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Mastering Redis

Mastering Redis

By : Vidyasagar N V, Nelson
3.3 (3)
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Mastering Redis

Mastering Redis

3.3 (3)
By: Vidyasagar N V, 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 (13 chapters)
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12
Index

Conventions

In this book, you will find a number of text styles that distinguish between different kinds of information. Here are some examples of these styles and an explanation of their meaning.

Code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles are shown as follows: "First, when you call a timeout with the EXPIRE command on a key, the timeout can only be cleared if you delete the key or replace the key."

A block of code is set as follows:

defcreate_tea(datastore, name, time, size):
  # Increment and save global counter
  tea_counter = datastore.incr("global/teas")
  tea_key = "tea/{}".format(tea_counter)
 datastore.hmset(tea_key,
      {"name": name,
      "brew-time": time,
      "box-size": size})
  return tea_key

Any command-line input or output is written as follows:

127.0.0.1:6379> LATENCY HISTORY command
1) 1) (integer) 1433877379
   2) (integer) 1000
2) 1) (integer) 1433877394
   2) (integer) 250

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