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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 Cassandra stores data


Database systems use a variety of structures to represent data on disk. Most traditional relational systems use a tabular approach, which enables the kinds of random access queries supported by these systems. But in order to achieve Cassandra's hallmark write performance, it must avoid these sorts of random access disk seeks, because random disk I/O tends to be a significant bottleneck. Instead, the system employs a log-structured storage engine, which allows it to write data sequentially to both a commit log and Cassandra's permanent structure, SSTables.

Implications of log-structured storage

When a write is received, it is written simultaneously to the commit log and to an in- memory representation of the table, called a memtable. Note that the commit log is what provides durability of writes in Cassandra. Memtables are then periodically flushed to disk in the form of immutable SSTables.

Data in SSTables is split into partitions (which map to the primary key) and...

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