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Liu Shuo updated SPARK-43182: ----------------------------- Attachment: part-m-00000.zip > Mutilple tables join with limit when AE is enabled and one table is skewed > -------------------------------------------------------------------------- > > Key: SPARK-43182 > URL: https://issues.apache.org/jira/browse/SPARK-43182 > Project: Spark > Issue Type: Bug > Components: SQL > Affects Versions: 3.4.0 > Reporter: Liu Shuo > Priority: Critical > Attachments: part-m-00000.zip > > > When we test AE in Spark3.4.0 with the following case, we find If we disable > AE or enable Ae but disable skewJoin, the sql will finish in 20s, but if we > enable AE and enable skewJoin,it will take very long time. > The test case: > {code:java} > ###uncompress the data.zip, and put files under '/tmp/spark-warehouse/data/' > dir. > create table source_aqe(c1 int,c18 string) using csv options(path > 'file:///tmp/spark-warehouse/data/'); > create table hive_snappy_aqe_table1(c1 int)stored as PARQUET partitioned > by(c18 string); > insert into table hive_snappy_aqe_table1 partition(c18=1)select c1 from > source_aqe; > insert into table hive_snappy_aqe_table1 partition(c18=2)select c1 from > source_aqe limit 120000; > insert into table hive_snappy_aqe_table1 partition(c18=3)select c1 from > source_aqe limit 150000;create table hive_snappy_aqe_table2(c1 int)stored as > PARQUET partitioned by(c18 string); > insert into table hive_snappy_aqe_table2 partition(c18=1)select c1 from > source_aqe limit 160000; > insert into table hive_snappy_aqe_table2 partition(c18=2)select c1 from > source_aqe limit 120000;create table hive_snappy_aqe_table3(c1 int)stored as > PARQUET partitioned by(c18 string); > insert into table hive_snappy_aqe_table3 partition(c18=1)select c1 from > source_aqe limit 160000; > insert into table hive_snappy_aqe_table3 partition(c18=2)select c1 from > source_aqe limit 120000; > set spark.sql.adaptive.enabled=false; > set spark.sql.adaptive.forceOptimizeSkewedJoin = false; > set spark.sql.adaptive.skewJoin.skewedPartitionFactor=1; > set spark.sql.adaptive.skewJoin.skewedPartitionThresholdInBytes=10KB; > set spark.sql.adaptive.advisoryPartitionSizeInBytes=100KB; > set spark.sql.autoBroadcastJoinThreshold = 51200; > > ###it will finish in 20s > select * from hive_snappy_aqe_table1 join hive_snappy_aqe_table2 on > hive_snappy_aqe_table1.c18=hive_snappy_aqe_table2.c18 join > hive_snappy_aqe_table3 on > hive_snappy_aqe_table1.c18=hive_snappy_aqe_table3.c18 limit 10; > set spark.sql.adaptive.enabled=true; > set spark.sql.adaptive.forceOptimizeSkewedJoin = true; > set spark.sql.adaptive.skewJoin.skewedPartitionFactor=1; > set spark.sql.adaptive.skewJoin.skewedPartitionThresholdInBytes=10KB; > set spark.sql.adaptive.advisoryPartitionSizeInBytes=100KB; > set spark.sql.autoBroadcastJoinThreshold = 51200; > ###it will take very long time > select * from hive_snappy_aqe_table1 join hive_snappy_aqe_table2 on > hive_snappy_aqe_table1.c18=hive_snappy_aqe_table2.c18 join > hive_snappy_aqe_table3 on > hive_snappy_aqe_table1.c18=hive_snappy_aqe_table3.c18 limit 10; > {code} -- This message was sent by Atlassian Jira (v8.20.10#820010) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org