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

Chapter 4. Hadoop and MapReduce Framework for R

In this chapter we are entering the diverse world of Big Data tools and applications that can be relatively easily integrated with the R language. In this chapter, we will present you with a set of guidelines and tips on the following topics:

  • Deploying cloud-based virtual machines with Hadoop, the ready-to-use Hadoop Distributed File System (HDFS), and MapReduce frameworks

  • Configuring your instance/virtual machine to include essential libraries and useful supplementary tools for data management in HDFS

  • Managing HDFS using shell/Terminal commands and running a simple MapReduce word count in Java for comparison

  • Integrating R statistical environment with Hadoop on a single-node cluster

  • Managing files in HDFS and run simple MapReduce jobs using the rhadoop bundle of R packages

  • Carrying out more complex MapReduce tasks on large-scale electricity meter readings datasets on a multi-node HDInsight cluster on Microsoft Azure

However, just before we dive into...