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Big data with Hadoop MapReduce: a classroom approach

By: Jeyaraj, RathinarajaContributor(s): Pugalendhi, Ganeshkumar | Paul, AnandMaterial type: TextTextPublication details: Canda Apple Academic Press 2021 Description: xx, 406 pISBN: 9781774634844Subject(s): Big data | Apache Hadoop | MapReduce (Computer file)DDC classification: 005.74 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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Item type Current library Collection Call number Copy number Status Date due Barcode
Book Book Indian Institute of Management LRC
General Stacks
IT & Decisions Sciences 005.74 JEY (Browse shelf(Opens below)) 1 Available 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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