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https://issues.apache.org/jira/browse/HBASE-745?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12616962#action_12616962
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stack commented on HBASE-745:
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Hey Billy: Yeah, it was committed a while back. In my comments above, I'm
not very enthusiastic because I did not see BIG gains in our simple
PerformanceEvaluation. But thinking on it more, Luo Ning's simple rule is
kinda elegant and in real-life situations is probably saving truckloads of CPU
and I/O.
> 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: Luo Ning
> 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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