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https://issues.apache.org/jira/browse/HADOOP-1245?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#action_12533873
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Rick Cox commented on HADOOP-1245:
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Thanks. I can certainly modify the patch as Michael suggests, though there is a 
setting for mapred.tasktracker.tasks.maximum in hadoop-default.xml, so it seems 
like a user would really have to go out of her way to not have any setting 
present on the tasktracker.

> value for mapred.tasktracker.tasks.maximum taken from jobtracker, not 
> tasktracker
> ---------------------------------------------------------------------------------
>
>                 Key: HADOOP-1245
>                 URL: https://issues.apache.org/jira/browse/HADOOP-1245
>             Project: Hadoop
>          Issue Type: Bug
>          Components: mapred
>    Affects Versions: 0.12.3
>            Reporter: Michael Bieniosek
>            Assignee: Michael Bieniosek
>         Attachments: tasktracker-max-tasks-1245.patch
>
>
> I want to create a cluster with machines with different numbers of CPUs.  
> Consequently, each machine should have a different value for 
> mapred.tasktracker.tasks.maximum, since my map tasks are CPU bound.
> When a new job starts up, the jobtracker uses its (single) value for 
> mapred.tasktracker.tasks.maximum to assign tasks.  This means that each 
> tasktracker gets the same number of tasks, regardless of how I configured 
> that particular machine.
> The jobtracker should not consult its config for the value of 
> mapred.tasktracker.tasks.maximum.  It should assign tasks (or allow 
> tasktrackers to request tasks) according to each tasktracker's value of 
> mapred.tasktracker.tasks.maximum.
> Originally, I thought the behavior was slightly different, so this issue 
> contained this text:
> After the first task finishes on each tasktracker, the tasktracker will 
> request new tasks from the jobtracker according to the tasktracker's value 
> for mapred.tasktracker.tasks.maximum.  So after the first round of map tasks 
> is done, the cluster reverts to a mode that works well for heterogeneous 
> clusters.

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