[GitHub] [spark] cloud-fan edited a comment on pull request #29692: [SPARK-32830][SQL] Optimize Skewed BroadcastNestedLoopJoin with AQE

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

cloud-fan edited a comment on pull request #29692:
URL: https://github.com/apache/spark/pull/29692#issuecomment-690931387


   If the user manually adds a shuffle (DISTRIBUTE BY) in the query before broadcast join, I think we can take care of the skew. Spark query optimizer should not add the extra shuffle by itself, as it's likely to cause perf regression.
   
   But we need to be careful to break output partitioning by splitting the skewed partitions, and cause extra shuffle.


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