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| <!--- | ||
| 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. | ||
| --> | ||
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| # Supported Spark Data Types | ||
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| The following Spark data types are currently available: | ||
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| <!-- based on org.apache.comet.serde.QueryPlanSerde.supportedDataType --> | ||
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| - Primitives | ||
| - Boolean | ||
| - Byte | ||
| - Short | ||
| - Integer | ||
| - Long | ||
| - Float | ||
| - Double | ||
| - String | ||
| - Binary | ||
| - Decimal | ||
| - Temporal | ||
| - Date | ||
| - Timestamp | ||
| - TimestampNTZ | ||
| - Null |
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| <!--- | ||
| 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. | ||
| --> | ||
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| # Installing DataFusion Comet | ||
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| Make sure the following requirements are met and software installed on your machine. | ||
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| ## Supported Platforms | ||
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| - Linux | ||
| - Apple OSX (Intel and Apple Silicon) | ||
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| ## Requirements | ||
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| - Apache Spark 3.2, 3.3, or 3.4 | ||
| - JDK 8 and up | ||
| - GLIBC 2.17 (Centos 7) and up | ||
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| ## Using a Published Release | ||
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| There are no public releases available yet, so it is necessary to build from source as described in the next section. | ||
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| ## Building From Source | ||
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| Clone the repository: | ||
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| ```commandline | ||
| git clone https://github.com/apache/datafusion-comet.git | ||
| ``` | ||
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| Build Comet for a specific Spark version: | ||
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| ```commandline | ||
| cd datafusion-comet | ||
| make release PROFILES="-Pspark-3.4" | ||
| ``` | ||
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| Note that the project builds for Scala 2.12 by default but can be built for Scala 2.13 using an additional profile: | ||
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| ```commandline | ||
| make release PROFILES="-Pspark-3.4 -Pscala-2.13" | ||
| ``` | ||
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| ## Run Spark with Comet enabled | ||
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| Make sure `SPARK_HOME` points to the same Spark version as Comet was built for. | ||
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| ```commandline | ||
| $SPARK_HOME/bin/spark-shell \ | ||
| --jars spark/target/comet-spark-spark3.4_2.12-0.1.0-SNAPSHOT.jar \ | ||
| --conf spark.sql.extensions=org.apache.comet.CometSparkSessionExtensions \ | ||
| --conf spark.comet.enabled=true \ | ||
| --conf spark.comet.exec.enabled=true \ | ||
| --conf spark.comet.exec.all.enabled=true | ||
| ``` | ||
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| ### Verify Comet enabled for Spark SQL query | ||
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| Create a test Parquet source | ||
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| ```scala | ||
| scala> (0 until 10).toDF("a").write.mode("overwrite").parquet("/tmp/test") | ||
| ``` | ||
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| Query the data from the test source and check: | ||
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| - INFO message shows the native Comet library has been initialized. | ||
| - The query plan reflects Comet operators being used for this query instead of Spark ones | ||
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| ```scala | ||
| scala> spark.read.parquet("/tmp/test").createOrReplaceTempView("t1") | ||
| scala> spark.sql("select * from t1 where a > 5").explain | ||
| INFO src/lib.rs: Comet native library initialized | ||
| == Physical Plan == | ||
| *(1) ColumnarToRow | ||
| +- CometFilter [a#14], (isnotnull(a#14) AND (a#14 > 5)) | ||
| +- CometScan parquet [a#14] Batched: true, DataFilters: [isnotnull(a#14), (a#14 > 5)], | ||
| Format: CometParquet, Location: InMemoryFileIndex(1 paths)[file:/tmp/test], PartitionFilters: [], | ||
| PushedFilters: [IsNotNull(a), GreaterThan(a,5)], ReadSchema: struct<a:int> | ||
| ``` | ||
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| ### Enable Comet shuffle | ||
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| Comet shuffle feature is disabled by default. To enable it, please add related configs: | ||
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| ``` | ||
| --conf spark.shuffle.manager=org.apache.spark.sql.comet.execution.shuffle.CometShuffleManager | ||
| --conf spark.comet.exec.shuffle.enabled=true | ||
| ``` | ||
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| Above configs enable Comet native shuffle which only supports hash partition and single partition. | ||
| Comet native shuffle doesn't support complex types yet. | ||
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| Comet doesn't have official release yet so currently the only way to test it is to build jar and include it in your | ||
| Spark application. Depending on your deployment mode you may also need to set the driver & executor class path(s) to | ||
| explicitly contain Comet otherwise Spark may use a different class-loader for the Comet components than its internal | ||
| components which will then fail at runtime. For example: | ||
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| ``` | ||
| --driver-class-path spark/target/comet-spark-spark3.4_2.12-0.1.0-SNAPSHOT.jar | ||
| ``` | ||
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| Some cluster managers may require additional configuration, see https://spark.apache.org/docs/latest/cluster-overview.html | ||
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| To enable columnar shuffle which supports all partitioning and basic complex types, one more config is required: | ||
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| ``` | ||
| --conf spark.comet.columnar.shuffle.enabled=true | ||
| ``` |
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| <!--- | ||
| 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. | ||
| --> | ||
|
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| # Supported Spark Operators | ||
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| The following Spark operators are currently available: | ||
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| - FileSourceScanExec/BatchScanExec for Parquet | ||
| - Projection | ||
| - Filter | ||
| - Sort | ||
| - Hash Aggregate | ||
| - Limit | ||
| - Sort-merge Join | ||
| - Hash Join | ||
| - Shuffle | ||
| - Expand |
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| <!--- | ||
| 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. | ||
| --> | ||
|
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| # Comet Overview | ||
|
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| Comet runs Spark SQL queries using the native Apache DataFusion runtime, which is | ||
| typically faster and more resource efficient than JVM based runtimes. | ||
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|  | ||
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| Comet aims to support: | ||
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| - a native Parquet implementation, including both reader and writer | ||
| - full implementation of Spark operators, including | ||
| Filter/Project/Aggregation/Join/Exchange etc. | ||
| - full implementation of Spark built-in expressions | ||
| - a UDF framework for users to migrate their existing UDF to native | ||
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| ## Architecture | ||
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| The following diagram illustrates the architecture of Comet: | ||
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|  | ||
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| ## Current Status | ||
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| The project is currently integrated into Apache Spark 3.2, 3.3, and 3.4. | ||
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| ## Feature Parity with Apache Spark | ||
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| The project strives to keep feature parity with Apache Spark, that is, | ||
| users should expect the same behavior (w.r.t features, configurations, | ||
| query results, etc) with Comet turned on or turned off in their Spark | ||
| jobs. In addition, Comet extension should automatically detect unsupported | ||
| features and fallback to Spark engine. | ||
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| To achieve this, besides unit tests within Comet itself, we also re-use | ||
| Spark SQL tests and make sure they all pass with Comet extension | ||
| enabled. |