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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 Mon, 05 Jan 2009 18:55:44 GMT

    [ https://issues.apache.org/jira/browse/HIVE-105?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12660853#action_12660853
] 

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

It's possible that user just want to set "hive.exec.maxreducers" instead of specifying the
exact number.

These parameters are session-wide. Currently there is no way to control the number of reducers
in the different stages of the same query. So a group-by query which process a lot of raw
data may have very small amount of intermediate data before the final aggregation.

By setting the "hive.exec.maxreducers", the user makes sure his tasks does not occupy the
whole cluster (given that preemption is NOT done yet).


> 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
>
> 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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