QuadTree solves the spatial search problem by applying the "divide and conquer" principle to 2D space. QuadTree recursively subdivides 2D space into four quadrants for efficient spatial queries.
I wonder like if we are given 3 coordinates, like maybe for a 3D space, then we can probably extend this analogy to 3D, or nD binary search. And probably create like a general nD data structure for it.
The analogy of a 2D binary search is great.
I wonder like if we are given 3 coordinates, like maybe for a 3D space, then we can probably extend this analogy to 3D, or nD binary search. And probably create like a general nD data structure for it.
Just wondering.
For 3D space, there are other data structure like OctTrees.
I don't think it's easy to have an nD data structure, which guarantees the same level of performance!