[jira] Commented: (HADOOP-5830) Reuse output collectors across maps running on the same jvm

["Hong Tang (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/HADOOP-5830?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12709302#action_12709302 ] 

Hong Tang commented on HADOOP-5830:
-----------------------------------

To minimize the impact on the job latency, we may disable this when less than x% map finishes.

> Reuse output collectors across maps running on the same jvm
> -----------------------------------------------------------
>
>                 Key: HADOOP-5830
>                 URL: https://issues.apache.org/jira/browse/HADOOP-5830
>             Project: Hadoop Core
>          Issue Type: Improvement
>          Components: mapred
>            Reporter: Arun C Murthy
>
> We have evidence that cutting the shuffle-crossbar between maps and reduces (m * r) leads to perfomant applications since:
> # It cuts down the number of connections necessary to shuffle and hence reduces load on the serving-side (TaskTracker) and improves latency (terasort, HADOOP-1338, HADOOP-5223)
> # Reduces seeks required for the TaskTracker to serve the map-outputs
> So far we've had to manually tune applications to cut down the shuffle- crossbar by having fatter maps with custom input formats etc. For e.g. we saw a significant improvement while running the petasort when we went from ~800,000 maps to 80,00 maps (1.5G to 15G per map) i.e. from 48+ hours to 16 hours,  
> The downsides are:
> # The burden falls on the application-writer to tune this with custom input-formats etc.
> # The naive method of using a higher min.split.size leads to considerable non-local i/o on the maps.
> Given these, the proposal is to keep the 'output collector' open across jvm reuse for maps, there-by enabling 'combiners' across map-tasks. This would have the happy-effect of fixing both the above. The downsides are that it will add latency to jobs (since map-outputs cannot be shuffled till a few maps on the same jvm are done, then followed by a final sort/merge/combine) and the failure cases get a bit more complicated.
> Thoughts? Lets discuss...

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