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From Arun C Murthy <...@hortonworks.com>
Subject Re: Non data-local scheduling
Date Mon, 07 Oct 2013 20:58:47 GMT
It's cluster-wide setting and scheduler-specific.

For CS please set yarn.scheduler.capacity.node-locality-delay to #machines you have in your
rack (typically 20 or 40). 

Looks like the doc in capacity-scheduler.xml is broken, would you mind opening a jira to fix
it and add it to the the http://hadoop.apache.org/docs/current/hadoop-yarn/hadoop-yarn-site/CapacityScheduler.html?


On Oct 3, 2013, at 9:57 AM, André Hacker <andrephacker@gmail.com> wrote:

> Hi,
> I have a 25 node cluster, running hadoop 2.1.0-beta, with capacity scheduler (default
settings for scheduler) and replication factor 3.
> I have exclusive access to the cluster to run a benchmark job and I wonder why there
are so few data-local and so many rack-local maps.
> The input format calculates 44 input splits and 44 map tasks, however, it seems to be
random how many of them are processed data locally. Here the counters of my last tries:
> data-local / rack-local:
> Test 1: data-local:15 rack-local: 29
> Test 2: data-local:18 rack-local: 26
> I don't understand why there is not always 100% data local. This should not be a problem
since the blocks of my input file are distributed over all nodes.
> Maybe someone can give me a hint.
> Thanks,
> André Hacker, TU Berlin

Arun C. Murthy
Hortonworks Inc.

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