R High Performance Programming: Overcome performance difficulties in R with a range of exciting techniques and solutions

Aloysius Shao Qin Lim

Tjhi W Chandra

$9.99 ~~$19.99~~

4.4 (14 Ratings)

eBook Jan 2015 176 pages 1st Edition

Aloysius Shao Qin Lim

Tjhi W Chandra

$9.99 ~~$19.99~~

4.4 (14 Ratings)

eBook Jan 2015 176 pages 1st Edition

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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.

Who is this book for?

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

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adnan baloch Mar 09, 2015

This book deserves to be on the shelf of any serious R user. The author explains the details of R's inner workings so the readers get a good idea about its limitations. Benchmarks are the mainstay of any performance enthusiast. The author dedicates an entire chapter to helping readers understand how to measure the performance of their code so they can quickly find out if they are on the right track when tuning their code for speed. Sometimes the best optimizations are simple ones. Such tweaks get their own chapter in the book. As any programmer knows, compiling is the quickest way to make code fly. Excellent coverage of this aspect is provided by the author. With the proliferation of GPU's in every new PC, serious data scientists now have another weapon in their arsenal. The author shows us how to take the GPU out for a ride and unleash its power. Not all tasks are best suited for GPU's so the author explains how to ensure that the right processing unit is used for the right job. Getting the best out of R by making the most of available RAM, supercharging R with parallel computation, using databases to assist in processing tasks and stepping into the world of Big Data are also explored by the author and promise to take the reader's R expertise to a whole new level.

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Arda Apr 13, 2015

This is a great book covering almost all approaches you may want to take when you need to squeeze some more performance out of your existing R code. It covers almost all aspects of optimization, from reducing time complexity of your applications (ie, profiling, identifying bottlenecks, using compiled code for bottlenecks, using GPUs etc) to reducing space complexity (memory optimization, tweaks for working with resource restrained systems) to horizontal scaling. The last step (RHadoop) can be a good stepping stone if all else fails and you need to use a distributed solution.

ruben Apr 11, 2015

Hello very interesting book important topics that programmers do not gave follow in the R programming procedures.I like all the chapters because it explain the basics so we can go on doing and applying the main concepts.In my opinion the kind of topics rarely don't cover in a regular class so for me that I used this informstion it was a nice experience to teach this kind of information very helpful.Thanks.

Massera Riccardo Mar 04, 2015

R High Performance Programming is an excellent book to help R programmers to take advantage of all the features of the language and solve practical performance problems or bottlenecks that they might encounter processing large amounts of data.Every chapter explains a topic with simple but meaningful examples,showing which tools to use and how to pick the right packages from CRAN.The reader is also given the choice to only read certain chapters if he does not want to delve into the more advanced topics.The book starts by introducing the reader to R features, the language internals and its memory model.The authors then explain how to correctly measure code performance and the basic tricks that can be adopted when coding an R program to ensure code runs fast and does not waste computing resources.After this introductory part, the book deals with a set of advanced techniques to get your programs running even faster, like developing code compiled for R, accelerating the computation by taking advantage of the GPU, optimizing the memory footprint and processing large datasets with limited resources.For scenarios where the previous techniques are not sufficient, the last chapters deal with parallelization or R programs, offloading the processing to a database and dealing with Big Data with an example running on AWS.In conclusion, I really enjoyed reading this book because it is written in a very simple and understandable manner also for less experienced programmers and even complex subjects are explained in a simple way.

A. Zubarev Feb 22, 2015

R High Performance Programming is probably a unique book in terms of the material covered, I just have not see yet to date a book that is dedicated to increasing the computational capacity of the R language.And I need to state frankly, since R has left the academic circles a long time ago and now is being used more and more in applications involving the Big Data calibre of projects a developer or an R user needs to understand its limitations and perhaps even be able to shrug off some misconceptions that surface on and off about the R’s Big Data suitability.This book will make you prepared to cope with those who encroach on R’s capability to process petabytes of data. Bedsides, since the authors have a very broad outlook on the technologies and succeeded to cover very difficult topics in simple terms this book actually is of an asset to any software developer, using any language on any platformWhat do you need for this book: preferably a *NIX based 64 bit machine capable enough to run a Virtual Machine with an NVIDIA GPU. An Amazon EWS account. Eclipse R Add on (R Studio was cited as storing object state). A Windows user will be able to learn as much, but some of the libraries covered in the book (just a few) were not ported to Windows at the time of my reading.Aloysius and William cover the code execution benchmarking techniques at the beginning very well and then make you embark on wonderful journey to exploring an array of CRAN packages, third party tools and frameworks, the book includes the use of Hadoop, PostgreSQL, MonetDB (vertical data store), Pivotal SciDB, and more so you will not be limited to a narrow subset of tools to use under your belt, it will be something like dirking from the firehose!I read this book in one breath, it is was just that a fascinating journey. I now think I need to come back, and read several chapters of immense interest to me: code pre-compilation (just so easy to take advantage of), the FF, dplyr and BigMemory package (just take advantage of somebody giving you a hand). I will experiment with at least one database, perhaps MonetDB as being at fingertips reach.If I had a small complaint that would be for the absence of the statistical visualizations code – I just would like to benchmark my own improvements.All in all, it is a fantastic book, thank you Aloysius and William! A very timely release Packt!My verdict, is it a superb reading!

R High Performance Programming: Overcome performance difficulties in R with a range of exciting techniques and solutions

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