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https://issues.apache.org/jira/browse/HADOOP-3136?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12631663#action_12631663
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Matei Zaharia commented on HADOOP-3136:
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At the very least, it would help to schedule at least one reduce and one map
per heartbeat, because those are pretty independent. This seemed to make a
difference in my tests using Gridmix at Facebook because Gridmix would some
periods of time when it wouldn't launch reduces at all. Beyond that, for maps,
maybe it would also help to limit the number you launch per heartbeat (say to
2), or to ask the job for tasks until it stops giving you local tasks? The
current patch seems to go all out asking for tasks from the top job in the
queue.
> 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, 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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