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From Srigurunath Chakravarthi <srig...@yahoo-inc.com>
Subject Re: Proper blocksize and io.sort.mb setting when using compressed LZO files
Date Mon, 27 Sep 2010 16:56:47 GMT
 Your math is right - 1400 MB would be a good setting for io.sort.mb.

 fs.inmemorysize.mb - what Hadoop version are you using? I suspect that this may be deprecated.
If it is supported, you can set it to 1400 MB too. I know it is recognized by .21 (and older

 Increasing io.sort.factor to 100 or even 1000 is advisable.

 On the reduce side, to see if you are already hitting this limit, you can observe reduce
task logs. The spill messages will tell you if spills are occurring every 10 files instead
of occurring when the collected map output size reaches fs.inmemorysize.mb.
 On the map size I don't know how io.sort.factor gets used. It probably imposes a limit on
number of spills (and forces additonal merge steps if spills exceed that limit).

 In any case setting it to a higher value such as 100 blindly is ok since it won't degrade

Hope this helps,

----- Original Message -----
From: pig <hadoopnode@gmail.com>
To: common-user@hadoop.apache.org <common-user@hadoop.apache.org>
Sent: Mon Sep 27 07:15:29 2010
Subject: Re: Proper blocksize and io.sort.mb setting when using compressed LZO files

HI Sriguru,

Thank you for the tips.  Just to clarify a few things.

Our machines have 32 GB of RAM.

I'm planning on setting each machine to run 12 mappers and 2 reducers with
the heap size set to 2048MB so total memory usage for the heap at 28GB.

If this is the case should io.sort.mb be set to 70% of 2048MB (so ~1400 MB)?

Also, I did not see a fs.inmemorysize.mb setting in any of the hadoop
configuration files.  Is that the correct setting I should be looking for?
Should this also be set to 70% of the heap size or does it need to share
with the io.sort.mb setting.

I assume if I'm bumping up io.sort.mb that much I also need to increase
io.sort.factor from the default of 10.  Is there a recommended relation
between these two?

Thank you for your help!


On Sun, Sep 26, 2010 at 3:05 AM, Srigurunath Chakravarthi <
sriguru@yahoo-inc.com> wrote:

> Ed,
>  Tuning io.sort.mb will be certainly worthwhile if you have enough RAM to
> allow for a higher Java heap per map task without risking swapping.
>  Similarly, you can decrease spills on the reduce side using
> fs.inmemorysize.mb.
> You can use the following thumb rules for tuning those two:
> - Set these to ~70% of Java heap size. Pick heap sizes to utilize ~80% RAM
> across all processes (maps, reducers, TT, DN, other)
> - Set it small enough to avoid swap activity, but
> - Set it large enough to minimize disk spills.
> - Ensure that io.sort.factor is set large enough to allow full use of
> buffer space.
> - Balance space for output records (default 95%) & record meta-data (5%).
> Use io.sort.spill.percent and io.sort.record.percent
>  Your mileage may vary. We've seen job exec time improvements worth 1-3%
> via spill-avoidance for miscellaneous applications.
>  Your other option of running a map per 32MB or 64MB of input should give
> you better performance if your map task execution time is significant (i.e.,
> much larger than a few seconds) compared to the overhead of launching map
> tasks and reading input.
> Regards,
> Sriguru
> >-----Original Message-----
> >From: pig [mailto:hadoopnode@gmail.com]
> >Sent: Saturday, September 25, 2010 2:36 AM
> >To: common-user@hadoop.apache.org
> >Subject: Proper blocksize and io.sort.mb setting when using compressed
> >LZO files
> >
> >Hello,
> >
> >We just recently switched to using lzo compressed file input for our
> >hadoop
> >cluster using Kevin Weil's lzo library.  The files are pretty uniform
> >in
> >size at around 200MB compressed.  Our block size is 256MB.
> >Decompressed the
> >average LZO input file is around 1.0GB.  I noticed lots of our jobs are
> >now
> >spilling lots of data to disk.  We have almost 3x more spilled records
> >than
> >map input records for example.  I'm guessing this is because each
> >mapper is
> >getting a 200 MB lzo file which decompresses into 1GB of data per
> >mapper.
> >
> >Would you recommend solving this by reducing the block size to 64MB, or
> >even
> >32MB and then using the LZO indexer so that a single 200MB lzo file is
> >actually split among 3 or 4 mappers?  Would it be better to play with
> >the
> >io.sort.mb value?  Or, would it be best to play with both? Right now
> >the
> >io.sort.mb value is the default 200MB. Have other lzo users had to
> >adjust
> >their block size to compensate for the "expansion" of the data after
> >decompression?
> >
> >Thank you for any help!
> >
> >~Ed
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