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)

Beyond two columns


We've now seen a table with two columns in its primary key: a partition key and a clustering column. As it turns out, neither of these roles is limited to a single column. A table can define one or more partition key columns and zero or more clustering columns.

Multiple clustering columns

Clustering columns are not limited to one field as specified before. Let's take a look at how multiple clustering columns work and facilitate data ordering. To illustrate this, we will recreate our status updates table so that it is clustered by the date and time when the user updated their status:

CREATE TABLE "user_status_updates_by_datetime" ( 
  "username" text, 
  "status_date" date, 
  "status_time" time, 
  "body" text, 
  PRIMARY KEY ("username", "status_date", "status_time") 
);

We have created a new table user_status_updates_by_datetime as shown next:

  • Partition key: username, which is a text field.
  • Clustering columns: status_date and status_time. Rows for a particular username are...