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Cassandra 3.x High Availability

You're reading from   Cassandra 3.x High Availability Achieve scalability and high availability without compromising on performance

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Product type Paperback
Published in Aug 2016
Publisher
ISBN-13 9781786462107
Length 196 pages
Edition 2nd Edition
Languages
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Author (1):
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Robbie Strickland Robbie Strickland
Author Profile Icon Robbie Strickland
Robbie Strickland
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Table of Contents (10) Chapters Close

Preface 1. Cassandras Approach to High Availability 2. Data Distribution FREE CHAPTER 3. Replication 4. Data Centers 5. Scaling Out 6. High Availability Features in the Native Java Client 7. Modeling for Availability 8. Anti-Patterns 9. Failing Gracefully

Balancing the replication factor with consistency

There are many considerations when choosing a replication factor, including availability, performance, and consistency. Since our topic is high availability, let's presume your desire is to maintain data availability in the case of node failure.

It's important to understand exactly what your failure tolerance is, and this will likely be different depending on the nature of the data. The definition of failure is probably going to vary among use cases as well, as one case might consider data loss a failure, whereas another accepts data loss as long as all queries return.

Achieving the desired availability, consistency, and performance targets requires coordinating your replication factor with your application's consistency level configurations. In order to assist you in your efforts to achieve this balance, let's consider a single data center cluster of 10 nodes and examine the impact of various configuration combinations...

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