Details
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Improvement
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Status: Closed
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Minor
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Resolution: Fixed
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3.0.0-alpha1
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None
Description
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.
Attachments
Attachments
Issue Links
- is depended upon by
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HBASE-14098 Allow dropping caches behind compactions
- Closed
- is duplicated by
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HDFS-4184 Add the ability for Client to provide more hint information for DataNode to manage the OS buffer cache more accurate
- Resolved
- is related to
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HDFS-4966 implement advisory caching for RawLocalFilesystem
- Open
- relates to
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HBASE-10052 use HDFS advisory caching to avoid caching HFiles that are not going to be read again (because they are being compacted)
- Closed