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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