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Modern Big Data Processing with Hadoop

You're reading from   Modern Big Data Processing with Hadoop Expert techniques for architecting end-to-end big data solutions to get valuable insights

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Product type Paperback
Published in Mar 2018
Publisher Packt
ISBN-13 9781787122765
Length 394 pages
Edition 1st Edition
Languages
Concepts
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Authors (3):
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Manoj R Patil Manoj R Patil
Author Profile Icon Manoj R Patil
Manoj R Patil
Prashant Shindgikar Prashant Shindgikar
Author Profile Icon Prashant Shindgikar
Prashant Shindgikar
V Naresh Kumar V Naresh Kumar
Author Profile Icon V Naresh Kumar
V Naresh Kumar
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Toc

Table of Contents (12) Chapters Close

Preface 1. Enterprise Data Architecture Principles 2. Hadoop Life Cycle Management FREE CHAPTER 3. Hadoop Design Consideration 4. Data Movement Techniques 5. Data Modeling in Hadoop 6. Designing Real-Time Streaming Data Pipelines 7. Large-Scale Data Processing Frameworks 8. Building Enterprise Search Platform 9. Designing Data Visualization Solutions 10. Developing Applications Using the Cloud 11. Production Hadoop Cluster Deployment

Setting up a Hadoop cluster with Ambari

In this section, we will learn how to set up a brand new Hadoop cluster from scratch using Ambari. In order to do this, we are going to need four servers – one server for running the Ambari server and three other nodes for running the Hadoop components.

Server configurations

The following table displays the configurations of the servers we are using as part of this exercise:

Server Type

Name

CPU

RAM

DISK

Ambari Server node

master

1

3.7 GB

100 GB

Hadoop node 1

node-1

2

13 GB

250 GB

Hadoop node 2

node-2

2

13 GB

250 GB

Hadoop node 3

node-3

2

13 GB

250 GB

Since this is a sample setup, we are good with this configuration...

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