Book Image

Mastering Apache Cassandra

By : Nishant Neeraj
Book Image

Mastering Apache Cassandra

By: Nishant Neeraj

Overview of this book

<p>Apache Cassandra is the perfect choice for building fault tolerant and scalable databases. Implementing Cassandra will enable you to take advantage of its features which include replication of data across multiple datacenters with lower latency rates. This book details these features that will guide you towards mastering the art of building high performing databases without compromising on performance.</p> <p>Mastering Apache Cassandra aims to give enough knowledge to enable you to program pragmatically and help you understand the limitations of Cassandra. You will also learn how to deploy a production setup and monitor it, understand what happens under the hood, and how to optimize and integrate it with other software.</p> <p>Mastering Apache Cassandra begins with a discussion on understanding Cassandra’s philosophy and design decisions while helping you understand how you can implement it to resolve business issues and run complex applications simultaneously.</p> <p>You will also get to know about how various components of Cassandra work with each other to give a robust distributed system. The different mechanisms that it provides to solve old problems in new ways are not as twisted as they seem; Cassandra is all about simplicity. Learn how to set up a cluster that can face a tornado of data reads and writes without wincing.</p> <p>If you are a beginner, you can use the examples to help you play around with Cassandra and test the water. If you are at an intermediate level, you may prefer to use this guide to help you dive into the architecture. To a DevOp, this book will help you manage and optimize your infrastructure. To a CTO, this book will help you unleash the power of Cassandra and discover the resources that it requires.</p>
Table of Contents (17 chapters)
Mastering Apache Cassandra
Credits
About the Author
Acknowledgments
About the Reviewers
www.PacktPub.com
Preface
Index

Cassandra with Hadoop MapReduce


Cassandra provides built-in support for Hadoop. If you have ever written a MapReduce program, you will find out that writing a MapReduce task with Cassandra is quite similar to how one would write a MapReduce task for the data stored in HDFS. Cassandra supports input to Hadoop with ColumnFamilyInputFormat and output with ColumnFamilyOutputFormat classes, respectively. Apart from these, you will need to put Cassandra-specific settings for Hadoop via ConfigHelper. These three classes are enough to get you started. One other class that might be worth looking at is BulkOutputFormat. All these classes are under the org.apache.cassandra.hadoop.* package.

Note

To be able to compile the MapReduce code that uses Cassandra as a data source or data sink, you must have cassandra-all.jar in your classpath. You will also need to make Hadoop to be able to see jars in the Cassandra library. We will discuss this later in this chapter.

Let's understand the classes that we will...