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 <[EMAIL PROTECTED]> wrote:
> 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.
> André Hacker, TU Berlin
Arun C. Murthy
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