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Hudson commented on HDFS-4817: ------------------------------ SUCCESS: Integrated in Hadoop-Yarn-trunk #355 (See [https://builds.apache.org/job/Hadoop-Yarn-trunk/355/]) 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. -- This message was sent by Atlassian JIRA (v6.1#6144)