Merge branch 'master' into spark-ordered-list-state

.github/trigger_files/IO_Iceberg_Integration_Tests.json

@@ -1,4 +1,4 @@
 {
     "comment": "Modify this file in a trivial way to cause this test suite to run",
-    "modification": 3
+    "modification": 5
 }

.github/trigger_files/beam_PostCommit_Java_ValidatesRunner_Spark.json

@@ -3,5 +3,6 @@
   "https://github.com/apache/beam/pull/31156": "noting that PR #31156 should run this test",
   "https://github.com/apache/beam/pull/31798": "noting that PR #31798 should run this test",
   "https://github.com/apache/beam/pull/32546": "noting that PR #32546 should run this test",
+  "https://github.com/apache/beam/pull/33267": "noting that PR #33267 should run this test",
   "https://github.com/apache/beam/pull/33322": "noting that PR #33322 should run this test"
 }

.github/trigger_files/beam_PostCommit_Java_ValidatesRunner_SparkStructuredStreaming.json

@@ -2,5 +2,6 @@
   "comment": "Modify this file in a trivial way to cause this test suite to run",
   "https://github.com/apache/beam/pull/31156": "noting that PR #31156 should run this test",
   "https://github.com/apache/beam/pull/31798": "noting that PR #31798 should run this test",
-  "https://github.com/apache/beam/pull/32546": "noting that PR #32546 should run this test"
+  "https://github.com/apache/beam/pull/32546": "noting that PR #32546 should run this test",
+  "https://github.com/apache/beam/pull/33267": "noting that PR #33267 should run this test"
 }

.github/trigger_files/beam_PostCommit_Java_ValidatesRunner_Spark_Java11.json

@@ -3,5 +3,6 @@
   "https://github.com/apache/beam/pull/31156": "noting that PR #31156 should run this test",
   "https://github.com/apache/beam/pull/31798": "noting that PR #31798 should run this test",
   "https://github.com/apache/beam/pull/32546": "noting that PR #32546 should run this test",
+  "https://github.com/apache/beam/pull/33267": "noting that PR #33267 should run this test",
   "https://github.com/apache/beam/pull/33322": "noting that PR #33322 should run this test"
 }

.github/workflows/beam_PostCommit_Java_ValidatesRunner_Flink.yml

@@ -93,4 +93,3 @@ jobs:
           commit: '${{ env.prsha || env.GITHUB_SHA }}'
           comment_mode: ${{ github.event_name == 'issue_comment'  && 'always' || 'off' }}
           files: '**/build/test-results/**/*.xml'
-          large_files: true

.github/workflows/beam_PostCommit_Java_ValidatesRunner_Flink_Java8.yml

@@ -110,4 +110,3 @@ jobs:
           commit: '${{ env.prsha || env.GITHUB_SHA }}'
           comment_mode: ${{ github.event_name == 'issue_comment'  && 'always' || 'off' }}
           files: '**/build/test-results/**/*.xml'
-          large_files: true

.github/workflows/beam_Wordcount_Python_Cost_Benchmark_Dataflow.yml → .github/workflows/beam_Python_CostBenchmarks_Dataflow.yml

@@ -13,9 +13,11 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-name: Wordcount Python Cost Benchmarks Dataflow
+name: Python Cost Benchmarks Dataflow
 
 on:
+  schedule:
+    - cron: '30 18 * * 6' # Run at 6:30 pm UTC on Saturdays
   workflow_dispatch:
 
 #Setting explicit permissions for the action to avoid the default permissions which are `write-all` in case of pull_request_target event
@@ -47,16 +49,17 @@ env:
   INFLUXDB_USER_PASSWORD: ${{ secrets.INFLUXDB_USER_PASSWORD }}
 
