[GitHub] maropu commented on issue #23731: [SPARK-26572][SQL] fix aggregate codegen result evaluation

[GitBox <gi...@apache.org>]

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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