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Learning Hadoop 2

You're reading from   Learning Hadoop 2 Design and implement data processing, lifecycle management, and analytic workflows with the cutting-edge toolbox of Hadoop 2

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Product type Paperback
Published in Feb 2015
Publisher Packt
ISBN-13 9781783285518
Length 382 pages
Edition 1st Edition
Tools
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Toc

Table of Contents (13) Chapters Close

Preface 1. Introduction 2. Storage FREE CHAPTER 3. Processing – MapReduce and Beyond 4. Real-time Computation with Samza 5. Iterative Computation with Spark 6. Data Analysis with Apache Pig 7. Hadoop and SQL 8. Data Lifecycle Management 9. Making Development Easier 10. Running a Hadoop Cluster 11. Where to Go Next Index

Chapter 2. Storage

After the overview of Hadoop in the previous chapter, we will now start looking at its various component parts in more detail. We will start at the conceptual bottom of the stack in this chapter: the means and mechanisms for storing data within Hadoop. In particular, we will discuss the following topics:

  • Describe the architecture of the Hadoop Distributed File System (HDFS)
  • Show what enhancements to HDFS have been made in Hadoop 2
  • Explore how to access HDFS using command-line tools and the Java API
  • Give a brief description of ZooKeeper—another (sort of) filesystem within Hadoop
  • Survey considerations for storing data in Hadoop and the available file formats

In Chapter 3, Processing – MapReduce and Beyond, we will describe how Hadoop provides the framework to allow data to be processed.

You have been reading a chapter from
Learning Hadoop 2
Published in: Feb 2015
Publisher: Packt
ISBN-13: 9781783285518
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