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https://issues.apache.org/jira/browse/HADOOP-3136?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12633903#action_12633903
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Arun C Murthy commented on HADOOP-3136:
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Ok, with HADOOP-249 getting in it's imperative for us to consider jvm-reuse in
the scheduling algorithms too - it really behooves us to think much harder
about the _global_ scheduling problem and it probably requires a prototype or
two to really get under the skin of the beast. I'll go ahead and open a new
jira for that.
Meanwhile, given the benefits of assigning multiple tasks, I'd propose we go
ahead and do a quick-fix along the lines suggested by Runping/Eric. It clearly
is a win over what we have currently. Thoughts?
> 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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