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chore: [comet-parquet-exec] merge from main 20240116 (#1299)
* feat: support array_append (#1072) * feat: support array_append * formatted code * rewrite array_append plan to match spark behaviour and fixed bug in QueryPlan serde * remove unwrap * Fix for Spark 3.3 * refactor array_append binary expression serde code * Disabled array_append test for spark 4.0+ * chore: Simplify CometShuffleMemoryAllocator to use Spark unified memory allocator (#1063) * docs: Update benchmarking.md (#1085) * feat: Require offHeap memory to be enabled (always use unified memory) (#1062) * Require offHeap memory * remove unused import * use off heap memory in stability tests * reorder imports * test: Restore one test in CometExecSuite by adding COMET_SHUFFLE_MODE config (#1087) * Add changelog for 0.4.0 (#1089) * chore: Prepare for 0.5.0 development (#1090) * Update version number for build * update docs * build: Skip installation of spark-integration and fuzz testing modules (#1091) * Add hint for finding the GPG key to use when publishing to maven (#1093) * docs: Update documentation for 0.4.0 release (#1096) * update TPC-H results * update Maven links * update benchmarking guide and add TPC-DS results * include q72 * fix: Unsigned type related bugs (#1095) ## Which issue does this PR close? Closes #1067 ## Rationale for this change Bug fix. A few expressions were failing some unsigned type related tests ## What changes are included in this PR? - For `u8`/`u16`, switched to use `generate_cast_to_signed!` in order to copy full i16/i32 width instead of padding zeros in the higher bits - `u64` becomes `Decimal(20, 0)` but there was a bug in `round()` (`>` vs `>=`) ## How are these changes tested? Put back tests for unsigned types * chore: Include first ScanExec batch in metrics (#1105) * include first batch in ScanExec metrics * record row count metric * fix regression * chore: Improve CometScan metrics (#1100) * Add native metrics for plan creation * make messages consistent * Include get_next_batch cost in metrics * formatting * fix double count of rows * chore: Add custom metric for native shuffle fetching batches from JVM (#1108) * feat: support array_insert (#1073) * Part of the implementation of array_insert * Missing methods * Working version * Reformat code * Fix code-style * Add comments about spark's implementation. * Implement negative indices + fix tests for spark < 3.4 * Fix code-style * Fix scalastyle * Fix tests for spark < 3.4 * Fixes & tests - added test for the negative index - added test for the legacy spark mode * Use assume(isSpark34Plus) in tests * Test else-branch & improve coverage * Update native/spark-expr/src/list.rs Co-authored-by: Andy Grove <[email protected]> * Fix fallback test In one case there is a zero in index and test fails due to spark error * Adjust the behaviour for the NULL case to Spark * Move the logic of type checking to the method * Fix code-style --------- Co-authored-by: Andy Grove <[email protected]> * feat: enable decimal to decimal cast of different precision and scale (#1086) * enable decimal to decimal cast of different precision and scale * add more test cases for negative scale and higher precision * add check for compatibility for decimal to decimal * fix code style * Update spark/src/main/scala/org/apache/comet/expressions/CometCast.scala Co-authored-by: Andy Grove <[email protected]> * fix the nit in comment --------- Co-authored-by: himadripal <[email protected]> Co-authored-by: Andy Grove <[email protected]> * docs: fix readme FGPA/FPGA typo (#1117) * fix: Use RDD partition index (#1112) * fix: Use RDD partition index * fix * fix * fix * fix: Various metrics bug fixes and improvements (#1111) * fix: Don't create CometScanExec for subclasses of ParquetFileFormat (#1129) * Use exact class comparison for parquet scan * Add test * Add comment * fix: Fix metrics regressions (#1132) * fix metrics issues * clippy * update tests * docs: Add more technical detail and new diagram to Comet plugin overview (#1119) * Add more technical detail and new diagram to Comet plugin overview * update diagram * add info on Arrow IPC * update diagram * update diagram * update docs * address feedback * Stop passing Java config map into native createPlan (#1101) * feat: Improve ScanExec native metrics (#1133) * save * remove shuffle jvm metric and update tuning guide * docs * add source for all ScanExecs * address feedback * address feedback * chore: Remove unused StringView struct (#1143) * Remove unused StringView struct * remove more dead code * docs: Add some documentation explaining how shuffle works (#1148) * add some notes on shuffle * reads * improve docs * test: enable more Spark 4.0 tests (#1145) ## Which issue does this PR close? Part of #372 and #551 ## Rationale for this change To be ready for Spark 4.0 ## What changes are included in this PR? This PR enables more Spark 4.0 tests that were fixed by recent changes ## How are these changes tested? tests enabled * chore: Refactor cast to use SparkCastOptions param (#1146) * Refactor cast to use SparkCastOptions param * update tests * update benches * update benches * update benches * Enable more scenarios in CometExecBenchmark. (#1151) * chore: Move more expressions from core crate to spark-expr crate (#1152) * move aggregate expressions to spark-expr crate * move more expressions * move benchmark * normalize_nan * bitwise not * comet scalar funcs * update bench imports * remove dead code (#1155) * fix: Spark 4.0-preview1 SPARK-47120 (#1156) ## Which issue does this PR close? Part of #372 and #551 ## Rationale for this change To be ready for Spark 