Parallel R: Data Analysis in the Distributed World
Parallel R: Data Analysis in the Distributed World
By: Stephen Weston, Q Ethan McCallum | Publisher: Shroff/O'Reilly | Year: 2012
ISBN: 9789350236802
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Description
It’stough to argue with R as a high-quality, cross-platform, open sourcestatistical software product—unless you’re in the business of crunching BigData. This concise book introduces you to several strategies for using R toanalyze large datasets. You’ll learn the basics of Snow, Multicore, Parallel,and some Hadoop-related tools, including how to find them, how to use them,when they work well, and when they don’t.
Withthese packages, you can overcome R’s single-threaded nature by spreading workacross multiple CPUs, or offloading work to multiple machines to address R’smemory barrier.
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Snow: works well in a traditional cluster environment
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Multicore: popular for multiprocessor and multicore computers
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Parallel: part of the upcoming R 2.14.0 release
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R+Hadoop: provides low-level access to a popular form of cluster computing
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RHIPE: uses Hadoop’s power with R’s language and interactive shell
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Segue: lets you use Elastic MapReduce as a backend for lapply-style operations