Parallel R Q. Ethan McCallum

ISBN: 9781449309923

Published: November 2nd 2011

Paperback

126 pages


Description

Parallel R  by  Q. Ethan McCallum

Parallel R by Q. Ethan McCallum
November 2nd 2011 | Paperback | PDF, EPUB, FB2, DjVu, AUDIO, mp3, RTF | 126 pages | ISBN: 9781449309923 | 8.65 Mb

It’s tough to argue with R as a high-quality, cross-platform, open source statistical software product—unless you’re in the business of crunching Big Data. This concise book introduces you to several strategies for using R to analyze large datasets.MoreIt’s tough to argue with R as a high-quality, cross-platform, open source statistical software product—unless you’re in the business of crunching Big Data.

This concise book introduces you to several strategies for using R to analyze 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.With these packages, you can overcome R’s single-threaded nature by spreading work across multiple CPUs, or offloading work to multiple machines to address R’s memory barrier.Snow: works well in a traditional cluster environmentMulticore: popular for multiprocessor and multicore computersParallel: part of the upcoming R 2.14.0 releaseR+Hadoop: provides low-level access to a popular form of cluster computingRHIPE: uses Hadoop’s power with R’s language and interactive shellSegue: lets you use Elastic MapReduce as a backend for lapply-style operations



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