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https://issues.apache.org/jira/browse/SPARK-32096?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Zikun updated SPARK-32096:
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Summary: Improve sorting performance for Spark SQL rank window function
(was: Support top-N sort for Spark SQL rank window function)
> Improve sorting performance for Spark SQL rank window function
> ---------------------------------------------------------------
>
> Key: SPARK-32096
> URL: https://issues.apache.org/jira/browse/SPARK-32096
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 3.0.0
> Environment: Any environment that supports Spark.
> Reporter: Zikun
> Priority: Major
>
> In Spark SQL, there are two types of sort execution, *_SortExec_* and
> *_TakeOrderedAndProjectExec_* .
> *_SortExec_* is a general sorting execution and it does not support top-N
> sort.
> *_TakeOrderedAndProjectExec_* is the execution for top-N sort in Spark.
> Spark SQL rank window function needs to sort the data locally and it relies
> on the execution plan *_SortExec_* to sort the data in each physical data
> partition. When the filter of the window rank (e.g. rank <= 100) is specified
> in a user's query, the filter can actually be pushed down to the SortExec and
> then we let SortExec operates top-N sort.
> Right now SortExec does not support top-N sort and we need to extend the
> capability of SortExec to support top-N sort.
> Or if SortExec is not considered as the right execution choice, we can create
> a new execution plan called topNSortExec to do top-N sort in each local
> partition if a filter on the window rank is specified.
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