4.0 ## What changes are included in this PR? This PR fixes the new test SPARK-47120 added in Spark 4.0 ## How are these changes tested? tests enabled * chore: Move string kernels and expressions to spark-expr crate (#1164) * Move string kernels and expressions to spark-expr crate * remove unused hash kernel * remove unused dependencies * chore: Move remaining expressions to spark-expr crate + some minor refactoring (#1165) * move CheckOverflow to spark-expr crate * move NegativeExpr to spark-expr crate * move UnboundColumn to spark-expr crate * move ExpandExec from execution::datafusion::operators to execution::operators * refactoring to remove datafusion subpackage * update imports in benches * fix * fix * chore: Add ignored tests for reading complex types from Parquet (#1167) * Add ignored tests for reading structs from Parquet * add basic map test * add tests for Map and Array * feat: Add Spark-compatible implementation of SchemaAdapterFactory (#1169) * Add Spark-compatible SchemaAdapterFactory implementation * remove prototype code * fix * refactor * implement more cast logic * implement more cast logic * add basic test * improve test * cleanup * fmt * add support for casting unsigned int to signed int * clippy * address feedback * fix test * fix: Document enabling comet explain plan usage in Spark (4.0) (#1176) * test: enabling Spark tests with offHeap requirement (#1177) ## Which issue does this PR close? ## Rationale for this change After #1062 We have not running Spark tests for native execution ## What changes are included in this PR? Removed the off heap requirement for testing ## How are these changes tested? Bringing back Spark tests for native execution * feat: Improve shuffle metrics (second attempt) (#1175) * improve shuffle metrics * docs * more metrics * refactor * address feedback * fix: stddev_pop should not directly return 0.0 when count is 1.0 (#1184) * add test * fix * fix * fix * feat: Make native shuffle compression configurable and respect `spark.shuffle.compress` (#1185) * Make shuffle compression codec and level configurable * remove lz4 references * docs * update comment * clippy * fix benches * clippy * clippy * disable test for miri * remove lz4 reference from proto * minor: move shuffle classes from common to spark (#1193) * minor: refactor decodeBatches to make private in broadcast exchange (#1195) * minor: refactor prepare_output so that it does not require an ExecutionContext (#1194) * fix: fix missing explanation for then branch in case when (#1200) * minor: remove unused source files (#1202) * chore: Upgrade to DataFusion 44.0.0-rc2 (#1154) * move aggregate expressions to spark-expr crate * move more expressions * move benchmark * normalize_nan * bitwise not * comet scalar funcs * update bench imports * save * save * save * remove unused imports * clippy * implement more hashers * implement Hash and PartialEq * implement Hash and PartialEq * implement Hash and PartialEq * benches * fix ScalarUDFImpl.return_type failure * exclude test from miri * ignore correct test * ignore another test * remove miri checks * use return_type_from_exprs * Revert "use return_type_from_exprs" This reverts commit febc1f1. * use DF main branch * hacky workaround for regression in ScalarUDFImpl.return_type * fix repo url * pin to revision * bump to latest rev * bump to latest DF rev * bump DF to rev 9f530dd * add Cargo.lock * bump DF version * no default features * Revert "remove miri checks" This reverts commit 4638fe3. * Update pin to DataFusion e99e02b9b9093ceb0c13a2dd32a2a89beba47930 * update pin * Update Cargo.toml Bump to 44.0.0-rc2 * update cargo lock * revert miri change --------- Co-authored-by: Andrew Lamb <[email protected]> * feat: add support for array_contains expression (#1163) * feat: add support for array_contains expression * test: add unit test for array_contains function * Removes unnecessary case expression for handling null values * chore: Move more expressions from core crate to spark-expr crate (#1152) * move aggregate expressions to spark-expr crate * move more expressions * move benchmark * normalize_nan * bitwise not * comet scalar funcs * update bench imports * remove dead code (#1155) * fix: Spark 4.0-preview1 SPARK-47120 (#1156) ## Which issue does this PR close? Part of #372 and #551 ## Rationale for this change To be ready for Spark 4.0 ## What changes are included in this PR? This PR fixes the new test SPARK-47120 added in Spark 4.0 ## How are these changes tested? tests enabled * chore: Move string kernels and expressions to spark-expr crate (#1164) * Move string kernels and expressions to spark-expr crate * remove unused hash kernel * remove unused dependencies * chore: Move remaining expressions to spark-expr crate + some minor refactoring (#1165) * move CheckOverflow to spark-expr crate * move NegativeExpr to spark-expr crate * move UnboundColumn to spark-expr crate * move ExpandExec from execution::datafusion::operators to execution::operators * refactoring to remove datafusion subpackage * update imports in benches * fix * fix * chore: Add ignored tests for reading complex types from Parquet (#1167) * Add ignored tests for reading structs from Parquet * add basic map test * add tests for Map and Array * feat: Add Spark-compatible implementation of SchemaAdapterFactory (#1169) * Add Spark-compatible SchemaAdapterFactory implementation * remove prototype code * fix * refactor * implement more cast logic * implement more cast logic * add basic test * improve test * cleanup * fmt * add support for casting unsigned int to signed int * clippy * address feedback * fix test * fix: Document enabling comet explain plan usage in