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https://issues.apache.org/jira/browse/HDFS-13752?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16670976#comment-16670976
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Hadoop QA commented on HDFS-13752:
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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 8s{color}
| {color:red} HDFS-13752 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-13752 |
| Console output |
https://builds.apache.org/job/PreCommit-HDFS-Build/25405/console |
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This message was automatically generated.
> fs.Path stores file path in java.net.URI causes big memory waste
> ----------------------------------------------------------------
>
> Key: HDFS-13752
> URL: https://issues.apache.org/jira/browse/HDFS-13752
> Project: Hadoop HDFS
> Issue Type: Improvement
> Components: fs
> Affects Versions: 2.7.6
> Environment: Hive 2.1.1 and hadoop 2.7.6
> Reporter: Barnabas Maidics
> Priority: Major
> Attachments: HDFS-13752.001.patch, HDFS-13752.002.patch,
> HDFS-13752.003.patch, HDFSbenchmark.pdf, Screen Shot 2018-07-20 at
> 11.12.38.png, heapdump-100000partitions.html, measurement.pdf
>
>
> I was looking at HiveServer2 memory usage, and a big percentage of this was
> because of org.apache.hadoop.fs.Path, where you store file paths in a
> java.net.URI object. The URI implementation stores the same string in 3
> different objects (see the attached image). In Hive when there are many
> partitions this cause a big memory usage. In my particular case 42% of memory
> was used by java.net.URI so it could be reduced to 14%.
> I wonder if the community is open to replace it with a more memory efficient
> implementation and what other things should be considered here? It can be a
> huge memory improvement for Hadoop and for Hive as well.
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