 jobs:
-  beam_Inference_Python_Benchmarks_Dataflow:
+  beam_Python_Cost_Benchmarks_Dataflow:
     if: |
-      github.event_name == 'workflow_dispatch'
+      github.event_name == 'workflow_dispatch' ||
+      (github.event_name == 'schedule' && github.repository == 'apache/beam')
     runs-on: [self-hosted, ubuntu-20.04, main]
     timeout-minutes: 900
     name: ${{ matrix.job_name }} (${{ matrix.job_phrase }})
     strategy:
       matrix:
-        job_name: ["beam_Wordcount_Python_Cost_Benchmarks_Dataflow"]
-        job_phrase: ["Run Wordcount Cost Benchmark"]
+        job_name: ["beam_Python_CostBenchmark_Dataflow"]
+        job_phrase: ["Run Python Dataflow Cost Benchmarks"]
     steps:
       - uses: actions/checkout@v4
       - name: Setup repository
@@ -76,10 +79,11 @@ jobs:
           test-language: python
           argument-file-paths: |
             ${{ github.workspace }}/.github/workflows/cost-benchmarks-pipeline-options/python_wordcount.txt
+            ${{ github.workspace }}/.github/workflows/cost-benchmarks-pipeline-options/python_tf_mnist_classification.txt
       # The env variables are created and populated in the test-arguments-action as "<github.job>_test_arguments_<argument_file_paths_index>"
       - name: get current time
         run: echo "NOW_UTC=$(date '+%m%d%H%M%S' --utc)" >> $GITHUB_ENV
-      - name: run wordcount on Dataflow Python
+      - name: Run wordcount on Dataflow
         uses: ./.github/actions/gradle-command-self-hosted-action
         timeout-minutes: 30
         with:
@@ -88,4 +92,15 @@ jobs:
             -PloadTest.mainClass=apache_beam.testing.benchmarks.wordcount.wordcount \
             -Prunner=DataflowRunner \
             -PpythonVersion=3.10 \
-            '-PloadTest.args=${{ env.beam_Inference_Python_Benchmarks_Dataflow_test_arguments_1 }} --job_name=benchmark-tests-wordcount-python-${{env.NOW_UTC}} --output=gs://temp-storage-for-end-to-end-tests/wordcount/result_wordcount-${{env.NOW_UTC}}.txt' \
+            '-PloadTest.args=${{ env.beam_Python_Cost_Benchmarks_Dataflow_test_arguments_1 }} --job_name=benchmark-tests-wordcount-python-${{env.NOW_UTC}} --output_file=gs://temp-storage-for-end-to-end-tests/wordcount/result_wordcount-${{env.NOW_UTC}}.txt' \
+      - name: Run Tensorflow MNIST Image Classification on Dataflow
+        uses: ./.github/actions/gradle-command-self-hosted-action
+        timeout-minutes: 30
+        with:
+          gradle-command: :sdks:python:apache_beam:testing:load_tests:run
+          arguments: |
+            -PloadTest.mainClass=apache_beam.testing.benchmarks.inference.tensorflow_mnist_classification_cost_benchmark \
+            -Prunner=DataflowRunner \
+            -PpythonVersion=3.10 \
+            -PloadTest.requirementsTxtFile=apache_beam/ml/inference/tensorflow_tests_requirements.txt \
+            '-PloadTest.args=${{ env.beam_Python_Cost_Benchmarks_Dataflow_test_arguments_2 }} --job_name=benchmark-tests-tf-mnist-classification-python-${{env.NOW_UTC}} --input_file=gs://apache-beam-ml/testing/inputs/it_mnist_data.csv --output_file=gs://temp-storage-for-end-to-end-tests/inference/result_tf_mnist-${{env.NOW_UTC}}.txt --model=gs://apache-beam-ml/models/tensorflow/mnist/' \

.github/workflows/cost-benchmarks-pipeline-options/python_tf_mnist_classification.txt

@@ -0,0 +1,29 @@
+#  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.
+
+--region=us-central1
+--machine_type=n1-standard-2
+--num_workers=1
+--disk_size_gb=50
+--autoscaling_algorithm=NONE
+--input_options={}
+--staging_location=gs://temp-storage-for-perf-tests/loadtests
+--temp_location=gs://temp-storage-for-perf-tests/loadtests
+--requirements_file=apache_beam/ml/inference/tensorflow_tests_requirements.txt
+--publish_to_big_query=true
+--metrics_dataset=beam_run_inference
+--metrics_table=tf_mnist_classification
+--runner=DataflowRunner

CHANGES.md

@@ -31,6 +31,7 @@
 
 ## New Features / Improvements
 
+* The datetime module is now available for use in jinja templatization for yaml.
 * X feature added (Java/Python) ([#X](https://github.com/apache/beam/issues/X)).
 
