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https://issues.apache.org/jira/browse/HADOOP-8541?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13403615#comment-13403615
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Aaron T. Myers commented on HADOOP-8541:
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+1, this would be a great addition to our existing metrics capabilities.
> 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
> Reporter: Andrew Wang
>
> 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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