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Date: Wed, 24 Sep 2008 23:43:44 -0700 (PDT)
From: "eric baldeschwieler (JIRA)" <jira@apache.org>
To: core-dev@hadoop.apache.org
Subject: [jira] Commented: (HADOOP-3136) Assign multiple tasks per
 TaskTracker heartbeat
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    [ https://issues.apache.org/jira/browse/HADOOP-3136?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12634388#action_12634388 ] 

eric baldeschwieler commented on HADOOP-3136:
---------------------------------------------

+1 on TESTING the heuristic.  I'm worried about cases where we over schedule the first half of the cluster and leave the other half idle or remote scheduled.


> 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: 0.20.0
>
>         Attachments: HADOOP-3136_0_20080805.patch, HADOOP-3136_1_20080809.patch, HADOOP-3136_2_20080911.patch
>
>
> 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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