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https://issues.apache.org/jira/browse/HDFS-10175?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15217401#comment-15217401
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Jitendra Nath Pandey commented on HDFS-10175:
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Each entry in the map should be around 24 bytes (8 bytes for key enum pointer,
8 bytes for value object pointer and 8 bytes for the long counter). The EnumMap
uses arrays unlike a hashmap, and enum keys would be singleton. Therefore
overheads are negligible.
For 48 entries it is 1.1KB per FS, and even for 1000 threads it is only 1.1MB.
Triple that and its 3.3 MB. For java processes that create 1000 threads this is
trivial amount of memory.
> add per-operation stats to FileSystem.Statistics
> ------------------------------------------------
>
> Key: HDFS-10175
> URL: https://issues.apache.org/jira/browse/HDFS-10175
> Project: Hadoop HDFS
> Issue Type: Improvement
> Components: hdfs-client
> Reporter: Ram Venkatesh
> Assignee: Mingliang Liu
> Attachments: HDFS-10175.000.patch, HDFS-10175.001.patch,
> HDFS-10175.002.patch, HDFS-10175.003.patch
>
>
> Currently FileSystem.Statistics exposes the following statistics:
> BytesRead
> BytesWritten
> ReadOps
> LargeReadOps
> WriteOps
> These are in-turn exposed as job counters by MapReduce and other frameworks.
> There is logic within DfsClient to map operations to these counters that can
> be confusing, for instance, mkdirs counts as a writeOp.
> Proposed enhancement:
> Add a statistic for each DfsClient operation including create, append,
> createSymlink, delete, exists, mkdirs, rename and expose them as new
> properties on the Statistics object. The operation-specific counters can be
> used for analyzing the load imposed by a particular job on HDFS.
> For example, we can use them to identify jobs that end up creating a large
> number of files.
> Once this information is available in the Statistics object, the app
> frameworks like MapReduce can expose them as additional counters to be
> aggregated and recorded as part of job summary.
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