A caching mechanism to implement efficient online advertising delivery algorithm in Golang.

As an efficient programming language, Golang has been welcomed by more and more developers in recent years and is widely used in various scenarios. In the advertising platform scenario, in order to achieve accurate advertising delivery, it is necessary to quickly calculate the selection, sorting, filtering and other processes of ads to achieve efficient advertising delivery. In order to optimize this process, the caching mechanism has become an inevitable part.

Generally speaking, the process of the advertising platform is as follows: When users browse the web, the advertising platform collects the user’s information through various methods, and uses the advertising selection algorithm to select advertisers that match the user’s information and advertisers. Advertising on demand. Then, through sorting and filtering algorithms, the ads that can finally be placed are obtained, and operations such as ad exposure and clicks are performed. Based on this process, we can divide the algorithm parts into two categories: ad selection algorithms and sorting and filtering algorithms.

For the ad selection algorithm, the client will not interact frequently with the ad platform. Generally there will be no performance bottlenecks. As for the sorting and filtering algorithm, since it involves a lot of calculations, it will be very time-consuming to recalculate every time a user requests it, so it is particularly important to introduce a caching mechanism.

To implement the caching mechanism of efficient online advertising delivery algorithm in Golang, we can consider using a combination of memory caching and disk caching. For common cache libraries, such as redis, memcache, etc., problems such as connection pool shortages may occur under high concurrency conditions, and Golang's native Map data structure can avoid these problems well.

The data we need to store in the cache is mainly divided into two categories: advertising selection results and final sorting results. For the final sorting result, since the number of advertisements is relatively small, it can be cached directly in the memory. As for the advertisement selection results, since the selection needs to be based on user information, it is necessary to calculate the hash value based on the user information and store the hash value as a key. At the same time, in order to avoid excessive memory usage, you can set policies such as cache expiration time to achieve efficient use of memory.

When the program starts, the data in the last cache can be restored. At the same time, during the running of the program, by using timer concurrency control, the cached data in the memory can be regularly stored on the disk to cope with abnormal program exit and other situations. In this way, the reliability of the program can be improved while ensuring the correctness of the data.

In general, the caching mechanism to implement efficient online advertising delivery algorithm in Golang can be divided into the following steps:

1. Use Map data structure for memory caching.
2. Calculate the hash value based on user information and store it with the hash value as the key.
3. Set policies such as cache expiration time to achieve efficient use of memory.
4. Restore the data in the last cache when the program starts.
5. Regularly store the cached data in the memory to the disk to deal with abnormal program exit and other situations.

Through the implementation of the above steps, we can improve the efficiency of advertising while ensuring the accuracy of the data, provide users with a better advertising experience, and provide advertisers with better advertising. Effect.

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