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

A single-node Hadoop in Cloud


Hopefully by now you should have obtained an understanding of what outcomes you can achieve by running MapReduce jobs in Hadoop or by using other Hadoop components. In this chapter, we will put theory into practice.

We will begin by creating a Linux-based virtual machine with a pre-installed Hortonworks distribution of Hadoop through Microsoft Azure. The reason why we opt for a pre-installed, ready-to-use Hadoop is because this book is not about Hadoop per se, and we also want you to start implementing MapReduce jobs in the R language as soon as possible.

Once you have your Hadoop virtual machine configured and prepared for Big Data crunching we will present you with a simple word count example initially carried out in Java. This example will serve as a comparison for a similar job run in R.

Finally, we will perform a word count task in the R language. Before that, however, we will guide you through some additional configuration operations and we will explain how...