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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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Replication across data centers

In previous chapters, we have touched on the idea that Cassandra can automatically replicate across multiple data centers. There are other systems that allow for similar replication; however, the ease of configuration and general robustness set Cassandra apart. Let's take a detailed look at how this works.

Setting replication factors

You will recall from Chapter 3, Replication that replication is configured via CQL at the keyspace level. Since we're on the topic of multiple data centers, it's important to understand that you'll always want to use the NetworkTopologyStrategy, since the SimpleStrategy does not allow for setting replication factor for each data center.

Attempting to use SimpleStrategy in a multi-data center environment would result in random replica placement across data centers. Coordination traffic across nodes would incur significant latency, as requests would often require nodes in more than one data center to satisfy the...

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