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Big Data Analytics with Hadoop 3

You're reading from   Big Data Analytics with Hadoop 3 Build highly effective analytics solutions to gain valuable insight into your big data

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Product type Paperback
Published in May 2018
Publisher Packt
ISBN-13 9781788628846
Length 482 pages
Edition 1st Edition
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Author (1):
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Sridhar Alla Sridhar Alla
Author Profile Icon Sridhar Alla
Sridhar Alla
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Table of Contents (13) Chapters Close

Preface 1. Introduction to Hadoop FREE CHAPTER 2. Overview of Big Data Analytics 3. Big Data Processing with MapReduce 4. Scientific Computing and Big Data Analysis with Python and Hadoop 5. Statistical Big Data Computing with R and Hadoop 6. Batch Analytics with Apache Spark 7. Real-Time Analytics with Apache Spark 8. Batch Analytics with Apache Flink 9. Stream Processing with Apache Flink 10. Visualizing Big Data 11. Introduction to Cloud Computing 12. Using Amazon Web Services

Introduction to Hadoop

This chapter introduces the reader to the world of Hadoop and the core components of Hadoop, namely the Hadoop Distributed File System (HDFS) and MapReduce. We will start by introducing the changes and new features in the Hadoop 3 release. Particularly, we will talk about the new features of HDFS and Yet Another Resource Negotiator (YARN), and changes to client applications. Furthermore, we will also install a Hadoop cluster locally and demonstrate the new features such as erasure coding (EC) and the timeline service. As as quick note, Chapter 10, Visualizing Big Data shows you how to create a Hadoop cluster in AWS.

In a nutshell, the following topics will be covered throughout this chapter:

  • HDFS
    • High availability
    • Intra-DataNode balancer
    • EC
    • Port mapping
  • MapReduce
    • Task-level optimization
  • YARN
    • Opportunistic containers
    • Timeline service v.2
    • Docker containerization
  • Other changes
  • Installation of Hadoop 3.1
    • HDFS
    • YARN
    • EC
    • Timeline service v.2
You have been reading a chapter from
Big Data Analytics with Hadoop 3
Published in: May 2018
Publisher: Packt
ISBN-13: 9781788628846
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