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Posted to reviews@spark.apache.org by GitBox <gi...@apache.org> on 2020/09/10 11:16:02 UTC

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

cloud-fan commented on pull request #29692:
URL: https://github.com/apache/spark/pull/29692#issuecomment-690172209


   What's the high-level idea? We can handle skew SMJ because there is a shuffle and we can split the partition with the granularity of shuffle blocks. Broadcast join doesn't have shuffles.


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