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https://issues.apache.org/jira/browse/HADOOP-3136?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12622221#action_12622221
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Devaraj Das commented on HADOOP-3136:
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I think that we should give less tasks of a particular type (map/reduce) when
the corresponding load of that type is less. So for e.g., if a TT asks for
task(s) to run, and at this point of time, we have 200 as the
remaining-map-load and 1000 free map slots, we should give out just 1 task to
this TT. The logic in the patch would give out more than that (to be precise,
it would be the number of available slots on that TT), right? Also, should we
consider the "free" slots as opposed to the total number of slots in the
calculation for maxMapLoad (or reduceLoad).
> 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
>
> Attachments: HADOOP-3136_0_20080805.patch,
> HADOOP-3136_1_20080809.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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