Spark (4.0) (#1176) * test: enabling Spark tests with offHeap requirement (#1177) ## Which issue does this PR close? ## Rationale for this change After #1062 We have not running Spark tests for native execution ## What changes are included in this PR? Removed the off heap requirement for testing ## How are these changes tested? Bringing back Spark tests for native execution * feat: Improve shuffle metrics (second attempt) (#1175) * improve shuffle metrics * docs * more metrics * refactor * address feedback * fix: stddev_pop should not directly return 0.0 when count is 1.0 (#1184) * add test * fix * fix * fix * feat: Make native shuffle compression configurable and respect `spark.shuffle.compress` (#1185) * Make shuffle compression codec and level configurable * remove lz4 references * docs * update comment * clippy * fix benches * clippy * clippy * disable test for miri * remove lz4 reference from proto * minor: move shuffle classes from common to spark (#1193) * minor: refactor decodeBatches to make private in broadcast exchange (#1195) * minor: refactor prepare_output so that it does not require an ExecutionContext (#1194) * fix: fix missing explanation for then branch in case when (#1200) * minor: remove unused source files (#1202) * chore: Upgrade to DataFusion 44.0.0-rc2 (#1154) * move aggregate expressions to spark-expr crate * move more expressions * move benchmark * normalize_nan * bitwise not * comet scalar funcs * update bench imports * save * save * save * remove unused imports * clippy * implement more hashers * implement Hash and PartialEq * implement Hash and PartialEq * implement Hash and PartialEq * benches * fix ScalarUDFImpl.return_type failure * exclude test from miri * ignore correct test * ignore another test * remove miri checks * use return_type_from_exprs * Revert "use return_type_from_exprs" This reverts commit febc1f1. * use DF main branch * hacky workaround for regression in ScalarUDFImpl.return_type * fix repo url * pin to revision * bump to latest rev * bump to latest DF rev * bump DF to rev 9f530dd * add Cargo.lock * bump DF version * no default features * Revert "remove miri checks" This reverts commit 4638fe3. * Update pin to DataFusion e99e02b9b9093ceb0c13a2dd32a2a89beba47930 * update pin * Update Cargo.toml Bump to 44.0.0-rc2 * update cargo lock * revert miri change --------- Co-authored-by: Andrew Lamb <[email protected]> * update UT Signed-off-by: Dharan Aditya <[email protected]> * fix typo in UT Signed-off-by: Dharan Aditya <[email protected]> --------- Signed-off-by: Dharan Aditya <[email protected]> Co-authored-by: Andy Grove <[email protected]> Co-authored-by: KAZUYUKI TANIMURA <[email protected]> Co-authored-by: Parth Chandra <[email protected]> Co-authored-by: Liang-Chi Hsieh <[email protected]> Co-authored-by: Raz Luvaton <[email protected]> Co-authored-by: Andrew Lamb <[email protected]> * feat: Add a `spark.comet.exec.memoryPool` configuration for experimenting with various datafusion memory pool setups. (#1021) * feat: Reenable tests for filtered SMJ anti join (#1211) * feat: reenable filtered SMJ Anti join tests * feat: reenable filtered SMJ Anti join tests * feat: reenable filtered SMJ Anti join tests * feat: reenable filtered SMJ Anti join tests * Add CoalesceBatchesExec around SMJ with join filter * adding `CoalesceBatches` * adding `CoalesceBatches` * adding `CoalesceBatches` * feat: reenable filtered SMJ Anti join tests * feat: reenable filtered SMJ Anti join tests --------- Co-authored-by: Andy Grove <[email protected]> * chore: Add safety check to CometBuffer (#1050) * chore: Add safety check to CometBuffer * Add CometColumnarToRowExec * fix * fix * more * Update plan stability results * fix * fix * fix * Revert "fix" This reverts commit 9bad173. * Revert "Revert "fix"" This reverts commit d527ad1. * fix BucketedReadWithoutHiveSupportSuite * fix SparkPlanSuite * remove unreachable code (#1213) * test: Enable Comet by default except some tests in SparkSessionExtensionSuite (#1201) ## Which issue does this PR close? Part of #1197 ## Rationale for this change Since `loadCometExtension` in the diffs were not using `isCometEnabled`, `SparkSessionExtensionSuite` was not using Comet. Once enabled, some test failures discovered ## What changes are included in this PR? `loadCometExtension` now uses `isCometEnabled` that enables Comet by default Temporary ignore the failing tests in SparkSessionExtensionSuite ## How are these changes tested? existing tests * extract struct expressions to folders based on spark grouping (#1216) * chore: extract static invoke expressions to folders based on spark grouping (#1217) * extract static invoke expressions to folders based on spark grouping * Update native/spark-expr/src/static_invoke/mod.rs Co-authored-by: Andy Grove <[email protected]> --------- Co-authored-by: Andy Grove <[email protected]> * chore: Follow-on PR to fully enable onheap memory usage (#1210) * Make datafusion's native memory pool configurable * save * fix * Update memory calculation and add draft documentation * ready for review * ready for review * address feedback * Update docs/source/user-guide/tuning.md Co-authored-by: Liang-Chi Hsieh <[email protected]> * Update docs/source/user-guide/tuning.md Co-authored-by: Kristin Cowalcijk <[email protected]> * Update docs/source/user-guide/tuning.md Co-authored-by: Liang-Chi Hsieh <[email protected]> * Update docs/source/user-guide/tuning.md Co-authored-by: Liang-Chi Hsieh <[email protected]> * remove unused config --------- Co-authored-by: Kristin Cowalcijk <[email protected]> Co-authored-by: Liang-Chi Hsieh <[email protected]> * feat: Move shuffle block decompression and