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From "Nitay Joffe (JIRA)" <j...@apache.org>
Subject [jira] Commented: (HBASE-1477) Contention on META stalls mapreduce job execution
Date Wed, 03 Jun 2009 07:58:07 GMT

    [ https://issues.apache.org/jira/browse/HBASE-1477?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12715856#action_12715856

Nitay Joffe commented on HBASE-1477:

I like this idea Andrew. We should try that out and see if it can handle the load.

> Contention on META stalls mapreduce job execution
> -------------------------------------------------
>                 Key: HBASE-1477
>                 URL: https://issues.apache.org/jira/browse/HBASE-1477
>             Project: Hadoop HBase
>          Issue Type: Bug
>            Reporter: Andrew Purtell
> From  Jeremy Pinkham up on hbase-users@: 
> bq. A typical mapper in the job takes several minutes, how many minutes depends on whether
I use the the region partitioner and how many I let run concurrently... it's been anywhere
from 2 minutes with no partitioner and small concurrency (5 mappers) to 8 minutes with the
region partitioner and high concurrency (150 mappers).  This seems to directly correlate with
how long it takes to do a simple count of .META. while each job is running (2 seconds to 1
> bq. I was able to get past this issue affecting my data load by reorganizing some of
my workflow and data structures to force the ordering of keys without the region partitioner.
 Those changes appear to have side stepped the problem for me as I can now load from 100+
mappers without seeing the degradation that I was seeing with 40 when using the partitioner
(and getting some sweet numbers in the requests column of the UI).  It's still an interesting
scaling situation with the region partitioner, but I'm good to go without it.
> I have seen this also in the form of freezing of master UI during high load, where the
UI comes back as soon as load is reduced. When I thread dump it looks like all IPC handlers
on the region server hosting .META. are busy. 

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