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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 2. Getting Started with Your First Topology FREE CHAPTER 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

Replication in Cassandra and strategies


Replicating means to create a copy. This copy makes the data redundant and thus available even when one node fails or goes down. In Cassandra, you have the option to specify the replication factor as part of the creation of the keyspace or to later modify it. Attributes that need to be specified in this context are as follows:

  • Replication factor: This is a numeric value specifying the number of replicas

  • Strategy: This could be simple strategy or topology strategy; this decides the placement of replicas across the cluster

Internally, Cassandra uses the row key to store replicas or copies of data across various nodes on the cluster. A replication factor of n means there are n copies of data stored on n different nodes. There are certain rules of thumb with replication, and they are as follows:

  • A replication factor should never be more than the number of nodes in a cluster, or you will run into exceptions due to not enough replicas and Cassandra will start...

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