Discussion on how to solve the cache penetration problem in Go language.

With the development of Internet technology, caching technology plays an increasingly important role in website development. The purpose of caching is to pre-store data in memory so that the data can be obtained faster the next time it is requested. However, not all data in the cache can be cached. Some data, such as some illegal requests, cannot be cached. When these illegal requests frequently access the website, it may cause cache penetration problems, thus affecting the performance and security of the website. This article will focus on how to deal with the problem of cache penetration in the Go language.

1. What is cache penetration

First, let us understand what cache penetration is. Cache penetration means that when users frequently visit the website, the system will save the requested data in the cache. However, when some illegal requests frequently access the website, these requests will directly access the database through the cache, and the data queried by these requests will not be cached. This will result in the lack of data required for the access request in the cache, so that the data cannot be obtained directly from the cache and the data needs to be obtained from the database again, thus affecting the performance of the system.

2. Cache penetration problem in Go language

In Go language, cache penetration is also a very common problem. Through the caching technology of the Go language, we can save some commonly used data in the cache in advance so that the data can be obtained more quickly the next time the request is made. However, if there are some illegal requests to access the website, the data required by these requests may not be cached. This will cause us to be unable to obtain the data required for the request from the cache and need to re-obtain the data from the database, resulting in a decrease in system performance.

3. Solution to cache penetration problem

1. Bloom filter

The Bloom filter is a random space-efficient Data structure that can be used to detect whether an element is in a collection. Its advantage is that space efficiency and query time are very good, but its disadvantage is that it has a certain misrecognition rate and difficulty in deletion. In Go language, we can use the bloomfilter library to implement the function of bloom filter. Using Bloom filters, you can quickly determine whether a request is legal, thereby effectively preventing cache penetration.

2. Cache empty value

Whether the requested data is queried from the database or the cache, if the requested data does not exist, a null value will be returned as the result. At this time, we can store the requested key-value pair in the cache, and the value is empty, so that if the key exists in the cache next time, the empty value can be returned directly, thus avoiding querying data from the database. Of course, this method needs to ensure that the expiration time of null values ​​in the cache cannot be too long, otherwise it will lead to more and more null values ​​in the cache, thus affecting the performance of the system.

3. Data preheating

Data preheating means loading commonly used data into the cache before the system is running so that it can run faster when the system is running. to obtain data. Through data preheating, the problem of cache penetration can be effectively avoided. However, the cached data may change frequently, which requires us to adjust the frequency of data warm-up to ensure the latest data.

4. Current limiting control

Current limiting control refers to limiting requests before entering the system to avoid system overload. By setting the maximum number of concurrent requests, you can effectively control the system load and reduce cache penetration problems.

4. Summary

Go language, as an emerging programming language, is also widely used in caching technology. Cache penetration is a very common problem, and Go is no exception. In order to avoid this problem, we can solve it through bloom filters, cache null values, data preheating and current limiting control. At the same time, we also need to control the update frequency of cached data to ensure that the cached data is up-to-date. Through these methods, we can better solve the problem of cache penetration and improve the performance and security of the system.

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