Home Database Redis Comparison of Redis implementation of high-concurrency flash sale system solutions

Comparison of Redis implementation of high-concurrency flash sale system solutions

Jun 21, 2023 am 08:15 AM
redis High concurrency Flash kill system

In recent years, with the continuous advancement of Internet technology and the growing needs of users, e-commerce platforms in various industries are also accelerating digital transformation. As one of the most popular promotion methods on e-commerce platforms, flash sale activities have also become the focus of imitation and competition among major platforms. However, the technical challenges brought by high concurrency also make it extremely difficult to design a stable, fast, and safe flash sale system. In this context, Redis, as a high-performance memory database, plays an increasingly important role. This article uses Redis as the core to discuss and compare solutions on how to implement a high-concurrency flash sale system.

1. Problems with the traditional flash sale system

In e-commerce platforms such as Taobao and JD.com, random drawing and order of purchase time are used to implement the flash sale process. However, as users With the continuous growth and unexpected traffic peak, this method gradually exposed some problems, the biggest of which is inefficiency and instability, such as:

1. Product information cannot be cached: flash sale products Quantity, price and other information need to be obtained in real time and continuously updated. Therefore, too many requests will cause the load of the data server to surge instantly and the server to crash.

2. High concurrency pressure: At the moment the flash sale starts, all waiting users will instantly trigger a large number of requests. If the server's concurrent processing capabilities and bandwidth are not enhanced, it will not be able to withstand this strong pressure.

3. Data consistency problem: If multiple users purchase the same product at the same time, the inventory and purchase quantity may be inconsistent. In the traditional flash sale system, a program needs to be designed to ensure strong consistency of data. sex. However, this guarantee results in a severe performance degradation of the system.

2. Advantages of using Redis to implement the flash sale system

In order to solve the problems of the traditional flash sale system, the method of using Redis to implement the flash sale system has been widely adopted. The advantages of this method mainly include the following aspects:

1. Strong data caching capability: Redis is a memory-based database, and its caching capability is much higher than traditional relational databases or file caching systems. It can greatly improve the response speed and stability of flash sale events.

2. High concurrent processing capability: Redis adopts a single-threaded processing mode, which has extremely high performance in terms of processing speed, concurrency pressure and data consistency, and can effectively handle high concurrent requests.

3. Good data structure support: Redis supports a variety of data structures, such as strings, hashes, lists, sets, etc., which can facilitate various data operations in the flash sale system.

3. Comparison of Redis’ solutions for implementing the flash sale system

Regarding the specific solutions for Redis to implement the flash sale system, you can compare them based on their different advantages and disadvantages in the implementation process, and select the most suitable solution.

1. Pre-reduce inventory and then join the queue

This plan is to initialize all flash sale products into Redis and save the quantity of the products into a Key. Before the flash sale starts, The quantity of the product is subtracted from the flash sale inventory, and then the product ID is pushed into the message queue. The user obtains the product ID from the queue and queries the inventory. If the inventory is found to be insufficient, a flash sale failure is returned.

The advantage of this solution is that it is simple to implement and can effectively avoid overselling and underselling during high concurrency. However, for malicious attacks or large-volume flash sales, the pre-inventory reduction process will increase the IO load of Redis and easily cause an avalanche effect.

2. Optimistic locking (CAS)

In this solution, you only need to initialize a hash table of flash sale products, which stores product ID, inventory and other information, every time a flash sale request arrives When the time comes, the inventory is read first. If the inventory is sufficient, the inventory is reduced and the flash sale is successfully obtained through the CAS operation. If the CAS operation fails, it means that other users have already grabbed the product before and need to return to Flash Sale Failure. The optimistic locking solution can well solve the problems of high concurrent read requests and concurrent inventory modifications.

3. Distributed lock

This solution mainly protects the flash sale product inventory in Redis by introducing a distributed lock mechanism, so that each request needs to obtain the lock when processing Only then can subsequent processing operations be carried out to prevent multiple requests from being modified at the same time. The distributed lock solution can ensure data consistency and security, but because the lock itself includes a lock release operation, it may cause additional IO operations.

4. Reverse proxy cache

This solution uses reverse proxy servers such as Nginx as a cache to cache requests and data to avoid bottlenecks during rush buying activities. For flash sale activities, Nginx, as a reverse proxy server, can cache requests for hot products into memory first, and can add multi-level caches in a cascading manner. When subsequent requests come in, the data in the cache can be accessed first to avoid frequent access to cache libraries such as Redis. This solution can effectively solve the performance bottleneck problem under high concurrency.

4. Conclusion

Based on the comparison of the above solutions, the Redis solution to implement the flash sale system is not a silver bullet. Different solutions have different implementation methods and processing methods, and their respective advantages and disadvantages are also different. Therefore, in the actual application process, you need to comprehensively consider the applicability, advantages and disadvantages of these solutions according to your actual situation and needs, and select the most suitable solution to ensure the performance and stability of the flash sale system under high concurrency.

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