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Big Data Analytics with R and Hadoop: Setup an integrated infrastructure of R and Hadoop to turn your data analytics into Big data Analytics/ Vignesh Prajapati

By: Material type: TextTextPublication details: Shroff Publishers & Distr, 2014.Description: vi,219 pISBN:
  • 9789351104100
Subject(s): DDC classification:
  • 519.502855133  PRA-B
Summary: If you're an R developer looking to harness the power of big data analytics with Hadoop, then this book tells you everything you need to integrate the two. You'll end up capable of building a data analytics engine with huge potential. Overview Write Hadoop MapReduce within R Learn data analytics with R and the Hadoop platform Handle HDFS data within R Understand Hadoop streaming with R Encode and enrich datasets into R In Detail 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. 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. 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. What you will learn from this book Integrate R and Hadoop via RHIPE, RHadoop, and Hadoop streaming Develop and run a MapReduce application that runs with R and Hadoop Handle HDFS data from within R using RHIPE and RHadoop Run Hadoop streaming and MapReduce with R Import and export from various data sources to R Approach Big Data Analytics with R and Hadoop is a tutorial style book that focuses on all the powerful big data tasks that can be achieved by integrating R and Hadoop. Who this book is written for This book is ideal for R developers who are looking for a way to perform big data analytics with Hadoop. This book is also aimed at those who know Hadoop and want to build some intelligent applications over Big data with R packages. It would be helpful if readers have basic knowledge of R.
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Item type Current library Home library Collection Call number Status Date due Barcode
Book Book Dept. of Computational Biology and Bioinformatics Processing Center Dept. of Computational Biology and Bioinformatics 519.502855133 PRA-B (Browse shelf(Opens below)) Available DCB2730
Book Book Dept. of Futures Studies Processing Center Dept. of Futures Studies Wind Forecasting 006.312 PRA (Browse shelf(Opens below)) Available DFSWF5

If you're an R developer looking to harness the power of big data analytics with Hadoop, then this book tells you everything you need to integrate the two. You'll end up capable of building a data analytics engine with huge potential. Overview Write Hadoop MapReduce within R Learn data analytics with R and the Hadoop platform Handle HDFS data within R Understand Hadoop streaming with R Encode and enrich datasets into R In Detail 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. 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. 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. What you will learn from this book Integrate R and Hadoop via RHIPE, RHadoop, and Hadoop streaming Develop and run a MapReduce application that runs with R and Hadoop Handle HDFS data from within R using RHIPE and RHadoop Run Hadoop streaming and MapReduce with R Import and export from various data sources to R Approach Big Data Analytics with R and Hadoop is a tutorial style book that focuses on all the powerful big data tasks that can be achieved by integrating R and Hadoop. Who this book is written for This book is ideal for R developers who are looking for a way to perform big data analytics with Hadoop. This book is also aimed at those who know Hadoop and want to build some intelligent applications over Big data with R packages. It would be helpful if readers have basic knowledge of R.

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