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
About the Author
About the Reviewers

Learning R

This book assumes that you have been previously exposed to R programming language, and this chapter will serve more as a revision, and an overview, of the most essential operations, rather than a very thorough handbook on R. The goal of this work is to present you with specific R applications related to Big Data and the way you can combine R with your existing Big Data analytics workflows instead of teaching you basics of data processing in R. There is a substantial number of great introductory and beginner-level books on R available at IT specialized bookstores or online, directly from Packt Publishing, and other respected publishers, as well as on the Amazon store. Some recommendations include the following:

  • R in Action: Data Analysis and Graphics with R by Robert Kabacoff (2015), 2nd edition, Manning Publications

  • R Cookbook by Paul Teetor (2011), O'Reilly

  • Discovering Statistics Using R by Andy Field, Jeremy Miles, and Zoe Field (2012), SAGE Publications

  • R for Data Science by...