Computing the sum of elements over a sliding window is a textbook interview question.
By storing the last window and its sum in memory, we can process elements and answer queries in constant time and near-optimal space.
In this talk, I will discuss a variant of this problem where the user specifies the window size i≤n query time, and only an upper bound n is known in advance.
As window sizes in practice may be large, standard practice is to settle on approximation algorithms that use sub-linear space.
I will present upper and lower bounds on the space required for approximating such queries.