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From "Andrew Wang (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HBASE-5786) Implement histogram metrics for flush and compaction latencies and sizes.
Date Fri, 22 Jun 2012 18:00:45 GMT

    [ https://issues.apache.org/jira/browse/HBASE-5786?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13399486#comment-13399486

Andrew Wang commented on HBASE-5786:

I don't think you can assume a normal distribution for latency. I think it looks more Zipfian
in practice, or maybe bi-modal because of cache misses. Also, a 5% error on a 95th percentile
is kind of huge; IIUC, that means it's actually reporting between the 90th and 100th percentile.
[1] by the same authors as your link discusses sampling for high-percentiles.

I found [2] which I think is well-suited for our use case, since it can do approximate quantiles
on a sliding time window. Space and time bounds seems to be O(reasonable log factors). Somehow
mashing up [2] to use [1] would be most optimal, but doing just [2] is probably okay too.

[1] http://www.cs.rutgers.edu/~muthu/bquant.pdf
[2] http://infolab.stanford.edu/~manku/papers/04pods-sliding.pdf
> Implement histogram metrics for flush and compaction latencies and sizes.
> -------------------------------------------------------------------------
>                 Key: HBASE-5786
>                 URL: https://issues.apache.org/jira/browse/HBASE-5786
>             Project: HBase
>          Issue Type: New Feature
>          Components: metrics, regionserver
>    Affects Versions: 0.92.2, 0.94.0, 0.96.0
>            Reporter: Jonathan Hsieh
> Average time for region operations doesn't really tell a useful story when that help
diagnose anomalous conditions.
> It would be extremely useful to add histogramming metrics similar to HBASE-5533 for region
operations like flush, compaction and splitting.  The probably should be forward biased at
a much coarser granularity however (maybe decay every day?) 

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