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https://issues.apache.org/jira/browse/HDFS-4817?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13787922#comment-13787922
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Hudson commented on HDFS-4817:
------------------------------

SUCCESS: Integrated in Hadoop-trunk-Commit #4558 (See 
[https://builds.apache.org/job/Hadoop-trunk-Commit/4558/])
HDFS-4817. Moving changelog to Release 2.2.0 section to reflect the backport. 
(acmurthy: 
http://svn.apache.org/viewcvs.cgi/?root=Apache-SVN&view=rev&rev=1529751)
* /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/CHANGES.txt


> make HDFS advisory caching configurable on a per-file basis
> -----------------------------------------------------------
>
>                 Key: HDFS-4817
>                 URL: https://issues.apache.org/jira/browse/HDFS-4817
>             Project: Hadoop HDFS
>          Issue Type: Improvement
>          Components: hdfs-client
>    Affects Versions: 3.0.0
>            Reporter: Colin Patrick McCabe
>            Assignee: Colin Patrick McCabe
>            Priority: Minor
>             Fix For: 2.2.0
>
>         Attachments: HDFS-4817.001.patch, HDFS-4817.002.patch, 
> HDFS-4817.004.patch, HDFS-4817.006.patch, HDFS-4817.007.patch, 
> HDFS-4817.008.patch, HDFS-4817.009.patch, HDFS-4817.010.patch, 
> HDFS-4817-b2.1.001.patch
>
>
> HADOOP-7753 and related JIRAs introduced some performance optimizations for 
> the DataNode.  One of them was readahead.  When readahead is enabled, the 
> DataNode starts reading the next bytes it thinks it will need in the block 
> file, before the client requests them.  This helps hide the latency of 
> rotational media and send larger reads down to the device.  Another 
> optimization was "drop-behind."  Using this optimization, we could remove 
> files from the Linux page cache after they were no longer needed.
> Using {{dfs.datanode.drop.cache.behind.writes}} and 
> {{dfs.datanode.drop.cache.behind.reads}} can improve performance  
> substantially on many MapReduce jobs.  In our internal benchmarks, we have 
> seen speedups of 40% on certain workloads.  The reason is because if we know 
> the block data will not be read again any time soon, keeping it out of memory 
> allows more memory to be used by the other processes on the system.  See 
> HADOOP-7714 for more benchmarks.
> We would like to turn on these configurations on a per-file or per-client 
> basis, rather than on the DataNode as a whole.  This will allow more users to 
> actually make use of them.  It would also be good to add unit tests for the 
> drop-cache code path, to ensure that it is functioning as we expect.



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