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https://issues.apache.org/jira/browse/SPARK-51398?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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ASF GitHub Bot updated SPARK-51398:
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Labels: pull-request-available (was: )
> SparkSQL supports sorting in the shuffle phase.
> -----------------------------------------------
>
> Key: SPARK-51398
> URL: https://issues.apache.org/jira/browse/SPARK-51398
> Project: Spark
> Issue Type: New Feature
> Components: SQL
> Affects Versions: 3.5.5
> Reporter: Chenyu Zheng
> Priority: Major
> Labels: pull-request-available
>
> Currently, SparkSQL does not perform any sorting on the shuffle side. This
> issue hopes to provide an option to enable sorting in the shuffle phase.
> Why do we need to sort on the shuffle side?
> In some cloud scenarios, we want to avoid using disk for Spark job.
> How to avoid using disk for Spark tasks?
> Some job need to aggregate or sort. If the data is too large to fit in
> memory, spilling to disk is necessary. If we can move sort to shuffle, then
> use remote shuffle service, we can avoid disk operations.
> What are the main changes in this issue?
> (1) The change only applies to scenarios with shuffle. Therefore, sorting
> within a window is not supported.
> (2) Sorting during the shuffle phase. This can avoid introducing SortExec
> after shuffle and avoid spilling.
> (4) Provide memory-based HashAggregateExec to avoid spilling.
> For join, use sort merge join, and the SortExec in reduce phase will be
> automatically deleted.
> For aggregation. Use memory-based HashAggregateExec on the map side. Use
> SortAggregateExec on the reduce side. The SortExec will be automatically
> deleted between shuffle and SortAggregateExec.
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