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https://issues.apache.org/jira/browse/HDFS-6914?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15806015#comment-15806015
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Hadoop QA commented on HDFS-6914:
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| (x) *{color:red}-1 overall{color}* |
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|| Vote || Subsystem || Runtime || Comment ||
| {color:blue}0{color} | {color:blue} reexec {color} | {color:blue} 0m
0s{color} | {color:blue} Docker mode activated. {color} |
| {color:red}-1{color} | {color:red} patch {color} | {color:red} 0m 5s{color}
| {color:red} HDFS-6914 does not apply to trunk. Rebase required? Wrong Branch?
See https://wiki.apache.org/hadoop/HowToContribute for help. {color} |
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|| Subsystem || Report/Notes ||
| JIRA Issue | HDFS-6914 |
| JIRA Patch URL |
https://issues.apache.org/jira/secure/attachment/12671201/HDFS-6914.v2.patch |
| Console output |
https://builds.apache.org/job/PreCommit-HDFS-Build/18082/console |
| Powered by | Apache Yetus 0.5.0-SNAPSHOT http://yetus.apache.org |
This message was automatically generated.
> Resolve huge memory consumption Issue with OIV processing PB-based fsimages
> ---------------------------------------------------------------------------
>
> Key: HDFS-6914
> URL: https://issues.apache.org/jira/browse/HDFS-6914
> Project: Hadoop HDFS
> Issue Type: Bug
> Affects Versions: 2.4.1
> Reporter: Hao Chen
> Labels: hdfs
> Attachments: HDFS-6914.patch, HDFS-6914.v2.patch
>
>
> For better managing and supporting a lot of large hadoop clusters in
> production, we internally need to automatically export fsimage to delimited
> text files in LSR style and then analyse with hive or pig or build system
> metrics for real-time analyzing.
> However due to the internal layout changes introduced by the protobuf-based
> fsimage, OIV processing program consumes excessive amount of memory. For
> example, in order to export the fsimage in size of 8GB, it should have taken
> about 85GB memory which is really not reasonable and impacted performance of
> other services badly in the same server.
> To resolve above problem, I submit this patch which will reduce memory
> consumption of OIV LSR processing by 50%.
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