Parallel R

R is a wonderful thing, indeed: in recent years this free, open-source product has become a popular toolkit for statistical analysis and programming. Two of R’s limitations — that it is single-threaded and memory-bound — become especially troublesome in the current era of large-scale data analysis. It’s possible to break past these boundaries by putting R on the parallel path. Parallel R will describe how to give R parallel muscle. Coverage will include stalwarts such as snow and multicore, and also newer techniques such as Hadoop and Amazon’s cloud computing platform.

Table of Contents

Chapter 1. Getting Started
Chapter 2. snow
Chapter 3. multicore
Chapter 4. parallel
Chapter 5. A Primer on MapReduce and Hadoop
Chapter 6. R+Hadoop
Chapter 7. RHIPE
Chapter 8. Segue
Chapter 9. New and Upcoming