Big data with Hadoop MapReduce: a classroom approach

By:

Jeyaraj, Rathinaraja

Contributor(s):

Material type: Text

TextPublication details: Apple Academic Press Canda 2021Description: xx, 406 pISBN:

9781774634844

Subject(s):

DDC classification:

005.74 JEY

Summary: 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.

List(s) this item appears in: IT & Decision Sciences | Fiction

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Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Book	Indian Institute of Management LRC General Stacks	IT & Decisions Sciences	005.74 JEY (Browse shelf(Opens below))	1	Checked out	10/03/2024	004366

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.

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.

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