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https://issues.apache.org/jira/browse/HBASE-745?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12615538#action_12615538
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Billy Pearson commented on HBASE-745:
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I lost my data I was running to test large import so re downloading I will be
able to run my test on the patch in about 24 hours when I get done processing
my dataset again.
Your last post sounds better and more correct if the patch is working correct
we pick up efficiency when we do not have to compact the larger mapfiles with
every compaction.
I would assume this will help with the users that still have 32bit server keep
the region server under the 2gb limit by flushing a little more often if needed
under load.
> scaling of one regionserver, improving memory and cpu usage
> -----------------------------------------------------------
>
> Key: HBASE-745
> URL: https://issues.apache.org/jira/browse/HBASE-745
> Project: Hadoop HBase
> Issue Type: Improvement
> Components: regionserver
> Affects Versions: 0.1.3, 0.2.0
> Environment: hadoop 0.17.1
> Reporter: LN
> Priority: Minor
> Attachments: hbase-745-for-0.2.patch, HBASE-745.compact.patch
>
>
> after weeks testing hbase 0.1.3 and hadoop(0.16.4, 0.17.1), i found there are
> many works to do, before a particular regionserver can handle data about
> 100G, or even more. i'd share my opions here with stack, and other developers.
> first, the easiest way improving scalability of regionserver is upgrading
> hardware, use 64bit os and 8G memory for the regionserver process, and speed
> up disk io.
> besides hardware, following are software bottlenecks i found in regionserver:
> 1. as data increasing, compaction was eating cpu(with io) times, the total
> compaction time is basicly linear relative to whole data size, even worse,
> sometimes square relavtive to that size.
> 2. memory usage are depends on opened mapfiles
> 3. network connection are depends on opened mapfiles, see HADOOP-2341 and
> HBASE-24.
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