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From Claudio Martella <claudio.marte...@tis.bz.it>
Subject On the relationship between MultithreadedMapper and tasks
Date Sat, 05 Nov 2011 17:47:29 GMT
Hello list,

I have a task where I have compare the entries of a big sequencefile
with the entries of many small sequencefiles.

Basically you could describe it like this:

for entry in bigSequenceFile:
    for file in listOfSmallFiles:
        for entry2 in file:
            compare(entry, entry2)

My approach is to use a map-only job. I put the big file in HDFS in the
directory which will be the inputPath for the job and the small files in
HDFS in another directory.
Then in my mapper I will load all the small files in memory and will
compare them to the records which will be sent to me in map() from the
big file.

Something like this:

map(key, value):
    for list in smallFiles:
        for entry in list:
            compare(value, entry)

As I don't want, on each node, to load the files multiple times wasting
memory, I thought about using a MultithreadedMapper, load the my small
files at setup() (ideally called once at the instantiation of the
object) into a datastructure (i.e. a LinkedList, smallFiles in the
pseudocode) shared between the threads.

So basically each node would create only one task with more threads each
running on one CPU and sharing the in-memory datastructure.

The problem I'm facing is that for each thread the setup() method is
called once (so #threads times in total), which is not what I want as it
will load the smallFiles multiple times on a shared datastructure.

Also I'm afraid I'm not able to control the number of these
MultithreadedMappers ran on each node (I want only one).

Can anybody help me out understanding how I can leverage
MultithreadedMapper to get what I want (there's very little info on the
internet about MultithreadedMapper)?


Claudio Martella
Free Software & Open Technologies

TIS innovation park
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Tel. +39 0471 068 123
Fax  +39 0471 068 129
claudio.martella@tis.bz.it http://www.tis.bz.it

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