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Cassandra 3.x High Availability

Cassandra 3.x High Availability

By : Strickland
3.8 (6)
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Cassandra 3.x High Availability

Cassandra 3.x High Availability

3.8 (6)
By: Strickland

Overview of this book

Apache Cassandra is a massively scalable, peer-to-peer database designed for 100 percent uptime, with deployments in the tens of thousands of nodes, all supporting petabytes of data. This book offers a practical insight into building highly available, real-world applications using Apache Cassandra. The book starts with the fundamentals, helping you to understand how Apache Cassandra’s architecture allows it to achieve 100 percent uptime when other systems struggle to do so. You’ll get an excellent understanding of data distribution, replication, and Cassandra’s highly tunable consistency model. Then we take an in-depth look at Cassandra's robust support for multiple data centers, and you’ll see how to scale out a cluster. Next, the book explores the domain of application design, with chapters discussing the native driver and data modeling. Lastly, you’ll find out how to steer clear of common anti-patterns and take advantage of Cassandra’s ability to fail gracefully.
Table of Contents (10 chapters)
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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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