Github user mgaido91 commented on a diff in the pull request:
https://github.com/apache/spark/pull/21529#discussion_r195066108
--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/execution/PlannerSuite.scala ---
@@ -679,6 +679,17 @@ class PlannerSuite extends SharedSQLContext {
}
assert(rangeExecInZeroPartition.head.outputPartitioning ==
UnknownPartitioning(0))
}
+
+ test("SPARK-24495: EnsureRequirements can return wrong plan when reusing
the same key in join") {
+ withSQLConf(("spark.sql.shuffle.partitions", "1"),
+ ("spark.sql.constraintPropagation.enabled", "false"),
+ ("spark.sql.autoBroadcastJoinThreshold", "-1")) {
+ val df1 = spark.range(100).repartition(2, $"id", $"id")
--- End diff --
yes, but if we remove the transformUp as you correctly suggested, if we do
not use HashPartitioning we do not test the proper behavior of the `reorder`
method. So I think that using the HashPartitioning is a better test for this
change. What do you think?
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