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From "Kevin Wilfong (Commented) (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HIVE-2621) Allow multiple group bys with the same input data and spray keys to be run on the same reducer.
Date Thu, 22 Dec 2011 18:13:31 GMT

    [ https://issues.apache.org/jira/browse/HIVE-2621?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13174945#comment-13174945
] 

Kevin Wilfong commented on HIVE-2621:
-------------------------------------

There are currently two ways of getting common distincts, the current way checks that all
distinct expressions in the subqueries are the same.  My new code doesn't depend on this,
it tries to construct subsets of the subqueries such that this is true for each subset.

The advantage of doing it in the form
if (optimizeMultiGroupBy) {
  ...
} else {
  <group queries by common distinct and group by expressions>
  for each group:
    if (size of group > 1 && etc.) {
      <new code>
    } else {
      <old code>
    }
}

is that the block of code inside the optimizeMultiGroupBy if statement can produce 2 map reduce
jobs where the new code might produce many.

After looking at it more carefully, I can get rid of the singlemrMultiGroupBy if statement
and the code within the block because it produces the same result that my new code would except
that the new code can handle filters as well.

After removing that code, the only remaining code above the if statement will be the poorly
named getCommonDistinctExprs (as it only returns the common distinct expressions provided
a lot of conditions are met including a requirement that all the distinct expressions are
common), which I should be able to modify to use my new code.
                
> 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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