Librería Portfolio

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.



BASICS OF R

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

R SERVER

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 BIG DATA

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

RHadoop

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()

Appendices

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