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https://issues.apache.org/jira/browse/HIVE-105?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12654020#action_12654020
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Namit Jain commented on HIVE-105:
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The intention of capping mapred.reduce.tasks is to not let the user kill
himself by having too many reducers in case of large map
input jobs. There is no need for another parameter, I thought
mapred.reduce.tasks currently controls maximum reducer count for all hadoop
jobs. Most of the users may not change the default size per reducer. This gives
them a control which they are already using to
have a bound.
Explain plan can be enhanced to show input size for root tasks.
Without going into the details, there needs to be query stage specific
variables for number of reducers which overrides everything.
> 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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