

GraphLab: A New Parallel Framework for Machine Learning - helwr
http://www.graphlab.ml.cmu.edu/

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mark_l_watson
I read through the pagerank example, looks interesting. That said, with such a
rich infrastructure built up around Hadoop (Cascading, Pig, Hive, Elastic
MapReduce deployment, etc.) I am not sure how much sense it makes to consider
another platform for horizontally scaling out calculations over large data
sets.

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akshayubhat
GraphLab is intended for efficiently parallelizing Processing intensive
Machine learning algorithms, this is different from "Bring Computation near
data" philosophy of Hadoop/HDFS/Map-Reduce. Generally most of enterprise
mapreduce application are primarily IO intensive, in that case it is important
to have multiple machines accessing data from multiple disks.

GraphLab would be suitable for machines with multiple processors or the new
cloud on chip machines which have ~40+ Cores.

Most of the Machine Learning algorithms tend to be processing intensive, and
simple abstractions such as Map-Reduce dont help a lot, thus GraphLab has its
own niche to serve.

