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Posted to issues@spark.apache.org by "Zikun (Jira)" <ji...@apache.org> on 2020/06/24 21:15:00 UTC
[jira] [Updated] (SPARK-32096) Support top-N sort for Spark SQL
rank window function
[ https://issues.apache.org/jira/browse/SPARK-32096?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Zikun updated SPARK-32096:
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Summary: Support top-N sort for Spark SQL rank window function (was: Support top-N sort for Spark SQL window function)
> Support top-N sort 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
> Fix For: 3.1.0
>
>
> 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 rank is specified.
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