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https://issues.apache.org/jira/browse/HADOOP-8541?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Andrew Wang updated HADOOP-8541:
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Attachment: hadoop-8541-1.patch
First attempt at a patch. I added a new MutableQuantiles class that tracks
hardcoded quantiles, and rolls over at the specified interval.
The test cases are pretty thorough, but I'm going to work on hooking this into
either HDFS or HBase to make sure the API feels right.
> 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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