You are viewing a plain text version of this content. The canonical link for it is here.
Posted to mapreduce-issues@hadoop.apache.org by "Niels Basjes (JIRA)" <ji...@apache.org> on 2014/06/16 15:42:02 UTC

[jira] [Created] (MAPREDUCE-5928) Deadlock allocating containers for mappers and reducers

Niels Basjes created MAPREDUCE-5928:
---------------------------------------

             Summary: Deadlock allocating containers for mappers and reducers
                 Key: MAPREDUCE-5928
                 URL: https://issues.apache.org/jira/browse/MAPREDUCE-5928
             Project: Hadoop Map/Reduce
          Issue Type: Bug
         Environment: Hadoop 2.4.0 (as packaged by HortonWorks in HDP 2.1.2)
            Reporter: Niels Basjes


I have a small cluster consisting of 8 desktop class systems (1 master + 7 workers).
Due to the small memory of these systems I configured yarn as follows:
{quote}
yarn.nodemanager.resource.memory-mb = 2200
yarn.scheduler.minimum-allocation-mb = 250
{quote}
On my client I did
{quote}
mapreduce.map.memory.mb = 512
mapreduce.reduce.memory.mb = 512
{quote}
Now I run a job with 27 mappers and 32 reducers.
After a while I saw this deadlock occur:
-	All nodes had been filled to their maximum capacity with reducers.
-	1 Mapper was waiting for a container slot to start in.

I tried killing reducer attempts but that didn't help (new reducer attempts simply took the existing container).

*Workaround*:
I set this value from my job. The default value is 0.05 (= 5%)
{quote}
mapreduce.job.reduce.slowstart.completedmaps = 0.99f
{quote}




--
This message was sent by Atlassian JIRA
(v6.2#6252)