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From "Zheng Shao (JIRA)" <j...@apache.org>
Subject [jira] Commented: (HIVE-105) estimate number of required reducers and other map-reduce parameters automatically
Date Fri, 23 Jan 2009 00:01:59 GMT

    [ https://issues.apache.org/jira/browse/HIVE-105?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12666354#action_12666354
] 

Zheng Shao commented on HIVE-105:
---------------------------------

It seems we still need some discussion or commit the infrastructure before Part B can be done.

What about committing Part A by itself and open a new Jira for Part B?

Part A is self-complete in that:
1. If the user set the number of reducers (through mapred.reduce.tasks), Hive will do exactly
it does before.
2. If the user does not, then Hive will automatically figure out the number of reducers for
each phase.

1 also makes sure the user can always make Hive behave like before.


> estimate number of required reducers and other map-reduce parameters automatically
> ----------------------------------------------------------------------------------
>
>                 Key: HIVE-105
>                 URL: https://issues.apache.org/jira/browse/HIVE-105
>             Project: Hadoop Hive
>          Issue Type: Improvement
>          Components: Query Processor
>            Reporter: Joydeep Sen Sarma
>            Assignee: Zheng Shao
>         Attachments: HIVE-105.1.patch
>
>
> currently users have to specify number of reducers. In a multi-user environment - we
generally ask users to be prudent in selecting number of reducers (since they are long running
and block other users). Also - large number of reducers produce large number of output files
- which puts pressure on namenode resources.
> there are other map-reduce parameters - for example the min split size and the proposed
use of combinefileinputformat that are also fairly tricky for the user to determine (since
they depend on map side selectivity and cluster size). This will become totally critical when
there is integration with BI tools since there will be no opportunity to optimize job settings
and there will be a wide variety of jobs.
> This jira calls for automating the selection of such parameters - possibly by a best
effort at estimating map side selectivity/output size using sampling and determining such
parameters from there.

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