decoding to native code and add LZ4 & Snappy support (#1192) * Implement native decoding and decompression * revert some variable renaming for smaller diff * fix oom issues? * make NativeBatchDecoderIterator more consistent with ArrowReaderIterator * fix oom and prep for review * format * Add LZ4 support * clippy, new benchmark * rename metrics, clean up lz4 code * update test * Add support for snappy * format * change default back to lz4 * make metrics more accurate * format * clippy * use faster unsafe version of lz4_flex * Make compression codec configurable for columnar shuffle * clippy * fix bench * fmt * address feedback * address feedback * address feedback * minor code simplification * cargo fmt * overflow check * rename compression level config * address feedback * address feedback * rename constant * chore: extract agg_funcs expressions to folders based on spark grouping (#1224) * extract agg_funcs expressions to folders based on spark grouping * fix rebase * extract datetime_funcs expressions to folders based on spark grouping (#1222) Co-authored-by: Andy Grove <[email protected]> * chore: use datafusion from crates.io (#1232) * chore: extract strings file to `strings_func` like in spark grouping (#1215) * chore: extract predicate_functions expressions to folders based on spark grouping (#1218) * extract predicate_functions expressions to folders based on spark grouping * code review changes --------- Co-authored-by: Andy Grove <[email protected]> * build(deps): bump protobuf version to 3.21.12 (#1234) * extract json_funcs expressions to folders based on spark grouping (#1220) Co-authored-by: Andy Grove <[email protected]> * test: Enable shuffle by default in Spark tests (#1240) ## Which issue does this PR close? ## Rationale for this change Because `isCometShuffleEnabled` is false by default, some tests were not reached ## What changes are included in this PR? Removed `isCometShuffleEnabled` and updated spark test diff ## How are these changes tested? existing test * chore: extract hash_funcs expressions to folders based on spark grouping (#1221) * extract hash_funcs expressions to folders based on spark grouping * extract hash_funcs expressions to folders based on spark grouping --------- Co-authored-by: Andy Grove <[email protected]> * fix: Fall back to Spark for unsupported partition or sort expressions in window aggregates (#1253) * perf: Improve query planning to more reliably fall back to columnar shuffle when native shuffle is not supported (#1209) * fix regression (#1259) * feat: add support for array_remove expression (#1179) * wip: array remove * added comet expression test * updated test cases * fixed array_remove function for null values * removed commented code * remove unnecessary code * updated the test for 'array_remove' * added test for array_remove in case the input array is null * wip: case array is empty * removed test case for empty array * fix: Fall back to Spark for distinct aggregates (#1262) * fall back to Spark for distinct aggregates * update expected plans for 3.4 * update expected plans for 3.5 * force build * add comment * feat: Implement custom RecordBatch serde for shuffle for improved performance (#1190) * Implement faster encoder for shuffle blocks * make code more concise * enable fast encoding for columnar shuffle * update benches * test all int types * test float * remaining types * add Snappy and Zstd(6) back to benchmark * fix regression * Update native/core/src/execution/shuffle/codec.rs Co-authored-by: Liang-Chi Hsieh <[email protected]> * address feedback * support nullable flag --------- Co-authored-by: Liang-Chi Hsieh <[email protected]> * docs: Update TPC-H benchmark results (#1257) * fix: disable initCap by default (#1276) * fix: disable initCap by default * Update spark/src/main/scala/org/apache/comet/serde/QueryPlanSerde.scala Co-authored-by: Andy Grove <[email protected]> * address review comments --------- Co-authored-by: Andy Grove <[email protected]> * chore: Add changelog for 0.5.0 (#1278) * Add changelog * revert accidental change * move 2 items to performance section * update TPC-DS results for 0.5.0 (#1277) * fix: cast timestamp to decimal is unsupported (#1281) * fix: cast timestamp to decimal is unsupported * fix style * revert test name and mark as ignore * add comment * chore: Start 0.6.0 development (#1286) * start 0.6.0 development * update some docs * Revert a change * update CI * docs: Fix links and provide complete benchmarking scripts (#1284) * fix links and provide complete scripts * fix path * fix incorrect text * feat: Add HasRowIdMapping interface (#1288) * fix style * fix * fix for plan serialization --------- Signed-off-by: Dharan Aditya <[email protected]> Co-authored-by: NoeB <[email protected]> Co-authored-by: Liang-Chi Hsieh <[email protected]> Co-authored-by: Raz Luvaton <[email protected]> Co-authored-by: Andy Grove <[email protected]> Co-authored-by: KAZUYUKI TANIMURA <[email protected]> Co-authored-by: Sem <[email protected]> Co-authored-by: Himadri Pal <[email protected]> Co-authored-by: himadripal <[email protected]> Co-authored-by: gstvg <[email protected]> Co-authored-by: Adam Binford <[email protected]> Co-authored-by: Matt Butrovich <[email protected]> Co-authored-by: Raz Luvaton <[email protected]> Co-authored-by: Andrew Lamb <[email protected]> Co-authored-by: Dharan Aditya <[email protected]> Co-authored-by: Kristin Cowalcijk <[email protected]> Co-authored-by: Oleks V <[email protected]> Co-authored-by: Zhen Wang <[email protected]> Co-authored-by: Jagdish Parihar <[email protected]>
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‎.github/workflows/spark_sql_test.yml

