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.
Meta 与 Google 签下十亿美元算力大单
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「該怎麼說呢？在奧運贏得獎牌對每位運動員而言都是改變人生的經歷。五度奪牌的難度更是呈指數級增長——每面獎牌對我而言同樣艱辛，但外界的期待值卻不斷攀升，對吧？」
真要拿这套方案去赌消费者是否认可，还是要看最后的路测报告，否则很难服众。