Parallel R
Mccallum, Q. Ethan
Sold by HPB-Emerald, Dallas, TX, U.S.A.
AbeBooks Seller since September 15, 2017
Used - Soft cover
Condition: Used - Very good
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Quantity: 1 available
Add to basketSold by HPB-Emerald, Dallas, TX, U.S.A.
AbeBooks Seller since September 15, 2017
Condition: Used - Very good
Quantity: 1 available
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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. 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 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"About this title" may belong to another edition of this title.
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