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Detailed explanation of Redis' implementation of high concurrency access control

王林
王林Original
2023-06-20 08:27:061497browse

With the vigorous development of the Internet, the problem of high concurrency has increasingly become an urgent problem that needs to be solved. For many websites and applications, the key to achieving high concurrency is access control, which requires the use of some reliable tools to achieve this goal. This article will focus on introducing an access control method including Redis to help web developers achieve reliable high-concurrency access control.

What is access control?

Access control refers to the method of restricting certain people or certain systems from accessing your resources or services. In websites and programs, access control can prevent unauthorized access and unauthorized use through some technical means.

For example, in an e-commerce website, most operations require users to log in, and only logged-in users can view a specific page. This login page is actually an access control page that prevents unauthorized users from viewing secret information.

How to achieve high concurrency access control?

When a website or application really becomes popular, achieving high concurrent access control becomes an extremely difficult and complex task. However, this problem can be solved using some efficient techniques and tools. Among them, Redis is a reliable access control tool.

Redis is an open source, in-memory key-value storage data structure server that can be used as a database, cache, and messaging middleware. It supports different stored data types and operations, including strings, hash tables, sets, ordered sets, bitmaps, hyperloglog, geospatial indexes, etc. Redis is also efficient, scalable, and reliable, making it an ideal choice for implementing access control in high-concurrency environments.

The following are some basic steps to use Redis to achieve high concurrent access control:

  1. Add the client IP address to the Redis cache

When a new When a client makes a request to the server, we need to first add the client's IP address to the Redis cache. This cache is usually stored in the form of a collection, with each element representing an IP address.

In this process, we need to determine a timeout to ensure that each IP address is only stored in the cache for a certain period of time to prevent a large number of junk IP addresses from blocking the cache.

  1. Check client request frequency

When a client requests the server, we need to check the client's request frequency within a specific time period to determine whether it is exceeded Limited request frequency. A counter can be used here to record the number of requests and decide whether to continue processing the request based on the set frequency limit.

If the request frequency exceeds the specified limit, we can perform some corresponding processing, such as rejecting the request, delaying the execution time of the request, etc.

  1. Cache request response

When the server responds to the request, we can also use some caching methods to cache the server's response, so that the next time the same request arrives, we You can reduce the load on the server by getting the response from Redis.

This cache is usually stored in the form of a collection. Each element identifies a request, and its value is the content of the server response. The use of this cache can reduce server load, increase experience speed and reduce resource consumption.

  1. Number of manual request submissions

In some cases, we may need to manually specify the client's request permission, which may be useful in some specific situations. For example, for certain high-priority client requests, we can manually customize the priority to ensure that these requests are responded to first.

In this case, we can use the zset data type in Redis to record the number of requests and permissions when each client accesses, so as to facilitate manual submission or withdrawal.

Summary

Redis is a very powerful tool that can achieve efficient, scalable and reliable high-concurrency access control. By using Redis, we can add IP addresses to the cache, limit request frequency, cache responses and manually submit requests to achieve efficient access control.

Although Redis itself can achieve many functions, we should fully understand our "business needs" and implement access control policies based on it. It is worth noting that if Redis is used unreasonably, it may cause corresponding problems with access control, so developers must have the corresponding technical knowledge and experience to implement different access control strategies.

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