Book Image

Learning Apache Cassandra - Second Edition

Book Image

Learning Apache Cassandra - Second Edition

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 (14 chapters)

Looking up follow relationships


Now that we've studiously designed our follow tables to efficiently support our application's data access patterns, let's do some data access. To start, we'll want to give alice an interface to manage the list of users she follows; this interface will, of course, need to show her who she currently follows:

  SELECT "followed_username" 
  FROM "user_outbound_follows" 
  WHERE "follower_username" = 'alice';

Here, we ask for all of the outbound follows in the partition of alice: an efficient query since it only looks up a single partition's worth of data. As expected, we see that alice follows bob and carol:

Note that the usernames returned are in alphabetical order: this is not a coincidence. Since followed_username is the clustering column in the user_outbound_follows table, the rows are stored in string order of the followed user's username. While this isn't critical to the functionality of our application, it's a happy bonus feature of the data structure we...