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https://issues.apache.org/jira/browse/HIVE-105?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12668118#action_12668118
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Namit Jain commented on HIVE-105:
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This change breaks the current behavior for group-by:
For the second stage, the number of reducers are inferred currently
irrespective of what the user sets the number of reducers to.
However, if the number of reducers are set, it will be carried over to the 2nd
stage also.
Since, number of reducers is a function of data size by default now, we can get
rid of it in explain plan
> 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, HIVE-105.2.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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