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https://issues.apache.org/jira/browse/SPARK-24650?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon resolved SPARK-24650.
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Resolution: Incomplete
> GroupingSet
> -----------
>
> Key: SPARK-24650
> URL: https://issues.apache.org/jira/browse/SPARK-24650
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 2.3.1
> Environment: CDH 5.X, Spark 2.3
> Reporter: Mihir Sahu
> Priority: Major
> Labels: Grouping, Sets, bulk-closed
>
> If a grouping set is used in spark sql, then the plan does not perform
> optimally.
> If input to a grouping set is X rows and the grouping sets has y group, then
> the number of rows that are processed is currently x*y rows.
> Example : Let a Dataframe have col1, col2, col3 and col4 columns and number
> of row be rowNo.
> and grouping set consist of : (1) col1, col2, col3 (2) col2,col4 (3) col1,col2
> Number of row processed in such case is 3*(rowNos * size of each row).
> However is this the optimal way of processing data.
> If the groups of y are derivable for each other, can we reduce the amount of
> volume processed by removing columns as we progress to the lower dimension of
> processing.
> Currently while doing processing percentile, a lot of data seems to be
> processed causing performance issue.
> Need to look if this can be optimised
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