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

Coroutines using Redis and Python

At the 2015 Open Repositories conference in Indianapolis, I was approached by Mark Matienzo, Director of Technology at the Digital Public Library of America, to join a team for pitching ideas at a contest sponsored by the conference. Our pitch was for a Linked Data Fragments Server with caching that would enable people and organizations to provide a simple and well-understood service to query and get back RDF triples from a graph database instead of supporting full resource-heavy SPARQL endpoints that even for the largest website is difficult to keep and run for users. Linked Data Fragments, first proposed by Ruben Verborgh at Ghent University in Belgium, constructs a triple pattern fragment made up of a subjects, predicates, and object statements that combine to query a Linked Data store and returns a Linked Data Fragment made up of triples matching the query along with metadata and paging information.

Although our team did not win the pitch contest, with...