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with:
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spark-version: ${{ matrix.spark-version.full }}
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spark-short-version: ${{ matrix.spark-version.short }}
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comet-version: '0.5.0-SNAPSHOT' # TODO: get this from pom.xml
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comet-version: '0.6.0-SNAPSHOT' # TODO: get this from pom.xml
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- name: Run Spark tests
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cd apache-spark

‎.github/workflows/spark_sql_test_ansi.yml

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comet-version: '0.5.0-SNAPSHOT' # TODO: get this from pom.xml
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comet-version: '0.6.0-SNAPSHOT' # TODO: get this from pom.xml
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- name: Run Spark tests
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‎common/pom.xml

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<parent>
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<groupId>org.apache.datafusion</groupId>
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<artifactId>comet-parent-spark${spark.version.short}_${scala.binary.version}</artifactId>
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<version>0.5.0-SNAPSHOT</version>
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<version>0.6.0-SNAPSHOT</version>
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<relativePath>../pom.xml</relativePath>
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‎common/src/main/java/org/apache/comet/vector/HasRowIdMapping.java

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/*
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* Licensed to the Apache Software Foundation (ASF) under one
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* or more contributor license agreements. See the NOTICE file
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* distributed with this work for additional information
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* regarding copyright ownership. The ASF licenses this file
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* to you under the Apache License, Version 2.0 (the
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* "License"); you may not use this file except in compliance
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* with the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing,
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* software distributed under the License is distributed on an
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* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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* KIND, either express or implied. See the License for the
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* specific language governing permissions and limitations
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* under the License.
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*/
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package org.apache.comet.vector;
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/**
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* An interface could be implemented by vectors that have row id mapping.
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*
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* <p>For example, Iceberg's DeleteFile has a row id mapping to map row id to position. This
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* interface is used to set and get the row id mapping. The row id mapping is an array of integers,
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* where the index is the row id and the value is the position. Here is an example:
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* [0,1,2,3,4,5,6,7] -- Original status of the row id mapping array Position delete 2, 6
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* [0,1,3,4,5,7,-,-] -- After applying position deletes [Set Num records to 6]
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*/
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public interface HasRowIdMapping {
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default void setRowIdMapping(int[] rowIdMapping) {
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throw new UnsupportedOperationException("setRowIdMapping is not supported");
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}
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default int[] getRowIdMapping() {
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throw new UnsupportedOperationException("getRowIdMapping is not supported");
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}
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}

