Authors
Simon Walkowiak

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Zacharias Voulgaris
Dipanjan Sarkar

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Big Data Analytics with R
By :
Big Data Analytics with R
By:
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 nonrelational 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
Free Chapter
The Era of Big Data
Introduction to R Programming Language and Statistical Environment
Unleashing the Power of R from Within
Hadoop and MapReduce Framework for R
R with Relational Database Management Systems (RDBMSs)
R with NonRelational (NoSQL) Databases
Faster than Hadoop  Spark with R
Machine Learning Methods for Big Data in R
The Future of R  Big, Fast, and Smart Data
Customer Reviews