Visibility of likes by friends on WeChat Moments: How to efficiently process massive data and avoid database pressure?

The secret of the WeChat Moments’ Like Visibility Technology: How to deal with the challenges of massive data?

Likes and comments on WeChat Moments are only visible to friends. Behind this is the complex system design, not a simple database query. This article will explore in-depth how WeChat can efficiently process huge data and high concurrent traffic to avoid the pressure caused by direct intersection operations of databases.

The traditional method is to obtain the set of liked user IDs and the set of user friend IDs respectively, and then find the intersection, which is not feasible under the huge user scale of WeChat. The article points out that WeChat Moments does not rely on traditional relational databases. Before 2015, the implementation methods of "friend likes visible" and "friends circle of friends can be seen". Like data is treated as a data type similar to the content posted on Moments.

The core is to integrate relationship data such as "follow", "subscribe", and "friends" into feed stream processing. The sorting of feed streams in the circle of friends is relatively simple, and it can be arranged in chronological order, without the need for complex personalized recommendation algorithms. Even though the number of fans on platforms such as Weibo far exceeds the number of WeChat friends, WeChat's unique technical solution still effectively avoids the performance bottleneck of database intersection computing and realizes the visibility of friend likes. This involves data storage, optimization of retrieval methods, and effective management of user relationships.

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