Key Features
Book Description
What you will learn
- Benchmark and profile R programs to solve performance bottlenecks
- Understand how CPU, memory, and disk input/output constraints can limit the performance of R programs
- Optimize R code to run faster and use less memory
- Use compiled code in R and other languages such as C to speed up computations
- Harness the power of GPUs for computational speed
- Process data sets that are larger than memory using diskbased memory and chunking
- Tap into the capacity of multiple CPUs using parallel computing
- Leverage the power of advanced database systems and Big Data tools from within R
Who this book is for
This book is for programmers and developers who want to improve the performance of their R programs by making them run faster with large data sets or who are trying to solve a pesky performance problem.
Table of Contents
- Understanding R performance?Why is R sometimes so slow?
- Measuring how well R code performs
- Simple tweaks to make R code run faster
- Using compiled code for greater speed
- Using GPUs to run R even faster
- Simple tweaks to use less RAM
- Processing large data sets with limited RAM
- Multiplying performance with parallel computing
- Off-Loading Data Processing to Database Systems
- R and Big, Fast Data
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