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https://issues.apache.org/jira/browse/SPARK-32012?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17138024#comment-17138024
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Apache Spark commented on SPARK-32012:
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User 'viirya' has created a pull request for this issue:
https://github.com/apache/spark/pull/28846
> Incrementally create and materialize query stage to avoid unnecessary local
> shuffle
> -----------------------------------------------------------------------------------
>
> Key: SPARK-32012
> URL: https://issues.apache.org/jira/browse/SPARK-32012
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 3.1.0
> Reporter: L. C. Hsieh
> Assignee: L. C. Hsieh
> Priority: Major
>
> The current way of creating query stage in AQE is in batch. For example, the
> children of a sort merge join will be materialized as query stages in a
> batch. Then AQE brings the optimization in and optimize sort merge join to
> broadcast join. Except for the broadcasted exchange, we don't need do any
> exchange on another side of join but we already materialized the exchange.
> Currently AQE wraps the materialized exchange with local reader, but it still
> brings unnecessary I/O. We can avoid unnecessary local shuffle by
> incrementally creating query stage.
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