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 Excel


Excel is a spreadsheet application developed by Microsoft to be run on Windows and Mac OS, which has a similar function to R for performing statistical computation, graphical visualization, and data modeling. Excel is provided by Microsoft with the Microsoft Office bundle, which mainly supports .xls spreadsheet data file format. In case, we want to read or write to Microsoft Excel spreadsheets from within R, we can use many available R packages. But one of the popular and working R library is xlsx.

This package programmatically provides control of the Excel files using R. The high level API of this allows users to read a spread sheet of the .xlsx document into a data.frame and writing data.frame to a file. This package is basically developed by Adrian A. Dragulescu.

Installing Excel

Here, we are considering the .xls file as the data source, which can be built and maintained with the help of Microsoft Excel 97/2000/XP/2003.

The following are the prerequisites for the xlsx...