Learning Apache Cassandra - Manage Fault Tolerant and Scalable Real-Time Data

Key Features

• Learn how to install and use Cassandra from the ground up
• Design rich schemas that capture the relationships between different data types using compound primary keys
• Master the advanced features available in Cassandra 2.0 through a step-by-step tutorial that builds a real-world application's database layer.

Book Description

Cassandra is a distributed database that stands out for its robust feature set and intuitive interface, while still providing the high availability and scalability of a distributed store.

Starting from installing Cassandra and creating your first keyspace, to mastering the different table structures Cassandra offers and exploring the latest and most powerful features of the Cassandra Query Language, CQL3, this book explores each topic through the lens of a real-world example application. With plenty of examples, tips, and clear explanations, you'll master compound primary keys, collection columns, lightweight transactions, and many other advanced aspects of Cassandra.

By the end of the book, you'll be fully equipped to build powerful, scalable Cassandra database layers for your applications.

What you will learn

• Install Cassandra and create your first keyspace
• Choose the right table structure for the task at hand in a variety of scenarios
• Use range slice queries for efficient data access
• Effortlessly handle concurrent updates with collection columns
• Ensure data integrity with lightweight transactions and logged batches
• Understand eventual consistency and use the right consistency level for your situation
• Implement best practices for data modeling and access

About the Author

Mat Brown is a professional software engineer in Brooklyn, New York. In his career, he has focused on building consumer-facing web and mobile applications for several companies; he currently works at Genius.

Table of Contents

1. Getting up and Running with Cassandra
2. The First Table
3. Organizing Related Data
4. Beyond Key-value Lookup
5. Establishing Relationships
6. Denormalizing Data for Maximum Performance
7. Expanding Your Data Model
8. Collections, Tuples, and User-defined Types
9. Aggregating Time-series Data
10. How Cassandra Distributes Data