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Agree on this. Although the 80% figure is probably more like 99% (I have no metrics, but 80% feels too low to make this point)



It's about 99% if you haven't run it through a profiler and optimized the hot spots. With such, you can get it down to 90% or so.


I have noticed that great code and terrible code often have the same characteristics on profiles: in both cases, slowness is spread around everywhere.


In this video, David Gross says something along the lines of "if your data is laid out in a memory inefficient manner, it will be the bottleneck everywhere." If you're dependent on a database query for everything, that will be your bottleneck. If your in-memory structures are cache inefficient, that will be your bottleneck. But once you've fixed all of this (if you can), hot paths and whatnot matter

https://m.youtube.com/watch?v=8uAW5FQtcvE


i've noticed the opposite, usually performance is bottlenecked by specific and unpredictable hot spots




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