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

Exploring the HadoopStreaming R package


HadoopStreaming is an R package developed by David S. Rosenberg. We can say this is a simple framework for MapReduce scripting. This also runs without Hadoop for operating data in a streaming fashion. We can consider this R package as a Hadoop MapReduce initiator. For any analyst or developer who is not able to recall the Hadoop streaming command to be passed in the command prompt, this package will be helpful to quickly run the Hadoop MapReduce job.

The three main features of this package are as follows:

  • Chunkwise data reading: The package allows chunkwise data reading and writing for Hadoop streaming. This feature will overcome memory issues.

  • Supports various data formats: The package allows the reading and writing of data in three different data formats.

  • Robust utility for the Hadoop streaming command: The package also allows users to specify the command-line argument for Hadoop streaming.

This package is mainly designed with three functions for reading...