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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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How to scale up


Properly scaling up your Cassandra cluster is not a difficult process, but it does require you to carefully follow established procedures to avoid undesirable side effects. There are two general approaches to consider:

  • Upgrade in place: To upgrade in place involves taking each node out of the ring, one at a time, bringing its new replacement online, and allowing the new node to bootstrap. This choice makes the most sense if a subset of your cluster needs upgrading rather than an entire data center. This assumes, of course, that your replication factor is greater than ONE. To upgrade an entire data center, it may be preferable to allow replication to automatically build the new nodes.

  • Using data center replication: Since Cassandra already supports bringing up another data center via replication, you can use this mechanism to populate your new hardware with existing data and then switch to the new data center when replication is complete.

Upgrading in place

If you have determined...

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