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https://issues.apache.org/jira/browse/HIVE-2621?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13174891#comment-13174891
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Namit Jain commented on HIVE-2621:
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Let me take a look at the code again:
But the general flow should be as follows:
if hive.multigroupby.singlereducer is true (which should always be),
find common distincts.
(or the check hive.multigroupby.singlereducer can be done inside find
common distincts function itself)
if common distincts == null
old (current) approach - map side aggr should be used
else:
new code path
What do you think ? That way, we are guaranteed that the existing behavior is
not changed.
This new parameter is only affecting distincts, and we it is very easy to turn
it off
I know the code is kind of messy here, but can you spend some time to
modularize it,
and reuse as much as possible ?
> 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
>
>
> 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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