We use "data cubes", as per Jim Gray's paper, http://web.stanford.edu/class/cs345d-01/rl/olap.pdf http://web.stanford.edu/class/cs345d-01/rl/olap.pdf. When I s

We use "data cubes", as per Jim Gray's paper, http://web.stanford.edu/class/cs345d-01/rl/olap.pdf http://web.stanford.edu/class/cs345d-01/rl/olap.pdf. When I say "screen", I mean (e.g.) your laptop's screen resolution. If you're going to display a heatmap on a screen with p pixels, we (roughly) touch only O(p) memory cells on query time, independently of the dataset size. When you say "you don't see the uniqueness", I'm not sure what you're comparing it against, so I can't say anything more. You mentioned gkd-trees earlier: is that the comparison you mean? In that case, these are two completely different data structures. For example, (at least as described on the 2009 siggraph paper), you can't subset on a categorical dimension of the pixels. In the case of the data structure we created, we can report (for example) a heatmap of all geolocated tweets generated by an iPhone, or all geolocated tweets generated by a windows phone, or all geolocated tweets irrespective of device, without having to scan the 200M tweet database.