如何设计一个高效的Like系统？

Question

I'm trying to create a Like/Unlike system akin to Facebook's for an existing comments section of a website, and I need help in designing the system.

Currently, every product on the website has a comments section and members can post and like comments. I need to know each member has posted how many comments and each of his comments has received how many likes. Of course, I need to know who liked what comments too (partly so that I can prevent a user from liking a comment more than once) for analytical purposes.

The naive way of implementing a Like system to the current comments module is to create a new table in the database that has foreign keys to the CommentID and UserID. Then for every "like" given to a comment by a user, I would insert a row to this new table with the targeting comment ID and user ID.

While this might work, the massive amount of comments and users is going to cause this table to grow quickly and retrieving records from and doing counts on this huge table will become slow and inefficient. I can index either one of the columns, but I don't know how effective it would be. The website has over a million comments.

I'm using PHP and MySQL. For a system like this with a huge database, how should I designing a Like system so that it is more optimised and stable?

Answer 1

Your main concern will be a lot of counts, so the easy thing to do is to keep a separate count in your comments table.

Then you can create a TRIGGER that increments/decrements the count based on a like/unlike.

That way you only use the big table to figure out if a user already voted.

Answer 2

For scalability, do not include the count column in the same table with other things. This is a rare case where "vertical partitioning" is beneficial. Why? The LIKEs/UNLIKEs will come fast and furious. If the code to do the increment/decrement hits a table used for other things (such as the text of the Comment), there will be an unacceptable amount of contention between the two.

This tip is the first of many steps toward being able to scale to Facebook levels. The other tips will come, not from a free forum, but from the team of smart engineers you will have to hire to get to that level. (Hints: Sharding, Buffering, Showing Estimates, etc.)