Details

    • Type: New Feature
    • Status: Closed
    • Priority: Major
    • Resolution: Fixed
    • Affects Version/s: 0.20.203.0, 0.23.0
    • Fix Version/s: 0.23.1
    • Component/s: distcp, mrv2
    • Labels:
      None
    • Hadoop Flags:
      Reviewed
    • Release Note:
      DistCpV2 added to hadoop-tools.
    • Tags:
      distcp distcpv2 DynamicInputFormat

      Description

      This is a slightly modified version of the DistCp rewrite that Yahoo uses in production today. The rewrite was ground-up, with specific focus on:
      1. improved startup time (postponing as much work as possible to the MR job)
      2. support for multiple copy-strategies
      3. new features (e.g. -atomic, -async, -bandwidth.)
      4. improved programmatic use
      Some effort has gone into refactoring what used to be achieved by a single large (1.7 KLOC) source file, into a design that (hopefully) reads better too.

      The proposed DistCpV2 preserves command-line-compatibility with the old version, and should be a drop-in replacement.

      New to v2:

      1. Copy-strategies and the DynamicInputFormat:
      A copy-strategy determines the policy by which source-file-paths are distributed between map-tasks. (These boil down to the choice of the input-format.)
      If no strategy is explicitly specified on the command-line, the policy chosen is "uniform size", where v2 behaves identically to old-DistCp. (The number of bytes transferred by each map-task is roughly equal, at a per-file granularity.)
      Alternatively, v2 ships with a "dynamic" copy-strategy (in the DynamicInputFormat). This policy acknowledges that
      (a) dividing files based only on file-size might not be an even distribution (E.g. if some datanodes are slower than others, or if some files are skipped.)
      (b) a "static" association of a source-path to a map increases the likelihood of long-tails during copy.
      The "dynamic" strategy divides the list-of-source-paths into a number (> nMaps) of smaller parts. When each map completes its current list of paths, it picks up a new list to process, if available. So if a map-task is stuck on a slow (and not necessarily large) file, other maps can pick up the slack. The thinner the file-list is sliced, the greater the parallelism (and the lower the chances of long-tails). Within reason, of course: the number of these short-lived list-files is capped at an overridable maximum.
      Internal benchmarks against source/target clusters with some slow(ish) datanodes have indicated significant performance gains when using the dynamic-strategy. Gains are most pronounced when nFiles greatly exceeds nMaps.
      Please note that the DynamicInputFormat might prove useful outside of DistCp. It is hence available as a mapred/lib, unfettered to DistCpV2. Also note that the copy-strategies have no bearing on the CopyMapper.map() implementation.

      2. Improved startup-time and programmatic use:
      When the old-DistCp runs with -update, and creates the list-of-source-paths, it attempts to filter out files that might be skipped (by comparing file-sizes, checksums, etc.) This significantly increases the startup time (or the time spent in serial processing till the MR job is launched), blocking the calling-thread. This becomes pronounced as nFiles increases. (Internal benchmarks have seen situations where more time is spent setting up the job than on the actual transfer.)
      DistCpV2 postpones as much work as possible to the MR job. The file-listing isn't filtered until the map-task runs (at which time, identical files are skipped). DistCpV2 can now be run "asynchronously". The program quits at job-launch, logging the job-id for tracking. Programmatically, the DistCp.execute() returns a Job instance for progress-tracking.

      3. New features:
      (a) -async: As described in #2.
      (b) -atomic: Data is copied to a (user-specifiable) tmp-location, and then moved atomically to destination.
      (c) -bandwidth: Enforces a limit on the bandwidth consumed per map.
      (d) -strategy: As above.

      A more comprehensive description the newer features, how the dynamic-strategy works, etc. is available in src/site/xdoc/, and in the pdf that's generated therefrom, during the build.

      High on the list of things to do is support to parallelize copies on a per-block level. (i.e. Incorporation of HDFS-222.)

      I look forward to comments, suggestions and discussion that will hopefully ensue. I have this running against Hadoop 0.20.203.0. I also have a port to 0.23.0 (complete with unit-tests).

      P.S.
      A tip of the hat to Srikanth (Sundarrajan) and Venkatesh (Seetharamaiah), for ideas, code, reviews and guidance. Although much of the code is mine, the idea to use the DFS to implement "dynamic" input-splits wasn't.

        Attachments

        1. 2765_hadoop-branch-0.23.patch
          397 kB
          Mithun Radhakrishnan
        2. 2765_trunk.patch
          397 kB
          Mithun Radhakrishnan
        3. distcpv2_patch_hadoop-trunk_tucu_reviewed.patch
          397 kB
          Mithun Radhakrishnan
        4. distcpv2_patch_0.23.1-SNAPSHOT_tucu_reviewed.patch
          397 kB
          Mithun Radhakrishnan
        5. distcpv2_hadoop-trunk.patch
          396 kB
          Mithun Radhakrishnan
        6. distcpv2_hadoop-0.23.1.patch
          396 kB
          Mithun Radhakrishnan
        7. distcpv2_hadoop-0.23.1.patch
          396 kB
          Mithun Radhakrishnan
        8. distcpv2_trunk_post_review_1.patch
          403 kB
          Mithun Radhakrishnan
        9. distcpv2_trunk.patch
          402 kB
          Mithun Radhakrishnan
        10. distcpv2.20.203.patch
          419 kB
          Mithun Radhakrishnan

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              • Assignee:
                mithun Mithun Radhakrishnan
                Reporter:
                mithun Mithun Radhakrishnan
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                • Created:
                  Updated:
                  Resolved: