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)

Write complexity and data integrity


The amount of work we need to do to write data in the fully normalized strategy is basically equal to what we needed to do with a partially normalized layout. Our storage needs to increase by a bit; now we're storing one full copy of each status update for every follower the author has. However, storage is cheap, and writing data in Cassandra is cheap, so we've managed to make our timeline read pattern far more efficient at a low cost.

One concern in any sort of denormalized scenario is data integrity. At the Cassandra level, the only thing stopping us from adding a status update to the user_status_updates table is forgetting to add copies as appropriate to the home_status_updates table, or vice versa. Even worse, if a user deletes a status update and we don't properly remove copies from all the home_status_updates table, the user's followers might see status updates that they aren't supposed to.

For the most part, the responsibility for maintaining data...