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https://issues.apache.org/jira/browse/HIVE-2621?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13978907#comment-13978907
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Lefty Leverenz commented on HIVE-2621:
--------------------------------------

Thanks Kevin.

> Allow multiple group bys with the same input data and spray keys to be run on 
> the same reducer.
> -----------------------------------------------------------------------------------------------
>
>                 Key: HIVE-2621
>                 URL: https://issues.apache.org/jira/browse/HIVE-2621
>             Project: Hive
>          Issue Type: New Feature
>            Reporter: Kevin Wilfong
>            Assignee: Kevin Wilfong
>             Fix For: 0.9.0
>
>         Attachments: ASF.LICENSE.NOT.GRANTED--HIVE-2621.D567.1.patch, 
> ASF.LICENSE.NOT.GRANTED--HIVE-2621.D567.2.patch, 
> ASF.LICENSE.NOT.GRANTED--HIVE-2621.D567.3.patch, 
> ASF.LICENSE.NOT.GRANTED--HIVE-2621.D567.4.patch, HIVE-2621.1.patch.txt
>
>
> Currently, when a user runs a query, such as a multi-insert, where each 
> insertion subclause consists of a simple query followed by a group by, the 
> group bys for each clause are run on a separate reducer.  This requires 
> writing the data for each group by clause to an intermediate file, and then 
> reading it back.  This uses a significant amount of the total CPU consumed by 
> the query for an otherwise simple query.
> If the subclauses are grouped by their distinct expressions and group by 
> keys, with all of the group by expressions for a group of subclauses run on a 
> single reducer, this would reduce the amount of reading/writing to 
> intermediate files for some queries.
> To do this, for each group of subclauses, in the mapper we would execute a 
> the filters for each subclause 'or'd together (provided each subclause has a 
> filter) followed by a reduce sink.  In the reducer, the child operators would 
> be each subclauses filter followed by the group by and any subsequent 
> operations.
> Note that this would require turning off map aggregation, so we would need to 
> make using this type of plan configurable.



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