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docs: Fix links and provide complete benchmarking scripts (#1284)
* fix links and provide complete scripts * fix path * fix incorrect text
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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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--master $SPARK_MASTER \
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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`.
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## Current Benchmark Results
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- [Benchmarks derived from TPC-H](benchmark-results/tpc-h)

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