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From "Devaraj Das (JIRA)" <j...@apache.org>
Subject [jira] Commented: (HADOOP-3136) Assign multiple tasks per TaskTracker heartbeat
Date Sun, 03 Aug 2008 14:13:44 GMT

    [ https://issues.apache.org/jira/browse/HADOOP-3136?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12619329#action_12619329
] 

Devaraj Das commented on HADOOP-3136:
-------------------------------------

The runnable task queue on each TT sounds good from the point of view of globally optimal
scheduling. The tasktrackers would then require to handle priority/fairness among the multiple
jobs. It appears to me that handling fairness/priority is easier at the JT end.

> Assign multiple tasks per TaskTracker heartbeat
> -----------------------------------------------
>
>                 Key: HADOOP-3136
>                 URL: https://issues.apache.org/jira/browse/HADOOP-3136
>             Project: Hadoop Core
>          Issue Type: Improvement
>          Components: mapred
>            Reporter: Devaraj Das
>            Assignee: Arun C Murthy
>             Fix For: 0.19.0
>
>
> In today's logic of finding a new task, we assign only one task per heartbeat.
> We probably could give the tasktracker multiple tasks subject to the max number of free
slots it has - for maps we could assign it data local tasks. We could probably run some logic
to decide what to give it if we run out of data local tasks (e.g., tasks from overloaded racks,
tasks that have least locality, etc.). In addition to maps, if it has reduce slots free, we
could give it reduce task(s) as well. Again for reduces we could probably run some logic to
give more tasks to nodes that are closer to nodes running most maps (assuming data generated
is proportional to the number of maps). For e.g., if rack1 has 70% of the input splits, and
we know that most maps are data/rack local, we try to schedule ~70% of the reducers there.
> Thoughts?

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