Situation:
I am currently designing a feed system for a social website whereby each user has a feed of their friends' activities. I have two possible methods how to generate the feeds and I would like to ask which is best in terms of ability to scale.
Events from all users are collected in one central database table, event_log. Users are paired as friends in the table friends. The RDBMS we are using is MySQL.
Standard method:
When a user requests their feed page, the system generates the feed by inner joining event_log with friends. The result is then cached and set to timeout after 5 minutes. Scaling is achieved by varying this timeout.
Hypothesised method:
A task runs in the background and for each new, unprocessed item in event_log, it creates entries in the database table user_feed pairing that event with all of the users who are friends with the user who initiated the event. One table row pairs one event with one user.
The problems with the standard method are well known – what if a lot of people's caches expire at the same time? The solution also does not scale well – the brief is for feeds to update as close to real-time as possible
The hypothesised solution in my eyes seems much better; all processing is done offline so no user waits for a page to generate and there are no joins so database tables can be sharded across physical machines. However, if a user has 100,000 friends and creates 20 events in one session, then that results in inserting 2,000,000 rows into the database.
Question:
The question boils down to two points:
Is this worst-case scenario mentioned above problematic, i.e. does table size have an impact on MySQL performance and are there any issues with this mass inserting of data for each event?
Is there anything else I have missed?
