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Posted to dev@pig.apache.org by "Richard Ding (JIRA)" <ji...@apache.org> on 2009/10/05 21:30:31 UTC

[jira] Updated: (PIG-983) PERFORMANCE: multi-query optimization on multiple group bys following a join or cogroup

     [ https://issues.apache.org/jira/browse/PIG-983?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Richard Ding updated PIG-983:
-----------------------------

    Status: Patch Available  (was: Open)

> PERFORMANCE: multi-query optimization on multiple group bys following a join or cogroup
> ---------------------------------------------------------------------------------------
>
>                 Key: PIG-983
>                 URL: https://issues.apache.org/jira/browse/PIG-983
>             Project: Pig
>          Issue Type: Improvement
>          Components: impl
>            Reporter: Richard Ding
>            Assignee: Richard Ding
>         Attachments: PIG-983.patch
>
>
> The current multi-query optimizer works well with pig scripts like this one:
> {code}
> data = LOAD 'input' AS (a:chararray, b:int, c:int);
> A = GROUP data BY b;
> B = GROUP data BY c;
> C = FOREACH A GENERATE group, COUNT(data);
> D = FOREACH B GENERATE group, SUM(data.b);
> STORE C INTO 'output1';
> STORE D INTO 'output2';
> {code}
> In this case the original three Map-Reduce jobs are merged into one MR job by the optimizer.
> The current optimizer, however, won't reduce the number of MR jobs for the scripts in which multiple group bys follow a join or a cogroup, such as this one:
> {code}
> data1 = LOAD 'input1' AS (a1:chararray, b1:int, c1:int);
> data2 = LOAD 'input2' AS (a2:chararray, b2:int, c2:int);
> A = JOIN data1 BY a1, data2 BY a2;
> B = GROUP A BY data1::b1;
> C = GROUP B BY data2::c2;
> D = FOREACH B GENERATE group, COUNT(A);
> E = FOREACH C GENERATE group, SUM(A.data2::b2);
> STORE D INTO 'output1';
> STORE E INTO 'output2';                        
> {code}
> Three MR jobs are still needed to run this script.
> Multi-query optimizer should work with this kind of scripts by merging the group bys and reducing the overall MR jobs. 

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