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Posted to reviews@spark.apache.org by GitBox <gi...@apache.org> on 2019/12/13 03:51:08 UTC
[GitHub] [spark] maryannxue commented on issue #26814: [SPARK-30186][SQL]
support Dynamic Partition Pruning in Adaptive Execution
maryannxue commented on issue #26814: [SPARK-30186][SQL] support Dynamic Partition Pruning in Adaptive Execution
URL: https://github.com/apache/spark/pull/26814#issuecomment-565289542
The plan is due to change over the entire process of query execution, so planning the dynamic filters for the whole plan in each re-optimization iteration is definitely the least efficient way. A join can swing from a SMJ to a BHJ or the other way around from time to time, and that affects the applicability of a SubqueryBroadcast DPP filter, and you may end up changing and replanning the filter back and forth.
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