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From "Hadoop QA (JIRA)" <j...@apache.org>
Subject [jira] Commented: (MAPREDUCE-885) More efficient SQL queries for DBInputFormat
Date Wed, 19 Aug 2009 00:49:14 GMT

    [ https://issues.apache.org/jira/browse/MAPREDUCE-885?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12744809#action_12744809
] 

Hadoop QA commented on MAPREDUCE-885:
-------------------------------------

-1 overall.  Here are the results of testing the latest attachment 
  http://issues.apache.org/jira/secure/attachment/12416936/MAPREDUCE-885.patch
  against trunk revision 805324.

    +1 @author.  The patch does not contain any @author tags.

    +1 tests included.  The patch appears to include 4 new or modified tests.

    -1 patch.  The patch command could not apply the patch.

Console output: http://hudson.zones.apache.org/hudson/job/Mapreduce-Patch-vesta.apache.org/490/console

This message is automatically generated.

> More efficient SQL queries for DBInputFormat
> --------------------------------------------
>
>                 Key: MAPREDUCE-885
>                 URL: https://issues.apache.org/jira/browse/MAPREDUCE-885
>             Project: Hadoop Map/Reduce
>          Issue Type: Improvement
>            Reporter: Aaron Kimball
>            Assignee: Aaron Kimball
>         Attachments: MAPREDUCE-885.patch
>
>
> DBInputFormat generates InputSplits by counting the available rows in a table, and selecting
subsections of the table via the "LIMIT" and "OFFSET" SQL keywords. These are only meaningful
in an ordered context, so the query also includes an "ORDER BY" clause on an index column.
The resulting queries are often inefficient and require full table scans. Actually using multiple
mappers with these queries can lead to O(n^2) behavior in the database, where n is the number
of splits. Attempting to use parallelism with these queries is counter-productive.
> A better mechanism is to organize splits based on data values themselves, which can be
performed in the WHERE clause, allowing for index range scans of tables, and can better exploit
parallelism in the database.

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