I can’t think of a single time I’ve needed a sorted list of only numbers. It’s always numbers and something else, like names or dates. Maybe for median calculations, but I don’t even use those that much either. Especially in telemetry, where mean is easy and median is not.

▲

pvillano 4 hours ago | parent | next [-]

To be pedantic, median is cheaper than sorting. O(n) with a quicksort-like algorithm.

Also, if you're taking an average of floating point numbers, you might want to sort it first and add from smallest to largest, to better preserve precision

▲

lscharen 3 hours ago | parent [-]

An aside, but I recently learned -- if one is willing to use a very modest amount of memory -- summing floating-point numbers with no loss of precision is effectively a solved problem with the XSUM algorithm.

https://glizen.com/radfordneal/ftp/xsum.pdf

	▲	tialaramex 2 hours ago \| parent [-]
		That paper explains some useful optimisation details, but obviously since the floats are all (either infinity or) some multiple of a known tiny fraction (their smallest non-zero number), we can definitely sum them accurately.

▲

vlovich123 4 hours ago | parent | prev [-]

If the primary key is the number, it still works (and dates are just numbers by the way) because you can sort a heterogenous dataset by a single numeric key pretty trivially.

But sorting by arbitrary strings like names can’t avoid comparison sort.