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Parallel R (Data Analysis in the Distributed World)
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Product Details
Author:
Q McCallum, Stephen Weston
Format:
Paperback
Pages:
120
Publisher:
O'Reilly Media (November 29, 2011)
Language:
English
ISBN-13:
9781449309923
ISBN-10:
1449309925
Dimensions:
7" x 9.19"
File:
TWO RIVERS-PERSEUS-Metadata_Only_Perseus_Distribution_Customer_Group_Metadata_20251022163324-20251022.xml
Folder:
TWO RIVERS
List Price:
$21.99
As low as:
$18.91
Publisher Identifier:
P-PER
Discount Code:
C
Case Pack:
34
Country of Origin:
United States
Pub Discount:
60
Weight:
7.52oz
Imprint:
O'Reilly Media
Overview
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
