Do you know what the 8 major application scenarios of Redis are?
The following column Redis Tutorial will introduce you to the 8 major application scenarios of Redis. I hope it will be helpful to friends in need!
8 major application scenarios of Redis!
I have talked about the introduction of Redis before and the advantages brought by using Redis. This chapter sorts out the application scenarios of Redis, which is also very important. Whether you can learn well or not, the key is to be able to implement it normally. .
Let’s analyze the application scenarios of Redis one by one.
1. Caching
Caching is now a must-have for almost all medium and large websites. Reasonable use of caching can not only improve website access speed, but also greatly reduce the pressure on the database. Redis provides key expiration function and flexible key elimination strategy. Therefore, Redis is now used in many caching situations.
2. Rankings
Many websites have ranking applications, such as JD.com’s monthly sales list, product new rankings by time, etc. The ordered set data structure provided by Redis can implement various complex ranking applications.
3. Counter
What is a counter, such as the number of views of products on e-commerce websites, the number of video plays on video websites, etc. In order to ensure the real-time performance of the data, 1 must be given for each browsing. When the concurrency is high, it will undoubtedly be a challenge and pressure to request database operations every time. The incr command provided by Redis implements counter functions and memory operations with very good performance and is very suitable for these counting scenarios.
4. Distributed session
In cluster mode, when there are not many applications, it is generally sufficient to use the session replication function that comes with the container. When the number of applications increases and the system becomes relatively complex, Generally, a session service centered on an in-memory database such as Redis is built. The session is no longer managed by the container, but by the session service and the in-memory database.
5. Distributed lock
Distributed technology is used in many Internet companies. The technical challenge brought by distributed technology is concurrent access to the same resource, such as global ID, Scenarios such as inventory reduction and flash sales, and scenarios with low concurrency can be implemented using database pessimistic locks and optimistic locks. However, in scenarios with high concurrency, it is not ideal to use database locks to control concurrent access to resources. Affects database performance. You can use the setnx function of Redis to write distributed locks. If the setting returns 1, it means the lock acquisition is successful. Otherwise, the lock acquisition fails. There are more details to consider in actual applications.
6. Social Network
Likes, dislikes, following/being followed, mutual friends, etc. are the basic functions of social networking sites. The number of visits to social networking sites is usually relatively large, and traditional The relational database type is not suitable for storing this type of data. The hash, set and other data structures provided by Redis can easily implement these functions.
7. Latest list
Redis list structure, LPUSH can insert a content ID as a keyword at the head of the list, LTRIM can be used to limit the number of lists, so that the list will always have N IDs. There is no need to query the latest list, just go to the corresponding content page based on the ID.
8. Message system
Message queue is a necessary middleware for large websites, such as ActiveMQ, RabbitMQ, Kafka and other popular message queue middleware. It is mainly used for business decoupling, traffic peak reduction and Asynchronously process services with low real-time performance. Redis provides publish/subscribe and blocking queue functions, which can implement a simple message queue system. In addition, this cannot be compared with professional message middleware.
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