Simplifying parallel implementation of algorithms on Hadoop with Pig Latin

Date Issued
2015
Author(s)
Abstract
In this paper we present a general technique for
parallelizing regular algorithms with the tools the Hadoop ecosystem offers: MapReduce, HDFS, HBase and Pig. This framework
can be applied for parallelizing algorithms for feature selection,
clustering, machine learning etc. It consists of several steps: load
the datasets in HDFS, apply some transformations if they are
needed, store the datasets in HBase, and implement the algorithm
in Pig with the help of User Defined Functions.
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Hadoop, MapReduce, HB...

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SimplifyingMapReducedevelopmentonHadoopandHBasewithPigLatin-EftimZdravevski.pdf

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