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https://issues.apache.org/jira/browse/HBASE-745?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12615532#action_12615532
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stack commented on HBASE-745:
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Hmm. Took another look. Comparison is a little more complicated than I above
suppose. I did a recheck of the number of data files post completion of the
without patch run, about ten minutes after it ended; about the same amount of
time that had elapsed when I went to check the withpatch test. The number of
data files is rising as is the aggregate of all time spent compacting. Would
seem then that the patch cuts time spent compacting by some 10-20% or so in the
test I just ran.
> 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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