : : : : +- BroadcastExchange (19) + : : : : +- * ColumnarToRow (18) + : : : : +- CometFilter (17) + : : : : +- CometScan parquet spark_catalog.default.customer_demographics (16) + : : : +- BroadcastExchange (25) + : : : +- * ColumnarToRow (24) + : : : +- CometFilter (23) + : : : +- CometScan parquet spark_catalog.default.customer_demographics (22) + : : +- BroadcastExchange (32) + : : +- * ColumnarToRow (31) + : : +- CometProject (30) + : : +- CometFilter (29) + : : +- CometScan parquet spark_catalog.default.customer_address (28) + : +- ReusedExchange (35) + +- BroadcastExchange (41) + +- * ColumnarToRow (40) + +- CometFilter (39) + +- CometScan parquet spark_catalog.default.reason (38) + + +(1) Scan parquet spark_catalog.default.web_sales +Output [7]: [ws_item_sk#1, ws_web_page_sk#2, ws_order_number#3, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#7), dynamicpruningexpression(ws_sold_date_sk#7 IN dynamicpruning#8)] +PushedFilters: [IsNotNull(ws_item_sk), IsNotNull(ws_order_number), IsNotNull(ws_web_page_sk), Or(Or(And(GreaterThanOrEqual(ws_sales_price,100.00),LessThanOrEqual(ws_sales_price,150.00)),And(GreaterThanOrEqual(ws_sales_price,50.00),LessThanOrEqual(ws_sales_price,100.00))),And(GreaterThanOrEqual(ws_sales_price,150.00),LessThanOrEqual(ws_sales_price,200.00))), Or(Or(And(GreaterThanOrEqual(ws_net_profit,100.00),LessThanOrEqual(ws_net_profit,200.00)),And(GreaterThanOrEqual(ws_net_profit,150.00),LessThanOrEqual(ws_net_profit,300.00))),And(GreaterThanOrEqual(ws_net_profit,50.00),LessThanOrEqual(ws_net_profit,250.00)))] +ReadSchema: struct + +(2) CometFilter +Input [7]: [ws_item_sk#1, ws_web_page_sk#2, ws_order_number#3, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7] +Condition : ((((isnotnull(ws_item_sk#1) AND isnotnull(ws_order_number#3)) AND isnotnull(ws_web_page_sk#2)) AND ((((ws_sales_price#5 >= 100.00) AND (ws_sales_price#5 <= 150.00)) OR ((ws_sales_price#5 >= 50.00) AND (ws_sales_price#5 <= 100.00))) OR ((ws_sales_price#5 >= 150.00) AND (ws_sales_price#5 <= 200.00)))) AND ((((ws_net_profit#6 >= 100.00) AND (ws_net_profit#6 <= 200.00)) OR ((ws_net_profit#6 >= 150.00) AND (ws_net_profit#6 <= 300.00))) OR ((ws_net_profit#6 >= 50.00) AND (ws_net_profit#6 <= 250.00)))) + +(3) CometBroadcastExchange +Input [7]: [ws_item_sk#1, ws_web_page_sk#2, ws_order_number#3, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7] +Arguments: [ws_item_sk#1, ws_web_page_sk#2, ws_order_number#3, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7] + +(4) Scan parquet spark_catalog.default.web_returns +Output [9]: [wr_item_sk#9, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_order_number#14, wr_fee#15, wr_refunded_cash#16, wr_returned_date_sk#17] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_returns] +PushedFilters: [IsNotNull(wr_item_sk), IsNotNull(wr_order_number), IsNotNull(wr_refunded_cdemo_sk), IsNotNull(wr_returning_cdemo_sk), IsNotNull(wr_refunded_addr_sk), IsNotNull(wr_reason_sk)] +ReadSchema: struct + +(5) CometFilter +Input [9]: [wr_item_sk#9, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_order_number#14, wr_fee#15, wr_refunded_cash#16, wr_returned_date_sk#17] +Condition : (((((isnotnull(wr_item_sk#9) AND isnotnull(wr_order_number#14)) AND isnotnull(wr_refunded_cdemo_sk#10)) AND isnotnull(wr_returning_cdemo_sk#12)) AND isnotnull(wr_refunded_addr_sk#11)) AND isnotnull(wr_reason_sk#13)) + +(6) CometProject +Input [9]: [wr_item_sk#9, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_order_number#14, wr_fee#15, wr_refunded_cash#16, wr_returned_date_sk#17] +Arguments: [wr_item_sk#9, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_order_number#14, wr_fee#15, wr_refunded_cash#16], [wr_item_sk#9, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_order_number#14, wr_fee#15, wr_refunded_cash#16] + +(7) CometBroadcastHashJoin +Left output [7]: [ws_item_sk#1, ws_web_page_sk#2, ws_order_number#3, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7] +Right output [8]: [wr_item_sk#9, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_order_number#14, wr_fee#15, wr_refunded_cash#16] +Arguments: [ws_item_sk#1, ws_order_number#3], [wr_item_sk#9, wr_order_number#14], Inner + +(8) CometProject +Input [15]: [ws_item_sk#1, ws_web_page_sk#2, ws_order_number#3, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7, wr_item_sk#9, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_order_number#14, wr_fee#15, wr_refunded_cash#16] +Arguments: [ws_web_page_sk#2, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16], [ws_web_page_sk#2, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16] + +(9) ColumnarToRow [codegen id : 7] +Input [11]: [ws_web_page_sk#2, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16] + +(10) Scan parquet spark_catalog.default.web_page +Output [1]: [wp_web_page_sk#18] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_page] +PushedFilters: [IsNotNull(wp_web_page_sk)] +ReadSchema: struct + +(11) CometFilter +Input [1]: [wp_web_page_sk#18] +Condition : isnotnull(wp_web_page_sk#18) + +(12) ColumnarToRow [codegen id : 1] +Input [1]: [wp_web_page_sk#18] + +(13) BroadcastExchange +Input [1]: [wp_web_page_sk#18] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(14) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [ws_web_page_sk#2] +Right keys [1]: [wp_web_page_sk#18] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 7] +Output [10]: [ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16] +Input [12]: [ws_web_page_sk#2, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16, wp_web_page_sk#18] + +(16) Scan parquet spark_catalog.default.customer_demographics +Output [3]: [cd_demo_sk#19, cd_marital_status#20, cd_education_status#21] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_demo_sk), IsNotNull(cd_marital_status), IsNotNull(cd_education_status), Or(Or(And(EqualTo(cd_marital_status,M),EqualTo(cd_education_status,Advanced Degree )),And(EqualTo(cd_marital_status,S),EqualTo(cd_education_status,College ))),And(EqualTo(cd_marital_status,W),EqualTo(cd_education_status,2 yr Degree )))] +ReadSchema: struct + +(17) CometFilter +Input [3]: [cd_demo_sk#19, cd_marital_status#20, cd_education_status#21] +Condition : (((isnotnull(cd_demo_sk#19) AND isnotnull(cd_marital_status#20)) AND isnotnull(cd_education_status#21)) AND ((((cd_marital_status#20 = M) AND (cd_education_status#21 = Advanced Degree )) OR ((cd_marital_status#20 = S) AND (cd_education_status#21 = College ))) OR ((cd_marital_status#20 = W) AND (cd_education_status#21 = 2 yr Degree )))) + +(18) ColumnarToRow [codegen id : 2] +Input [3]: [cd_demo_sk#19, cd_marital_status#20, cd_education_status#21] + +(19) BroadcastExchange +Input [3]: [cd_demo_sk#19, cd_marital_status#20, cd_education_status#21] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(20) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [wr_refunded_cdemo_sk#10] +Right keys [1]: [cd_demo_sk#19] +Join type: Inner +Join condition: ((((((cd_marital_status#20 = M) AND (cd_education_status#21 = Advanced Degree )) AND (ws_sales_price#5 >= 100.00)) AND (ws_sales_price#5 <= 150.00)) OR ((((cd_marital_status#20 = S) AND (cd_education_status#21 = College )) AND (ws_sales_price#5 >= 50.00)) AND (ws_sales_price#5 <= 100.00))) OR ((((cd_marital_status#20 = W) AND (cd_education_status#21 = 2 yr Degree )) AND (ws_sales_price#5 >= 150.00)) AND (ws_sales_price#5 <= 200.00))) + +(21) Project [codegen id : 7] +Output [10]: [ws_quantity#4, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16, cd_marital_status#20, cd_education_status#21] +Input [13]: [ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16, cd_demo_sk#19, cd_marital_status#20, cd_education_status#21] + +(22) Scan parquet spark_catalog.default.customer_demographics +Output [3]: [cd_demo_sk#22, cd_marital_status#23, cd_education_status#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_demo_sk), IsNotNull(cd_marital_status), IsNotNull(cd_education_status)] +ReadSchema: struct + +(23) CometFilter +Input [3]: [cd_demo_sk#22, cd_marital_status#23, cd_education_status#24] +Condition : ((isnotnull(cd_demo_sk#22) AND isnotnull(cd_marital_status#23)) AND isnotnull(cd_education_status#24)) + +(24) ColumnarToRow [codegen id : 3] +Input [3]: [cd_demo_sk#22, cd_marital_status#23, cd_education_status#24] + +(25) BroadcastExchange +Input [3]: [cd_demo_sk#22, cd_marital_status#23, cd_education_status#24] +Arguments: HashedRelationBroadcastMode(List(input[0, int, false], input[1, string, false], input[2, string, false]),false), [plan_id=3] + +(26) BroadcastHashJoin [codegen id : 7] +Left keys [3]: [wr_returning_cdemo_sk#12, cd_marital_status#20, cd_education_status#21] +Right keys [3]: [cd_demo_sk#22, cd_marital_status#23, cd_education_status#24] +Join type: Inner +Join condition: None + +(27) Project [codegen id : 7] +Output [7]: [ws_quantity#4, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_addr_sk#11, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16] +Input [13]: [ws_quantity#4, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16, cd_marital_status#20, cd_education_status#21, cd_demo_sk#22, cd_marital_status#23, cd_education_status#24] + +(28) Scan parquet spark_catalog.default.customer_address +Output [3]: [ca_address_sk#25, ca_state#26, ca_country#27] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_country), EqualTo(ca_country,United States), IsNotNull(ca_address_sk), Or(Or(In(ca_state, [IN,NJ,OH]),In(ca_state, [CT,KY,WI])),In(ca_state, [AR,IA,LA]))] +ReadSchema: struct + +(29) CometFilter +Input [3]: [ca_address_sk#25, ca_state#26, ca_country#27] +Condition : (((isnotnull(ca_country#27) AND (ca_country#27 = United States)) AND isnotnull(ca_address_sk#25)) AND ((ca_state#26 IN (IN,OH,NJ) OR ca_state#26 IN (WI,CT,KY)) OR ca_state#26 IN (LA,IA,AR))) + +(30) CometProject +Input [3]: [ca_address_sk#25, ca_state#26, ca_country#27] +Arguments: [ca_address_sk#25, ca_state#26], [ca_address_sk#25, ca_state#26] + +(31) ColumnarToRow [codegen id : 4] +Input [2]: [ca_address_sk#25, ca_state#26] + +(32) BroadcastExchange +Input [2]: [ca_address_sk#25, ca_state#26] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(33) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [wr_refunded_addr_sk#11] +Right keys [1]: [ca_address_sk#25] +Join type: Inner +Join condition: ((((ca_state#26 IN (IN,OH,NJ) AND (ws_net_profit#6 >= 100.00)) AND (ws_net_profit#6 <= 200.00)) OR ((ca_state#26 IN (WI,CT,KY) AND (ws_net_profit#6 >= 150.00)) AND (ws_net_profit#6 <= 300.00))) OR ((ca_state#26 IN (LA,IA,AR) AND (ws_net_profit#6 >= 50.00)) AND (ws_net_profit#6 <= 250.00))) + +(34) Project [codegen id : 7] +Output [5]: [ws_quantity#4, ws_sold_date_sk#7, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16] +Input [9]: [ws_quantity#4, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_addr_sk#11, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16, ca_address_sk#25, ca_state#26] + +(35) ReusedExchange [Reuses operator id: 52] +Output [1]: [d_date_sk#28] + +(36) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [ws_sold_date_sk#7] +Right keys [1]: [d_date_sk#28] +Join type: Inner +Join condition: None + +(37) Project [codegen id : 7] +Output [4]: [ws_quantity#4, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16] +Input [6]: [ws_quantity#4, ws_sold_date_sk#7, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16, d_date_sk#28] + +(38) Scan parquet spark_catalog.default.reason +Output [2]: [r_reason_sk#29, r_reason_desc#30] +Batched: true +Location [not included in comparison]/{warehouse_dir}/reason] +PushedFilters: [IsNotNull(r_reason_sk)] +ReadSchema: struct + +(39) CometFilter +Input [2]: [r_reason_sk#29, r_reason_desc#30] +Condition : isnotnull(r_reason_sk#29) + +(40) ColumnarToRow [codegen id : 6] +Input [2]: [r_reason_sk#29, r_reason_desc#30] + +(41) BroadcastExchange +Input [2]: [r_reason_sk#29, r_reason_desc#30] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(42) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [wr_reason_sk#13] +Right keys [1]: [r_reason_sk#29] +Join type: Inner +Join condition: None + +(43) Project [codegen id : 7] +Output [4]: [ws_quantity#4, wr_fee#15, wr_refunded_cash#16, r_reason_desc#30] +Input [6]: [ws_quantity#4, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16, r_reason_sk#29, r_reason_desc#30] + +(44) HashAggregate [codegen id : 7] +Input [4]: [ws_quantity#4, wr_fee#15, wr_refunded_cash#16, r_reason_desc#30] +Keys [1]: [r_reason_desc#30] +Functions [3]: [partial_avg(ws_quantity#4), partial_avg(UnscaledValue(wr_refunded_cash#16)), partial_avg(UnscaledValue(wr_fee#15))] +Aggregate Attributes [6]: [sum#31, count#32, sum#33, count#34, sum#35, count#36] +Results [7]: [r_reason_desc#30, sum#37, count#38, sum#39, count#40, sum#41, count#42] + +(45) Exchange +Input [7]: [r_reason_desc#30, sum#37, count#38, sum#39, count#40, sum#41, count#42] +Arguments: hashpartitioning(r_reason_desc#30, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(46) HashAggregate [codegen id : 8] +Input [7]: [r_reason_desc#30, sum#37, count#38, sum#39, count#40, sum#41, count#42] +Keys [1]: [r_reason_desc#30] +Functions [3]: [avg(ws_quantity#4), avg(UnscaledValue(wr_refunded_cash#16)), avg(UnscaledValue(wr_fee#15))] +Aggregate Attributes [3]: [avg(ws_quantity#4)#43, avg(UnscaledValue(wr_refunded_cash#16))#44, avg(UnscaledValue(wr_fee#15))#45] +Results [4]: [substr(r_reason_desc#30, 1, 20) AS substr(r_reason_desc, 1, 20)#46, avg(ws_quantity#4)#43 AS avg(ws_quantity)#47, cast((avg(UnscaledValue(wr_refunded_cash#16))#44 / 100.0) as decimal(11,6)) AS avg(wr_refunded_cash)#48, cast((avg(UnscaledValue(wr_fee#15))#45 / 100.0) as decimal(11,6)) AS avg(wr_fee)#49] + +(47) TakeOrderedAndProject +Input [4]: [substr(r_reason_desc, 1, 20)#46, avg(ws_quantity)#47, avg(wr_refunded_cash)#48, avg(wr_fee)#49] +Arguments: 100, [substr(r_reason_desc, 1, 20)#46 ASC NULLS FIRST, avg(ws_quantity)#47 ASC NULLS FIRST, avg(wr_refunded_cash)#48 ASC NULLS FIRST, avg(wr_fee)#49 ASC NULLS FIRST], [substr(r_reason_desc, 1, 20)#46, avg(ws_quantity)#47, avg(wr_refunded_cash)#48, avg(wr_fee)#49] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (52) ++- * ColumnarToRow (51) + +- CometProject (50) + +- CometFilter (49) + +- CometScan parquet spark_catalog.default.date_dim (48) + + +(48) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#28, d_year#50] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2000), IsNotNull(d_date_sk)] +ReadSchema: struct + +(49) CometFilter +Input [2]: [d_date_sk#28, d_year#50] +Condition : ((isnotnull(d_year#50) AND (d_year#50 = 2000)) AND isnotnull(d_date_sk#28)) + +(50) CometProject +Input [2]: [d_date_sk#28, d_year#50] +Arguments: [d_date_sk#28], [d_date_sk#28] + +(51) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#28] + +(52) BroadcastExchange +Input [1]: [d_date_sk#28] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q85/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q85/simplified.txt new file mode 100644 index 0000000000..7c5ee727b7 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q85/simplified.txt @@ -0,0 +1,75 @@ +TakeOrderedAndProject [substr(r_reason_desc, 1, 20),avg(ws_quantity),avg(wr_refunded_cash),avg(wr_fee)] + WholeStageCodegen (8) + HashAggregate [r_reason_desc,sum,count,sum,count,sum,count] [avg(ws_quantity),avg(UnscaledValue(wr_refunded_cash)),avg(UnscaledValue(wr_fee)),substr(r_reason_desc, 1, 20),avg(ws_quantity),avg(wr_refunded_cash),avg(wr_fee),sum,count,sum,count,sum,count] + InputAdapter + Exchange [r_reason_desc] #1 + WholeStageCodegen (7) + HashAggregate [r_reason_desc,ws_quantity,wr_refunded_cash,wr_fee] [sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + Project [ws_quantity,wr_fee,wr_refunded_cash,r_reason_desc] + BroadcastHashJoin [wr_reason_sk,r_reason_sk] + Project [ws_quantity,wr_reason_sk,wr_fee,wr_refunded_cash] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_quantity,ws_sold_date_sk,wr_reason_sk,wr_fee,wr_refunded_cash] + BroadcastHashJoin [wr_refunded_addr_sk,ca_address_sk,ca_state,ws_net_profit] + Project [ws_quantity,ws_net_profit,ws_sold_date_sk,wr_refunded_addr_sk,wr_reason_sk,wr_fee,wr_refunded_cash] + BroadcastHashJoin [wr_returning_cdemo_sk,cd_marital_status,cd_education_status,cd_demo_sk,cd_marital_status,cd_education_status] + Project [ws_quantity,ws_net_profit,ws_sold_date_sk,wr_refunded_addr_sk,wr_returning_cdemo_sk,wr_reason_sk,wr_fee,wr_refunded_cash,cd_marital_status,cd_education_status] + BroadcastHashJoin [wr_refunded_cdemo_sk,cd_demo_sk,cd_marital_status,cd_education_status,ws_sales_price] + Project [ws_quantity,ws_sales_price,ws_net_profit,ws_sold_date_sk,wr_refunded_cdemo_sk,wr_refunded_addr_sk,wr_returning_cdemo_sk,wr_reason_sk,wr_fee,wr_refunded_cash] + BroadcastHashJoin [ws_web_page_sk,wp_web_page_sk] + ColumnarToRow + InputAdapter + CometProject [ws_web_page_sk,ws_quantity,ws_sales_price,ws_net_profit,ws_sold_date_sk,wr_refunded_cdemo_sk,wr_refunded_addr_sk,wr_returning_cdemo_sk,wr_reason_sk,wr_fee,wr_refunded_cash] + CometBroadcastHashJoin [ws_item_sk,ws_order_number,wr_item_sk,wr_order_number] + CometBroadcastExchange #2 + CometFilter [ws_item_sk,ws_order_number,ws_web_page_sk,ws_sales_price,ws_net_profit] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_web_page_sk,ws_order_number,ws_quantity,ws_sales_price,ws_net_profit,ws_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + CometProject [wr_item_sk,wr_refunded_cdemo_sk,wr_refunded_addr_sk,wr_returning_cdemo_sk,wr_reason_sk,wr_order_number,wr_fee,wr_refunded_cash] + CometFilter [wr_item_sk,wr_order_number,wr_refunded_cdemo_sk,wr_returning_cdemo_sk,wr_refunded_addr_sk,wr_reason_sk] + CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_refunded_cdemo_sk,wr_refunded_addr_sk,wr_returning_cdemo_sk,wr_reason_sk,wr_order_number,wr_fee,wr_refunded_cash,wr_returned_date_sk] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [wp_web_page_sk] + CometScan parquet spark_catalog.default.web_page [wp_web_page_sk] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [cd_demo_sk,cd_marital_status,cd_education_status] + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_marital_status,cd_education_status] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometFilter [cd_demo_sk,cd_marital_status,cd_education_status] + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_marital_status,cd_education_status] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (4) + ColumnarToRow + InputAdapter + CometProject [ca_address_sk,ca_state] + CometFilter [ca_country,ca_address_sk,ca_state] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state,ca_country] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (6) + ColumnarToRow + InputAdapter + CometFilter [r_reason_sk] + CometScan parquet spark_catalog.default.reason [r_reason_sk,r_reason_desc] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q86/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q86/explain.txt new file mode 100644 index 0000000000..5bfd2925d2 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q86/explain.txt @@ -0,0 +1,155 @@ +== Physical Plan == +TakeOrderedAndProject (21) ++- * Project (20) + +- Window (19) + +- * Sort (18) + +- Exchange (17) + +- * HashAggregate (16) + +- Exchange (15) + +- * HashAggregate (14) + +- * Expand (13) + +- * Project (12) + +- * BroadcastHashJoin Inner BuildRight (11) + :- * Project (6) + : +- * BroadcastHashJoin Inner BuildRight (5) + : :- * ColumnarToRow (3) + : : +- CometFilter (2) + : : +- CometScan parquet spark_catalog.default.web_sales (1) + : +- ReusedExchange (4) + +- BroadcastExchange (10) + +- * ColumnarToRow (9) + +- CometFilter (8) + +- CometScan parquet spark_catalog.default.item (7) + + +(1) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_item_sk#1, ws_net_paid#2, ws_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#3), dynamicpruningexpression(ws_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [ws_item_sk#1, ws_net_paid#2, ws_sold_date_sk#3] +Condition : isnotnull(ws_item_sk#1) + +(3) ColumnarToRow [codegen id : 3] +Input [3]: [ws_item_sk#1, ws_net_paid#2, ws_sold_date_sk#3] + +(4) ReusedExchange [Reuses operator id: 26] +Output [1]: [d_date_sk#5] + +(5) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ws_sold_date_sk#3] +Right keys [1]: [d_date_sk#5] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 3] +Output [2]: [ws_item_sk#1, ws_net_paid#2] +Input [4]: [ws_item_sk#1, ws_net_paid#2, ws_sold_date_sk#3, d_date_sk#5] + +(7) Scan parquet spark_catalog.default.item +Output [3]: [i_item_sk#6, i_class#7, i_category#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(8) CometFilter +Input [3]: [i_item_sk#6, i_class#7, i_category#8] +Condition : isnotnull(i_item_sk#6) + +(9) ColumnarToRow [codegen id : 2] +Input [3]: [i_item_sk#6, i_class#7, i_category#8] + +(10) BroadcastExchange +Input [3]: [i_item_sk#6, i_class#7, i_category#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ws_item_sk#1] +Right keys [1]: [i_item_sk#6] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [3]: [ws_net_paid#2, i_category#8, i_class#7] +Input [5]: [ws_item_sk#1, ws_net_paid#2, i_item_sk#6, i_class#7, i_category#8] + +(13) Expand [codegen id : 3] +Input [3]: [ws_net_paid#2, i_category#8, i_class#7] +Arguments: [[ws_net_paid#2, i_category#8, i_class#7, 0], [ws_net_paid#2, i_category#8, null, 1], [ws_net_paid#2, null, null, 3]], [ws_net_paid#2, i_category#9, i_class#10, spark_grouping_id#11] + +(14) HashAggregate [codegen id : 3] +Input [4]: [ws_net_paid#2, i_category#9, i_class#10, spark_grouping_id#11] +Keys [3]: [i_category#9, i_class#10, spark_grouping_id#11] +Functions [1]: [partial_sum(UnscaledValue(ws_net_paid#2))] +Aggregate Attributes [1]: [sum#12] +Results [4]: [i_category#9, i_class#10, spark_grouping_id#11, sum#13] + +(15) Exchange +Input [4]: [i_category#9, i_class#10, spark_grouping_id#11, sum#13] +Arguments: hashpartitioning(i_category#9, i_class#10, spark_grouping_id#11, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(16) HashAggregate [codegen id : 4] +Input [4]: [i_category#9, i_class#10, spark_grouping_id#11, sum#13] +Keys [3]: [i_category#9, i_class#10, spark_grouping_id#11] +Functions [1]: [sum(UnscaledValue(ws_net_paid#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_net_paid#2))#14] +Results [7]: [MakeDecimal(sum(UnscaledValue(ws_net_paid#2))#14,17,2) AS total_sum#15, i_category#9, i_class#10, (cast((shiftright(spark_grouping_id#11, 1) & 1) as tinyint) + cast((shiftright(spark_grouping_id#11, 0) & 1) as tinyint)) AS lochierarchy#16, MakeDecimal(sum(UnscaledValue(ws_net_paid#2))#14,17,2) AS _w0#17, (cast((shiftright(spark_grouping_id#11, 1) & 1) as tinyint) + cast((shiftright(spark_grouping_id#11, 0) & 1) as tinyint)) AS _w1#18, CASE WHEN (cast((shiftright(spark_grouping_id#11, 0) & 1) as tinyint) = 0) THEN i_category#9 END AS _w2#19] + +(17) Exchange +Input [7]: [total_sum#15, i_category#9, i_class#10, lochierarchy#16, _w0#17, _w1#18, _w2#19] +Arguments: hashpartitioning(_w1#18, _w2#19, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(18) Sort [codegen id : 5] +Input [7]: [total_sum#15, i_category#9, i_class#10, lochierarchy#16, _w0#17, _w1#18, _w2#19] +Arguments: [_w1#18 ASC NULLS FIRST, _w2#19 ASC NULLS FIRST, _w0#17 DESC NULLS LAST], false, 0 + +(19) Window +Input [7]: [total_sum#15, i_category#9, i_class#10, lochierarchy#16, _w0#17, _w1#18, _w2#19] +Arguments: [rank(_w0#17) windowspecdefinition(_w1#18, _w2#19, _w0#17 DESC NULLS LAST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rank_within_parent#20], [_w1#18, _w2#19], [_w0#17 DESC NULLS LAST] + +(20) Project [codegen id : 6] +Output [5]: [total_sum#15, i_category#9, i_class#10, lochierarchy#16, rank_within_parent#20] +Input [8]: [total_sum#15, i_category#9, i_class#10, lochierarchy#16, _w0#17, _w1#18, _w2#19, rank_within_parent#20] + +(21) TakeOrderedAndProject +Input [5]: [total_sum#15, i_category#9, i_class#10, lochierarchy#16, rank_within_parent#20] +Arguments: 100, [lochierarchy#16 DESC NULLS LAST, CASE WHEN (lochierarchy#16 = 0) THEN i_category#9 END ASC NULLS FIRST, rank_within_parent#20 ASC NULLS FIRST], [total_sum#15, i_category#9, i_class#10, lochierarchy#16, rank_within_parent#20] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (26) ++- * ColumnarToRow (25) + +- CometProject (24) + +- CometFilter (23) + +- CometScan parquet spark_catalog.default.date_dim (22) + + +(22) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#5, d_month_seq#21] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)] +ReadSchema: struct + +(23) CometFilter +Input [2]: [d_date_sk#5, d_month_seq#21] +Condition : (((isnotnull(d_month_seq#21) AND (d_month_seq#21 >= 1200)) AND (d_month_seq#21 <= 1211)) AND isnotnull(d_date_sk#5)) + +(24) CometProject +Input [2]: [d_date_sk#5, d_month_seq#21] +Arguments: [d_date_sk#5], [d_date_sk#5] + +(25) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#5] + +(26) BroadcastExchange +Input [1]: [d_date_sk#5] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q86/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q86/simplified.txt new file mode 100644 index 0000000000..f9db2ce7a4 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q86/simplified.txt @@ -0,0 +1,41 @@ +TakeOrderedAndProject [lochierarchy,i_category,rank_within_parent,total_sum,i_class] + WholeStageCodegen (6) + Project [total_sum,i_category,i_class,lochierarchy,rank_within_parent] + InputAdapter + Window [_w0,_w1,_w2] + WholeStageCodegen (5) + Sort [_w1,_w2,_w0] + InputAdapter + Exchange [_w1,_w2] #1 + WholeStageCodegen (4) + HashAggregate [i_category,i_class,spark_grouping_id,sum] [sum(UnscaledValue(ws_net_paid)),total_sum,lochierarchy,_w0,_w1,_w2,sum] + InputAdapter + Exchange [i_category,i_class,spark_grouping_id] #2 + WholeStageCodegen (3) + HashAggregate [i_category,i_class,spark_grouping_id,ws_net_paid] [sum,sum] + Expand [ws_net_paid,i_category,i_class] + Project [ws_net_paid,i_category,i_class] + BroadcastHashJoin [ws_item_sk,i_item_sk] + Project [ws_item_sk,ws_net_paid] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_net_paid,ws_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_month_seq,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_class,i_category] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q87/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q87/explain.txt new file mode 100644 index 0000000000..a4c9f13ce6 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q87/explain.txt @@ -0,0 +1,321 @@ +== Physical Plan == +* HashAggregate (47) ++- Exchange (46) + +- * HashAggregate (45) + +- * Project (44) + +- * BroadcastHashJoin LeftAnti BuildRight (43) + :- * BroadcastHashJoin LeftAnti BuildRight (29) + : :- * HashAggregate (15) + : : +- Exchange (14) + : : +- * HashAggregate (13) + : : +- * Project (12) + : : +- * BroadcastHashJoin Inner BuildRight (11) + : : :- * Project (6) + : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- ReusedExchange (4) + : : +- BroadcastExchange (10) + : : +- * ColumnarToRow (9) + : : +- CometFilter (8) + : : +- CometScan parquet spark_catalog.default.customer (7) + : +- BroadcastExchange (28) + : +- * HashAggregate (27) + : +- Exchange (26) + : +- * HashAggregate (25) + : +- * Project (24) + : +- * BroadcastHashJoin Inner BuildRight (23) + : :- * Project (21) + : : +- * BroadcastHashJoin Inner BuildRight (20) + : : :- * ColumnarToRow (18) + : : : +- CometFilter (17) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (16) + : : +- ReusedExchange (19) + : +- ReusedExchange (22) + +- BroadcastExchange (42) + +- * HashAggregate (41) + +- Exchange (40) + +- * HashAggregate (39) + +- * Project (38) + +- * BroadcastHashJoin Inner BuildRight (37) + :- * Project (35) + : +- * BroadcastHashJoin Inner BuildRight (34) + : :- * ColumnarToRow (32) + : : +- CometFilter (31) + : : +- CometScan parquet spark_catalog.default.web_sales (30) + : +- ReusedExchange (33) + +- ReusedExchange (36) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [2]: [ss_customer_sk#1, ss_sold_date_sk#2] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#2), dynamicpruningexpression(ss_sold_date_sk#2 IN dynamicpruning#3)] +PushedFilters: [IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(2) CometFilter +Input [2]: [ss_customer_sk#1, ss_sold_date_sk#2] +Condition : isnotnull(ss_customer_sk#1) + +(3) ColumnarToRow [codegen id : 3] +Input [2]: [ss_customer_sk#1, ss_sold_date_sk#2] + +(4) ReusedExchange [Reuses operator id: 52] +Output [2]: [d_date_sk#4, d_date#5] + +(5) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_sold_date_sk#2] +Right keys [1]: [d_date_sk#4] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 3] +Output [2]: [ss_customer_sk#1, d_date#5] +Input [4]: [ss_customer_sk#1, ss_sold_date_sk#2, d_date_sk#4, d_date#5] + +(7) Scan parquet spark_catalog.default.customer +Output [3]: [c_customer_sk#6, c_first_name#7, c_last_name#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk)] +ReadSchema: struct + +(8) CometFilter +Input [3]: [c_customer_sk#6, c_first_name#7, c_last_name#8] +Condition : isnotnull(c_customer_sk#6) + +(9) ColumnarToRow [codegen id : 2] +Input [3]: [c_customer_sk#6, c_first_name#7, c_last_name#8] + +(10) BroadcastExchange +Input [3]: [c_customer_sk#6, c_first_name#7, c_last_name#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_customer_sk#1] +Right keys [1]: [c_customer_sk#6] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [3]: [c_last_name#8, c_first_name#7, d_date#5] +Input [5]: [ss_customer_sk#1, d_date#5, c_customer_sk#6, c_first_name#7, c_last_name#8] + +(13) HashAggregate [codegen id : 3] +Input [3]: [c_last_name#8, c_first_name#7, d_date#5] +Keys [3]: [c_last_name#8, c_first_name#7, d_date#5] +Functions: [] +Aggregate Attributes: [] +Results [3]: [c_last_name#8, c_first_name#7, d_date#5] + +(14) Exchange +Input [3]: [c_last_name#8, c_first_name#7, d_date#5] +Arguments: hashpartitioning(c_last_name#8, c_first_name#7, d_date#5, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 12] +Input [3]: [c_last_name#8, c_first_name#7, d_date#5] +Keys [3]: [c_last_name#8, c_first_name#7, d_date#5] +Functions: [] +Aggregate Attributes: [] +Results [3]: [c_last_name#8, c_first_name#7, d_date#5] + +(16) Scan parquet spark_catalog.default.catalog_sales +Output [2]: [cs_bill_customer_sk#9, cs_sold_date_sk#10] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#10), dynamicpruningexpression(cs_sold_date_sk#10 IN dynamicpruning#11)] +PushedFilters: [IsNotNull(cs_bill_customer_sk)] +ReadSchema: struct + +(17) CometFilter +Input [2]: [cs_bill_customer_sk#9, cs_sold_date_sk#10] +Condition : isnotnull(cs_bill_customer_sk#9) + +(18) ColumnarToRow [codegen id : 6] +Input [2]: [cs_bill_customer_sk#9, cs_sold_date_sk#10] + +(19) ReusedExchange [Reuses operator id: 52] +Output [2]: [d_date_sk#12, d_date#13] + +(20) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [cs_sold_date_sk#10] +Right keys [1]: [d_date_sk#12] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 6] +Output [2]: [cs_bill_customer_sk#9, d_date#13] +Input [4]: [cs_bill_customer_sk#9, cs_sold_date_sk#10, d_date_sk#12, d_date#13] + +(22) ReusedExchange [Reuses operator id: 10] +Output [3]: [c_customer_sk#14, c_first_name#15, c_last_name#16] + +(23) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [cs_bill_customer_sk#9] +Right keys [1]: [c_customer_sk#14] +Join type: Inner +Join condition: None + +(24) Project [codegen id : 6] +Output [3]: [c_last_name#16, c_first_name#15, d_date#13] +Input [5]: [cs_bill_customer_sk#9, d_date#13, c_customer_sk#14, c_first_name#15, c_last_name#16] + +(25) HashAggregate [codegen id : 6] +Input [3]: [c_last_name#16, c_first_name#15, d_date#13] +Keys [3]: [c_last_name#16, c_first_name#15, d_date#13] +Functions: [] +Aggregate Attributes: [] +Results [3]: [c_last_name#16, c_first_name#15, d_date#13] + +(26) Exchange +Input [3]: [c_last_name#16, c_first_name#15, d_date#13] +Arguments: hashpartitioning(c_last_name#16, c_first_name#15, d_date#13, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(27) HashAggregate [codegen id : 7] +Input [3]: [c_last_name#16, c_first_name#15, d_date#13] +Keys [3]: [c_last_name#16, c_first_name#15, d_date#13] +Functions: [] +Aggregate Attributes: [] +Results [3]: [c_last_name#16, c_first_name#15, d_date#13] + +(28) BroadcastExchange +Input [3]: [c_last_name#16, c_first_name#15, d_date#13] +Arguments: HashedRelationBroadcastMode(List(coalesce(input[0, string, true], ), isnull(input[0, string, true]), coalesce(input[1, string, true], ), isnull(input[1, string, true]), coalesce(input[2, date, true], 1970-01-01), isnull(input[2, date, true])),false), [plan_id=4] + +(29) BroadcastHashJoin [codegen id : 12] +Left keys [6]: [coalesce(c_last_name#8, ), isnull(c_last_name#8), coalesce(c_first_name#7, ), isnull(c_first_name#7), coalesce(d_date#5, 1970-01-01), isnull(d_date#5)] +Right keys [6]: [coalesce(c_last_name#16, ), isnull(c_last_name#16), coalesce(c_first_name#15, ), isnull(c_first_name#15), coalesce(d_date#13, 1970-01-01), isnull(d_date#13)] +Join type: LeftAnti +Join condition: None + +(30) Scan parquet spark_catalog.default.web_sales +Output [2]: [ws_bill_customer_sk#17, ws_sold_date_sk#18] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#18), dynamicpruningexpression(ws_sold_date_sk#18 IN dynamicpruning#19)] +PushedFilters: [IsNotNull(ws_bill_customer_sk)] +ReadSchema: struct + +(31) CometFilter +Input [2]: [ws_bill_customer_sk#17, ws_sold_date_sk#18] +Condition : isnotnull(ws_bill_customer_sk#17) + +(32) ColumnarToRow [codegen id : 10] +Input [2]: [ws_bill_customer_sk#17, ws_sold_date_sk#18] + +(33) ReusedExchange [Reuses operator id: 52] +Output [2]: [d_date_sk#20, d_date#21] + +(34) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [ws_sold_date_sk#18] +Right keys [1]: [d_date_sk#20] +Join type: Inner +Join condition: None + +(35) Project [codegen id : 10] +Output [2]: [ws_bill_customer_sk#17, d_date#21] +Input [4]: [ws_bill_customer_sk#17, ws_sold_date_sk#18, d_date_sk#20, d_date#21] + +(36) ReusedExchange [Reuses operator id: 10] +Output [3]: [c_customer_sk#22, c_first_name#23, c_last_name#24] + +(37) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [ws_bill_customer_sk#17] +Right keys [1]: [c_customer_sk#22] +Join type: Inner +Join condition: None + +(38) Project [codegen id : 10] +Output [3]: [c_last_name#24, c_first_name#23, d_date#21] +Input [5]: [ws_bill_customer_sk#17, d_date#21, c_customer_sk#22, c_first_name#23, c_last_name#24] + +(39) HashAggregate [codegen id : 10] +Input [3]: [c_last_name#24, c_first_name#23, d_date#21] +Keys [3]: [c_last_name#24, c_first_name#23, d_date#21] +Functions: [] +Aggregate Attributes: [] +Results [3]: [c_last_name#24, c_first_name#23, d_date#21] + +(40) Exchange +Input [3]: [c_last_name#24, c_first_name#23, d_date#21] +Arguments: hashpartitioning(c_last_name#24, c_first_name#23, d_date#21, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(41) HashAggregate [codegen id : 11] +Input [3]: [c_last_name#24, c_first_name#23, d_date#21] +Keys [3]: [c_last_name#24, c_first_name#23, d_date#21] +Functions: [] +Aggregate Attributes: [] +Results [3]: [c_last_name#24, c_first_name#23, d_date#21] + +(42) BroadcastExchange +Input [3]: [c_last_name#24, c_first_name#23, d_date#21] +Arguments: HashedRelationBroadcastMode(List(coalesce(input[0, string, true], ), isnull(input[0, string, true]), coalesce(input[1, string, true], ), isnull(input[1, string, true]), coalesce(input[2, date, true], 1970-01-01), isnull(input[2, date, true])),false), [plan_id=6] + +(43) BroadcastHashJoin [codegen id : 12] +Left keys [6]: [coalesce(c_last_name#8, ), isnull(c_last_name#8), coalesce(c_first_name#7, ), isnull(c_first_name#7), coalesce(d_date#5, 1970-01-01), isnull(d_date#5)] +Right keys [6]: [coalesce(c_last_name#24, ), isnull(c_last_name#24), coalesce(c_first_name#23, ), isnull(c_first_name#23), coalesce(d_date#21, 1970-01-01), isnull(d_date#21)] +Join type: LeftAnti +Join condition: None + +(44) Project [codegen id : 12] +Output: [] +Input [3]: [c_last_name#8, c_first_name#7, d_date#5] + +(45) HashAggregate [codegen id : 12] +Input: [] +Keys: [] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#25] +Results [1]: [count#26] + +(46) Exchange +Input [1]: [count#26] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=7] + +(47) HashAggregate [codegen id : 13] +Input [1]: [count#26] +Keys: [] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#27] +Results [1]: [count(1)#27 AS count(1)#28] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#2 IN dynamicpruning#3 +BroadcastExchange (52) ++- * ColumnarToRow (51) + +- CometProject (50) + +- CometFilter (49) + +- CometScan parquet spark_catalog.default.date_dim (48) + + +(48) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#4, d_date#5, d_month_seq#29] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)] +ReadSchema: struct + +(49) CometFilter +Input [3]: [d_date_sk#4, d_date#5, d_month_seq#29] +Condition : (((isnotnull(d_month_seq#29) AND (d_month_seq#29 >= 1200)) AND (d_month_seq#29 <= 1211)) AND isnotnull(d_date_sk#4)) + +(50) CometProject +Input [3]: [d_date_sk#4, d_date#5, d_month_seq#29] +Arguments: [d_date_sk#4, d_date#5], [d_date_sk#4, d_date#5] + +(51) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#4, d_date#5] + +(52) BroadcastExchange +Input [2]: [d_date_sk#4, d_date#5] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + +Subquery:2 Hosting operator id = 16 Hosting Expression = cs_sold_date_sk#10 IN dynamicpruning#3 + +Subquery:3 Hosting operator id = 30 Hosting Expression = ws_sold_date_sk#18 IN dynamicpruning#3 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q87/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q87/simplified.txt new file mode 100644 index 0000000000..315afe6602 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q87/simplified.txt @@ -0,0 +1,81 @@ +WholeStageCodegen (13) + HashAggregate [count] [count(1),count(1),count] + InputAdapter + Exchange #1 + WholeStageCodegen (12) + HashAggregate [count,count] + Project + BroadcastHashJoin [c_last_name,c_first_name,d_date,c_last_name,c_first_name,d_date] + BroadcastHashJoin [c_last_name,c_first_name,d_date,c_last_name,c_first_name,d_date] + HashAggregate [c_last_name,c_first_name,d_date] + InputAdapter + Exchange [c_last_name,c_first_name,d_date] #2 + WholeStageCodegen (3) + HashAggregate [c_last_name,c_first_name,d_date] + Project [c_last_name,c_first_name,d_date] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Project [ss_customer_sk,d_date] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk] + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_date] + CometFilter [d_month_seq,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date,d_month_seq] + InputAdapter + ReusedExchange [d_date_sk,d_date] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_first_name,c_last_name] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (7) + HashAggregate [c_last_name,c_first_name,d_date] + InputAdapter + Exchange [c_last_name,c_first_name,d_date] #6 + WholeStageCodegen (6) + HashAggregate [c_last_name,c_first_name,d_date] + Project [c_last_name,c_first_name,d_date] + BroadcastHashJoin [cs_bill_customer_sk,c_customer_sk] + Project [cs_bill_customer_sk,d_date] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [cs_bill_customer_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk,d_date] #3 + InputAdapter + ReusedExchange [c_customer_sk,c_first_name,c_last_name] #4 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (11) + HashAggregate [c_last_name,c_first_name,d_date] + InputAdapter + Exchange [c_last_name,c_first_name,d_date] #8 + WholeStageCodegen (10) + HashAggregate [c_last_name,c_first_name,d_date] + Project [c_last_name,c_first_name,d_date] + BroadcastHashJoin [ws_bill_customer_sk,c_customer_sk] + Project [ws_bill_customer_sk,d_date] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ws_bill_customer_sk] + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk,d_date] #3 + InputAdapter + ReusedExchange [c_customer_sk,c_first_name,c_last_name] #4 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q88/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q88/explain.txt new file mode 100644 index 0000000000..a5f68e5648 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q88/explain.txt @@ -0,0 +1,1031 @@ +== Physical Plan == +* BroadcastNestedLoopJoin Inner BuildRight (182) +:- * BroadcastNestedLoopJoin Inner BuildRight (160) +: :- * BroadcastNestedLoopJoin Inner BuildRight (138) +: : :- * BroadcastNestedLoopJoin Inner BuildRight (116) +: : : :- * BroadcastNestedLoopJoin Inner BuildRight (94) +: : : : :- * BroadcastNestedLoopJoin Inner BuildRight (72) +: : : : : :- * BroadcastNestedLoopJoin Inner BuildRight (50) +: : : : : : :- * HashAggregate (28) +: : : : : : : +- Exchange (27) +: : : : : : : +- * HashAggregate (26) +: : : : : : : +- * Project (25) +: : : : : : : +- * BroadcastHashJoin Inner BuildRight (24) +: : : : : : : :- * Project (18) +: : : : : : : : +- * BroadcastHashJoin Inner BuildRight (17) +: : : : : : : : :- * Project (11) +: : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (10) +: : : : : : : : : :- * ColumnarToRow (4) +: : : : : : : : : : +- CometProject (3) +: : : : : : : : : : +- CometFilter (2) +: : : : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) +: : : : : : : : : +- BroadcastExchange (9) +: : : : : : : : : +- * ColumnarToRow (8) +: : : : : : : : : +- CometProject (7) +: : : : : : : : : +- CometFilter (6) +: : : : : : : : : +- CometScan parquet spark_catalog.default.household_demographics (5) +: : : : : : : : +- BroadcastExchange (16) +: : : : : : : : +- * ColumnarToRow (15) +: : : : : : : : +- CometProject (14) +: : : : : : : : +- CometFilter (13) +: : : : : : : : +- CometScan parquet spark_catalog.default.time_dim (12) +: : : : : : : +- BroadcastExchange (23) +: : : : : : : +- * ColumnarToRow (22) +: : : : : : : +- CometProject (21) +: : : : : : : +- CometFilter (20) +: : : : : : : +- CometScan parquet spark_catalog.default.store (19) +: : : : : : +- BroadcastExchange (49) +: : : : : : +- * HashAggregate (48) +: : : : : : +- Exchange (47) +: : : : : : +- * HashAggregate (46) +: : : : : : +- * Project (45) +: : : : : : +- * BroadcastHashJoin Inner BuildRight (44) +: : : : : : :- * Project (42) +: : : : : : : +- * BroadcastHashJoin Inner BuildRight (41) +: : : : : : : :- * Project (35) +: : : : : : : : +- * BroadcastHashJoin Inner BuildRight (34) +: : : : : : : : :- * ColumnarToRow (32) +: : : : : : : : : +- CometProject (31) +: : : : : : : : : +- CometFilter (30) +: : : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (29) +: : : : : : : : +- ReusedExchange (33) +: : : : : : : +- BroadcastExchange (40) +: : : : : : : +- * ColumnarToRow (39) +: : : : : : : +- CometProject (38) +: : : : : : : +- CometFilter (37) +: : : : : : : +- CometScan parquet spark_catalog.default.time_dim (36) +: : : : : : +- ReusedExchange (43) +: : : : : +- BroadcastExchange (71) +: : : : : +- * HashAggregate (70) +: : : : : +- Exchange (69) +: : : : : +- * HashAggregate (68) +: : : : : +- * Project (67) +: : : : : +- * BroadcastHashJoin Inner BuildRight (66) +: : : : : :- * Project (64) +: : : : : : +- * BroadcastHashJoin Inner BuildRight (63) +: : : : : : :- * Project (57) +: : : : : : : +- * BroadcastHashJoin Inner BuildRight (56) +: : : : : : : :- * ColumnarToRow (54) +: : : : : : : : +- CometProject (53) +: : : : : : : : +- CometFilter (52) +: : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (51) +: : : : : : : +- ReusedExchange (55) +: : : : : : +- BroadcastExchange (62) +: : : : : : +- * ColumnarToRow (61) +: : : : : : +- CometProject (60) +: : : : : : +- CometFilter (59) +: : : : : : +- CometScan parquet spark_catalog.default.time_dim (58) +: : : : : +- ReusedExchange (65) +: : : : +- BroadcastExchange (93) +: : : : +- * HashAggregate (92) +: : : : +- Exchange (91) +: : : : +- * HashAggregate (90) +: : : : +- * Project (89) +: : : : +- * BroadcastHashJoin Inner BuildRight (88) +: : : : :- * Project (86) +: : : : : +- * BroadcastHashJoin Inner BuildRight (85) +: : : : : :- * Project (79) +: : : : : : +- * BroadcastHashJoin Inner BuildRight (78) +: : : : : : :- * ColumnarToRow (76) +: : : : : : : +- CometProject (75) +: : : : : : : +- CometFilter (74) +: : : : : : : +- CometScan parquet spark_catalog.default.store_sales (73) +: : : : : : +- ReusedExchange (77) +: : : : : +- BroadcastExchange (84) +: : : : : +- * ColumnarToRow (83) +: : : : : +- CometProject (82) +: : : : : +- CometFilter (81) +: : : : : +- CometScan parquet spark_catalog.default.time_dim (80) +: : : : +- ReusedExchange (87) +: : : +- BroadcastExchange (115) +: : : +- * HashAggregate (114) +: : : +- Exchange (113) +: : : +- * HashAggregate (112) +: : : +- * Project (111) +: : : +- * BroadcastHashJoin Inner BuildRight (110) +: : : :- * Project (108) +: : : : +- * BroadcastHashJoin Inner BuildRight (107) +: : : : :- * Project (101) +: : : : : +- * BroadcastHashJoin Inner BuildRight (100) +: : : : : :- * ColumnarToRow (98) +: : : : : : +- CometProject (97) +: : : : : : +- CometFilter (96) +: : : : : : +- CometScan parquet spark_catalog.default.store_sales (95) +: : : : : +- ReusedExchange (99) +: : : : +- BroadcastExchange (106) +: : : : +- * ColumnarToRow (105) +: : : : +- CometProject (104) +: : : : +- CometFilter (103) +: : : : +- CometScan parquet spark_catalog.default.time_dim (102) +: : : +- ReusedExchange (109) +: : +- BroadcastExchange (137) +: : +- * HashAggregate (136) +: : +- Exchange (135) +: : +- * HashAggregate (134) +: : +- * Project (133) +: : +- * BroadcastHashJoin Inner BuildRight (132) +: : :- * Project (130) +: : : +- * BroadcastHashJoin Inner BuildRight (129) +: : : :- * Project (123) +: : : : +- * BroadcastHashJoin Inner BuildRight (122) +: : : : :- * ColumnarToRow (120) +: : : : : +- CometProject (119) +: : : : : +- CometFilter (118) +: : : : : +- CometScan parquet spark_catalog.default.store_sales (117) +: : : : +- ReusedExchange (121) +: : : +- BroadcastExchange (128) +: : : +- * ColumnarToRow (127) +: : : +- CometProject (126) +: : : +- CometFilter (125) +: : : +- CometScan parquet spark_catalog.default.time_dim (124) +: : +- ReusedExchange (131) +: +- BroadcastExchange (159) +: +- * HashAggregate (158) +: +- Exchange (157) +: +- * HashAggregate (156) +: +- * Project (155) +: +- * BroadcastHashJoin Inner BuildRight (154) +: :- * Project (152) +: : +- * BroadcastHashJoin Inner BuildRight (151) +: : :- * Project (145) +: : : +- * BroadcastHashJoin Inner BuildRight (144) +: : : :- * ColumnarToRow (142) +: : : : +- CometProject (141) +: : : : +- CometFilter (140) +: : : : +- CometScan parquet spark_catalog.default.store_sales (139) +: : : +- ReusedExchange (143) +: : +- BroadcastExchange (150) +: : +- * ColumnarToRow (149) +: : +- CometProject (148) +: : +- CometFilter (147) +: : +- CometScan parquet spark_catalog.default.time_dim (146) +: +- ReusedExchange (153) ++- BroadcastExchange (181) + +- * HashAggregate (180) + +- Exchange (179) + +- * HashAggregate (178) + +- * Project (177) + +- * BroadcastHashJoin Inner BuildRight (176) + :- * Project (174) + : +- * BroadcastHashJoin Inner BuildRight (173) + : :- * Project (167) + : : +- * BroadcastHashJoin Inner BuildRight (166) + : : :- * ColumnarToRow (164) + : : : +- CometProject (163) + : : : +- CometFilter (162) + : : : +- CometScan parquet spark_catalog.default.store_sales (161) + : : +- ReusedExchange (165) + : +- BroadcastExchange (172) + : +- * ColumnarToRow (171) + : +- CometProject (170) + : +- CometFilter (169) + : +- CometScan parquet spark_catalog.default.time_dim (168) + +- ReusedExchange (175) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_sold_date_sk#4] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_hdemo_sk), IsNotNull(ss_sold_time_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(2) CometFilter +Input [4]: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_sold_date_sk#4] +Condition : ((isnotnull(ss_hdemo_sk#2) AND isnotnull(ss_sold_time_sk#1)) AND isnotnull(ss_store_sk#3)) + +(3) CometProject +Input [4]: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_sold_date_sk#4] +Arguments: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3], [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3] + +(4) ColumnarToRow [codegen id : 4] +Input [3]: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3] + +(5) Scan parquet spark_catalog.default.household_demographics +Output [3]: [hd_demo_sk#5, hd_dep_count#6, hd_vehicle_count#7] +Batched: true +Location [not included in comparison]/{warehouse_dir}/household_demographics] +PushedFilters: [Or(Or(And(EqualTo(hd_dep_count,4),LessThanOrEqual(hd_vehicle_count,6)),And(EqualTo(hd_dep_count,2),LessThanOrEqual(hd_vehicle_count,4))),And(EqualTo(hd_dep_count,0),LessThanOrEqual(hd_vehicle_count,2))), IsNotNull(hd_demo_sk)] +ReadSchema: struct + +(6) CometFilter +Input [3]: [hd_demo_sk#5, hd_dep_count#6, hd_vehicle_count#7] +Condition : (((((hd_dep_count#6 = 4) AND (hd_vehicle_count#7 <= 6)) OR ((hd_dep_count#6 = 2) AND (hd_vehicle_count#7 <= 4))) OR ((hd_dep_count#6 = 0) AND (hd_vehicle_count#7 <= 2))) AND isnotnull(hd_demo_sk#5)) + +(7) CometProject +Input [3]: [hd_demo_sk#5, hd_dep_count#6, hd_vehicle_count#7] +Arguments: [hd_demo_sk#5], [hd_demo_sk#5] + +(8) ColumnarToRow [codegen id : 1] +Input [1]: [hd_demo_sk#5] + +(9) BroadcastExchange +Input [1]: [hd_demo_sk#5] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(10) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_hdemo_sk#2] +Right keys [1]: [hd_demo_sk#5] +Join type: Inner +Join condition: None + +(11) Project [codegen id : 4] +Output [2]: [ss_sold_time_sk#1, ss_store_sk#3] +Input [4]: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3, hd_demo_sk#5] + +(12) Scan parquet spark_catalog.default.time_dim +Output [3]: [t_time_sk#8, t_hour#9, t_minute#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/time_dim] +PushedFilters: [IsNotNull(t_hour), IsNotNull(t_minute), EqualTo(t_hour,8), GreaterThanOrEqual(t_minute,30), IsNotNull(t_time_sk)] +ReadSchema: struct + +(13) CometFilter +Input [3]: [t_time_sk#8, t_hour#9, t_minute#10] +Condition : ((((isnotnull(t_hour#9) AND isnotnull(t_minute#10)) AND (t_hour#9 = 8)) AND (t_minute#10 >= 30)) AND isnotnull(t_time_sk#8)) + +(14) CometProject +Input [3]: [t_time_sk#8, t_hour#9, t_minute#10] +Arguments: [t_time_sk#8], [t_time_sk#8] + +(15) ColumnarToRow [codegen id : 2] +Input [1]: [t_time_sk#8] + +(16) BroadcastExchange +Input [1]: [t_time_sk#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(17) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_time_sk#1] +Right keys [1]: [t_time_sk#8] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 4] +Output [1]: [ss_store_sk#3] +Input [3]: [ss_sold_time_sk#1, ss_store_sk#3, t_time_sk#8] + +(19) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#11, s_store_name#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_name), EqualTo(s_store_name,ese), IsNotNull(s_store_sk)] +ReadSchema: struct + +(20) CometFilter +Input [2]: [s_store_sk#11, s_store_name#12] +Condition : ((isnotnull(s_store_name#12) AND (s_store_name#12 = ese)) AND isnotnull(s_store_sk#11)) + +(21) CometProject +Input [2]: [s_store_sk#11, s_store_name#12] +Arguments: [s_store_sk#11], [s_store_sk#11] + +(22) ColumnarToRow [codegen id : 3] +Input [1]: [s_store_sk#11] + +(23) BroadcastExchange +Input [1]: [s_store_sk#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_store_sk#3] +Right keys [1]: [s_store_sk#11] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 4] +Output: [] +Input [2]: [ss_store_sk#3, s_store_sk#11] + +(26) HashAggregate [codegen id : 4] +Input: [] +Keys: [] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#13] +Results [1]: [count#14] + +(27) Exchange +Input [1]: [count#14] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=4] + +(28) HashAggregate [codegen id : 40] +Input [1]: [count#14] +Keys: [] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#15] +Results [1]: [count(1)#15 AS h8_30_to_9#16] + +(29) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_sold_time_sk#17, ss_hdemo_sk#18, ss_store_sk#19, ss_sold_date_sk#20] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_hdemo_sk), IsNotNull(ss_sold_time_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(30) CometFilter +Input [4]: [ss_sold_time_sk#17, ss_hdemo_sk#18, ss_store_sk#19, ss_sold_date_sk#20] +Condition : ((isnotnull(ss_hdemo_sk#18) AND isnotnull(ss_sold_time_sk#17)) AND isnotnull(ss_store_sk#19)) + +(31) CometProject +Input [4]: [ss_sold_time_sk#17, ss_hdemo_sk#18, ss_store_sk#19, ss_sold_date_sk#20] +Arguments: [ss_sold_time_sk#17, ss_hdemo_sk#18, ss_store_sk#19], [ss_sold_time_sk#17, ss_hdemo_sk#18, ss_store_sk#19] + +(32) ColumnarToRow [codegen id : 8] +Input [3]: [ss_sold_time_sk#17, ss_hdemo_sk#18, ss_store_sk#19] + +(33) ReusedExchange [Reuses operator id: 9] +Output [1]: [hd_demo_sk#21] + +(34) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_hdemo_sk#18] +Right keys [1]: [hd_demo_sk#21] +Join type: Inner +Join condition: None + +(35) Project [codegen id : 8] +Output [2]: [ss_sold_time_sk#17, ss_store_sk#19] +Input [4]: [ss_sold_time_sk#17, ss_hdemo_sk#18, ss_store_sk#19, hd_demo_sk#21] + +(36) Scan parquet spark_catalog.default.time_dim +Output [3]: [t_time_sk#22, t_hour#23, t_minute#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/time_dim] +PushedFilters: [IsNotNull(t_hour), IsNotNull(t_minute), EqualTo(t_hour,9), LessThan(t_minute,30), IsNotNull(t_time_sk)] +ReadSchema: struct + +(37) CometFilter +Input [3]: [t_time_sk#22, t_hour#23, t_minute#24] +Condition : ((((isnotnull(t_hour#23) AND isnotnull(t_minute#24)) AND (t_hour#23 = 9)) AND (t_minute#24 < 30)) AND isnotnull(t_time_sk#22)) + +(38) CometProject +Input [3]: [t_time_sk#22, t_hour#23, t_minute#24] +Arguments: [t_time_sk#22], [t_time_sk#22] + +(39) ColumnarToRow [codegen id : 6] +Input [1]: [t_time_sk#22] + +(40) BroadcastExchange +Input [1]: [t_time_sk#22] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +(41) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_sold_time_sk#17] +Right keys [1]: [t_time_sk#22] +Join type: Inner +Join condition: None + +(42) Project [codegen id : 8] +Output [1]: [ss_store_sk#19] +Input [3]: [ss_sold_time_sk#17, ss_store_sk#19, t_time_sk#22] + +(43) ReusedExchange [Reuses operator id: 23] +Output [1]: [s_store_sk#25] + +(44) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_store_sk#19] +Right keys [1]: [s_store_sk#25] +Join type: Inner +Join condition: None + +(45) Project [codegen id : 8] +Output: [] +Input [2]: [ss_store_sk#19, s_store_sk#25] + +(46) HashAggregate [codegen id : 8] +Input: [] +Keys: [] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#26] +Results [1]: [count#27] + +(47) Exchange +Input [1]: [count#27] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=6] + +(48) HashAggregate [codegen id : 9] +Input [1]: [count#27] +Keys: [] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#28] +Results [1]: [count(1)#28 AS h9_to_9_30#29] + +(49) BroadcastExchange +Input [1]: [h9_to_9_30#29] +Arguments: IdentityBroadcastMode, [plan_id=7] + +(50) BroadcastNestedLoopJoin [codegen id : 40] +Join type: Inner +Join condition: None + +(51) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_sold_time_sk#30, ss_hdemo_sk#31, ss_store_sk#32, ss_sold_date_sk#33] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_hdemo_sk), IsNotNull(ss_sold_time_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(52) CometFilter +Input [4]: [ss_sold_time_sk#30, ss_hdemo_sk#31, ss_store_sk#32, ss_sold_date_sk#33] +Condition : ((isnotnull(ss_hdemo_sk#31) AND isnotnull(ss_sold_time_sk#30)) AND isnotnull(ss_store_sk#32)) + +(53) CometProject +Input [4]: [ss_sold_time_sk#30, ss_hdemo_sk#31, ss_store_sk#32, ss_sold_date_sk#33] +Arguments: [ss_sold_time_sk#30, ss_hdemo_sk#31, ss_store_sk#32], [ss_sold_time_sk#30, ss_hdemo_sk#31, ss_store_sk#32] + +(54) ColumnarToRow [codegen id : 13] +Input [3]: [ss_sold_time_sk#30, ss_hdemo_sk#31, ss_store_sk#32] + +(55) ReusedExchange [Reuses operator id: 9] +Output [1]: [hd_demo_sk#34] + +(56) BroadcastHashJoin [codegen id : 13] +Left keys [1]: [ss_hdemo_sk#31] +Right keys [1]: [hd_demo_sk#34] +Join type: Inner +Join condition: None + +(57) Project [codegen id : 13] +Output [2]: [ss_sold_time_sk#30, ss_store_sk#32] +Input [4]: [ss_sold_time_sk#30, ss_hdemo_sk#31, ss_store_sk#32, hd_demo_sk#34] + +(58) Scan parquet spark_catalog.default.time_dim +Output [3]: [t_time_sk#35, t_hour#36, t_minute#37] +Batched: true +Location [not included in comparison]/{warehouse_dir}/time_dim] +PushedFilters: [IsNotNull(t_hour), IsNotNull(t_minute), EqualTo(t_hour,9), GreaterThanOrEqual(t_minute,30), IsNotNull(t_time_sk)] +ReadSchema: struct + +(59) CometFilter +Input [3]: [t_time_sk#35, t_hour#36, t_minute#37] +Condition : ((((isnotnull(t_hour#36) AND isnotnull(t_minute#37)) AND (t_hour#36 = 9)) AND (t_minute#37 >= 30)) AND isnotnull(t_time_sk#35)) + +(60) CometProject +Input [3]: [t_time_sk#35, t_hour#36, t_minute#37] +Arguments: [t_time_sk#35], [t_time_sk#35] + +(61) ColumnarToRow [codegen id : 11] +Input [1]: [t_time_sk#35] + +(62) BroadcastExchange +Input [1]: [t_time_sk#35] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + +(63) BroadcastHashJoin [codegen id : 13] +Left keys [1]: [ss_sold_time_sk#30] +Right keys [1]: [t_time_sk#35] +Join type: Inner +Join condition: None + +(64) Project [codegen id : 13] +Output [1]: [ss_store_sk#32] +Input [3]: [ss_sold_time_sk#30, ss_store_sk#32, t_time_sk#35] + +(65) ReusedExchange [Reuses operator id: 23] +Output [1]: [s_store_sk#38] + +(66) BroadcastHashJoin [codegen id : 13] +Left keys [1]: [ss_store_sk#32] +Right keys [1]: [s_store_sk#38] +Join type: Inner +Join condition: None + +(67) Project [codegen id : 13] +Output: [] +Input [2]: [ss_store_sk#32, s_store_sk#38] + +(68) HashAggregate [codegen id : 13] +Input: [] +Keys: [] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#39] +Results [1]: [count#40] + +(69) Exchange +Input [1]: [count#40] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=9] + +(70) HashAggregate [codegen id : 14] +Input [1]: [count#40] +Keys: [] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#41] +Results [1]: [count(1)#41 AS h9_30_to_10#42] + +(71) BroadcastExchange +Input [1]: [h9_30_to_10#42] +Arguments: IdentityBroadcastMode, [plan_id=10] + +(72) BroadcastNestedLoopJoin [codegen id : 40] +Join type: Inner +Join condition: None + +(73) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_sold_time_sk#43, ss_hdemo_sk#44, ss_store_sk#45, ss_sold_date_sk#46] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_hdemo_sk), IsNotNull(ss_sold_time_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(74) CometFilter +Input [4]: [ss_sold_time_sk#43, ss_hdemo_sk#44, ss_store_sk#45, ss_sold_date_sk#46] +Condition : ((isnotnull(ss_hdemo_sk#44) AND isnotnull(ss_sold_time_sk#43)) AND isnotnull(ss_store_sk#45)) + +(75) CometProject +Input [4]: [ss_sold_time_sk#43, ss_hdemo_sk#44, ss_store_sk#45, ss_sold_date_sk#46] +Arguments: [ss_sold_time_sk#43, ss_hdemo_sk#44, ss_store_sk#45], [ss_sold_time_sk#43, ss_hdemo_sk#44, ss_store_sk#45] + +(76) ColumnarToRow [codegen id : 18] +Input [3]: [ss_sold_time_sk#43, ss_hdemo_sk#44, ss_store_sk#45] + +(77) ReusedExchange [Reuses operator id: 9] +Output [1]: [hd_demo_sk#47] + +(78) BroadcastHashJoin [codegen id : 18] +Left keys [1]: [ss_hdemo_sk#44] +Right keys [1]: [hd_demo_sk#47] +Join type: Inner +Join condition: None + +(79) Project [codegen id : 18] +Output [2]: [ss_sold_time_sk#43, ss_store_sk#45] +Input [4]: [ss_sold_time_sk#43, ss_hdemo_sk#44, ss_store_sk#45, hd_demo_sk#47] + +(80) Scan parquet spark_catalog.default.time_dim +Output [3]: [t_time_sk#48, t_hour#49, t_minute#50] +Batched: true +Location [not included in comparison]/{warehouse_dir}/time_dim] +PushedFilters: [IsNotNull(t_hour), IsNotNull(t_minute), EqualTo(t_hour,10), LessThan(t_minute,30), IsNotNull(t_time_sk)] +ReadSchema: struct + +(81) CometFilter +Input [3]: [t_time_sk#48, t_hour#49, t_minute#50] +Condition : ((((isnotnull(t_hour#49) AND isnotnull(t_minute#50)) AND (t_hour#49 = 10)) AND (t_minute#50 < 30)) AND isnotnull(t_time_sk#48)) + +(82) CometProject +Input [3]: [t_time_sk#48, t_hour#49, t_minute#50] +Arguments: [t_time_sk#48], [t_time_sk#48] + +(83) ColumnarToRow [codegen id : 16] +Input [1]: [t_time_sk#48] + +(84) BroadcastExchange +Input [1]: [t_time_sk#48] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=11] + +(85) BroadcastHashJoin [codegen id : 18] +Left keys [1]: [ss_sold_time_sk#43] +Right keys [1]: [t_time_sk#48] +Join type: Inner +Join condition: None + +(86) Project [codegen id : 18] +Output [1]: [ss_store_sk#45] +Input [3]: [ss_sold_time_sk#43, ss_store_sk#45, t_time_sk#48] + +(87) ReusedExchange [Reuses operator id: 23] +Output [1]: [s_store_sk#51] + +(88) BroadcastHashJoin [codegen id : 18] +Left keys [1]: [ss_store_sk#45] +Right keys [1]: [s_store_sk#51] +Join type: Inner +Join condition: None + +(89) Project [codegen id : 18] +Output: [] +Input [2]: [ss_store_sk#45, s_store_sk#51] + +(90) HashAggregate [codegen id : 18] +Input: [] +Keys: [] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#52] +Results [1]: [count#53] + +(91) Exchange +Input [1]: [count#53] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=12] + +(92) HashAggregate [codegen id : 19] +Input [1]: [count#53] +Keys: [] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#54] +Results [1]: [count(1)#54 AS h10_to_10_30#55] + +(93) BroadcastExchange +Input [1]: [h10_to_10_30#55] +Arguments: IdentityBroadcastMode, [plan_id=13] + +(94) BroadcastNestedLoopJoin [codegen id : 40] +Join type: Inner +Join condition: None + +(95) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_sold_time_sk#56, ss_hdemo_sk#57, ss_store_sk#58, ss_sold_date_sk#59] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_hdemo_sk), IsNotNull(ss_sold_time_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(96) CometFilter +Input [4]: [ss_sold_time_sk#56, ss_hdemo_sk#57, ss_store_sk#58, ss_sold_date_sk#59] +Condition : ((isnotnull(ss_hdemo_sk#57) AND isnotnull(ss_sold_time_sk#56)) AND isnotnull(ss_store_sk#58)) + +(97) CometProject +Input [4]: [ss_sold_time_sk#56, ss_hdemo_sk#57, ss_store_sk#58, ss_sold_date_sk#59] +Arguments: [ss_sold_time_sk#56, ss_hdemo_sk#57, ss_store_sk#58], [ss_sold_time_sk#56, ss_hdemo_sk#57, ss_store_sk#58] + +(98) ColumnarToRow [codegen id : 23] +Input [3]: [ss_sold_time_sk#56, ss_hdemo_sk#57, ss_store_sk#58] + +(99) ReusedExchange [Reuses operator id: 9] +Output [1]: [hd_demo_sk#60] + +(100) BroadcastHashJoin [codegen id : 23] +Left keys [1]: [ss_hdemo_sk#57] +Right keys [1]: [hd_demo_sk#60] +Join type: Inner +Join condition: None + +(101) Project [codegen id : 23] +Output [2]: [ss_sold_time_sk#56, ss_store_sk#58] +Input [4]: [ss_sold_time_sk#56, ss_hdemo_sk#57, ss_store_sk#58, hd_demo_sk#60] + +(102) Scan parquet spark_catalog.default.time_dim +Output [3]: [t_time_sk#61, t_hour#62, t_minute#63] +Batched: true +Location [not included in comparison]/{warehouse_dir}/time_dim] +PushedFilters: [IsNotNull(t_hour), IsNotNull(t_minute), EqualTo(t_hour,10), GreaterThanOrEqual(t_minute,30), IsNotNull(t_time_sk)] +ReadSchema: struct + +(103) CometFilter +Input [3]: [t_time_sk#61, t_hour#62, t_minute#63] +Condition : ((((isnotnull(t_hour#62) AND isnotnull(t_minute#63)) AND (t_hour#62 = 10)) AND (t_minute#63 >= 30)) AND isnotnull(t_time_sk#61)) + +(104) CometProject +Input [3]: [t_time_sk#61, t_hour#62, t_minute#63] +Arguments: [t_time_sk#61], [t_time_sk#61] + +(105) ColumnarToRow [codegen id : 21] +Input [1]: [t_time_sk#61] + +(106) BroadcastExchange +Input [1]: [t_time_sk#61] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=14] + +(107) BroadcastHashJoin [codegen id : 23] +Left keys [1]: [ss_sold_time_sk#56] +Right keys [1]: [t_time_sk#61] +Join type: Inner +Join condition: None + +(108) Project [codegen id : 23] +Output [1]: [ss_store_sk#58] +Input [3]: [ss_sold_time_sk#56, ss_store_sk#58, t_time_sk#61] + +(109) ReusedExchange [Reuses operator id: 23] +Output [1]: [s_store_sk#64] + +(110) BroadcastHashJoin [codegen id : 23] +Left keys [1]: [ss_store_sk#58] +Right keys [1]: [s_store_sk#64] +Join type: Inner +Join condition: None + +(111) Project [codegen id : 23] +Output: [] +Input [2]: [ss_store_sk#58, s_store_sk#64] + +(112) HashAggregate [codegen id : 23] +Input: [] +Keys: [] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#65] +Results [1]: [count#66] + +(113) Exchange +Input [1]: [count#66] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=15] + +(114) HashAggregate [codegen id : 24] +Input [1]: [count#66] +Keys: [] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#67] +Results [1]: [count(1)#67 AS h10_30_to_11#68] + +(115) BroadcastExchange +Input [1]: [h10_30_to_11#68] +Arguments: IdentityBroadcastMode, [plan_id=16] + +(116) BroadcastNestedLoopJoin [codegen id : 40] +Join type: Inner +Join condition: None + +(117) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_sold_time_sk#69, ss_hdemo_sk#70, ss_store_sk#71, ss_sold_date_sk#72] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_hdemo_sk), IsNotNull(ss_sold_time_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(118) CometFilter +Input [4]: [ss_sold_time_sk#69, ss_hdemo_sk#70, ss_store_sk#71, ss_sold_date_sk#72] +Condition : ((isnotnull(ss_hdemo_sk#70) AND isnotnull(ss_sold_time_sk#69)) AND isnotnull(ss_store_sk#71)) + +(119) CometProject +Input [4]: [ss_sold_time_sk#69, ss_hdemo_sk#70, ss_store_sk#71, ss_sold_date_sk#72] +Arguments: [ss_sold_time_sk#69, ss_hdemo_sk#70, ss_store_sk#71], [ss_sold_time_sk#69, ss_hdemo_sk#70, ss_store_sk#71] + +(120) ColumnarToRow [codegen id : 28] +Input [3]: [ss_sold_time_sk#69, ss_hdemo_sk#70, ss_store_sk#71] + +(121) ReusedExchange [Reuses operator id: 9] +Output [1]: [hd_demo_sk#73] + +(122) BroadcastHashJoin [codegen id : 28] +Left keys [1]: [ss_hdemo_sk#70] +Right keys [1]: [hd_demo_sk#73] +Join type: Inner +Join condition: None + +(123) Project [codegen id : 28] +Output [2]: [ss_sold_time_sk#69, ss_store_sk#71] +Input [4]: [ss_sold_time_sk#69, ss_hdemo_sk#70, ss_store_sk#71, hd_demo_sk#73] + +(124) Scan parquet spark_catalog.default.time_dim +Output [3]: [t_time_sk#74, t_hour#75, t_minute#76] +Batched: true +Location [not included in comparison]/{warehouse_dir}/time_dim] +PushedFilters: [IsNotNull(t_hour), IsNotNull(t_minute), EqualTo(t_hour,11), LessThan(t_minute,30), IsNotNull(t_time_sk)] +ReadSchema: struct + +(125) CometFilter +Input [3]: [t_time_sk#74, t_hour#75, t_minute#76] +Condition : ((((isnotnull(t_hour#75) AND isnotnull(t_minute#76)) AND (t_hour#75 = 11)) AND (t_minute#76 < 30)) AND isnotnull(t_time_sk#74)) + +(126) CometProject +Input [3]: [t_time_sk#74, t_hour#75, t_minute#76] +Arguments: [t_time_sk#74], [t_time_sk#74] + +(127) ColumnarToRow [codegen id : 26] +Input [1]: [t_time_sk#74] + +(128) BroadcastExchange +Input [1]: [t_time_sk#74] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=17] + +(129) BroadcastHashJoin [codegen id : 28] +Left keys [1]: [ss_sold_time_sk#69] +Right keys [1]: [t_time_sk#74] +Join type: Inner +Join condition: None + +(130) Project [codegen id : 28] +Output [1]: [ss_store_sk#71] +Input [3]: [ss_sold_time_sk#69, ss_store_sk#71, t_time_sk#74] + +(131) ReusedExchange [Reuses operator id: 23] +Output [1]: [s_store_sk#77] + +(132) BroadcastHashJoin [codegen id : 28] +Left keys [1]: [ss_store_sk#71] +Right keys [1]: [s_store_sk#77] +Join type: Inner +Join condition: None + +(133) Project [codegen id : 28] +Output: [] +Input [2]: [ss_store_sk#71, s_store_sk#77] + +(134) HashAggregate [codegen id : 28] +Input: [] +Keys: [] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#78] +Results [1]: [count#79] + +(135) Exchange +Input [1]: [count#79] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=18] + +(136) HashAggregate [codegen id : 29] +Input [1]: [count#79] +Keys: [] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#80] +Results [1]: [count(1)#80 AS h11_to_11_30#81] + +(137) BroadcastExchange +Input [1]: [h11_to_11_30#81] +Arguments: IdentityBroadcastMode, [plan_id=19] + +(138) BroadcastNestedLoopJoin [codegen id : 40] +Join type: Inner +Join condition: None + +(139) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_sold_time_sk#82, ss_hdemo_sk#83, ss_store_sk#84, ss_sold_date_sk#85] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_hdemo_sk), IsNotNull(ss_sold_time_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(140) CometFilter +Input [4]: [ss_sold_time_sk#82, ss_hdemo_sk#83, ss_store_sk#84, ss_sold_date_sk#85] +Condition : ((isnotnull(ss_hdemo_sk#83) AND isnotnull(ss_sold_time_sk#82)) AND isnotnull(ss_store_sk#84)) + +(141) CometProject +Input [4]: [ss_sold_time_sk#82, ss_hdemo_sk#83, ss_store_sk#84, ss_sold_date_sk#85] +Arguments: [ss_sold_time_sk#82, ss_hdemo_sk#83, ss_store_sk#84], [ss_sold_time_sk#82, ss_hdemo_sk#83, ss_store_sk#84] + +(142) ColumnarToRow [codegen id : 33] +Input [3]: [ss_sold_time_sk#82, ss_hdemo_sk#83, ss_store_sk#84] + +(143) ReusedExchange [Reuses operator id: 9] +Output [1]: [hd_demo_sk#86] + +(144) BroadcastHashJoin [codegen id : 33] +Left keys [1]: [ss_hdemo_sk#83] +Right keys [1]: [hd_demo_sk#86] +Join type: Inner +Join condition: None + +(145) Project [codegen id : 33] +Output [2]: [ss_sold_time_sk#82, ss_store_sk#84] +Input [4]: [ss_sold_time_sk#82, ss_hdemo_sk#83, ss_store_sk#84, hd_demo_sk#86] + +(146) Scan parquet spark_catalog.default.time_dim +Output [3]: [t_time_sk#87, t_hour#88, t_minute#89] +Batched: true +Location [not included in comparison]/{warehouse_dir}/time_dim] +PushedFilters: [IsNotNull(t_hour), IsNotNull(t_minute), EqualTo(t_hour,11), GreaterThanOrEqual(t_minute,30), IsNotNull(t_time_sk)] +ReadSchema: struct + +(147) CometFilter +Input [3]: [t_time_sk#87, t_hour#88, t_minute#89] +Condition : ((((isnotnull(t_hour#88) AND isnotnull(t_minute#89)) AND (t_hour#88 = 11)) AND (t_minute#89 >= 30)) AND isnotnull(t_time_sk#87)) + +(148) CometProject +Input [3]: [t_time_sk#87, t_hour#88, t_minute#89] +Arguments: [t_time_sk#87], [t_time_sk#87] + +(149) ColumnarToRow [codegen id : 31] +Input [1]: [t_time_sk#87] + +(150) BroadcastExchange +Input [1]: [t_time_sk#87] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=20] + +(151) BroadcastHashJoin [codegen id : 33] +Left keys [1]: [ss_sold_time_sk#82] +Right keys [1]: [t_time_sk#87] +Join type: Inner +Join condition: None + +(152) Project [codegen id : 33] +Output [1]: [ss_store_sk#84] +Input [3]: [ss_sold_time_sk#82, ss_store_sk#84, t_time_sk#87] + +(153) ReusedExchange [Reuses operator id: 23] +Output [1]: [s_store_sk#90] + +(154) BroadcastHashJoin [codegen id : 33] +Left keys [1]: [ss_store_sk#84] +Right keys [1]: [s_store_sk#90] +Join type: Inner +Join condition: None + +(155) Project [codegen id : 33] +Output: [] +Input [2]: [ss_store_sk#84, s_store_sk#90] + +(156) HashAggregate [codegen id : 33] +Input: [] +Keys: [] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#91] +Results [1]: [count#92] + +(157) Exchange +Input [1]: [count#92] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=21] + +(158) HashAggregate [codegen id : 34] +Input [1]: [count#92] +Keys: [] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#93] +Results [1]: [count(1)#93 AS h11_30_to_12#94] + +(159) BroadcastExchange +Input [1]: [h11_30_to_12#94] +Arguments: IdentityBroadcastMode, [plan_id=22] + +(160) BroadcastNestedLoopJoin [codegen id : 40] +Join type: Inner +Join condition: None + +(161) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_sold_time_sk#95, ss_hdemo_sk#96, ss_store_sk#97, ss_sold_date_sk#98] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_hdemo_sk), IsNotNull(ss_sold_time_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(162) CometFilter +Input [4]: [ss_sold_time_sk#95, ss_hdemo_sk#96, ss_store_sk#97, ss_sold_date_sk#98] +Condition : ((isnotnull(ss_hdemo_sk#96) AND isnotnull(ss_sold_time_sk#95)) AND isnotnull(ss_store_sk#97)) + +(163) CometProject +Input [4]: [ss_sold_time_sk#95, ss_hdemo_sk#96, ss_store_sk#97, ss_sold_date_sk#98] +Arguments: [ss_sold_time_sk#95, ss_hdemo_sk#96, ss_store_sk#97], [ss_sold_time_sk#95, ss_hdemo_sk#96, ss_store_sk#97] + +(164) ColumnarToRow [codegen id : 38] +Input [3]: [ss_sold_time_sk#95, ss_hdemo_sk#96, ss_store_sk#97] + +(165) ReusedExchange [Reuses operator id: 9] +Output [1]: [hd_demo_sk#99] + +(166) BroadcastHashJoin [codegen id : 38] +Left keys [1]: [ss_hdemo_sk#96] +Right keys [1]: [hd_demo_sk#99] +Join type: Inner +Join condition: None + +(167) Project [codegen id : 38] +Output [2]: [ss_sold_time_sk#95, ss_store_sk#97] +Input [4]: [ss_sold_time_sk#95, ss_hdemo_sk#96, ss_store_sk#97, hd_demo_sk#99] + +(168) Scan parquet spark_catalog.default.time_dim +Output [3]: [t_time_sk#100, t_hour#101, t_minute#102] +Batched: true +Location [not included in comparison]/{warehouse_dir}/time_dim] +PushedFilters: [IsNotNull(t_hour), IsNotNull(t_minute), EqualTo(t_hour,12), LessThan(t_minute,30), IsNotNull(t_time_sk)] +ReadSchema: struct + +(169) CometFilter +Input [3]: [t_time_sk#100, t_hour#101, t_minute#102] +Condition : ((((isnotnull(t_hour#101) AND isnotnull(t_minute#102)) AND (t_hour#101 = 12)) AND (t_minute#102 < 30)) AND isnotnull(t_time_sk#100)) + +(170) CometProject +Input [3]: [t_time_sk#100, t_hour#101, t_minute#102] +Arguments: [t_time_sk#100], [t_time_sk#100] + +(171) ColumnarToRow [codegen id : 36] +Input [1]: [t_time_sk#100] + +(172) BroadcastExchange +Input [1]: [t_time_sk#100] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=23] + +(173) BroadcastHashJoin [codegen id : 38] +Left keys [1]: [ss_sold_time_sk#95] +Right keys [1]: [t_time_sk#100] +Join type: Inner +Join condition: None + +(174) Project [codegen id : 38] +Output [1]: [ss_store_sk#97] +Input [3]: [ss_sold_time_sk#95, ss_store_sk#97, t_time_sk#100] + +(175) ReusedExchange [Reuses operator id: 23] +Output [1]: [s_store_sk#103] + +(176) BroadcastHashJoin [codegen id : 38] +Left keys [1]: [ss_store_sk#97] +Right keys [1]: [s_store_sk#103] +Join type: Inner +Join condition: None + +(177) Project [codegen id : 38] +Output: [] +Input [2]: [ss_store_sk#97, s_store_sk#103] + +(178) HashAggregate [codegen id : 38] +Input: [] +Keys: [] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#104] +Results [1]: [count#105] + +(179) Exchange +Input [1]: [count#105] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=24] + +(180) HashAggregate [codegen id : 39] +Input [1]: [count#105] +Keys: [] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#106] +Results [1]: [count(1)#106 AS h12_to_12_30#107] + +(181) BroadcastExchange +Input [1]: [h12_to_12_30#107] +Arguments: IdentityBroadcastMode, [plan_id=25] + +(182) BroadcastNestedLoopJoin [codegen id : 40] +Join type: Inner +Join condition: None + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q88/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q88/simplified.txt new file mode 100644 index 0000000000..b497e0bab6 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q88/simplified.txt @@ -0,0 +1,265 @@ +WholeStageCodegen (40) + BroadcastNestedLoopJoin + BroadcastNestedLoopJoin + BroadcastNestedLoopJoin + BroadcastNestedLoopJoin + BroadcastNestedLoopJoin + BroadcastNestedLoopJoin + BroadcastNestedLoopJoin + HashAggregate [count] [count(1),h8_30_to_9,count] + InputAdapter + Exchange #1 + WholeStageCodegen (4) + HashAggregate [count,count] + Project + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_store_sk] + BroadcastHashJoin [ss_sold_time_sk,t_time_sk] + Project [ss_sold_time_sk,ss_store_sk] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + ColumnarToRow + InputAdapter + CometProject [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] + CometFilter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk,ss_sold_date_sk] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [hd_demo_sk] + CometFilter [hd_dep_count,hd_vehicle_count,hd_demo_sk] + CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_dep_count,hd_vehicle_count] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometProject [t_time_sk] + CometFilter [t_hour,t_minute,t_time_sk] + CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour,t_minute] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometProject [s_store_sk] + CometFilter [s_store_name,s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (9) + HashAggregate [count] [count(1),h9_to_9_30,count] + InputAdapter + Exchange #6 + WholeStageCodegen (8) + HashAggregate [count,count] + Project + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_store_sk] + BroadcastHashJoin [ss_sold_time_sk,t_time_sk] + Project [ss_sold_time_sk,ss_store_sk] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + ColumnarToRow + InputAdapter + CometProject [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] + CometFilter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk,ss_sold_date_sk] + InputAdapter + ReusedExchange [hd_demo_sk] #2 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (6) + ColumnarToRow + InputAdapter + CometProject [t_time_sk] + CometFilter [t_hour,t_minute,t_time_sk] + CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour,t_minute] + InputAdapter + ReusedExchange [s_store_sk] #4 + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (14) + HashAggregate [count] [count(1),h9_30_to_10,count] + InputAdapter + Exchange #9 + WholeStageCodegen (13) + HashAggregate [count,count] + Project + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_store_sk] + BroadcastHashJoin [ss_sold_time_sk,t_time_sk] + Project [ss_sold_time_sk,ss_store_sk] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + ColumnarToRow + InputAdapter + CometProject [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] + CometFilter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk,ss_sold_date_sk] + InputAdapter + ReusedExchange [hd_demo_sk] #2 + InputAdapter + BroadcastExchange #10 + WholeStageCodegen (11) + ColumnarToRow + InputAdapter + CometProject [t_time_sk] + CometFilter [t_hour,t_minute,t_time_sk] + CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour,t_minute] + InputAdapter + ReusedExchange [s_store_sk] #4 + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (19) + HashAggregate [count] [count(1),h10_to_10_30,count] + InputAdapter + Exchange #12 + WholeStageCodegen (18) + HashAggregate [count,count] + Project + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_store_sk] + BroadcastHashJoin [ss_sold_time_sk,t_time_sk] + Project [ss_sold_time_sk,ss_store_sk] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + ColumnarToRow + InputAdapter + CometProject [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] + CometFilter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk,ss_sold_date_sk] + InputAdapter + ReusedExchange [hd_demo_sk] #2 + InputAdapter + BroadcastExchange #13 + WholeStageCodegen (16) + ColumnarToRow + InputAdapter + CometProject [t_time_sk] + CometFilter [t_hour,t_minute,t_time_sk] + CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour,t_minute] + InputAdapter + ReusedExchange [s_store_sk] #4 + InputAdapter + BroadcastExchange #14 + WholeStageCodegen (24) + HashAggregate [count] [count(1),h10_30_to_11,count] + InputAdapter + Exchange #15 + WholeStageCodegen (23) + HashAggregate [count,count] + Project + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_store_sk] + BroadcastHashJoin [ss_sold_time_sk,t_time_sk] + Project [ss_sold_time_sk,ss_store_sk] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + ColumnarToRow + InputAdapter + CometProject [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] + CometFilter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk,ss_sold_date_sk] + InputAdapter + ReusedExchange [hd_demo_sk] #2 + InputAdapter + BroadcastExchange #16 + WholeStageCodegen (21) + ColumnarToRow + InputAdapter + CometProject [t_time_sk] + CometFilter [t_hour,t_minute,t_time_sk] + CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour,t_minute] + InputAdapter + ReusedExchange [s_store_sk] #4 + InputAdapter + BroadcastExchange #17 + WholeStageCodegen (29) + HashAggregate [count] [count(1),h11_to_11_30,count] + InputAdapter + Exchange #18 + WholeStageCodegen (28) + HashAggregate [count,count] + Project + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_store_sk] + BroadcastHashJoin [ss_sold_time_sk,t_time_sk] + Project [ss_sold_time_sk,ss_store_sk] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + ColumnarToRow + InputAdapter + CometProject [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] + CometFilter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk,ss_sold_date_sk] + InputAdapter + ReusedExchange [hd_demo_sk] #2 + InputAdapter + BroadcastExchange #19 + WholeStageCodegen (26) + ColumnarToRow + InputAdapter + CometProject [t_time_sk] + CometFilter [t_hour,t_minute,t_time_sk] + CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour,t_minute] + InputAdapter + ReusedExchange [s_store_sk] #4 + InputAdapter + BroadcastExchange #20 + WholeStageCodegen (34) + HashAggregate [count] [count(1),h11_30_to_12,count] + InputAdapter + Exchange #21 + WholeStageCodegen (33) + HashAggregate [count,count] + Project + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_store_sk] + BroadcastHashJoin [ss_sold_time_sk,t_time_sk] + Project [ss_sold_time_sk,ss_store_sk] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + ColumnarToRow + InputAdapter + CometProject [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] + CometFilter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk,ss_sold_date_sk] + InputAdapter + ReusedExchange [hd_demo_sk] #2 + InputAdapter + BroadcastExchange #22 + WholeStageCodegen (31) + ColumnarToRow + InputAdapter + CometProject [t_time_sk] + CometFilter [t_hour,t_minute,t_time_sk] + CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour,t_minute] + InputAdapter + ReusedExchange [s_store_sk] #4 + InputAdapter + BroadcastExchange #23 + WholeStageCodegen (39) + HashAggregate [count] [count(1),h12_to_12_30,count] + InputAdapter + Exchange #24 + WholeStageCodegen (38) + HashAggregate [count,count] + Project + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_store_sk] + BroadcastHashJoin [ss_sold_time_sk,t_time_sk] + Project [ss_sold_time_sk,ss_store_sk] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + ColumnarToRow + InputAdapter + CometProject [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] + CometFilter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk,ss_sold_date_sk] + InputAdapter + ReusedExchange [hd_demo_sk] #2 + InputAdapter + BroadcastExchange #25 + WholeStageCodegen (36) + ColumnarToRow + InputAdapter + CometProject [t_time_sk] + CometFilter [t_hour,t_minute,t_time_sk] + CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour,t_minute] + InputAdapter + ReusedExchange [s_store_sk] #4 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q89/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q89/explain.txt new file mode 100644 index 0000000000..3657266e23 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q89/explain.txt @@ -0,0 +1,189 @@ +== Physical Plan == +TakeOrderedAndProject (27) ++- * Project (26) + +- * Filter (25) + +- Window (24) + +- * Sort (23) + +- Exchange (22) + +- * HashAggregate (21) + +- Exchange (20) + +- * HashAggregate (19) + +- * Project (18) + +- * BroadcastHashJoin Inner BuildRight (17) + :- * Project (12) + : +- * BroadcastHashJoin Inner BuildRight (11) + : :- * Project (9) + : : +- * BroadcastHashJoin Inner BuildRight (8) + : : :- * ColumnarToRow (3) + : : : +- CometFilter (2) + : : : +- CometScan parquet spark_catalog.default.item (1) + : : +- BroadcastExchange (7) + : : +- * ColumnarToRow (6) + : : +- CometFilter (5) + : : +- CometScan parquet spark_catalog.default.store_sales (4) + : +- ReusedExchange (10) + +- BroadcastExchange (16) + +- * ColumnarToRow (15) + +- CometFilter (14) + +- CometScan parquet spark_catalog.default.store (13) + + +(1) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [Or(And(In(i_category, [Books ,Electronics ,Sports ]),In(i_class, [computers ,football ,stereo ])),And(In(i_category, [Jewelry ,Men ,Women ]),In(i_class, [birdal ,dresses ,shirts ]))), IsNotNull(i_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [4]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4] +Condition : (((i_category#4 IN (Books ,Electronics ,Sports ) AND i_class#3 IN (computers ,stereo ,football )) OR (i_category#4 IN (Men ,Jewelry ,Women ) AND i_class#3 IN (shirts ,birdal ,dresses ))) AND isnotnull(i_item_sk#1)) + +(3) ColumnarToRow [codegen id : 4] +Input [4]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4] + +(4) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#5, ss_store_sk#6, ss_sales_price#7, ss_sold_date_sk#8] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#8), dynamicpruningexpression(ss_sold_date_sk#8 IN dynamicpruning#9)] +PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(5) CometFilter +Input [4]: [ss_item_sk#5, ss_store_sk#6, ss_sales_price#7, ss_sold_date_sk#8] +Condition : (isnotnull(ss_item_sk#5) AND isnotnull(ss_store_sk#6)) + +(6) ColumnarToRow [codegen id : 1] +Input [4]: [ss_item_sk#5, ss_store_sk#6, ss_sales_price#7, ss_sold_date_sk#8] + +(7) BroadcastExchange +Input [4]: [ss_item_sk#5, ss_store_sk#6, ss_sales_price#7, ss_sold_date_sk#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [i_item_sk#1] +Right keys [1]: [ss_item_sk#5] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 4] +Output [6]: [i_brand#2, i_class#3, i_category#4, ss_store_sk#6, ss_sales_price#7, ss_sold_date_sk#8] +Input [8]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4, ss_item_sk#5, ss_store_sk#6, ss_sales_price#7, ss_sold_date_sk#8] + +(10) ReusedExchange [Reuses operator id: 32] +Output [2]: [d_date_sk#10, d_moy#11] + +(11) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_date_sk#8] +Right keys [1]: [d_date_sk#10] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 4] +Output [6]: [i_brand#2, i_class#3, i_category#4, ss_store_sk#6, ss_sales_price#7, d_moy#11] +Input [8]: [i_brand#2, i_class#3, i_category#4, ss_store_sk#6, ss_sales_price#7, ss_sold_date_sk#8, d_date_sk#10, d_moy#11] + +(13) Scan parquet spark_catalog.default.store +Output [3]: [s_store_sk#12, s_store_name#13, s_company_name#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(14) CometFilter +Input [3]: [s_store_sk#12, s_store_name#13, s_company_name#14] +Condition : isnotnull(s_store_sk#12) + +(15) ColumnarToRow [codegen id : 3] +Input [3]: [s_store_sk#12, s_store_name#13, s_company_name#14] + +(16) BroadcastExchange +Input [3]: [s_store_sk#12, s_store_name#13, s_company_name#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(17) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_store_sk#6] +Right keys [1]: [s_store_sk#12] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 4] +Output [7]: [i_brand#2, i_class#3, i_category#4, ss_sales_price#7, d_moy#11, s_store_name#13, s_company_name#14] +Input [9]: [i_brand#2, i_class#3, i_category#4, ss_store_sk#6, ss_sales_price#7, d_moy#11, s_store_sk#12, s_store_name#13, s_company_name#14] + +(19) HashAggregate [codegen id : 4] +Input [7]: [i_brand#2, i_class#3, i_category#4, ss_sales_price#7, d_moy#11, s_store_name#13, s_company_name#14] +Keys [6]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11] +Functions [1]: [partial_sum(UnscaledValue(ss_sales_price#7))] +Aggregate Attributes [1]: [sum#15] +Results [7]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum#16] + +(20) Exchange +Input [7]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum#16] +Arguments: hashpartitioning(i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(21) HashAggregate [codegen id : 5] +Input [7]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum#16] +Keys [6]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11] +Functions [1]: [sum(UnscaledValue(ss_sales_price#7))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_sales_price#7))#17] +Results [8]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, MakeDecimal(sum(UnscaledValue(ss_sales_price#7))#17,17,2) AS sum_sales#18, MakeDecimal(sum(UnscaledValue(ss_sales_price#7))#17,17,2) AS _w0#19] + +(22) Exchange +Input [8]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum_sales#18, _w0#19] +Arguments: hashpartitioning(i_category#4, i_brand#2, s_store_name#13, s_company_name#14, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(23) Sort [codegen id : 6] +Input [8]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum_sales#18, _w0#19] +Arguments: [i_category#4 ASC NULLS FIRST, i_brand#2 ASC NULLS FIRST, s_store_name#13 ASC NULLS FIRST, s_company_name#14 ASC NULLS FIRST], false, 0 + +(24) Window +Input [8]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum_sales#18, _w0#19] +Arguments: [avg(_w0#19) windowspecdefinition(i_category#4, i_brand#2, s_store_name#13, s_company_name#14, specifiedwindowframe(RowFrame, unboundedpreceding$(), unboundedfollowing$())) AS avg_monthly_sales#20], [i_category#4, i_brand#2, s_store_name#13, s_company_name#14] + +(25) Filter [codegen id : 7] +Input [9]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum_sales#18, _w0#19, avg_monthly_sales#20] +Condition : CASE WHEN NOT (avg_monthly_sales#20 = 0.000000) THEN ((abs((sum_sales#18 - avg_monthly_sales#20)) / avg_monthly_sales#20) > 0.1000000000000000) END + +(26) Project [codegen id : 7] +Output [8]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum_sales#18, avg_monthly_sales#20] +Input [9]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum_sales#18, _w0#19, avg_monthly_sales#20] + +(27) TakeOrderedAndProject +Input [8]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum_sales#18, avg_monthly_sales#20] +Arguments: 100, [(sum_sales#18 - avg_monthly_sales#20) ASC NULLS FIRST, s_store_name#13 ASC NULLS FIRST], [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum_sales#18, avg_monthly_sales#20] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#8 IN dynamicpruning#9 +BroadcastExchange (32) ++- * ColumnarToRow (31) + +- CometProject (30) + +- CometFilter (29) + +- CometScan parquet spark_catalog.default.date_dim (28) + + +(28) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#10, d_year#21, d_moy#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,1999), IsNotNull(d_date_sk)] +ReadSchema: struct + +(29) CometFilter +Input [3]: [d_date_sk#10, d_year#21, d_moy#11] +Condition : ((isnotnull(d_year#21) AND (d_year#21 = 1999)) AND isnotnull(d_date_sk#10)) + +(30) CometProject +Input [3]: [d_date_sk#10, d_year#21, d_moy#11] +Arguments: [d_date_sk#10, d_moy#11], [d_date_sk#10, d_moy#11] + +(31) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#10, d_moy#11] + +(32) BroadcastExchange +Input [2]: [d_date_sk#10, d_moy#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q89/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q89/simplified.txt new file mode 100644 index 0000000000..bb9e4e17e2 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q89/simplified.txt @@ -0,0 +1,50 @@ +TakeOrderedAndProject [sum_sales,avg_monthly_sales,s_store_name,i_category,i_class,i_brand,s_company_name,d_moy] + WholeStageCodegen (7) + Project [i_category,i_class,i_brand,s_store_name,s_company_name,d_moy,sum_sales,avg_monthly_sales] + Filter [avg_monthly_sales,sum_sales] + InputAdapter + Window [_w0,i_category,i_brand,s_store_name,s_company_name] + WholeStageCodegen (6) + Sort [i_category,i_brand,s_store_name,s_company_name] + InputAdapter + Exchange [i_category,i_brand,s_store_name,s_company_name] #1 + WholeStageCodegen (5) + HashAggregate [i_category,i_class,i_brand,s_store_name,s_company_name,d_moy,sum] [sum(UnscaledValue(ss_sales_price)),sum_sales,_w0,sum] + InputAdapter + Exchange [i_category,i_class,i_brand,s_store_name,s_company_name,d_moy] #2 + WholeStageCodegen (4) + HashAggregate [i_category,i_class,i_brand,s_store_name,s_company_name,d_moy,ss_sales_price] [sum,sum] + Project [i_brand,i_class,i_category,ss_sales_price,d_moy,s_store_name,s_company_name] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [i_brand,i_class,i_category,ss_store_sk,ss_sales_price,d_moy] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [i_brand,i_class,i_category,ss_store_sk,ss_sales_price,ss_sold_date_sk] + BroadcastHashJoin [i_item_sk,ss_item_sk] + ColumnarToRow + InputAdapter + CometFilter [i_category,i_class,i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_class,i_category] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk,ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_moy] + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + ReusedExchange [d_date_sk,d_moy] #4 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name,s_company_name] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q9/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q9/explain.txt new file mode 100644 index 0000000000..69c23211be --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q9/explain.txt @@ -0,0 +1,303 @@ +== Physical Plan == +* Project (4) ++- * ColumnarToRow (3) + +- CometFilter (2) + +- CometScan parquet spark_catalog.default.reason (1) + + +(1) Scan parquet spark_catalog.default.reason +Output [1]: [r_reason_sk#1] +Batched: true +Location [not included in comparison]/{warehouse_dir}/reason] +PushedFilters: [IsNotNull(r_reason_sk), EqualTo(r_reason_sk,1)] +ReadSchema: struct + +(2) CometFilter +Input [1]: [r_reason_sk#1] +Condition : (isnotnull(r_reason_sk#1) AND (r_reason_sk#1 = 1)) + +(3) ColumnarToRow [codegen id : 1] +Input [1]: [r_reason_sk#1] + +(4) Project [codegen id : 1] +Output [5]: [CASE WHEN (Subquery scalar-subquery#2, [id=#3].count(1) > 62316685) THEN ReusedSubquery Subquery scalar-subquery#2, [id=#3].avg(ss_ext_discount_amt) ELSE ReusedSubquery Subquery scalar-subquery#2, [id=#3].avg(ss_net_paid) END AS bucket1#4, CASE WHEN (Subquery scalar-subquery#5, [id=#6].count(1) > 19045798) THEN ReusedSubquery Subquery scalar-subquery#5, [id=#6].avg(ss_ext_discount_amt) ELSE ReusedSubquery Subquery scalar-subquery#5, [id=#6].avg(ss_net_paid) END AS bucket2#7, CASE WHEN (Subquery scalar-subquery#8, [id=#9].count(1) > 365541424) THEN ReusedSubquery Subquery scalar-subquery#8, [id=#9].avg(ss_ext_discount_amt) ELSE ReusedSubquery Subquery scalar-subquery#8, [id=#9].avg(ss_net_paid) END AS bucket3#10, CASE WHEN (Subquery scalar-subquery#11, [id=#12].count(1) > 216357808) THEN ReusedSubquery Subquery scalar-subquery#11, [id=#12].avg(ss_ext_discount_amt) ELSE ReusedSubquery Subquery scalar-subquery#11, [id=#12].avg(ss_net_paid) END AS bucket4#13, CASE WHEN (Subquery scalar-subquery#14, [id=#15].count(1) > 184483884) THEN ReusedSubquery Subquery scalar-subquery#14, [id=#15].avg(ss_ext_discount_amt) ELSE ReusedSubquery Subquery scalar-subquery#14, [id=#15].avg(ss_net_paid) END AS bucket5#16] +Input [1]: [r_reason_sk#1] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = Subquery scalar-subquery#2, [id=#3] +* Project (12) ++- * HashAggregate (11) + +- Exchange (10) + +- * HashAggregate (9) + +- * ColumnarToRow (8) + +- CometProject (7) + +- CometFilter (6) + +- CometScan parquet spark_catalog.default.store_sales (5) + + +(5) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_quantity#17, ss_ext_discount_amt#18, ss_net_paid#19, ss_sold_date_sk#20] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_quantity), GreaterThanOrEqual(ss_quantity,1), LessThanOrEqual(ss_quantity,20)] +ReadSchema: struct + +(6) CometFilter +Input [4]: [ss_quantity#17, ss_ext_discount_amt#18, ss_net_paid#19, ss_sold_date_sk#20] +Condition : ((isnotnull(ss_quantity#17) AND (ss_quantity#17 >= 1)) AND (ss_quantity#17 <= 20)) + +(7) CometProject +Input [4]: [ss_quantity#17, ss_ext_discount_amt#18, ss_net_paid#19, ss_sold_date_sk#20] +Arguments: [ss_ext_discount_amt#18, ss_net_paid#19], [ss_ext_discount_amt#18, ss_net_paid#19] + +(8) ColumnarToRow [codegen id : 1] +Input [2]: [ss_ext_discount_amt#18, ss_net_paid#19] + +(9) HashAggregate [codegen id : 1] +Input [2]: [ss_ext_discount_amt#18, ss_net_paid#19] +Keys: [] +Functions [3]: [partial_count(1), partial_avg(UnscaledValue(ss_ext_discount_amt#18)), partial_avg(UnscaledValue(ss_net_paid#19))] +Aggregate Attributes [5]: [count#21, sum#22, count#23, sum#24, count#25] +Results [5]: [count#26, sum#27, count#28, sum#29, count#30] + +(10) Exchange +Input [5]: [count#26, sum#27, count#28, sum#29, count#30] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=1] + +(11) HashAggregate [codegen id : 2] +Input [5]: [count#26, sum#27, count#28, sum#29, count#30] +Keys: [] +Functions [3]: [count(1), avg(UnscaledValue(ss_ext_discount_amt#18)), avg(UnscaledValue(ss_net_paid#19))] +Aggregate Attributes [3]: [count(1)#31, avg(UnscaledValue(ss_ext_discount_amt#18))#32, avg(UnscaledValue(ss_net_paid#19))#33] +Results [3]: [count(1)#31 AS count(1)#34, cast((avg(UnscaledValue(ss_ext_discount_amt#18))#32 / 100.0) as decimal(11,6)) AS avg(ss_ext_discount_amt)#35, cast((avg(UnscaledValue(ss_net_paid#19))#33 / 100.0) as decimal(11,6)) AS avg(ss_net_paid)#36] + +(12) Project [codegen id : 2] +Output [1]: [named_struct(count(1), count(1)#34, avg(ss_ext_discount_amt), avg(ss_ext_discount_amt)#35, avg(ss_net_paid), avg(ss_net_paid)#36) AS mergedValue#37] +Input [3]: [count(1)#34, avg(ss_ext_discount_amt)#35, avg(ss_net_paid)#36] + +Subquery:2 Hosting operator id = 4 Hosting Expression = ReusedSubquery Subquery scalar-subquery#2, [id=#3] + +Subquery:3 Hosting operator id = 4 Hosting Expression = ReusedSubquery Subquery scalar-subquery#2, [id=#3] + +Subquery:4 Hosting operator id = 4 Hosting Expression = Subquery scalar-subquery#5, [id=#6] +* Project (20) ++- * HashAggregate (19) + +- Exchange (18) + +- * HashAggregate (17) + +- * ColumnarToRow (16) + +- CometProject (15) + +- CometFilter (14) + +- CometScan parquet spark_catalog.default.store_sales (13) + + +(13) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_quantity#38, ss_ext_discount_amt#39, ss_net_paid#40, ss_sold_date_sk#41] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_quantity), GreaterThanOrEqual(ss_quantity,21), LessThanOrEqual(ss_quantity,40)] +ReadSchema: struct + +(14) CometFilter +Input [4]: [ss_quantity#38, ss_ext_discount_amt#39, ss_net_paid#40, ss_sold_date_sk#41] +Condition : ((isnotnull(ss_quantity#38) AND (ss_quantity#38 >= 21)) AND (ss_quantity#38 <= 40)) + +(15) CometProject +Input [4]: [ss_quantity#38, ss_ext_discount_amt#39, ss_net_paid#40, ss_sold_date_sk#41] +Arguments: [ss_ext_discount_amt#39, ss_net_paid#40], [ss_ext_discount_amt#39, ss_net_paid#40] + +(16) ColumnarToRow [codegen id : 1] +Input [2]: [ss_ext_discount_amt#39, ss_net_paid#40] + +(17) HashAggregate [codegen id : 1] +Input [2]: [ss_ext_discount_amt#39, ss_net_paid#40] +Keys: [] +Functions [3]: [partial_count(1), partial_avg(UnscaledValue(ss_ext_discount_amt#39)), partial_avg(UnscaledValue(ss_net_paid#40))] +Aggregate Attributes [5]: [count#42, sum#43, count#44, sum#45, count#46] +Results [5]: [count#47, sum#48, count#49, sum#50, count#51] + +(18) Exchange +Input [5]: [count#47, sum#48, count#49, sum#50, count#51] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=2] + +(19) HashAggregate [codegen id : 2] +Input [5]: [count#47, sum#48, count#49, sum#50, count#51] +Keys: [] +Functions [3]: [count(1), avg(UnscaledValue(ss_ext_discount_amt#39)), avg(UnscaledValue(ss_net_paid#40))] +Aggregate Attributes [3]: [count(1)#52, avg(UnscaledValue(ss_ext_discount_amt#39))#53, avg(UnscaledValue(ss_net_paid#40))#54] +Results [3]: [count(1)#52 AS count(1)#55, cast((avg(UnscaledValue(ss_ext_discount_amt#39))#53 / 100.0) as decimal(11,6)) AS avg(ss_ext_discount_amt)#56, cast((avg(UnscaledValue(ss_net_paid#40))#54 / 100.0) as decimal(11,6)) AS avg(ss_net_paid)#57] + +(20) Project [codegen id : 2] +Output [1]: [named_struct(count(1), count(1)#55, avg(ss_ext_discount_amt), avg(ss_ext_discount_amt)#56, avg(ss_net_paid), avg(ss_net_paid)#57) AS mergedValue#58] +Input [3]: [count(1)#55, avg(ss_ext_discount_amt)#56, avg(ss_net_paid)#57] + +Subquery:5 Hosting operator id = 4 Hosting Expression = ReusedSubquery Subquery scalar-subquery#5, [id=#6] + +Subquery:6 Hosting operator id = 4 Hosting Expression = ReusedSubquery Subquery scalar-subquery#5, [id=#6] + +Subquery:7 Hosting operator id = 4 Hosting Expression = Subquery scalar-subquery#8, [id=#9] +* Project (28) ++- * HashAggregate (27) + +- Exchange (26) + +- * HashAggregate (25) + +- * ColumnarToRow (24) + +- CometProject (23) + +- CometFilter (22) + +- CometScan parquet spark_catalog.default.store_sales (21) + + +(21) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_quantity#59, ss_ext_discount_amt#60, ss_net_paid#61, ss_sold_date_sk#62] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_quantity), GreaterThanOrEqual(ss_quantity,41), LessThanOrEqual(ss_quantity,60)] +ReadSchema: struct + +(22) CometFilter +Input [4]: [ss_quantity#59, ss_ext_discount_amt#60, ss_net_paid#61, ss_sold_date_sk#62] +Condition : ((isnotnull(ss_quantity#59) AND (ss_quantity#59 >= 41)) AND (ss_quantity#59 <= 60)) + +(23) CometProject +Input [4]: [ss_quantity#59, ss_ext_discount_amt#60, ss_net_paid#61, ss_sold_date_sk#62] +Arguments: [ss_ext_discount_amt#60, ss_net_paid#61], [ss_ext_discount_amt#60, ss_net_paid#61] + +(24) ColumnarToRow [codegen id : 1] +Input [2]: [ss_ext_discount_amt#60, ss_net_paid#61] + +(25) HashAggregate [codegen id : 1] +Input [2]: [ss_ext_discount_amt#60, ss_net_paid#61] +Keys: [] +Functions [3]: [partial_count(1), partial_avg(UnscaledValue(ss_ext_discount_amt#60)), partial_avg(UnscaledValue(ss_net_paid#61))] +Aggregate Attributes [5]: [count#63, sum#64, count#65, sum#66, count#67] +Results [5]: [count#68, sum#69, count#70, sum#71, count#72] + +(26) Exchange +Input [5]: [count#68, sum#69, count#70, sum#71, count#72] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=3] + +(27) HashAggregate [codegen id : 2] +Input [5]: [count#68, sum#69, count#70, sum#71, count#72] +Keys: [] +Functions [3]: [count(1), avg(UnscaledValue(ss_ext_discount_amt#60)), avg(UnscaledValue(ss_net_paid#61))] +Aggregate Attributes [3]: [count(1)#73, avg(UnscaledValue(ss_ext_discount_amt#60))#74, avg(UnscaledValue(ss_net_paid#61))#75] +Results [3]: [count(1)#73 AS count(1)#76, cast((avg(UnscaledValue(ss_ext_discount_amt#60))#74 / 100.0) as decimal(11,6)) AS avg(ss_ext_discount_amt)#77, cast((avg(UnscaledValue(ss_net_paid#61))#75 / 100.0) as decimal(11,6)) AS avg(ss_net_paid)#78] + +(28) Project [codegen id : 2] +Output [1]: [named_struct(count(1), count(1)#76, avg(ss_ext_discount_amt), avg(ss_ext_discount_amt)#77, avg(ss_net_paid), avg(ss_net_paid)#78) AS mergedValue#79] +Input [3]: [count(1)#76, avg(ss_ext_discount_amt)#77, avg(ss_net_paid)#78] + +Subquery:8 Hosting operator id = 4 Hosting Expression = ReusedSubquery Subquery scalar-subquery#8, [id=#9] + +Subquery:9 Hosting operator id = 4 Hosting Expression = ReusedSubquery Subquery scalar-subquery#8, [id=#9] + +Subquery:10 Hosting operator id = 4 Hosting Expression = Subquery scalar-subquery#11, [id=#12] +* Project (36) ++- * HashAggregate (35) + +- Exchange (34) + +- * HashAggregate (33) + +- * ColumnarToRow (32) + +- CometProject (31) + +- CometFilter (30) + +- CometScan parquet spark_catalog.default.store_sales (29) + + +(29) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_quantity#80, ss_ext_discount_amt#81, ss_net_paid#82, ss_sold_date_sk#83] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_quantity), GreaterThanOrEqual(ss_quantity,61), LessThanOrEqual(ss_quantity,80)] +ReadSchema: struct + +(30) CometFilter +Input [4]: [ss_quantity#80, ss_ext_discount_amt#81, ss_net_paid#82, ss_sold_date_sk#83] +Condition : ((isnotnull(ss_quantity#80) AND (ss_quantity#80 >= 61)) AND (ss_quantity#80 <= 80)) + +(31) CometProject +Input [4]: [ss_quantity#80, ss_ext_discount_amt#81, ss_net_paid#82, ss_sold_date_sk#83] +Arguments: [ss_ext_discount_amt#81, ss_net_paid#82], [ss_ext_discount_amt#81, ss_net_paid#82] + +(32) ColumnarToRow [codegen id : 1] +Input [2]: [ss_ext_discount_amt#81, ss_net_paid#82] + +(33) HashAggregate [codegen id : 1] +Input [2]: [ss_ext_discount_amt#81, ss_net_paid#82] +Keys: [] +Functions [3]: [partial_count(1), partial_avg(UnscaledValue(ss_ext_discount_amt#81)), partial_avg(UnscaledValue(ss_net_paid#82))] +Aggregate Attributes [5]: [count#84, sum#85, count#86, sum#87, count#88] +Results [5]: [count#89, sum#90, count#91, sum#92, count#93] + +(34) Exchange +Input [5]: [count#89, sum#90, count#91, sum#92, count#93] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=4] + +(35) HashAggregate [codegen id : 2] +Input [5]: [count#89, sum#90, count#91, sum#92, count#93] +Keys: [] +Functions [3]: [count(1), avg(UnscaledValue(ss_ext_discount_amt#81)), avg(UnscaledValue(ss_net_paid#82))] +Aggregate Attributes [3]: [count(1)#94, avg(UnscaledValue(ss_ext_discount_amt#81))#95, avg(UnscaledValue(ss_net_paid#82))#96] +Results [3]: [count(1)#94 AS count(1)#97, cast((avg(UnscaledValue(ss_ext_discount_amt#81))#95 / 100.0) as decimal(11,6)) AS avg(ss_ext_discount_amt)#98, cast((avg(UnscaledValue(ss_net_paid#82))#96 / 100.0) as decimal(11,6)) AS avg(ss_net_paid)#99] + +(36) Project [codegen id : 2] +Output [1]: [named_struct(count(1), count(1)#97, avg(ss_ext_discount_amt), avg(ss_ext_discount_amt)#98, avg(ss_net_paid), avg(ss_net_paid)#99) AS mergedValue#100] +Input [3]: [count(1)#97, avg(ss_ext_discount_amt)#98, avg(ss_net_paid)#99] + +Subquery:11 Hosting operator id = 4 Hosting Expression = ReusedSubquery Subquery scalar-subquery#11, [id=#12] + +Subquery:12 Hosting operator id = 4 Hosting Expression = ReusedSubquery Subquery scalar-subquery#11, [id=#12] + +Subquery:13 Hosting operator id = 4 Hosting Expression = Subquery scalar-subquery#14, [id=#15] +* Project (44) ++- * HashAggregate (43) + +- Exchange (42) + +- * HashAggregate (41) + +- * ColumnarToRow (40) + +- CometProject (39) + +- CometFilter (38) + +- CometScan parquet spark_catalog.default.store_sales (37) + + +(37) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_quantity#101, ss_ext_discount_amt#102, ss_net_paid#103, ss_sold_date_sk#104] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_quantity), GreaterThanOrEqual(ss_quantity,81), LessThanOrEqual(ss_quantity,100)] +ReadSchema: struct + +(38) CometFilter +Input [4]: [ss_quantity#101, ss_ext_discount_amt#102, ss_net_paid#103, ss_sold_date_sk#104] +Condition : ((isnotnull(ss_quantity#101) AND (ss_quantity#101 >= 81)) AND (ss_quantity#101 <= 100)) + +(39) CometProject +Input [4]: [ss_quantity#101, ss_ext_discount_amt#102, ss_net_paid#103, ss_sold_date_sk#104] +Arguments: [ss_ext_discount_amt#102, ss_net_paid#103], [ss_ext_discount_amt#102, ss_net_paid#103] + +(40) ColumnarToRow [codegen id : 1] +Input [2]: [ss_ext_discount_amt#102, ss_net_paid#103] + +(41) HashAggregate [codegen id : 1] +Input [2]: [ss_ext_discount_amt#102, ss_net_paid#103] +Keys: [] +Functions [3]: [partial_count(1), partial_avg(UnscaledValue(ss_ext_discount_amt#102)), partial_avg(UnscaledValue(ss_net_paid#103))] +Aggregate Attributes [5]: [count#105, sum#106, count#107, sum#108, count#109] +Results [5]: [count#110, sum#111, count#112, sum#113, count#114] + +(42) Exchange +Input [5]: [count#110, sum#111, count#112, sum#113, count#114] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=5] + +(43) HashAggregate [codegen id : 2] +Input [5]: [count#110, sum#111, count#112, sum#113, count#114] +Keys: [] +Functions [3]: [count(1), avg(UnscaledValue(ss_ext_discount_amt#102)), avg(UnscaledValue(ss_net_paid#103))] +Aggregate Attributes [3]: [count(1)#115, avg(UnscaledValue(ss_ext_discount_amt#102))#116, avg(UnscaledValue(ss_net_paid#103))#117] +Results [3]: [count(1)#115 AS count(1)#118, cast((avg(UnscaledValue(ss_ext_discount_amt#102))#116 / 100.0) as decimal(11,6)) AS avg(ss_ext_discount_amt)#119, cast((avg(UnscaledValue(ss_net_paid#103))#117 / 100.0) as decimal(11,6)) AS avg(ss_net_paid)#120] + +(44) Project [codegen id : 2] +Output [1]: [named_struct(count(1), count(1)#118, avg(ss_ext_discount_amt), avg(ss_ext_discount_amt)#119, avg(ss_net_paid), avg(ss_net_paid)#120) AS mergedValue#121] +Input [3]: [count(1)#118, avg(ss_ext_discount_amt)#119, avg(ss_net_paid)#120] + +Subquery:14 Hosting operator id = 4 Hosting Expression = ReusedSubquery Subquery scalar-subquery#14, [id=#15] + +Subquery:15 Hosting operator id = 4 Hosting Expression = ReusedSubquery Subquery scalar-subquery#14, [id=#15] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q9/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q9/simplified.txt new file mode 100644 index 0000000000..fdd3bd2932 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q9/simplified.txt @@ -0,0 +1,81 @@ +WholeStageCodegen (1) + Project + Subquery #1 + WholeStageCodegen (2) + Project [count(1),avg(ss_ext_discount_amt),avg(ss_net_paid)] + HashAggregate [count,sum,count,sum,count] [count(1),avg(UnscaledValue(ss_ext_discount_amt)),avg(UnscaledValue(ss_net_paid)),count(1),avg(ss_ext_discount_amt),avg(ss_net_paid),count,sum,count,sum,count] + InputAdapter + Exchange #1 + WholeStageCodegen (1) + HashAggregate [ss_ext_discount_amt,ss_net_paid] [count,sum,count,sum,count,count,sum,count,sum,count] + ColumnarToRow + InputAdapter + CometProject [ss_ext_discount_amt,ss_net_paid] + CometFilter [ss_quantity] + CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_ext_discount_amt,ss_net_paid,ss_sold_date_sk] + ReusedSubquery [mergedValue] #1 + ReusedSubquery [mergedValue] #1 + Subquery #2 + WholeStageCodegen (2) + Project [count(1),avg(ss_ext_discount_amt),avg(ss_net_paid)] + HashAggregate [count,sum,count,sum,count] [count(1),avg(UnscaledValue(ss_ext_discount_amt)),avg(UnscaledValue(ss_net_paid)),count(1),avg(ss_ext_discount_amt),avg(ss_net_paid),count,sum,count,sum,count] + InputAdapter + Exchange #2 + WholeStageCodegen (1) + HashAggregate [ss_ext_discount_amt,ss_net_paid] [count,sum,count,sum,count,count,sum,count,sum,count] + ColumnarToRow + InputAdapter + CometProject [ss_ext_discount_amt,ss_net_paid] + CometFilter [ss_quantity] + CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_ext_discount_amt,ss_net_paid,ss_sold_date_sk] + ReusedSubquery [mergedValue] #2 + ReusedSubquery [mergedValue] #2 + Subquery #3 + WholeStageCodegen (2) + Project [count(1),avg(ss_ext_discount_amt),avg(ss_net_paid)] + HashAggregate [count,sum,count,sum,count] [count(1),avg(UnscaledValue(ss_ext_discount_amt)),avg(UnscaledValue(ss_net_paid)),count(1),avg(ss_ext_discount_amt),avg(ss_net_paid),count,sum,count,sum,count] + InputAdapter + Exchange #3 + WholeStageCodegen (1) + HashAggregate [ss_ext_discount_amt,ss_net_paid] [count,sum,count,sum,count,count,sum,count,sum,count] + ColumnarToRow + InputAdapter + CometProject [ss_ext_discount_amt,ss_net_paid] + CometFilter [ss_quantity] + CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_ext_discount_amt,ss_net_paid,ss_sold_date_sk] + ReusedSubquery [mergedValue] #3 + ReusedSubquery [mergedValue] #3 + Subquery #4 + WholeStageCodegen (2) + Project [count(1),avg(ss_ext_discount_amt),avg(ss_net_paid)] + HashAggregate [count,sum,count,sum,count] [count(1),avg(UnscaledValue(ss_ext_discount_amt)),avg(UnscaledValue(ss_net_paid)),count(1),avg(ss_ext_discount_amt),avg(ss_net_paid),count,sum,count,sum,count] + InputAdapter + Exchange #4 + WholeStageCodegen (1) + HashAggregate [ss_ext_discount_amt,ss_net_paid] [count,sum,count,sum,count,count,sum,count,sum,count] + ColumnarToRow + InputAdapter + CometProject [ss_ext_discount_amt,ss_net_paid] + CometFilter [ss_quantity] + CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_ext_discount_amt,ss_net_paid,ss_sold_date_sk] + ReusedSubquery [mergedValue] #4 + ReusedSubquery [mergedValue] #4 + Subquery #5 + WholeStageCodegen (2) + Project [count(1),avg(ss_ext_discount_amt),avg(ss_net_paid)] + HashAggregate [count,sum,count,sum,count] [count(1),avg(UnscaledValue(ss_ext_discount_amt)),avg(UnscaledValue(ss_net_paid)),count(1),avg(ss_ext_discount_amt),avg(ss_net_paid),count,sum,count,sum,count] + InputAdapter + Exchange #5 + WholeStageCodegen (1) + HashAggregate [ss_ext_discount_amt,ss_net_paid] [count,sum,count,sum,count,count,sum,count,sum,count] + ColumnarToRow + InputAdapter + CometProject [ss_ext_discount_amt,ss_net_paid] + CometFilter [ss_quantity] + CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_ext_discount_amt,ss_net_paid,ss_sold_date_sk] + ReusedSubquery [mergedValue] #5 + ReusedSubquery [mergedValue] #5 + ColumnarToRow + InputAdapter + CometFilter [r_reason_sk] + CometScan parquet spark_catalog.default.reason [r_reason_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q90/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q90/explain.txt new file mode 100644 index 0000000000..fcfbca847a --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q90/explain.txt @@ -0,0 +1,292 @@ +== Physical Plan == +* Project (51) ++- * BroadcastNestedLoopJoin Inner BuildRight (50) + :- * HashAggregate (28) + : +- Exchange (27) + : +- * HashAggregate (26) + : +- * Project (25) + : +- * BroadcastHashJoin Inner BuildRight (24) + : :- * Project (18) + : : +- * BroadcastHashJoin Inner BuildRight (17) + : : :- * Project (11) + : : : +- * BroadcastHashJoin Inner BuildRight (10) + : : : :- * ColumnarToRow (4) + : : : : +- CometProject (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.web_sales (1) + : : : +- BroadcastExchange (9) + : : : +- * ColumnarToRow (8) + : : : +- CometProject (7) + : : : +- CometFilter (6) + : : : +- CometScan parquet spark_catalog.default.household_demographics (5) + : : +- BroadcastExchange (16) + : : +- * ColumnarToRow (15) + : : +- CometProject (14) + : : +- CometFilter (13) + : : +- CometScan parquet spark_catalog.default.time_dim (12) + : +- BroadcastExchange (23) + : +- * ColumnarToRow (22) + : +- CometProject (21) + : +- CometFilter (20) + : +- CometScan parquet spark_catalog.default.web_page (19) + +- BroadcastExchange (49) + +- * HashAggregate (48) + +- Exchange (47) + +- * HashAggregate (46) + +- * Project (45) + +- * BroadcastHashJoin Inner BuildRight (44) + :- * Project (42) + : +- * BroadcastHashJoin Inner BuildRight (41) + : :- * Project (35) + : : +- * BroadcastHashJoin Inner BuildRight (34) + : : :- * ColumnarToRow (32) + : : : +- CometProject (31) + : : : +- CometFilter (30) + : : : +- CometScan parquet spark_catalog.default.web_sales (29) + : : +- ReusedExchange (33) + : +- BroadcastExchange (40) + : +- * ColumnarToRow (39) + : +- CometProject (38) + : +- CometFilter (37) + : +- CometScan parquet spark_catalog.default.time_dim (36) + +- ReusedExchange (43) + + +(1) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_sold_time_sk#1, ws_ship_hdemo_sk#2, ws_web_page_sk#3, ws_sold_date_sk#4] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_sales] +PushedFilters: [IsNotNull(ws_ship_hdemo_sk), IsNotNull(ws_sold_time_sk), IsNotNull(ws_web_page_sk)] +ReadSchema: struct + +(2) CometFilter +Input [4]: [ws_sold_time_sk#1, ws_ship_hdemo_sk#2, ws_web_page_sk#3, ws_sold_date_sk#4] +Condition : ((isnotnull(ws_ship_hdemo_sk#2) AND isnotnull(ws_sold_time_sk#1)) AND isnotnull(ws_web_page_sk#3)) + +(3) CometProject +Input [4]: [ws_sold_time_sk#1, ws_ship_hdemo_sk#2, ws_web_page_sk#3, ws_sold_date_sk#4] +Arguments: [ws_sold_time_sk#1, ws_ship_hdemo_sk#2, ws_web_page_sk#3], [ws_sold_time_sk#1, ws_ship_hdemo_sk#2, ws_web_page_sk#3] + +(4) ColumnarToRow [codegen id : 4] +Input [3]: [ws_sold_time_sk#1, ws_ship_hdemo_sk#2, ws_web_page_sk#3] + +(5) Scan parquet spark_catalog.default.household_demographics +Output [2]: [hd_demo_sk#5, hd_dep_count#6] +Batched: true +Location [not included in comparison]/{warehouse_dir}/household_demographics] +PushedFilters: [IsNotNull(hd_dep_count), EqualTo(hd_dep_count,6), IsNotNull(hd_demo_sk)] +ReadSchema: struct + +(6) CometFilter +Input [2]: [hd_demo_sk#5, hd_dep_count#6] +Condition : ((isnotnull(hd_dep_count#6) AND (hd_dep_count#6 = 6)) AND isnotnull(hd_demo_sk#5)) + +(7) CometProject +Input [2]: [hd_demo_sk#5, hd_dep_count#6] +Arguments: [hd_demo_sk#5], [hd_demo_sk#5] + +(8) ColumnarToRow [codegen id : 1] +Input [1]: [hd_demo_sk#5] + +(9) BroadcastExchange +Input [1]: [hd_demo_sk#5] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(10) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ws_ship_hdemo_sk#2] +Right keys [1]: [hd_demo_sk#5] +Join type: Inner +Join condition: None + +(11) Project [codegen id : 4] +Output [2]: [ws_sold_time_sk#1, ws_web_page_sk#3] +Input [4]: [ws_sold_time_sk#1, ws_ship_hdemo_sk#2, ws_web_page_sk#3, hd_demo_sk#5] + +(12) Scan parquet spark_catalog.default.time_dim +Output [2]: [t_time_sk#7, t_hour#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/time_dim] +PushedFilters: [IsNotNull(t_hour), GreaterThanOrEqual(t_hour,8), LessThanOrEqual(t_hour,9), IsNotNull(t_time_sk)] +ReadSchema: struct + +(13) CometFilter +Input [2]: [t_time_sk#7, t_hour#8] +Condition : (((isnotnull(t_hour#8) AND (t_hour#8 >= 8)) AND (t_hour#8 <= 9)) AND isnotnull(t_time_sk#7)) + +(14) CometProject +Input [2]: [t_time_sk#7, t_hour#8] +Arguments: [t_time_sk#7], [t_time_sk#7] + +(15) ColumnarToRow [codegen id : 2] +Input [1]: [t_time_sk#7] + +(16) BroadcastExchange +Input [1]: [t_time_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(17) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ws_sold_time_sk#1] +Right keys [1]: [t_time_sk#7] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 4] +Output [1]: [ws_web_page_sk#3] +Input [3]: [ws_sold_time_sk#1, ws_web_page_sk#3, t_time_sk#7] + +(19) Scan parquet spark_catalog.default.web_page +Output [2]: [wp_web_page_sk#9, wp_char_count#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_page] +PushedFilters: [IsNotNull(wp_char_count), GreaterThanOrEqual(wp_char_count,5000), LessThanOrEqual(wp_char_count,5200), IsNotNull(wp_web_page_sk)] +ReadSchema: struct + +(20) CometFilter +Input [2]: [wp_web_page_sk#9, wp_char_count#10] +Condition : (((isnotnull(wp_char_count#10) AND (wp_char_count#10 >= 5000)) AND (wp_char_count#10 <= 5200)) AND isnotnull(wp_web_page_sk#9)) + +(21) CometProject +Input [2]: [wp_web_page_sk#9, wp_char_count#10] +Arguments: [wp_web_page_sk#9], [wp_web_page_sk#9] + +(22) ColumnarToRow [codegen id : 3] +Input [1]: [wp_web_page_sk#9] + +(23) BroadcastExchange +Input [1]: [wp_web_page_sk#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ws_web_page_sk#3] +Right keys [1]: [wp_web_page_sk#9] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 4] +Output: [] +Input [2]: [ws_web_page_sk#3, wp_web_page_sk#9] + +(26) HashAggregate [codegen id : 4] +Input: [] +Keys: [] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#11] +Results [1]: [count#12] + +(27) Exchange +Input [1]: [count#12] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=4] + +(28) HashAggregate [codegen id : 10] +Input [1]: [count#12] +Keys: [] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#13] +Results [1]: [count(1)#13 AS amc#14] + +(29) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_sold_time_sk#15, ws_ship_hdemo_sk#16, ws_web_page_sk#17, ws_sold_date_sk#18] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_sales] +PushedFilters: [IsNotNull(ws_ship_hdemo_sk), IsNotNull(ws_sold_time_sk), IsNotNull(ws_web_page_sk)] +ReadSchema: struct + +(30) CometFilter +Input [4]: [ws_sold_time_sk#15, ws_ship_hdemo_sk#16, ws_web_page_sk#17, ws_sold_date_sk#18] +Condition : ((isnotnull(ws_ship_hdemo_sk#16) AND isnotnull(ws_sold_time_sk#15)) AND isnotnull(ws_web_page_sk#17)) + +(31) CometProject +Input [4]: [ws_sold_time_sk#15, ws_ship_hdemo_sk#16, ws_web_page_sk#17, ws_sold_date_sk#18] +Arguments: [ws_sold_time_sk#15, ws_ship_hdemo_sk#16, ws_web_page_sk#17], [ws_sold_time_sk#15, ws_ship_hdemo_sk#16, ws_web_page_sk#17] + +(32) ColumnarToRow [codegen id : 8] +Input [3]: [ws_sold_time_sk#15, ws_ship_hdemo_sk#16, ws_web_page_sk#17] + +(33) ReusedExchange [Reuses operator id: 9] +Output [1]: [hd_demo_sk#19] + +(34) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ws_ship_hdemo_sk#16] +Right keys [1]: [hd_demo_sk#19] +Join type: Inner +Join condition: None + +(35) Project [codegen id : 8] +Output [2]: [ws_sold_time_sk#15, ws_web_page_sk#17] +Input [4]: [ws_sold_time_sk#15, ws_ship_hdemo_sk#16, ws_web_page_sk#17, hd_demo_sk#19] + +(36) Scan parquet spark_catalog.default.time_dim +Output [2]: [t_time_sk#20, t_hour#21] +Batched: true +Location [not included in comparison]/{warehouse_dir}/time_dim] +PushedFilters: [IsNotNull(t_hour), GreaterThanOrEqual(t_hour,19), LessThanOrEqual(t_hour,20), IsNotNull(t_time_sk)] +ReadSchema: struct + +(37) CometFilter +Input [2]: [t_time_sk#20, t_hour#21] +Condition : (((isnotnull(t_hour#21) AND (t_hour#21 >= 19)) AND (t_hour#21 <= 20)) AND isnotnull(t_time_sk#20)) + +(38) CometProject +Input [2]: [t_time_sk#20, t_hour#21] +Arguments: [t_time_sk#20], [t_time_sk#20] + +(39) ColumnarToRow [codegen id : 6] +Input [1]: [t_time_sk#20] + +(40) BroadcastExchange +Input [1]: [t_time_sk#20] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +(41) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ws_sold_time_sk#15] +Right keys [1]: [t_time_sk#20] +Join type: Inner +Join condition: None + +(42) Project [codegen id : 8] +Output [1]: [ws_web_page_sk#17] +Input [3]: [ws_sold_time_sk#15, ws_web_page_sk#17, t_time_sk#20] + +(43) ReusedExchange [Reuses operator id: 23] +Output [1]: [wp_web_page_sk#22] + +(44) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ws_web_page_sk#17] +Right keys [1]: [wp_web_page_sk#22] +Join type: Inner +Join condition: None + +(45) Project [codegen id : 8] +Output: [] +Input [2]: [ws_web_page_sk#17, wp_web_page_sk#22] + +(46) HashAggregate [codegen id : 8] +Input: [] +Keys: [] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#23] +Results [1]: [count#24] + +(47) Exchange +Input [1]: [count#24] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=6] + +(48) HashAggregate [codegen id : 9] +Input [1]: [count#24] +Keys: [] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#25] +Results [1]: [count(1)#25 AS pmc#26] + +(49) BroadcastExchange +Input [1]: [pmc#26] +Arguments: IdentityBroadcastMode, [plan_id=7] + +(50) BroadcastNestedLoopJoin [codegen id : 10] +Join type: Inner +Join condition: None + +(51) Project [codegen id : 10] +Output [1]: [(cast(amc#14 as decimal(15,4)) / cast(pmc#26 as decimal(15,4))) AS am_pm_ratio#27] +Input [2]: [amc#14, pmc#26] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q90/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q90/simplified.txt new file mode 100644 index 0000000000..c4e04b06bc --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q90/simplified.txt @@ -0,0 +1,74 @@ +WholeStageCodegen (10) + Project [amc,pmc] + BroadcastNestedLoopJoin + HashAggregate [count] [count(1),amc,count] + InputAdapter + Exchange #1 + WholeStageCodegen (4) + HashAggregate [count,count] + Project + BroadcastHashJoin [ws_web_page_sk,wp_web_page_sk] + Project [ws_web_page_sk] + BroadcastHashJoin [ws_sold_time_sk,t_time_sk] + Project [ws_sold_time_sk,ws_web_page_sk] + BroadcastHashJoin [ws_ship_hdemo_sk,hd_demo_sk] + ColumnarToRow + InputAdapter + CometProject [ws_sold_time_sk,ws_ship_hdemo_sk,ws_web_page_sk] + CometFilter [ws_ship_hdemo_sk,ws_sold_time_sk,ws_web_page_sk] + CometScan parquet spark_catalog.default.web_sales [ws_sold_time_sk,ws_ship_hdemo_sk,ws_web_page_sk,ws_sold_date_sk] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [hd_demo_sk] + CometFilter [hd_dep_count,hd_demo_sk] + CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_dep_count] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometProject [t_time_sk] + CometFilter [t_hour,t_time_sk] + CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometProject [wp_web_page_sk] + CometFilter [wp_char_count,wp_web_page_sk] + CometScan parquet spark_catalog.default.web_page [wp_web_page_sk,wp_char_count] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (9) + HashAggregate [count] [count(1),pmc,count] + InputAdapter + Exchange #6 + WholeStageCodegen (8) + HashAggregate [count,count] + Project + BroadcastHashJoin [ws_web_page_sk,wp_web_page_sk] + Project [ws_web_page_sk] + BroadcastHashJoin [ws_sold_time_sk,t_time_sk] + Project [ws_sold_time_sk,ws_web_page_sk] + BroadcastHashJoin [ws_ship_hdemo_sk,hd_demo_sk] + ColumnarToRow + InputAdapter + CometProject [ws_sold_time_sk,ws_ship_hdemo_sk,ws_web_page_sk] + CometFilter [ws_ship_hdemo_sk,ws_sold_time_sk,ws_web_page_sk] + CometScan parquet spark_catalog.default.web_sales [ws_sold_time_sk,ws_ship_hdemo_sk,ws_web_page_sk,ws_sold_date_sk] + InputAdapter + ReusedExchange [hd_demo_sk] #2 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (6) + ColumnarToRow + InputAdapter + CometProject [t_time_sk] + CometFilter [t_hour,t_time_sk] + CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour] + InputAdapter + ReusedExchange [wp_web_page_sk] #4 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q91/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q91/explain.txt new file mode 100644 index 0000000000..61f35489a2 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q91/explain.txt @@ -0,0 +1,281 @@ +== Physical Plan == +* Sort (43) ++- Exchange (42) + +- * HashAggregate (41) + +- Exchange (40) + +- * HashAggregate (39) + +- * Project (38) + +- * BroadcastHashJoin Inner BuildRight (37) + :- * Project (31) + : +- * BroadcastHashJoin Inner BuildRight (30) + : :- * Project (25) + : : +- * BroadcastHashJoin Inner BuildRight (24) + : : :- * Project (18) + : : : +- * BroadcastHashJoin Inner BuildRight (17) + : : : :- * Project (12) + : : : : +- * BroadcastHashJoin Inner BuildRight (11) + : : : : :- * Project (9) + : : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : : :- * ColumnarToRow (3) + : : : : : : +- CometFilter (2) + : : : : : : +- CometScan parquet spark_catalog.default.call_center (1) + : : : : : +- BroadcastExchange (7) + : : : : : +- * ColumnarToRow (6) + : : : : : +- CometFilter (5) + : : : : : +- CometScan parquet spark_catalog.default.catalog_returns (4) + : : : : +- ReusedExchange (10) + : : : +- BroadcastExchange (16) + : : : +- * ColumnarToRow (15) + : : : +- CometFilter (14) + : : : +- CometScan parquet spark_catalog.default.customer (13) + : : +- BroadcastExchange (23) + : : +- * ColumnarToRow (22) + : : +- CometProject (21) + : : +- CometFilter (20) + : : +- CometScan parquet spark_catalog.default.customer_address (19) + : +- BroadcastExchange (29) + : +- * ColumnarToRow (28) + : +- CometFilter (27) + : +- CometScan parquet spark_catalog.default.customer_demographics (26) + +- BroadcastExchange (36) + +- * ColumnarToRow (35) + +- CometProject (34) + +- CometFilter (33) + +- CometScan parquet spark_catalog.default.household_demographics (32) + + +(1) Scan parquet spark_catalog.default.call_center +Output [4]: [cc_call_center_sk#1, cc_call_center_id#2, cc_name#3, cc_manager#4] +Batched: true +Location [not included in comparison]/{warehouse_dir}/call_center] +PushedFilters: [IsNotNull(cc_call_center_sk)] +ReadSchema: struct + +(2) CometFilter +Input [4]: [cc_call_center_sk#1, cc_call_center_id#2, cc_name#3, cc_manager#4] +Condition : isnotnull(cc_call_center_sk#1) + +(3) ColumnarToRow [codegen id : 7] +Input [4]: [cc_call_center_sk#1, cc_call_center_id#2, cc_name#3, cc_manager#4] + +(4) Scan parquet spark_catalog.default.catalog_returns +Output [4]: [cr_returning_customer_sk#5, cr_call_center_sk#6, cr_net_loss#7, cr_returned_date_sk#8] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cr_returned_date_sk#8), dynamicpruningexpression(cr_returned_date_sk#8 IN dynamicpruning#9)] +PushedFilters: [IsNotNull(cr_call_center_sk), IsNotNull(cr_returning_customer_sk)] +ReadSchema: struct + +(5) CometFilter +Input [4]: [cr_returning_customer_sk#5, cr_call_center_sk#6, cr_net_loss#7, cr_returned_date_sk#8] +Condition : (isnotnull(cr_call_center_sk#6) AND isnotnull(cr_returning_customer_sk#5)) + +(6) ColumnarToRow [codegen id : 1] +Input [4]: [cr_returning_customer_sk#5, cr_call_center_sk#6, cr_net_loss#7, cr_returned_date_sk#8] + +(7) BroadcastExchange +Input [4]: [cr_returning_customer_sk#5, cr_call_center_sk#6, cr_net_loss#7, cr_returned_date_sk#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[1, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [cc_call_center_sk#1] +Right keys [1]: [cr_call_center_sk#6] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 7] +Output [6]: [cc_call_center_id#2, cc_name#3, cc_manager#4, cr_returning_customer_sk#5, cr_net_loss#7, cr_returned_date_sk#8] +Input [8]: [cc_call_center_sk#1, cc_call_center_id#2, cc_name#3, cc_manager#4, cr_returning_customer_sk#5, cr_call_center_sk#6, cr_net_loss#7, cr_returned_date_sk#8] + +(10) ReusedExchange [Reuses operator id: 48] +Output [1]: [d_date_sk#10] + +(11) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [cr_returned_date_sk#8] +Right keys [1]: [d_date_sk#10] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 7] +Output [5]: [cc_call_center_id#2, cc_name#3, cc_manager#4, cr_returning_customer_sk#5, cr_net_loss#7] +Input [7]: [cc_call_center_id#2, cc_name#3, cc_manager#4, cr_returning_customer_sk#5, cr_net_loss#7, cr_returned_date_sk#8, d_date_sk#10] + +(13) Scan parquet spark_catalog.default.customer +Output [4]: [c_customer_sk#11, c_current_cdemo_sk#12, c_current_hdemo_sk#13, c_current_addr_sk#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_current_addr_sk), IsNotNull(c_current_cdemo_sk), IsNotNull(c_current_hdemo_sk)] +ReadSchema: struct + +(14) CometFilter +Input [4]: [c_customer_sk#11, c_current_cdemo_sk#12, c_current_hdemo_sk#13, c_current_addr_sk#14] +Condition : (((isnotnull(c_customer_sk#11) AND isnotnull(c_current_addr_sk#14)) AND isnotnull(c_current_cdemo_sk#12)) AND isnotnull(c_current_hdemo_sk#13)) + +(15) ColumnarToRow [codegen id : 3] +Input [4]: [c_customer_sk#11, c_current_cdemo_sk#12, c_current_hdemo_sk#13, c_current_addr_sk#14] + +(16) BroadcastExchange +Input [4]: [c_customer_sk#11, c_current_cdemo_sk#12, c_current_hdemo_sk#13, c_current_addr_sk#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(17) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [cr_returning_customer_sk#5] +Right keys [1]: [c_customer_sk#11] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 7] +Output [7]: [cc_call_center_id#2, cc_name#3, cc_manager#4, cr_net_loss#7, c_current_cdemo_sk#12, c_current_hdemo_sk#13, c_current_addr_sk#14] +Input [9]: [cc_call_center_id#2, cc_name#3, cc_manager#4, cr_returning_customer_sk#5, cr_net_loss#7, c_customer_sk#11, c_current_cdemo_sk#12, c_current_hdemo_sk#13, c_current_addr_sk#14] + +(19) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#15, ca_gmt_offset#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_gmt_offset), EqualTo(ca_gmt_offset,-7.00), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(20) CometFilter +Input [2]: [ca_address_sk#15, ca_gmt_offset#16] +Condition : ((isnotnull(ca_gmt_offset#16) AND (ca_gmt_offset#16 = -7.00)) AND isnotnull(ca_address_sk#15)) + +(21) CometProject +Input [2]: [ca_address_sk#15, ca_gmt_offset#16] +Arguments: [ca_address_sk#15], [ca_address_sk#15] + +(22) ColumnarToRow [codegen id : 4] +Input [1]: [ca_address_sk#15] + +(23) BroadcastExchange +Input [1]: [ca_address_sk#15] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [c_current_addr_sk#14] +Right keys [1]: [ca_address_sk#15] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 7] +Output [6]: [cc_call_center_id#2, cc_name#3, cc_manager#4, cr_net_loss#7, c_current_cdemo_sk#12, c_current_hdemo_sk#13] +Input [8]: [cc_call_center_id#2, cc_name#3, cc_manager#4, cr_net_loss#7, c_current_cdemo_sk#12, c_current_hdemo_sk#13, c_current_addr_sk#14, ca_address_sk#15] + +(26) Scan parquet spark_catalog.default.customer_demographics +Output [3]: [cd_demo_sk#17, cd_marital_status#18, cd_education_status#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [Or(And(EqualTo(cd_marital_status,M),EqualTo(cd_education_status,Unknown )),And(EqualTo(cd_marital_status,W),EqualTo(cd_education_status,Advanced Degree ))), IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(27) CometFilter +Input [3]: [cd_demo_sk#17, cd_marital_status#18, cd_education_status#19] +Condition : ((((cd_marital_status#18 = M) AND (cd_education_status#19 = Unknown )) OR ((cd_marital_status#18 = W) AND (cd_education_status#19 = Advanced Degree ))) AND isnotnull(cd_demo_sk#17)) + +(28) ColumnarToRow [codegen id : 5] +Input [3]: [cd_demo_sk#17, cd_marital_status#18, cd_education_status#19] + +(29) BroadcastExchange +Input [3]: [cd_demo_sk#17, cd_marital_status#18, cd_education_status#19] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(30) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [c_current_cdemo_sk#12] +Right keys [1]: [cd_demo_sk#17] +Join type: Inner +Join condition: None + +(31) Project [codegen id : 7] +Output [7]: [cc_call_center_id#2, cc_name#3, cc_manager#4, cr_net_loss#7, c_current_hdemo_sk#13, cd_marital_status#18, cd_education_status#19] +Input [9]: [cc_call_center_id#2, cc_name#3, cc_manager#4, cr_net_loss#7, c_current_cdemo_sk#12, c_current_hdemo_sk#13, cd_demo_sk#17, cd_marital_status#18, cd_education_status#19] + +(32) Scan parquet spark_catalog.default.household_demographics +Output [2]: [hd_demo_sk#20, hd_buy_potential#21] +Batched: true +Location [not included in comparison]/{warehouse_dir}/household_demographics] +PushedFilters: [IsNotNull(hd_buy_potential), StringStartsWith(hd_buy_potential,Unknown), IsNotNull(hd_demo_sk)] +ReadSchema: struct + +(33) CometFilter +Input [2]: [hd_demo_sk#20, hd_buy_potential#21] +Condition : ((isnotnull(hd_buy_potential#21) AND StartsWith(hd_buy_potential#21, Unknown)) AND isnotnull(hd_demo_sk#20)) + +(34) CometProject +Input [2]: [hd_demo_sk#20, hd_buy_potential#21] +Arguments: [hd_demo_sk#20], [hd_demo_sk#20] + +(35) ColumnarToRow [codegen id : 6] +Input [1]: [hd_demo_sk#20] + +(36) BroadcastExchange +Input [1]: [hd_demo_sk#20] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +(37) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [c_current_hdemo_sk#13] +Right keys [1]: [hd_demo_sk#20] +Join type: Inner +Join condition: None + +(38) Project [codegen id : 7] +Output [6]: [cc_call_center_id#2, cc_name#3, cc_manager#4, cr_net_loss#7, cd_marital_status#18, cd_education_status#19] +Input [8]: [cc_call_center_id#2, cc_name#3, cc_manager#4, cr_net_loss#7, c_current_hdemo_sk#13, cd_marital_status#18, cd_education_status#19, hd_demo_sk#20] + +(39) HashAggregate [codegen id : 7] +Input [6]: [cc_call_center_id#2, cc_name#3, cc_manager#4, cr_net_loss#7, cd_marital_status#18, cd_education_status#19] +Keys [5]: [cc_call_center_id#2, cc_name#3, cc_manager#4, cd_marital_status#18, cd_education_status#19] +Functions [1]: [partial_sum(UnscaledValue(cr_net_loss#7))] +Aggregate Attributes [1]: [sum#22] +Results [6]: [cc_call_center_id#2, cc_name#3, cc_manager#4, cd_marital_status#18, cd_education_status#19, sum#23] + +(40) Exchange +Input [6]: [cc_call_center_id#2, cc_name#3, cc_manager#4, cd_marital_status#18, cd_education_status#19, sum#23] +Arguments: hashpartitioning(cc_call_center_id#2, cc_name#3, cc_manager#4, cd_marital_status#18, cd_education_status#19, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(41) HashAggregate [codegen id : 8] +Input [6]: [cc_call_center_id#2, cc_name#3, cc_manager#4, cd_marital_status#18, cd_education_status#19, sum#23] +Keys [5]: [cc_call_center_id#2, cc_name#3, cc_manager#4, cd_marital_status#18, cd_education_status#19] +Functions [1]: [sum(UnscaledValue(cr_net_loss#7))] +Aggregate Attributes [1]: [sum(UnscaledValue(cr_net_loss#7))#24] +Results [4]: [cc_call_center_id#2 AS Call_Center#25, cc_name#3 AS Call_Center_Name#26, cc_manager#4 AS Manager#27, MakeDecimal(sum(UnscaledValue(cr_net_loss#7))#24,17,2) AS Returns_Loss#28] + +(42) Exchange +Input [4]: [Call_Center#25, Call_Center_Name#26, Manager#27, Returns_Loss#28] +Arguments: rangepartitioning(Returns_Loss#28 DESC NULLS LAST, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(43) Sort [codegen id : 9] +Input [4]: [Call_Center#25, Call_Center_Name#26, Manager#27, Returns_Loss#28] +Arguments: [Returns_Loss#28 DESC NULLS LAST], true, 0 + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = cr_returned_date_sk#8 IN dynamicpruning#9 +BroadcastExchange (48) ++- * ColumnarToRow (47) + +- CometProject (46) + +- CometFilter (45) + +- CometScan parquet spark_catalog.default.date_dim (44) + + +(44) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#10, d_year#29, d_moy#30] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,1998), EqualTo(d_moy,11), IsNotNull(d_date_sk)] +ReadSchema: struct + +(45) CometFilter +Input [3]: [d_date_sk#10, d_year#29, d_moy#30] +Condition : ((((isnotnull(d_year#29) AND isnotnull(d_moy#30)) AND (d_year#29 = 1998)) AND (d_moy#30 = 11)) AND isnotnull(d_date_sk#10)) + +(46) CometProject +Input [3]: [d_date_sk#10, d_year#29, d_moy#30] +Arguments: [d_date_sk#10], [d_date_sk#10] + +(47) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#10] + +(48) BroadcastExchange +Input [1]: [d_date_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q91/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q91/simplified.txt new file mode 100644 index 0000000000..e5d62e3c0b --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q91/simplified.txt @@ -0,0 +1,73 @@ +WholeStageCodegen (9) + Sort [Returns_Loss] + InputAdapter + Exchange [Returns_Loss] #1 + WholeStageCodegen (8) + HashAggregate [cc_call_center_id,cc_name,cc_manager,cd_marital_status,cd_education_status,sum] [sum(UnscaledValue(cr_net_loss)),Call_Center,Call_Center_Name,Manager,Returns_Loss,sum] + InputAdapter + Exchange [cc_call_center_id,cc_name,cc_manager,cd_marital_status,cd_education_status] #2 + WholeStageCodegen (7) + HashAggregate [cc_call_center_id,cc_name,cc_manager,cd_marital_status,cd_education_status,cr_net_loss] [sum,sum] + Project [cc_call_center_id,cc_name,cc_manager,cr_net_loss,cd_marital_status,cd_education_status] + BroadcastHashJoin [c_current_hdemo_sk,hd_demo_sk] + Project [cc_call_center_id,cc_name,cc_manager,cr_net_loss,c_current_hdemo_sk,cd_marital_status,cd_education_status] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk] + Project [cc_call_center_id,cc_name,cc_manager,cr_net_loss,c_current_cdemo_sk,c_current_hdemo_sk] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [cc_call_center_id,cc_name,cc_manager,cr_net_loss,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk] + BroadcastHashJoin [cr_returning_customer_sk,c_customer_sk] + Project [cc_call_center_id,cc_name,cc_manager,cr_returning_customer_sk,cr_net_loss] + BroadcastHashJoin [cr_returned_date_sk,d_date_sk] + Project [cc_call_center_id,cc_name,cc_manager,cr_returning_customer_sk,cr_net_loss,cr_returned_date_sk] + BroadcastHashJoin [cc_call_center_sk,cr_call_center_sk] + ColumnarToRow + InputAdapter + CometFilter [cc_call_center_sk] + CometScan parquet spark_catalog.default.call_center [cc_call_center_sk,cc_call_center_id,cc_name,cc_manager] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [cr_call_center_sk,cr_returning_customer_sk] + CometScan parquet spark_catalog.default.catalog_returns [cr_returning_customer_sk,cr_call_center_sk,cr_net_loss,cr_returned_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_moy,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_current_addr_sk,c_current_cdemo_sk,c_current_hdemo_sk] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (4) + ColumnarToRow + InputAdapter + CometProject [ca_address_sk] + CometFilter [ca_gmt_offset,ca_address_sk] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_gmt_offset] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (5) + ColumnarToRow + InputAdapter + CometFilter [cd_marital_status,cd_education_status,cd_demo_sk] + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_marital_status,cd_education_status] + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (6) + ColumnarToRow + InputAdapter + CometProject [hd_demo_sk] + CometFilter [hd_buy_potential,hd_demo_sk] + CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_buy_potential] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q92/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q92/explain.txt new file mode 100644 index 0000000000..5f1f961686 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q92/explain.txt @@ -0,0 +1,209 @@ +== Physical Plan == +* HashAggregate (29) ++- Exchange (28) + +- * HashAggregate (27) + +- * Project (26) + +- * BroadcastHashJoin Inner BuildRight (25) + :- * Project (23) + : +- * BroadcastHashJoin Inner BuildRight (22) + : :- * Project (10) + : : +- * BroadcastHashJoin Inner BuildRight (9) + : : :- * ColumnarToRow (3) + : : : +- CometFilter (2) + : : : +- CometScan parquet spark_catalog.default.web_sales (1) + : : +- BroadcastExchange (8) + : : +- * ColumnarToRow (7) + : : +- CometProject (6) + : : +- CometFilter (5) + : : +- CometScan parquet spark_catalog.default.item (4) + : +- BroadcastExchange (21) + : +- * Filter (20) + : +- * HashAggregate (19) + : +- Exchange (18) + : +- * HashAggregate (17) + : +- * Project (16) + : +- * BroadcastHashJoin Inner BuildRight (15) + : :- * ColumnarToRow (13) + : : +- CometFilter (12) + : : +- CometScan parquet spark_catalog.default.web_sales (11) + : +- ReusedExchange (14) + +- ReusedExchange (24) + + +(1) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_item_sk#1, ws_ext_discount_amt#2, ws_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#3), dynamicpruningexpression(ws_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(ws_item_sk), IsNotNull(ws_ext_discount_amt)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [ws_item_sk#1, ws_ext_discount_amt#2, ws_sold_date_sk#3] +Condition : (isnotnull(ws_item_sk#1) AND isnotnull(ws_ext_discount_amt#2)) + +(3) ColumnarToRow [codegen id : 6] +Input [3]: [ws_item_sk#1, ws_ext_discount_amt#2, ws_sold_date_sk#3] + +(4) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#5, i_manufact_id#6] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_manufact_id), EqualTo(i_manufact_id,350), IsNotNull(i_item_sk)] +ReadSchema: struct + +(5) CometFilter +Input [2]: [i_item_sk#5, i_manufact_id#6] +Condition : ((isnotnull(i_manufact_id#6) AND (i_manufact_id#6 = 350)) AND isnotnull(i_item_sk#5)) + +(6) CometProject +Input [2]: [i_item_sk#5, i_manufact_id#6] +Arguments: [i_item_sk#5], [i_item_sk#5] + +(7) ColumnarToRow [codegen id : 1] +Input [1]: [i_item_sk#5] + +(8) BroadcastExchange +Input [1]: [i_item_sk#5] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ws_item_sk#1] +Right keys [1]: [i_item_sk#5] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 6] +Output [3]: [ws_ext_discount_amt#2, ws_sold_date_sk#3, i_item_sk#5] +Input [4]: [ws_item_sk#1, ws_ext_discount_amt#2, ws_sold_date_sk#3, i_item_sk#5] + +(11) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_item_sk#7, ws_ext_discount_amt#8, ws_sold_date_sk#9] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#9), dynamicpruningexpression(ws_sold_date_sk#9 IN dynamicpruning#10)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(12) CometFilter +Input [3]: [ws_item_sk#7, ws_ext_discount_amt#8, ws_sold_date_sk#9] +Condition : isnotnull(ws_item_sk#7) + +(13) ColumnarToRow [codegen id : 3] +Input [3]: [ws_item_sk#7, ws_ext_discount_amt#8, ws_sold_date_sk#9] + +(14) ReusedExchange [Reuses operator id: 34] +Output [1]: [d_date_sk#11] + +(15) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ws_sold_date_sk#9] +Right keys [1]: [d_date_sk#11] +Join type: Inner +Join condition: None + +(16) Project [codegen id : 3] +Output [2]: [ws_item_sk#7, ws_ext_discount_amt#8] +Input [4]: [ws_item_sk#7, ws_ext_discount_amt#8, ws_sold_date_sk#9, d_date_sk#11] + +(17) HashAggregate [codegen id : 3] +Input [2]: [ws_item_sk#7, ws_ext_discount_amt#8] +Keys [1]: [ws_item_sk#7] +Functions [1]: [partial_avg(UnscaledValue(ws_ext_discount_amt#8))] +Aggregate Attributes [2]: [sum#12, count#13] +Results [3]: [ws_item_sk#7, sum#14, count#15] + +(18) Exchange +Input [3]: [ws_item_sk#7, sum#14, count#15] +Arguments: hashpartitioning(ws_item_sk#7, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(19) HashAggregate [codegen id : 4] +Input [3]: [ws_item_sk#7, sum#14, count#15] +Keys [1]: [ws_item_sk#7] +Functions [1]: [avg(UnscaledValue(ws_ext_discount_amt#8))] +Aggregate Attributes [1]: [avg(UnscaledValue(ws_ext_discount_amt#8))#16] +Results [2]: [(1.3 * cast((avg(UnscaledValue(ws_ext_discount_amt#8))#16 / 100.0) as decimal(11,6))) AS (1.3 * avg(ws_ext_discount_amt))#17, ws_item_sk#7] + +(20) Filter [codegen id : 4] +Input [2]: [(1.3 * avg(ws_ext_discount_amt))#17, ws_item_sk#7] +Condition : isnotnull((1.3 * avg(ws_ext_discount_amt))#17) + +(21) BroadcastExchange +Input [2]: [(1.3 * avg(ws_ext_discount_amt))#17, ws_item_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[1, int, true] as bigint)),false), [plan_id=3] + +(22) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [i_item_sk#5] +Right keys [1]: [ws_item_sk#7] +Join type: Inner +Join condition: (cast(ws_ext_discount_amt#2 as decimal(14,7)) > (1.3 * avg(ws_ext_discount_amt))#17) + +(23) Project [codegen id : 6] +Output [2]: [ws_ext_discount_amt#2, ws_sold_date_sk#3] +Input [5]: [ws_ext_discount_amt#2, ws_sold_date_sk#3, i_item_sk#5, (1.3 * avg(ws_ext_discount_amt))#17, ws_item_sk#7] + +(24) ReusedExchange [Reuses operator id: 34] +Output [1]: [d_date_sk#18] + +(25) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ws_sold_date_sk#3] +Right keys [1]: [d_date_sk#18] +Join type: Inner +Join condition: None + +(26) Project [codegen id : 6] +Output [1]: [ws_ext_discount_amt#2] +Input [3]: [ws_ext_discount_amt#2, ws_sold_date_sk#3, d_date_sk#18] + +(27) HashAggregate [codegen id : 6] +Input [1]: [ws_ext_discount_amt#2] +Keys: [] +Functions [1]: [partial_sum(UnscaledValue(ws_ext_discount_amt#2))] +Aggregate Attributes [1]: [sum#19] +Results [1]: [sum#20] + +(28) Exchange +Input [1]: [sum#20] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=4] + +(29) HashAggregate [codegen id : 7] +Input [1]: [sum#20] +Keys: [] +Functions [1]: [sum(UnscaledValue(ws_ext_discount_amt#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_ext_discount_amt#2))#21] +Results [1]: [MakeDecimal(sum(UnscaledValue(ws_ext_discount_amt#2))#21,17,2) AS Excess Discount Amount #22] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (34) ++- * ColumnarToRow (33) + +- CometProject (32) + +- CometFilter (31) + +- CometScan parquet spark_catalog.default.date_dim (30) + + +(30) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#18, d_date#23] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,2000-01-27), LessThanOrEqual(d_date,2000-04-26), IsNotNull(d_date_sk)] +ReadSchema: struct + +(31) CometFilter +Input [2]: [d_date_sk#18, d_date#23] +Condition : (((isnotnull(d_date#23) AND (d_date#23 >= 2000-01-27)) AND (d_date#23 <= 2000-04-26)) AND isnotnull(d_date_sk#18)) + +(32) CometProject +Input [2]: [d_date_sk#18, d_date#23] +Arguments: [d_date_sk#18], [d_date_sk#18] + +(33) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#18] + +(34) BroadcastExchange +Input [1]: [d_date_sk#18] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +Subquery:2 Hosting operator id = 11 Hosting Expression = ws_sold_date_sk#9 IN dynamicpruning#4 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q92/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q92/simplified.txt new file mode 100644 index 0000000000..a5e724c1ff --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q92/simplified.txt @@ -0,0 +1,52 @@ +WholeStageCodegen (7) + HashAggregate [sum] [sum(UnscaledValue(ws_ext_discount_amt)),Excess Discount Amount ,sum] + InputAdapter + Exchange #1 + WholeStageCodegen (6) + HashAggregate [ws_ext_discount_amt] [sum,sum] + Project [ws_ext_discount_amt] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_ext_discount_amt,ws_sold_date_sk] + BroadcastHashJoin [i_item_sk,ws_item_sk,ws_ext_discount_amt,(1.3 * avg(ws_ext_discount_amt))] + Project [ws_ext_discount_amt,ws_sold_date_sk,i_item_sk] + BroadcastHashJoin [ws_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk,ws_ext_discount_amt] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_ext_discount_amt,ws_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [i_item_sk] + CometFilter [i_manufact_id,i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_manufact_id] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (4) + Filter [(1.3 * avg(ws_ext_discount_amt))] + HashAggregate [ws_item_sk,sum,count] [avg(UnscaledValue(ws_ext_discount_amt)),(1.3 * avg(ws_ext_discount_amt)),sum,count] + InputAdapter + Exchange [ws_item_sk] #5 + WholeStageCodegen (3) + HashAggregate [ws_item_sk,ws_ext_discount_amt] [sum,count,sum,count] + Project [ws_item_sk,ws_ext_discount_amt] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_ext_discount_amt,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk] #2 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q93/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q93/explain.txt new file mode 100644 index 0000000000..00ed822f2b --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q93/explain.txt @@ -0,0 +1,138 @@ +== Physical Plan == +TakeOrderedAndProject (24) ++- * HashAggregate (23) + +- Exchange (22) + +- * HashAggregate (21) + +- * Project (20) + +- * BroadcastHashJoin Inner BuildRight (19) + :- * Project (13) + : +- * SortMergeJoin Inner (12) + : :- * Sort (5) + : : +- Exchange (4) + : : +- * ColumnarToRow (3) + : : +- CometProject (2) + : : +- CometScan parquet spark_catalog.default.store_sales (1) + : +- * Sort (11) + : +- Exchange (10) + : +- * ColumnarToRow (9) + : +- CometProject (8) + : +- CometFilter (7) + : +- CometScan parquet spark_catalog.default.store_returns (6) + +- BroadcastExchange (18) + +- * ColumnarToRow (17) + +- CometProject (16) + +- CometFilter (15) + +- CometScan parquet spark_catalog.default.reason (14) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [6]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_sales_price#5, ss_sold_date_sk#6] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +ReadSchema: struct + +(2) CometProject +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_sales_price#5, ss_sold_date_sk#6] +Arguments: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_sales_price#5], [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_sales_price#5] + +(3) ColumnarToRow [codegen id : 1] +Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_sales_price#5] + +(4) Exchange +Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_sales_price#5] +Arguments: hashpartitioning(ss_item_sk#1, ss_ticket_number#3, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(5) Sort [codegen id : 2] +Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_sales_price#5] +Arguments: [ss_item_sk#1 ASC NULLS FIRST, ss_ticket_number#3 ASC NULLS FIRST], false, 0 + +(6) Scan parquet spark_catalog.default.store_returns +Output [5]: [sr_item_sk#7, sr_reason_sk#8, sr_ticket_number#9, sr_return_quantity#10, sr_returned_date_sk#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_returns] +PushedFilters: [IsNotNull(sr_item_sk), IsNotNull(sr_ticket_number), IsNotNull(sr_reason_sk)] +ReadSchema: struct + +(7) CometFilter +Input [5]: [sr_item_sk#7, sr_reason_sk#8, sr_ticket_number#9, sr_return_quantity#10, sr_returned_date_sk#11] +Condition : ((isnotnull(sr_item_sk#7) AND isnotnull(sr_ticket_number#9)) AND isnotnull(sr_reason_sk#8)) + +(8) CometProject +Input [5]: [sr_item_sk#7, sr_reason_sk#8, sr_ticket_number#9, sr_return_quantity#10, sr_returned_date_sk#11] +Arguments: [sr_item_sk#7, sr_reason_sk#8, sr_ticket_number#9, sr_return_quantity#10], [sr_item_sk#7, sr_reason_sk#8, sr_ticket_number#9, sr_return_quantity#10] + +(9) ColumnarToRow [codegen id : 3] +Input [4]: [sr_item_sk#7, sr_reason_sk#8, sr_ticket_number#9, sr_return_quantity#10] + +(10) Exchange +Input [4]: [sr_item_sk#7, sr_reason_sk#8, sr_ticket_number#9, sr_return_quantity#10] +Arguments: hashpartitioning(sr_item_sk#7, sr_ticket_number#9, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(11) Sort [codegen id : 4] +Input [4]: [sr_item_sk#7, sr_reason_sk#8, sr_ticket_number#9, sr_return_quantity#10] +Arguments: [sr_item_sk#7 ASC NULLS FIRST, sr_ticket_number#9 ASC NULLS FIRST], false, 0 + +(12) SortMergeJoin [codegen id : 6] +Left keys [2]: [ss_item_sk#1, ss_ticket_number#3] +Right keys [2]: [sr_item_sk#7, sr_ticket_number#9] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 6] +Output [5]: [ss_customer_sk#2, ss_quantity#4, ss_sales_price#5, sr_reason_sk#8, sr_return_quantity#10] +Input [9]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_sales_price#5, sr_item_sk#7, sr_reason_sk#8, sr_ticket_number#9, sr_return_quantity#10] + +(14) Scan parquet spark_catalog.default.reason +Output [2]: [r_reason_sk#12, r_reason_desc#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/reason] +PushedFilters: [IsNotNull(r_reason_desc), EqualTo(r_reason_desc,reason 28 ), IsNotNull(r_reason_sk)] +ReadSchema: struct + +(15) CometFilter +Input [2]: [r_reason_sk#12, r_reason_desc#13] +Condition : ((isnotnull(r_reason_desc#13) AND (r_reason_desc#13 = reason 28 )) AND isnotnull(r_reason_sk#12)) + +(16) CometProject +Input [2]: [r_reason_sk#12, r_reason_desc#13] +Arguments: [r_reason_sk#12], [r_reason_sk#12] + +(17) ColumnarToRow [codegen id : 5] +Input [1]: [r_reason_sk#12] + +(18) BroadcastExchange +Input [1]: [r_reason_sk#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(19) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [sr_reason_sk#8] +Right keys [1]: [r_reason_sk#12] +Join type: Inner +Join condition: None + +(20) Project [codegen id : 6] +Output [2]: [ss_customer_sk#2, CASE WHEN isnotnull(sr_return_quantity#10) THEN (cast((ss_quantity#4 - sr_return_quantity#10) as decimal(10,0)) * ss_sales_price#5) ELSE (cast(ss_quantity#4 as decimal(10,0)) * ss_sales_price#5) END AS act_sales#14] +Input [6]: [ss_customer_sk#2, ss_quantity#4, ss_sales_price#5, sr_reason_sk#8, sr_return_quantity#10, r_reason_sk#12] + +(21) HashAggregate [codegen id : 6] +Input [2]: [ss_customer_sk#2, act_sales#14] +Keys [1]: [ss_customer_sk#2] +Functions [1]: [partial_sum(act_sales#14)] +Aggregate Attributes [2]: [sum#15, isEmpty#16] +Results [3]: [ss_customer_sk#2, sum#17, isEmpty#18] + +(22) Exchange +Input [3]: [ss_customer_sk#2, sum#17, isEmpty#18] +Arguments: hashpartitioning(ss_customer_sk#2, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(23) HashAggregate [codegen id : 7] +Input [3]: [ss_customer_sk#2, sum#17, isEmpty#18] +Keys [1]: [ss_customer_sk#2] +Functions [1]: [sum(act_sales#14)] +Aggregate Attributes [1]: [sum(act_sales#14)#19] +Results [2]: [ss_customer_sk#2, sum(act_sales#14)#19 AS sumsales#20] + +(24) TakeOrderedAndProject +Input [2]: [ss_customer_sk#2, sumsales#20] +Arguments: 100, [sumsales#20 ASC NULLS FIRST, ss_customer_sk#2 ASC NULLS FIRST], [ss_customer_sk#2, sumsales#20] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q93/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q93/simplified.txt new file mode 100644 index 0000000000..3ec7ac7b6a --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q93/simplified.txt @@ -0,0 +1,40 @@ +TakeOrderedAndProject [sumsales,ss_customer_sk] + WholeStageCodegen (7) + HashAggregate [ss_customer_sk,sum,isEmpty] [sum(act_sales),sumsales,sum,isEmpty] + InputAdapter + Exchange [ss_customer_sk] #1 + WholeStageCodegen (6) + HashAggregate [ss_customer_sk,act_sales] [sum,isEmpty,sum,isEmpty] + Project [ss_customer_sk,sr_return_quantity,ss_quantity,ss_sales_price] + BroadcastHashJoin [sr_reason_sk,r_reason_sk] + Project [ss_customer_sk,ss_quantity,ss_sales_price,sr_reason_sk,sr_return_quantity] + SortMergeJoin [ss_item_sk,ss_ticket_number,sr_item_sk,sr_ticket_number] + InputAdapter + WholeStageCodegen (2) + Sort [ss_item_sk,ss_ticket_number] + InputAdapter + Exchange [ss_item_sk,ss_ticket_number] #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [ss_item_sk,ss_customer_sk,ss_ticket_number,ss_quantity,ss_sales_price] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_ticket_number,ss_quantity,ss_sales_price,ss_sold_date_sk] + InputAdapter + WholeStageCodegen (4) + Sort [sr_item_sk,sr_ticket_number] + InputAdapter + Exchange [sr_item_sk,sr_ticket_number] #3 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometProject [sr_item_sk,sr_reason_sk,sr_ticket_number,sr_return_quantity] + CometFilter [sr_item_sk,sr_ticket_number,sr_reason_sk] + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_reason_sk,sr_ticket_number,sr_return_quantity,sr_returned_date_sk] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (5) + ColumnarToRow + InputAdapter + CometProject [r_reason_sk] + CometFilter [r_reason_desc,r_reason_sk] + CometScan parquet spark_catalog.default.reason [r_reason_sk,r_reason_desc] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q94/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q94/explain.txt new file mode 100644 index 0000000000..d71f96e158 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q94/explain.txt @@ -0,0 +1,260 @@ +== Physical Plan == +* HashAggregate (45) ++- Exchange (44) + +- * HashAggregate (43) + +- * HashAggregate (42) + +- * HashAggregate (41) + +- * Project (40) + +- * BroadcastHashJoin Inner BuildRight (39) + :- * Project (33) + : +- * BroadcastHashJoin Inner BuildRight (32) + : :- * Project (26) + : : +- * BroadcastHashJoin Inner BuildRight (25) + : : :- * SortMergeJoin LeftAnti (19) + : : : :- * Project (13) + : : : : +- * SortMergeJoin LeftSemi (12) + : : : : :- * Sort (6) + : : : : : +- Exchange (5) + : : : : : +- * ColumnarToRow (4) + : : : : : +- CometProject (3) + : : : : : +- CometFilter (2) + : : : : : +- CometScan parquet spark_catalog.default.web_sales (1) + : : : : +- * Sort (11) + : : : : +- Exchange (10) + : : : : +- * ColumnarToRow (9) + : : : : +- CometProject (8) + : : : : +- CometScan parquet spark_catalog.default.web_sales (7) + : : : +- * Sort (18) + : : : +- Exchange (17) + : : : +- * ColumnarToRow (16) + : : : +- CometProject (15) + : : : +- CometScan parquet spark_catalog.default.web_returns (14) + : : +- BroadcastExchange (24) + : : +- * ColumnarToRow (23) + : : +- CometProject (22) + : : +- CometFilter (21) + : : +- CometScan parquet spark_catalog.default.date_dim (20) + : +- BroadcastExchange (31) + : +- * ColumnarToRow (30) + : +- CometProject (29) + : +- CometFilter (28) + : +- CometScan parquet spark_catalog.default.customer_address (27) + +- BroadcastExchange (38) + +- * ColumnarToRow (37) + +- CometProject (36) + +- CometFilter (35) + +- CometScan parquet spark_catalog.default.web_site (34) + + +(1) Scan parquet spark_catalog.default.web_sales +Output [8]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_warehouse_sk#4, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7, ws_sold_date_sk#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_sales] +PushedFilters: [IsNotNull(ws_ship_date_sk), IsNotNull(ws_ship_addr_sk), IsNotNull(ws_web_site_sk)] +ReadSchema: struct + +(2) CometFilter +Input [8]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_warehouse_sk#4, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7, ws_sold_date_sk#8] +Condition : ((isnotnull(ws_ship_date_sk#1) AND isnotnull(ws_ship_addr_sk#2)) AND isnotnull(ws_web_site_sk#3)) + +(3) CometProject +Input [8]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_warehouse_sk#4, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7, ws_sold_date_sk#8] +Arguments: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_warehouse_sk#4, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7], [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_warehouse_sk#4, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7] + +(4) ColumnarToRow [codegen id : 1] +Input [7]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_warehouse_sk#4, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7] + +(5) Exchange +Input [7]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_warehouse_sk#4, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7] +Arguments: hashpartitioning(ws_order_number#5, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(6) Sort [codegen id : 2] +Input [7]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_warehouse_sk#4, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7] +Arguments: [ws_order_number#5 ASC NULLS FIRST], false, 0 + +(7) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_warehouse_sk#9, ws_order_number#10, ws_sold_date_sk#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_sales] +ReadSchema: struct + +(8) CometProject +Input [3]: [ws_warehouse_sk#9, ws_order_number#10, ws_sold_date_sk#11] +Arguments: [ws_warehouse_sk#9, ws_order_number#10], [ws_warehouse_sk#9, ws_order_number#10] + +(9) ColumnarToRow [codegen id : 3] +Input [2]: [ws_warehouse_sk#9, ws_order_number#10] + +(10) Exchange +Input [2]: [ws_warehouse_sk#9, ws_order_number#10] +Arguments: hashpartitioning(ws_order_number#10, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(11) Sort [codegen id : 4] +Input [2]: [ws_warehouse_sk#9, ws_order_number#10] +Arguments: [ws_order_number#10 ASC NULLS FIRST], false, 0 + +(12) SortMergeJoin [codegen id : 5] +Left keys [1]: [ws_order_number#5] +Right keys [1]: [ws_order_number#10] +Join type: LeftSemi +Join condition: NOT (ws_warehouse_sk#4 = ws_warehouse_sk#9) + +(13) Project [codegen id : 5] +Output [6]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7] +Input [7]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_warehouse_sk#4, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7] + +(14) Scan parquet spark_catalog.default.web_returns +Output [2]: [wr_order_number#12, wr_returned_date_sk#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_returns] +ReadSchema: struct + +(15) CometProject +Input [2]: [wr_order_number#12, wr_returned_date_sk#13] +Arguments: [wr_order_number#12], [wr_order_number#12] + +(16) ColumnarToRow [codegen id : 6] +Input [1]: [wr_order_number#12] + +(17) Exchange +Input [1]: [wr_order_number#12] +Arguments: hashpartitioning(wr_order_number#12, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(18) Sort [codegen id : 7] +Input [1]: [wr_order_number#12] +Arguments: [wr_order_number#12 ASC NULLS FIRST], false, 0 + +(19) SortMergeJoin [codegen id : 11] +Left keys [1]: [ws_order_number#5] +Right keys [1]: [wr_order_number#12] +Join type: LeftAnti +Join condition: None + +(20) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#14, d_date#15] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,1999-02-01), LessThanOrEqual(d_date,1999-04-02), IsNotNull(d_date_sk)] +ReadSchema: struct + +(21) CometFilter +Input [2]: [d_date_sk#14, d_date#15] +Condition : (((isnotnull(d_date#15) AND (d_date#15 >= 1999-02-01)) AND (d_date#15 <= 1999-04-02)) AND isnotnull(d_date_sk#14)) + +(22) CometProject +Input [2]: [d_date_sk#14, d_date#15] +Arguments: [d_date_sk#14], [d_date_sk#14] + +(23) ColumnarToRow [codegen id : 8] +Input [1]: [d_date_sk#14] + +(24) BroadcastExchange +Input [1]: [d_date_sk#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(25) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [ws_ship_date_sk#1] +Right keys [1]: [d_date_sk#14] +Join type: Inner +Join condition: None + +(26) Project [codegen id : 11] +Output [5]: [ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7] +Input [7]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7, d_date_sk#14] + +(27) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#16, ca_state#17] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_state), EqualTo(ca_state,IL), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(28) CometFilter +Input [2]: [ca_address_sk#16, ca_state#17] +Condition : ((isnotnull(ca_state#17) AND (ca_state#17 = IL)) AND isnotnull(ca_address_sk#16)) + +(29) CometProject +Input [2]: [ca_address_sk#16, ca_state#17] +Arguments: [ca_address_sk#16], [ca_address_sk#16] + +(30) ColumnarToRow [codegen id : 9] +Input [1]: [ca_address_sk#16] + +(31) BroadcastExchange +Input [1]: [ca_address_sk#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +(32) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [ws_ship_addr_sk#2] +Right keys [1]: [ca_address_sk#16] +Join type: Inner +Join condition: None + +(33) Project [codegen id : 11] +Output [4]: [ws_web_site_sk#3, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7] +Input [6]: [ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7, ca_address_sk#16] + +(34) Scan parquet spark_catalog.default.web_site +Output [2]: [web_site_sk#18, web_company_name#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_site] +PushedFilters: [IsNotNull(web_company_name), EqualTo(web_company_name,pri ), IsNotNull(web_site_sk)] +ReadSchema: struct + +(35) CometFilter +Input [2]: [web_site_sk#18, web_company_name#19] +Condition : ((isnotnull(web_company_name#19) AND (web_company_name#19 = pri )) AND isnotnull(web_site_sk#18)) + +(36) CometProject +Input [2]: [web_site_sk#18, web_company_name#19] +Arguments: [web_site_sk#18], [web_site_sk#18] + +(37) ColumnarToRow [codegen id : 10] +Input [1]: [web_site_sk#18] + +(38) BroadcastExchange +Input [1]: [web_site_sk#18] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6] + +(39) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [ws_web_site_sk#3] +Right keys [1]: [web_site_sk#18] +Join type: Inner +Join condition: None + +(40) Project [codegen id : 11] +Output [3]: [ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7] +Input [5]: [ws_web_site_sk#3, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7, web_site_sk#18] + +(41) HashAggregate [codegen id : 11] +Input [3]: [ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7] +Keys [1]: [ws_order_number#5] +Functions [2]: [partial_sum(UnscaledValue(ws_ext_ship_cost#6)), partial_sum(UnscaledValue(ws_net_profit#7))] +Aggregate Attributes [2]: [sum(UnscaledValue(ws_ext_ship_cost#6))#20, sum(UnscaledValue(ws_net_profit#7))#21] +Results [3]: [ws_order_number#5, sum#22, sum#23] + +(42) HashAggregate [codegen id : 11] +Input [3]: [ws_order_number#5, sum#22, sum#23] +Keys [1]: [ws_order_number#5] +Functions [2]: [merge_sum(UnscaledValue(ws_ext_ship_cost#6)), merge_sum(UnscaledValue(ws_net_profit#7))] +Aggregate Attributes [2]: [sum(UnscaledValue(ws_ext_ship_cost#6))#20, sum(UnscaledValue(ws_net_profit#7))#21] +Results [3]: [ws_order_number#5, sum#22, sum#23] + +(43) HashAggregate [codegen id : 11] +Input [3]: [ws_order_number#5, sum#22, sum#23] +Keys: [] +Functions [3]: [merge_sum(UnscaledValue(ws_ext_ship_cost#6)), merge_sum(UnscaledValue(ws_net_profit#7)), partial_count(distinct ws_order_number#5)] +Aggregate Attributes [3]: [sum(UnscaledValue(ws_ext_ship_cost#6))#20, sum(UnscaledValue(ws_net_profit#7))#21, count(ws_order_number#5)#24] +Results [3]: [sum#22, sum#23, count#25] + +(44) Exchange +Input [3]: [sum#22, sum#23, count#25] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=7] + +(45) HashAggregate [codegen id : 12] +Input [3]: [sum#22, sum#23, count#25] +Keys: [] +Functions [3]: [sum(UnscaledValue(ws_ext_ship_cost#6)), sum(UnscaledValue(ws_net_profit#7)), count(distinct ws_order_number#5)] +Aggregate Attributes [3]: [sum(UnscaledValue(ws_ext_ship_cost#6))#20, sum(UnscaledValue(ws_net_profit#7))#21, count(ws_order_number#5)#24] +Results [3]: [count(ws_order_number#5)#24 AS order count #26, MakeDecimal(sum(UnscaledValue(ws_ext_ship_cost#6))#20,17,2) AS total shipping cost #27, MakeDecimal(sum(UnscaledValue(ws_net_profit#7))#21,17,2) AS total net profit #28] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q94/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q94/simplified.txt new file mode 100644 index 0000000000..34ddde7687 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q94/simplified.txt @@ -0,0 +1,74 @@ +WholeStageCodegen (12) + HashAggregate [sum,sum,count] [sum(UnscaledValue(ws_ext_ship_cost)),sum(UnscaledValue(ws_net_profit)),count(ws_order_number),order count ,total shipping cost ,total net profit ,sum,sum,count] + InputAdapter + Exchange #1 + WholeStageCodegen (11) + HashAggregate [ws_order_number] [sum(UnscaledValue(ws_ext_ship_cost)),sum(UnscaledValue(ws_net_profit)),count(ws_order_number),sum,sum,count,sum,sum,count] + HashAggregate [ws_order_number] [sum(UnscaledValue(ws_ext_ship_cost)),sum(UnscaledValue(ws_net_profit)),sum,sum,sum,sum] + HashAggregate [ws_order_number,ws_ext_ship_cost,ws_net_profit] [sum(UnscaledValue(ws_ext_ship_cost)),sum(UnscaledValue(ws_net_profit)),sum,sum,sum,sum] + Project [ws_order_number,ws_ext_ship_cost,ws_net_profit] + BroadcastHashJoin [ws_web_site_sk,web_site_sk] + Project [ws_web_site_sk,ws_order_number,ws_ext_ship_cost,ws_net_profit] + BroadcastHashJoin [ws_ship_addr_sk,ca_address_sk] + Project [ws_ship_addr_sk,ws_web_site_sk,ws_order_number,ws_ext_ship_cost,ws_net_profit] + BroadcastHashJoin [ws_ship_date_sk,d_date_sk] + SortMergeJoin [ws_order_number,wr_order_number] + InputAdapter + WholeStageCodegen (5) + Project [ws_ship_date_sk,ws_ship_addr_sk,ws_web_site_sk,ws_order_number,ws_ext_ship_cost,ws_net_profit] + SortMergeJoin [ws_order_number,ws_order_number,ws_warehouse_sk,ws_warehouse_sk] + InputAdapter + WholeStageCodegen (2) + Sort [ws_order_number] + InputAdapter + Exchange [ws_order_number] #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [ws_ship_date_sk,ws_ship_addr_sk,ws_web_site_sk,ws_warehouse_sk,ws_order_number,ws_ext_ship_cost,ws_net_profit] + CometFilter [ws_ship_date_sk,ws_ship_addr_sk,ws_web_site_sk] + CometScan parquet spark_catalog.default.web_sales [ws_ship_date_sk,ws_ship_addr_sk,ws_web_site_sk,ws_warehouse_sk,ws_order_number,ws_ext_ship_cost,ws_net_profit,ws_sold_date_sk] + InputAdapter + WholeStageCodegen (4) + Sort [ws_order_number] + InputAdapter + Exchange [ws_order_number] #3 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometProject [ws_warehouse_sk,ws_order_number] + CometScan parquet spark_catalog.default.web_sales [ws_warehouse_sk,ws_order_number,ws_sold_date_sk] + InputAdapter + WholeStageCodegen (7) + Sort [wr_order_number] + InputAdapter + Exchange [wr_order_number] #4 + WholeStageCodegen (6) + ColumnarToRow + InputAdapter + CometProject [wr_order_number] + CometScan parquet spark_catalog.default.web_returns [wr_order_number,wr_returned_date_sk] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (8) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (9) + ColumnarToRow + InputAdapter + CometProject [ca_address_sk] + CometFilter [ca_state,ca_address_sk] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (10) + ColumnarToRow + InputAdapter + CometProject [web_site_sk] + CometFilter [web_company_name,web_site_sk] + CometScan parquet spark_catalog.default.web_site [web_site_sk,web_company_name] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q95/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q95/explain.txt new file mode 100644 index 0000000000..c8cdce0553 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q95/explain.txt @@ -0,0 +1,330 @@ +== Physical Plan == +* HashAggregate (58) ++- Exchange (57) + +- * HashAggregate (56) + +- * HashAggregate (55) + +- * HashAggregate (54) + +- * Project (53) + +- * BroadcastHashJoin Inner BuildRight (52) + :- * Project (46) + : +- * BroadcastHashJoin Inner BuildRight (45) + : :- * Project (39) + : : +- * BroadcastHashJoin Inner BuildRight (38) + : : :- * SortMergeJoin LeftSemi (32) + : : : :- * SortMergeJoin LeftSemi (17) + : : : : :- * Sort (6) + : : : : : +- Exchange (5) + : : : : : +- * ColumnarToRow (4) + : : : : : +- CometProject (3) + : : : : : +- CometFilter (2) + : : : : : +- CometScan parquet spark_catalog.default.web_sales (1) + : : : : +- * Project (16) + : : : : +- * SortMergeJoin Inner (15) + : : : : :- * Sort (12) + : : : : : +- Exchange (11) + : : : : : +- * ColumnarToRow (10) + : : : : : +- CometProject (9) + : : : : : +- CometFilter (8) + : : : : : +- CometScan parquet spark_catalog.default.web_sales (7) + : : : : +- * Sort (14) + : : : : +- ReusedExchange (13) + : : : +- * Project (31) + : : : +- * SortMergeJoin Inner (30) + : : : :- * Sort (23) + : : : : +- Exchange (22) + : : : : +- * ColumnarToRow (21) + : : : : +- CometProject (20) + : : : : +- CometFilter (19) + : : : : +- CometScan parquet spark_catalog.default.web_returns (18) + : : : +- * Project (29) + : : : +- * SortMergeJoin Inner (28) + : : : :- * Sort (25) + : : : : +- ReusedExchange (24) + : : : +- * Sort (27) + : : : +- ReusedExchange (26) + : : +- BroadcastExchange (37) + : : +- * ColumnarToRow (36) + : : +- CometProject (35) + : : +- CometFilter (34) + : : +- CometScan parquet spark_catalog.default.date_dim (33) + : +- BroadcastExchange (44) + : +- * ColumnarToRow (43) + : +- CometProject (42) + : +- CometFilter (41) + : +- CometScan parquet spark_catalog.default.customer_address (40) + +- BroadcastExchange (51) + +- * ColumnarToRow (50) + +- CometProject (49) + +- CometFilter (48) + +- CometScan parquet spark_catalog.default.web_site (47) + + +(1) Scan parquet spark_catalog.default.web_sales +Output [7]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6, ws_sold_date_sk#7] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_sales] +PushedFilters: [IsNotNull(ws_ship_date_sk), IsNotNull(ws_ship_addr_sk), IsNotNull(ws_web_site_sk)] +ReadSchema: struct + +(2) CometFilter +Input [7]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6, ws_sold_date_sk#7] +Condition : ((isnotnull(ws_ship_date_sk#1) AND isnotnull(ws_ship_addr_sk#2)) AND isnotnull(ws_web_site_sk#3)) + +(3) CometProject +Input [7]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6, ws_sold_date_sk#7] +Arguments: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6], [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6] + +(4) ColumnarToRow [codegen id : 1] +Input [6]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6] + +(5) Exchange +Input [6]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6] +Arguments: hashpartitioning(ws_order_number#4, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(6) Sort [codegen id : 2] +Input [6]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6] +Arguments: [ws_order_number#4 ASC NULLS FIRST], false, 0 + +(7) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_warehouse_sk#8, ws_order_number#9, ws_sold_date_sk#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_sales] +PushedFilters: [IsNotNull(ws_order_number), IsNotNull(ws_warehouse_sk)] +ReadSchema: struct + +(8) CometFilter +Input [3]: [ws_warehouse_sk#8, ws_order_number#9, ws_sold_date_sk#10] +Condition : (isnotnull(ws_order_number#9) AND isnotnull(ws_warehouse_sk#8)) + +(9) CometProject +Input [3]: [ws_warehouse_sk#8, ws_order_number#9, ws_sold_date_sk#10] +Arguments: [ws_warehouse_sk#8, ws_order_number#9], [ws_warehouse_sk#8, ws_order_number#9] + +(10) ColumnarToRow [codegen id : 3] +Input [2]: [ws_warehouse_sk#8, ws_order_number#9] + +(11) Exchange +Input [2]: [ws_warehouse_sk#8, ws_order_number#9] +Arguments: hashpartitioning(ws_order_number#9, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(12) Sort [codegen id : 4] +Input [2]: [ws_warehouse_sk#8, ws_order_number#9] +Arguments: [ws_order_number#9 ASC NULLS FIRST], false, 0 + +(13) ReusedExchange [Reuses operator id: 11] +Output [2]: [ws_warehouse_sk#11, ws_order_number#12] + +(14) Sort [codegen id : 6] +Input [2]: [ws_warehouse_sk#11, ws_order_number#12] +Arguments: [ws_order_number#12 ASC NULLS FIRST], false, 0 + +(15) SortMergeJoin [codegen id : 7] +Left keys [1]: [ws_order_number#9] +Right keys [1]: [ws_order_number#12] +Join type: Inner +Join condition: NOT (ws_warehouse_sk#8 = ws_warehouse_sk#11) + +(16) Project [codegen id : 7] +Output [1]: [ws_order_number#9] +Input [4]: [ws_warehouse_sk#8, ws_order_number#9, ws_warehouse_sk#11, ws_order_number#12] + +(17) SortMergeJoin [codegen id : 8] +Left keys [1]: [ws_order_number#4] +Right keys [1]: [ws_order_number#9] +Join type: LeftSemi +Join condition: None + +(18) Scan parquet spark_catalog.default.web_returns +Output [2]: [wr_order_number#13, wr_returned_date_sk#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_returns] +PushedFilters: [IsNotNull(wr_order_number)] +ReadSchema: struct + +(19) CometFilter +Input [2]: [wr_order_number#13, wr_returned_date_sk#14] +Condition : isnotnull(wr_order_number#13) + +(20) CometProject +Input [2]: [wr_order_number#13, wr_returned_date_sk#14] +Arguments: [wr_order_number#13], [wr_order_number#13] + +(21) ColumnarToRow [codegen id : 9] +Input [1]: [wr_order_number#13] + +(22) Exchange +Input [1]: [wr_order_number#13] +Arguments: hashpartitioning(wr_order_number#13, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(23) Sort [codegen id : 10] +Input [1]: [wr_order_number#13] +Arguments: [wr_order_number#13 ASC NULLS FIRST], false, 0 + +(24) ReusedExchange [Reuses operator id: 11] +Output [2]: [ws_warehouse_sk#15, ws_order_number#16] + +(25) Sort [codegen id : 12] +Input [2]: [ws_warehouse_sk#15, ws_order_number#16] +Arguments: [ws_order_number#16 ASC NULLS FIRST], false, 0 + +(26) ReusedExchange [Reuses operator id: 11] +Output [2]: [ws_warehouse_sk#17, ws_order_number#18] + +(27) Sort [codegen id : 14] +Input [2]: [ws_warehouse_sk#17, ws_order_number#18] +Arguments: [ws_order_number#18 ASC NULLS FIRST], false, 0 + +(28) SortMergeJoin [codegen id : 15] +Left keys [1]: [ws_order_number#16] +Right keys [1]: [ws_order_number#18] +Join type: Inner +Join condition: NOT (ws_warehouse_sk#15 = ws_warehouse_sk#17) + +(29) Project [codegen id : 15] +Output [1]: [ws_order_number#16] +Input [4]: [ws_warehouse_sk#15, ws_order_number#16, ws_warehouse_sk#17, ws_order_number#18] + +(30) SortMergeJoin [codegen id : 16] +Left keys [1]: [wr_order_number#13] +Right keys [1]: [ws_order_number#16] +Join type: Inner +Join condition: None + +(31) Project [codegen id : 16] +Output [1]: [wr_order_number#13] +Input [2]: [wr_order_number#13, ws_order_number#16] + +(32) SortMergeJoin [codegen id : 20] +Left keys [1]: [ws_order_number#4] +Right keys [1]: [wr_order_number#13] +Join type: LeftSemi +Join condition: None + +(33) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#19, d_date#20] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,1999-02-01), LessThanOrEqual(d_date,1999-04-02), IsNotNull(d_date_sk)] +ReadSchema: struct + +(34) CometFilter +Input [2]: [d_date_sk#19, d_date#20] +Condition : (((isnotnull(d_date#20) AND (d_date#20 >= 1999-02-01)) AND (d_date#20 <= 1999-04-02)) AND isnotnull(d_date_sk#19)) + +(35) CometProject +Input [2]: [d_date_sk#19, d_date#20] +Arguments: [d_date_sk#19], [d_date_sk#19] + +(36) ColumnarToRow [codegen id : 17] +Input [1]: [d_date_sk#19] + +(37) BroadcastExchange +Input [1]: [d_date_sk#19] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(38) BroadcastHashJoin [codegen id : 20] +Left keys [1]: [ws_ship_date_sk#1] +Right keys [1]: [d_date_sk#19] +Join type: Inner +Join condition: None + +(39) Project [codegen id : 20] +Output [5]: [ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6] +Input [7]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6, d_date_sk#19] + +(40) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#21, ca_state#22] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_state), EqualTo(ca_state,IL), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(41) CometFilter +Input [2]: [ca_address_sk#21, ca_state#22] +Condition : ((isnotnull(ca_state#22) AND (ca_state#22 = IL)) AND isnotnull(ca_address_sk#21)) + +(42) CometProject +Input [2]: [ca_address_sk#21, ca_state#22] +Arguments: [ca_address_sk#21], [ca_address_sk#21] + +(43) ColumnarToRow [codegen id : 18] +Input [1]: [ca_address_sk#21] + +(44) BroadcastExchange +Input [1]: [ca_address_sk#21] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +(45) BroadcastHashJoin [codegen id : 20] +Left keys [1]: [ws_ship_addr_sk#2] +Right keys [1]: [ca_address_sk#21] +Join type: Inner +Join condition: None + +(46) Project [codegen id : 20] +Output [4]: [ws_web_site_sk#3, ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6] +Input [6]: [ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6, ca_address_sk#21] + +(47) Scan parquet spark_catalog.default.web_site +Output [2]: [web_site_sk#23, web_company_name#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_site] +PushedFilters: [IsNotNull(web_company_name), EqualTo(web_company_name,pri ), IsNotNull(web_site_sk)] +ReadSchema: struct + +(48) CometFilter +Input [2]: [web_site_sk#23, web_company_name#24] +Condition : ((isnotnull(web_company_name#24) AND (web_company_name#24 = pri )) AND isnotnull(web_site_sk#23)) + +(49) CometProject +Input [2]: [web_site_sk#23, web_company_name#24] +Arguments: [web_site_sk#23], [web_site_sk#23] + +(50) ColumnarToRow [codegen id : 19] +Input [1]: [web_site_sk#23] + +(51) BroadcastExchange +Input [1]: [web_site_sk#23] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6] + +(52) BroadcastHashJoin [codegen id : 20] +Left keys [1]: [ws_web_site_sk#3] +Right keys [1]: [web_site_sk#23] +Join type: Inner +Join condition: None + +(53) Project [codegen id : 20] +Output [3]: [ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6] +Input [5]: [ws_web_site_sk#3, ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6, web_site_sk#23] + +(54) HashAggregate [codegen id : 20] +Input [3]: [ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6] +Keys [1]: [ws_order_number#4] +Functions [2]: [partial_sum(UnscaledValue(ws_ext_ship_cost#5)), partial_sum(UnscaledValue(ws_net_profit#6))] +Aggregate Attributes [2]: [sum(UnscaledValue(ws_ext_ship_cost#5))#25, sum(UnscaledValue(ws_net_profit#6))#26] +Results [3]: [ws_order_number#4, sum#27, sum#28] + +(55) HashAggregate [codegen id : 20] +Input [3]: [ws_order_number#4, sum#27, sum#28] +Keys [1]: [ws_order_number#4] +Functions [2]: [merge_sum(UnscaledValue(ws_ext_ship_cost#5)), merge_sum(UnscaledValue(ws_net_profit#6))] +Aggregate Attributes [2]: [sum(UnscaledValue(ws_ext_ship_cost#5))#25, sum(UnscaledValue(ws_net_profit#6))#26] +Results [3]: [ws_order_number#4, sum#27, sum#28] + +(56) HashAggregate [codegen id : 20] +Input [3]: [ws_order_number#4, sum#27, sum#28] +Keys: [] +Functions [3]: [merge_sum(UnscaledValue(ws_ext_ship_cost#5)), merge_sum(UnscaledValue(ws_net_profit#6)), partial_count(distinct ws_order_number#4)] +Aggregate Attributes [3]: [sum(UnscaledValue(ws_ext_ship_cost#5))#25, sum(UnscaledValue(ws_net_profit#6))#26, count(ws_order_number#4)#29] +Results [3]: [sum#27, sum#28, count#30] + +(57) Exchange +Input [3]: [sum#27, sum#28, count#30] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=7] + +(58) HashAggregate [codegen id : 21] +Input [3]: [sum#27, sum#28, count#30] +Keys: [] +Functions [3]: [sum(UnscaledValue(ws_ext_ship_cost#5)), sum(UnscaledValue(ws_net_profit#6)), count(distinct ws_order_number#4)] +Aggregate Attributes [3]: [sum(UnscaledValue(ws_ext_ship_cost#5))#25, sum(UnscaledValue(ws_net_profit#6))#26, count(ws_order_number#4)#29] +Results [3]: [count(ws_order_number#4)#29 AS order count #31, MakeDecimal(sum(UnscaledValue(ws_ext_ship_cost#5))#25,17,2) AS total shipping cost #32, MakeDecimal(sum(UnscaledValue(ws_net_profit#6))#26,17,2) AS total net profit #33] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q95/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q95/simplified.txt new file mode 100644 index 0000000000..5b699890cf --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q95/simplified.txt @@ -0,0 +1,102 @@ +WholeStageCodegen (21) + HashAggregate [sum,sum,count] [sum(UnscaledValue(ws_ext_ship_cost)),sum(UnscaledValue(ws_net_profit)),count(ws_order_number),order count ,total shipping cost ,total net profit ,sum,sum,count] + InputAdapter + Exchange #1 + WholeStageCodegen (20) + HashAggregate [ws_order_number] [sum(UnscaledValue(ws_ext_ship_cost)),sum(UnscaledValue(ws_net_profit)),count(ws_order_number),sum,sum,count,sum,sum,count] + HashAggregate [ws_order_number] [sum(UnscaledValue(ws_ext_ship_cost)),sum(UnscaledValue(ws_net_profit)),sum,sum,sum,sum] + HashAggregate [ws_order_number,ws_ext_ship_cost,ws_net_profit] [sum(UnscaledValue(ws_ext_ship_cost)),sum(UnscaledValue(ws_net_profit)),sum,sum,sum,sum] + Project [ws_order_number,ws_ext_ship_cost,ws_net_profit] + BroadcastHashJoin [ws_web_site_sk,web_site_sk] + Project [ws_web_site_sk,ws_order_number,ws_ext_ship_cost,ws_net_profit] + BroadcastHashJoin [ws_ship_addr_sk,ca_address_sk] + Project [ws_ship_addr_sk,ws_web_site_sk,ws_order_number,ws_ext_ship_cost,ws_net_profit] + BroadcastHashJoin [ws_ship_date_sk,d_date_sk] + SortMergeJoin [ws_order_number,wr_order_number] + InputAdapter + WholeStageCodegen (8) + SortMergeJoin [ws_order_number,ws_order_number] + InputAdapter + WholeStageCodegen (2) + Sort [ws_order_number] + InputAdapter + Exchange [ws_order_number] #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [ws_ship_date_sk,ws_ship_addr_sk,ws_web_site_sk,ws_order_number,ws_ext_ship_cost,ws_net_profit] + CometFilter [ws_ship_date_sk,ws_ship_addr_sk,ws_web_site_sk] + CometScan parquet spark_catalog.default.web_sales [ws_ship_date_sk,ws_ship_addr_sk,ws_web_site_sk,ws_order_number,ws_ext_ship_cost,ws_net_profit,ws_sold_date_sk] + InputAdapter + WholeStageCodegen (7) + Project [ws_order_number] + SortMergeJoin [ws_order_number,ws_order_number,ws_warehouse_sk,ws_warehouse_sk] + InputAdapter + WholeStageCodegen (4) + Sort [ws_order_number] + InputAdapter + Exchange [ws_order_number] #3 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometProject [ws_warehouse_sk,ws_order_number] + CometFilter [ws_order_number,ws_warehouse_sk] + CometScan parquet spark_catalog.default.web_sales [ws_warehouse_sk,ws_order_number,ws_sold_date_sk] + InputAdapter + WholeStageCodegen (6) + Sort [ws_order_number] + InputAdapter + ReusedExchange [ws_warehouse_sk,ws_order_number] #3 + InputAdapter + WholeStageCodegen (16) + Project [wr_order_number] + SortMergeJoin [wr_order_number,ws_order_number] + InputAdapter + WholeStageCodegen (10) + Sort [wr_order_number] + InputAdapter + Exchange [wr_order_number] #4 + WholeStageCodegen (9) + ColumnarToRow + InputAdapter + CometProject [wr_order_number] + CometFilter [wr_order_number] + CometScan parquet spark_catalog.default.web_returns [wr_order_number,wr_returned_date_sk] + InputAdapter + WholeStageCodegen (15) + Project [ws_order_number] + SortMergeJoin [ws_order_number,ws_order_number,ws_warehouse_sk,ws_warehouse_sk] + InputAdapter + WholeStageCodegen (12) + Sort [ws_order_number] + InputAdapter + ReusedExchange [ws_warehouse_sk,ws_order_number] #3 + InputAdapter + WholeStageCodegen (14) + Sort [ws_order_number] + InputAdapter + ReusedExchange [ws_warehouse_sk,ws_order_number] #3 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (17) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (18) + ColumnarToRow + InputAdapter + CometProject [ca_address_sk] + CometFilter [ca_state,ca_address_sk] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (19) + ColumnarToRow + InputAdapter + CometProject [web_site_sk] + CometFilter [web_company_name,web_site_sk] + CometScan parquet spark_catalog.default.web_site [web_site_sk,web_company_name] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q96/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q96/explain.txt new file mode 100644 index 0000000000..60c262e9c4 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q96/explain.txt @@ -0,0 +1,163 @@ +== Physical Plan == +* HashAggregate (28) ++- Exchange (27) + +- * HashAggregate (26) + +- * Project (25) + +- * BroadcastHashJoin Inner BuildRight (24) + :- * Project (18) + : +- * BroadcastHashJoin Inner BuildRight (17) + : :- * Project (11) + : : +- * BroadcastHashJoin Inner BuildRight (10) + : : :- * ColumnarToRow (4) + : : : +- CometProject (3) + : : : +- CometFilter (2) + : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : +- BroadcastExchange (9) + : : +- * ColumnarToRow (8) + : : +- CometProject (7) + : : +- CometFilter (6) + : : +- CometScan parquet spark_catalog.default.household_demographics (5) + : +- BroadcastExchange (16) + : +- * ColumnarToRow (15) + : +- CometProject (14) + : +- CometFilter (13) + : +- CometScan parquet spark_catalog.default.time_dim (12) + +- BroadcastExchange (23) + +- * ColumnarToRow (22) + +- CometProject (21) + +- CometFilter (20) + +- CometScan parquet spark_catalog.default.store (19) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_sold_date_sk#4] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_hdemo_sk), IsNotNull(ss_sold_time_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(2) CometFilter +Input [4]: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_sold_date_sk#4] +Condition : ((isnotnull(ss_hdemo_sk#2) AND isnotnull(ss_sold_time_sk#1)) AND isnotnull(ss_store_sk#3)) + +(3) CometProject +Input [4]: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_sold_date_sk#4] +Arguments: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3], [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3] + +(4) ColumnarToRow [codegen id : 4] +Input [3]: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3] + +(5) Scan parquet spark_catalog.default.household_demographics +Output [2]: [hd_demo_sk#5, hd_dep_count#6] +Batched: true +Location [not included in comparison]/{warehouse_dir}/household_demographics] +PushedFilters: [IsNotNull(hd_dep_count), EqualTo(hd_dep_count,7), IsNotNull(hd_demo_sk)] +ReadSchema: struct + +(6) CometFilter +Input [2]: [hd_demo_sk#5, hd_dep_count#6] +Condition : ((isnotnull(hd_dep_count#6) AND (hd_dep_count#6 = 7)) AND isnotnull(hd_demo_sk#5)) + +(7) CometProject +Input [2]: [hd_demo_sk#5, hd_dep_count#6] +Arguments: [hd_demo_sk#5], [hd_demo_sk#5] + +(8) ColumnarToRow [codegen id : 1] +Input [1]: [hd_demo_sk#5] + +(9) BroadcastExchange +Input [1]: [hd_demo_sk#5] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(10) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_hdemo_sk#2] +Right keys [1]: [hd_demo_sk#5] +Join type: Inner +Join condition: None + +(11) Project [codegen id : 4] +Output [2]: [ss_sold_time_sk#1, ss_store_sk#3] +Input [4]: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3, hd_demo_sk#5] + +(12) Scan parquet spark_catalog.default.time_dim +Output [3]: [t_time_sk#7, t_hour#8, t_minute#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/time_dim] +PushedFilters: [IsNotNull(t_hour), IsNotNull(t_minute), EqualTo(t_hour,20), GreaterThanOrEqual(t_minute,30), IsNotNull(t_time_sk)] +ReadSchema: struct + +(13) CometFilter +Input [3]: [t_time_sk#7, t_hour#8, t_minute#9] +Condition : ((((isnotnull(t_hour#8) AND isnotnull(t_minute#9)) AND (t_hour#8 = 20)) AND (t_minute#9 >= 30)) AND isnotnull(t_time_sk#7)) + +(14) CometProject +Input [3]: [t_time_sk#7, t_hour#8, t_minute#9] +Arguments: [t_time_sk#7], [t_time_sk#7] + +(15) ColumnarToRow [codegen id : 2] +Input [1]: [t_time_sk#7] + +(16) BroadcastExchange +Input [1]: [t_time_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(17) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_time_sk#1] +Right keys [1]: [t_time_sk#7] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 4] +Output [1]: [ss_store_sk#3] +Input [3]: [ss_sold_time_sk#1, ss_store_sk#3, t_time_sk#7] + +(19) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#10, s_store_name#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_name), EqualTo(s_store_name,ese), IsNotNull(s_store_sk)] +ReadSchema: struct + +(20) CometFilter +Input [2]: [s_store_sk#10, s_store_name#11] +Condition : ((isnotnull(s_store_name#11) AND (s_store_name#11 = ese)) AND isnotnull(s_store_sk#10)) + +(21) CometProject +Input [2]: [s_store_sk#10, s_store_name#11] +Arguments: [s_store_sk#10], [s_store_sk#10] + +(22) ColumnarToRow [codegen id : 3] +Input [1]: [s_store_sk#10] + +(23) BroadcastExchange +Input [1]: [s_store_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_store_sk#3] +Right keys [1]: [s_store_sk#10] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 4] +Output: [] +Input [2]: [ss_store_sk#3, s_store_sk#10] + +(26) HashAggregate [codegen id : 4] +Input: [] +Keys: [] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#12] +Results [1]: [count#13] + +(27) Exchange +Input [1]: [count#13] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=4] + +(28) HashAggregate [codegen id : 5] +Input [1]: [count#13] +Keys: [] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#14] +Results [1]: [count(1)#14 AS count(1)#15] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q96/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q96/simplified.txt new file mode 100644 index 0000000000..d1438f48eb --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q96/simplified.txt @@ -0,0 +1,41 @@ +WholeStageCodegen (5) + HashAggregate [count] [count(1),count(1),count] + InputAdapter + Exchange #1 + WholeStageCodegen (4) + HashAggregate [count,count] + Project + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_store_sk] + BroadcastHashJoin [ss_sold_time_sk,t_time_sk] + Project [ss_sold_time_sk,ss_store_sk] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + ColumnarToRow + InputAdapter + CometProject [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] + CometFilter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk,ss_sold_date_sk] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [hd_demo_sk] + CometFilter [hd_dep_count,hd_demo_sk] + CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_dep_count] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometProject [t_time_sk] + CometFilter [t_hour,t_minute,t_time_sk] + CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour,t_minute] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometProject [s_store_sk] + CometFilter [s_store_name,s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q97/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q97/explain.txt new file mode 100644 index 0000000000..66ccf4f223 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q97/explain.txt @@ -0,0 +1,179 @@ +== Physical Plan == +* HashAggregate (23) ++- Exchange (22) + +- * HashAggregate (21) + +- * Project (20) + +- * SortMergeJoin FullOuter (19) + :- * Sort (9) + : +- * HashAggregate (8) + : +- Exchange (7) + : +- * HashAggregate (6) + : +- * Project (5) + : +- * BroadcastHashJoin Inner BuildRight (4) + : :- * ColumnarToRow (2) + : : +- CometScan parquet spark_catalog.default.store_sales (1) + : +- ReusedExchange (3) + +- * Sort (18) + +- * HashAggregate (17) + +- Exchange (16) + +- * HashAggregate (15) + +- * Project (14) + +- * BroadcastHashJoin Inner BuildRight (13) + :- * ColumnarToRow (11) + : +- CometScan parquet spark_catalog.default.catalog_sales (10) + +- ReusedExchange (12) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_item_sk#1, ss_customer_sk#2, ss_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#3), dynamicpruningexpression(ss_sold_date_sk#3 IN dynamicpruning#4)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 2] +Input [3]: [ss_item_sk#1, ss_customer_sk#2, ss_sold_date_sk#3] + +(3) ReusedExchange [Reuses operator id: 28] +Output [1]: [d_date_sk#5] + +(4) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [ss_sold_date_sk#3] +Right keys [1]: [d_date_sk#5] +Join type: Inner +Join condition: None + +(5) Project [codegen id : 2] +Output [2]: [ss_item_sk#1, ss_customer_sk#2] +Input [4]: [ss_item_sk#1, ss_customer_sk#2, ss_sold_date_sk#3, d_date_sk#5] + +(6) HashAggregate [codegen id : 2] +Input [2]: [ss_item_sk#1, ss_customer_sk#2] +Keys [2]: [ss_customer_sk#2, ss_item_sk#1] +Functions: [] +Aggregate Attributes: [] +Results [2]: [ss_customer_sk#2, ss_item_sk#1] + +(7) Exchange +Input [2]: [ss_customer_sk#2, ss_item_sk#1] +Arguments: hashpartitioning(ss_customer_sk#2, ss_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(8) HashAggregate [codegen id : 3] +Input [2]: [ss_customer_sk#2, ss_item_sk#1] +Keys [2]: [ss_customer_sk#2, ss_item_sk#1] +Functions: [] +Aggregate Attributes: [] +Results [2]: [ss_customer_sk#2 AS customer_sk#6, ss_item_sk#1 AS item_sk#7] + +(9) Sort [codegen id : 3] +Input [2]: [customer_sk#6, item_sk#7] +Arguments: [customer_sk#6 ASC NULLS FIRST, item_sk#7 ASC NULLS FIRST], false, 0 + +(10) Scan parquet spark_catalog.default.catalog_sales +Output [3]: [cs_bill_customer_sk#8, cs_item_sk#9, cs_sold_date_sk#10] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#10), dynamicpruningexpression(cs_sold_date_sk#10 IN dynamicpruning#11)] +ReadSchema: struct + +(11) ColumnarToRow [codegen id : 5] +Input [3]: [cs_bill_customer_sk#8, cs_item_sk#9, cs_sold_date_sk#10] + +(12) ReusedExchange [Reuses operator id: 28] +Output [1]: [d_date_sk#12] + +(13) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [cs_sold_date_sk#10] +Right keys [1]: [d_date_sk#12] +Join type: Inner +Join condition: None + +(14) Project [codegen id : 5] +Output [2]: [cs_bill_customer_sk#8, cs_item_sk#9] +Input [4]: [cs_bill_customer_sk#8, cs_item_sk#9, cs_sold_date_sk#10, d_date_sk#12] + +(15) HashAggregate [codegen id : 5] +Input [2]: [cs_bill_customer_sk#8, cs_item_sk#9] +Keys [2]: [cs_bill_customer_sk#8, cs_item_sk#9] +Functions: [] +Aggregate Attributes: [] +Results [2]: [cs_bill_customer_sk#8, cs_item_sk#9] + +(16) Exchange +Input [2]: [cs_bill_customer_sk#8, cs_item_sk#9] +Arguments: hashpartitioning(cs_bill_customer_sk#8, cs_item_sk#9, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(17) HashAggregate [codegen id : 6] +Input [2]: [cs_bill_customer_sk#8, cs_item_sk#9] +Keys [2]: [cs_bill_customer_sk#8, cs_item_sk#9] +Functions: [] +Aggregate Attributes: [] +Results [2]: [cs_bill_customer_sk#8 AS customer_sk#13, cs_item_sk#9 AS item_sk#14] + +(18) Sort [codegen id : 6] +Input [2]: [customer_sk#13, item_sk#14] +Arguments: [customer_sk#13 ASC NULLS FIRST, item_sk#14 ASC NULLS FIRST], false, 0 + +(19) SortMergeJoin [codegen id : 7] +Left keys [2]: [customer_sk#6, item_sk#7] +Right keys [2]: [customer_sk#13, item_sk#14] +Join type: FullOuter +Join condition: None + +(20) Project [codegen id : 7] +Output [2]: [customer_sk#6, customer_sk#13] +Input [4]: [customer_sk#6, item_sk#7, customer_sk#13, item_sk#14] + +(21) HashAggregate [codegen id : 7] +Input [2]: [customer_sk#6, customer_sk#13] +Keys: [] +Functions [3]: [partial_sum(CASE WHEN (isnotnull(customer_sk#6) AND isnull(customer_sk#13)) THEN 1 ELSE 0 END), partial_sum(CASE WHEN (isnull(customer_sk#6) AND isnotnull(customer_sk#13)) THEN 1 ELSE 0 END), partial_sum(CASE WHEN (isnotnull(customer_sk#6) AND isnotnull(customer_sk#13)) THEN 1 ELSE 0 END)] +Aggregate Attributes [3]: [sum#15, sum#16, sum#17] +Results [3]: [sum#18, sum#19, sum#20] + +(22) Exchange +Input [3]: [sum#18, sum#19, sum#20] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=3] + +(23) HashAggregate [codegen id : 8] +Input [3]: [sum#18, sum#19, sum#20] +Keys: [] +Functions [3]: [sum(CASE WHEN (isnotnull(customer_sk#6) AND isnull(customer_sk#13)) THEN 1 ELSE 0 END), sum(CASE WHEN (isnull(customer_sk#6) AND isnotnull(customer_sk#13)) THEN 1 ELSE 0 END), sum(CASE WHEN (isnotnull(customer_sk#6) AND isnotnull(customer_sk#13)) THEN 1 ELSE 0 END)] +Aggregate Attributes [3]: [sum(CASE WHEN (isnotnull(customer_sk#6) AND isnull(customer_sk#13)) THEN 1 ELSE 0 END)#21, sum(CASE WHEN (isnull(customer_sk#6) AND isnotnull(customer_sk#13)) THEN 1 ELSE 0 END)#22, sum(CASE WHEN (isnotnull(customer_sk#6) AND isnotnull(customer_sk#13)) THEN 1 ELSE 0 END)#23] +Results [3]: [sum(CASE WHEN (isnotnull(customer_sk#6) AND isnull(customer_sk#13)) THEN 1 ELSE 0 END)#21 AS store_only#24, sum(CASE WHEN (isnull(customer_sk#6) AND isnotnull(customer_sk#13)) THEN 1 ELSE 0 END)#22 AS catalog_only#25, sum(CASE WHEN (isnotnull(customer_sk#6) AND isnotnull(customer_sk#13)) THEN 1 ELSE 0 END)#23 AS store_and_catalog#26] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (28) ++- * ColumnarToRow (27) + +- CometProject (26) + +- CometFilter (25) + +- CometScan parquet spark_catalog.default.date_dim (24) + + +(24) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#5, d_month_seq#27] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)] +ReadSchema: struct + +(25) CometFilter +Input [2]: [d_date_sk#5, d_month_seq#27] +Condition : (((isnotnull(d_month_seq#27) AND (d_month_seq#27 >= 1200)) AND (d_month_seq#27 <= 1211)) AND isnotnull(d_date_sk#5)) + +(26) CometProject +Input [2]: [d_date_sk#5, d_month_seq#27] +Arguments: [d_date_sk#5], [d_date_sk#5] + +(27) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#5] + +(28) BroadcastExchange +Input [1]: [d_date_sk#5] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +Subquery:2 Hosting operator id = 10 Hosting Expression = cs_sold_date_sk#10 IN dynamicpruning#4 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q97/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q97/simplified.txt new file mode 100644 index 0000000000..be9c20a560 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q97/simplified.txt @@ -0,0 +1,47 @@ +WholeStageCodegen (8) + HashAggregate [sum,sum,sum] [sum(CASE WHEN (isnotnull(customer_sk) AND isnull(customer_sk)) THEN 1 ELSE 0 END),sum(CASE WHEN (isnull(customer_sk) AND isnotnull(customer_sk)) THEN 1 ELSE 0 END),sum(CASE WHEN (isnotnull(customer_sk) AND isnotnull(customer_sk)) THEN 1 ELSE 0 END),store_only,catalog_only,store_and_catalog,sum,sum,sum] + InputAdapter + Exchange #1 + WholeStageCodegen (7) + HashAggregate [customer_sk,customer_sk] [sum,sum,sum,sum,sum,sum] + Project [customer_sk,customer_sk] + SortMergeJoin [customer_sk,item_sk,customer_sk,item_sk] + InputAdapter + WholeStageCodegen (3) + Sort [customer_sk,item_sk] + HashAggregate [ss_customer_sk,ss_item_sk] [customer_sk,item_sk] + InputAdapter + Exchange [ss_customer_sk,ss_item_sk] #2 + WholeStageCodegen (2) + HashAggregate [ss_customer_sk,ss_item_sk] + Project [ss_item_sk,ss_customer_sk] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_month_seq,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + WholeStageCodegen (6) + Sort [customer_sk,item_sk] + HashAggregate [cs_bill_customer_sk,cs_item_sk] [customer_sk,item_sk] + InputAdapter + Exchange [cs_bill_customer_sk,cs_item_sk] #4 + WholeStageCodegen (5) + HashAggregate [cs_bill_customer_sk,cs_item_sk] + Project [cs_bill_customer_sk,cs_item_sk] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_item_sk,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q98/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q98/explain.txt new file mode 100644 index 0000000000..3d66a07d07 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q98/explain.txt @@ -0,0 +1,160 @@ +== Physical Plan == +* Project (22) ++- * Sort (21) + +- Exchange (20) + +- * Project (19) + +- Window (18) + +- * Sort (17) + +- Exchange (16) + +- * HashAggregate (15) + +- Exchange (14) + +- * HashAggregate (13) + +- * Project (12) + +- * BroadcastHashJoin Inner BuildRight (11) + :- * Project (9) + : +- * BroadcastHashJoin Inner BuildRight (8) + : :- * ColumnarToRow (3) + : : +- CometFilter (2) + : : +- CometScan parquet spark_catalog.default.store_sales (1) + : +- BroadcastExchange (7) + : +- * ColumnarToRow (6) + : +- CometFilter (5) + : +- CometScan parquet spark_catalog.default.item (4) + +- ReusedExchange (10) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_item_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#3), dynamicpruningexpression(ss_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [ss_item_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3] +Condition : isnotnull(ss_item_sk#1) + +(3) ColumnarToRow [codegen id : 3] +Input [3]: [ss_item_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3] + +(4) Scan parquet spark_catalog.default.item +Output [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [In(i_category, [Books ,Home ,Sports ]), IsNotNull(i_item_sk)] +ReadSchema: struct + +(5) CometFilter +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Condition : (i_category#10 IN (Sports ,Books ,Home ) AND isnotnull(i_item_sk#5)) + +(6) ColumnarToRow [codegen id : 1] +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] + +(7) BroadcastExchange +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#5] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 3] +Output [7]: [ss_ext_sales_price#2, ss_sold_date_sk#3, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Input [9]: [ss_item_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3, i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] + +(10) ReusedExchange [Reuses operator id: 27] +Output [1]: [d_date_sk#11] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_sold_date_sk#3] +Right keys [1]: [d_date_sk#11] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [6]: [ss_ext_sales_price#2, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Input [8]: [ss_ext_sales_price#2, ss_sold_date_sk#3, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10, d_date_sk#11] + +(13) HashAggregate [codegen id : 3] +Input [6]: [ss_ext_sales_price#2, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Keys [5]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8] +Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#2))] +Aggregate Attributes [1]: [sum#12] +Results [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] + +(14) Exchange +Input [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] +Arguments: hashpartitioning(i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 4] +Input [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] +Keys [5]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8] +Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#2))#14] +Results [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#2))#14,17,2) AS itemrevenue#15, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#2))#14,17,2) AS _w0#16, i_item_id#6] + +(16) Exchange +Input [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16, i_item_id#6] +Arguments: hashpartitioning(i_class#9, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(17) Sort [codegen id : 5] +Input [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16, i_item_id#6] +Arguments: [i_class#9 ASC NULLS FIRST], false, 0 + +(18) Window +Input [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16, i_item_id#6] +Arguments: [sum(_w0#16) windowspecdefinition(i_class#9, specifiedwindowframe(RowFrame, unboundedpreceding$(), unboundedfollowing$())) AS _we0#17], [i_class#9] + +(19) Project [codegen id : 6] +Output [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, ((_w0#16 * 100) / _we0#17) AS revenueratio#18, i_item_id#6] +Input [8]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16, i_item_id#6, _we0#17] + +(20) Exchange +Input [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, revenueratio#18, i_item_id#6] +Arguments: rangepartitioning(i_category#10 ASC NULLS FIRST, i_class#9 ASC NULLS FIRST, i_item_id#6 ASC NULLS FIRST, i_item_desc#7 ASC NULLS FIRST, revenueratio#18 ASC NULLS FIRST, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(21) Sort [codegen id : 7] +Input [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, revenueratio#18, i_item_id#6] +Arguments: [i_category#10 ASC NULLS FIRST, i_class#9 ASC NULLS FIRST, i_item_id#6 ASC NULLS FIRST, i_item_desc#7 ASC NULLS FIRST, revenueratio#18 ASC NULLS FIRST], true, 0 + +(22) Project [codegen id : 7] +Output [6]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, revenueratio#18] +Input [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, revenueratio#18, i_item_id#6] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (27) ++- * ColumnarToRow (26) + +- CometProject (25) + +- CometFilter (24) + +- CometScan parquet spark_catalog.default.date_dim (23) + + +(23) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#11, d_date#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,1999-02-22), LessThanOrEqual(d_date,1999-03-24), IsNotNull(d_date_sk)] +ReadSchema: struct + +(24) CometFilter +Input [2]: [d_date_sk#11, d_date#19] +Condition : (((isnotnull(d_date#19) AND (d_date#19 >= 1999-02-22)) AND (d_date#19 <= 1999-03-24)) AND isnotnull(d_date_sk#11)) + +(25) CometProject +Input [2]: [d_date_sk#11, d_date#19] +Arguments: [d_date_sk#11], [d_date_sk#11] + +(26) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#11] + +(27) BroadcastExchange +Input [1]: [d_date_sk#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q98/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q98/simplified.txt new file mode 100644 index 0000000000..9eabb9977c --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q98/simplified.txt @@ -0,0 +1,44 @@ +WholeStageCodegen (7) + Project [i_item_desc,i_category,i_class,i_current_price,itemrevenue,revenueratio] + Sort [i_category,i_class,i_item_id,i_item_desc,revenueratio] + InputAdapter + Exchange [i_category,i_class,i_item_id,i_item_desc,revenueratio] #1 + WholeStageCodegen (6) + Project [i_item_desc,i_category,i_class,i_current_price,itemrevenue,_w0,_we0,i_item_id] + InputAdapter + Window [_w0,i_class] + WholeStageCodegen (5) + Sort [i_class] + InputAdapter + Exchange [i_class] #2 + WholeStageCodegen (4) + HashAggregate [i_item_id,i_item_desc,i_category,i_class,i_current_price,sum] [sum(UnscaledValue(ss_ext_sales_price)),itemrevenue,_w0,sum] + InputAdapter + Exchange [i_item_id,i_item_desc,i_category,i_class,i_current_price] #3 + WholeStageCodegen (3) + HashAggregate [i_item_id,i_item_desc,i_category,i_class,i_current_price,ss_ext_sales_price] [sum,sum] + Project [ss_ext_sales_price,i_item_id,i_item_desc,i_current_price,i_class,i_category] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_ext_sales_price,ss_sold_date_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] + BroadcastHashJoin [ss_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ext_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [i_category,i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] + InputAdapter + ReusedExchange [d_date_sk] #4 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q99/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q99/explain.txt new file mode 100644 index 0000000000..9365550266 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q99/explain.txt @@ -0,0 +1,187 @@ +== Physical Plan == +TakeOrderedAndProject (32) ++- * HashAggregate (31) + +- Exchange (30) + +- * HashAggregate (29) + +- * Project (28) + +- * BroadcastHashJoin Inner BuildRight (27) + :- * Project (21) + : +- * BroadcastHashJoin Inner BuildRight (20) + : :- * Project (15) + : : +- * BroadcastHashJoin Inner BuildRight (14) + : : :- * Project (9) + : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) + : : : +- BroadcastExchange (7) + : : : +- * ColumnarToRow (6) + : : : +- CometFilter (5) + : : : +- CometScan parquet spark_catalog.default.warehouse (4) + : : +- BroadcastExchange (13) + : : +- * ColumnarToRow (12) + : : +- CometFilter (11) + : : +- CometScan parquet spark_catalog.default.ship_mode (10) + : +- BroadcastExchange (19) + : +- * ColumnarToRow (18) + : +- CometFilter (17) + : +- CometScan parquet spark_catalog.default.call_center (16) + +- BroadcastExchange (26) + +- * ColumnarToRow (25) + +- CometProject (24) + +- CometFilter (23) + +- CometScan parquet spark_catalog.default.date_dim (22) + + +(1) Scan parquet spark_catalog.default.catalog_sales +Output [5]: [cs_ship_date_sk#1, cs_call_center_sk#2, cs_ship_mode_sk#3, cs_warehouse_sk#4, cs_sold_date_sk#5] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_sales] +PushedFilters: [IsNotNull(cs_warehouse_sk), IsNotNull(cs_ship_mode_sk), IsNotNull(cs_call_center_sk), IsNotNull(cs_ship_date_sk)] +ReadSchema: struct + +(2) CometFilter +Input [5]: [cs_ship_date_sk#1, cs_call_center_sk#2, cs_ship_mode_sk#3, cs_warehouse_sk#4, cs_sold_date_sk#5] +Condition : (((isnotnull(cs_warehouse_sk#4) AND isnotnull(cs_ship_mode_sk#3)) AND isnotnull(cs_call_center_sk#2)) AND isnotnull(cs_ship_date_sk#1)) + +(3) ColumnarToRow [codegen id : 5] +Input [5]: [cs_ship_date_sk#1, cs_call_center_sk#2, cs_ship_mode_sk#3, cs_warehouse_sk#4, cs_sold_date_sk#5] + +(4) Scan parquet spark_catalog.default.warehouse +Output [2]: [w_warehouse_sk#6, w_warehouse_name#7] +Batched: true +Location [not included in comparison]/{warehouse_dir}/warehouse] +PushedFilters: [IsNotNull(w_warehouse_sk)] +ReadSchema: struct + +(5) CometFilter +Input [2]: [w_warehouse_sk#6, w_warehouse_name#7] +Condition : isnotnull(w_warehouse_sk#6) + +(6) ColumnarToRow [codegen id : 1] +Input [2]: [w_warehouse_sk#6, w_warehouse_name#7] + +(7) BroadcastExchange +Input [2]: [w_warehouse_sk#6, w_warehouse_name#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [cs_warehouse_sk#4] +Right keys [1]: [w_warehouse_sk#6] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 5] +Output [5]: [cs_ship_date_sk#1, cs_call_center_sk#2, cs_ship_mode_sk#3, cs_sold_date_sk#5, w_warehouse_name#7] +Input [7]: [cs_ship_date_sk#1, cs_call_center_sk#2, cs_ship_mode_sk#3, cs_warehouse_sk#4, cs_sold_date_sk#5, w_warehouse_sk#6, w_warehouse_name#7] + +(10) Scan parquet spark_catalog.default.ship_mode +Output [2]: [sm_ship_mode_sk#8, sm_type#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/ship_mode] +PushedFilters: [IsNotNull(sm_ship_mode_sk)] +ReadSchema: struct + +(11) CometFilter +Input [2]: [sm_ship_mode_sk#8, sm_type#9] +Condition : isnotnull(sm_ship_mode_sk#8) + +(12) ColumnarToRow [codegen id : 2] +Input [2]: [sm_ship_mode_sk#8, sm_type#9] + +(13) BroadcastExchange +Input [2]: [sm_ship_mode_sk#8, sm_type#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(14) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [cs_ship_mode_sk#3] +Right keys [1]: [sm_ship_mode_sk#8] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 5] +Output [5]: [cs_ship_date_sk#1, cs_call_center_sk#2, cs_sold_date_sk#5, w_warehouse_name#7, sm_type#9] +Input [7]: [cs_ship_date_sk#1, cs_call_center_sk#2, cs_ship_mode_sk#3, cs_sold_date_sk#5, w_warehouse_name#7, sm_ship_mode_sk#8, sm_type#9] + +(16) Scan parquet spark_catalog.default.call_center +Output [2]: [cc_call_center_sk#10, cc_name#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/call_center] +PushedFilters: [IsNotNull(cc_call_center_sk)] +ReadSchema: struct + +(17) CometFilter +Input [2]: [cc_call_center_sk#10, cc_name#11] +Condition : isnotnull(cc_call_center_sk#10) + +(18) ColumnarToRow [codegen id : 3] +Input [2]: [cc_call_center_sk#10, cc_name#11] + +(19) BroadcastExchange +Input [2]: [cc_call_center_sk#10, cc_name#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(20) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [cs_call_center_sk#2] +Right keys [1]: [cc_call_center_sk#10] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 5] +Output [5]: [cs_ship_date_sk#1, cs_sold_date_sk#5, w_warehouse_name#7, sm_type#9, cc_name#11] +Input [7]: [cs_ship_date_sk#1, cs_call_center_sk#2, cs_sold_date_sk#5, w_warehouse_name#7, sm_type#9, cc_call_center_sk#10, cc_name#11] + +(22) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#12, d_month_seq#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)] +ReadSchema: struct + +(23) CometFilter +Input [2]: [d_date_sk#12, d_month_seq#13] +Condition : (((isnotnull(d_month_seq#13) AND (d_month_seq#13 >= 1200)) AND (d_month_seq#13 <= 1211)) AND isnotnull(d_date_sk#12)) + +(24) CometProject +Input [2]: [d_date_sk#12, d_month_seq#13] +Arguments: [d_date_sk#12], [d_date_sk#12] + +(25) ColumnarToRow [codegen id : 4] +Input [1]: [d_date_sk#12] + +(26) BroadcastExchange +Input [1]: [d_date_sk#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(27) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [cs_ship_date_sk#1] +Right keys [1]: [d_date_sk#12] +Join type: Inner +Join condition: None + +(28) Project [codegen id : 5] +Output [5]: [cs_ship_date_sk#1, cs_sold_date_sk#5, sm_type#9, cc_name#11, substr(w_warehouse_name#7, 1, 20) AS _groupingexpression#14] +Input [6]: [cs_ship_date_sk#1, cs_sold_date_sk#5, w_warehouse_name#7, sm_type#9, cc_name#11, d_date_sk#12] + +(29) HashAggregate [codegen id : 5] +Input [5]: [cs_ship_date_sk#1, cs_sold_date_sk#5, sm_type#9, cc_name#11, _groupingexpression#14] +Keys [3]: [_groupingexpression#14, sm_type#9, cc_name#11] +Functions [5]: [partial_sum(CASE WHEN ((cs_ship_date_sk#1 - cs_sold_date_sk#5) <= 30) THEN 1 ELSE 0 END), partial_sum(CASE WHEN (((cs_ship_date_sk#1 - cs_sold_date_sk#5) > 30) AND ((cs_ship_date_sk#1 - cs_sold_date_sk#5) <= 60)) THEN 1 ELSE 0 END), partial_sum(CASE WHEN (((cs_ship_date_sk#1 - cs_sold_date_sk#5) > 60) AND ((cs_ship_date_sk#1 - cs_sold_date_sk#5) <= 90)) THEN 1 ELSE 0 END), partial_sum(CASE WHEN (((cs_ship_date_sk#1 - cs_sold_date_sk#5) > 90) AND ((cs_ship_date_sk#1 - cs_sold_date_sk#5) <= 120)) THEN 1 ELSE 0 END), partial_sum(CASE WHEN ((cs_ship_date_sk#1 - cs_sold_date_sk#5) > 120) THEN 1 ELSE 0 END)] +Aggregate Attributes [5]: [sum#15, sum#16, sum#17, sum#18, sum#19] +Results [8]: [_groupingexpression#14, sm_type#9, cc_name#11, sum#20, sum#21, sum#22, sum#23, sum#24] + +(30) Exchange +Input [8]: [_groupingexpression#14, sm_type#9, cc_name#11, sum#20, sum#21, sum#22, sum#23, sum#24] +Arguments: hashpartitioning(_groupingexpression#14, sm_type#9, cc_name#11, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(31) HashAggregate [codegen id : 6] +Input [8]: [_groupingexpression#14, sm_type#9, cc_name#11, sum#20, sum#21, sum#22, sum#23, sum#24] +Keys [3]: [_groupingexpression#14, sm_type#9, cc_name#11] +Functions [5]: [sum(CASE WHEN ((cs_ship_date_sk#1 - cs_sold_date_sk#5) <= 30) THEN 1 ELSE 0 END), sum(CASE WHEN (((cs_ship_date_sk#1 - cs_sold_date_sk#5) > 30) AND ((cs_ship_date_sk#1 - cs_sold_date_sk#5) <= 60)) THEN 1 ELSE 0 END), sum(CASE WHEN (((cs_ship_date_sk#1 - cs_sold_date_sk#5) > 60) AND ((cs_ship_date_sk#1 - cs_sold_date_sk#5) <= 90)) THEN 1 ELSE 0 END), sum(CASE WHEN (((cs_ship_date_sk#1 - cs_sold_date_sk#5) > 90) AND ((cs_ship_date_sk#1 - cs_sold_date_sk#5) <= 120)) THEN 1 ELSE 0 END), sum(CASE WHEN ((cs_ship_date_sk#1 - cs_sold_date_sk#5) > 120) THEN 1 ELSE 0 END)] +Aggregate Attributes [5]: [sum(CASE WHEN ((cs_ship_date_sk#1 - cs_sold_date_sk#5) <= 30) THEN 1 ELSE 0 END)#25, sum(CASE WHEN (((cs_ship_date_sk#1 - cs_sold_date_sk#5) > 30) AND ((cs_ship_date_sk#1 - cs_sold_date_sk#5) <= 60)) THEN 1 ELSE 0 END)#26, sum(CASE WHEN (((cs_ship_date_sk#1 - cs_sold_date_sk#5) > 60) AND ((cs_ship_date_sk#1 - cs_sold_date_sk#5) <= 90)) THEN 1 ELSE 0 END)#27, sum(CASE WHEN (((cs_ship_date_sk#1 - cs_sold_date_sk#5) > 90) AND ((cs_ship_date_sk#1 - cs_sold_date_sk#5) <= 120)) THEN 1 ELSE 0 END)#28, sum(CASE WHEN ((cs_ship_date_sk#1 - cs_sold_date_sk#5) > 120) THEN 1 ELSE 0 END)#29] +Results [8]: [_groupingexpression#14 AS substr(w_warehouse_name, 1, 20)#30, sm_type#9, cc_name#11, sum(CASE WHEN ((cs_ship_date_sk#1 - cs_sold_date_sk#5) <= 30) THEN 1 ELSE 0 END)#25 AS 30 days #31, sum(CASE WHEN (((cs_ship_date_sk#1 - cs_sold_date_sk#5) > 30) AND ((cs_ship_date_sk#1 - cs_sold_date_sk#5) <= 60)) THEN 1 ELSE 0 END)#26 AS 31 - 60 days #32, sum(CASE WHEN (((cs_ship_date_sk#1 - cs_sold_date_sk#5) > 60) AND ((cs_ship_date_sk#1 - cs_sold_date_sk#5) <= 90)) THEN 1 ELSE 0 END)#27 AS 61 - 90 days #33, sum(CASE WHEN (((cs_ship_date_sk#1 - cs_sold_date_sk#5) > 90) AND ((cs_ship_date_sk#1 - cs_sold_date_sk#5) <= 120)) THEN 1 ELSE 0 END)#28 AS 91 - 120 days #34, sum(CASE WHEN ((cs_ship_date_sk#1 - cs_sold_date_sk#5) > 120) THEN 1 ELSE 0 END)#29 AS >120 days #35] + +(32) TakeOrderedAndProject +Input [8]: [substr(w_warehouse_name, 1, 20)#30, sm_type#9, cc_name#11, 30 days #31, 31 - 60 days #32, 61 - 90 days #33, 91 - 120 days #34, >120 days #35] +Arguments: 100, [substr(w_warehouse_name, 1, 20)#30 ASC NULLS FIRST, sm_type#9 ASC NULLS FIRST, cc_name#11 ASC NULLS FIRST], [substr(w_warehouse_name, 1, 20)#30, sm_type#9, cc_name#11, 30 days #31, 31 - 60 days #32, 61 - 90 days #33, 91 - 120 days #34, >120 days #35] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q99/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q99/simplified.txt new file mode 100644 index 0000000000..c5f25f0795 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q99/simplified.txt @@ -0,0 +1,48 @@ +TakeOrderedAndProject [substr(w_warehouse_name, 1, 20),sm_type,cc_name,30 days ,31 - 60 days ,61 - 90 days ,91 - 120 days ,>120 days ] + WholeStageCodegen (6) + HashAggregate [_groupingexpression,sm_type,cc_name,sum,sum,sum,sum,sum] [sum(CASE WHEN ((cs_ship_date_sk - cs_sold_date_sk) <= 30) THEN 1 ELSE 0 END),sum(CASE WHEN (((cs_ship_date_sk - cs_sold_date_sk) > 30) AND ((cs_ship_date_sk - cs_sold_date_sk) <= 60)) THEN 1 ELSE 0 END),sum(CASE WHEN (((cs_ship_date_sk - cs_sold_date_sk) > 60) AND ((cs_ship_date_sk - cs_sold_date_sk) <= 90)) THEN 1 ELSE 0 END),sum(CASE WHEN (((cs_ship_date_sk - cs_sold_date_sk) > 90) AND ((cs_ship_date_sk - cs_sold_date_sk) <= 120)) THEN 1 ELSE 0 END),sum(CASE WHEN ((cs_ship_date_sk - cs_sold_date_sk) > 120) THEN 1 ELSE 0 END),substr(w_warehouse_name, 1, 20),30 days ,31 - 60 days ,61 - 90 days ,91 - 120 days ,>120 days ,sum,sum,sum,sum,sum] + InputAdapter + Exchange [_groupingexpression,sm_type,cc_name] #1 + WholeStageCodegen (5) + HashAggregate [_groupingexpression,sm_type,cc_name,cs_ship_date_sk,cs_sold_date_sk] [sum,sum,sum,sum,sum,sum,sum,sum,sum,sum] + Project [cs_ship_date_sk,cs_sold_date_sk,sm_type,cc_name,w_warehouse_name] + BroadcastHashJoin [cs_ship_date_sk,d_date_sk] + Project [cs_ship_date_sk,cs_sold_date_sk,w_warehouse_name,sm_type,cc_name] + BroadcastHashJoin [cs_call_center_sk,cc_call_center_sk] + Project [cs_ship_date_sk,cs_call_center_sk,cs_sold_date_sk,w_warehouse_name,sm_type] + BroadcastHashJoin [cs_ship_mode_sk,sm_ship_mode_sk] + Project [cs_ship_date_sk,cs_call_center_sk,cs_ship_mode_sk,cs_sold_date_sk,w_warehouse_name] + BroadcastHashJoin [cs_warehouse_sk,w_warehouse_sk] + ColumnarToRow + InputAdapter + CometFilter [cs_warehouse_sk,cs_ship_mode_sk,cs_call_center_sk,cs_ship_date_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_ship_date_sk,cs_call_center_sk,cs_ship_mode_sk,cs_warehouse_sk,cs_sold_date_sk] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [w_warehouse_sk] + CometScan parquet spark_catalog.default.warehouse [w_warehouse_sk,w_warehouse_name] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [sm_ship_mode_sk] + CometScan parquet spark_catalog.default.ship_mode [sm_ship_mode_sk,sm_type] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometFilter [cc_call_center_sk] + CometScan parquet spark_catalog.default.call_center [cc_call_center_sk,cc_name] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (4) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_month_seq,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q10a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q10a/explain.txt new file mode 100644 index 0000000000..be0e98db20 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q10a/explain.txt @@ -0,0 +1,272 @@ +== Physical Plan == +TakeOrderedAndProject (41) ++- * HashAggregate (40) + +- Exchange (39) + +- * HashAggregate (38) + +- * Project (37) + +- * BroadcastHashJoin Inner BuildRight (36) + :- * Project (31) + : +- * BroadcastHashJoin Inner BuildRight (30) + : :- * Project (24) + : : +- * BroadcastHashJoin LeftSemi BuildRight (23) + : : :- * BroadcastHashJoin LeftSemi BuildRight (10) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.customer (1) + : : : +- BroadcastExchange (9) + : : : +- * Project (8) + : : : +- * BroadcastHashJoin Inner BuildRight (7) + : : : :- * ColumnarToRow (5) + : : : : +- CometScan parquet spark_catalog.default.store_sales (4) + : : : +- ReusedExchange (6) + : : +- BroadcastExchange (22) + : : +- Union (21) + : : :- * Project (15) + : : : +- * BroadcastHashJoin Inner BuildRight (14) + : : : :- * ColumnarToRow (12) + : : : : +- CometScan parquet spark_catalog.default.web_sales (11) + : : : +- ReusedExchange (13) + : : +- * Project (20) + : : +- * BroadcastHashJoin Inner BuildRight (19) + : : :- * ColumnarToRow (17) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (16) + : : +- ReusedExchange (18) + : +- BroadcastExchange (29) + : +- * ColumnarToRow (28) + : +- CometProject (27) + : +- CometFilter (26) + : +- CometScan parquet spark_catalog.default.customer_address (25) + +- BroadcastExchange (35) + +- * ColumnarToRow (34) + +- CometFilter (33) + +- CometScan parquet spark_catalog.default.customer_demographics (32) + + +(1) Scan parquet spark_catalog.default.customer +Output [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_current_addr_sk), IsNotNull(c_current_cdemo_sk)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3] +Condition : (isnotnull(c_current_addr_sk#3) AND isnotnull(c_current_cdemo_sk#2)) + +(3) ColumnarToRow [codegen id : 9] +Input [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3] + +(4) Scan parquet spark_catalog.default.store_sales +Output [2]: [ss_customer_sk#4, ss_sold_date_sk#5] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#5), dynamicpruningexpression(ss_sold_date_sk#5 IN dynamicpruning#6)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 2] +Input [2]: [ss_customer_sk#4, ss_sold_date_sk#5] + +(6) ReusedExchange [Reuses operator id: 46] +Output [1]: [d_date_sk#7] + +(7) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [ss_sold_date_sk#5] +Right keys [1]: [d_date_sk#7] +Join type: Inner +Join condition: None + +(8) Project [codegen id : 2] +Output [1]: [ss_customer_sk#4] +Input [3]: [ss_customer_sk#4, ss_sold_date_sk#5, d_date_sk#7] + +(9) BroadcastExchange +Input [1]: [ss_customer_sk#4] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(10) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_customer_sk#1] +Right keys [1]: [ss_customer_sk#4] +Join type: LeftSemi +Join condition: None + +(11) Scan parquet spark_catalog.default.web_sales +Output [2]: [ws_bill_customer_sk#8, ws_sold_date_sk#9] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#9), dynamicpruningexpression(ws_sold_date_sk#9 IN dynamicpruning#10)] +ReadSchema: struct + +(12) ColumnarToRow [codegen id : 4] +Input [2]: [ws_bill_customer_sk#8, ws_sold_date_sk#9] + +(13) ReusedExchange [Reuses operator id: 46] +Output [1]: [d_date_sk#11] + +(14) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ws_sold_date_sk#9] +Right keys [1]: [d_date_sk#11] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 4] +Output [1]: [ws_bill_customer_sk#8 AS customer_sk#12] +Input [3]: [ws_bill_customer_sk#8, ws_sold_date_sk#9, d_date_sk#11] + +(16) Scan parquet spark_catalog.default.catalog_sales +Output [2]: [cs_ship_customer_sk#13, cs_sold_date_sk#14] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#14), dynamicpruningexpression(cs_sold_date_sk#14 IN dynamicpruning#15)] +ReadSchema: struct + +(17) ColumnarToRow [codegen id : 6] +Input [2]: [cs_ship_customer_sk#13, cs_sold_date_sk#14] + +(18) ReusedExchange [Reuses operator id: 46] +Output [1]: [d_date_sk#16] + +(19) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [cs_sold_date_sk#14] +Right keys [1]: [d_date_sk#16] +Join type: Inner +Join condition: None + +(20) Project [codegen id : 6] +Output [1]: [cs_ship_customer_sk#13 AS customer_sk#17] +Input [3]: [cs_ship_customer_sk#13, cs_sold_date_sk#14, d_date_sk#16] + +(21) Union + +(22) BroadcastExchange +Input [1]: [customer_sk#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(23) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_customer_sk#1] +Right keys [1]: [customer_sk#12] +Join type: LeftSemi +Join condition: None + +(24) Project [codegen id : 9] +Output [2]: [c_current_cdemo_sk#2, c_current_addr_sk#3] +Input [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3] + +(25) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#18, ca_county#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [In(ca_county, [Dona Ana County,Douglas County,Gaines County,Richland County,Walker County]), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(26) CometFilter +Input [2]: [ca_address_sk#18, ca_county#19] +Condition : (ca_county#19 IN (Walker County,Richland County,Gaines County,Douglas County,Dona Ana County) AND isnotnull(ca_address_sk#18)) + +(27) CometProject +Input [2]: [ca_address_sk#18, ca_county#19] +Arguments: [ca_address_sk#18], [ca_address_sk#18] + +(28) ColumnarToRow [codegen id : 7] +Input [1]: [ca_address_sk#18] + +(29) BroadcastExchange +Input [1]: [ca_address_sk#18] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(30) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_current_addr_sk#3] +Right keys [1]: [ca_address_sk#18] +Join type: Inner +Join condition: None + +(31) Project [codegen id : 9] +Output [1]: [c_current_cdemo_sk#2] +Input [3]: [c_current_cdemo_sk#2, c_current_addr_sk#3, ca_address_sk#18] + +(32) Scan parquet spark_catalog.default.customer_demographics +Output [9]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(33) CometFilter +Input [9]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] +Condition : isnotnull(cd_demo_sk#20) + +(34) ColumnarToRow [codegen id : 8] +Input [9]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] + +(35) BroadcastExchange +Input [9]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(36) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_current_cdemo_sk#2] +Right keys [1]: [cd_demo_sk#20] +Join type: Inner +Join condition: None + +(37) Project [codegen id : 9] +Output [8]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] +Input [10]: [c_current_cdemo_sk#2, cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] + +(38) HashAggregate [codegen id : 9] +Input [8]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] +Keys [8]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#29] +Results [9]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28, count#30] + +(39) Exchange +Input [9]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28, count#30] +Arguments: hashpartitioning(cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(40) HashAggregate [codegen id : 10] +Input [9]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28, count#30] +Keys [8]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#31] +Results [14]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, count(1)#31 AS cnt1#32, cd_purchase_estimate#24, count(1)#31 AS cnt2#33, cd_credit_rating#25, count(1)#31 AS cnt3#34, cd_dep_count#26, count(1)#31 AS cnt4#35, cd_dep_employed_count#27, count(1)#31 AS cnt5#36, cd_dep_college_count#28, count(1)#31 AS cnt6#37] + +(41) TakeOrderedAndProject +Input [14]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, cnt1#32, cd_purchase_estimate#24, cnt2#33, cd_credit_rating#25, cnt3#34, cd_dep_count#26, cnt4#35, cd_dep_employed_count#27, cnt5#36, cd_dep_college_count#28, cnt6#37] +Arguments: 100, [cd_gender#21 ASC NULLS FIRST, cd_marital_status#22 ASC NULLS FIRST, cd_education_status#23 ASC NULLS FIRST, cd_purchase_estimate#24 ASC NULLS FIRST, cd_credit_rating#25 ASC NULLS FIRST, cd_dep_count#26 ASC NULLS FIRST, cd_dep_employed_count#27 ASC NULLS FIRST, cd_dep_college_count#28 ASC NULLS FIRST], [cd_gender#21, cd_marital_status#22, cd_education_status#23, cnt1#32, cd_purchase_estimate#24, cnt2#33, cd_credit_rating#25, cnt3#34, cd_dep_count#26, cnt4#35, cd_dep_employed_count#27, cnt5#36, cd_dep_college_count#28, cnt6#37] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6 +BroadcastExchange (46) ++- * ColumnarToRow (45) + +- CometProject (44) + +- CometFilter (43) + +- CometScan parquet spark_catalog.default.date_dim (42) + + +(42) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#7, d_year#38, d_moy#39] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2002), GreaterThanOrEqual(d_moy,4), LessThanOrEqual(d_moy,7), IsNotNull(d_date_sk)] +ReadSchema: struct + +(43) CometFilter +Input [3]: [d_date_sk#7, d_year#38, d_moy#39] +Condition : (((((isnotnull(d_year#38) AND isnotnull(d_moy#39)) AND (d_year#38 = 2002)) AND (d_moy#39 >= 4)) AND (d_moy#39 <= 7)) AND isnotnull(d_date_sk#7)) + +(44) CometProject +Input [3]: [d_date_sk#7, d_year#38, d_moy#39] +Arguments: [d_date_sk#7], [d_date_sk#7] + +(45) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#7] + +(46) BroadcastExchange +Input [1]: [d_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6] + +Subquery:2 Hosting operator id = 11 Hosting Expression = ws_sold_date_sk#9 IN dynamicpruning#6 + +Subquery:3 Hosting operator id = 16 Hosting Expression = cs_sold_date_sk#14 IN dynamicpruning#6 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q10a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q10a/simplified.txt new file mode 100644 index 0000000000..3eb2210a6e --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q10a/simplified.txt @@ -0,0 +1,72 @@ +TakeOrderedAndProject [cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating,cd_dep_count,cd_dep_employed_count,cd_dep_college_count,cnt1,cnt2,cnt3,cnt4,cnt5,cnt6] + WholeStageCodegen (10) + HashAggregate [cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating,cd_dep_count,cd_dep_employed_count,cd_dep_college_count,count] [count(1),cnt1,cnt2,cnt3,cnt4,cnt5,cnt6,count] + InputAdapter + Exchange [cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] #1 + WholeStageCodegen (9) + HashAggregate [cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] [count,count] + Project [cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk] + Project [c_current_cdemo_sk] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [c_current_cdemo_sk,c_current_addr_sk] + BroadcastHashJoin [c_customer_sk,customer_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + ColumnarToRow + InputAdapter + CometFilter [c_current_addr_sk,c_current_cdemo_sk] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (2) + Project [ss_customer_sk] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_moy,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + Union + WholeStageCodegen (4) + Project [ws_bill_customer_sk] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + WholeStageCodegen (6) + Project [cs_ship_customer_sk] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_ship_customer_sk,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (7) + ColumnarToRow + InputAdapter + CometProject [ca_address_sk] + CometFilter [ca_county,ca_address_sk] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_county] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (8) + ColumnarToRow + InputAdapter + CometFilter [cd_demo_sk] + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q11/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q11/explain.txt new file mode 100644 index 0000000000..daa1f52436 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q11/explain.txt @@ -0,0 +1,477 @@ +== Physical Plan == +TakeOrderedAndProject (71) ++- * Project (70) + +- * BroadcastHashJoin Inner BuildRight (69) + :- * Project (52) + : +- * BroadcastHashJoin Inner BuildRight (51) + : :- * BroadcastHashJoin Inner BuildRight (33) + : : :- * Filter (16) + : : : +- * HashAggregate (15) + : : : +- Exchange (14) + : : : +- * HashAggregate (13) + : : : +- * Project (12) + : : : +- * BroadcastHashJoin Inner BuildRight (11) + : : : :- * Project (9) + : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) + : : : : : +- CometScan parquet spark_catalog.default.customer (1) + : : : : +- BroadcastExchange (7) + : : : : +- * ColumnarToRow (6) + : : : : +- CometFilter (5) + : : : : +- CometScan parquet spark_catalog.default.store_sales (4) + : : : +- ReusedExchange (10) + : : +- BroadcastExchange (32) + : : +- * HashAggregate (31) + : : +- Exchange (30) + : : +- * HashAggregate (29) + : : +- * Project (28) + : : +- * BroadcastHashJoin Inner BuildRight (27) + : : :- * Project (25) + : : : +- * BroadcastHashJoin Inner BuildRight (24) + : : : :- * ColumnarToRow (19) + : : : : +- CometFilter (18) + : : : : +- CometScan parquet spark_catalog.default.customer (17) + : : : +- BroadcastExchange (23) + : : : +- * ColumnarToRow (22) + : : : +- CometFilter (21) + : : : +- CometScan parquet spark_catalog.default.store_sales (20) + : : +- ReusedExchange (26) + : +- BroadcastExchange (50) + : +- * Filter (49) + : +- * HashAggregate (48) + : +- Exchange (47) + : +- * HashAggregate (46) + : +- * Project (45) + : +- * BroadcastHashJoin Inner BuildRight (44) + : :- * Project (42) + : : +- * BroadcastHashJoin Inner BuildRight (41) + : : :- * ColumnarToRow (36) + : : : +- CometFilter (35) + : : : +- CometScan parquet spark_catalog.default.customer (34) + : : +- BroadcastExchange (40) + : : +- * ColumnarToRow (39) + : : +- CometFilter (38) + : : +- CometScan parquet spark_catalog.default.web_sales (37) + : +- ReusedExchange (43) + +- BroadcastExchange (68) + +- * HashAggregate (67) + +- Exchange (66) + +- * HashAggregate (65) + +- * Project (64) + +- * BroadcastHashJoin Inner BuildRight (63) + :- * Project (61) + : +- * BroadcastHashJoin Inner BuildRight (60) + : :- * ColumnarToRow (55) + : : +- CometFilter (54) + : : +- CometScan parquet spark_catalog.default.customer (53) + : +- BroadcastExchange (59) + : +- * ColumnarToRow (58) + : +- CometFilter (57) + : +- CometScan parquet spark_catalog.default.web_sales (56) + +- ReusedExchange (62) + + +(1) Scan parquet spark_catalog.default.customer +Output [8]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(2) CometFilter +Input [8]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8] +Condition : (isnotnull(c_customer_sk#1) AND isnotnull(c_customer_id#2)) + +(3) ColumnarToRow [codegen id : 3] +Input [8]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8] + +(4) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#12), dynamicpruningexpression(ss_sold_date_sk#12 IN dynamicpruning#13)] +PushedFilters: [IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(5) CometFilter +Input [4]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12] +Condition : isnotnull(ss_customer_sk#9) + +(6) ColumnarToRow [codegen id : 1] +Input [4]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12] + +(7) BroadcastExchange +Input [4]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [c_customer_sk#1] +Right keys [1]: [ss_customer_sk#9] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 3] +Output [10]: [c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12] +Input [12]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12] + +(10) ReusedExchange [Reuses operator id: 75] +Output [2]: [d_date_sk#14, d_year#15] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_sold_date_sk#12] +Right keys [1]: [d_date_sk#14] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [10]: [c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, ss_ext_discount_amt#10, ss_ext_list_price#11, d_year#15] +Input [12]: [c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12, d_date_sk#14, d_year#15] + +(13) HashAggregate [codegen id : 3] +Input [10]: [c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, ss_ext_discount_amt#10, ss_ext_list_price#11, d_year#15] +Keys [8]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#15, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8] +Functions [1]: [partial_sum(UnscaledValue((ss_ext_list_price#11 - ss_ext_discount_amt#10)))] +Aggregate Attributes [1]: [sum#16] +Results [9]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#15, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, sum#17] + +(14) Exchange +Input [9]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#15, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, sum#17] +Arguments: hashpartitioning(c_customer_id#2, c_first_name#3, c_last_name#4, d_year#15, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 16] +Input [9]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#15, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, sum#17] +Keys [8]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#15, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8] +Functions [1]: [sum(UnscaledValue((ss_ext_list_price#11 - ss_ext_discount_amt#10)))] +Aggregate Attributes [1]: [sum(UnscaledValue((ss_ext_list_price#11 - ss_ext_discount_amt#10)))#18] +Results [2]: [c_customer_id#2 AS customer_id#19, MakeDecimal(sum(UnscaledValue((ss_ext_list_price#11 - ss_ext_discount_amt#10)))#18,18,2) AS year_total#20] + +(16) Filter [codegen id : 16] +Input [2]: [customer_id#19, year_total#20] +Condition : (isnotnull(year_total#20) AND (year_total#20 > 0.00)) + +(17) Scan parquet spark_catalog.default.customer +Output [8]: [c_customer_sk#21, c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(18) CometFilter +Input [8]: [c_customer_sk#21, c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28] +Condition : (isnotnull(c_customer_sk#21) AND isnotnull(c_customer_id#22)) + +(19) ColumnarToRow [codegen id : 6] +Input [8]: [c_customer_sk#21, c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28] + +(20) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_customer_sk#29, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#32), dynamicpruningexpression(ss_sold_date_sk#32 IN dynamicpruning#33)] +PushedFilters: [IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(21) CometFilter +Input [4]: [ss_customer_sk#29, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32] +Condition : isnotnull(ss_customer_sk#29) + +(22) ColumnarToRow [codegen id : 4] +Input [4]: [ss_customer_sk#29, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32] + +(23) BroadcastExchange +Input [4]: [ss_customer_sk#29, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [c_customer_sk#21] +Right keys [1]: [ss_customer_sk#29] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 6] +Output [10]: [c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32] +Input [12]: [c_customer_sk#21, c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, ss_customer_sk#29, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32] + +(26) ReusedExchange [Reuses operator id: 79] +Output [2]: [d_date_sk#34, d_year#35] + +(27) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_sold_date_sk#32] +Right keys [1]: [d_date_sk#34] +Join type: Inner +Join condition: None + +(28) Project [codegen id : 6] +Output [10]: [c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, ss_ext_discount_amt#30, ss_ext_list_price#31, d_year#35] +Input [12]: [c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32, d_date_sk#34, d_year#35] + +(29) HashAggregate [codegen id : 6] +Input [10]: [c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, ss_ext_discount_amt#30, ss_ext_list_price#31, d_year#35] +Keys [8]: [c_customer_id#22, c_first_name#23, c_last_name#24, d_year#35, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28] +Functions [1]: [partial_sum(UnscaledValue((ss_ext_list_price#31 - ss_ext_discount_amt#30)))] +Aggregate Attributes [1]: [sum#36] +Results [9]: [c_customer_id#22, c_first_name#23, c_last_name#24, d_year#35, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, sum#37] + +(30) Exchange +Input [9]: [c_customer_id#22, c_first_name#23, c_last_name#24, d_year#35, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, sum#37] +Arguments: hashpartitioning(c_customer_id#22, c_first_name#23, c_last_name#24, d_year#35, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(31) HashAggregate [codegen id : 7] +Input [9]: [c_customer_id#22, c_first_name#23, c_last_name#24, d_year#35, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, sum#37] +Keys [8]: [c_customer_id#22, c_first_name#23, c_last_name#24, d_year#35, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28] +Functions [1]: [sum(UnscaledValue((ss_ext_list_price#31 - ss_ext_discount_amt#30)))] +Aggregate Attributes [1]: [sum(UnscaledValue((ss_ext_list_price#31 - ss_ext_discount_amt#30)))#18] +Results [5]: [c_customer_id#22 AS customer_id#38, c_first_name#23 AS customer_first_name#39, c_last_name#24 AS customer_last_name#40, c_email_address#28 AS customer_email_address#41, MakeDecimal(sum(UnscaledValue((ss_ext_list_price#31 - ss_ext_discount_amt#30)))#18,18,2) AS year_total#42] + +(32) BroadcastExchange +Input [5]: [customer_id#38, customer_first_name#39, customer_last_name#40, customer_email_address#41, year_total#42] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=5] + +(33) BroadcastHashJoin [codegen id : 16] +Left keys [1]: [customer_id#19] +Right keys [1]: [customer_id#38] +Join type: Inner +Join condition: None + +(34) Scan parquet spark_catalog.default.customer +Output [8]: [c_customer_sk#43, c_customer_id#44, c_first_name#45, c_last_name#46, c_preferred_cust_flag#47, c_birth_country#48, c_login#49, c_email_address#50] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(35) CometFilter +Input [8]: [c_customer_sk#43, c_customer_id#44, c_first_name#45, c_last_name#46, c_preferred_cust_flag#47, c_birth_country#48, c_login#49, c_email_address#50] +Condition : (isnotnull(c_customer_sk#43) AND isnotnull(c_customer_id#44)) + +(36) ColumnarToRow [codegen id : 10] +Input [8]: [c_customer_sk#43, c_customer_id#44, c_first_name#45, c_last_name#46, c_preferred_cust_flag#47, c_birth_country#48, c_login#49, c_email_address#50] + +(37) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_bill_customer_sk#51, ws_ext_discount_amt#52, ws_ext_list_price#53, ws_sold_date_sk#54] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#54), dynamicpruningexpression(ws_sold_date_sk#54 IN dynamicpruning#55)] +PushedFilters: [IsNotNull(ws_bill_customer_sk)] +ReadSchema: struct + +(38) CometFilter +Input [4]: [ws_bill_customer_sk#51, ws_ext_discount_amt#52, ws_ext_list_price#53, ws_sold_date_sk#54] +Condition : isnotnull(ws_bill_customer_sk#51) + +(39) ColumnarToRow [codegen id : 8] +Input [4]: [ws_bill_customer_sk#51, ws_ext_discount_amt#52, ws_ext_list_price#53, ws_sold_date_sk#54] + +(40) BroadcastExchange +Input [4]: [ws_bill_customer_sk#51, ws_ext_discount_amt#52, ws_ext_list_price#53, ws_sold_date_sk#54] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6] + +(41) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [c_customer_sk#43] +Right keys [1]: [ws_bill_customer_sk#51] +Join type: Inner +Join condition: None + +(42) Project [codegen id : 10] +Output [10]: [c_customer_id#44, c_first_name#45, c_last_name#46, c_preferred_cust_flag#47, c_birth_country#48, c_login#49, c_email_address#50, ws_ext_discount_amt#52, ws_ext_list_price#53, ws_sold_date_sk#54] +Input [12]: [c_customer_sk#43, c_customer_id#44, c_first_name#45, c_last_name#46, c_preferred_cust_flag#47, c_birth_country#48, c_login#49, c_email_address#50, ws_bill_customer_sk#51, ws_ext_discount_amt#52, ws_ext_list_price#53, ws_sold_date_sk#54] + +(43) ReusedExchange [Reuses operator id: 75] +Output [2]: [d_date_sk#56, d_year#57] + +(44) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [ws_sold_date_sk#54] +Right keys [1]: [d_date_sk#56] +Join type: Inner +Join condition: None + +(45) Project [codegen id : 10] +Output [10]: [c_customer_id#44, c_first_name#45, c_last_name#46, c_preferred_cust_flag#47, c_birth_country#48, c_login#49, c_email_address#50, ws_ext_discount_amt#52, ws_ext_list_price#53, d_year#57] +Input [12]: [c_customer_id#44, c_first_name#45, c_last_name#46, c_preferred_cust_flag#47, c_birth_country#48, c_login#49, c_email_address#50, ws_ext_discount_amt#52, ws_ext_list_price#53, ws_sold_date_sk#54, d_date_sk#56, d_year#57] + +(46) HashAggregate [codegen id : 10] +Input [10]: [c_customer_id#44, c_first_name#45, c_last_name#46, c_preferred_cust_flag#47, c_birth_country#48, c_login#49, c_email_address#50, ws_ext_discount_amt#52, ws_ext_list_price#53, d_year#57] +Keys [8]: [c_customer_id#44, c_first_name#45, c_last_name#46, c_preferred_cust_flag#47, c_birth_country#48, c_login#49, c_email_address#50, d_year#57] +Functions [1]: [partial_sum(UnscaledValue((ws_ext_list_price#53 - ws_ext_discount_amt#52)))] +Aggregate Attributes [1]: [sum#58] +Results [9]: [c_customer_id#44, c_first_name#45, c_last_name#46, c_preferred_cust_flag#47, c_birth_country#48, c_login#49, c_email_address#50, d_year#57, sum#59] + +(47) Exchange +Input [9]: [c_customer_id#44, c_first_name#45, c_last_name#46, c_preferred_cust_flag#47, c_birth_country#48, c_login#49, c_email_address#50, d_year#57, sum#59] +Arguments: hashpartitioning(c_customer_id#44, c_first_name#45, c_last_name#46, c_preferred_cust_flag#47, c_birth_country#48, c_login#49, c_email_address#50, d_year#57, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(48) HashAggregate [codegen id : 11] +Input [9]: [c_customer_id#44, c_first_name#45, c_last_name#46, c_preferred_cust_flag#47, c_birth_country#48, c_login#49, c_email_address#50, d_year#57, sum#59] +Keys [8]: [c_customer_id#44, c_first_name#45, c_last_name#46, c_preferred_cust_flag#47, c_birth_country#48, c_login#49, c_email_address#50, d_year#57] +Functions [1]: [sum(UnscaledValue((ws_ext_list_price#53 - ws_ext_discount_amt#52)))] +Aggregate Attributes [1]: [sum(UnscaledValue((ws_ext_list_price#53 - ws_ext_discount_amt#52)))#60] +Results [2]: [c_customer_id#44 AS customer_id#61, MakeDecimal(sum(UnscaledValue((ws_ext_list_price#53 - ws_ext_discount_amt#52)))#60,18,2) AS year_total#62] + +(49) Filter [codegen id : 11] +Input [2]: [customer_id#61, year_total#62] +Condition : (isnotnull(year_total#62) AND (year_total#62 > 0.00)) + +(50) BroadcastExchange +Input [2]: [customer_id#61, year_total#62] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=8] + +(51) BroadcastHashJoin [codegen id : 16] +Left keys [1]: [customer_id#19] +Right keys [1]: [customer_id#61] +Join type: Inner +Join condition: None + +(52) Project [codegen id : 16] +Output [8]: [customer_id#19, year_total#20, customer_id#38, customer_first_name#39, customer_last_name#40, customer_email_address#41, year_total#42, year_total#62] +Input [9]: [customer_id#19, year_total#20, customer_id#38, customer_first_name#39, customer_last_name#40, customer_email_address#41, year_total#42, customer_id#61, year_total#62] + +(53) Scan parquet spark_catalog.default.customer +Output [8]: [c_customer_sk#63, c_customer_id#64, c_first_name#65, c_last_name#66, c_preferred_cust_flag#67, c_birth_country#68, c_login#69, c_email_address#70] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(54) CometFilter +Input [8]: [c_customer_sk#63, c_customer_id#64, c_first_name#65, c_last_name#66, c_preferred_cust_flag#67, c_birth_country#68, c_login#69, c_email_address#70] +Condition : (isnotnull(c_customer_sk#63) AND isnotnull(c_customer_id#64)) + +(55) ColumnarToRow [codegen id : 14] +Input [8]: [c_customer_sk#63, c_customer_id#64, c_first_name#65, c_last_name#66, c_preferred_cust_flag#67, c_birth_country#68, c_login#69, c_email_address#70] + +(56) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_bill_customer_sk#71, ws_ext_discount_amt#72, ws_ext_list_price#73, ws_sold_date_sk#74] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#74), dynamicpruningexpression(ws_sold_date_sk#74 