Book Image

Big Data Analytics with R

By : Simon Walkowiak
Book Image

Big Data Analytics with R

By: Simon Walkowiak

Overview of this book

Big Data analytics is the process of examining large and complex data sets that often exceed the computational capabilities. R is a leading programming language of data science, consisting of powerful functions to tackle all problems related to Big Data processing. The book will begin with a brief introduction to the Big Data world and its current industry standards. With introduction to the R language and presenting its development, structure, applications in real world, and its shortcomings. Book will progress towards revision of major R functions for data management and transformations. Readers will be introduce to Cloud based Big Data solutions (e.g. Amazon EC2 instances and Amazon RDS, Microsoft Azure and its HDInsight clusters) and also provide guidance on R connectivity with relational and non-relational databases such as MongoDB and HBase etc. It will further expand to include Big Data tools such as Apache Hadoop ecosystem, HDFS and MapReduce frameworks. Also other R compatible tools such as Apache Spark, its machine learning library Spark MLlib, as well as H2O.
Table of Contents (16 chapters)
Big Data Analytics with R
Credits
About the Author
Acknowledgement
About the Reviewers
www.PacktPub.com
Preface

Revisiting R basics


In the following section we will present a short revision of the most useful and frequently applied R functions and statements. We will start from a quick R and RStudio installation guide and then proceed to creating R data structures, data manipulation, and transformation techniques, and basic methods used in Exploratory Data Analysis (EDA). Although the R codes listed in this book have been tested extensively, as always in such cases, please make sure that your equipment is not faulty and note that you will be running all the following scripts at your own risk.

Getting R and RStudio ready

Depending on your operating system (whether Mac OS X, Windows, or Linux) you can download and install specific base R files directly from https://cran.r-project.org/ . If you prefer to use RStudio IDE you still need to install the R core available from CRAN website first and then download and run installers of the most recent version of RStudio IDE specific for your platform from https...