peter-toth commented on a change in pull request #25479:
[SPARK-28356][SHUFFLE][FOLLOWUP] Fix case with different pre-shuffle partition
numbers
URL: https://github.com/apache/spark/pull/25479#discussion_r314814514
##########
File path:
sql/core/src/test/scala/org/apache/spark/sql/execution/ReduceNumShufflePartitionsSuite.scala
##########
@@ -587,4 +587,22 @@ class ReduceNumShufflePartitionsSuite extends
SparkFunSuite with BeforeAndAfterA
}
withSparkSession(test, 200, None)
}
+
+ test("Union two datasets with different pre-shuffle partition number") {
+ val test: SparkSession => Unit = { spark: SparkSession =>
+ val df1 = spark.range(3).join(spark.range(3), "id").toDF()
+ val df2 = spark.range(3).groupBy().sum()
+
+ val resultDf = df1.union(df2)
+
+ checkAnswer(resultDf, Seq((0), (1), (2), (3)).map(i => Row(i)))
Review comment:
It does. The plan is:
```
AdaptiveSparkPlan(isFinalPlan=false)
+- Union
:- Project [id#0L]
: +- SortMergeJoin [id#0L], [id#2L], Inner
: :- Sort [id#0L ASC NULLS FIRST], false, 0
: : +- Exchange hashpartitioning(id#0L, 5), true
: : +- Range (0, 3, step=1, splits=12)
: +- Sort [id#2L ASC NULLS FIRST], false, 0
: +- Exchange hashpartitioning(id#2L, 5), true
: +- Range (0, 3, step=1, splits=12)
+- HashAggregate(keys=[], functions=[sum(id#6L)], output=[sum(id)#10L])
+- Exchange SinglePartition, true
+- HashAggregate(keys=[], functions=[partial_sum(id#6L)],
output=[sum#14L])
+- Range (0, 3, step=1, splits=12)
```
and the error comes from this assert:
https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/execution/adaptive/ReduceNumShufflePartitions.scala#L136
Honestly I'm not sure why the `Exchange SinglePartition` has `true`
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