‎docs/source/contributor-guide/benchmark-results/tpc-ds.md

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# Apache DataFusion Comet: Benchmarks Derived From TPC-DS
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The following benchmarks were performed on a two node Kubernetes cluster with
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data stored locally in Parquet format on NVMe storage. Performance characteristics will vary in different environments
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The following benchmarks were performed on a Linux workstation with PCIe 5, AMD 7950X CPU (16 cores), 128 GB RAM, and
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data stored locally in Parquet format on NVMe storage. Performance characteristics will vary in different environments
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and we encourage you to run these benchmarks in your own environments.
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The tracking issue for improving TPC-DS performance is [#858](https://github.com/apache/datafusion-comet/issues/858).
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- [Spark](0.5.0/spark-tpcds.json)
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- [Comet](0.5.0/comet-tpcds.json)
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# Scripts
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Here are the scripts that were used to generate these results.
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## Apache Spark
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```shell
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#!/bin/bash
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$SPARK_HOME/bin/spark-submit \
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--master $SPARK_MASTER \
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--conf spark.driver.memory=8G \
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--conf spark.executor.memory=32G \
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--conf spark.executor.instances=2 \
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--conf spark.executor.cores=8 \
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--conf spark.cores.max=16 \
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--conf spark.eventLog.enabled=true \
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tpcbench.py \
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--benchmark tpcds \
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--name spark \
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--data /mnt/bigdata/tpcds/sf100/ \
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--queries ../../tpcds/ \
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--output . \
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--iterations 5
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```
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## Apache Spark + Comet
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```shell
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#!/bin/bash
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$SPARK_HOME/bin/spark-submit \
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--conf spark.driver.memory=8G \
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--conf spark.executor.instances=2 \
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--conf spark.executor.memory=16G \
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--conf spark.executor.cores=8 \
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--total-executor-cores=16 \
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--conf spark.eventLog.enabled=true \
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--conf spark.driver.maxResultSize=2G \
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--conf spark.memory.offHeap.enabled=true \
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--conf spark.memory.offHeap.size=24g \
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--jars $COMET_JAR \
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--conf spark.driver.extraClassPath=$COMET_JAR \
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--conf spark.executor.extraClassPath=$COMET_JAR \
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--conf spark.plugins=org.apache.spark.CometPlugin \
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--conf spark.comet.enabled=true \
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--conf spark.comet.cast.allowIncompatible=true \
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--conf spark.comet.exec.replaceSortMergeJoin=false \
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--conf spark.comet.exec.shuffle.enabled=true \
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--conf spark.comet.exec.shuffle.mode=auto \
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--conf spark.comet.exec.shuffle.fallbackToColumnar=true \
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--conf spark.comet.exec.shuffle.compression.codec=lz4 \
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--conf spark.shuffle.manager=org.apache.spark.sql.comet.execution.shuffle.CometShuffleManager \
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tpcbench.py \
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--name comet \
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--benchmark tpcds \
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--data /mnt/bigdata/tpcds/sf100/ \
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--queries ../../tpcds/ \
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--output . \
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--iterations 5
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```

