64D COUNTR DES_CS SBRM ; CS.base = selector
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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This article originally appeared on Engadget at https://www.engadget.com/gaming/pc/hp-says-ram-now-accounts-for-more-than-a-third-of-its-pc-costs-192914150.html?src=rss
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