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

Understanding data analytics problems


In this section, we have included three practical data analytics problems with various stages of data-driven activity with R and Hadoop technologies. These data analytics problem definitions are designed such that readers can understand how Big Data analytics can be done with the analytical power of functions, packages of R, and the computational powers of Hadoop.

The data analytics problem definitions are as follows:

  • Exploring the categorization of web pages

  • Computing the frequency of changes in the stock market

  • Predicting the sale price of a blue book for bulldozers (case study)

Exploring web pages categorization

This data analytics problem is designed to identify the category of a web page of a website, which may categorized popularity wise as high, medium, or low (regular), based on the visit count of the pages. While designing the data requirement stage of the data analytics life cycle, we will see how to collect these types of data from Google Analytics...