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From stack <st...@duboce.net>
Subject Re: master performance
Date Tue, 02 Jun 2009 03:53:17 GMT
And check that you have block caching enabled on your .META. table.  Do
"describe '.META.'" in the shell.  Its on by default but maybe you migrated
from an older version or something else got in the way of its working.


On Mon, Jun 1, 2009 at 8:36 PM, stack <stack@duboce.net> wrote:

> What Ryan said and then can you try same test after a major compaction?
> Does it make a difference?  You can force it in shell by doing "hbase>
> major_compaction '.META.'" IIRC (Type 'tools' in shell to get help
> syntax).   What size are your jobs?  Short-lived?  Seconds or minutes?  Each
> job needs to build up cache or region locations.  To do this, its trip to
> .META.  Longer-lived jobs will save on trips to .META.  Also, take a thread
> dump when its slow ("kill -QUIT PID_OF_MASTER") and send it to us.  Do it a
> few times.  We'll take a look see.
> Should be better in 0.20.0 but maybe a few things we can do meantime.
> St.Ack
> On Mon, Jun 1, 2009 at 5:31 PM, Jeremy Pinkham <jeremy@lotame.com> wrote:
>> sorry for the novel...
>> I've been experiencing some problems with my hbase cluster and hoping
>> someone can point me in the right direction.  I have a 40 node cluster
>> running 0.19.0.  Each node has 4 cores, 8GB (2GB dedicated to the
>> regionserver), and 1TB data disk.  The master is on a dedicated machine
>> separate from the namenode and the jobtracker.  There is a single table with
>> 4 column families and 3700 regions evenly spread across the 40 nodes.  The
>> TTL's match our loading pace well enough that we don't typically see too
>> many splits anymore.
>> In trying to troubleshoot some larger issues with bulk loads on this
>> cluster I have created a test scenario to try and narrow the problem based
>> on various symptoms.  This test is map/reduce job that is using the
>> HRegionPartitioner (as an easy way to generate some traffic to the master
>> for meta data).  I've been running this job with various size inputs to
>> gauge the effect of different numbers of mappers and have found that as the
>> number of concurrent mappers creeps up to what I think are still small
>> numbers (<50 mappers), the performance of the master is dramatically
>> impacted.  I'm judging the performance here simply by checking the response
>> time of the UI on the master, since that has historically been a good
>> indication of when the cluster is getting into trouble during our loads
>> (which I'm sure could mean a lot of things), although i suppose it's
>> possible to two are unrelated.
>> The UI normally takes about 5-7 seconds to refresh master.jsp.  Running a
>> job with 5 mappers doesn't seem to impact it too much, but a job with 38
>> mappers makes the UI completely unresponsive for anywhere from 30 seconds to
>> several minutes during the run.  During this time, there is nothing
>> happening in the logs, scans/gets from within the shell continue to work
>> fine, and ganglia/top show the box to be virtually idle.  All links off of
>> master.jsp work fine, so I presume it's something about the master pulling
>> info from the individual nodes, but those UI's are also perfectly
>> responsive.
>> This same cluster used to run on just 20 nodes without issue, so I'm
>> curious if I've crossed some threshold of horizontal scalability or if there
>> is just a tuning parameter that I'm missing that might take care of this, or
>> if there is something known between 0.19.0 and 0.19.3 that might be a
>> factor.
>> Thanks
>> jeremy
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