How would you do it given that you can't know ahead of time which articles have been deleted? If you pick a random int from 1 to N, there's a probability that y

How would you do it given that you can't know ahead of time which articles have been deleted? If you pick a random int from 1 to N, there's a probability that you'd get a bad result. If the proportion of bad pages is greater than good pages (a not-unlikely hypothesis given spam) then repeatedly picking a random int from 1 to N will take a few rerolls. I agree that rerolling is probably a fine strategy, but it's not obvious that everyone would be willing to just trust probability like that. In fact, if you set up your own wiki with 99 bad pages and 1 good page, hitting the random article button won't work most of the time. You could of course pick a random number from 1 to M, where M is the number of valid articles. But that runs into the same problem of how do you map the 1-to-M number back to an actual article id? This method may be biased, but it's constant performance. (I still prefer just keeping all valid articles in memory and choosing a random one of those. There are only 7M as of October, so including the deleted pages, there's probably ~70M, which is on the same order as HN's total item count. Heck, even creating one file per valid article on disk and doing a random search with "find . -type f | shuf -n 1" probably wouldn't be terrible if you cache the result every few seconds, though that'd also be biased in its own way.)