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https://issues.apache.org/jira/browse/HDFS-14276?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16889636#comment-16889636
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Hadoop QA commented on HDFS-14276:
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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 6s{color}
| {color:red} HDFS-14276 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-14276 |
| Console output |
https://builds.apache.org/job/PreCommit-HDFS-Build/27270/console |
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This message was automatically generated.
> [SBN read] Reduce tailing overhead
> ----------------------------------
>
> Key: HDFS-14276
> URL: https://issues.apache.org/jira/browse/HDFS-14276
> Project: Hadoop HDFS
> Issue Type: Improvement
> Components: ha, namenode
> Affects Versions: 3.3.0
> Environment: Hardware: 4-node cluster, each node has 4 core, Xeon
> 2.5Ghz, 25GB memory.
> Software: CentOS 7.4, CDH 6.0 + Consistent Reads from Standby, Kerberos, SSL,
> RPC encryption + Data Transfer Encryption.
> Reporter: Wei-Chiu Chuang
> Assignee: Wei-Chiu Chuang
> Priority: Major
> Attachments: HDFS-14276.000.patch, Screen Shot 2019-02-12 at 10.51.41
> PM.png, Screen Shot 2019-02-14 at 11.50.37 AM.png
>
>
> When Observer setsĀ {{dfs.ha.tail-edits.period}} = {{0ms}}, it tails edit log
> continuously in order to fetch the latest edits, but there is a lot of
> overhead in doing so.
> Critically, edit log tailer should _not_ update NameDirSize metric every
> time. It has nothing to do with fetching edits, and it involves lots of
> directory space calculation.
> Profiler suggests a non-trivial chunk of time is spent for nothing.
> Other than this, the biggest overhead is in the communication to
> serialize/deserialize messages to/from JNs. I am looking for ways to reduce
> the cost because it's burning 30% of my CPU time even when the cluster is
> idle.
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