The pathological case for skylinesort is the optimal case for quicksort: uniformly randomly distributed data. In this case skylinesort is 3-4x slower than qui

The pathological case for skylinesort is the optimal case for quicksort: uniformly randomly distributed data. In this case skylinesort is 3-4x slower than quicksort. It's still not like the pathological case of quicksort, which takes quadratic time: it's an effectively log-linear worst case. My advice is to use skylinesort when you have or can have tons of empty memory and have clustered data. Clustered means there's repetition of data points or they are in some ranges more than others. But in practice whenever your data isn't uniformly randomly distributed, skylinesort is better.