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

Summary


Although the main goal of this chapter was to focus on data processing in Hadoop using the R language, throughout its various parts and sections you've been exposed to numerous different techniques and approaches used in Big Data analytics. We only hope that it wasn't too overwhelming!

We kicked off by introducing you to the diversity of Hadoop ecosystem, its tools and applications available to users, HDFS, and MapReduce frameworks.

We then created a single-node Hadoop cluster in which we carried out a simple word count MapReduce exercise in Java and the R languages, and we also showed you how to manage HDFS from the Linux command line and RStudio Server.

Finally, we achieved something that you probably won't be able to find in many (if any!) R books currently available on the market. We setup and configured a fully operational multi-node Hadoop cluster with R and RStudio Server installed and we crunched some real Big Data around 414,000,000 rows of electricity smart meter readings...