 ## Breaking Changes
@@ -64,14 +65,21 @@
 
 * gcs-connector config options can be set via GcsOptions (Java) ([#32769](https://github.com/apache/beam/pull/32769)).
 * Support for X source added (Java/Python) ([#X](https://github.com/apache/beam/issues/X)).
+* [Managed Iceberg] Support partitioning by time (year, month, day, hour) for types `date`, `time`, `timestamp`, and `timestamp(tz)` ([#32939](https://github.com/apache/beam/pull/32939))
 * Upgraded the default version of Hadoop dependencies to 3.4.1. Hadoop 2.10.2 is still supported (Java) ([#33011](https://github.com/apache/beam/issues/33011)).
+* [BigQueryIO] Create managed BigLake tables dynamically ([#33125](https://github.com/apache/beam/pull/33125))
 
 ## New Features / Improvements
 
-* Added OrderedList state support in SparkRunner ([#33211](https://github.com/apache/beam/issues/33211)).
 * Improved batch performance of SparkRunner's GroupByKey ([#20943](https://github.com/apache/beam/pull/20943)).
 * Support OnWindowExpiration in Prism ([#32211](https://github.com/apache/beam/issues/32211)).
   * This enables initial Java GroupIntoBatches support.
+* Added support for stateful processing in Spark Runner for streaming pipelines. Timer functionality is not yet supported and will be implemented in a future release ([#33237](https://github.com/apache/beam/issues/33237)).
+* Improved batch performance of SparkRunner's GroupByKey ([#20943](https://github.com/apache/beam/pull/20943)).
+* Support OnWindowExpiration in Prism ([#32211](https://github.com/apache/beam/issues/32211)).
+  * This enables initial Java GroupIntoBatches support.
+* Support OrderedListState in Prism ([#32929](https://github.com/apache/beam/issues/32929)).
+* Added OrderedList state support in SparkRunner ([#33211](https://github.com/apache/beam/issues/33211)).
 * X feature added (Java/Python) ([#X](https://github.com/apache/beam/issues/X)).
 
 ## Breaking Changes

buildSrc/src/main/groovy/org/apache/beam/gradle/BeamModulePlugin.groovy

@@ -606,7 +606,7 @@ class BeamModulePlugin implements Plugin<Project> {
     def gax_version = "2.55.0"
     def google_ads_version = "33.0.0"
     def google_clients_version = "2.0.0"
-    def google_cloud_bigdataoss_version = "2.2.16"
+    def google_cloud_bigdataoss_version = "2.2.26"
     // [bomupgrader] determined by: com.google.cloud:google-cloud-spanner, consistent with: google_cloud_platform_libraries_bom
     def google_cloud_spanner_version = "6.79.0"
     def google_code_gson_version = "2.10.1"

contributor-docs/code-change-guide.md

@@ -375,6 +375,9 @@ Follow these steps for Maven projects.
       <id>Maven-Snapshot</id>
       <name>maven snapshot repository</name>
       <url>https://repository.apache.org/content/groups/snapshots/</url>
+      <releases>
+        <enabled>false</enabled>
+      </releases>
     </repository>
     ```
 

runners/prism/java/build.gradle

@@ -233,10 +233,6 @@ def createPrismValidatesRunnerTask = { name, environmentType ->
       excludeCategories 'org.apache.beam.sdk.testing.UsesExternalService'
       excludeCategories 'org.apache.beam.sdk.testing.UsesSdkHarnessEnvironment'
 
-      // Not yet implemented in Prism
-      // https://github.com/apache/beam/issues/32929
-      excludeCategories 'org.apache.beam.sdk.testing.UsesOrderedListState'
-
       // Not supported in Portable Java SDK yet.
       // https://github.com/apache/beam/issues?q=is%3Aissue+is%3Aopen+MultimapState
       excludeCategories 'org.apache.beam.sdk.testing.UsesMultimapState'

runners/spark/spark_runner.gradle

@@ -345,7 +345,7 @@ def validatesRunnerStreaming = tasks.register("validatesRunnerStreaming", Test)
     excludeCategories 'org.apache.beam.sdk.testing.UsesSdkHarnessEnvironment'
 
