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From "Richard Ding (JIRA)" <j...@apache.org>
Subject [jira] Created: (PIG-983) PERFORMANCE: multi-query optimization on multiple group bys following a join or cogroup
Date Wed, 30 Sep 2009 18:23:23 GMT
PERFORMANCE: multi-query optimization on multiple group bys following a join or cogroup
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                 Key: PIG-983
                 URL: https://issues.apache.org/jira/browse/PIG-983
             Project: Pig
          Issue Type: Improvement
          Components: impl
            Reporter: Richard Ding


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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