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From "Mithun Radhakrishnan (JIRA)" <j...@apache.org>
Subject [jira] [Created] (MAPREDUCE-2765) DistCpV2: Rewrite to improve startup time, support multiple copy-strategies (including the "DynamicInputFormat"), improve copy performance and to improve code readability.
Date Tue, 02 Aug 2011 12:05:27 GMT
DistCpV2: Rewrite to improve startup time, support multiple copy-strategies (including the
"DynamicInputFormat"), improve copy performance and to improve code readability.

                 Key: MAPREDUCE-2765
                 URL: https://issues.apache.org/jira/browse/MAPREDUCE-2765
             Project: Hadoop Map/Reduce
          Issue Type: New Feature
          Components: distcp
    Affects Versions:
            Reporter: Mithun Radhakrishnan

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 
		(i)  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.)
		(ii) 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:
	(i)   -async: As described in #2.
	(ii)  -atomic: Data is copied to a (user-specifiable) tmp-location, and then moved atomically
to destination.
	(iii) -bandwidth: Enforces a limit on the bandwidth consumed per map.
	(iv)  -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.

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

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.

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