Stop Joining Millions of Rows for Every Single Swipe

TL;DR: Dating apps avoid the architectural nightmare of joining millions of left-swipe records by using Bloom filters. By hashing user IDs into a bit array, they get a 100% guarantee that a '0' means a user is new, while accepting a rare false positive as a necessary trade-off for high-concurrency performance. I’ve seen plenty of teams try to scale discovery feeds by throwing more hardware at SQL joins, and it is a losing game. If I have to check a user’s entire history of left swipes against a pool of millions of profiles every time they refresh their deck, the database isn't just going to be slow—it’s going to stop breathing. We aren't talking about a simple query; we are talking about a cross-reference that grows every time a user interacts with the app. Scaling a discovery engine requires moving away from absolute row-level checks and toward probabilistic data structures. When I look at how top-tier apps handle the "have they seen this person?" problem, I don’t see massive JOIN sta