Book Image

Mastering Apache Cassandra 3.x - Third Edition

By : Aaron Ploetz, Tejaswi Malepati, Nishant Neeraj
Book Image

Mastering Apache Cassandra 3.x - Third Edition

By: Aaron Ploetz, Tejaswi Malepati, Nishant Neeraj

Overview of this book

With ever-increasing rates of data creation, the demand for storing data fast and reliably becomes a need. Apache Cassandra is the perfect choice for building fault-tolerant and scalable databases. Mastering Apache Cassandra 3.x teaches you how to build and architect your clusters, configure and work with your nodes, and program in a high-throughput environment, helping you understand the power of Cassandra as per the new features. Once you’ve covered a brief recap of the basics, you’ll move on to deploying and monitoring a production setup and optimizing and integrating it with other software. You’ll work with the advanced features of CQL and the new storage engine in order to understand how they function on the server-side. You’ll explore the integration and interaction of Cassandra components, followed by discovering features such as token allocation algorithm, CQL3, vnodes, lightweight transactions, and data modelling in detail. Last but not least you will get to grips with Apache Spark. By the end of this book, you’ll be able to analyse big data, and build and manage high-performance databases for your application.
Table of Contents (12 chapters)

An overview of Cassandra data modeling

Understanding how Apache Cassandra organizes data under the hood is essential to knowing how to use it properly. When examining Cassandra's data organization, it is important to determine which version of Apache Cassandra you are working with. Apache Cassandra 3.0 represents a significant shift in the way data is both stored and accessed, which warrants a discussion on the evolution of CQL.

Before we get started, let's create a keyspace for this chapter's work:

CREATE KEYSPACE packt_ch3 WITH replication =
{'class': 'NetworkTopologyStrategy', 'ClockworkAngels':'1'};

To preface this discussion, let's create an example table. Let's assume that we want to store data about a music playlist, including the band's name, albums, song titles, and some additional data about the songs...