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Hudson commented on HADOOP-14938:
---------------------------------
SUCCESS: Integrated in Jenkins build Hadoop-trunk-Commit #13081 (See [https://builds.apache.org/job/Hadoop-trunk-Commit/13081/])
HADOOP-14938. Configuration.updatingResource map should be initialized (rkanter: rev e163f41850bd09a17d3102a3af0af2e3cd831ab0)
* (edit) hadoop-common-project/hadoop-common/src/main/java/org/apache/hadoop/conf/Configuration.java
> 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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