Yuming Wang created SPARK-29655:
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Summary: Prefer bucket join if adaptive execution is enabled and
maxNumPostShufflePartitions != bucket number
Key: SPARK-29655
URL: https://issues.apache.org/jira/browse/SPARK-29655
Project: Spark
Issue Type: Improvement
Components: SQL
Affects Versions: 3.0.0
Reporter: Yuming Wang
Prefer bucketing join if adaptive execution is enabled and
maxNumPostShufflePartitions != bucket number. How to reproduce:
{code:scala}
import org.apache.spark.sql.SaveMode
spark.conf.set("spark.sql.autoBroadcastJoinThreshold", -1)
spark.conf.set("spark.sql.shuffle.partitions", 4)
val bucketedTableName = "bucketed_table"
spark.range(10).write.bucketBy(4,
"id").sortBy("id").mode(SaveMode.Overwrite).saveAsTable(bucketedTableName)
val bucketedTable = spark.table(bucketedTableName)
val df = spark.range(4)
df.join(bucketedTable, "id").explain()
spark.conf.set("spark.sql.adaptive.enabled", true)
spark.conf.set("spark.sql.adaptive.shuffle.maxNumPostShufflePartitions", 5)
df.join(bucketedTable, "id").explain()
{code}
Output:
{noformat}
== Physical Plan ==
AdaptiveSparkPlan(isFinalPlan=false)
+- Project [id#5L]
+- SortMergeJoin [id#5L], [id#3L], Inner
:- Sort [id#5L ASC NULLS FIRST], false, 0
: +- Exchange hashpartitioning(id#5L, 5), true, [id=#92]
: +- Range (0, 4, step=1, splits=16)
+- Sort [id#3L ASC NULLS FIRST], false, 0
+- Exchange hashpartitioning(id#3L, 5), true, [id=#93]
+- Project [id#3L]
+- Filter isnotnull(id#3L)
+- FileScan parquet default.bucketed_table[id#3L] Batched:
true, DataFilters: [isnotnull(id#3L)], Format: Parquet, Location:
InMemoryFileIndex[file:/root/spark-3.0.0-preview-bin-hadoop3.2/spark-warehouse/bucketed_table],
PartitionFilters: [], PushedFilters: [IsNotNull(id)], ReadSchema:
struct<id:bigint>, SelectedBucketsCount: 4 out of 4
{noformat}
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