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https://issues.apache.org/jira/browse/HIVE-105?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12665675#action_12665675
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Ashish Thusoo commented on HIVE-105:
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Many times the hints are at a query block level e.d.
select /*+ hint1. */ .. from (select /*+ hint2. */ ...
if we flatten it all out as parameters, we would then have to have a mechanism
to name query blocks....
that is why for query specific things, people have used hints in the past...
In fact if we can control the plan by hints, we would be easily able to pass
the reducer count along with the hints...
> 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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