Book Image

Mastering Redis

By : Jeremy Nelson
Book Image

Mastering Redis

By: Jeremy Nelson

Overview of this book

Redis is the most popular, open-source, key value data structure server that provides a wide range of capabilities on which multiple platforms can be be built. Its fast and flexible data structures give your existing applications an edge in the development environment. This book is a practical guide which aims to help you deep dive into the world of Redis data structure to exploit its excellent features. We start our journey by understanding the need of Redis in brief, followed by an explanation of Advanced key management. Next, you will learn about design patterns, best practices for using Redis in DevOps environment and Docker containerization paradigm in detail. After this, you will understand the concept of scaling with Redis cluster and Redis Sentinel , followed by a through explanation of incorporating Redis with NoSQL technologies such as Elasticsearch and MongoDB. At the end of this section, you will be able to develop competent applications using these technologies. You will then explore the message queuing and task management features of Redis and will be able to implement them in your applications. Finally, you will learn how Redis can be used to build real-time data analytic dashboards, for different disparate data streams.
Table of Contents (18 chapters)
Mastering Redis
About the Author
About the Reviewers

Chapter 6. Scaling with Redis Cluster and Sentinel

This chapter first explores a crucial strategy of scaling large datasets with Redis by partitioning, or splitting up, the data across multiple Redis instances. By looking at various algorithms that different groups and projects have taken in sharding data, including one of the most successful efforts to do this with Redis, Twitter's Twemproxy project. This provides the background and history behind one of the biggest changes to Redis in the past few years; the inclusion of Redis cluster into the stable branch of Redis in version 3. We'll move from the Twemproxy approach to sharding Redis instances, to the strategy ultimately adopted and implemented in the Redis cluster. We will then experiment with using a Redis cluster with a couple of large datasets and see how client application code should be modified to be able to use the Redis cluster.

Regardless of the partitioning strategy taken to use Redis with large data, managing and supporting...