‎docs/source/contributor-guide/benchmark-results/tpc-h.md

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The tracking issue for improving TPC-H performance is [#391](https://github.com/apache/datafusion-comet/issues/391).
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![](../../_static/images/benchmark-results/0.5.0-SNAPSHOT-2025-01-09/tpch_allqueries.png)
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![](../../_static/images/benchmark-results/0.5.0/tpch_allqueries.png)
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Here is a breakdown showing relative performance of Spark and Comet for each query.
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![](../../_static/images/benchmark-results/0.5.0-SNAPSHOT-2025-01-09/tpch_queries_compare.png)
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![](../../_static/images/benchmark-results/0.5.0/tpch_queries_compare.png)
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The following chart shows how much Comet currently accelerates each query from the benchmark in relative terms.
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![](../../_static/images/benchmark-results/0.5.0-SNAPSHOT-2025-01-09/tpch_queries_speedup_rel.png)
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![](../../_static/images/benchmark-results/0.5.0/tpch_queries_speedup_rel.png)
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The following chart shows how much Comet currently accelerates each query from the benchmark in absolute terms.
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![](../../_static/images/benchmark-results/0.5.0-SNAPSHOT-2025-01-09/tpch_queries_speedup_abs.png)
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![](../../_static/images/benchmark-results/0.5.0/tpch_queries_speedup_abs.png)
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The raw results of these benchmarks in JSON format is available here:
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- [Spark](0.5.0/spark-tpch.json)
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- [Comet](0.5.0/comet-tpch.json)
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# Scripts
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Here are the scripts that were used to generate these results.
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## Apache Spark
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```shell
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#!/bin/bash
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$SPARK_HOME/bin/spark-submit \
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--master $SPARK_MASTER \
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--conf spark.driver.memory=8G \
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--conf spark.executor.instances=1 \
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--conf spark.executor.cores=8 \
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--conf spark.cores.max=8 \
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--conf spark.executor.memory=16g \
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--conf spark.memory.offHeap.enabled=true \
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--conf spark.memory.offHeap.size=16g \
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--conf spark.eventLog.enabled=true \
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tpcbench.py \
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--name spark \
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--benchmark tpch \
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--data /mnt/bigdata/tpch/sf100/ \
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--queries ../../tpch/queries \
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--output . \
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--iterations 5
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```
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## Apache Spark + Comet
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```shell
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#!/bin/bash
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$SPARK_HOME/bin/spark-submit \
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--master $SPARK_MASTER \
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--conf spark.driver.memory=8G \
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--conf spark.executor.instances=1 \
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--conf spark.executor.cores=8 \
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--conf spark.cores.max=8 \
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--conf spark.executor.memory=16g \
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--conf spark.memory.offHeap.enabled=true \
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--conf spark.memory.offHeap.size=16g \
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--conf spark.comet.exec.replaceSortMergeJoin=true \
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--conf spark.eventLog.enabled=true \
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--jars $COMET_JAR \
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--driver-class-path $COMET_JAR \
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--conf spark.driver.extraClassPath=$COMET_JAR \
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--conf spark.executor.extraClassPath=$COMET_JAR \
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--conf spark.sql.extensions=org.apache.comet.CometSparkSessionExtensions \
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--conf spark.comet.enabled=true \
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--conf spark.comet.exec.shuffle.enabled=true \
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--conf spark.comet.exec.shuffle.mode=auto \
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--conf spark.comet.exec.shuffle.fallbackToColumnar=true \
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--conf spark.comet.exec.shuffle.compression.codec=lz4 \
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--conf spark.shuffle.manager=org.apache.spark.sql.comet.execution.shuffle.CometShuffleManager \
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tpcbench.py \
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--name comet \
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--benchmark tpch \
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--data /mnt/bigdata/tpch/sf100/ \
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--queries ../../tpch/queries \
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--output . \
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--iterations 5
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```

‎docs/source/contributor-guide/benchmarking.md

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We also have many micro benchmarks that can be run from an IDE located [here](https://github.com/apache/datafusion-comet/tree/main/spark/src/test/scala/org/apache/spark/sql/benchmark).
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Here are example commands for running the benchmarks against a Spark cluster. This command will need to be
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adapted based on the Spark environment and location of data files.
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These commands are intended to be run from the `runners/datafusion-comet` directory in the `datafusion-benchmarks`
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repository.
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## Running Benchmarks Against Apache Spark
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```shell
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$SPARK_HOME/bin/spark-submit \
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--master $SPARK_MASTER \
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--conf spark.driver.memory=8G \
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--conf spark.executor.instances=1 \
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--conf spark.executor.memory=32G \
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--conf spark.executor.cores=8 \
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--conf spark.cores.max=8 \
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tpcbench.py \
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--benchmark tpch \
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--data /mnt/bigdata/tpch/sf100/ \
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--queries ../../tpch/queries \
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--iterations 3
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```
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## Running Benchmarks Against Apache Spark with Apache DataFusion Comet Enabled
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### TPC-H
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```shell
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$SPARK_HOME/bin/spark-submit \
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--master $SPARK_MASTER \
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--conf spark.driver.memory=8G \
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--conf spark.executor.instances=1 \
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--conf spark.executor.memory=16G \
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--conf spark.executor.cores=8 \
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--conf spark.cores.max=8 \
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--conf spark.memory.offHeap.enabled=true \
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--conf spark.memory.offHeap.size=16g \
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--jars $COMET_JAR \
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--conf spark.driver.extraClassPath=$COMET_JAR \
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--conf spark.executor.extraClassPath=$COMET_JAR \
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--conf spark.plugins=org.apache.spark.CometPlugin \
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--conf spark.comet.cast.allowIncompatible=true \
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--conf spark.comet.exec.replaceSortMergeJoin=true \
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--conf spark.shuffle.manager=org.apache.spark.sql.comet.execution.shuffle.CometShuffleManager \
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--conf spark.comet.exec.shuffle.enabled=true \
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--conf spark.comet.exec.shuffle.mode=auto \
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--conf spark.comet.exec.shuffle.enableFastEncoding=true \
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--conf spark.comet.exec.shuffle.fallbackToColumnar=true \
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--conf spark.comet.exec.shuffle.compression.codec=lz4 \
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tpcbench.py \
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--benchmark tpch \
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--data /mnt/bigdata/tpch/sf100/ \
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--queries ../../tpch/queries \
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--iterations 3
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```
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### TPC-DS
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For TPC-DS, use `spark.comet.exec.replaceSortMergeJoin=false`.

