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From "Aaron T. Myers (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (HADOOP-8541) Better high-percentile latency metrics
Date Tue, 03 Jul 2012 20:50:35 GMT

     [ https://issues.apache.org/jira/browse/HADOOP-8541?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel

Aaron T. Myers updated HADOOP-8541:

    Status: Patch Available  (was: Open)

Marking PA for Andrew so that Jenkins runs.
> Better high-percentile latency metrics
> --------------------------------------
>                 Key: HADOOP-8541
>                 URL: https://issues.apache.org/jira/browse/HADOOP-8541
>             Project: Hadoop Common
>          Issue Type: Improvement
>          Components: metrics
>    Affects Versions: 2.0.0-alpha
>            Reporter: Andrew Wang
>            Assignee: Andrew Wang
>             Fix For: 2.0.1-alpha
>         Attachments: hadoop-8541-1.patch
> Based on discussion in HBASE-6261 and with some HDFS devs, I'd like to make better high-percentile
latency metrics a part of hadoop-common.
> I've already got a working implementation of [1], an efficient algorithm for estimating
quantiles on a stream of values. It allows you to specify arbitrary quantiles to track (e.g.
50th, 75th, 90th, 95th, 99th), along with tight error bounds. This estimator can be snapshotted
and reset periodically to get a feel for how these percentiles are changing over time.
> I propose creating a new MutableQuantiles class that does this. [1] isn't completely
without overhead (~1MB memory for reasonably sized windows), which is why I hesitate to add
it to the existing MutableStat class.
> [1] Cormode, Korn, Muthukrishnan, and Srivastava. "Effective Computation of Biased Quantiles
over Data Streams" in ICDE 2005.

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