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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

Product type Paperback

Published in Oct 2018

Publisher Packt

ISBN-13 9781788999830

Length 220 pages

Edition 1st Edition

Languages

Java

Tools

Hadoop

Concepts

Big Data

Author (1):

Hrishikesh Vijay Karambelkar

View More author details

Table of Contents (10) Chapters

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

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Summary

In this chapter, we have took a deep dive into HDFS. We tried to figure out how HDFS works and its key features. We looked at different data flow patterns of HDFS, where we can see HDFS in different roles. This was supported with various configuration files of HDFS and key attributes. We also looked at various command-line interface commands for HDFS and the Hadoop shell. Finally, we looked at the data structures that are used by HDFS with some examples.

In the next chapter, we will study the creation of a new MapReduce application with Apache Hadoop MapReduce.

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Authors (1)

Vijay Karambelkar

Vijay Karambelkar

Hrishikesh Vijay Karambelkar is an innovator and an enterprise architect with 16 years of software design and development experience, specifically in the areas of big data, enterprise search, data analytics, text mining, and databases. He is passionate about architecting new software implementations for the next generation of software solutions for various industries, including oil and gas, chemicals, manufacturing, utilities, healthcare, and government infrastructure. In the past, he has authored three books for Packt Publishing: two editions of Scaling Big Data with Hadoop and Solr and one of Scaling Apache Solr. He has also worked with graph databases, and some of his work has been published at international conferences such as VLDB and ICDE.

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