‎docs/source/contributor-guide/debugging.md

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@@ -130,7 +130,7 @@ Then build the Comet as [described](https://github.com/apache/arrow-datafusion-c
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Start Comet with `RUST_BACKTRACE=1`
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```console
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RUST_BACKTRACE=1 $SPARK_HOME/spark-shell --jars spark/target/comet-spark-spark3.4_2.12-0.5.0-SNAPSHOT.jar --conf spark.plugins=org.apache.spark.CometPlugin --conf spark.comet.enabled=true --conf spark.comet.exec.enabled=true
133+
RUST_BACKTRACE=1 $SPARK_HOME/spark-shell --jars spark/target/comet-spark-spark3.4_2.12-0.6.0-SNAPSHOT.jar --conf spark.plugins=org.apache.spark.CometPlugin --conf spark.comet.enabled=true --conf spark.comet.exec.enabled=true
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```
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Get the expanded exception details

‎docs/source/user-guide/installation.md

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Make sure `SPARK_HOME` points to the same Spark version as Comet was built for.
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```console
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export COMET_JAR=spark/target/comet-spark-spark3.4_2.12-0.5.0-SNAPSHOT.jar
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export COMET_JAR=spark/target/comet-spark-spark3.4_2.12-0.6.0-SNAPSHOT.jar
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$SPARK_HOME/bin/spark-shell \
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--jars $COMET_JAR \
@@ -130,7 +130,7 @@ explicitly contain Comet otherwise Spark may use a different class-loader for th
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components which will then fail at runtime. For example:
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```
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--driver-class-path spark/target/comet-spark-spark3.4_2.12-0.5.0-SNAPSHOT.jar
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--driver-class-path spark/target/comet-spark-spark3.4_2.12-0.6.0-SNAPSHOT.jar
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```
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Some cluster managers may require additional configuration, see <https://spark.apache.org/docs/latest/cluster-overview.html>

‎fuzz-testing/pom.xml

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<parent>
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<groupId>org.apache.datafusion</groupId>
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<artifactId>comet-parent-spark${spark.version.short}_${scala.binary.version}</artifactId>
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<version>0.5.0-SNAPSHOT</version>
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<version>0.6.0-SNAPSHOT</version>
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<relativePath>../pom.xml</relativePath>
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</parent>
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‎native/Cargo.lock

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Some generated files are not rendered by default. Learn more about customizing how changed files appear on GitHub.

‎native/Cargo.toml

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resolver = "2"
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[workspace.package]
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version = "0.5.0"
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version = "0.6.0"
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homepage = "https://datafusion.apache.org/comet"
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repository = "https://github.com/apache/datafusion-comet"
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authors = ["Apache DataFusion <[email protected]>"]
@@ -48,8 +48,8 @@ datafusion-expr-common = { version = "44.0.0", default-features = false }
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datafusion-execution = { version = "44.0.0", default-features = false }
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datafusion-physical-plan = { version = "44.0.0", default-features = false }
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datafusion-physical-expr = { version = "44.0.0", default-features = false }
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datafusion-comet-spark-expr = { path = "spark-expr", version = "0.5.0" }
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datafusion-comet-proto = { path = "proto", version = "0.5.0" }
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datafusion-comet-spark-expr = { path = "spark-expr", version = "0.6.0" }
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datafusion-comet-proto = { path = "proto", version = "0.6.0" }
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chrono = { version = "0.4", default-features = false, features = ["clock"] }
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chrono-tz = { version = "0.8" }
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futures = "0.3.28"

‎pom.xml

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</parent>
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<groupId>org.apache.datafusion</groupId>
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<artifactId>comet-parent-spark${spark.version.short}_${scala.binary.version}</artifactId>
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<version>0.5.0-SNAPSHOT</version>
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<version>0.6.0-SNAPSHOT</version>
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<packaging>pom</packaging>
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<name>Comet Project Parent POM</name>
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‎spark-integration/pom.xml

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<parent>
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<groupId>org.apache.datafusion</groupId>
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<artifactId>comet-parent-spark${spark.version.short}_${scala.binary.version}</artifactId>
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<version>0.5.0-SNAPSHOT</version>
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<version>0.6.0-SNAPSHOT</version>
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<relativePath>../pom.xml</relativePath>
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</parent>
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