maropu commented on issue #23731: [SPARK-26572][SQL] fix aggregate codegen result evaluation URL: https://github.com/apache/spark/pull/23731#issuecomment-460110603 I think we should handle this case in a planner? For example, if we turn off broadcast join, the behaviour changes; ``` scala> val baseTable = Seq((1), (1)).toDF("idx") scala> val distinctWithId = baseTable.distinct.withColumn("id", functions.monotonically_increasing_id()) scala> baseTable.join(distinctWithId, "idx").show +---+------------+ |idx| id| +---+------------+ | 1|369367187456| | 1|369367187457| +---+------------+ sql("SET spark.sql.autoBroadcastJoinThreshold=-1") scala> baseTable.join(distinctWithId, "idx").show +---+------------+ |idx| id| +---+------------+ | 1|369367187456| | 1|369367187456| +---+------------+ ``` Could you check again?
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