IN dynamicpruning#75)] +PushedFilters: [IsNotNull(ws_bill_customer_sk)] +ReadSchema: struct + +(57) CometFilter +Input [4]: [ws_bill_customer_sk#71, ws_ext_discount_amt#72, ws_ext_list_price#73, ws_sold_date_sk#74] +Condition : isnotnull(ws_bill_customer_sk#71) + +(58) ColumnarToRow [codegen id : 12] +Input [4]: [ws_bill_customer_sk#71, ws_ext_discount_amt#72, ws_ext_list_price#73, ws_sold_date_sk#74] + +(59) BroadcastExchange +Input [4]: [ws_bill_customer_sk#71, ws_ext_discount_amt#72, ws_ext_list_price#73, ws_sold_date_sk#74] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=9] + +(60) BroadcastHashJoin [codegen id : 14] +Left keys [1]: [c_customer_sk#63] +Right keys [1]: [ws_bill_customer_sk#71] +Join type: Inner +Join condition: None + +(61) Project [codegen id : 14] +Output [10]: [c_customer_id#64, c_first_name#65, c_last_name#66, c_preferred_cust_flag#67, c_birth_country#68, c_login#69, c_email_address#70, ws_ext_discount_amt#72, ws_ext_list_price#73, ws_sold_date_sk#74] +Input [12]: [c_customer_sk#63, c_customer_id#64, c_first_name#65, c_last_name#66, c_preferred_cust_flag#67, c_birth_country#68, c_login#69, c_email_address#70, ws_bill_customer_sk#71, ws_ext_discount_amt#72, ws_ext_list_price#73, ws_sold_date_sk#74] + +(62) ReusedExchange [Reuses operator id: 79] +Output [2]: [d_date_sk#76, d_year#77] + +(63) BroadcastHashJoin [codegen id : 14] +Left keys [1]: [ws_sold_date_sk#74] +Right keys [1]: [d_date_sk#76] +Join type: Inner +Join condition: None + +(64) Project [codegen id : 14] +Output [10]: [c_customer_id#64, c_first_name#65, c_last_name#66, c_preferred_cust_flag#67, c_birth_country#68, c_login#69, c_email_address#70, ws_ext_discount_amt#72, ws_ext_list_price#73, d_year#77] +Input [12]: [c_customer_id#64, c_first_name#65, c_last_name#66, c_preferred_cust_flag#67, c_birth_country#68, c_login#69, c_email_address#70, ws_ext_discount_amt#72, ws_ext_list_price#73, ws_sold_date_sk#74, d_date_sk#76, d_year#77] + +(65) HashAggregate [codegen id : 14] +Input [10]: [c_customer_id#64, c_first_name#65, c_last_name#66, c_preferred_cust_flag#67, c_birth_country#68, c_login#69, c_email_address#70, ws_ext_discount_amt#72, ws_ext_list_price#73, d_year#77] +Keys [8]: [c_customer_id#64, c_first_name#65, c_last_name#66, c_preferred_cust_flag#67, c_birth_country#68, c_login#69, c_email_address#70, d_year#77] +Functions [1]: [partial_sum(UnscaledValue((ws_ext_list_price#73 - ws_ext_discount_amt#72)))] +Aggregate Attributes [1]: [sum#78] +Results [9]: [c_customer_id#64, c_first_name#65, c_last_name#66, c_preferred_cust_flag#67, c_birth_country#68, c_login#69, c_email_address#70, d_year#77, sum#79] + +(66) Exchange +Input [9]: [c_customer_id#64, c_first_name#65, c_last_name#66, c_preferred_cust_flag#67, c_birth_country#68, c_login#69, c_email_address#70, d_year#77, sum#79] +Arguments: hashpartitioning(c_customer_id#64, c_first_name#65, c_last_name#66, c_preferred_cust_flag#67, c_birth_country#68, c_login#69, c_email_address#70, d_year#77, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(67) HashAggregate [codegen id : 15] +Input [9]: [c_customer_id#64, c_first_name#65, c_last_name#66, c_preferred_cust_flag#67, c_birth_country#68, c_login#69, c_email_address#70, d_year#77, sum#79] +Keys [8]: [c_customer_id#64, c_first_name#65, c_last_name#66, c_preferred_cust_flag#67, c_birth_country#68, c_login#69, c_email_address#70, d_year#77] +Functions [1]: [sum(UnscaledValue((ws_ext_list_price#73 - ws_ext_discount_amt#72)))] +Aggregate Attributes [1]: [sum(UnscaledValue((ws_ext_list_price#73 - ws_ext_discount_amt#72)))#60] +Results [2]: [c_customer_id#64 AS customer_id#80, MakeDecimal(sum(UnscaledValue((ws_ext_list_price#73 - ws_ext_discount_amt#72)))#60,18,2) AS year_total#81] + +(68) BroadcastExchange +Input [2]: [customer_id#80, year_total#81] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=11] + +(69) BroadcastHashJoin [codegen id : 16] +Left keys [1]: [customer_id#19] +Right keys [1]: [customer_id#80] +Join type: Inner +Join condition: (CASE WHEN (year_total#62 > 0.00) THEN (year_total#81 / year_total#62) ELSE 0E-20 END > CASE WHEN (year_total#20 > 0.00) THEN (year_total#42 / year_total#20) ELSE 0E-20 END) + +(70) Project [codegen id : 16] +Output [4]: [customer_id#38, customer_first_name#39, customer_last_name#40, customer_email_address#41] +Input [10]: [customer_id#19, year_total#20, customer_id#38, customer_first_name#39, customer_last_name#40, customer_email_address#41, year_total#42, year_total#62, customer_id#80, year_total#81] + +(71) TakeOrderedAndProject +Input [4]: [customer_id#38, customer_first_name#39, customer_last_name#40, customer_email_address#41] +Arguments: 100, [customer_id#38 ASC NULLS FIRST, customer_first_name#39 ASC NULLS FIRST, customer_last_name#40 ASC NULLS FIRST, customer_email_address#41 ASC NULLS FIRST], [customer_id#38, customer_first_name#39, customer_last_name#40, customer_email_address#41] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#12 IN dynamicpruning#13 +BroadcastExchange (75) ++- * ColumnarToRow (74) + +- CometFilter (73) + +- CometScan parquet spark_catalog.default.date_dim (72) + + +(72) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#14, d_year#15] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(73) CometFilter +Input [2]: [d_date_sk#14, d_year#15] +Condition : ((isnotnull(d_year#15) AND (d_year#15 = 2001)) AND isnotnull(d_date_sk#14)) + +(74) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#14, d_year#15] + +(75) BroadcastExchange +Input [2]: [d_date_sk#14, d_year#15] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=12] + +Subquery:2 Hosting operator id = 20 Hosting Expression = ss_sold_date_sk#32 IN dynamicpruning#33 +BroadcastExchange (79) ++- * ColumnarToRow (78) + +- CometFilter (77) + +- CometScan parquet spark_catalog.default.date_dim (76) + + +(76) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#34, d_year#35] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2002), IsNotNull(d_date_sk)] +ReadSchema: struct + +(77) CometFilter +Input [2]: [d_date_sk#34, d_year#35] +Condition : ((isnotnull(d_year#35) AND (d_year#35 = 2002)) AND isnotnull(d_date_sk#34)) + +(78) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#34, d_year#35] + +(79) BroadcastExchange +Input [2]: [d_date_sk#34, d_year#35] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=13] + +Subquery:3 Hosting operator id = 37 Hosting Expression = ws_sold_date_sk#54 IN dynamicpruning#13 + +Subquery:4 Hosting operator id = 56 Hosting Expression = ws_sold_date_sk#74 IN dynamicpruning#33 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q11/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q11/simplified.txt new file mode 100644 index 0000000000..0a30aba051 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q11/simplified.txt @@ -0,0 +1,122 @@ +TakeOrderedAndProject [customer_id,customer_first_name,customer_last_name,customer_email_address] + WholeStageCodegen (16) + Project [customer_id,customer_first_name,customer_last_name,customer_email_address] + BroadcastHashJoin [customer_id,customer_id,year_total,year_total,year_total,year_total] + Project [customer_id,year_total,customer_id,customer_first_name,customer_last_name,customer_email_address,year_total,year_total] + BroadcastHashJoin [customer_id,customer_id] + BroadcastHashJoin [customer_id,customer_id] + Filter [year_total] + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,sum] [sum(UnscaledValue((ss_ext_list_price - ss_ext_discount_amt))),customer_id,year_total,sum] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,d_year,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] #1 + WholeStageCodegen (3) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_list_price,ss_ext_discount_amt] [sum,sum] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_discount_amt,ss_ext_list_price,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_discount_amt,ss_ext_list_price,ss_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk] + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_ext_discount_amt,ss_ext_list_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk,d_year] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (7) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,sum] [sum(UnscaledValue((ss_ext_list_price - ss_ext_discount_amt))),customer_id,customer_first_name,customer_last_name,customer_email_address,year_total,sum] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,d_year,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] #5 + WholeStageCodegen (6) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_list_price,ss_ext_discount_amt] [sum,sum] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_discount_amt,ss_ext_list_price,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_discount_amt,ss_ext_list_price,ss_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (4) + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk] + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_ext_discount_amt,ss_ext_list_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #7 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk,d_year] #7 + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (11) + Filter [year_total] + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,sum] [sum(UnscaledValue((ws_ext_list_price - ws_ext_discount_amt))),customer_id,year_total,sum] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year] #9 + WholeStageCodegen (10) + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,ws_ext_list_price,ws_ext_discount_amt] [sum,sum] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ws_ext_discount_amt,ws_ext_list_price,d_year] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ws_ext_discount_amt,ws_ext_list_price,ws_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] + InputAdapter + BroadcastExchange #10 + WholeStageCodegen (8) + ColumnarToRow + InputAdapter + CometFilter [ws_bill_customer_sk] + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_ext_discount_amt,ws_ext_list_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk,d_year] #3 + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (15) + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,sum] [sum(UnscaledValue((ws_ext_list_price - ws_ext_discount_amt))),customer_id,year_total,sum] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year] #12 + WholeStageCodegen (14) + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,ws_ext_list_price,ws_ext_discount_amt] [sum,sum] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ws_ext_discount_amt,ws_ext_list_price,d_year] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ws_ext_discount_amt,ws_ext_list_price,ws_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] + InputAdapter + BroadcastExchange #13 + WholeStageCodegen (12) + ColumnarToRow + InputAdapter + CometFilter [ws_bill_customer_sk] + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_ext_discount_amt,ws_ext_list_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk,d_year] #7 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q12/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q12/explain.txt new file mode 100644 index 0000000000..c39a71879d --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q12/explain.txt @@ -0,0 +1,150 @@ +== Physical Plan == +TakeOrderedAndProject (20) ++- * Project (19) + +- Window (18) + +- * Sort (17) + +- Exchange (16) + +- * HashAggregate (15) + +- Exchange (14) + +- * HashAggregate (13) + +- * Project (12) + +- * BroadcastHashJoin Inner BuildRight (11) + :- * Project (9) + : +- * BroadcastHashJoin Inner BuildRight (8) + : :- * ColumnarToRow (3) + : : +- CometFilter (2) + : : +- CometScan parquet spark_catalog.default.web_sales (1) + : +- BroadcastExchange (7) + : +- * ColumnarToRow (6) + : +- CometFilter (5) + : +- CometScan parquet spark_catalog.default.item (4) + +- ReusedExchange (10) + + +(1) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_item_sk#1, ws_ext_sales_price#2, ws_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#3), dynamicpruningexpression(ws_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [ws_item_sk#1, ws_ext_sales_price#2, ws_sold_date_sk#3] +Condition : isnotnull(ws_item_sk#1) + +(3) ColumnarToRow [codegen id : 3] +Input [3]: [ws_item_sk#1, ws_ext_sales_price#2, ws_sold_date_sk#3] + +(4) Scan parquet spark_catalog.default.item +Output [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [In(i_category, [Books ,Home ,Sports ]), IsNotNull(i_item_sk)] +ReadSchema: struct + +(5) CometFilter +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Condition : (i_category#10 IN (Sports ,Books ,Home ) AND isnotnull(i_item_sk#5)) + +(6) ColumnarToRow [codegen id : 1] +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] + +(7) BroadcastExchange +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ws_item_sk#1] +Right keys [1]: [i_item_sk#5] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 3] +Output [7]: [ws_ext_sales_price#2, ws_sold_date_sk#3, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Input [9]: [ws_item_sk#1, ws_ext_sales_price#2, ws_sold_date_sk#3, i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] + +(10) ReusedExchange [Reuses operator id: 25] +Output [1]: [d_date_sk#11] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ws_sold_date_sk#3] +Right keys [1]: [d_date_sk#11] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [6]: [ws_ext_sales_price#2, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Input [8]: [ws_ext_sales_price#2, ws_sold_date_sk#3, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10, d_date_sk#11] + +(13) HashAggregate [codegen id : 3] +Input [6]: [ws_ext_sales_price#2, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Keys [5]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8] +Functions [1]: [partial_sum(UnscaledValue(ws_ext_sales_price#2))] +Aggregate Attributes [1]: [sum#12] +Results [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] + +(14) Exchange +Input [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] +Arguments: hashpartitioning(i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 4] +Input [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] +Keys [5]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8] +Functions [1]: [sum(UnscaledValue(ws_ext_sales_price#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_ext_sales_price#2))#14] +Results [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, MakeDecimal(sum(UnscaledValue(ws_ext_sales_price#2))#14,17,2) AS itemrevenue#15, MakeDecimal(sum(UnscaledValue(ws_ext_sales_price#2))#14,17,2) AS _w0#16] + +(16) Exchange +Input [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16] +Arguments: hashpartitioning(i_class#9, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(17) Sort [codegen id : 5] +Input [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16] +Arguments: [i_class#9 ASC NULLS FIRST], false, 0 + +(18) Window +Input [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16] +Arguments: [sum(_w0#16) windowspecdefinition(i_class#9, specifiedwindowframe(RowFrame, unboundedpreceding$(), unboundedfollowing$())) AS _we0#17], [i_class#9] + +(19) Project [codegen id : 6] +Output [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, ((_w0#16 * 100) / _we0#17) AS revenueratio#18] +Input [8]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16, _we0#17] + +(20) TakeOrderedAndProject +Input [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, revenueratio#18] +Arguments: 100, [i_category#10 ASC NULLS FIRST, i_class#9 ASC NULLS FIRST, i_item_id#6 ASC NULLS FIRST, i_item_desc#7 ASC NULLS FIRST, revenueratio#18 ASC NULLS FIRST], [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, revenueratio#18] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (25) ++- * ColumnarToRow (24) + +- CometProject (23) + +- CometFilter (22) + +- CometScan parquet spark_catalog.default.date_dim (21) + + +(21) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#11, d_date#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,1999-02-22), LessThanOrEqual(d_date,1999-03-24), IsNotNull(d_date_sk)] +ReadSchema: struct + +(22) CometFilter +Input [2]: [d_date_sk#11, d_date#19] +Condition : (((isnotnull(d_date#19) AND (d_date#19 >= 1999-02-22)) AND (d_date#19 <= 1999-03-24)) AND isnotnull(d_date_sk#11)) + +(23) CometProject +Input [2]: [d_date_sk#11, d_date#19] +Arguments: [d_date_sk#11], [d_date_sk#11] + +(24) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#11] + +(25) BroadcastExchange +Input [1]: [d_date_sk#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q12/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q12/simplified.txt new file mode 100644 index 0000000000..1bc2538b48 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q12/simplified.txt @@ -0,0 +1,40 @@ +TakeOrderedAndProject [i_category,i_class,i_item_id,i_item_desc,revenueratio,i_current_price,itemrevenue] + WholeStageCodegen (6) + Project [i_item_id,i_item_desc,i_category,i_class,i_current_price,itemrevenue,_w0,_we0] + InputAdapter + Window [_w0,i_class] + WholeStageCodegen (5) + Sort [i_class] + InputAdapter + Exchange [i_class] #1 + WholeStageCodegen (4) + HashAggregate [i_item_id,i_item_desc,i_category,i_class,i_current_price,sum] [sum(UnscaledValue(ws_ext_sales_price)),itemrevenue,_w0,sum] + InputAdapter + Exchange [i_item_id,i_item_desc,i_category,i_class,i_current_price] #2 + WholeStageCodegen (3) + HashAggregate [i_item_id,i_item_desc,i_category,i_class,i_current_price,ws_ext_sales_price] [sum,sum] + Project [ws_ext_sales_price,i_item_id,i_item_desc,i_current_price,i_class,i_category] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_ext_sales_price,ws_sold_date_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] + BroadcastHashJoin [ws_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_ext_sales_price,ws_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [i_category,i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] + InputAdapter + ReusedExchange [d_date_sk] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14/explain.txt new file mode 100644 index 0000000000..ec52cea9f9 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14/explain.txt @@ -0,0 +1,759 @@ +== Physical Plan == +TakeOrderedAndProject (84) ++- * BroadcastHashJoin Inner BuildRight (83) + :- * Filter (66) + : +- * HashAggregate (65) + : +- Exchange (64) + : +- * HashAggregate (63) + : +- * Project (62) + : +- * BroadcastHashJoin Inner BuildRight (61) + : :- * Project (59) + : : +- * BroadcastHashJoin Inner BuildRight (58) + : : :- * BroadcastHashJoin LeftSemi BuildRight (51) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- BroadcastExchange (50) + : : : +- * Project (49) + : : : +- * BroadcastHashJoin Inner BuildRight (48) + : : : :- * ColumnarToRow (6) + : : : : +- CometFilter (5) + : : : : +- CometScan parquet spark_catalog.default.item (4) + : : : +- BroadcastExchange (47) + : : : +- * BroadcastHashJoin LeftSemi BuildRight (46) + : : : :- * HashAggregate (35) + : : : : +- Exchange (34) + : : : : +- * HashAggregate (33) + : : : : +- * Project (32) + : : : : +- * BroadcastHashJoin Inner BuildRight (31) + : : : : :- * Project (29) + : : : : : +- * BroadcastHashJoin Inner BuildRight (28) + : : : : : :- * ColumnarToRow (9) + : : : : : : +- CometFilter (8) + : : : : : : +- CometScan parquet spark_catalog.default.store_sales (7) + : : : : : +- BroadcastExchange (27) + : : : : : +- * BroadcastHashJoin LeftSemi BuildRight (26) + : : : : : :- * ColumnarToRow (12) + : : : : : : +- CometFilter (11) + : : : : : : +- CometScan parquet spark_catalog.default.item (10) + : : : : : +- BroadcastExchange (25) + : : : : : +- * Project (24) + : : : : : +- * BroadcastHashJoin Inner BuildRight (23) + : : : : : :- * Project (21) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (20) + : : : : : : :- * ColumnarToRow (15) + : : : : : : : +- CometFilter (14) + : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (13) + : : : : : : +- BroadcastExchange (19) + : : : : : : +- * ColumnarToRow (18) + : : : : : : +- CometFilter (17) + : : : : : : +- CometScan parquet spark_catalog.default.item (16) + : : : : : +- ReusedExchange (22) + : : : : +- ReusedExchange (30) + : : : +- BroadcastExchange (45) + : : : +- * Project (44) + : : : +- * BroadcastHashJoin Inner BuildRight (43) + : : : :- * Project (41) + : : : : +- * BroadcastHashJoin Inner BuildRight (40) + : : : : :- * ColumnarToRow (38) + : : : : : +- CometFilter (37) + : : : : : +- CometScan parquet spark_catalog.default.web_sales (36) + : : : : +- ReusedExchange (39) + : : : +- ReusedExchange (42) + : : +- BroadcastExchange (57) + : : +- * BroadcastHashJoin LeftSemi BuildRight (56) + : : :- * ColumnarToRow (54) + : : : +- CometFilter (53) + : : : +- CometScan parquet spark_catalog.default.item (52) + : : +- ReusedExchange (55) + : +- ReusedExchange (60) + +- BroadcastExchange (82) + +- * Filter (81) + +- * HashAggregate (80) + +- Exchange (79) + +- * HashAggregate (78) + +- * Project (77) + +- * BroadcastHashJoin Inner BuildRight (76) + :- * Project (74) + : +- * BroadcastHashJoin Inner BuildRight (73) + : :- * BroadcastHashJoin LeftSemi BuildRight (71) + : : :- * ColumnarToRow (69) + : : : +- CometFilter (68) + : : : +- CometScan parquet spark_catalog.default.store_sales (67) + : : +- ReusedExchange (70) + : +- ReusedExchange (72) + +- ReusedExchange (75) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#4), dynamicpruningexpression(ss_sold_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4] +Condition : isnotnull(ss_item_sk#1) + +(3) ColumnarToRow [codegen id : 25] +Input [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4] + +(4) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id)] +ReadSchema: struct + +(5) CometFilter +Input [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] +Condition : ((isnotnull(i_brand_id#7) AND isnotnull(i_class_id#8)) AND isnotnull(i_category_id#9)) + +(6) ColumnarToRow [codegen id : 11] +Input [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] + +(7) Scan parquet spark_catalog.default.store_sales +Output [2]: [ss_item_sk#10, ss_sold_date_sk#11] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#11), dynamicpruningexpression(ss_sold_date_sk#11 IN dynamicpruning#12)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(8) CometFilter +Input [2]: [ss_item_sk#10, ss_sold_date_sk#11] +Condition : isnotnull(ss_item_sk#10) + +(9) ColumnarToRow [codegen id : 6] +Input [2]: [ss_item_sk#10, ss_sold_date_sk#11] + +(10) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id)] +ReadSchema: struct + +(11) CometFilter +Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] +Condition : (((isnotnull(i_item_sk#13) AND isnotnull(i_brand_id#14)) AND isnotnull(i_class_id#15)) AND isnotnull(i_category_id#16)) + +(12) ColumnarToRow [codegen id : 4] +Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] + +(13) Scan parquet spark_catalog.default.catalog_sales +Output [2]: [cs_item_sk#17, cs_sold_date_sk#18] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#18), dynamicpruningexpression(cs_sold_date_sk#18 IN dynamicpruning#19)] +PushedFilters: [IsNotNull(cs_item_sk)] +ReadSchema: struct + +(14) CometFilter +Input [2]: [cs_item_sk#17, cs_sold_date_sk#18] +Condition : isnotnull(cs_item_sk#17) + +(15) ColumnarToRow [codegen id : 3] +Input [2]: [cs_item_sk#17, cs_sold_date_sk#18] + +(16) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(17) CometFilter +Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] +Condition : isnotnull(i_item_sk#20) + +(18) ColumnarToRow [codegen id : 1] +Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] + +(19) BroadcastExchange +Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(20) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cs_item_sk#17] +Right keys [1]: [i_item_sk#20] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 3] +Output [4]: [cs_sold_date_sk#18, i_brand_id#21, i_class_id#22, i_category_id#23] +Input [6]: [cs_item_sk#17, cs_sold_date_sk#18, i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] + +(22) ReusedExchange [Reuses operator id: 117] +Output [1]: [d_date_sk#24] + +(23) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cs_sold_date_sk#18] +Right keys [1]: [d_date_sk#24] +Join type: Inner +Join condition: None + +(24) Project [codegen id : 3] +Output [3]: [i_brand_id#21, i_class_id#22, i_category_id#23] +Input [5]: [cs_sold_date_sk#18, i_brand_id#21, i_class_id#22, i_category_id#23, d_date_sk#24] + +(25) BroadcastExchange +Input [3]: [i_brand_id#21, i_class_id#22, i_category_id#23] +Arguments: HashedRelationBroadcastMode(List(coalesce(input[0, int, true], 0), isnull(input[0, int, true]), coalesce(input[1, int, true], 0), isnull(input[1, int, true]), coalesce(input[2, int, true], 0), isnull(input[2, int, true])),false), [plan_id=2] + +(26) BroadcastHashJoin [codegen id : 4] +Left keys [6]: [coalesce(i_brand_id#14, 0), isnull(i_brand_id#14), coalesce(i_class_id#15, 0), isnull(i_class_id#15), coalesce(i_category_id#16, 0), isnull(i_category_id#16)] +Right keys [6]: [coalesce(i_brand_id#21, 0), isnull(i_brand_id#21), coalesce(i_class_id#22, 0), isnull(i_class_id#22), coalesce(i_category_id#23, 0), isnull(i_category_id#23)] +Join type: LeftSemi +Join condition: None + +(27) BroadcastExchange +Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(28) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_item_sk#10] +Right keys [1]: [i_item_sk#13] +Join type: Inner +Join condition: None + +(29) Project [codegen id : 6] +Output [4]: [ss_sold_date_sk#11, i_brand_id#14, i_class_id#15, i_category_id#16] +Input [6]: [ss_item_sk#10, ss_sold_date_sk#11, i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] + +(30) ReusedExchange [Reuses operator id: 117] +Output [1]: [d_date_sk#25] + +(31) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_sold_date_sk#11] +Right keys [1]: [d_date_sk#25] +Join type: Inner +Join condition: None + +(32) Project [codegen id : 6] +Output [3]: [i_brand_id#14 AS brand_id#26, i_class_id#15 AS class_id#27, i_category_id#16 AS category_id#28] +Input [5]: [ss_sold_date_sk#11, i_brand_id#14, i_class_id#15, i_category_id#16, d_date_sk#25] + +(33) HashAggregate [codegen id : 6] +Input [3]: [brand_id#26, class_id#27, category_id#28] +Keys [3]: [brand_id#26, class_id#27, category_id#28] +Functions: [] +Aggregate Attributes: [] +Results [3]: [brand_id#26, class_id#27, category_id#28] + +(34) Exchange +Input [3]: [brand_id#26, class_id#27, category_id#28] +Arguments: hashpartitioning(brand_id#26, class_id#27, category_id#28, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(35) HashAggregate [codegen id : 10] +Input [3]: [brand_id#26, class_id#27, category_id#28] +Keys [3]: [brand_id#26, class_id#27, category_id#28] +Functions: [] +Aggregate Attributes: [] +Results [3]: [brand_id#26, class_id#27, category_id#28] + +(36) Scan parquet spark_catalog.default.web_sales +Output [2]: [ws_item_sk#29, ws_sold_date_sk#30] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#30), dynamicpruningexpression(ws_sold_date_sk#30 IN dynamicpruning#31)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(37) CometFilter +Input [2]: [ws_item_sk#29, ws_sold_date_sk#30] +Condition : isnotnull(ws_item_sk#29) + +(38) ColumnarToRow [codegen id : 9] +Input [2]: [ws_item_sk#29, ws_sold_date_sk#30] + +(39) ReusedExchange [Reuses operator id: 19] +Output [4]: [i_item_sk#32, i_brand_id#33, i_class_id#34, i_category_id#35] + +(40) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ws_item_sk#29] +Right keys [1]: [i_item_sk#32] +Join type: Inner +Join condition: None + +(41) Project [codegen id : 9] +Output [4]: [ws_sold_date_sk#30, i_brand_id#33, i_class_id#34, i_category_id#35] +Input [6]: [ws_item_sk#29, ws_sold_date_sk#30, i_item_sk#32, i_brand_id#33, i_class_id#34, i_category_id#35] + +(42) ReusedExchange [Reuses operator id: 117] +Output [1]: [d_date_sk#36] + +(43) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ws_sold_date_sk#30] +Right keys [1]: [d_date_sk#36] +Join type: Inner +Join condition: None + +(44) Project [codegen id : 9] +Output [3]: [i_brand_id#33, i_class_id#34, i_category_id#35] +Input [5]: [ws_sold_date_sk#30, i_brand_id#33, i_class_id#34, i_category_id#35, d_date_sk#36] + +(45) BroadcastExchange +Input [3]: [i_brand_id#33, i_class_id#34, i_category_id#35] +Arguments: HashedRelationBroadcastMode(List(coalesce(input[0, int, true], 0), isnull(input[0, int, true]), coalesce(input[1, int, true], 0), isnull(input[1, int, true]), coalesce(input[2, int, true], 0), isnull(input[2, int, true])),false), [plan_id=5] + +(46) BroadcastHashJoin [codegen id : 10] +Left keys [6]: [coalesce(brand_id#26, 0), isnull(brand_id#26), coalesce(class_id#27, 0), isnull(class_id#27), coalesce(category_id#28, 0), isnull(category_id#28)] +Right keys [6]: [coalesce(i_brand_id#33, 0), isnull(i_brand_id#33), coalesce(i_class_id#34, 0), isnull(i_class_id#34), coalesce(i_category_id#35, 0), isnull(i_category_id#35)] +Join type: LeftSemi +Join condition: None + +(47) BroadcastExchange +Input [3]: [brand_id#26, class_id#27, category_id#28] +Arguments: HashedRelationBroadcastMode(List(input[0, int, true], input[1, int, true], input[2, int, true]),false), [plan_id=6] + +(48) BroadcastHashJoin [codegen id : 11] +Left keys [3]: [i_brand_id#7, i_class_id#8, i_category_id#9] +Right keys [3]: [brand_id#26, class_id#27, category_id#28] +Join type: Inner +Join condition: None + +(49) Project [codegen id : 11] +Output [1]: [i_item_sk#6 AS ss_item_sk#37] +Input [7]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9, brand_id#26, class_id#27, category_id#28] + +(50) BroadcastExchange +Input [1]: [ss_item_sk#37] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +(51) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [ss_item_sk#37] +Join type: LeftSemi +Join condition: None + +(52) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id)] +ReadSchema: struct + +(53) CometFilter +Input [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] +Condition : (((isnotnull(i_item_sk#38) AND isnotnull(i_brand_id#39)) AND isnotnull(i_class_id#40)) AND isnotnull(i_category_id#41)) + +(54) ColumnarToRow [codegen id : 23] +Input [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] + +(55) ReusedExchange [Reuses operator id: 50] +Output [1]: [ss_item_sk#37] + +(56) BroadcastHashJoin [codegen id : 23] +Left keys [1]: [i_item_sk#38] +Right keys [1]: [ss_item_sk#37] +Join type: LeftSemi +Join condition: None + +(57) BroadcastExchange +Input [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8] + +(58) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#38] +Join type: Inner +Join condition: None + +(59) Project [codegen id : 25] +Output [6]: [ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4, i_brand_id#39, i_class_id#40, i_category_id#41] +Input [8]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4, i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] + +(60) ReusedExchange [Reuses operator id: 108] +Output [1]: [d_date_sk#42] + +(61) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_sold_date_sk#4] +Right keys [1]: [d_date_sk#42] +Join type: Inner +Join condition: None + +(62) Project [codegen id : 25] +Output [5]: [ss_quantity#2, ss_list_price#3, i_brand_id#39, i_class_id#40, i_category_id#41] +Input [7]: [ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4, i_brand_id#39, i_class_id#40, i_category_id#41, d_date_sk#42] + +(63) HashAggregate [codegen id : 25] +Input [5]: [ss_quantity#2, ss_list_price#3, i_brand_id#39, i_class_id#40, i_category_id#41] +Keys [3]: [i_brand_id#39, i_class_id#40, i_category_id#41] +Functions [2]: [partial_sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3)), partial_count(1)] +Aggregate Attributes [3]: [sum#43, isEmpty#44, count#45] +Results [6]: [i_brand_id#39, i_class_id#40, i_category_id#41, sum#46, isEmpty#47, count#48] + +(64) Exchange +Input [6]: [i_brand_id#39, i_class_id#40, i_category_id#41, sum#46, isEmpty#47, count#48] +Arguments: hashpartitioning(i_brand_id#39, i_class_id#40, i_category_id#41, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(65) HashAggregate [codegen id : 52] +Input [6]: [i_brand_id#39, i_class_id#40, i_category_id#41, sum#46, isEmpty#47, count#48] +Keys [3]: [i_brand_id#39, i_class_id#40, i_category_id#41] +Functions [2]: [sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3)), count(1)] +Aggregate Attributes [2]: [sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3))#49, count(1)#50] +Results [6]: [store AS channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3))#49 AS sales#52, count(1)#50 AS number_sales#53] + +(66) Filter [codegen id : 52] +Input [6]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sales#52, number_sales#53] +Condition : (isnotnull(sales#52) AND (cast(sales#52 as decimal(32,6)) > cast(Subquery scalar-subquery#54, [id=#55] as decimal(32,6)))) + +(67) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#56, ss_quantity#57, ss_list_price#58, ss_sold_date_sk#59] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#59), dynamicpruningexpression(ss_sold_date_sk#59 IN dynamicpruning#60)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(68) CometFilter +Input [4]: [ss_item_sk#56, ss_quantity#57, ss_list_price#58, ss_sold_date_sk#59] +Condition : isnotnull(ss_item_sk#56) + +(69) ColumnarToRow [codegen id : 50] +Input [4]: [ss_item_sk#56, ss_quantity#57, ss_list_price#58, ss_sold_date_sk#59] + +(70) ReusedExchange [Reuses operator id: 50] +Output [1]: [ss_item_sk#61] + +(71) BroadcastHashJoin [codegen id : 50] +Left keys [1]: [ss_item_sk#56] +Right keys [1]: [ss_item_sk#61] +Join type: LeftSemi +Join condition: None + +(72) ReusedExchange [Reuses operator id: 57] +Output [4]: [i_item_sk#62, i_brand_id#63, i_class_id#64, i_category_id#65] + +(73) BroadcastHashJoin [codegen id : 50] +Left keys [1]: [ss_item_sk#56] +Right keys [1]: [i_item_sk#62] +Join type: Inner +Join condition: None + +(74) Project [codegen id : 50] +Output [6]: [ss_quantity#57, ss_list_price#58, ss_sold_date_sk#59, i_brand_id#63, i_class_id#64, i_category_id#65] +Input [8]: [ss_item_sk#56, ss_quantity#57, ss_list_price#58, ss_sold_date_sk#59, i_item_sk#62, i_brand_id#63, i_class_id#64, i_category_id#65] + +(75) ReusedExchange [Reuses operator id: 122] +Output [1]: [d_date_sk#66] + +(76) BroadcastHashJoin [codegen id : 50] +Left keys [1]: [ss_sold_date_sk#59] +Right keys [1]: [d_date_sk#66] +Join type: Inner +Join condition: None + +(77) Project [codegen id : 50] +Output [5]: [ss_quantity#57, ss_list_price#58, i_brand_id#63, i_class_id#64, i_category_id#65] +Input [7]: [ss_quantity#57, ss_list_price#58, ss_sold_date_sk#59, i_brand_id#63, i_class_id#64, i_category_id#65, d_date_sk#66] + +(78) HashAggregate [codegen id : 50] +Input [5]: [ss_quantity#57, ss_list_price#58, i_brand_id#63, i_class_id#64, i_category_id#65] +Keys [3]: [i_brand_id#63, i_class_id#64, i_category_id#65] +Functions [2]: [partial_sum((cast(ss_quantity#57 as decimal(10,0)) * ss_list_price#58)), partial_count(1)] +Aggregate Attributes [3]: [sum#67, isEmpty#68, count#69] +Results [6]: [i_brand_id#63, i_class_id#64, i_category_id#65, sum#70, isEmpty#71, count#72] + +(79) Exchange +Input [6]: [i_brand_id#63, i_class_id#64, i_category_id#65, sum#70, isEmpty#71, count#72] +Arguments: hashpartitioning(i_brand_id#63, i_class_id#64, i_category_id#65, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(80) HashAggregate [codegen id : 51] +Input [6]: [i_brand_id#63, i_class_id#64, i_category_id#65, sum#70, isEmpty#71, count#72] +Keys [3]: [i_brand_id#63, i_class_id#64, i_category_id#65] +Functions [2]: [sum((cast(ss_quantity#57 as decimal(10,0)) * ss_list_price#58)), count(1)] +Aggregate Attributes [2]: [sum((cast(ss_quantity#57 as decimal(10,0)) * ss_list_price#58))#73, count(1)#74] +Results [6]: [store AS channel#75, i_brand_id#63, i_class_id#64, i_category_id#65, sum((cast(ss_quantity#57 as decimal(10,0)) * ss_list_price#58))#73 AS sales#76, count(1)#74 AS number_sales#77] + +(81) Filter [codegen id : 51] +Input [6]: [channel#75, i_brand_id#63, i_class_id#64, i_category_id#65, sales#76, number_sales#77] +Condition : (isnotnull(sales#76) AND (cast(sales#76 as decimal(32,6)) > cast(ReusedSubquery Subquery scalar-subquery#54, [id=#55] as decimal(32,6)))) + +(82) BroadcastExchange +Input [6]: [channel#75, i_brand_id#63, i_class_id#64, i_category_id#65, sales#76, number_sales#77] +Arguments: HashedRelationBroadcastMode(List(input[1, int, true], input[2, int, true], input[3, int, true]),false), [plan_id=11] + +(83) BroadcastHashJoin [codegen id : 52] +Left keys [3]: [i_brand_id#39, i_class_id#40, i_category_id#41] +Right keys [3]: [i_brand_id#63, i_class_id#64, i_category_id#65] +Join type: Inner +Join condition: None + +(84) TakeOrderedAndProject +Input [12]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sales#52, number_sales#53, channel#75, i_brand_id#63, i_class_id#64, i_category_id#65, sales#76, number_sales#77] +Arguments: 100, [i_brand_id#39 ASC NULLS FIRST, i_class_id#40 ASC NULLS FIRST, i_category_id#41 ASC NULLS FIRST], [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sales#52, number_sales#53, channel#75, i_brand_id#63, i_class_id#64, i_category_id#65, sales#76, number_sales#77] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 66 Hosting Expression = Subquery scalar-subquery#54, [id=#55] +* HashAggregate (103) ++- Exchange (102) + +- * HashAggregate (101) + +- Union (100) + :- * Project (89) + : +- * BroadcastHashJoin Inner BuildRight (88) + : :- * ColumnarToRow (86) + : : +- CometScan parquet spark_catalog.default.store_sales (85) + : +- ReusedExchange (87) + :- * Project (94) + : +- * BroadcastHashJoin Inner BuildRight (93) + : :- * ColumnarToRow (91) + : : +- CometScan parquet spark_catalog.default.catalog_sales (90) + : +- ReusedExchange (92) + +- * Project (99) + +- * BroadcastHashJoin Inner BuildRight (98) + :- * ColumnarToRow (96) + : +- CometScan parquet spark_catalog.default.web_sales (95) + +- ReusedExchange (97) + + +(85) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_quantity#78, ss_list_price#79, ss_sold_date_sk#80] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#80), dynamicpruningexpression(ss_sold_date_sk#80 IN dynamicpruning#81)] +ReadSchema: struct + +(86) ColumnarToRow [codegen id : 2] +Input [3]: [ss_quantity#78, ss_list_price#79, ss_sold_date_sk#80] + +(87) ReusedExchange [Reuses operator id: 117] +Output [1]: [d_date_sk#82] + +(88) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [ss_sold_date_sk#80] +Right keys [1]: [d_date_sk#82] +Join type: Inner +Join condition: None + +(89) Project [codegen id : 2] +Output [2]: [ss_quantity#78 AS quantity#83, ss_list_price#79 AS list_price#84] +Input [4]: [ss_quantity#78, ss_list_price#79, ss_sold_date_sk#80, d_date_sk#82] + +(90) Scan parquet spark_catalog.default.catalog_sales +Output [3]: [cs_quantity#85, cs_list_price#86, cs_sold_date_sk#87] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#87), dynamicpruningexpression(cs_sold_date_sk#87 IN dynamicpruning#88)] +ReadSchema: struct + +(91) ColumnarToRow [codegen id : 4] +Input [3]: [cs_quantity#85, cs_list_price#86, cs_sold_date_sk#87] + +(92) ReusedExchange [Reuses operator id: 117] +Output [1]: [d_date_sk#89] + +(93) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [cs_sold_date_sk#87] +Right keys [1]: [d_date_sk#89] +Join type: Inner +Join condition: None + +(94) Project [codegen id : 4] +Output [2]: [cs_quantity#85 AS quantity#90, cs_list_price#86 AS list_price#91] +Input [4]: [cs_quantity#85, cs_list_price#86, cs_sold_date_sk#87, d_date_sk#89] + +(95) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_quantity#92, ws_list_price#93, ws_sold_date_sk#94] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#94), dynamicpruningexpression(ws_sold_date_sk#94 IN dynamicpruning#95)] +ReadSchema: struct + +(96) ColumnarToRow [codegen id : 6] +Input [3]: [ws_quantity#92, ws_list_price#93, ws_sold_date_sk#94] + +(97) ReusedExchange [Reuses operator id: 117] +Output [1]: [d_date_sk#96] + +(98) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ws_sold_date_sk#94] +Right keys [1]: [d_date_sk#96] +Join type: Inner +Join condition: None + +(99) Project [codegen id : 6] +Output [2]: [ws_quantity#92 AS quantity#97, ws_list_price#93 AS list_price#98] +Input [4]: [ws_quantity#92, ws_list_price#93, ws_sold_date_sk#94, d_date_sk#96] + +(100) Union + +(101) HashAggregate [codegen id : 7] +Input [2]: [quantity#83, list_price#84] +Keys: [] +Functions [1]: [partial_avg((cast(quantity#83 as decimal(10,0)) * list_price#84))] +Aggregate Attributes [2]: [sum#99, count#100] +Results [2]: [sum#101, count#102] + +(102) Exchange +Input [2]: [sum#101, count#102] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=12] + +(103) HashAggregate [codegen id : 8] +Input [2]: [sum#101, count#102] +Keys: [] +Functions [1]: [avg((cast(quantity#83 as decimal(10,0)) * list_price#84))] +Aggregate Attributes [1]: [avg((cast(quantity#83 as decimal(10,0)) * list_price#84))#103] +Results [1]: [avg((cast(quantity#83 as decimal(10,0)) * list_price#84))#103 AS average_sales#104] + +Subquery:2 Hosting operator id = 85 Hosting Expression = ss_sold_date_sk#80 IN dynamicpruning#12 + +Subquery:3 Hosting operator id = 90 Hosting Expression = cs_sold_date_sk#87 IN dynamicpruning#12 + +Subquery:4 Hosting operator id = 95 Hosting Expression = ws_sold_date_sk#94 IN dynamicpruning#12 + +Subquery:5 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (108) ++- * ColumnarToRow (107) + +- CometProject (106) + +- CometFilter (105) + +- CometScan parquet spark_catalog.default.date_dim (104) + + +(104) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#42, d_week_seq#105] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_week_seq), EqualTo(d_week_seq,ScalarSubquery#106), IsNotNull(d_date_sk)] +ReadSchema: struct + +(105) CometFilter +Input [2]: [d_date_sk#42, d_week_seq#105] +Condition : ((isnotnull(d_week_seq#105) AND (d_week_seq#105 = ReusedSubquery Subquery scalar-subquery#106, [id=#107])) AND isnotnull(d_date_sk#42)) + +(106) CometProject +Input [2]: [d_date_sk#42, d_week_seq#105] +Arguments: [d_date_sk#42], [d_date_sk#42] + +(107) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#42] + +(108) BroadcastExchange +Input [1]: [d_date_sk#42] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=13] + +Subquery:6 Hosting operator id = 105 Hosting Expression = ReusedSubquery Subquery scalar-subquery#106, [id=#107] + +Subquery:7 Hosting operator id = 104 Hosting Expression = Subquery scalar-subquery#106, [id=#107] +* ColumnarToRow (112) ++- CometProject (111) + +- CometFilter (110) + +- CometScan parquet spark_catalog.default.date_dim (109) + + +(109) Scan parquet spark_catalog.default.date_dim +Output [4]: [d_week_seq#108, d_year#109, d_moy#110, d_dom#111] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), IsNotNull(d_dom), EqualTo(d_year,1999), EqualTo(d_moy,12), EqualTo(d_dom,16)] +ReadSchema: struct + +(110) CometFilter +Input [4]: [d_week_seq#108, d_year#109, d_moy#110, d_dom#111] +Condition : (((((isnotnull(d_year#109) AND isnotnull(d_moy#110)) AND isnotnull(d_dom#111)) AND (d_year#109 = 1999)) AND (d_moy#110 = 12)) AND (d_dom#111 = 16)) + +(111) CometProject +Input [4]: [d_week_seq#108, d_year#109, d_moy#110, d_dom#111] +Arguments: [d_week_seq#108], [d_week_seq#108] + +(112) ColumnarToRow [codegen id : 1] +Input [1]: [d_week_seq#108] + +Subquery:8 Hosting operator id = 7 Hosting Expression = ss_sold_date_sk#11 IN dynamicpruning#12 +BroadcastExchange (117) ++- * ColumnarToRow (116) + +- CometProject (115) + +- CometFilter (114) + +- CometScan parquet spark_catalog.default.date_dim (113) + + +(113) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#25, d_year#112] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), GreaterThanOrEqual(d_year,1998), LessThanOrEqual(d_year,2000), IsNotNull(d_date_sk)] +ReadSchema: struct + +(114) CometFilter +Input [2]: [d_date_sk#25, d_year#112] +Condition : (((isnotnull(d_year#112) AND (d_year#112 >= 1998)) AND (d_year#112 <= 2000)) AND isnotnull(d_date_sk#25)) + +(115) CometProject +Input [2]: [d_date_sk#25, d_year#112] +Arguments: [d_date_sk#25], [d_date_sk#25] + +(116) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#25] + +(117) BroadcastExchange +Input [1]: [d_date_sk#25] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=14] + +Subquery:9 Hosting operator id = 13 Hosting Expression = cs_sold_date_sk#18 IN dynamicpruning#12 + +Subquery:10 Hosting operator id = 36 Hosting Expression = ws_sold_date_sk#30 IN dynamicpruning#12 + +Subquery:11 Hosting operator id = 81 Hosting Expression = ReusedSubquery Subquery scalar-subquery#54, [id=#55] + +Subquery:12 Hosting operator id = 67 Hosting Expression = ss_sold_date_sk#59 IN dynamicpruning#60 +BroadcastExchange (122) ++- * ColumnarToRow (121) + +- CometProject (120) + +- CometFilter (119) + +- CometScan parquet spark_catalog.default.date_dim (118) + + +(118) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#66, d_week_seq#113] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_week_seq), EqualTo(d_week_seq,ScalarSubquery#114), IsNotNull(d_date_sk)] +ReadSchema: struct + +(119) CometFilter +Input [2]: [d_date_sk#66, d_week_seq#113] +Condition : ((isnotnull(d_week_seq#113) AND (d_week_seq#113 = ReusedSubquery Subquery scalar-subquery#114, [id=#115])) AND isnotnull(d_date_sk#66)) + +(120) CometProject +Input [2]: [d_date_sk#66, d_week_seq#113] +Arguments: [d_date_sk#66], [d_date_sk#66] + +(121) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#66] + +(122) BroadcastExchange +Input [1]: [d_date_sk#66] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=15] + +Subquery:13 Hosting operator id = 119 Hosting Expression = ReusedSubquery Subquery scalar-subquery#114, [id=#115] + +Subquery:14 Hosting operator id = 118 Hosting Expression = Subquery scalar-subquery#114, [id=#115] +* ColumnarToRow (126) ++- CometProject (125) + +- CometFilter (124) + +- CometScan parquet spark_catalog.default.date_dim (123) + + +(123) Scan parquet spark_catalog.default.date_dim +Output [4]: [d_week_seq#116, d_year#117, d_moy#118, d_dom#119] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), IsNotNull(d_dom), EqualTo(d_year,1998), EqualTo(d_moy,12), EqualTo(d_dom,16)] +ReadSchema: struct + +(124) CometFilter +Input [4]: [d_week_seq#116, d_year#117, d_moy#118, d_dom#119] +Condition : (((((isnotnull(d_year#117) AND isnotnull(d_moy#118)) AND isnotnull(d_dom#119)) AND (d_year#117 = 1998)) AND (d_moy#118 = 12)) AND (d_dom#119 = 16)) + +(125) CometProject +Input [4]: [d_week_seq#116, d_year#117, d_moy#118, d_dom#119] +Arguments: [d_week_seq#116], [d_week_seq#116] + +(126) ColumnarToRow [codegen id : 1] +Input [1]: [d_week_seq#116] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14/simplified.txt new file mode 100644 index 0000000000..55aa823ab8 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14/simplified.txt @@ -0,0 +1,204 @@ +TakeOrderedAndProject [i_brand_id,i_class_id,i_category_id,channel,sales,number_sales,channel,i_brand_id,i_class_id,i_category_id,sales,number_sales] + WholeStageCodegen (52) + BroadcastHashJoin [i_brand_id,i_class_id,i_category_id,i_brand_id,i_class_id,i_category_id] + Filter [sales] + Subquery #4 + WholeStageCodegen (8) + HashAggregate [sum,count] [avg((cast(quantity as decimal(10,0)) * list_price)),average_sales,sum,count] + InputAdapter + Exchange #12 + WholeStageCodegen (7) + HashAggregate [quantity,list_price] [sum,count,sum,count] + InputAdapter + Union + WholeStageCodegen (2) + Project [ss_quantity,ss_list_price] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_list_price,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #3 + InputAdapter + ReusedExchange [d_date_sk] #6 + WholeStageCodegen (4) + Project [cs_quantity,cs_list_price] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_quantity,cs_list_price,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #3 + InputAdapter + ReusedExchange [d_date_sk] #6 + WholeStageCodegen (6) + Project [ws_quantity,ws_list_price] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_quantity,ws_list_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #3 + InputAdapter + ReusedExchange [d_date_sk] #6 + HashAggregate [i_brand_id,i_class_id,i_category_id,sum,isEmpty,count] [sum((cast(ss_quantity as decimal(10,0)) * ss_list_price)),count(1),channel,sales,number_sales,sum,isEmpty,count] + InputAdapter + Exchange [i_brand_id,i_class_id,i_category_id] #1 + WholeStageCodegen (25) + HashAggregate [i_brand_id,i_class_id,i_category_id,ss_quantity,ss_list_price] [sum,isEmpty,count,sum,isEmpty,count] + Project [ss_quantity,ss_list_price,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_quantity,ss_list_price,ss_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + BroadcastHashJoin [ss_item_sk,ss_item_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_quantity,ss_list_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_week_seq,d_date_sk] + ReusedSubquery [d_week_seq] #2 + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_week_seq] + Subquery #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_week_seq] + CometFilter [d_year,d_moy,d_dom] + CometScan parquet spark_catalog.default.date_dim [d_week_seq,d_year,d_moy,d_dom] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (11) + Project [i_item_sk] + BroadcastHashJoin [i_brand_id,i_class_id,i_category_id,brand_id,class_id,category_id] + ColumnarToRow + InputAdapter + CometFilter [i_brand_id,i_class_id,i_category_id] + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (10) + BroadcastHashJoin [brand_id,class_id,category_id,i_brand_id,i_class_id,i_category_id] + HashAggregate [brand_id,class_id,category_id] + InputAdapter + Exchange [brand_id,class_id,category_id] #5 + WholeStageCodegen (6) + HashAggregate [brand_id,class_id,category_id] + Project [i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #3 + BroadcastExchange #6 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (4) + BroadcastHashJoin [i_brand_id,i_class_id,i_category_id,i_brand_id,i_class_id,i_category_id] + ColumnarToRow + InputAdapter + CometFilter [i_item_sk,i_brand_id,i_class_id,i_category_id] + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (3) + Project [i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #3 + InputAdapter + BroadcastExchange #9 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] + InputAdapter + ReusedExchange [d_date_sk] #6 + InputAdapter + ReusedExchange [d_date_sk] #6 + InputAdapter + BroadcastExchange #10 + WholeStageCodegen (9) + Project [i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ws_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #3 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id] #9 + InputAdapter + ReusedExchange [d_date_sk] #6 + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (23) + BroadcastHashJoin [i_item_sk,ss_item_sk] + ColumnarToRow + InputAdapter + CometFilter [i_item_sk,i_brand_id,i_class_id,i_category_id] + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] + InputAdapter + ReusedExchange [ss_item_sk] #3 + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #13 + WholeStageCodegen (51) + Filter [sales] + ReusedSubquery [average_sales] #4 + HashAggregate [i_brand_id,i_class_id,i_category_id,sum,isEmpty,count] [sum((cast(ss_quantity as decimal(10,0)) * ss_list_price)),count(1),channel,sales,number_sales,sum,isEmpty,count] + InputAdapter + Exchange [i_brand_id,i_class_id,i_category_id] #14 + WholeStageCodegen (50) + HashAggregate [i_brand_id,i_class_id,i_category_id,ss_quantity,ss_list_price] [sum,isEmpty,count,sum,isEmpty,count] + Project [ss_quantity,ss_list_price,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_quantity,ss_list_price,ss_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + BroadcastHashJoin [ss_item_sk,ss_item_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_quantity,ss_list_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #5 + BroadcastExchange #15 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_week_seq,d_date_sk] + ReusedSubquery [d_week_seq] #6 + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_week_seq] + Subquery #6 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_week_seq] + CometFilter [d_year,d_moy,d_dom] + CometScan parquet spark_catalog.default.date_dim [d_week_seq,d_year,d_moy,d_dom] + InputAdapter + ReusedExchange [ss_item_sk] #3 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id] #11 + InputAdapter + ReusedExchange [d_date_sk] #15 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14a/explain.txt new file mode 100644 index 0000000000..d76059e019 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14a/explain.txt @@ -0,0 +1,964 @@ +== Physical Plan == +TakeOrderedAndProject (125) ++- * HashAggregate (124) + +- Exchange (123) + +- * HashAggregate (122) + +- Union (121) + :- * HashAggregate (100) + : +- Exchange (99) + : +- * HashAggregate (98) + : +- Union (97) + : :- * Filter (66) + : : +- * HashAggregate (65) + : : +- Exchange (64) + : : +- * HashAggregate (63) + : : +- * Project (62) + : : +- * BroadcastHashJoin Inner BuildRight (61) + : : :- * Project (59) + : : : +- * BroadcastHashJoin Inner BuildRight (58) + : : : :- * BroadcastHashJoin LeftSemi BuildRight (51) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : +- BroadcastExchange (50) + : : : : +- * Project (49) + : : : : +- * BroadcastHashJoin Inner BuildRight (48) + : : : : :- * ColumnarToRow (6) + : : : : : +- CometFilter (5) + : : : : : +- CometScan parquet spark_catalog.default.item (4) + : : : : +- BroadcastExchange (47) + : : : : +- * BroadcastHashJoin LeftSemi BuildRight (46) + : : : : :- * HashAggregate (35) + : : : : : +- Exchange (34) + : : : : : +- * HashAggregate (33) + : : : : : +- * Project (32) + : : : : : +- * BroadcastHashJoin Inner BuildRight (31) + : : : : : :- * Project (29) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (28) + : : : : : : :- * ColumnarToRow (9) + : : : : : : : +- CometFilter (8) + : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (7) + : : : : : : +- BroadcastExchange (27) + : : : : : : +- * BroadcastHashJoin LeftSemi BuildRight (26) + : : : : : : :- * ColumnarToRow (12) + : : : : : : : +- CometFilter (11) + : : : : : : : +- CometScan parquet spark_catalog.default.item (10) + : : : : : : +- BroadcastExchange (25) + : : : : : : +- * Project (24) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (23) + : : : : : : :- * Project (21) + : : : : : : : +- * BroadcastHashJoin Inner BuildRight (20) + : : : : : : : :- * ColumnarToRow (15) + : : : : : : : : +- CometFilter (14) + : : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (13) + : : : : : : : +- BroadcastExchange (19) + : : : : : : : +- * ColumnarToRow (18) + : : : : : : : +- CometFilter (17) + : : : : : : : +- CometScan parquet spark_catalog.default.item (16) + : : : : : : +- ReusedExchange (22) + : : : : : +- ReusedExchange (30) + : : : : +- BroadcastExchange (45) + : : : : +- * Project (44) + : : : : +- * BroadcastHashJoin Inner BuildRight (43) + : : : : :- * Project (41) + : : : : : +- * BroadcastHashJoin Inner BuildRight (40) + : : : : : :- * ColumnarToRow (38) + : : : : : : +- CometFilter (37) + : : : : : : +- CometScan parquet spark_catalog.default.web_sales (36) + : : : : : +- ReusedExchange (39) + : : : : +- ReusedExchange (42) + : : : +- BroadcastExchange (57) + : : : +- * BroadcastHashJoin LeftSemi BuildRight (56) + : : : :- * ColumnarToRow (54) + : : : : +- CometFilter (53) + : : : : +- CometScan parquet spark_catalog.default.item (52) + : : : +- ReusedExchange (55) + : : +- ReusedExchange (60) + : :- * Filter (81) + : : +- * HashAggregate (80) + : : +- Exchange (79) + : : +- * HashAggregate (78) + : : +- * Project (77) + : : +- * BroadcastHashJoin Inner BuildRight (76) + : : :- * Project (74) + : : : +- * BroadcastHashJoin Inner BuildRight (73) + : : : :- * BroadcastHashJoin LeftSemi BuildRight (71) + : : : : :- * ColumnarToRow (69) + : : : : : +- CometFilter (68) + : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (67) + : : : : +- ReusedExchange (70) + : : : +- ReusedExchange (72) + : : +- ReusedExchange (75) + : +- * Filter (96) + : +- * HashAggregate (95) + : +- Exchange (94) + : +- * HashAggregate (93) + : +- * Project (92) + : +- * BroadcastHashJoin Inner BuildRight (91) + : :- * Project (89) + : : +- * BroadcastHashJoin Inner BuildRight (88) + : : :- * BroadcastHashJoin LeftSemi BuildRight (86) + : : : :- * ColumnarToRow (84) + : : : : +- CometFilter (83) + : : : : +- CometScan parquet spark_catalog.default.web_sales (82) + : : : +- ReusedExchange (85) + : : +- ReusedExchange (87) + : +- ReusedExchange (90) + :- * HashAggregate (105) + : +- Exchange (104) + : +- * HashAggregate (103) + : +- * HashAggregate (102) + : +- ReusedExchange (101) + :- * HashAggregate (110) + : +- Exchange (109) + : +- * HashAggregate (108) + : +- * HashAggregate (107) + : +- ReusedExchange (106) + :- * HashAggregate (115) + : +- Exchange (114) + : +- * HashAggregate (113) + : +- * HashAggregate (112) + : +- ReusedExchange (111) + +- * HashAggregate (120) + +- Exchange (119) + +- * HashAggregate (118) + +- * HashAggregate (117) + +- ReusedExchange (116) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#4), dynamicpruningexpression(ss_sold_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4] +Condition : isnotnull(ss_item_sk#1) + +(3) ColumnarToRow [codegen id : 25] +Input [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4] + +(4) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id)] +ReadSchema: struct + +(5) CometFilter +Input [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] +Condition : ((isnotnull(i_brand_id#7) AND isnotnull(i_class_id#8)) AND isnotnull(i_category_id#9)) + +(6) ColumnarToRow [codegen id : 11] +Input [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] + +(7) Scan parquet spark_catalog.default.store_sales +Output [2]: [ss_item_sk#10, ss_sold_date_sk#11] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#11), dynamicpruningexpression(ss_sold_date_sk#11 IN dynamicpruning#12)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(8) CometFilter +Input [2]: [ss_item_sk#10, ss_sold_date_sk#11] +Condition : isnotnull(ss_item_sk#10) + +(9) ColumnarToRow [codegen id : 6] +Input [2]: [ss_item_sk#10, ss_sold_date_sk#11] + +(10) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id)] +ReadSchema: struct + +(11) CometFilter +Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] +Condition : (((isnotnull(i_item_sk#13) AND isnotnull(i_brand_id#14)) AND isnotnull(i_class_id#15)) AND isnotnull(i_category_id#16)) + +(12) ColumnarToRow [codegen id : 4] +Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] + +(13) Scan parquet spark_catalog.default.catalog_sales +Output [2]: [cs_item_sk#17, cs_sold_date_sk#18] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#18), dynamicpruningexpression(cs_sold_date_sk#18 IN dynamicpruning#19)] +PushedFilters: [IsNotNull(cs_item_sk)] +ReadSchema: struct + +(14) CometFilter +Input [2]: [cs_item_sk#17, cs_sold_date_sk#18] +Condition : isnotnull(cs_item_sk#17) + +(15) ColumnarToRow [codegen id : 3] +Input [2]: [cs_item_sk#17, cs_sold_date_sk#18] + +(16) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(17) CometFilter +Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] +Condition : isnotnull(i_item_sk#20) + +(18) ColumnarToRow [codegen id : 1] +Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] + +(19) BroadcastExchange +Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(20) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cs_item_sk#17] +Right keys [1]: [i_item_sk#20] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 3] +Output [4]: [cs_sold_date_sk#18, i_brand_id#21, i_class_id#22, i_category_id#23] +Input [6]: [cs_item_sk#17, cs_sold_date_sk#18, i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] + +(22) ReusedExchange [Reuses operator id: 159] +Output [1]: [d_date_sk#24] + +(23) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cs_sold_date_sk#18] +Right keys [1]: [d_date_sk#24] +Join type: Inner +Join condition: None + +(24) Project [codegen id : 3] +Output [3]: [i_brand_id#21, i_class_id#22, i_category_id#23] +Input [5]: [cs_sold_date_sk#18, i_brand_id#21, i_class_id#22, i_category_id#23, d_date_sk#24] + +(25) BroadcastExchange +Input [3]: [i_brand_id#21, i_class_id#22, i_category_id#23] +Arguments: HashedRelationBroadcastMode(List(coalesce(input[0, int, true], 0), isnull(input[0, int, true]), coalesce(input[1, int, true], 0), isnull(input[1, int, true]), coalesce(input[2, int, true], 0), isnull(input[2, int, true])),false), [plan_id=2] + +(26) BroadcastHashJoin [codegen id : 4] +Left keys [6]: [coalesce(i_brand_id#14, 0), isnull(i_brand_id#14), coalesce(i_class_id#15, 0), isnull(i_class_id#15), coalesce(i_category_id#16, 0), isnull(i_category_id#16)] +Right keys [6]: [coalesce(i_brand_id#21, 0), isnull(i_brand_id#21), coalesce(i_class_id#22, 0), isnull(i_class_id#22), coalesce(i_category_id#23, 0), isnull(i_category_id#23)] +Join type: LeftSemi +Join condition: None + +(27) BroadcastExchange +Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(28) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_item_sk#10] +Right keys [1]: [i_item_sk#13] +Join type: Inner +Join condition: None + +(29) Project [codegen id : 6] +Output [4]: [ss_sold_date_sk#11, i_brand_id#14, i_class_id#15, i_category_id#16] +Input [6]: [ss_item_sk#10, ss_sold_date_sk#11, i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] + +(30) ReusedExchange [Reuses operator id: 159] +Output [1]: [d_date_sk#25] + +(31) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_sold_date_sk#11] +Right keys [1]: [d_date_sk#25] +Join type: Inner +Join condition: None + +(32) Project [codegen id : 6] +Output [3]: [i_brand_id#14 AS brand_id#26, i_class_id#15 AS class_id#27, i_category_id#16 AS category_id#28] +Input [5]: [ss_sold_date_sk#11, i_brand_id#14, i_class_id#15, i_category_id#16, d_date_sk#25] + +(33) HashAggregate [codegen id : 6] +Input [3]: [brand_id#26, class_id#27, category_id#28] +Keys [3]: [brand_id#26, class_id#27, category_id#28] +Functions: [] +Aggregate Attributes: [] +Results [3]: [brand_id#26, class_id#27, category_id#28] + +(34) Exchange +Input [3]: [brand_id#26, class_id#27, category_id#28] +Arguments: hashpartitioning(brand_id#26, class_id#27, category_id#28, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(35) HashAggregate [codegen id : 10] +Input [3]: [brand_id#26, class_id#27, category_id#28] +Keys [3]: [brand_id#26, class_id#27, category_id#28] +Functions: [] +Aggregate Attributes: [] +Results [3]: [brand_id#26, class_id#27, category_id#28] + +(36) Scan parquet spark_catalog.default.web_sales +Output [2]: [ws_item_sk#29, ws_sold_date_sk#30] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#30), dynamicpruningexpression(ws_sold_date_sk#30 IN dynamicpruning#31)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(37) CometFilter +Input [2]: [ws_item_sk#29, ws_sold_date_sk#30] +Condition : isnotnull(ws_item_sk#29) + +(38) ColumnarToRow [codegen id : 9] +Input [2]: [ws_item_sk#29, ws_sold_date_sk#30] + +(39) ReusedExchange [Reuses operator id: 19] +Output [4]: [i_item_sk#32, i_brand_id#33, i_class_id#34, i_category_id#35] + +(40) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ws_item_sk#29] +Right keys [1]: [i_item_sk#32] +Join type: Inner +Join condition: None + +(41) Project [codegen id : 9] +Output [4]: [ws_sold_date_sk#30, i_brand_id#33, i_class_id#34, i_category_id#35] +Input [6]: [ws_item_sk#29, ws_sold_date_sk#30, i_item_sk#32, i_brand_id#33, i_class_id#34, i_category_id#35] + +(42) ReusedExchange [Reuses operator id: 159] +Output [1]: [d_date_sk#36] + +(43) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ws_sold_date_sk#30] +Right keys [1]: [d_date_sk#36] +Join type: Inner +Join condition: None + +(44) Project [codegen id : 9] +Output [3]: [i_brand_id#33, i_class_id#34, i_category_id#35] +Input [5]: [ws_sold_date_sk#30, i_brand_id#33, i_class_id#34, i_category_id#35, d_date_sk#36] + +(45) BroadcastExchange +Input [3]: [i_brand_id#33, i_class_id#34, i_category_id#35] +Arguments: HashedRelationBroadcastMode(List(coalesce(input[0, int, true], 0), isnull(input[0, int, true]), coalesce(input[1, int, true], 0), isnull(input[1, int, true]), coalesce(input[2, int, true], 0), isnull(input[2, int, true])),false), [plan_id=5] + +(46) BroadcastHashJoin [codegen id : 10] +Left keys [6]: [coalesce(brand_id#26, 0), isnull(brand_id#26), coalesce(class_id#27, 0), isnull(class_id#27), coalesce(category_id#28, 0), isnull(category_id#28)] +Right keys [6]: [coalesce(i_brand_id#33, 0), isnull(i_brand_id#33), coalesce(i_class_id#34, 0), isnull(i_class_id#34), coalesce(i_category_id#35, 0), isnull(i_category_id#35)] +Join type: LeftSemi +Join condition: None + +(47) BroadcastExchange +Input [3]: [brand_id#26, class_id#27, category_id#28] +Arguments: HashedRelationBroadcastMode(List(input[0, int, true], input[1, int, true], input[2, int, true]),false), [plan_id=6] + +(48) BroadcastHashJoin [codegen id : 11] +Left keys [3]: [i_brand_id#7, i_class_id#8, i_category_id#9] +Right keys [3]: [brand_id#26, class_id#27, category_id#28] +Join type: Inner +Join condition: None + +(49) Project [codegen id : 11] +Output [1]: [i_item_sk#6 AS ss_item_sk#37] +Input [7]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9, brand_id#26, class_id#27, category_id#28] + +(50) BroadcastExchange +Input [1]: [ss_item_sk#37] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +(51) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [ss_item_sk#37] +Join type: LeftSemi +Join condition: None + +(52) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(53) CometFilter +Input [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] +Condition : isnotnull(i_item_sk#38) + +(54) ColumnarToRow [codegen id : 23] +Input [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] + +(55) ReusedExchange [Reuses operator id: 50] +Output [1]: [ss_item_sk#37] + +(56) BroadcastHashJoin [codegen id : 23] +Left keys [1]: [i_item_sk#38] +Right keys [1]: [ss_item_sk#37] +Join type: LeftSemi +Join condition: None + +(57) BroadcastExchange +Input [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8] + +(58) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#38] +Join type: Inner +Join condition: None + +(59) Project [codegen id : 25] +Output [6]: [ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4, i_brand_id#39, i_class_id#40, i_category_id#41] +Input [8]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4, i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] + +(60) ReusedExchange [Reuses operator id: 154] +Output [1]: [d_date_sk#42] + +(61) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_sold_date_sk#4] +Right keys [1]: [d_date_sk#42] +Join type: Inner +Join condition: None + +(62) Project [codegen id : 25] +Output [5]: [ss_quantity#2, ss_list_price#3, i_brand_id#39, i_class_id#40, i_category_id#41] +Input [7]: [ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4, i_brand_id#39, i_class_id#40, i_category_id#41, d_date_sk#42] + +(63) HashAggregate [codegen id : 25] +Input [5]: [ss_quantity#2, ss_list_price#3, i_brand_id#39, i_class_id#40, i_category_id#41] +Keys [3]: [i_brand_id#39, i_class_id#40, i_category_id#41] +Functions [2]: [partial_sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3)), partial_count(1)] +Aggregate Attributes [3]: [sum#43, isEmpty#44, count#45] +Results [6]: [i_brand_id#39, i_class_id#40, i_category_id#41, sum#46, isEmpty#47, count#48] + +(64) Exchange +Input [6]: [i_brand_id#39, i_class_id#40, i_category_id#41, sum#46, isEmpty#47, count#48] +Arguments: hashpartitioning(i_brand_id#39, i_class_id#40, i_category_id#41, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(65) HashAggregate [codegen id : 26] +Input [6]: [i_brand_id#39, i_class_id#40, i_category_id#41, sum#46, isEmpty#47, count#48] +Keys [3]: [i_brand_id#39, i_class_id#40, i_category_id#41] +Functions [2]: [sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3)), count(1)] +Aggregate Attributes [2]: [sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3))#49, count(1)#50] +Results [6]: [store AS channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3))#49 AS sales#52, count(1)#50 AS number_sales#53] + +(66) Filter [codegen id : 26] +Input [6]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sales#52, number_sales#53] +Condition : (isnotnull(sales#52) AND (cast(sales#52 as decimal(32,6)) > cast(Subquery scalar-subquery#54, [id=#55] as decimal(32,6)))) + +(67) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_item_sk#56, cs_quantity#57, cs_list_price#58, cs_sold_date_sk#59] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#59), dynamicpruningexpression(cs_sold_date_sk#59 IN dynamicpruning#60)] +PushedFilters: [IsNotNull(cs_item_sk)] +ReadSchema: struct + +(68) CometFilter +Input [4]: [cs_item_sk#56, cs_quantity#57, cs_list_price#58, cs_sold_date_sk#59] +Condition : isnotnull(cs_item_sk#56) + +(69) ColumnarToRow [codegen id : 51] +Input [4]: [cs_item_sk#56, cs_quantity#57, cs_list_price#58, cs_sold_date_sk#59] + +(70) ReusedExchange [Reuses operator id: 50] +Output [1]: [ss_item_sk#61] + +(71) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [cs_item_sk#56] +Right keys [1]: [ss_item_sk#61] +Join type: LeftSemi +Join condition: None + +(72) ReusedExchange [Reuses operator id: 57] +Output [4]: [i_item_sk#62, i_brand_id#63, i_class_id#64, i_category_id#65] + +(73) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [cs_item_sk#56] +Right keys [1]: [i_item_sk#62] +Join type: Inner +Join condition: None + +(74) Project [codegen id : 51] +Output [6]: [cs_quantity#57, cs_list_price#58, cs_sold_date_sk#59, i_brand_id#63, i_class_id#64, i_category_id#65] +Input [8]: [cs_item_sk#56, cs_quantity#57, cs_list_price#58, cs_sold_date_sk#59, i_item_sk#62, i_brand_id#63, i_class_id#64, i_category_id#65] + +(75) ReusedExchange [Reuses operator id: 154] +Output [1]: [d_date_sk#66] + +(76) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [cs_sold_date_sk#59] +Right keys [1]: [d_date_sk#66] +Join type: Inner +Join condition: None + +(77) Project [codegen id : 51] +Output [5]: [cs_quantity#57, cs_list_price#58, i_brand_id#63, i_class_id#64, i_category_id#65] +Input [7]: [cs_quantity#57, cs_list_price#58, cs_sold_date_sk#59, i_brand_id#63, i_class_id#64, i_category_id#65, d_date_sk#66] + +(78) HashAggregate [codegen id : 51] +Input [5]: [cs_quantity#57, cs_list_price#58, i_brand_id#63, i_class_id#64, i_category_id#65] +Keys [3]: [i_brand_id#63, i_class_id#64, i_category_id#65] +Functions [2]: [partial_sum((cast(cs_quantity#57 as decimal(10,0)) * cs_list_price#58)), partial_count(1)] +Aggregate Attributes [3]: [sum#67, isEmpty#68, count#69] +Results [6]: [i_brand_id#63, i_class_id#64, i_category_id#65, sum#70, isEmpty#71, count#72] + +(79) Exchange +Input [6]: [i_brand_id#63, i_class_id#64, i_category_id#65, sum#70, isEmpty#71, count#72] +Arguments: hashpartitioning(i_brand_id#63, i_class_id#64, i_category_id#65, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(80) HashAggregate [codegen id : 52] +Input [6]: [i_brand_id#63, i_class_id#64, i_category_id#65, sum#70, isEmpty#71, count#72] +Keys [3]: [i_brand_id#63, i_class_id#64, i_category_id#65] +Functions [2]: [sum((cast(cs_quantity#57 as decimal(10,0)) * cs_list_price#58)), count(1)] +Aggregate Attributes [2]: [sum((cast(cs_quantity#57 as decimal(10,0)) * cs_list_price#58))#73, count(1)#74] +Results [6]: [catalog AS channel#75, i_brand_id#63, i_class_id#64, i_category_id#65, sum((cast(cs_quantity#57 as decimal(10,0)) * cs_list_price#58))#73 AS sales#76, count(1)#74 AS number_sales#77] + +(81) Filter [codegen id : 52] +Input [6]: [channel#75, i_brand_id#63, i_class_id#64, i_category_id#65, sales#76, number_sales#77] +Condition : (isnotnull(sales#76) AND (cast(sales#76 as decimal(32,6)) > cast(ReusedSubquery Subquery scalar-subquery#54, [id=#55] as decimal(32,6)))) + +(82) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_item_sk#78, ws_quantity#79, ws_list_price#80, ws_sold_date_sk#81] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#81), dynamicpruningexpression(ws_sold_date_sk#81 IN dynamicpruning#82)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(83) CometFilter +Input [4]: [ws_item_sk#78, ws_quantity#79, ws_list_price#80, ws_sold_date_sk#81] +Condition : isnotnull(ws_item_sk#78) + +(84) ColumnarToRow [codegen id : 77] +Input [4]: [ws_item_sk#78, ws_quantity#79, ws_list_price#80, ws_sold_date_sk#81] + +(85) ReusedExchange [Reuses operator id: 50] +Output [1]: [ss_item_sk#83] + +(86) BroadcastHashJoin [codegen id : 77] +Left keys [1]: [ws_item_sk#78] +Right keys [1]: [ss_item_sk#83] +Join type: LeftSemi +Join condition: None + +(87) ReusedExchange [Reuses operator id: 57] +Output [4]: [i_item_sk#84, i_brand_id#85, i_class_id#86, i_category_id#87] + +(88) BroadcastHashJoin [codegen id : 77] +Left keys [1]: [ws_item_sk#78] +Right keys [1]: [i_item_sk#84] +Join type: Inner +Join condition: None + +(89) Project [codegen id : 77] +Output [6]: [ws_quantity#79, ws_list_price#80, ws_sold_date_sk#81, i_brand_id#85, i_class_id#86, i_category_id#87] +Input [8]: [ws_item_sk#78, ws_quantity#79, ws_list_price#80, ws_sold_date_sk#81, i_item_sk#84, i_brand_id#85, i_class_id#86, i_category_id#87] + +(90) ReusedExchange [Reuses operator id: 154] +Output [1]: [d_date_sk#88] + +(91) BroadcastHashJoin [codegen id : 77] +Left keys [1]: [ws_sold_date_sk#81] +Right keys [1]: [d_date_sk#88] +Join type: Inner +Join condition: None + +(92) Project [codegen id : 77] +Output [5]: [ws_quantity#79, ws_list_price#80, i_brand_id#85, i_class_id#86, i_category_id#87] +Input [7]: [ws_quantity#79, ws_list_price#80, ws_sold_date_sk#81, i_brand_id#85, i_class_id#86, i_category_id#87, d_date_sk#88] + +(93) HashAggregate [codegen id : 77] +Input [5]: [ws_quantity#79, ws_list_price#80, i_brand_id#85, i_class_id#86, i_category_id#87] +Keys [3]: [i_brand_id#85, i_class_id#86, i_category_id#87] +Functions [2]: [partial_sum((cast(ws_quantity#79 as decimal(10,0)) * ws_list_price#80)), partial_count(1)] +Aggregate Attributes [3]: [sum#89, isEmpty#90, count#91] +Results [6]: [i_brand_id#85, i_class_id#86, i_category_id#87, sum#92, isEmpty#93, count#94] + +(94) Exchange +Input [6]: [i_brand_id#85, i_class_id#86, i_category_id#87, sum#92, isEmpty#93, count#94] +Arguments: hashpartitioning(i_brand_id#85, i_class_id#86, i_category_id#87, 5), ENSURE_REQUIREMENTS, [plan_id=11] + +(95) HashAggregate [codegen id : 78] +Input [6]: [i_brand_id#85, i_class_id#86, i_category_id#87, sum#92, isEmpty#93, count#94] +Keys [3]: [i_brand_id#85, i_class_id#86, i_category_id#87] +Functions [2]: [sum((cast(ws_quantity#79 as decimal(10,0)) * ws_list_price#80)), count(1)] +Aggregate Attributes [2]: [sum((cast(ws_quantity#79 as decimal(10,0)) * ws_list_price#80))#95, count(1)#96] +Results [6]: [web AS channel#97, i_brand_id#85, i_class_id#86, i_category_id#87, sum((cast(ws_quantity#79 as decimal(10,0)) * ws_list_price#80))#95 AS sales#98, count(1)#96 AS number_sales#99] + +(96) Filter [codegen id : 78] +Input [6]: [channel#97, i_brand_id#85, i_class_id#86, i_category_id#87, sales#98, number_sales#99] +Condition : (isnotnull(sales#98) AND (cast(sales#98 as decimal(32,6)) > cast(ReusedSubquery Subquery scalar-subquery#54, [id=#55] as decimal(32,6)))) + +(97) Union + +(98) HashAggregate [codegen id : 79] +Input [6]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sales#52, number_sales#53] +Keys [4]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41] +Functions [2]: [partial_sum(sales#52), partial_sum(number_sales#53)] +Aggregate Attributes [3]: [sum#100, isEmpty#101, sum#102] +Results [7]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sum#103, isEmpty#104, sum#105] + +(99) Exchange +Input [7]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sum#103, isEmpty#104, sum#105] +Arguments: hashpartitioning(channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, 5), ENSURE_REQUIREMENTS, [plan_id=12] + +(100) HashAggregate [codegen id : 80] +Input [7]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sum#103, isEmpty#104, sum#105] +Keys [4]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41] +Functions [2]: [sum(sales#52), sum(number_sales#53)] +Aggregate Attributes [2]: [sum(sales#52)#106, sum(number_sales#53)#107] +Results [6]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sum(sales#52)#106 AS sum_sales#108, sum(number_sales#53)#107 AS number_sales#109] + +(101) ReusedExchange [Reuses operator id: 99] +Output [7]: [channel#110, i_brand_id#111, i_class_id#112, i_category_id#113, sum#114, isEmpty#115, sum#116] + +(102) HashAggregate [codegen id : 160] +Input [7]: [channel#110, i_brand_id#111, i_class_id#112, i_category_id#113, sum#114, isEmpty#115, sum#116] +Keys [4]: [channel#110, i_brand_id#111, i_class_id#112, i_category_id#113] +Functions [2]: [sum(sales#117), sum(number_sales#118)] +Aggregate Attributes [2]: [sum(sales#117)#106, sum(number_sales#118)#107] +Results [5]: [channel#110, i_brand_id#111, i_class_id#112, sum(sales#117)#106 AS sum_sales#119, sum(number_sales#118)#107 AS number_sales#120] + +(103) HashAggregate [codegen id : 160] +Input [5]: [channel#110, i_brand_id#111, i_class_id#112, sum_sales#119, number_sales#120] +Keys [3]: [channel#110, i_brand_id#111, i_class_id#112] +Functions [2]: [partial_sum(sum_sales#119), partial_sum(number_sales#120)] +Aggregate Attributes [3]: [sum#121, isEmpty#122, sum#123] +Results [6]: [channel#110, i_brand_id#111, i_class_id#112, sum#124, isEmpty#125, sum#126] + +(104) Exchange +Input [6]: [channel#110, i_brand_id#111, i_class_id#112, sum#124, isEmpty#125, sum#126] +Arguments: hashpartitioning(channel#110, i_brand_id#111, i_class_id#112, 5), ENSURE_REQUIREMENTS, [plan_id=13] + +(105) HashAggregate [codegen id : 161] +Input [6]: [channel#110, i_brand_id#111, i_class_id#112, sum#124, isEmpty#125, sum#126] +Keys [3]: [channel#110, i_brand_id#111, i_class_id#112] +Functions [2]: [sum(sum_sales#119), sum(number_sales#120)] +Aggregate Attributes [2]: [sum(sum_sales#119)#127, sum(number_sales#120)#128] +Results [6]: [channel#110, i_brand_id#111, i_class_id#112, null AS i_category_id#129, sum(sum_sales#119)#127 AS sum(sum_sales)#130, sum(number_sales#120)#128 AS sum(number_sales)#131] + +(106) ReusedExchange [Reuses operator id: 99] +Output [7]: [channel#132, i_brand_id#133, i_class_id#134, i_category_id#135, sum#136, isEmpty#137, sum#138] + +(107) HashAggregate [codegen id : 241] +Input [7]: [channel#132, i_brand_id#133, i_class_id#134, i_category_id#135, sum#136, isEmpty#137, sum#138] +Keys [4]: [channel#132, i_brand_id#133, i_class_id#134, i_category_id#135] +Functions [2]: [sum(sales#139), sum(number_sales#140)] +Aggregate Attributes [2]: [sum(sales#139)#106, sum(number_sales#140)#107] +Results [4]: [channel#132, i_brand_id#133, sum(sales#139)#106 AS sum_sales#141, sum(number_sales#140)#107 AS number_sales#142] + +(108) HashAggregate [codegen id : 241] +Input [4]: [channel#132, i_brand_id#133, sum_sales#141, number_sales#142] +Keys [2]: [channel#132, i_brand_id#133] +Functions [2]: [partial_sum(sum_sales#141), partial_sum(number_sales#142)] +Aggregate Attributes [3]: [sum#143, isEmpty#144, sum#145] +Results [5]: [channel#132, i_brand_id#133, sum#146, isEmpty#147, sum#148] + +(109) Exchange +Input [5]: [channel#132, i_brand_id#133, sum#146, isEmpty#147, sum#148] +Arguments: hashpartitioning(channel#132, i_brand_id#133, 5), ENSURE_REQUIREMENTS, [plan_id=14] + +(110) HashAggregate [codegen id : 242] +Input [5]: [channel#132, i_brand_id#133, sum#146, isEmpty#147, sum#148] +Keys [2]: [channel#132, i_brand_id#133] +Functions [2]: [sum(sum_sales#141), sum(number_sales#142)] +Aggregate Attributes [2]: [sum(sum_sales#141)#149, sum(number_sales#142)#150] +Results [6]: [channel#132, i_brand_id#133, null AS i_class_id#151, null AS i_category_id#152, sum(sum_sales#141)#149 AS sum(sum_sales)#153, sum(number_sales#142)#150 AS sum(number_sales)#154] + +(111) ReusedExchange [Reuses operator id: 99] +Output [7]: [channel#155, i_brand_id#156, i_class_id#157, i_category_id#158, sum#159, isEmpty#160, sum#161] + +(112) HashAggregate [codegen id : 322] +Input [7]: [channel#155, i_brand_id#156, i_class_id#157, i_category_id#158, sum#159, isEmpty#160, sum#161] +Keys [4]: [channel#155, i_brand_id#156, i_class_id#157, i_category_id#158] +Functions [2]: [sum(sales#162), sum(number_sales#163)] +Aggregate Attributes [2]: [sum(sales#162)#106, sum(number_sales#163)#107] +Results [3]: [channel#155, sum(sales#162)#106 AS sum_sales#164, sum(number_sales#163)#107 AS number_sales#165] + +(113) HashAggregate [codegen id : 322] +Input [3]: [channel#155, sum_sales#164, number_sales#165] +Keys [1]: [channel#155] +Functions [2]: [partial_sum(sum_sales#164), partial_sum(number_sales#165)] +Aggregate Attributes [3]: [sum#166, isEmpty#167, sum#168] +Results [4]: [channel#155, sum#169, isEmpty#170, sum#171] + +(114) Exchange +Input [4]: [channel#155, sum#169, isEmpty#170, sum#171] +Arguments: hashpartitioning(channel#155, 5), ENSURE_REQUIREMENTS, [plan_id=15] + +(115) HashAggregate [codegen id : 323] +Input [4]: [channel#155, sum#169, isEmpty#170, sum#171] +Keys [1]: [channel#155] +Functions [2]: [sum(sum_sales#164), sum(number_sales#165)] +Aggregate Attributes [2]: [sum(sum_sales#164)#172, sum(number_sales#165)#173] +Results [6]: [channel#155, null AS i_brand_id#174, null AS i_class_id#175, null AS i_category_id#176, sum(sum_sales#164)#172 AS sum(sum_sales)#177, sum(number_sales#165)#173 AS sum(number_sales)#178] + +(116) ReusedExchange [Reuses operator id: 99] +Output [7]: [channel#179, i_brand_id#180, i_class_id#181, i_category_id#182, sum#183, isEmpty#184, sum#185] + +(117) HashAggregate [codegen id : 403] +Input [7]: [channel#179, i_brand_id#180, i_class_id#181, i_category_id#182, sum#183, isEmpty#184, sum#185] +Keys [4]: [channel#179, i_brand_id#180, i_class_id#181, i_category_id#182] +Functions [2]: [sum(sales#186), sum(number_sales#187)] +Aggregate Attributes [2]: [sum(sales#186)#106, sum(number_sales#187)#107] +Results [2]: [sum(sales#186)#106 AS sum_sales#188, sum(number_sales#187)#107 AS number_sales#189] + +(118) HashAggregate [codegen id : 403] +Input [2]: [sum_sales#188, number_sales#189] +Keys: [] +Functions [2]: [partial_sum(sum_sales#188), partial_sum(number_sales#189)] +Aggregate Attributes [3]: [sum#190, isEmpty#191, sum#192] +Results [3]: [sum#193, isEmpty#194, sum#195] + +(119) Exchange +Input [3]: [sum#193, isEmpty#194, sum#195] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=16] + +(120) HashAggregate [codegen id : 404] +Input [3]: [sum#193, isEmpty#194, sum#195] +Keys: [] +Functions [2]: [sum(sum_sales#188), sum(number_sales#189)] +Aggregate Attributes [2]: [sum(sum_sales#188)#196, sum(number_sales#189)#197] +Results [6]: [null AS channel#198, null AS i_brand_id#199, null AS i_class_id#200, null AS i_category_id#201, sum(sum_sales#188)#196 AS sum(sum_sales)#202, sum(number_sales#189)#197 AS sum(number_sales)#203] + +(121) Union + +(122) HashAggregate [codegen id : 405] +Input [6]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sum_sales#108, number_sales#109] +Keys [6]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sum_sales#108, number_sales#109] +Functions: [] +Aggregate Attributes: [] +Results [6]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sum_sales#108, number_sales#109] + +(123) Exchange +Input [6]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sum_sales#108, number_sales#109] +Arguments: hashpartitioning(channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sum_sales#108, number_sales#109, 5), ENSURE_REQUIREMENTS, [plan_id=17] + +(124) HashAggregate [codegen id : 406] +Input [6]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sum_sales#108, number_sales#109] +Keys [6]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sum_sales#108, number_sales#109] +Functions: [] +Aggregate Attributes: [] +Results [6]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sum_sales#108, number_sales#109] + +(125) TakeOrderedAndProject +Input [6]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sum_sales#108, number_sales#109] +Arguments: 100, [channel#51 ASC NULLS FIRST, i_brand_id#39 ASC NULLS FIRST, i_class_id#40 ASC NULLS FIRST, i_category_id#41 ASC NULLS FIRST], [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sum_sales#108, number_sales#109] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 66 Hosting Expression = Subquery scalar-subquery#54, [id=#55] +* HashAggregate (144) ++- Exchange (143) + +- * HashAggregate (142) + +- Union (141) + :- * Project (130) + : +- * BroadcastHashJoin Inner BuildRight (129) + : :- * ColumnarToRow (127) + : : +- CometScan parquet spark_catalog.default.store_sales (126) + : +- ReusedExchange (128) + :- * Project (135) + : +- * BroadcastHashJoin Inner BuildRight (134) + : :- * ColumnarToRow (132) + : : +- CometScan parquet spark_catalog.default.catalog_sales (131) + : +- ReusedExchange (133) + +- * Project (140) + +- * BroadcastHashJoin Inner BuildRight (139) + :- * ColumnarToRow (137) + : +- CometScan parquet spark_catalog.default.web_sales (136) + +- ReusedExchange (138) + + +(126) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_quantity#204, ss_list_price#205, ss_sold_date_sk#206] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#206), dynamicpruningexpression(ss_sold_date_sk#206 IN dynamicpruning#207)] +ReadSchema: struct + +(127) ColumnarToRow [codegen id : 2] +Input [3]: [ss_quantity#204, ss_list_price#205, ss_sold_date_sk#206] + +(128) ReusedExchange [Reuses operator id: 159] +Output [1]: [d_date_sk#208] + +(129) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [ss_sold_date_sk#206] +Right keys [1]: [d_date_sk#208] +Join type: Inner +Join condition: None + +(130) Project [codegen id : 2] +Output [2]: [ss_quantity#204 AS quantity#209, ss_list_price#205 AS list_price#210] +Input [4]: [ss_quantity#204, ss_list_price#205, ss_sold_date_sk#206, d_date_sk#208] + +(131) Scan parquet spark_catalog.default.catalog_sales +Output [3]: [cs_quantity#211, cs_list_price#212, cs_sold_date_sk#213] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#213), dynamicpruningexpression(cs_sold_date_sk#213 IN dynamicpruning#214)] +ReadSchema: struct + +(132) ColumnarToRow [codegen id : 4] +Input [3]: [cs_quantity#211, cs_list_price#212, cs_sold_date_sk#213] + +(133) ReusedExchange [Reuses operator id: 149] +Output [1]: [d_date_sk#215] + +(134) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [cs_sold_date_sk#213] +Right keys [1]: [d_date_sk#215] +Join type: Inner +Join condition: None + +(135) Project [codegen id : 4] +Output [2]: [cs_quantity#211 AS quantity#216, cs_list_price#212 AS list_price#217] +Input [4]: [cs_quantity#211, cs_list_price#212, cs_sold_date_sk#213, d_date_sk#215] + +(136) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_quantity#218, ws_list_price#219, ws_sold_date_sk#220] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#220), dynamicpruningexpression(ws_sold_date_sk#220 IN dynamicpruning#221)] +ReadSchema: struct + +(137) ColumnarToRow [codegen id : 6] +Input [3]: [ws_quantity#218, ws_list_price#219, ws_sold_date_sk#220] + +(138) ReusedExchange [Reuses operator id: 149] +Output [1]: [d_date_sk#222] + +(139) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ws_sold_date_sk#220] +Right keys [1]: [d_date_sk#222] +Join type: Inner +Join condition: None + +(140) Project [codegen id : 6] +Output [2]: [ws_quantity#218 AS quantity#223, ws_list_price#219 AS list_price#224] +Input [4]: [ws_quantity#218, ws_list_price#219, ws_sold_date_sk#220, d_date_sk#222] + +(141) Union + +(142) HashAggregate [codegen id : 7] +Input [2]: [quantity#209, list_price#210] +Keys: [] +Functions [1]: [partial_avg((cast(quantity#209 as decimal(10,0)) * list_price#210))] +Aggregate Attributes [2]: [sum#225, count#226] +Results [2]: [sum#227, count#228] + +(143) Exchange +Input [2]: [sum#227, count#228] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=18] + +(144) HashAggregate [codegen id : 8] +Input [2]: [sum#227, count#228] +Keys: [] +Functions [1]: [avg((cast(quantity#209 as decimal(10,0)) * list_price#210))] +Aggregate Attributes [1]: [avg((cast(quantity#209 as decimal(10,0)) * list_price#210))#229] +Results [1]: [avg((cast(quantity#209 as decimal(10,0)) * list_price#210))#229 AS average_sales#230] + +Subquery:2 Hosting operator id = 126 Hosting Expression = ss_sold_date_sk#206 IN dynamicpruning#12 + +Subquery:3 Hosting operator id = 131 Hosting Expression = cs_sold_date_sk#213 IN dynamicpruning#214 +BroadcastExchange (149) ++- * ColumnarToRow (148) + +- CometProject (147) + +- CometFilter (146) + +- CometScan parquet spark_catalog.default.date_dim (145) + + +(145) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#215, d_year#231] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), GreaterThanOrEqual(d_year,1998), LessThanOrEqual(d_year,2000), IsNotNull(d_date_sk)] +ReadSchema: struct + +(146) CometFilter +Input [2]: [d_date_sk#215, d_year#231] +Condition : (((isnotnull(d_year#231) AND (d_year#231 >= 1998)) AND (d_year#231 <= 2000)) AND isnotnull(d_date_sk#215)) + +(147) CometProject +Input [2]: [d_date_sk#215, d_year#231] +Arguments: [d_date_sk#215], [d_date_sk#215] + +(148) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#215] + +(149) BroadcastExchange +Input [1]: [d_date_sk#215] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=19] + +Subquery:4 Hosting operator id = 136 Hosting Expression = ws_sold_date_sk#220 IN dynamicpruning#214 + +Subquery:5 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (154) ++- * ColumnarToRow (153) + +- CometProject (152) + +- CometFilter (151) + +- CometScan parquet spark_catalog.default.date_dim (150) + + +(150) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#42, d_year#232, d_moy#233] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2000), EqualTo(d_moy,11), IsNotNull(d_date_sk)] +ReadSchema: struct + +(151) CometFilter +Input [3]: [d_date_sk#42, d_year#232, d_moy#233] +Condition : ((((isnotnull(d_year#232) AND isnotnull(d_moy#233)) AND (d_year#232 = 2000)) AND (d_moy#233 = 11)) AND isnotnull(d_date_sk#42)) + +(152) CometProject +Input [3]: [d_date_sk#42, d_year#232, d_moy#233] +Arguments: [d_date_sk#42], [d_date_sk#42] + +(153) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#42] + +(154) BroadcastExchange +Input [1]: [d_date_sk#42] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=20] + +Subquery:6 Hosting operator id = 7 Hosting Expression = ss_sold_date_sk#11 IN dynamicpruning#12 +BroadcastExchange (159) ++- * ColumnarToRow (158) + +- CometProject (157) + +- CometFilter (156) + +- CometScan parquet spark_catalog.default.date_dim (155) + + +(155) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#25, d_year#234] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), GreaterThanOrEqual(d_year,1999), LessThanOrEqual(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(156) CometFilter +Input [2]: [d_date_sk#25, d_year#234] +Condition : (((isnotnull(d_year#234) AND (d_year#234 >= 1999)) AND (d_year#234 <= 2001)) AND isnotnull(d_date_sk#25)) + +(157) CometProject +Input [2]: [d_date_sk#25, d_year#234] +Arguments: [d_date_sk#25], [d_date_sk#25] + +(158) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#25] + +(159) BroadcastExchange +Input [1]: [d_date_sk#25] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=21] + +Subquery:7 Hosting operator id = 13 Hosting Expression = cs_sold_date_sk#18 IN dynamicpruning#12 + +Subquery:8 Hosting operator id = 36 Hosting Expression = ws_sold_date_sk#30 IN dynamicpruning#12 + +Subquery:9 Hosting operator id = 81 Hosting Expression = ReusedSubquery Subquery scalar-subquery#54, [id=#55] + +Subquery:10 Hosting operator id = 67 Hosting Expression = cs_sold_date_sk#59 IN dynamicpruning#5 + +Subquery:11 Hosting operator id = 96 Hosting Expression = ReusedSubquery Subquery scalar-subquery#54, [id=#55] + +Subquery:12 Hosting operator id = 82 Hosting Expression = ws_sold_date_sk#81 IN dynamicpruning#5 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14a/simplified.txt new file mode 100644 index 0000000000..a203f9620b --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14a/simplified.txt @@ -0,0 +1,261 @@ +TakeOrderedAndProject [channel,i_brand_id,i_class_id,i_category_id,sum_sales,number_sales] + WholeStageCodegen (406) + HashAggregate [channel,i_brand_id,i_class_id,i_category_id,sum_sales,number_sales] + InputAdapter + Exchange [channel,i_brand_id,i_class_id,i_category_id,sum_sales,number_sales] #1 + WholeStageCodegen (405) + HashAggregate [channel,i_brand_id,i_class_id,i_category_id,sum_sales,number_sales] + InputAdapter + Union + WholeStageCodegen (80) + HashAggregate [channel,i_brand_id,i_class_id,i_category_id,sum,isEmpty,sum] [sum(sales),sum(number_salesL),sum_sales,number_sales,sum,isEmpty,sum] + InputAdapter + Exchange [channel,i_brand_id,i_class_id,i_category_id] #2 + WholeStageCodegen (79) + HashAggregate [channel,i_brand_id,i_class_id,i_category_id,sales,number_sales] [sum,isEmpty,sum,sum,isEmpty,sum] + InputAdapter + Union + WholeStageCodegen (26) + Filter [sales] + Subquery #3 + WholeStageCodegen (8) + HashAggregate [sum,count] [avg((cast(quantity as decimal(10,0)) * list_price)),average_sales,sum,count] + InputAdapter + Exchange #14 + WholeStageCodegen (7) + HashAggregate [quantity,list_price] [sum,count,sum,count] + InputAdapter + Union + WholeStageCodegen (2) + Project [ss_quantity,ss_list_price] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_list_price,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk] #8 + WholeStageCodegen (4) + Project [cs_quantity,cs_list_price] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_quantity,cs_list_price,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #4 + BroadcastExchange #15 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk] #15 + WholeStageCodegen (6) + Project [ws_quantity,ws_list_price] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_quantity,ws_list_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #4 + InputAdapter + ReusedExchange [d_date_sk] #15 + HashAggregate [i_brand_id,i_class_id,i_category_id,sum,isEmpty,count] [sum((cast(ss_quantity as decimal(10,0)) * ss_list_price)),count(1),channel,sales,number_sales,sum,isEmpty,count] + InputAdapter + Exchange [i_brand_id,i_class_id,i_category_id] #3 + WholeStageCodegen (25) + HashAggregate [i_brand_id,i_class_id,i_category_id,ss_quantity,ss_list_price] [sum,isEmpty,count,sum,isEmpty,count] + Project [ss_quantity,ss_list_price,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_quantity,ss_list_price,ss_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + BroadcastHashJoin [ss_item_sk,ss_item_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_quantity,ss_list_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_moy,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (11) + Project [i_item_sk] + BroadcastHashJoin [i_brand_id,i_class_id,i_category_id,brand_id,class_id,category_id] + ColumnarToRow + InputAdapter + CometFilter [i_brand_id,i_class_id,i_category_id] + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (10) + BroadcastHashJoin [brand_id,class_id,category_id,i_brand_id,i_class_id,i_category_id] + HashAggregate [brand_id,class_id,category_id] + InputAdapter + Exchange [brand_id,class_id,category_id] #7 + WholeStageCodegen (6) + HashAggregate [brand_id,class_id,category_id] + Project [i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #8 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + BroadcastExchange #9 + WholeStageCodegen (4) + BroadcastHashJoin [i_brand_id,i_class_id,i_category_id,i_brand_id,i_class_id,i_category_id] + ColumnarToRow + InputAdapter + CometFilter [i_item_sk,i_brand_id,i_class_id,i_category_id] + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] + InputAdapter + BroadcastExchange #10 + WholeStageCodegen (3) + Project [i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] + InputAdapter + ReusedExchange [d_date_sk] #8 + InputAdapter + ReusedExchange [d_date_sk] #8 + InputAdapter + BroadcastExchange #12 + WholeStageCodegen (9) + Project [i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ws_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id] #11 + InputAdapter + ReusedExchange [d_date_sk] #8 + InputAdapter + BroadcastExchange #13 + WholeStageCodegen (23) + BroadcastHashJoin [i_item_sk,ss_item_sk] + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] + InputAdapter + ReusedExchange [ss_item_sk] #5 + InputAdapter + ReusedExchange [d_date_sk] #4 + WholeStageCodegen (52) + Filter [sales] + ReusedSubquery [average_sales] #3 + HashAggregate [i_brand_id,i_class_id,i_category_id,sum,isEmpty,count] [sum((cast(cs_quantity as decimal(10,0)) * cs_list_price)),count(1),channel,sales,number_sales,sum,isEmpty,count] + InputAdapter + Exchange [i_brand_id,i_class_id,i_category_id] #16 + WholeStageCodegen (51) + HashAggregate [i_brand_id,i_class_id,i_category_id,cs_quantity,cs_list_price] [sum,isEmpty,count,sum,isEmpty,count] + Project [cs_quantity,cs_list_price,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_quantity,cs_list_price,cs_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + BroadcastHashJoin [cs_item_sk,ss_item_sk] + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_quantity,cs_list_price,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [ss_item_sk] #5 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id] #13 + InputAdapter + ReusedExchange [d_date_sk] #4 + WholeStageCodegen (78) + Filter [sales] + ReusedSubquery [average_sales] #3 + HashAggregate [i_brand_id,i_class_id,i_category_id,sum,isEmpty,count] [sum((cast(ws_quantity as decimal(10,0)) * ws_list_price)),count(1),channel,sales,number_sales,sum,isEmpty,count] + InputAdapter + Exchange [i_brand_id,i_class_id,i_category_id] #17 + WholeStageCodegen (77) + HashAggregate [i_brand_id,i_class_id,i_category_id,ws_quantity,ws_list_price] [sum,isEmpty,count,sum,isEmpty,count] + Project [ws_quantity,ws_list_price,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_quantity,ws_list_price,ws_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ws_item_sk,i_item_sk] + BroadcastHashJoin [ws_item_sk,ss_item_sk] + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_quantity,ws_list_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [ss_item_sk] #5 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id] #13 + InputAdapter + ReusedExchange [d_date_sk] #4 + WholeStageCodegen (161) + HashAggregate [channel,i_brand_id,i_class_id,sum,isEmpty,sum] [sum(sum_sales),sum(number_salesL),i_category_id,sum(sum_sales),sum(number_sales),sum,isEmpty,sum] + InputAdapter + Exchange [channel,i_brand_id,i_class_id] #18 + WholeStageCodegen (160) + HashAggregate [channel,i_brand_id,i_class_id,sum_sales,number_sales] [sum,isEmpty,sum,sum,isEmpty,sum] + HashAggregate [channel,i_brand_id,i_class_id,i_category_id,sum,isEmpty,sum] [sum(sales),sum(number_salesL),sum_sales,number_sales,sum,isEmpty,sum] + InputAdapter + ReusedExchange [channel,i_brand_id,i_class_id,i_category_id,sum,isEmpty,sum] #2 + WholeStageCodegen (242) + HashAggregate [channel,i_brand_id,sum,isEmpty,sum] [sum(sum_sales),sum(number_salesL),i_class_id,i_category_id,sum(sum_sales),sum(number_sales),sum,isEmpty,sum] + InputAdapter + Exchange [channel,i_brand_id] #19 + WholeStageCodegen (241) + HashAggregate [channel,i_brand_id,sum_sales,number_sales] [sum,isEmpty,sum,sum,isEmpty,sum] + HashAggregate [channel,i_brand_id,i_class_id,i_category_id,sum,isEmpty,sum] [sum(sales),sum(number_salesL),sum_sales,number_sales,sum,isEmpty,sum] + InputAdapter + ReusedExchange [channel,i_brand_id,i_class_id,i_category_id,sum,isEmpty,sum] #2 + WholeStageCodegen (323) + HashAggregate [channel,sum,isEmpty,sum] [sum(sum_sales),sum(number_salesL),i_brand_id,i_class_id,i_category_id,sum(sum_sales),sum(number_sales),sum,isEmpty,sum] + InputAdapter + Exchange [channel] #20 + WholeStageCodegen (322) + HashAggregate [channel,sum_sales,number_sales] [sum,isEmpty,sum,sum,isEmpty,sum] + HashAggregate [channel,i_brand_id,i_class_id,i_category_id,sum,isEmpty,sum] [sum(sales),sum(number_salesL),sum_sales,number_sales,sum,isEmpty,sum] + InputAdapter + ReusedExchange [channel,i_brand_id,i_class_id,i_category_id,sum,isEmpty,sum] #2 + WholeStageCodegen (404) + HashAggregate [sum,isEmpty,sum] [sum(sum_sales),sum(number_salesL),channel,i_brand_id,i_class_id,i_category_id,sum(sum_sales),sum(number_sales),sum,isEmpty,sum] + InputAdapter + Exchange #21 + WholeStageCodegen (403) + HashAggregate [sum_sales,number_sales] [sum,isEmpty,sum,sum,isEmpty,sum] + HashAggregate [channel,i_brand_id,i_class_id,i_category_id,sum,isEmpty,sum] [sum(sales),sum(number_salesL),sum_sales,number_sales,sum,isEmpty,sum] + InputAdapter + ReusedExchange [channel,i_brand_id,i_class_id,i_category_id,sum,isEmpty,sum] #2 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q18a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q18a/explain.txt new file mode 100644 index 0000000000..8bcc0c6bac --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q18a/explain.txt @@ -0,0 +1,909 @@ +== Physical Plan == +TakeOrderedAndProject (153) ++- Union (152) + :- * HashAggregate (41) + : +- Exchange (40) + : +- * HashAggregate (39) + : +- * Project (38) + : +- * BroadcastHashJoin Inner BuildRight (37) + : :- * Project (32) + : : +- * BroadcastHashJoin Inner BuildRight (31) + : : :- * Project (29) + : : : +- * BroadcastHashJoin Inner BuildRight (28) + : : : :- * Project (23) + : : : : +- * BroadcastHashJoin Inner BuildRight (22) + : : : : :- * Project (17) + : : : : : +- * BroadcastHashJoin Inner BuildRight (16) + : : : : : :- * Project (10) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (9) + : : : : : : :- * ColumnarToRow (3) + : : : : : : : +- CometFilter (2) + : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) + : : : : : : +- BroadcastExchange (8) + : : : : : : +- * ColumnarToRow (7) + : : : : : : +- CometProject (6) + : : : : : : +- CometFilter (5) + : : : : : : +- CometScan parquet spark_catalog.default.customer_demographics (4) + : : : : : +- BroadcastExchange (15) + : : : : : +- * ColumnarToRow (14) + : : : : : +- CometProject (13) + : : : : : +- CometFilter (12) + : : : : : +- CometScan parquet spark_catalog.default.customer (11) + : : : : +- BroadcastExchange (21) + : : : : +- * ColumnarToRow (20) + : : : : +- CometFilter (19) + : : : : +- CometScan parquet spark_catalog.default.customer_demographics (18) + : : : +- BroadcastExchange (27) + : : : +- * ColumnarToRow (26) + : : : +- CometFilter (25) + : : : +- CometScan parquet spark_catalog.default.customer_address (24) + : : +- ReusedExchange (30) + : +- BroadcastExchange (36) + : +- * ColumnarToRow (35) + : +- CometFilter (34) + : +- CometScan parquet spark_catalog.default.item (33) + :- * HashAggregate (68) + : +- Exchange (67) + : +- * HashAggregate (66) + : +- * Project (65) + : +- * BroadcastHashJoin Inner BuildRight (64) + : :- * Project (62) + : : +- * BroadcastHashJoin Inner BuildRight (61) + : : :- * Project (59) + : : : +- * BroadcastHashJoin Inner BuildRight (58) + : : : :- * Project (53) + : : : : +- * BroadcastHashJoin Inner BuildRight (52) + : : : : :- * Project (50) + : : : : : +- * BroadcastHashJoin Inner BuildRight (49) + : : : : : :- * Project (47) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (46) + : : : : : : :- * ColumnarToRow (44) + : : : : : : : +- CometFilter (43) + : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (42) + : : : : : : +- ReusedExchange (45) + : : : : : +- ReusedExchange (48) + : : : : +- ReusedExchange (51) + : : : +- BroadcastExchange (57) + : : : +- * ColumnarToRow (56) + : : : +- CometFilter (55) + : : : +- CometScan parquet spark_catalog.default.customer_address (54) + : : +- ReusedExchange (60) + : +- ReusedExchange (63) + :- * HashAggregate (96) + : +- Exchange (95) + : +- * HashAggregate (94) + : +- * Project (93) + : +- * BroadcastHashJoin Inner BuildRight (92) + : :- * Project (90) + : : +- * BroadcastHashJoin Inner BuildRight (89) + : : :- * Project (87) + : : : +- * BroadcastHashJoin Inner BuildRight (86) + : : : :- * Project (80) + : : : : +- * BroadcastHashJoin Inner BuildRight (79) + : : : : :- * Project (77) + : : : : : +- * BroadcastHashJoin Inner BuildRight (76) + : : : : : :- * Project (74) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (73) + : : : : : : :- * ColumnarToRow (71) + : : : : : : : +- CometFilter (70) + : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (69) + : : : : : : +- ReusedExchange (72) + : : : : : +- ReusedExchange (75) + : : : : +- ReusedExchange (78) + : : : +- BroadcastExchange (85) + : : : +- * ColumnarToRow (84) + : : : +- CometProject (83) + : : : +- CometFilter (82) + : : : +- CometScan parquet spark_catalog.default.customer_address (81) + : : +- ReusedExchange (88) + : +- ReusedExchange (91) + :- * HashAggregate (124) + : +- Exchange (123) + : +- * HashAggregate (122) + : +- * Project (121) + : +- * BroadcastHashJoin Inner BuildRight (120) + : :- * Project (118) + : : +- * BroadcastHashJoin Inner BuildRight (117) + : : :- * Project (115) + : : : +- * BroadcastHashJoin Inner BuildRight (114) + : : : :- * Project (108) + : : : : +- * BroadcastHashJoin Inner BuildRight (107) + : : : : :- * Project (105) + : : : : : +- * BroadcastHashJoin Inner BuildRight (104) + : : : : : :- * Project (102) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (101) + : : : : : : :- * ColumnarToRow (99) + : : : : : : : +- CometFilter (98) + : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (97) + : : : : : : +- ReusedExchange (100) + : : : : : +- ReusedExchange (103) + : : : : +- ReusedExchange (106) + : : : +- BroadcastExchange (113) + : : : +- * ColumnarToRow (112) + : : : +- CometProject (111) + : : : +- CometFilter (110) + : : : +- CometScan parquet spark_catalog.default.customer_address (109) + : : +- ReusedExchange (116) + : +- ReusedExchange (119) + +- * HashAggregate (151) + +- Exchange (150) + +- * HashAggregate (149) + +- * Project (148) + +- * BroadcastHashJoin Inner BuildRight (147) + :- * Project (142) + : +- * BroadcastHashJoin Inner BuildRight (141) + : :- * Project (139) + : : +- * BroadcastHashJoin Inner BuildRight (138) + : : :- * Project (136) + : : : +- * BroadcastHashJoin Inner BuildRight (135) + : : : :- * Project (133) + : : : : +- * BroadcastHashJoin Inner BuildRight (132) + : : : : :- * Project (130) + : : : : : +- * BroadcastHashJoin Inner BuildRight (129) + : : : : : :- * ColumnarToRow (127) + : : : : : : +- CometFilter (126) + : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (125) + : : : : : +- ReusedExchange (128) + : : : : +- ReusedExchange (131) + : : : +- ReusedExchange (134) + : : +- ReusedExchange (137) + : +- ReusedExchange (140) + +- BroadcastExchange (146) + +- * ColumnarToRow (145) + +- CometFilter (144) + +- CometScan parquet spark_catalog.default.item (143) + + +(1) Scan parquet spark_catalog.default.catalog_sales +Output [9]: [cs_bill_customer_sk#1, cs_bill_cdemo_sk#2, cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#9), dynamicpruningexpression(cs_sold_date_sk#9 IN dynamicpruning#10)] +PushedFilters: [IsNotNull(cs_bill_cdemo_sk), IsNotNull(cs_bill_customer_sk), IsNotNull(cs_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [9]: [cs_bill_customer_sk#1, cs_bill_cdemo_sk#2, cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9] +Condition : ((isnotnull(cs_bill_cdemo_sk#2) AND isnotnull(cs_bill_customer_sk#1)) AND isnotnull(cs_item_sk#3)) + +(3) ColumnarToRow [codegen id : 7] +Input [9]: [cs_bill_customer_sk#1, cs_bill_cdemo_sk#2, cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9] + +(4) Scan parquet spark_catalog.default.customer_demographics +Output [4]: [cd_demo_sk#11, cd_gender#12, cd_education_status#13, cd_dep_count#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_gender), IsNotNull(cd_education_status), EqualTo(cd_gender,M), EqualTo(cd_education_status,College ), IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(5) CometFilter +Input [4]: [cd_demo_sk#11, cd_gender#12, cd_education_status#13, cd_dep_count#14] +Condition : ((((isnotnull(cd_gender#12) AND isnotnull(cd_education_status#13)) AND (cd_gender#12 = M)) AND (cd_education_status#13 = College )) AND isnotnull(cd_demo_sk#11)) + +(6) CometProject +Input [4]: [cd_demo_sk#11, cd_gender#12, cd_education_status#13, cd_dep_count#14] +Arguments: [cd_demo_sk#11, cd_dep_count#14], [cd_demo_sk#11, cd_dep_count#14] + +(7) ColumnarToRow [codegen id : 1] +Input [2]: [cd_demo_sk#11, cd_dep_count#14] + +(8) BroadcastExchange +Input [2]: [cd_demo_sk#11, cd_dep_count#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [cs_bill_cdemo_sk#2] +Right keys [1]: [cd_demo_sk#11] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 7] +Output [9]: [cs_bill_customer_sk#1, cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14] +Input [11]: [cs_bill_customer_sk#1, cs_bill_cdemo_sk#2, cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_demo_sk#11, cd_dep_count#14] + +(11) Scan parquet spark_catalog.default.customer +Output [5]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_month#18, c_birth_year#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [In(c_birth_month, [1,10,12,4,5,9]), IsNotNull(c_customer_sk), IsNotNull(c_current_cdemo_sk), IsNotNull(c_current_addr_sk)] +ReadSchema: struct + +(12) CometFilter +Input [5]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_month#18, c_birth_year#19] +Condition : (((c_birth_month#18 IN (9,5,12,4,1,10) AND isnotnull(c_customer_sk#15)) AND isnotnull(c_current_cdemo_sk#16)) AND isnotnull(c_current_addr_sk#17)) + +(13) CometProject +Input [5]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_month#18, c_birth_year#19] +Arguments: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19], [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19] + +(14) ColumnarToRow [codegen id : 2] +Input [4]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19] + +(15) BroadcastExchange +Input [4]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(16) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [cs_bill_customer_sk#1] +Right keys [1]: [c_customer_sk#15] +Join type: Inner +Join condition: None + +(17) Project [codegen id : 7] +Output [11]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19] +Input [13]: [cs_bill_customer_sk#1, cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14, c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19] + +(18) Scan parquet spark_catalog.default.customer_demographics +Output [1]: [cd_demo_sk#20] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(19) CometFilter +Input [1]: [cd_demo_sk#20] +Condition : isnotnull(cd_demo_sk#20) + +(20) ColumnarToRow [codegen id : 3] +Input [1]: [cd_demo_sk#20] + +(21) BroadcastExchange +Input [1]: [cd_demo_sk#20] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(22) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [c_current_cdemo_sk#16] +Right keys [1]: [cd_demo_sk#20] +Join type: Inner +Join condition: None + +(23) Project [codegen id : 7] +Output [10]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14, c_current_addr_sk#17, c_birth_year#19] +Input [12]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19, cd_demo_sk#20] + +(24) Scan parquet spark_catalog.default.customer_address +Output [4]: [ca_address_sk#21, ca_county#22, ca_state#23, ca_country#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [In(ca_state, [AL,MS,NC,ND,OK,TN,WI]), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(25) CometFilter +Input [4]: [ca_address_sk#21, ca_county#22, ca_state#23, ca_country#24] +Condition : (ca_state#23 IN (ND,WI,AL,NC,OK,MS,TN) AND isnotnull(ca_address_sk#21)) + +(26) ColumnarToRow [codegen id : 4] +Input [4]: [ca_address_sk#21, ca_county#22, ca_state#23, ca_country#24] + +(27) BroadcastExchange +Input [4]: [ca_address_sk#21, ca_county#22, ca_state#23, ca_country#24] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(28) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [c_current_addr_sk#17] +Right keys [1]: [ca_address_sk#21] +Join type: Inner +Join condition: None + +(29) Project [codegen id : 7] +Output [12]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14, c_birth_year#19, ca_county#22, ca_state#23, ca_country#24] +Input [14]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14, c_current_addr_sk#17, c_birth_year#19, ca_address_sk#21, ca_county#22, ca_state#23, ca_country#24] + +(30) ReusedExchange [Reuses operator id: 158] +Output [1]: [d_date_sk#25] + +(31) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [cs_sold_date_sk#9] +Right keys [1]: [d_date_sk#25] +Join type: Inner +Join condition: None + +(32) Project [codegen id : 7] +Output [11]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, ca_county#22, ca_state#23, ca_country#24] +Input [13]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14, c_birth_year#19, ca_county#22, ca_state#23, ca_country#24, d_date_sk#25] + +(33) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#26, i_item_id#27] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(34) CometFilter +Input [2]: [i_item_sk#26, i_item_id#27] +Condition : isnotnull(i_item_sk#26) + +(35) ColumnarToRow [codegen id : 6] +Input [2]: [i_item_sk#26, i_item_id#27] + +(36) BroadcastExchange +Input [2]: [i_item_sk#26, i_item_id#27] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(37) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [cs_item_sk#3] +Right keys [1]: [i_item_sk#26] +Join type: Inner +Join condition: None + +(38) Project [codegen id : 7] +Output [11]: [i_item_id#27, ca_country#24, ca_state#23, ca_county#22, cast(cs_quantity#4 as decimal(12,2)) AS agg1#28, cast(cs_list_price#5 as decimal(12,2)) AS agg2#29, cast(cs_coupon_amt#7 as decimal(12,2)) AS agg3#30, cast(cs_sales_price#6 as decimal(12,2)) AS agg4#31, cast(cs_net_profit#8 as decimal(12,2)) AS agg5#32, cast(c_birth_year#19 as decimal(12,2)) AS agg6#33, cast(cd_dep_count#14 as decimal(12,2)) AS agg7#34] +Input [13]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, ca_county#22, ca_state#23, ca_country#24, i_item_sk#26, i_item_id#27] + +(39) HashAggregate [codegen id : 7] +Input [11]: [i_item_id#27, ca_country#24, ca_state#23, ca_county#22, agg1#28, agg2#29, agg3#30, agg4#31, agg5#32, agg6#33, agg7#34] +Keys [4]: [i_item_id#27, ca_country#24, ca_state#23, ca_county#22] +Functions [7]: [partial_avg(agg1#28), partial_avg(agg2#29), partial_avg(agg3#30), partial_avg(agg4#31), partial_avg(agg5#32), partial_avg(agg6#33), partial_avg(agg7#34)] +Aggregate Attributes [14]: [sum#35, count#36, sum#37, count#38, sum#39, count#40, sum#41, count#42, sum#43, count#44, sum#45, count#46, sum#47, count#48] +Results [18]: [i_item_id#27, ca_country#24, ca_state#23, ca_county#22, sum#49, count#50, sum#51, count#52, sum#53, count#54, sum#55, count#56, sum#57, count#58, sum#59, count#60, sum#61, count#62] + +(40) Exchange +Input [18]: [i_item_id#27, ca_country#24, ca_state#23, ca_county#22, sum#49, count#50, sum#51, count#52, sum#53, count#54, sum#55, count#56, sum#57, count#58, sum#59, count#60, sum#61, count#62] +Arguments: hashpartitioning(i_item_id#27, ca_country#24, ca_state#23, ca_county#22, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(41) HashAggregate [codegen id : 8] +Input [18]: [i_item_id#27, ca_country#24, ca_state#23, ca_county#22, sum#49, count#50, sum#51, count#52, sum#53, count#54, sum#55, count#56, sum#57, count#58, sum#59, count#60, sum#61, count#62] +Keys [4]: [i_item_id#27, ca_country#24, ca_state#23, ca_county#22] +Functions [7]: [avg(agg1#28), avg(agg2#29), avg(agg3#30), avg(agg4#31), avg(agg5#32), avg(agg6#33), avg(agg7#34)] +Aggregate Attributes [7]: [avg(agg1#28)#63, avg(agg2#29)#64, avg(agg3#30)#65, avg(agg4#31)#66, avg(agg5#32)#67, avg(agg6#33)#68, avg(agg7#34)#69] +Results [11]: [i_item_id#27, ca_country#24, ca_state#23, ca_county#22, avg(agg1#28)#63 AS agg1#70, avg(agg2#29)#64 AS agg2#71, avg(agg3#30)#65 AS agg3#72, avg(agg4#31)#66 AS agg4#73, avg(agg5#32)#67 AS agg5#74, avg(agg6#33)#68 AS agg6#75, avg(agg7#34)#69 AS agg7#76] + +(42) Scan parquet spark_catalog.default.catalog_sales +Output [9]: [cs_bill_customer_sk#77, cs_bill_cdemo_sk#78, cs_item_sk#79, cs_quantity#80, cs_list_price#81, cs_sales_price#82, cs_coupon_amt#83, cs_net_profit#84, cs_sold_date_sk#85] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#85), dynamicpruningexpression(cs_sold_date_sk#85 IN dynamicpruning#86)] +PushedFilters: [IsNotNull(cs_bill_cdemo_sk), IsNotNull(cs_bill_customer_sk), IsNotNull(cs_item_sk)] +ReadSchema: struct + +(43) CometFilter +Input [9]: [cs_bill_customer_sk#77, cs_bill_cdemo_sk#78, cs_item_sk#79, cs_quantity#80, cs_list_price#81, cs_sales_price#82, cs_coupon_amt#83, cs_net_profit#84, cs_sold_date_sk#85] +Condition : ((isnotnull(cs_bill_cdemo_sk#78) AND isnotnull(cs_bill_customer_sk#77)) AND isnotnull(cs_item_sk#79)) + +(44) ColumnarToRow [codegen id : 15] +Input [9]: [cs_bill_customer_sk#77, cs_bill_cdemo_sk#78, cs_item_sk#79, cs_quantity#80, cs_list_price#81, cs_sales_price#82, cs_coupon_amt#83, cs_net_profit#84, cs_sold_date_sk#85] + +(45) ReusedExchange [Reuses operator id: 8] +Output [2]: [cd_demo_sk#87, cd_dep_count#88] + +(46) BroadcastHashJoin [codegen id : 15] +Left keys [1]: [cs_bill_cdemo_sk#78] +Right keys [1]: [cd_demo_sk#87] +Join type: Inner +Join condition: None + +(47) Project [codegen id : 15] +Output [9]: [cs_bill_customer_sk#77, cs_item_sk#79, cs_quantity#80, cs_list_price#81, cs_sales_price#82, cs_coupon_amt#83, cs_net_profit#84, cs_sold_date_sk#85, cd_dep_count#88] +Input [11]: [cs_bill_customer_sk#77, cs_bill_cdemo_sk#78, cs_item_sk#79, cs_quantity#80, cs_list_price#81, cs_sales_price#82, cs_coupon_amt#83, cs_net_profit#84, cs_sold_date_sk#85, cd_demo_sk#87, cd_dep_count#88] + +(48) ReusedExchange [Reuses operator id: 15] +Output [4]: [c_customer_sk#89, c_current_cdemo_sk#90, c_current_addr_sk#91, c_birth_year#92] + +(49) BroadcastHashJoin [codegen id : 15] +Left keys [1]: [cs_bill_customer_sk#77] +Right keys [1]: [c_customer_sk#89] +Join type: Inner +Join condition: None + +(50) Project [codegen id : 15] +Output [11]: [cs_item_sk#79, cs_quantity#80, cs_list_price#81, cs_sales_price#82, cs_coupon_amt#83, cs_net_profit#84, cs_sold_date_sk#85, cd_dep_count#88, c_current_cdemo_sk#90, c_current_addr_sk#91, c_birth_year#92] +Input [13]: [cs_bill_customer_sk#77, cs_item_sk#79, cs_quantity#80, cs_list_price#81, cs_sales_price#82, cs_coupon_amt#83, cs_net_profit#84, cs_sold_date_sk#85, cd_dep_count#88, c_customer_sk#89, c_current_cdemo_sk#90, c_current_addr_sk#91, c_birth_year#92] + +(51) ReusedExchange [Reuses operator id: 21] +Output [1]: [cd_demo_sk#93] + +(52) BroadcastHashJoin [codegen id : 15] +Left keys [1]: [c_current_cdemo_sk#90] +Right keys [1]: [cd_demo_sk#93] +Join type: Inner +Join condition: None + +(53) Project [codegen id : 15] +Output [10]: [cs_item_sk#79, cs_quantity#80, cs_list_price#81, cs_sales_price#82, cs_coupon_amt#83, cs_net_profit#84, cs_sold_date_sk#85, cd_dep_count#88, c_current_addr_sk#91, c_birth_year#92] +Input [12]: [cs_item_sk#79, cs_quantity#80, cs_list_price#81, cs_sales_price#82, cs_coupon_amt#83, cs_net_profit#84, cs_sold_date_sk#85, cd_dep_count#88, c_current_cdemo_sk#90, c_current_addr_sk#91, c_birth_year#92, cd_demo_sk#93] + +(54) Scan parquet spark_catalog.default.customer_address +Output [3]: [ca_address_sk#94, ca_state#95, ca_country#96] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [In(ca_state, [AL,MS,NC,ND,OK,TN,WI]), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(55) CometFilter +Input [3]: [ca_address_sk#94, ca_state#95, ca_country#96] +Condition : (ca_state#95 IN (ND,WI,AL,NC,OK,MS,TN) AND isnotnull(ca_address_sk#94)) + +(56) ColumnarToRow [codegen id : 12] +Input [3]: [ca_address_sk#94, ca_state#95, ca_country#96] + +(57) BroadcastExchange +Input [3]: [ca_address_sk#94, ca_state#95, ca_country#96] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=7] + +(58) BroadcastHashJoin [codegen id : 15] +Left keys [1]: [c_current_addr_sk#91] +Right keys [1]: [ca_address_sk#94] +Join type: Inner +Join condition: None + +(59) Project [codegen id : 15] +Output [11]: [cs_item_sk#79, cs_quantity#80, cs_list_price#81, cs_sales_price#82, cs_coupon_amt#83, cs_net_profit#84, cs_sold_date_sk#85, cd_dep_count#88, c_birth_year#92, ca_state#95, ca_country#96] +Input [13]: [cs_item_sk#79, cs_quantity#80, cs_list_price#81, cs_sales_price#82, cs_coupon_amt#83, cs_net_profit#84, cs_sold_date_sk#85, cd_dep_count#88, c_current_addr_sk#91, c_birth_year#92, ca_address_sk#94, ca_state#95, ca_country#96] + +(60) ReusedExchange [Reuses operator id: 158] +Output [1]: [d_date_sk#97] + +(61) BroadcastHashJoin [codegen id : 15] +Left keys [1]: [cs_sold_date_sk#85] +Right keys [1]: [d_date_sk#97] +Join type: Inner +Join condition: None + +(62) Project [codegen id : 15] +Output [10]: [cs_item_sk#79, cs_quantity#80, cs_list_price#81, cs_sales_price#82, cs_coupon_amt#83, cs_net_profit#84, cd_dep_count#88, c_birth_year#92, ca_state#95, ca_country#96] +Input [12]: [cs_item_sk#79, cs_quantity#80, cs_list_price#81, cs_sales_price#82, cs_coupon_amt#83, cs_net_profit#84, cs_sold_date_sk#85, cd_dep_count#88, c_birth_year#92, ca_state#95, ca_country#96, d_date_sk#97] + +(63) ReusedExchange [Reuses operator id: 36] +Output [2]: [i_item_sk#98, i_item_id#99] + +(64) BroadcastHashJoin [codegen id : 15] +Left keys [1]: [cs_item_sk#79] +Right keys [1]: [i_item_sk#98] +Join type: Inner +Join condition: None + +(65) Project [codegen id : 15] +Output [10]: [i_item_id#99, ca_country#96, ca_state#95, cast(cs_quantity#80 as decimal(12,2)) AS agg1#100, cast(cs_list_price#81 as decimal(12,2)) AS agg2#101, cast(cs_coupon_amt#83 as decimal(12,2)) AS agg3#102, cast(cs_sales_price#82 as decimal(12,2)) AS agg4#103, cast(cs_net_profit#84 as decimal(12,2)) AS agg5#104, cast(c_birth_year#92 as decimal(12,2)) AS agg6#105, cast(cd_dep_count#88 as decimal(12,2)) AS agg7#106] +Input [12]: [cs_item_sk#79, cs_quantity#80, cs_list_price#81, cs_sales_price#82, cs_coupon_amt#83, cs_net_profit#84, cd_dep_count#88, c_birth_year#92, ca_state#95, ca_country#96, i_item_sk#98, i_item_id#99] + +(66) HashAggregate [codegen id : 15] +Input [10]: [i_item_id#99, ca_country#96, ca_state#95, agg1#100, agg2#101, agg3#102, agg4#103, agg5#104, agg6#105, agg7#106] +Keys [3]: [i_item_id#99, ca_country#96, ca_state#95] +Functions [7]: [partial_avg(agg1#100), partial_avg(agg2#101), partial_avg(agg3#102), partial_avg(agg4#103), partial_avg(agg5#104), partial_avg(agg6#105), partial_avg(agg7#106)] +Aggregate Attributes [14]: [sum#107, count#108, sum#109, count#110, sum#111, count#112, sum#113, count#114, sum#115, count#116, sum#117, count#118, sum#119, count#120] +Results [17]: [i_item_id#99, ca_country#96, ca_state#95, sum#121, count#122, sum#123, count#124, sum#125, count#126, sum#127, count#128, sum#129, count#130, sum#131, count#132, sum#133, count#134] + +(67) Exchange +Input [17]: [i_item_id#99, ca_country#96, ca_state#95, sum#121, count#122, sum#123, count#124, sum#125, count#126, sum#127, count#128, sum#129, count#130, sum#131, count#132, sum#133, count#134] +Arguments: hashpartitioning(i_item_id#99, ca_country#96, ca_state#95, 5), ENSURE_REQUIREMENTS, [plan_id=8] + +(68) HashAggregate [codegen id : 16] +Input [17]: [i_item_id#99, ca_country#96, ca_state#95, sum#121, count#122, sum#123, count#124, sum#125, count#126, sum#127, count#128, sum#129, count#130, sum#131, count#132, sum#133, count#134] +Keys [3]: [i_item_id#99, ca_country#96, ca_state#95] +Functions [7]: [avg(agg1#100), avg(agg2#101), avg(agg3#102), avg(agg4#103), avg(agg5#104), avg(agg6#105), avg(agg7#106)] +Aggregate Attributes [7]: [avg(agg1#100)#135, avg(agg2#101)#136, avg(agg3#102)#137, avg(agg4#103)#138, avg(agg5#104)#139, avg(agg6#105)#140, avg(agg7#106)#141] +Results [11]: [i_item_id#99, ca_country#96, ca_state#95, null AS county#142, avg(agg1#100)#135 AS agg1#143, avg(agg2#101)#136 AS agg2#144, avg(agg3#102)#137 AS agg3#145, avg(agg4#103)#138 AS agg4#146, avg(agg5#104)#139 AS agg5#147, avg(agg6#105)#140 AS agg6#148, avg(agg7#106)#141 AS agg7#149] + +(69) Scan parquet spark_catalog.default.catalog_sales +Output [9]: [cs_bill_customer_sk#150, cs_bill_cdemo_sk#151, cs_item_sk#152, cs_quantity#153, cs_list_price#154, cs_sales_price#155, cs_coupon_amt#156, cs_net_profit#157, cs_sold_date_sk#158] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#158), dynamicpruningexpression(cs_sold_date_sk#158 IN dynamicpruning#159)] +PushedFilters: [IsNotNull(cs_bill_cdemo_sk), IsNotNull(cs_bill_customer_sk), IsNotNull(cs_item_sk)] +ReadSchema: struct + +(70) CometFilter +Input [9]: [cs_bill_customer_sk#150, cs_bill_cdemo_sk#151, cs_item_sk#152, cs_quantity#153, cs_list_price#154, cs_sales_price#155, cs_coupon_amt#156, cs_net_profit#157, cs_sold_date_sk#158] +Condition : ((isnotnull(cs_bill_cdemo_sk#151) AND isnotnull(cs_bill_customer_sk#150)) AND isnotnull(cs_item_sk#152)) + +(71) ColumnarToRow [codegen id : 23] +Input [9]: [cs_bill_customer_sk#150, cs_bill_cdemo_sk#151, cs_item_sk#152, cs_quantity#153, cs_list_price#154, cs_sales_price#155, cs_coupon_amt#156, cs_net_profit#157, cs_sold_date_sk#158] + +(72) ReusedExchange [Reuses operator id: 8] +Output [2]: [cd_demo_sk#160, cd_dep_count#161] + +(73) BroadcastHashJoin [codegen id : 23] +Left keys [1]: [cs_bill_cdemo_sk#151] +Right keys [1]: [cd_demo_sk#160] +Join type: Inner +Join condition: None + +(74) Project [codegen id : 23] +Output [9]: [cs_bill_customer_sk#150, cs_item_sk#152, cs_quantity#153, cs_list_price#154, cs_sales_price#155, cs_coupon_amt#156, cs_net_profit#157, cs_sold_date_sk#158, cd_dep_count#161] +Input [11]: [cs_bill_customer_sk#150, cs_bill_cdemo_sk#151, cs_item_sk#152, cs_quantity#153, cs_list_price#154, cs_sales_price#155, cs_coupon_amt#156, cs_net_profit#157, cs_sold_date_sk#158, cd_demo_sk#160, cd_dep_count#161] + +(75) ReusedExchange [Reuses operator id: 15] +Output [4]: [c_customer_sk#162, c_current_cdemo_sk#163, c_current_addr_sk#164, c_birth_year#165] + +(76) BroadcastHashJoin [codegen id : 23] +Left keys [1]: [cs_bill_customer_sk#150] +Right keys [1]: [c_customer_sk#162] +Join type: Inner +Join condition: None + +(77) Project [codegen id : 23] +Output [11]: [cs_item_sk#152, cs_quantity#153, cs_list_price#154, cs_sales_price#155, cs_coupon_amt#156, cs_net_profit#157, cs_sold_date_sk#158, cd_dep_count#161, c_current_cdemo_sk#163, c_current_addr_sk#164, c_birth_year#165] +Input [13]: [cs_bill_customer_sk#150, cs_item_sk#152, cs_quantity#153, cs_list_price#154, cs_sales_price#155, cs_coupon_amt#156, cs_net_profit#157, cs_sold_date_sk#158, cd_dep_count#161, c_customer_sk#162, c_current_cdemo_sk#163, c_current_addr_sk#164, c_birth_year#165] + +(78) ReusedExchange [Reuses operator id: 21] +Output [1]: [cd_demo_sk#166] + +(79) BroadcastHashJoin [codegen id : 23] +Left keys [1]: [c_current_cdemo_sk#163] +Right keys [1]: [cd_demo_sk#166] +Join type: Inner +Join condition: None + +(80) Project [codegen id : 23] +Output [10]: [cs_item_sk#152, cs_quantity#153, cs_list_price#154, cs_sales_price#155, cs_coupon_amt#156, cs_net_profit#157, cs_sold_date_sk#158, cd_dep_count#161, c_current_addr_sk#164, c_birth_year#165] +Input [12]: [cs_item_sk#152, cs_quantity#153, cs_list_price#154, cs_sales_price#155, cs_coupon_amt#156, cs_net_profit#157, cs_sold_date_sk#158, cd_dep_count#161, c_current_cdemo_sk#163, c_current_addr_sk#164, c_birth_year#165, cd_demo_sk#166] + +(81) Scan parquet spark_catalog.default.customer_address +Output [3]: [ca_address_sk#167, ca_state#168, ca_country#169] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [In(ca_state, [AL,MS,NC,ND,OK,TN,WI]), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(82) CometFilter +Input [3]: [ca_address_sk#167, ca_state#168, ca_country#169] +Condition : (ca_state#168 IN (ND,WI,AL,NC,OK,MS,TN) AND isnotnull(ca_address_sk#167)) + +(83) CometProject +Input [3]: [ca_address_sk#167, ca_state#168, ca_country#169] +Arguments: [ca_address_sk#167, ca_country#169], [ca_address_sk#167, ca_country#169] + +(84) ColumnarToRow [codegen id : 20] +Input [2]: [ca_address_sk#167, ca_country#169] + +(85) BroadcastExchange +Input [2]: [ca_address_sk#167, ca_country#169] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=9] + +(86) BroadcastHashJoin [codegen id : 23] +Left keys [1]: [c_current_addr_sk#164] +Right keys [1]: [ca_address_sk#167] +Join type: Inner +Join condition: None + +(87) Project [codegen id : 23] +Output [10]: [cs_item_sk#152, cs_quantity#153, cs_list_price#154, cs_sales_price#155, cs_coupon_amt#156, cs_net_profit#157, cs_sold_date_sk#158, cd_dep_count#161, c_birth_year#165, ca_country#169] +Input [12]: [cs_item_sk#152, cs_quantity#153, cs_list_price#154, cs_sales_price#155, cs_coupon_amt#156, cs_net_profit#157, cs_sold_date_sk#158, cd_dep_count#161, c_current_addr_sk#164, c_birth_year#165, ca_address_sk#167, ca_country#169] + +(88) ReusedExchange [Reuses operator id: 158] +Output [1]: [d_date_sk#170] + +(89) BroadcastHashJoin [codegen id : 23] +Left keys [1]: [cs_sold_date_sk#158] +Right keys [1]: [d_date_sk#170] +Join type: Inner +Join condition: None + +(90) Project [codegen id : 23] +Output [9]: [cs_item_sk#152, cs_quantity#153, cs_list_price#154, cs_sales_price#155, cs_coupon_amt#156, cs_net_profit#157, cd_dep_count#161, c_birth_year#165, ca_country#169] +Input [11]: [cs_item_sk#152, cs_quantity#153, cs_list_price#154, cs_sales_price#155, cs_coupon_amt#156, cs_net_profit#157, cs_sold_date_sk#158, cd_dep_count#161, c_birth_year#165, ca_country#169, d_date_sk#170] + +(91) ReusedExchange [Reuses operator id: 36] +Output [2]: [i_item_sk#171, i_item_id#172] + +(92) BroadcastHashJoin [codegen id : 23] +Left keys [1]: [cs_item_sk#152] +Right keys [1]: [i_item_sk#171] +Join type: Inner +Join condition: None + +(93) Project [codegen id : 23] +Output [9]: [i_item_id#172, ca_country#169, cast(cs_quantity#153 as decimal(12,2)) AS agg1#173, cast(cs_list_price#154 as decimal(12,2)) AS agg2#174, cast(cs_coupon_amt#156 as decimal(12,2)) AS agg3#175, cast(cs_sales_price#155 as decimal(12,2)) AS agg4#176, cast(cs_net_profit#157 as decimal(12,2)) AS agg5#177, cast(c_birth_year#165 as decimal(12,2)) AS agg6#178, cast(cd_dep_count#161 as decimal(12,2)) AS agg7#179] +Input [11]: [cs_item_sk#152, cs_quantity#153, cs_list_price#154, cs_sales_price#155, cs_coupon_amt#156, cs_net_profit#157, cd_dep_count#161, c_birth_year#165, ca_country#169, i_item_sk#171, i_item_id#172] + +(94) HashAggregate [codegen id : 23] +Input [9]: [i_item_id#172, ca_country#169, agg1#173, agg2#174, agg3#175, agg4#176, agg5#177, agg6#178, agg7#179] +Keys [2]: [i_item_id#172, ca_country#169] +Functions [7]: [partial_avg(agg1#173), partial_avg(agg2#174), partial_avg(agg3#175), partial_avg(agg4#176), partial_avg(agg5#177), partial_avg(agg6#178), partial_avg(agg7#179)] +Aggregate Attributes [14]: [sum#180, count#181, sum#182, count#183, sum#184, count#185, sum#186, count#187, sum#188, count#189, sum#190, count#191, sum#192, count#193] +Results [16]: [i_item_id#172, ca_country#169, sum#194, count#195, sum#196, count#197, sum#198, count#199, sum#200, count#201, sum#202, count#203, sum#204, count#205, sum#206, count#207] + +(95) Exchange +Input [16]: [i_item_id#172, ca_country#169, sum#194, count#195, sum#196, count#197, sum#198, count#199, sum#200, count#201, sum#202, count#203, sum#204, count#205, sum#206, count#207] +Arguments: hashpartitioning(i_item_id#172, ca_country#169, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(96) HashAggregate [codegen id : 24] +Input [16]: [i_item_id#172, ca_country#169, sum#194, count#195, sum#196, count#197, sum#198, count#199, sum#200, count#201, sum#202, count#203, sum#204, count#205, sum#206, count#207] +Keys [2]: [i_item_id#172, ca_country#169] +Functions [7]: [avg(agg1#173), avg(agg2#174), avg(agg3#175), avg(agg4#176), avg(agg5#177), avg(agg6#178), avg(agg7#179)] +Aggregate Attributes [7]: [avg(agg1#173)#208, avg(agg2#174)#209, avg(agg3#175)#210, avg(agg4#176)#211, avg(agg5#177)#212, avg(agg6#178)#213, avg(agg7#179)#214] +Results [11]: [i_item_id#172, ca_country#169, null AS ca_state#215, null AS county#216, avg(agg1#173)#208 AS agg1#217, avg(agg2#174)#209 AS agg2#218, avg(agg3#175)#210 AS agg3#219, avg(agg4#176)#211 AS agg4#220, avg(agg5#177)#212 AS agg5#221, avg(agg6#178)#213 AS agg6#222, avg(agg7#179)#214 AS agg7#223] + +(97) Scan parquet spark_catalog.default.catalog_sales +Output [9]: [cs_bill_customer_sk#224, cs_bill_cdemo_sk#225, cs_item_sk#226, cs_quantity#227, cs_list_price#228, cs_sales_price#229, cs_coupon_amt#230, cs_net_profit#231, cs_sold_date_sk#232] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#232), dynamicpruningexpression(cs_sold_date_sk#232 IN dynamicpruning#233)] +PushedFilters: [IsNotNull(cs_bill_cdemo_sk), IsNotNull(cs_bill_customer_sk), IsNotNull(cs_item_sk)] +ReadSchema: struct + +(98) CometFilter +Input [9]: [cs_bill_customer_sk#224, cs_bill_cdemo_sk#225, cs_item_sk#226, cs_quantity#227, cs_list_price#228, cs_sales_price#229, cs_coupon_amt#230, cs_net_profit#231, cs_sold_date_sk#232] +Condition : ((isnotnull(cs_bill_cdemo_sk#225) AND isnotnull(cs_bill_customer_sk#224)) AND isnotnull(cs_item_sk#226)) + +(99) ColumnarToRow [codegen id : 31] +Input [9]: [cs_bill_customer_sk#224, cs_bill_cdemo_sk#225, cs_item_sk#226, cs_quantity#227, cs_list_price#228, cs_sales_price#229, cs_coupon_amt#230, cs_net_profit#231, cs_sold_date_sk#232] + +(100) ReusedExchange [Reuses operator id: 8] +Output [2]: [cd_demo_sk#234, cd_dep_count#235] + +(101) BroadcastHashJoin [codegen id : 31] +Left keys [1]: [cs_bill_cdemo_sk#225] +Right keys [1]: [cd_demo_sk#234] +Join type: Inner +Join condition: None + +(102) Project [codegen id : 31] +Output [9]: [cs_bill_customer_sk#224, cs_item_sk#226, cs_quantity#227, cs_list_price#228, cs_sales_price#229, cs_coupon_amt#230, cs_net_profit#231, cs_sold_date_sk#232, cd_dep_count#235] +Input [11]: [cs_bill_customer_sk#224, cs_bill_cdemo_sk#225, cs_item_sk#226, cs_quantity#227, cs_list_price#228, cs_sales_price#229, cs_coupon_amt#230, cs_net_profit#231, cs_sold_date_sk#232, cd_demo_sk#234, cd_dep_count#235] + +(103) ReusedExchange [Reuses operator id: 15] +Output [4]: [c_customer_sk#236, c_current_cdemo_sk#237, c_current_addr_sk#238, c_birth_year#239] + +(104) BroadcastHashJoin [codegen id : 31] +Left keys [1]: [cs_bill_customer_sk#224] +Right keys [1]: [c_customer_sk#236] +Join type: Inner +Join condition: None + +(105) Project [codegen id : 31] +Output [11]: [cs_item_sk#226, cs_quantity#227, cs_list_price#228, cs_sales_price#229, cs_coupon_amt#230, cs_net_profit#231, cs_sold_date_sk#232, cd_dep_count#235, c_current_cdemo_sk#237, c_current_addr_sk#238, c_birth_year#239] +Input [13]: [cs_bill_customer_sk#224, cs_item_sk#226, cs_quantity#227, cs_list_price#228, cs_sales_price#229, cs_coupon_amt#230, cs_net_profit#231, cs_sold_date_sk#232, cd_dep_count#235, c_customer_sk#236, c_current_cdemo_sk#237, c_current_addr_sk#238, c_birth_year#239] + +(106) ReusedExchange [Reuses operator id: 21] +Output [1]: [cd_demo_sk#240] + +(107) BroadcastHashJoin [codegen id : 31] +Left keys [1]: [c_current_cdemo_sk#237] +Right keys [1]: [cd_demo_sk#240] +Join type: Inner +Join condition: None + +(108) Project [codegen id : 31] +Output [10]: [cs_item_sk#226, cs_quantity#227, cs_list_price#228, cs_sales_price#229, cs_coupon_amt#230, cs_net_profit#231, cs_sold_date_sk#232, cd_dep_count#235, c_current_addr_sk#238, c_birth_year#239] +Input [12]: [cs_item_sk#226, cs_quantity#227, cs_list_price#228, cs_sales_price#229, cs_coupon_amt#230, cs_net_profit#231, cs_sold_date_sk#232, cd_dep_count#235, c_current_cdemo_sk#237, c_current_addr_sk#238, c_birth_year#239, cd_demo_sk#240] + +(109) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#241, ca_state#242] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [In(ca_state, [AL,MS,NC,ND,OK,TN,WI]), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(110) CometFilter +Input [2]: [ca_address_sk#241, ca_state#242] +Condition : (ca_state#242 IN (ND,WI,AL,NC,OK,MS,TN) AND isnotnull(ca_address_sk#241)) + +(111) CometProject +Input [2]: [ca_address_sk#241, ca_state#242] +Arguments: [ca_address_sk#241], [ca_address_sk#241] + +(112) ColumnarToRow [codegen id : 28] +Input [1]: [ca_address_sk#241] + +(113) BroadcastExchange +Input [1]: [ca_address_sk#241] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=11] + +(114) BroadcastHashJoin [codegen id : 31] +Left keys [1]: [c_current_addr_sk#238] +Right keys [1]: [ca_address_sk#241] +Join type: Inner +Join condition: None + +(115) Project [codegen id : 31] +Output [9]: [cs_item_sk#226, cs_quantity#227, cs_list_price#228, cs_sales_price#229, cs_coupon_amt#230, cs_net_profit#231, cs_sold_date_sk#232, cd_dep_count#235, c_birth_year#239] +Input [11]: [cs_item_sk#226, cs_quantity#227, cs_list_price#228, cs_sales_price#229, cs_coupon_amt#230, cs_net_profit#231, cs_sold_date_sk#232, cd_dep_count#235, c_current_addr_sk#238, c_birth_year#239, ca_address_sk#241] + +(116) ReusedExchange [Reuses operator id: 158] +Output [1]: [d_date_sk#243] + +(117) BroadcastHashJoin [codegen id : 31] +Left keys [1]: [cs_sold_date_sk#232] +Right keys [1]: [d_date_sk#243] +Join type: Inner +Join condition: None + +(118) Project [codegen id : 31] +Output [8]: [cs_item_sk#226, cs_quantity#227, cs_list_price#228, cs_sales_price#229, cs_coupon_amt#230, cs_net_profit#231, cd_dep_count#235, c_birth_year#239] +Input [10]: [cs_item_sk#226, cs_quantity#227, cs_list_price#228, cs_sales_price#229, cs_coupon_amt#230, cs_net_profit#231, cs_sold_date_sk#232, cd_dep_count#235, c_birth_year#239, d_date_sk#243] + +(119) ReusedExchange [Reuses operator id: 36] +Output [2]: [i_item_sk#244, i_item_id#245] + +(120) BroadcastHashJoin [codegen id : 31] +Left keys [1]: [cs_item_sk#226] +Right keys [1]: [i_item_sk#244] +Join type: Inner +Join condition: None + +(121) Project [codegen id : 31] +Output [8]: [i_item_id#245, cast(cs_quantity#227 as decimal(12,2)) AS agg1#246, cast(cs_list_price#228 as decimal(12,2)) AS agg2#247, cast(cs_coupon_amt#230 as decimal(12,2)) AS agg3#248, cast(cs_sales_price#229 as decimal(12,2)) AS agg4#249, cast(cs_net_profit#231 as decimal(12,2)) AS agg5#250, cast(c_birth_year#239 as decimal(12,2)) AS agg6#251, cast(cd_dep_count#235 as decimal(12,2)) AS agg7#252] +Input [10]: [cs_item_sk#226, cs_quantity#227, cs_list_price#228, cs_sales_price#229, cs_coupon_amt#230, cs_net_profit#231, cd_dep_count#235, c_birth_year#239, i_item_sk#244, i_item_id#245] + +(122) HashAggregate [codegen id : 31] +Input [8]: [i_item_id#245, agg1#246, agg2#247, agg3#248, agg4#249, agg5#250, agg6#251, agg7#252] +Keys [1]: [i_item_id#245] +Functions [7]: [partial_avg(agg1#246), partial_avg(agg2#247), partial_avg(agg3#248), partial_avg(agg4#249), partial_avg(agg5#250), partial_avg(agg6#251), partial_avg(agg7#252)] +Aggregate Attributes [14]: [sum#253, count#254, sum#255, count#256, sum#257, count#258, sum#259, count#260, sum#261, count#262, sum#263, count#264, sum#265, count#266] +Results [15]: [i_item_id#245, sum#267, count#268, sum#269, count#270, sum#271, count#272, sum#273, count#274, sum#275, count#276, sum#277, count#278, sum#279, count#280] + +(123) Exchange +Input [15]: [i_item_id#245, sum#267, count#268, sum#269, count#270, sum#271, count#272, sum#273, count#274, sum#275, count#276, sum#277, count#278, sum#279, count#280] +Arguments: hashpartitioning(i_item_id#245, 5), ENSURE_REQUIREMENTS, [plan_id=12] + +(124) HashAggregate [codegen id : 32] +Input [15]: [i_item_id#245, sum#267, count#268, sum#269, count#270, sum#271, count#272, sum#273, count#274, sum#275, count#276, sum#277, count#278, sum#279, count#280] +Keys [1]: [i_item_id#245] +Functions [7]: [avg(agg1#246), avg(agg2#247), avg(agg3#248), avg(agg4#249), avg(agg5#250), avg(agg6#251), avg(agg7#252)] +Aggregate Attributes [7]: [avg(agg1#246)#281, avg(agg2#247)#282, avg(agg3#248)#283, avg(agg4#249)#284, avg(agg5#250)#285, avg(agg6#251)#286, avg(agg7#252)#287] +Results [11]: [i_item_id#245, null AS ca_country#288, null AS ca_state#289, null AS county#290, avg(agg1#246)#281 AS agg1#291, avg(agg2#247)#282 AS agg2#292, avg(agg3#248)#283 AS agg3#293, avg(agg4#249)#284 AS agg4#294, avg(agg5#250)#285 AS agg5#295, avg(agg6#251)#286 AS agg6#296, avg(agg7#252)#287 AS agg7#297] + +(125) Scan parquet spark_catalog.default.catalog_sales +Output [9]: [cs_bill_customer_sk#298, cs_bill_cdemo_sk#299, cs_item_sk#300, cs_quantity#301, cs_list_price#302, cs_sales_price#303, cs_coupon_amt#304, cs_net_profit#305, cs_sold_date_sk#306] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#306), dynamicpruningexpression(cs_sold_date_sk#306 IN dynamicpruning#307)] +PushedFilters: [IsNotNull(cs_bill_cdemo_sk), IsNotNull(cs_bill_customer_sk), IsNotNull(cs_item_sk)] +ReadSchema: struct + +(126) CometFilter +Input [9]: [cs_bill_customer_sk#298, cs_bill_cdemo_sk#299, cs_item_sk#300, cs_quantity#301, cs_list_price#302, cs_sales_price#303, cs_coupon_amt#304, cs_net_profit#305, cs_sold_date_sk#306] +Condition : ((isnotnull(cs_bill_cdemo_sk#299) AND isnotnull(cs_bill_customer_sk#298)) AND isnotnull(cs_item_sk#300)) + +(127) ColumnarToRow [codegen id : 39] +Input [9]: [cs_bill_customer_sk#298, cs_bill_cdemo_sk#299, cs_item_sk#300, cs_quantity#301, cs_list_price#302, cs_sales_price#303, cs_coupon_amt#304, cs_net_profit#305, cs_sold_date_sk#306] + +(128) ReusedExchange [Reuses operator id: 8] +Output [2]: [cd_demo_sk#308, cd_dep_count#309] + +(129) BroadcastHashJoin [codegen id : 39] +Left keys [1]: [cs_bill_cdemo_sk#299] +Right keys [1]: [cd_demo_sk#308] +Join type: Inner +Join condition: None + +(130) Project [codegen id : 39] +Output [9]: [cs_bill_customer_sk#298, cs_item_sk#300, cs_quantity#301, cs_list_price#302, cs_sales_price#303, cs_coupon_amt#304, cs_net_profit#305, cs_sold_date_sk#306, cd_dep_count#309] +Input [11]: [cs_bill_customer_sk#298, cs_bill_cdemo_sk#299, cs_item_sk#300, cs_quantity#301, cs_list_price#302, cs_sales_price#303, cs_coupon_amt#304, cs_net_profit#305, cs_sold_date_sk#306, cd_demo_sk#308, cd_dep_count#309] + +(131) ReusedExchange [Reuses operator id: 15] +Output [4]: [c_customer_sk#310, c_current_cdemo_sk#311, c_current_addr_sk#312, c_birth_year#313] + +(132) BroadcastHashJoin [codegen id : 39] +Left keys [1]: [cs_bill_customer_sk#298] +Right keys [1]: [c_customer_sk#310] +Join type: Inner +Join condition: None + +(133) Project [codegen id : 39] +Output [11]: [cs_item_sk#300, cs_quantity#301, cs_list_price#302, cs_sales_price#303, cs_coupon_amt#304, cs_net_profit#305, cs_sold_date_sk#306, cd_dep_count#309, c_current_cdemo_sk#311, c_current_addr_sk#312, c_birth_year#313] +Input [13]: [cs_bill_customer_sk#298, cs_item_sk#300, cs_quantity#301, cs_list_price#302, cs_sales_price#303, cs_coupon_amt#304, cs_net_profit#305, cs_sold_date_sk#306, cd_dep_count#309, c_customer_sk#310, c_current_cdemo_sk#311, c_current_addr_sk#312, c_birth_year#313] + +(134) ReusedExchange [Reuses operator id: 21] +Output [1]: [cd_demo_sk#314] + +(135) BroadcastHashJoin [codegen id : 39] +Left keys [1]: [c_current_cdemo_sk#311] +Right keys [1]: [cd_demo_sk#314] +Join type: Inner +Join condition: None + +(136) Project [codegen id : 39] +Output [10]: [cs_item_sk#300, cs_quantity#301, cs_list_price#302, cs_sales_price#303, cs_coupon_amt#304, cs_net_profit#305, cs_sold_date_sk#306, cd_dep_count#309, c_current_addr_sk#312, c_birth_year#313] +Input [12]: [cs_item_sk#300, cs_quantity#301, cs_list_price#302, cs_sales_price#303, cs_coupon_amt#304, cs_net_profit#305, cs_sold_date_sk#306, cd_dep_count#309, c_current_cdemo_sk#311, c_current_addr_sk#312, c_birth_year#313, cd_demo_sk#314] + +(137) ReusedExchange [Reuses operator id: 113] +Output [1]: [ca_address_sk#315] + +(138) BroadcastHashJoin [codegen id : 39] +Left keys [1]: [c_current_addr_sk#312] +Right keys [1]: [ca_address_sk#315] +Join type: Inner +Join condition: None + +(139) Project [codegen id : 39] +Output [9]: [cs_item_sk#300, cs_quantity#301, cs_list_price#302, cs_sales_price#303, cs_coupon_amt#304, cs_net_profit#305, cs_sold_date_sk#306, cd_dep_count#309, c_birth_year#313] +Input [11]: [cs_item_sk#300, cs_quantity#301, cs_list_price#302, cs_sales_price#303, cs_coupon_amt#304, cs_net_profit#305, cs_sold_date_sk#306, cd_dep_count#309, c_current_addr_sk#312, c_birth_year#313, ca_address_sk#315] + +(140) ReusedExchange [Reuses operator id: 158] +Output [1]: [d_date_sk#316] + +(141) BroadcastHashJoin [codegen id : 39] +Left keys [1]: [cs_sold_date_sk#306] +Right keys [1]: [d_date_sk#316] +Join type: Inner +Join condition: None + +(142) Project [codegen id : 39] +Output [8]: [cs_item_sk#300, cs_quantity#301, cs_list_price#302, cs_sales_price#303, cs_coupon_amt#304, cs_net_profit#305, cd_dep_count#309, c_birth_year#313] +Input [10]: [cs_item_sk#300, cs_quantity#301, cs_list_price#302, cs_sales_price#303, cs_coupon_amt#304, cs_net_profit#305, cs_sold_date_sk#306, cd_dep_count#309, c_birth_year#313, d_date_sk#316] + +(143) Scan parquet spark_catalog.default.item +Output [1]: [i_item_sk#317] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(144) CometFilter +Input [1]: [i_item_sk#317] +Condition : isnotnull(i_item_sk#317) + +(145) ColumnarToRow [codegen id : 38] +Input [1]: [i_item_sk#317] + +(146) BroadcastExchange +Input [1]: [i_item_sk#317] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=13] + +(147) BroadcastHashJoin [codegen id : 39] +Left keys [1]: [cs_item_sk#300] +Right keys [1]: [i_item_sk#317] +Join type: Inner +Join condition: None + +(148) Project [codegen id : 39] +Output [7]: [cast(cs_quantity#301 as decimal(12,2)) AS agg1#318, cast(cs_list_price#302 as decimal(12,2)) AS agg2#319, cast(cs_coupon_amt#304 as decimal(12,2)) AS agg3#320, cast(cs_sales_price#303 as decimal(12,2)) AS agg4#321, cast(cs_net_profit#305 as decimal(12,2)) AS agg5#322, cast(c_birth_year#313 as decimal(12,2)) AS agg6#323, cast(cd_dep_count#309 as decimal(12,2)) AS agg7#324] +Input [9]: [cs_item_sk#300, cs_quantity#301, cs_list_price#302, cs_sales_price#303, cs_coupon_amt#304, cs_net_profit#305, cd_dep_count#309, c_birth_year#313, i_item_sk#317] + +(149) HashAggregate [codegen id : 39] +Input [7]: [agg1#318, agg2#319, agg3#320, agg4#321, agg5#322, agg6#323, agg7#324] +Keys: [] +Functions [7]: [partial_avg(agg1#318), partial_avg(agg2#319), partial_avg(agg3#320), partial_avg(agg4#321), partial_avg(agg5#322), partial_avg(agg6#323), partial_avg(agg7#324)] +Aggregate Attributes [14]: [sum#325, count#326, sum#327, count#328, sum#329, count#330, sum#331, count#332, sum#333, count#334, sum#335, count#336, sum#337, count#338] +Results [14]: [sum#339, count#340, sum#341, count#342, sum#343, count#344, sum#345, count#346, sum#347, count#348, sum#349, count#350, sum#351, count#352] + +(150) Exchange +Input [14]: [sum#339, count#340, sum#341, count#342, sum#343, count#344, sum#345, count#346, sum#347, count#348, sum#349, count#350, sum#351, count#352] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=14] + +(151) HashAggregate [codegen id : 40] +Input [14]: [sum#339, count#340, sum#341, count#342, sum#343, count#344, sum#345, count#346, sum#347, count#348, sum#349, count#350, sum#351, count#352] +Keys: [] +Functions [7]: [avg(agg1#318), avg(agg2#319), avg(agg3#320), avg(agg4#321), avg(agg5#322), avg(agg6#323), avg(agg7#324)] +Aggregate Attributes [7]: [avg(agg1#318)#353, avg(agg2#319)#354, avg(agg3#320)#355, avg(agg4#321)#356, avg(agg5#322)#357, avg(agg6#323)#358, avg(agg7#324)#359] +Results [11]: [null AS i_item_id#360, null AS ca_country#361, null AS ca_state#362, null AS county#363, avg(agg1#318)#353 AS agg1#364, avg(agg2#319)#354 AS agg2#365, avg(agg3#320)#355 AS agg3#366, avg(agg4#321)#356 AS agg4#367, avg(agg5#322)#357 AS agg5#368, avg(agg6#323)#358 AS agg6#369, avg(agg7#324)#359 AS agg7#370] + +(152) Union + +(153) TakeOrderedAndProject +Input [11]: [i_item_id#27, ca_country#24, ca_state#23, ca_county#22, agg1#70, agg2#71, agg3#72, agg4#73, agg5#74, agg6#75, agg7#76] +Arguments: 100, [ca_country#24 ASC NULLS FIRST, ca_state#23 ASC NULLS FIRST, ca_county#22 ASC NULLS FIRST, i_item_id#27 ASC NULLS FIRST], [i_item_id#27, ca_country#24, ca_state#23, ca_county#22, agg1#70, agg2#71, agg3#72, agg4#73, agg5#74, agg6#75, agg7#76] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#9 IN dynamicpruning#10 +BroadcastExchange (158) ++- * ColumnarToRow (157) + +- CometProject (156) + +- CometFilter (155) + +- CometScan parquet spark_catalog.default.date_dim (154) + + +(154) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#25, d_year#371] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(155) CometFilter +Input [2]: [d_date_sk#25, d_year#371] +Condition : ((isnotnull(d_year#371) AND (d_year#371 = 2001)) AND isnotnull(d_date_sk#25)) + +(156) CometProject +Input [2]: [d_date_sk#25, d_year#371] +Arguments: [d_date_sk#25], [d_date_sk#25] + +(157) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#25] + +(158) BroadcastExchange +Input [1]: [d_date_sk#25] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=15] + +Subquery:2 Hosting operator id = 42 Hosting Expression = cs_sold_date_sk#85 IN dynamicpruning#10 + +Subquery:3 Hosting operator id = 69 Hosting Expression = cs_sold_date_sk#158 IN dynamicpruning#10 + +Subquery:4 Hosting operator id = 97 Hosting Expression = cs_sold_date_sk#232 IN dynamicpruning#10 + +Subquery:5 Hosting operator id = 125 Hosting Expression = cs_sold_date_sk#306 IN dynamicpruning#10 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q18a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q18a/simplified.txt new file mode 100644 index 0000000000..f02809572c --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q18a/simplified.txt @@ -0,0 +1,233 @@ +TakeOrderedAndProject [ca_country,ca_state,ca_county,i_item_id,agg1,agg2,agg3,agg4,agg5,agg6,agg7] + Union + WholeStageCodegen (8) + HashAggregate [i_item_id,ca_country,ca_state,ca_county,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] [avg(agg1),avg(agg2),avg(agg3),avg(agg4),avg(agg5),avg(agg6),avg(agg7),agg1,agg2,agg3,agg4,agg5,agg6,agg7,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + InputAdapter + Exchange [i_item_id,ca_country,ca_state,ca_county] #1 + WholeStageCodegen (7) + HashAggregate [i_item_id,ca_country,ca_state,ca_county,agg1,agg2,agg3,agg4,agg5,agg6,agg7] [sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + Project [i_item_id,ca_country,ca_state,ca_county,cs_quantity,cs_list_price,cs_coupon_amt,cs_sales_price,cs_net_profit,c_birth_year,cd_dep_count] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cd_dep_count,c_birth_year,ca_county,ca_state,ca_country] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_birth_year,ca_county,ca_state,ca_country] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_current_addr_sk,c_birth_year] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_current_cdemo_sk,c_current_addr_sk,c_birth_year] + BroadcastHashJoin [cs_bill_customer_sk,c_customer_sk] + Project [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count] + BroadcastHashJoin [cs_bill_cdemo_sk,cd_demo_sk] + ColumnarToRow + InputAdapter + CometFilter [cs_bill_cdemo_sk,cs_bill_customer_sk,cs_item_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_bill_cdemo_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [cd_demo_sk,cd_dep_count] + CometFilter [cd_gender,cd_education_status,cd_demo_sk] + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_education_status,cd_dep_count] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometProject [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk,c_birth_year] + CometFilter [c_birth_month,c_customer_sk,c_current_cdemo_sk,c_current_addr_sk] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk,c_birth_month,c_birth_year] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometFilter [cd_demo_sk] + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (4) + ColumnarToRow + InputAdapter + CometFilter [ca_state,ca_address_sk] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_county,ca_state,ca_country] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (6) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] + WholeStageCodegen (16) + HashAggregate [i_item_id,ca_country,ca_state,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] [avg(agg1),avg(agg2),avg(agg3),avg(agg4),avg(agg5),avg(agg6),avg(agg7),county,agg1,agg2,agg3,agg4,agg5,agg6,agg7,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + InputAdapter + Exchange [i_item_id,ca_country,ca_state] #8 + WholeStageCodegen (15) + HashAggregate [i_item_id,ca_country,ca_state,agg1,agg2,agg3,agg4,agg5,agg6,agg7] [sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + Project [i_item_id,ca_country,ca_state,cs_quantity,cs_list_price,cs_coupon_amt,cs_sales_price,cs_net_profit,c_birth_year,cd_dep_count] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cd_dep_count,c_birth_year,ca_state,ca_country] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_birth_year,ca_state,ca_country] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_current_addr_sk,c_birth_year] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_current_cdemo_sk,c_current_addr_sk,c_birth_year] + BroadcastHashJoin [cs_bill_customer_sk,c_customer_sk] + Project [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count] + BroadcastHashJoin [cs_bill_cdemo_sk,cd_demo_sk] + ColumnarToRow + InputAdapter + CometFilter [cs_bill_cdemo_sk,cs_bill_customer_sk,cs_item_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_bill_cdemo_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [cd_demo_sk,cd_dep_count] #3 + InputAdapter + ReusedExchange [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk,c_birth_year] #4 + InputAdapter + ReusedExchange [cd_demo_sk] #5 + InputAdapter + BroadcastExchange #9 + WholeStageCodegen (12) + ColumnarToRow + InputAdapter + CometFilter [ca_state,ca_address_sk] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state,ca_country] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + ReusedExchange [i_item_sk,i_item_id] #7 + WholeStageCodegen (24) + HashAggregate [i_item_id,ca_country,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] [avg(agg1),avg(agg2),avg(agg3),avg(agg4),avg(agg5),avg(agg6),avg(agg7),ca_state,county,agg1,agg2,agg3,agg4,agg5,agg6,agg7,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + InputAdapter + Exchange [i_item_id,ca_country] #10 + WholeStageCodegen (23) + HashAggregate [i_item_id,ca_country,agg1,agg2,agg3,agg4,agg5,agg6,agg7] [sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + Project [i_item_id,ca_country,cs_quantity,cs_list_price,cs_coupon_amt,cs_sales_price,cs_net_profit,c_birth_year,cd_dep_count] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cd_dep_count,c_birth_year,ca_country] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_birth_year,ca_country] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_current_addr_sk,c_birth_year] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_current_cdemo_sk,c_current_addr_sk,c_birth_year] + BroadcastHashJoin [cs_bill_customer_sk,c_customer_sk] + Project [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count] + BroadcastHashJoin [cs_bill_cdemo_sk,cd_demo_sk] + ColumnarToRow + InputAdapter + CometFilter [cs_bill_cdemo_sk,cs_bill_customer_sk,cs_item_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_bill_cdemo_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [cd_demo_sk,cd_dep_count] #3 + InputAdapter + ReusedExchange [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk,c_birth_year] #4 + InputAdapter + ReusedExchange [cd_demo_sk] #5 + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (20) + ColumnarToRow + InputAdapter + CometProject [ca_address_sk,ca_country] + CometFilter [ca_state,ca_address_sk] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state,ca_country] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + ReusedExchange [i_item_sk,i_item_id] #7 + WholeStageCodegen (32) + HashAggregate [i_item_id,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] [avg(agg1),avg(agg2),avg(agg3),avg(agg4),avg(agg5),avg(agg6),avg(agg7),ca_country,ca_state,county,agg1,agg2,agg3,agg4,agg5,agg6,agg7,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + InputAdapter + Exchange [i_item_id] #12 + WholeStageCodegen (31) + HashAggregate [i_item_id,agg1,agg2,agg3,agg4,agg5,agg6,agg7] [sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + Project [i_item_id,cs_quantity,cs_list_price,cs_coupon_amt,cs_sales_price,cs_net_profit,c_birth_year,cd_dep_count] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cd_dep_count,c_birth_year] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_birth_year] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_current_addr_sk,c_birth_year] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_current_cdemo_sk,c_current_addr_sk,c_birth_year] + BroadcastHashJoin [cs_bill_customer_sk,c_customer_sk] + Project [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count] + BroadcastHashJoin [cs_bill_cdemo_sk,cd_demo_sk] + ColumnarToRow + InputAdapter + CometFilter [cs_bill_cdemo_sk,cs_bill_customer_sk,cs_item_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_bill_cdemo_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [cd_demo_sk,cd_dep_count] #3 + InputAdapter + ReusedExchange [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk,c_birth_year] #4 + InputAdapter + ReusedExchange [cd_demo_sk] #5 + InputAdapter + BroadcastExchange #13 + WholeStageCodegen (28) + ColumnarToRow + InputAdapter + CometProject [ca_address_sk] + CometFilter [ca_state,ca_address_sk] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + ReusedExchange [i_item_sk,i_item_id] #7 + WholeStageCodegen (40) + HashAggregate [sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] [avg(agg1),avg(agg2),avg(agg3),avg(agg4),avg(agg5),avg(agg6),avg(agg7),i_item_id,ca_country,ca_state,county,agg1,agg2,agg3,agg4,agg5,agg6,agg7,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + InputAdapter + Exchange #14 + WholeStageCodegen (39) + HashAggregate [agg1,agg2,agg3,agg4,agg5,agg6,agg7] [sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + Project [cs_quantity,cs_list_price,cs_coupon_amt,cs_sales_price,cs_net_profit,c_birth_year,cd_dep_count] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cd_dep_count,c_birth_year] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_birth_year] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_current_addr_sk,c_birth_year] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_current_cdemo_sk,c_current_addr_sk,c_birth_year] + BroadcastHashJoin [cs_bill_customer_sk,c_customer_sk] + Project [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count] + BroadcastHashJoin [cs_bill_cdemo_sk,cd_demo_sk] + ColumnarToRow + InputAdapter + CometFilter [cs_bill_cdemo_sk,cs_bill_customer_sk,cs_item_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_bill_cdemo_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [cd_demo_sk,cd_dep_count] #3 + InputAdapter + ReusedExchange [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk,c_birth_year] #4 + InputAdapter + ReusedExchange [cd_demo_sk] #5 + InputAdapter + ReusedExchange [ca_address_sk] #13 + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #15 + WholeStageCodegen (38) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q20/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q20/explain.txt new file mode 100644 index 0000000000..1304af2e10 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q20/explain.txt @@ -0,0 +1,150 @@ +== Physical Plan == +TakeOrderedAndProject (20) ++- * Project (19) + +- Window (18) + +- * Sort (17) + +- Exchange (16) + +- * HashAggregate (15) + +- Exchange (14) + +- * HashAggregate (13) + +- * Project (12) + +- * BroadcastHashJoin Inner BuildRight (11) + :- * Project (9) + : +- * BroadcastHashJoin Inner BuildRight (8) + : :- * ColumnarToRow (3) + : : +- CometFilter (2) + : : +- CometScan parquet spark_catalog.default.catalog_sales (1) + : +- BroadcastExchange (7) + : +- * ColumnarToRow (6) + : +- CometFilter (5) + : +- CometScan parquet spark_catalog.default.item (4) + +- ReusedExchange (10) + + +(1) Scan parquet spark_catalog.default.catalog_sales +Output [3]: [cs_item_sk#1, cs_ext_sales_price#2, cs_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#3), dynamicpruningexpression(cs_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(cs_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [cs_item_sk#1, cs_ext_sales_price#2, cs_sold_date_sk#3] +Condition : isnotnull(cs_item_sk#1) + +(3) ColumnarToRow [codegen id : 3] +Input [3]: [cs_item_sk#1, cs_ext_sales_price#2, cs_sold_date_sk#3] + +(4) Scan parquet spark_catalog.default.item +Output [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [In(i_category, [Books ,Home ,Sports ]), IsNotNull(i_item_sk)] +ReadSchema: struct + +(5) CometFilter +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Condition : (i_category#10 IN (Sports ,Books ,Home ) AND isnotnull(i_item_sk#5)) + +(6) ColumnarToRow [codegen id : 1] +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] + +(7) BroadcastExchange +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cs_item_sk#1] +Right keys [1]: [i_item_sk#5] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 3] +Output [7]: [cs_ext_sales_price#2, cs_sold_date_sk#3, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Input [9]: [cs_item_sk#1, cs_ext_sales_price#2, cs_sold_date_sk#3, i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] + +(10) ReusedExchange [Reuses operator id: 25] +Output [1]: [d_date_sk#11] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cs_sold_date_sk#3] +Right keys [1]: [d_date_sk#11] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [6]: [cs_ext_sales_price#2, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Input [8]: [cs_ext_sales_price#2, cs_sold_date_sk#3, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10, d_date_sk#11] + +(13) HashAggregate [codegen id : 3] +Input [6]: [cs_ext_sales_price#2, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Keys [5]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8] +Functions [1]: [partial_sum(UnscaledValue(cs_ext_sales_price#2))] +Aggregate Attributes [1]: [sum#12] +Results [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] + +(14) Exchange +Input [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] +Arguments: hashpartitioning(i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 4] +Input [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] +Keys [5]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8] +Functions [1]: [sum(UnscaledValue(cs_ext_sales_price#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(cs_ext_sales_price#2))#14] +Results [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, MakeDecimal(sum(UnscaledValue(cs_ext_sales_price#2))#14,17,2) AS itemrevenue#15, MakeDecimal(sum(UnscaledValue(cs_ext_sales_price#2))#14,17,2) AS _w0#16] + +(16) Exchange +Input [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16] +Arguments: hashpartitioning(i_class#9, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(17) Sort [codegen id : 5] +Input [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16] +Arguments: [i_class#9 ASC NULLS FIRST], false, 0 + +(18) Window +Input [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16] +Arguments: [sum(_w0#16) windowspecdefinition(i_class#9, specifiedwindowframe(RowFrame, unboundedpreceding$(), unboundedfollowing$())) AS _we0#17], [i_class#9] + +(19) Project [codegen id : 6] +Output [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, ((_w0#16 * 100) / _we0#17) AS revenueratio#18] +Input [8]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16, _we0#17] + +(20) TakeOrderedAndProject +Input [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, revenueratio#18] +Arguments: 100, [i_category#10 ASC NULLS FIRST, i_class#9 ASC NULLS FIRST, i_item_id#6 ASC NULLS FIRST, i_item_desc#7 ASC NULLS FIRST, revenueratio#18 ASC NULLS FIRST], [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, revenueratio#18] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (25) ++- * ColumnarToRow (24) + +- CometProject (23) + +- CometFilter (22) + +- CometScan parquet spark_catalog.default.date_dim (21) + + +(21) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#11, d_date#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,1999-02-22), LessThanOrEqual(d_date,1999-03-24), IsNotNull(d_date_sk)] +ReadSchema: struct + +(22) CometFilter +Input [2]: [d_date_sk#11, d_date#19] +Condition : (((isnotnull(d_date#19) AND (d_date#19 >= 1999-02-22)) AND (d_date#19 <= 1999-03-24)) AND isnotnull(d_date_sk#11)) + +(23) CometProject +Input [2]: [d_date_sk#11, d_date#19] +Arguments: [d_date_sk#11], [d_date_sk#11] + +(24) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#11] + +(25) BroadcastExchange +Input [1]: [d_date_sk#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q20/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q20/simplified.txt new file mode 100644 index 0000000000..2a2a392cd0 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q20/simplified.txt @@ -0,0 +1,40 @@ +TakeOrderedAndProject [i_category,i_class,i_item_id,i_item_desc,revenueratio,i_current_price,itemrevenue] + WholeStageCodegen (6) + Project [i_item_id,i_item_desc,i_category,i_class,i_current_price,itemrevenue,_w0,_we0] + InputAdapter + Window [_w0,i_class] + WholeStageCodegen (5) + Sort [i_class] + InputAdapter + Exchange [i_class] #1 + WholeStageCodegen (4) + HashAggregate [i_item_id,i_item_desc,i_category,i_class,i_current_price,sum] [sum(UnscaledValue(cs_ext_sales_price)),itemrevenue,_w0,sum] + InputAdapter + Exchange [i_item_id,i_item_desc,i_category,i_class,i_current_price] #2 + WholeStageCodegen (3) + HashAggregate [i_item_id,i_item_desc,i_category,i_class,i_current_price,cs_ext_sales_price] [sum,sum] + Project [cs_ext_sales_price,i_item_id,i_item_desc,i_current_price,i_class,i_category] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_ext_sales_price,cs_sold_date_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] + BroadcastHashJoin [cs_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_ext_sales_price,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [i_category,i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] + InputAdapter + ReusedExchange [d_date_sk] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22/explain.txt new file mode 100644 index 0000000000..fdebdc8a4e --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22/explain.txt @@ -0,0 +1,161 @@ +== Physical Plan == +TakeOrderedAndProject (22) ++- * HashAggregate (21) + +- Exchange (20) + +- * HashAggregate (19) + +- * Expand (18) + +- * Project (17) + +- * BroadcastNestedLoopJoin Inner BuildRight (16) + :- * Project (12) + : +- * BroadcastHashJoin Inner BuildRight (11) + : :- * Project (6) + : : +- * BroadcastHashJoin Inner BuildRight (5) + : : :- * ColumnarToRow (3) + : : : +- CometFilter (2) + : : : +- CometScan parquet spark_catalog.default.inventory (1) + : : +- ReusedExchange (4) + : +- BroadcastExchange (10) + : +- * ColumnarToRow (9) + : +- CometFilter (8) + : +- CometScan parquet spark_catalog.default.item (7) + +- BroadcastExchange (15) + +- * ColumnarToRow (14) + +- CometScan parquet spark_catalog.default.warehouse (13) + + +(1) Scan parquet spark_catalog.default.inventory +Output [3]: [inv_item_sk#1, inv_quantity_on_hand#2, inv_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(inv_date_sk#3), dynamicpruningexpression(inv_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(inv_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [inv_item_sk#1, inv_quantity_on_hand#2, inv_date_sk#3] +Condition : isnotnull(inv_item_sk#1) + +(3) ColumnarToRow [codegen id : 4] +Input [3]: [inv_item_sk#1, inv_quantity_on_hand#2, inv_date_sk#3] + +(4) ReusedExchange [Reuses operator id: 27] +Output [1]: [d_date_sk#5] + +(5) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [inv_date_sk#3] +Right keys [1]: [d_date_sk#5] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 4] +Output [2]: [inv_item_sk#1, inv_quantity_on_hand#2] +Input [4]: [inv_item_sk#1, inv_quantity_on_hand#2, inv_date_sk#3, d_date_sk#5] + +(7) Scan parquet spark_catalog.default.item +Output [5]: [i_item_sk#6, i_brand#7, i_class#8, i_category#9, i_product_name#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(8) CometFilter +Input [5]: [i_item_sk#6, i_brand#7, i_class#8, i_category#9, i_product_name#10] +Condition : isnotnull(i_item_sk#6) + +(9) ColumnarToRow [codegen id : 2] +Input [5]: [i_item_sk#6, i_brand#7, i_class#8, i_category#9, i_product_name#10] + +(10) BroadcastExchange +Input [5]: [i_item_sk#6, i_brand#7, i_class#8, i_category#9, i_product_name#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(11) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [inv_item_sk#1] +Right keys [1]: [i_item_sk#6] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 4] +Output [5]: [inv_quantity_on_hand#2, i_brand#7, i_class#8, i_category#9, i_product_name#10] +Input [7]: [inv_item_sk#1, inv_quantity_on_hand#2, i_item_sk#6, i_brand#7, i_class#8, i_category#9, i_product_name#10] + +(13) Scan parquet spark_catalog.default.warehouse +Output: [] +Batched: true +Location [not included in comparison]/{warehouse_dir}/warehouse] +ReadSchema: struct<> + +(14) ColumnarToRow [codegen id : 3] +Input: [] + +(15) BroadcastExchange +Input: [] +Arguments: IdentityBroadcastMode, [plan_id=2] + +(16) BroadcastNestedLoopJoin [codegen id : 4] +Join type: Inner +Join condition: None + +(17) Project [codegen id : 4] +Output [5]: [inv_quantity_on_hand#2, i_product_name#10, i_brand#7, i_class#8, i_category#9] +Input [5]: [inv_quantity_on_hand#2, i_brand#7, i_class#8, i_category#9, i_product_name#10] + +(18) Expand [codegen id : 4] +Input [5]: [inv_quantity_on_hand#2, i_product_name#10, i_brand#7, i_class#8, i_category#9] +Arguments: [[inv_quantity_on_hand#2, i_product_name#10, i_brand#7, i_class#8, i_category#9, 0], [inv_quantity_on_hand#2, i_product_name#10, i_brand#7, i_class#8, null, 1], [inv_quantity_on_hand#2, i_product_name#10, i_brand#7, null, null, 3], [inv_quantity_on_hand#2, i_product_name#10, null, null, null, 7], [inv_quantity_on_hand#2, null, null, null, null, 15]], [inv_quantity_on_hand#2, i_product_name#11, i_brand#12, i_class#13, i_category#14, spark_grouping_id#15] + +(19) HashAggregate [codegen id : 4] +Input [6]: [inv_quantity_on_hand#2, i_product_name#11, i_brand#12, i_class#13, i_category#14, spark_grouping_id#15] +Keys [5]: [i_product_name#11, i_brand#12, i_class#13, i_category#14, spark_grouping_id#15] +Functions [1]: [partial_avg(inv_quantity_on_hand#2)] +Aggregate Attributes [2]: [sum#16, count#17] +Results [7]: [i_product_name#11, i_brand#12, i_class#13, i_category#14, spark_grouping_id#15, sum#18, count#19] + +(20) Exchange +Input [7]: [i_product_name#11, i_brand#12, i_class#13, i_category#14, spark_grouping_id#15, sum#18, count#19] +Arguments: hashpartitioning(i_product_name#11, i_brand#12, i_class#13, i_category#14, spark_grouping_id#15, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(21) HashAggregate [codegen id : 5] +Input [7]: [i_product_name#11, i_brand#12, i_class#13, i_category#14, spark_grouping_id#15, sum#18, count#19] +Keys [5]: [i_product_name#11, i_brand#12, i_class#13, i_category#14, spark_grouping_id#15] +Functions [1]: [avg(inv_quantity_on_hand#2)] +Aggregate Attributes [1]: [avg(inv_quantity_on_hand#2)#20] +Results [5]: [i_product_name#11, i_brand#12, i_class#13, i_category#14, avg(inv_quantity_on_hand#2)#20 AS qoh#21] + +(22) TakeOrderedAndProject +Input [5]: [i_product_name#11, i_brand#12, i_class#13, i_category#14, qoh#21] +Arguments: 100, [qoh#21 ASC NULLS FIRST, i_product_name#11 ASC NULLS FIRST, i_brand#12 ASC NULLS FIRST, i_class#13 ASC NULLS FIRST, i_category#14 ASC NULLS FIRST], [i_product_name#11, i_brand#12, i_class#13, i_category#14, qoh#21] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = inv_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (27) ++- * ColumnarToRow (26) + +- CometProject (25) + +- CometFilter (24) + +- CometScan parquet spark_catalog.default.date_dim (23) + + +(23) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#5, d_month_seq#22] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)] +ReadSchema: struct + +(24) CometFilter +Input [2]: [d_date_sk#5, d_month_seq#22] +Condition : (((isnotnull(d_month_seq#22) AND (d_month_seq#22 >= 1200)) AND (d_month_seq#22 <= 1211)) AND isnotnull(d_date_sk#5)) + +(25) CometProject +Input [2]: [d_date_sk#5, d_month_seq#22] +Arguments: [d_date_sk#5], [d_date_sk#5] + +(26) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#5] + +(27) BroadcastExchange +Input [1]: [d_date_sk#5] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22/simplified.txt new file mode 100644 index 0000000000..63a428d4e4 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22/simplified.txt @@ -0,0 +1,41 @@ +TakeOrderedAndProject [qoh,i_product_name,i_brand,i_class,i_category] + WholeStageCodegen (5) + HashAggregate [i_product_name,i_brand,i_class,i_category,spark_grouping_id,sum,count] [avg(inv_quantity_on_hand),qoh,sum,count] + InputAdapter + Exchange [i_product_name,i_brand,i_class,i_category,spark_grouping_id] #1 + WholeStageCodegen (4) + HashAggregate [i_product_name,i_brand,i_class,i_category,spark_grouping_id,inv_quantity_on_hand] [sum,count,sum,count] + Expand [inv_quantity_on_hand,i_product_name,i_brand,i_class,i_category] + Project [inv_quantity_on_hand,i_product_name,i_brand,i_class,i_category] + BroadcastNestedLoopJoin + Project [inv_quantity_on_hand,i_brand,i_class,i_category,i_product_name] + BroadcastHashJoin [inv_item_sk,i_item_sk] + Project [inv_item_sk,inv_quantity_on_hand] + BroadcastHashJoin [inv_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [inv_item_sk] + CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_quantity_on_hand,inv_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_month_seq,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_class,i_category,i_product_name] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.warehouse diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22a/explain.txt new file mode 100644 index 0000000000..1e5f5c2f7b --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22a/explain.txt @@ -0,0 +1,315 @@ +== Physical Plan == +TakeOrderedAndProject (45) ++- Union (44) + :- * HashAggregate (23) + : +- * HashAggregate (22) + : +- * HashAggregate (21) + : +- Exchange (20) + : +- * HashAggregate (19) + : +- * Project (18) + : +- * BroadcastHashJoin Inner BuildRight (17) + : :- * Project (12) + : : +- * BroadcastHashJoin Inner BuildRight (11) + : : :- * Project (6) + : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.inventory (1) + : : : +- ReusedExchange (4) + : : +- BroadcastExchange (10) + : : +- * ColumnarToRow (9) + : : +- CometFilter (8) + : : +- CometScan parquet spark_catalog.default.item (7) + : +- BroadcastExchange (16) + : +- * ColumnarToRow (15) + : +- CometFilter (14) + : +- CometScan parquet spark_catalog.default.warehouse (13) + :- * HashAggregate (28) + : +- Exchange (27) + : +- * HashAggregate (26) + : +- * HashAggregate (25) + : +- ReusedExchange (24) + :- * HashAggregate (33) + : +- Exchange (32) + : +- * HashAggregate (31) + : +- * HashAggregate (30) + : +- ReusedExchange (29) + :- * HashAggregate (38) + : +- Exchange (37) + : +- * HashAggregate (36) + : +- * HashAggregate (35) + : +- ReusedExchange (34) + +- * HashAggregate (43) + +- Exchange (42) + +- * HashAggregate (41) + +- * HashAggregate (40) + +- ReusedExchange (39) + + +(1) Scan parquet spark_catalog.default.inventory +Output [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(inv_date_sk#4), dynamicpruningexpression(inv_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(inv_item_sk), IsNotNull(inv_warehouse_sk)] +ReadSchema: struct + +(2) CometFilter +Input [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] +Condition : (isnotnull(inv_item_sk#1) AND isnotnull(inv_warehouse_sk#2)) + +(3) ColumnarToRow [codegen id : 4] +Input [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] + +(4) ReusedExchange [Reuses operator id: 50] +Output [1]: [d_date_sk#6] + +(5) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [inv_date_sk#4] +Right keys [1]: [d_date_sk#6] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 4] +Output [3]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3] +Input [5]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4, d_date_sk#6] + +(7) Scan parquet spark_catalog.default.item +Output [5]: [i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(8) CometFilter +Input [5]: [i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11] +Condition : isnotnull(i_item_sk#7) + +(9) ColumnarToRow [codegen id : 2] +Input [5]: [i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11] + +(10) BroadcastExchange +Input [5]: [i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(11) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [inv_item_sk#1] +Right keys [1]: [i_item_sk#7] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 4] +Output [6]: [inv_warehouse_sk#2, inv_quantity_on_hand#3, i_brand#8, i_class#9, i_category#10, i_product_name#11] +Input [8]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11] + +(13) Scan parquet spark_catalog.default.warehouse +Output [1]: [w_warehouse_sk#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/warehouse] +PushedFilters: [IsNotNull(w_warehouse_sk)] +ReadSchema: struct + +(14) CometFilter +Input [1]: [w_warehouse_sk#12] +Condition : isnotnull(w_warehouse_sk#12) + +(15) ColumnarToRow [codegen id : 3] +Input [1]: [w_warehouse_sk#12] + +(16) BroadcastExchange +Input [1]: [w_warehouse_sk#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(17) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [inv_warehouse_sk#2] +Right keys [1]: [w_warehouse_sk#12] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 4] +Output [5]: [inv_quantity_on_hand#3, i_brand#8, i_class#9, i_category#10, i_product_name#11] +Input [7]: [inv_warehouse_sk#2, inv_quantity_on_hand#3, i_brand#8, i_class#9, i_category#10, i_product_name#11, w_warehouse_sk#12] + +(19) HashAggregate [codegen id : 4] +Input [5]: [inv_quantity_on_hand#3, i_brand#8, i_class#9, i_category#10, i_product_name#11] +Keys [4]: [i_product_name#11, i_brand#8, i_class#9, i_category#10] +Functions [1]: [partial_avg(inv_quantity_on_hand#3)] +Aggregate Attributes [2]: [sum#13, count#14] +Results [6]: [i_product_name#11, i_brand#8, i_class#9, i_category#10, sum#15, count#16] + +(20) Exchange +Input [6]: [i_product_name#11, i_brand#8, i_class#9, i_category#10, sum#15, count#16] +Arguments: hashpartitioning(i_product_name#11, i_brand#8, i_class#9, i_category#10, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(21) HashAggregate [codegen id : 5] +Input [6]: [i_product_name#11, i_brand#8, i_class#9, i_category#10, sum#15, count#16] +Keys [4]: [i_product_name#11, i_brand#8, i_class#9, i_category#10] +Functions [1]: [avg(inv_quantity_on_hand#3)] +Aggregate Attributes [1]: [avg(inv_quantity_on_hand#3)#17] +Results [5]: [i_product_name#11, i_brand#8, i_class#9, i_category#10, avg(inv_quantity_on_hand#3)#17 AS qoh#18] + +(22) HashAggregate [codegen id : 5] +Input [5]: [i_product_name#11, i_brand#8, i_class#9, i_category#10, qoh#18] +Keys [4]: [i_product_name#11, i_brand#8, i_class#9, i_category#10] +Functions [1]: [partial_avg(qoh#18)] +Aggregate Attributes [2]: [sum#19, count#20] +Results [6]: [i_product_name#11, i_brand#8, i_class#9, i_category#10, sum#21, count#22] + +(23) HashAggregate [codegen id : 5] +Input [6]: [i_product_name#11, i_brand#8, i_class#9, i_category#10, sum#21, count#22] +Keys [4]: [i_product_name#11, i_brand#8, i_class#9, i_category#10] +Functions [1]: [avg(qoh#18)] +Aggregate Attributes [1]: [avg(qoh#18)#23] +Results [5]: [i_product_name#11 AS i_product_name#24, i_brand#8 AS i_brand#25, i_class#9 AS i_class#26, i_category#10 AS i_category#27, avg(qoh#18)#23 AS qoh#28] + +(24) ReusedExchange [Reuses operator id: 20] +Output [6]: [i_product_name#29, i_brand#30, i_class#31, i_category#32, sum#33, count#34] + +(25) HashAggregate [codegen id : 10] +Input [6]: [i_product_name#29, i_brand#30, i_class#31, i_category#32, sum#33, count#34] +Keys [4]: [i_product_name#29, i_brand#30, i_class#31, i_category#32] +Functions [1]: [avg(inv_quantity_on_hand#35)] +Aggregate Attributes [1]: [avg(inv_quantity_on_hand#35)#17] +Results [4]: [i_product_name#29, i_brand#30, i_class#31, avg(inv_quantity_on_hand#35)#17 AS qoh#36] + +(26) HashAggregate [codegen id : 10] +Input [4]: [i_product_name#29, i_brand#30, i_class#31, qoh#36] +Keys [3]: [i_product_name#29, i_brand#30, i_class#31] +Functions [1]: [partial_avg(qoh#36)] +Aggregate Attributes [2]: [sum#37, count#38] +Results [5]: [i_product_name#29, i_brand#30, i_class#31, sum#39, count#40] + +(27) Exchange +Input [5]: [i_product_name#29, i_brand#30, i_class#31, sum#39, count#40] +Arguments: hashpartitioning(i_product_name#29, i_brand#30, i_class#31, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(28) HashAggregate [codegen id : 11] +Input [5]: [i_product_name#29, i_brand#30, i_class#31, sum#39, count#40] +Keys [3]: [i_product_name#29, i_brand#30, i_class#31] +Functions [1]: [avg(qoh#36)] +Aggregate Attributes [1]: [avg(qoh#36)#41] +Results [5]: [i_product_name#29, i_brand#30, i_class#31, null AS i_category#42, avg(qoh#36)#41 AS qoh#43] + +(29) ReusedExchange [Reuses operator id: 20] +Output [6]: [i_product_name#44, i_brand#45, i_class#46, i_category#47, sum#48, count#49] + +(30) HashAggregate [codegen id : 16] +Input [6]: [i_product_name#44, i_brand#45, i_class#46, i_category#47, sum#48, count#49] +Keys [4]: [i_product_name#44, i_brand#45, i_class#46, i_category#47] +Functions [1]: [avg(inv_quantity_on_hand#50)] +Aggregate Attributes [1]: [avg(inv_quantity_on_hand#50)#17] +Results [3]: [i_product_name#44, i_brand#45, avg(inv_quantity_on_hand#50)#17 AS qoh#51] + +(31) HashAggregate [codegen id : 16] +Input [3]: [i_product_name#44, i_brand#45, qoh#51] +Keys [2]: [i_product_name#44, i_brand#45] +Functions [1]: [partial_avg(qoh#51)] +Aggregate Attributes [2]: [sum#52, count#53] +Results [4]: [i_product_name#44, i_brand#45, sum#54, count#55] + +(32) Exchange +Input [4]: [i_product_name#44, i_brand#45, sum#54, count#55] +Arguments: hashpartitioning(i_product_name#44, i_brand#45, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(33) HashAggregate [codegen id : 17] +Input [4]: [i_product_name#44, i_brand#45, sum#54, count#55] +Keys [2]: [i_product_name#44, i_brand#45] +Functions [1]: [avg(qoh#51)] +Aggregate Attributes [1]: [avg(qoh#51)#56] +Results [5]: [i_product_name#44, i_brand#45, null AS i_class#57, null AS i_category#58, avg(qoh#51)#56 AS qoh#59] + +(34) ReusedExchange [Reuses operator id: 20] +Output [6]: [i_product_name#60, i_brand#61, i_class#62, i_category#63, sum#64, count#65] + +(35) HashAggregate [codegen id : 22] +Input [6]: [i_product_name#60, i_brand#61, i_class#62, i_category#63, sum#64, count#65] +Keys [4]: [i_product_name#60, i_brand#61, i_class#62, i_category#63] +Functions [1]: [avg(inv_quantity_on_hand#66)] +Aggregate Attributes [1]: [avg(inv_quantity_on_hand#66)#17] +Results [2]: [i_product_name#60, avg(inv_quantity_on_hand#66)#17 AS qoh#67] + +(36) HashAggregate [codegen id : 22] +Input [2]: [i_product_name#60, qoh#67] +Keys [1]: [i_product_name#60] +Functions [1]: [partial_avg(qoh#67)] +Aggregate Attributes [2]: [sum#68, count#69] +Results [3]: [i_product_name#60, sum#70, count#71] + +(37) Exchange +Input [3]: [i_product_name#60, sum#70, count#71] +Arguments: hashpartitioning(i_product_name#60, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(38) HashAggregate [codegen id : 23] +Input [3]: [i_product_name#60, sum#70, count#71] +Keys [1]: [i_product_name#60] +Functions [1]: [avg(qoh#67)] +Aggregate Attributes [1]: [avg(qoh#67)#72] +Results [5]: [i_product_name#60, null AS i_brand#73, null AS i_class#74, null AS i_category#75, avg(qoh#67)#72 AS qoh#76] + +(39) ReusedExchange [Reuses operator id: 20] +Output [6]: [i_product_name#77, i_brand#78, i_class#79, i_category#80, sum#81, count#82] + +(40) HashAggregate [codegen id : 28] +Input [6]: [i_product_name#77, i_brand#78, i_class#79, i_category#80, sum#81, count#82] +Keys [4]: [i_product_name#77, i_brand#78, i_class#79, i_category#80] +Functions [1]: [avg(inv_quantity_on_hand#83)] +Aggregate Attributes [1]: [avg(inv_quantity_on_hand#83)#17] +Results [1]: [avg(inv_quantity_on_hand#83)#17 AS qoh#84] + +(41) HashAggregate [codegen id : 28] +Input [1]: [qoh#84] +Keys: [] +Functions [1]: [partial_avg(qoh#84)] +Aggregate Attributes [2]: [sum#85, count#86] +Results [2]: [sum#87, count#88] + +(42) Exchange +Input [2]: [sum#87, count#88] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=7] + +(43) HashAggregate [codegen id : 29] +Input [2]: [sum#87, count#88] +Keys: [] +Functions [1]: [avg(qoh#84)] +Aggregate Attributes [1]: [avg(qoh#84)#89] +Results [5]: [null AS i_product_name#90, null AS i_brand#91, null AS i_class#92, null AS i_category#93, avg(qoh#84)#89 AS qoh#94] + +(44) Union + +(45) TakeOrderedAndProject +Input [5]: [i_product_name#24, i_brand#25, i_class#26, i_category#27, qoh#28] +Arguments: 100, [qoh#28 ASC NULLS FIRST, i_product_name#24 ASC NULLS FIRST, i_brand#25 ASC NULLS FIRST, i_class#26 ASC NULLS FIRST, i_category#27 ASC NULLS FIRST], [i_product_name#24, i_brand#25, i_class#26, i_category#27, qoh#28] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = inv_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (50) ++- * ColumnarToRow (49) + +- CometProject (48) + +- CometFilter (47) + +- CometScan parquet spark_catalog.default.date_dim (46) + + +(46) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#6, d_month_seq#95] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1212), LessThanOrEqual(d_month_seq,1223), IsNotNull(d_date_sk)] +ReadSchema: struct + +(47) CometFilter +Input [2]: [d_date_sk#6, d_month_seq#95] +Condition : (((isnotnull(d_month_seq#95) AND (d_month_seq#95 >= 1212)) AND (d_month_seq#95 <= 1223)) AND isnotnull(d_date_sk#6)) + +(48) CometProject +Input [2]: [d_date_sk#6, d_month_seq#95] +Arguments: [d_date_sk#6], [d_date_sk#6] + +(49) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#6] + +(50) BroadcastExchange +Input [1]: [d_date_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22a/simplified.txt new file mode 100644 index 0000000000..3aa0745ad7 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22a/simplified.txt @@ -0,0 +1,80 @@ +TakeOrderedAndProject [qoh,i_product_name,i_brand,i_class,i_category] + Union + WholeStageCodegen (5) + HashAggregate [i_product_name,i_brand,i_class,i_category,sum,count] [avg(qoh),i_product_name,i_brand,i_class,i_category,qoh,sum,count] + HashAggregate [i_product_name,i_brand,i_class,i_category,qoh] [sum,count,sum,count] + HashAggregate [i_product_name,i_brand,i_class,i_category,sum,count] [avg(inv_quantity_on_hand),qoh,sum,count] + InputAdapter + Exchange [i_product_name,i_brand,i_class,i_category] #1 + WholeStageCodegen (4) + HashAggregate [i_product_name,i_brand,i_class,i_category,inv_quantity_on_hand] [sum,count,sum,count] + Project [inv_quantity_on_hand,i_brand,i_class,i_category,i_product_name] + BroadcastHashJoin [inv_warehouse_sk,w_warehouse_sk] + Project [inv_warehouse_sk,inv_quantity_on_hand,i_brand,i_class,i_category,i_product_name] + BroadcastHashJoin [inv_item_sk,i_item_sk] + Project [inv_item_sk,inv_warehouse_sk,inv_quantity_on_hand] + BroadcastHashJoin [inv_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [inv_item_sk,inv_warehouse_sk] + CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_month_seq,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_class,i_category,i_product_name] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometFilter [w_warehouse_sk] + CometScan parquet spark_catalog.default.warehouse [w_warehouse_sk] + WholeStageCodegen (11) + HashAggregate [i_product_name,i_brand,i_class,sum,count] [avg(qoh),i_category,qoh,sum,count] + InputAdapter + Exchange [i_product_name,i_brand,i_class] #5 + WholeStageCodegen (10) + HashAggregate [i_product_name,i_brand,i_class,qoh] [sum,count,sum,count] + HashAggregate [i_product_name,i_brand,i_class,i_category,sum,count] [avg(inv_quantity_on_hand),qoh,sum,count] + InputAdapter + ReusedExchange [i_product_name,i_brand,i_class,i_category,sum,count] #1 + WholeStageCodegen (17) + HashAggregate [i_product_name,i_brand,sum,count] [avg(qoh),i_class,i_category,qoh,sum,count] + InputAdapter + Exchange [i_product_name,i_brand] #6 + WholeStageCodegen (16) + HashAggregate [i_product_name,i_brand,qoh] [sum,count,sum,count] + HashAggregate [i_product_name,i_brand,i_class,i_category,sum,count] [avg(inv_quantity_on_hand),qoh,sum,count] + InputAdapter + ReusedExchange [i_product_name,i_brand,i_class,i_category,sum,count] #1 + WholeStageCodegen (23) + HashAggregate [i_product_name,sum,count] [avg(qoh),i_brand,i_class,i_category,qoh,sum,count] + InputAdapter + Exchange [i_product_name] #7 + WholeStageCodegen (22) + HashAggregate [i_product_name,qoh] [sum,count,sum,count] + HashAggregate [i_product_name,i_brand,i_class,i_category,sum,count] [avg(inv_quantity_on_hand),qoh,sum,count] + InputAdapter + ReusedExchange [i_product_name,i_brand,i_class,i_category,sum,count] #1 + WholeStageCodegen (29) + HashAggregate [sum,count] [avg(qoh),i_product_name,i_brand,i_class,i_category,qoh,sum,count] + InputAdapter + Exchange #8 + WholeStageCodegen (28) + HashAggregate [qoh] [sum,count,sum,count] + HashAggregate [i_product_name,i_brand,i_class,i_category,sum,count] [avg(inv_quantity_on_hand),qoh,sum,count] + InputAdapter + ReusedExchange [i_product_name,i_brand,i_class,i_category,sum,count] #1 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q24/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q24/explain.txt new file mode 100644 index 0000000000..0cba9b0599 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q24/explain.txt @@ -0,0 +1,437 @@ +== Physical Plan == +* Sort (48) ++- Exchange (47) + +- * Filter (46) + +- * HashAggregate (45) + +- Exchange (44) + +- * HashAggregate (43) + +- * HashAggregate (42) + +- Exchange (41) + +- * HashAggregate (40) + +- * Project (39) + +- * BroadcastHashJoin Inner BuildRight (38) + :- * Project (33) + : +- * BroadcastHashJoin Inner BuildRight (32) + : :- * Project (27) + : : +- * BroadcastHashJoin Inner BuildRight (26) + : : :- * Project (21) + : : : +- * BroadcastHashJoin Inner BuildRight (20) + : : : :- * Project (14) + : : : : +- * SortMergeJoin Inner (13) + : : : : :- * Sort (6) + : : : : : +- Exchange (5) + : : : : : +- * ColumnarToRow (4) + : : : : : +- CometProject (3) + : : : : : +- CometFilter (2) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : +- * Sort (12) + : : : : +- Exchange (11) + : : : : +- * ColumnarToRow (10) + : : : : +- CometProject (9) + : : : : +- CometFilter (8) + : : : : +- CometScan parquet spark_catalog.default.store_returns (7) + : : : +- BroadcastExchange (19) + : : : +- * ColumnarToRow (18) + : : : +- CometProject (17) + : : : +- CometFilter (16) + : : : +- CometScan parquet spark_catalog.default.store (15) + : : +- BroadcastExchange (25) + : : +- * ColumnarToRow (24) + : : +- CometFilter (23) + : : +- CometScan parquet spark_catalog.default.item (22) + : +- BroadcastExchange (31) + : +- * ColumnarToRow (30) + : +- CometFilter (29) + : +- CometScan parquet spark_catalog.default.customer (28) + +- BroadcastExchange (37) + +- * ColumnarToRow (36) + +- CometFilter (35) + +- CometScan parquet spark_catalog.default.customer_address (34) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, ss_sold_date_sk#6] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_ticket_number), IsNotNull(ss_item_sk), IsNotNull(ss_store_sk), IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(2) CometFilter +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, ss_sold_date_sk#6] +Condition : (((isnotnull(ss_ticket_number#4) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_store_sk#3)) AND isnotnull(ss_customer_sk#2)) + +(3) CometProject +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, ss_sold_date_sk#6] +Arguments: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5], [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5] + +(4) ColumnarToRow [codegen id : 1] +Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5] + +(5) Exchange +Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5] +Arguments: hashpartitioning(ss_ticket_number#4, ss_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(6) Sort [codegen id : 2] +Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5] +Arguments: [ss_ticket_number#4 ASC NULLS FIRST, ss_item_sk#1 ASC NULLS FIRST], false, 0 + +(7) Scan parquet spark_catalog.default.store_returns +Output [3]: [sr_item_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_returns] +PushedFilters: [IsNotNull(sr_ticket_number), IsNotNull(sr_item_sk)] +ReadSchema: struct + +(8) CometFilter +Input [3]: [sr_item_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] +Condition : (isnotnull(sr_ticket_number#8) AND isnotnull(sr_item_sk#7)) + +(9) CometProject +Input [3]: [sr_item_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] +Arguments: [sr_item_sk#7, sr_ticket_number#8], [sr_item_sk#7, sr_ticket_number#8] + +(10) ColumnarToRow [codegen id : 3] +Input [2]: [sr_item_sk#7, sr_ticket_number#8] + +(11) Exchange +Input [2]: [sr_item_sk#7, sr_ticket_number#8] +Arguments: hashpartitioning(sr_ticket_number#8, sr_item_sk#7, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(12) Sort [codegen id : 4] +Input [2]: [sr_item_sk#7, sr_ticket_number#8] +Arguments: [sr_ticket_number#8 ASC NULLS FIRST, sr_item_sk#7 ASC NULLS FIRST], false, 0 + +(13) SortMergeJoin [codegen id : 9] +Left keys [2]: [ss_ticket_number#4, ss_item_sk#1] +Right keys [2]: [sr_ticket_number#8, sr_item_sk#7] +Join type: Inner +Join condition: None + +(14) Project [codegen id : 9] +Output [4]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_net_paid#5] +Input [7]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, sr_item_sk#7, sr_ticket_number#8] + +(15) Scan parquet spark_catalog.default.store +Output [5]: [s_store_sk#10, s_store_name#11, s_market_id#12, s_state#13, s_zip#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_market_id), EqualTo(s_market_id,8), IsNotNull(s_store_sk), IsNotNull(s_zip)] +ReadSchema: struct + +(16) CometFilter +Input [5]: [s_store_sk#10, s_store_name#11, s_market_id#12, s_state#13, s_zip#14] +Condition : (((isnotnull(s_market_id#12) AND (s_market_id#12 = 8)) AND isnotnull(s_store_sk#10)) AND isnotnull(s_zip#14)) + +(17) CometProject +Input [5]: [s_store_sk#10, s_store_name#11, s_market_id#12, s_state#13, s_zip#14] +Arguments: [s_store_sk#10, s_store_name#11, s_state#13, s_zip#14], [s_store_sk#10, s_store_name#11, s_state#13, s_zip#14] + +(18) ColumnarToRow [codegen id : 5] +Input [4]: [s_store_sk#10, s_store_name#11, s_state#13, s_zip#14] + +(19) BroadcastExchange +Input [4]: [s_store_sk#10, s_store_name#11, s_state#13, s_zip#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(20) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_store_sk#3] +Right keys [1]: [s_store_sk#10] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 9] +Output [6]: [ss_item_sk#1, ss_customer_sk#2, ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14] +Input [8]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_net_paid#5, s_store_sk#10, s_store_name#11, s_state#13, s_zip#14] + +(22) Scan parquet spark_catalog.default.item +Output [6]: [i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_color), EqualTo(i_color,pale ), IsNotNull(i_item_sk)] +ReadSchema: struct + +(23) CometFilter +Input [6]: [i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] +Condition : ((isnotnull(i_color#18) AND (i_color#18 = pale )) AND isnotnull(i_item_sk#15)) + +(24) ColumnarToRow [codegen id : 6] +Input [6]: [i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] + +(25) BroadcastExchange +Input [6]: [i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(26) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#15] +Join type: Inner +Join condition: None + +(27) Project [codegen id : 9] +Output [10]: [ss_customer_sk#2, ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] +Input [12]: [ss_item_sk#1, ss_customer_sk#2, ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14, i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] + +(28) Scan parquet spark_catalog.default.customer +Output [5]: [c_customer_sk#21, c_current_addr_sk#22, c_first_name#23, c_last_name#24, c_birth_country#25] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_current_addr_sk), IsNotNull(c_birth_country)] +ReadSchema: struct + +(29) CometFilter +Input [5]: [c_customer_sk#21, c_current_addr_sk#22, c_first_name#23, c_last_name#24, c_birth_country#25] +Condition : ((isnotnull(c_customer_sk#21) AND isnotnull(c_current_addr_sk#22)) AND isnotnull(c_birth_country#25)) + +(30) ColumnarToRow [codegen id : 7] +Input [5]: [c_customer_sk#21, c_current_addr_sk#22, c_first_name#23, c_last_name#24, c_birth_country#25] + +(31) BroadcastExchange +Input [5]: [c_customer_sk#21, c_current_addr_sk#22, c_first_name#23, c_last_name#24, c_birth_country#25] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(32) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_customer_sk#2] +Right keys [1]: [c_customer_sk#21] +Join type: Inner +Join condition: None + +(33) Project [codegen id : 9] +Output [13]: [ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20, c_current_addr_sk#22, c_first_name#23, c_last_name#24, c_birth_country#25] +Input [15]: [ss_customer_sk#2, ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20, c_customer_sk#21, c_current_addr_sk#22, c_first_name#23, c_last_name#24, c_birth_country#25] + +(34) Scan parquet spark_catalog.default.customer_address +Output [4]: [ca_address_sk#26, ca_state#27, ca_zip#28, ca_country#29] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk), IsNotNull(ca_country), IsNotNull(ca_zip)] +ReadSchema: struct + +(35) CometFilter +Input [4]: [ca_address_sk#26, ca_state#27, ca_zip#28, ca_country#29] +Condition : ((isnotnull(ca_address_sk#26) AND isnotnull(ca_country#29)) AND isnotnull(ca_zip#28)) + +(36) ColumnarToRow [codegen id : 8] +Input [4]: [ca_address_sk#26, ca_state#27, ca_zip#28, ca_country#29] + +(37) BroadcastExchange +Input [4]: [ca_address_sk#26, ca_state#27, ca_zip#28, ca_country#29] +Arguments: HashedRelationBroadcastMode(List(input[0, int, false], upper(input[3, string, false]), input[2, string, false]),false), [plan_id=6] + +(38) BroadcastHashJoin [codegen id : 9] +Left keys [3]: [c_current_addr_sk#22, c_birth_country#25, s_zip#14] +Right keys [3]: [ca_address_sk#26, upper(ca_country#29), ca_zip#28] +Join type: Inner +Join condition: None + +(39) Project [codegen id : 9] +Output [11]: [ss_net_paid#5, s_store_name#11, s_state#13, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20, c_first_name#23, c_last_name#24, ca_state#27] +Input [17]: [ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20, c_current_addr_sk#22, c_first_name#23, c_last_name#24, c_birth_country#25, ca_address_sk#26, ca_state#27, ca_zip#28, ca_country#29] + +(40) HashAggregate [codegen id : 9] +Input [11]: [ss_net_paid#5, s_store_name#11, s_state#13, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20, c_first_name#23, c_last_name#24, ca_state#27] +Keys [10]: [c_last_name#24, c_first_name#23, s_store_name#11, ca_state#27, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17] +Functions [1]: [partial_sum(UnscaledValue(ss_net_paid#5))] +Aggregate Attributes [1]: [sum#30] +Results [11]: [c_last_name#24, c_first_name#23, s_store_name#11, ca_state#27, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17, sum#31] + +(41) Exchange +Input [11]: [c_last_name#24, c_first_name#23, s_store_name#11, ca_state#27, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17, sum#31] +Arguments: hashpartitioning(c_last_name#24, c_first_name#23, s_store_name#11, ca_state#27, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(42) HashAggregate [codegen id : 10] +Input [11]: [c_last_name#24, c_first_name#23, s_store_name#11, ca_state#27, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17, sum#31] +Keys [10]: [c_last_name#24, c_first_name#23, s_store_name#11, ca_state#27, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17] +Functions [1]: [sum(UnscaledValue(ss_net_paid#5))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_paid#5))#32] +Results [4]: [c_last_name#24, c_first_name#23, s_store_name#11, MakeDecimal(sum(UnscaledValue(ss_net_paid#5))#32,17,2) AS netpaid#33] + +(43) HashAggregate [codegen id : 10] +Input [4]: [c_last_name#24, c_first_name#23, s_store_name#11, netpaid#33] +Keys [3]: [c_last_name#24, c_first_name#23, s_store_name#11] +Functions [1]: [partial_sum(netpaid#33)] +Aggregate Attributes [2]: [sum#34, isEmpty#35] +Results [5]: [c_last_name#24, c_first_name#23, s_store_name#11, sum#36, isEmpty#37] + +(44) Exchange +Input [5]: [c_last_name#24, c_first_name#23, s_store_name#11, sum#36, isEmpty#37] +Arguments: hashpartitioning(c_last_name#24, c_first_name#23, s_store_name#11, 5), ENSURE_REQUIREMENTS, [plan_id=8] + +(45) HashAggregate [codegen id : 11] +Input [5]: [c_last_name#24, c_first_name#23, s_store_name#11, sum#36, isEmpty#37] +Keys [3]: [c_last_name#24, c_first_name#23, s_store_name#11] +Functions [1]: [sum(netpaid#33)] +Aggregate Attributes [1]: [sum(netpaid#33)#38] +Results [4]: [c_last_name#24, c_first_name#23, s_store_name#11, sum(netpaid#33)#38 AS paid#39] + +(46) Filter [codegen id : 11] +Input [4]: [c_last_name#24, c_first_name#23, s_store_name#11, paid#39] +Condition : (isnotnull(paid#39) AND (cast(paid#39 as decimal(33,8)) > cast(Subquery scalar-subquery#40, [id=#41] as decimal(33,8)))) + +(47) Exchange +Input [4]: [c_last_name#24, c_first_name#23, s_store_name#11, paid#39] +Arguments: rangepartitioning(c_last_name#24 ASC NULLS FIRST, c_first_name#23 ASC NULLS FIRST, s_store_name#11 ASC NULLS FIRST, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(48) Sort [codegen id : 12] +Input [4]: [c_last_name#24, c_first_name#23, s_store_name#11, paid#39] +Arguments: [c_last_name#24 ASC NULLS FIRST, c_first_name#23 ASC NULLS FIRST, s_store_name#11 ASC NULLS FIRST], true, 0 + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 46 Hosting Expression = Subquery scalar-subquery#40, [id=#41] +* HashAggregate (75) ++- Exchange (74) + +- * HashAggregate (73) + +- * HashAggregate (72) + +- Exchange (71) + +- * HashAggregate (70) + +- * Project (69) + +- * BroadcastHashJoin Inner BuildRight (68) + :- * Project (66) + : +- * BroadcastHashJoin Inner BuildRight (65) + : :- * Project (63) + : : +- * BroadcastHashJoin Inner BuildRight (62) + : : :- * Project (57) + : : : +- * BroadcastHashJoin Inner BuildRight (56) + : : : :- * Project (54) + : : : : +- * SortMergeJoin Inner (53) + : : : : :- * Sort (50) + : : : : : +- ReusedExchange (49) + : : : : +- * Sort (52) + : : : : +- ReusedExchange (51) + : : : +- ReusedExchange (55) + : : +- BroadcastExchange (61) + : : +- * ColumnarToRow (60) + : : +- CometFilter (59) + : : +- CometScan parquet spark_catalog.default.item (58) + : +- ReusedExchange (64) + +- ReusedExchange (67) + + +(49) ReusedExchange [Reuses operator id: 5] +Output [5]: [ss_item_sk#42, ss_customer_sk#43, ss_store_sk#44, ss_ticket_number#45, ss_net_paid#46] + +(50) Sort [codegen id : 2] +Input [5]: [ss_item_sk#42, ss_customer_sk#43, ss_store_sk#44, ss_ticket_number#45, ss_net_paid#46] +Arguments: [ss_ticket_number#45 ASC NULLS FIRST, ss_item_sk#42 ASC NULLS FIRST], false, 0 + +(51) ReusedExchange [Reuses operator id: 11] +Output [2]: [sr_item_sk#47, sr_ticket_number#48] + +(52) Sort [codegen id : 4] +Input [2]: [sr_item_sk#47, sr_ticket_number#48] +Arguments: [sr_ticket_number#48 ASC NULLS FIRST, sr_item_sk#47 ASC NULLS FIRST], false, 0 + +(53) SortMergeJoin [codegen id : 9] +Left keys [2]: [ss_ticket_number#45, ss_item_sk#42] +Right keys [2]: [sr_ticket_number#48, sr_item_sk#47] +Join type: Inner +Join condition: None + +(54) Project [codegen id : 9] +Output [4]: [ss_item_sk#42, ss_customer_sk#43, ss_store_sk#44, ss_net_paid#46] +Input [7]: [ss_item_sk#42, ss_customer_sk#43, ss_store_sk#44, ss_ticket_number#45, ss_net_paid#46, sr_item_sk#47, sr_ticket_number#48] + +(55) ReusedExchange [Reuses operator id: 19] +Output [4]: [s_store_sk#49, s_store_name#50, s_state#51, s_zip#52] + +(56) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_store_sk#44] +Right keys [1]: [s_store_sk#49] +Join type: Inner +Join condition: None + +(57) Project [codegen id : 9] +Output [6]: [ss_item_sk#42, ss_customer_sk#43, ss_net_paid#46, s_store_name#50, s_state#51, s_zip#52] +Input [8]: [ss_item_sk#42, ss_customer_sk#43, ss_store_sk#44, ss_net_paid#46, s_store_sk#49, s_store_name#50, s_state#51, s_zip#52] + +(58) Scan parquet spark_catalog.default.item +Output [6]: [i_item_sk#53, i_current_price#54, i_size#55, i_color#56, i_units#57, i_manager_id#58] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(59) CometFilter +Input [6]: [i_item_sk#53, i_current_price#54, i_size#55, i_color#56, i_units#57, i_manager_id#58] +Condition : isnotnull(i_item_sk#53) + +(60) ColumnarToRow [codegen id : 6] +Input [6]: [i_item_sk#53, i_current_price#54, i_size#55, i_color#56, i_units#57, i_manager_id#58] + +(61) BroadcastExchange +Input [6]: [i_item_sk#53, i_current_price#54, i_size#55, i_color#56, i_units#57, i_manager_id#58] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=10] + +(62) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_item_sk#42] +Right keys [1]: [i_item_sk#53] +Join type: Inner +Join condition: None + +(63) Project [codegen id : 9] +Output [10]: [ss_customer_sk#43, ss_net_paid#46, s_store_name#50, s_state#51, s_zip#52, i_current_price#54, i_size#55, i_color#56, i_units#57, i_manager_id#58] +Input [12]: [ss_item_sk#42, ss_customer_sk#43, ss_net_paid#46, s_store_name#50, s_state#51, s_zip#52, i_item_sk#53, i_current_price#54, i_size#55, i_color#56, i_units#57, i_manager_id#58] + +(64) ReusedExchange [Reuses operator id: 31] +Output [5]: [c_customer_sk#59, c_current_addr_sk#60, c_first_name#61, c_last_name#62, c_birth_country#63] + +(65) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_customer_sk#43] +Right keys [1]: [c_customer_sk#59] +Join type: Inner +Join condition: None + +(66) Project [codegen id : 9] +Output [13]: [ss_net_paid#46, s_store_name#50, s_state#51, s_zip#52, i_current_price#54, i_size#55, i_color#56, i_units#57, i_manager_id#58, c_current_addr_sk#60, c_first_name#61, c_last_name#62, c_birth_country#63] +Input [15]: [ss_customer_sk#43, ss_net_paid#46, s_store_name#50, s_state#51, s_zip#52, i_current_price#54, i_size#55, i_color#56, i_units#57, i_manager_id#58, c_customer_sk#59, c_current_addr_sk#60, c_first_name#61, c_last_name#62, c_birth_country#63] + +(67) ReusedExchange [Reuses operator id: 37] +Output [4]: [ca_address_sk#64, ca_state#65, ca_zip#66, ca_country#67] + +(68) BroadcastHashJoin [codegen id : 9] +Left keys [3]: [c_current_addr_sk#60, c_birth_country#63, s_zip#52] +Right keys [3]: [ca_address_sk#64, upper(ca_country#67), ca_zip#66] +Join type: Inner +Join condition: None + +(69) Project [codegen id : 9] +Output [11]: [ss_net_paid#46, s_store_name#50, s_state#51, i_current_price#54, i_size#55, i_color#56, i_units#57, i_manager_id#58, c_first_name#61, c_last_name#62, ca_state#65] +Input [17]: [ss_net_paid#46, s_store_name#50, s_state#51, s_zip#52, i_current_price#54, i_size#55, i_color#56, i_units#57, i_manager_id#58, c_current_addr_sk#60, c_first_name#61, c_last_name#62, c_birth_country#63, ca_address_sk#64, ca_state#65, ca_zip#66, ca_country#67] + +(70) HashAggregate [codegen id : 9] +Input [11]: [ss_net_paid#46, s_store_name#50, s_state#51, i_current_price#54, i_size#55, i_color#56, i_units#57, i_manager_id#58, c_first_name#61, c_last_name#62, ca_state#65] +Keys [10]: [c_last_name#62, c_first_name#61, s_store_name#50, ca_state#65, s_state#51, i_color#56, i_current_price#54, i_manager_id#58, i_units#57, i_size#55] +Functions [1]: [partial_sum(UnscaledValue(ss_net_paid#46))] +Aggregate Attributes [1]: [sum#68] +Results [11]: [c_last_name#62, c_first_name#61, s_store_name#50, ca_state#65, s_state#51, i_color#56, i_current_price#54, i_manager_id#58, i_units#57, i_size#55, sum#69] + +(71) Exchange +Input [11]: [c_last_name#62, c_first_name#61, s_store_name#50, ca_state#65, s_state#51, i_color#56, i_current_price#54, i_manager_id#58, i_units#57, i_size#55, sum#69] +Arguments: hashpartitioning(c_last_name#62, c_first_name#61, s_store_name#50, ca_state#65, s_state#51, i_color#56, i_current_price#54, i_manager_id#58, i_units#57, i_size#55, 5), ENSURE_REQUIREMENTS, [plan_id=11] + +(72) HashAggregate [codegen id : 10] +Input [11]: [c_last_name#62, c_first_name#61, s_store_name#50, ca_state#65, s_state#51, i_color#56, i_current_price#54, i_manager_id#58, i_units#57, i_size#55, sum#69] +Keys [10]: [c_last_name#62, c_first_name#61, s_store_name#50, ca_state#65, s_state#51, i_color#56, i_current_price#54, i_manager_id#58, i_units#57, i_size#55] +Functions [1]: [sum(UnscaledValue(ss_net_paid#46))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_paid#46))#32] +Results [1]: [MakeDecimal(sum(UnscaledValue(ss_net_paid#46))#32,17,2) AS netpaid#70] + +(73) HashAggregate [codegen id : 10] +Input [1]: [netpaid#70] +Keys: [] +Functions [1]: [partial_avg(netpaid#70)] +Aggregate Attributes [2]: [sum#71, count#72] +Results [2]: [sum#73, count#74] + +(74) Exchange +Input [2]: [sum#73, count#74] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=12] + +(75) HashAggregate [codegen id : 11] +Input [2]: [sum#73, count#74] +Keys: [] +Functions [1]: [avg(netpaid#70)] +Aggregate Attributes [1]: [avg(netpaid#70)#75] +Results [1]: [(0.05 * avg(netpaid#70)#75) AS (0.05 * avg(netpaid))#76] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q24/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q24/simplified.txt new file mode 100644 index 0000000000..7024f439fc --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q24/simplified.txt @@ -0,0 +1,122 @@ +WholeStageCodegen (12) + Sort [c_last_name,c_first_name,s_store_name] + InputAdapter + Exchange [c_last_name,c_first_name,s_store_name] #1 + WholeStageCodegen (11) + Filter [paid] + Subquery #1 + WholeStageCodegen (11) + HashAggregate [sum,count] [avg(netpaid),(0.05 * avg(netpaid)),sum,count] + InputAdapter + Exchange #10 + WholeStageCodegen (10) + HashAggregate [netpaid] [sum,count,sum,count] + HashAggregate [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size,sum] [sum(UnscaledValue(ss_net_paid)),netpaid,sum] + InputAdapter + Exchange [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size] #11 + WholeStageCodegen (9) + HashAggregate [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size,ss_net_paid] [sum,sum] + Project [ss_net_paid,s_store_name,s_state,i_current_price,i_size,i_color,i_units,i_manager_id,c_first_name,c_last_name,ca_state] + BroadcastHashJoin [c_current_addr_sk,c_birth_country,s_zip,ca_address_sk,ca_country,ca_zip] + Project [ss_net_paid,s_store_name,s_state,s_zip,i_current_price,i_size,i_color,i_units,i_manager_id,c_current_addr_sk,c_first_name,c_last_name,c_birth_country] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Project [ss_customer_sk,ss_net_paid,s_store_name,s_state,s_zip,i_current_price,i_size,i_color,i_units,i_manager_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_customer_sk,ss_net_paid,s_store_name,s_state,s_zip] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_customer_sk,ss_store_sk,ss_net_paid] + SortMergeJoin [ss_ticket_number,ss_item_sk,sr_ticket_number,sr_item_sk] + InputAdapter + WholeStageCodegen (2) + Sort [ss_ticket_number,ss_item_sk] + InputAdapter + ReusedExchange [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_net_paid] #4 + InputAdapter + WholeStageCodegen (4) + Sort [sr_ticket_number,sr_item_sk] + InputAdapter + ReusedExchange [sr_item_sk,sr_ticket_number] #5 + InputAdapter + ReusedExchange [s_store_sk,s_store_name,s_state,s_zip] #6 + InputAdapter + BroadcastExchange #12 + WholeStageCodegen (6) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price,i_size,i_color,i_units,i_manager_id] + InputAdapter + ReusedExchange [c_customer_sk,c_current_addr_sk,c_first_name,c_last_name,c_birth_country] #8 + InputAdapter + ReusedExchange [ca_address_sk,ca_state,ca_zip,ca_country] #9 + HashAggregate [c_last_name,c_first_name,s_store_name,sum,isEmpty] [sum(netpaid),paid,sum,isEmpty] + InputAdapter + Exchange [c_last_name,c_first_name,s_store_name] #2 + WholeStageCodegen (10) + HashAggregate [c_last_name,c_first_name,s_store_name,netpaid] [sum,isEmpty,sum,isEmpty] + HashAggregate [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size,sum] [sum(UnscaledValue(ss_net_paid)),netpaid,sum] + InputAdapter + Exchange [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size] #3 + WholeStageCodegen (9) + HashAggregate [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size,ss_net_paid] [sum,sum] + Project [ss_net_paid,s_store_name,s_state,i_current_price,i_size,i_color,i_units,i_manager_id,c_first_name,c_last_name,ca_state] + BroadcastHashJoin [c_current_addr_sk,c_birth_country,s_zip,ca_address_sk,ca_country,ca_zip] + Project [ss_net_paid,s_store_name,s_state,s_zip,i_current_price,i_size,i_color,i_units,i_manager_id,c_current_addr_sk,c_first_name,c_last_name,c_birth_country] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Project [ss_customer_sk,ss_net_paid,s_store_name,s_state,s_zip,i_current_price,i_size,i_color,i_units,i_manager_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_customer_sk,ss_net_paid,s_store_name,s_state,s_zip] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_customer_sk,ss_store_sk,ss_net_paid] + SortMergeJoin [ss_ticket_number,ss_item_sk,sr_ticket_number,sr_item_sk] + InputAdapter + WholeStageCodegen (2) + Sort [ss_ticket_number,ss_item_sk] + InputAdapter + Exchange [ss_ticket_number,ss_item_sk] #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_net_paid] + CometFilter [ss_ticket_number,ss_item_sk,ss_store_sk,ss_customer_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_net_paid,ss_sold_date_sk] + InputAdapter + WholeStageCodegen (4) + Sort [sr_ticket_number,sr_item_sk] + InputAdapter + Exchange [sr_ticket_number,sr_item_sk] #5 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometProject [sr_item_sk,sr_ticket_number] + CometFilter [sr_ticket_number,sr_item_sk] + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_returned_date_sk] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (5) + ColumnarToRow + InputAdapter + CometProject [s_store_sk,s_store_name,s_state,s_zip] + CometFilter [s_market_id,s_store_sk,s_zip] + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name,s_market_id,s_state,s_zip] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (6) + ColumnarToRow + InputAdapter + CometFilter [i_color,i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price,i_size,i_color,i_units,i_manager_id] + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (7) + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_current_addr_sk,c_birth_country] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_addr_sk,c_first_name,c_last_name,c_birth_country] + InputAdapter + BroadcastExchange #9 + WholeStageCodegen (8) + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk,ca_country,ca_zip] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state,ca_zip,ca_country] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q27a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q27a/explain.txt new file mode 100644 index 0000000000..fc43e7271b --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q27a/explain.txt @@ -0,0 +1,457 @@ +== Physical Plan == +TakeOrderedAndProject (73) ++- Union (72) + :- * HashAggregate (28) + : +- Exchange (27) + : +- * HashAggregate (26) + : +- * Project (25) + : +- * BroadcastHashJoin Inner BuildRight (24) + : :- * Project (19) + : : +- * BroadcastHashJoin Inner BuildRight (18) + : : :- * Project (13) + : : : +- * BroadcastHashJoin Inner BuildRight (12) + : : : :- * Project (10) + : : : : +- * BroadcastHashJoin Inner BuildRight (9) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : +- BroadcastExchange (8) + : : : : +- * ColumnarToRow (7) + : : : : +- CometProject (6) + : : : : +- CometFilter (5) + : : : : +- CometScan parquet spark_catalog.default.customer_demographics (4) + : : : +- ReusedExchange (11) + : : +- BroadcastExchange (17) + : : +- * ColumnarToRow (16) + : : +- CometFilter (15) + : : +- CometScan parquet spark_catalog.default.store (14) + : +- BroadcastExchange (23) + : +- * ColumnarToRow (22) + : +- CometFilter (21) + : +- CometScan parquet spark_catalog.default.item (20) + :- * HashAggregate (50) + : +- Exchange (49) + : +- * HashAggregate (48) + : +- * Project (47) + : +- * BroadcastHashJoin Inner BuildRight (46) + : :- * Project (44) + : : +- * BroadcastHashJoin Inner BuildRight (43) + : : :- * Project (37) + : : : +- * BroadcastHashJoin Inner BuildRight (36) + : : : :- * Project (34) + : : : : +- * BroadcastHashJoin Inner BuildRight (33) + : : : : :- * ColumnarToRow (31) + : : : : : +- CometFilter (30) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (29) + : : : : +- ReusedExchange (32) + : : : +- ReusedExchange (35) + : : +- BroadcastExchange (42) + : : +- * ColumnarToRow (41) + : : +- CometProject (40) + : : +- CometFilter (39) + : : +- CometScan parquet spark_catalog.default.store (38) + : +- ReusedExchange (45) + +- * HashAggregate (71) + +- Exchange (70) + +- * HashAggregate (69) + +- * Project (68) + +- * BroadcastHashJoin Inner BuildRight (67) + :- * Project (62) + : +- * BroadcastHashJoin Inner BuildRight (61) + : :- * Project (59) + : : +- * BroadcastHashJoin Inner BuildRight (58) + : : :- * Project (56) + : : : +- * BroadcastHashJoin Inner BuildRight (55) + : : : :- * ColumnarToRow (53) + : : : : +- CometFilter (52) + : : : : +- CometScan parquet spark_catalog.default.store_sales (51) + : : : +- ReusedExchange (54) + : : +- ReusedExchange (57) + : +- ReusedExchange (60) + +- BroadcastExchange (66) + +- * ColumnarToRow (65) + +- CometFilter (64) + +- CometScan parquet spark_catalog.default.item (63) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [8]: [ss_item_sk#1, ss_cdemo_sk#2, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#8), dynamicpruningexpression(ss_sold_date_sk#8 IN dynamicpruning#9)] +PushedFilters: [IsNotNull(ss_cdemo_sk), IsNotNull(ss_store_sk), IsNotNull(ss_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [8]: [ss_item_sk#1, ss_cdemo_sk#2, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8] +Condition : ((isnotnull(ss_cdemo_sk#2) AND isnotnull(ss_store_sk#3)) AND isnotnull(ss_item_sk#1)) + +(3) ColumnarToRow [codegen id : 5] +Input [8]: [ss_item_sk#1, ss_cdemo_sk#2, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8] + +(4) Scan parquet spark_catalog.default.customer_demographics +Output [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_gender), IsNotNull(cd_marital_status), IsNotNull(cd_education_status), EqualTo(cd_gender,F), EqualTo(cd_marital_status,W), EqualTo(cd_education_status,Primary ), IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(5) CometFilter +Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] +Condition : ((((((isnotnull(cd_gender#11) AND isnotnull(cd_marital_status#12)) AND isnotnull(cd_education_status#13)) AND (cd_gender#11 = F)) AND (cd_marital_status#12 = W)) AND (cd_education_status#13 = Primary )) AND isnotnull(cd_demo_sk#10)) + +(6) CometProject +Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] +Arguments: [cd_demo_sk#10], [cd_demo_sk#10] + +(7) ColumnarToRow [codegen id : 1] +Input [1]: [cd_demo_sk#10] + +(8) BroadcastExchange +Input [1]: [cd_demo_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_cdemo_sk#2] +Right keys [1]: [cd_demo_sk#10] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 5] +Output [7]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8] +Input [9]: [ss_item_sk#1, ss_cdemo_sk#2, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8, cd_demo_sk#10] + +(11) ReusedExchange [Reuses operator id: 78] +Output [1]: [d_date_sk#14] + +(12) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_sold_date_sk#8] +Right keys [1]: [d_date_sk#14] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 5] +Output [6]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7] +Input [8]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8, d_date_sk#14] + +(14) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#15, s_state#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_state), EqualTo(s_state,TN), IsNotNull(s_store_sk)] +ReadSchema: struct + +(15) CometFilter +Input [2]: [s_store_sk#15, s_state#16] +Condition : ((isnotnull(s_state#16) AND (s_state#16 = TN)) AND isnotnull(s_store_sk#15)) + +(16) ColumnarToRow [codegen id : 3] +Input [2]: [s_store_sk#15, s_state#16] + +(17) BroadcastExchange +Input [2]: [s_store_sk#15, s_state#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(18) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_store_sk#3] +Right keys [1]: [s_store_sk#15] +Join type: Inner +Join condition: None + +(19) Project [codegen id : 5] +Output [6]: [ss_item_sk#1, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, s_state#16] +Input [8]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, s_store_sk#15, s_state#16] + +(20) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#17, i_item_id#18] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(21) CometFilter +Input [2]: [i_item_sk#17, i_item_id#18] +Condition : isnotnull(i_item_sk#17) + +(22) ColumnarToRow [codegen id : 4] +Input [2]: [i_item_sk#17, i_item_id#18] + +(23) BroadcastExchange +Input [2]: [i_item_sk#17, i_item_id#18] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#17] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 5] +Output [6]: [i_item_id#18, s_state#16, ss_quantity#4 AS agg1#19, ss_list_price#5 AS agg2#20, ss_coupon_amt#7 AS agg3#21, ss_sales_price#6 AS agg4#22] +Input [8]: [ss_item_sk#1, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, s_state#16, i_item_sk#17, i_item_id#18] + +(26) HashAggregate [codegen id : 5] +Input [6]: [i_item_id#18, s_state#16, agg1#19, agg2#20, agg3#21, agg4#22] +Keys [2]: [i_item_id#18, s_state#16] +Functions [4]: [partial_avg(agg1#19), partial_avg(UnscaledValue(agg2#20)), partial_avg(UnscaledValue(agg3#21)), partial_avg(UnscaledValue(agg4#22))] +Aggregate Attributes [8]: [sum#23, count#24, sum#25, count#26, sum#27, count#28, sum#29, count#30] +Results [10]: [i_item_id#18, s_state#16, sum#31, count#32, sum#33, count#34, sum#35, count#36, sum#37, count#38] + +(27) Exchange +Input [10]: [i_item_id#18, s_state#16, sum#31, count#32, sum#33, count#34, sum#35, count#36, sum#37, count#38] +Arguments: hashpartitioning(i_item_id#18, s_state#16, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(28) HashAggregate [codegen id : 6] +Input [10]: [i_item_id#18, s_state#16, sum#31, count#32, sum#33, count#34, sum#35, count#36, sum#37, count#38] +Keys [2]: [i_item_id#18, s_state#16] +Functions [4]: [avg(agg1#19), avg(UnscaledValue(agg2#20)), avg(UnscaledValue(agg3#21)), avg(UnscaledValue(agg4#22))] +Aggregate Attributes [4]: [avg(agg1#19)#39, avg(UnscaledValue(agg2#20))#40, avg(UnscaledValue(agg3#21))#41, avg(UnscaledValue(agg4#22))#42] +Results [7]: [i_item_id#18, s_state#16, 0 AS g_state#43, avg(agg1#19)#39 AS agg1#44, cast((avg(UnscaledValue(agg2#20))#40 / 100.0) as decimal(11,6)) AS agg2#45, cast((avg(UnscaledValue(agg3#21))#41 / 100.0) as decimal(11,6)) AS agg3#46, cast((avg(UnscaledValue(agg4#22))#42 / 100.0) as decimal(11,6)) AS agg4#47] + +(29) Scan parquet spark_catalog.default.store_sales +Output [8]: [ss_item_sk#48, ss_cdemo_sk#49, ss_store_sk#50, ss_quantity#51, ss_list_price#52, ss_sales_price#53, ss_coupon_amt#54, ss_sold_date_sk#55] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#55), dynamicpruningexpression(ss_sold_date_sk#55 IN dynamicpruning#56)] +PushedFilters: [IsNotNull(ss_cdemo_sk), IsNotNull(ss_store_sk), IsNotNull(ss_item_sk)] +ReadSchema: struct + +(30) CometFilter +Input [8]: [ss_item_sk#48, ss_cdemo_sk#49, ss_store_sk#50, ss_quantity#51, ss_list_price#52, ss_sales_price#53, ss_coupon_amt#54, ss_sold_date_sk#55] +Condition : ((isnotnull(ss_cdemo_sk#49) AND isnotnull(ss_store_sk#50)) AND isnotnull(ss_item_sk#48)) + +(31) ColumnarToRow [codegen id : 11] +Input [8]: [ss_item_sk#48, ss_cdemo_sk#49, ss_store_sk#50, ss_quantity#51, ss_list_price#52, ss_sales_price#53, ss_coupon_amt#54, ss_sold_date_sk#55] + +(32) ReusedExchange [Reuses operator id: 8] +Output [1]: [cd_demo_sk#57] + +(33) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [ss_cdemo_sk#49] +Right keys [1]: [cd_demo_sk#57] +Join type: Inner +Join condition: None + +(34) Project [codegen id : 11] +Output [7]: [ss_item_sk#48, ss_store_sk#50, ss_quantity#51, ss_list_price#52, ss_sales_price#53, ss_coupon_amt#54, ss_sold_date_sk#55] +Input [9]: [ss_item_sk#48, ss_cdemo_sk#49, ss_store_sk#50, ss_quantity#51, ss_list_price#52, ss_sales_price#53, ss_coupon_amt#54, ss_sold_date_sk#55, cd_demo_sk#57] + +(35) ReusedExchange [Reuses operator id: 78] +Output [1]: [d_date_sk#58] + +(36) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [ss_sold_date_sk#55] +Right keys [1]: [d_date_sk#58] +Join type: Inner +Join condition: None + +(37) Project [codegen id : 11] +Output [6]: [ss_item_sk#48, ss_store_sk#50, ss_quantity#51, ss_list_price#52, ss_sales_price#53, ss_coupon_amt#54] +Input [8]: [ss_item_sk#48, ss_store_sk#50, ss_quantity#51, ss_list_price#52, ss_sales_price#53, ss_coupon_amt#54, ss_sold_date_sk#55, d_date_sk#58] + +(38) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#59, s_state#60] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_state), EqualTo(s_state,TN), IsNotNull(s_store_sk)] +ReadSchema: struct + +(39) CometFilter +Input [2]: [s_store_sk#59, s_state#60] +Condition : ((isnotnull(s_state#60) AND (s_state#60 = TN)) AND isnotnull(s_store_sk#59)) + +(40) CometProject +Input [2]: [s_store_sk#59, s_state#60] +Arguments: [s_store_sk#59], [s_store_sk#59] + +(41) ColumnarToRow [codegen id : 9] +Input [1]: [s_store_sk#59] + +(42) BroadcastExchange +Input [1]: [s_store_sk#59] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +(43) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [ss_store_sk#50] +Right keys [1]: [s_store_sk#59] +Join type: Inner +Join condition: None + +(44) Project [codegen id : 11] +Output [5]: [ss_item_sk#48, ss_quantity#51, ss_list_price#52, ss_sales_price#53, ss_coupon_amt#54] +Input [7]: [ss_item_sk#48, ss_store_sk#50, ss_quantity#51, ss_list_price#52, ss_sales_price#53, ss_coupon_amt#54, s_store_sk#59] + +(45) ReusedExchange [Reuses operator id: 23] +Output [2]: [i_item_sk#61, i_item_id#62] + +(46) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [ss_item_sk#48] +Right keys [1]: [i_item_sk#61] +Join type: Inner +Join condition: None + +(47) Project [codegen id : 11] +Output [5]: [i_item_id#62, ss_quantity#51 AS agg1#63, ss_list_price#52 AS agg2#64, ss_coupon_amt#54 AS agg3#65, ss_sales_price#53 AS agg4#66] +Input [7]: [ss_item_sk#48, ss_quantity#51, ss_list_price#52, ss_sales_price#53, ss_coupon_amt#54, i_item_sk#61, i_item_id#62] + +(48) HashAggregate [codegen id : 11] +Input [5]: [i_item_id#62, agg1#63, agg2#64, agg3#65, agg4#66] +Keys [1]: [i_item_id#62] +Functions [4]: [partial_avg(agg1#63), partial_avg(UnscaledValue(agg2#64)), partial_avg(UnscaledValue(agg3#65)), partial_avg(UnscaledValue(agg4#66))] +Aggregate Attributes [8]: [sum#67, count#68, sum#69, count#70, sum#71, count#72, sum#73, count#74] +Results [9]: [i_item_id#62, sum#75, count#76, sum#77, count#78, sum#79, count#80, sum#81, count#82] + +(49) Exchange +Input [9]: [i_item_id#62, sum#75, count#76, sum#77, count#78, sum#79, count#80, sum#81, count#82] +Arguments: hashpartitioning(i_item_id#62, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(50) HashAggregate [codegen id : 12] +Input [9]: [i_item_id#62, sum#75, count#76, sum#77, count#78, sum#79, count#80, sum#81, count#82] +Keys [1]: [i_item_id#62] +Functions [4]: [avg(agg1#63), avg(UnscaledValue(agg2#64)), avg(UnscaledValue(agg3#65)), avg(UnscaledValue(agg4#66))] +Aggregate Attributes [4]: [avg(agg1#63)#83, avg(UnscaledValue(agg2#64))#84, avg(UnscaledValue(agg3#65))#85, avg(UnscaledValue(agg4#66))#86] +Results [7]: [i_item_id#62, null AS s_state#87, 1 AS g_state#88, avg(agg1#63)#83 AS agg1#89, cast((avg(UnscaledValue(agg2#64))#84 / 100.0) as decimal(11,6)) AS agg2#90, cast((avg(UnscaledValue(agg3#65))#85 / 100.0) as decimal(11,6)) AS agg3#91, cast((avg(UnscaledValue(agg4#66))#86 / 100.0) as decimal(11,6)) AS agg4#92] + +(51) Scan parquet spark_catalog.default.store_sales +Output [8]: [ss_item_sk#93, ss_cdemo_sk#94, ss_store_sk#95, ss_quantity#96, ss_list_price#97, ss_sales_price#98, ss_coupon_amt#99, ss_sold_date_sk#100] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#100), dynamicpruningexpression(ss_sold_date_sk#100 IN dynamicpruning#101)] +PushedFilters: [IsNotNull(ss_cdemo_sk), IsNotNull(ss_store_sk), IsNotNull(ss_item_sk)] +ReadSchema: struct + +(52) CometFilter +Input [8]: [ss_item_sk#93, ss_cdemo_sk#94, ss_store_sk#95, ss_quantity#96, ss_list_price#97, ss_sales_price#98, ss_coupon_amt#99, ss_sold_date_sk#100] +Condition : ((isnotnull(ss_cdemo_sk#94) AND isnotnull(ss_store_sk#95)) AND isnotnull(ss_item_sk#93)) + +(53) ColumnarToRow [codegen id : 17] +Input [8]: [ss_item_sk#93, ss_cdemo_sk#94, ss_store_sk#95, ss_quantity#96, ss_list_price#97, ss_sales_price#98, ss_coupon_amt#99, ss_sold_date_sk#100] + +(54) ReusedExchange [Reuses operator id: 8] +Output [1]: [cd_demo_sk#102] + +(55) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ss_cdemo_sk#94] +Right keys [1]: [cd_demo_sk#102] +Join type: Inner +Join condition: None + +(56) Project [codegen id : 17] +Output [7]: [ss_item_sk#93, ss_store_sk#95, ss_quantity#96, ss_list_price#97, ss_sales_price#98, ss_coupon_amt#99, ss_sold_date_sk#100] +Input [9]: [ss_item_sk#93, ss_cdemo_sk#94, ss_store_sk#95, ss_quantity#96, ss_list_price#97, ss_sales_price#98, ss_coupon_amt#99, ss_sold_date_sk#100, cd_demo_sk#102] + +(57) ReusedExchange [Reuses operator id: 78] +Output [1]: [d_date_sk#103] + +(58) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ss_sold_date_sk#100] +Right keys [1]: [d_date_sk#103] +Join type: Inner +Join condition: None + +(59) Project [codegen id : 17] +Output [6]: [ss_item_sk#93, ss_store_sk#95, ss_quantity#96, ss_list_price#97, ss_sales_price#98, ss_coupon_amt#99] +Input [8]: [ss_item_sk#93, ss_store_sk#95, ss_quantity#96, ss_list_price#97, ss_sales_price#98, ss_coupon_amt#99, ss_sold_date_sk#100, d_date_sk#103] + +(60) ReusedExchange [Reuses operator id: 42] +Output [1]: [s_store_sk#104] + +(61) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ss_store_sk#95] +Right keys [1]: [s_store_sk#104] +Join type: Inner +Join condition: None + +(62) Project [codegen id : 17] +Output [5]: [ss_item_sk#93, ss_quantity#96, ss_list_price#97, ss_sales_price#98, ss_coupon_amt#99] +Input [7]: [ss_item_sk#93, ss_store_sk#95, ss_quantity#96, ss_list_price#97, ss_sales_price#98, ss_coupon_amt#99, s_store_sk#104] + +(63) Scan parquet spark_catalog.default.item +Output [1]: [i_item_sk#105] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(64) CometFilter +Input [1]: [i_item_sk#105] +Condition : isnotnull(i_item_sk#105) + +(65) ColumnarToRow [codegen id : 16] +Input [1]: [i_item_sk#105] + +(66) BroadcastExchange +Input [1]: [i_item_sk#105] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=7] + +(67) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ss_item_sk#93] +Right keys [1]: [i_item_sk#105] +Join type: Inner +Join condition: None + +(68) Project [codegen id : 17] +Output [4]: [ss_quantity#96 AS agg1#106, ss_list_price#97 AS agg2#107, ss_coupon_amt#99 AS agg3#108, ss_sales_price#98 AS agg4#109] +Input [6]: [ss_item_sk#93, ss_quantity#96, ss_list_price#97, ss_sales_price#98, ss_coupon_amt#99, i_item_sk#105] + +(69) HashAggregate [codegen id : 17] +Input [4]: [agg1#106, agg2#107, agg3#108, agg4#109] +Keys: [] +Functions [4]: [partial_avg(agg1#106), partial_avg(UnscaledValue(agg2#107)), partial_avg(UnscaledValue(agg3#108)), partial_avg(UnscaledValue(agg4#109))] +Aggregate Attributes [8]: [sum#110, count#111, sum#112, count#113, sum#114, count#115, sum#116, count#117] +Results [8]: [sum#118, count#119, sum#120, count#121, sum#122, count#123, sum#124, count#125] + +(70) Exchange +Input [8]: [sum#118, count#119, sum#120, count#121, sum#122, count#123, sum#124, count#125] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=8] + +(71) HashAggregate [codegen id : 18] +Input [8]: [sum#118, count#119, sum#120, count#121, sum#122, count#123, sum#124, count#125] +Keys: [] +Functions [4]: [avg(agg1#106), avg(UnscaledValue(agg2#107)), avg(UnscaledValue(agg3#108)), avg(UnscaledValue(agg4#109))] +Aggregate Attributes [4]: [avg(agg1#106)#126, avg(UnscaledValue(agg2#107))#127, avg(UnscaledValue(agg3#108))#128, avg(UnscaledValue(agg4#109))#129] +Results [7]: [null AS i_item_id#130, null AS s_state#131, 1 AS g_state#132, avg(agg1#106)#126 AS agg1#133, cast((avg(UnscaledValue(agg2#107))#127 / 100.0) as decimal(11,6)) AS agg2#134, cast((avg(UnscaledValue(agg3#108))#128 / 100.0) as decimal(11,6)) AS agg3#135, cast((avg(UnscaledValue(agg4#109))#129 / 100.0) as decimal(11,6)) AS agg4#136] + +(72) Union + +(73) TakeOrderedAndProject +Input [7]: [i_item_id#18, s_state#16, g_state#43, agg1#44, agg2#45, agg3#46, agg4#47] +Arguments: 100, [i_item_id#18 ASC NULLS FIRST, s_state#16 ASC NULLS FIRST], [i_item_id#18, s_state#16, g_state#43, agg1#44, agg2#45, agg3#46, agg4#47] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#8 IN dynamicpruning#9 +BroadcastExchange (78) ++- * ColumnarToRow (77) + +- CometProject (76) + +- CometFilter (75) + +- CometScan parquet spark_catalog.default.date_dim (74) + + +(74) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#14, d_year#137] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,1998), IsNotNull(d_date_sk)] +ReadSchema: struct + +(75) CometFilter +Input [2]: [d_date_sk#14, d_year#137] +Condition : ((isnotnull(d_year#137) AND (d_year#137 = 1998)) AND isnotnull(d_date_sk#14)) + +(76) CometProject +Input [2]: [d_date_sk#14, d_year#137] +Arguments: [d_date_sk#14], [d_date_sk#14] + +(77) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#14] + +(78) BroadcastExchange +Input [1]: [d_date_sk#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=9] + +Subquery:2 Hosting operator id = 29 Hosting Expression = ss_sold_date_sk#55 IN dynamicpruning#9 + +Subquery:3 Hosting operator id = 51 Hosting Expression = ss_sold_date_sk#100 IN dynamicpruning#9 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q27a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q27a/simplified.txt new file mode 100644 index 0000000000..32f003798d --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q27a/simplified.txt @@ -0,0 +1,117 @@ +TakeOrderedAndProject [i_item_id,s_state,g_state,agg1,agg2,agg3,agg4] + Union + WholeStageCodegen (6) + HashAggregate [i_item_id,s_state,sum,count,sum,count,sum,count,sum,count] [avg(agg1),avg(UnscaledValue(agg2)),avg(UnscaledValue(agg3)),avg(UnscaledValue(agg4)),g_state,agg1,agg2,agg3,agg4,sum,count,sum,count,sum,count,sum,count] + InputAdapter + Exchange [i_item_id,s_state] #1 + WholeStageCodegen (5) + HashAggregate [i_item_id,s_state,agg1,agg2,agg3,agg4] [sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + Project [i_item_id,s_state,ss_quantity,ss_list_price,ss_coupon_amt,ss_sales_price] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,s_state] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,ss_sold_date_sk] + BroadcastHashJoin [ss_cdemo_sk,cd_demo_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_cdemo_sk,ss_store_sk,ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_cdemo_sk,ss_store_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [cd_demo_sk] + CometFilter [cd_gender,cd_marital_status,cd_education_status,cd_demo_sk] + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_marital_status,cd_education_status] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometFilter [s_state,s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk,s_state] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (4) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] + WholeStageCodegen (12) + HashAggregate [i_item_id,sum,count,sum,count,sum,count,sum,count] [avg(agg1),avg(UnscaledValue(agg2)),avg(UnscaledValue(agg3)),avg(UnscaledValue(agg4)),s_state,g_state,agg1,agg2,agg3,agg4,sum,count,sum,count,sum,count,sum,count] + InputAdapter + Exchange [i_item_id] #6 + WholeStageCodegen (11) + HashAggregate [i_item_id,agg1,agg2,agg3,agg4] [sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + Project [i_item_id,ss_quantity,ss_list_price,ss_coupon_amt,ss_sales_price] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,ss_sold_date_sk] + BroadcastHashJoin [ss_cdemo_sk,cd_demo_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_cdemo_sk,ss_store_sk,ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_cdemo_sk,ss_store_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [cd_demo_sk] #3 + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (9) + ColumnarToRow + InputAdapter + CometProject [s_store_sk] + CometFilter [s_state,s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk,s_state] + InputAdapter + ReusedExchange [i_item_sk,i_item_id] #5 + WholeStageCodegen (18) + HashAggregate [sum,count,sum,count,sum,count,sum,count] [avg(agg1),avg(UnscaledValue(agg2)),avg(UnscaledValue(agg3)),avg(UnscaledValue(agg4)),i_item_id,s_state,g_state,agg1,agg2,agg3,agg4,sum,count,sum,count,sum,count,sum,count] + InputAdapter + Exchange #8 + WholeStageCodegen (17) + HashAggregate [agg1,agg2,agg3,agg4] [sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + Project [ss_quantity,ss_list_price,ss_coupon_amt,ss_sales_price] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,ss_sold_date_sk] + BroadcastHashJoin [ss_cdemo_sk,cd_demo_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_cdemo_sk,ss_store_sk,ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_cdemo_sk,ss_store_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [cd_demo_sk] #3 + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + ReusedExchange [s_store_sk] #7 + InputAdapter + BroadcastExchange #9 + WholeStageCodegen (16) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q34/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q34/explain.txt new file mode 100644 index 0000000000..387fa47f9b --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q34/explain.txt @@ -0,0 +1,218 @@ +== Physical Plan == +* Sort (32) ++- Exchange (31) + +- * Project (30) + +- * BroadcastHashJoin Inner BuildRight (29) + :- * Filter (24) + : +- * HashAggregate (23) + : +- Exchange (22) + : +- * HashAggregate (21) + : +- * Project (20) + : +- * BroadcastHashJoin Inner BuildRight (19) + : :- * Project (13) + : : +- * BroadcastHashJoin Inner BuildRight (12) + : : :- * Project (6) + : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- ReusedExchange (4) + : : +- BroadcastExchange (11) + : : +- * ColumnarToRow (10) + : : +- CometProject (9) + : : +- CometFilter (8) + : : +- CometScan parquet spark_catalog.default.store (7) + : +- BroadcastExchange (18) + : +- * ColumnarToRow (17) + : +- CometProject (16) + : +- CometFilter (15) + : +- CometScan parquet spark_catalog.default.household_demographics (14) + +- BroadcastExchange (28) + +- * ColumnarToRow (27) + +- CometFilter (26) + +- CometScan parquet spark_catalog.default.customer (25) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#5), dynamicpruningexpression(ss_sold_date_sk#5 IN dynamicpruning#6)] +PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_hdemo_sk), IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(2) CometFilter +Input [5]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5] +Condition : ((isnotnull(ss_store_sk#3) AND isnotnull(ss_hdemo_sk#2)) AND isnotnull(ss_customer_sk#1)) + +(3) ColumnarToRow [codegen id : 4] +Input [5]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5] + +(4) ReusedExchange [Reuses operator id: 37] +Output [1]: [d_date_sk#7] + +(5) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_date_sk#5] +Right keys [1]: [d_date_sk#7] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 4] +Output [4]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4] +Input [6]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5, d_date_sk#7] + +(7) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#8, s_county#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_county), EqualTo(s_county,Williamson County), IsNotNull(s_store_sk)] +ReadSchema: struct + +(8) CometFilter +Input [2]: [s_store_sk#8, s_county#9] +Condition : ((isnotnull(s_county#9) AND (s_county#9 = Williamson County)) AND isnotnull(s_store_sk#8)) + +(9) CometProject +Input [2]: [s_store_sk#8, s_county#9] +Arguments: [s_store_sk#8], [s_store_sk#8] + +(10) ColumnarToRow [codegen id : 2] +Input [1]: [s_store_sk#8] + +(11) BroadcastExchange +Input [1]: [s_store_sk#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(12) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_store_sk#3] +Right keys [1]: [s_store_sk#8] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 4] +Output [3]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_ticket_number#4] +Input [5]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, s_store_sk#8] + +(14) Scan parquet spark_catalog.default.household_demographics +Output [4]: [hd_demo_sk#10, hd_buy_potential#11, hd_dep_count#12, hd_vehicle_count#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/household_demographics] +PushedFilters: [IsNotNull(hd_vehicle_count), Or(EqualTo(hd_buy_potential,>10000 ),EqualTo(hd_buy_potential,unknown )), GreaterThan(hd_vehicle_count,0), IsNotNull(hd_demo_sk)] +ReadSchema: struct + +(15) CometFilter +Input [4]: [hd_demo_sk#10, hd_buy_potential#11, hd_dep_count#12, hd_vehicle_count#13] +Condition : ((((isnotnull(hd_vehicle_count#13) AND ((hd_buy_potential#11 = >10000 ) OR (hd_buy_potential#11 = unknown ))) AND (hd_vehicle_count#13 > 0)) AND CASE WHEN (hd_vehicle_count#13 > 0) THEN ((cast(hd_dep_count#12 as double) / cast(hd_vehicle_count#13 as double)) > 1.2) END) AND isnotnull(hd_demo_sk#10)) + +(16) CometProject +Input [4]: [hd_demo_sk#10, hd_buy_potential#11, hd_dep_count#12, hd_vehicle_count#13] +Arguments: [hd_demo_sk#10], [hd_demo_sk#10] + +(17) ColumnarToRow [codegen id : 3] +Input [1]: [hd_demo_sk#10] + +(18) BroadcastExchange +Input [1]: [hd_demo_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(19) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_hdemo_sk#2] +Right keys [1]: [hd_demo_sk#10] +Join type: Inner +Join condition: None + +(20) Project [codegen id : 4] +Output [2]: [ss_customer_sk#1, ss_ticket_number#4] +Input [4]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_ticket_number#4, hd_demo_sk#10] + +(21) HashAggregate [codegen id : 4] +Input [2]: [ss_customer_sk#1, ss_ticket_number#4] +Keys [2]: [ss_ticket_number#4, ss_customer_sk#1] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#14] +Results [3]: [ss_ticket_number#4, ss_customer_sk#1, count#15] + +(22) Exchange +Input [3]: [ss_ticket_number#4, ss_customer_sk#1, count#15] +Arguments: hashpartitioning(ss_ticket_number#4, ss_customer_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(23) HashAggregate [codegen id : 6] +Input [3]: [ss_ticket_number#4, ss_customer_sk#1, count#15] +Keys [2]: [ss_ticket_number#4, ss_customer_sk#1] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#16] +Results [3]: [ss_ticket_number#4, ss_customer_sk#1, count(1)#16 AS cnt#17] + +(24) Filter [codegen id : 6] +Input [3]: [ss_ticket_number#4, ss_customer_sk#1, cnt#17] +Condition : ((cnt#17 >= 15) AND (cnt#17 <= 20)) + +(25) Scan parquet spark_catalog.default.customer +Output [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk)] +ReadSchema: struct + +(26) CometFilter +Input [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] +Condition : isnotnull(c_customer_sk#18) + +(27) ColumnarToRow [codegen id : 5] +Input [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] + +(28) BroadcastExchange +Input [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(29) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_customer_sk#1] +Right keys [1]: [c_customer_sk#18] +Join type: Inner +Join condition: None + +(30) Project [codegen id : 6] +Output [6]: [c_last_name#21, c_first_name#20, c_salutation#19, c_preferred_cust_flag#22, ss_ticket_number#4, cnt#17] +Input [8]: [ss_ticket_number#4, ss_customer_sk#1, cnt#17, c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] + +(31) Exchange +Input [6]: [c_last_name#21, c_first_name#20, c_salutation#19, c_preferred_cust_flag#22, ss_ticket_number#4, cnt#17] +Arguments: rangepartitioning(c_last_name#21 ASC NULLS FIRST, c_first_name#20 ASC NULLS FIRST, c_salutation#19 ASC NULLS FIRST, c_preferred_cust_flag#22 DESC NULLS LAST, ss_ticket_number#4 ASC NULLS FIRST, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(32) Sort [codegen id : 7] +Input [6]: [c_last_name#21, c_first_name#20, c_salutation#19, c_preferred_cust_flag#22, ss_ticket_number#4, cnt#17] +Arguments: [c_last_name#21 ASC NULLS FIRST, c_first_name#20 ASC NULLS FIRST, c_salutation#19 ASC NULLS FIRST, c_preferred_cust_flag#22 DESC NULLS LAST, ss_ticket_number#4 ASC NULLS FIRST], true, 0 + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6 +BroadcastExchange (37) ++- * ColumnarToRow (36) + +- CometProject (35) + +- CometFilter (34) + +- CometScan parquet spark_catalog.default.date_dim (33) + + +(33) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#7, d_year#23, d_dom#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [Or(And(GreaterThanOrEqual(d_dom,1),LessThanOrEqual(d_dom,3)),And(GreaterThanOrEqual(d_dom,25),LessThanOrEqual(d_dom,28))), In(d_year, [1999,2000,2001]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(34) CometFilter +Input [3]: [d_date_sk#7, d_year#23, d_dom#24] +Condition : (((((d_dom#24 >= 1) AND (d_dom#24 <= 3)) OR ((d_dom#24 >= 25) AND (d_dom#24 <= 28))) AND d_year#23 IN (1999,2000,2001)) AND isnotnull(d_date_sk#7)) + +(35) CometProject +Input [3]: [d_date_sk#7, d_year#23, d_dom#24] +Arguments: [d_date_sk#7], [d_date_sk#7] + +(36) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#7] + +(37) BroadcastExchange +Input [1]: [d_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q34/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q34/simplified.txt new file mode 100644 index 0000000000..b473e48921 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q34/simplified.txt @@ -0,0 +1,56 @@ +WholeStageCodegen (7) + Sort [c_last_name,c_first_name,c_salutation,c_preferred_cust_flag,ss_ticket_number] + InputAdapter + Exchange [c_last_name,c_first_name,c_salutation,c_preferred_cust_flag,ss_ticket_number] #1 + WholeStageCodegen (6) + Project [c_last_name,c_first_name,c_salutation,c_preferred_cust_flag,ss_ticket_number,cnt] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Filter [cnt] + HashAggregate [ss_ticket_number,ss_customer_sk,count] [count(1),cnt,count] + InputAdapter + Exchange [ss_ticket_number,ss_customer_sk] #2 + WholeStageCodegen (4) + HashAggregate [ss_ticket_number,ss_customer_sk] [count,count] + Project [ss_customer_sk,ss_ticket_number] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + Project [ss_customer_sk,ss_hdemo_sk,ss_ticket_number] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_customer_sk,ss_hdemo_sk,ss_store_sk,ss_ticket_number] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk,ss_hdemo_sk,ss_customer_sk] + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_hdemo_sk,ss_store_sk,ss_ticket_number,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_dom,d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_dom] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometProject [s_store_sk] + CometFilter [s_county,s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk,s_county] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometProject [hd_demo_sk] + CometFilter [hd_vehicle_count,hd_buy_potential,hd_dep_count,hd_demo_sk] + CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_buy_potential,hd_dep_count,hd_vehicle_count] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (5) + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_salutation,c_first_name,c_last_name,c_preferred_cust_flag] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35/explain.txt new file mode 100644 index 0000000000..ce8753277a --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35/explain.txt @@ -0,0 +1,281 @@ +== Physical Plan == +TakeOrderedAndProject (42) ++- * HashAggregate (41) + +- Exchange (40) + +- * HashAggregate (39) + +- * Project (38) + +- * BroadcastHashJoin Inner BuildRight (37) + :- * Project (32) + : +- * BroadcastHashJoin Inner BuildRight (31) + : :- * Project (26) + : : +- * Filter (25) + : : +- * BroadcastHashJoin ExistenceJoin(exists#1) BuildRight (24) + : : :- * BroadcastHashJoin ExistenceJoin(exists#2) BuildRight (17) + : : : :- * BroadcastHashJoin LeftSemi BuildRight (10) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) + : : : : : +- CometScan parquet spark_catalog.default.customer (1) + : : : : +- BroadcastExchange (9) + : : : : +- * Project (8) + : : : : +- * BroadcastHashJoin Inner BuildRight (7) + : : : : :- * ColumnarToRow (5) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (4) + : : : : +- ReusedExchange (6) + : : : +- BroadcastExchange (16) + : : : +- * Project (15) + : : : +- * BroadcastHashJoin Inner BuildRight (14) + : : : :- * ColumnarToRow (12) + : : : : +- CometScan