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Learning Real-time Analytics with Storm and Cassandra

You're reading from   Learning Real-time Analytics with Storm and Cassandra Solve real-time analytics problems effectively using Storm and Cassandra

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Product type Paperback
Published in Mar 2015
Publisher
ISBN-13 9781784395490
Length 220 pages
Edition 1st Edition
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Author (1):
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Shilpi Saxena Shilpi Saxena
Author Profile Icon Shilpi Saxena
Shilpi Saxena
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Table of Contents (14) Chapters Close

Preface 1. Let's Understand Storm FREE CHAPTER 2. Getting Started with Your First Topology 3. Understanding Storm Internals by Examples 4. Storm in a Clustered Mode 5. Storm High Availability and Failover 6. Adding NoSQL Persistence to Storm 7. Cassandra Partitioning, High Availability, and Consistency 8. Cassandra Management and Maintenance 9. Storm Management and Maintenance 10. Advance Concepts in Storm 11. Distributed Cache and CEP with Storm A. Quiz Answers Index

The Storm cluster setup

Depicted in the following figure is the Storm and Zookeeper reference cluster that we set up in Chapter 2, Getting Started with Your First Topology.

We have three-node Zookeeper clusters for a three-node Storm cluster (which has one Nimbus and two supervisors).

We are using the recommended three-node Zookeeper clusters to avoid a single point of failure in the Storm set up.

The Zookeeper cluster should have an odd number of nodes. The reason for this requirement is that the Zookeeper election logic requires the leader to have an odd number of votes, and that combination is possible only when odd nodes are in the quorum, as shown in the following figure:

The Storm cluster setup
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