Parallel R: Data Analysis in the Distributed World

Parallel R: Data Analysis in the Distributed World by Q. Ethan McCallum

ISBN10: 1449309925
ISBN13: 978-1449309923
Author: Q. Ethan McCallum
Title: Parallel R: Data Analysis in the Distributed World
Publisher: O'Reilly Media; 1 edition (November 5, 2011)
Language: English
Size ePub: 1359 kb
Size PDF: 1870 kb
Rating: 4.4/5
Votes: 252
Pages:
Subcategory: Computer Science

Parallel R: Data Analysis in the Distributed World by Q. Ethan McCallum



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, including three chapters on using R and Hadoop together. You’ll learn the basics of Snow, Multicore, Parallel, Segue, RHIPE, and Hadoop Streaming, 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 environment
  • Multicore: popular for multiprocessor and multicore computers
  • Parallel: part of the upcoming R 2.14.0 release
  • R+Hadoop: provides low-level access to a popular form of cluster computing
  • RHIPE: uses Hadoop’s power with R’s language and interactive shell
  • Segue: lets you use Elastic MapReduce as a backend for lapply-style operations

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