parquet spark_catalog.default.web_sales (11) + : : : +- ReusedExchange (13) + : : +- BroadcastExchange (23) + : : +- * Project (22) + : : +- * BroadcastHashJoin Inner BuildRight (21) + : : :- * ColumnarToRow (19) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (18) + : : +- ReusedExchange (20) + : +- BroadcastExchange (30) + : +- * ColumnarToRow (29) + : +- CometFilter (28) + : +- CometScan parquet spark_catalog.default.customer_address (27) + +- BroadcastExchange (36) + +- * ColumnarToRow (35) + +- CometFilter (34) + +- CometScan parquet spark_catalog.default.customer_demographics (33) + + +(1) Scan parquet spark_catalog.default.customer +Output [3]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_current_addr_sk), IsNotNull(c_current_cdemo_sk)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5] +Condition : (isnotnull(c_current_addr_sk#5) AND isnotnull(c_current_cdemo_sk#4)) + +(3) ColumnarToRow [codegen id : 9] +Input [3]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5] + +(4) Scan parquet spark_catalog.default.store_sales +Output [2]: [ss_customer_sk#6, ss_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sold_date_sk#7 IN dynamicpruning#8)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 2] +Input [2]: [ss_customer_sk#6, ss_sold_date_sk#7] + +(6) ReusedExchange [Reuses operator id: 47] +Output [1]: [d_date_sk#9] + +(7) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [ss_sold_date_sk#7] +Right keys [1]: [d_date_sk#9] +Join type: Inner +Join condition: None + +(8) Project [codegen id : 2] +Output [1]: [ss_customer_sk#6] +Input [3]: [ss_customer_sk#6, ss_sold_date_sk#7, d_date_sk#9] + +(9) BroadcastExchange +Input [1]: [ss_customer_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(10) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_customer_sk#3] +Right keys [1]: [ss_customer_sk#6] +Join type: LeftSemi +Join condition: None + +(11) Scan parquet spark_catalog.default.web_sales +Output [2]: [ws_bill_customer_sk#10, ws_sold_date_sk#11] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#11), dynamicpruningexpression(ws_sold_date_sk#11 IN dynamicpruning#12)] +ReadSchema: struct + +(12) ColumnarToRow [codegen id : 4] +Input [2]: [ws_bill_customer_sk#10, ws_sold_date_sk#11] + +(13) ReusedExchange [Reuses operator id: 47] +Output [1]: [d_date_sk#13] + +(14) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ws_sold_date_sk#11] +Right keys [1]: [d_date_sk#13] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 4] +Output [1]: [ws_bill_customer_sk#10] +Input [3]: [ws_bill_customer_sk#10, ws_sold_date_sk#11, d_date_sk#13] + +(16) BroadcastExchange +Input [1]: [ws_bill_customer_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(17) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_customer_sk#3] +Right keys [1]: [ws_bill_customer_sk#10] +Join type: ExistenceJoin(exists#2) +Join condition: None + +(18) Scan parquet spark_catalog.default.catalog_sales +Output [2]: [cs_ship_customer_sk#14, cs_sold_date_sk#15] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#15), dynamicpruningexpression(cs_sold_date_sk#15 IN dynamicpruning#16)] +ReadSchema: struct + +(19) ColumnarToRow [codegen id : 6] +Input [2]: [cs_ship_customer_sk#14, cs_sold_date_sk#15] + +(20) ReusedExchange [Reuses operator id: 47] +Output [1]: [d_date_sk#17] + +(21) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [cs_sold_date_sk#15] +Right keys [1]: [d_date_sk#17] +Join type: Inner +Join condition: None + +(22) Project [codegen id : 6] +Output [1]: [cs_ship_customer_sk#14] +Input [3]: [cs_ship_customer_sk#14, cs_sold_date_sk#15, d_date_sk#17] + +(23) BroadcastExchange +Input [1]: [cs_ship_customer_sk#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_customer_sk#3] +Right keys [1]: [cs_ship_customer_sk#14] +Join type: ExistenceJoin(exists#1) +Join condition: None + +(25) Filter [codegen id : 9] +Input [5]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5, exists#2, exists#1] +Condition : (exists#2 OR exists#1) + +(26) Project [codegen id : 9] +Output [2]: [c_current_cdemo_sk#4, c_current_addr_sk#5] +Input [5]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5, exists#2, exists#1] + +(27) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#18, ca_state#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk)] +ReadSchema: struct + +(28) CometFilter +Input [2]: [ca_address_sk#18, ca_state#19] +Condition : isnotnull(ca_address_sk#18) + +(29) ColumnarToRow [codegen id : 7] +Input [2]: [ca_address_sk#18, ca_state#19] + +(30) BroadcastExchange +Input [2]: [ca_address_sk#18, ca_state#19] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(31) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_current_addr_sk#5] +Right keys [1]: [ca_address_sk#18] +Join type: Inner +Join condition: None + +(32) Project [codegen id : 9] +Output [2]: [c_current_cdemo_sk#4, ca_state#19] +Input [4]: [c_current_cdemo_sk#4, c_current_addr_sk#5, ca_address_sk#18, ca_state#19] + +(33) Scan parquet spark_catalog.default.customer_demographics +Output [6]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(34) CometFilter +Input [6]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Condition : isnotnull(cd_demo_sk#20) + +(35) ColumnarToRow [codegen id : 8] +Input [6]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] + +(36) BroadcastExchange +Input [6]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(37) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_current_cdemo_sk#4] +Right keys [1]: [cd_demo_sk#20] +Join type: Inner +Join condition: None + +(38) Project [codegen id : 9] +Output [6]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Input [8]: [c_current_cdemo_sk#4, ca_state#19, cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] + +(39) HashAggregate [codegen id : 9] +Input [6]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Keys [6]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Functions [10]: [partial_count(1), partial_avg(cd_dep_count#23), partial_max(cd_dep_count#23), partial_sum(cd_dep_count#23), partial_avg(cd_dep_employed_count#24), partial_max(cd_dep_employed_count#24), partial_sum(cd_dep_employed_count#24), partial_avg(cd_dep_college_count#25), partial_max(cd_dep_college_count#25), partial_sum(cd_dep_college_count#25)] +Aggregate Attributes [13]: [count#26, sum#27, count#28, max#29, sum#30, sum#31, count#32, max#33, sum#34, sum#35, count#36, max#37, sum#38] +Results [19]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25, count#39, sum#40, count#41, max#42, sum#43, sum#44, count#45, max#46, sum#47, sum#48, count#49, max#50, sum#51] + +(40) Exchange +Input [19]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25, count#39, sum#40, count#41, max#42, sum#43, sum#44, count#45, max#46, sum#47, sum#48, count#49, max#50, sum#51] +Arguments: hashpartitioning(ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(41) HashAggregate [codegen id : 10] +Input [19]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25, count#39, sum#40, count#41, max#42, sum#43, sum#44, count#45, max#46, sum#47, sum#48, count#49, max#50, sum#51] +Keys [6]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Functions [10]: [count(1), avg(cd_dep_count#23), max(cd_dep_count#23), sum(cd_dep_count#23), avg(cd_dep_employed_count#24), max(cd_dep_employed_count#24), sum(cd_dep_employed_count#24), avg(cd_dep_college_count#25), max(cd_dep_college_count#25), sum(cd_dep_college_count#25)] +Aggregate Attributes [10]: [count(1)#52, avg(cd_dep_count#23)#53, max(cd_dep_count#23)#54, sum(cd_dep_count#23)#55, avg(cd_dep_employed_count#24)#56, max(cd_dep_employed_count#24)#57, sum(cd_dep_employed_count#24)#58, avg(cd_dep_college_count#25)#59, max(cd_dep_college_count#25)#60, sum(cd_dep_college_count#25)#61] +Results [18]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, count(1)#52 AS cnt1#62, avg(cd_dep_count#23)#53 AS avg(cd_dep_count)#63, max(cd_dep_count#23)#54 AS max(cd_dep_count)#64, sum(cd_dep_count#23)#55 AS sum(cd_dep_count)#65, cd_dep_employed_count#24, count(1)#52 AS cnt2#66, avg(cd_dep_employed_count#24)#56 AS avg(cd_dep_employed_count)#67, max(cd_dep_employed_count#24)#57 AS max(cd_dep_employed_count)#68, sum(cd_dep_employed_count#24)#58 AS sum(cd_dep_employed_count)#69, cd_dep_college_count#25, count(1)#52 AS cnt3#70, avg(cd_dep_college_count#25)#59 AS avg(cd_dep_college_count)#71, max(cd_dep_college_count#25)#60 AS max(cd_dep_college_count)#72, sum(cd_dep_college_count#25)#61 AS sum(cd_dep_college_count)#73] + +(42) TakeOrderedAndProject +Input [18]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cnt1#62, avg(cd_dep_count)#63, max(cd_dep_count)#64, sum(cd_dep_count)#65, cd_dep_employed_count#24, cnt2#66, avg(cd_dep_employed_count)#67, max(cd_dep_employed_count)#68, sum(cd_dep_employed_count)#69, cd_dep_college_count#25, cnt3#70, avg(cd_dep_college_count)#71, max(cd_dep_college_count)#72, sum(cd_dep_college_count)#73] +Arguments: 100, [ca_state#19 ASC NULLS FIRST, cd_gender#21 ASC NULLS FIRST, cd_marital_status#22 ASC NULLS FIRST, cd_dep_count#23 ASC NULLS FIRST, cd_dep_employed_count#24 ASC NULLS FIRST, cd_dep_college_count#25 ASC NULLS FIRST], [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cnt1#62, avg(cd_dep_count)#63, max(cd_dep_count)#64, sum(cd_dep_count)#65, cd_dep_employed_count#24, cnt2#66, avg(cd_dep_employed_count)#67, max(cd_dep_employed_count)#68, sum(cd_dep_employed_count)#69, cd_dep_college_count#25, cnt3#70, avg(cd_dep_college_count)#71, max(cd_dep_college_count)#72, sum(cd_dep_college_count)#73] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (47) ++- * ColumnarToRow (46) + +- CometProject (45) + +- CometFilter (44) + +- CometScan parquet spark_catalog.default.date_dim (43) + + +(43) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#9, d_year#74, d_qoy#75] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_qoy), EqualTo(d_year,2002), LessThan(d_qoy,4), IsNotNull(d_date_sk)] +ReadSchema: struct + +(44) CometFilter +Input [3]: [d_date_sk#9, d_year#74, d_qoy#75] +Condition : ((((isnotnull(d_year#74) AND isnotnull(d_qoy#75)) AND (d_year#74 = 2002)) AND (d_qoy#75 < 4)) AND isnotnull(d_date_sk#9)) + +(45) CometProject +Input [3]: [d_date_sk#9, d_year#74, d_qoy#75] +Arguments: [d_date_sk#9], [d_date_sk#9] + +(46) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#9] + +(47) BroadcastExchange +Input [1]: [d_date_sk#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +Subquery:2 Hosting operator id = 11 Hosting Expression = ws_sold_date_sk#11 IN dynamicpruning#8 + +Subquery:3 Hosting operator id = 18 Hosting Expression = cs_sold_date_sk#15 IN dynamicpruning#8 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35/simplified.txt new file mode 100644 index 0000000000..dc724ca919 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35/simplified.txt @@ -0,0 +1,74 @@ +TakeOrderedAndProject [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count,cnt1,avg(cd_dep_count),max(cd_dep_count),sum(cd_dep_count),cnt2,avg(cd_dep_employed_count),max(cd_dep_employed_count),sum(cd_dep_employed_count),cnt3,avg(cd_dep_college_count),max(cd_dep_college_count),sum(cd_dep_college_count)] + WholeStageCodegen (10) + HashAggregate [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count,count,sum,count,max,sum,sum,count,max,sum,sum,count,max,sum] [count(1),avg(cd_dep_count),max(cd_dep_count),sum(cd_dep_count),avg(cd_dep_employed_count),max(cd_dep_employed_count),sum(cd_dep_employed_count),avg(cd_dep_college_count),max(cd_dep_college_count),sum(cd_dep_college_count),cnt1,avg(cd_dep_count),max(cd_dep_count),sum(cd_dep_count),cnt2,avg(cd_dep_employed_count),max(cd_dep_employed_count),sum(cd_dep_employed_count),cnt3,avg(cd_dep_college_count),max(cd_dep_college_count),sum(cd_dep_college_count),count,sum,count,max,sum,sum,count,max,sum,sum,count,max,sum] + InputAdapter + Exchange [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] #1 + WholeStageCodegen (9) + HashAggregate [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] [count,sum,count,max,sum,sum,count,max,sum,sum,count,max,sum,count,sum,count,max,sum,sum,count,max,sum,sum,count,max,sum] + Project [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk] + Project [c_current_cdemo_sk,ca_state] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [c_current_cdemo_sk,c_current_addr_sk] + Filter [exists,exists] + BroadcastHashJoin [c_customer_sk,cs_ship_customer_sk] + BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + ColumnarToRow + InputAdapter + CometFilter [c_current_addr_sk,c_current_cdemo_sk] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (2) + Project [ss_customer_sk] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_qoy,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_qoy] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (4) + Project [ws_bill_customer_sk] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (6) + Project [cs_ship_customer_sk] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_ship_customer_sk,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (7) + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (8) + ColumnarToRow + InputAdapter + CometFilter [cd_demo_sk] + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35a/explain.txt new file mode 100644 index 0000000000..648b19933c --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35a/explain.txt @@ -0,0 +1,267 @@ +== Physical Plan == +TakeOrderedAndProject (40) ++- * HashAggregate (39) + +- Exchange (38) + +- * HashAggregate (37) + +- * Project (36) + +- * BroadcastHashJoin Inner BuildRight (35) + :- * Project (30) + : +- * BroadcastHashJoin Inner BuildRight (29) + : :- * Project (24) + : : +- * BroadcastHashJoin LeftSemi BuildRight (23) + : : :- * BroadcastHashJoin LeftSemi BuildRight (10) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.customer (1) + : : : +- BroadcastExchange (9) + : : : +- * Project (8) + : : : +- * BroadcastHashJoin Inner BuildRight (7) + : : : :- * ColumnarToRow (5) + : : : : +- CometScan parquet spark_catalog.default.store_sales (4) + : : : +- ReusedExchange (6) + : : +- BroadcastExchange (22) + : : +- Union (21) + : : :- * Project (15) + : : : +- * BroadcastHashJoin Inner BuildRight (14) + : : : :- * ColumnarToRow (12) + : : : : +- CometScan parquet spark_catalog.default.web_sales (11) + : : : +- ReusedExchange (13) + : : +- * Project (20) + : : +- * BroadcastHashJoin Inner BuildRight (19) + : : :- * ColumnarToRow (17) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (16) + : : +- ReusedExchange (18) + : +- BroadcastExchange (28) + : +- * ColumnarToRow (27) + : +- CometFilter (26) + : +- CometScan parquet spark_catalog.default.customer_address (25) + +- BroadcastExchange (34) + +- * ColumnarToRow (33) + +- CometFilter (32) + +- CometScan parquet spark_catalog.default.customer_demographics (31) + + +(1) Scan parquet spark_catalog.default.customer +Output [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_current_addr_sk), IsNotNull(c_current_cdemo_sk)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3] +Condition : (isnotnull(c_current_addr_sk#3) AND isnotnull(c_current_cdemo_sk#2)) + +(3) ColumnarToRow [codegen id : 9] +Input [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3] + +(4) Scan parquet spark_catalog.default.store_sales +Output [2]: [ss_customer_sk#4, ss_sold_date_sk#5] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#5), dynamicpruningexpression(ss_sold_date_sk#5 IN dynamicpruning#6)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 2] +Input [2]: [ss_customer_sk#4, ss_sold_date_sk#5] + +(6) ReusedExchange [Reuses operator id: 45] +Output [1]: [d_date_sk#7] + +(7) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [ss_sold_date_sk#5] +Right keys [1]: [d_date_sk#7] +Join type: Inner +Join condition: None + +(8) Project [codegen id : 2] +Output [1]: [ss_customer_sk#4] +Input [3]: [ss_customer_sk#4, ss_sold_date_sk#5, d_date_sk#7] + +(9) BroadcastExchange +Input [1]: [ss_customer_sk#4] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(10) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_customer_sk#1] +Right keys [1]: [ss_customer_sk#4] +Join type: LeftSemi +Join condition: None + +(11) Scan parquet spark_catalog.default.web_sales +Output [2]: [ws_bill_customer_sk#8, ws_sold_date_sk#9] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#9), dynamicpruningexpression(ws_sold_date_sk#9 IN dynamicpruning#10)] +ReadSchema: struct + +(12) ColumnarToRow [codegen id : 4] +Input [2]: [ws_bill_customer_sk#8, ws_sold_date_sk#9] + +(13) ReusedExchange [Reuses operator id: 45] +Output [1]: [d_date_sk#11] + +(14) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ws_sold_date_sk#9] +Right keys [1]: [d_date_sk#11] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 4] +Output [1]: [ws_bill_customer_sk#8 AS customsk#12] +Input [3]: [ws_bill_customer_sk#8, ws_sold_date_sk#9, d_date_sk#11] + +(16) Scan parquet spark_catalog.default.catalog_sales +Output [2]: [cs_ship_customer_sk#13, cs_sold_date_sk#14] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#14), dynamicpruningexpression(cs_sold_date_sk#14 IN dynamicpruning#15)] +ReadSchema: struct + +(17) ColumnarToRow [codegen id : 6] +Input [2]: [cs_ship_customer_sk#13, cs_sold_date_sk#14] + +(18) ReusedExchange [Reuses operator id: 45] +Output [1]: [d_date_sk#16] + +(19) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [cs_sold_date_sk#14] +Right keys [1]: [d_date_sk#16] +Join type: Inner +Join condition: None + +(20) Project [codegen id : 6] +Output [1]: [cs_ship_customer_sk#13 AS customsk#17] +Input [3]: [cs_ship_customer_sk#13, cs_sold_date_sk#14, d_date_sk#16] + +(21) Union + +(22) BroadcastExchange +Input [1]: [customsk#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(23) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_customer_sk#1] +Right keys [1]: [customsk#12] +Join type: LeftSemi +Join condition: None + +(24) Project [codegen id : 9] +Output [2]: [c_current_cdemo_sk#2, c_current_addr_sk#3] +Input [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3] + +(25) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#18, ca_state#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk)] +ReadSchema: struct + +(26) CometFilter +Input [2]: [ca_address_sk#18, ca_state#19] +Condition : isnotnull(ca_address_sk#18) + +(27) ColumnarToRow [codegen id : 7] +Input [2]: [ca_address_sk#18, ca_state#19] + +(28) BroadcastExchange +Input [2]: [ca_address_sk#18, ca_state#19] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(29) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_current_addr_sk#3] +Right keys [1]: [ca_address_sk#18] +Join type: Inner +Join condition: None + +(30) Project [codegen id : 9] +Output [2]: [c_current_cdemo_sk#2, ca_state#19] +Input [4]: [c_current_cdemo_sk#2, c_current_addr_sk#3, ca_address_sk#18, ca_state#19] + +(31) Scan parquet spark_catalog.default.customer_demographics +Output [6]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(32) CometFilter +Input [6]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Condition : isnotnull(cd_demo_sk#20) + +(33) ColumnarToRow [codegen id : 8] +Input [6]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] + +(34) BroadcastExchange +Input [6]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(35) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_current_cdemo_sk#2] +Right keys [1]: [cd_demo_sk#20] +Join type: Inner +Join condition: None + +(36) Project [codegen id : 9] +Output [6]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Input [8]: [c_current_cdemo_sk#2, ca_state#19, cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] + +(37) HashAggregate [codegen id : 9] +Input [6]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Keys [6]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Functions [10]: [partial_count(1), partial_avg(cd_dep_count#23), partial_max(cd_dep_count#23), partial_sum(cd_dep_count#23), partial_avg(cd_dep_employed_count#24), partial_max(cd_dep_employed_count#24), partial_sum(cd_dep_employed_count#24), partial_avg(cd_dep_college_count#25), partial_max(cd_dep_college_count#25), partial_sum(cd_dep_college_count#25)] +Aggregate Attributes [13]: [count#26, sum#27, count#28, max#29, sum#30, sum#31, count#32, max#33, sum#34, sum#35, count#36, max#37, sum#38] +Results [19]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25, count#39, sum#40, count#41, max#42, sum#43, sum#44, count#45, max#46, sum#47, sum#48, count#49, max#50, sum#51] + +(38) Exchange +Input [19]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25, count#39, sum#40, count#41, max#42, sum#43, sum#44, count#45, max#46, sum#47, sum#48, count#49, max#50, sum#51] +Arguments: hashpartitioning(ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(39) HashAggregate [codegen id : 10] +Input [19]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25, count#39, sum#40, count#41, max#42, sum#43, sum#44, count#45, max#46, sum#47, sum#48, count#49, max#50, sum#51] +Keys [6]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Functions [10]: [count(1), avg(cd_dep_count#23), max(cd_dep_count#23), sum(cd_dep_count#23), avg(cd_dep_employed_count#24), max(cd_dep_employed_count#24), sum(cd_dep_employed_count#24), avg(cd_dep_college_count#25), max(cd_dep_college_count#25), sum(cd_dep_college_count#25)] +Aggregate Attributes [10]: [count(1)#52, avg(cd_dep_count#23)#53, max(cd_dep_count#23)#54, sum(cd_dep_count#23)#55, avg(cd_dep_employed_count#24)#56, max(cd_dep_employed_count#24)#57, sum(cd_dep_employed_count#24)#58, avg(cd_dep_college_count#25)#59, max(cd_dep_college_count#25)#60, sum(cd_dep_college_count#25)#61] +Results [18]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, count(1)#52 AS cnt1#62, avg(cd_dep_count#23)#53 AS avg(cd_dep_count)#63, max(cd_dep_count#23)#54 AS max(cd_dep_count)#64, sum(cd_dep_count#23)#55 AS sum(cd_dep_count)#65, cd_dep_employed_count#24, count(1)#52 AS cnt2#66, avg(cd_dep_employed_count#24)#56 AS avg(cd_dep_employed_count)#67, max(cd_dep_employed_count#24)#57 AS max(cd_dep_employed_count)#68, sum(cd_dep_employed_count#24)#58 AS sum(cd_dep_employed_count)#69, cd_dep_college_count#25, count(1)#52 AS cnt3#70, avg(cd_dep_college_count#25)#59 AS avg(cd_dep_college_count)#71, max(cd_dep_college_count#25)#60 AS max(cd_dep_college_count)#72, sum(cd_dep_college_count#25)#61 AS sum(cd_dep_college_count)#73] + +(40) TakeOrderedAndProject +Input [18]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cnt1#62, avg(cd_dep_count)#63, max(cd_dep_count)#64, sum(cd_dep_count)#65, cd_dep_employed_count#24, cnt2#66, avg(cd_dep_employed_count)#67, max(cd_dep_employed_count)#68, sum(cd_dep_employed_count)#69, cd_dep_college_count#25, cnt3#70, avg(cd_dep_college_count)#71, max(cd_dep_college_count)#72, sum(cd_dep_college_count)#73] +Arguments: 100, [ca_state#19 ASC NULLS FIRST, cd_gender#21 ASC NULLS FIRST, cd_marital_status#22 ASC NULLS FIRST, cd_dep_count#23 ASC NULLS FIRST, cd_dep_employed_count#24 ASC NULLS FIRST, cd_dep_college_count#25 ASC NULLS FIRST], [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cnt1#62, avg(cd_dep_count)#63, max(cd_dep_count)#64, sum(cd_dep_count)#65, cd_dep_employed_count#24, cnt2#66, avg(cd_dep_employed_count)#67, max(cd_dep_employed_count)#68, sum(cd_dep_employed_count)#69, cd_dep_college_count#25, cnt3#70, avg(cd_dep_college_count)#71, max(cd_dep_college_count)#72, sum(cd_dep_college_count)#73] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6 +BroadcastExchange (45) ++- * ColumnarToRow (44) + +- CometProject (43) + +- CometFilter (42) + +- CometScan parquet spark_catalog.default.date_dim (41) + + +(41) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#7, d_year#74, d_qoy#75] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_qoy), EqualTo(d_year,1999), LessThan(d_qoy,4), IsNotNull(d_date_sk)] +ReadSchema: struct + +(42) CometFilter +Input [3]: [d_date_sk#7, d_year#74, d_qoy#75] +Condition : ((((isnotnull(d_year#74) AND isnotnull(d_qoy#75)) AND (d_year#74 = 1999)) AND (d_qoy#75 < 4)) AND isnotnull(d_date_sk#7)) + +(43) CometProject +Input [3]: [d_date_sk#7, d_year#74, d_qoy#75] +Arguments: [d_date_sk#7], [d_date_sk#7] + +(44) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#7] + +(45) BroadcastExchange +Input [1]: [d_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6] + +Subquery:2 Hosting operator id = 11 Hosting Expression = ws_sold_date_sk#9 IN dynamicpruning#6 + +Subquery:3 Hosting operator id = 16 Hosting Expression = cs_sold_date_sk#14 IN dynamicpruning#6 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35a/simplified.txt new file mode 100644 index 0000000000..e5cb940552 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35a/simplified.txt @@ -0,0 +1,71 @@ +TakeOrderedAndProject [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count,cnt1,avg(cd_dep_count),max(cd_dep_count),sum(cd_dep_count),cnt2,avg(cd_dep_employed_count),max(cd_dep_employed_count),sum(cd_dep_employed_count),cnt3,avg(cd_dep_college_count),max(cd_dep_college_count),sum(cd_dep_college_count)] + WholeStageCodegen (10) + HashAggregate [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count,count,sum,count,max,sum,sum,count,max,sum,sum,count,max,sum] [count(1),avg(cd_dep_count),max(cd_dep_count),sum(cd_dep_count),avg(cd_dep_employed_count),max(cd_dep_employed_count),sum(cd_dep_employed_count),avg(cd_dep_college_count),max(cd_dep_college_count),sum(cd_dep_college_count),cnt1,avg(cd_dep_count),max(cd_dep_count),sum(cd_dep_count),cnt2,avg(cd_dep_employed_count),max(cd_dep_employed_count),sum(cd_dep_employed_count),cnt3,avg(cd_dep_college_count),max(cd_dep_college_count),sum(cd_dep_college_count),count,sum,count,max,sum,sum,count,max,sum,sum,count,max,sum] + InputAdapter + Exchange [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] #1 + WholeStageCodegen (9) + HashAggregate [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] [count,sum,count,max,sum,sum,count,max,sum,sum,count,max,sum,count,sum,count,max,sum,sum,count,max,sum,sum,count,max,sum] + Project [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk] + Project [c_current_cdemo_sk,ca_state] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [c_current_cdemo_sk,c_current_addr_sk] + BroadcastHashJoin [c_customer_sk,customsk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + ColumnarToRow + InputAdapter + CometFilter [c_current_addr_sk,c_current_cdemo_sk] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (2) + Project [ss_customer_sk] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_qoy,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_qoy] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + Union + WholeStageCodegen (4) + Project [ws_bill_customer_sk] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + WholeStageCodegen (6) + Project [cs_ship_customer_sk] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_ship_customer_sk,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (7) + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (8) + ColumnarToRow + InputAdapter + CometFilter [cd_demo_sk] + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q36a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q36a/explain.txt new file mode 100644 index 0000000000..2610a698cb --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q36a/explain.txt @@ -0,0 +1,279 @@ +== Physical Plan == +TakeOrderedAndProject (41) ++- * Project (40) + +- Window (39) + +- * Sort (38) + +- Exchange (37) + +- * HashAggregate (36) + +- Exchange (35) + +- * HashAggregate (34) + +- Union (33) + :- * HashAggregate (22) + : +- Exchange (21) + : +- * HashAggregate (20) + : +- * Project (19) + : +- * BroadcastHashJoin Inner BuildRight (18) + : :- * Project (12) + : : +- * BroadcastHashJoin Inner BuildRight (11) + : : :- * Project (6) + : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- ReusedExchange (4) + : : +- BroadcastExchange (10) + : : +- * ColumnarToRow (9) + : : +- CometFilter (8) + : : +- CometScan parquet spark_catalog.default.item (7) + : +- BroadcastExchange (17) + : +- * ColumnarToRow (16) + : +- CometProject (15) + : +- CometFilter (14) + : +- CometScan parquet spark_catalog.default.store (13) + :- * HashAggregate (27) + : +- Exchange (26) + : +- * HashAggregate (25) + : +- * HashAggregate (24) + : +- ReusedExchange (23) + +- * HashAggregate (32) + +- Exchange (31) + +- * HashAggregate (30) + +- * HashAggregate (29) + +- ReusedExchange (28) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, ss_sold_date_sk#5] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#5), dynamicpruningexpression(ss_sold_date_sk#5 IN dynamicpruning#6)] +PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(2) CometFilter +Input [5]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, ss_sold_date_sk#5] +Condition : (isnotnull(ss_item_sk#1) AND isnotnull(ss_store_sk#2)) + +(3) ColumnarToRow [codegen id : 4] +Input [5]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, ss_sold_date_sk#5] + +(4) ReusedExchange [Reuses operator id: 46] +Output [1]: [d_date_sk#7] + +(5) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_date_sk#5] +Right keys [1]: [d_date_sk#7] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 4] +Output [4]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4] +Input [6]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, ss_sold_date_sk#5, d_date_sk#7] + +(7) Scan parquet spark_catalog.default.item +Output [3]: [i_item_sk#8, i_class#9, i_category#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(8) CometFilter +Input [3]: [i_item_sk#8, i_class#9, i_category#10] +Condition : isnotnull(i_item_sk#8) + +(9) ColumnarToRow [codegen id : 2] +Input [3]: [i_item_sk#8, i_class#9, i_category#10] + +(10) BroadcastExchange +Input [3]: [i_item_sk#8, i_class#9, i_category#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(11) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#8] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 4] +Output [5]: [ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, i_class#9, i_category#10] +Input [7]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, i_item_sk#8, i_class#9, i_category#10] + +(13) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#11, s_state#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_state), EqualTo(s_state,TN), IsNotNull(s_store_sk)] +ReadSchema: struct + +(14) CometFilter +Input [2]: [s_store_sk#11, s_state#12] +Condition : ((isnotnull(s_state#12) AND (s_state#12 = TN)) AND isnotnull(s_store_sk#11)) + +(15) CometProject +Input [2]: [s_store_sk#11, s_state#12] +Arguments: [s_store_sk#11], [s_store_sk#11] + +(16) ColumnarToRow [codegen id : 3] +Input [1]: [s_store_sk#11] + +(17) BroadcastExchange +Input [1]: [s_store_sk#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(18) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_store_sk#2] +Right keys [1]: [s_store_sk#11] +Join type: Inner +Join condition: None + +(19) Project [codegen id : 4] +Output [4]: [ss_ext_sales_price#3, ss_net_profit#4, i_class#9, i_category#10] +Input [6]: [ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, i_class#9, i_category#10, s_store_sk#11] + +(20) HashAggregate [codegen id : 4] +Input [4]: [ss_ext_sales_price#3, ss_net_profit#4, i_class#9, i_category#10] +Keys [2]: [i_category#10, i_class#9] +Functions [2]: [partial_sum(UnscaledValue(ss_net_profit#4)), partial_sum(UnscaledValue(ss_ext_sales_price#3))] +Aggregate Attributes [2]: [sum#13, sum#14] +Results [4]: [i_category#10, i_class#9, sum#15, sum#16] + +(21) Exchange +Input [4]: [i_category#10, i_class#9, sum#15, sum#16] +Arguments: hashpartitioning(i_category#10, i_class#9, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(22) HashAggregate [codegen id : 5] +Input [4]: [i_category#10, i_class#9, sum#15, sum#16] +Keys [2]: [i_category#10, i_class#9] +Functions [2]: [sum(UnscaledValue(ss_net_profit#4)), sum(UnscaledValue(ss_ext_sales_price#3))] +Aggregate Attributes [2]: [sum(UnscaledValue(ss_net_profit#4))#17, sum(UnscaledValue(ss_ext_sales_price#3))#18] +Results [6]: [cast((MakeDecimal(sum(UnscaledValue(ss_net_profit#4))#17,17,2) / MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#3))#18,17,2)) as decimal(38,11)) AS gross_margin#19, i_category#10, i_class#9, 0 AS t_category#20, 0 AS t_class#21, 0 AS lochierarchy#22] + +(23) ReusedExchange [Reuses operator id: 21] +Output [4]: [i_category#23, i_class#24, sum#25, sum#26] + +(24) HashAggregate [codegen id : 10] +Input [4]: [i_category#23, i_class#24, sum#25, sum#26] +Keys [2]: [i_category#23, i_class#24] +Functions [2]: [sum(UnscaledValue(ss_net_profit#27)), sum(UnscaledValue(ss_ext_sales_price#28))] +Aggregate Attributes [2]: [sum(UnscaledValue(ss_net_profit#27))#29, sum(UnscaledValue(ss_ext_sales_price#28))#30] +Results [3]: [MakeDecimal(sum(UnscaledValue(ss_net_profit#27))#29,17,2) AS ss_net_profit#31, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#28))#30,17,2) AS ss_ext_sales_price#32, i_category#23] + +(25) HashAggregate [codegen id : 10] +Input [3]: [ss_net_profit#31, ss_ext_sales_price#32, i_category#23] +Keys [1]: [i_category#23] +Functions [2]: [partial_sum(ss_net_profit#31), partial_sum(ss_ext_sales_price#32)] +Aggregate Attributes [4]: [sum#33, isEmpty#34, sum#35, isEmpty#36] +Results [5]: [i_category#23, sum#37, isEmpty#38, sum#39, isEmpty#40] + +(26) Exchange +Input [5]: [i_category#23, sum#37, isEmpty#38, sum#39, isEmpty#40] +Arguments: hashpartitioning(i_category#23, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(27) HashAggregate [codegen id : 11] +Input [5]: [i_category#23, sum#37, isEmpty#38, sum#39, isEmpty#40] +Keys [1]: [i_category#23] +Functions [2]: [sum(ss_net_profit#31), sum(ss_ext_sales_price#32)] +Aggregate Attributes [2]: [sum(ss_net_profit#31)#41, sum(ss_ext_sales_price#32)#42] +Results [6]: [(sum(ss_net_profit#31)#41 / sum(ss_ext_sales_price#32)#42) AS gross_margin#43, i_category#23, null AS i_class#44, 0 AS t_category#45, 1 AS t_class#46, 1 AS lochierarchy#47] + +(28) ReusedExchange [Reuses operator id: 21] +Output [4]: [i_category#48, i_class#49, sum#50, sum#51] + +(29) HashAggregate [codegen id : 16] +Input [4]: [i_category#48, i_class#49, sum#50, sum#51] +Keys [2]: [i_category#48, i_class#49] +Functions [2]: [sum(UnscaledValue(ss_net_profit#52)), sum(UnscaledValue(ss_ext_sales_price#53))] +Aggregate Attributes [2]: [sum(UnscaledValue(ss_net_profit#52))#29, sum(UnscaledValue(ss_ext_sales_price#53))#30] +Results [2]: [MakeDecimal(sum(UnscaledValue(ss_net_profit#52))#29,17,2) AS ss_net_profit#54, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#53))#30,17,2) AS ss_ext_sales_price#55] + +(30) HashAggregate [codegen id : 16] +Input [2]: [ss_net_profit#54, ss_ext_sales_price#55] +Keys: [] +Functions [2]: [partial_sum(ss_net_profit#54), partial_sum(ss_ext_sales_price#55)] +Aggregate Attributes [4]: [sum#56, isEmpty#57, sum#58, isEmpty#59] +Results [4]: [sum#60, isEmpty#61, sum#62, isEmpty#63] + +(31) Exchange +Input [4]: [sum#60, isEmpty#61, sum#62, isEmpty#63] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=5] + +(32) HashAggregate [codegen id : 17] +Input [4]: [sum#60, isEmpty#61, sum#62, isEmpty#63] +Keys: [] +Functions [2]: [sum(ss_net_profit#54), sum(ss_ext_sales_price#55)] +Aggregate Attributes [2]: [sum(ss_net_profit#54)#64, sum(ss_ext_sales_price#55)#65] +Results [6]: [(sum(ss_net_profit#54)#64 / sum(ss_ext_sales_price#55)#65) AS gross_margin#66, null AS i_category#67, null AS i_class#68, 1 AS t_category#69, 1 AS t_class#70, 2 AS lochierarchy#71] + +(33) Union + +(34) HashAggregate [codegen id : 18] +Input [6]: [gross_margin#19, i_category#10, i_class#9, t_category#20, t_class#21, lochierarchy#22] +Keys [6]: [gross_margin#19, i_category#10, i_class#9, t_category#20, t_class#21, lochierarchy#22] +Functions: [] +Aggregate Attributes: [] +Results [6]: [gross_margin#19, i_category#10, i_class#9, t_category#20, t_class#21, lochierarchy#22] + +(35) Exchange +Input [6]: [gross_margin#19, i_category#10, i_class#9, t_category#20, t_class#21, lochierarchy#22] +Arguments: hashpartitioning(gross_margin#19, i_category#10, i_class#9, t_category#20, t_class#21, lochierarchy#22, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(36) HashAggregate [codegen id : 19] +Input [6]: [gross_margin#19, i_category#10, i_class#9, t_category#20, t_class#21, lochierarchy#22] +Keys [6]: [gross_margin#19, i_category#10, i_class#9, t_category#20, t_class#21, lochierarchy#22] +Functions: [] +Aggregate Attributes: [] +Results [5]: [gross_margin#19, i_category#10, i_class#9, lochierarchy#22, CASE WHEN (t_class#21 = 0) THEN i_category#10 END AS _w0#72] + +(37) Exchange +Input [5]: [gross_margin#19, i_category#10, i_class#9, lochierarchy#22, _w0#72] +Arguments: hashpartitioning(lochierarchy#22, _w0#72, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(38) Sort [codegen id : 20] +Input [5]: [gross_margin#19, i_category#10, i_class#9, lochierarchy#22, _w0#72] +Arguments: [lochierarchy#22 ASC NULLS FIRST, _w0#72 ASC NULLS FIRST, gross_margin#19 ASC NULLS FIRST], false, 0 + +(39) Window +Input [5]: [gross_margin#19, i_category#10, i_class#9, lochierarchy#22, _w0#72] +Arguments: [rank(gross_margin#19) windowspecdefinition(lochierarchy#22, _w0#72, gross_margin#19 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rank_within_parent#73], [lochierarchy#22, _w0#72], [gross_margin#19 ASC NULLS FIRST] + +(40) Project [codegen id : 21] +Output [5]: [gross_margin#19, i_category#10, i_class#9, lochierarchy#22, rank_within_parent#73] +Input [6]: [gross_margin#19, i_category#10, i_class#9, lochierarchy#22, _w0#72, rank_within_parent#73] + +(41) TakeOrderedAndProject +Input [5]: [gross_margin#19, i_category#10, i_class#9, lochierarchy#22, rank_within_parent#73] +Arguments: 100, [lochierarchy#22 DESC NULLS LAST, CASE WHEN (lochierarchy#22 = 0) THEN i_category#10 END ASC NULLS FIRST, rank_within_parent#73 ASC NULLS FIRST], [gross_margin#19, i_category#10, i_class#9, lochierarchy#22, rank_within_parent#73] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6 +BroadcastExchange (46) ++- * ColumnarToRow (45) + +- CometProject (44) + +- CometFilter (43) + +- CometScan parquet spark_catalog.default.date_dim (42) + + +(42) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#7, d_year#74] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(43) CometFilter +Input [2]: [d_date_sk#7, d_year#74] +Condition : ((isnotnull(d_year#74) AND (d_year#74 = 2001)) AND isnotnull(d_date_sk#7)) + +(44) CometProject +Input [2]: [d_date_sk#7, d_year#74] +Arguments: [d_date_sk#7], [d_date_sk#7] + +(45) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#7] + +(46) BroadcastExchange +Input [1]: [d_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q36a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q36a/simplified.txt new file mode 100644 index 0000000000..f265d20995 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q36a/simplified.txt @@ -0,0 +1,76 @@ +TakeOrderedAndProject [lochierarchy,i_category,rank_within_parent,gross_margin,i_class] + WholeStageCodegen (21) + Project [gross_margin,i_category,i_class,lochierarchy,rank_within_parent] + InputAdapter + Window [gross_margin,lochierarchy,_w0] + WholeStageCodegen (20) + Sort [lochierarchy,_w0,gross_margin] + InputAdapter + Exchange [lochierarchy,_w0] #1 + WholeStageCodegen (19) + HashAggregate [gross_margin,i_category,i_class,t_category,t_class,lochierarchy] [_w0] + InputAdapter + Exchange [gross_margin,i_category,i_class,t_category,t_class,lochierarchy] #2 + WholeStageCodegen (18) + HashAggregate [gross_margin,i_category,i_class,t_category,t_class,lochierarchy] + InputAdapter + Union + WholeStageCodegen (5) + HashAggregate [i_category,i_class,sum,sum] [sum(UnscaledValue(ss_net_profit)),sum(UnscaledValue(ss_ext_sales_price)),gross_margin,t_category,t_class,lochierarchy,sum,sum] + InputAdapter + Exchange [i_category,i_class] #3 + WholeStageCodegen (4) + HashAggregate [i_category,i_class,ss_net_profit,ss_ext_sales_price] [sum,sum,sum,sum] + Project [ss_ext_sales_price,ss_net_profit,i_class,i_category] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_store_sk,ss_ext_sales_price,ss_net_profit,i_class,i_category] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_store_sk,ss_ext_sales_price,ss_net_profit] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk,ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_ext_sales_price,ss_net_profit,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_class,i_category] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometProject [s_store_sk] + CometFilter [s_state,s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk,s_state] + WholeStageCodegen (11) + HashAggregate [i_category,sum,isEmpty,sum,isEmpty] [sum(ss_net_profit),sum(ss_ext_sales_price),gross_margin,i_class,t_category,t_class,lochierarchy,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [i_category] #7 + WholeStageCodegen (10) + HashAggregate [i_category,ss_net_profit,ss_ext_sales_price] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + HashAggregate [i_category,i_class,sum,sum] [sum(UnscaledValue(ss_net_profit)),sum(UnscaledValue(ss_ext_sales_price)),ss_net_profit,ss_ext_sales_price,sum,sum] + InputAdapter + ReusedExchange [i_category,i_class,sum,sum] #3 + WholeStageCodegen (17) + HashAggregate [sum,isEmpty,sum,isEmpty] [sum(ss_net_profit),sum(ss_ext_sales_price),gross_margin,i_category,i_class,t_category,t_class,lochierarchy,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange #8 + WholeStageCodegen (16) + HashAggregate [ss_net_profit,ss_ext_sales_price] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + HashAggregate [i_category,i_class,sum,sum] [sum(UnscaledValue(ss_net_profit)),sum(UnscaledValue(ss_ext_sales_price)),ss_net_profit,ss_ext_sales_price,sum,sum] + InputAdapter + ReusedExchange [i_category,i_class,sum,sum] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q47/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q47/explain.txt new file mode 100644 index 0000000000..9cb7b35cb4 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q47/explain.txt @@ -0,0 +1,279 @@ +== Physical Plan == +TakeOrderedAndProject (45) ++- * Project (44) + +- * BroadcastHashJoin Inner BuildRight (43) + :- * Project (37) + : +- * BroadcastHashJoin Inner BuildRight (36) + : :- * Project (28) + : : +- * Filter (27) + : : +- Window (26) + : : +- * Filter (25) + : : +- Window (24) + : : +- * Sort (23) + : : +- Exchange (22) + : : +- * HashAggregate (21) + : : +- Exchange (20) + : : +- * HashAggregate (19) + : : +- * Project (18) + : : +- * BroadcastHashJoin Inner BuildRight (17) + : : :- * Project (12) + : : : +- * BroadcastHashJoin Inner BuildRight (11) + : : : :- * Project (9) + : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) + : : : : : +- CometScan parquet spark_catalog.default.item (1) + : : : : +- BroadcastExchange (7) + : : : : +- * ColumnarToRow (6) + : : : : +- CometFilter (5) + : : : : +- CometScan parquet spark_catalog.default.store_sales (4) + : : : +- ReusedExchange (10) + : : +- BroadcastExchange (16) + : : +- * ColumnarToRow (15) + : : +- CometFilter (14) + : : +- CometScan parquet spark_catalog.default.store (13) + : +- BroadcastExchange (35) + : +- * Project (34) + : +- Window (33) + : +- * Sort (32) + : +- Exchange (31) + : +- * HashAggregate (30) + : +- ReusedExchange (29) + +- BroadcastExchange (42) + +- * Project (41) + +- Window (40) + +- * Sort (39) + +- ReusedExchange (38) + + +(1) Scan parquet spark_catalog.default.item +Output [3]: [i_item_sk#1, i_brand#2, i_category#3] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_category), IsNotNull(i_brand)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [i_item_sk#1, i_brand#2, i_category#3] +Condition : ((isnotnull(i_item_sk#1) AND isnotnull(i_category#3)) AND isnotnull(i_brand#2)) + +(3) ColumnarToRow [codegen id : 4] +Input [3]: [i_item_sk#1, i_brand#2, i_category#3] + +(4) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#4, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sold_date_sk#7 IN dynamicpruning#8)] +PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(5) CometFilter +Input [4]: [ss_item_sk#4, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7] +Condition : (isnotnull(ss_item_sk#4) AND isnotnull(ss_store_sk#5)) + +(6) ColumnarToRow [codegen id : 1] +Input [4]: [ss_item_sk#4, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7] + +(7) BroadcastExchange +Input [4]: [ss_item_sk#4, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [i_item_sk#1] +Right keys [1]: [ss_item_sk#4] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 4] +Output [5]: [i_brand#2, i_category#3, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7] +Input [7]: [i_item_sk#1, i_brand#2, i_category#3, ss_item_sk#4, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7] + +(10) ReusedExchange [Reuses operator id: 49] +Output [3]: [d_date_sk#9, d_year#10, d_moy#11] + +(11) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_date_sk#7] +Right keys [1]: [d_date_sk#9] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 4] +Output [6]: [i_brand#2, i_category#3, ss_store_sk#5, ss_sales_price#6, d_year#10, d_moy#11] +Input [8]: [i_brand#2, i_category#3, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7, d_date_sk#9, d_year#10, d_moy#11] + +(13) Scan parquet spark_catalog.default.store +Output [3]: [s_store_sk#12, s_store_name#13, s_company_name#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk), IsNotNull(s_store_name), IsNotNull(s_company_name)] +ReadSchema: struct + +(14) CometFilter +Input [3]: [s_store_sk#12, s_store_name#13, s_company_name#14] +Condition : ((isnotnull(s_store_sk#12) AND isnotnull(s_store_name#13)) AND isnotnull(s_company_name#14)) + +(15) ColumnarToRow [codegen id : 3] +Input [3]: [s_store_sk#12, s_store_name#13, s_company_name#14] + +(16) BroadcastExchange +Input [3]: [s_store_sk#12, s_store_name#13, s_company_name#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(17) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_store_sk#5] +Right keys [1]: [s_store_sk#12] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 4] +Output [7]: [i_brand#2, i_category#3, ss_sales_price#6, d_year#10, d_moy#11, s_store_name#13, s_company_name#14] +Input [9]: [i_brand#2, i_category#3, ss_store_sk#5, ss_sales_price#6, d_year#10, d_moy#11, s_store_sk#12, s_store_name#13, s_company_name#14] + +(19) HashAggregate [codegen id : 4] +Input [7]: [i_brand#2, i_category#3, ss_sales_price#6, d_year#10, d_moy#11, s_store_name#13, s_company_name#14] +Keys [6]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11] +Functions [1]: [partial_sum(UnscaledValue(ss_sales_price#6))] +Aggregate Attributes [1]: [sum#15] +Results [7]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum#16] + +(20) Exchange +Input [7]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum#16] +Arguments: hashpartitioning(i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(21) HashAggregate [codegen id : 5] +Input [7]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum#16] +Keys [6]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11] +Functions [1]: [sum(UnscaledValue(ss_sales_price#6))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_sales_price#6))#17] +Results [8]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, MakeDecimal(sum(UnscaledValue(ss_sales_price#6))#17,17,2) AS sum_sales#18, MakeDecimal(sum(UnscaledValue(ss_sales_price#6))#17,17,2) AS _w0#19] + +(22) Exchange +Input [8]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, _w0#19] +Arguments: hashpartitioning(i_category#3, i_brand#2, s_store_name#13, s_company_name#14, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(23) Sort [codegen id : 6] +Input [8]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, _w0#19] +Arguments: [i_category#3 ASC NULLS FIRST, i_brand#2 ASC NULLS FIRST, s_store_name#13 ASC NULLS FIRST, s_company_name#14 ASC NULLS FIRST, d_year#10 ASC NULLS FIRST, d_moy#11 ASC NULLS FIRST], false, 0 + +(24) Window +Input [8]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, _w0#19] +Arguments: [rank(d_year#10, d_moy#11) windowspecdefinition(i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10 ASC NULLS FIRST, d_moy#11 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rn#20], [i_category#3, i_brand#2, s_store_name#13, s_company_name#14], [d_year#10 ASC NULLS FIRST, d_moy#11 ASC NULLS FIRST] + +(25) Filter [codegen id : 7] +Input [9]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, _w0#19, rn#20] +Condition : (isnotnull(d_year#10) AND (d_year#10 = 1999)) + +(26) Window +Input [9]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, _w0#19, rn#20] +Arguments: [avg(_w0#19) windowspecdefinition(i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, specifiedwindowframe(RowFrame, unboundedpreceding$(), unboundedfollowing$())) AS avg_monthly_sales#21], [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10] + +(27) Filter [codegen id : 22] +Input [10]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, _w0#19, rn#20, avg_monthly_sales#21] +Condition : ((isnotnull(avg_monthly_sales#21) AND (avg_monthly_sales#21 > 0.000000)) AND CASE WHEN (avg_monthly_sales#21 > 0.000000) THEN ((abs((sum_sales#18 - avg_monthly_sales#21)) / avg_monthly_sales#21) > 0.1000000000000000) END) + +(28) Project [codegen id : 22] +Output [9]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, avg_monthly_sales#21, rn#20] +Input [10]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, _w0#19, rn#20, avg_monthly_sales#21] + +(29) ReusedExchange [Reuses operator id: 20] +Output [7]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26, d_moy#27, sum#28] + +(30) HashAggregate [codegen id : 12] +Input [7]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26, d_moy#27, sum#28] +Keys [6]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26, d_moy#27] +Functions [1]: [sum(UnscaledValue(ss_sales_price#29))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_sales_price#29))#17] +Results [7]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26, d_moy#27, MakeDecimal(sum(UnscaledValue(ss_sales_price#29))#17,17,2) AS sum_sales#30] + +(31) Exchange +Input [7]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26, d_moy#27, sum_sales#30] +Arguments: hashpartitioning(i_category#22, i_brand#23, s_store_name#24, s_company_name#25, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(32) Sort [codegen id : 13] +Input [7]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26, d_moy#27, sum_sales#30] +Arguments: [i_category#22 ASC NULLS FIRST, i_brand#23 ASC NULLS FIRST, s_store_name#24 ASC NULLS FIRST, s_company_name#25 ASC NULLS FIRST, d_year#26 ASC NULLS FIRST, d_moy#27 ASC NULLS FIRST], false, 0 + +(33) Window +Input [7]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26, d_moy#27, sum_sales#30] +Arguments: [rank(d_year#26, d_moy#27) windowspecdefinition(i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26 ASC NULLS FIRST, d_moy#27 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rn#31], [i_category#22, i_brand#23, s_store_name#24, s_company_name#25], [d_year#26 ASC NULLS FIRST, d_moy#27 ASC NULLS FIRST] + +(34) Project [codegen id : 14] +Output [6]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, sum_sales#30, rn#31] +Input [8]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26, d_moy#27, sum_sales#30, rn#31] + +(35) BroadcastExchange +Input [6]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, sum_sales#30, rn#31] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true], input[1, string, true], input[2, string, true], input[3, string, true], (input[5, int, false] + 1)),false), [plan_id=6] + +(36) BroadcastHashJoin [codegen id : 22] +Left keys [5]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, rn#20] +Right keys [5]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, (rn#31 + 1)] +Join type: Inner +Join condition: None + +(37) Project [codegen id : 22] +Output [10]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, avg_monthly_sales#21, rn#20, sum_sales#30] +Input [15]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, avg_monthly_sales#21, rn#20, i_category#22, i_brand#23, s_store_name#24, s_company_name#25, sum_sales#30, rn#31] + +(38) ReusedExchange [Reuses operator id: 31] +Output [7]: [i_category#32, i_brand#33, s_store_name#34, s_company_name#35, d_year#36, d_moy#37, sum_sales#38] + +(39) Sort [codegen id : 20] +Input [7]: [i_category#32, i_brand#33, s_store_name#34, s_company_name#35, d_year#36, d_moy#37, sum_sales#38] +Arguments: [i_category#32 ASC NULLS FIRST, i_brand#33 ASC NULLS FIRST, s_store_name#34 ASC NULLS FIRST, s_company_name#35 ASC NULLS FIRST, d_year#36 ASC NULLS FIRST, d_moy#37 ASC NULLS FIRST], false, 0 + +(40) Window +Input [7]: [i_category#32, i_brand#33, s_store_name#34, s_company_name#35, d_year#36, d_moy#37, sum_sales#38] +Arguments: [rank(d_year#36, d_moy#37) windowspecdefinition(i_category#32, i_brand#33, s_store_name#34, s_company_name#35, d_year#36 ASC NULLS FIRST, d_moy#37 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rn#39], [i_category#32, i_brand#33, s_store_name#34, s_company_name#35], [d_year#36 ASC NULLS FIRST, d_moy#37 ASC NULLS FIRST] + +(41) Project [codegen id : 21] +Output [6]: [i_category#32, i_brand#33, s_store_name#34, s_company_name#35, sum_sales#38, rn#39] +Input [8]: [i_category#32, i_brand#33, s_store_name#34, s_company_name#35, d_year#36, d_moy#37, sum_sales#38, rn#39] + +(42) BroadcastExchange +Input [6]: [i_category#32, i_brand#33, s_store_name#34, s_company_name#35, sum_sales#38, rn#39] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true], input[1, string, true], input[2, string, true], input[3, string, true], (input[5, int, false] - 1)),false), [plan_id=7] + +(43) BroadcastHashJoin [codegen id : 22] +Left keys [5]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, rn#20] +Right keys [5]: [i_category#32, i_brand#33, s_store_name#34, s_company_name#35, (rn#39 - 1)] +Join type: Inner +Join condition: None + +(44) Project [codegen id : 22] +Output [7]: [i_category#3, d_year#10, d_moy#11, avg_monthly_sales#21, sum_sales#18, sum_sales#30 AS psum#40, sum_sales#38 AS nsum#41] +Input [16]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, avg_monthly_sales#21, rn#20, sum_sales#30, i_category#32, i_brand#33, s_store_name#34, s_company_name#35, sum_sales#38, rn#39] + +(45) TakeOrderedAndProject +Input [7]: [i_category#3, d_year#10, d_moy#11, avg_monthly_sales#21, sum_sales#18, psum#40, nsum#41] +Arguments: 100, [(sum_sales#18 - avg_monthly_sales#21) ASC NULLS FIRST, d_moy#11 ASC NULLS FIRST], [i_category#3, d_year#10, d_moy#11, avg_monthly_sales#21, sum_sales#18, psum#40, nsum#41] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (49) ++- * ColumnarToRow (48) + +- CometFilter (47) + +- CometScan parquet spark_catalog.default.date_dim (46) + + +(46) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#9, d_year#10, d_moy#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [Or(Or(EqualTo(d_year,1999),And(EqualTo(d_year,1998),EqualTo(d_moy,12))),And(EqualTo(d_year,2000),EqualTo(d_moy,1))), IsNotNull(d_date_sk)] +ReadSchema: struct + +(47) CometFilter +Input [3]: [d_date_sk#9, d_year#10, d_moy#11] +Condition : ((((d_year#10 = 1999) OR ((d_year#10 = 1998) AND (d_moy#11 = 12))) OR ((d_year#10 = 2000) AND (d_moy#11 = 1))) AND isnotnull(d_date_sk#9)) + +(48) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#9, d_year#10, d_moy#11] + +(49) BroadcastExchange +Input [3]: [d_date_sk#9, d_year#10, d_moy#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q47/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q47/simplified.txt new file mode 100644 index 0000000000..a548953052 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q47/simplified.txt @@ -0,0 +1,81 @@ +TakeOrderedAndProject [sum_sales,avg_monthly_sales,d_moy,i_category,d_year,psum,nsum] + WholeStageCodegen (22) + Project [i_category,d_year,d_moy,avg_monthly_sales,sum_sales,sum_sales,sum_sales] + BroadcastHashJoin [i_category,i_brand,s_store_name,s_company_name,rn,i_category,i_brand,s_store_name,s_company_name,rn] + Project [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy,sum_sales,avg_monthly_sales,rn,sum_sales] + BroadcastHashJoin [i_category,i_brand,s_store_name,s_company_name,rn,i_category,i_brand,s_store_name,s_company_name,rn] + Project [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy,sum_sales,avg_monthly_sales,rn] + Filter [avg_monthly_sales,sum_sales] + InputAdapter + Window [_w0,i_category,i_brand,s_store_name,s_company_name,d_year] + WholeStageCodegen (7) + Filter [d_year] + InputAdapter + Window [d_year,d_moy,i_category,i_brand,s_store_name,s_company_name] + WholeStageCodegen (6) + Sort [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy] + InputAdapter + Exchange [i_category,i_brand,s_store_name,s_company_name] #1 + WholeStageCodegen (5) + HashAggregate [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy,sum] [sum(UnscaledValue(ss_sales_price)),sum_sales,_w0,sum] + InputAdapter + Exchange [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy] #2 + WholeStageCodegen (4) + HashAggregate [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy,ss_sales_price] [sum,sum] + Project [i_brand,i_category,ss_sales_price,d_year,d_moy,s_store_name,s_company_name] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [i_brand,i_category,ss_store_sk,ss_sales_price,d_year,d_moy] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [i_brand,i_category,ss_store_sk,ss_sales_price,ss_sold_date_sk] + BroadcastHashJoin [i_item_sk,ss_item_sk] + ColumnarToRow + InputAdapter + CometFilter [i_item_sk,i_category,i_brand] + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_category] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk,ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_year,d_moy,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + ReusedExchange [d_date_sk,d_year,d_moy] #4 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometFilter [s_store_sk,s_store_name,s_company_name] + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name,s_company_name] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (14) + Project [i_category,i_brand,s_store_name,s_company_name,sum_sales,rn] + InputAdapter + Window [d_year,d_moy,i_category,i_brand,s_store_name,s_company_name] + WholeStageCodegen (13) + Sort [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy] + InputAdapter + Exchange [i_category,i_brand,s_store_name,s_company_name] #7 + WholeStageCodegen (12) + HashAggregate [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy,sum] [sum(UnscaledValue(ss_sales_price)),sum_sales,sum] + InputAdapter + ReusedExchange [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy,sum] #2 + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (21) + Project [i_category,i_brand,s_store_name,s_company_name,sum_sales,rn] + InputAdapter + Window [d_year,d_moy,i_category,i_brand,s_store_name,s_company_name] + WholeStageCodegen (20) + Sort [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy] + InputAdapter + ReusedExchange [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy,sum_sales] #7 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q49/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q49/explain.txt new file mode 100644 index 0000000000..6591c8b8a2 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q49/explain.txt @@ -0,0 +1,456 @@ +== Physical Plan == +TakeOrderedAndProject (74) ++- * HashAggregate (73) + +- Exchange (72) + +- * HashAggregate (71) + +- Union (70) + :- * Project (23) + : +- * Filter (22) + : +- Window (21) + : +- * Sort (20) + : +- Window (19) + : +- * Sort (18) + : +- Exchange (17) + : +- * HashAggregate (16) + : +- Exchange (15) + : +- * HashAggregate (14) + : +- * Project (13) + : +- * BroadcastHashJoin Inner BuildRight (12) + : :- * ColumnarToRow (10) + : : +- CometProject (9) + : : +- CometBroadcastHashJoin (8) + : : :- CometBroadcastExchange (4) + : : : +- CometProject (3) + : : : +- CometFilter (2) + : : : +- CometScan parquet spark_catalog.default.web_sales (1) + : : +- CometProject (7) + : : +- CometFilter (6) + : : +- CometScan parquet spark_catalog.default.web_returns (5) + : +- ReusedExchange (11) + :- * Project (46) + : +- * Filter (45) + : +- Window (44) + : +- * Sort (43) + : +- Window (42) + : +- * Sort (41) + : +- Exchange (40) + : +- * HashAggregate (39) + : +- Exchange (38) + : +- * HashAggregate (37) + : +- * Project (36) + : +- * BroadcastHashJoin Inner BuildRight (35) + : :- * ColumnarToRow (33) + : : +- CometProject (32) + : : +- CometBroadcastHashJoin (31) + : : :- CometBroadcastExchange (27) + : : : +- CometProject (26) + : : : +- CometFilter (25) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (24) + : : +- CometProject (30) + : : +- CometFilter (29) + : : +- CometScan parquet spark_catalog.default.catalog_returns (28) + : +- ReusedExchange (34) + +- * Project (69) + +- * Filter (68) + +- Window (67) + +- * Sort (66) + +- Window (65) + +- * Sort (64) + +- Exchange (63) + +- * HashAggregate (62) + +- Exchange (61) + +- * HashAggregate (60) + +- * Project (59) + +- * BroadcastHashJoin Inner BuildRight (58) + :- * ColumnarToRow (56) + : +- CometProject (55) + : +- CometBroadcastHashJoin (54) + : :- CometBroadcastExchange (50) + : : +- CometProject (49) + : : +- CometFilter (48) + : : +- CometScan parquet spark_catalog.default.store_sales (47) + : +- CometProject (53) + : +- CometFilter (52) + : +- CometScan parquet spark_catalog.default.store_returns (51) + +- ReusedExchange (57) + + +(1) Scan parquet spark_catalog.default.web_sales +Output [6]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_net_profit#5, ws_sold_date_sk#6] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#6), dynamicpruningexpression(ws_sold_date_sk#6 IN dynamicpruning#7)] +PushedFilters: [IsNotNull(ws_net_profit), IsNotNull(ws_net_paid), IsNotNull(ws_quantity), GreaterThan(ws_net_profit,1.00), GreaterThan(ws_net_paid,0.00), GreaterThan(ws_quantity,0), IsNotNull(ws_order_number), IsNotNull(ws_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [6]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_net_profit#5, ws_sold_date_sk#6] +Condition : (((((((isnotnull(ws_net_profit#5) AND isnotnull(ws_net_paid#4)) AND isnotnull(ws_quantity#3)) AND (ws_net_profit#5 > 1.00)) AND (ws_net_paid#4 > 0.00)) AND (ws_quantity#3 > 0)) AND isnotnull(ws_order_number#2)) AND isnotnull(ws_item_sk#1)) + +(3) CometProject +Input [6]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_net_profit#5, ws_sold_date_sk#6] +Arguments: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6], [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6] + +(4) CometBroadcastExchange +Input [5]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6] +Arguments: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6] + +(5) Scan parquet spark_catalog.default.web_returns +Output [5]: [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11, wr_returned_date_sk#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_returns] +PushedFilters: [IsNotNull(wr_return_amt), GreaterThan(wr_return_amt,10000.00), IsNotNull(wr_order_number), IsNotNull(wr_item_sk)] +ReadSchema: struct + +(6) CometFilter +Input [5]: [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11, wr_returned_date_sk#12] +Condition : (((isnotnull(wr_return_amt#11) AND (wr_return_amt#11 > 10000.00)) AND isnotnull(wr_order_number#9)) AND isnotnull(wr_item_sk#8)) + +(7) CometProject +Input [5]: [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11, wr_returned_date_sk#12] +Arguments: [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11], [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11] + +(8) CometBroadcastHashJoin +Left output [5]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6] +Right output [4]: [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11] +Arguments: [ws_order_number#2, ws_item_sk#1], [wr_order_number#9, wr_item_sk#8], Inner + +(9) CometProject +Input [9]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6, wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11] +Arguments: [ws_item_sk#1, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6, wr_return_quantity#10, wr_return_amt#11], [ws_item_sk#1, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6, wr_return_quantity#10, wr_return_amt#11] + +(10) ColumnarToRow [codegen id : 2] +Input [6]: [ws_item_sk#1, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6, wr_return_quantity#10, wr_return_amt#11] + +(11) ReusedExchange [Reuses operator id: 79] +Output [1]: [d_date_sk#13] + +(12) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [ws_sold_date_sk#6] +Right keys [1]: [d_date_sk#13] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 2] +Output [5]: [ws_item_sk#1, ws_quantity#3, ws_net_paid#4, wr_return_quantity#10, wr_return_amt#11] +Input [7]: [ws_item_sk#1, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6, wr_return_quantity#10, wr_return_amt#11, d_date_sk#13] + +(14) HashAggregate [codegen id : 2] +Input [5]: [ws_item_sk#1, ws_quantity#3, ws_net_paid#4, wr_return_quantity#10, wr_return_amt#11] +Keys [1]: [ws_item_sk#1] +Functions [4]: [partial_sum(coalesce(wr_return_quantity#10, 0)), partial_sum(coalesce(ws_quantity#3, 0)), partial_sum(coalesce(cast(wr_return_amt#11 as decimal(12,2)), 0.00)), partial_sum(coalesce(cast(ws_net_paid#4 as decimal(12,2)), 0.00))] +Aggregate Attributes [6]: [sum#14, sum#15, sum#16, isEmpty#17, sum#18, isEmpty#19] +Results [7]: [ws_item_sk#1, sum#20, sum#21, sum#22, isEmpty#23, sum#24, isEmpty#25] + +(15) Exchange +Input [7]: [ws_item_sk#1, sum#20, sum#21, sum#22, isEmpty#23, sum#24, isEmpty#25] +Arguments: hashpartitioning(ws_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(16) HashAggregate [codegen id : 3] +Input [7]: [ws_item_sk#1, sum#20, sum#21, sum#22, isEmpty#23, sum#24, isEmpty#25] +Keys [1]: [ws_item_sk#1] +Functions [4]: [sum(coalesce(wr_return_quantity#10, 0)), sum(coalesce(ws_quantity#3, 0)), sum(coalesce(cast(wr_return_amt#11 as decimal(12,2)), 0.00)), sum(coalesce(cast(ws_net_paid#4 as decimal(12,2)), 0.00))] +Aggregate Attributes [4]: [sum(coalesce(wr_return_quantity#10, 0))#26, sum(coalesce(ws_quantity#3, 0))#27, sum(coalesce(cast(wr_return_amt#11 as decimal(12,2)), 0.00))#28, sum(coalesce(cast(ws_net_paid#4 as decimal(12,2)), 0.00))#29] +Results [3]: [ws_item_sk#1 AS item#30, (cast(sum(coalesce(wr_return_quantity#10, 0))#26 as decimal(15,4)) / cast(sum(coalesce(ws_quantity#3, 0))#27 as decimal(15,4))) AS return_ratio#31, (cast(sum(coalesce(cast(wr_return_amt#11 as decimal(12,2)), 0.00))#28 as decimal(15,4)) / cast(sum(coalesce(cast(ws_net_paid#4 as decimal(12,2)), 0.00))#29 as decimal(15,4))) AS currency_ratio#32] + +(17) Exchange +Input [3]: [item#30, return_ratio#31, currency_ratio#32] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=2] + +(18) Sort [codegen id : 4] +Input [3]: [item#30, return_ratio#31, currency_ratio#32] +Arguments: [return_ratio#31 ASC NULLS FIRST], false, 0 + +(19) Window +Input [3]: [item#30, return_ratio#31, currency_ratio#32] +Arguments: [rank(return_ratio#31) windowspecdefinition(return_ratio#31 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS return_rank#33], [return_ratio#31 ASC NULLS FIRST] + +(20) Sort [codegen id : 5] +Input [4]: [item#30, return_ratio#31, currency_ratio#32, return_rank#33] +Arguments: [currency_ratio#32 ASC NULLS FIRST], false, 0 + +(21) Window +Input [4]: [item#30, return_ratio#31, currency_ratio#32, return_rank#33] +Arguments: [rank(currency_ratio#32) windowspecdefinition(currency_ratio#32 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS currency_rank#34], [currency_ratio#32 ASC NULLS FIRST] + +(22) Filter [codegen id : 6] +Input [5]: [item#30, return_ratio#31, currency_ratio#32, return_rank#33, currency_rank#34] +Condition : ((return_rank#33 <= 10) OR (currency_rank#34 <= 10)) + +(23) Project [codegen id : 6] +Output [5]: [web AS channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] +Input [5]: [item#30, return_ratio#31, currency_ratio#32, return_rank#33, currency_rank#34] + +(24) Scan parquet spark_catalog.default.catalog_sales +Output [6]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_net_profit#40, cs_sold_date_sk#41] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#41), dynamicpruningexpression(cs_sold_date_sk#41 IN dynamicpruning#42)] +PushedFilters: [IsNotNull(cs_net_profit), IsNotNull(cs_net_paid), IsNotNull(cs_quantity), GreaterThan(cs_net_profit,1.00), GreaterThan(cs_net_paid,0.00), GreaterThan(cs_quantity,0), IsNotNull(cs_order_number), IsNotNull(cs_item_sk)] +ReadSchema: struct + +(25) CometFilter +Input [6]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_net_profit#40, cs_sold_date_sk#41] +Condition : (((((((isnotnull(cs_net_profit#40) AND isnotnull(cs_net_paid#39)) AND isnotnull(cs_quantity#38)) AND (cs_net_profit#40 > 1.00)) AND (cs_net_paid#39 > 0.00)) AND (cs_quantity#38 > 0)) AND isnotnull(cs_order_number#37)) AND isnotnull(cs_item_sk#36)) + +(26) CometProject +Input [6]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_net_profit#40, cs_sold_date_sk#41] +Arguments: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41], [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41] + +(27) CometBroadcastExchange +Input [5]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41] +Arguments: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41] + +(28) Scan parquet spark_catalog.default.catalog_returns +Output [5]: [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46, cr_returned_date_sk#47] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_returns] +PushedFilters: [IsNotNull(cr_return_amount), GreaterThan(cr_return_amount,10000.00), IsNotNull(cr_order_number), IsNotNull(cr_item_sk)] +ReadSchema: struct + +(29) CometFilter +Input [5]: [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46, cr_returned_date_sk#47] +Condition : (((isnotnull(cr_return_amount#46) AND (cr_return_amount#46 > 10000.00)) AND isnotnull(cr_order_number#44)) AND isnotnull(cr_item_sk#43)) + +(30) CometProject +Input [5]: [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46, cr_returned_date_sk#47] +Arguments: [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46], [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46] + +(31) CometBroadcastHashJoin +Left output [5]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41] +Right output [4]: [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46] +Arguments: [cs_order_number#37, cs_item_sk#36], [cr_order_number#44, cr_item_sk#43], Inner + +(32) CometProject +Input [9]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41, cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46] +Arguments: [cs_item_sk#36, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41, cr_return_quantity#45, cr_return_amount#46], [cs_item_sk#36, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41, cr_return_quantity#45, cr_return_amount#46] + +(33) ColumnarToRow [codegen id : 8] +Input [6]: [cs_item_sk#36, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41, cr_return_quantity#45, cr_return_amount#46] + +(34) ReusedExchange [Reuses operator id: 79] +Output [1]: [d_date_sk#48] + +(35) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [cs_sold_date_sk#41] +Right keys [1]: [d_date_sk#48] +Join type: Inner +Join condition: None + +(36) Project [codegen id : 8] +Output [5]: [cs_item_sk#36, cs_quantity#38, cs_net_paid#39, cr_return_quantity#45, cr_return_amount#46] +Input [7]: [cs_item_sk#36, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41, cr_return_quantity#45, cr_return_amount#46, d_date_sk#48] + +(37) HashAggregate [codegen id : 8] +Input [5]: [cs_item_sk#36, cs_quantity#38, cs_net_paid#39, cr_return_quantity#45, cr_return_amount#46] +Keys [1]: [cs_item_sk#36] +Functions [4]: [partial_sum(coalesce(cr_return_quantity#45, 0)), partial_sum(coalesce(cs_quantity#38, 0)), partial_sum(coalesce(cast(cr_return_amount#46 as decimal(12,2)), 0.00)), partial_sum(coalesce(cast(cs_net_paid#39 as decimal(12,2)), 0.00))] +Aggregate Attributes [6]: [sum#49, sum#50, sum#51, isEmpty#52, sum#53, isEmpty#54] +Results [7]: [cs_item_sk#36, sum#55, sum#56, sum#57, isEmpty#58, sum#59, isEmpty#60] + +(38) Exchange +Input [7]: [cs_item_sk#36, sum#55, sum#56, sum#57, isEmpty#58, sum#59, isEmpty#60] +Arguments: hashpartitioning(cs_item_sk#36, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(39) HashAggregate [codegen id : 9] +Input [7]: [cs_item_sk#36, sum#55, sum#56, sum#57, isEmpty#58, sum#59, isEmpty#60] +Keys [1]: [cs_item_sk#36] +Functions [4]: [sum(coalesce(cr_return_quantity#45, 0)), sum(coalesce(cs_quantity#38, 0)), sum(coalesce(cast(cr_return_amount#46 as decimal(12,2)), 0.00)), sum(coalesce(cast(cs_net_paid#39 as decimal(12,2)), 0.00))] +Aggregate Attributes [4]: [sum(coalesce(cr_return_quantity#45, 0))#61, sum(coalesce(cs_quantity#38, 0))#62, sum(coalesce(cast(cr_return_amount#46 as decimal(12,2)), 0.00))#63, sum(coalesce(cast(cs_net_paid#39 as decimal(12,2)), 0.00))#64] +Results [3]: [cs_item_sk#36 AS item#65, (cast(sum(coalesce(cr_return_quantity#45, 0))#61 as decimal(15,4)) / cast(sum(coalesce(cs_quantity#38, 0))#62 as decimal(15,4))) AS return_ratio#66, (cast(sum(coalesce(cast(cr_return_amount#46 as decimal(12,2)), 0.00))#63 as decimal(15,4)) / cast(sum(coalesce(cast(cs_net_paid#39 as decimal(12,2)), 0.00))#64 as decimal(15,4))) AS currency_ratio#67] + +(40) Exchange +Input [3]: [item#65, return_ratio#66, currency_ratio#67] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=4] + +(41) Sort [codegen id : 10] +Input [3]: [item#65, return_ratio#66, currency_ratio#67] +Arguments: [return_ratio#66 ASC NULLS FIRST], false, 0 + +(42) Window +Input [3]: [item#65, return_ratio#66, currency_ratio#67] +Arguments: [rank(return_ratio#66) windowspecdefinition(return_ratio#66 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS return_rank#68], [return_ratio#66 ASC NULLS FIRST] + +(43) Sort [codegen id : 11] +Input [4]: [item#65, return_ratio#66, currency_ratio#67, return_rank#68] +Arguments: [currency_ratio#67 ASC NULLS FIRST], false, 0 + +(44) Window +Input [4]: [item#65, return_ratio#66, currency_ratio#67, return_rank#68] +Arguments: [rank(currency_ratio#67) windowspecdefinition(currency_ratio#67 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS currency_rank#69], [currency_ratio#67 ASC NULLS FIRST] + +(45) Filter [codegen id : 12] +Input [5]: [item#65, return_ratio#66, currency_ratio#67, return_rank#68, currency_rank#69] +Condition : ((return_rank#68 <= 10) OR (currency_rank#69 <= 10)) + +(46) Project [codegen id : 12] +Output [5]: [catalog AS channel#70, item#65, return_ratio#66, return_rank#68, currency_rank#69] +Input [5]: [item#65, return_ratio#66, currency_ratio#67, return_rank#68, currency_rank#69] + +(47) Scan parquet spark_catalog.default.store_sales +Output [6]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_net_profit#75, ss_sold_date_sk#76] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#76), dynamicpruningexpression(ss_sold_date_sk#76 IN dynamicpruning#77)] +PushedFilters: [IsNotNull(ss_net_profit), IsNotNull(ss_net_paid), IsNotNull(ss_quantity), GreaterThan(ss_net_profit,1.00), GreaterThan(ss_net_paid,0.00), GreaterThan(ss_quantity,0), IsNotNull(ss_ticket_number), IsNotNull(ss_item_sk)] +ReadSchema: struct + +(48) CometFilter +Input [6]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_net_profit#75, ss_sold_date_sk#76] +Condition : (((((((isnotnull(ss_net_profit#75) AND isnotnull(ss_net_paid#74)) AND isnotnull(ss_quantity#73)) AND (ss_net_profit#75 > 1.00)) AND (ss_net_paid#74 > 0.00)) AND (ss_quantity#73 > 0)) AND isnotnull(ss_ticket_number#72)) AND isnotnull(ss_item_sk#71)) + +(49) CometProject +Input [6]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_net_profit#75, ss_sold_date_sk#76] +Arguments: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76], [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76] + +(50) CometBroadcastExchange +Input [5]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76] +Arguments: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76] + +(51) Scan parquet spark_catalog.default.store_returns +Output [5]: [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81, sr_returned_date_sk#82] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_returns] +PushedFilters: [IsNotNull(sr_return_amt), GreaterThan(sr_return_amt,10000.00), IsNotNull(sr_ticket_number), IsNotNull(sr_item_sk)] +ReadSchema: struct + +(52) CometFilter +Input [5]: [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81, sr_returned_date_sk#82] +Condition : (((isnotnull(sr_return_amt#81) AND (sr_return_amt#81 > 10000.00)) AND isnotnull(sr_ticket_number#79)) AND isnotnull(sr_item_sk#78)) + +(53) CometProject +Input [5]: [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81, sr_returned_date_sk#82] +Arguments: [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81], [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81] + +(54) CometBroadcastHashJoin +Left output [5]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76] +Right output [4]: [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81] +Arguments: [ss_ticket_number#72, ss_item_sk#71], [sr_ticket_number#79, sr_item_sk#78], Inner + +(55) CometProject +Input [9]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76, sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81] +Arguments: [ss_item_sk#71, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76, sr_return_quantity#80, sr_return_amt#81], [ss_item_sk#71, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76, sr_return_quantity#80, sr_return_amt#81] + +(56) ColumnarToRow [codegen id : 14] +Input [6]: [ss_item_sk#71, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76, sr_return_quantity#80, sr_return_amt#81] + +(57) ReusedExchange [Reuses operator id: 79] +Output [1]: [d_date_sk#83] + +(58) BroadcastHashJoin [codegen id : 14] +Left keys [1]: [ss_sold_date_sk#76] +Right keys [1]: [d_date_sk#83] +Join type: Inner +Join condition: None + +(59) Project [codegen id : 14] +Output [5]: [ss_item_sk#71, ss_quantity#73, ss_net_paid#74, sr_return_quantity#80, sr_return_amt#81] +Input [7]: [ss_item_sk#71, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76, sr_return_quantity#80, sr_return_amt#81, d_date_sk#83] + +(60) HashAggregate [codegen id : 14] +Input [5]: [ss_item_sk#71, ss_quantity#73, ss_net_paid#74, sr_return_quantity#80, sr_return_amt#81] +Keys [1]: [ss_item_sk#71] +Functions [4]: [partial_sum(coalesce(sr_return_quantity#80, 0)), partial_sum(coalesce(ss_quantity#73, 0)), partial_sum(coalesce(cast(sr_return_amt#81 as decimal(12,2)), 0.00)), partial_sum(coalesce(cast(ss_net_paid#74 as decimal(12,2)), 0.00))] +Aggregate Attributes [6]: [sum#84, sum#85, sum#86, isEmpty#87, sum#88, isEmpty#89] +Results [7]: [ss_item_sk#71, sum#90, sum#91, sum#92, isEmpty#93, sum#94, isEmpty#95] + +(61) Exchange +Input [7]: [ss_item_sk#71, sum#90, sum#91, sum#92, isEmpty#93, sum#94, isEmpty#95] +Arguments: hashpartitioning(ss_item_sk#71, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(62) HashAggregate [codegen id : 15] +Input [7]: [ss_item_sk#71, sum#90, sum#91, sum#92, isEmpty#93, sum#94, isEmpty#95] +Keys [1]: [ss_item_sk#71] +Functions [4]: [sum(coalesce(sr_return_quantity#80, 0)), sum(coalesce(ss_quantity#73, 0)), sum(coalesce(cast(sr_return_amt#81 as decimal(12,2)), 0.00)), sum(coalesce(cast(ss_net_paid#74 as decimal(12,2)), 0.00))] +Aggregate Attributes [4]: [sum(coalesce(sr_return_quantity#80, 0))#96, sum(coalesce(ss_quantity#73, 0))#97, sum(coalesce(cast(sr_return_amt#81 as decimal(12,2)), 0.00))#98, sum(coalesce(cast(ss_net_paid#74 as decimal(12,2)), 0.00))#99] +Results [3]: [ss_item_sk#71 AS item#100, (cast(sum(coalesce(sr_return_quantity#80, 0))#96 as decimal(15,4)) / cast(sum(coalesce(ss_quantity#73, 0))#97 as decimal(15,4))) AS return_ratio#101, (cast(sum(coalesce(cast(sr_return_amt#81 as decimal(12,2)), 0.00))#98 as decimal(15,4)) / cast(sum(coalesce(cast(ss_net_paid#74 as decimal(12,2)), 0.00))#99 as decimal(15,4))) AS currency_ratio#102] + +(63) Exchange +Input [3]: [item#100, return_ratio#101, currency_ratio#102] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=6] + +(64) Sort [codegen id : 16] +Input [3]: [item#100, return_ratio#101, currency_ratio#102] +Arguments: [return_ratio#101 ASC NULLS FIRST], false, 0 + +(65) Window +Input [3]: [item#100, return_ratio#101, currency_ratio#102] +Arguments: [rank(return_ratio#101) windowspecdefinition(return_ratio#101 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS return_rank#103], [return_ratio#101 ASC NULLS FIRST] + +(66) Sort [codegen id : 17] +Input [4]: [item#100, return_ratio#101, currency_ratio#102, return_rank#103] +Arguments: [currency_ratio#102 ASC NULLS FIRST], false, 0 + +(67) Window +Input [4]: [item#100, return_ratio#101, currency_ratio#102, return_rank#103] +Arguments: [rank(currency_ratio#102) windowspecdefinition(currency_ratio#102 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS currency_rank#104], [currency_ratio#102 ASC NULLS FIRST] + +(68) Filter [codegen id : 18] +Input [5]: [item#100, return_ratio#101, currency_ratio#102, return_rank#103, currency_rank#104] +Condition : ((return_rank#103 <= 10) OR (currency_rank#104 <= 10)) + +(69) Project [codegen id : 18] +Output [5]: [store AS channel#105, item#100, return_ratio#101, return_rank#103, currency_rank#104] +Input [5]: [item#100, return_ratio#101, currency_ratio#102, return_rank#103, currency_rank#104] + +(70) Union + +(71) HashAggregate [codegen id : 19] +Input [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] +Keys [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] +Functions: [] +Aggregate Attributes: [] +Results [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] + +(72) Exchange +Input [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] +Arguments: hashpartitioning(channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(73) HashAggregate [codegen id : 20] +Input [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] +Keys [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] +Functions: [] +Aggregate Attributes: [] +Results [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] + +(74) TakeOrderedAndProject +Input [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] +Arguments: 100, [channel#35 ASC NULLS FIRST, return_rank#33 ASC NULLS FIRST, currency_rank#34 ASC NULLS FIRST, item#30 ASC NULLS FIRST], [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#6 IN dynamicpruning#7 +BroadcastExchange (79) ++- * ColumnarToRow (78) + +- CometProject (77) + +- CometFilter (76) + +- CometScan parquet spark_catalog.default.date_dim (75) + + +(75) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#13, d_year#106, d_moy#107] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2001), EqualTo(d_moy,12), IsNotNull(d_date_sk)] +ReadSchema: struct + +(76) CometFilter +Input [3]: [d_date_sk#13, d_year#106, d_moy#107] +Condition : ((((isnotnull(d_year#106) AND isnotnull(d_moy#107)) AND (d_year#106 = 2001)) AND (d_moy#107 = 12)) AND isnotnull(d_date_sk#13)) + +(77) CometProject +Input [3]: [d_date_sk#13, d_year#106, d_moy#107] +Arguments: [d_date_sk#13], [d_date_sk#13] + +(78) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#13] + +(79) BroadcastExchange +Input [1]: [d_date_sk#13] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + +Subquery:2 Hosting operator id = 24 Hosting Expression = cs_sold_date_sk#41 IN dynamicpruning#7 + +Subquery:3 Hosting operator id = 47 Hosting Expression = ss_sold_date_sk#76 IN dynamicpruning#7 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q49/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q49/simplified.txt new file mode 100644 index 0000000000..43ebf34cc0 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q49/simplified.txt @@ -0,0 +1,121 @@ +TakeOrderedAndProject [channel,return_rank,currency_rank,item,return_ratio] + WholeStageCodegen (20) + HashAggregate [channel,item,return_ratio,return_rank,currency_rank] + InputAdapter + Exchange [channel,item,return_ratio,return_rank,currency_rank] #1 + WholeStageCodegen (19) + HashAggregate [channel,item,return_ratio,return_rank,currency_rank] + InputAdapter + Union + WholeStageCodegen (6) + Project [item,return_ratio,return_rank,currency_rank] + Filter [return_rank,currency_rank] + InputAdapter + Window [currency_ratio] + WholeStageCodegen (5) + Sort [currency_ratio] + InputAdapter + Window [return_ratio] + WholeStageCodegen (4) + Sort [return_ratio] + InputAdapter + Exchange #2 + WholeStageCodegen (3) + HashAggregate [ws_item_sk,sum,sum,sum,isEmpty,sum,isEmpty] [sum(coalesce(wr_return_quantity, 0)),sum(coalesce(ws_quantity, 0)),sum(coalesce(cast(wr_return_amt as decimal(12,2)), 0.00)),sum(coalesce(cast(ws_net_paid as decimal(12,2)), 0.00)),item,return_ratio,currency_ratio,sum,sum,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [ws_item_sk] #3 + WholeStageCodegen (2) + HashAggregate [ws_item_sk,wr_return_quantity,ws_quantity,wr_return_amt,ws_net_paid] [sum,sum,sum,isEmpty,sum,isEmpty,sum,sum,sum,isEmpty,sum,isEmpty] + Project [ws_item_sk,ws_quantity,ws_net_paid,wr_return_quantity,wr_return_amt] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometProject [ws_item_sk,ws_quantity,ws_net_paid,ws_sold_date_sk,wr_return_quantity,wr_return_amt] + CometBroadcastHashJoin [ws_order_number,ws_item_sk,wr_order_number,wr_item_sk] + CometBroadcastExchange #4 + CometProject [ws_item_sk,ws_order_number,ws_quantity,ws_net_paid,ws_sold_date_sk] + CometFilter [ws_net_profit,ws_net_paid,ws_quantity,ws_order_number,ws_item_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_order_number,ws_quantity,ws_net_paid,ws_net_profit,ws_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #5 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_moy,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + CometProject [wr_item_sk,wr_order_number,wr_return_quantity,wr_return_amt] + CometFilter [wr_return_amt,wr_order_number,wr_item_sk] + CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_order_number,wr_return_quantity,wr_return_amt,wr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk] #5 + WholeStageCodegen (12) + Project [item,return_ratio,return_rank,currency_rank] + Filter [return_rank,currency_rank] + InputAdapter + Window [currency_ratio] + WholeStageCodegen (11) + Sort [currency_ratio] + InputAdapter + Window [return_ratio] + WholeStageCodegen (10) + Sort [return_ratio] + InputAdapter + Exchange #6 + WholeStageCodegen (9) + HashAggregate [cs_item_sk,sum,sum,sum,isEmpty,sum,isEmpty] [sum(coalesce(cr_return_quantity, 0)),sum(coalesce(cs_quantity, 0)),sum(coalesce(cast(cr_return_amount as decimal(12,2)), 0.00)),sum(coalesce(cast(cs_net_paid as decimal(12,2)), 0.00)),item,return_ratio,currency_ratio,sum,sum,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [cs_item_sk] #7 + WholeStageCodegen (8) + HashAggregate [cs_item_sk,cr_return_quantity,cs_quantity,cr_return_amount,cs_net_paid] [sum,sum,sum,isEmpty,sum,isEmpty,sum,sum,sum,isEmpty,sum,isEmpty] + Project [cs_item_sk,cs_quantity,cs_net_paid,cr_return_quantity,cr_return_amount] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometProject [cs_item_sk,cs_quantity,cs_net_paid,cs_sold_date_sk,cr_return_quantity,cr_return_amount] + CometBroadcastHashJoin [cs_order_number,cs_item_sk,cr_order_number,cr_item_sk] + CometBroadcastExchange #8 + CometProject [cs_item_sk,cs_order_number,cs_quantity,cs_net_paid,cs_sold_date_sk] + CometFilter [cs_net_profit,cs_net_paid,cs_quantity,cs_order_number,cs_item_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_order_number,cs_quantity,cs_net_paid,cs_net_profit,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + CometProject [cr_item_sk,cr_order_number,cr_return_quantity,cr_return_amount] + CometFilter [cr_return_amount,cr_order_number,cr_item_sk] + CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_return_quantity,cr_return_amount,cr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk] #5 + WholeStageCodegen (18) + Project [item,return_ratio,return_rank,currency_rank] + Filter [return_rank,currency_rank] + InputAdapter + Window [currency_ratio] + WholeStageCodegen (17) + Sort [currency_ratio] + InputAdapter + Window [return_ratio] + WholeStageCodegen (16) + Sort [return_ratio] + InputAdapter + Exchange #9 + WholeStageCodegen (15) + HashAggregate [ss_item_sk,sum,sum,sum,isEmpty,sum,isEmpty] [sum(coalesce(sr_return_quantity, 0)),sum(coalesce(ss_quantity, 0)),sum(coalesce(cast(sr_return_amt as decimal(12,2)), 0.00)),sum(coalesce(cast(ss_net_paid as decimal(12,2)), 0.00)),item,return_ratio,currency_ratio,sum,sum,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [ss_item_sk] #10 + WholeStageCodegen (14) + HashAggregate [ss_item_sk,sr_return_quantity,ss_quantity,sr_return_amt,ss_net_paid] [sum,sum,sum,isEmpty,sum,isEmpty,sum,sum,sum,isEmpty,sum,isEmpty] + Project [ss_item_sk,ss_quantity,ss_net_paid,sr_return_quantity,sr_return_amt] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometProject [ss_item_sk,ss_quantity,ss_net_paid,ss_sold_date_sk,sr_return_quantity,sr_return_amt] + CometBroadcastHashJoin [ss_ticket_number,ss_item_sk,sr_ticket_number,sr_item_sk] + CometBroadcastExchange #11 + CometProject [ss_item_sk,ss_ticket_number,ss_quantity,ss_net_paid,ss_sold_date_sk] + CometFilter [ss_net_profit,ss_net_paid,ss_quantity,ss_ticket_number,ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ticket_number,ss_quantity,ss_net_paid,ss_net_profit,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + CometProject [sr_item_sk,sr_ticket_number,sr_return_quantity,sr_return_amt] + CometFilter [sr_return_amt,sr_ticket_number,sr_item_sk] + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_return_quantity,sr_return_amt,sr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk] #5 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q51a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q51a/explain.txt new file mode 100644 index 0000000000..3892f250a7 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q51a/explain.txt @@ -0,0 +1,416 @@ +== Physical Plan == +TakeOrderedAndProject (67) ++- * Filter (66) + +- * HashAggregate (65) + +- * HashAggregate (64) + +- * Project (63) + +- * BroadcastHashJoin Inner BuildRight (62) + :- Window (56) + : +- * Sort (55) + : +- Exchange (54) + : +- * Project (53) + : +- * Filter (52) + : +- * SortMergeJoin FullOuter (51) + : :- * Sort (25) + : : +- Exchange (24) + : : +- * HashAggregate (23) + : : +- Exchange (22) + : : +- * HashAggregate (21) + : : +- * Project (20) + : : +- * BroadcastHashJoin Inner BuildRight (19) + : : :- * Project (13) + : : : +- Window (12) + : : : +- * Sort (11) + : : : +- Exchange (10) + : : : +- * HashAggregate (9) + : : : +- Exchange (8) + : : : +- * HashAggregate (7) + : : : +- * Project (6) + : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.web_sales (1) + : : : +- ReusedExchange (4) + : : +- BroadcastExchange (18) + : : +- * Project (17) + : : +- Window (16) + : : +- * Sort (15) + : : +- ReusedExchange (14) + : +- * Sort (50) + : +- Exchange (49) + : +- * HashAggregate (48) + : +- Exchange (47) + : +- * HashAggregate (46) + : +- * Project (45) + : +- * BroadcastHashJoin Inner BuildRight (44) + : :- * Project (38) + : : +- Window (37) + : : +- * Sort (36) + : : +- Exchange (35) + : : +- * HashAggregate (34) + : : +- Exchange (33) + : : +- * HashAggregate (32) + : : +- * Project (31) + : : +- * BroadcastHashJoin Inner BuildRight (30) + : : :- * ColumnarToRow (28) + : : : +- CometFilter (27) + : : : +- CometScan parquet spark_catalog.default.store_sales (26) + : : +- ReusedExchange (29) + : +- BroadcastExchange (43) + : +- * Project (42) + : +- Window (41) + : +- * Sort (40) + : +- ReusedExchange (39) + +- BroadcastExchange (61) + +- * Project (60) + +- Window (59) + +- * Sort (58) + +- ReusedExchange (57) + + +(1) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_item_sk#1, ws_sales_price#2, ws_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#3), dynamicpruningexpression(ws_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [ws_item_sk#1, ws_sales_price#2, ws_sold_date_sk#3] +Condition : isnotnull(ws_item_sk#1) + +(3) ColumnarToRow [codegen id : 2] +Input [3]: [ws_item_sk#1, ws_sales_price#2, ws_sold_date_sk#3] + +(4) ReusedExchange [Reuses operator id: 72] +Output [2]: [d_date_sk#5, d_date#6] + +(5) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [ws_sold_date_sk#3] +Right keys [1]: [d_date_sk#5] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 2] +Output [3]: [ws_item_sk#1, ws_sales_price#2, d_date#6] +Input [5]: [ws_item_sk#1, ws_sales_price#2, ws_sold_date_sk#3, d_date_sk#5, d_date#6] + +(7) HashAggregate [codegen id : 2] +Input [3]: [ws_item_sk#1, ws_sales_price#2, d_date#6] +Keys [2]: [ws_item_sk#1, d_date#6] +Functions [1]: [partial_sum(UnscaledValue(ws_sales_price#2))] +Aggregate Attributes [1]: [sum#7] +Results [3]: [ws_item_sk#1, d_date#6, sum#8] + +(8) Exchange +Input [3]: [ws_item_sk#1, d_date#6, sum#8] +Arguments: hashpartitioning(ws_item_sk#1, d_date#6, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(9) HashAggregate [codegen id : 3] +Input [3]: [ws_item_sk#1, d_date#6, sum#8] +Keys [2]: [ws_item_sk#1, d_date#6] +Functions [1]: [sum(UnscaledValue(ws_sales_price#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_sales_price#2))#9] +Results [4]: [ws_item_sk#1 AS item_sk#10, d_date#6, MakeDecimal(sum(UnscaledValue(ws_sales_price#2))#9,17,2) AS sumws#11, ws_item_sk#1] + +(10) Exchange +Input [4]: [item_sk#10, d_date#6, sumws#11, ws_item_sk#1] +Arguments: hashpartitioning(ws_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(11) Sort [codegen id : 4] +Input [4]: [item_sk#10, d_date#6, sumws#11, ws_item_sk#1] +Arguments: [ws_item_sk#1 ASC NULLS FIRST, d_date#6 ASC NULLS FIRST], false, 0 + +(12) Window +Input [4]: [item_sk#10, d_date#6, sumws#11, ws_item_sk#1] +Arguments: [row_number() windowspecdefinition(ws_item_sk#1, d_date#6 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rk#12], [ws_item_sk#1], [d_date#6 ASC NULLS FIRST] + +(13) Project [codegen id : 10] +Output [4]: [item_sk#10, d_date#6, sumws#11, rk#12] +Input [5]: [item_sk#10, d_date#6, sumws#11, ws_item_sk#1, rk#12] + +(14) ReusedExchange [Reuses operator id: 10] +Output [4]: [item_sk#13, d_date#14, sumws#15, ws_item_sk#16] + +(15) Sort [codegen id : 8] +Input [4]: [item_sk#13, d_date#14, sumws#15, ws_item_sk#16] +Arguments: [ws_item_sk#16 ASC NULLS FIRST, d_date#14 ASC NULLS FIRST], false, 0 + +(16) Window +Input [4]: [item_sk#13, d_date#14, sumws#15, ws_item_sk#16] +Arguments: [row_number() windowspecdefinition(ws_item_sk#16, d_date#14 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rk#17], [ws_item_sk#16], [d_date#14 ASC NULLS FIRST] + +(17) Project [codegen id : 9] +Output [3]: [item_sk#13, sumws#15, rk#17] +Input [5]: [item_sk#13, d_date#14, sumws#15, ws_item_sk#16, rk#17] + +(18) BroadcastExchange +Input [3]: [item_sk#13, sumws#15, rk#17] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(19) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [item_sk#10] +Right keys [1]: [item_sk#13] +Join type: Inner +Join condition: (rk#12 >= rk#17) + +(20) Project [codegen id : 10] +Output [4]: [item_sk#10, d_date#6, sumws#11, sumws#15] +Input [7]: [item_sk#10, d_date#6, sumws#11, rk#12, item_sk#13, sumws#15, rk#17] + +(21) HashAggregate [codegen id : 10] +Input [4]: [item_sk#10, d_date#6, sumws#11, sumws#15] +Keys [3]: [item_sk#10, d_date#6, sumws#11] +Functions [1]: [partial_sum(sumws#15)] +Aggregate Attributes [2]: [sum#18, isEmpty#19] +Results [5]: [item_sk#10, d_date#6, sumws#11, sum#20, isEmpty#21] + +(22) Exchange +Input [5]: [item_sk#10, d_date#6, sumws#11, sum#20, isEmpty#21] +Arguments: hashpartitioning(item_sk#10, d_date#6, sumws#11, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(23) HashAggregate [codegen id : 11] +Input [5]: [item_sk#10, d_date#6, sumws#11, sum#20, isEmpty#21] +Keys [3]: [item_sk#10, d_date#6, sumws#11] +Functions [1]: [sum(sumws#15)] +Aggregate Attributes [1]: [sum(sumws#15)#22] +Results [3]: [item_sk#10, d_date#6, sum(sumws#15)#22 AS cume_sales#23] + +(24) Exchange +Input [3]: [item_sk#10, d_date#6, cume_sales#23] +Arguments: hashpartitioning(item_sk#10, d_date#6, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(25) Sort [codegen id : 12] +Input [3]: [item_sk#10, d_date#6, cume_sales#23] +Arguments: [item_sk#10 ASC NULLS FIRST, d_date#6 ASC NULLS FIRST], false, 0 + +(26) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_item_sk#24, ss_sales_price#25, ss_sold_date_sk#26] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#26), dynamicpruningexpression(ss_sold_date_sk#26 IN dynamicpruning#27)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(27) CometFilter +Input [3]: [ss_item_sk#24, ss_sales_price#25, ss_sold_date_sk#26] +Condition : isnotnull(ss_item_sk#24) + +(28) ColumnarToRow [codegen id : 14] +Input [3]: [ss_item_sk#24, ss_sales_price#25, ss_sold_date_sk#26] + +(29) ReusedExchange [Reuses operator id: 72] +Output [2]: [d_date_sk#28, d_date#29] + +(30) BroadcastHashJoin [codegen id : 14] +Left keys [1]: [ss_sold_date_sk#26] +Right keys [1]: [d_date_sk#28] +Join type: Inner +Join condition: None + +(31) Project [codegen id : 14] +Output [3]: [ss_item_sk#24, ss_sales_price#25, d_date#29] +Input [5]: [ss_item_sk#24, ss_sales_price#25, ss_sold_date_sk#26, d_date_sk#28, d_date#29] + +(32) HashAggregate [codegen id : 14] +Input [3]: [ss_item_sk#24, ss_sales_price#25, d_date#29] +Keys [2]: [ss_item_sk#24, d_date#29] +Functions [1]: [partial_sum(UnscaledValue(ss_sales_price#25))] +Aggregate Attributes [1]: [sum#30] +Results [3]: [ss_item_sk#24, d_date#29, sum#31] + +(33) Exchange +Input [3]: [ss_item_sk#24, d_date#29, sum#31] +Arguments: hashpartitioning(ss_item_sk#24, d_date#29, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(34) HashAggregate [codegen id : 15] +Input [3]: [ss_item_sk#24, d_date#29, sum#31] +Keys [2]: [ss_item_sk#24, d_date#29] +Functions [1]: [sum(UnscaledValue(ss_sales_price#25))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_sales_price#25))#32] +Results [4]: [ss_item_sk#24 AS item_sk#33, d_date#29, MakeDecimal(sum(UnscaledValue(ss_sales_price#25))#32,17,2) AS sumss#34, ss_item_sk#24] + +(35) Exchange +Input [4]: [item_sk#33, d_date#29, sumss#34, ss_item_sk#24] +Arguments: hashpartitioning(ss_item_sk#24, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(36) Sort [codegen id : 16] +Input [4]: [item_sk#33, d_date#29, sumss#34, ss_item_sk#24] +Arguments: [ss_item_sk#24 ASC NULLS FIRST, d_date#29 ASC NULLS FIRST], false, 0 + +(37) Window +Input [4]: [item_sk#33, d_date#29, sumss#34, ss_item_sk#24] +Arguments: [row_number() windowspecdefinition(ss_item_sk#24, d_date#29 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rk#35], [ss_item_sk#24], [d_date#29 ASC NULLS FIRST] + +(38) Project [codegen id : 22] +Output [4]: [item_sk#33, d_date#29, sumss#34, rk#35] +Input [5]: [item_sk#33, d_date#29, sumss#34, ss_item_sk#24, rk#35] + +(39) ReusedExchange [Reuses operator id: 35] +Output [4]: [item_sk#36, d_date#37, sumss#38, ss_item_sk#39] + +(40) Sort [codegen id : 20] +Input [4]: [item_sk#36, d_date#37, sumss#38, ss_item_sk#39] +Arguments: [ss_item_sk#39 ASC NULLS FIRST, d_date#37 ASC NULLS FIRST], false, 0 + +(41) Window +Input [4]: [item_sk#36, d_date#37, sumss#38, ss_item_sk#39] +Arguments: [row_number() windowspecdefinition(ss_item_sk#39, d_date#37 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rk#40], [ss_item_sk#39], [d_date#37 ASC NULLS FIRST] + +(42) Project [codegen id : 21] +Output [3]: [item_sk#36, sumss#38, rk#40] +Input [5]: [item_sk#36, d_date#37, sumss#38, ss_item_sk#39, rk#40] + +(43) BroadcastExchange +Input [3]: [item_sk#36, sumss#38, rk#40] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + +(44) BroadcastHashJoin [codegen id : 22] +Left keys [1]: [item_sk#33] +Right keys [1]: [item_sk#36] +Join type: Inner +Join condition: (rk#35 >= rk#40) + +(45) Project [codegen id : 22] +Output [4]: [item_sk#33, d_date#29, sumss#34, sumss#38] +Input [7]: [item_sk#33, d_date#29, sumss#34, rk#35, item_sk#36, sumss#38, rk#40] + +(46) HashAggregate [codegen id : 22] +Input [4]: [item_sk#33, d_date#29, sumss#34, sumss#38] +Keys [3]: [item_sk#33, d_date#29, sumss#34] +Functions [1]: [partial_sum(sumss#38)] +Aggregate Attributes [2]: [sum#41, isEmpty#42] +Results [5]: [item_sk#33, d_date#29, sumss#34, sum#43, isEmpty#44] + +(47) Exchange +Input [5]: [item_sk#33, d_date#29, sumss#34, sum#43, isEmpty#44] +Arguments: hashpartitioning(item_sk#33, d_date#29, sumss#34, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(48) HashAggregate [codegen id : 23] +Input [5]: [item_sk#33, d_date#29, sumss#34, sum#43, isEmpty#44] +Keys [3]: [item_sk#33, d_date#29, sumss#34] +Functions [1]: [sum(sumss#38)] +Aggregate Attributes [1]: [sum(sumss#38)#45] +Results [3]: [item_sk#33, d_date#29, sum(sumss#38)#45 AS cume_sales#46] + +(49) Exchange +Input [3]: [item_sk#33, d_date#29, cume_sales#46] +Arguments: hashpartitioning(item_sk#33, d_date#29, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(50) Sort [codegen id : 24] +Input [3]: [item_sk#33, d_date#29, cume_sales#46] +Arguments: [item_sk#33 ASC NULLS FIRST, d_date#29 ASC NULLS FIRST], false, 0 + +(51) SortMergeJoin [codegen id : 25] +Left keys [2]: [item_sk#10, d_date#6] +Right keys [2]: [item_sk#33, d_date#29] +Join type: FullOuter +Join condition: None + +(52) Filter [codegen id : 25] +Input [6]: [item_sk#10, d_date#6, cume_sales#23, item_sk#33, d_date#29, cume_sales#46] +Condition : isnotnull(CASE WHEN isnotnull(item_sk#10) THEN item_sk#10 ELSE item_sk#33 END) + +(53) Project [codegen id : 25] +Output [4]: [CASE WHEN isnotnull(item_sk#10) THEN item_sk#10 ELSE item_sk#33 END AS item_sk#47, CASE WHEN isnotnull(d_date#6) THEN d_date#6 ELSE d_date#29 END AS d_date#48, cume_sales#23 AS web_sales#49, cume_sales#46 AS store_sales#50] +Input [6]: [item_sk#10, d_date#6, cume_sales#23, item_sk#33, d_date#29, cume_sales#46] + +(54) Exchange +Input [4]: [item_sk#47, d_date#48, web_sales#49, store_sales#50] +Arguments: hashpartitioning(item_sk#47, 5), ENSURE_REQUIREMENTS, [plan_id=11] + +(55) Sort [codegen id : 26] +Input [4]: [item_sk#47, d_date#48, web_sales#49, store_sales#50] +Arguments: [item_sk#47 ASC NULLS FIRST, d_date#48 ASC NULLS FIRST], false, 0 + +(56) Window +Input [4]: [item_sk#47, d_date#48, web_sales#49, store_sales#50] +Arguments: [row_number() windowspecdefinition(item_sk#47, d_date#48 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rk#51], [item_sk#47], [d_date#48 ASC NULLS FIRST] + +(57) ReusedExchange [Reuses operator id: 54] +Output [4]: [item_sk#52, d_date#53, web_sales#54, store_sales#55] + +(58) Sort [codegen id : 52] +Input [4]: [item_sk#52, d_date#53, web_sales#54, store_sales#55] +Arguments: [item_sk#52 ASC NULLS FIRST, d_date#53 ASC NULLS FIRST], false, 0 + +(59) Window +Input [4]: [item_sk#52, d_date#53, web_sales#54, store_sales#55] +Arguments: [row_number() windowspecdefinition(item_sk#52, d_date#53 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rk#56], [item_sk#52], [d_date#53 ASC NULLS FIRST] + +(60) Project [codegen id : 53] +Output [4]: [item_sk#52, web_sales#54, store_sales#55, rk#56] +Input [5]: [item_sk#52, d_date#53, web_sales#54, store_sales#55, rk#56] + +(61) BroadcastExchange +Input [4]: [item_sk#52, web_sales#54, store_sales#55, rk#56] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=12] + +(62) BroadcastHashJoin [codegen id : 54] +Left keys [1]: [item_sk#47] +Right keys [1]: [item_sk#52] +Join type: Inner +Join condition: (rk#51 >= rk#56) + +(63) Project [codegen id : 54] +Output [6]: [item_sk#47, d_date#48, web_sales#49, store_sales#50, web_sales#54, store_sales#55] +Input [9]: [item_sk#47, d_date#48, web_sales#49, store_sales#50, rk#51, item_sk#52, web_sales#54, store_sales#55, rk#56] + +(64) HashAggregate [codegen id : 54] +Input [6]: [item_sk#47, d_date#48, web_sales#49, store_sales#50, web_sales#54, store_sales#55] +Keys [4]: [item_sk#47, d_date#48, web_sales#49, store_sales#50] +Functions [2]: [partial_max(web_sales#54), partial_max(store_sales#55)] +Aggregate Attributes [2]: [max#57, max#58] +Results [6]: [item_sk#47, d_date#48, web_sales#49, store_sales#50, max#59, max#60] + +(65) HashAggregate [codegen id : 54] +Input [6]: [item_sk#47, d_date#48, web_sales#49, store_sales#50, max#59, max#60] +Keys [4]: [item_sk#47, d_date#48, web_sales#49, store_sales#50] +Functions [2]: [max(web_sales#54), max(store_sales#55)] +Aggregate Attributes [2]: [max(web_sales#54)#61, max(store_sales#55)#62] +Results [6]: [item_sk#47, d_date#48, web_sales#49, store_sales#50, max(web_sales#54)#61 AS web_cumulative#63, max(store_sales#55)#62 AS store_cumulative#64] + +(66) Filter [codegen id : 54] +Input [6]: [item_sk#47, d_date#48, web_sales#49, store_sales#50, web_cumulative#63, store_cumulative#64] +Condition : ((isnotnull(web_cumulative#63) AND isnotnull(store_cumulative#64)) AND (web_cumulative#63 > store_cumulative#64)) + +(67) TakeOrderedAndProject +Input [6]: [item_sk#47, d_date#48, web_sales#49, store_sales#50, web_cumulative#63, store_cumulative#64] +Arguments: 100, [item_sk#47 ASC NULLS FIRST, d_date#48 ASC NULLS FIRST], [item_sk#47, d_date#48, web_sales#49, store_sales#50, web_cumulative#63, store_cumulative#64] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (72) ++- * ColumnarToRow (71) + +- CometProject (70) + +- CometFilter (69) + +- CometScan parquet spark_catalog.default.date_dim (68) + + +(68) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#5, d_date#6, d_month_seq#65] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1212), LessThanOrEqual(d_month_seq,1223), IsNotNull(d_date_sk)] +ReadSchema: struct + +(69) CometFilter +Input [3]: [d_date_sk#5, d_date#6, d_month_seq#65] +Condition : (((isnotnull(d_month_seq#65) AND (d_month_seq#65 >= 1212)) AND (d_month_seq#65 <= 1223)) AND isnotnull(d_date_sk#5)) + +(70) CometProject +Input [3]: [d_date_sk#5, d_date#6, d_month_seq#65] +Arguments: [d_date_sk#5, d_date#6], [d_date_sk#5, d_date#6] + +(71) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#5, d_date#6] + +(72) BroadcastExchange +Input [2]: [d_date_sk#5, d_date#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=13] + +Subquery:2 Hosting operator id = 26 Hosting Expression = ss_sold_date_sk#26 IN dynamicpruning#4 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q51a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q51a/simplified.txt new file mode 100644 index 0000000000..3109290dc7 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q51a/simplified.txt @@ -0,0 +1,124 @@ +TakeOrderedAndProject [item_sk,d_date,web_sales,store_sales,web_cumulative,store_cumulative] + WholeStageCodegen (54) + Filter [web_cumulative,store_cumulative] + HashAggregate [item_sk,d_date,web_sales,store_sales,max,max] [max(web_sales),max(store_sales),web_cumulative,store_cumulative,max,max] + HashAggregate [item_sk,d_date,web_sales,store_sales,web_sales,store_sales] [max,max,max,max] + Project [item_sk,d_date,web_sales,store_sales,web_sales,store_sales] + BroadcastHashJoin [item_sk,item_sk,rk,rk] + InputAdapter + Window [item_sk,d_date] + WholeStageCodegen (26) + Sort [item_sk,d_date] + InputAdapter + Exchange [item_sk] #1 + WholeStageCodegen (25) + Project [item_sk,item_sk,d_date,d_date,cume_sales,cume_sales] + Filter [item_sk,item_sk] + SortMergeJoin [item_sk,d_date,item_sk,d_date] + InputAdapter + WholeStageCodegen (12) + Sort [item_sk,d_date] + InputAdapter + Exchange [item_sk,d_date] #2 + WholeStageCodegen (11) + HashAggregate [item_sk,d_date,sumws,sum,isEmpty] [sum(sumws),cume_sales,sum,isEmpty] + InputAdapter + Exchange [item_sk,d_date,sumws] #3 + WholeStageCodegen (10) + HashAggregate [item_sk,d_date,sumws,sumws] [sum,isEmpty,sum,isEmpty] + Project [item_sk,d_date,sumws,sumws] + BroadcastHashJoin [item_sk,item_sk,rk,rk] + Project [item_sk,d_date,sumws,rk] + InputAdapter + Window [ws_item_sk,d_date] + WholeStageCodegen (4) + Sort [ws_item_sk,d_date] + InputAdapter + Exchange [ws_item_sk] #4 + WholeStageCodegen (3) + HashAggregate [ws_item_sk,d_date,sum] [sum(UnscaledValue(ws_sales_price)),item_sk,sumws,sum] + InputAdapter + Exchange [ws_item_sk,d_date] #5 + WholeStageCodegen (2) + HashAggregate [ws_item_sk,d_date,ws_sales_price] [sum,sum] + Project [ws_item_sk,ws_sales_price,d_date] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_sales_price,ws_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #6 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_date] + CometFilter [d_month_seq,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date,d_month_seq] + InputAdapter + ReusedExchange [d_date_sk,d_date] #6 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (9) + Project [item_sk,sumws,rk] + InputAdapter + Window [ws_item_sk,d_date] + WholeStageCodegen (8) + Sort [ws_item_sk,d_date] + InputAdapter + ReusedExchange [item_sk,d_date,sumws,ws_item_sk] #4 + InputAdapter + WholeStageCodegen (24) + Sort [item_sk,d_date] + InputAdapter + Exchange [item_sk,d_date] #8 + WholeStageCodegen (23) + HashAggregate [item_sk,d_date,sumss,sum,isEmpty] [sum(sumss),cume_sales,sum,isEmpty] + InputAdapter + Exchange [item_sk,d_date,sumss] #9 + WholeStageCodegen (22) + HashAggregate [item_sk,d_date,sumss,sumss] [sum,isEmpty,sum,isEmpty] + Project [item_sk,d_date,sumss,sumss] + BroadcastHashJoin [item_sk,item_sk,rk,rk] + Project [item_sk,d_date,sumss,rk] + InputAdapter + Window [ss_item_sk,d_date] + WholeStageCodegen (16) + Sort [ss_item_sk,d_date] + InputAdapter + Exchange [ss_item_sk] #10 + WholeStageCodegen (15) + HashAggregate [ss_item_sk,d_date,sum] [sum(UnscaledValue(ss_sales_price)),item_sk,sumss,sum] + InputAdapter + Exchange [ss_item_sk,d_date] #11 + WholeStageCodegen (14) + HashAggregate [ss_item_sk,d_date,ss_sales_price] [sum,sum] + Project [ss_item_sk,ss_sales_price,d_date] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_sales_price,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk,d_date] #6 + InputAdapter + BroadcastExchange #12 + WholeStageCodegen (21) + Project [item_sk,sumss,rk] + InputAdapter + Window [ss_item_sk,d_date] + WholeStageCodegen (20) + Sort [ss_item_sk,d_date] + InputAdapter + ReusedExchange [item_sk,d_date,sumss,ss_item_sk] #10 + InputAdapter + BroadcastExchange #13 + WholeStageCodegen (53) + Project [item_sk,web_sales,store_sales,rk] + InputAdapter + Window [item_sk,d_date] + WholeStageCodegen (52) + Sort [item_sk,d_date] + InputAdapter + ReusedExchange [item_sk,d_date,web_sales,store_sales] #1 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q57/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q57/explain.txt new file mode 100644 index 0000000000..dd64cc7bc8 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q57/explain.txt @@ -0,0 +1,279 @@ +== Physical Plan == +TakeOrderedAndProject (45) ++- * Project (44) + +- * BroadcastHashJoin Inner BuildRight (43) + :- * Project (37) + : +- * BroadcastHashJoin Inner BuildRight (36) + : :- * Project (28) + : : +- * Filter (27) + : : +- Window (26) + : : +- * Filter (25) + : : +- Window (24) + : : +- * Sort (23) + : : +- Exchange (22) + : : +- * HashAggregate (21) + : : +- Exchange (20) + : : +- * HashAggregate (19) + : : +- * Project (18) + : : +- * BroadcastHashJoin Inner BuildRight (17) + : : :- * Project (12) + : : : +- * BroadcastHashJoin Inner BuildRight (11) + : : : :- * Project (9) + : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) + : : : : : +- CometScan parquet spark_catalog.default.item (1) + : : : : +- BroadcastExchange (7) + : : : : +- * ColumnarToRow (6) + : : : : +- CometFilter (5) + : : : : +- CometScan parquet spark_catalog.default.catalog_sales (4) + : : : +- ReusedExchange (10) + : : +- BroadcastExchange (16) + : : +- * ColumnarToRow (15) + : : +- CometFilter (14) + : : +- CometScan parquet spark_catalog.default.call_center (13) + : +- BroadcastExchange (35) + : +- * Project (34) + : +- Window (33) + : +- * Sort (32) + : +- Exchange (31) + : +- * HashAggregate (30) + : +- ReusedExchange (29) + +- BroadcastExchange (42) + +- * Project (41) + +- Window (40) + +- * Sort (39) + +- ReusedExchange (38) + + +(1) Scan parquet spark_catalog.default.item +Output [3]: [i_item_sk#1, i_brand#2, i_category#3] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_category), IsNotNull(i_brand)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [i_item_sk#1, i_brand#2, i_category#3] +Condition : ((isnotnull(i_item_sk#1) AND isnotnull(i_category#3)) AND isnotnull(i_brand#2)) + +(3) ColumnarToRow [codegen id : 4] +Input [3]: [i_item_sk#1, i_brand#2, i_category#3] + +(4) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_call_center_sk#4, cs_item_sk#5, cs_sales_price#6, cs_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#7), dynamicpruningexpression(cs_sold_date_sk#7 IN dynamicpruning#8)] +PushedFilters: [IsNotNull(cs_item_sk), IsNotNull(cs_call_center_sk)] +ReadSchema: struct + +(5) CometFilter +Input [4]: [cs_call_center_sk#4, cs_item_sk#5, cs_sales_price#6, cs_sold_date_sk#7] +Condition : (isnotnull(cs_item_sk#5) AND isnotnull(cs_call_center_sk#4)) + +(6) ColumnarToRow [codegen id : 1] +Input [4]: [cs_call_center_sk#4, cs_item_sk#5, cs_sales_price#6, cs_sold_date_sk#7] + +(7) BroadcastExchange +Input [4]: [cs_call_center_sk#4, cs_item_sk#5, cs_sales_price#6, cs_sold_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[1, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [i_item_sk#1] +Right keys [1]: [cs_item_sk#5] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 4] +Output [5]: [i_brand#2, i_category#3, cs_call_center_sk#4, cs_sales_price#6, cs_sold_date_sk#7] +Input [7]: [i_item_sk#1, i_brand#2, i_category#3, cs_call_center_sk#4, cs_item_sk#5, cs_sales_price#6, cs_sold_date_sk#7] + +(10) ReusedExchange [Reuses operator id: 49] +Output [3]: [d_date_sk#9, d_year#10, d_moy#11] + +(11) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [cs_sold_date_sk#7] +Right keys [1]: [d_date_sk#9] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 4] +Output [6]: [i_brand#2, i_category#3, cs_call_center_sk#4, cs_sales_price#6, d_year#10, d_moy#11] +Input [8]: [i_brand#2, i_category#3, cs_call_center_sk#4, cs_sales_price#6, cs_sold_date_sk#7, d_date_sk#9, d_year#10, d_moy#11] + +(13) Scan parquet spark_catalog.default.call_center +Output [2]: [cc_call_center_sk#12, cc_name#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/call_center] +PushedFilters: [IsNotNull(cc_call_center_sk), IsNotNull(cc_name)] +ReadSchema: struct + +(14) CometFilter +Input [2]: [cc_call_center_sk#12, cc_name#13] +Condition : (isnotnull(cc_call_center_sk#12) AND isnotnull(cc_name#13)) + +(15) ColumnarToRow [codegen id : 3] +Input [2]: [cc_call_center_sk#12, cc_name#13] + +(16) BroadcastExchange +Input [2]: [cc_call_center_sk#12, cc_name#13] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(17) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [cs_call_center_sk#4] +Right keys [1]: [cc_call_center_sk#12] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 4] +Output [6]: [i_brand#2, i_category#3, cs_sales_price#6, d_year#10, d_moy#11, cc_name#13] +Input [8]: [i_brand#2, i_category#3, cs_call_center_sk#4, cs_sales_price#6, d_year#10, d_moy#11, cc_call_center_sk#12, cc_name#13] + +(19) HashAggregate [codegen id : 4] +Input [6]: [i_brand#2, i_category#3, cs_sales_price#6, d_year#10, d_moy#11, cc_name#13] +Keys [5]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11] +Functions [1]: [partial_sum(UnscaledValue(cs_sales_price#6))] +Aggregate Attributes [1]: [sum#14] +Results [6]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum#15] + +(20) Exchange +Input [6]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum#15] +Arguments: hashpartitioning(i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(21) HashAggregate [codegen id : 5] +Input [6]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum#15] +Keys [5]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11] +Functions [1]: [sum(UnscaledValue(cs_sales_price#6))] +Aggregate Attributes [1]: [sum(UnscaledValue(cs_sales_price#6))#16] +Results [7]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, MakeDecimal(sum(UnscaledValue(cs_sales_price#6))#16,17,2) AS sum_sales#17, MakeDecimal(sum(UnscaledValue(cs_sales_price#6))#16,17,2) AS _w0#18] + +(22) Exchange +Input [7]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, _w0#18] +Arguments: hashpartitioning(i_category#3, i_brand#2, cc_name#13, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(23) Sort [codegen id : 6] +Input [7]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, _w0#18] +Arguments: [i_category#3 ASC NULLS FIRST, i_brand#2 ASC NULLS FIRST, cc_name#13 ASC NULLS FIRST, d_year#10 ASC NULLS FIRST, d_moy#11 ASC NULLS FIRST], false, 0 + +(24) Window +Input [7]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, _w0#18] +Arguments: [rank(d_year#10, d_moy#11) windowspecdefinition(i_category#3, i_brand#2, cc_name#13, d_year#10 ASC NULLS FIRST, d_moy#11 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rn#19], [i_category#3, i_brand#2, cc_name#13], [d_year#10 ASC NULLS FIRST, d_moy#11 ASC NULLS FIRST] + +(25) Filter [codegen id : 7] +Input [8]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, _w0#18, rn#19] +Condition : (isnotnull(d_year#10) AND (d_year#10 = 1999)) + +(26) Window +Input [8]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, _w0#18, rn#19] +Arguments: [avg(_w0#18) windowspecdefinition(i_category#3, i_brand#2, cc_name#13, d_year#10, specifiedwindowframe(RowFrame, unboundedpreceding$(), unboundedfollowing$())) AS avg_monthly_sales#20], [i_category#3, i_brand#2, cc_name#13, d_year#10] + +(27) Filter [codegen id : 22] +Input [9]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, _w0#18, rn#19, avg_monthly_sales#20] +Condition : ((isnotnull(avg_monthly_sales#20) AND (avg_monthly_sales#20 > 0.000000)) AND CASE WHEN (avg_monthly_sales#20 > 0.000000) THEN ((abs((sum_sales#17 - avg_monthly_sales#20)) / avg_monthly_sales#20) > 0.1000000000000000) END) + +(28) Project [codegen id : 22] +Output [8]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, avg_monthly_sales#20, rn#19] +Input [9]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, _w0#18, rn#19, avg_monthly_sales#20] + +(29) ReusedExchange [Reuses operator id: 20] +Output [6]: [i_category#21, i_brand#22, cc_name#23, d_year#24, d_moy#25, sum#26] + +(30) HashAggregate [codegen id : 12] +Input [6]: [i_category#21, i_brand#22, cc_name#23, d_year#24, d_moy#25, sum#26] +Keys [5]: [i_category#21, i_brand#22, cc_name#23, d_year#24, d_moy#25] +Functions [1]: [sum(UnscaledValue(cs_sales_price#27))] +Aggregate Attributes [1]: [sum(UnscaledValue(cs_sales_price#27))#16] +Results [6]: [i_category#21, i_brand#22, cc_name#23, d_year#24, d_moy#25, MakeDecimal(sum(UnscaledValue(cs_sales_price#27))#16,17,2) AS sum_sales#28] + +(31) Exchange +Input [6]: [i_category#21, i_brand#22, cc_name#23, d_year#24, d_moy#25, sum_sales#28] +Arguments: hashpartitioning(i_category#21, i_brand#22, cc_name#23, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(32) Sort [codegen id : 13] +Input [6]: [i_category#21, i_brand#22, cc_name#23, d_year#24, d_moy#25, sum_sales#28] +Arguments: [i_category#21 ASC NULLS FIRST, i_brand#22 ASC NULLS FIRST, cc_name#23 ASC NULLS FIRST, d_year#24 ASC NULLS FIRST, d_moy#25 ASC NULLS FIRST], false, 0 + +(33) Window +Input [6]: [i_category#21, i_brand#22, cc_name#23, d_year#24, d_moy#25, sum_sales#28] +Arguments: [rank(d_year#24, d_moy#25) windowspecdefinition(i_category#21, i_brand#22, cc_name#23, d_year#24 ASC NULLS FIRST, d_moy#25 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rn#29], [i_category#21, i_brand#22, cc_name#23], [d_year#24 ASC NULLS FIRST, d_moy#25 ASC NULLS FIRST] + +(34) Project [codegen id : 14] +Output [5]: [i_category#21, i_brand#22, cc_name#23, sum_sales#28, rn#29] +Input [7]: [i_category#21, i_brand#22, cc_name#23, d_year#24, d_moy#25, sum_sales#28, rn#29] + +(35) BroadcastExchange +Input [5]: [i_category#21, i_brand#22, cc_name#23, sum_sales#28, rn#29] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true], input[1, string, true], input[2, string, true], (input[4, int, false] + 1)),false), [plan_id=6] + +(36) BroadcastHashJoin [codegen id : 22] +Left keys [4]: [i_category#3, i_brand#2, cc_name#13, rn#19] +Right keys [4]: [i_category#21, i_brand#22, cc_name#23, (rn#29 + 1)] +Join type: Inner +Join condition: None + +(37) Project [codegen id : 22] +Output [9]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, avg_monthly_sales#20, rn#19, sum_sales#28] +Input [13]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, avg_monthly_sales#20, rn#19, i_category#21, i_brand#22, cc_name#23, sum_sales#28, rn#29] + +(38) ReusedExchange [Reuses operator id: 31] +Output [6]: [i_category#30, i_brand#31, cc_name#32, d_year#33, d_moy#34, sum_sales#35] + +(39) Sort [codegen id : 20] +Input [6]: [i_category#30, i_brand#31, cc_name#32, d_year#33, d_moy#34, sum_sales#35] +Arguments: [i_category#30 ASC NULLS FIRST, i_brand#31 ASC NULLS FIRST, cc_name#32 ASC NULLS FIRST, d_year#33 ASC NULLS FIRST, d_moy#34 ASC NULLS FIRST], false, 0 + +(40) Window +Input [6]: [i_category#30, i_brand#31, cc_name#32, d_year#33, d_moy#34, sum_sales#35] +Arguments: [rank(d_year#33, d_moy#34) windowspecdefinition(i_category#30, i_brand#31, cc_name#32, d_year#33 ASC NULLS FIRST, d_moy#34 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rn#36], [i_category#30, i_brand#31, cc_name#32], [d_year#33 ASC NULLS FIRST, d_moy#34 ASC NULLS FIRST] + +(41) Project [codegen id : 21] +Output [5]: [i_category#30, i_brand#31, cc_name#32, sum_sales#35, rn#36] +Input [7]: [i_category#30, i_brand#31, cc_name#32, d_year#33, d_moy#34, sum_sales#35, rn#36] + +(42) BroadcastExchange +Input [5]: [i_category#30, i_brand#31, cc_name#32, sum_sales#35, rn#36] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true], input[1, string, true], input[2, string, true], (input[4, int, false] - 1)),false), [plan_id=7] + +(43) BroadcastHashJoin [codegen id : 22] +Left keys [4]: [i_category#3, i_brand#2, cc_name#13, rn#19] +Right keys [4]: [i_category#30, i_brand#31, cc_name#32, (rn#36 - 1)] +Join type: Inner +Join condition: None + +(44) Project [codegen id : 22] +Output [8]: [i_category#3, i_brand#2, d_year#10, d_moy#11, avg_monthly_sales#20, sum_sales#17, sum_sales#28 AS psum#37, sum_sales#35 AS nsum#38] +Input [14]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, avg_monthly_sales#20, rn#19, sum_sales#28, i_category#30, i_brand#31, cc_name#32, sum_sales#35, rn#36] + +(45) TakeOrderedAndProject +Input [8]: [i_category#3, i_brand#2, d_year#10, d_moy#11, avg_monthly_sales#20, sum_sales#17, psum#37, nsum#38] +Arguments: 100, [(sum_sales#17 - avg_monthly_sales#20) ASC NULLS FIRST, d_year#10 ASC NULLS FIRST], [i_category#3, i_brand#2, d_year#10, d_moy#11, avg_monthly_sales#20, sum_sales#17, psum#37, nsum#38] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = cs_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (49) ++- * ColumnarToRow (48) + +- CometFilter (47) + +- CometScan parquet spark_catalog.default.date_dim (46) + + +(46) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#9, d_year#10, d_moy#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [Or(Or(EqualTo(d_year,1999),And(EqualTo(d_year,1998),EqualTo(d_moy,12))),And(EqualTo(d_year,2000),EqualTo(d_moy,1))), IsNotNull(d_date_sk)] +ReadSchema: struct + +(47) CometFilter +Input [3]: [d_date_sk#9, d_year#10, d_moy#11] +Condition : ((((d_year#10 = 1999) OR ((d_year#10 = 1998) AND (d_moy#11 = 12))) OR ((d_year#10 = 2000) AND (d_moy#11 = 1))) AND isnotnull(d_date_sk#9)) + +(48) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#9, d_year#10, d_moy#11] + +(49) BroadcastExchange +Input [3]: [d_date_sk#9, d_year#10, d_moy#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q57/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q57/simplified.txt new file mode 100644 index 0000000000..56e33be9e4 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q57/simplified.txt @@ -0,0 +1,81 @@ +TakeOrderedAndProject [sum_sales,avg_monthly_sales,d_year,i_category,i_brand,d_moy,psum,nsum] + WholeStageCodegen (22) + Project [i_category,i_brand,d_year,d_moy,avg_monthly_sales,sum_sales,sum_sales,sum_sales] + BroadcastHashJoin [i_category,i_brand,cc_name,rn,i_category,i_brand,cc_name,rn] + Project [i_category,i_brand,cc_name,d_year,d_moy,sum_sales,avg_monthly_sales,rn,sum_sales] + BroadcastHashJoin [i_category,i_brand,cc_name,rn,i_category,i_brand,cc_name,rn] + Project [i_category,i_brand,cc_name,d_year,d_moy,sum_sales,avg_monthly_sales,rn] + Filter [avg_monthly_sales,sum_sales] + InputAdapter + Window [_w0,i_category,i_brand,cc_name,d_year] + WholeStageCodegen (7) + Filter [d_year] + InputAdapter + Window [d_year,d_moy,i_category,i_brand,cc_name] + WholeStageCodegen (6) + Sort [i_category,i_brand,cc_name,d_year,d_moy] + InputAdapter + Exchange [i_category,i_brand,cc_name] #1 + WholeStageCodegen (5) + HashAggregate [i_category,i_brand,cc_name,d_year,d_moy,sum] [sum(UnscaledValue(cs_sales_price)),sum_sales,_w0,sum] + InputAdapter + Exchange [i_category,i_brand,cc_name,d_year,d_moy] #2 + WholeStageCodegen (4) + HashAggregate [i_category,i_brand,cc_name,d_year,d_moy,cs_sales_price] [sum,sum] + Project [i_brand,i_category,cs_sales_price,d_year,d_moy,cc_name] + BroadcastHashJoin [cs_call_center_sk,cc_call_center_sk] + Project [i_brand,i_category,cs_call_center_sk,cs_sales_price,d_year,d_moy] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [i_brand,i_category,cs_call_center_sk,cs_sales_price,cs_sold_date_sk] + BroadcastHashJoin [i_item_sk,cs_item_sk] + ColumnarToRow + InputAdapter + CometFilter [i_item_sk,i_category,i_brand] + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_category] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk,cs_call_center_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_call_center_sk,cs_item_sk,cs_sales_price,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_year,d_moy,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + ReusedExchange [d_date_sk,d_year,d_moy] #4 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometFilter [cc_call_center_sk,cc_name] + CometScan parquet spark_catalog.default.call_center [cc_call_center_sk,cc_name] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (14) + Project [i_category,i_brand,cc_name,sum_sales,rn] + InputAdapter + Window [d_year,d_moy,i_category,i_brand,cc_name] + WholeStageCodegen (13) + Sort [i_category,i_brand,cc_name,d_year,d_moy] + InputAdapter + Exchange [i_category,i_brand,cc_name] #7 + WholeStageCodegen (12) + HashAggregate [i_category,i_brand,cc_name,d_year,d_moy,sum] [sum(UnscaledValue(cs_sales_price)),sum_sales,sum] + InputAdapter + ReusedExchange [i_category,i_brand,cc_name,d_year,d_moy,sum] #2 + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (21) + Project [i_category,i_brand,cc_name,sum_sales,rn] + InputAdapter + Window [d_year,d_moy,i_category,i_brand,cc_name] + WholeStageCodegen (20) + Sort [i_category,i_brand,cc_name,d_year,d_moy] + InputAdapter + ReusedExchange [i_category,i_brand,cc_name,d_year,d_moy,sum_sales] #7 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q5a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q5a/explain.txt new file mode 100644 index 0000000000..2769e772ae --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q5a/explain.txt @@ -0,0 +1,542 @@ +== Physical Plan == +TakeOrderedAndProject (83) ++- * HashAggregate (82) + +- Exchange (81) + +- * HashAggregate (80) + +- Union (79) + :- * HashAggregate (68) + : +- Exchange (67) + : +- * HashAggregate (66) + : +- Union (65) + : :- * HashAggregate (20) + : : +- Exchange (19) + : : +- * HashAggregate (18) + : : +- * Project (17) + : : +- * BroadcastHashJoin Inner BuildRight (16) + : : :- * Project (11) + : : : +- * BroadcastHashJoin Inner BuildRight (10) + : : : :- * ColumnarToRow (8) + : : : : +- CometUnion (7) + : : : : :- CometProject (3) + : : : : : +- CometFilter (2) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : +- CometProject (6) + : : : : +- CometFilter (5) + : : : : +- CometScan parquet spark_catalog.default.store_returns (4) + : : : +- ReusedExchange (9) + : : +- BroadcastExchange (15) + : : +- * ColumnarToRow (14) + : : +- CometFilter (13) + : : +- CometScan parquet spark_catalog.default.store (12) + : :- * HashAggregate (40) + : : +- Exchange (39) + : : +- * HashAggregate (38) + : : +- * Project (37) + : : +- * BroadcastHashJoin Inner BuildRight (36) + : : :- * Project (31) + : : : +- * BroadcastHashJoin Inner BuildRight (30) + : : : :- * ColumnarToRow (28) + : : : : +- CometUnion (27) + : : : : :- CometProject (23) + : : : : : +- CometFilter (22) + : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (21) + : : : : +- CometProject (26) + : : : : +- CometFilter (25) + : : : : +- CometScan parquet spark_catalog.default.catalog_returns (24) + : : : +- ReusedExchange (29) + : : +- BroadcastExchange (35) + : : +- * ColumnarToRow (34) + : : +- CometFilter (33) + : : +- CometScan parquet spark_catalog.default.catalog_page (32) + : +- * HashAggregate (64) + : +- Exchange (63) + : +- * HashAggregate (62) + : +- * Project (61) + : +- * BroadcastHashJoin Inner BuildRight (60) + : :- * Project (55) + : : +- * BroadcastHashJoin Inner BuildRight (54) + : : :- * ColumnarToRow (52) + : : : +- CometUnion (51) + : : : :- CometProject (43) + : : : : +- CometFilter (42) + : : : : +- CometScan parquet spark_catalog.default.web_sales (41) + : : : +- CometProject (50) + : : : +- CometBroadcastHashJoin (49) + : : : :- CometBroadcastExchange (45) + : : : : +- CometScan parquet spark_catalog.default.web_returns (44) + : : : +- CometProject (48) + : : : +- CometFilter (47) + : : : +- CometScan parquet spark_catalog.default.web_sales (46) + : : +- ReusedExchange (53) + : +- BroadcastExchange (59) + : +- * ColumnarToRow (58) + : +- CometFilter (57) + : +- CometScan parquet spark_catalog.default.web_site (56) + :- * HashAggregate (73) + : +- Exchange (72) + : +- * HashAggregate (71) + : +- * HashAggregate (70) + : +- ReusedExchange (69) + +- * HashAggregate (78) + +- Exchange (77) + +- * HashAggregate (76) + +- * HashAggregate (75) + +- ReusedExchange (74) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#4), dynamicpruningexpression(ss_sold_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(ss_store_sk)] +ReadSchema: struct + +(2) CometFilter +Input [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] +Condition : isnotnull(ss_store_sk#1) + +(3) CometProject +Input [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] +Arguments: [store_sk#6, date_sk#7, sales_price#8, profit#9, return_amt#10, net_loss#11], [ss_store_sk#1 AS store_sk#6, ss_sold_date_sk#4 AS date_sk#7, ss_ext_sales_price#2 AS sales_price#8, ss_net_profit#3 AS profit#9, 0.00 AS return_amt#10, 0.00 AS net_loss#11] + +(4) Scan parquet spark_catalog.default.store_returns +Output [4]: [sr_store_sk#12, sr_return_amt#13, sr_net_loss#14, sr_returned_date_sk#15] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(sr_returned_date_sk#15), dynamicpruningexpression(sr_returned_date_sk#15 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(sr_store_sk)] +ReadSchema: struct + +(5) CometFilter +Input [4]: [sr_store_sk#12, sr_return_amt#13, sr_net_loss#14, sr_returned_date_sk#15] +Condition : isnotnull(sr_store_sk#12) + +(6) CometProject +Input [4]: [sr_store_sk#12, sr_return_amt#13, sr_net_loss#14, sr_returned_date_sk#15] +Arguments: [store_sk#16, date_sk#17, sales_price#18, profit#19, return_amt#20, net_loss#21], [sr_store_sk#12 AS store_sk#16, sr_returned_date_sk#15 AS date_sk#17, 0.00 AS sales_price#18, 0.00 AS profit#19, sr_return_amt#13 AS return_amt#20, sr_net_loss#14 AS net_loss#21] + +(7) CometUnion +Child 0 Input [6]: [store_sk#6, date_sk#7, sales_price#8, profit#9, return_amt#10, net_loss#11] +Child 1 Input [6]: [store_sk#16, date_sk#17, sales_price#18, profit#19, return_amt#20, net_loss#21] + +(8) ColumnarToRow [codegen id : 3] +Input [6]: [store_sk#6, date_sk#7, sales_price#8, profit#9, return_amt#10, net_loss#11] + +(9) ReusedExchange [Reuses operator id: 88] +Output [1]: [d_date_sk#22] + +(10) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [date_sk#7] +Right keys [1]: [d_date_sk#22] +Join type: Inner +Join condition: None + +(11) Project [codegen id : 3] +Output [5]: [store_sk#6, sales_price#8, profit#9, return_amt#10, net_loss#11] +Input [7]: [store_sk#6, date_sk#7, sales_price#8, profit#9, return_amt#10, net_loss#11, d_date_sk#22] + +(12) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#23, s_store_id#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(13) CometFilter +Input [2]: [s_store_sk#23, s_store_id#24] +Condition : isnotnull(s_store_sk#23) + +(14) ColumnarToRow [codegen id : 2] +Input [2]: [s_store_sk#23, s_store_id#24] + +(15) BroadcastExchange +Input [2]: [s_store_sk#23, s_store_id#24] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(16) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [store_sk#6] +Right keys [1]: [s_store_sk#23] +Join type: Inner +Join condition: None + +(17) Project [codegen id : 3] +Output [5]: [sales_price#8, profit#9, return_amt#10, net_loss#11, s_store_id#24] +Input [7]: [store_sk#6, sales_price#8, profit#9, return_amt#10, net_loss#11, s_store_sk#23, s_store_id#24] + +(18) HashAggregate [codegen id : 3] +Input [5]: [sales_price#8, profit#9, return_amt#10, net_loss#11, s_store_id#24] +Keys [1]: [s_store_id#24] +Functions [4]: [partial_sum(UnscaledValue(sales_price#8)), partial_sum(UnscaledValue(return_amt#10)), partial_sum(UnscaledValue(profit#9)), partial_sum(UnscaledValue(net_loss#11))] +Aggregate Attributes [4]: [sum#25, sum#26, sum#27, sum#28] +Results [5]: [s_store_id#24, sum#29, sum#30, sum#31, sum#32] + +(19) Exchange +Input [5]: [s_store_id#24, sum#29, sum#30, sum#31, sum#32] +Arguments: hashpartitioning(s_store_id#24, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(20) HashAggregate [codegen id : 4] +Input [5]: [s_store_id#24, sum#29, sum#30, sum#31, sum#32] +Keys [1]: [s_store_id#24] +Functions [4]: [sum(UnscaledValue(sales_price#8)), sum(UnscaledValue(return_amt#10)), sum(UnscaledValue(profit#9)), sum(UnscaledValue(net_loss#11))] +Aggregate Attributes [4]: [sum(UnscaledValue(sales_price#8))#33, sum(UnscaledValue(return_amt#10))#34, sum(UnscaledValue(profit#9))#35, sum(UnscaledValue(net_loss#11))#36] +Results [5]: [store channel AS channel#37, concat(store, s_store_id#24) AS id#38, MakeDecimal(sum(UnscaledValue(sales_price#8))#33,17,2) AS sales#39, MakeDecimal(sum(UnscaledValue(return_amt#10))#34,17,2) AS returns#40, (MakeDecimal(sum(UnscaledValue(profit#9))#35,17,2) - MakeDecimal(sum(UnscaledValue(net_loss#11))#36,17,2)) AS profit#41] + +(21) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_catalog_page_sk#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#45), dynamicpruningexpression(cs_sold_date_sk#45 IN dynamicpruning#46)] +PushedFilters: [IsNotNull(cs_catalog_page_sk)] +ReadSchema: struct + +(22) CometFilter +Input [4]: [cs_catalog_page_sk#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] +Condition : isnotnull(cs_catalog_page_sk#42) + +(23) CometProject +Input [4]: [cs_catalog_page_sk#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] +Arguments: [page_sk#47, date_sk#48, sales_price#49, profit#50, return_amt#51, net_loss#52], [cs_catalog_page_sk#42 AS page_sk#47, cs_sold_date_sk#45 AS date_sk#48, cs_ext_sales_price#43 AS sales_price#49, cs_net_profit#44 AS profit#50, 0.00 AS return_amt#51, 0.00 AS net_loss#52] + +(24) Scan parquet spark_catalog.default.catalog_returns +Output [4]: [cr_catalog_page_sk#53, cr_return_amount#54, cr_net_loss#55, cr_returned_date_sk#56] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cr_returned_date_sk#56), dynamicpruningexpression(cr_returned_date_sk#56 IN dynamicpruning#46)] +PushedFilters: [IsNotNull(cr_catalog_page_sk)] +ReadSchema: struct + +(25) CometFilter +Input [4]: [cr_catalog_page_sk#53, cr_return_amount#54, cr_net_loss#55, cr_returned_date_sk#56] +Condition : isnotnull(cr_catalog_page_sk#53) + +(26) CometProject +Input [4]: [cr_catalog_page_sk#53, cr_return_amount#54, cr_net_loss#55, cr_returned_date_sk#56] +Arguments: [page_sk#57, date_sk#58, sales_price#59, profit#60, return_amt#61, net_loss#62], [cr_catalog_page_sk#53 AS page_sk#57, cr_returned_date_sk#56 AS date_sk#58, 0.00 AS sales_price#59, 0.00 AS profit#60, cr_return_amount#54 AS return_amt#61, cr_net_loss#55 AS net_loss#62] + +(27) CometUnion +Child 0 Input [6]: [page_sk#47, date_sk#48, sales_price#49, profit#50, return_amt#51, net_loss#52] +Child 1 Input [6]: [page_sk#57, date_sk#58, sales_price#59, profit#60, return_amt#61, net_loss#62] + +(28) ColumnarToRow [codegen id : 7] +Input [6]: [page_sk#47, date_sk#48, sales_price#49, profit#50, return_amt#51, net_loss#52] + +(29) ReusedExchange [Reuses operator id: 88] +Output [1]: [d_date_sk#63] + +(30) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [date_sk#48] +Right keys [1]: [d_date_sk#63] +Join type: Inner +Join condition: None + +(31) Project [codegen id : 7] +Output [5]: [page_sk#47, sales_price#49, profit#50, return_amt#51, net_loss#52] +Input [7]: [page_sk#47, date_sk#48, sales_price#49, profit#50, return_amt#51, net_loss#52, d_date_sk#63] + +(32) Scan parquet spark_catalog.default.catalog_page +Output [2]: [cp_catalog_page_sk#64, cp_catalog_page_id#65] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_page] +PushedFilters: [IsNotNull(cp_catalog_page_sk)] +ReadSchema: struct + +(33) CometFilter +Input [2]: [cp_catalog_page_sk#64, cp_catalog_page_id#65] +Condition : isnotnull(cp_catalog_page_sk#64) + +(34) ColumnarToRow [codegen id : 6] +Input [2]: [cp_catalog_page_sk#64, cp_catalog_page_id#65] + +(35) BroadcastExchange +Input [2]: [cp_catalog_page_sk#64, cp_catalog_page_id#65] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(36) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [page_sk#47] +Right keys [1]: [cp_catalog_page_sk#64] +Join type: Inner +Join condition: None + +(37) Project [codegen id : 7] +Output [5]: [sales_price#49, profit#50, return_amt#51, net_loss#52, cp_catalog_page_id#65] +Input [7]: [page_sk#47, sales_price#49, profit#50, return_amt#51, net_loss#52, cp_catalog_page_sk#64, cp_catalog_page_id#65] + +(38) HashAggregate [codegen id : 7] +Input [5]: [sales_price#49, profit#50, return_amt#51, net_loss#52, cp_catalog_page_id#65] +Keys [1]: [cp_catalog_page_id#65] +Functions [4]: [partial_sum(UnscaledValue(sales_price#49)), partial_sum(UnscaledValue(return_amt#51)), partial_sum(UnscaledValue(profit#50)), partial_sum(UnscaledValue(net_loss#52))] +Aggregate Attributes [4]: [sum#66, sum#67, sum#68, sum#69] +Results [5]: [cp_catalog_page_id#65, sum#70, sum#71, sum#72, sum#73] + +(39) Exchange +Input [5]: [cp_catalog_page_id#65, sum#70, sum#71, sum#72, sum#73] +Arguments: hashpartitioning(cp_catalog_page_id#65, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(40) HashAggregate [codegen id : 8] +Input [5]: [cp_catalog_page_id#65, sum#70, sum#71, sum#72, sum#73] +Keys [1]: [cp_catalog_page_id#65] +Functions [4]: [sum(UnscaledValue(sales_price#49)), sum(UnscaledValue(return_amt#51)), sum(UnscaledValue(profit#50)), sum(UnscaledValue(net_loss#52))] +Aggregate Attributes [4]: [sum(UnscaledValue(sales_price#49))#74, sum(UnscaledValue(return_amt#51))#75, sum(UnscaledValue(profit#50))#76, sum(UnscaledValue(net_loss#52))#77] +Results [5]: [catalog channel AS channel#78, concat(catalog_page, cp_catalog_page_id#65) AS id#79, MakeDecimal(sum(UnscaledValue(sales_price#49))#74,17,2) AS sales#80, MakeDecimal(sum(UnscaledValue(return_amt#51))#75,17,2) AS returns#81, (MakeDecimal(sum(UnscaledValue(profit#50))#76,17,2) - MakeDecimal(sum(UnscaledValue(net_loss#52))#77,17,2)) AS profit#82] + +(41) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_web_site_sk#83, ws_ext_sales_price#84, ws_net_profit#85, ws_sold_date_sk#86] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#86), dynamicpruningexpression(ws_sold_date_sk#86 IN dynamicpruning#87)] +PushedFilters: [IsNotNull(ws_web_site_sk)] +ReadSchema: struct + +(42) CometFilter +Input [4]: [ws_web_site_sk#83, ws_ext_sales_price#84, ws_net_profit#85, ws_sold_date_sk#86] +Condition : isnotnull(ws_web_site_sk#83) + +(43) CometProject +Input [4]: [ws_web_site_sk#83, ws_ext_sales_price#84, ws_net_profit#85, ws_sold_date_sk#86] +Arguments: [wsr_web_site_sk#88, date_sk#89, sales_price#90, profit#91, return_amt#92, net_loss#93], [ws_web_site_sk#83 AS wsr_web_site_sk#88, ws_sold_date_sk#86 AS date_sk#89, ws_ext_sales_price#84 AS sales_price#90, ws_net_profit#85 AS profit#91, 0.00 AS return_amt#92, 0.00 AS net_loss#93] + +(44) Scan parquet spark_catalog.default.web_returns +Output [5]: [wr_item_sk#94, wr_order_number#95, wr_return_amt#96, wr_net_loss#97, wr_returned_date_sk#98] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(wr_returned_date_sk#98), dynamicpruningexpression(wr_returned_date_sk#98 IN dynamicpruning#87)] +ReadSchema: struct + +(45) CometBroadcastExchange +Input [5]: [wr_item_sk#94, wr_order_number#95, wr_return_amt#96, wr_net_loss#97, wr_returned_date_sk#98] +Arguments: [wr_item_sk#94, wr_order_number#95, wr_return_amt#96, wr_net_loss#97, wr_returned_date_sk#98] + +(46) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101, ws_sold_date_sk#102] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_sales] +PushedFilters: [IsNotNull(ws_item_sk), IsNotNull(ws_order_number), IsNotNull(ws_web_site_sk)] +ReadSchema: struct + +(47) CometFilter +Input [4]: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101, ws_sold_date_sk#102] +Condition : ((isnotnull(ws_item_sk#99) AND isnotnull(ws_order_number#101)) AND isnotnull(ws_web_site_sk#100)) + +(48) CometProject +Input [4]: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101, ws_sold_date_sk#102] +Arguments: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101], [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101] + +(49) CometBroadcastHashJoin +Left output [5]: [wr_item_sk#94, wr_order_number#95, wr_return_amt#96, wr_net_loss#97, wr_returned_date_sk#98] +Right output [3]: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101] +Arguments: [wr_item_sk#94, wr_order_number#95], [ws_item_sk#99, ws_order_number#101], Inner + +(50) CometProject +Input [8]: [wr_item_sk#94, wr_order_number#95, wr_return_amt#96, wr_net_loss#97, wr_returned_date_sk#98, ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101] +Arguments: [wsr_web_site_sk#103, date_sk#104, sales_price#105, profit#106, return_amt#107, net_loss#108], [ws_web_site_sk#100 AS wsr_web_site_sk#103, wr_returned_date_sk#98 AS date_sk#104, 0.00 AS sales_price#105, 0.00 AS profit#106, wr_return_amt#96 AS return_amt#107, wr_net_loss#97 AS net_loss#108] + +(51) CometUnion +Child 0 Input [6]: [wsr_web_site_sk#88, date_sk#89, sales_price#90, profit#91, return_amt#92, net_loss#93] +Child 1 Input [6]: [wsr_web_site_sk#103, date_sk#104, sales_price#105, profit#106, return_amt#107, net_loss#108] + +(52) ColumnarToRow [codegen id : 11] +Input [6]: [wsr_web_site_sk#88, date_sk#89, sales_price#90, profit#91, return_amt#92, net_loss#93] + +(53) ReusedExchange [Reuses operator id: 88] +Output [1]: [d_date_sk#109] + +(54) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [date_sk#89] +Right keys [1]: [d_date_sk#109] +Join type: Inner +Join condition: None + +(55) Project [codegen id : 11] +Output [5]: [wsr_web_site_sk#88, sales_price#90, profit#91, return_amt#92, net_loss#93] +Input [7]: [wsr_web_site_sk#88, date_sk#89, sales_price#90, profit#91, return_amt#92, net_loss#93, d_date_sk#109] + +(56) Scan parquet spark_catalog.default.web_site +Output [2]: [web_site_sk#110, web_site_id#111] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_site] +PushedFilters: [IsNotNull(web_site_sk)] +ReadSchema: struct + +(57) CometFilter +Input [2]: [web_site_sk#110, web_site_id#111] +Condition : isnotnull(web_site_sk#110) + +(58) ColumnarToRow [codegen id : 10] +Input [2]: [web_site_sk#110, web_site_id#111] + +(59) BroadcastExchange +Input [2]: [web_site_sk#110, web_site_id#111] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(60) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [wsr_web_site_sk#88] +Right keys [1]: [web_site_sk#110] +Join type: Inner +Join condition: None + +(61) Project [codegen id : 11] +Output [5]: [sales_price#90, profit#91, return_amt#92, net_loss#93, web_site_id#111] +Input [7]: [wsr_web_site_sk#88, sales_price#90, profit#91, return_amt#92, net_loss#93, web_site_sk#110, web_site_id#111] + +(62) HashAggregate [codegen id : 11] +Input [5]: [sales_price#90, profit#91, return_amt#92, net_loss#93, web_site_id#111] +Keys [1]: [web_site_id#111] +Functions [4]: [partial_sum(UnscaledValue(sales_price#90)), partial_sum(UnscaledValue(return_amt#92)), partial_sum(UnscaledValue(profit#91)), partial_sum(UnscaledValue(net_loss#93))] +Aggregate Attributes [4]: [sum#112, sum#113, sum#114, sum#115] +Results [5]: [web_site_id#111, sum#116, sum#117, sum#118, sum#119] + +(63) Exchange +Input [5]: [web_site_id#111, sum#116, sum#117, sum#118, sum#119] +Arguments: hashpartitioning(web_site_id#111, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(64) HashAggregate [codegen id : 12] +Input [5]: [web_site_id#111, sum#116, sum#117, sum#118, sum#119] +Keys [1]: [web_site_id#111] +Functions [4]: [sum(UnscaledValue(sales_price#90)), sum(UnscaledValue(return_amt#92)), sum(UnscaledValue(profit#91)), sum(UnscaledValue(net_loss#93))] +Aggregate Attributes [4]: [sum(UnscaledValue(sales_price#90))#120, sum(UnscaledValue(return_amt#92))#121, sum(UnscaledValue(profit#91))#122, sum(UnscaledValue(net_loss#93))#123] +Results [5]: [web channel AS channel#124, concat(web_site, web_site_id#111) AS id#125, MakeDecimal(sum(UnscaledValue(sales_price#90))#120,17,2) AS sales#126, MakeDecimal(sum(UnscaledValue(return_amt#92))#121,17,2) AS returns#127, (MakeDecimal(sum(UnscaledValue(profit#91))#122,17,2) - MakeDecimal(sum(UnscaledValue(net_loss#93))#123,17,2)) AS profit#128] + +(65) Union + +(66) HashAggregate [codegen id : 13] +Input [5]: [channel#37, id#38, sales#39, returns#40, profit#41] +Keys [2]: [channel#37, id#38] +Functions [3]: [partial_sum(sales#39), partial_sum(returns#40), partial_sum(profit#41)] +Aggregate Attributes [6]: [sum#129, isEmpty#130, sum#131, isEmpty#132, sum#133, isEmpty#134] +Results [8]: [channel#37, id#38, sum#135, isEmpty#136, sum#137, isEmpty#138, sum#139, isEmpty#140] + +(67) Exchange +Input [8]: [channel#37, id#38, sum#135, isEmpty#136, sum#137, isEmpty#138, sum#139, isEmpty#140] +Arguments: hashpartitioning(channel#37, id#38, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(68) HashAggregate [codegen id : 14] +Input [8]: [channel#37, id#38, sum#135, isEmpty#136, sum#137, isEmpty#138, sum#139, isEmpty#140] +Keys [2]: [channel#37, id#38] +Functions [3]: [sum(sales#39), sum(returns#40), sum(profit#41)] +Aggregate Attributes [3]: [sum(sales#39)#141, sum(returns#40)#142, sum(profit#41)#143] +Results [5]: [channel#37, id#38, cast(sum(sales#39)#141 as decimal(37,2)) AS sales#144, cast(sum(returns#40)#142 as decimal(37,2)) AS returns#145, cast(sum(profit#41)#143 as decimal(38,2)) AS profit#146] + +(69) ReusedExchange [Reuses operator id: 67] +Output [8]: [channel#147, id#148, sum#149, isEmpty#150, sum#151, isEmpty#152, sum#153, isEmpty#154] + +(70) HashAggregate [codegen id : 28] +Input [8]: [channel#147, id#148, sum#149, isEmpty#150, sum#151, isEmpty#152, sum#153, isEmpty#154] +Keys [2]: [channel#147, id#148] +Functions [3]: [sum(sales#155), sum(returns#156), sum(profit#157)] +Aggregate Attributes [3]: [sum(sales#155)#141, sum(returns#156)#142, sum(profit#157)#143] +Results [4]: [channel#147, sum(sales#155)#141 AS sales#158, sum(returns#156)#142 AS returns#159, sum(profit#157)#143 AS profit#160] + +(71) HashAggregate [codegen id : 28] +Input [4]: [channel#147, sales#158, returns#159, profit#160] +Keys [1]: [channel#147] +Functions [3]: [partial_sum(sales#158), partial_sum(returns#159), partial_sum(profit#160)] +Aggregate Attributes [6]: [sum#161, isEmpty#162, sum#163, isEmpty#164, sum#165, isEmpty#166] +Results [7]: [channel#147, sum#167, isEmpty#168, sum#169, isEmpty#170, sum#171, isEmpty#172] + +(72) Exchange +Input [7]: [channel#147, sum#167, isEmpty#168, sum#169, isEmpty#170, sum#171, isEmpty#172] +Arguments: hashpartitioning(channel#147, 5), ENSURE_REQUIREMENTS, [plan_id=8] + +(73) HashAggregate [codegen id : 29] +Input [7]: [channel#147, sum#167, isEmpty#168, sum#169, isEmpty#170, sum#171, isEmpty#172] +Keys [1]: [channel#147] +Functions [3]: [sum(sales#158), sum(returns#159), sum(profit#160)] +Aggregate Attributes [3]: [sum(sales#158)#173, sum(returns#159)#174, sum(profit#160)#175] +Results [5]: [channel#147, null AS id#176, sum(sales#158)#173 AS sum(sales)#177, sum(returns#159)#174 AS sum(returns)#178, sum(profit#160)#175 AS sum(profit)#179] + +(74) ReusedExchange [Reuses operator id: 67] +Output [8]: [channel#180, id#181, sum#182, isEmpty#183, sum#184, isEmpty#185, sum#186, isEmpty#187] + +(75) HashAggregate [codegen id : 43] +Input [8]: [channel#180, id#181, sum#182, isEmpty#183, sum#184, isEmpty#185, sum#186, isEmpty#187] +Keys [2]: [channel#180, id#181] +Functions [3]: [sum(sales#188), sum(returns#189), sum(profit#190)] +Aggregate Attributes [3]: [sum(sales#188)#141, sum(returns#189)#142, sum(profit#190)#143] +Results [3]: [sum(sales#188)#141 AS sales#191, sum(returns#189)#142 AS returns#192, sum(profit#190)#143 AS profit#193] + +(76) HashAggregate [codegen id : 43] +Input [3]: [sales#191, returns#192, profit#193] +Keys: [] +Functions [3]: [partial_sum(sales#191), partial_sum(returns#192), partial_sum(profit#193)] +Aggregate Attributes [6]: [sum#194, isEmpty#195, sum#196, isEmpty#197, sum#198, isEmpty#199] +Results [6]: [sum#200, isEmpty#201, sum#202, isEmpty#203, sum#204, isEmpty#205] + +(77) Exchange +Input [6]: [sum#200, isEmpty#201, sum#202, isEmpty#203, sum#204, isEmpty#205] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=9] + +(78) HashAggregate [codegen id : 44] +Input [6]: [sum#200, isEmpty#201, sum#202, isEmpty#203, sum#204, isEmpty#205] +Keys: [] +Functions [3]: [sum(sales#191), sum(returns#192), sum(profit#193)] +Aggregate Attributes [3]: [sum(sales#191)#206, sum(returns#192)#207, sum(profit#193)#208] +Results [5]: [null AS channel#209, null AS id#210, sum(sales#191)#206 AS sum(sales)#211, sum(returns#192)#207 AS sum(returns)#212, sum(profit#193)#208 AS sum(profit)#213] + +(79) Union + +(80) HashAggregate [codegen id : 45] +Input [5]: [channel#37, id#38, sales#144, returns#145, profit#146] +Keys [5]: [channel#37, id#38, sales#144, returns#145, profit#146] +Functions: [] +Aggregate Attributes: [] +Results [5]: [channel#37, id#38, sales#144, returns#145, profit#146] + +(81) Exchange +Input [5]: [channel#37, id#38, sales#144, returns#145, profit#146] +Arguments: hashpartitioning(channel#37, id#38, sales#144, returns#145, profit#146, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(82) HashAggregate [codegen id : 46] +Input [5]: [channel#37, id#38, sales#144, returns#145, profit#146] +Keys [5]: [channel#37, id#38, sales#144, returns#145, profit#146] +Functions: [] +Aggregate Attributes: [] +Results [5]: [channel#37, id#38, sales#144, returns#145, profit#146] + +(83) TakeOrderedAndProject +Input [5]: [channel#37, id#38, sales#144, returns#145, profit#146] +Arguments: 100, [channel#37 ASC NULLS FIRST, id#38 ASC NULLS FIRST], [channel#37, id#38, sales#144, returns#145, profit#146] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (88) ++- * ColumnarToRow (87) + +- CometProject (86) + +- CometFilter (85) + +- CometScan parquet spark_catalog.default.date_dim (84) + + +(84) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#22, d_date#214] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,1998-08-04), LessThanOrEqual(d_date,1998-08-18), IsNotNull(d_date_sk)] +ReadSchema: struct + +(85) CometFilter +Input [2]: [d_date_sk#22, d_date#214] +Condition : (((isnotnull(d_date#214) AND (d_date#214 >= 1998-08-04)) AND (d_date#214 <= 1998-08-18)) AND isnotnull(d_date_sk#22)) + +(86) CometProject +Input [2]: [d_date_sk#22, d_date#214] +Arguments: [d_date_sk#22], [d_date_sk#22] + +(87) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#22] + +(88) BroadcastExchange +Input [1]: [d_date_sk#22] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=11] + +Subquery:2 Hosting operator id = 4 Hosting Expression = sr_returned_date_sk#15 IN dynamicpruning#5 + +Subquery:3 Hosting operator id = 21 Hosting Expression = cs_sold_date_sk#45 IN dynamicpruning#5 + +Subquery:4 Hosting operator id = 24 Hosting Expression = cr_returned_date_sk#56 IN dynamicpruning#5 + +Subquery:5 Hosting operator id = 41 Hosting Expression = ws_sold_date_sk#86 IN dynamicpruning#5 + +Subquery:6 Hosting operator id = 44 Hosting Expression = wr_returned_date_sk#98 IN dynamicpruning#5 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q5a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q5a/simplified.txt new file mode 100644 index 0000000000..aaec304fd0 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q5a/simplified.txt @@ -0,0 +1,136 @@ +TakeOrderedAndProject [channel,id,sales,returns,profit] + WholeStageCodegen (46) + HashAggregate [channel,id,sales,returns,profit] + InputAdapter + Exchange [channel,id,sales,returns,profit] #1 + WholeStageCodegen (45) + HashAggregate [channel,id,sales,returns,profit] + InputAdapter + Union + WholeStageCodegen (14) + HashAggregate [channel,id,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [channel,id] #2 + WholeStageCodegen (13) + HashAggregate [channel,id,sales,returns,profit] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Union + WholeStageCodegen (4) + HashAggregate [s_store_id,sum,sum,sum,sum] [sum(UnscaledValue(sales_price)),sum(UnscaledValue(return_amt)),sum(UnscaledValue(profit)),sum(UnscaledValue(net_loss)),channel,id,sales,returns,profit,sum,sum,sum,sum] + InputAdapter + Exchange [s_store_id] #3 + WholeStageCodegen (3) + HashAggregate [s_store_id,sales_price,return_amt,profit,net_loss] [sum,sum,sum,sum,sum,sum,sum,sum] + Project [sales_price,profit,return_amt,net_loss,s_store_id] + BroadcastHashJoin [store_sk,s_store_sk] + Project [store_sk,sales_price,profit,return_amt,net_loss] + BroadcastHashJoin [date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometUnion + CometProject [ss_store_sk,ss_sold_date_sk,ss_ext_sales_price,ss_net_profit] [store_sk,date_sk,sales_price,profit,return_amt,net_loss] + CometFilter [ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_store_sk,ss_ext_sales_price,ss_net_profit,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + CometProject [sr_store_sk,sr_returned_date_sk,sr_return_amt,sr_net_loss] [store_sk,date_sk,sales_price,profit,return_amt,net_loss] + CometFilter [sr_store_sk] + CometScan parquet spark_catalog.default.store_returns [sr_store_sk,sr_return_amt,sr_net_loss,sr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_id] + WholeStageCodegen (8) + HashAggregate [cp_catalog_page_id,sum,sum,sum,sum] [sum(UnscaledValue(sales_price)),sum(UnscaledValue(return_amt)),sum(UnscaledValue(profit)),sum(UnscaledValue(net_loss)),channel,id,sales,returns,profit,sum,sum,sum,sum] + InputAdapter + Exchange [cp_catalog_page_id] #6 + WholeStageCodegen (7) + HashAggregate [cp_catalog_page_id,sales_price,return_amt,profit,net_loss] [sum,sum,sum,sum,sum,sum,sum,sum] + Project [sales_price,profit,return_amt,net_loss,cp_catalog_page_id] + BroadcastHashJoin [page_sk,cp_catalog_page_sk] + Project [page_sk,sales_price,profit,return_amt,net_loss] + BroadcastHashJoin [date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometUnion + CometProject [cs_catalog_page_sk,cs_sold_date_sk,cs_ext_sales_price,cs_net_profit] [page_sk,date_sk,sales_price,profit,return_amt,net_loss] + CometFilter [cs_catalog_page_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_catalog_page_sk,cs_ext_sales_price,cs_net_profit,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + CometProject [cr_catalog_page_sk,cr_returned_date_sk,cr_return_amount,cr_net_loss] [page_sk,date_sk,sales_price,profit,return_amt,net_loss] + CometFilter [cr_catalog_page_sk] + CometScan parquet spark_catalog.default.catalog_returns [cr_catalog_page_sk,cr_return_amount,cr_net_loss,cr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (6) + ColumnarToRow + InputAdapter + CometFilter [cp_catalog_page_sk] + CometScan parquet spark_catalog.default.catalog_page [cp_catalog_page_sk,cp_catalog_page_id] + WholeStageCodegen (12) + HashAggregate [web_site_id,sum,sum,sum,sum] [sum(UnscaledValue(sales_price)),sum(UnscaledValue(return_amt)),sum(UnscaledValue(profit)),sum(UnscaledValue(net_loss)),channel,id,sales,returns,profit,sum,sum,sum,sum] + InputAdapter + Exchange [web_site_id] #8 + WholeStageCodegen (11) + HashAggregate [web_site_id,sales_price,return_amt,profit,net_loss] [sum,sum,sum,sum,sum,sum,sum,sum] + Project [sales_price,profit,return_amt,net_loss,web_site_id] + BroadcastHashJoin [wsr_web_site_sk,web_site_sk] + Project [wsr_web_site_sk,sales_price,profit,return_amt,net_loss] + BroadcastHashJoin [date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometUnion + CometProject [ws_web_site_sk,ws_sold_date_sk,ws_ext_sales_price,ws_net_profit] [wsr_web_site_sk,date_sk,sales_price,profit,return_amt,net_loss] + CometFilter [ws_web_site_sk] + CometScan parquet spark_catalog.default.web_sales [ws_web_site_sk,ws_ext_sales_price,ws_net_profit,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + CometProject [ws_web_site_sk,wr_returned_date_sk,wr_return_amt,wr_net_loss] [wsr_web_site_sk,date_sk,sales_price,profit,return_amt,net_loss] + CometBroadcastHashJoin [wr_item_sk,wr_order_number,ws_item_sk,ws_order_number] + CometBroadcastExchange #9 + CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_order_number,wr_return_amt,wr_net_loss,wr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + CometProject [ws_item_sk,ws_web_site_sk,ws_order_number] + CometFilter [ws_item_sk,ws_order_number,ws_web_site_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_web_site_sk,ws_order_number,ws_sold_date_sk] + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #10 + WholeStageCodegen (10) + ColumnarToRow + InputAdapter + CometFilter [web_site_sk] + CometScan parquet spark_catalog.default.web_site [web_site_sk,web_site_id] + WholeStageCodegen (29) + HashAggregate [channel,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),id,sum(sales),sum(returns),sum(profit),sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [channel] #11 + WholeStageCodegen (28) + HashAggregate [channel,sales,returns,profit] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + HashAggregate [channel,id,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + ReusedExchange [channel,id,sum,isEmpty,sum,isEmpty,sum,isEmpty] #2 + WholeStageCodegen (44) + HashAggregate [sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),channel,id,sum(sales),sum(returns),sum(profit),sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange #12 + WholeStageCodegen (43) + HashAggregate [sales,returns,profit] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + HashAggregate [channel,id,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + ReusedExchange [channel,id,sum,isEmpty,sum,isEmpty,sum,isEmpty] #2 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q6/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q6/explain.txt new file mode 100644 index 0000000000..a71a3a875b --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q6/explain.txt @@ -0,0 +1,309 @@ +== Physical Plan == +TakeOrderedAndProject (39) ++- * Filter (38) + +- * HashAggregate (37) + +- Exchange (36) + +- * HashAggregate (35) + +- * Project (34) + +- * BroadcastHashJoin Inner BuildRight (33) + :- * Project (18) + : +- * BroadcastHashJoin Inner BuildRight (17) + : :- * Project (15) + : : +- * BroadcastHashJoin Inner BuildRight (14) + : : :- * Project (9) + : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.customer_address (1) + : : : +- BroadcastExchange (7) + : : : +- * ColumnarToRow (6) + : : : +- CometFilter (5) + : : : +- CometScan parquet spark_catalog.default.customer (4) + : : +- BroadcastExchange (13) + : : +- * ColumnarToRow (12) + : : +- CometFilter (11) + : : +- CometScan parquet spark_catalog.default.store_sales (10) + : +- ReusedExchange (16) + +- BroadcastExchange (32) + +- * Project (31) + +- * BroadcastHashJoin Inner BuildRight (30) + :- * ColumnarToRow (21) + : +- CometFilter (20) + : +- CometScan parquet spark_catalog.default.item (19) + +- BroadcastExchange (29) + +- * Filter (28) + +- * HashAggregate (27) + +- Exchange (26) + +- * HashAggregate (25) + +- * ColumnarToRow (24) + +- CometFilter (23) + +- CometScan parquet spark_catalog.default.item (22) + + +(1) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#1, ca_state#2] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk)] +ReadSchema: struct + +(2) CometFilter +Input [2]: [ca_address_sk#1, ca_state#2] +Condition : isnotnull(ca_address_sk#1) + +(3) ColumnarToRow [codegen id : 7] +Input [2]: [ca_address_sk#1, ca_state#2] + +(4) Scan parquet spark_catalog.default.customer +Output [2]: [c_customer_sk#3, c_current_addr_sk#4] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_current_addr_sk), IsNotNull(c_customer_sk)] +ReadSchema: struct + +(5) CometFilter +Input [2]: [c_customer_sk#3, c_current_addr_sk#4] +Condition : (isnotnull(c_current_addr_sk#4) AND isnotnull(c_customer_sk#3)) + +(6) ColumnarToRow [codegen id : 1] +Input [2]: [c_customer_sk#3, c_current_addr_sk#4] + +(7) BroadcastExchange +Input [2]: [c_customer_sk#3, c_current_addr_sk#4] +Arguments: HashedRelationBroadcastMode(List(cast(input[1, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [ca_address_sk#1] +Right keys [1]: [c_current_addr_sk#4] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 7] +Output [2]: [ca_state#2, c_customer_sk#3] +Input [4]: [ca_address_sk#1, ca_state#2, c_customer_sk#3, c_current_addr_sk#4] + +(10) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_item_sk#5, ss_customer_sk#6, ss_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sold_date_sk#7 IN dynamicpruning#8)] +PushedFilters: [IsNotNull(ss_customer_sk), IsNotNull(ss_item_sk)] +ReadSchema: struct + +(11) CometFilter +Input [3]: [ss_item_sk#5, ss_customer_sk#6, ss_sold_date_sk#7] +Condition : (isnotnull(ss_customer_sk#6) AND isnotnull(ss_item_sk#5)) + +(12) ColumnarToRow [codegen id : 2] +Input [3]: [ss_item_sk#5, ss_customer_sk#6, ss_sold_date_sk#7] + +(13) BroadcastExchange +Input [3]: [ss_item_sk#5, ss_customer_sk#6, ss_sold_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[1, int, false] as bigint)),false), [plan_id=2] + +(14) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [c_customer_sk#3] +Right keys [1]: [ss_customer_sk#6] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 7] +Output [3]: [ca_state#2, ss_item_sk#5, ss_sold_date_sk#7] +Input [5]: [ca_state#2, c_customer_sk#3, ss_item_sk#5, ss_customer_sk#6, ss_sold_date_sk#7] + +(16) ReusedExchange [Reuses operator id: 44] +Output [1]: [d_date_sk#9] + +(17) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [ss_sold_date_sk#7] +Right keys [1]: [d_date_sk#9] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 7] +Output [2]: [ca_state#2, ss_item_sk#5] +Input [4]: [ca_state#2, ss_item_sk#5, ss_sold_date_sk#7, d_date_sk#9] + +(19) Scan parquet spark_catalog.default.item +Output [3]: [i_item_sk#10, i_current_price#11, i_category#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_current_price), IsNotNull(i_category), IsNotNull(i_item_sk)] +ReadSchema: struct + +(20) CometFilter +Input [3]: [i_item_sk#10, i_current_price#11, i_category#12] +Condition : ((isnotnull(i_current_price#11) AND isnotnull(i_category#12)) AND isnotnull(i_item_sk#10)) + +(21) ColumnarToRow [codegen id : 6] +Input [3]: [i_item_sk#10, i_current_price#11, i_category#12] + +(22) Scan parquet spark_catalog.default.item +Output [2]: [i_current_price#13, i_category#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_category)] +ReadSchema: struct + +(23) CometFilter +Input [2]: [i_current_price#13, i_category#14] +Condition : isnotnull(i_category#14) + +(24) ColumnarToRow [codegen id : 4] +Input [2]: [i_current_price#13, i_category#14] + +(25) HashAggregate [codegen id : 4] +Input [2]: [i_current_price#13, i_category#14] +Keys [1]: [i_category#14] +Functions [1]: [partial_avg(UnscaledValue(i_current_price#13))] +Aggregate Attributes [2]: [sum#15, count#16] +Results [3]: [i_category#14, sum#17, count#18] + +(26) Exchange +Input [3]: [i_category#14, sum#17, count#18] +Arguments: hashpartitioning(i_category#14, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(27) HashAggregate [codegen id : 5] +Input [3]: [i_category#14, sum#17, count#18] +Keys [1]: [i_category#14] +Functions [1]: [avg(UnscaledValue(i_current_price#13))] +Aggregate Attributes [1]: [avg(UnscaledValue(i_current_price#13))#19] +Results [2]: [cast((avg(UnscaledValue(i_current_price#13))#19 / 100.0) as decimal(11,6)) AS avg(i_current_price)#20, i_category#14] + +(28) Filter [codegen id : 5] +Input [2]: [avg(i_current_price)#20, i_category#14] +Condition : isnotnull(avg(i_current_price)#20) + +(29) BroadcastExchange +Input [2]: [avg(i_current_price)#20, i_category#14] +Arguments: HashedRelationBroadcastMode(List(input[1, string, true]),false), [plan_id=4] + +(30) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [i_category#12] +Right keys [1]: [i_category#14] +Join type: Inner +Join condition: (cast(i_current_price#11 as decimal(14,7)) > (1.2 * avg(i_current_price)#20)) + +(31) Project [codegen id : 6] +Output [1]: [i_item_sk#10] +Input [5]: [i_item_sk#10, i_current_price#11, i_category#12, avg(i_current_price)#20, i_category#14] + +(32) BroadcastExchange +Input [1]: [i_item_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +(33) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [ss_item_sk#5] +Right keys [1]: [i_item_sk#10] +Join type: Inner +Join condition: None + +(34) Project [codegen id : 7] +Output [1]: [ca_state#2] +Input [3]: [ca_state#2, ss_item_sk#5, i_item_sk#10] + +(35) HashAggregate [codegen id : 7] +Input [1]: [ca_state#2] +Keys [1]: [ca_state#2] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#21] +Results [2]: [ca_state#2, count#22] + +(36) Exchange +Input [2]: [ca_state#2, count#22] +Arguments: hashpartitioning(ca_state#2, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(37) HashAggregate [codegen id : 8] +Input [2]: [ca_state#2, count#22] +Keys [1]: [ca_state#2] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#23] +Results [2]: [ca_state#2 AS state#24, count(1)#23 AS cnt#25] + +(38) Filter [codegen id : 8] +Input [2]: [state#24, cnt#25] +Condition : (cnt#25 >= 10) + +(39) TakeOrderedAndProject +Input [2]: [state#24, cnt#25] +Arguments: 100, [cnt#25 ASC NULLS FIRST, state#24 ASC NULLS FIRST], [state#24, cnt#25] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 10 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (44) ++- * ColumnarToRow (43) + +- CometProject (42) + +- CometFilter (41) + +- CometScan parquet spark_catalog.default.date_dim (40) + + +(40) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#9, d_month_seq#26] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), EqualTo(d_month_seq,ScalarSubquery#27), IsNotNull(d_date_sk)] +ReadSchema: struct + +(41) CometFilter +Input [2]: [d_date_sk#9, d_month_seq#26] +Condition : ((isnotnull(d_month_seq#26) AND (d_month_seq#26 = ReusedSubquery Subquery scalar-subquery#27, [id=#28])) AND isnotnull(d_date_sk#9)) + +(42) CometProject +Input [2]: [d_date_sk#9, d_month_seq#26] +Arguments: [d_date_sk#9], [d_date_sk#9] + +(43) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#9] + +(44) BroadcastExchange +Input [1]: [d_date_sk#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +Subquery:2 Hosting operator id = 41 Hosting Expression = ReusedSubquery Subquery scalar-subquery#27, [id=#28] + +Subquery:3 Hosting operator id = 40 Hosting Expression = Subquery scalar-subquery#27, [id=#28] +* HashAggregate (51) ++- Exchange (50) + +- * ColumnarToRow (49) + +- CometHashAggregate (48) + +- CometProject (47) + +- CometFilter (46) + +- CometScan parquet spark_catalog.default.date_dim (45) + + +(45) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_month_seq#29, d_year#30, d_moy#31] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2000), EqualTo(d_moy,1)] +ReadSchema: struct + +(46) CometFilter +Input [3]: [d_month_seq#29, d_year#30, d_moy#31] +Condition : (((isnotnull(d_year#30) AND isnotnull(d_moy#31)) AND (d_year#30 = 2000)) AND (d_moy#31 = 1)) + +(47) CometProject +Input [3]: [d_month_seq#29, d_year#30, d_moy#31] +Arguments: [d_month_seq#29], [d_month_seq#29] + +(48) CometHashAggregate +Input [1]: [d_month_seq#29] +Keys [1]: [d_month_seq#29] +Functions: [] + +(49) ColumnarToRow [codegen id : 1] +Input [1]: [d_month_seq#29] + +(50) Exchange +Input [1]: [d_month_seq#29] +Arguments: hashpartitioning(d_month_seq#29, 5), ENSURE_REQUIREMENTS, [plan_id=8] + +(51) HashAggregate [codegen id : 2] +Input [1]: [d_month_seq#29] +Keys [1]: [d_month_seq#29] +Functions: [] +Aggregate Attributes: [] +Results [1]: [d_month_seq#29] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q6/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q6/simplified.txt new file mode 100644 index 0000000000..c2d5a6ce83 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q6/simplified.txt @@ -0,0 +1,79 @@ +TakeOrderedAndProject [cnt,state] + WholeStageCodegen (8) + Filter [cnt] + HashAggregate [ca_state,count] [count(1),state,cnt,count] + InputAdapter + Exchange [ca_state] #1 + WholeStageCodegen (7) + HashAggregate [ca_state] [count,count] + Project [ca_state] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ca_state,ss_item_sk] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ca_state,ss_item_sk,ss_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + Project [ca_state,c_customer_sk] + BroadcastHashJoin [ca_address_sk,c_current_addr_sk] + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [c_current_addr_sk,c_customer_sk] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_addr_sk] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk,ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_month_seq,d_date_sk] + ReusedSubquery [d_month_seq] #2 + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] + Subquery #2 + WholeStageCodegen (2) + HashAggregate [d_month_seq] + InputAdapter + Exchange [d_month_seq] #5 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometHashAggregate [d_month_seq] + CometProject [d_month_seq] + CometFilter [d_year,d_moy] + CometScan parquet spark_catalog.default.date_dim [d_month_seq,d_year,d_moy] + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (6) + Project [i_item_sk] + BroadcastHashJoin [i_category,i_category,i_current_price,avg(i_current_price)] + ColumnarToRow + InputAdapter + CometFilter [i_current_price,i_category,i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price,i_category] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (5) + Filter [avg(i_current_price)] + HashAggregate [i_category,sum,count] [avg(UnscaledValue(i_current_price)),avg(i_current_price),sum,count] + InputAdapter + Exchange [i_category] #8 + WholeStageCodegen (4) + HashAggregate [i_category,i_current_price] [sum,count,sum,count] + ColumnarToRow + InputAdapter + CometFilter [i_category] + CometScan parquet spark_catalog.default.item [i_current_price,i_category] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q64/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q64/explain.txt new file mode 100644 index 0000000000..e50a522b80 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q64/explain.txt @@ -0,0 +1,1064 @@ +== Physical Plan == +* Sort (181) ++- Exchange (180) + +- * Project (179) + +- * SortMergeJoin Inner (178) + :- * Sort (110) + : +- Exchange (109) + : +- * HashAggregate (108) + : +- * HashAggregate (107) + : +- * Project (106) + : +- * BroadcastHashJoin Inner BuildRight (105) + : :- * Project (99) + : : +- * BroadcastHashJoin Inner BuildRight (98) + : : :- * Project (96) + : : : +- * BroadcastHashJoin Inner BuildRight (95) + : : : :- * Project (90) + : : : : +- * BroadcastHashJoin Inner BuildRight (89) + : : : : :- * Project (87) + : : : : : +- * BroadcastHashJoin Inner BuildRight (86) + : : : : : :- * Project (81) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (80) + : : : : : : :- * Project (78) + : : : : : : : +- * BroadcastHashJoin Inner BuildRight (77) + : : : : : : : :- * Project (72) + : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (71) + : : : : : : : : :- * Project (66) + : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (65) + : : : : : : : : : :- * Project (63) + : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (62) + : : : : : : : : : : :- * Project (57) + : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (56) + : : : : : : : : : : : :- * Project (54) + : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (53) + : : : : : : : : : : : : :- * Project (48) + : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (47) + : : : : : : : : : : : : : :- * Project (42) + : : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (41) + : : : : : : : : : : : : : : :- * Project (36) + : : : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (35) + : : : : : : : : : : : : : : : :- * Project (33) + : : : : : : : : : : : : : : : : +- * SortMergeJoin Inner (32) + : : : : : : : : : : : : : : : : :- * Sort (11) + : : : : : : : : : : : : : : : : : +- Exchange (10) + : : : : : : : : : : : : : : : : : +- * ColumnarToRow (9) + : : : : : : : : : : : : : : : : : +- CometProject (8) + : : : : : : : : : : : : : : : : : +- CometBroadcastHashJoin (7) + : : : : : : : : : : : : : : : : : :- CometBroadcastExchange (3) + : : : : : : : : : : : : : : : : : : +- CometFilter (2) + : : : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : : : : : : : : : : : : : : +- CometProject (6) + : : : : : : : : : : : : : : : : : +- CometFilter (5) + : : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store_returns (4) + : : : : : : : : : : : : : : : : +- * Sort (31) + : : : : : : : : : : : : : : : : +- * Project (30) + : : : : : : : : : : : : : : : : +- * Filter (29) + : : : : : : : : : : : : : : : : +- * HashAggregate (28) + : : : : : : : : : : : : : : : : +- Exchange (27) + : : : : : : : : : : : : : : : : +- * HashAggregate (26) + : : : : : : : : : : : : : : : : +- * Project (25) + : : : : : : : : : : : : : : : : +- * SortMergeJoin Inner (24) + : : : : : : : : : : : : : : : : :- * Sort (17) + : : : : : : : : : : : : : : : : : +- Exchange (16) + : : : : : : : : : : : : : : : : : +- * ColumnarToRow (15) + : : : : : : : : : : : : : : : : : +- CometProject (14) + : : : : : : : : : : : : : : : : : +- CometFilter (13) + : : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (12) + : : : : : : : : : : : : : : : : +- * Sort (23) + : : : : : : : : : : : : : : : : +- Exchange (22) + : : : : : : : : : : : : : : : : +- * ColumnarToRow (21) + : : : : : : : : : : : : : : : : +- CometProject (20) + : : : : : : : : : : : : : : : : +- CometFilter (19) + : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.catalog_returns (18) + : : : : : : : : : : : : : : : +- ReusedExchange (34) + : : : : : : : : : : : : : : +- BroadcastExchange (40) + : : : : : : : : : : : : : : +- * ColumnarToRow (39) + : : : : : : : : : : : : : : +- CometFilter (38) + : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store (37) + : : : : : : : : : : : : : +- BroadcastExchange (46) + : : : : : : : : : : : : : +- * ColumnarToRow (45) + : : : : : : : : : : : : : +- CometFilter (44) + : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.customer (43) + : : : : : : : : : : : : +- BroadcastExchange (52) + : : : : : : : : : : : : +- * ColumnarToRow (51) + : : : : : : : : : : : : +- CometFilter (50) + : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.date_dim (49) + : : : : : : : : : : : +- ReusedExchange (55) + : : : : : : : : : : +- BroadcastExchange (61) + : : : : : : : : : : +- * ColumnarToRow (60) + : : : : : : : : : : +- CometFilter (59) + : : : : : : : : : : +- CometScan parquet spark_catalog.default.customer_demographics (58) + : : : : : : : : : +- ReusedExchange (64) + : : : : : : : : +- BroadcastExchange (70) + : : : : : : : : +- * ColumnarToRow (69) + : : : : : : : : +- CometFilter (68) + : : : : : : : : +- CometScan parquet spark_catalog.default.promotion (67) + : : : : : : : +- BroadcastExchange (76) + : : : : : : : +- * ColumnarToRow (75) + : : : : : : : +- CometFilter (74) + : : : : : : : +- CometScan parquet spark_catalog.default.household_demographics (73) + : : : : : : +- ReusedExchange (79) + : : : : : +- BroadcastExchange (85) + : : : : : +- * ColumnarToRow (84) + : : : : : +- CometFilter (83) + : : : : : +- CometScan parquet spark_catalog.default.customer_address (82) + : : : : +- ReusedExchange (88) + : : : +- BroadcastExchange (94) + : : : +- * ColumnarToRow (93) + : : : +- CometFilter (92) + : : : +- CometScan parquet spark_catalog.default.income_band (91) + : : +- ReusedExchange (97) + : +- BroadcastExchange (104) + : +- * ColumnarToRow (103) + : +- CometProject (102) + : +- CometFilter (101) + : +- CometScan parquet spark_catalog.default.item (100) + +- * Sort (177) + +- Exchange (176) + +- * HashAggregate (175) + +- * HashAggregate (174) + +- * Project (173) + +- * BroadcastHashJoin Inner BuildRight (172) + :- * Project (170) + : +- * BroadcastHashJoin Inner BuildRight (169) + : :- * Project (167) + : : +- * BroadcastHashJoin Inner BuildRight (166) + : : :- * Project (164) + : : : +- * BroadcastHashJoin Inner BuildRight (163) + : : : :- * Project (161) + : : : : +- * BroadcastHashJoin Inner BuildRight (160) + : : : : :- * Project (158) + : : : : : +- * BroadcastHashJoin Inner BuildRight (157) + : : : : : :- * Project (155) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (154) + : : : : : : :- * Project (152) + : : : : : : : +- * BroadcastHashJoin Inner BuildRight (151) + : : : : : : : :- * Project (149) + : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (148) + : : : : : : : : :- * Project (146) + : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (145) + : : : : : : : : : :- * Project (143) + : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (142) + : : : : : : : : : : :- * Project (140) + : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (139) + : : : : : : : : : : : :- * Project (137) + : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (136) + : : : : : : : : : : : : :- * Project (134) + : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (133) + : : : : : : : : : : : : : :- * Project (131) + : : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (130) + : : : : : : : : : : : : : : :- * Project (128) + : : : : : : : : : : : : : : : +- * SortMergeJoin Inner (127) + : : : : : : : : : : : : : : : :- * Sort (121) + : : : : : : : : : : : : : : : : +- Exchange (120) + : : : : : : : : : : : : : : : : +- * ColumnarToRow (119) + : : : : : : : : : : : : : : : : +- CometProject (118) + : : : : : : : : : : : : : : : : +- CometBroadcastHashJoin (117) + : : : : : : : : : : : : : : : : :- CometBroadcastExchange (113) + : : : : : : : : : : : : : : : : : +- CometFilter (112) + : : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (111) + : : : : : : : : : : : : : : : : +- CometProject (116) + : : : : : : : : : : : : : : : : +- CometFilter (115) + : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store_returns (114) + : : : : : : : : : : : : : : : +- * Sort (126) + : : : : : : : : : : : : : : : +- * Project (125) + : : : : : : : : : : : : : : : +- * Filter (124) + : : : : : : : : : : : : : : : +- * HashAggregate (123) + : : : : : : : : : : : : : : : +- ReusedExchange (122) + : : : : : : : : : : : : : : +- ReusedExchange (129) + : : : : : : : : : : : : : +- ReusedExchange (132) + : : : : : : : : : : : : +- ReusedExchange (135) + : : : : : : : : : : : +- ReusedExchange (138) + : : : : : : : : : : +- ReusedExchange (141) + : : : : : : : : : +- ReusedExchange (144) + : : : : : : : : +- ReusedExchange (147) + : : : : : : : +- ReusedExchange (150) + : : : : : : +- ReusedExchange (153) + : : : : : +- ReusedExchange (156) + : : : : +- ReusedExchange (159) + : : : +- ReusedExchange (162) + : : +- ReusedExchange (165) + : +- ReusedExchange (168) + +- ReusedExchange (171) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_ticket_number#8, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#12), dynamicpruningexpression(ss_sold_date_sk#12 IN dynamicpruning#13)] +PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_ticket_number), IsNotNull(ss_store_sk), IsNotNull(ss_customer_sk), IsNotNull(ss_cdemo_sk), IsNotNull(ss_promo_sk), IsNotNull(ss_hdemo_sk), IsNotNull(ss_addr_sk)] +ReadSchema: struct + +(2) CometFilter +Input [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_ticket_number#8, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] +Condition : (((((((isnotnull(ss_item_sk#1) AND isnotnull(ss_ticket_number#8)) AND isnotnull(ss_store_sk#6)) AND isnotnull(ss_customer_sk#2)) AND isnotnull(ss_cdemo_sk#3)) AND isnotnull(ss_promo_sk#7)) AND isnotnull(ss_hdemo_sk#4)) AND isnotnull(ss_addr_sk#5)) + +(3) CometBroadcastExchange +Input [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_ticket_number#8, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] +Arguments: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_ticket_number#8, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] + +(4) Scan parquet spark_catalog.default.store_returns +Output [3]: [sr_item_sk#14, sr_ticket_number#15, sr_returned_date_sk#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_returns] +PushedFilters: [IsNotNull(sr_item_sk), IsNotNull(sr_ticket_number)] +ReadSchema: struct + +(5) CometFilter +Input [3]: [sr_item_sk#14, sr_ticket_number#15, sr_returned_date_sk#16] +Condition : (isnotnull(sr_item_sk#14) AND isnotnull(sr_ticket_number#15)) + +(6) CometProject +Input [3]: [sr_item_sk#14, sr_ticket_number#15, sr_returned_date_sk#16] +Arguments: [sr_item_sk#14, sr_ticket_number#15], [sr_item_sk#14, sr_ticket_number#15] + +(7) CometBroadcastHashJoin +Left output [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_ticket_number#8, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] +Right output [2]: [sr_item_sk#14, sr_ticket_number#15] +Arguments: [ss_item_sk#1, ss_ticket_number#8], [sr_item_sk#14, sr_ticket_number#15], Inner + +(8) CometProject +Input [14]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_ticket_number#8, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12, sr_item_sk#14, sr_ticket_number#15] +Arguments: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12], [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] + +(9) ColumnarToRow [codegen id : 1] +Input [11]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] + +(10) Exchange +Input [11]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] +Arguments: hashpartitioning(ss_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(11) Sort [codegen id : 2] +Input [11]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] +Arguments: [ss_item_sk#1 ASC NULLS FIRST], false, 0 + +(12) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19, cs_sold_date_sk#20] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_sales] +PushedFilters: [IsNotNull(cs_item_sk), IsNotNull(cs_order_number)] +ReadSchema: struct + +(13) CometFilter +Input [4]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19, cs_sold_date_sk#20] +Condition : (isnotnull(cs_item_sk#17) AND isnotnull(cs_order_number#18)) + +(14) CometProject +Input [4]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19, cs_sold_date_sk#20] +Arguments: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19], [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19] + +(15) ColumnarToRow [codegen id : 3] +Input [3]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19] + +(16) Exchange +Input [3]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19] +Arguments: hashpartitioning(cs_item_sk#17, cs_order_number#18, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(17) Sort [codegen id : 4] +Input [3]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19] +Arguments: [cs_item_sk#17 ASC NULLS FIRST, cs_order_number#18 ASC NULLS FIRST], false, 0 + +(18) Scan parquet spark_catalog.default.catalog_returns +Output [6]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25, cr_returned_date_sk#26] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_returns] +PushedFilters: [IsNotNull(cr_item_sk), IsNotNull(cr_order_number)] +ReadSchema: struct + +(19) CometFilter +Input [6]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25, cr_returned_date_sk#26] +Condition : (isnotnull(cr_item_sk#21) AND isnotnull(cr_order_number#22)) + +(20) CometProject +Input [6]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25, cr_returned_date_sk#26] +Arguments: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25], [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] + +(21) ColumnarToRow [codegen id : 5] +Input [5]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] + +(22) Exchange +Input [5]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] +Arguments: hashpartitioning(cr_item_sk#21, cr_order_number#22, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(23) Sort [codegen id : 6] +Input [5]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] +Arguments: [cr_item_sk#21 ASC NULLS FIRST, cr_order_number#22 ASC NULLS FIRST], false, 0 + +(24) SortMergeJoin [codegen id : 7] +Left keys [2]: [cs_item_sk#17, cs_order_number#18] +Right keys [2]: [cr_item_sk#21, cr_order_number#22] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 7] +Output [5]: [cs_item_sk#17, cs_ext_list_price#19, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] +Input [8]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19, cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] + +(26) HashAggregate [codegen id : 7] +Input [5]: [cs_item_sk#17, cs_ext_list_price#19, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] +Keys [1]: [cs_item_sk#17] +Functions [2]: [partial_sum(UnscaledValue(cs_ext_list_price#19)), partial_sum(((cr_refunded_cash#23 + cr_reversed_charge#24) + cr_store_credit#25))] +Aggregate Attributes [3]: [sum#27, sum#28, isEmpty#29] +Results [4]: [cs_item_sk#17, sum#30, sum#31, isEmpty#32] + +(27) Exchange +Input [4]: [cs_item_sk#17, sum#30, sum#31, isEmpty#32] +Arguments: hashpartitioning(cs_item_sk#17, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(28) HashAggregate [codegen id : 8] +Input [4]: [cs_item_sk#17, sum#30, sum#31, isEmpty#32] +Keys [1]: [cs_item_sk#17] +Functions [2]: [sum(UnscaledValue(cs_ext_list_price#19)), sum(((cr_refunded_cash#23 + cr_reversed_charge#24) + cr_store_credit#25))] +Aggregate Attributes [2]: [sum(UnscaledValue(cs_ext_list_price#19))#33, sum(((cr_refunded_cash#23 + cr_reversed_charge#24) + cr_store_credit#25))#34] +Results [3]: [cs_item_sk#17, MakeDecimal(sum(UnscaledValue(cs_ext_list_price#19))#33,17,2) AS sale#35, sum(((cr_refunded_cash#23 + cr_reversed_charge#24) + cr_store_credit#25))#34 AS refund#36] + +(29) Filter [codegen id : 8] +Input [3]: [cs_item_sk#17, sale#35, refund#36] +Condition : ((isnotnull(sale#35) AND isnotnull(refund#36)) AND (cast(sale#35 as decimal(21,2)) > (2 * refund#36))) + +(30) Project [codegen id : 8] +Output [1]: [cs_item_sk#17] +Input [3]: [cs_item_sk#17, sale#35, refund#36] + +(31) Sort [codegen id : 8] +Input [1]: [cs_item_sk#17] +Arguments: [cs_item_sk#17 ASC NULLS FIRST], false, 0 + +(32) SortMergeJoin [codegen id : 24] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [cs_item_sk#17] +Join type: Inner +Join condition: None + +(33) Project [codegen id : 24] +Output [11]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] +Input [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12, cs_item_sk#17] + +(34) ReusedExchange [Reuses operator id: 185] +Output [2]: [d_date_sk#37, d_year#38] + +(35) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [ss_sold_date_sk#12] +Right keys [1]: [d_date_sk#37] +Join type: Inner +Join condition: None + +(36) Project [codegen id : 24] +Output [11]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38] +Input [13]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12, d_date_sk#37, d_year#38] + +(37) Scan parquet spark_catalog.default.store +Output [3]: [s_store_sk#39, s_store_name#40, s_zip#41] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk), IsNotNull(s_store_name), IsNotNull(s_zip)] +ReadSchema: struct + +(38) CometFilter +Input [3]: [s_store_sk#39, s_store_name#40, s_zip#41] +Condition : ((isnotnull(s_store_sk#39) AND isnotnull(s_store_name#40)) AND isnotnull(s_zip#41)) + +(39) ColumnarToRow [codegen id : 10] +Input [3]: [s_store_sk#39, s_store_name#40, s_zip#41] + +(40) BroadcastExchange +Input [3]: [s_store_sk#39, s_store_name#40, s_zip#41] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(41) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [ss_store_sk#6] +Right keys [1]: [s_store_sk#39] +Join type: Inner +Join condition: None + +(42) Project [codegen id : 24] +Output [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41] +Input [14]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_sk#39, s_store_name#40, s_zip#41] + +(43) Scan parquet spark_catalog.default.customer +Output [6]: [c_customer_sk#42, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_first_sales_date_sk), IsNotNull(c_first_shipto_date_sk), IsNotNull(c_current_cdemo_sk), IsNotNull(c_current_hdemo_sk), IsNotNull(c_current_addr_sk)] +ReadSchema: struct + +(44) CometFilter +Input [6]: [c_customer_sk#42, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] +Condition : (((((isnotnull(c_customer_sk#42) AND isnotnull(c_first_sales_date_sk#47)) AND isnotnull(c_first_shipto_date_sk#46)) AND isnotnull(c_current_cdemo_sk#43)) AND isnotnull(c_current_hdemo_sk#44)) AND isnotnull(c_current_addr_sk#45)) + +(45) ColumnarToRow [codegen id : 11] +Input [6]: [c_customer_sk#42, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] + +(46) BroadcastExchange +Input [6]: [c_customer_sk#42, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6] + +(47) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [ss_customer_sk#2] +Right keys [1]: [c_customer_sk#42] +Join type: Inner +Join condition: None + +(48) Project [codegen id : 24] +Output [16]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] +Input [18]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_customer_sk#42, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] + +(49) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#48, d_year#49] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date_sk)] +ReadSchema: struct + +(50) CometFilter +Input [2]: [d_date_sk#48, d_year#49] +Condition : isnotnull(d_date_sk#48) + +(51) ColumnarToRow [codegen id : 12] +Input [2]: [d_date_sk#48, d_year#49] + +(52) BroadcastExchange +Input [2]: [d_date_sk#48, d_year#49] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=7] + +(53) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [c_first_sales_date_sk#47] +Right keys [1]: [d_date_sk#48] +Join type: Inner +Join condition: None + +(54) Project [codegen id : 24] +Output [16]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, d_year#49] +Input [18]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47, d_date_sk#48, d_year#49] + +(55) ReusedExchange [Reuses operator id: 52] +Output [2]: [d_date_sk#50, d_year#51] + +(56) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [c_first_shipto_date_sk#46] +Right keys [1]: [d_date_sk#50] +Join type: Inner +Join condition: None + +(57) Project [codegen id : 24] +Output [16]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51] +Input [18]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, d_year#49, d_date_sk#50, d_year#51] + +(58) Scan parquet spark_catalog.default.customer_demographics +Output [2]: [cd_demo_sk#52, cd_marital_status#53] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_demo_sk), IsNotNull(cd_marital_status)] +ReadSchema: struct + +(59) CometFilter +Input [2]: [cd_demo_sk#52, cd_marital_status#53] +Condition : (isnotnull(cd_demo_sk#52) AND isnotnull(cd_marital_status#53)) + +(60) ColumnarToRow [codegen id : 14] +Input [2]: [cd_demo_sk#52, cd_marital_status#53] + +(61) BroadcastExchange +Input [2]: [cd_demo_sk#52, cd_marital_status#53] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8] + +(62) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [ss_cdemo_sk#3] +Right keys [1]: [cd_demo_sk#52] +Join type: Inner +Join condition: None + +(63) Project [codegen id : 24] +Output [16]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, cd_marital_status#53] +Input [18]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, cd_demo_sk#52, cd_marital_status#53] + +(64) ReusedExchange [Reuses operator id: 61] +Output [2]: [cd_demo_sk#54, cd_marital_status#55] + +(65) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [c_current_cdemo_sk#43] +Right keys [1]: [cd_demo_sk#54] +Join type: Inner +Join condition: NOT (cd_marital_status#53 = cd_marital_status#55) + +(66) Project [codegen id : 24] +Output [14]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51] +Input [18]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, cd_marital_status#53, cd_demo_sk#54, cd_marital_status#55] + +(67) Scan parquet spark_catalog.default.promotion +Output [1]: [p_promo_sk#56] +Batched: true +Location [not included in comparison]/{warehouse_dir}/promotion] +PushedFilters: [IsNotNull(p_promo_sk)] +ReadSchema: struct + +(68) CometFilter +Input [1]: [p_promo_sk#56] +Condition : isnotnull(p_promo_sk#56) + +(69) ColumnarToRow [codegen id : 16] +Input [1]: [p_promo_sk#56] + +(70) BroadcastExchange +Input [1]: [p_promo_sk#56] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=9] + +(71) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [ss_promo_sk#7] +Right keys [1]: [p_promo_sk#56] +Join type: Inner +Join condition: None + +(72) Project [codegen id : 24] +Output [13]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51] +Input [15]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, p_promo_sk#56] + +(73) Scan parquet spark_catalog.default.household_demographics +Output [2]: [hd_demo_sk#57, hd_income_band_sk#58] +Batched: true +Location [not included in comparison]/{warehouse_dir}/household_demographics] +PushedFilters: [IsNotNull(hd_demo_sk), IsNotNull(hd_income_band_sk)] +ReadSchema: struct + +(74) CometFilter +Input [2]: [hd_demo_sk#57, hd_income_band_sk#58] +Condition : (isnotnull(hd_demo_sk#57) AND isnotnull(hd_income_band_sk#58)) + +(75) ColumnarToRow [codegen id : 17] +Input [2]: [hd_demo_sk#57, hd_income_band_sk#58] + +(76) BroadcastExchange +Input [2]: [hd_demo_sk#57, hd_income_band_sk#58] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=10] + +(77) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [ss_hdemo_sk#4] +Right keys [1]: [hd_demo_sk#57] +Join type: Inner +Join condition: None + +(78) Project [codegen id : 24] +Output [13]: [ss_item_sk#1, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58] +Input [15]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, hd_demo_sk#57, hd_income_band_sk#58] + +(79) ReusedExchange [Reuses operator id: 76] +Output [2]: [hd_demo_sk#59, hd_income_band_sk#60] + +(80) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [c_current_hdemo_sk#44] +Right keys [1]: [hd_demo_sk#59] +Join type: Inner +Join condition: None + +(81) Project [codegen id : 24] +Output [13]: [ss_item_sk#1, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60] +Input [15]: [ss_item_sk#1, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58, hd_demo_sk#59, hd_income_band_sk#60] + +(82) Scan parquet spark_catalog.default.customer_address +Output [5]: [ca_address_sk#61, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk)] +ReadSchema: struct + +(83) CometFilter +Input [5]: [ca_address_sk#61, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] +Condition : isnotnull(ca_address_sk#61) + +(84) ColumnarToRow [codegen id : 19] +Input [5]: [ca_address_sk#61, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] + +(85) BroadcastExchange +Input [5]: [ca_address_sk#61, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=11] + +(86) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [ss_addr_sk#5] +Right keys [1]: [ca_address_sk#61] +Join type: Inner +Join condition: None + +(87) Project [codegen id : 24] +Output [16]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] +Input [18]: [ss_item_sk#1, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60, ca_address_sk#61, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] + +(88) ReusedExchange [Reuses operator id: 85] +Output [5]: [ca_address_sk#66, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70] + +(89) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [c_current_addr_sk#45] +Right keys [1]: [ca_address_sk#66] +Join type: Inner +Join condition: None + +(90) Project [codegen id : 24] +Output [19]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70] +Input [21]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_address_sk#66, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70] + +(91) Scan parquet spark_catalog.default.income_band +Output [1]: [ib_income_band_sk#71] +Batched: true +Location [not included in comparison]/{warehouse_dir}/income_band] +PushedFilters: [IsNotNull(ib_income_band_sk)] +ReadSchema: struct + +(92) CometFilter +Input [1]: [ib_income_band_sk#71] +Condition : isnotnull(ib_income_band_sk#71) + +(93) ColumnarToRow [codegen id : 21] +Input [1]: [ib_income_band_sk#71] + +(94) BroadcastExchange +Input [1]: [ib_income_band_sk#71] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=12] + +(95) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [hd_income_band_sk#58] +Right keys [1]: [ib_income_band_sk#71] +Join type: Inner +Join condition: None + +(96) Project [codegen id : 24] +Output [18]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70] +Input [20]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, ib_income_band_sk#71] + +(97) ReusedExchange [Reuses operator id: 94] +Output [1]: [ib_income_band_sk#72] + +(98) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [hd_income_band_sk#60] +Right keys [1]: [ib_income_band_sk#72] +Join type: Inner +Join condition: None + +(99) Project [codegen id : 24] +Output [17]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70] +Input [19]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, ib_income_band_sk#72] + +(100) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#73, i_current_price#74, i_color#75, i_product_name#76] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_current_price), In(i_color, [burlywood ,floral ,indian ,medium ,purple ,spring ]), GreaterThanOrEqual(i_current_price,64.00), LessThanOrEqual(i_current_price,74.00), GreaterThanOrEqual(i_current_price,65.00), LessThanOrEqual(i_current_price,79.00), IsNotNull(i_item_sk)] +ReadSchema: struct + +(101) CometFilter +Input [4]: [i_item_sk#73, i_current_price#74, i_color#75, i_product_name#76] +Condition : ((((((isnotnull(i_current_price#74) AND i_color#75 IN (purple ,burlywood ,indian ,spring ,floral ,medium )) AND (i_current_price#74 >= 64.00)) AND (i_current_price#74 <= 74.00)) AND (i_current_price#74 >= 65.00)) AND (i_current_price#74 <= 79.00)) AND isnotnull(i_item_sk#73)) + +(102) CometProject +Input [4]: [i_item_sk#73, i_current_price#74, i_color#75, i_product_name#76] +Arguments: [i_item_sk#73, i_product_name#76], [i_item_sk#73, i_product_name#76] + +(103) ColumnarToRow [codegen id : 23] +Input [2]: [i_item_sk#73, i_product_name#76] + +(104) BroadcastExchange +Input [2]: [i_item_sk#73, i_product_name#76] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=13] + +(105) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#73] +Join type: Inner +Join condition: None + +(106) Project [codegen id : 24] +Output [18]: [ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, d_year#49, d_year#51, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, i_item_sk#73, i_product_name#76] +Input [19]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, i_item_sk#73, i_product_name#76] + +(107) HashAggregate [codegen id : 24] +Input [18]: [ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, d_year#49, d_year#51, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, i_item_sk#73, i_product_name#76] +Keys [15]: [i_product_name#76, i_item_sk#73, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, d_year#38, d_year#49, d_year#51] +Functions [4]: [partial_count(1), partial_sum(UnscaledValue(ss_wholesale_cost#9)), partial_sum(UnscaledValue(ss_list_price#10)), partial_sum(UnscaledValue(ss_coupon_amt#11))] +Aggregate Attributes [4]: [count#77, sum#78, sum#79, sum#80] +Results [19]: [i_product_name#76, i_item_sk#73, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, d_year#38, d_year#49, d_year#51, count#81, sum#82, sum#83, sum#84] + +(108) HashAggregate [codegen id : 24] +Input [19]: [i_product_name#76, i_item_sk#73, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, d_year#38, d_year#49, d_year#51, count#81, sum#82, sum#83, sum#84] +Keys [15]: [i_product_name#76, i_item_sk#73, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, d_year#38, d_year#49, d_year#51] +Functions [4]: [count(1), sum(UnscaledValue(ss_wholesale_cost#9)), sum(UnscaledValue(ss_list_price#10)), sum(UnscaledValue(ss_coupon_amt#11))] +Aggregate Attributes [4]: [count(1)#85, sum(UnscaledValue(ss_wholesale_cost#9))#86, sum(UnscaledValue(ss_list_price#10))#87, sum(UnscaledValue(ss_coupon_amt#11))#88] +Results [17]: [i_product_name#76 AS product_name#89, i_item_sk#73 AS item_sk#90, s_store_name#40 AS store_name#91, s_zip#41 AS store_zip#92, ca_street_number#62 AS b_street_number#93, ca_street_name#63 AS b_streen_name#94, ca_city#64 AS b_city#95, ca_zip#65 AS b_zip#96, ca_street_number#67 AS c_street_number#97, ca_street_name#68 AS c_street_name#98, ca_city#69 AS c_city#99, ca_zip#70 AS c_zip#100, d_year#38 AS syear#101, count(1)#85 AS cnt#102, MakeDecimal(sum(UnscaledValue(ss_wholesale_cost#9))#86,17,2) AS s1#103, MakeDecimal(sum(UnscaledValue(ss_list_price#10))#87,17,2) AS s2#104, MakeDecimal(sum(UnscaledValue(ss_coupon_amt#11))#88,17,2) AS s3#105] + +(109) Exchange +Input [17]: [product_name#89, item_sk#90, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105] +Arguments: hashpartitioning(item_sk#90, store_name#91, store_zip#92, 5), ENSURE_REQUIREMENTS, [plan_id=14] + +(110) Sort [codegen id : 25] +Input [17]: [product_name#89, item_sk#90, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105] +Arguments: [item_sk#90 ASC NULLS FIRST, store_name#91 ASC NULLS FIRST, store_zip#92 ASC NULLS FIRST], false, 0 + +(111) Scan parquet spark_catalog.default.store_sales +Output [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#117), dynamicpruningexpression(ss_sold_date_sk#117 IN dynamicpruning#118)] +PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_ticket_number), IsNotNull(ss_store_sk), IsNotNull(ss_customer_sk), IsNotNull(ss_cdemo_sk), IsNotNull(ss_promo_sk), IsNotNull(ss_hdemo_sk), IsNotNull(ss_addr_sk)] +ReadSchema: struct + +(112) CometFilter +Input [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] +Condition : (((((((isnotnull(ss_item_sk#106) AND isnotnull(ss_ticket_number#113)) AND isnotnull(ss_store_sk#111)) AND isnotnull(ss_customer_sk#107)) AND isnotnull(ss_cdemo_sk#108)) AND isnotnull(ss_promo_sk#112)) AND isnotnull(ss_hdemo_sk#109)) AND isnotnull(ss_addr_sk#110)) + +(113) CometBroadcastExchange +Input [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] +Arguments: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] + +(114) Scan parquet spark_catalog.default.store_returns +Output [3]: [sr_item_sk#119, sr_ticket_number#120, sr_returned_date_sk#121] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_returns] +PushedFilters: [IsNotNull(sr_item_sk), IsNotNull(sr_ticket_number)] +ReadSchema: struct + +(115) CometFilter +Input [3]: [sr_item_sk#119, sr_ticket_number#120, sr_returned_date_sk#121] +Condition : (isnotnull(sr_item_sk#119) AND isnotnull(sr_ticket_number#120)) + +(116) CometProject +Input [3]: [sr_item_sk#119, sr_ticket_number#120, sr_returned_date_sk#121] +Arguments: [sr_item_sk#119, sr_ticket_number#120], [sr_item_sk#119, sr_ticket_number#120] + +(117) CometBroadcastHashJoin +Left output [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] +Right output [2]: [sr_item_sk#119, sr_ticket_number#120] +Arguments: [ss_item_sk#106, ss_ticket_number#113], [sr_item_sk#119, sr_ticket_number#120], Inner + +(118) CometProject +Input [14]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117, sr_item_sk#119, sr_ticket_number#120] +Arguments: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117], [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] + +(119) ColumnarToRow [codegen id : 26] +Input [11]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] + +(120) Exchange +Input [11]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] +Arguments: hashpartitioning(ss_item_sk#106, 5), ENSURE_REQUIREMENTS, [plan_id=15] + +(121) Sort [codegen id : 27] +Input [11]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] +Arguments: [ss_item_sk#106 ASC NULLS FIRST], false, 0 + +(122) ReusedExchange [Reuses operator id: 27] +Output [4]: [cs_item_sk#122, sum#123, sum#124, isEmpty#125] + +(123) HashAggregate [codegen id : 33] +Input [4]: [cs_item_sk#122, sum#123, sum#124, isEmpty#125] +Keys [1]: [cs_item_sk#122] +Functions [2]: [sum(UnscaledValue(cs_ext_list_price#126)), sum(((cr_refunded_cash#127 + cr_reversed_charge#128) + cr_store_credit#129))] +Aggregate Attributes [2]: [sum(UnscaledValue(cs_ext_list_price#126))#33, sum(((cr_refunded_cash#127 + cr_reversed_charge#128) + cr_store_credit#129))#34] +Results [3]: [cs_item_sk#122, MakeDecimal(sum(UnscaledValue(cs_ext_list_price#126))#33,17,2) AS sale#130, sum(((cr_refunded_cash#127 + cr_reversed_charge#128) + cr_store_credit#129))#34 AS refund#131] + +(124) Filter [codegen id : 33] +Input [3]: [cs_item_sk#122, sale#130, refund#131] +Condition : ((isnotnull(sale#130) AND isnotnull(refund#131)) AND (cast(sale#130 as decimal(21,2)) > (2 * refund#131))) + +(125) Project [codegen id : 33] +Output [1]: [cs_item_sk#122] +Input [3]: [cs_item_sk#122, sale#130, refund#131] + +(126) Sort [codegen id : 33] +Input [1]: [cs_item_sk#122] +Arguments: [cs_item_sk#122 ASC NULLS FIRST], false, 0 + +(127) SortMergeJoin [codegen id : 49] +Left keys [1]: [ss_item_sk#106] +Right keys [1]: [cs_item_sk#122] +Join type: Inner +Join condition: None + +(128) Project [codegen id : 49] +Output [11]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] +Input [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117, cs_item_sk#122] + +(129) ReusedExchange [Reuses operator id: 189] +Output [2]: [d_date_sk#132, d_year#133] + +(130) BroadcastHashJoin [codegen id : 49] +Left keys [1]: [ss_sold_date_sk#117] +Right keys [1]: [d_date_sk#132] +Join type: Inner +Join condition: None + +(131) Project [codegen id : 49] +Output [11]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133] +Input [13]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117, d_date_sk#132, d_year#133] + +(132) ReusedExchange [Reuses operator id: 40] +Output [3]: [s_store_sk#134, s_store_name#135, s_zip#136] + +(133) BroadcastHashJoin [codegen id : 49] +Left keys [1]: [ss_store_sk#111] +Right keys [1]: [s_store_sk#134] +Join type: Inner +Join condition: None + +(134) Project [codegen id : 49] +Output [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136] +Input [14]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_sk#134, s_store_name#135, s_zip#136] + +(135) ReusedExchange [Reuses operator id: 46] +Output [6]: [c_customer_sk#137, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, c_first_sales_date_sk#142] + +(136) BroadcastHashJoin [codegen id : 49] +Left keys [1]: [ss_customer_sk#107] +Right keys [1]: [c_customer_sk#137] +Join type: Inner +Join condition: None + +(137) Project [codegen id : 49] +Output [16]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, c_first_sales_date_sk#142] +Input [18]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_customer_sk#137, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, c_first_sales_date_sk#142] + +(138) ReusedExchange [Reuses operator id: 52] +Output [2]: [d_date_sk#143, d_year#144] + +(139) BroadcastHashJoin [codegen id : 49] +Left keys [1]: [c_first_sales_date_sk#142] +Right keys [1]: [d_date_sk#143] +Join type: Inner +Join condition: None + +(140) Project [codegen id : 49] +Output [16]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, d_year#144] +Input [18]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, c_first_sales_date_sk#142, d_date_sk#143, d_year#144] + +(141) ReusedExchange [Reuses operator id: 52] +Output [2]: [d_date_sk#145, d_year#146] + +(142) BroadcastHashJoin [codegen id : 49] +Left keys [1]: [c_first_shipto_date_sk#141] +Right keys [1]: [d_date_sk#145] +Join type: Inner +Join condition: None + +(143) Project [codegen id : 49] +Output [16]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146] +Input [18]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, d_year#144, d_date_sk#145, d_year#146] + +(144) ReusedExchange [Reuses operator id: 61] +Output [2]: [cd_demo_sk#147, cd_marital_status#148] + +(145) BroadcastHashJoin [codegen id : 49] +Left keys [1]: [ss_cdemo_sk#108] +Right keys [1]: [cd_demo_sk#147] +Join type: Inner +Join condition: None + +(146) Project [codegen id : 49] +Output [16]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, cd_marital_status#148] +Input [18]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, cd_demo_sk#147, cd_marital_status#148] + +(147) ReusedExchange [Reuses operator id: 61] +Output [2]: [cd_demo_sk#149, cd_marital_status#150] + +(148) BroadcastHashJoin [codegen id : 49] +Left keys [1]: [c_current_cdemo_sk#138] +Right keys [1]: [cd_demo_sk#149] +Join type: Inner +Join condition: NOT (cd_marital_status#148 = cd_marital_status#150) + +(149) Project [codegen id : 49] +Output [14]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146] +Input [18]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, cd_marital_status#148, cd_demo_sk#149, cd_marital_status#150] + +(150) ReusedExchange [Reuses operator id: 70] +Output [1]: [p_promo_sk#151] + +(151) BroadcastHashJoin [codegen id : 49] +Left keys [1]: [ss_promo_sk#112] +Right keys [1]: [p_promo_sk#151] +Join type: Inner +Join condition: None + +(152) Project [codegen id : 49] +Output [13]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146] +Input [15]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, p_promo_sk#151] + +(153) ReusedExchange [Reuses operator id: 76] +Output [2]: [hd_demo_sk#152, hd_income_band_sk#153] + +(154) BroadcastHashJoin [codegen id : 49] +Left keys [1]: [ss_hdemo_sk#109] +Right keys [1]: [hd_demo_sk#152] +Join type: Inner +Join condition: None + +(155) Project [codegen id : 49] +Output [13]: [ss_item_sk#106, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153] +Input [15]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, hd_demo_sk#152, hd_income_band_sk#153] + +(156) ReusedExchange [Reuses operator id: 76] +Output [2]: [hd_demo_sk#154, hd_income_band_sk#155] + +(157) BroadcastHashJoin [codegen id : 49] +Left keys [1]: [c_current_hdemo_sk#139] +Right keys [1]: [hd_demo_sk#154] +Join type: Inner +Join condition: None + +(158) Project [codegen id : 49] +Output [13]: [ss_item_sk#106, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155] +Input [15]: [ss_item_sk#106, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153, hd_demo_sk#154, hd_income_band_sk#155] + +(159) ReusedExchange [Reuses operator id: 85] +Output [5]: [ca_address_sk#156, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160] + +(160) BroadcastHashJoin [codegen id : 49] +Left keys [1]: [ss_addr_sk#110] +Right keys [1]: [ca_address_sk#156] +Join type: Inner +Join condition: None + +(161) Project [codegen id : 49] +Output [16]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160] +Input [18]: [ss_item_sk#106, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155, ca_address_sk#156, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160] + +(162) ReusedExchange [Reuses operator id: 85] +Output [5]: [ca_address_sk#161, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165] + +(163) BroadcastHashJoin [codegen id : 49] +Left keys [1]: [c_current_addr_sk#140] +Right keys [1]: [ca_address_sk#161] +Join type: Inner +Join condition: None + +(164) Project [codegen id : 49] +Output [19]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165] +Input [21]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_address_sk#161, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165] + +(165) ReusedExchange [Reuses operator id: 94] +Output [1]: [ib_income_band_sk#166] + +(166) BroadcastHashJoin [codegen id : 49] +Left keys [1]: [hd_income_band_sk#153] +Right keys [1]: [ib_income_band_sk#166] +Join type: Inner +Join condition: None + +(167) Project [codegen id : 49] +Output [18]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165] +Input [20]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, ib_income_band_sk#166] + +(168) ReusedExchange [Reuses operator id: 94] +Output [1]: [ib_income_band_sk#167] + +(169) BroadcastHashJoin [codegen id : 49] +Left keys [1]: [hd_income_band_sk#155] +Right keys [1]: [ib_income_band_sk#167] +Join type: Inner +Join condition: None + +(170) Project [codegen id : 49] +Output [17]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165] +Input [19]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, ib_income_band_sk#167] + +(171) ReusedExchange [Reuses operator id: 104] +Output [2]: [i_item_sk#168, i_product_name#169] + +(172) BroadcastHashJoin [codegen id : 49] +Left keys [1]: [ss_item_sk#106] +Right keys [1]: [i_item_sk#168] +Join type: Inner +Join condition: None + +(173) Project [codegen id : 49] +Output [18]: [ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, d_year#144, d_year#146, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, i_item_sk#168, i_product_name#169] +Input [19]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, i_item_sk#168, i_product_name#169] + +(174) HashAggregate [codegen id : 49] +Input [18]: [ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, d_year#144, d_year#146, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, i_item_sk#168, i_product_name#169] +Keys [15]: [i_product_name#169, i_item_sk#168, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, d_year#133, d_year#144, d_year#146] +Functions [4]: [partial_count(1), partial_sum(UnscaledValue(ss_wholesale_cost#114)), partial_sum(UnscaledValue(ss_list_price#115)), partial_sum(UnscaledValue(ss_coupon_amt#116))] +Aggregate Attributes [4]: [count#77, sum#170, sum#171, sum#172] +Results [19]: [i_product_name#169, i_item_sk#168, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, d_year#133, d_year#144, d_year#146, count#81, sum#173, sum#174, sum#175] + +(175) HashAggregate [codegen id : 49] +Input [19]: [i_product_name#169, i_item_sk#168, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, d_year#133, d_year#144, d_year#146, count#81, sum#173, sum#174, sum#175] +Keys [15]: [i_product_name#169, i_item_sk#168, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, d_year#133, d_year#144, d_year#146] +Functions [4]: [count(1), sum(UnscaledValue(ss_wholesale_cost#114)), sum(UnscaledValue(ss_list_price#115)), sum(UnscaledValue(ss_coupon_amt#116))] +Aggregate Attributes [4]: [count(1)#85, sum(UnscaledValue(ss_wholesale_cost#114))#86, sum(UnscaledValue(ss_list_price#115))#87, sum(UnscaledValue(ss_coupon_amt#116))#88] +Results [8]: [i_item_sk#168 AS item_sk#176, s_store_name#135 AS store_name#177, s_zip#136 AS store_zip#178, d_year#133 AS syear#179, count(1)#85 AS cnt#180, MakeDecimal(sum(UnscaledValue(ss_wholesale_cost#114))#86,17,2) AS s1#181, MakeDecimal(sum(UnscaledValue(ss_list_price#115))#87,17,2) AS s2#182, MakeDecimal(sum(UnscaledValue(ss_coupon_amt#116))#88,17,2) AS s3#183] + +(176) Exchange +Input [8]: [item_sk#176, store_name#177, store_zip#178, syear#179, cnt#180, s1#181, s2#182, s3#183] +Arguments: hashpartitioning(item_sk#176, store_name#177, store_zip#178, 5), ENSURE_REQUIREMENTS, [plan_id=16] + +(177) Sort [codegen id : 50] +Input [8]: [item_sk#176, store_name#177, store_zip#178, syear#179, cnt#180, s1#181, s2#182, s3#183] +Arguments: [item_sk#176 ASC NULLS FIRST, store_name#177 ASC NULLS FIRST, store_zip#178 ASC NULLS FIRST], false, 0 + +(178) SortMergeJoin [codegen id : 51] +Left keys [3]: [item_sk#90, store_name#91, store_zip#92] +Right keys [3]: [item_sk#176, store_name#177, store_zip#178] +Join type: Inner +Join condition: (cnt#180 <= cnt#102) + +(179) Project [codegen id : 51] +Output [21]: [product_name#89, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105, s1#181, s2#182, s3#183, syear#179, cnt#180] +Input [25]: [product_name#89, item_sk#90, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105, item_sk#176, store_name#177, store_zip#178, syear#179, cnt#180, s1#181, s2#182, s3#183] + +(180) Exchange +Input [21]: [product_name#89, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105, s1#181, s2#182, s3#183, syear#179, cnt#180] +Arguments: rangepartitioning(product_name#89 ASC NULLS FIRST, store_name#91 ASC NULLS FIRST, cnt#180 ASC NULLS FIRST, s1#103 ASC NULLS FIRST, s1#181 ASC NULLS FIRST, 5), ENSURE_REQUIREMENTS, [plan_id=17] + +(181) Sort [codegen id : 52] +Input [21]: [product_name#89, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105, s1#181, s2#182, s3#183, syear#179, cnt#180] +Arguments: [product_name#89 ASC NULLS FIRST, store_name#91 ASC NULLS FIRST, cnt#180 ASC NULLS FIRST, s1#103 ASC NULLS FIRST, s1#181 ASC NULLS FIRST], true, 0 + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#12 IN dynamicpruning#13 +BroadcastExchange (185) ++- * ColumnarToRow (184) + +- CometFilter (183) + +- CometScan parquet spark_catalog.default.date_dim (182) + + +(182) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#37, d_year#38] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,1999), IsNotNull(d_date_sk)] +ReadSchema: struct + +(183) CometFilter +Input [2]: [d_date_sk#37, d_year#38] +Condition : ((isnotnull(d_year#38) AND (d_year#38 = 1999)) AND isnotnull(d_date_sk#37)) + +(184) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#37, d_year#38] + +(185) BroadcastExchange +Input [2]: [d_date_sk#37, d_year#38] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=18] + +Subquery:2 Hosting operator id = 111 Hosting Expression = ss_sold_date_sk#117 IN dynamicpruning#118 +BroadcastExchange (189) ++- * ColumnarToRow (188) + +- CometFilter (187) + +- CometScan parquet spark_catalog.default.date_dim (186) + + +(186) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#132, d_year#133] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2000), IsNotNull(d_date_sk)] +ReadSchema: struct + +(187) CometFilter +Input [2]: [d_date_sk#132, d_year#133] +Condition : ((isnotnull(d_year#133) AND (d_year#133 = 2000)) AND isnotnull(d_date_sk#132)) + +(188) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#132, d_year#133] + +(189) BroadcastExchange +Input [2]: [d_date_sk#132, d_year#133] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=19] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q64/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q64/simplified.txt new file mode 100644 index 0000000000..2a0bc5bced --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q64/simplified.txt @@ -0,0 +1,281 @@ +WholeStageCodegen (52) + Sort [product_name,store_name,cnt,s1,s1] + InputAdapter + Exchange [product_name,store_name,cnt,s1,s1] #1 + WholeStageCodegen (51) + Project [product_name,store_name,store_zip,b_street_number,b_streen_name,b_city,b_zip,c_street_number,c_street_name,c_city,c_zip,syear,cnt,s1,s2,s3,s1,s2,s3,syear,cnt] + SortMergeJoin [item_sk,store_name,store_zip,item_sk,store_name,store_zip,cnt,cnt] + InputAdapter + WholeStageCodegen (25) + Sort [item_sk,store_name,store_zip] + InputAdapter + Exchange [item_sk,store_name,store_zip] #2 + WholeStageCodegen (24) + HashAggregate [i_product_name,i_item_sk,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,d_year,d_year,d_year,count,sum,sum,sum] [count(1),sum(UnscaledValue(ss_wholesale_cost)),sum(UnscaledValue(ss_list_price)),sum(UnscaledValue(ss_coupon_amt)),product_name,item_sk,store_name,store_zip,b_street_number,b_streen_name,b_city,b_zip,c_street_number,c_street_name,c_city,c_zip,syear,cnt,s1,s2,s3,count,sum,sum,sum] + HashAggregate [i_product_name,i_item_sk,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,d_year,d_year,d_year,ss_wholesale_cost,ss_list_price,ss_coupon_amt] [count,sum,sum,sum,count,sum,sum,sum] + Project [ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,d_year,d_year,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,i_item_sk,i_product_name] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,d_year,d_year,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip] + BroadcastHashJoin [hd_income_band_sk,ib_income_band_sk] + Project [ss_item_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,d_year,d_year,hd_income_band_sk,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip] + BroadcastHashJoin [hd_income_band_sk,ib_income_band_sk] + Project [ss_item_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,d_year,d_year,hd_income_band_sk,hd_income_band_sk,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [ss_item_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_addr_sk,d_year,d_year,hd_income_band_sk,hd_income_band_sk,ca_street_number,ca_street_name,ca_city,ca_zip] + BroadcastHashJoin [ss_addr_sk,ca_address_sk] + Project [ss_item_sk,ss_addr_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_addr_sk,d_year,d_year,hd_income_band_sk,hd_income_band_sk] + BroadcastHashJoin [c_current_hdemo_sk,hd_demo_sk] + Project [ss_item_sk,ss_addr_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year,hd_income_band_sk] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + Project [ss_item_sk,ss_hdemo_sk,ss_addr_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year] + BroadcastHashJoin [ss_promo_sk,p_promo_sk] + Project [ss_item_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk,cd_marital_status,cd_marital_status] + Project [ss_item_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year,cd_marital_status] + BroadcastHashJoin [ss_cdemo_sk,cd_demo_sk] + Project [ss_item_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year] + BroadcastHashJoin [c_first_shipto_date_sk,d_date_sk] + Project [ss_item_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,c_first_shipto_date_sk,d_year] + BroadcastHashJoin [c_first_sales_date_sk,d_date_sk] + Project [ss_item_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,c_first_shipto_date_sk,c_first_sales_date_sk] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + SortMergeJoin [ss_item_sk,cs_item_sk] + InputAdapter + WholeStageCodegen (2) + Sort [ss_item_sk] + InputAdapter + Exchange [ss_item_sk] #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + CometBroadcastHashJoin [ss_item_sk,ss_ticket_number,sr_item_sk,sr_ticket_number] + CometBroadcastExchange #4 + CometFilter [ss_item_sk,ss_ticket_number,ss_store_sk,ss_customer_sk,ss_cdemo_sk,ss_promo_sk,ss_hdemo_sk,ss_addr_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_ticket_number,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #5 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + CometProject [sr_item_sk,sr_ticket_number] + CometFilter [sr_item_sk,sr_ticket_number] + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_returned_date_sk] + InputAdapter + WholeStageCodegen (8) + Sort [cs_item_sk] + Project [cs_item_sk] + Filter [sale,refund] + HashAggregate [cs_item_sk,sum,sum,isEmpty] [sum(UnscaledValue(cs_ext_list_price)),sum(((cr_refunded_cash + cr_reversed_charge) + cr_store_credit)),sale,refund,sum,sum,isEmpty] + InputAdapter + Exchange [cs_item_sk] #6 + WholeStageCodegen (7) + HashAggregate [cs_item_sk,cs_ext_list_price,cr_refunded_cash,cr_reversed_charge,cr_store_credit] [sum,sum,isEmpty,sum,sum,isEmpty] + Project [cs_item_sk,cs_ext_list_price,cr_refunded_cash,cr_reversed_charge,cr_store_credit] + SortMergeJoin [cs_item_sk,cs_order_number,cr_item_sk,cr_order_number] + InputAdapter + WholeStageCodegen (4) + Sort [cs_item_sk,cs_order_number] + InputAdapter + Exchange [cs_item_sk,cs_order_number] #7 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometProject [cs_item_sk,cs_order_number,cs_ext_list_price] + CometFilter [cs_item_sk,cs_order_number] + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_order_number,cs_ext_list_price,cs_sold_date_sk] + InputAdapter + WholeStageCodegen (6) + Sort [cr_item_sk,cr_order_number] + InputAdapter + Exchange [cr_item_sk,cr_order_number] #8 + WholeStageCodegen (5) + ColumnarToRow + InputAdapter + CometProject [cr_item_sk,cr_order_number,cr_refunded_cash,cr_reversed_charge,cr_store_credit] + CometFilter [cr_item_sk,cr_order_number] + CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_refunded_cash,cr_reversed_charge,cr_store_credit,cr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk,d_year] #5 + InputAdapter + BroadcastExchange #9 + WholeStageCodegen (10) + ColumnarToRow + InputAdapter + CometFilter [s_store_sk,s_store_name,s_zip] + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name,s_zip] + InputAdapter + BroadcastExchange #10 + WholeStageCodegen (11) + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_first_sales_date_sk,c_first_shipto_date_sk,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,c_first_shipto_date_sk,c_first_sales_date_sk] + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (12) + ColumnarToRow + InputAdapter + CometFilter [d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk,d_year] #11 + InputAdapter + BroadcastExchange #12 + WholeStageCodegen (14) + ColumnarToRow + InputAdapter + CometFilter [cd_demo_sk,cd_marital_status] + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_marital_status] + InputAdapter + ReusedExchange [cd_demo_sk,cd_marital_status] #12 + InputAdapter + BroadcastExchange #13 + WholeStageCodegen (16) + ColumnarToRow + InputAdapter + CometFilter [p_promo_sk] + CometScan parquet spark_catalog.default.promotion [p_promo_sk] + InputAdapter + BroadcastExchange #14 + WholeStageCodegen (17) + ColumnarToRow + InputAdapter + CometFilter [hd_demo_sk,hd_income_band_sk] + CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_income_band_sk] + InputAdapter + ReusedExchange [hd_demo_sk,hd_income_band_sk] #14 + InputAdapter + BroadcastExchange #15 + WholeStageCodegen (19) + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk] + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_street_number,ca_street_name,ca_city,ca_zip] + InputAdapter + ReusedExchange [ca_address_sk,ca_street_number,ca_street_name,ca_city,ca_zip] #15 + InputAdapter + BroadcastExchange #16 + WholeStageCodegen (21) + ColumnarToRow + InputAdapter + CometFilter [ib_income_band_sk] + CometScan parquet spark_catalog.default.income_band [ib_income_band_sk] + InputAdapter + ReusedExchange [ib_income_band_sk] #16 + InputAdapter + BroadcastExchange #17 + WholeStageCodegen (23) + ColumnarToRow + InputAdapter + CometProject [i_item_sk,i_product_name] + CometFilter [i_current_price,i_color,i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price,i_color,i_product_name] + InputAdapter + WholeStageCodegen (50) + Sort [item_sk,store_name,store_zip] + InputAdapter + Exchange [item_sk,store_name,store_zip] #18 + WholeStageCodegen (49) + HashAggregate [i_product_name,i_item_sk,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,d_year,d_year,d_year,count,sum,sum,sum] [count(1),sum(UnscaledValue(ss_wholesale_cost)),sum(UnscaledValue(ss_list_price)),sum(UnscaledValue(ss_coupon_amt)),item_sk,store_name,store_zip,syear,cnt,s1,s2,s3,count,sum,sum,sum] + HashAggregate [i_product_name,i_item_sk,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,d_year,d_year,d_year,ss_wholesale_cost,ss_list_price,ss_coupon_amt] [count,sum,sum,sum,count,sum,sum,sum] + Project [ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,d_year,d_year,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,i_item_sk,i_product_name] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,d_year,d_year,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip] + BroadcastHashJoin [hd_income_band_sk,ib_income_band_sk] + Project [ss_item_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,d_year,d_year,hd_income_band_sk,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip] + BroadcastHashJoin [hd_income_band_sk,ib_income_band_sk] + Project [ss_item_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,d_year,d_year,hd_income_band_sk,hd_income_band_sk,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [ss_item_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_addr_sk,d_year,d_year,hd_income_band_sk,hd_income_band_sk,ca_street_number,ca_street_name,ca_city,ca_zip] + BroadcastHashJoin [ss_addr_sk,ca_address_sk] + Project [ss_item_sk,ss_addr_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_addr_sk,d_year,d_year,hd_income_band_sk,hd_income_band_sk] + BroadcastHashJoin [c_current_hdemo_sk,hd_demo_sk] + Project [ss_item_sk,ss_addr_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year,hd_income_band_sk] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + Project [ss_item_sk,ss_hdemo_sk,ss_addr_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year] + BroadcastHashJoin [ss_promo_sk,p_promo_sk] + Project [ss_item_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk,cd_marital_status,cd_marital_status] + Project [ss_item_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year,cd_marital_status] + BroadcastHashJoin [ss_cdemo_sk,cd_demo_sk] + Project [ss_item_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year] + BroadcastHashJoin [c_first_shipto_date_sk,d_date_sk] + Project [ss_item_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,c_first_shipto_date_sk,d_year] + BroadcastHashJoin [c_first_sales_date_sk,d_date_sk] + Project [ss_item_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,c_first_shipto_date_sk,c_first_sales_date_sk] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + SortMergeJoin [ss_item_sk,cs_item_sk] + InputAdapter + WholeStageCodegen (27) + Sort [ss_item_sk] + InputAdapter + Exchange [ss_item_sk] #19 + WholeStageCodegen (26) + ColumnarToRow + InputAdapter + CometProject [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + CometBroadcastHashJoin [ss_item_sk,ss_ticket_number,sr_item_sk,sr_ticket_number] + CometBroadcastExchange #20 + CometFilter [ss_item_sk,ss_ticket_number,ss_store_sk,ss_customer_sk,ss_cdemo_sk,ss_promo_sk,ss_hdemo_sk,ss_addr_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_ticket_number,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #21 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + CometProject [sr_item_sk,sr_ticket_number] + CometFilter [sr_item_sk,sr_ticket_number] + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_returned_date_sk] + InputAdapter + WholeStageCodegen (33) + Sort [cs_item_sk] + Project [cs_item_sk] + Filter [sale,refund] + HashAggregate [cs_item_sk,sum,sum,isEmpty] [sum(UnscaledValue(cs_ext_list_price)),sum(((cr_refunded_cash + cr_reversed_charge) + cr_store_credit)),sale,refund,sum,sum,isEmpty] + InputAdapter + ReusedExchange [cs_item_sk,sum,sum,isEmpty] #6 + InputAdapter + ReusedExchange [d_date_sk,d_year] #21 + InputAdapter + ReusedExchange [s_store_sk,s_store_name,s_zip] #9 + InputAdapter + ReusedExchange [c_customer_sk,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,c_first_shipto_date_sk,c_first_sales_date_sk] #10 + InputAdapter + ReusedExchange [d_date_sk,d_year] #11 + InputAdapter + ReusedExchange [d_date_sk,d_year] #11 + InputAdapter + ReusedExchange [cd_demo_sk,cd_marital_status] #12 + InputAdapter + ReusedExchange [cd_demo_sk,cd_marital_status] #12 + InputAdapter + ReusedExchange [p_promo_sk] #13 + InputAdapter + ReusedExchange [hd_demo_sk,hd_income_band_sk] #14 + InputAdapter + ReusedExchange [hd_demo_sk,hd_income_band_sk] #14 + InputAdapter + ReusedExchange [ca_address_sk,ca_street_number,ca_street_name,ca_city,ca_zip] #15 + InputAdapter + ReusedExchange [ca_address_sk,ca_street_number,ca_street_name,ca_city,ca_zip] #15 + InputAdapter + ReusedExchange [ib_income_band_sk] #16 + InputAdapter + ReusedExchange [ib_income_band_sk] #16 + InputAdapter + ReusedExchange [i_item_sk,i_product_name] #17 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q67a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q67a/explain.txt new file mode 100644 index 0000000000..6ca27323ac --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q67a/explain.txt @@ -0,0 +1,466 @@ +== Physical Plan == +TakeOrderedAndProject (70) ++- * Filter (69) + +- Window (68) + +- WindowGroupLimit (67) + +- * Sort (66) + +- Exchange (65) + +- WindowGroupLimit (64) + +- * Sort (63) + +- Union (62) + :- * HashAggregate (21) + : +- Exchange (20) + : +- * HashAggregate (19) + : +- * Project (18) + : +- * BroadcastHashJoin Inner BuildRight (17) + : :- * Project (12) + : : +- * BroadcastHashJoin Inner BuildRight (11) + : : :- * Project (6) + : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- ReusedExchange (4) + : : +- BroadcastExchange (10) + : : +- * ColumnarToRow (9) + : : +- CometFilter (8) + : : +- CometScan parquet spark_catalog.default.store (7) + : +- BroadcastExchange (16) + : +- * ColumnarToRow (15) + : +- CometFilter (14) + : +- CometScan parquet spark_catalog.default.item (13) + :- * HashAggregate (26) + : +- Exchange (25) + : +- * HashAggregate (24) + : +- * HashAggregate (23) + : +- ReusedExchange (22) + :- * HashAggregate (31) + : +- Exchange (30) + : +- * HashAggregate (29) + : +- * HashAggregate (28) + : +- ReusedExchange (27) + :- * HashAggregate (36) + : +- Exchange (35) + : +- * HashAggregate (34) + : +- * HashAggregate (33) + : +- ReusedExchange (32) + :- * HashAggregate (41) + : +- Exchange (40) + : +- * HashAggregate (39) + : +- * HashAggregate (38) + : +- ReusedExchange (37) + :- * HashAggregate (46) + : +- Exchange (45) + : +- * HashAggregate (44) + : +- * HashAggregate (43) + : +- ReusedExchange (42) + :- * HashAggregate (51) + : +- Exchange (50) + : +- * HashAggregate (49) + : +- * HashAggregate (48) + : +- ReusedExchange (47) + :- * HashAggregate (56) + : +- Exchange (55) + : +- * HashAggregate (54) + : +- * HashAggregate (53) + : +- ReusedExchange (52) + +- * HashAggregate (61) + +- Exchange (60) + +- * HashAggregate (59) + +- * HashAggregate (58) + +- ReusedExchange (57) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, ss_sold_date_sk#5] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#5), dynamicpruningexpression(ss_sold_date_sk#5 IN dynamicpruning#6)] +PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [5]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, ss_sold_date_sk#5] +Condition : (isnotnull(ss_store_sk#2) AND isnotnull(ss_item_sk#1)) + +(3) ColumnarToRow [codegen id : 4] +Input [5]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, ss_sold_date_sk#5] + +(4) ReusedExchange [Reuses operator id: 75] +Output [4]: [d_date_sk#7, d_year#8, d_moy#9, d_qoy#10] + +(5) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_date_sk#5] +Right keys [1]: [d_date_sk#7] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 4] +Output [7]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, d_year#8, d_moy#9, d_qoy#10] +Input [9]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, ss_sold_date_sk#5, d_date_sk#7, d_year#8, d_moy#9, d_qoy#10] + +(7) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#11, s_store_id#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(8) CometFilter +Input [2]: [s_store_sk#11, s_store_id#12] +Condition : isnotnull(s_store_sk#11) + +(9) ColumnarToRow [codegen id : 2] +Input [2]: [s_store_sk#11, s_store_id#12] + +(10) BroadcastExchange +Input [2]: [s_store_sk#11, s_store_id#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(11) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_store_sk#2] +Right keys [1]: [s_store_sk#11] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 4] +Output [7]: [ss_item_sk#1, ss_quantity#3, ss_sales_price#4, d_year#8, d_moy#9, d_qoy#10, s_store_id#12] +Input [9]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, d_year#8, d_moy#9, d_qoy#10, s_store_sk#11, s_store_id#12] + +(13) Scan parquet spark_catalog.default.item +Output [5]: [i_item_sk#13, i_brand#14, i_class#15, i_category#16, i_product_name#17] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(14) CometFilter +Input [5]: [i_item_sk#13, i_brand#14, i_class#15, i_category#16, i_product_name#17] +Condition : isnotnull(i_item_sk#13) + +(15) ColumnarToRow [codegen id : 3] +Input [5]: [i_item_sk#13, i_brand#14, i_class#15, i_category#16, i_product_name#17] + +(16) BroadcastExchange +Input [5]: [i_item_sk#13, i_brand#14, i_class#15, i_category#16, i_product_name#17] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(17) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#13] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 4] +Output [10]: [ss_quantity#3, ss_sales_price#4, d_year#8, d_moy#9, d_qoy#10, s_store_id#12, i_brand#14, i_class#15, i_category#16, i_product_name#17] +Input [12]: [ss_item_sk#1, ss_quantity#3, ss_sales_price#4, d_year#8, d_moy#9, d_qoy#10, s_store_id#12, i_item_sk#13, i_brand#14, i_class#15, i_category#16, i_product_name#17] + +(19) HashAggregate [codegen id : 4] +Input [10]: [ss_quantity#3, ss_sales_price#4, d_year#8, d_moy#9, d_qoy#10, s_store_id#12, i_brand#14, i_class#15, i_category#16, i_product_name#17] +Keys [8]: [i_category#16, i_class#15, i_brand#14, i_product_name#17, d_year#8, d_qoy#10, d_moy#9, s_store_id#12] +Functions [1]: [partial_sum(coalesce((ss_sales_price#4 * cast(ss_quantity#3 as decimal(10,0))), 0.00))] +Aggregate Attributes [2]: [sum#18, isEmpty#19] +Results [10]: [i_category#16, i_class#15, i_brand#14, i_product_name#17, d_year#8, d_qoy#10, d_moy#9, s_store_id#12, sum#20, isEmpty#21] + +(20) Exchange +Input [10]: [i_category#16, i_class#15, i_brand#14, i_product_name#17, d_year#8, d_qoy#10, d_moy#9, s_store_id#12, sum#20, isEmpty#21] +Arguments: hashpartitioning(i_category#16, i_class#15, i_brand#14, i_product_name#17, d_year#8, d_qoy#10, d_moy#9, s_store_id#12, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(21) HashAggregate [codegen id : 5] +Input [10]: [i_category#16, i_class#15, i_brand#14, i_product_name#17, d_year#8, d_qoy#10, d_moy#9, s_store_id#12, sum#20, isEmpty#21] +Keys [8]: [i_category#16, i_class#15, i_brand#14, i_product_name#17, d_year#8, d_qoy#10, d_moy#9, s_store_id#12] +Functions [1]: [sum(coalesce((ss_sales_price#4 * cast(ss_quantity#3 as decimal(10,0))), 0.00))] +Aggregate Attributes [1]: [sum(coalesce((ss_sales_price#4 * cast(ss_quantity#3 as decimal(10,0))), 0.00))#22] +Results [9]: [i_category#16 AS i_category#23, i_class#15 AS i_class#24, i_brand#14 AS i_brand#25, i_product_name#17 AS i_product_name#26, d_year#8 AS d_year#27, d_qoy#10 AS d_qoy#28, d_moy#9 AS d_moy#29, s_store_id#12 AS s_store_id#30, cast(sum(coalesce((ss_sales_price#4 * cast(ss_quantity#3 as decimal(10,0))), 0.00))#22 as decimal(38,2)) AS sumsales#31] + +(22) ReusedExchange [Reuses operator id: 20] +Output [10]: [i_category#32, i_class#33, i_brand#34, i_product_name#35, d_year#36, d_qoy#37, d_moy#38, s_store_id#39, sum#40, isEmpty#41] + +(23) HashAggregate [codegen id : 10] +Input [10]: [i_category#32, i_class#33, i_brand#34, i_product_name#35, d_year#36, d_qoy#37, d_moy#38, s_store_id#39, sum#40, isEmpty#41] +Keys [8]: [i_category#32, i_class#33, i_brand#34, i_product_name#35, d_year#36, d_qoy#37, d_moy#38, s_store_id#39] +Functions [1]: [sum(coalesce((ss_sales_price#42 * cast(ss_quantity#43 as decimal(10,0))), 0.00))] +Aggregate Attributes [1]: [sum(coalesce((ss_sales_price#42 * cast(ss_quantity#43 as decimal(10,0))), 0.00))#22] +Results [8]: [i_category#32, i_class#33, i_brand#34, i_product_name#35, d_year#36, d_qoy#37, d_moy#38, sum(coalesce((ss_sales_price#42 * cast(ss_quantity#43 as decimal(10,0))), 0.00))#22 AS sumsales#44] + +(24) HashAggregate [codegen id : 10] +Input [8]: [i_category#32, i_class#33, i_brand#34, i_product_name#35, d_year#36, d_qoy#37, d_moy#38, sumsales#44] +Keys [7]: [i_category#32, i_class#33, i_brand#34, i_product_name#35, d_year#36, d_qoy#37, d_moy#38] +Functions [1]: [partial_sum(sumsales#44)] +Aggregate Attributes [2]: [sum#45, isEmpty#46] +Results [9]: [i_category#32, i_class#33, i_brand#34, i_product_name#35, d_year#36, d_qoy#37, d_moy#38, sum#47, isEmpty#48] + +(25) Exchange +Input [9]: [i_category#32, i_class#33, i_brand#34, i_product_name#35, d_year#36, d_qoy#37, d_moy#38, sum#47, isEmpty#48] +Arguments: hashpartitioning(i_category#32, i_class#33, i_brand#34, i_product_name#35, d_year#36, d_qoy#37, d_moy#38, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(26) HashAggregate [codegen id : 11] +Input [9]: [i_category#32, i_class#33, i_brand#34, i_product_name#35, d_year#36, d_qoy#37, d_moy#38, sum#47, isEmpty#48] +Keys [7]: [i_category#32, i_class#33, i_brand#34, i_product_name#35, d_year#36, d_qoy#37, d_moy#38] +Functions [1]: [sum(sumsales#44)] +Aggregate Attributes [1]: [sum(sumsales#44)#49] +Results [9]: [i_category#32, i_class#33, i_brand#34, i_product_name#35, d_year#36, d_qoy#37, d_moy#38, null AS s_store_id#50, sum(sumsales#44)#49 AS sumsales#51] + +(27) ReusedExchange [Reuses operator id: 20] +Output [10]: [i_category#52, i_class#53, i_brand#54, i_product_name#55, d_year#56, d_qoy#57, d_moy#58, s_store_id#59, sum#60, isEmpty#61] + +(28) HashAggregate [codegen id : 16] +Input [10]: [i_category#52, i_class#53, i_brand#54, i_product_name#55, d_year#56, d_qoy#57, d_moy#58, s_store_id#59, sum#60, isEmpty#61] +Keys [8]: [i_category#52, i_class#53, i_brand#54, i_product_name#55, d_year#56, d_qoy#57, d_moy#58, s_store_id#59] +Functions [1]: [sum(coalesce((ss_sales_price#62 * cast(ss_quantity#63 as decimal(10,0))), 0.00))] +Aggregate Attributes [1]: [sum(coalesce((ss_sales_price#62 * cast(ss_quantity#63 as decimal(10,0))), 0.00))#22] +Results [7]: [i_category#52, i_class#53, i_brand#54, i_product_name#55, d_year#56, d_qoy#57, sum(coalesce((ss_sales_price#62 * cast(ss_quantity#63 as decimal(10,0))), 0.00))#22 AS sumsales#64] + +(29) HashAggregate [codegen id : 16] +Input [7]: [i_category#52, i_class#53, i_brand#54, i_product_name#55, d_year#56, d_qoy#57, sumsales#64] +Keys [6]: [i_category#52, i_class#53, i_brand#54, i_product_name#55, d_year#56, d_qoy#57] +Functions [1]: [partial_sum(sumsales#64)] +Aggregate Attributes [2]: [sum#65, isEmpty#66] +Results [8]: [i_category#52, i_class#53, i_brand#54, i_product_name#55, d_year#56, d_qoy#57, sum#67, isEmpty#68] + +(30) Exchange +Input [8]: [i_category#52, i_class#53, i_brand#54, i_product_name#55, d_year#56, d_qoy#57, sum#67, isEmpty#68] +Arguments: hashpartitioning(i_category#52, i_class#53, i_brand#54, i_product_name#55, d_year#56, d_qoy#57, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(31) HashAggregate [codegen id : 17] +Input [8]: [i_category#52, i_class#53, i_brand#54, i_product_name#55, d_year#56, d_qoy#57, sum#67, isEmpty#68] +Keys [6]: [i_category#52, i_class#53, i_brand#54, i_product_name#55, d_year#56, d_qoy#57] +Functions [1]: [sum(sumsales#64)] +Aggregate Attributes [1]: [sum(sumsales#64)#69] +Results [9]: [i_category#52, i_class#53, i_brand#54, i_product_name#55, d_year#56, d_qoy#57, null AS d_moy#70, null AS s_store_id#71, sum(sumsales#64)#69 AS sumsales#72] + +(32) ReusedExchange [Reuses operator id: 20] +Output [10]: [i_category#73, i_class#74, i_brand#75, i_product_name#76, d_year#77, d_qoy#78, d_moy#79, s_store_id#80, sum#81, isEmpty#82] + +(33) HashAggregate [codegen id : 22] +Input [10]: [i_category#73, i_class#74, i_brand#75, i_product_name#76, d_year#77, d_qoy#78, d_moy#79, s_store_id#80, sum#81, isEmpty#82] +Keys [8]: [i_category#73, i_class#74, i_brand#75, i_product_name#76, d_year#77, d_qoy#78, d_moy#79, s_store_id#80] +Functions [1]: [sum(coalesce((ss_sales_price#83 * cast(ss_quantity#84 as decimal(10,0))), 0.00))] +Aggregate Attributes [1]: [sum(coalesce((ss_sales_price#83 * cast(ss_quantity#84 as decimal(10,0))), 0.00))#22] +Results [6]: [i_category#73, i_class#74, i_brand#75, i_product_name#76, d_year#77, sum(coalesce((ss_sales_price#83 * cast(ss_quantity#84 as decimal(10,0))), 0.00))#22 AS sumsales#85] + +(34) HashAggregate [codegen id : 22] +Input [6]: [i_category#73, i_class#74, i_brand#75, i_product_name#76, d_year#77, sumsales#85] +Keys [5]: [i_category#73, i_class#74, i_brand#75, i_product_name#76, d_year#77] +Functions [1]: [partial_sum(sumsales#85)] +Aggregate Attributes [2]: [sum#86, isEmpty#87] +Results [7]: [i_category#73, i_class#74, i_brand#75, i_product_name#76, d_year#77, sum#88, isEmpty#89] + +(35) Exchange +Input [7]: [i_category#73, i_class#74, i_brand#75, i_product_name#76, d_year#77, sum#88, isEmpty#89] +Arguments: hashpartitioning(i_category#73, i_class#74, i_brand#75, i_product_name#76, d_year#77, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(36) HashAggregate [codegen id : 23] +Input [7]: [i_category#73, i_class#74, i_brand#75, i_product_name#76, d_year#77, sum#88, isEmpty#89] +Keys [5]: [i_category#73, i_class#74, i_brand#75, i_product_name#76, d_year#77] +Functions [1]: [sum(sumsales#85)] +Aggregate Attributes [1]: [sum(sumsales#85)#90] +Results [9]: [i_category#73, i_class#74, i_brand#75, i_product_name#76, d_year#77, null AS d_qoy#91, null AS d_moy#92, null AS s_store_id#93, sum(sumsales#85)#90 AS sumsales#94] + +(37) ReusedExchange [Reuses operator id: 20] +Output [10]: [i_category#95, i_class#96, i_brand#97, i_product_name#98, d_year#99, d_qoy#100, d_moy#101, s_store_id#102, sum#103, isEmpty#104] + +(38) HashAggregate [codegen id : 28] +Input [10]: [i_category#95, i_class#96, i_brand#97, i_product_name#98, d_year#99, d_qoy#100, d_moy#101, s_store_id#102, sum#103, isEmpty#104] +Keys [8]: [i_category#95, i_class#96, i_brand#97, i_product_name#98, d_year#99, d_qoy#100, d_moy#101, s_store_id#102] +Functions [1]: [sum(coalesce((ss_sales_price#105 * cast(ss_quantity#106 as decimal(10,0))), 0.00))] +Aggregate Attributes [1]: [sum(coalesce((ss_sales_price#105 * cast(ss_quantity#106 as decimal(10,0))), 0.00))#22] +Results [5]: [i_category#95, i_class#96, i_brand#97, i_product_name#98, sum(coalesce((ss_sales_price#105 * cast(ss_quantity#106 as decimal(10,0))), 0.00))#22 AS sumsales#107] + +(39) HashAggregate [codegen id : 28] +Input [5]: [i_category#95, i_class#96, i_brand#97, i_product_name#98, sumsales#107] +Keys [4]: [i_category#95, i_class#96, i_brand#97, i_product_name#98] +Functions [1]: [partial_sum(sumsales#107)] +Aggregate Attributes [2]: [sum#108, isEmpty#109] +Results [6]: [i_category#95, i_class#96, i_brand#97, i_product_name#98, sum#110, isEmpty#111] + +(40) Exchange +Input [6]: [i_category#95, i_class#96, i_brand#97, i_product_name#98, sum#110, isEmpty#111] +Arguments: hashpartitioning(i_category#95, i_class#96, i_brand#97, i_product_name#98, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(41) HashAggregate [codegen id : 29] +Input [6]: [i_category#95, i_class#96, i_brand#97, i_product_name#98, sum#110, isEmpty#111] +Keys [4]: [i_category#95, i_class#96, i_brand#97, i_product_name#98] +Functions [1]: [sum(sumsales#107)] +Aggregate Attributes [1]: [sum(sumsales#107)#112] +Results [9]: [i_category#95, i_class#96, i_brand#97, i_product_name#98, null AS d_year#113, null AS d_qoy#114, null AS d_moy#115, null AS s_store_id#116, sum(sumsales#107)#112 AS sumsales#117] + +(42) ReusedExchange [Reuses operator id: 20] +Output [10]: [i_category#118, i_class#119, i_brand#120, i_product_name#121, d_year#122, d_qoy#123, d_moy#124, s_store_id#125, sum#126, isEmpty#127] + +(43) HashAggregate [codegen id : 34] +Input [10]: [i_category#118, i_class#119, i_brand#120, i_product_name#121, d_year#122, d_qoy#123, d_moy#124, s_store_id#125, sum#126, isEmpty#127] +Keys [8]: [i_category#118, i_class#119, i_brand#120, i_product_name#121, d_year#122, d_qoy#123, d_moy#124, s_store_id#125] +Functions [1]: [sum(coalesce((ss_sales_price#128 * cast(ss_quantity#129 as decimal(10,0))), 0.00))] +Aggregate Attributes [1]: [sum(coalesce((ss_sales_price#128 * cast(ss_quantity#129 as decimal(10,0))), 0.00))#22] +Results [4]: [i_category#118, i_class#119, i_brand#120, sum(coalesce((ss_sales_price#128 * cast(ss_quantity#129 as decimal(10,0))), 0.00))#22 AS sumsales#130] + +(44) HashAggregate [codegen id : 34] +Input [4]: [i_category#118, i_class#119, i_brand#120, sumsales#130] +Keys [3]: [i_category#118, i_class#119, i_brand#120] +Functions [1]: [partial_sum(sumsales#130)] +Aggregate Attributes [2]: [sum#131, isEmpty#132] +Results [5]: [i_category#118, i_class#119, i_brand#120, sum#133, isEmpty#134] + +(45) Exchange +Input [5]: [i_category#118, i_class#119, i_brand#120, sum#133, isEmpty#134] +Arguments: hashpartitioning(i_category#118, i_class#119, i_brand#120, 5), ENSURE_REQUIREMENTS, [plan_id=8] + +(46) HashAggregate [codegen id : 35] +Input [5]: [i_category#118, i_class#119, i_brand#120, sum#133, isEmpty#134] +Keys [3]: [i_category#118, i_class#119, i_brand#120] +Functions [1]: [sum(sumsales#130)] +Aggregate Attributes [1]: [sum(sumsales#130)#135] +Results [9]: [i_category#118, i_class#119, i_brand#120, null AS i_product_name#136, null AS d_year#137, null AS d_qoy#138, null AS d_moy#139, null AS s_store_id#140, sum(sumsales#130)#135 AS sumsales#141] + +(47) ReusedExchange [Reuses operator id: 20] +Output [10]: [i_category#142, i_class#143, i_brand#144, i_product_name#145, d_year#146, d_qoy#147, d_moy#148, s_store_id#149, sum#150, isEmpty#151] + +(48) HashAggregate [codegen id : 40] +Input [10]: [i_category#142, i_class#143, i_brand#144, i_product_name#145, d_year#146, d_qoy#147, d_moy#148, s_store_id#149, sum#150, isEmpty#151] +Keys [8]: [i_category#142, i_class#143, i_brand#144, i_product_name#145, d_year#146, d_qoy#147, d_moy#148, s_store_id#149] +Functions [1]: [sum(coalesce((ss_sales_price#152 * cast(ss_quantity#153 as decimal(10,0))), 0.00))] +Aggregate Attributes [1]: [sum(coalesce((ss_sales_price#152 * cast(ss_quantity#153 as decimal(10,0))), 0.00))#22] +Results [3]: [i_category#142, i_class#143, sum(coalesce((ss_sales_price#152 * cast(ss_quantity#153 as decimal(10,0))), 0.00))#22 AS sumsales#154] + +(49) HashAggregate [codegen id : 40] +Input [3]: [i_category#142, i_class#143, sumsales#154] +Keys [2]: [i_category#142, i_class#143] +Functions [1]: [partial_sum(sumsales#154)] +Aggregate Attributes [2]: [sum#155, isEmpty#156] +Results [4]: [i_category#142, i_class#143, sum#157, isEmpty#158] + +(50) Exchange +Input [4]: [i_category#142, i_class#143, sum#157, isEmpty#158] +Arguments: hashpartitioning(i_category#142, i_class#143, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(51) HashAggregate [codegen id : 41] +Input [4]: [i_category#142, i_class#143, sum#157, isEmpty#158] +Keys [2]: [i_category#142, i_class#143] +Functions [1]: [sum(sumsales#154)] +Aggregate Attributes [1]: [sum(sumsales#154)#159] +Results [9]: [i_category#142, i_class#143, null AS i_brand#160, null AS i_product_name#161, null AS d_year#162, null AS d_qoy#163, null AS d_moy#164, null AS s_store_id#165, sum(sumsales#154)#159 AS sumsales#166] + +(52) ReusedExchange [Reuses operator id: 20] +Output [10]: [i_category#167, i_class#168, i_brand#169, i_product_name#170, d_year#171, d_qoy#172, d_moy#173, s_store_id#174, sum#175, isEmpty#176] + +(53) HashAggregate [codegen id : 46] +Input [10]: [i_category#167, i_class#168, i_brand#169, i_product_name#170, d_year#171, d_qoy#172, d_moy#173, s_store_id#174, sum#175, isEmpty#176] +Keys [8]: [i_category#167, i_class#168, i_brand#169, i_product_name#170, d_year#171, d_qoy#172, d_moy#173, s_store_id#174] +Functions [1]: [sum(coalesce((ss_sales_price#177 * cast(ss_quantity#178 as decimal(10,0))), 0.00))] +Aggregate Attributes [1]: [sum(coalesce((ss_sales_price#177 * cast(ss_quantity#178 as decimal(10,0))), 0.00))#22] +Results [2]: [i_category#167, sum(coalesce((ss_sales_price#177 * cast(ss_quantity#178 as decimal(10,0))), 0.00))#22 AS sumsales#179] + +(54) HashAggregate [codegen id : 46] +Input [2]: [i_category#167, sumsales#179] +Keys [1]: [i_category#167] +Functions [1]: [partial_sum(sumsales#179)] +Aggregate Attributes [2]: [sum#180, isEmpty#181] +Results [3]: [i_category#167, sum#182, isEmpty#183] + +(55) Exchange +Input [3]: [i_category#167, sum#182, isEmpty#183] +Arguments: hashpartitioning(i_category#167, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(56) HashAggregate [codegen id : 47] +Input [3]: [i_category#167, sum#182, isEmpty#183] +Keys [1]: [i_category#167] +Functions [1]: [sum(sumsales#179)] +Aggregate Attributes [1]: [sum(sumsales#179)#184] +Results [9]: [i_category#167, null AS i_class#185, null AS i_brand#186, null AS i_product_name#187, null AS d_year#188, null AS d_qoy#189, null AS d_moy#190, null AS s_store_id#191, sum(sumsales#179)#184 AS sumsales#192] + +(57) ReusedExchange [Reuses operator id: 20] +Output [10]: [i_category#193, i_class#194, i_brand#195, i_product_name#196, d_year#197, d_qoy#198, d_moy#199, s_store_id#200, sum#201, isEmpty#202] + +(58) HashAggregate [codegen id : 52] +Input [10]: [i_category#193, i_class#194, i_brand#195, i_product_name#196, d_year#197, d_qoy#198, d_moy#199, s_store_id#200, sum#201, isEmpty#202] +Keys [8]: [i_category#193, i_class#194, i_brand#195, i_product_name#196, d_year#197, d_qoy#198, d_moy#199, s_store_id#200] +Functions [1]: [sum(coalesce((ss_sales_price#203 * cast(ss_quantity#204 as decimal(10,0))), 0.00))] +Aggregate Attributes [1]: [sum(coalesce((ss_sales_price#203 * cast(ss_quantity#204 as decimal(10,0))), 0.00))#22] +Results [1]: [sum(coalesce((ss_sales_price#203 * cast(ss_quantity#204 as decimal(10,0))), 0.00))#22 AS sumsales#205] + +(59) HashAggregate [codegen id : 52] +Input [1]: [sumsales#205] +Keys: [] +Functions [1]: [partial_sum(sumsales#205)] +Aggregate Attributes [2]: [sum#206, isEmpty#207] +Results [2]: [sum#208, isEmpty#209] + +(60) Exchange +Input [2]: [sum#208, isEmpty#209] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=11] + +(61) HashAggregate [codegen id : 53] +Input [2]: [sum#208, isEmpty#209] +Keys: [] +Functions [1]: [sum(sumsales#205)] +Aggregate Attributes [1]: [sum(sumsales#205)#210] +Results [9]: [null AS i_category#211, null AS i_class#212, null AS i_brand#213, null AS i_product_name#214, null AS d_year#215, null AS d_qoy#216, null AS d_moy#217, null AS s_store_id#218, sum(sumsales#205)#210 AS sumsales#219] + +(62) Union + +(63) Sort [codegen id : 54] +Input [9]: [i_category#23, i_class#24, i_brand#25, i_product_name#26, d_year#27, d_qoy#28, d_moy#29, s_store_id#30, sumsales#31] +Arguments: [i_category#23 ASC NULLS FIRST, sumsales#31 DESC NULLS LAST], false, 0 + +(64) WindowGroupLimit +Input [9]: [i_category#23, i_class#24, i_brand#25, i_product_name#26, d_year#27, d_qoy#28, d_moy#29, s_store_id#30, sumsales#31] +Arguments: [i_category#23], [sumsales#31 DESC NULLS LAST], rank(sumsales#31), 100, Partial + +(65) Exchange +Input [9]: [i_category#23, i_class#24, i_brand#25, i_product_name#26, d_year#27, d_qoy#28, d_moy#29, s_store_id#30, sumsales#31] +Arguments: hashpartitioning(i_category#23, 5), ENSURE_REQUIREMENTS, [plan_id=12] + +(66) Sort [codegen id : 55] +Input [9]: [i_category#23, i_class#24, i_brand#25, i_product_name#26, d_year#27, d_qoy#28, d_moy#29, s_store_id#30, sumsales#31] +Arguments: [i_category#23 ASC NULLS FIRST, sumsales#31 DESC NULLS LAST], false, 0 + +(67) WindowGroupLimit +Input [9]: [i_category#23, i_class#24, i_brand#25, i_product_name#26, d_year#27, d_qoy#28, d_moy#29, s_store_id#30, sumsales#31] +Arguments: [i_category#23], [sumsales#31 DESC NULLS LAST], rank(sumsales#31), 100, Final + +(68) Window +Input [9]: [i_category#23, i_class#24, i_brand#25, i_product_name#26, d_year#27, d_qoy#28, d_moy#29, s_store_id#30, sumsales#31] +Arguments: [rank(sumsales#31) windowspecdefinition(i_category#23, sumsales#31 DESC NULLS LAST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rk#220], [i_category#23], [sumsales#31 DESC NULLS LAST] + +(69) Filter [codegen id : 56] +Input [10]: [i_category#23, i_class#24, i_brand#25, i_product_name#26, d_year#27, d_qoy#28, d_moy#29, s_store_id#30, sumsales#31, rk#220] +Condition : (rk#220 <= 100) + +(70) TakeOrderedAndProject +Input [10]: [i_category#23, i_class#24, i_brand#25, i_product_name#26, d_year#27, d_qoy#28, d_moy#29, s_store_id#30, sumsales#31, rk#220] +Arguments: 100, [i_category#23 ASC NULLS FIRST, i_class#24 ASC NULLS FIRST, i_brand#25 ASC NULLS FIRST, i_product_name#26 ASC NULLS FIRST, d_year#27 ASC NULLS FIRST, d_qoy#28 ASC NULLS FIRST, d_moy#29 ASC NULLS FIRST, s_store_id#30 ASC NULLS FIRST, sumsales#31 ASC NULLS FIRST, rk#220 ASC NULLS FIRST], [i_category#23, i_class#24, i_brand#25, i_product_name#26, d_year#27, d_qoy#28, d_moy#29, s_store_id#30, sumsales#31, rk#220] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6 +BroadcastExchange (75) ++- * ColumnarToRow (74) + +- CometProject (73) + +- CometFilter (72) + +- CometScan parquet spark_catalog.default.date_dim (71) + + +(71) Scan parquet spark_catalog.default.date_dim +Output [5]: [d_date_sk#7, d_month_seq#221, d_year#8, d_moy#9, d_qoy#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1212), LessThanOrEqual(d_month_seq,1223), IsNotNull(d_date_sk)] +ReadSchema: struct + +(72) CometFilter +Input [5]: [d_date_sk#7, d_month_seq#221, d_year#8, d_moy#9, d_qoy#10] +Condition : (((isnotnull(d_month_seq#221) AND (d_month_seq#221 >= 1212)) AND (d_month_seq#221 <= 1223)) AND isnotnull(d_date_sk#7)) + +(73) CometProject +Input [5]: [d_date_sk#7, d_month_seq#221, d_year#8, d_moy#9, d_qoy#10] +Arguments: [d_date_sk#7, d_year#8, d_moy#9, d_qoy#10], [d_date_sk#7, d_year#8, d_moy#9, d_qoy#10] + +(74) ColumnarToRow [codegen id : 1] +Input [4]: [d_date_sk#7, d_year#8, d_moy#9, d_qoy#10] + +(75) BroadcastExchange +Input [4]: [d_date_sk#7, d_year#8, d_moy#9, d_qoy#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=13] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q67a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q67a/simplified.txt new file mode 100644 index 0000000000..4d2d3972d9 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q67a/simplified.txt @@ -0,0 +1,127 @@ +TakeOrderedAndProject [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sumsales,rk] + WholeStageCodegen (56) + Filter [rk] + InputAdapter + Window [sumsales,i_category] + WindowGroupLimit [i_category,sumsales] + WholeStageCodegen (55) + Sort [i_category,sumsales] + InputAdapter + Exchange [i_category] #1 + WindowGroupLimit [i_category,sumsales] + WholeStageCodegen (54) + Sort [i_category,sumsales] + InputAdapter + Union + WholeStageCodegen (5) + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sum,isEmpty] [sum(coalesce((ss_sales_price * cast(ss_quantity as decimal(10,0))), 0.00)),i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sumsales,sum,isEmpty] + InputAdapter + Exchange [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id] #2 + WholeStageCodegen (4) + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,ss_sales_price,ss_quantity] [sum,isEmpty,sum,isEmpty] + Project [ss_quantity,ss_sales_price,d_year,d_moy,d_qoy,s_store_id,i_brand,i_class,i_category,i_product_name] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_quantity,ss_sales_price,d_year,d_moy,d_qoy,s_store_id] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,ss_sales_price,d_year,d_moy,d_qoy] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk,ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_quantity,ss_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_year,d_moy,d_qoy] + CometFilter [d_month_seq,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq,d_year,d_moy,d_qoy] + InputAdapter + ReusedExchange [d_date_sk,d_year,d_moy,d_qoy] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_id] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_class,i_category,i_product_name] + WholeStageCodegen (11) + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,sum,isEmpty] [sum(sumsales),s_store_id,sumsales,sum,isEmpty] + InputAdapter + Exchange [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy] #6 + WholeStageCodegen (10) + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,sumsales] [sum,isEmpty,sum,isEmpty] + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sum,isEmpty] [sum(coalesce((ss_sales_price * cast(ss_quantity as decimal(10,0))), 0.00)),sumsales,sum,isEmpty] + InputAdapter + ReusedExchange [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sum,isEmpty] #2 + WholeStageCodegen (17) + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,sum,isEmpty] [sum(sumsales),d_moy,s_store_id,sumsales,sum,isEmpty] + InputAdapter + Exchange [i_category,i_class,i_brand,i_product_name,d_year,d_qoy] #7 + WholeStageCodegen (16) + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,sumsales] [sum,isEmpty,sum,isEmpty] + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sum,isEmpty] [sum(coalesce((ss_sales_price * cast(ss_quantity as decimal(10,0))), 0.00)),sumsales,sum,isEmpty] + InputAdapter + ReusedExchange [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sum,isEmpty] #2 + WholeStageCodegen (23) + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,sum,isEmpty] [sum(sumsales),d_qoy,d_moy,s_store_id,sumsales,sum,isEmpty] + InputAdapter + Exchange [i_category,i_class,i_brand,i_product_name,d_year] #8 + WholeStageCodegen (22) + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,sumsales] [sum,isEmpty,sum,isEmpty] + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sum,isEmpty] [sum(coalesce((ss_sales_price * cast(ss_quantity as decimal(10,0))), 0.00)),sumsales,sum,isEmpty] + InputAdapter + ReusedExchange [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sum,isEmpty] #2 + WholeStageCodegen (29) + HashAggregate [i_category,i_class,i_brand,i_product_name,sum,isEmpty] [sum(sumsales),d_year,d_qoy,d_moy,s_store_id,sumsales,sum,isEmpty] + InputAdapter + Exchange [i_category,i_class,i_brand,i_product_name] #9 + WholeStageCodegen (28) + HashAggregate [i_category,i_class,i_brand,i_product_name,sumsales] [sum,isEmpty,sum,isEmpty] + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sum,isEmpty] [sum(coalesce((ss_sales_price * cast(ss_quantity as decimal(10,0))), 0.00)),sumsales,sum,isEmpty] + InputAdapter + ReusedExchange [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sum,isEmpty] #2 + WholeStageCodegen (35) + HashAggregate [i_category,i_class,i_brand,sum,isEmpty] [sum(sumsales),i_product_name,d_year,d_qoy,d_moy,s_store_id,sumsales,sum,isEmpty] + InputAdapter + Exchange [i_category,i_class,i_brand] #10 + WholeStageCodegen (34) + HashAggregate [i_category,i_class,i_brand,sumsales] [sum,isEmpty,sum,isEmpty] + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sum,isEmpty] [sum(coalesce((ss_sales_price * cast(ss_quantity as decimal(10,0))), 0.00)),sumsales,sum,isEmpty] + InputAdapter + ReusedExchange [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sum,isEmpty] #2 + WholeStageCodegen (41) + HashAggregate [i_category,i_class,sum,isEmpty] [sum(sumsales),i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sumsales,sum,isEmpty] + InputAdapter + Exchange [i_category,i_class] #11 + WholeStageCodegen (40) + HashAggregate [i_category,i_class,sumsales] [sum,isEmpty,sum,isEmpty] + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sum,isEmpty] [sum(coalesce((ss_sales_price * cast(ss_quantity as decimal(10,0))), 0.00)),sumsales,sum,isEmpty] + InputAdapter + ReusedExchange [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sum,isEmpty] #2 + WholeStageCodegen (47) + HashAggregate [i_category,sum,isEmpty] [sum(sumsales),i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sumsales,sum,isEmpty] + InputAdapter + Exchange [i_category] #12 + WholeStageCodegen (46) + HashAggregate [i_category,sumsales] [sum,isEmpty,sum,isEmpty] + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sum,isEmpty] [sum(coalesce((ss_sales_price * cast(ss_quantity as decimal(10,0))), 0.00)),sumsales,sum,isEmpty] + InputAdapter + ReusedExchange [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sum,isEmpty] #2 + WholeStageCodegen (53) + HashAggregate [sum,isEmpty] [sum(sumsales),i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sumsales,sum,isEmpty] + InputAdapter + Exchange #13 + WholeStageCodegen (52) + HashAggregate [sumsales] [sum,isEmpty,sum,isEmpty] + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sum,isEmpty] [sum(coalesce((ss_sales_price * cast(ss_quantity as decimal(10,0))), 0.00)),sumsales,sum,isEmpty] + InputAdapter + ReusedExchange [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sum,isEmpty] #2 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q70a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q70a/explain.txt new file mode 100644 index 0000000000..6a81a2ec1c --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q70a/explain.txt @@ -0,0 +1,368 @@ +== Physical Plan == +TakeOrderedAndProject (56) ++- * Project (55) + +- Window (54) + +- * Sort (53) + +- Exchange (52) + +- * HashAggregate (51) + +- Exchange (50) + +- * HashAggregate (49) + +- Union (48) + :- * HashAggregate (37) + : +- Exchange (36) + : +- * HashAggregate (35) + : +- * Project (34) + : +- * BroadcastHashJoin Inner BuildRight (33) + : :- * Project (6) + : : +- * BroadcastHashJoin Inner BuildRight (5) + : : :- * ColumnarToRow (3) + : : : +- CometFilter (2) + : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : +- ReusedExchange (4) + : +- BroadcastExchange (32) + : +- * BroadcastHashJoin LeftSemi BuildRight (31) + : :- * ColumnarToRow (9) + : : +- CometFilter (8) + : : +- CometScan parquet spark_catalog.default.store (7) + : +- BroadcastExchange (30) + : +- * Project (29) + : +- * Filter (28) + : +- Window (27) + : +- WindowGroupLimit (26) + : +- * Sort (25) + : +- * HashAggregate (24) + : +- Exchange (23) + : +- * HashAggregate (22) + : +- * Project (21) + : +- * BroadcastHashJoin Inner BuildRight (20) + : :- * Project (18) + : : +- * BroadcastHashJoin Inner BuildRight (17) + : : :- * ColumnarToRow (12) + : : : +- CometFilter (11) + : : : +- CometScan parquet spark_catalog.default.store_sales (10) + : : +- BroadcastExchange (16) + : : +- * ColumnarToRow (15) + : : +- CometFilter (14) + : : +- CometScan parquet spark_catalog.default.store (13) + : +- ReusedExchange (19) + :- * HashAggregate (42) + : +- Exchange (41) + : +- * HashAggregate (40) + : +- * HashAggregate (39) + : +- ReusedExchange (38) + +- * HashAggregate (47) + +- Exchange (46) + +- * HashAggregate (45) + +- * HashAggregate (44) + +- ReusedExchange (43) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_store_sk#1, ss_net_profit#2, ss_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#3), dynamicpruningexpression(ss_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(ss_store_sk)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [ss_store_sk#1, ss_net_profit#2, ss_sold_date_sk#3] +Condition : isnotnull(ss_store_sk#1) + +(3) ColumnarToRow [codegen id : 8] +Input [3]: [ss_store_sk#1, ss_net_profit#2, ss_sold_date_sk#3] + +(4) ReusedExchange [Reuses operator id: 61] +Output [1]: [d_date_sk#5] + +(5) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_sold_date_sk#3] +Right keys [1]: [d_date_sk#5] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 8] +Output [2]: [ss_store_sk#1, ss_net_profit#2] +Input [4]: [ss_store_sk#1, ss_net_profit#2, ss_sold_date_sk#3, d_date_sk#5] + +(7) Scan parquet spark_catalog.default.store +Output [3]: [s_store_sk#6, s_county#7, s_state#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(8) CometFilter +Input [3]: [s_store_sk#6, s_county#7, s_state#8] +Condition : isnotnull(s_store_sk#6) + +(9) ColumnarToRow [codegen id : 7] +Input [3]: [s_store_sk#6, s_county#7, s_state#8] + +(10) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_store_sk#9, ss_net_profit#10, ss_sold_date_sk#11] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#11), dynamicpruningexpression(ss_sold_date_sk#11 IN dynamicpruning#12)] +PushedFilters: [IsNotNull(ss_store_sk)] +ReadSchema: struct + +(11) CometFilter +Input [3]: [ss_store_sk#9, ss_net_profit#10, ss_sold_date_sk#11] +Condition : isnotnull(ss_store_sk#9) + +(12) ColumnarToRow [codegen id : 4] +Input [3]: [ss_store_sk#9, ss_net_profit#10, ss_sold_date_sk#11] + +(13) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#13, s_state#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(14) CometFilter +Input [2]: [s_store_sk#13, s_state#14] +Condition : isnotnull(s_store_sk#13) + +(15) ColumnarToRow [codegen id : 2] +Input [2]: [s_store_sk#13, s_state#14] + +(16) BroadcastExchange +Input [2]: [s_store_sk#13, s_state#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(17) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_store_sk#9] +Right keys [1]: [s_store_sk#13] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 4] +Output [3]: [ss_net_profit#10, ss_sold_date_sk#11, s_state#14] +Input [5]: [ss_store_sk#9, ss_net_profit#10, ss_sold_date_sk#11, s_store_sk#13, s_state#14] + +(19) ReusedExchange [Reuses operator id: 61] +Output [1]: [d_date_sk#15] + +(20) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_date_sk#11] +Right keys [1]: [d_date_sk#15] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 4] +Output [2]: [ss_net_profit#10, s_state#14] +Input [4]: [ss_net_profit#10, ss_sold_date_sk#11, s_state#14, d_date_sk#15] + +(22) HashAggregate [codegen id : 4] +Input [2]: [ss_net_profit#10, s_state#14] +Keys [1]: [s_state#14] +Functions [1]: [partial_sum(UnscaledValue(ss_net_profit#10))] +Aggregate Attributes [1]: [sum#16] +Results [2]: [s_state#14, sum#17] + +(23) Exchange +Input [2]: [s_state#14, sum#17] +Arguments: hashpartitioning(s_state#14, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(24) HashAggregate [codegen id : 5] +Input [2]: [s_state#14, sum#17] +Keys [1]: [s_state#14] +Functions [1]: [sum(UnscaledValue(ss_net_profit#10))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_profit#10))#18] +Results [3]: [s_state#14, MakeDecimal(sum(UnscaledValue(ss_net_profit#10))#18,17,2) AS _w0#19, s_state#14] + +(25) Sort [codegen id : 5] +Input [3]: [s_state#14, _w0#19, s_state#14] +Arguments: [s_state#14 ASC NULLS FIRST, _w0#19 DESC NULLS LAST], false, 0 + +(26) WindowGroupLimit +Input [3]: [s_state#14, _w0#19, s_state#14] +Arguments: [s_state#14], [_w0#19 DESC NULLS LAST], rank(_w0#19), 5, Final + +(27) Window +Input [3]: [s_state#14, _w0#19, s_state#14] +Arguments: [rank(_w0#19) windowspecdefinition(s_state#14, _w0#19 DESC NULLS LAST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS ranking#20], [s_state#14], [_w0#19 DESC NULLS LAST] + +(28) Filter [codegen id : 6] +Input [4]: [s_state#14, _w0#19, s_state#14, ranking#20] +Condition : (ranking#20 <= 5) + +(29) Project [codegen id : 6] +Output [1]: [s_state#14] +Input [4]: [s_state#14, _w0#19, s_state#14, ranking#20] + +(30) BroadcastExchange +Input [1]: [s_state#14] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=3] + +(31) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [s_state#8] +Right keys [1]: [s_state#14] +Join type: LeftSemi +Join condition: None + +(32) BroadcastExchange +Input [3]: [s_store_sk#6, s_county#7, s_state#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(33) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_store_sk#1] +Right keys [1]: [s_store_sk#6] +Join type: Inner +Join condition: None + +(34) Project [codegen id : 8] +Output [3]: [ss_net_profit#2, s_county#7, s_state#8] +Input [5]: [ss_store_sk#1, ss_net_profit#2, s_store_sk#6, s_county#7, s_state#8] + +(35) HashAggregate [codegen id : 8] +Input [3]: [ss_net_profit#2, s_county#7, s_state#8] +Keys [2]: [s_state#8, s_county#7] +Functions [1]: [partial_sum(UnscaledValue(ss_net_profit#2))] +Aggregate Attributes [1]: [sum#21] +Results [3]: [s_state#8, s_county#7, sum#22] + +(36) Exchange +Input [3]: [s_state#8, s_county#7, sum#22] +Arguments: hashpartitioning(s_state#8, s_county#7, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(37) HashAggregate [codegen id : 9] +Input [3]: [s_state#8, s_county#7, sum#22] +Keys [2]: [s_state#8, s_county#7] +Functions [1]: [sum(UnscaledValue(ss_net_profit#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_profit#2))#23] +Results [6]: [cast(MakeDecimal(sum(UnscaledValue(ss_net_profit#2))#23,17,2) as decimal(27,2)) AS total_sum#24, s_state#8, s_county#7, 0 AS g_state#25, 0 AS g_county#26, 0 AS lochierarchy#27] + +(38) ReusedExchange [Reuses operator id: 36] +Output [3]: [s_state#28, s_county#29, sum#30] + +(39) HashAggregate [codegen id : 18] +Input [3]: [s_state#28, s_county#29, sum#30] +Keys [2]: [s_state#28, s_county#29] +Functions [1]: [sum(UnscaledValue(ss_net_profit#31))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_profit#31))#23] +Results [2]: [MakeDecimal(sum(UnscaledValue(ss_net_profit#31))#23,17,2) AS total_sum#32, s_state#28] + +(40) HashAggregate [codegen id : 18] +Input [2]: [total_sum#32, s_state#28] +Keys [1]: [s_state#28] +Functions [1]: [partial_sum(total_sum#32)] +Aggregate Attributes [2]: [sum#33, isEmpty#34] +Results [3]: [s_state#28, sum#35, isEmpty#36] + +(41) Exchange +Input [3]: [s_state#28, sum#35, isEmpty#36] +Arguments: hashpartitioning(s_state#28, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(42) HashAggregate [codegen id : 19] +Input [3]: [s_state#28, sum#35, isEmpty#36] +Keys [1]: [s_state#28] +Functions [1]: [sum(total_sum#32)] +Aggregate Attributes [1]: [sum(total_sum#32)#37] +Results [6]: [sum(total_sum#32)#37 AS total_sum#38, s_state#28, null AS s_county#39, 0 AS g_state#40, 1 AS g_county#41, 1 AS lochierarchy#42] + +(43) ReusedExchange [Reuses operator id: 36] +Output [3]: [s_state#43, s_county#44, sum#45] + +(44) HashAggregate [codegen id : 28] +Input [3]: [s_state#43, s_county#44, sum#45] +Keys [2]: [s_state#43, s_county#44] +Functions [1]: [sum(UnscaledValue(ss_net_profit#46))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_profit#46))#23] +Results [1]: [MakeDecimal(sum(UnscaledValue(ss_net_profit#46))#23,17,2) AS total_sum#47] + +(45) HashAggregate [codegen id : 28] +Input [1]: [total_sum#47] +Keys: [] +Functions [1]: [partial_sum(total_sum#47)] +Aggregate Attributes [2]: [sum#48, isEmpty#49] +Results [2]: [sum#50, isEmpty#51] + +(46) Exchange +Input [2]: [sum#50, isEmpty#51] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=7] + +(47) HashAggregate [codegen id : 29] +Input [2]: [sum#50, isEmpty#51] +Keys: [] +Functions [1]: [sum(total_sum#47)] +Aggregate Attributes [1]: [sum(total_sum#47)#52] +Results [6]: [sum(total_sum#47)#52 AS total_sum#53, null AS s_state#54, null AS s_county#55, 1 AS g_state#56, 1 AS g_county#57, 2 AS lochierarchy#58] + +(48) Union + +(49) HashAggregate [codegen id : 30] +Input [6]: [total_sum#24, s_state#8, s_county#7, g_state#25, g_county#26, lochierarchy#27] +Keys [6]: [total_sum#24, s_state#8, s_county#7, g_state#25, g_county#26, lochierarchy#27] +Functions: [] +Aggregate Attributes: [] +Results [6]: [total_sum#24, s_state#8, s_county#7, g_state#25, g_county#26, lochierarchy#27] + +(50) Exchange +Input [6]: [total_sum#24, s_state#8, s_county#7, g_state#25, g_county#26, lochierarchy#27] +Arguments: hashpartitioning(total_sum#24, s_state#8, s_county#7, g_state#25, g_county#26, lochierarchy#27, 5), ENSURE_REQUIREMENTS, [plan_id=8] + +(51) HashAggregate [codegen id : 31] +Input [6]: [total_sum#24, s_state#8, s_county#7, g_state#25, g_county#26, lochierarchy#27] +Keys [6]: [total_sum#24, s_state#8, s_county#7, g_state#25, g_county#26, lochierarchy#27] +Functions: [] +Aggregate Attributes: [] +Results [5]: [total_sum#24, s_state#8, s_county#7, lochierarchy#27, CASE WHEN (g_county#26 = 0) THEN s_state#8 END AS _w0#59] + +(52) Exchange +Input [5]: [total_sum#24, s_state#8, s_county#7, lochierarchy#27, _w0#59] +Arguments: hashpartitioning(lochierarchy#27, _w0#59, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(53) Sort [codegen id : 32] +Input [5]: [total_sum#24, s_state#8, s_county#7, lochierarchy#27, _w0#59] +Arguments: [lochierarchy#27 ASC NULLS FIRST, _w0#59 ASC NULLS FIRST, total_sum#24 DESC NULLS LAST], false, 0 + +(54) Window +Input [5]: [total_sum#24, s_state#8, s_county#7, lochierarchy#27, _w0#59] +Arguments: [rank(total_sum#24) windowspecdefinition(lochierarchy#27, _w0#59, total_sum#24 DESC NULLS LAST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rank_within_parent#60], [lochierarchy#27, _w0#59], [total_sum#24 DESC NULLS LAST] + +(55) Project [codegen id : 33] +Output [5]: [total_sum#24, s_state#8, s_county#7, lochierarchy#27, rank_within_parent#60] +Input [6]: [total_sum#24, s_state#8, s_county#7, lochierarchy#27, _w0#59, rank_within_parent#60] + +(56) TakeOrderedAndProject +Input [5]: [total_sum#24, s_state#8, s_county#7, lochierarchy#27, rank_within_parent#60] +Arguments: 100, [lochierarchy#27 DESC NULLS LAST, CASE WHEN (lochierarchy#27 = 0) THEN s_state#8 END ASC NULLS FIRST, rank_within_parent#60 ASC NULLS FIRST], [total_sum#24, s_state#8, s_county#7, lochierarchy#27, rank_within_parent#60] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (61) ++- * ColumnarToRow (60) + +- CometProject (59) + +- CometFilter (58) + +- CometScan parquet spark_catalog.default.date_dim (57) + + +(57) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#5, d_month_seq#61] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1212), LessThanOrEqual(d_month_seq,1223), IsNotNull(d_date_sk)] +ReadSchema: struct + +(58) CometFilter +Input [2]: [d_date_sk#5, d_month_seq#61] +Condition : (((isnotnull(d_month_seq#61) AND (d_month_seq#61 >= 1212)) AND (d_month_seq#61 <= 1223)) AND isnotnull(d_date_sk#5)) + +(59) CometProject +Input [2]: [d_date_sk#5, d_month_seq#61] +Arguments: [d_date_sk#5], [d_date_sk#5] + +(60) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#5] + +(61) BroadcastExchange +Input [1]: [d_date_sk#5] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=10] + +Subquery:2 Hosting operator id = 10 Hosting Expression = ss_sold_date_sk#11 IN dynamicpruning#4 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q70a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q70a/simplified.txt new file mode 100644 index 0000000000..2fd04badf8 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q70a/simplified.txt @@ -0,0 +1,100 @@ +TakeOrderedAndProject [lochierarchy,s_state,rank_within_parent,total_sum,s_county] + WholeStageCodegen (33) + Project [total_sum,s_state,s_county,lochierarchy,rank_within_parent] + InputAdapter + Window [total_sum,lochierarchy,_w0] + WholeStageCodegen (32) + Sort [lochierarchy,_w0,total_sum] + InputAdapter + Exchange [lochierarchy,_w0] #1 + WholeStageCodegen (31) + HashAggregate [total_sum,s_state,s_county,g_state,g_county,lochierarchy] [_w0] + InputAdapter + Exchange [total_sum,s_state,s_county,g_state,g_county,lochierarchy] #2 + WholeStageCodegen (30) + HashAggregate [total_sum,s_state,s_county,g_state,g_county,lochierarchy] + InputAdapter + Union + WholeStageCodegen (9) + HashAggregate [s_state,s_county,sum] [sum(UnscaledValue(ss_net_profit)),total_sum,g_state,g_county,lochierarchy,sum] + InputAdapter + Exchange [s_state,s_county] #3 + WholeStageCodegen (8) + HashAggregate [s_state,s_county,ss_net_profit] [sum,sum] + Project [ss_net_profit,s_county,s_state] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_store_sk,ss_net_profit] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_store_sk,ss_net_profit,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_month_seq,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (7) + BroadcastHashJoin [s_state,s_state] + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk,s_county,s_state] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (6) + Project [s_state] + Filter [ranking] + InputAdapter + Window [_w0,s_state] + WindowGroupLimit [s_state,_w0] + WholeStageCodegen (5) + Sort [s_state,_w0] + HashAggregate [sum] [sum(UnscaledValue(ss_net_profit)),_w0,s_state,sum] + InputAdapter + Exchange [s_state] #7 + WholeStageCodegen (4) + HashAggregate [s_state,ss_net_profit] [sum,sum] + Project [ss_net_profit,s_state] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_net_profit,ss_sold_date_sk,s_state] + BroadcastHashJoin [ss_store_sk,s_store_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_store_sk,ss_net_profit,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk,s_state] + InputAdapter + ReusedExchange [d_date_sk] #4 + WholeStageCodegen (19) + HashAggregate [s_state,sum,isEmpty] [sum(total_sum),total_sum,s_county,g_state,g_county,lochierarchy,sum,isEmpty] + InputAdapter + Exchange [s_state] #9 + WholeStageCodegen (18) + HashAggregate [s_state,total_sum] [sum,isEmpty,sum,isEmpty] + HashAggregate [s_state,s_county,sum] [sum(UnscaledValue(ss_net_profit)),total_sum,sum] + InputAdapter + ReusedExchange [s_state,s_county,sum] #3 + WholeStageCodegen (29) + HashAggregate [sum,isEmpty] [sum(total_sum),total_sum,s_state,s_county,g_state,g_county,lochierarchy,sum,isEmpty] + InputAdapter + Exchange #10 + WholeStageCodegen (28) + HashAggregate [total_sum] [sum,isEmpty,sum,isEmpty] + HashAggregate [s_state,s_county,sum] [sum(UnscaledValue(ss_net_profit)),total_sum,sum] + InputAdapter + ReusedExchange [s_state,s_county,sum] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q72/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q72/explain.txt new file mode 100644 index 0000000000..c885738383 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q72/explain.txt @@ -0,0 +1,433 @@ +== Physical Plan == +TakeOrderedAndProject (70) ++- * HashAggregate (69) + +- Exchange (68) + +- * HashAggregate (67) + +- * Project (66) + +- * SortMergeJoin LeftOuter (65) + :- * Sort (58) + : +- Exchange (57) + : +- * Project (56) + : +- * BroadcastHashJoin LeftOuter BuildRight (55) + : :- * Project (50) + : : +- * BroadcastHashJoin Inner BuildRight (49) + : : :- * Project (44) + : : : +- * BroadcastHashJoin Inner BuildRight (43) + : : : :- * Project (38) + : : : : +- * BroadcastHashJoin Inner BuildRight (37) + : : : : :- * Project (35) + : : : : : +- * BroadcastHashJoin Inner BuildRight (34) + : : : : : :- * Project (28) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (27) + : : : : : : :- * Project (21) + : : : : : : : +- * BroadcastHashJoin Inner BuildRight (20) + : : : : : : : :- * Project (15) + : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (14) + : : : : : : : : :- * Project (9) + : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : : : : : : :- * ColumnarToRow (3) + : : : : : : : : : : +- CometFilter (2) + : : : : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) + : : : : : : : : : +- BroadcastExchange (7) + : : : : : : : : : +- * ColumnarToRow (6) + : : : : : : : : : +- CometFilter (5) + : : : : : : : : : +- CometScan parquet spark_catalog.default.inventory (4) + : : : : : : : : +- BroadcastExchange (13) + : : : : : : : : +- * ColumnarToRow (12) + : : : : : : : : +- CometFilter (11) + : : : : : : : : +- CometScan parquet spark_catalog.default.warehouse (10) + : : : : : : : +- BroadcastExchange (19) + : : : : : : : +- * ColumnarToRow (18) + : : : : : : : +- CometFilter (17) + : : : : : : : +- CometScan parquet spark_catalog.default.item (16) + : : : : : : +- BroadcastExchange (26) + : : : : : : +- * ColumnarToRow (25) + : : : : : : +- CometProject (24) + : : : : : : +- CometFilter (23) + : : : : : : +- CometScan parquet spark_catalog.default.customer_demographics (22) + : : : : : +- BroadcastExchange (33) + : : : : : +- * ColumnarToRow (32) + : : : : : +- CometProject (31) + : : : : : +- CometFilter (30) + : : : : : +- CometScan parquet spark_catalog.default.household_demographics (29) + : : : : +- ReusedExchange (36) + : : : +- BroadcastExchange (42) + : : : +- * ColumnarToRow (41) + : : : +- CometFilter (40) + : : : +- CometScan parquet spark_catalog.default.date_dim (39) + : : +- BroadcastExchange (48) + : : +- * ColumnarToRow (47) + : : +- CometFilter (46) + : : +- CometScan parquet spark_catalog.default.date_dim (45) + : +- BroadcastExchange (54) + : +- * ColumnarToRow (53) + : +- CometFilter (52) + : +- CometScan parquet spark_catalog.default.promotion (51) + +- * Sort (64) + +- Exchange (63) + +- * ColumnarToRow (62) + +- CometProject (61) + +- CometFilter (60) + +- CometScan parquet spark_catalog.default.catalog_returns (59) + + +(1) Scan parquet spark_catalog.default.catalog_sales +Output [8]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_quantity#7, cs_sold_date_sk#8] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#8), dynamicpruningexpression(cs_sold_date_sk#8 IN dynamicpruning#9)] +PushedFilters: [IsNotNull(cs_quantity), IsNotNull(cs_item_sk), IsNotNull(cs_bill_cdemo_sk), IsNotNull(cs_bill_hdemo_sk), IsNotNull(cs_ship_date_sk)] +ReadSchema: struct + +(2) CometFilter +Input [8]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_quantity#7, cs_sold_date_sk#8] +Condition : ((((isnotnull(cs_quantity#7) AND isnotnull(cs_item_sk#4)) AND isnotnull(cs_bill_cdemo_sk#2)) AND isnotnull(cs_bill_hdemo_sk#3)) AND isnotnull(cs_ship_date_sk#1)) + +(3) ColumnarToRow [codegen id : 10] +Input [8]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_quantity#7, cs_sold_date_sk#8] + +(4) Scan parquet spark_catalog.default.inventory +Output [4]: [inv_item_sk#10, inv_warehouse_sk#11, inv_quantity_on_hand#12, inv_date_sk#13] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(inv_date_sk#13)] +PushedFilters: [IsNotNull(inv_quantity_on_hand), IsNotNull(inv_item_sk), IsNotNull(inv_warehouse_sk)] +ReadSchema: struct + +(5) CometFilter +Input [4]: [inv_item_sk#10, inv_warehouse_sk#11, inv_quantity_on_hand#12, inv_date_sk#13] +Condition : ((isnotnull(inv_quantity_on_hand#12) AND isnotnull(inv_item_sk#10)) AND isnotnull(inv_warehouse_sk#11)) + +(6) ColumnarToRow [codegen id : 1] +Input [4]: [inv_item_sk#10, inv_warehouse_sk#11, inv_quantity_on_hand#12, inv_date_sk#13] + +(7) BroadcastExchange +Input [4]: [inv_item_sk#10, inv_warehouse_sk#11, inv_quantity_on_hand#12, inv_date_sk#13] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_item_sk#4] +Right keys [1]: [inv_item_sk#10] +Join type: Inner +Join condition: (inv_quantity_on_hand#12 < cs_quantity#7) + +(9) Project [codegen id : 10] +Output [9]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_warehouse_sk#11, inv_date_sk#13] +Input [12]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_quantity#7, cs_sold_date_sk#8, inv_item_sk#10, inv_warehouse_sk#11, inv_quantity_on_hand#12, inv_date_sk#13] + +(10) Scan parquet spark_catalog.default.warehouse +Output [2]: [w_warehouse_sk#14, w_warehouse_name#15] +Batched: true +Location [not included in comparison]/{warehouse_dir}/warehouse] +PushedFilters: [IsNotNull(w_warehouse_sk)] +ReadSchema: struct + +(11) CometFilter +Input [2]: [w_warehouse_sk#14, w_warehouse_name#15] +Condition : isnotnull(w_warehouse_sk#14) + +(12) ColumnarToRow [codegen id : 2] +Input [2]: [w_warehouse_sk#14, w_warehouse_name#15] + +(13) BroadcastExchange +Input [2]: [w_warehouse_sk#14, w_warehouse_name#15] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(14) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [inv_warehouse_sk#11] +Right keys [1]: [w_warehouse_sk#14] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 10] +Output [9]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15] +Input [11]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_warehouse_sk#11, inv_date_sk#13, w_warehouse_sk#14, w_warehouse_name#15] + +(16) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#16, i_item_desc#17] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(17) CometFilter +Input [2]: [i_item_sk#16, i_item_desc#17] +Condition : isnotnull(i_item_sk#16) + +(18) ColumnarToRow [codegen id : 3] +Input [2]: [i_item_sk#16, i_item_desc#17] + +(19) BroadcastExchange +Input [2]: [i_item_sk#16, i_item_desc#17] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(20) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_item_sk#4] +Right keys [1]: [i_item_sk#16] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 10] +Output [10]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17] +Input [11]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15, i_item_sk#16, i_item_desc#17] + +(22) Scan parquet spark_catalog.default.customer_demographics +Output [2]: [cd_demo_sk#18, cd_marital_status#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_marital_status), EqualTo(cd_marital_status,M), IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(23) CometFilter +Input [2]: [cd_demo_sk#18, cd_marital_status#19] +Condition : ((isnotnull(cd_marital_status#19) AND (cd_marital_status#19 = M)) AND isnotnull(cd_demo_sk#18)) + +(24) CometProject +Input [2]: [cd_demo_sk#18, cd_marital_status#19] +Arguments: [cd_demo_sk#18], [cd_demo_sk#18] + +(25) ColumnarToRow [codegen id : 4] +Input [1]: [cd_demo_sk#18] + +(26) BroadcastExchange +Input [1]: [cd_demo_sk#18] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(27) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_bill_cdemo_sk#2] +Right keys [1]: [cd_demo_sk#18] +Join type: Inner +Join condition: None + +(28) Project [codegen id : 10] +Output [9]: [cs_ship_date_sk#1, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17] +Input [11]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17, cd_demo_sk#18] + +(29) Scan parquet spark_catalog.default.household_demographics +Output [2]: [hd_demo_sk#20, hd_buy_potential#21] +Batched: true +Location [not included in comparison]/{warehouse_dir}/household_demographics] +PushedFilters: [IsNotNull(hd_buy_potential), EqualTo(hd_buy_potential,1001-5000 ), IsNotNull(hd_demo_sk)] +ReadSchema: struct + +(30) CometFilter +Input [2]: [hd_demo_sk#20, hd_buy_potential#21] +Condition : ((isnotnull(hd_buy_potential#21) AND (hd_buy_potential#21 = 1001-5000 )) AND isnotnull(hd_demo_sk#20)) + +(31) CometProject +Input [2]: [hd_demo_sk#20, hd_buy_potential#21] +Arguments: [hd_demo_sk#20], [hd_demo_sk#20] + +(32) ColumnarToRow [codegen id : 5] +Input [1]: [hd_demo_sk#20] + +(33) BroadcastExchange +Input [1]: [hd_demo_sk#20] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +(34) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_bill_hdemo_sk#3] +Right keys [1]: [hd_demo_sk#20] +Join type: Inner +Join condition: None + +(35) Project [codegen id : 10] +Output [8]: [cs_ship_date_sk#1, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17] +Input [10]: [cs_ship_date_sk#1, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17, hd_demo_sk#20] + +(36) ReusedExchange [Reuses operator id: 75] +Output [3]: [d_date_sk#22, d_date#23, d_week_seq#24] + +(37) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_sold_date_sk#8] +Right keys [1]: [d_date_sk#22] +Join type: Inner +Join condition: None + +(38) Project [codegen id : 10] +Output [9]: [cs_ship_date_sk#1, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17, d_date#23, d_week_seq#24] +Input [11]: [cs_ship_date_sk#1, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17, d_date_sk#22, d_date#23, d_week_seq#24] + +(39) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#25, d_week_seq#26] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_week_seq), IsNotNull(d_date_sk)] +ReadSchema: struct + +(40) CometFilter +Input [2]: [d_date_sk#25, d_week_seq#26] +Condition : (isnotnull(d_week_seq#26) AND isnotnull(d_date_sk#25)) + +(41) ColumnarToRow [codegen id : 7] +Input [2]: [d_date_sk#25, d_week_seq#26] + +(42) BroadcastExchange +Input [2]: [d_date_sk#25, d_week_seq#26] +Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[1, int, false] as bigint), 32) | (cast(input[0, int, false] as bigint) & 4294967295))),false), [plan_id=6] + +(43) BroadcastHashJoin [codegen id : 10] +Left keys [2]: [d_week_seq#24, inv_date_sk#13] +Right keys [2]: [d_week_seq#26, d_date_sk#25] +Join type: Inner +Join condition: None + +(44) Project [codegen id : 10] +Output [8]: [cs_ship_date_sk#1, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_date#23, d_week_seq#24] +Input [11]: [cs_ship_date_sk#1, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17, d_date#23, d_week_seq#24, d_date_sk#25, d_week_seq#26] + +(45) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#27, d_date#28] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), IsNotNull(d_date_sk)] +ReadSchema: struct + +(46) CometFilter +Input [2]: [d_date_sk#27, d_date#28] +Condition : (isnotnull(d_date#28) AND isnotnull(d_date_sk#27)) + +(47) ColumnarToRow [codegen id : 8] +Input [2]: [d_date_sk#27, d_date#28] + +(48) BroadcastExchange +Input [2]: [d_date_sk#27, d_date#28] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=7] + +(49) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_ship_date_sk#1] +Right keys [1]: [d_date_sk#27] +Join type: Inner +Join condition: (d_date#28 > date_add(d_date#23, 5)) + +(50) Project [codegen id : 10] +Output [6]: [cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_week_seq#24] +Input [10]: [cs_ship_date_sk#1, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_date#23, d_week_seq#24, d_date_sk#27, d_date#28] + +(51) Scan parquet spark_catalog.default.promotion +Output [1]: [p_promo_sk#29] +Batched: true +Location [not included in comparison]/{warehouse_dir}/promotion] +PushedFilters: [IsNotNull(p_promo_sk)] +ReadSchema: struct + +(52) CometFilter +Input [1]: [p_promo_sk#29] +Condition : isnotnull(p_promo_sk#29) + +(53) ColumnarToRow [codegen id : 9] +Input [1]: [p_promo_sk#29] + +(54) BroadcastExchange +Input [1]: [p_promo_sk#29] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8] + +(55) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_promo_sk#5] +Right keys [1]: [p_promo_sk#29] +Join type: LeftOuter +Join condition: None + +(56) Project [codegen id : 10] +Output [5]: [cs_item_sk#4, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_week_seq#24] +Input [7]: [cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_week_seq#24, p_promo_sk#29] + +(57) Exchange +Input [5]: [cs_item_sk#4, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_week_seq#24] +Arguments: hashpartitioning(cs_item_sk#4, cs_order_number#6, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(58) Sort [codegen id : 11] +Input [5]: [cs_item_sk#4, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_week_seq#24] +Arguments: [cs_item_sk#4 ASC NULLS FIRST, cs_order_number#6 ASC NULLS FIRST], false, 0 + +(59) Scan parquet spark_catalog.default.catalog_returns +Output [3]: [cr_item_sk#30, cr_order_number#31, cr_returned_date_sk#32] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_returns] +PushedFilters: [IsNotNull(cr_item_sk), IsNotNull(cr_order_number)] +ReadSchema: struct + +(60) CometFilter +Input [3]: [cr_item_sk#30, cr_order_number#31, cr_returned_date_sk#32] +Condition : (isnotnull(cr_item_sk#30) AND isnotnull(cr_order_number#31)) + +(61) CometProject +Input [3]: [cr_item_sk#30, cr_order_number#31, cr_returned_date_sk#32] +Arguments: [cr_item_sk#30, cr_order_number#31], [cr_item_sk#30, cr_order_number#31] + +(62) ColumnarToRow [codegen id : 12] +Input [2]: [cr_item_sk#30, cr_order_number#31] + +(63) Exchange +Input [2]: [cr_item_sk#30, cr_order_number#31] +Arguments: hashpartitioning(cr_item_sk#30, cr_order_number#31, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(64) Sort [codegen id : 13] +Input [2]: [cr_item_sk#30, cr_order_number#31] +Arguments: [cr_item_sk#30 ASC NULLS FIRST, cr_order_number#31 ASC NULLS FIRST], false, 0 + +(65) SortMergeJoin [codegen id : 14] +Left keys [2]: [cs_item_sk#4, cs_order_number#6] +Right keys [2]: [cr_item_sk#30, cr_order_number#31] +Join type: LeftOuter +Join condition: None + +(66) Project [codegen id : 14] +Output [3]: [w_warehouse_name#15, i_item_desc#17, d_week_seq#24] +Input [7]: [cs_item_sk#4, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_week_seq#24, cr_item_sk#30, cr_order_number#31] + +(67) HashAggregate [codegen id : 14] +Input [3]: [w_warehouse_name#15, i_item_desc#17, d_week_seq#24] +Keys [3]: [i_item_desc#17, w_warehouse_name#15, d_week_seq#24] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#33] +Results [4]: [i_item_desc#17, w_warehouse_name#15, d_week_seq#24, count#34] + +(68) Exchange +Input [4]: [i_item_desc#17, w_warehouse_name#15, d_week_seq#24, count#34] +Arguments: hashpartitioning(i_item_desc#17, w_warehouse_name#15, d_week_seq#24, 5), ENSURE_REQUIREMENTS, [plan_id=11] + +(69) HashAggregate [codegen id : 15] +Input [4]: [i_item_desc#17, w_warehouse_name#15, d_week_seq#24, count#34] +Keys [3]: [i_item_desc#17, w_warehouse_name#15, d_week_seq#24] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#35] +Results [6]: [i_item_desc#17, w_warehouse_name#15, d_week_seq#24, count(1)#35 AS no_promo#36, count(1)#35 AS promo#37, count(1)#35 AS total_cnt#38] + +(70) TakeOrderedAndProject +Input [6]: [i_item_desc#17, w_warehouse_name#15, d_week_seq#24, no_promo#36, promo#37, total_cnt#38] +Arguments: 100, [total_cnt#38 DESC NULLS LAST, i_item_desc#17 ASC NULLS FIRST, w_warehouse_name#15 ASC NULLS FIRST, d_week_seq#24 ASC NULLS FIRST], [i_item_desc#17, w_warehouse_name#15, d_week_seq#24, no_promo#36, promo#37, total_cnt#38] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#8 IN dynamicpruning#9 +BroadcastExchange (75) ++- * ColumnarToRow (74) + +- CometProject (73) + +- CometFilter (72) + +- CometScan parquet spark_catalog.default.date_dim (71) + + +(71) Scan parquet spark_catalog.default.date_dim +Output [4]: [d_date_sk#22, d_date#23, d_week_seq#24, d_year#39] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk), IsNotNull(d_week_seq), IsNotNull(d_date)] +ReadSchema: struct + +(72) CometFilter +Input [4]: [d_date_sk#22, d_date#23, d_week_seq#24, d_year#39] +Condition : ((((isnotnull(d_year#39) AND (d_year#39 = 2001)) AND isnotnull(d_date_sk#22)) AND isnotnull(d_week_seq#24)) AND isnotnull(d_date#23)) + +(73) CometProject +Input [4]: [d_date_sk#22, d_date#23, d_week_seq#24, d_year#39] +Arguments: [d_date_sk#22, d_date#23, d_week_seq#24], [d_date_sk#22, d_date#23, d_week_seq#24] + +(74) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#22, d_date#23, d_week_seq#24] + +(75) BroadcastExchange +Input [3]: [d_date_sk#22, d_date#23, d_week_seq#24] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=12] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q72/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q72/simplified.txt new file mode 100644 index 0000000000..17fc9dee7e --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q72/simplified.txt @@ -0,0 +1,116 @@ +TakeOrderedAndProject [total_cnt,i_item_desc,w_warehouse_name,d_week_seq,no_promo,promo] + WholeStageCodegen (15) + HashAggregate [i_item_desc,w_warehouse_name,d_week_seq,count] [count(1),no_promo,promo,total_cnt,count] + InputAdapter + Exchange [i_item_desc,w_warehouse_name,d_week_seq] #1 + WholeStageCodegen (14) + HashAggregate [i_item_desc,w_warehouse_name,d_week_seq] [count,count] + Project [w_warehouse_name,i_item_desc,d_week_seq] + SortMergeJoin [cs_item_sk,cs_order_number,cr_item_sk,cr_order_number] + InputAdapter + WholeStageCodegen (11) + Sort [cs_item_sk,cs_order_number] + InputAdapter + Exchange [cs_item_sk,cs_order_number] #2 + WholeStageCodegen (10) + Project [cs_item_sk,cs_order_number,w_warehouse_name,i_item_desc,d_week_seq] + BroadcastHashJoin [cs_promo_sk,p_promo_sk] + Project [cs_item_sk,cs_promo_sk,cs_order_number,w_warehouse_name,i_item_desc,d_week_seq] + BroadcastHashJoin [cs_ship_date_sk,d_date_sk,d_date,d_date] + Project [cs_ship_date_sk,cs_item_sk,cs_promo_sk,cs_order_number,w_warehouse_name,i_item_desc,d_date,d_week_seq] + BroadcastHashJoin [d_week_seq,inv_date_sk,d_week_seq,d_date_sk] + Project [cs_ship_date_sk,cs_item_sk,cs_promo_sk,cs_order_number,inv_date_sk,w_warehouse_name,i_item_desc,d_date,d_week_seq] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_ship_date_sk,cs_item_sk,cs_promo_sk,cs_order_number,cs_sold_date_sk,inv_date_sk,w_warehouse_name,i_item_desc] + BroadcastHashJoin [cs_bill_hdemo_sk,hd_demo_sk] + Project [cs_ship_date_sk,cs_bill_hdemo_sk,cs_item_sk,cs_promo_sk,cs_order_number,cs_sold_date_sk,inv_date_sk,w_warehouse_name,i_item_desc] + BroadcastHashJoin [cs_bill_cdemo_sk,cd_demo_sk] + Project [cs_ship_date_sk,cs_bill_cdemo_sk,cs_bill_hdemo_sk,cs_item_sk,cs_promo_sk,cs_order_number,cs_sold_date_sk,inv_date_sk,w_warehouse_name,i_item_desc] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Project [cs_ship_date_sk,cs_bill_cdemo_sk,cs_bill_hdemo_sk,cs_item_sk,cs_promo_sk,cs_order_number,cs_sold_date_sk,inv_date_sk,w_warehouse_name] + BroadcastHashJoin [inv_warehouse_sk,w_warehouse_sk] + Project [cs_ship_date_sk,cs_bill_cdemo_sk,cs_bill_hdemo_sk,cs_item_sk,cs_promo_sk,cs_order_number,cs_sold_date_sk,inv_warehouse_sk,inv_date_sk] + BroadcastHashJoin [cs_item_sk,inv_item_sk,inv_quantity_on_hand,cs_quantity] + ColumnarToRow + InputAdapter + CometFilter [cs_quantity,cs_item_sk,cs_bill_cdemo_sk,cs_bill_hdemo_sk,cs_ship_date_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_ship_date_sk,cs_bill_cdemo_sk,cs_bill_hdemo_sk,cs_item_sk,cs_promo_sk,cs_order_number,cs_quantity,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_date,d_week_seq] + CometFilter [d_year,d_date_sk,d_week_seq,d_date] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date,d_week_seq,d_year] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [inv_quantity_on_hand,inv_item_sk,inv_warehouse_sk] + CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [w_warehouse_sk] + CometScan parquet spark_catalog.default.warehouse [w_warehouse_sk,w_warehouse_name] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_desc] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (4) + ColumnarToRow + InputAdapter + CometProject [cd_demo_sk] + CometFilter [cd_marital_status,cd_demo_sk] + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_marital_status] + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (5) + ColumnarToRow + InputAdapter + CometProject [hd_demo_sk] + CometFilter [hd_buy_potential,hd_demo_sk] + CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_buy_potential] + InputAdapter + ReusedExchange [d_date_sk,d_date,d_week_seq] #3 + InputAdapter + BroadcastExchange #9 + WholeStageCodegen (7) + ColumnarToRow + InputAdapter + CometFilter [d_week_seq,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_week_seq] + InputAdapter + BroadcastExchange #10 + WholeStageCodegen (8) + ColumnarToRow + InputAdapter + CometFilter [d_date,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (9) + ColumnarToRow + InputAdapter + CometFilter [p_promo_sk] + CometScan parquet spark_catalog.default.promotion [p_promo_sk] + InputAdapter + WholeStageCodegen (13) + Sort [cr_item_sk,cr_order_number] + InputAdapter + Exchange [cr_item_sk,cr_order_number] #12 + WholeStageCodegen (12) + ColumnarToRow + InputAdapter + CometProject [cr_item_sk,cr_order_number] + CometFilter [cr_item_sk,cr_order_number] + CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_returned_date_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q74/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q74/explain.txt new file mode 100644 index 0000000000..ad8c33ca1d --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q74/explain.txt @@ -0,0 +1,477 @@ +== Physical Plan == +TakeOrderedAndProject (71) ++- * Project (70) + +- * BroadcastHashJoin Inner BuildRight (69) + :- * Project (52) + : +- * BroadcastHashJoin Inner BuildRight (51) + : :- * BroadcastHashJoin Inner BuildRight (33) + : : :- * Filter (16) + : : : +- * HashAggregate (15) + : : : +- Exchange (14) + : : : +- * HashAggregate (13) + : : : +- * Project (12) + : : : +- * BroadcastHashJoin Inner BuildRight (11) + : : : :- * Project (9) + : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) + : : : : : +- CometScan parquet spark_catalog.default.customer (1) + : : : : +- BroadcastExchange (7) + : : : : +- * ColumnarToRow (6) + : : : : +- CometFilter (5) + : : : : +- CometScan parquet spark_catalog.default.store_sales (4) + : : : +- ReusedExchange (10) + : : +- BroadcastExchange (32) + : : +- * HashAggregate (31) + : : +- Exchange (30) + : : +- * HashAggregate (29) + : : +- * Project (28) + : : +- * BroadcastHashJoin Inner BuildRight (27) + : : :- * Project (25) + : : : +- * BroadcastHashJoin Inner BuildRight (24) + : : : :- * ColumnarToRow (19) + : : : : +- CometFilter (18) + : : : : +- CometScan parquet spark_catalog.default.customer (17) + : : : +- BroadcastExchange (23) + : : : +- * ColumnarToRow (22) + : : : +- CometFilter (21) + : : : +- CometScan parquet spark_catalog.default.store_sales (20) + : : +- ReusedExchange (26) + : +- BroadcastExchange (50) + : +- * Filter (49) + : +- * HashAggregate (48) + : +- Exchange (47) + : +- * HashAggregate (46) + : +- * Project (45) + : +- * BroadcastHashJoin Inner BuildRight (44) + : :- * Project (42) + : : +- * BroadcastHashJoin Inner BuildRight (41) + : : :- * ColumnarToRow (36) + : : : +- CometFilter (35) + : : : +- CometScan parquet spark_catalog.default.customer (34) + : : +- BroadcastExchange (40) + : : +- * ColumnarToRow (39) + : : +- CometFilter (38) + : : +- CometScan parquet spark_catalog.default.web_sales (37) + : +- ReusedExchange (43) + +- BroadcastExchange (68) + +- * HashAggregate (67) + +- Exchange (66) + +- * HashAggregate (65) + +- * Project (64) + +- * BroadcastHashJoin Inner BuildRight (63) + :- * Project (61) + : +- * BroadcastHashJoin Inner BuildRight (60) + : :- * ColumnarToRow (55) + : : +- CometFilter (54) + : : +- CometScan parquet spark_catalog.default.customer (53) + : +- BroadcastExchange (59) + : +- * ColumnarToRow (58) + : +- CometFilter (57) + : +- CometScan parquet spark_catalog.default.web_sales (56) + +- ReusedExchange (62) + + +(1) Scan parquet spark_catalog.default.customer +Output [4]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(2) CometFilter +Input [4]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4] +Condition : (isnotnull(c_customer_sk#1) AND isnotnull(c_customer_id#2)) + +(3) ColumnarToRow [codegen id : 3] +Input [4]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4] + +(4) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_customer_sk#5, ss_net_paid#6, ss_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sold_date_sk#7 IN dynamicpruning#8)] +PushedFilters: [IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(5) CometFilter +Input [3]: [ss_customer_sk#5, ss_net_paid#6, ss_sold_date_sk#7] +Condition : isnotnull(ss_customer_sk#5) + +(6) ColumnarToRow [codegen id : 1] +Input [3]: [ss_customer_sk#5, ss_net_paid#6, ss_sold_date_sk#7] + +(7) BroadcastExchange +Input [3]: [ss_customer_sk#5, ss_net_paid#6, ss_sold_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [c_customer_sk#1] +Right keys [1]: [ss_customer_sk#5] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 3] +Output [5]: [c_customer_id#2, c_first_name#3, c_last_name#4, ss_net_paid#6, ss_sold_date_sk#7] +Input [7]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4, ss_customer_sk#5, ss_net_paid#6, ss_sold_date_sk#7] + +(10) ReusedExchange [Reuses operator id: 75] +Output [2]: [d_date_sk#9, d_year#10] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_sold_date_sk#7] +Right keys [1]: [d_date_sk#9] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [5]: [c_customer_id#2, c_first_name#3, c_last_name#4, ss_net_paid#6, d_year#10] +Input [7]: [c_customer_id#2, c_first_name#3, c_last_name#4, ss_net_paid#6, ss_sold_date_sk#7, d_date_sk#9, d_year#10] + +(13) HashAggregate [codegen id : 3] +Input [5]: [c_customer_id#2, c_first_name#3, c_last_name#4, ss_net_paid#6, d_year#10] +Keys [4]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#10] +Functions [1]: [partial_sum(UnscaledValue(ss_net_paid#6))] +Aggregate Attributes [1]: [sum#11] +Results [5]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#10, sum#12] + +(14) Exchange +Input [5]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#10, sum#12] +Arguments: hashpartitioning(c_customer_id#2, c_first_name#3, c_last_name#4, d_year#10, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 16] +Input [5]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#10, sum#12] +Keys [4]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#10] +Functions [1]: [sum(UnscaledValue(ss_net_paid#6))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_paid#6))#13] +Results [2]: [c_customer_id#2 AS customer_id#14, MakeDecimal(sum(UnscaledValue(ss_net_paid#6))#13,17,2) AS year_total#15] + +(16) Filter [codegen id : 16] +Input [2]: [customer_id#14, year_total#15] +Condition : (isnotnull(year_total#15) AND (year_total#15 > 0.00)) + +(17) Scan parquet spark_catalog.default.customer +Output [4]: [c_customer_sk#16, c_customer_id#17, c_first_name#18, c_last_name#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(18) CometFilter +Input [4]: [c_customer_sk#16, c_customer_id#17, c_first_name#18, c_last_name#19] +Condition : (isnotnull(c_customer_sk#16) AND isnotnull(c_customer_id#17)) + +(19) ColumnarToRow [codegen id : 6] +Input [4]: [c_customer_sk#16, c_customer_id#17, c_first_name#18, c_last_name#19] + +(20) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_customer_sk#20, ss_net_paid#21, ss_sold_date_sk#22] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#22), dynamicpruningexpression(ss_sold_date_sk#22 IN dynamicpruning#23)] +PushedFilters: [IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(21) CometFilter +Input [3]: [ss_customer_sk#20, ss_net_paid#21, ss_sold_date_sk#22] +Condition : isnotnull(ss_customer_sk#20) + +(22) ColumnarToRow [codegen id : 4] +Input [3]: [ss_customer_sk#20, ss_net_paid#21, ss_sold_date_sk#22] + +(23) BroadcastExchange +Input [3]: [ss_customer_sk#20, ss_net_paid#21, ss_sold_date_sk#22] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [c_customer_sk#16] +Right keys [1]: [ss_customer_sk#20] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 6] +Output [5]: [c_customer_id#17, c_first_name#18, c_last_name#19, ss_net_paid#21, ss_sold_date_sk#22] +Input [7]: [c_customer_sk#16, c_customer_id#17, c_first_name#18, c_last_name#19, ss_customer_sk#20, ss_net_paid#21, ss_sold_date_sk#22] + +(26) ReusedExchange [Reuses operator id: 79] +Output [2]: [d_date_sk#24, d_year#25] + +(27) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_sold_date_sk#22] +Right keys [1]: [d_date_sk#24] +Join type: Inner +Join condition: None + +(28) Project [codegen id : 6] +Output [5]: [c_customer_id#17, c_first_name#18, c_last_name#19, ss_net_paid#21, d_year#25] +Input [7]: [c_customer_id#17, c_first_name#18, c_last_name#19, ss_net_paid#21, ss_sold_date_sk#22, d_date_sk#24, d_year#25] + +(29) HashAggregate [codegen id : 6] +Input [5]: [c_customer_id#17, c_first_name#18, c_last_name#19, ss_net_paid#21, d_year#25] +Keys [4]: [c_customer_id#17, c_first_name#18, c_last_name#19, d_year#25] +Functions [1]: [partial_sum(UnscaledValue(ss_net_paid#21))] +Aggregate Attributes [1]: [sum#26] +Results [5]: [c_customer_id#17, c_first_name#18, c_last_name#19, d_year#25, sum#27] + +(30) Exchange +Input [5]: [c_customer_id#17, c_first_name#18, c_last_name#19, d_year#25, sum#27] +Arguments: hashpartitioning(c_customer_id#17, c_first_name#18, c_last_name#19, d_year#25, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(31) HashAggregate [codegen id : 7] +Input [5]: [c_customer_id#17, c_first_name#18, c_last_name#19, d_year#25, sum#27] +Keys [4]: [c_customer_id#17, c_first_name#18, c_last_name#19, d_year#25] +Functions [1]: [sum(UnscaledValue(ss_net_paid#21))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_paid#21))#13] +Results [4]: [c_customer_id#17 AS customer_id#28, c_first_name#18 AS customer_first_name#29, c_last_name#19 AS customer_last_name#30, MakeDecimal(sum(UnscaledValue(ss_net_paid#21))#13,17,2) AS year_total#31] + +(32) BroadcastExchange +Input [4]: [customer_id#28, customer_first_name#29, customer_last_name#30, year_total#31] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=5] + +(33) BroadcastHashJoin [codegen id : 16] +Left keys [1]: [customer_id#14] +Right keys [1]: [customer_id#28] +Join type: Inner +Join condition: None + +(34) Scan parquet spark_catalog.default.customer +Output [4]: [c_customer_sk#32, c_customer_id#33, c_first_name#34, c_last_name#35] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(35) CometFilter +Input [4]: [c_customer_sk#32, c_customer_id#33, c_first_name#34, c_last_name#35] +Condition : (isnotnull(c_customer_sk#32) AND isnotnull(c_customer_id#33)) + +(36) ColumnarToRow [codegen id : 10] +Input [4]: [c_customer_sk#32, c_customer_id#33, c_first_name#34, c_last_name#35] + +(37) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_bill_customer_sk#36, ws_net_paid#37, ws_sold_date_sk#38] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#38), dynamicpruningexpression(ws_sold_date_sk#38 IN dynamicpruning#39)] +PushedFilters: [IsNotNull(ws_bill_customer_sk)] +ReadSchema: struct + +(38) CometFilter +Input [3]: [ws_bill_customer_sk#36, ws_net_paid#37, ws_sold_date_sk#38] +Condition : isnotnull(ws_bill_customer_sk#36) + +(39) ColumnarToRow [codegen id : 8] +Input [3]: [ws_bill_customer_sk#36, ws_net_paid#37, ws_sold_date_sk#38] + +(40) BroadcastExchange +Input [3]: [ws_bill_customer_sk#36, ws_net_paid#37, ws_sold_date_sk#38] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6] + +(41) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [c_customer_sk#32] +Right keys [1]: [ws_bill_customer_sk#36] +Join type: Inner +Join condition: None + +(42) Project [codegen id : 10] +Output [5]: [c_customer_id#33, c_first_name#34, c_last_name#35, ws_net_paid#37, ws_sold_date_sk#38] +Input [7]: [c_customer_sk#32, c_customer_id#33, c_first_name#34, c_last_name#35, ws_bill_customer_sk#36, ws_net_paid#37, ws_sold_date_sk#38] + +(43) ReusedExchange [Reuses operator id: 75] +Output [2]: [d_date_sk#40, d_year#41] + +(44) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [ws_sold_date_sk#38] +Right keys [1]: [d_date_sk#40] +Join type: Inner +Join condition: None + +(45) Project [codegen id : 10] +Output [5]: [c_customer_id#33, c_first_name#34, c_last_name#35, ws_net_paid#37, d_year#41] +Input [7]: [c_customer_id#33, c_first_name#34, c_last_name#35, ws_net_paid#37, ws_sold_date_sk#38, d_date_sk#40, d_year#41] + +(46) HashAggregate [codegen id : 10] +Input [5]: [c_customer_id#33, c_first_name#34, c_last_name#35, ws_net_paid#37, d_year#41] +Keys [4]: [c_customer_id#33, c_first_name#34, c_last_name#35, d_year#41] +Functions [1]: [partial_sum(UnscaledValue(ws_net_paid#37))] +Aggregate Attributes [1]: [sum#42] +Results [5]: [c_customer_id#33, c_first_name#34, c_last_name#35, d_year#41, sum#43] + +(47) Exchange +Input [5]: [c_customer_id#33, c_first_name#34, c_last_name#35, d_year#41, sum#43] +Arguments: hashpartitioning(c_customer_id#33, c_first_name#34, c_last_name#35, d_year#41, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(48) HashAggregate [codegen id : 11] +Input [5]: [c_customer_id#33, c_first_name#34, c_last_name#35, d_year#41, sum#43] +Keys [4]: [c_customer_id#33, c_first_name#34, c_last_name#35, d_year#41] +Functions [1]: [sum(UnscaledValue(ws_net_paid#37))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_net_paid#37))#44] +Results [2]: [c_customer_id#33 AS customer_id#45, MakeDecimal(sum(UnscaledValue(ws_net_paid#37))#44,17,2) AS year_total#46] + +(49) Filter [codegen id : 11] +Input [2]: [customer_id#45, year_total#46] +Condition : (isnotnull(year_total#46) AND (year_total#46 > 0.00)) + +(50) BroadcastExchange +Input [2]: [customer_id#45, year_total#46] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=8] + +(51) BroadcastHashJoin [codegen id : 16] +Left keys [1]: [customer_id#14] +Right keys [1]: [customer_id#45] +Join type: Inner +Join condition: None + +(52) Project [codegen id : 16] +Output [7]: [customer_id#14, year_total#15, customer_id#28, customer_first_name#29, customer_last_name#30, year_total#31, year_total#46] +Input [8]: [customer_id#14, year_total#15, customer_id#28, customer_first_name#29, customer_last_name#30, year_total#31, customer_id#45, year_total#46] + +(53) Scan parquet spark_catalog.default.customer +Output [4]: [c_customer_sk#47, c_customer_id#48, c_first_name#49, c_last_name#50] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(54) CometFilter +Input [4]: [c_customer_sk#47, c_customer_id#48, c_first_name#49, c_last_name#50] +Condition : (isnotnull(c_customer_sk#47) AND isnotnull(c_customer_id#48)) + +(55) ColumnarToRow [codegen id : 14] +Input [4]: [c_customer_sk#47, c_customer_id#48, c_first_name#49, c_last_name#50] + +(56) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_bill_customer_sk#51, ws_net_paid#52, ws_sold_date_sk#53] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#53), dynamicpruningexpression(ws_sold_date_sk#53 IN dynamicpruning#54)] +PushedFilters: [IsNotNull(ws_bill_customer_sk)] +ReadSchema: struct + +(57) CometFilter +Input [3]: [ws_bill_customer_sk#51, ws_net_paid#52, ws_sold_date_sk#53] +Condition : isnotnull(ws_bill_customer_sk#51) + +(58) ColumnarToRow [codegen id : 12] +Input [3]: [ws_bill_customer_sk#51, ws_net_paid#52, ws_sold_date_sk#53] + +(59) BroadcastExchange +Input [3]: [ws_bill_customer_sk#51, ws_net_paid#52, ws_sold_date_sk#53] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=9] + +(60) BroadcastHashJoin [codegen id : 14] +Left keys [1]: [c_customer_sk#47] +Right keys [1]: [ws_bill_customer_sk#51] +Join type: Inner +Join condition: None + +(61) Project [codegen id : 14] +Output [5]: [c_customer_id#48, c_first_name#49, c_last_name#50, ws_net_paid#52, ws_sold_date_sk#53] +Input [7]: [c_customer_sk#47, c_customer_id#48, c_first_name#49, c_last_name#50, ws_bill_customer_sk#51, ws_net_paid#52, ws_sold_date_sk#53] + +(62) ReusedExchange [Reuses operator id: 79] +Output [2]: [d_date_sk#55, d_year#56] + +(63) BroadcastHashJoin [codegen id : 14] +Left keys [1]: [ws_sold_date_sk#53] +Right keys [1]: [d_date_sk#55] +Join type: Inner +Join condition: None + +(64) Project [codegen id : 14] +Output [5]: [c_customer_id#48, c_first_name#49, c_last_name#50, ws_net_paid#52, d_year#56] +Input [7]: [c_customer_id#48, c_first_name#49, c_last_name#50, ws_net_paid#52, ws_sold_date_sk#53, d_date_sk#55, d_year#56] + +(65) HashAggregate [codegen id : 14] +Input [5]: [c_customer_id#48, c_first_name#49, c_last_name#50, ws_net_paid#52, d_year#56] +Keys [4]: [c_customer_id#48, c_first_name#49, c_last_name#50, d_year#56] +Functions [1]: [partial_sum(UnscaledValue(ws_net_paid#52))] +Aggregate Attributes [1]: [sum#57] +Results [5]: [c_customer_id#48, c_first_name#49, c_last_name#50, d_year#56, sum#58] + +(66) Exchange +Input [5]: [c_customer_id#48, c_first_name#49, c_last_name#50, d_year#56, sum#58] +Arguments: hashpartitioning(c_customer_id#48, c_first_name#49, c_last_name#50, d_year#56, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(67) HashAggregate [codegen id : 15] +Input [5]: [c_customer_id#48, c_first_name#49, c_last_name#50, d_year#56, sum#58] +Keys [4]: [c_customer_id#48, c_first_name#49, c_last_name#50, d_year#56] +Functions [1]: [sum(UnscaledValue(ws_net_paid#52))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_net_paid#52))#44] +Results [2]: [c_customer_id#48 AS customer_id#59, MakeDecimal(sum(UnscaledValue(ws_net_paid#52))#44,17,2) AS year_total#60] + +(68) BroadcastExchange +Input [2]: [customer_id#59, year_total#60] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=11] + +(69) BroadcastHashJoin [codegen id : 16] +Left keys [1]: [customer_id#14] +Right keys [1]: [customer_id#59] +Join type: Inner +Join condition: (CASE WHEN (year_total#46 > 0.00) THEN (year_total#60 / year_total#46) END > CASE WHEN (year_total#15 > 0.00) THEN (year_total#31 / year_total#15) END) + +(70) Project [codegen id : 16] +Output [3]: [customer_id#28, customer_first_name#29, customer_last_name#30] +Input [9]: [customer_id#14, year_total#15, customer_id#28, customer_first_name#29, customer_last_name#30, year_total#31, year_total#46, customer_id#59, year_total#60] + +(71) TakeOrderedAndProject +Input [3]: [customer_id#28, customer_first_name#29, customer_last_name#30] +Arguments: 100, [customer_first_name#29 ASC NULLS FIRST, customer_id#28 ASC NULLS FIRST, customer_last_name#30 ASC NULLS FIRST], [customer_id#28, customer_first_name#29, customer_last_name#30] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (75) ++- * ColumnarToRow (74) + +- CometFilter (73) + +- CometScan parquet spark_catalog.default.date_dim (72) + + +(72) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#9, d_year#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), In(d_year, [2001,2002]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(73) CometFilter +Input [2]: [d_date_sk#9, d_year#10] +Condition : (((isnotnull(d_year#10) AND (d_year#10 = 2001)) AND d_year#10 IN (2001,2002)) AND isnotnull(d_date_sk#9)) + +(74) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#9, d_year#10] + +(75) BroadcastExchange +Input [2]: [d_date_sk#9, d_year#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=12] + +Subquery:2 Hosting operator id = 20 Hosting Expression = ss_sold_date_sk#22 IN dynamicpruning#23 +BroadcastExchange (79) ++- * ColumnarToRow (78) + +- CometFilter (77) + +- CometScan parquet spark_catalog.default.date_dim (76) + + +(76) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#24, d_year#25] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2002), In(d_year, [2001,2002]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(77) CometFilter +Input [2]: [d_date_sk#24, d_year#25] +Condition : (((isnotnull(d_year#25) AND (d_year#25 = 2002)) AND d_year#25 IN (2001,2002)) AND isnotnull(d_date_sk#24)) + +(78) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#24, d_year#25] + +(79) BroadcastExchange +Input [2]: [d_date_sk#24, d_year#25] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=13] + +Subquery:3 Hosting operator id = 37 Hosting Expression = ws_sold_date_sk#38 IN dynamicpruning#8 + +Subquery:4 Hosting operator id = 56 Hosting Expression = ws_sold_date_sk#53 IN dynamicpruning#23 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q74/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q74/simplified.txt new file mode 100644 index 0000000000..26989b0c00 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q74/simplified.txt @@ -0,0 +1,122 @@ +TakeOrderedAndProject [customer_first_name,customer_id,customer_last_name] + WholeStageCodegen (16) + Project [customer_id,customer_first_name,customer_last_name] + BroadcastHashJoin [customer_id,customer_id,year_total,year_total,year_total,year_total] + Project [customer_id,year_total,customer_id,customer_first_name,customer_last_name,year_total,year_total] + BroadcastHashJoin [customer_id,customer_id] + BroadcastHashJoin [customer_id,customer_id] + Filter [year_total] + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,sum] [sum(UnscaledValue(ss_net_paid)),customer_id,year_total,sum] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,d_year] #1 + WholeStageCodegen (3) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,ss_net_paid] [sum,sum] + Project [c_customer_id,c_first_name,c_last_name,ss_net_paid,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,ss_net_paid,ss_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk] + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_net_paid,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk,d_year] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (7) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,sum] [sum(UnscaledValue(ss_net_paid)),customer_id,customer_first_name,customer_last_name,year_total,sum] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,d_year] #5 + WholeStageCodegen (6) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,ss_net_paid] [sum,sum] + Project [c_customer_id,c_first_name,c_last_name,ss_net_paid,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,ss_net_paid,ss_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (4) + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk] + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_net_paid,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #7 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk,d_year] #7 + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (11) + Filter [year_total] + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,sum] [sum(UnscaledValue(ws_net_paid)),customer_id,year_total,sum] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,d_year] #9 + WholeStageCodegen (10) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,ws_net_paid] [sum,sum] + Project [c_customer_id,c_first_name,c_last_name,ws_net_paid,d_year] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,ws_net_paid,ws_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name] + InputAdapter + BroadcastExchange #10 + WholeStageCodegen (8) + ColumnarToRow + InputAdapter + CometFilter [ws_bill_customer_sk] + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_net_paid,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk,d_year] #3 + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (15) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,sum] [sum(UnscaledValue(ws_net_paid)),customer_id,year_total,sum] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,d_year] #12 + WholeStageCodegen (14) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,ws_net_paid] [sum,sum] + Project [c_customer_id,c_first_name,c_last_name,ws_net_paid,d_year] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,ws_net_paid,ws_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name] + InputAdapter + BroadcastExchange #13 + WholeStageCodegen (12) + ColumnarToRow + InputAdapter + CometFilter [ws_bill_customer_sk] + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_net_paid,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk,d_year] #7 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q75/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q75/explain.txt new file mode 100644 index 0000000000..5c8480a96a --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q75/explain.txt @@ -0,0 +1,779 @@ +== Physical Plan == +TakeOrderedAndProject (129) ++- * Project (128) + +- * SortMergeJoin Inner (127) + :- * Sort (71) + : +- Exchange (70) + : +- * Filter (69) + : +- * HashAggregate (68) + : +- Exchange (67) + : +- * HashAggregate (66) + : +- * HashAggregate (65) + : +- Exchange (64) + : +- * HashAggregate (63) + : +- Union (62) + : :- * Project (23) + : : +- * SortMergeJoin LeftOuter (22) + : : :- * Sort (15) + : : : +- Exchange (14) + : : : +- * Project (13) + : : : +- * BroadcastHashJoin Inner BuildRight (12) + : : : :- * Project (10) + : : : : +- * BroadcastHashJoin Inner BuildRight (9) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) + : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) + : : : : +- BroadcastExchange (8) + : : : : +- * ColumnarToRow (7) + : : : : +- CometProject (6) + : : : : +- CometFilter (5) + : : : : +- CometScan parquet spark_catalog.default.item (4) + : : : +- ReusedExchange (11) + : : +- * Sort (21) + : : +- Exchange (20) + : : +- * ColumnarToRow (19) + : : +- CometProject (18) + : : +- CometFilter (17) + : : +- CometScan parquet spark_catalog.default.catalog_returns (16) + : :- * Project (42) + : : +- * SortMergeJoin LeftOuter (41) + : : :- * Sort (34) + : : : +- Exchange (33) + : : : +- * Project (32) + : : : +- * BroadcastHashJoin Inner BuildRight (31) + : : : :- * Project (29) + : : : : +- * BroadcastHashJoin Inner BuildRight (28) + : : : : :- * ColumnarToRow (26) + : : : : : +- CometFilter (25) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (24) + : : : : +- ReusedExchange (27) + : : : +- ReusedExchange (30) + : : +- * Sort (40) + : : +- Exchange (39) + : : +- * ColumnarToRow (38) + : : +- CometProject (37) + : : +- CometFilter (36) + : : +- CometScan parquet spark_catalog.default.store_returns (35) + : +- * Project (61) + : +- * SortMergeJoin LeftOuter (60) + : :- * Sort (53) + : : +- Exchange (52) + : : +- * Project (51) + : : +- * BroadcastHashJoin Inner BuildRight (50) + : : :- * Project (48) + : : : +- * BroadcastHashJoin Inner BuildRight (47) + : : : :- * ColumnarToRow (45) + : : : : +- CometFilter (44) + : : : : +- CometScan parquet spark_catalog.default.web_sales (43) + : : : +- ReusedExchange (46) + : : +- ReusedExchange (49) + : +- * Sort (59) + : +- Exchange (58) + : +- * ColumnarToRow (57) + : +- CometProject (56) + : +- CometFilter (55) + : +- CometScan parquet spark_catalog.default.web_returns (54) + +- * Sort (126) + +- Exchange (125) + +- * Filter (124) + +- * HashAggregate (123) + +- Exchange (122) + +- * HashAggregate (121) + +- * HashAggregate (120) + +- Exchange (119) + +- * HashAggregate (118) + +- Union (117) + :- * Project (86) + : +- * SortMergeJoin LeftOuter (85) + : :- * Sort (82) + : : +- Exchange (81) + : : +- * Project (80) + : : +- * BroadcastHashJoin Inner BuildRight (79) + : : :- * Project (77) + : : : +- * BroadcastHashJoin Inner BuildRight (76) + : : : :- * ColumnarToRow (74) + : : : : +- CometFilter (73) + : : : : +- CometScan parquet spark_catalog.default.catalog_sales (72) + : : : +- ReusedExchange (75) + : : +- ReusedExchange (78) + : +- * Sort (84) + : +- ReusedExchange (83) + :- * Project (101) + : +- * SortMergeJoin LeftOuter (100) + : :- * Sort (97) + : : +- Exchange (96) + : : +- * Project (95) + : : +- * BroadcastHashJoin Inner BuildRight (94) + : : :- * Project (92) + : : : +- * BroadcastHashJoin Inner BuildRight (91) + : : : :- * ColumnarToRow (89) + : : : : +- CometFilter (88) + : : : : +- CometScan parquet spark_catalog.default.store_sales (87) + : : : +- ReusedExchange (90) + : : +- ReusedExchange (93) + : +- * Sort (99) + : +- ReusedExchange (98) + +- * Project (116) + +- * SortMergeJoin LeftOuter (115) + :- * Sort (112) + : +- Exchange (111) + : +- * Project (110) + : +- * BroadcastHashJoin Inner BuildRight (109) + : :- * Project (107) + : : +- * BroadcastHashJoin Inner BuildRight (106) + : : :- * ColumnarToRow (104) + : : : +- CometFilter (103) + : : : +- CometScan parquet spark_catalog.default.web_sales (102) + : : +- ReusedExchange (105) + : +- ReusedExchange (108) + +- * Sort (114) + +- ReusedExchange (113) + + +(1) Scan parquet spark_catalog.default.catalog_sales +Output [5]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, cs_sold_date_sk#5] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#5), dynamicpruningexpression(cs_sold_date_sk#5 IN dynamicpruning#6)] +PushedFilters: [IsNotNull(cs_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [5]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, cs_sold_date_sk#5] +Condition : isnotnull(cs_item_sk#1) + +(3) ColumnarToRow [codegen id : 3] +Input [5]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, cs_sold_date_sk#5] + +(4) Scan parquet spark_catalog.default.item +Output [6]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_category#11, i_manufact_id#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_category), EqualTo(i_category,Books ), IsNotNull(i_item_sk), IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id), IsNotNull(i_manufact_id)] +ReadSchema: struct + +(5) CometFilter +Input [6]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_category#11, i_manufact_id#12] +Condition : ((((((isnotnull(i_category#11) AND (i_category#11 = Books )) AND isnotnull(i_item_sk#7)) AND isnotnull(i_brand_id#8)) AND isnotnull(i_class_id#9)) AND isnotnull(i_category_id#10)) AND isnotnull(i_manufact_id#12)) + +(6) CometProject +Input [6]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_category#11, i_manufact_id#12] +Arguments: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12], [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] + +(7) ColumnarToRow [codegen id : 1] +Input [5]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] + +(8) BroadcastExchange +Input [5]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cs_item_sk#1] +Right keys [1]: [i_item_sk#7] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 3] +Output [9]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, cs_sold_date_sk#5, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] +Input [10]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, cs_sold_date_sk#5, i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] + +(11) ReusedExchange [Reuses operator id: 133] +Output [2]: [d_date_sk#13, d_year#14] + +(12) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cs_sold_date_sk#5] +Right keys [1]: [d_date_sk#13] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 3] +Output [9]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, d_year#14] +Input [11]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, cs_sold_date_sk#5, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, d_date_sk#13, d_year#14] + +(14) Exchange +Input [9]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, d_year#14] +Arguments: hashpartitioning(cs_order_number#2, cs_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) Sort [codegen id : 4] +Input [9]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, d_year#14] +Arguments: [cs_order_number#2 ASC NULLS FIRST, cs_item_sk#1 ASC NULLS FIRST], false, 0 + +(16) Scan parquet spark_catalog.default.catalog_returns +Output [5]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18, cr_returned_date_sk#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_returns] +PushedFilters: [IsNotNull(cr_order_number), IsNotNull(cr_item_sk)] +ReadSchema: struct + +(17) CometFilter +Input [5]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18, cr_returned_date_sk#19] +Condition : (isnotnull(cr_order_number#16) AND isnotnull(cr_item_sk#15)) + +(18) CometProject +Input [5]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18, cr_returned_date_sk#19] +Arguments: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18], [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18] + +(19) ColumnarToRow [codegen id : 5] +Input [4]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18] + +(20) Exchange +Input [4]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18] +Arguments: hashpartitioning(cr_order_number#16, cr_item_sk#15, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(21) Sort [codegen id : 6] +Input [4]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18] +Arguments: [cr_order_number#16 ASC NULLS FIRST, cr_item_sk#15 ASC NULLS FIRST], false, 0 + +(22) SortMergeJoin [codegen id : 7] +Left keys [2]: [cs_order_number#2, cs_item_sk#1] +Right keys [2]: [cr_order_number#16, cr_item_sk#15] +Join type: LeftOuter +Join condition: None + +(23) Project [codegen id : 7] +Output [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, (cs_quantity#3 - coalesce(cr_return_quantity#17, 0)) AS sales_cnt#20, (cs_ext_sales_price#4 - coalesce(cr_return_amount#18, 0.00)) AS sales_amt#21] +Input [13]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, d_year#14, cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18] + +(24) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, ss_sold_date_sk#26] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#26), dynamicpruningexpression(ss_sold_date_sk#26 IN dynamicpruning#27)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(25) CometFilter +Input [5]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, ss_sold_date_sk#26] +Condition : isnotnull(ss_item_sk#22) + +(26) ColumnarToRow [codegen id : 10] +Input [5]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, ss_sold_date_sk#26] + +(27) ReusedExchange [Reuses operator id: 8] +Output [5]: [i_item_sk#28, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32] + +(28) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [ss_item_sk#22] +Right keys [1]: [i_item_sk#28] +Join type: Inner +Join condition: None + +(29) Project [codegen id : 10] +Output [9]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, ss_sold_date_sk#26, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32] +Input [10]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, ss_sold_date_sk#26, i_item_sk#28, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32] + +(30) ReusedExchange [Reuses operator id: 133] +Output [2]: [d_date_sk#33, d_year#34] + +(31) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [ss_sold_date_sk#26] +Right keys [1]: [d_date_sk#33] +Join type: Inner +Join condition: None + +(32) Project [codegen id : 10] +Output [9]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32, d_year#34] +Input [11]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, ss_sold_date_sk#26, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32, d_date_sk#33, d_year#34] + +(33) Exchange +Input [9]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32, d_year#34] +Arguments: hashpartitioning(ss_ticket_number#23, ss_item_sk#22, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(34) Sort [codegen id : 11] +Input [9]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32, d_year#34] +Arguments: [ss_ticket_number#23 ASC NULLS FIRST, ss_item_sk#22 ASC NULLS FIRST], false, 0 + +(35) Scan parquet spark_catalog.default.store_returns +Output [5]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38, sr_returned_date_sk#39] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_returns] +PushedFilters: [IsNotNull(sr_ticket_number), IsNotNull(sr_item_sk)] +ReadSchema: struct + +(36) CometFilter +Input [5]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38, sr_returned_date_sk#39] +Condition : (isnotnull(sr_ticket_number#36) AND isnotnull(sr_item_sk#35)) + +(37) CometProject +Input [5]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38, sr_returned_date_sk#39] +Arguments: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38], [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38] + +(38) ColumnarToRow [codegen id : 12] +Input [4]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38] + +(39) Exchange +Input [4]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38] +Arguments: hashpartitioning(sr_ticket_number#36, sr_item_sk#35, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(40) Sort [codegen id : 13] +Input [4]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38] +Arguments: [sr_ticket_number#36 ASC NULLS FIRST, sr_item_sk#35 ASC NULLS FIRST], false, 0 + +(41) SortMergeJoin [codegen id : 14] +Left keys [2]: [ss_ticket_number#23, ss_item_sk#22] +Right keys [2]: [sr_ticket_number#36, sr_item_sk#35] +Join type: LeftOuter +Join condition: None + +(42) Project [codegen id : 14] +Output [7]: [d_year#34, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32, (ss_quantity#24 - coalesce(sr_return_quantity#37, 0)) AS sales_cnt#40, (ss_ext_sales_price#25 - coalesce(sr_return_amt#38, 0.00)) AS sales_amt#41] +Input [13]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32, d_year#34, sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38] + +(43) Scan parquet spark_catalog.default.web_sales +Output [5]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, ws_sold_date_sk#46] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#46), dynamicpruningexpression(ws_sold_date_sk#46 IN dynamicpruning#47)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(44) CometFilter +Input [5]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, ws_sold_date_sk#46] +Condition : isnotnull(ws_item_sk#42) + +(45) ColumnarToRow [codegen id : 17] +Input [5]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, ws_sold_date_sk#46] + +(46) ReusedExchange [Reuses operator id: 8] +Output [5]: [i_item_sk#48, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52] + +(47) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ws_item_sk#42] +Right keys [1]: [i_item_sk#48] +Join type: Inner +Join condition: None + +(48) Project [codegen id : 17] +Output [9]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, ws_sold_date_sk#46, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52] +Input [10]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, ws_sold_date_sk#46, i_item_sk#48, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52] + +(49) ReusedExchange [Reuses operator id: 133] +Output [2]: [d_date_sk#53, d_year#54] + +(50) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ws_sold_date_sk#46] +Right keys [1]: [d_date_sk#53] +Join type: Inner +Join condition: None + +(51) Project [codegen id : 17] +Output [9]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52, d_year#54] +Input [11]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, ws_sold_date_sk#46, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52, d_date_sk#53, d_year#54] + +(52) Exchange +Input [9]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52, d_year#54] +Arguments: hashpartitioning(ws_order_number#43, ws_item_sk#42, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(53) Sort [codegen id : 18] +Input [9]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52, d_year#54] +Arguments: [ws_order_number#43 ASC NULLS FIRST, ws_item_sk#42 ASC NULLS FIRST], false, 0 + +(54) Scan parquet spark_catalog.default.web_returns +Output [5]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58, wr_returned_date_sk#59] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_returns] +PushedFilters: [IsNotNull(wr_order_number), IsNotNull(wr_item_sk)] +ReadSchema: struct + +(55) CometFilter +Input [5]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58, wr_returned_date_sk#59] +Condition : (isnotnull(wr_order_number#56) AND isnotnull(wr_item_sk#55)) + +(56) CometProject +Input [5]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58, wr_returned_date_sk#59] +Arguments: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58], [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58] + +(57) ColumnarToRow [codegen id : 19] +Input [4]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58] + +(58) Exchange +Input [4]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58] +Arguments: hashpartitioning(wr_order_number#56, wr_item_sk#55, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(59) Sort [codegen id : 20] +Input [4]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58] +Arguments: [wr_order_number#56 ASC NULLS FIRST, wr_item_sk#55 ASC NULLS FIRST], false, 0 + +(60) SortMergeJoin [codegen id : 21] +Left keys [2]: [ws_order_number#43, ws_item_sk#42] +Right keys [2]: [wr_order_number#56, wr_item_sk#55] +Join type: LeftOuter +Join condition: None + +(61) Project [codegen id : 21] +Output [7]: [d_year#54, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52, (ws_quantity#44 - coalesce(wr_return_quantity#57, 0)) AS sales_cnt#60, (ws_ext_sales_price#45 - coalesce(wr_return_amt#58, 0.00)) AS sales_amt#61] +Input [13]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52, d_year#54, wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58] + +(62) Union + +(63) HashAggregate [codegen id : 22] +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21] +Keys [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21] +Functions: [] +Aggregate Attributes: [] +Results [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21] + +(64) Exchange +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21] +Arguments: hashpartitioning(d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21, 5), ENSURE_REQUIREMENTS, [plan_id=8] + +(65) HashAggregate [codegen id : 23] +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21] +Keys [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21] +Functions: [] +Aggregate Attributes: [] +Results [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21] + +(66) HashAggregate [codegen id : 23] +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21] +Keys [5]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] +Functions [2]: [partial_sum(sales_cnt#20), partial_sum(UnscaledValue(sales_amt#21))] +Aggregate Attributes [2]: [sum#62, sum#63] +Results [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sum#64, sum#65] + +(67) Exchange +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sum#64, sum#65] +Arguments: hashpartitioning(d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(68) HashAggregate [codegen id : 24] +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sum#64, sum#65] +Keys [5]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] +Functions [2]: [sum(sales_cnt#20), sum(UnscaledValue(sales_amt#21))] +Aggregate Attributes [2]: [sum(sales_cnt#20)#66, sum(UnscaledValue(sales_amt#21))#67] +Results [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sum(sales_cnt#20)#66 AS sales_cnt#68, MakeDecimal(sum(UnscaledValue(sales_amt#21))#67,18,2) AS sales_amt#69] + +(69) Filter [codegen id : 24] +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#68, sales_amt#69] +Condition : isnotnull(sales_cnt#68) + +(70) Exchange +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#68, sales_amt#69] +Arguments: hashpartitioning(i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(71) Sort [codegen id : 25] +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#68, sales_amt#69] +Arguments: [i_brand_id#8 ASC NULLS FIRST, i_class_id#9 ASC NULLS FIRST, i_category_id#10 ASC NULLS FIRST, i_manufact_id#12 ASC NULLS FIRST], false, 0 + +(72) Scan parquet spark_catalog.default.catalog_sales +Output [5]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, cs_sold_date_sk#74] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#74), dynamicpruningexpression(cs_sold_date_sk#74 IN dynamicpruning#75)] +PushedFilters: [IsNotNull(cs_item_sk)] +ReadSchema: struct + +(73) CometFilter +Input [5]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, cs_sold_date_sk#74] +Condition : isnotnull(cs_item_sk#70) + +(74) ColumnarToRow [codegen id : 28] +Input [5]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, cs_sold_date_sk#74] + +(75) ReusedExchange [Reuses operator id: 8] +Output [5]: [i_item_sk#76, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80] + +(76) BroadcastHashJoin [codegen id : 28] +Left keys [1]: [cs_item_sk#70] +Right keys [1]: [i_item_sk#76] +Join type: Inner +Join condition: None + +(77) Project [codegen id : 28] +Output [9]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, cs_sold_date_sk#74, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80] +Input [10]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, cs_sold_date_sk#74, i_item_sk#76, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80] + +(78) ReusedExchange [Reuses operator id: 137] +Output [2]: [d_date_sk#81, d_year#82] + +(79) BroadcastHashJoin [codegen id : 28] +Left keys [1]: [cs_sold_date_sk#74] +Right keys [1]: [d_date_sk#81] +Join type: Inner +Join condition: None + +(80) Project [codegen id : 28] +Output [9]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, d_year#82] +Input [11]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, cs_sold_date_sk#74, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, d_date_sk#81, d_year#82] + +(81) Exchange +Input [9]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, d_year#82] +Arguments: hashpartitioning(cs_order_number#71, cs_item_sk#70, 5), ENSURE_REQUIREMENTS, [plan_id=11] + +(82) Sort [codegen id : 29] +Input [9]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, d_year#82] +Arguments: [cs_order_number#71 ASC NULLS FIRST, cs_item_sk#70 ASC NULLS FIRST], false, 0 + +(83) ReusedExchange [Reuses operator id: 20] +Output [4]: [cr_item_sk#83, cr_order_number#84, cr_return_quantity#85, cr_return_amount#86] + +(84) Sort [codegen id : 31] +Input [4]: [cr_item_sk#83, cr_order_number#84, cr_return_quantity#85, cr_return_amount#86] +Arguments: [cr_order_number#84 ASC NULLS FIRST, cr_item_sk#83 ASC NULLS FIRST], false, 0 + +(85) SortMergeJoin [codegen id : 32] +Left keys [2]: [cs_order_number#71, cs_item_sk#70] +Right keys [2]: [cr_order_number#84, cr_item_sk#83] +Join type: LeftOuter +Join condition: None + +(86) Project [codegen id : 32] +Output [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, (cs_quantity#72 - coalesce(cr_return_quantity#85, 0)) AS sales_cnt#87, (cs_ext_sales_price#73 - coalesce(cr_return_amount#86, 0.00)) AS sales_amt#88] +Input [13]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, d_year#82, cr_item_sk#83, cr_order_number#84, cr_return_quantity#85, cr_return_amount#86] + +(87) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, ss_sold_date_sk#93] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#93), dynamicpruningexpression(ss_sold_date_sk#93 IN dynamicpruning#94)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(88) CometFilter +Input [5]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, ss_sold_date_sk#93] +Condition : isnotnull(ss_item_sk#89) + +(89) ColumnarToRow [codegen id : 35] +Input [5]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, ss_sold_date_sk#93] + +(90) ReusedExchange [Reuses operator id: 8] +Output [5]: [i_item_sk#95, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99] + +(91) BroadcastHashJoin [codegen id : 35] +Left keys [1]: [ss_item_sk#89] +Right keys [1]: [i_item_sk#95] +Join type: Inner +Join condition: None + +(92) Project [codegen id : 35] +Output [9]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, ss_sold_date_sk#93, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99] +Input [10]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, ss_sold_date_sk#93, i_item_sk#95, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99] + +(93) ReusedExchange [Reuses operator id: 137] +Output [2]: [d_date_sk#100, d_year#101] + +(94) BroadcastHashJoin [codegen id : 35] +Left keys [1]: [ss_sold_date_sk#93] +Right keys [1]: [d_date_sk#100] +Join type: Inner +Join condition: None + +(95) Project [codegen id : 35] +Output [9]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99, d_year#101] +Input [11]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, ss_sold_date_sk#93, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99, d_date_sk#100, d_year#101] + +(96) Exchange +Input [9]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99, d_year#101] +Arguments: hashpartitioning(ss_ticket_number#90, ss_item_sk#89, 5), ENSURE_REQUIREMENTS, [plan_id=12] + +(97) Sort [codegen id : 36] +Input [9]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99, d_year#101] +Arguments: [ss_ticket_number#90 ASC NULLS FIRST, ss_item_sk#89 ASC NULLS FIRST], false, 0 + +(98) ReusedExchange [Reuses operator id: 39] +Output [4]: [sr_item_sk#102, sr_ticket_number#103, sr_return_quantity#104, sr_return_amt#105] + +(99) Sort [codegen id : 38] +Input [4]: [sr_item_sk#102, sr_ticket_number#103, sr_return_quantity#104, sr_return_amt#105] +Arguments: [sr_ticket_number#103 ASC NULLS FIRST, sr_item_sk#102 ASC NULLS FIRST], false, 0 + +(100) SortMergeJoin [codegen id : 39] +Left keys [2]: [ss_ticket_number#90, ss_item_sk#89] +Right keys [2]: [sr_ticket_number#103, sr_item_sk#102] +Join type: LeftOuter +Join condition: None + +(101) Project [codegen id : 39] +Output [7]: [d_year#101, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99, (ss_quantity#91 - coalesce(sr_return_quantity#104, 0)) AS sales_cnt#106, (ss_ext_sales_price#92 - coalesce(sr_return_amt#105, 0.00)) AS sales_amt#107] +Input [13]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99, d_year#101, sr_item_sk#102, sr_ticket_number#103, sr_return_quantity#104, sr_return_amt#105] + +(102) Scan parquet spark_catalog.default.web_sales +Output [5]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, ws_sold_date_sk#112] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#112), dynamicpruningexpression(ws_sold_date_sk#112 IN dynamicpruning#113)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(103) CometFilter +Input [5]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, ws_sold_date_sk#112] +Condition : isnotnull(ws_item_sk#108) + +(104) ColumnarToRow [codegen id : 42] +Input [5]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, ws_sold_date_sk#112] + +(105) ReusedExchange [Reuses operator id: 8] +Output [5]: [i_item_sk#114, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118] + +(106) BroadcastHashJoin [codegen id : 42] +Left keys [1]: [ws_item_sk#108] +Right keys [1]: [i_item_sk#114] +Join type: Inner +Join condition: None + +(107) Project [codegen id : 42] +Output [9]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, ws_sold_date_sk#112, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118] +Input [10]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, ws_sold_date_sk#112, i_item_sk#114, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118] + +(108) ReusedExchange [Reuses operator id: 137] +Output [2]: [d_date_sk#119, d_year#120] + +(109) BroadcastHashJoin [codegen id : 42] +Left keys [1]: [ws_sold_date_sk#112] +Right keys [1]: [d_date_sk#119] +Join type: Inner +Join condition: None + +(110) Project [codegen id : 42] +Output [9]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118, d_year#120] +Input [11]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, ws_sold_date_sk#112, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118, d_date_sk#119, d_year#120] + +(111) Exchange +Input [9]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118, d_year#120] +Arguments: hashpartitioning(ws_order_number#109, ws_item_sk#108, 5), ENSURE_REQUIREMENTS, [plan_id=13] + +(112) Sort [codegen id : 43] +Input [9]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118, d_year#120] +Arguments: [ws_order_number#109 ASC NULLS FIRST, ws_item_sk#108 ASC NULLS FIRST], false, 0 + +(113) ReusedExchange [Reuses operator id: 58] +Output [4]: [wr_item_sk#121, wr_order_number#122, wr_return_quantity#123, wr_return_amt#124] + +(114) Sort [codegen id : 45] +Input [4]: [wr_item_sk#121, wr_order_number#122, wr_return_quantity#123, wr_return_amt#124] +Arguments: [wr_order_number#122 ASC NULLS FIRST, wr_item_sk#121 ASC NULLS FIRST], false, 0 + +(115) SortMergeJoin [codegen id : 46] +Left keys [2]: [ws_order_number#109, ws_item_sk#108] +Right keys [2]: [wr_order_number#122, wr_item_sk#121] +Join type: LeftOuter +Join condition: None + +(116) Project [codegen id : 46] +Output [7]: [d_year#120, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118, (ws_quantity#110 - coalesce(wr_return_quantity#123, 0)) AS sales_cnt#125, (ws_ext_sales_price#111 - coalesce(wr_return_amt#124, 0.00)) AS sales_amt#126] +Input [13]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118, d_year#120, wr_item_sk#121, wr_order_number#122, wr_return_quantity#123, wr_return_amt#124] + +(117) Union + +(118) HashAggregate [codegen id : 47] +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88] +Keys [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88] +Functions: [] +Aggregate Attributes: [] +Results [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88] + +(119) Exchange +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88] +Arguments: hashpartitioning(d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88, 5), ENSURE_REQUIREMENTS, [plan_id=14] + +(120) HashAggregate [codegen id : 48] +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88] +Keys [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88] +Functions: [] +Aggregate Attributes: [] +Results [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88] + +(121) HashAggregate [codegen id : 48] +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88] +Keys [5]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80] +Functions [2]: [partial_sum(sales_cnt#87), partial_sum(UnscaledValue(sales_amt#88))] +Aggregate Attributes [2]: [sum#127, sum#128] +Results [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sum#129, sum#130] + +(122) Exchange +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sum#129, sum#130] +Arguments: hashpartitioning(d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, 5), ENSURE_REQUIREMENTS, [plan_id=15] + +(123) HashAggregate [codegen id : 49] +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sum#129, sum#130] +Keys [5]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80] +Functions [2]: [sum(sales_cnt#87), sum(UnscaledValue(sales_amt#88))] +Aggregate Attributes [2]: [sum(sales_cnt#87)#66, sum(UnscaledValue(sales_amt#88))#67] +Results [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sum(sales_cnt#87)#66 AS sales_cnt#131, MakeDecimal(sum(UnscaledValue(sales_amt#88))#67,18,2) AS sales_amt#132] + +(124) Filter [codegen id : 49] +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#131, sales_amt#132] +Condition : isnotnull(sales_cnt#131) + +(125) Exchange +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#131, sales_amt#132] +Arguments: hashpartitioning(i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, 5), ENSURE_REQUIREMENTS, [plan_id=16] + +(126) Sort [codegen id : 50] +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#131, sales_amt#132] +Arguments: [i_brand_id#77 ASC NULLS FIRST, i_class_id#78 ASC NULLS FIRST, i_category_id#79 ASC NULLS FIRST, i_manufact_id#80 ASC NULLS FIRST], false, 0 + +(127) SortMergeJoin [codegen id : 51] +Left keys [4]: [i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] +Right keys [4]: [i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80] +Join type: Inner +Join condition: ((cast(sales_cnt#68 as decimal(17,2)) / cast(sales_cnt#131 as decimal(17,2))) < 0.90000000000000000000) + +(128) Project [codegen id : 51] +Output [10]: [d_year#82 AS prev_year#133, d_year#14 AS year#134, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#131 AS prev_yr_cnt#135, sales_cnt#68 AS curr_yr_cnt#136, (sales_cnt#68 - sales_cnt#131) AS sales_cnt_diff#137, (sales_amt#69 - sales_amt#132) AS sales_amt_diff#138] +Input [14]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#68, sales_amt#69, d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#131, sales_amt#132] + +(129) TakeOrderedAndProject +Input [10]: [prev_year#133, year#134, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, prev_yr_cnt#135, curr_yr_cnt#136, sales_cnt_diff#137, sales_amt_diff#138] +Arguments: 100, [sales_cnt_diff#137 ASC NULLS FIRST, sales_amt_diff#138 ASC NULLS FIRST], [prev_year#133, year#134, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, prev_yr_cnt#135, curr_yr_cnt#136, sales_cnt_diff#137, sales_amt_diff#138] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#5 IN dynamicpruning#6 +BroadcastExchange (133) ++- * ColumnarToRow (132) + +- CometFilter (131) + +- CometScan parquet spark_catalog.default.date_dim (130) + + +(130) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#13, d_year#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2002), IsNotNull(d_date_sk)] +ReadSchema: struct + +(131) CometFilter +Input [2]: [d_date_sk#13, d_year#14] +Condition : ((isnotnull(d_year#14) AND (d_year#14 = 2002)) AND isnotnull(d_date_sk#13)) + +(132) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#13, d_year#14] + +(133) BroadcastExchange +Input [2]: [d_date_sk#13, d_year#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=17] + +Subquery:2 Hosting operator id = 24 Hosting Expression = ss_sold_date_sk#26 IN dynamicpruning#6 + +Subquery:3 Hosting operator id = 43 Hosting Expression = ws_sold_date_sk#46 IN dynamicpruning#6 + +Subquery:4 Hosting operator id = 72 Hosting Expression = cs_sold_date_sk#74 IN dynamicpruning#75 +BroadcastExchange (137) ++- * ColumnarToRow (136) + +- CometFilter (135) + +- CometScan parquet spark_catalog.default.date_dim (134) + + +(134) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#81, d_year#82] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(135) CometFilter +Input [2]: [d_date_sk#81, d_year#82] +Condition : ((isnotnull(d_year#82) AND (d_year#82 = 2001)) AND isnotnull(d_date_sk#81)) + +(136) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#81, d_year#82] + +(137) BroadcastExchange +Input [2]: [d_date_sk#81, d_year#82] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=18] + +Subquery:5 Hosting operator id = 87 Hosting Expression = ss_sold_date_sk#93 IN dynamicpruning#75 + +Subquery:6 Hosting operator id = 102 Hosting Expression = ws_sold_date_sk#112 IN dynamicpruning#75 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q75/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q75/simplified.txt new file mode 100644 index 0000000000..9939b2fe21 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q75/simplified.txt @@ -0,0 +1,240 @@ +TakeOrderedAndProject [sales_cnt_diff,sales_amt_diff,prev_year,year,i_brand_id,i_class_id,i_category_id,i_manufact_id,prev_yr_cnt,curr_yr_cnt] + WholeStageCodegen (51) + Project [d_year,d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_cnt,sales_amt,sales_amt] + SortMergeJoin [i_brand_id,i_class_id,i_category_id,i_manufact_id,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_cnt] + InputAdapter + WholeStageCodegen (25) + Sort [i_brand_id,i_class_id,i_category_id,i_manufact_id] + InputAdapter + Exchange [i_brand_id,i_class_id,i_category_id,i_manufact_id] #1 + WholeStageCodegen (24) + Filter [sales_cnt] + HashAggregate [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sum,sum] [sum(sales_cnt),sum(UnscaledValue(sales_amt)),sales_cnt,sales_amt,sum,sum] + InputAdapter + Exchange [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id] #2 + WholeStageCodegen (23) + HashAggregate [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_amt] [sum,sum,sum,sum] + HashAggregate [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_amt] + InputAdapter + Exchange [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_amt] #3 + WholeStageCodegen (22) + HashAggregate [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_amt] + InputAdapter + Union + WholeStageCodegen (7) + Project [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,cs_quantity,cr_return_quantity,cs_ext_sales_price,cr_return_amount] + SortMergeJoin [cs_order_number,cs_item_sk,cr_order_number,cr_item_sk] + InputAdapter + WholeStageCodegen (4) + Sort [cs_order_number,cs_item_sk] + InputAdapter + Exchange [cs_order_number,cs_item_sk] #4 + WholeStageCodegen (3) + Project [cs_item_sk,cs_order_number,cs_quantity,cs_ext_sales_price,i_brand_id,i_class_id,i_category_id,i_manufact_id,d_year] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_item_sk,cs_order_number,cs_quantity,cs_ext_sales_price,cs_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_order_number,cs_quantity,cs_ext_sales_price,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #5 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] + CometFilter [i_category,i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id,i_category,i_manufact_id] + InputAdapter + ReusedExchange [d_date_sk,d_year] #5 + InputAdapter + WholeStageCodegen (6) + Sort [cr_order_number,cr_item_sk] + InputAdapter + Exchange [cr_order_number,cr_item_sk] #7 + WholeStageCodegen (5) + ColumnarToRow + InputAdapter + CometProject [cr_item_sk,cr_order_number,cr_return_quantity,cr_return_amount] + CometFilter [cr_order_number,cr_item_sk] + CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_return_quantity,cr_return_amount,cr_returned_date_sk] + WholeStageCodegen (14) + Project [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,ss_quantity,sr_return_quantity,ss_ext_sales_price,sr_return_amt] + SortMergeJoin [ss_ticket_number,ss_item_sk,sr_ticket_number,sr_item_sk] + InputAdapter + WholeStageCodegen (11) + Sort [ss_ticket_number,ss_item_sk] + InputAdapter + Exchange [ss_ticket_number,ss_item_sk] #8 + WholeStageCodegen (10) + Project [ss_item_sk,ss_ticket_number,ss_quantity,ss_ext_sales_price,i_brand_id,i_class_id,i_category_id,i_manufact_id,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_ticket_number,ss_quantity,ss_ext_sales_price,ss_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ticket_number,ss_quantity,ss_ext_sales_price,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] #6 + InputAdapter + ReusedExchange [d_date_sk,d_year] #5 + InputAdapter + WholeStageCodegen (13) + Sort [sr_ticket_number,sr_item_sk] + InputAdapter + Exchange [sr_ticket_number,sr_item_sk] #9 + WholeStageCodegen (12) + ColumnarToRow + InputAdapter + CometProject [sr_item_sk,sr_ticket_number,sr_return_quantity,sr_return_amt] + CometFilter [sr_ticket_number,sr_item_sk] + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_return_quantity,sr_return_amt,sr_returned_date_sk] + WholeStageCodegen (21) + Project [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,ws_quantity,wr_return_quantity,ws_ext_sales_price,wr_return_amt] + SortMergeJoin [ws_order_number,ws_item_sk,wr_order_number,wr_item_sk] + InputAdapter + WholeStageCodegen (18) + Sort [ws_order_number,ws_item_sk] + InputAdapter + Exchange [ws_order_number,ws_item_sk] #10 + WholeStageCodegen (17) + Project [ws_item_sk,ws_order_number,ws_quantity,ws_ext_sales_price,i_brand_id,i_class_id,i_category_id,i_manufact_id,d_year] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_item_sk,ws_order_number,ws_quantity,ws_ext_sales_price,ws_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] + BroadcastHashJoin [ws_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_order_number,ws_quantity,ws_ext_sales_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] #6 + InputAdapter + ReusedExchange [d_date_sk,d_year] #5 + InputAdapter + WholeStageCodegen (20) + Sort [wr_order_number,wr_item_sk] + InputAdapter + Exchange [wr_order_number,wr_item_sk] #11 + WholeStageCodegen (19) + ColumnarToRow + InputAdapter + CometProject [wr_item_sk,wr_order_number,wr_return_quantity,wr_return_amt] + CometFilter [wr_order_number,wr_item_sk] + CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_order_number,wr_return_quantity,wr_return_amt,wr_returned_date_sk] + InputAdapter + WholeStageCodegen (50) + Sort [i_brand_id,i_class_id,i_category_id,i_manufact_id] + InputAdapter + Exchange [i_brand_id,i_class_id,i_category_id,i_manufact_id] #12 + WholeStageCodegen (49) + Filter [sales_cnt] + HashAggregate [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sum,sum] [sum(sales_cnt),sum(UnscaledValue(sales_amt)),sales_cnt,sales_amt,sum,sum] + InputAdapter + Exchange [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id] #13 + WholeStageCodegen (48) + HashAggregate [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_amt] [sum,sum,sum,sum] + HashAggregate [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_amt] + InputAdapter + Exchange [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_amt] #14 + WholeStageCodegen (47) + HashAggregate [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_amt] + InputAdapter + Union + WholeStageCodegen (32) + Project [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,cs_quantity,cr_return_quantity,cs_ext_sales_price,cr_return_amount] + SortMergeJoin [cs_order_number,cs_item_sk,cr_order_number,cr_item_sk] + InputAdapter + WholeStageCodegen (29) + Sort [cs_order_number,cs_item_sk] + InputAdapter + Exchange [cs_order_number,cs_item_sk] #15 + WholeStageCodegen (28) + Project [cs_item_sk,cs_order_number,cs_quantity,cs_ext_sales_price,i_brand_id,i_class_id,i_category_id,i_manufact_id,d_year] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_item_sk,cs_order_number,cs_quantity,cs_ext_sales_price,cs_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_order_number,cs_quantity,cs_ext_sales_price,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #16 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] #6 + InputAdapter + ReusedExchange [d_date_sk,d_year] #16 + InputAdapter + WholeStageCodegen (31) + Sort [cr_order_number,cr_item_sk] + InputAdapter + ReusedExchange [cr_item_sk,cr_order_number,cr_return_quantity,cr_return_amount] #7 + WholeStageCodegen (39) + Project [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,ss_quantity,sr_return_quantity,ss_ext_sales_price,sr_return_amt] + SortMergeJoin [ss_ticket_number,ss_item_sk,sr_ticket_number,sr_item_sk] + InputAdapter + WholeStageCodegen (36) + Sort [ss_ticket_number,ss_item_sk] + InputAdapter + Exchange [ss_ticket_number,ss_item_sk] #17 + WholeStageCodegen (35) + Project [ss_item_sk,ss_ticket_number,ss_quantity,ss_ext_sales_price,i_brand_id,i_class_id,i_category_id,i_manufact_id,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_ticket_number,ss_quantity,ss_ext_sales_price,ss_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ticket_number,ss_quantity,ss_ext_sales_price,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] #6 + InputAdapter + ReusedExchange [d_date_sk,d_year] #16 + InputAdapter + WholeStageCodegen (38) + Sort [sr_ticket_number,sr_item_sk] + InputAdapter + ReusedExchange [sr_item_sk,sr_ticket_number,sr_return_quantity,sr_return_amt] #9 + WholeStageCodegen (46) + Project [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,ws_quantity,wr_return_quantity,ws_ext_sales_price,wr_return_amt] + SortMergeJoin [ws_order_number,ws_item_sk,wr_order_number,wr_item_sk] + InputAdapter + WholeStageCodegen (43) + Sort [ws_order_number,ws_item_sk] + InputAdapter + Exchange [ws_order_number,ws_item_sk] #18 + WholeStageCodegen (42) + Project [ws_item_sk,ws_order_number,ws_quantity,ws_ext_sales_price,i_brand_id,i_class_id,i_category_id,i_manufact_id,d_year] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_item_sk,ws_order_number,ws_quantity,ws_ext_sales_price,ws_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] + BroadcastHashJoin [ws_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_order_number,ws_quantity,ws_ext_sales_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] #6 + InputAdapter + ReusedExchange [d_date_sk,d_year] #16 + InputAdapter + WholeStageCodegen (45) + Sort [wr_order_number,wr_item_sk] + InputAdapter + ReusedExchange [wr_item_sk,wr_order_number,wr_return_quantity,wr_return_amt] #11 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q77a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q77a/explain.txt new file mode 100644 index 0000000000..5c18652670 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q77a/explain.txt @@ -0,0 +1,632 @@ +== Physical Plan == +TakeOrderedAndProject (98) ++- * HashAggregate (97) + +- Exchange (96) + +- * HashAggregate (95) + +- Union (94) + :- * HashAggregate (83) + : +- Exchange (82) + : +- * HashAggregate (81) + : +- Union (80) + : :- * Project (30) + : : +- * BroadcastHashJoin LeftOuter BuildRight (29) + : : :- * HashAggregate (15) + : : : +- Exchange (14) + : : : +- * HashAggregate (13) + : : : +- * Project (12) + : : : +- * BroadcastHashJoin Inner BuildRight (11) + : : : :- * Project (6) + : : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : +- ReusedExchange (4) + : : : +- BroadcastExchange (10) + : : : +- * ColumnarToRow (9) + : : : +- CometFilter (8) + : : : +- CometScan parquet spark_catalog.default.store (7) + : : +- BroadcastExchange (28) + : : +- * HashAggregate (27) + : : +- Exchange (26) + : : +- * HashAggregate (25) + : : +- * Project (24) + : : +- * BroadcastHashJoin Inner BuildRight (23) + : : :- * Project (21) + : : : +- * BroadcastHashJoin Inner BuildRight (20) + : : : :- * ColumnarToRow (18) + : : : : +- CometFilter (17) + : : : : +- CometScan parquet spark_catalog.default.store_returns (16) + : : : +- ReusedExchange (19) + : : +- ReusedExchange (22) + : :- * Project (49) + : : +- * BroadcastNestedLoopJoin Inner BuildLeft (48) + : : :- BroadcastExchange (39) + : : : +- * HashAggregate (38) + : : : +- Exchange (37) + : : : +- * HashAggregate (36) + : : : +- * Project (35) + : : : +- * BroadcastHashJoin Inner BuildRight (34) + : : : :- * ColumnarToRow (32) + : : : : +- CometScan parquet spark_catalog.default.catalog_sales (31) + : : : +- ReusedExchange (33) + : : +- * HashAggregate (47) + : : +- Exchange (46) + : : +- * HashAggregate (45) + : : +- * Project (44) + : : +- * BroadcastHashJoin Inner BuildRight (43) + : : :- * ColumnarToRow (41) + : : : +- CometScan parquet spark_catalog.default.catalog_returns (40) + : : +- ReusedExchange (42) + : +- * Project (79) + : +- * BroadcastHashJoin LeftOuter BuildRight (78) + : :- * HashAggregate (64) + : : +- Exchange (63) + : : +- * HashAggregate (62) + : : +- * Project (61) + : : +- * BroadcastHashJoin Inner BuildRight (60) + : : :- * Project (55) + : : : +- * BroadcastHashJoin Inner BuildRight (54) + : : : :- * ColumnarToRow (52) + : : : : +- CometFilter (51) + : : : : +- CometScan parquet spark_catalog.default.web_sales (50) + : : : +- ReusedExchange (53) + : : +- BroadcastExchange (59) + : : +- * ColumnarToRow (58) + : : +- CometFilter (57) + : : +- CometScan parquet spark_catalog.default.web_page (56) + : +- BroadcastExchange (77) + : +- * HashAggregate (76) + : +- Exchange (75) + : +- * HashAggregate (74) + : +- * Project (73) + : +- * BroadcastHashJoin Inner BuildRight (72) + : :- * Project (70) + : : +- * BroadcastHashJoin Inner BuildRight (69) + : : :- * ColumnarToRow (67) + : : : +- CometFilter (66) + : : : +- CometScan parquet spark_catalog.default.web_returns (65) + : : +- ReusedExchange (68) + : +- ReusedExchange (71) + :- * HashAggregate (88) + : +- Exchange (87) + : +- * HashAggregate (86) + : +- * HashAggregate (85) + : +- ReusedExchange (84) + +- * HashAggregate (93) + +- Exchange (92) + +- * HashAggregate (91) + +- * HashAggregate (90) + +- ReusedExchange (89) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#4), dynamicpruningexpression(ss_sold_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(ss_store_sk)] +ReadSchema: struct + +(2) CometFilter +Input [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] +Condition : isnotnull(ss_store_sk#1) + +(3) ColumnarToRow [codegen id : 3] +Input [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] + +(4) ReusedExchange [Reuses operator id: 103] +Output [1]: [d_date_sk#6] + +(5) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_sold_date_sk#4] +Right keys [1]: [d_date_sk#6] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 3] +Output [3]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3] +Input [5]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4, d_date_sk#6] + +(7) Scan parquet spark_catalog.default.store +Output [1]: [s_store_sk#7] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(8) CometFilter +Input [1]: [s_store_sk#7] +Condition : isnotnull(s_store_sk#7) + +(9) ColumnarToRow [codegen id : 2] +Input [1]: [s_store_sk#7] + +(10) BroadcastExchange +Input [1]: [s_store_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_store_sk#1] +Right keys [1]: [s_store_sk#7] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [3]: [ss_ext_sales_price#2, ss_net_profit#3, s_store_sk#7] +Input [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, s_store_sk#7] + +(13) HashAggregate [codegen id : 3] +Input [3]: [ss_ext_sales_price#2, ss_net_profit#3, s_store_sk#7] +Keys [1]: [s_store_sk#7] +Functions [2]: [partial_sum(UnscaledValue(ss_ext_sales_price#2)), partial_sum(UnscaledValue(ss_net_profit#3))] +Aggregate Attributes [2]: [sum#8, sum#9] +Results [3]: [s_store_sk#7, sum#10, sum#11] + +(14) Exchange +Input [3]: [s_store_sk#7, sum#10, sum#11] +Arguments: hashpartitioning(s_store_sk#7, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 