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Apache Hadoop 3 Quick Start Guide

You're reading from   Apache Hadoop 3 Quick Start Guide Learn about big data processing and analytics

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Product type Paperback
Published in Oct 2018
Publisher Packt
ISBN-13 9781788999830
Length 220 pages
Edition 1st Edition
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Author (1):
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Hrishikesh Vijay Karambelkar Hrishikesh Vijay Karambelkar
Author Profile Icon Hrishikesh Vijay Karambelkar
Hrishikesh Vijay Karambelkar
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Table of Contents (10) Chapters Close

Preface 1. Hadoop 3.0 - Background and Introduction FREE CHAPTER 2. Planning and Setting Up Hadoop Clusters 3. Deep Dive into the Hadoop Distributed File System 4. Developing MapReduce Applications 5. Building Rich YARN Applications 6. Monitoring and Administration of a Hadoop Cluster 7. Demystifying Hadoop Ecosystem Components 8. Advanced Topics in Apache Hadoop 9. Other Books You May Enjoy

How HDFS works

When we set up a Hadoop cluster, Hadoop creates a virtual layer on top of your local filesystem (such as a Windows- or Linux-based filesystem). As you might have noticed, HDFS does not map to any physical filesystem on operating system, but Hadoop offers abstraction on top of your Local FS to provide a fault-tolerant distributed filesystem service with HDFS. The overall design and access pattern in HDFS is like a Linux-based filesystem. The following diagram shows the high-level architecture of HDFS:

We have covered NameNode, Secondary Name, and DataNode in Chapter 1, Hadoop 3.0 - Background and Introduction Each file sent to HDFS is sliced into a number of blocks that need to be distributed. The NameNode maintains the registry (or name table) of all of the nodes present in the data in the local filesystem path specified with dfs.namenode.name.dir in hdfs-site...

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