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https://issues.apache.org/jira/browse/HIVE-2621?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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He Yongqiang updated HIVE-2621:
-------------------------------
Resolution: Fixed
Status: Resolved (was: Patch Available)
committed, 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
> Attachments: HIVE-2621.1.patch.txt, HIVE-2621.D567.1.patch,
> HIVE-2621.D567.2.patch, HIVE-2621.D567.3.patch, HIVE-2621.D567.4.patch
>
>
> 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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