8] +Input [3]: [s_store_sk#7, sum#10, sum#11] +Keys [1]: [s_store_sk#7] +Functions [2]: [sum(UnscaledValue(ss_ext_sales_price#2)), sum(UnscaledValue(ss_net_profit#3))] +Aggregate Attributes [2]: [sum(UnscaledValue(ss_ext_sales_price#2))#12, sum(UnscaledValue(ss_net_profit#3))#13] +Results [3]: [s_store_sk#7, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#2))#12,17,2) AS sales#14, MakeDecimal(sum(UnscaledValue(ss_net_profit#3))#13,17,2) AS profit#15] + +(16) Scan parquet spark_catalog.default.store_returns +Output [4]: [sr_store_sk#16, sr_return_amt#17, sr_net_loss#18, sr_returned_date_sk#19] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(sr_returned_date_sk#19), dynamicpruningexpression(sr_returned_date_sk#19 IN dynamicpruning#20)] +PushedFilters: [IsNotNull(sr_store_sk)] +ReadSchema: struct + +(17) CometFilter +Input [4]: [sr_store_sk#16, sr_return_amt#17, sr_net_loss#18, sr_returned_date_sk#19] +Condition : isnotnull(sr_store_sk#16) + +(18) ColumnarToRow [codegen id : 6] +Input [4]: [sr_store_sk#16, sr_return_amt#17, sr_net_loss#18, sr_returned_date_sk#19] + +(19) ReusedExchange [Reuses operator id: 103] +Output [1]: [d_date_sk#21] + +(20) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [sr_returned_date_sk#19] +Right keys [1]: [d_date_sk#21] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 6] +Output [3]: [sr_store_sk#16, sr_return_amt#17, sr_net_loss#18] +Input [5]: [sr_store_sk#16, sr_return_amt#17, sr_net_loss#18, sr_returned_date_sk#19, d_date_sk#21] + +(22) ReusedExchange [Reuses operator id: 10] +Output [1]: [s_store_sk#22] + +(23) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [sr_store_sk#16] +Right keys [1]: [s_store_sk#22] +Join type: Inner +Join condition: None + +(24) Project [codegen id : 6] +Output [3]: [sr_return_amt#17, sr_net_loss#18, s_store_sk#22] +Input [4]: [sr_store_sk#16, sr_return_amt#17, sr_net_loss#18, s_store_sk#22] + +(25) HashAggregate [codegen id : 6] +Input [3]: [sr_return_amt#17, sr_net_loss#18, s_store_sk#22] +Keys [1]: [s_store_sk#22] +Functions [2]: [partial_sum(UnscaledValue(sr_return_amt#17)), partial_sum(UnscaledValue(sr_net_loss#18))] +Aggregate Attributes [2]: [sum#23, sum#24] +Results [3]: [s_store_sk#22, sum#25, sum#26] + +(26) Exchange +Input [3]: [s_store_sk#22, sum#25, sum#26] +Arguments: hashpartitioning(s_store_sk#22, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(27) HashAggregate [codegen id : 7] +Input [3]: [s_store_sk#22, sum#25, sum#26] +Keys [1]: [s_store_sk#22] +Functions [2]: [sum(UnscaledValue(sr_return_amt#17)), sum(UnscaledValue(sr_net_loss#18))] +Aggregate Attributes [2]: [sum(UnscaledValue(sr_return_amt#17))#27, sum(UnscaledValue(sr_net_loss#18))#28] +Results [3]: [s_store_sk#22, MakeDecimal(sum(UnscaledValue(sr_return_amt#17))#27,17,2) AS returns#29, MakeDecimal(sum(UnscaledValue(sr_net_loss#18))#28,17,2) AS profit_loss#30] + +(28) BroadcastExchange +Input [3]: [s_store_sk#22, returns#29, profit_loss#30] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(29) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [s_store_sk#7] +Right keys [1]: [s_store_sk#22] +Join type: LeftOuter +Join condition: None + +(30) Project [codegen id : 8] +Output [5]: [store channel AS channel#31, s_store_sk#7 AS id#32, sales#14, coalesce(returns#29, 0.00) AS returns#33, (profit#15 - coalesce(profit_loss#30, 0.00)) AS profit#34] +Input [6]: [s_store_sk#7, sales#14, profit#15, s_store_sk#22, returns#29, profit_loss#30] + +(31) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_call_center_sk#35, cs_ext_sales_price#36, cs_net_profit#37, cs_sold_date_sk#38] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#38), dynamicpruningexpression(cs_sold_date_sk#38 IN dynamicpruning#39)] +ReadSchema: struct + +(32) ColumnarToRow [codegen id : 10] +Input [4]: [cs_call_center_sk#35, cs_ext_sales_price#36, cs_net_profit#37, cs_sold_date_sk#38] + +(33) ReusedExchange [Reuses operator id: 103] +Output [1]: [d_date_sk#40] + +(34) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_sold_date_sk#38] +Right keys [1]: [d_date_sk#40] +Join type: Inner +Join condition: None + +(35) Project [codegen id : 10] +Output [3]: [cs_call_center_sk#35, cs_ext_sales_price#36, cs_net_profit#37] +Input [5]: [cs_call_center_sk#35, cs_ext_sales_price#36, cs_net_profit#37, cs_sold_date_sk#38, d_date_sk#40] + +(36) HashAggregate [codegen id : 10] +Input [3]: [cs_call_center_sk#35, cs_ext_sales_price#36, cs_net_profit#37] +Keys [1]: [cs_call_center_sk#35] +Functions [2]: [partial_sum(UnscaledValue(cs_ext_sales_price#36)), partial_sum(UnscaledValue(cs_net_profit#37))] +Aggregate Attributes [2]: [sum#41, sum#42] +Results [3]: [cs_call_center_sk#35, sum#43, sum#44] + +(37) Exchange +Input [3]: [cs_call_center_sk#35, sum#43, sum#44] +Arguments: hashpartitioning(cs_call_center_sk#35, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(38) HashAggregate [codegen id : 11] +Input [3]: [cs_call_center_sk#35, sum#43, sum#44] +Keys [1]: [cs_call_center_sk#35] +Functions [2]: [sum(UnscaledValue(cs_ext_sales_price#36)), sum(UnscaledValue(cs_net_profit#37))] +Aggregate Attributes [2]: [sum(UnscaledValue(cs_ext_sales_price#36))#45, sum(UnscaledValue(cs_net_profit#37))#46] +Results [3]: [cs_call_center_sk#35, MakeDecimal(sum(UnscaledValue(cs_ext_sales_price#36))#45,17,2) AS sales#47, MakeDecimal(sum(UnscaledValue(cs_net_profit#37))#46,17,2) AS profit#48] + +(39) BroadcastExchange +Input [3]: [cs_call_center_sk#35, sales#47, profit#48] +Arguments: IdentityBroadcastMode, [plan_id=6] + +(40) Scan parquet spark_catalog.default.catalog_returns +Output [3]: [cr_return_amount#49, cr_net_loss#50, cr_returned_date_sk#51] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cr_returned_date_sk#51), dynamicpruningexpression(cr_returned_date_sk#51 IN dynamicpruning#52)] +ReadSchema: struct + +(41) ColumnarToRow [codegen id : 13] +Input [3]: [cr_return_amount#49, cr_net_loss#50, cr_returned_date_sk#51] + +(42) ReusedExchange [Reuses operator id: 103] +Output [1]: [d_date_sk#53] + +(43) BroadcastHashJoin [codegen id : 13] +Left keys [1]: [cr_returned_date_sk#51] +Right keys [1]: [d_date_sk#53] +Join type: Inner +Join condition: None + +(44) Project [codegen id : 13] +Output [2]: [cr_return_amount#49, cr_net_loss#50] +Input [4]: [cr_return_amount#49, cr_net_loss#50, cr_returned_date_sk#51, d_date_sk#53] + +(45) HashAggregate [codegen id : 13] +Input [2]: [cr_return_amount#49, cr_net_loss#50] +Keys: [] +Functions [2]: [partial_sum(UnscaledValue(cr_return_amount#49)), partial_sum(UnscaledValue(cr_net_loss#50))] +Aggregate Attributes [2]: [sum#54, sum#55] +Results [2]: [sum#56, sum#57] + +(46) Exchange +Input [2]: [sum#56, sum#57] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=7] + +(47) HashAggregate +Input [2]: [sum#56, sum#57] +Keys: [] +Functions [2]: [sum(UnscaledValue(cr_return_amount#49)), sum(UnscaledValue(cr_net_loss#50))] +Aggregate Attributes [2]: [sum(UnscaledValue(cr_return_amount#49))#58, sum(UnscaledValue(cr_net_loss#50))#59] +Results [2]: [MakeDecimal(sum(UnscaledValue(cr_return_amount#49))#58,17,2) AS returns#60, MakeDecimal(sum(UnscaledValue(cr_net_loss#50))#59,17,2) AS profit_loss#61] + +(48) BroadcastNestedLoopJoin [codegen id : 14] +Join type: Inner +Join condition: None + +(49) Project [codegen id : 14] +Output [5]: [catalog channel AS channel#62, cs_call_center_sk#35 AS id#63, sales#47, returns#60, (profit#48 - profit_loss#61) AS profit#64] +Input [5]: [cs_call_center_sk#35, sales#47, profit#48, returns#60, profit_loss#61] + +(50) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_web_page_sk#65, ws_ext_sales_price#66, ws_net_profit#67, ws_sold_date_sk#68] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#68), dynamicpruningexpression(ws_sold_date_sk#68 IN dynamicpruning#69)] +PushedFilters: [IsNotNull(ws_web_page_sk)] +ReadSchema: struct + +(51) CometFilter +Input [4]: [ws_web_page_sk#65, ws_ext_sales_price#66, ws_net_profit#67, ws_sold_date_sk#68] +Condition : isnotnull(ws_web_page_sk#65) + +(52) ColumnarToRow [codegen id : 17] +Input [4]: [ws_web_page_sk#65, ws_ext_sales_price#66, ws_net_profit#67, ws_sold_date_sk#68] + +(53) ReusedExchange [Reuses operator id: 103] +Output [1]: [d_date_sk#70] + +(54) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ws_sold_date_sk#68] +Right keys [1]: [d_date_sk#70] +Join type: Inner +Join condition: None + +(55) Project [codegen id : 17] +Output [3]: [ws_web_page_sk#65, ws_ext_sales_price#66, ws_net_profit#67] +Input [5]: [ws_web_page_sk#65, ws_ext_sales_price#66, ws_net_profit#67, ws_sold_date_sk#68, d_date_sk#70] + +(56) Scan parquet spark_catalog.default.web_page +Output [1]: [wp_web_page_sk#71] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_page] +PushedFilters: [IsNotNull(wp_web_page_sk)] +ReadSchema: struct + +(57) CometFilter +Input [1]: [wp_web_page_sk#71] +Condition : isnotnull(wp_web_page_sk#71) + +(58) ColumnarToRow [codegen id : 16] +Input [1]: [wp_web_page_sk#71] + +(59) BroadcastExchange +Input [1]: [wp_web_page_sk#71] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8] + +(60) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ws_web_page_sk#65] +Right keys [1]: [wp_web_page_sk#71] +Join type: Inner +Join condition: None + +(61) Project [codegen id : 17] +Output [3]: [ws_ext_sales_price#66, ws_net_profit#67, wp_web_page_sk#71] +Input [4]: [ws_web_page_sk#65, ws_ext_sales_price#66, ws_net_profit#67, wp_web_page_sk#71] + +(62) HashAggregate [codegen id : 17] +Input [3]: [ws_ext_sales_price#66, ws_net_profit#67, wp_web_page_sk#71] +Keys [1]: [wp_web_page_sk#71] +Functions [2]: [partial_sum(UnscaledValue(ws_ext_sales_price#66)), partial_sum(UnscaledValue(ws_net_profit#67))] +Aggregate Attributes [2]: [sum#72, sum#73] +Results [3]: [wp_web_page_sk#71, sum#74, sum#75] + +(63) Exchange +Input [3]: [wp_web_page_sk#71, sum#74, sum#75] +Arguments: hashpartitioning(wp_web_page_sk#71, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(64) HashAggregate [codegen id : 22] +Input [3]: [wp_web_page_sk#71, sum#74, sum#75] +Keys [1]: [wp_web_page_sk#71] +Functions [2]: [sum(UnscaledValue(ws_ext_sales_price#66)), sum(UnscaledValue(ws_net_profit#67))] +Aggregate Attributes [2]: [sum(UnscaledValue(ws_ext_sales_price#66))#76, sum(UnscaledValue(ws_net_profit#67))#77] +Results [3]: [wp_web_page_sk#71, MakeDecimal(sum(UnscaledValue(ws_ext_sales_price#66))#76,17,2) AS sales#78, MakeDecimal(sum(UnscaledValue(ws_net_profit#67))#77,17,2) AS profit#79] + +(65) Scan parquet spark_catalog.default.web_returns +Output [4]: [wr_web_page_sk#80, wr_return_amt#81, wr_net_loss#82, wr_returned_date_sk#83] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(wr_returned_date_sk#83), dynamicpruningexpression(wr_returned_date_sk#83 IN dynamicpruning#84)] +PushedFilters: [IsNotNull(wr_web_page_sk)] +ReadSchema: struct + +(66) CometFilter +Input [4]: [wr_web_page_sk#80, wr_return_amt#81, wr_net_loss#82, wr_returned_date_sk#83] +Condition : isnotnull(wr_web_page_sk#80) + +(67) ColumnarToRow [codegen id : 20] +Input [4]: [wr_web_page_sk#80, wr_return_amt#81, wr_net_loss#82, wr_returned_date_sk#83] + +(68) ReusedExchange [Reuses operator id: 103] +Output [1]: [d_date_sk#85] + +(69) BroadcastHashJoin [codegen id : 20] +Left keys [1]: [wr_returned_date_sk#83] +Right keys [1]: [d_date_sk#85] +Join type: Inner +Join condition: None + +(70) Project [codegen id : 20] +Output [3]: [wr_web_page_sk#80, wr_return_amt#81, wr_net_loss#82] +Input [5]: [wr_web_page_sk#80, wr_return_amt#81, wr_net_loss#82, wr_returned_date_sk#83, d_date_sk#85] + +(71) ReusedExchange [Reuses operator id: 59] +Output [1]: [wp_web_page_sk#86] + +(72) BroadcastHashJoin [codegen id : 20] +Left keys [1]: [wr_web_page_sk#80] +Right keys [1]: [wp_web_page_sk#86] +Join type: Inner +Join condition: None + +(73) Project [codegen id : 20] +Output [3]: [wr_return_amt#81, wr_net_loss#82, wp_web_page_sk#86] +Input [4]: [wr_web_page_sk#80, wr_return_amt#81, wr_net_loss#82, wp_web_page_sk#86] + +(74) HashAggregate [codegen id : 20] +Input [3]: [wr_return_amt#81, wr_net_loss#82, wp_web_page_sk#86] +Keys [1]: [wp_web_page_sk#86] +Functions [2]: [partial_sum(UnscaledValue(wr_return_amt#81)), partial_sum(UnscaledValue(wr_net_loss#82))] +Aggregate Attributes [2]: [sum#87, sum#88] +Results [3]: [wp_web_page_sk#86, sum#89, sum#90] + +(75) Exchange +Input [3]: [wp_web_page_sk#86, sum#89, sum#90] +Arguments: hashpartitioning(wp_web_page_sk#86, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(76) HashAggregate [codegen id : 21] +Input [3]: [wp_web_page_sk#86, sum#89, sum#90] +Keys [1]: [wp_web_page_sk#86] +Functions [2]: [sum(UnscaledValue(wr_return_amt#81)), sum(UnscaledValue(wr_net_loss#82))] +Aggregate Attributes [2]: [sum(UnscaledValue(wr_return_amt#81))#91, sum(UnscaledValue(wr_net_loss#82))#92] +Results [3]: [wp_web_page_sk#86, MakeDecimal(sum(UnscaledValue(wr_return_amt#81))#91,17,2) AS returns#93, MakeDecimal(sum(UnscaledValue(wr_net_loss#82))#92,17,2) AS profit_loss#94] + +(77) BroadcastExchange +Input [3]: [wp_web_page_sk#86, returns#93, profit_loss#94] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=11] + +(78) BroadcastHashJoin [codegen id : 22] +Left keys [1]: [wp_web_page_sk#71] +Right keys [1]: [wp_web_page_sk#86] +Join type: LeftOuter +Join condition: None + +(79) Project [codegen id : 22] +Output [5]: [web channel AS channel#95, wp_web_page_sk#71 AS id#96, sales#78, coalesce(returns#93, 0.00) AS returns#97, (profit#79 - coalesce(profit_loss#94, 0.00)) AS profit#98] +Input [6]: [wp_web_page_sk#71, sales#78, profit#79, wp_web_page_sk#86, returns#93, profit_loss#94] + +(80) Union + +(81) HashAggregate [codegen id : 23] +Input [5]: [channel#31, id#32, sales#14, returns#33, profit#34] +Keys [2]: [channel#31, id#32] +Functions [3]: [partial_sum(sales#14), partial_sum(returns#33), partial_sum(profit#34)] +Aggregate Attributes [6]: [sum#99, isEmpty#100, sum#101, isEmpty#102, sum#103, isEmpty#104] +Results [8]: [channel#31, id#32, sum#105, isEmpty#106, sum#107, isEmpty#108, sum#109, isEmpty#110] + +(82) Exchange +Input [8]: [channel#31, id#32, sum#105, isEmpty#106, sum#107, isEmpty#108, sum#109, isEmpty#110] +Arguments: hashpartitioning(channel#31, id#32, 5), ENSURE_REQUIREMENTS, [plan_id=12] + +(83) HashAggregate [codegen id : 24] +Input [8]: [channel#31, id#32, sum#105, isEmpty#106, sum#107, isEmpty#108, sum#109, isEmpty#110] +Keys [2]: [channel#31, id#32] +Functions [3]: [sum(sales#14), sum(returns#33), sum(profit#34)] +Aggregate Attributes [3]: [sum(sales#14)#111, sum(returns#33)#112, sum(profit#34)#113] +Results [5]: [channel#31, id#32, cast(sum(sales#14)#111 as decimal(37,2)) AS sales#114, cast(sum(returns#33)#112 as decimal(37,2)) AS returns#115, cast(sum(profit#34)#113 as decimal(38,2)) AS profit#116] + +(84) ReusedExchange [Reuses operator id: 82] +Output [8]: [channel#117, id#118, sum#119, isEmpty#120, sum#121, isEmpty#122, sum#123, isEmpty#124] + +(85) HashAggregate [codegen id : 48] +Input [8]: [channel#117, id#118, sum#119, isEmpty#120, sum#121, isEmpty#122, sum#123, isEmpty#124] +Keys [2]: [channel#117, id#118] +Functions [3]: [sum(sales#125), sum(returns#126), sum(profit#127)] +Aggregate Attributes [3]: [sum(sales#125)#111, sum(returns#126)#112, sum(profit#127)#113] +Results [4]: [channel#117, sum(sales#125)#111 AS sales#128, sum(returns#126)#112 AS returns#129, sum(profit#127)#113 AS profit#130] + +(86) HashAggregate [codegen id : 48] +Input [4]: [channel#117, sales#128, returns#129, profit#130] +Keys [1]: [channel#117] +Functions [3]: [partial_sum(sales#128), partial_sum(returns#129), partial_sum(profit#130)] +Aggregate Attributes [6]: [sum#131, isEmpty#132, sum#133, isEmpty#134, sum#135, isEmpty#136] +Results [7]: [channel#117, sum#137, isEmpty#138, sum#139, isEmpty#140, sum#141, isEmpty#142] + +(87) Exchange +Input [7]: [channel#117, sum#137, isEmpty#138, sum#139, isEmpty#140, sum#141, isEmpty#142] +Arguments: hashpartitioning(channel#117, 5), ENSURE_REQUIREMENTS, [plan_id=13] + +(88) HashAggregate [codegen id : 49] +Input [7]: [channel#117, sum#137, isEmpty#138, sum#139, isEmpty#140, sum#141, isEmpty#142] +Keys [1]: [channel#117] +Functions [3]: [sum(sales#128), sum(returns#129), sum(profit#130)] +Aggregate Attributes [3]: [sum(sales#128)#143, sum(returns#129)#144, sum(profit#130)#145] +Results [5]: [channel#117, null AS id#146, sum(sales#128)#143 AS sales#147, sum(returns#129)#144 AS returns#148, sum(profit#130)#145 AS profit#149] + +(89) ReusedExchange [Reuses operator id: 82] +Output [8]: [channel#150, id#151, sum#152, isEmpty#153, sum#154, isEmpty#155, sum#156, isEmpty#157] + +(90) HashAggregate [codegen id : 73] +Input [8]: [channel#150, id#151, sum#152, isEmpty#153, sum#154, isEmpty#155, sum#156, isEmpty#157] +Keys [2]: [channel#150, id#151] +Functions [3]: [sum(sales#158), sum(returns#159), sum(profit#160)] +Aggregate Attributes [3]: [sum(sales#158)#111, sum(returns#159)#112, sum(profit#160)#113] +Results [3]: [sum(sales#158)#111 AS sales#161, sum(returns#159)#112 AS returns#162, sum(profit#160)#113 AS profit#163] + +(91) HashAggregate [codegen id : 73] +Input [3]: [sales#161, returns#162, profit#163] +Keys: [] +Functions [3]: [partial_sum(sales#161), partial_sum(returns#162), partial_sum(profit#163)] +Aggregate Attributes [6]: [sum#164, isEmpty#165, sum#166, isEmpty#167, sum#168, isEmpty#169] +Results [6]: [sum#170, isEmpty#171, sum#172, isEmpty#173, sum#174, isEmpty#175] + +(92) Exchange +Input [6]: [sum#170, isEmpty#171, sum#172, isEmpty#173, sum#174, isEmpty#175] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=14] + +(93) HashAggregate [codegen id : 74] +Input [6]: [sum#170, isEmpty#171, sum#172, isEmpty#173, sum#174, isEmpty#175] +Keys: [] +Functions [3]: [sum(sales#161), sum(returns#162), sum(profit#163)] +Aggregate Attributes [3]: [sum(sales#161)#176, sum(returns#162)#177, sum(profit#163)#178] +Results [5]: [null AS channel#179, null AS id#180, sum(sales#161)#176 AS sales#181, sum(returns#162)#177 AS returns#182, sum(profit#163)#178 AS profit#183] + +(94) Union + +(95) HashAggregate [codegen id : 75] +Input [5]: [channel#31, id#32, sales#114, returns#115, profit#116] +Keys [5]: [channel#31, id#32, sales#114, returns#115, profit#116] +Functions: [] +Aggregate Attributes: [] +Results [5]: [channel#31, id#32, sales#114, returns#115, profit#116] + +(96) Exchange +Input [5]: [channel#31, id#32, sales#114, returns#115, profit#116] +Arguments: hashpartitioning(channel#31, id#32, sales#114, returns#115, profit#116, 5), ENSURE_REQUIREMENTS, [plan_id=15] + +(97) HashAggregate [codegen id : 76] +Input [5]: [channel#31, id#32, sales#114, returns#115, profit#116] +Keys [5]: [channel#31, id#32, sales#114, returns#115, profit#116] +Functions: [] +Aggregate Attributes: [] +Results [5]: [channel#31, id#32, sales#114, returns#115, profit#116] + +(98) TakeOrderedAndProject +Input [5]: [channel#31, id#32, sales#114, returns#115, profit#116] +Arguments: 100, [channel#31 ASC NULLS FIRST, id#32 ASC NULLS FIRST], [channel#31, id#32, sales#114, returns#115, profit#116] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (103) ++- * ColumnarToRow (102) + +- CometProject (101) + +- CometFilter (100) + +- CometScan parquet spark_catalog.default.date_dim (99) + + +(99) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#6, d_date#184] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,1998-08-04), LessThanOrEqual(d_date,1998-09-03), IsNotNull(d_date_sk)] +ReadSchema: struct + +(100) CometFilter +Input [2]: [d_date_sk#6, d_date#184] +Condition : (((isnotnull(d_date#184) AND (d_date#184 >= 1998-08-04)) AND (d_date#184 <= 1998-09-03)) AND isnotnull(d_date_sk#6)) + +(101) CometProject +Input [2]: [d_date_sk#6, d_date#184] +Arguments: [d_date_sk#6], [d_date_sk#6] + +(102) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#6] + +(103) BroadcastExchange +Input [1]: [d_date_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=16] + +Subquery:2 Hosting operator id = 16 Hosting Expression = sr_returned_date_sk#19 IN dynamicpruning#5 + +Subquery:3 Hosting operator id = 31 Hosting Expression = cs_sold_date_sk#38 IN dynamicpruning#5 + +Subquery:4 Hosting operator id = 40 Hosting Expression = cr_returned_date_sk#51 IN dynamicpruning#5 + +Subquery:5 Hosting operator id = 50 Hosting Expression = ws_sold_date_sk#68 IN dynamicpruning#5 + +Subquery:6 Hosting operator id = 65 Hosting Expression = wr_returned_date_sk#83 IN dynamicpruning#5 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q77a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q77a/simplified.txt new file mode 100644 index 0000000000..670a7e6c3e --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q77a/simplified.txt @@ -0,0 +1,168 @@ +TakeOrderedAndProject [channel,id,sales,returns,profit] + WholeStageCodegen (76) + HashAggregate [channel,id,sales,returns,profit] + InputAdapter + Exchange [channel,id,sales,returns,profit] #1 + WholeStageCodegen (75) + HashAggregate [channel,id,sales,returns,profit] + InputAdapter + Union + WholeStageCodegen (24) + HashAggregate [channel,id,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [channel,id] #2 + WholeStageCodegen (23) + HashAggregate [channel,id,sales,returns,profit] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Union + WholeStageCodegen (8) + Project [s_store_sk,sales,returns,profit,profit_loss] + BroadcastHashJoin [s_store_sk,s_store_sk] + HashAggregate [s_store_sk,sum,sum] [sum(UnscaledValue(ss_ext_sales_price)),sum(UnscaledValue(ss_net_profit)),sales,profit,sum,sum] + InputAdapter + Exchange [s_store_sk] #3 + WholeStageCodegen (3) + HashAggregate [s_store_sk,ss_ext_sales_price,ss_net_profit] [sum,sum,sum,sum] + Project [ss_ext_sales_price,ss_net_profit,s_store_sk] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_store_sk,ss_ext_sales_price,ss_net_profit] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_store_sk,ss_ext_sales_price,ss_net_profit,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (7) + HashAggregate [s_store_sk,sum,sum] [sum(UnscaledValue(sr_return_amt)),sum(UnscaledValue(sr_net_loss)),returns,profit_loss,sum,sum] + InputAdapter + Exchange [s_store_sk] #7 + WholeStageCodegen (6) + HashAggregate [s_store_sk,sr_return_amt,sr_net_loss] [sum,sum,sum,sum] + Project [sr_return_amt,sr_net_loss,s_store_sk] + BroadcastHashJoin [sr_store_sk,s_store_sk] + Project [sr_store_sk,sr_return_amt,sr_net_loss] + BroadcastHashJoin [sr_returned_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [sr_store_sk] + CometScan parquet spark_catalog.default.store_returns [sr_store_sk,sr_return_amt,sr_net_loss,sr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + ReusedExchange [s_store_sk] #5 + WholeStageCodegen (14) + Project [cs_call_center_sk,sales,returns,profit,profit_loss] + BroadcastNestedLoopJoin + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (11) + HashAggregate [cs_call_center_sk,sum,sum] [sum(UnscaledValue(cs_ext_sales_price)),sum(UnscaledValue(cs_net_profit)),sales,profit,sum,sum] + InputAdapter + Exchange [cs_call_center_sk] #9 + WholeStageCodegen (10) + HashAggregate [cs_call_center_sk,cs_ext_sales_price,cs_net_profit] [sum,sum,sum,sum] + Project [cs_call_center_sk,cs_ext_sales_price,cs_net_profit] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_call_center_sk,cs_ext_sales_price,cs_net_profit,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #4 + HashAggregate [sum,sum] [sum(UnscaledValue(cr_return_amount)),sum(UnscaledValue(cr_net_loss)),returns,profit_loss,sum,sum] + InputAdapter + Exchange #10 + WholeStageCodegen (13) + HashAggregate [cr_return_amount,cr_net_loss] [sum,sum,sum,sum] + Project [cr_return_amount,cr_net_loss] + BroadcastHashJoin [cr_returned_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_returns [cr_return_amount,cr_net_loss,cr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #4 + WholeStageCodegen (22) + Project [wp_web_page_sk,sales,returns,profit,profit_loss] + BroadcastHashJoin [wp_web_page_sk,wp_web_page_sk] + HashAggregate [wp_web_page_sk,sum,sum] [sum(UnscaledValue(ws_ext_sales_price)),sum(UnscaledValue(ws_net_profit)),sales,profit,sum,sum] + InputAdapter + Exchange [wp_web_page_sk] #11 + WholeStageCodegen (17) + HashAggregate [wp_web_page_sk,ws_ext_sales_price,ws_net_profit] [sum,sum,sum,sum] + Project [ws_ext_sales_price,ws_net_profit,wp_web_page_sk] + BroadcastHashJoin [ws_web_page_sk,wp_web_page_sk] + Project [ws_web_page_sk,ws_ext_sales_price,ws_net_profit] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ws_web_page_sk] + CometScan parquet spark_catalog.default.web_sales [ws_web_page_sk,ws_ext_sales_price,ws_net_profit,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #12 + WholeStageCodegen (16) + ColumnarToRow + InputAdapter + CometFilter [wp_web_page_sk] + CometScan parquet spark_catalog.default.web_page [wp_web_page_sk] + InputAdapter + BroadcastExchange #13 + WholeStageCodegen (21) + HashAggregate [wp_web_page_sk,sum,sum] [sum(UnscaledValue(wr_return_amt)),sum(UnscaledValue(wr_net_loss)),returns,profit_loss,sum,sum] + InputAdapter + Exchange [wp_web_page_sk] #14 + WholeStageCodegen (20) + HashAggregate [wp_web_page_sk,wr_return_amt,wr_net_loss] [sum,sum,sum,sum] + Project [wr_return_amt,wr_net_loss,wp_web_page_sk] + BroadcastHashJoin [wr_web_page_sk,wp_web_page_sk] + Project [wr_web_page_sk,wr_return_amt,wr_net_loss] + BroadcastHashJoin [wr_returned_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [wr_web_page_sk] + CometScan parquet spark_catalog.default.web_returns [wr_web_page_sk,wr_return_amt,wr_net_loss,wr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + ReusedExchange [wp_web_page_sk] #12 + WholeStageCodegen (49) + HashAggregate [channel,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),id,sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [channel] #15 + WholeStageCodegen (48) + HashAggregate [channel,sales,returns,profit] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + HashAggregate [channel,id,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + ReusedExchange [channel,id,sum,isEmpty,sum,isEmpty,sum,isEmpty] #2 + WholeStageCodegen (74) + HashAggregate [sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),channel,id,sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange #16 + WholeStageCodegen (73) + HashAggregate [sales,returns,profit] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + HashAggregate [channel,id,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + ReusedExchange [channel,id,sum,isEmpty,sum,isEmpty,sum,isEmpty] #2 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q78/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q78/explain.txt new file mode 100644 index 0000000000..c7ee5b1c95 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q78/explain.txt @@ -0,0 +1,431 @@ +== Physical Plan == +TakeOrderedAndProject (70) ++- * Project (69) + +- * SortMergeJoin Inner (68) + :- * Project (45) + : +- * SortMergeJoin Inner (44) + : :- * Sort (21) + : : +- * HashAggregate (20) + : : +- Exchange (19) + : : +- * HashAggregate (18) + : : +- * Project (17) + : : +- * BroadcastHashJoin Inner BuildRight (16) + : : :- * Project (14) + : : : +- * Filter (13) + : : : +- * SortMergeJoin LeftOuter (12) + : : : :- * Sort (5) + : : : : +- Exchange (4) + : : : : +- * ColumnarToRow (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- * Sort (11) + : : : +- Exchange (10) + : : : +- * ColumnarToRow (9) + : : : +- CometProject (8) + : : : +- CometFilter (7) + : : : +- CometScan parquet spark_catalog.default.store_returns (6) + : : +- ReusedExchange (15) + : +- * Sort (43) + : +- * Filter (42) + : +- * HashAggregate (41) + : +- Exchange (40) + : +- * HashAggregate (39) + : +- * Project (38) + : +- * BroadcastHashJoin Inner BuildRight (37) + : :- * Project (35) + : : +- * Filter (34) + : : +- * SortMergeJoin LeftOuter (33) + : : :- * Sort (26) + : : : +- Exchange (25) + : : : +- * ColumnarToRow (24) + : : : +- CometFilter (23) + : : : +- CometScan parquet spark_catalog.default.web_sales (22) + : : +- * Sort (32) + : : +- Exchange (31) + : : +- * ColumnarToRow (30) + : : +- CometProject (29) + : : +- CometFilter (28) + : : +- CometScan parquet spark_catalog.default.web_returns (27) + : +- ReusedExchange (36) + +- * Sort (67) + +- * Filter (66) + +- * HashAggregate (65) + +- Exchange (64) + +- * HashAggregate (63) + +- * Project (62) + +- * BroadcastHashJoin Inner BuildRight (61) + :- * Project (59) + : +- * Filter (58) + : +- * SortMergeJoin LeftOuter (57) + : :- * Sort (50) + : : +- Exchange (49) + : : +- * ColumnarToRow (48) + : : +- CometFilter (47) + : : +- CometScan parquet spark_catalog.default.catalog_sales (46) + : +- * Sort (56) + : +- Exchange (55) + : +- * ColumnarToRow (54) + : +- CometProject (53) + : +- CometFilter (52) + : +- CometScan parquet spark_catalog.default.catalog_returns (51) + +- ReusedExchange (60) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [7]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sold_date_sk#7 IN dynamicpruning#8)] +PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(2) CometFilter +Input [7]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7] +Condition : (isnotnull(ss_item_sk#1) AND isnotnull(ss_customer_sk#2)) + +(3) ColumnarToRow [codegen id : 1] +Input [7]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7] + +(4) Exchange +Input [7]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7] +Arguments: hashpartitioning(ss_ticket_number#3, ss_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(5) Sort [codegen id : 2] +Input [7]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7] +Arguments: [ss_ticket_number#3 ASC NULLS FIRST, ss_item_sk#1 ASC NULLS FIRST], false, 0 + +(6) Scan parquet spark_catalog.default.store_returns +Output [3]: [sr_item_sk#9, sr_ticket_number#10, sr_returned_date_sk#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_returns] +PushedFilters: [IsNotNull(sr_ticket_number), IsNotNull(sr_item_sk)] +ReadSchema: struct + +(7) CometFilter +Input [3]: [sr_item_sk#9, sr_ticket_number#10, sr_returned_date_sk#11] +Condition : (isnotnull(sr_ticket_number#10) AND isnotnull(sr_item_sk#9)) + +(8) CometProject +Input [3]: [sr_item_sk#9, sr_ticket_number#10, sr_returned_date_sk#11] +Arguments: [sr_item_sk#9, sr_ticket_number#10], [sr_item_sk#9, sr_ticket_number#10] + +(9) ColumnarToRow [codegen id : 3] +Input [2]: [sr_item_sk#9, sr_ticket_number#10] + +(10) Exchange +Input [2]: [sr_item_sk#9, sr_ticket_number#10] +Arguments: hashpartitioning(sr_ticket_number#10, sr_item_sk#9, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(11) Sort [codegen id : 4] +Input [2]: [sr_item_sk#9, sr_ticket_number#10] +Arguments: [sr_ticket_number#10 ASC NULLS FIRST, sr_item_sk#9 ASC NULLS FIRST], false, 0 + +(12) SortMergeJoin [codegen id : 6] +Left keys [2]: [ss_ticket_number#3, ss_item_sk#1] +Right keys [2]: [sr_ticket_number#10, sr_item_sk#9] +Join type: LeftOuter +Join condition: None + +(13) Filter [codegen id : 6] +Input [9]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7, sr_item_sk#9, sr_ticket_number#10] +Condition : isnull(sr_ticket_number#10) + +(14) Project [codegen id : 6] +Output [6]: [ss_item_sk#1, ss_customer_sk#2, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7] +Input [9]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7, sr_item_sk#9, sr_ticket_number#10] + +(15) ReusedExchange [Reuses operator id: 74] +Output [2]: [d_date_sk#12, d_year#13] + +(16) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_sold_date_sk#7] +Right keys [1]: [d_date_sk#12] +Join type: Inner +Join condition: None + +(17) Project [codegen id : 6] +Output [6]: [ss_item_sk#1, ss_customer_sk#2, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, d_year#13] +Input [8]: [ss_item_sk#1, ss_customer_sk#2, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7, d_date_sk#12, d_year#13] + +(18) HashAggregate [codegen id : 6] +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, d_year#13] +Keys [3]: [d_year#13, ss_item_sk#1, ss_customer_sk#2] +Functions [3]: [partial_sum(ss_quantity#4), partial_sum(UnscaledValue(ss_wholesale_cost#5)), partial_sum(UnscaledValue(ss_sales_price#6))] +Aggregate Attributes [3]: [sum#14, sum#15, sum#16] +Results [6]: [d_year#13, ss_item_sk#1, ss_customer_sk#2, sum#17, sum#18, sum#19] + +(19) Exchange +Input [6]: [d_year#13, ss_item_sk#1, ss_customer_sk#2, sum#17, sum#18, sum#19] +Arguments: hashpartitioning(d_year#13, ss_item_sk#1, ss_customer_sk#2, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(20) HashAggregate [codegen id : 7] +Input [6]: [d_year#13, ss_item_sk#1, ss_customer_sk#2, sum#17, sum#18, sum#19] +Keys [3]: [d_year#13, ss_item_sk#1, ss_customer_sk#2] +Functions [3]: [sum(ss_quantity#4), sum(UnscaledValue(ss_wholesale_cost#5)), sum(UnscaledValue(ss_sales_price#6))] +Aggregate Attributes [3]: [sum(ss_quantity#4)#20, sum(UnscaledValue(ss_wholesale_cost#5))#21, sum(UnscaledValue(ss_sales_price#6))#22] +Results [6]: [d_year#13 AS ss_sold_year#23, ss_item_sk#1, ss_customer_sk#2, sum(ss_quantity#4)#20 AS ss_qty#24, MakeDecimal(sum(UnscaledValue(ss_wholesale_cost#5))#21,17,2) AS ss_wc#25, MakeDecimal(sum(UnscaledValue(ss_sales_price#6))#22,17,2) AS ss_sp#26] + +(21) Sort [codegen id : 7] +Input [6]: [ss_sold_year#23, ss_item_sk#1, ss_customer_sk#2, ss_qty#24, ss_wc#25, ss_sp#26] +Arguments: [ss_sold_year#23 ASC NULLS FIRST, ss_item_sk#1 ASC NULLS FIRST, ss_customer_sk#2 ASC NULLS FIRST], false, 0 + +(22) Scan parquet spark_catalog.default.web_sales +Output [7]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_order_number#29, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#33), dynamicpruningexpression(ws_sold_date_sk#33 IN dynamicpruning#34)] +PushedFilters: [IsNotNull(ws_item_sk), IsNotNull(ws_bill_customer_sk)] +ReadSchema: struct + +(23) CometFilter +Input [7]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_order_number#29, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33] +Condition : (isnotnull(ws_item_sk#27) AND isnotnull(ws_bill_customer_sk#28)) + +(24) ColumnarToRow [codegen id : 8] +Input [7]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_order_number#29, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33] + +(25) Exchange +Input [7]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_order_number#29, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33] +Arguments: hashpartitioning(ws_order_number#29, ws_item_sk#27, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(26) Sort [codegen id : 9] +Input [7]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_order_number#29, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33] +Arguments: [ws_order_number#29 ASC NULLS FIRST, ws_item_sk#27 ASC NULLS FIRST], false, 0 + +(27) Scan parquet spark_catalog.default.web_returns +Output [3]: [wr_item_sk#35, wr_order_number#36, wr_returned_date_sk#37] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_returns] +PushedFilters: [IsNotNull(wr_order_number), IsNotNull(wr_item_sk)] +ReadSchema: struct + +(28) CometFilter +Input [3]: [wr_item_sk#35, wr_order_number#36, wr_returned_date_sk#37] +Condition : (isnotnull(wr_order_number#36) AND isnotnull(wr_item_sk#35)) + +(29) CometProject +Input [3]: [wr_item_sk#35, wr_order_number#36, wr_returned_date_sk#37] +Arguments: [wr_item_sk#35, wr_order_number#36], [wr_item_sk#35, wr_order_number#36] + +(30) ColumnarToRow [codegen id : 10] +Input [2]: [wr_item_sk#35, wr_order_number#36] + +(31) Exchange +Input [2]: [wr_item_sk#35, wr_order_number#36] +Arguments: hashpartitioning(wr_order_number#36, wr_item_sk#35, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(32) Sort [codegen id : 11] +Input [2]: [wr_item_sk#35, wr_order_number#36] +Arguments: [wr_order_number#36 ASC NULLS FIRST, wr_item_sk#35 ASC NULLS FIRST], false, 0 + +(33) SortMergeJoin [codegen id : 13] +Left keys [2]: [ws_order_number#29, ws_item_sk#27] +Right keys [2]: [wr_order_number#36, wr_item_sk#35] +Join type: LeftOuter +Join condition: None + +(34) Filter [codegen id : 13] +Input [9]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_order_number#29, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33, wr_item_sk#35, wr_order_number#36] +Condition : isnull(wr_order_number#36) + +(35) Project [codegen id : 13] +Output [6]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33] +Input [9]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_order_number#29, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33, wr_item_sk#35, wr_order_number#36] + +(36) ReusedExchange [Reuses operator id: 74] +Output [2]: [d_date_sk#38, d_year#39] + +(37) BroadcastHashJoin [codegen id : 13] +Left keys [1]: [ws_sold_date_sk#33] +Right keys [1]: [d_date_sk#38] +Join type: Inner +Join condition: None + +(38) Project [codegen id : 13] +Output [6]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, d_year#39] +Input [8]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33, d_date_sk#38, d_year#39] + +(39) HashAggregate [codegen id : 13] +Input [6]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, d_year#39] +Keys [3]: [d_year#39, ws_item_sk#27, ws_bill_customer_sk#28] +Functions [3]: [partial_sum(ws_quantity#30), partial_sum(UnscaledValue(ws_wholesale_cost#31)), partial_sum(UnscaledValue(ws_sales_price#32))] +Aggregate Attributes [3]: [sum#40, sum#41, sum#42] +Results [6]: [d_year#39, ws_item_sk#27, ws_bill_customer_sk#28, sum#43, sum#44, sum#45] + +(40) Exchange +Input [6]: [d_year#39, ws_item_sk#27, ws_bill_customer_sk#28, sum#43, sum#44, sum#45] +Arguments: hashpartitioning(d_year#39, ws_item_sk#27, ws_bill_customer_sk#28, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(41) HashAggregate [codegen id : 14] +Input [6]: [d_year#39, ws_item_sk#27, ws_bill_customer_sk#28, sum#43, sum#44, sum#45] +Keys [3]: [d_year#39, ws_item_sk#27, ws_bill_customer_sk#28] +Functions [3]: [sum(ws_quantity#30), sum(UnscaledValue(ws_wholesale_cost#31)), sum(UnscaledValue(ws_sales_price#32))] +Aggregate Attributes [3]: [sum(ws_quantity#30)#46, sum(UnscaledValue(ws_wholesale_cost#31))#47, sum(UnscaledValue(ws_sales_price#32))#48] +Results [6]: [d_year#39 AS ws_sold_year#49, ws_item_sk#27, ws_bill_customer_sk#28 AS ws_customer_sk#50, sum(ws_quantity#30)#46 AS ws_qty#51, MakeDecimal(sum(UnscaledValue(ws_wholesale_cost#31))#47,17,2) AS ws_wc#52, MakeDecimal(sum(UnscaledValue(ws_sales_price#32))#48,17,2) AS ws_sp#53] + +(42) Filter [codegen id : 14] +Input [6]: [ws_sold_year#49, ws_item_sk#27, ws_customer_sk#50, ws_qty#51, ws_wc#52, ws_sp#53] +Condition : (coalesce(ws_qty#51, 0) > 0) + +(43) Sort [codegen id : 14] +Input [6]: [ws_sold_year#49, ws_item_sk#27, ws_customer_sk#50, ws_qty#51, ws_wc#52, ws_sp#53] +Arguments: [ws_sold_year#49 ASC NULLS FIRST, ws_item_sk#27 ASC NULLS FIRST, ws_customer_sk#50 ASC NULLS FIRST], false, 0 + +(44) SortMergeJoin [codegen id : 15] +Left keys [3]: [ss_sold_year#23, ss_item_sk#1, ss_customer_sk#2] +Right keys [3]: [ws_sold_year#49, ws_item_sk#27, ws_customer_sk#50] +Join type: Inner +Join condition: None + +(45) Project [codegen id : 15] +Output [9]: [ss_sold_year#23, ss_item_sk#1, ss_customer_sk#2, ss_qty#24, ss_wc#25, ss_sp#26, ws_qty#51, ws_wc#52, ws_sp#53] +Input [12]: [ss_sold_year#23, ss_item_sk#1, ss_customer_sk#2, ss_qty#24, ss_wc#25, ss_sp#26, ws_sold_year#49, ws_item_sk#27, ws_customer_sk#50, ws_qty#51, ws_wc#52, ws_sp#53] + +(46) Scan parquet spark_catalog.default.catalog_sales +Output [7]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_order_number#56, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#60), dynamicpruningexpression(cs_sold_date_sk#60 IN dynamicpruning#61)] +PushedFilters: [IsNotNull(cs_item_sk), IsNotNull(cs_bill_customer_sk)] +ReadSchema: struct + +(47) CometFilter +Input [7]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_order_number#56, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60] +Condition : (isnotnull(cs_item_sk#55) AND isnotnull(cs_bill_customer_sk#54)) + +(48) ColumnarToRow [codegen id : 16] +Input [7]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_order_number#56, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60] + +(49) Exchange +Input [7]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_order_number#56, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60] +Arguments: hashpartitioning(cs_order_number#56, cs_item_sk#55, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(50) Sort [codegen id : 17] +Input [7]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_order_number#56, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60] +Arguments: [cs_order_number#56 ASC NULLS FIRST, cs_item_sk#55 ASC NULLS FIRST], false, 0 + +(51) Scan parquet spark_catalog.default.catalog_returns +Output [3]: [cr_item_sk#62, cr_order_number#63, cr_returned_date_sk#64] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_returns] +PushedFilters: [IsNotNull(cr_order_number), IsNotNull(cr_item_sk)] +ReadSchema: struct + +(52) CometFilter +Input [3]: [cr_item_sk#62, cr_order_number#63, cr_returned_date_sk#64] +Condition : (isnotnull(cr_order_number#63) AND isnotnull(cr_item_sk#62)) + +(53) CometProject +Input [3]: [cr_item_sk#62, cr_order_number#63, cr_returned_date_sk#64] +Arguments: [cr_item_sk#62, cr_order_number#63], [cr_item_sk#62, cr_order_number#63] + +(54) ColumnarToRow [codegen id : 18] +Input [2]: [cr_item_sk#62, cr_order_number#63] + +(55) Exchange +Input [2]: [cr_item_sk#62, cr_order_number#63] +Arguments: hashpartitioning(cr_order_number#63, cr_item_sk#62, 5), ENSURE_REQUIREMENTS, [plan_id=8] + +(56) Sort [codegen id : 19] +Input [2]: [cr_item_sk#62, cr_order_number#63] +Arguments: [cr_order_number#63 ASC NULLS FIRST, cr_item_sk#62 ASC NULLS FIRST], false, 0 + +(57) SortMergeJoin [codegen id : 21] +Left keys [2]: [cs_order_number#56, cs_item_sk#55] +Right keys [2]: [cr_order_number#63, cr_item_sk#62] +Join type: LeftOuter +Join condition: None + +(58) Filter [codegen id : 21] +Input [9]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_order_number#56, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60, cr_item_sk#62, cr_order_number#63] +Condition : isnull(cr_order_number#63) + +(59) Project [codegen id : 21] +Output [6]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60] +Input [9]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_order_number#56, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60, cr_item_sk#62, cr_order_number#63] + +(60) ReusedExchange [Reuses operator id: 74] +Output [2]: [d_date_sk#65, d_year#66] + +(61) BroadcastHashJoin [codegen id : 21] +Left keys [1]: [cs_sold_date_sk#60] +Right keys [1]: [d_date_sk#65] +Join type: Inner +Join condition: None + +(62) Project [codegen id : 21] +Output [6]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, d_year#66] +Input [8]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60, d_date_sk#65, d_year#66] + +(63) HashAggregate [codegen id : 21] +Input [6]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, d_year#66] +Keys [3]: [d_year#66, cs_item_sk#55, cs_bill_customer_sk#54] +Functions [3]: [partial_sum(cs_quantity#57), partial_sum(UnscaledValue(cs_wholesale_cost#58)), partial_sum(UnscaledValue(cs_sales_price#59))] +Aggregate Attributes [3]: [sum#67, sum#68, sum#69] +Results [6]: [d_year#66, cs_item_sk#55, cs_bill_customer_sk#54, sum#70, sum#71, sum#72] + +(64) Exchange +Input [6]: [d_year#66, cs_item_sk#55, cs_bill_customer_sk#54, sum#70, sum#71, sum#72] +Arguments: hashpartitioning(d_year#66, cs_item_sk#55, cs_bill_customer_sk#54, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(65) HashAggregate [codegen id : 22] +Input [6]: [d_year#66, cs_item_sk#55, cs_bill_customer_sk#54, sum#70, sum#71, sum#72] +Keys [3]: [d_year#66, cs_item_sk#55, cs_bill_customer_sk#54] +Functions [3]: [sum(cs_quantity#57), sum(UnscaledValue(cs_wholesale_cost#58)), sum(UnscaledValue(cs_sales_price#59))] +Aggregate Attributes [3]: [sum(cs_quantity#57)#73, sum(UnscaledValue(cs_wholesale_cost#58))#74, sum(UnscaledValue(cs_sales_price#59))#75] +Results [6]: [d_year#66 AS cs_sold_year#76, cs_item_sk#55, cs_bill_customer_sk#54 AS cs_customer_sk#77, sum(cs_quantity#57)#73 AS cs_qty#78, MakeDecimal(sum(UnscaledValue(cs_wholesale_cost#58))#74,17,2) AS cs_wc#79, MakeDecimal(sum(UnscaledValue(cs_sales_price#59))#75,17,2) AS cs_sp#80] + +(66) Filter [codegen id : 22] +Input [6]: [cs_sold_year#76, cs_item_sk#55, cs_customer_sk#77, cs_qty#78, cs_wc#79, cs_sp#80] +Condition : (coalesce(cs_qty#78, 0) > 0) + +(67) Sort [codegen id : 22] +Input [6]: [cs_sold_year#76, cs_item_sk#55, cs_customer_sk#77, cs_qty#78, cs_wc#79, cs_sp#80] +Arguments: [cs_sold_year#76 ASC NULLS FIRST, cs_item_sk#55 ASC NULLS FIRST, cs_customer_sk#77 ASC NULLS FIRST], false, 0 + +(68) SortMergeJoin [codegen id : 23] +Left keys [3]: [ss_sold_year#23, ss_item_sk#1, ss_customer_sk#2] +Right keys [3]: [cs_sold_year#76, cs_item_sk#55, cs_customer_sk#77] +Join type: Inner +Join condition: None + +(69) Project [codegen id : 23] +Output [13]: [round((cast(ss_qty#24 as double) / cast(coalesce((ws_qty#51 + cs_qty#78), 1) as double)), 2) AS ratio#81, ss_qty#24 AS store_qty#82, ss_wc#25 AS store_wholesale_cost#83, ss_sp#26 AS store_sales_price#84, (coalesce(ws_qty#51, 0) + coalesce(cs_qty#78, 0)) AS other_chan_qty#85, (coalesce(ws_wc#52, 0.00) + coalesce(cs_wc#79, 0.00)) AS other_chan_wholesale_cost#86, (coalesce(ws_sp#53, 0.00) + coalesce(cs_sp#80, 0.00)) AS other_chan_sales_price#87, ss_sold_year#23, ss_item_sk#1, ss_customer_sk#2, ss_qty#24, ss_wc#25, ss_sp#26] +Input [15]: [ss_sold_year#23, ss_item_sk#1, ss_customer_sk#2, ss_qty#24, ss_wc#25, ss_sp#26, ws_qty#51, ws_wc#52, ws_sp#53, cs_sold_year#76, cs_item_sk#55, cs_customer_sk#77, cs_qty#78, cs_wc#79, cs_sp#80] + +(70) TakeOrderedAndProject +Input [13]: [ratio#81, store_qty#82, store_wholesale_cost#83, store_sales_price#84, other_chan_qty#85, other_chan_wholesale_cost#86, other_chan_sales_price#87, ss_sold_year#23, ss_item_sk#1, ss_customer_sk#2, ss_qty#24, ss_wc#25, ss_sp#26] +Arguments: 100, [ss_sold_year#23 ASC NULLS FIRST, ss_item_sk#1 ASC NULLS FIRST, ss_customer_sk#2 ASC NULLS FIRST, ss_qty#24 DESC NULLS LAST, ss_wc#25 DESC NULLS LAST, ss_sp#26 DESC NULLS LAST, other_chan_qty#85 ASC NULLS FIRST, other_chan_wholesale_cost#86 ASC NULLS FIRST, other_chan_sales_price#87 ASC NULLS FIRST, ratio#81 ASC NULLS FIRST], [ratio#81, store_qty#82, store_wholesale_cost#83, store_sales_price#84, other_chan_qty#85, other_chan_wholesale_cost#86, other_chan_sales_price#87] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (74) ++- * ColumnarToRow (73) + +- CometFilter (72) + +- CometScan parquet spark_catalog.default.date_dim (71) + + +(71) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#12, d_year#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2000), IsNotNull(d_date_sk)] +ReadSchema: struct + +(72) CometFilter +Input [2]: [d_date_sk#12, d_year#13] +Condition : ((isnotnull(d_year#13) AND (d_year#13 = 2000)) AND isnotnull(d_date_sk#12)) + +(73) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#12, d_year#13] + +(74) BroadcastExchange +Input [2]: [d_date_sk#12, d_year#13] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=10] + +Subquery:2 Hosting operator id = 22 Hosting Expression = ws_sold_date_sk#33 IN dynamicpruning#8 + +Subquery:3 Hosting operator id = 46 Hosting Expression = cs_sold_date_sk#60 IN dynamicpruning#8 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q78/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q78/simplified.txt new file mode 100644 index 0000000000..49bd173f67 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q78/simplified.txt @@ -0,0 +1,127 @@ +TakeOrderedAndProject [ss_sold_year,ss_item_sk,ss_customer_sk,ss_qty,ss_wc,ss_sp,other_chan_qty,other_chan_wholesale_cost,other_chan_sales_price,ratio,store_qty,store_wholesale_cost,store_sales_price] + WholeStageCodegen (23) + Project [ss_qty,ws_qty,cs_qty,ss_wc,ss_sp,ws_wc,cs_wc,ws_sp,cs_sp,ss_sold_year,ss_item_sk,ss_customer_sk] + SortMergeJoin [ss_sold_year,ss_item_sk,ss_customer_sk,cs_sold_year,cs_item_sk,cs_customer_sk] + InputAdapter + WholeStageCodegen (15) + Project [ss_sold_year,ss_item_sk,ss_customer_sk,ss_qty,ss_wc,ss_sp,ws_qty,ws_wc,ws_sp] + SortMergeJoin [ss_sold_year,ss_item_sk,ss_customer_sk,ws_sold_year,ws_item_sk,ws_customer_sk] + InputAdapter + WholeStageCodegen (7) + Sort [ss_sold_year,ss_item_sk,ss_customer_sk] + HashAggregate [d_year,ss_item_sk,ss_customer_sk,sum,sum,sum] [sum(ss_quantity),sum(UnscaledValue(ss_wholesale_cost)),sum(UnscaledValue(ss_sales_price)),ss_sold_year,ss_qty,ss_wc,ss_sp,sum,sum,sum] + InputAdapter + Exchange [d_year,ss_item_sk,ss_customer_sk] #1 + WholeStageCodegen (6) + HashAggregate [d_year,ss_item_sk,ss_customer_sk,ss_quantity,ss_wholesale_cost,ss_sales_price] [sum,sum,sum,sum,sum,sum] + Project [ss_item_sk,ss_customer_sk,ss_quantity,ss_wholesale_cost,ss_sales_price,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_customer_sk,ss_quantity,ss_wholesale_cost,ss_sales_price,ss_sold_date_sk] + Filter [sr_ticket_number] + SortMergeJoin [ss_ticket_number,ss_item_sk,sr_ticket_number,sr_item_sk] + InputAdapter + WholeStageCodegen (2) + Sort [ss_ticket_number,ss_item_sk] + InputAdapter + Exchange [ss_ticket_number,ss_item_sk] #2 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk,ss_customer_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_ticket_number,ss_quantity,ss_wholesale_cost,ss_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + WholeStageCodegen (4) + Sort [sr_ticket_number,sr_item_sk] + InputAdapter + Exchange [sr_ticket_number,sr_item_sk] #4 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometProject [sr_item_sk,sr_ticket_number] + CometFilter [sr_ticket_number,sr_item_sk] + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk,d_year] #3 + InputAdapter + WholeStageCodegen (14) + Sort [ws_sold_year,ws_item_sk,ws_customer_sk] + Filter [ws_qty] + HashAggregate [d_year,ws_item_sk,ws_bill_customer_sk,sum,sum,sum] [sum(ws_quantity),sum(UnscaledValue(ws_wholesale_cost)),sum(UnscaledValue(ws_sales_price)),ws_sold_year,ws_customer_sk,ws_qty,ws_wc,ws_sp,sum,sum,sum] + InputAdapter + Exchange [d_year,ws_item_sk,ws_bill_customer_sk] #5 + WholeStageCodegen (13) + HashAggregate [d_year,ws_item_sk,ws_bill_customer_sk,ws_quantity,ws_wholesale_cost,ws_sales_price] [sum,sum,sum,sum,sum,sum] + Project [ws_item_sk,ws_bill_customer_sk,ws_quantity,ws_wholesale_cost,ws_sales_price,d_year] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_item_sk,ws_bill_customer_sk,ws_quantity,ws_wholesale_cost,ws_sales_price,ws_sold_date_sk] + Filter [wr_order_number] + SortMergeJoin [ws_order_number,ws_item_sk,wr_order_number,wr_item_sk] + InputAdapter + WholeStageCodegen (9) + Sort [ws_order_number,ws_item_sk] + InputAdapter + Exchange [ws_order_number,ws_item_sk] #6 + WholeStageCodegen (8) + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk,ws_bill_customer_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_bill_customer_sk,ws_order_number,ws_quantity,ws_wholesale_cost,ws_sales_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + WholeStageCodegen (11) + Sort [wr_order_number,wr_item_sk] + InputAdapter + Exchange [wr_order_number,wr_item_sk] #7 + WholeStageCodegen (10) + ColumnarToRow + InputAdapter + CometProject [wr_item_sk,wr_order_number] + CometFilter [wr_order_number,wr_item_sk] + CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_order_number,wr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk,d_year] #3 + InputAdapter + WholeStageCodegen (22) + Sort [cs_sold_year,cs_item_sk,cs_customer_sk] + Filter [cs_qty] + HashAggregate [d_year,cs_item_sk,cs_bill_customer_sk,sum,sum,sum] [sum(cs_quantity),sum(UnscaledValue(cs_wholesale_cost)),sum(UnscaledValue(cs_sales_price)),cs_sold_year,cs_customer_sk,cs_qty,cs_wc,cs_sp,sum,sum,sum] + InputAdapter + Exchange [d_year,cs_item_sk,cs_bill_customer_sk] #8 + WholeStageCodegen (21) + HashAggregate [d_year,cs_item_sk,cs_bill_customer_sk,cs_quantity,cs_wholesale_cost,cs_sales_price] [sum,sum,sum,sum,sum,sum] + Project [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_wholesale_cost,cs_sales_price,d_year] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_wholesale_cost,cs_sales_price,cs_sold_date_sk] + Filter [cr_order_number] + SortMergeJoin [cs_order_number,cs_item_sk,cr_order_number,cr_item_sk] + InputAdapter + WholeStageCodegen (17) + Sort [cs_order_number,cs_item_sk] + InputAdapter + Exchange [cs_order_number,cs_item_sk] #9 + WholeStageCodegen (16) + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk,cs_bill_customer_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_item_sk,cs_order_number,cs_quantity,cs_wholesale_cost,cs_sales_price,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + WholeStageCodegen (19) + Sort [cr_order_number,cr_item_sk] + InputAdapter + Exchange [cr_order_number,cr_item_sk] #10 + WholeStageCodegen (18) + ColumnarToRow + InputAdapter + CometProject [cr_item_sk,cr_order_number] + CometFilter [cr_order_number,cr_item_sk] + CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk,d_year] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q80a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q80a/explain.txt new file mode 100644 index 0000000000..8f47f4f0e7 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q80a/explain.txt @@ -0,0 +1,730 @@ +== Physical Plan == +TakeOrderedAndProject (120) ++- * HashAggregate (119) + +- Exchange (118) + +- * HashAggregate (117) + +- Union (116) + :- * HashAggregate (105) + : +- Exchange (104) + : +- * HashAggregate (103) + : +- Union (102) + : :- * HashAggregate (39) + : : +- Exchange (38) + : : +- * HashAggregate (37) + : : +- * Project (36) + : : +- * BroadcastHashJoin Inner BuildRight (35) + : : :- * Project (29) + : : : +- * BroadcastHashJoin Inner BuildRight (28) + : : : :- * Project (22) + : : : : +- * BroadcastHashJoin Inner BuildRight (21) + : : : : :- * Project (16) + : : : : : +- * BroadcastHashJoin Inner BuildRight (15) + : : : : : :- * Project (13) + : : : : : : +- * SortMergeJoin LeftOuter (12) + : : : : : : :- * Sort (5) + : : : : : : : +- Exchange (4) + : : : : : : : +- * ColumnarToRow (3) + : : : : : : : +- CometFilter (2) + : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : : : +- * Sort (11) + : : : : : : +- Exchange (10) + : : : : : : +- * ColumnarToRow (9) + : : : : : : +- CometProject (8) + : : : : : : +- CometFilter (7) + : : : : : : +- CometScan parquet spark_catalog.default.store_returns (6) + : : : : : +- ReusedExchange (14) + : : : : +- BroadcastExchange (20) + : : : : +- * ColumnarToRow (19) + : : : : +- CometFilter (18) + : : : : +- CometScan parquet spark_catalog.default.store (17) + : : : +- BroadcastExchange (27) + : : : +- * ColumnarToRow (26) + : : : +- CometProject (25) + : : : +- CometFilter (24) + : : : +- CometScan parquet spark_catalog.default.item (23) + : : +- BroadcastExchange (34) + : : +- * ColumnarToRow (33) + : : +- CometProject (32) + : : +- CometFilter (31) + : : +- CometScan parquet spark_catalog.default.promotion (30) + : :- * HashAggregate (70) + : : +- Exchange (69) + : : +- * HashAggregate (68) + : : +- * Project (67) + : : +- * BroadcastHashJoin Inner BuildRight (66) + : : :- * Project (64) + : : : +- * BroadcastHashJoin Inner BuildRight (63) + : : : :- * Project (61) + : : : : +- * BroadcastHashJoin Inner BuildRight (60) + : : : : :- * Project (55) + : : : : : +- * BroadcastHashJoin Inner BuildRight (54) + : : : : : :- * Project (52) + : : : : : : +- * SortMergeJoin LeftOuter (51) + : : : : : : :- * Sort (44) + : : : : : : : +- Exchange (43) + : : : : : : : +- * ColumnarToRow (42) + : : : : : : : +- CometFilter (41) + : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (40) + : : : : : : +- * Sort (50) + : : : : : : +- Exchange (49) + : : : : : : +- * ColumnarToRow (48) + : : : : : : +- CometProject (47) + : : : : : : +- CometFilter (46) + : : : : : : +- CometScan parquet spark_catalog.default.catalog_returns (45) + : : : : : +- ReusedExchange (53) + : : : : +- BroadcastExchange (59) + : : : : +- * ColumnarToRow (58) + : : : : +- CometFilter (57) + : : : : +- CometScan parquet spark_catalog.default.catalog_page (56) + : : : +- ReusedExchange (62) + : : +- ReusedExchange (65) + : +- * HashAggregate (101) + : +- Exchange (100) + : +- * HashAggregate (99) + : +- * Project (98) + : +- * BroadcastHashJoin Inner BuildRight (97) + : :- * Project (95) + : : +- * BroadcastHashJoin Inner BuildRight (94) + : : :- * Project (92) + : : : +- * BroadcastHashJoin Inner BuildRight (91) + : : : :- * Project (86) + : : : : +- * BroadcastHashJoin Inner BuildRight (85) + : : : : :- * Project (83) + : : : : : +- * SortMergeJoin LeftOuter (82) + : : : : : :- * Sort (75) + : : : : : : +- Exchange (74) + : : : : : : +- * ColumnarToRow (73) + : : : : : : +- CometFilter (72) + : : : : : : +- CometScan parquet spark_catalog.default.web_sales (71) + : : : : : +- * Sort (81) + : : : : : +- Exchange (80) + : : : : : +- * ColumnarToRow (79) + : : : : : +- CometProject (78) + : : : : : +- CometFilter (77) + : : : : : +- CometScan parquet spark_catalog.default.web_returns (76) + : : : : +- ReusedExchange (84) + : : : +- BroadcastExchange (90) + : : : +- * ColumnarToRow (89) + : : : +- CometFilter (88) + : : : +- CometScan parquet spark_catalog.default.web_site (87) + : : +- ReusedExchange (93) + : +- ReusedExchange (96) + :- * HashAggregate (110) + : +- Exchange (109) + : +- * HashAggregate (108) + : +- * HashAggregate (107) + : +- ReusedExchange (106) + +- * HashAggregate (115) + +- Exchange (114) + +- * HashAggregate (113) + +- * HashAggregate (112) + +- ReusedExchange (111) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [7]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ticket_number#4, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sold_date_sk#7 IN dynamicpruning#8)] +PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_item_sk), IsNotNull(ss_promo_sk)] +ReadSchema: struct + +(2) CometFilter +Input [7]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ticket_number#4, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] +Condition : ((isnotnull(ss_store_sk#2) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_promo_sk#3)) + +(3) ColumnarToRow [codegen id : 1] +Input [7]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ticket_number#4, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] + +(4) Exchange +Input [7]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ticket_number#4, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] +Arguments: hashpartitioning(ss_item_sk#1, ss_ticket_number#4, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(5) Sort [codegen id : 2] +Input [7]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ticket_number#4, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] +Arguments: [ss_item_sk#1 ASC NULLS FIRST, ss_ticket_number#4 ASC NULLS FIRST], false, 0 + +(6) Scan parquet spark_catalog.default.store_returns +Output [5]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12, sr_returned_date_sk#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_returns] +PushedFilters: [IsNotNull(sr_item_sk), IsNotNull(sr_ticket_number)] +ReadSchema: struct + +(7) CometFilter +Input [5]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12, sr_returned_date_sk#13] +Condition : (isnotnull(sr_item_sk#9) AND isnotnull(sr_ticket_number#10)) + +(8) CometProject +Input [5]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12, sr_returned_date_sk#13] +Arguments: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12], [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12] + +(9) ColumnarToRow [codegen id : 3] +Input [4]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12] + +(10) Exchange +Input [4]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12] +Arguments: hashpartitioning(sr_item_sk#9, sr_ticket_number#10, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(11) Sort [codegen id : 4] +Input [4]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12] +Arguments: [sr_item_sk#9 ASC NULLS FIRST, sr_ticket_number#10 ASC NULLS FIRST], false, 0 + +(12) SortMergeJoin [codegen id : 9] +Left keys [2]: [ss_item_sk#1, ss_ticket_number#4] +Right keys [2]: [sr_item_sk#9, sr_ticket_number#10] +Join type: LeftOuter +Join condition: None + +(13) Project [codegen id : 9] +Output [8]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7, sr_return_amt#11, sr_net_loss#12] +Input [11]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ticket_number#4, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7, sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12] + +(14) ReusedExchange [Reuses operator id: 125] +Output [1]: [d_date_sk#14] + +(15) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_sold_date_sk#7] +Right keys [1]: [d_date_sk#14] +Join type: Inner +Join condition: None + +(16) Project [codegen id : 9] +Output [7]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ext_sales_price#5, ss_net_profit#6, sr_return_amt#11, sr_net_loss#12] +Input [9]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7, sr_return_amt#11, sr_net_loss#12, d_date_sk#14] + +(17) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#15, s_store_id#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(18) CometFilter +Input [2]: [s_store_sk#15, s_store_id#16] +Condition : isnotnull(s_store_sk#15) + +(19) ColumnarToRow [codegen id : 6] +Input [2]: [s_store_sk#15, s_store_id#16] + +(20) BroadcastExchange +Input [2]: [s_store_sk#15, s_store_id#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(21) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_store_sk#2] +Right keys [1]: [s_store_sk#15] +Join type: Inner +Join condition: None + +(22) Project [codegen id : 9] +Output [7]: [ss_item_sk#1, ss_promo_sk#3, ss_ext_sales_price#5, ss_net_profit#6, sr_return_amt#11, sr_net_loss#12, s_store_id#16] +Input [9]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ext_sales_price#5, ss_net_profit#6, sr_return_amt#11, sr_net_loss#12, s_store_sk#15, s_store_id#16] + +(23) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#17, i_current_price#18] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_current_price), GreaterThan(i_current_price,50.00), IsNotNull(i_item_sk)] +ReadSchema: struct + +(24) CometFilter +Input [2]: [i_item_sk#17, i_current_price#18] +Condition : ((isnotnull(i_current_price#18) AND (i_current_price#18 > 50.00)) AND isnotnull(i_item_sk#17)) + +(25) CometProject +Input [2]: [i_item_sk#17, i_current_price#18] +Arguments: [i_item_sk#17], [i_item_sk#17] + +(26) ColumnarToRow [codegen id : 7] +Input [1]: [i_item_sk#17] + +(27) BroadcastExchange +Input [1]: [i_item_sk#17] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(28) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#17] +Join type: Inner +Join condition: None + +(29) Project [codegen id : 9] +Output [6]: [ss_promo_sk#3, ss_ext_sales_price#5, ss_net_profit#6, sr_return_amt#11, sr_net_loss#12, s_store_id#16] +Input [8]: [ss_item_sk#1, ss_promo_sk#3, ss_ext_sales_price#5, ss_net_profit#6, sr_return_amt#11, sr_net_loss#12, s_store_id#16, i_item_sk#17] + +(30) Scan parquet spark_catalog.default.promotion +Output [2]: [p_promo_sk#19, p_channel_tv#20] +Batched: true +Location [not included in comparison]/{warehouse_dir}/promotion] +PushedFilters: [IsNotNull(p_channel_tv), EqualTo(p_channel_tv,N), IsNotNull(p_promo_sk)] +ReadSchema: struct + +(31) CometFilter +Input [2]: [p_promo_sk#19, p_channel_tv#20] +Condition : ((isnotnull(p_channel_tv#20) AND (p_channel_tv#20 = N)) AND isnotnull(p_promo_sk#19)) + +(32) CometProject +Input [2]: [p_promo_sk#19, p_channel_tv#20] +Arguments: [p_promo_sk#19], [p_promo_sk#19] + +(33) ColumnarToRow [codegen id : 8] +Input [1]: [p_promo_sk#19] + +(34) BroadcastExchange +Input [1]: [p_promo_sk#19] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +(35) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_promo_sk#3] +Right keys [1]: [p_promo_sk#19] +Join type: Inner +Join condition: None + +(36) Project [codegen id : 9] +Output [5]: [ss_ext_sales_price#5, ss_net_profit#6, sr_return_amt#11, sr_net_loss#12, s_store_id#16] +Input [7]: [ss_promo_sk#3, ss_ext_sales_price#5, ss_net_profit#6, sr_return_amt#11, sr_net_loss#12, s_store_id#16, p_promo_sk#19] + +(37) HashAggregate [codegen id : 9] +Input [5]: [ss_ext_sales_price#5, ss_net_profit#6, sr_return_amt#11, sr_net_loss#12, s_store_id#16] +Keys [1]: [s_store_id#16] +Functions [3]: [partial_sum(UnscaledValue(ss_ext_sales_price#5)), partial_sum(coalesce(cast(sr_return_amt#11 as decimal(12,2)), 0.00)), partial_sum((ss_net_profit#6 - coalesce(cast(sr_net_loss#12 as decimal(12,2)), 0.00)))] +Aggregate Attributes [5]: [sum#21, sum#22, isEmpty#23, sum#24, isEmpty#25] +Results [6]: [s_store_id#16, sum#26, sum#27, isEmpty#28, sum#29, isEmpty#30] + +(38) Exchange +Input [6]: [s_store_id#16, sum#26, sum#27, isEmpty#28, sum#29, isEmpty#30] +Arguments: hashpartitioning(s_store_id#16, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(39) HashAggregate [codegen id : 10] +Input [6]: [s_store_id#16, sum#26, sum#27, isEmpty#28, sum#29, isEmpty#30] +Keys [1]: [s_store_id#16] +Functions [3]: [sum(UnscaledValue(ss_ext_sales_price#5)), sum(coalesce(cast(sr_return_amt#11 as decimal(12,2)), 0.00)), sum((ss_net_profit#6 - coalesce(cast(sr_net_loss#12 as decimal(12,2)), 0.00)))] +Aggregate Attributes [3]: [sum(UnscaledValue(ss_ext_sales_price#5))#31, sum(coalesce(cast(sr_return_amt#11 as decimal(12,2)), 0.00))#32, sum((ss_net_profit#6 - coalesce(cast(sr_net_loss#12 as decimal(12,2)), 0.00)))#33] +Results [5]: [store channel AS channel#34, concat(store, s_store_id#16) AS id#35, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#5))#31,17,2) AS sales#36, sum(coalesce(cast(sr_return_amt#11 as decimal(12,2)), 0.00))#32 AS returns#37, sum((ss_net_profit#6 - coalesce(cast(sr_net_loss#12 as decimal(12,2)), 0.00)))#33 AS profit#38] + +(40) Scan parquet spark_catalog.default.catalog_sales +Output [7]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_order_number#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#45), dynamicpruningexpression(cs_sold_date_sk#45 IN dynamicpruning#46)] +PushedFilters: [IsNotNull(cs_catalog_page_sk), IsNotNull(cs_item_sk), IsNotNull(cs_promo_sk)] +ReadSchema: struct + +(41) CometFilter +Input [7]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_order_number#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] +Condition : ((isnotnull(cs_catalog_page_sk#39) AND isnotnull(cs_item_sk#40)) AND isnotnull(cs_promo_sk#41)) + +(42) ColumnarToRow [codegen id : 11] +Input [7]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_order_number#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] + +(43) Exchange +Input [7]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_order_number#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] +Arguments: hashpartitioning(cs_item_sk#40, cs_order_number#42, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(44) Sort [codegen id : 12] +Input [7]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_order_number#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] +Arguments: [cs_item_sk#40 ASC NULLS FIRST, cs_order_number#42 ASC NULLS FIRST], false, 0 + +(45) Scan parquet spark_catalog.default.catalog_returns +Output [5]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50, cr_returned_date_sk#51] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_returns] +PushedFilters: [IsNotNull(cr_item_sk), IsNotNull(cr_order_number)] +ReadSchema: struct + +(46) CometFilter +Input [5]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50, cr_returned_date_sk#51] +Condition : (isnotnull(cr_item_sk#47) AND isnotnull(cr_order_number#48)) + +(47) CometProject +Input [5]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50, cr_returned_date_sk#51] +Arguments: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50], [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50] + +(48) ColumnarToRow [codegen id : 13] +Input [4]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50] + +(49) Exchange +Input [4]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50] +Arguments: hashpartitioning(cr_item_sk#47, cr_order_number#48, 5), ENSURE_REQUIREMENTS, [plan_id=8] + +(50) Sort [codegen id : 14] +Input [4]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50] +Arguments: [cr_item_sk#47 ASC NULLS FIRST, cr_order_number#48 ASC NULLS FIRST], false, 0 + +(51) SortMergeJoin [codegen id : 19] +Left keys [2]: [cs_item_sk#40, cs_order_number#42] +Right keys [2]: [cr_item_sk#47, cr_order_number#48] +Join type: LeftOuter +Join condition: None + +(52) Project [codegen id : 19] +Output [8]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45, cr_return_amount#49, cr_net_loss#50] +Input [11]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_order_number#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45, cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50] + +(53) ReusedExchange [Reuses operator id: 125] +Output [1]: [d_date_sk#52] + +(54) BroadcastHashJoin [codegen id : 19] +Left keys [1]: [cs_sold_date_sk#45] +Right keys [1]: [d_date_sk#52] +Join type: Inner +Join condition: None + +(55) Project [codegen id : 19] +Output [7]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_ext_sales_price#43, cs_net_profit#44, cr_return_amount#49, cr_net_loss#50] +Input [9]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45, cr_return_amount#49, cr_net_loss#50, d_date_sk#52] + +(56) Scan parquet spark_catalog.default.catalog_page +Output [2]: [cp_catalog_page_sk#53, cp_catalog_page_id#54] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_page] +PushedFilters: [IsNotNull(cp_catalog_page_sk)] +ReadSchema: struct + +(57) CometFilter +Input [2]: [cp_catalog_page_sk#53, cp_catalog_page_id#54] +Condition : isnotnull(cp_catalog_page_sk#53) + +(58) ColumnarToRow [codegen id : 16] +Input [2]: [cp_catalog_page_sk#53, cp_catalog_page_id#54] + +(59) BroadcastExchange +Input [2]: [cp_catalog_page_sk#53, cp_catalog_page_id#54] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=9] + +(60) BroadcastHashJoin [codegen id : 19] +Left keys [1]: [cs_catalog_page_sk#39] +Right keys [1]: [cp_catalog_page_sk#53] +Join type: Inner +Join condition: None + +(61) Project [codegen id : 19] +Output [7]: [cs_item_sk#40, cs_promo_sk#41, cs_ext_sales_price#43, cs_net_profit#44, cr_return_amount#49, cr_net_loss#50, cp_catalog_page_id#54] +Input [9]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_ext_sales_price#43, cs_net_profit#44, cr_return_amount#49, cr_net_loss#50, cp_catalog_page_sk#53, cp_catalog_page_id#54] + +(62) ReusedExchange [Reuses operator id: 27] +Output [1]: [i_item_sk#55] + +(63) BroadcastHashJoin [codegen id : 19] +Left keys [1]: [cs_item_sk#40] +Right keys [1]: [i_item_sk#55] +Join type: Inner +Join condition: None + +(64) Project [codegen id : 19] +Output [6]: [cs_promo_sk#41, cs_ext_sales_price#43, cs_net_profit#44, cr_return_amount#49, cr_net_loss#50, cp_catalog_page_id#54] +Input [8]: [cs_item_sk#40, cs_promo_sk#41, cs_ext_sales_price#43, cs_net_profit#44, cr_return_amount#49, cr_net_loss#50, cp_catalog_page_id#54, i_item_sk#55] + +(65) ReusedExchange [Reuses operator id: 34] +Output [1]: [p_promo_sk#56] + +(66) BroadcastHashJoin [codegen id : 19] +Left keys [1]: [cs_promo_sk#41] +Right keys [1]: [p_promo_sk#56] +Join type: Inner +Join condition: None + +(67) Project [codegen id : 19] +Output [5]: [cs_ext_sales_price#43, cs_net_profit#44, cr_return_amount#49, cr_net_loss#50, cp_catalog_page_id#54] +Input [7]: [cs_promo_sk#41, cs_ext_sales_price#43, cs_net_profit#44, cr_return_amount#49, cr_net_loss#50, cp_catalog_page_id#54, p_promo_sk#56] + +(68) HashAggregate [codegen id : 19] +Input [5]: [cs_ext_sales_price#43, cs_net_profit#44, cr_return_amount#49, cr_net_loss#50, cp_catalog_page_id#54] +Keys [1]: [cp_catalog_page_id#54] +Functions [3]: [partial_sum(UnscaledValue(cs_ext_sales_price#43)), partial_sum(coalesce(cast(cr_return_amount#49 as decimal(12,2)), 0.00)), partial_sum((cs_net_profit#44 - coalesce(cast(cr_net_loss#50 as decimal(12,2)), 0.00)))] +Aggregate Attributes [5]: [sum#57, sum#58, isEmpty#59, sum#60, isEmpty#61] +Results [6]: [cp_catalog_page_id#54, sum#62, sum#63, isEmpty#64, sum#65, isEmpty#66] + +(69) Exchange +Input [6]: [cp_catalog_page_id#54, sum#62, sum#63, isEmpty#64, sum#65, isEmpty#66] +Arguments: hashpartitioning(cp_catalog_page_id#54, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(70) HashAggregate [codegen id : 20] +Input [6]: [cp_catalog_page_id#54, sum#62, sum#63, isEmpty#64, sum#65, isEmpty#66] +Keys [1]: [cp_catalog_page_id#54] +Functions [3]: [sum(UnscaledValue(cs_ext_sales_price#43)), sum(coalesce(cast(cr_return_amount#49 as decimal(12,2)), 0.00)), sum((cs_net_profit#44 - coalesce(cast(cr_net_loss#50 as decimal(12,2)), 0.00)))] +Aggregate Attributes [3]: [sum(UnscaledValue(cs_ext_sales_price#43))#67, sum(coalesce(cast(cr_return_amount#49 as decimal(12,2)), 0.00))#68, sum((cs_net_profit#44 - coalesce(cast(cr_net_loss#50 as decimal(12,2)), 0.00)))#69] +Results [5]: [catalog channel AS channel#70, concat(catalog_page, cp_catalog_page_id#54) AS id#71, MakeDecimal(sum(UnscaledValue(cs_ext_sales_price#43))#67,17,2) AS sales#72, sum(coalesce(cast(cr_return_amount#49 as decimal(12,2)), 0.00))#68 AS returns#73, sum((cs_net_profit#44 - coalesce(cast(cr_net_loss#50 as decimal(12,2)), 0.00)))#69 AS profit#74] + +(71) Scan parquet spark_catalog.default.web_sales +Output [7]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_order_number#78, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#81), dynamicpruningexpression(ws_sold_date_sk#81 IN dynamicpruning#82)] +PushedFilters: [IsNotNull(ws_web_site_sk), IsNotNull(ws_item_sk), IsNotNull(ws_promo_sk)] +ReadSchema: struct + +(72) CometFilter +Input [7]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_order_number#78, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81] +Condition : ((isnotnull(ws_web_site_sk#76) AND isnotnull(ws_item_sk#75)) AND isnotnull(ws_promo_sk#77)) + +(73) ColumnarToRow [codegen id : 21] +Input [7]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_order_number#78, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81] + +(74) Exchange +Input [7]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_order_number#78, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81] +Arguments: hashpartitioning(ws_item_sk#75, ws_order_number#78, 5), ENSURE_REQUIREMENTS, [plan_id=11] + +(75) Sort [codegen id : 22] +Input [7]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_order_number#78, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81] +Arguments: [ws_item_sk#75 ASC NULLS FIRST, ws_order_number#78 ASC NULLS FIRST], false, 0 + +(76) Scan parquet spark_catalog.default.web_returns +Output [5]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86, wr_returned_date_sk#87] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_returns] +PushedFilters: [IsNotNull(wr_item_sk), IsNotNull(wr_order_number)] +ReadSchema: struct + +(77) CometFilter +Input [5]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86, wr_returned_date_sk#87] +Condition : (isnotnull(wr_item_sk#83) AND isnotnull(wr_order_number#84)) + +(78) CometProject +Input [5]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86, wr_returned_date_sk#87] +Arguments: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86], [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86] + +(79) ColumnarToRow [codegen id : 23] +Input [4]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86] + +(80) Exchange +Input [4]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86] +Arguments: hashpartitioning(wr_item_sk#83, wr_order_number#84, 5), ENSURE_REQUIREMENTS, [plan_id=12] + +(81) Sort [codegen id : 24] +Input [4]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86] +Arguments: [wr_item_sk#83 ASC NULLS FIRST, wr_order_number#84 ASC NULLS FIRST], false, 0 + +(82) SortMergeJoin [codegen id : 29] +Left keys [2]: [ws_item_sk#75, ws_order_number#78] +Right keys [2]: [wr_item_sk#83, wr_order_number#84] +Join type: LeftOuter +Join condition: None + +(83) Project [codegen id : 29] +Output [8]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81, wr_return_amt#85, wr_net_loss#86] +Input [11]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_order_number#78, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81, wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86] + +(84) ReusedExchange [Reuses operator id: 125] +Output [1]: [d_date_sk#88] + +(85) BroadcastHashJoin [codegen id : 29] +Left keys [1]: [ws_sold_date_sk#81] +Right keys [1]: [d_date_sk#88] +Join type: Inner +Join condition: None + +(86) Project [codegen id : 29] +Output [7]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_ext_sales_price#79, ws_net_profit#80, wr_return_amt#85, wr_net_loss#86] +Input [9]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81, wr_return_amt#85, wr_net_loss#86, d_date_sk#88] + +(87) Scan parquet spark_catalog.default.web_site +Output [2]: [web_site_sk#89, web_site_id#90] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_site] +PushedFilters: [IsNotNull(web_site_sk)] +ReadSchema: struct + +(88) CometFilter +Input [2]: [web_site_sk#89, web_site_id#90] +Condition : isnotnull(web_site_sk#89) + +(89) ColumnarToRow [codegen id : 26] +Input [2]: [web_site_sk#89, web_site_id#90] + +(90) BroadcastExchange +Input [2]: [web_site_sk#89, web_site_id#90] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=13] + +(91) BroadcastHashJoin [codegen id : 29] +Left keys [1]: [ws_web_site_sk#76] +Right keys [1]: [web_site_sk#89] +Join type: Inner +Join condition: None + +(92) Project [codegen id : 29] +Output [7]: [ws_item_sk#75, ws_promo_sk#77, ws_ext_sales_price#79, ws_net_profit#80, wr_return_amt#85, wr_net_loss#86, web_site_id#90] +Input [9]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_ext_sales_price#79, ws_net_profit#80, wr_return_amt#85, wr_net_loss#86, web_site_sk#89, web_site_id#90] + +(93) ReusedExchange [Reuses operator id: 27] +Output [1]: [i_item_sk#91] + +(94) BroadcastHashJoin [codegen id : 29] +Left keys [1]: [ws_item_sk#75] +Right keys [1]: [i_item_sk#91] +Join type: Inner +Join condition: None + +(95) Project [codegen id : 29] +Output [6]: [ws_promo_sk#77, ws_ext_sales_price#79, ws_net_profit#80, wr_return_amt#85, wr_net_loss#86, web_site_id#90] +Input [8]: [ws_item_sk#75, ws_promo_sk#77, ws_ext_sales_price#79, ws_net_profit#80, wr_return_amt#85, wr_net_loss#86, web_site_id#90, i_item_sk#91] + +(96) ReusedExchange [Reuses operator id: 34] +Output [1]: [p_promo_sk#92] + +(97) BroadcastHashJoin [codegen id : 29] +Left keys [1]: [ws_promo_sk#77] +Right keys [1]: [p_promo_sk#92] +Join type: Inner +Join condition: None + +(98) Project [codegen id : 29] +Output [5]: [ws_ext_sales_price#79, ws_net_profit#80, wr_return_amt#85, wr_net_loss#86, web_site_id#90] +Input [7]: [ws_promo_sk#77, ws_ext_sales_price#79, ws_net_profit#80, wr_return_amt#85, wr_net_loss#86, web_site_id#90, p_promo_sk#92] + +(99) HashAggregate [codegen id : 29] +Input [5]: [ws_ext_sales_price#79, ws_net_profit#80, wr_return_amt#85, wr_net_loss#86, web_site_id#90] +Keys [1]: [web_site_id#90] +Functions [3]: [partial_sum(UnscaledValue(ws_ext_sales_price#79)), partial_sum(coalesce(cast(wr_return_amt#85 as decimal(12,2)), 0.00)), partial_sum((ws_net_profit#80 - coalesce(cast(wr_net_loss#86 as decimal(12,2)), 0.00)))] +Aggregate Attributes [5]: [sum#93, sum#94, isEmpty#95, sum#96, isEmpty#97] +Results [6]: [web_site_id#90, sum#98, sum#99, isEmpty#100, sum#101, isEmpty#102] + +(100) Exchange +Input [6]: [web_site_id#90, sum#98, sum#99, isEmpty#100, sum#101, isEmpty#102] +Arguments: hashpartitioning(web_site_id#90, 5), ENSURE_REQUIREMENTS, [plan_id=14] + +(101) HashAggregate [codegen id : 30] +Input [6]: [web_site_id#90, sum#98, sum#99, isEmpty#100, sum#101, isEmpty#102] +Keys [1]: [web_site_id#90] +Functions [3]: [sum(UnscaledValue(ws_ext_sales_price#79)), sum(coalesce(cast(wr_return_amt#85 as decimal(12,2)), 0.00)), sum((ws_net_profit#80 - coalesce(cast(wr_net_loss#86 as decimal(12,2)), 0.00)))] +Aggregate Attributes [3]: [sum(UnscaledValue(ws_ext_sales_price#79))#103, sum(coalesce(cast(wr_return_amt#85 as decimal(12,2)), 0.00))#104, sum((ws_net_profit#80 - coalesce(cast(wr_net_loss#86 as decimal(12,2)), 0.00)))#105] +Results [5]: [web channel AS channel#106, concat(web_site, web_site_id#90) AS id#107, MakeDecimal(sum(UnscaledValue(ws_ext_sales_price#79))#103,17,2) AS sales#108, sum(coalesce(cast(wr_return_amt#85 as decimal(12,2)), 0.00))#104 AS returns#109, sum((ws_net_profit#80 - coalesce(cast(wr_net_loss#86 as decimal(12,2)), 0.00)))#105 AS profit#110] + +(102) Union + +(103) HashAggregate [codegen id : 31] +Input [5]: [channel#34, id#35, sales#36, returns#37, profit#38] +Keys [2]: [channel#34, id#35] +Functions [3]: [partial_sum(sales#36), partial_sum(returns#37), partial_sum(profit#38)] +Aggregate Attributes [6]: [sum#111, isEmpty#112, sum#113, isEmpty#114, sum#115, isEmpty#116] +Results [8]: [channel#34, id#35, sum#117, isEmpty#118, sum#119, isEmpty#120, sum#121, isEmpty#122] + +(104) Exchange +Input [8]: [channel#34, id#35, sum#117, isEmpty#118, sum#119, isEmpty#120, sum#121, isEmpty#122] +Arguments: hashpartitioning(channel#34, id#35, 5), ENSURE_REQUIREMENTS, [plan_id=15] + +(105) HashAggregate [codegen id : 32] +Input [8]: [channel#34, id#35, sum#117, isEmpty#118, sum#119, isEmpty#120, sum#121, isEmpty#122] +Keys [2]: [channel#34, id#35] +Functions [3]: [sum(sales#36), sum(returns#37), sum(profit#38)] +Aggregate Attributes [3]: [sum(sales#36)#123, sum(returns#37)#124, sum(profit#38)#125] +Results [5]: [channel#34, id#35, cast(sum(sales#36)#123 as decimal(37,2)) AS sales#126, cast(sum(returns#37)#124 as decimal(38,2)) AS returns#127, cast(sum(profit#38)#125 as decimal(38,2)) AS profit#128] + +(106) ReusedExchange [Reuses operator id: 104] +Output [8]: [channel#129, id#130, sum#131, isEmpty#132, sum#133, isEmpty#134, sum#135, isEmpty#136] + +(107) HashAggregate [codegen id : 64] +Input [8]: [channel#129, id#130, sum#131, isEmpty#132, sum#133, isEmpty#134, sum#135, isEmpty#136] +Keys [2]: [channel#129, id#130] +Functions [3]: [sum(sales#137), sum(returns#138), sum(profit#139)] +Aggregate Attributes [3]: [sum(sales#137)#123, sum(returns#138)#124, sum(profit#139)#125] +Results [4]: [channel#129, sum(sales#137)#123 AS sales#140, sum(returns#138)#124 AS returns#141, sum(profit#139)#125 AS profit#142] + +(108) HashAggregate [codegen id : 64] +Input [4]: [channel#129, sales#140, returns#141, profit#142] +Keys [1]: [channel#129] +Functions [3]: [partial_sum(sales#140), partial_sum(returns#141), partial_sum(profit#142)] +Aggregate Attributes [6]: [sum#143, isEmpty#144, sum#145, isEmpty#146, sum#147, isEmpty#148] +Results [7]: [channel#129, sum#149, isEmpty#150, sum#151, isEmpty#152, sum#153, isEmpty#154] + +(109) Exchange +Input [7]: [channel#129, sum#149, isEmpty#150, sum#151, isEmpty#152, sum#153, isEmpty#154] +Arguments: hashpartitioning(channel#129, 5), ENSURE_REQUIREMENTS, [plan_id=16] + +(110) HashAggregate [codegen id : 65] +Input [7]: [channel#129, sum#149, isEmpty#150, sum#151, isEmpty#152, sum#153, isEmpty#154] +Keys [1]: [channel#129] +Functions [3]: [sum(sales#140), sum(returns#141), sum(profit#142)] +Aggregate Attributes [3]: [sum(sales#140)#155, sum(returns#141)#156, sum(profit#142)#157] +Results [5]: [channel#129, null AS id#158, sum(sales#140)#155 AS sales#159, sum(returns#141)#156 AS returns#160, sum(profit#142)#157 AS profit#161] + +(111) ReusedExchange [Reuses operator id: 104] +Output [8]: [channel#162, id#163, sum#164, isEmpty#165, sum#166, isEmpty#167, sum#168, isEmpty#169] + +(112) HashAggregate [codegen id : 97] +Input [8]: [channel#162, id#163, sum#164, isEmpty#165, sum#166, isEmpty#167, sum#168, isEmpty#169] +Keys [2]: [channel#162, id#163] +Functions [3]: [sum(sales#170), sum(returns#171), sum(profit#172)] +Aggregate Attributes [3]: [sum(sales#170)#123, sum(returns#171)#124, sum(profit#172)#125] +Results [3]: [sum(sales#170)#123 AS sales#173, sum(returns#171)#124 AS returns#174, sum(profit#172)#125 AS profit#175] + +(113) HashAggregate [codegen id : 97] +Input [3]: [sales#173, returns#174, profit#175] +Keys: [] +Functions [3]: [partial_sum(sales#173), partial_sum(returns#174), partial_sum(profit#175)] +Aggregate Attributes [6]: [sum#176, isEmpty#177, sum#178, isEmpty#179, sum#180, isEmpty#181] +Results [6]: [sum#182, isEmpty#183, sum#184, isEmpty#185, sum#186, isEmpty#187] + +(114) Exchange +Input [6]: [sum#182, isEmpty#183, sum#184, isEmpty#185, sum#186, isEmpty#187] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=17] + +(115) HashAggregate [codegen id : 98] +Input [6]: [sum#182, isEmpty#183, sum#184, isEmpty#185, sum#186, isEmpty#187] +Keys: [] +Functions [3]: [sum(sales#173), sum(returns#174), sum(profit#175)] +Aggregate Attributes [3]: [sum(sales#173)#188, sum(returns#174)#189, sum(profit#175)#190] +Results [5]: [null AS channel#191, null AS id#192, sum(sales#173)#188 AS sales#193, sum(returns#174)#189 AS returns#194, sum(profit#175)#190 AS profit#195] + +(116) Union + +(117) HashAggregate [codegen id : 99] +Input [5]: [channel#34, id#35, sales#126, returns#127, profit#128] +Keys [5]: [channel#34, id#35, sales#126, returns#127, profit#128] +Functions: [] +Aggregate Attributes: [] +Results [5]: [channel#34, id#35, sales#126, returns#127, profit#128] + +(118) Exchange +Input [5]: [channel#34, id#35, sales#126, returns#127, profit#128] +Arguments: hashpartitioning(channel#34, id#35, sales#126, returns#127, profit#128, 5), ENSURE_REQUIREMENTS, [plan_id=18] + +(119) HashAggregate [codegen id : 100] +Input [5]: [channel#34, id#35, sales#126, returns#127, profit#128] +Keys [5]: [channel#34, id#35, sales#126, returns#127, profit#128] +Functions: [] +Aggregate Attributes: [] +Results [5]: [channel#34, id#35, sales#126, returns#127, profit#128] + +(120) TakeOrderedAndProject +Input [5]: [channel#34, id#35, sales#126, returns#127, profit#128] +Arguments: 100, [channel#34 ASC NULLS FIRST, id#35 ASC NULLS FIRST], [channel#34, id#35, sales#126, returns#127, profit#128] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (125) ++- * ColumnarToRow (124) + +- CometProject (123) + +- CometFilter (122) + +- CometScan parquet spark_catalog.default.date_dim (121) + + +(121) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#14, d_date#196] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,1998-08-04), LessThanOrEqual(d_date,1998-09-03), IsNotNull(d_date_sk)] +ReadSchema: struct + +(122) CometFilter +Input [2]: [d_date_sk#14, d_date#196] +Condition : (((isnotnull(d_date#196) AND (d_date#196 >= 1998-08-04)) AND (d_date#196 <= 1998-09-03)) AND isnotnull(d_date_sk#14)) + +(123) CometProject +Input [2]: [d_date_sk#14, d_date#196] +Arguments: [d_date_sk#14], [d_date_sk#14] + +(124) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#14] + +(125) BroadcastExchange +Input [1]: [d_date_sk#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=19] + +Subquery:2 Hosting operator id = 40 Hosting Expression = cs_sold_date_sk#45 IN dynamicpruning#8 + +Subquery:3 Hosting operator id = 71 Hosting Expression = ws_sold_date_sk#81 IN dynamicpruning#8 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q80a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q80a/simplified.txt new file mode 100644 index 0000000000..34e47dcbaf --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q80a/simplified.txt @@ -0,0 +1,207 @@ +TakeOrderedAndProject [channel,id,sales,returns,profit] + WholeStageCodegen (100) + HashAggregate [channel,id,sales,returns,profit] + InputAdapter + Exchange [channel,id,sales,returns,profit] #1 + WholeStageCodegen (99) + HashAggregate [channel,id,sales,returns,profit] + InputAdapter + Union + WholeStageCodegen (32) + HashAggregate [channel,id,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [channel,id] #2 + WholeStageCodegen (31) + HashAggregate [channel,id,sales,returns,profit] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Union + WholeStageCodegen (10) + HashAggregate [s_store_id,sum,sum,isEmpty,sum,isEmpty] [sum(UnscaledValue(ss_ext_sales_price)),sum(coalesce(cast(sr_return_amt as decimal(12,2)), 0.00)),sum((ss_net_profit - coalesce(cast(sr_net_loss as decimal(12,2)), 0.00))),channel,id,sales,returns,profit,sum,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [s_store_id] #3 + WholeStageCodegen (9) + HashAggregate [s_store_id,ss_ext_sales_price,sr_return_amt,ss_net_profit,sr_net_loss] [sum,sum,isEmpty,sum,isEmpty,sum,sum,isEmpty,sum,isEmpty] + Project [ss_ext_sales_price,ss_net_profit,sr_return_amt,sr_net_loss,s_store_id] + BroadcastHashJoin [ss_promo_sk,p_promo_sk] + Project [ss_promo_sk,ss_ext_sales_price,ss_net_profit,sr_return_amt,sr_net_loss,s_store_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_promo_sk,ss_ext_sales_price,ss_net_profit,sr_return_amt,sr_net_loss,s_store_id] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_store_sk,ss_promo_sk,ss_ext_sales_price,ss_net_profit,sr_return_amt,sr_net_loss] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_store_sk,ss_promo_sk,ss_ext_sales_price,ss_net_profit,ss_sold_date_sk,sr_return_amt,sr_net_loss] + SortMergeJoin [ss_item_sk,ss_ticket_number,sr_item_sk,sr_ticket_number] + InputAdapter + WholeStageCodegen (2) + Sort [ss_item_sk,ss_ticket_number] + InputAdapter + Exchange [ss_item_sk,ss_ticket_number] #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk,ss_item_sk,ss_promo_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_promo_sk,ss_ticket_number,ss_ext_sales_price,ss_net_profit,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #5 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + WholeStageCodegen (4) + Sort [sr_item_sk,sr_ticket_number] + InputAdapter + Exchange [sr_item_sk,sr_ticket_number] #6 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometProject [sr_item_sk,sr_ticket_number,sr_return_amt,sr_net_loss] + CometFilter [sr_item_sk,sr_ticket_number] + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_return_amt,sr_net_loss,sr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk] #5 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (6) + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_id] + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (7) + ColumnarToRow + InputAdapter + CometProject [i_item_sk] + CometFilter [i_current_price,i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price] + InputAdapter + BroadcastExchange #9 + WholeStageCodegen (8) + ColumnarToRow + InputAdapter + CometProject [p_promo_sk] + CometFilter [p_channel_tv,p_promo_sk] + CometScan parquet spark_catalog.default.promotion [p_promo_sk,p_channel_tv] + WholeStageCodegen (20) + HashAggregate [cp_catalog_page_id,sum,sum,isEmpty,sum,isEmpty] [sum(UnscaledValue(cs_ext_sales_price)),sum(coalesce(cast(cr_return_amount as decimal(12,2)), 0.00)),sum((cs_net_profit - coalesce(cast(cr_net_loss as decimal(12,2)), 0.00))),channel,id,sales,returns,profit,sum,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [cp_catalog_page_id] #10 + WholeStageCodegen (19) + HashAggregate [cp_catalog_page_id,cs_ext_sales_price,cr_return_amount,cs_net_profit,cr_net_loss] [sum,sum,isEmpty,sum,isEmpty,sum,sum,isEmpty,sum,isEmpty] + Project [cs_ext_sales_price,cs_net_profit,cr_return_amount,cr_net_loss,cp_catalog_page_id] + BroadcastHashJoin [cs_promo_sk,p_promo_sk] + Project [cs_promo_sk,cs_ext_sales_price,cs_net_profit,cr_return_amount,cr_net_loss,cp_catalog_page_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Project [cs_item_sk,cs_promo_sk,cs_ext_sales_price,cs_net_profit,cr_return_amount,cr_net_loss,cp_catalog_page_id] + BroadcastHashJoin [cs_catalog_page_sk,cp_catalog_page_sk] + Project [cs_catalog_page_sk,cs_item_sk,cs_promo_sk,cs_ext_sales_price,cs_net_profit,cr_return_amount,cr_net_loss] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_catalog_page_sk,cs_item_sk,cs_promo_sk,cs_ext_sales_price,cs_net_profit,cs_sold_date_sk,cr_return_amount,cr_net_loss] + SortMergeJoin [cs_item_sk,cs_order_number,cr_item_sk,cr_order_number] + InputAdapter + WholeStageCodegen (12) + Sort [cs_item_sk,cs_order_number] + InputAdapter + Exchange [cs_item_sk,cs_order_number] #11 + WholeStageCodegen (11) + ColumnarToRow + InputAdapter + CometFilter [cs_catalog_page_sk,cs_item_sk,cs_promo_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_catalog_page_sk,cs_item_sk,cs_promo_sk,cs_order_number,cs_ext_sales_price,cs_net_profit,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + WholeStageCodegen (14) + Sort [cr_item_sk,cr_order_number] + InputAdapter + Exchange [cr_item_sk,cr_order_number] #12 + WholeStageCodegen (13) + ColumnarToRow + InputAdapter + CometProject [cr_item_sk,cr_order_number,cr_return_amount,cr_net_loss] + CometFilter [cr_item_sk,cr_order_number] + CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_return_amount,cr_net_loss,cr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk] #5 + InputAdapter + BroadcastExchange #13 + WholeStageCodegen (16) + ColumnarToRow + InputAdapter + CometFilter [cp_catalog_page_sk] + CometScan parquet spark_catalog.default.catalog_page [cp_catalog_page_sk,cp_catalog_page_id] + InputAdapter + ReusedExchange [i_item_sk] #8 + InputAdapter + ReusedExchange [p_promo_sk] #9 + WholeStageCodegen (30) + HashAggregate [web_site_id,sum,sum,isEmpty,sum,isEmpty] [sum(UnscaledValue(ws_ext_sales_price)),sum(coalesce(cast(wr_return_amt as decimal(12,2)), 0.00)),sum((ws_net_profit - coalesce(cast(wr_net_loss as decimal(12,2)), 0.00))),channel,id,sales,returns,profit,sum,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [web_site_id] #14 + WholeStageCodegen (29) + HashAggregate [web_site_id,ws_ext_sales_price,wr_return_amt,ws_net_profit,wr_net_loss] [sum,sum,isEmpty,sum,isEmpty,sum,sum,isEmpty,sum,isEmpty] + Project [ws_ext_sales_price,ws_net_profit,wr_return_amt,wr_net_loss,web_site_id] + BroadcastHashJoin [ws_promo_sk,p_promo_sk] + Project [ws_promo_sk,ws_ext_sales_price,ws_net_profit,wr_return_amt,wr_net_loss,web_site_id] + BroadcastHashJoin [ws_item_sk,i_item_sk] + Project [ws_item_sk,ws_promo_sk,ws_ext_sales_price,ws_net_profit,wr_return_amt,wr_net_loss,web_site_id] + BroadcastHashJoin [ws_web_site_sk,web_site_sk] + Project [ws_item_sk,ws_web_site_sk,ws_promo_sk,ws_ext_sales_price,ws_net_profit,wr_return_amt,wr_net_loss] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_item_sk,ws_web_site_sk,ws_promo_sk,ws_ext_sales_price,ws_net_profit,ws_sold_date_sk,wr_return_amt,wr_net_loss] + SortMergeJoin [ws_item_sk,ws_order_number,wr_item_sk,wr_order_number] + InputAdapter + WholeStageCodegen (22) + Sort [ws_item_sk,ws_order_number] + InputAdapter + Exchange [ws_item_sk,ws_order_number] #15 + WholeStageCodegen (21) + ColumnarToRow + InputAdapter + CometFilter [ws_web_site_sk,ws_item_sk,ws_promo_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_web_site_sk,ws_promo_sk,ws_order_number,ws_ext_sales_price,ws_net_profit,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + WholeStageCodegen (24) + Sort [wr_item_sk,wr_order_number] + InputAdapter + Exchange [wr_item_sk,wr_order_number] #16 + WholeStageCodegen (23) + ColumnarToRow + InputAdapter + CometProject [wr_item_sk,wr_order_number,wr_return_amt,wr_net_loss] + CometFilter [wr_item_sk,wr_order_number] + CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_order_number,wr_return_amt,wr_net_loss,wr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk] #5 + InputAdapter + BroadcastExchange #17 + WholeStageCodegen (26) + ColumnarToRow + InputAdapter + CometFilter [web_site_sk] + CometScan parquet spark_catalog.default.web_site [web_site_sk,web_site_id] + InputAdapter + ReusedExchange [i_item_sk] #8 + InputAdapter + ReusedExchange [p_promo_sk] #9 + WholeStageCodegen (65) + HashAggregate [channel,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),id,sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [channel] #18 + WholeStageCodegen (64) + HashAggregate [channel,sales,returns,profit] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + HashAggregate [channel,id,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + ReusedExchange [channel,id,sum,isEmpty,sum,isEmpty,sum,isEmpty] #2 + WholeStageCodegen (98) + HashAggregate [sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),channel,id,sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange #19 + WholeStageCodegen (97) + HashAggregate [sales,returns,profit] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + HashAggregate [channel,id,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + ReusedExchange [channel,id,sum,isEmpty,sum,isEmpty,sum,isEmpty] #2 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q86a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q86a/explain.txt new file mode 100644 index 0000000000..58e7f58253 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q86a/explain.txt @@ -0,0 +1,240 @@ +== Physical Plan == +TakeOrderedAndProject (34) ++- * Project (33) + +- Window (32) + +- * Sort (31) + +- Exchange (30) + +- * HashAggregate (29) + +- Exchange (28) + +- * HashAggregate (27) + +- Union (26) + :- * HashAggregate (15) + : +- Exchange (14) + : +- * HashAggregate (13) + : +- * Project (12) + : +- * BroadcastHashJoin Inner BuildRight (11) + : :- * Project (6) + : : +- * BroadcastHashJoin Inner BuildRight (5) + : : :- * ColumnarToRow (3) + : : : +- CometFilter (2) + : : : +- CometScan parquet spark_catalog.default.web_sales (1) + : : +- ReusedExchange (4) + : +- BroadcastExchange (10) + : +- * ColumnarToRow (9) + : +- CometFilter (8) + : +- CometScan parquet spark_catalog.default.item (7) + :- * HashAggregate (20) + : +- Exchange (19) + : +- * HashAggregate (18) + : +- * HashAggregate (17) + : +- ReusedExchange (16) + +- * HashAggregate (25) + +- Exchange (24) + +- * HashAggregate (23) + +- * HashAggregate (22) + +- ReusedExchange (21) + + +(1) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_item_sk#1, ws_net_paid#2, ws_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#3), dynamicpruningexpression(ws_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [ws_item_sk#1, ws_net_paid#2, ws_sold_date_sk#3] +Condition : isnotnull(ws_item_sk#1) + +(3) ColumnarToRow [codegen id : 3] +Input [3]: [ws_item_sk#1, ws_net_paid#2, ws_sold_date_sk#3] + +(4) ReusedExchange [Reuses operator id: 39] +Output [1]: [d_date_sk#5] + +(5) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ws_sold_date_sk#3] +Right keys [1]: [d_date_sk#5] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 3] +Output [2]: [ws_item_sk#1, ws_net_paid#2] +Input [4]: [ws_item_sk#1, ws_net_paid#2, ws_sold_date_sk#3, d_date_sk#5] + +(7) Scan parquet spark_catalog.default.item +Output [3]: [i_item_sk#6, i_class#7, i_category#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(8) CometFilter +Input [3]: [i_item_sk#6, i_class#7, i_category#8] +Condition : isnotnull(i_item_sk#6) + +(9) ColumnarToRow [codegen id : 2] +Input [3]: [i_item_sk#6, i_class#7, i_category#8] + +(10) BroadcastExchange +Input [3]: [i_item_sk#6, i_class#7, i_category#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ws_item_sk#1] +Right keys [1]: [i_item_sk#6] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [3]: [ws_net_paid#2, i_class#7, i_category#8] +Input [5]: [ws_item_sk#1, ws_net_paid#2, i_item_sk#6, i_class#7, i_category#8] + +(13) HashAggregate [codegen id : 3] +Input [3]: [ws_net_paid#2, i_class#7, i_category#8] +Keys [2]: [i_category#8, i_class#7] +Functions [1]: [partial_sum(UnscaledValue(ws_net_paid#2))] +Aggregate Attributes [1]: [sum#9] +Results [3]: [i_category#8, i_class#7, sum#10] + +(14) Exchange +Input [3]: [i_category#8, i_class#7, sum#10] +Arguments: hashpartitioning(i_category#8, i_class#7, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 4] +Input [3]: [i_category#8, i_class#7, sum#10] +Keys [2]: [i_category#8, i_class#7] +Functions [1]: [sum(UnscaledValue(ws_net_paid#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_net_paid#2))#11] +Results [6]: [cast(MakeDecimal(sum(UnscaledValue(ws_net_paid#2))#11,17,2) as decimal(27,2)) AS total_sum#12, i_category#8, i_class#7, 0 AS g_category#13, 0 AS g_class#14, 0 AS lochierarchy#15] + +(16) ReusedExchange [Reuses operator id: 14] +Output [3]: [i_category#16, i_class#17, sum#18] + +(17) HashAggregate [codegen id : 8] +Input [3]: [i_category#16, i_class#17, sum#18] +Keys [2]: [i_category#16, i_class#17] +Functions [1]: [sum(UnscaledValue(ws_net_paid#19))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_net_paid#19))#11] +Results [2]: [MakeDecimal(sum(UnscaledValue(ws_net_paid#19))#11,17,2) AS total_sum#20, i_category#16] + +(18) HashAggregate [codegen id : 8] +Input [2]: [total_sum#20, i_category#16] +Keys [1]: [i_category#16] +Functions [1]: [partial_sum(total_sum#20)] +Aggregate Attributes [2]: [sum#21, isEmpty#22] +Results [3]: [i_category#16, sum#23, isEmpty#24] + +(19) Exchange +Input [3]: [i_category#16, sum#23, isEmpty#24] +Arguments: hashpartitioning(i_category#16, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(20) HashAggregate [codegen id : 9] +Input [3]: [i_category#16, sum#23, isEmpty#24] +Keys [1]: [i_category#16] +Functions [1]: [sum(total_sum#20)] +Aggregate Attributes [1]: [sum(total_sum#20)#25] +Results [6]: [sum(total_sum#20)#25 AS total_sum#26, i_category#16, null AS i_class#27, 0 AS g_category#28, 1 AS g_class#29, 1 AS lochierarchy#30] + +(21) ReusedExchange [Reuses operator id: 14] +Output [3]: [i_category#31, i_class#32, sum#33] + +(22) HashAggregate [codegen id : 13] +Input [3]: [i_category#31, i_class#32, sum#33] +Keys [2]: [i_category#31, i_class#32] +Functions [1]: [sum(UnscaledValue(ws_net_paid#34))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_net_paid#34))#11] +Results [1]: [MakeDecimal(sum(UnscaledValue(ws_net_paid#34))#11,17,2) AS total_sum#35] + +(23) HashAggregate [codegen id : 13] +Input [1]: [total_sum#35] +Keys: [] +Functions [1]: [partial_sum(total_sum#35)] +Aggregate Attributes [2]: [sum#36, isEmpty#37] +Results [2]: [sum#38, isEmpty#39] + +(24) Exchange +Input [2]: [sum#38, isEmpty#39] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=4] + +(25) HashAggregate [codegen id : 14] +Input [2]: [sum#38, isEmpty#39] +Keys: [] +Functions [1]: [sum(total_sum#35)] +Aggregate Attributes [1]: [sum(total_sum#35)#40] +Results [6]: [sum(total_sum#35)#40 AS total_sum#41, null AS i_category#42, null AS i_class#43, 1 AS g_category#44, 1 AS g_class#45, 2 AS lochierarchy#46] + +(26) Union + +(27) HashAggregate [codegen id : 15] +Input [6]: [total_sum#12, i_category#8, i_class#7, g_category#13, g_class#14, lochierarchy#15] +Keys [6]: [total_sum#12, i_category#8, i_class#7, g_category#13, g_class#14, lochierarchy#15] +Functions: [] +Aggregate Attributes: [] +Results [6]: [total_sum#12, i_category#8, i_class#7, g_category#13, g_class#14, lochierarchy#15] + +(28) Exchange +Input [6]: [total_sum#12, i_category#8, i_class#7, g_category#13, g_class#14, lochierarchy#15] +Arguments: hashpartitioning(total_sum#12, i_category#8, i_class#7, g_category#13, g_class#14, lochierarchy#15, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(29) HashAggregate [codegen id : 16] +Input [6]: [total_sum#12, i_category#8, i_class#7, g_category#13, g_class#14, lochierarchy#15] +Keys [6]: [total_sum#12, i_category#8, i_class#7, g_category#13, g_class#14, lochierarchy#15] +Functions: [] +Aggregate Attributes: [] +Results [5]: [total_sum#12, i_category#8, i_class#7, lochierarchy#15, CASE WHEN (g_class#14 = 0) THEN i_category#8 END AS _w0#47] + +(30) Exchange +Input [5]: [total_sum#12, i_category#8, i_class#7, lochierarchy#15, _w0#47] +Arguments: hashpartitioning(lochierarchy#15, _w0#47, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(31) Sort [codegen id : 17] +Input [5]: [total_sum#12, i_category#8, i_class#7, lochierarchy#15, _w0#47] +Arguments: [lochierarchy#15 ASC NULLS FIRST, _w0#47 ASC NULLS FIRST, total_sum#12 DESC NULLS LAST], false, 0 + +(32) Window +Input [5]: [total_sum#12, i_category#8, i_class#7, lochierarchy#15, _w0#47] +Arguments: [rank(total_sum#12) windowspecdefinition(lochierarchy#15, _w0#47, total_sum#12 DESC NULLS LAST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rank_within_parent#48], [lochierarchy#15, _w0#47], [total_sum#12 DESC NULLS LAST] + +(33) Project [codegen id : 18] +Output [5]: [total_sum#12, i_category#8, i_class#7, lochierarchy#15, rank_within_parent#48] +Input [6]: [total_sum#12, i_category#8, i_class#7, lochierarchy#15, _w0#47, rank_within_parent#48] + +(34) TakeOrderedAndProject +Input [5]: [total_sum#12, i_category#8, i_class#7, lochierarchy#15, rank_within_parent#48] +Arguments: 100, [lochierarchy#15 DESC NULLS LAST, CASE WHEN (lochierarchy#15 = 0) THEN i_category#8 END ASC NULLS FIRST, rank_within_parent#48 ASC NULLS FIRST], [total_sum#12, i_category#8, i_class#7, lochierarchy#15, rank_within_parent#48] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (39) ++- * ColumnarToRow (38) + +- CometProject (37) + +- CometFilter (36) + +- CometScan parquet spark_catalog.default.date_dim (35) + + +(35) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#5, d_month_seq#49] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1212), LessThanOrEqual(d_month_seq,1223), IsNotNull(d_date_sk)] +ReadSchema: struct + +(36) CometFilter +Input [2]: [d_date_sk#5, d_month_seq#49] +Condition : (((isnotnull(d_month_seq#49) AND (d_month_seq#49 >= 1212)) AND (d_month_seq#49 <= 1223)) AND isnotnull(d_date_sk#5)) + +(37) CometProject +Input [2]: [d_date_sk#5, d_month_seq#49] +Arguments: [d_date_sk#5], [d_date_sk#5] + +(38) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#5] + +(39) BroadcastExchange +Input [1]: [d_date_sk#5] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q86a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q86a/simplified.txt new file mode 100644 index 0000000000..5c5e088857 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q86a/simplified.txt @@ -0,0 +1,66 @@ +TakeOrderedAndProject [lochierarchy,i_category,rank_within_parent,total_sum,i_class] + WholeStageCodegen (18) + Project [total_sum,i_category,i_class,lochierarchy,rank_within_parent] + InputAdapter + Window [total_sum,lochierarchy,_w0] + WholeStageCodegen (17) + Sort [lochierarchy,_w0,total_sum] + InputAdapter + Exchange [lochierarchy,_w0] #1 + WholeStageCodegen (16) + HashAggregate [total_sum,i_category,i_class,g_category,g_class,lochierarchy] [_w0] + InputAdapter + Exchange [total_sum,i_category,i_class,g_category,g_class,lochierarchy] #2 + WholeStageCodegen (15) + HashAggregate [total_sum,i_category,i_class,g_category,g_class,lochierarchy] + InputAdapter + Union + WholeStageCodegen (4) + HashAggregate [i_category,i_class,sum] [sum(UnscaledValue(ws_net_paid)),total_sum,g_category,g_class,lochierarchy,sum] + InputAdapter + Exchange [i_category,i_class] #3 + WholeStageCodegen (3) + HashAggregate [i_category,i_class,ws_net_paid] [sum,sum] + Project [ws_net_paid,i_class,i_category] + BroadcastHashJoin [ws_item_sk,i_item_sk] + Project [ws_item_sk,ws_net_paid] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_net_paid,ws_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_month_seq,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_class,i_category] + WholeStageCodegen (9) + HashAggregate [i_category,sum,isEmpty] [sum(total_sum),total_sum,i_class,g_category,g_class,lochierarchy,sum,isEmpty] + InputAdapter + Exchange [i_category] #6 + WholeStageCodegen (8) + HashAggregate [i_category,total_sum] [sum,isEmpty,sum,isEmpty] + HashAggregate [i_category,i_class,sum] [sum(UnscaledValue(ws_net_paid)),total_sum,sum] + InputAdapter + ReusedExchange [i_category,i_class,sum] #3 + WholeStageCodegen (14) + HashAggregate [sum,isEmpty] [sum(total_sum),total_sum,i_category,i_class,g_category,g_class,lochierarchy,sum,isEmpty] + InputAdapter + Exchange #7 + WholeStageCodegen (13) + HashAggregate [total_sum] [sum,isEmpty,sum,isEmpty] + HashAggregate [i_category,i_class,sum] [sum(UnscaledValue(ws_net_paid)),total_sum,sum] + InputAdapter + ReusedExchange [i_category,i_class,sum] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q98/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q98/explain.txt new file mode 100644 index 0000000000..f77b7ec93b --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q98/explain.txt @@ -0,0 +1,155 @@ +== Physical Plan == +* Sort (21) ++- Exchange (20) + +- * Project (19) + +- Window (18) + +- * Sort (17) + +- Exchange (16) + +- * HashAggregate (15) + +- Exchange (14) + +- * HashAggregate (13) + +- * Project (12) + +- * BroadcastHashJoin Inner BuildRight (11) + :- * Project (9) + : +- * BroadcastHashJoin Inner BuildRight (8) + : :- * ColumnarToRow (3) + : : +- CometFilter (2) + : : +- CometScan parquet spark_catalog.default.store_sales (1) + : +- BroadcastExchange (7) + : +- * ColumnarToRow (6) + : +- CometFilter (5) + : +- CometScan parquet spark_catalog.default.item (4) + +- ReusedExchange (10) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_item_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#3), dynamicpruningexpression(ss_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(2) CometFilter +Input [3]: [ss_item_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3] +Condition : isnotnull(ss_item_sk#1) + +(3) ColumnarToRow [codegen id : 3] +Input [3]: [ss_item_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3] + +(4) Scan parquet spark_catalog.default.item +Output [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [In(i_category, [Books ,Home ,Sports ]), IsNotNull(i_item_sk)] +ReadSchema: struct + +(5) CometFilter +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Condition : (i_category#10 IN (Sports ,Books ,Home ) AND isnotnull(i_item_sk#5)) + +(6) ColumnarToRow [codegen id : 1] +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] + +(7) BroadcastExchange +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#5] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 3] +Output [7]: [ss_ext_sales_price#2, ss_sold_date_sk#3, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Input [9]: [ss_item_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3, i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] + +(10) ReusedExchange [Reuses operator id: 26] +Output [1]: [d_date_sk#11] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_sold_date_sk#3] +Right keys [1]: [d_date_sk#11] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [6]: [ss_ext_sales_price#2, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Input [8]: [ss_ext_sales_price#2, ss_sold_date_sk#3, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10, d_date_sk#11] + +(13) HashAggregate [codegen id : 3] +Input [6]: [ss_ext_sales_price#2, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Keys [5]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8] +Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#2))] +Aggregate Attributes [1]: [sum#12] +Results [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] + +(14) Exchange +Input [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] +Arguments: hashpartitioning(i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 4] +Input [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] +Keys [5]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8] +Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#2))#14] +Results [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#2))#14,17,2) AS itemrevenue#15, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#2))#14,17,2) AS _w0#16] + +(16) Exchange +Input [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16] +Arguments: hashpartitioning(i_class#9, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(17) Sort [codegen id : 5] +Input [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16] +Arguments: [i_class#9 ASC NULLS FIRST], false, 0 + +(18) Window +Input [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16] +Arguments: [sum(_w0#16) windowspecdefinition(i_class#9, specifiedwindowframe(RowFrame, unboundedpreceding$(), unboundedfollowing$())) AS _we0#17], [i_class#9] + +(19) Project [codegen id : 6] +Output [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, ((_w0#16 * 100) / _we0#17) AS revenueratio#18] +Input [8]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16, _we0#17] + +(20) Exchange +Input [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, revenueratio#18] +Arguments: rangepartitioning(i_category#10 ASC NULLS FIRST, i_class#9 ASC NULLS FIRST, i_item_id#6 ASC NULLS FIRST, i_item_desc#7 ASC NULLS FIRST, revenueratio#18 ASC NULLS FIRST, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(21) Sort [codegen id : 7] +Input [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, revenueratio#18] +Arguments: [i_category#10 ASC NULLS FIRST, i_class#9 ASC NULLS FIRST, i_item_id#6 ASC NULLS FIRST, i_item_desc#7 ASC NULLS FIRST, revenueratio#18 ASC NULLS FIRST], true, 0 + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (26) ++- * ColumnarToRow (25) + +- CometProject (24) + +- CometFilter (23) + +- CometScan parquet spark_catalog.default.date_dim (22) + + +(22) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#11, d_date#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,1999-02-22), LessThanOrEqual(d_date,1999-03-24), IsNotNull(d_date_sk)] +ReadSchema: struct + +(23) CometFilter +Input [2]: [d_date_sk#11, d_date#19] +Condition : (((isnotnull(d_date#19) AND (d_date#19 >= 1999-02-22)) AND (d_date#19 <= 1999-03-24)) AND isnotnull(d_date_sk#11)) + +(24) CometProject +Input [2]: [d_date_sk#11, d_date#19] +Arguments: [d_date_sk#11], [d_date_sk#11] + +(25) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#11] + +(26) BroadcastExchange +Input [1]: [d_date_sk#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q98/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q98/simplified.txt new file mode 100644 index 0000000000..b7489a0aff --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q98/simplified.txt @@ -0,0 +1,43 @@ +WholeStageCodegen (7) + Sort [i_category,i_class,i_item_id,i_item_desc,revenueratio] + InputAdapter + Exchange [i_category,i_class,i_item_id,i_item_desc,revenueratio] #1 + WholeStageCodegen (6) + Project [i_item_id,i_item_desc,i_category,i_class,i_current_price,itemrevenue,_w0,_we0] + InputAdapter + Window [_w0,i_class] + WholeStageCodegen (5) + Sort [i_class] + InputAdapter + Exchange [i_class] #2 + WholeStageCodegen (4) + HashAggregate [i_item_id,i_item_desc,i_category,i_class,i_current_price,sum] [sum(UnscaledValue(ss_ext_sales_price)),itemrevenue,_w0,sum] + InputAdapter + Exchange [i_item_id,i_item_desc,i_category,i_class,i_current_price] #3 + WholeStageCodegen (3) + HashAggregate [i_item_id,i_item_desc,i_category,i_class,i_current_price,ss_ext_sales_price] [sum,sum] + Project [ss_ext_sales_price,i_item_id,i_item_desc,i_current_price,i_class,i_category] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_ext_sales_price,ss_sold_date_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] + BroadcastHashJoin [ss_item_sk,i_item_sk] + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ext_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [i_category,i_item_sk] + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] + InputAdapter + ReusedExchange [d_date_sk] #4 diff --git a/spark/src/test/scala/org/apache/comet/CometCastSuite.scala b/spark/src/test/scala/org/apache/comet/CometCastSuite.scala index 1710090e2a..fd2218965e 100644 --- a/spark/src/test/scala/org/apache/comet/CometCastSuite.scala +++ b/spark/src/test/scala/org/apache/comet/CometCastSuite.scala @@ -982,12 +982,18 @@ class CometCastSuite extends CometTestBase with AdaptiveSparkPlanHelper { fail(s"Comet should have failed with ${e.getCause.getMessage}") case (Some(sparkException), Some(cometException)) => // both systems threw an exception so we make sure they are the same - val sparkMessage = sparkException.getCause.getMessage + val sparkMessage = + if (sparkException.getCause != null) sparkException.getCause.getMessage else null // We have to workaround https://github.com/apache/datafusion-comet/issues/293 here by // removing the "Execution error: " error message prefix that is added by DataFusion - val cometMessage = cometException.getCause.getMessage - .replace("Execution error: ", "") - if (CometSparkSessionExtensions.isSpark34Plus) { + val cometMessage = cometException.getCause.getMessage.replace("Execution error: ", "") + if (CometSparkSessionExtensions.isSpark40Plus) { + // for Spark 4 we expect to sparkException carries the message + assert( + sparkException.getMessage + .replace(".WITH_SUGGESTION] ", "]") + .startsWith(cometMessage)) + } else if (CometSparkSessionExtensions.isSpark34Plus) { // for Spark 3.4 we expect to reproduce the error message exactly assert(cometMessage == sparkMessage) } else if (CometSparkSessionExtensions.isSpark33Plus) { diff --git a/spark/src/test/scala/org/apache/comet/exec/CometExecSuite.scala b/spark/src/test/scala/org/apache/comet/exec/CometExecSuite.scala index c85caeba75..0dc8510c33 100644 --- a/spark/src/test/scala/org/apache/comet/exec/CometExecSuite.scala +++ b/spark/src/test/scala/org/apache/comet/exec/CometExecSuite.scala @@ -49,7 +49,7 @@ import org.apache.spark.sql.internal.SQLConf.SESSION_LOCAL_TIMEZONE import org.apache.spark.unsafe.types.UTF8String import org.apache.comet.CometConf -import org.apache.comet.CometSparkSessionExtensions.{isSpark33Plus, isSpark34Plus} +import org.apache.comet.CometSparkSessionExtensions.{isSpark33Plus, isSpark34Plus, isSpark40Plus} class CometExecSuite extends CometTestBase { import testImplicits._ @@ -1055,7 +1055,11 @@ class CometExecSuite extends CometTestBase { val e = intercept[AnalysisException] { sql("CREATE TABLE t2(name STRING, part INTERVAL) USING PARQUET PARTITIONED BY (part)") }.getMessage - assert(e.contains("Cannot use interval")) + if (isSpark40Plus) { + assert(e.contains(" Cannot use \"INTERVAL\"")) + } else { + assert(e.contains("Cannot use interval")) + } } } } diff --git a/spark/src/test/scala/org/apache/comet/parquet/ParquetReadSuite.scala b/spark/src/test/scala/org/apache/comet/parquet/ParquetReadSuite.scala index f447522973..0b37f5ccf5 100644 --- a/spark/src/test/scala/org/apache/comet/parquet/ParquetReadSuite.scala +++ b/spark/src/test/scala/org/apache/comet/parquet/ParquetReadSuite.scala @@ -34,9 +34,7 @@ import org.apache.hadoop.fs.Path import org.apache.parquet.example.data.simple.SimpleGroup import org.apache.parquet.schema.MessageTypeParser import org.apache.spark.SparkException -import org.apache.spark.sql.CometTestBase -import org.apache.spark.sql.DataFrame -import org.apache.spark.sql.Row +import org.apache.spark.sql.{CometTestBase, DataFrame, Row} import org.apache.spark.sql.catalyst.expressions.GenericInternalRow import org.apache.spark.sql.catalyst.util.DateTimeUtils import org.apache.spark.sql.comet.CometBatchScanExec @@ -49,7 +47,7 @@ import org.apache.spark.unsafe.types.UTF8String import com.google.common.primitives.UnsignedLong import org.apache.comet.CometConf -import org.apache.comet.CometSparkSessionExtensions.isSpark34Plus +import org.apache.comet.CometSparkSessionExtensions.{isSpark34Plus, isSpark40Plus} abstract class ParquetReadSuite extends CometTestBase { import testImplicits._ @@ -1125,7 +1123,9 @@ abstract class ParquetReadSuite extends CometTestBase { } test("row group skipping doesn't overflow when reading into larger type") { - assume(isSpark34Plus) + // Spark 4.0 no longer fails for widening types + // https://github.com/apache/spark/commit/3361f25dc0ff6e5233903c26ee105711b79ba967 + assume(isSpark34Plus && !isSpark40Plus) withTempPath { path => Seq(0).toDF("a").write.parquet(path.toString) diff --git a/spark/src/test/scala/org/apache/spark/sql/comet/CometPlanStabilitySuite.scala b/spark/src/test/scala/org/apache/spark/sql/comet/CometPlanStabilitySuite.scala index 79d61f524a..691d2cd637 100644 --- a/spark/src/test/scala/org/apache/spark/sql/comet/CometPlanStabilitySuite.scala +++ b/spark/src/test/scala/org/apache/spark/sql/comet/CometPlanStabilitySuite.scala @@ -36,7 +36,7 @@ import org.apache.spark.sql.internal.SQLConf import org.apache.spark.sql.test.TestSparkSession import org.apache.comet.CometConf -import org.apache.comet.CometSparkSessionExtensions.isSpark34Plus +import org.apache.comet.CometSparkSessionExtensions.{isSpark34Plus, isSpark40Plus} /** * Similar to [[org.apache.spark.sql.PlanStabilitySuite]], checks that TPC-DS Comet plans don't @@ -298,8 +298,10 @@ trait CometPlanStabilitySuite extends DisableAdaptiveExecutionSuite with TPCDSBa } class CometTPCDSV1_4_PlanStabilitySuite extends CometPlanStabilitySuite { + private val planName = + if (isSpark40Plus) "approved-plans-v1_4-spark4_0" else "approved-plans-v1_4" override val goldenFilePath: String = - new File(baseResourcePath, "approved-plans-v1_4").getAbsolutePath + new File(baseResourcePath, planName).getAbsolutePath tpcdsQueries.foreach { q => test(s"check simplified (tpcds-v1.4/$q)") { @@ -309,8 +311,10 @@ class CometTPCDSV1_4_PlanStabilitySuite extends CometPlanStabilitySuite { } class CometTPCDSV2_7_PlanStabilitySuite extends CometPlanStabilitySuite { + private val planName = + if (isSpark40Plus) "approved-plans-v2_7-spark4_0" else "approved-plans-v2_7" override val goldenFilePath: String = - new File(baseResourcePath, "approved-plans-v2_7").getAbsolutePath + new File(baseResourcePath, planName).getAbsolutePath tpcdsQueriesV2_7_0.foreach { q => test(s"check simplified (tpcds-v2.7.0/$q)") { diff --git a/spark/src/test/scala/org/apache/spark/sql/comet/ParquetDatetimeRebaseSuite.scala b/spark/src/test/scala/org/apache/spark/sql/comet/ParquetDatetimeRebaseSuite.scala index 5bb7e8f706..a829d7449e 100644 --- a/spark/src/test/scala/org/apache/spark/sql/comet/ParquetDatetimeRebaseSuite.scala +++ b/spark/src/test/scala/org/apache/spark/sql/comet/ParquetDatetimeRebaseSuite.scala @@ -27,6 +27,7 @@ import org.apache.spark.sql.{CometTestBase, DataFrame, Dataset, Row} import org.apache.spark.sql.internal.SQLConf import org.apache.comet.CometConf +import org.apache.comet.CometSparkSessionExtensions.isSpark40Plus // This test checks if Comet reads ancient dates & timestamps that are before 1582, as if they are // read according to the `LegacyBehaviorPolicy.CORRECTED` mode (i.e., no rebase) in Spark. @@ -48,7 +49,8 @@ abstract class ParquetDatetimeRebaseSuite extends CometTestBase { val df = spark.read.parquet(file) // Parquet file written by 2.4.5 should throw exception for both Spark and Comet - if (exceptionOnRebase || sparkVersion == "2_4_5") { + // For Spark 4.0+, Parquet file written by 2.4.5 should not throw exception + if ((exceptionOnRebase || sparkVersion == "2_4_5") && (!isSpark40Plus || sparkVersion != "2_4_5")) { intercept[SparkException](df.collect()) } else { checkSparkNoRebaseAnswer(df) @@ -70,7 +72,8 @@ abstract class ParquetDatetimeRebaseSuite extends CometTestBase { val df = spark.read.parquet(file) // Parquet file written by 2.4.5 should throw exception for both Spark and Comet - if (exceptionOnRebase || sparkVersion == "2_4_5") { + // For Spark 4.0+, Parquet file written by 2.4.5 should not throw exception + if ((exceptionOnRebase || sparkVersion == "2_4_5") && (!isSpark40Plus || sparkVersion != "2_4_5")) { intercept[SparkException](df.collect()) } else { checkSparkNoRebaseAnswer(df) @@ -93,7 +96,8 @@ abstract class ParquetDatetimeRebaseSuite extends CometTestBase { val df = spark.read.parquet(file) // Parquet file written by 2.4.5 should throw exception for both Spark and Comet - if (exceptionOnRebase || sparkVersion == "2_4_5") { + // For Spark 4.0+, Parquet file written by 2.4.5 should not throw exception + if ((exceptionOnRebase || sparkVersion == "2_4_5") && (!isSpark40Plus || sparkVersion != "2_4_5")) { intercept[SparkException](df.collect()) } else { checkSparkNoRebaseAnswer(df) diff --git a/spark/src/test/spark-3.3-plus/org/apache/comet/CometExpression3_3PlusSuite.scala b/spark/src/test/spark-3.3-plus/org/apache/comet/CometExpression3_3PlusSuite.scala index 6102777fc5..d54c8dad09 100644 --- a/spark/src/test/spark-3.3-plus/org/apache/comet/CometExpression3_3PlusSuite.scala +++ b/spark/src/test/spark-3.3-plus/org/apache/comet/CometExpression3_3PlusSuite.scala @@ -25,7 +25,6 @@ import org.apache.spark.sql.catalyst.FunctionIdentifier import org.apache.spark.sql.catalyst.expressions.{BloomFilterMightContain, Expression, ExpressionInfo} import org.apache.spark.sql.functions.{col, lit} import org.apache.spark.util.sketch.BloomFilter - import java.io.ByteArrayOutputStream import scala.util.Random diff --git a/spark/src/test/spark-3.4-plus/org/apache/comet/exec/CometExec3_4PlusSuite.scala b/spark/src/test/spark-3.4-plus/org/apache/comet/exec/CometExec3_4PlusSuite.scala index 31d1ffbf77..764f7b18de 100644 --- a/spark/src/test/spark-3.4-plus/org/apache/comet/exec/CometExec3_4PlusSuite.scala +++ b/spark/src/test/spark-3.4-plus/org/apache/comet/exec/CometExec3_4PlusSuite.scala @@ -23,7 +23,6 @@ import org.scalactic.source.Position import org.scalatest.Tag import org.apache.spark.sql.CometTestBase - import org.apache.comet.CometConf /**