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From "Michael Bieniosek (JIRA)" <j...@apache.org>
Subject [jira] Commented: (HADOOP-1245) value for mapred.tasktracker.tasks.maximum taken from jobtracker, not tasktracker
Date Wed, 10 Oct 2007 21:33:51 GMT

    [ https://issues.apache.org/jira/browse/HADOOP-1245?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#action_12533881
] 

Michael Bieniosek commented on HADOOP-1245:
-------------------------------------------

Rick, I forgot about that.  So my suggestion would be rather useless.

> 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
>             Fix For: 0.16.0
>
>         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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