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https://issues.apache.org/jira/browse/HADOOP-8541?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13410708#comment-13410708
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Hadoop QA commented on HADOOP-8541:
-----------------------------------
-1 overall. Here are the results of testing the latest attachment
http://issues.apache.org/jira/secure/attachment/12535890/hadoop-8541-4.patch
against trunk revision .
+1 @author. The patch does not contain any @author tags.
+1 tests included. The patch appears to include 2 new or modified test
files.
+1 javac. The applied patch does not increase the total number of javac
compiler warnings.
+1 javadoc. The javadoc tool did not generate any warning messages.
+1 eclipse:eclipse. The patch built with eclipse:eclipse.
-1 findbugs. The patch appears to introduce 1 new Findbugs (version 1.3.9)
warnings.
+1 release audit. The applied patch does not increase the total number of
release audit warnings.
-1 core tests. The patch failed these unit tests in
hadoop-common-project/hadoop-common:
org.apache.hadoop.metrics2.util.TestSampleQuantiles
+1 contrib tests. The patch passed contrib unit tests.
Test results:
https://builds.apache.org/job/PreCommit-HADOOP-Build/1183//testReport/
Findbugs warnings:
https://builds.apache.org/job/PreCommit-HADOOP-Build/1183//artifact/trunk/patchprocess/newPatchFindbugsWarningshadoop-common.html
Console output:
https://builds.apache.org/job/PreCommit-HADOOP-Build/1183//console
This message is automatically generated.
> 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
> Attachments: hadoop-8541-1.patch, hadoop-8541-2.patch,
> hadoop-8541-3.patch, hadoop-8541-4.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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