Kinda disappointed by the simulation, where are all the viral posts?
I've been digging around for a while and haven't found any posts with more than 20 faves. The accounts I've found with ~1 million followers have little to no engagement. I want to see how a post with a million faves holds up to the promises of "fast constant time".
I'm especially curious about these queries — fave-count and has-user-faved — since a couple years ago Twitter stopped checking has-user-faved when rendering posts more than a month or so old, so I imagine it was expensive at scale.
The load generator generates boosts/favorites for a subset of posts that are randomly picked to be "popular". However, since the rate of posts is so high even individual posts picked to be "popular" are only getting ~70 reactions.
Tracking reactions is considerably easier than timeline fanout though, as a favorite does a small handful of things (updates set of users favoriting a status and sending a notification), while fanout has to do an operation on every follower (403 operations on average, sometimes up to 22M).
The code getting the favorite count for a status looks like:
The API server doesn't do these queries individually, which would be two roundtrips. It does them together in a query topology along with fetching other needed information (like number of boosts, number of replies, "has boosted", "has muted this status", etc.).
I've been digging around for a while and haven't found any posts with more than 20 faves. The accounts I've found with ~1 million followers have little to no engagement. I want to see how a post with a million faves holds up to the promises of "fast constant time".
I'm especially curious about these queries — fave-count and has-user-faved — since a couple years ago Twitter stopped checking has-user-faved when rendering posts more than a month or so old, so I imagine it was expensive at scale.