Big data with Hadoop MapReduce : a classroom approach

Author(s)

    • Jeyaraj, Rathinaraja
    • Pugalendhi, Ganeshkumar
    • Paul, Anand

Bibliographic Information

Big data with Hadoop MapReduce : a classroom approach

Rathinaraja Jeyaraj, Ganeshkumar Pugalendhi, Anand Paul

Apple Academic Press, c2021

  • : hardcover

Available at  / 1 libraries

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Note

Includes bibliographical references and index

Description and Table of Contents

Description

The authors provide an understanding of big data and MapReduce by clearly presenting the basic terminologies and concepts. They have employed over 100 illustrations and many worked-out examples to convey the concepts and methods used in big data, the inner workings of MapReduce, and single node/multi-node installation on physical/virtual machines. This book covers almost all the necessary information on Hadoop MapReduce for most online certification exams. Upon completing this book, readers will find it easy to understand other big data processing tools such as Spark, Storm, etc. Ultimately, readers will be able to: * understand what big data is and the factors that are involved * understand the inner workings of MapReduce, which is essential for certification exams * learn the features and weaknesses of MapReduce * set up Hadoop clusters with 100s of physical/virtual machines * create a virtual machine in AWS * write MapReduce with Eclipse in a simple way * understand other big data processing tools and their applications

Table of Contents

Preface. 1. Introduction to Big Data. 2. Hadoop Framework. 3. Hadoop 1.2.1 Installation. 4. Hadoop Ecosystem. 5. Hadoop 2.7.0. 6. Hadoop. 2.7.0 Installation. 7. Data Science. 8. MapReduce Exercise. 9. Case Study: Application Development for NYSE Dataset.

by "Nielsen BookData"

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