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Apache Hadoop 3 Quick Start Guide
Apache Hadoop 3 Quick Start Guide

Apache Hadoop 3 Quick Start Guide: Learn about big data processing and analytics

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Profile Icon Vijay Karambelkar
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€18.99 per month
Paperback Oct 2018 220 pages 1st Edition
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€13.98 €19.99
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€24.99
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Arrow left icon
Profile Icon Vijay Karambelkar
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€18.99 per month
Paperback Oct 2018 220 pages 1st Edition
eBook
€13.98 €19.99
Paperback
€24.99
Subscription
Free Trial
Renews at €18.99p/m
eBook
€13.98 €19.99
Paperback
€24.99
Subscription
Free Trial
Renews at €18.99p/m

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Apache Hadoop 3 Quick Start Guide

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...

Technical requirements

You will need Eclipse development environment and Java 8 installed on your system where you can run/tweak these examples. If you prefer to use maven, then you will need maven installed to compile the code. To run the example, you also need Apache Hadoop 3.1 setup on Linux system. Finally, to use the Git repository of this book, you need to install Git.

The code files of this chapter can be found on GitHub:
https://github.com/PacktPublishing/Apache-Hadoop-3-Quick-Start-Guide/tree/master/Chapter2

Check out the following video to see the code in action:

http://bit.ly/2Jofk5P

Prerequisites for Hadoop setup

In this section, we will look at the necessary prerequites for setting up Apache Hadoop in cluster or pseudo mode. Often, teams are forced to go through a major reinstallation of Hadoop and the data migration of their clusters due to improper planning for their cluster requirements. Hadoop can be installed on Windows as well as Linux; however, most productions that Hadoop installations run on are Unix or Linux-based platforms.

Preparing hardware for Hadoop

One important aspect of Hadoop setup is defining the hardware requirements and sizing before the start of a project. Although Apache Hadoop can run on commodity hardware, most of the implementations utilize server-class hardware for their Hadoop...

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Key benefits

  • Set up, configure and get started with Hadoop to get useful insights from large data sets
  • Work with the different components of Hadoop such as MapReduce, HDFS and YARN
  • Learn about the new features introduced in Hadoop 3

Description

Apache Hadoop is a widely used distributed data platform. It enables large datasets to be efficiently processed instead of using one large computer to store and process the data. This book will get you started with the Hadoop ecosystem, and introduce you to the main technical topics, including MapReduce, YARN, and HDFS. The book begins with an overview of big data and Apache Hadoop. Then, you will set up a pseudo Hadoop development environment and a multi-node enterprise Hadoop cluster. You will see how the parallel programming paradigm, such as MapReduce, can solve many complex data processing problems. The book also covers the important aspects of the big data software development lifecycle, including quality assurance and control, performance, administration, and monitoring. You will then learn about the Hadoop ecosystem, and tools such as Kafka, Sqoop, Flume, Pig, Hive, and HBase. Finally, you will look at advanced topics, including real time streaming using Apache Storm, and data analytics using Apache Spark. By the end of the book, you will be well versed with different configurations of the Hadoop 3 cluster.

Who is this book for?

Aspiring Big Data professionals who want to learn the essentials of Hadoop 3 will find this book to be useful. Existing Hadoop users who want to get up to speed with the new features introduced in Hadoop 3 will also benefit from this book. Having knowledge of Java programming will be an added advantage.

What you will learn

  • Store and analyze data at scale using HDFS, MapReduce and YARN
  • Install and configure Hadoop 3 in different modes
  • Use Yarn effectively to run different applications on Hadoop based platform
  • Understand and monitor how Hadoop cluster is managed
  • Consume streaming data using Storm, and then analyze it using Spark
  • Explore Apache Hadoop ecosystem components, such as Flume, Sqoop, HBase, Hive, and Kafka

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Oct 31, 2018
Length: 220 pages
Edition : 1st
Language : English
ISBN-13 : 9781788999830
Vendor :
Apache
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Languages :
Concepts :
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Product Details

Publication date : Oct 31, 2018
Length: 220 pages
Edition : 1st
Language : English
ISBN-13 : 9781788999830
Vendor :
Apache
Category :
Languages :
Concepts :
Tools :

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Table of Contents

9 Chapters
Hadoop 3.0 - Background and Introduction Chevron down icon Chevron up icon
Planning and Setting Up Hadoop Clusters Chevron down icon Chevron up icon
Deep Dive into the Hadoop Distributed File System Chevron down icon Chevron up icon
Developing MapReduce Applications Chevron down icon Chevron up icon
Building Rich YARN Applications Chevron down icon Chevron up icon
Monitoring and Administration of a Hadoop Cluster Chevron down icon Chevron up icon
Demystifying Hadoop Ecosystem Components Chevron down icon Chevron up icon
Advanced Topics in Apache Hadoop Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon
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