Book Image

Redis Essentials

Book Image

Redis Essentials

Overview of this book

Redis is the most popular in-memory key-value data store. It's very lightweight and its data types give it an edge over the other competitors. If you need an in-memory database or a high-performance cache system that is simple to use and highly scalable, Redis is what you need. Redis Essentials is a fast-paced guide that teaches the fundamentals on data types, explains how to manage data through commands, and shares experiences from big players in the industry. We start off by explaining the basics of Redis followed by the various data types such as Strings, hashes, lists, and more. Next, Common pitfalls for various scenarios are described, followed by solutions to ensure you do not fall into common traps. After this, major differences between client implementations in PHP, Python, and Ruby are presented. Next, you will learn how to extend Redis with Lua, get to know security techniques such as basic authorization, firewall rules, and SSL encryption, and discover how to use Twemproxy, Redis Sentinel, and Redis Cluster to scale infrastructures horizontally. At the end of this book, you will be able to utilize all the essential features of Redis to optimize your project's performance.
Table of Contents (17 chapters)
Redis Essentials
About the Authors
About the Reviewers
Clients for Your Favorite Language (Become a Redis Polyglot)

Adding uniqueness with Sorted Sets and HyperLogLog

This section presents two different Time Series implementations that support unique insertions (for example, unique visitors or concurrent video plays), which are very similar to the previous solutions.

The first implementation uses Sorted Sets, and it is based on the previous Hash implementation. The second implementation uses HyperLogLog, and it is based on the previous String implementation. Since these new implementations are very similar to previous ones, only the lines highlighted in bold are explained.

Each solution has pros and cons:

  • The Sorted Set solution works well and is 100% accurate

  • The HyperLogLog solution uses less memory than the Sorted Set solution, but it is only 99.19% accurate

The proper solution should be chosen based on how much data needs to be stored and how accurate it needs to be.

Create a file called timeseries-sorted-set.js, copy the content of timeseries-hash.js, and change the following:

function TimeSeries(client...