R for Programmers : Mastering the Tools book cover
1st Edition

R for Programmers
Mastering the Tools

ISBN 9781498736817
Published January 27, 2016 by CRC Press
354 Pages 112 B/W Illustrations

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Book Description

Unlike other books about R, written from the perspective of statistics, R for Programmers: Mastering the Tools is written from the perspective of programmers, providing a channel for programmers with expertise in other programming languages to quickly understand R. The contents are divided into four sections: The first section consists of the basics of R, which explains the advantages of using R, the installation of different versions of R, and the 12 frequently used packages of R. This will help you understand the tool packages, time series packages, and performance monitoring packages of R quickly.

The second section discusses the server of R, which examines the communication between R and other programming languages and the application of R as servers. This will help you integrate R with other programming languages and implement the server application of R. The third section discusses databases and big data, which covers the communication between R and various databases, as well as R’s integration with Hadoop. This will help you integrate R with the underlying level of other databases and implement the processing of big data by R, based on Hadoop.

The fourth section comprises the appendices, which introduce the installation of Java, various databases, and Hadoop. Because this is a reference book, there is no special sequence for reading all the chapters. You can choose the chapters in which you have an interest. If you are new to R, and you wish to master R comprehensively, simply follow the chapters in sequence.

Table of Contents


Basic R Packages
R Is the Most Worthwhile Programming Language to Learn
Installation of Different Versions of R
fortunes: Records the Wisdom of R
Using formatR to Format Codes Automatically
Multiuser Online Collaboration of R Development: RStudio Server
Foolproof Programming of R and JSON
High-Quality Graphic Rendering Library of R Cairo
A Peculiar Tool Set: caTools

Basic Packages of Time Series
Basic Time Series Library of R: zoo
Extensible Time Series: xts
Visualization of Time Series: plot.xts

Performance Monitoring Packages of R
Local Cache Tool of R: memoise
Performance Monitoring Tool of R: Rprof
Performance Visualization Tool of R: Lineprof


Cross-Platform Communication of R
Cross-Platform Communication between Rserve and Java
Rsession Makes It Easier for Java to Call R
High-Speed Channel between R and rJava
Cross-Platform Communication between Node.js and R

Server Implementation of R
A Detailed Elaboration of the Server Program of R: Rserve
The Client of Rserve in R: RSclient
An R Program Running on the Web: FastRWeb
Building a WebSocket Server by R


Database and NoSQL
Programming Guidance for the RMySQL Database
Connecting R with NoSQL: MongoDB
Connecting R with NoSQL: Redis
Connecting R with NoSQL: Cassandra
Connecting R with NoSQL: Hive
Extract Reverse Repurchase Information from Historical Data Using RHive

R Has Injected Statistical Elements into Hadoop
Installation and Use of RHadoop
RHadoop Experiment: Count the Times of the Appearance of Certain E-Mail Addresses
Implement the Collaborative Filtering Algorithm by RHadoop Based on MapReduce
Installation and Use of RHBase
Solve the Installation Error of RHadoop PipeMapRed.waitOutputThreads()

Installation of a Java Environment
Installation of MySQL
Installation of Redis
Installation of MongoDB
Installation of Cassandra
Installation of Hadoop
Installation of the Hive Environment
Installation of HBase

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Dan Zhang currently works at Qutke in the field of internet finance, leading a startup business of quantitative investment. As a programmer, he has worked in the area of program development for over ten years. Dan has developed mobile games as well as programming tools, and has worked on large Web application systems, internal CRM of companies, system integration of SOA, and big data tools based on Hadoop. Outsourcing, ecommerce, group purchase, payment, SNS and mobile SNS are all within his working range. He is familiar with four programming languages: R, Java, PHP, and JavaScript, and is knowledgeable of mass data storage, data analysis, and machine learning. His blog (http://blog.fens.me/) has a lot of R language original article.