Itís tough to argue with R as a high-quality, cross-platform, open source statistical software productóunless youíre in the business of crunching Big Data. This concise book introduces you to several strategies for using R to analyze large datasets. Youíll 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 donít.
With these packages, you can overcome Rís single-threaded nature by spreading work across multiple CPUs, or offloading work to multiple machines to address Rís 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 Hadoopís power with Rís language and interactive shell
- Segue: lets you use Elastic MapReduce as a backend for lapply-style operations
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Page Count (est.): 126
Pub Date: 11/2/2011