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This article introduces the relevant knowledge of "what problems can be solved by using Redis". In the operation of actual cases, many people will encounter such a dilemma. Then let the editor lead you to learn how to deal with these situations. I hope you can read it carefully and be able to achieve something!

Anyone with experience with memcached may know that users can only use the APPEND command to add data to the end of an existing string. Memcached declares in the documentation that you can use the APPEND command to manage the list of elements. That's good! The user can append the element to the end of a string and use that string as a list. But how do you delete these elements later? Memcached uses a blacklist (blacklist) to hide the elements in the list, thus avoiding reading, updating, and writing to the elements (including memcached writes after a database query). In contrast, Redis's LIST and SET allow users to add or remove elements directly.

Using Redis instead of memcached to solve the problem not only makes the code shorter, easier to understand, and easier to maintain, but also makes the code run faster (because users don't need to update the data by reading the database). In addition, in many other cases, Redis is much more efficient and easy to use than relational databases.

A common use of a database is to store long-term report data and use that report data as aggregate data (aggregates) within a fixed time frame. The common practice for collecting aggregate data is to insert rows into a report table, then collect the aggregate data by scanning the rows, and update the existing rows in the aggregation table based on the collected aggregate data. The reason for using row insertion for storage is that for most databases, row insertion is performed very quickly (rows are only written at the end of the hard disk file). However, updating rows in a table is a fairly slow operation, because such an update may cause a random random write as well as a random random read. In Redis, users can directly use atomic (atomic) INCR commands and their variants to calculate aggregate data, and because Redis stores data in memory 2, and command requests sent to Redis do not need to be processed by a typical query analyzer (parser) or query optimizer (optimizer), the speed of random writing to Redis stored data is always very fast.

Using Redis instead of relational database or other hard disk storage database can avoid writing unnecessary temporary data, save the trouble of scanning or deleting temporary data, and ultimately improve the performance of the program. Although the above are some simple examples, they are a good example of the fact that tools can greatly change the way people solve problems.

With the exception of the Task queue (task queue) mentioned in Chapter 6, most of this book is devoted to solving problems in real time. This book shows a variety of technologies and provides working code to help readers eliminate bottlenecks, simplify code, collect data, distribute data, build utilities (utility), and ultimately help readers accomplish the task of building software more easily. With the correct use of the technology described in the book, the reader's software can be expanded to dwarf the so-called "Web extension technology (web-sacle technology)".

This is the end of the content of "what problems can be solved by using Redis". Thank you for your reading. If you want to know more about the industry, you can follow the website, the editor will output more high-quality practical articles for you!

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