The efficiency depends on the query size relative to the data distribution. A small query in a sparse region prunes almost everything. A query that covers the whole space prunes nothing (because every node overlaps), degenerating to a brute-force scan. The quadtree gives you the most benefit when your queries are spatially local, which is exactly the common case for map applications, game physics, and spatial databases.
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Pretty neat huh? Those are all the vertices we need to render those two blocks in a chunk. Let's say we also do a similar process for getting the colors or uv coordinates of the chunk and we get an array with the same number of rows. For now, each face has the color red. Storing the vertices in B, we can simply just concatenate it to the side like this:。关于这个话题，新收录的资料提供了深入分析
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