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)

Choosing between tuples and user-defined types


As we saw, tuples and user-defined types have a lot in common. In both structures, a column contains a fixed, predefined set of fields, each of which can have its own type. Both structures are stored as frozen, meaning that Cassandra cannot perform discrete operations on their internal components. Both can be indexed and used in the WHERE clause of a query. So how do we decide which to use?

In most cases, a user-defined type is a better option. User-defined types give names to their fields, making it easier for application developers to reason about their usage. Also, user-defined types can be partially selected in queries, tuples cannot.

The only reason to use a tuple is convenience: a tuple does not need to be defined separately from its use in a column definition. So, for quick prototyping of schema structures, a tuple can be a better option. However, for a schema that's going into production, a user-defined type is nearly always going to be...