Book Image

Big Data Analytics with R and Hadoop

By : Vignesh Prajapati
Book Image

Big Data Analytics with R and Hadoop

By: Vignesh Prajapati

Overview of this book

<p>Big data analytics is the process of examining large amounts of data of a variety of types to uncover hidden patterns, unknown correlations, and other useful information. Such information can provide competitive advantages over rival organizations and result in business benefits, such as more effective marketing and increased revenue. New methods of working with big data, such as Hadoop and MapReduce, offer alternatives to traditional data warehousing. <br /><br />Big Data Analytics with R and Hadoop is focused on the techniques of integrating R and Hadoop by various tools such as RHIPE and RHadoop. A powerful data analytics engine can be built, which can process analytics algorithms over a large scale dataset in a scalable manner. This can be implemented through data analytics operations of R, MapReduce, and HDFS of Hadoop.<br /><br />You will start with the installation and configuration of R and Hadoop. Next, you will discover information on various practical data analytics examples with R and Hadoop. Finally, you will learn how to import/export from various data sources to R. Big Data Analytics with R and Hadoop will also give you an easy understanding of the R and Hadoop connectors RHIPE, RHadoop, and Hadoop streaming.</p>
Table of Contents (16 chapters)
Big Data Analytics with R and Hadoop
Credits
About the Author
Acknowledgment
About the Reviewers
www.PacktPub.com
Preface
Index

Chapter 3. Integrating R and Hadoop

From the first two chapters we got basic information on how to install the R and Hadoop tools. Also, we learned what the key features of Hadoop are and why they are integrated with R for Big Data solutions to business data problems. So with the integration of R and Hadoop we can forward data analytics to Big Data analytics. Both of these middleware are still getting improved for being used along with each other.

In Chapter 2, Writing Hadoop MapReduce Programs, we learned how to write a MapReduce program in Hadoop. In this chapter, we will learn to develop the MapReduce programs in R that run over the Hadoop cluster. This chapter will provide development tutorials on R and Hadoop with RHIPE and RHadoop. After installing R and Hadoop, we will see how R and Hadoop can be integrated using easy steps.

Before we start moving on to the installation, let's see what are the advantages of R and Hadoop integration within an organization. Since statisticians and data...