cloud-fan commented on code in PR #37014:
URL: https://github.com/apache/spark/pull/37014#discussion_r916505114
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sql/core/src/test/scala/org/apache/spark/sql/execution/adaptive/AdaptiveQueryExecSuite.scala:
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@@ -2602,6 +2602,59 @@ class AdaptiveQueryExecSuite
assert(findTopLevelBroadcastNestedLoopJoin(adaptivePlan).size == 1)
}
}
+
+ test("SPARK-39624 Support coalesce partition through CartesianProduct") {
+ def checkResultPartition(
+ df: Dataset[Row],
+ numShuffleReader: Int,
+ numPartition: Int): Unit = {
+ df.collect()
+ assert(collect(df.queryExecution.executedPlan) {
+ case r: AQEShuffleReadExec => r
+ }.size === numShuffleReader)
+ assert(df.rdd.partitions.length === numPartition)
+ }
+ withSQLConf(SQLConf.ADAPTIVE_EXECUTION_ENABLED.key -> "true",
+ SQLConf.COALESCE_PARTITIONS_ENABLED.key -> "true",
+ SQLConf.ADVISORY_PARTITION_SIZE_IN_BYTES.key -> "1048576",
+ SQLConf.COALESCE_PARTITIONS_MIN_PARTITION_NUM.key -> "1",
+ SQLConf.SHUFFLE_PARTITIONS.key -> "10") {
+ withTempView("t1", "t2", "t3") {
+ spark.sparkContext.parallelize((1 to 10).map(i => TestData(i,
i.toString)), 2)
+ .toDF().createOrReplaceTempView("t1")
+ spark.sparkContext.parallelize((1 to 10).map(i => TestData(i,
i.toString)), 4)
+ .toDF().createOrReplaceTempView("t2")
+ spark.sparkContext.parallelize((1 to 10).map(i => TestData(i,
i.toString)), 4)
+ .toDF().createOrReplaceTempView("t3")
+ // positive test that could be coalesced
+ checkResultPartition(
+ sql("""
+ |SELECT * FROM
+ |(SELECT * FROM t3) t3
+ |join (
+ |SELECT t1.key, t2.value FROM
+ |(SELECT * FROM t1 ) t1
+ |join (SELECT * FROM t2) t2
+ |on t1.value = t2.value) t
+ |on t3.key = t.key or t3.value=t.value
+ """.stripMargin),
+ numShuffleReader = 2,
+ numPartition = 4)
+ // negative test
+ checkResultPartition(
+ sql("""
+ |SELECT * FROM
+ |(SELECT * FROM t1)
+ |t1 join (SELECT * FROM t2)
+ |t2 on t1.key = t2.key
+ |or t1.value=t2.value
Review Comment:
Why doesn't this trigger a partition coalesce? isn't it a cartesian product?
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