andygrove commented on issue #1275:
URL:
https://github.com/apache/datafusion-comet/issues/1275#issuecomment-2787315942
I ran this test again with latest from main. I used this script to launch
spark-shell:
```shell
$SPARK_HOME/bin/spark-shell \
--master $SPARK_MASTER \
--conf spark.driver.memory=4G \
--conf spark.executor.instances=1 \
--conf spark.executor.cores=8 \
--conf spark.cores.max=8 \
--conf spark.executor.memory=16g \
--conf spark.memory.offHeap.enabled=true \
--conf spark.memory.offHeap.size=16g \
--conf spark.eventLog.enabled=false \
--jars $COMET_JAR \
--driver-class-path $COMET_JAR \
--conf spark.driver.extraClassPath=$COMET_JAR \
--conf spark.executor.extraClassPath=$COMET_JAR \
--conf spark.plugins=org.apache.spark.CometPlugin \
--conf
spark.shuffle.manager=org.apache.spark.sql.comet.execution.shuffle.CometShuffleManager
\
--conf spark.comet.enabled=true \
--conf spark.comet.cast.allowIncompatible=true \
--conf spark.comet.exec.replaceSortMergeJoin=true \
--conf spark.comet.exec.shuffle.enabled=true \
--conf spark.comet.exec.shuffle.fallbackToColumnar=true \
--conf spark.comet.exec.shuffle.compression.codec=lz4 \
--conf spark.comet.exec.shuffle.compression.level=1
```
I ran this query
```scala
spark.time(spark.read.parquet("/mnt/bigdata/tpcds/sf100/store_sales.parquet").repartition($"ss_item_sk").dropDuplicates(Seq("ss_item_sk",
"ss_quantity")).write.parquet("output.parquet"))
```
With Comet: 325s
With Spark: 77s
Observations:
- Scan is fast (45 seconds)
- Shuffle is fast (4.3 mins)
- Aggregate is slow (31.9 mins)
- ColumnarToRow is slow (36.8 mins)
- Aggregate takes
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