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https://issues.apache.org/jira/browse/MAPREDUCE-1859?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12903891#action_12903891
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Johannes Zillmann commented on MAPREDUCE-1859:
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The Capacity scheduler solution does not seem to be flexible engough for cases
where you have different kind of input source and different configurations of
input source and all these kinds and configurations are not known at cluster
startup.
If you have a system where a user can setup an import from a database the
limits they might want to put on that import can be very different cause one
imports something from a mysql-db, one from oracle, one from a clustered db,
one from a db wich is in other use as well, etc....
> maxConcurrentMapTask & maxConcurrentReduceTask per job
> ------------------------------------------------------
>
> Key: MAPREDUCE-1859
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-1859
> Project: Hadoop Map/Reduce
> Issue Type: New Feature
> Components: job submission
> Affects Versions: 0.20.2
> Reporter: Johannes Zillmann
>
> It would be valuable if one could specify the max number of map/reduce slots
> which should be used for a given job. An example would be an map-reduce job
> importing from a database where you don't want 50 map tasks querying one db
> at a time but also you don't want to shrink the overall map task count.
> Also this is probably already possible through Fair/Capacity-Scheduler or an
> own Extension i think it would be a good addition for the default
> TaskScheduler since this seems to be more then a rare used feature.
> This would have the benefit in situations where you don't have
> control/ownership over the cluster as well.
> And its more job-centric whereas the existing scheduler extensions seems to
> be more job-type-centric.
> Implementing this feature should be relatively straightforward. Adding
> something like jobConf.setMaxConcurrentMapTask(int) and respecting this
> configuration in JobQueueTaskScheduler.
> Not sure if this feature would be harmonical with the existing
> Fair/Capacity-Schedulers.
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