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From "Misha Dmitriev (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (HADOOP-14938) Configuration.updatingResource map should be initialized lazily
Date Fri, 13 Oct 2017 00:49:00 GMT

     [ https://issues.apache.org/jira/browse/HADOOP-14938?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Misha Dmitriev updated HADOOP-14938:
------------------------------------
    Attachment: HADOOP-14938.03.patch

> Configuration.updatingResource map should be initialized lazily
> ---------------------------------------------------------------
>
>                 Key: HADOOP-14938
>                 URL: https://issues.apache.org/jira/browse/HADOOP-14938
>             Project: Hadoop Common
>          Issue Type: Improvement
>            Reporter: Misha Dmitriev
>            Assignee: Misha Dmitriev
>         Attachments: HADOOP-14938.01.patch, HADOOP-14938.02.patch, HADOOP-14938.03.patch
>
>
> Using jxray (www.jxray.com), I've analyzed a heap dump of YARN RM running in a big cluster.
The tool uncovered several inefficiencies in the RM memory. It turns out that one of the biggest
sources of memory waste, responsible for almost 1/4 of used memory, is empty ConcurrentHashMap
instances in org.apache.hadoop.conf.Configuration.updatingResource:
> {code}
> 905,551K (24.0%): java.util.concurrent.ConcurrentHashMap: 22118 / 100% of empty 905,551K
(24.0%)
> ↖org.apache.hadoop.conf.Configuration.updatingResource
> ↖{j.u.WeakHashMap}.keys
> ↖Java Static org.apache.hadoop.conf.Configuration.REGISTRY
> {code}
> That is, there are 22118 empty ConcurrentHashMaps here, and they collectively waste ~905MB
of memory. This is caused by eager initialization of these maps. To address this problem,
we should initialize them lazily.



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