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? thanks! Arun On Oct 3, 2013, at 9:57 AM, André Hacker <[email protected]> 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. http://hortonworks.com/ -- CONFIDENTIALITY NOTICE NOTICE: This message is intended for the use of the individual or entity to which it is addressed and may contain information that is confidential, privileged and exempt from disclosure under applicable law. If the reader of this message is not the intended recipient, you are hereby notified that any printing, copying, dissemination, distribution, disclosure or forwarding of this communication is strictly prohibited. If you have received this communication in error, please contact the sender immediately and delete it from your system. Thank You.