     // State and Timers
-    excludeCategories 'org.apache.beam.sdk.testing.UsesStatefulParDo'
+    excludeCategories 'org.apache.beam.sdk.testing.UsesTestStreamWithMultipleStages'
     excludeCategories 'org.apache.beam.sdk.testing.UsesTimersInParDo'
     excludeCategories 'org.apache.beam.sdk.testing.UsesTimerMap'
     excludeCategories 'org.apache.beam.sdk.testing.UsesLoopingTimer'

runners/spark/src/main/java/org/apache/beam/runners/spark/coders/SparkRunnerKryoRegistrator.java

@@ -21,7 +21,7 @@
 import java.util.ArrayList;
 import java.util.LinkedHashMap;
 import org.apache.beam.runners.spark.io.MicrobatchSource;
-import org.apache.beam.runners.spark.stateful.SparkGroupAlsoByWindowViaWindowSet.StateAndTimers;
+import org.apache.beam.runners.spark.stateful.StateAndTimers;
 import org.apache.beam.runners.spark.translation.ValueAndCoderKryoSerializer;
 import org.apache.beam.runners.spark.translation.ValueAndCoderLazySerializable;
 import org.apache.beam.runners.spark.util.ByteArray;

runners/spark/src/main/java/org/apache/beam/runners/spark/stateful/SparkGroupAlsoByWindowViaWindowSet.java

@@ -17,6 +17,9 @@
  */
 package org.apache.beam.runners.spark.stateful;
 
+import static org.apache.beam.runners.spark.translation.TranslationUtils.checkpointIfNeeded;
+import static org.apache.beam.runners.spark.translation.TranslationUtils.getBatchDuration;
+
 import java.io.Serializable;
 import java.util.ArrayList;
 import java.util.Collection;
@@ -35,7 +38,6 @@
 import org.apache.beam.runners.core.metrics.MetricsContainerImpl;
 import org.apache.beam.runners.core.triggers.ExecutableTriggerStateMachine;
 import org.apache.beam.runners.core.triggers.TriggerStateMachines;
-import org.apache.beam.runners.spark.SparkPipelineOptions;
 import org.apache.beam.runners.spark.coders.CoderHelpers;
 import org.apache.beam.runners.spark.translation.ReifyTimestampsAndWindowsFunction;
 import org.apache.beam.runners.spark.translation.TranslationUtils;
@@ -60,10 +62,8 @@
 import org.apache.beam.vendor.guava.v32_1_2_jre.com.google.common.collect.AbstractIterator;
 import org.apache.beam.vendor.guava.v32_1_2_jre.com.google.common.collect.FluentIterable;
 import org.apache.beam.vendor.guava.v32_1_2_jre.com.google.common.collect.Lists;
-import org.apache.beam.vendor.guava.v32_1_2_jre.com.google.common.collect.Table;
 import org.apache.spark.api.java.JavaSparkContext$;
 import org.apache.spark.api.java.function.FlatMapFunction;
-import org.apache.spark.streaming.Duration;
 import org.apache.spark.streaming.api.java.JavaDStream;
 import org.apache.spark.streaming.api.java.JavaPairDStream;
 import org.apache.spark.streaming.dstream.DStream;
@@ -100,27 +100,6 @@ public class SparkGroupAlsoByWindowViaWindowSet implements Serializable {
   private static final Logger LOG =
       LoggerFactory.getLogger(SparkGroupAlsoByWindowViaWindowSet.class);
 
-  /** State and Timers wrapper. */
-  public static class StateAndTimers implements Serializable {
-    // Serializable state for internals (namespace to state tag to coded value).
-    private final Table<String, String, byte[]> state;
-    private final Collection<byte[]> serTimers;
-
-    private StateAndTimers(
-        final Table<String, String, byte[]> state, final Collection<byte[]> timers) {
-      this.state = state;
-      this.serTimers = timers;
-    }
-
-    Table<String, String, byte[]> getState() {
-      return state;
-    }
-
-    Collection<byte[]> getTimers() {
-      return serTimers;
-    }
-  }
-
   private static class OutputWindowedValueHolder<K, V>
       implements OutputWindowedValue<KV<K, Iterable<V>>> {
     private final List<WindowedValue<KV<K, Iterable<V>>>> windowedValues = new ArrayList<>();
@@ -348,7 +327,7 @@ private Collection<TimerInternals.TimerData> filterTimersEligibleForProcessing(
 
