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
Credits
About the Authors
Acknowledgments
About the Reviewers
www.PacktPub.com
Preface
5
Clients for Your Favorite Language (Become a Redis Polyglot)
Index

Chapter 3. Time Series (A Collection of Observations)

A time series is an ordered sequence of values (data points) made over a time interval. Time series are used in statistics, social networks, and communications engineering. Actually, they can be adopted in any domain that needs temporal measurements. They can be used to predict future stock market changes, real estate trends, environmental conditions, and more.

Examples of time series are:

  • Usage of specific words or terms in a newspaper over time

  • Minimum wage year-by-year

  • Daily changes in stock prices

  • Product purchases month-by-month

  • Climate changes

Many time series systems face challenges with storage, since a dataset can grow too large very quickly. When storing events every second, at least 86,400 data points are created every day, and storing so many data points over a long period of time is challenging, especially for in-memory data stores, such as Redis.

Another aspect of a time series is that as time goes by, the smallest granularities...