HADOOP ESSENTIALS A QUANTITATIVE APPROACH PDF

Liu Paperback : : Books Step-by-step procedures are also given on how to set up a four-node Linux cluster at minimum so hadoop essentials a quantitative approach you can run your MapReduce programs not only in local mode on your Mac OS X machine but also in fully distributed mode on a real cluster. In fact, all MapReduce programs presented in the book have been tested and verified in local mode and on such a Linux cluster. Rather than filled with disjointed, piecemeal code snippets to show Hadoop MapReduce programming features one at a time, it is designed to place your total Hadoop MapReduce programming Specifically, this text covers the following subjects: A Quantitative Approach Henry H. The book can also be used as a supplementary hadoop essentials a quantitative approach for a distributed computing or Hadoop course offered to upper-division college CS students. Prior to becoming a software engineer, he had a physicist career and published over 30 research hadoop essentials a quantitative approach in physics while working in the national labs of China, France, Germany, and the United States.

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Liu Paperback : : Books Step-by-step procedures are also given on how to set up a four-node Linux cluster at minimum so hadoop essentials a quantitative approach you can run your MapReduce programs not only in local mode on your Mac OS X machine but also in fully distributed mode on a real cluster.

In fact, all MapReduce programs presented in the book have been tested and verified in local mode and on such a Linux cluster. Rather than filled with disjointed, piecemeal code snippets to show Hadoop MapReduce programming features one at a time, it is designed to place your total Hadoop MapReduce programming Specifically, this text covers the following subjects: A Quantitative Approach Henry H.

The book can also be used as a supplementary hadoop essentials a quantitative approach for a distributed computing or Hadoop course offered to upper-division college CS students. Prior to becoming a software engineer, he had a physicist career and published over 30 research hadoop essentials a quantitative approach in physics while working in the national labs of China, France, Germany, and the United States.

Rather than filled with disjointed, piecemeal code snippets to show Hadoop MapReduce programming features hadoop essentials a quantitative approach at a time, it is designed to place your approavh Hadoop MapReduce programming learning process in a common application context of mining customer spending patterns ensconced in large volumes of credit card transaction record data.

Createspace Independent PubOct 31, — Computers — pages. This textbook adopts a unique approach quantitagive helping developers and CS students learn Hadoop MapReduce programming fast. Rather than heavily relying on essentiaals, verbose and sometimes even hadoop essentials a quantitative approach textual descriptions with sparse code snippets, this textbook uses Hadoop Java APIs, Hadoop configuration parameters, complete MapReduce programs and their execution logs and outputs to demonstrate how Hadoop MapReduce framework works and how to write MapReduce programs.

My library Help Advanced Book Search. His honors include being the author of another book titled Java Performance and Scalability: Related Articles

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HADOOP ESSENTIALS A QUANTITATIVE APPROACH DOWNLOAD

Dimensions: 9. Update May 1, : It has been verified that the MapReduce samples presented in the book work with the latest Hadoop stable release of 1. This book teaches Hadoop MapReduce programming. Written in a unique quantitative approach, this book helps you learn all about Hadoop MapReduce programming within a matter of several weeks if you are a Java developer or within a semester in a classroom environment for upper-division CS students. Enhanced with precise procedures and working, non-word-counting MapReduce programs, you will learn not only how to write MapReduce programs but also how they work at the Hadoop API and workflow levels. This is a proven approach to learning Hadoop MapReduce programming most effectively and efficiently. If you are a college professor and interested in an evaluation copy U.

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Hadoop Essentials: A Quantitative Approach

Liu This textbook adopts a unique approach to helping developers and CS students learn Hadoop MapReduce programming fast. Rather than filled with disjointed, piecemeal code snippets to show Hadoop MapReduce programming features one at a time, it is designed to place your total Hadoop MapReduce programming learning process in a common application context of mining customer spending patterns ensconced in large volumes of credit card transaction record data. Step-by-step procedures are also given on how to set up a four-node Linux cluster at minimum so that you can run your MapReduce programs not only in local mode on your Mac OS X machine but also in fully distributed mode on a real cluster. In fact, all MapReduce programs presented in the book have been tested and verified in local mode and on such a Linux cluster. This textbook mainly focuses on teaching Hadoop MapReduce programming in a scientific, objective, quantitative approach. Rather than heavily relying on subjective, verbose and sometimes even pompous textual descriptions with sparse code snippets, this textbook uses Hadoop Java APIs, Hadoop configuration parameters, complete MapReduce programs and their execution logs and outputs to demonstrate how Hadoop MapReduce framework works and how to write MapReduce programs.

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HADOOP ESSENTIALS A QUANTITATIVE APPROACH PDF

Rather than filled with disjointed, piecemeal code snippets to show Hadoop MapReduce programming features one at a time, it is designed to place your total Hadoop MapReduce programming learning process in a common application context of mining customer spending patterns ensconced in large volumes of credit card transaction record data. Step-by-step procedures are also given on how to set up a four-node Linux cluster at minimum so that you can run your MapReduce programs not only in local mode on your Mac OS X machine but also in fully distributed mode on a real cluster. In fact, all MapReduce programs presented in the book have been tested and verified in local mode and on such a Linux cluster. This textbook mainly focuses on teaching Hadoop MapReduce programming in a scientific, objective, quantitative approach. Rather than heavily relying on subjective, verbose and sometimes even pompous textual descriptions with sparse code snippets, this textbook uses Hadoop Java APIs, Hadoop configuration parameters, complete MapReduce programs and their execution logs and outputs to demonstrate how Hadoop MapReduce framework works and how to write MapReduce programs. The book can also be used as a supplementary textbook for a distributed computing or Hadoop course offered to upper-division college CS students.

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Hadoop Essentials : A Quantitative Approach

Vugis These items are shipped from and sold by different sellers. Amazon Advertising Find, attract, and engage customers. Hone your data engineering skills with R and explore fast, streaming, and scalable data analysis with the most cutting-edge technologies in the market. If you are a college professor and interested in an evaluation copy U. See all 6 reviews. It adopts a unique approach to helping developers and CS students learn Hadoop MapReduce programming fast.

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