             // empty outputs are filtered later using DStream filtering
             final StateAndTimers updated =
-                new StateAndTimers(
+                StateAndTimers.of(
                     stateInternals.getState(),
                     SparkTimerInternals.serializeTimers(
                         timerInternals.getTimers(), timerDataCoder));
@@ -466,21 +445,6 @@ private static <W extends BoundedWindow> TimerInternals.TimerDataCoderV2 timerDa
     return TimerInternals.TimerDataCoderV2.of(windowingStrategy.getWindowFn().windowCoder());
   }
 
-  private static void checkpointIfNeeded(
-      final DStream<Tuple2<ByteArray, Tuple2<StateAndTimers, List<byte[]>>>> firedStream,
-      final SerializablePipelineOptions options) {
-
-    final Long checkpointDurationMillis = getBatchDuration(options);
-
-    if (checkpointDurationMillis > 0) {
-      firedStream.checkpoint(new Duration(checkpointDurationMillis));
-    }
-  }
-
-  private static Long getBatchDuration(final SerializablePipelineOptions options) {
-    return options.get().as(SparkPipelineOptions.class).getCheckpointDurationMillis();
-  }
-
   private static <K, InputT> JavaDStream<WindowedValue<KV<K, Iterable<InputT>>>> stripStateValues(
       final DStream<Tuple2<ByteArray, Tuple2<StateAndTimers, List<byte[]>>>> firedStream,
       final Coder<K> keyCoder,

runners/spark/src/main/java/org/apache/beam/runners/spark/stateful/SparkStateInternals.java

@@ -69,7 +69,7 @@
 @SuppressWarnings({
   "nullness" // TODO(https://github.com/apache/beam/issues/20497)
 })
-class SparkStateInternals<K> implements StateInternals {
+public class SparkStateInternals<K> implements StateInternals {
 
   private final K key;
   // Serializable state for internals (namespace to state tag to coded value).
@@ -85,11 +85,11 @@ private SparkStateInternals(K key, Table<String, String, byte[]> stateTable) {
     this.stateTable = stateTable;
   }
 
-  static <K> SparkStateInternals<K> forKey(K key) {
+  public static <K> SparkStateInternals<K> forKey(K key) {
     return new SparkStateInternals<>(key);
   }
 
-  static <K> SparkStateInternals<K> forKeyAndState(
+  public static <K> SparkStateInternals<K> forKeyAndState(
       K key, Table<String, String, byte[]> stateTable) {
     return new SparkStateInternals<>(key, stateTable);
   }
@@ -417,17 +417,25 @@ public void put(MapKeyT key, MapValueT value) {
     @Override
     public ReadableState<MapValueT> computeIfAbsent(
         MapKeyT key, Function<? super MapKeyT, ? extends MapValueT> mappingFunction) {
-      Map<MapKeyT, MapValueT> sparkMapState = readValue();
+      Map<MapKeyT, MapValueT> sparkMapState = readAsMap();
       MapValueT current = sparkMapState.get(key);
       if (current == null) {
         put(key, mappingFunction.apply(key));
       }
       return ReadableStates.immediate(current);
     }
 
+    private Map<MapKeyT, MapValueT> readAsMap() {
+      Map<MapKeyT, MapValueT> mapState = readValue();
+      if (mapState == null) {
+        mapState = new HashMap<>();
+      }
+      return mapState;
+    }
+
     @Override
     public void remove(MapKeyT key) {
-      Map<MapKeyT, MapValueT> sparkMapState = readValue();
+      Map<MapKeyT, MapValueT> sparkMapState = readAsMap();
       sparkMapState.remove(key);
       writeValue(sparkMapState);
     }

runners/spark/src/main/java/org/apache/beam/runners/spark/stateful/SparkTimerInternals.java

@@ -107,7 +107,7 @@ public Collection<TimerData> getTimers() {
     return timers;
   }
 
-  void addTimers(Iterator<TimerData> timers) {
+  public void addTimers(Iterator<TimerData> timers) {
     while (timers.hasNext()) {
       TimerData timer = timers.next();
       this.timers.add(timer);
@@ -163,7 +163,8 @@ public void setTimer(
       Instant target,
       Instant outputTimestamp,
       TimeDomain timeDomain) {
-    throw new UnsupportedOperationException("Setting a timer by ID not yet supported.");
+    this.setTimer(
+        TimerData.of(timerId, timerFamilyId, namespace, target, outputTimestamp, timeDomain));
   }
 
   @Override