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https://issues.apache.org/jira/browse/HADOOP-18426?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17598744#comment-17598744
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ASF GitHub Bot commented on HADOOP-18426:
-----------------------------------------
zhangshuyan0 commented on PR #4811:
URL: https://github.com/apache/hadoop/pull/4811#issuecomment-1233756587
> @zhangshuyan0 It is great catch for me. Just suggest to add some
description from this PR and annotation for the new unit test. Thanks.
Thanks for your advice. I have added some comments to JIRA and the code to
make it clearer.
> Improve the accuracy of MutableStat mean
> ----------------------------------------
>
> Key: HADOOP-18426
> URL: https://issues.apache.org/jira/browse/HADOOP-18426
> Project: Hadoop Common
> Issue Type: Bug
> Reporter: Shuyan Zhang
> Assignee: Shuyan Zhang
> Priority: Major
> Labels: pull-request-available
>
> The current MutableStat mean calculation method is more prone to loss
> accuracy because the sum of samples is too large.
> Storing large integers in the double type results in a loss of accuracy. For
> example, 9223372036854775707 and 9223372036854775708 are both stored as
> doubles as 9223372036854776000. Therefore, we should try to avoid using the
> cumulative total sum method to calculate the average, but update the average
> every time we sample. All in all, we can process each sample on its own to
> improve mean accuracy.
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