Book Image

Redis Essentials

By : Maxwell Dayvson da Silva
Book Image

Redis Essentials

By: Maxwell Dayvson da Silva

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 (11 chapters)
5
5. Clients for Your Favorite Language (Become a Redis Polyglot)
10
Index

HyperLogLogs

A HyperLogLog is not actually a real data type in Redis. Conceptually, a HyperLogLog is an algorithm that uses randomization in order to provide a very good approximation of the number of unique elements that exist in a Set. It is fascinating because it only runs in O(1), constant time, and uses a very small amount of memory—up to 12 kB of memory per key. Although technically a HyperLogLog is not a real data type, we are going to consider it as one because Redis provides specific commands to manipulate Strings in order to calculate the cardinality of a set using the HyperLogLog algorithm.

The HyperLogLog algorithm is probabilistic, which means that it does not ensure 100 percent accuracy. The Redis implementation of the HyperLogLog has a standard error of 0.81 percent. In theory, there is no practical limit for the cardinality of the sets that can be counted.

The HyperLogLog algorithm was described originally in the paper HyperLogLog: The analysis of a near-optimal cardinality...