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https://issues.apache.org/jira/browse/MAPREDUCE-64?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Chris Douglas updated MAPREDUCE-64:
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Attachment: M64-5.patch
Thank you for the detailed comments, Hong.
bq. The logic of calculating the equator seems to be missing a multipication of
METASIZE
bq. In SpillThread: " if (bufend < bufindex && bufindex < bufstart)" should
probably be " if (bufend < bufstart) {"
bq. Buffer.write(byte[], int, int): "blockwrite = distkvi < distkve" should be
"blockwrite = distkvi <= distkve"
Great catches! Fixed.
bq. A potential inefficiency if we encounter a large record when there are few
(but not zero) records in the buffer - this would lead to these few records
written out as a single spill. A better way is to spill out the single large
record, and continue accumulating records after that.
This is an interesting idea. Clever implementations could also avoid skewing
the average record size disproportionately (possibly an independent issue).
Please file a JIRA.
bq. TestMapCollection: uniform random is used [...] Suggest to change to a
distribution that gives more weight to small values
Soright. Modified the random testcase.
bq. Any particular reason to shut down the thread in Buffer.flush() rather than
Buffer.close()?
Only history. The distinction between flush and close is not clear for a
Collector, particularly since one or the other is a noop for map-only/reducer'd
jobs. Pulling the MapOutputBuffer into a standalone class could help to refine
the distinction. Work such as MAPREDUCE-1211 would clearly benefit; IIRC, the
current version of that proposal also pulled out the collector. Filed
MAPREDUCE-1324 to track extracting the buffer from MapTask.
bq. I also have a couple of suggestions on refactoring the code to make it more
readable [...]
These are all good suggestions. I thought of the index-based code as inferring
high-level abstractions from low-level state, but the {{spillExists}},
{{spillInProgress}} flags distill a lot of esoteric, often redundant
calculation into a more understandable format. There's another missing
abstraction for setting/querying metadata, which could replace the inline
kvmeta manipulations. Since the testing/validation of this patch is difficult,
and you've already done the work, I'd like to postpone this to a separate issue
if that's OK.
bq. Other very minor nits [...]
Fixed all these.
Thank you again for so thorough a review.
> Map-side sort is hampered by io.sort.record.percent
> ---------------------------------------------------
>
> Key: MAPREDUCE-64
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-64
> Project: Hadoop Map/Reduce
> Issue Type: Bug
> Reporter: Arun C Murthy
> Assignee: Chris Douglas
> Attachments: M64-0.patch, M64-0i.png, M64-1.patch, M64-1i.png,
> M64-2.patch, M64-2i.png, M64-3.patch, M64-4.patch, M64-5.patch
>
>
> Currently io.sort.record.percent is a fairly obscure, per-job configurable,
> expert-level parameter which controls how much accounting space is available
> for records in the map-side sort buffer (io.sort.mb). Typically values for
> io.sort.mb (100) and io.sort.record.percent (0.05) imply that we can store
> ~350,000 records in the buffer before necessitating a sort/combine/spill.
> However for many applications which deal with small records e.g. the
> world-famous wordcount and it's family this implies we can only use 5-10% of
> io.sort.mb i.e. (5-10M) before we spill inspite of having _much_ more memory
> available in the sort-buffer. The word-count for e.g. results in ~12 spills
> (given hdfs block size of 64M). The presence of a combiner exacerbates the
> problem by piling serialization/deserialization of records too...
> Sure, jobs can configure io.sort.record.percent, but it's tedious and
> obscure; we really can do better by getting the framework to automagically
> pick it by using all available memory (upto io.sort.mb) for either the data
> or accounting.
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