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

Machine learning and Redis

While the hype cycle continues for what is generally called "Big Data", Redis offers numerous ways to actually accomplish some of what the advertising and media is promising to business users and leaders. Besides being a good choice for performing quick-and-dirty loading and manipulation of data, Redis also performs well as a staging platform for data in a transitional mode that is later manipulated towards a final state, depending on the application. Redis use as a datastore in machine learning techniques and approaches helps as an easily malleable store supporting a particular learning algorithm.

This section takes two supervised learning tasks, Näive Bayes and linear regression, to demonstrate different approaches to statistical analysis with Redis as a transitory datastore for intermediate results. For the first example, the dataset is a pre-existing set of 52 MARC21 records for Jane Austen's Pride and Prejudice and Herman Melville's Moby Dick. This dataset...