Big Data Analytics with R and Hadoop
Vignesh Prajapati
ISBN 10: 178216328X ISBN 13: 9781782163282
Editorial: Packt Publishing, 2013
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Descripción
Descripción:
Big Data Analytics with R and Hadoop | Vignesh Prajapati | Taschenbuch | Englisch | 2013 | Packt Publishing | EAN 9781782163282 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. N° de ref. del artículo 120648219
Sinopsis:
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.
About This Book
- 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
- 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
Acerca del autor: Vignesh Prajapati, from India, is a Big Data enthusiast, a Pingax (www.pingax. com) consultant and a software professional at Enjay. He is an experienced ML Data engineer. He is experienced with Machine learning and Big Data technologies such as R, Hadoop, Mahout, Pig, Hive, and related Hadoop components to analyze datasets to achieve informative insights by data analytics cycles. He pursued B.E from Gujarat Technological University in 2012 and started his career as Data Engineer at Tatvic. His professional experience includes working on the development of various Data analytics algorithms for Google Analytics data source, for providing economic value to the products. To get the ML in action, he implemented several analytical apps in collaboration with Google Analytics and Google Prediction API services. He also contributes to the R community by developing the RGoogleAnalytics' R library as an open source code Google project and writes articles on Data-driven technologies. Vignesh is not limited to a single domain; he has also worked for developing various interactive apps via various Google APIs, such as Google Analytics API, Realtime API, Google Prediction API, Google Chart API, and Translate API with the Java and PHP platforms. He is highly interested in the development of open source technologies. Vignesh has also reviewed the Apache Mahout Cookbook for Packt Publishing. This book provides a fresh, scope-oriented approach to the Mahout world for beginners as well as advanced users. Mahout Cookbook is specially designed to make users aware of the different possible machine learning applications, strategies, and algorithms to produce an intelligent as well as Big Data application.
"Sobre este título" puede pertenecer a otra edición de este libro.
Detalles bibliográficos
Título: Big Data Analytics with R and Hadoop
Editorial: Packt Publishing
Año de publicación: 2013
Encuadernación: Taschenbuch
Condición: Neu
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ISBN 10: 178216328X
ISBN 13: 9781782163282
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Paperback. Condición: New. 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.Key FeaturesWrite Hadoop MapReduce within RLearn data analytics with R and the Hadoop platformHandle HDFS data within RUnderstand Hadoop streaming with REncode and enrich datasets into RBook DescriptionBig 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 learnIntegrate R and Hadoop via RHIPE, RHadoop, and Hadoop streamingDevelop and run a MapReduce application that runs with R and HadoopHandle HDFS data from within R using RHIPE and RHadoopRun Hadoop streaming and MapReduce with RImport and export from various data sources to RWho this book is forThis 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. Nº de ref. del artículo: LU-9781782163282
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Condición: New. Über den AutorrnrnVignesh Prajapati, from India, is a Big Data enthusiast, a Pingax (www.pingax. com) consultant and a software professional at Enjay. He is an experienced ML Data engineer. He is experienced with Machine learning and Big Da. Nº de ref. del artículo: 4276586
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Packt Publishing Limited, GB, 2013
ISBN 10: 178216328X
ISBN 13: 9781782163282
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Paperback. Condición: New. 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.Key FeaturesWrite Hadoop MapReduce within RLearn data analytics with R and the Hadoop platformHandle HDFS data within RUnderstand Hadoop streaming with REncode and enrich datasets into RBook DescriptionBig 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 learnIntegrate R and Hadoop via RHIPE, RHadoop, and Hadoop streamingDevelop and run a MapReduce application that runs with R and HadoopHandle HDFS data from within R using RHIPE and RHadoopRun Hadoop streaming and MapReduce with RImport and export from various data sources to RWho this book is forThis 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. Nº de ref. del artículo: LU-9781782163282
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