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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

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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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Planning and Setting Up Hadoop Clusters

In the last chapter, we looked at big data problems, the history of Hadoop, along with an overview of big data, Hadoop architecture, and commercial offerings. This chapter will focus on hands-on, practical knowledge of how to set up Hadoop in different configurations. Apache Hadoop can be set up in the following three different configurations:

Developer mode: Developer mode can be used to run programs in a standalone manner. This arrangement does not require any Hadoop process daemons, and jars can run directly. This mode is useful if developers wish to debug their code on MapReduce.
Pseudo cluster (single node Hadoop): A pseudo cluster is a single node cluster that has similar capabilities to that of a standard cluster; it is also used for the development and testing of programs before they are deployed on a production cluster. Pseudo...

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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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