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From "Prasanth J (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HIVE-7156) Group-By operator stat-annotation only uses distinct approx to generate rollups
Date Fri, 12 Sep 2014 07:24:33 GMT

    [ https://issues.apache.org/jira/browse/HIVE-7156?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14131218#comment-14131218
] 

Prasanth J commented on HIVE-7156:
----------------------------------

[~hagleitn]/[~gopalv]/[~rhbutani] can someone plz take a look at this patch? The patch has
mostly test file changes. The code changes are small.

> Group-By operator stat-annotation only uses distinct approx to generate rollups
> -------------------------------------------------------------------------------
>
>                 Key: HIVE-7156
>                 URL: https://issues.apache.org/jira/browse/HIVE-7156
>             Project: Hive
>          Issue Type: Sub-task
>    Affects Versions: 0.14.0
>            Reporter: Gopal V
>            Assignee: Prasanth J
>         Attachments: HIVE-7156.1.patch, HIVE-7156.2.patch, HIVE-7156.3.patch, HIVE-7156.4.patch
>
>
> The stats annotation for a group-by only annotates the reduce-side row-count with the
distinct values.
> The map-side gets the row-count as the rows output instead of distinct * parallelism,
while the reducer side gets the correct parallelism.
> {code}
> hive> explain select distinct L_SHIPDATE from lineitem;
>       Vertices:
>         Map 1 
>             Map Operator Tree:
>                 TableScan
>                   alias: lineitem
>                   Statistics: Num rows: 5999989709 Data size: 4745677733354 Basic stats:
COMPLETE Column stats: COMPLETE
>                   Select Operator
>                     expressions: l_shipdate (type: string)
>                     outputColumnNames: l_shipdate
>                     Statistics: Num rows: 5999989709 Data size: 4745677733354 Basic stats:
COMPLETE Column stats: COMPLETE
>                     Group By Operator
>                       keys: l_shipdate (type: string)
>                       mode: hash
>                       outputColumnNames: _col0
>                       Statistics: Num rows: 5999989709 Data size: 563999032646 Basic
stats: COMPLETE Column stats: COMPLETE
>                       Reduce Output Operator
>                         key expressions: _col0 (type: string)
>                         sort order: +
>                         Map-reduce partition columns: _col0 (type: string)
>                         Statistics: Num rows: 5999989709 Data size: 563999032646 Basic
stats: COMPLETE Column stats: COMPLETE
>             Execution mode: vectorized
>         Reducer 2 
>             Reduce Operator Tree:
>               Group By Operator
>                 keys: KEY._col0 (type: string)
>                 mode: mergepartial
>                 outputColumnNames: _col0
>                 Statistics: Num rows: 1955 Data size: 183770 Basic stats: COMPLETE Column
stats: COMPLETE
>                 Select Operator
>                   expressions: _col0 (type: string)
>                   outputColumnNames: _col0
>                   Statistics: Num rows: 1955 Data size: 183770 Basic stats: COMPLETE
Column stats: COMPLETE
> {code}



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