[
https://issues.apache.org/jira/browse/MAPREDUCE-2841?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13199498#comment-13199498
]
Binglin Chang commented on MAPREDUCE-2841:
------------------------------------------
@Yongqiang
It seams BlockMapOutputBuffer only support BytesWritable currently? So
Wordcount & Terasort can't run directly . From the test result, Map Avg time
and sort time, I would say sort take about 40-50% time of whole map task,
because sort is CPU intensive, the CPU time should be more, about 50%-60%
maybe.
If my compiler assumption is right, total speedup for Wordcount mapper should
be 10x, sort speedup should be 10x-12x, and the rest(reader, mapper, merge,
spill combined) should be (10-0.5*12)/(1-0.5)=8.
I must say using quicksort to sort small buffers fit into cache then merge them
is a good idea, I should make this optimization too.
NativeTask currently use single thread currently, but I think all partition
based collector, including BlockMapOutputCollector) can take advantage of
parallel sort & spill I mentioned in the design doc, this needs code changes to
other part(TaskTracker,IndexCache maybe), and change map output file to a
directory.
> Task level native optimization
> ------------------------------
>
> Key: MAPREDUCE-2841
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-2841
> Project: Hadoop Map/Reduce
> Issue Type: Improvement
> Components: task
> Environment: x86-64 Linux
> Reporter: Binglin Chang
> Assignee: Binglin Chang
> Attachments: DESIGN.html, MAPREDUCE-2841.v1.patch,
> MAPREDUCE-2841.v2.patch, dualpivot-0.patch, dualpivotv20-0.patch
>
>
> I'm recently working on native optimization for MapTask based on JNI.
> The basic idea is that, add a NativeMapOutputCollector to handle k/v pairs
> emitted by mapper, therefore sort, spill, IFile serialization can all be done
> in native code, preliminary test(on Xeon E5410, jdk6u24) showed promising
> results:
> 1. Sort is about 3x-10x as fast as java(only binary string compare is
> supported)
> 2. IFile serialization speed is about 3x of java, about 500MB/s, if hardware
> CRC32C is used, things can get much faster(1G/s).
> 3. Merge code is not completed yet, so the test use enough io.sort.mb to
> prevent mid-spill
> This leads to a total speed up of 2x~3x for the whole MapTask, if
> IdentityMapper(mapper does nothing) is used.
> There are limitations of course, currently only Text and BytesWritable is
> supported, and I have not think through many things right now, such as how to
> support map side combine. I had some discussion with somebody familiar with
> hive, it seems that these limitations won't be much problem for Hive to
> benefit from those optimizations, at least. Advices or discussions about
> improving compatibility are most welcome:)
> Currently NativeMapOutputCollector has a static method called canEnable(),
> which checks if key/value type, comparator type, combiner are all compatible,
> then MapTask can choose to enable NativeMapOutputCollector.
> This is only a preliminary test, more work need to be done. I expect better
> final results, and I believe similar optimization can be adopt to reduce task
> and shuffle too.
--
This message is automatically generated by JIRA.
If you think it was sent incorrectly, please contact your JIRA administrators:
https://issues.apache.org/jira/secure/ContactAdministrators!default.jspa
For more information on JIRA, see: http://www.atlassian.com/software/jira
