If you don’t already have experience with Redis, you should at least read chapters 1 and 2 before reading any other chapter (except for appendix A, which includes the basic installation instructions). The first couple chapters will give you an idea of what Redis is, what it does, and why you might want to use it. From there, chapter 3 is an introduction to what each structure can do and the general concepts around them, and chapter 4 is about Redis administration and making choices about data persistence.
If you already have experience with Redis, you can go ahead and skip chapters 1 and 3 — they’re primarily introduction-level topics for people who don’t know what Redis is or what it does. Though chapter 2 is at the same level, it introduces a style used throughout the rest of the book: show a problem, solve the problem, revisit the problem later to improve it, and point out that there are even better solutions if you keep thinking about it.
When we revisit a topic, I mention where we first discussed the topic or problem. Not all of the topics require that you’ve read the earlier section to understand what’s going on, but trust me when I say that you’ll get much more out of the section talking about improving a solution X from a previous section Y if you read and remember the content from Y. This will help you to recognize examples in your own code where you can make similar improvements. But this recognition gets a lot harder if you don’t understand the earlier example.
If while reading a topic you think to yourself, “There’s a (better/faster/simpler) method to solve this problem,” great! Few of the solutions listed in this book are necessarily the “best” solution to a particular problem in Redis (or otherwise). The examples chosen are meant to get you thinking about solving a class of problems, and building solutions to problems in both intuitive and non-intuitive ways.
Remember that if you have difficulty understanding an example or how it works, the source code for each chapter includes a test runner, which offers example uses of almost every function and method defined in that chapter (including solutions to most of the exercises).
This book is divided into three parts. Part 1 introduces the basics of what Redis is and some examples of its use. Part 2 begins with documentation about many of the commands available in Redis, and then grows to encompass Redis administration and ever more expansive application components that Redis can support. Part 3 completes the content with methods to help you scale Redis using memory-saving techniques, horizontal sharding, and Lua scripting.
Chapter 1 is a basic introduction to what Redis is. It introduces the five data structures that are available in Redis, compares Redis to other databases, and implements a simple article aggregation site that allows voting on submitted articles.
Chapter 2 picks up the pace a little bit, where we use Redis to improve application performance and offer some basic web analytics. If you have little-to-no background with Redis, you may want to start with chapter 2 to understand why Redis has become so popular in recent years (simplicity and performance).
Chapter 3 is mostly a command reference with examples of almost all of the commonly used commands, including basic transactions, sorting, and expiring keys.
Chapter 4 combines the concepts of data persistence, performance, failure recovery, and data loss protection. While some sections are primarily geared toward the systems administration side of things, sections 4.4 and 4.5 discuss Redis transactions and pipelined command performance in depth, which is a must-read for beginner and intermediate Redis users, as we revisit the problem introduced in 4.4 later in the book. Chapter 5 is where we discuss Redis as a database for supporting logging, counters, IP-address-to-location lookup, and other service configuration.
In chapter 6, I introduce components that are very useful when dealing with growing applications, including autocomplete, locking, task queues, messaging, and even file distribution.
Through chapter 7, I introduce and deeply examine a class of search-based problems and solutions that can change the way you think about data querying and filtering.
Chapter 8 goes in depth into the construction of a full Twitter-like social network, and includes implementations for the entire back end, including a streaming API.
Chapter 9 discusses the major techniques for reducing memory use when using Redis at scale, including structure sharding and the use of short structures.
Chapter 10 discusses the horizontal sharding and slaving of Redis to offer greater performance and access to more memory when a single Redis server can’t sustain your needs.
Chapter 11 discusses the use of Lua scripting as a server-side method of extending Redis functionality, and in some cases as a way of improving performance.
Appendix A primarily discusses basic installation of Redis, Python, and the Redis client library for Python in Linux, OS X, and Windows.
Appendix B is a reference to various other resources that might be useful when using Redis. It includes documentation references to some Python language constructs that we use, references to other examples of Redis being used, third-party libraries for using Redis for a variety of tasks, and more.
All source code in listings or in text is in a fixed-width font like this to separate it from ordinary text. Code annotations accompany many of the listings, highlighting important concepts. In some cases, numbered bullets link to explanations that follow the listing.
You can download the source code for all listings from the Manning website, www.manning.com/RedisinAction. If you would like to see translations into other programming languages or would like to browse the Python source code online, you can find the source code in the GitHub repository, www.github.com/josiahcarlson/redis-in-action.
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After graduating college, Dr. Josiah Carlson continued his education at UC Irvine, where he studied theoretical computer science. While applying theory in his spare time, he worked on and off as a teaching assistant, taking up occasional contract programming positions. Near the end of his graduate school career, Josiah found academic positions rare, so he started his professional career at Networks in Motion, where he worked on real-time GPS navigation software and a traffic incident notification system.
Since leaving Networks in Motion, Josiah has worked for Google, and then later for Adly, where he first learned about and began using Redis for content-targeting advertising and Twitter analytics platforms. Several months later, Josiah was a regular participant on the Redis mailing list, where he answered hundreds of questions about using and configuring Redis. Shortly after leaving Adly for ChowNow, where Josiah acts as Chief Architect and cofounder, he began working on Redis in Action, which you are now reading.