So far, through our journey across using Cassandra, we have been working with a single instance to create tables and test all the cool features provided by Cassandra. We haven't taken advantage of the distributed nature of Cassandra. With a single-node cluster, most operations don't require any sort of tweaking or performance tuning. Even the configuration operations can be left as default for the most part. But with a multi-node cluster, quite a few changes are required in order to get a balance between throughput and availability as well as getting gossip and other internal Cassandra operations to work properly. In this section, we will set up a 3-node cluster.
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Learning Apache Cassandra
By :
Learning Apache Cassandra
By:
Overview of this book
Cassandra is a distributed database that stands out thanks to its robust feature set and intuitive interface, while providing high availability and scalability of a distributed data store. This book will introduce you to the rich feature set offered by Cassandra, and empower you to create and manage a highly scalable, performant and fault-tolerant database layer.
The book starts by explaining the new features implemented in Cassandra 3.x and get you set up with Cassandra. Then you’ll walk through data modeling in Cassandra and the rich feature set available to design a flexible schema. Next you’ll learn to create tables with composite partition keys, collections and user-defined types and get to know different methods to avoid denormalization of data. You will then proceed to create user-defined functions and aggregates in Cassandra. Then, you will set up a multi node cluster and see how the dynamics of Cassandra change with it. Finally, you will implement some application-level optimizations using a Java client.
By the end of this book, you'll be fully equipped to build powerful, scalable Cassandra database layers for your applications.
Table of Contents (15 chapters)
Preface
Free Chapter
Getting Up and Running with Cassandra
The First Table
Organizing Related Data
Beyond Key-Value Lookup
Establishing Relationships
Denormalizing Data for Maximum Performance
Expanding Your Data Model
Collections, Tuples, and User-Defined Types
Aggregating Time-Series Data
How Cassandra Distributes Data
Cassandra Multi-Node Cluster
Application Development Using the Java Driver
Peeking under the Hood
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