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.
Here's a concrete example from far return (RETF). The microcode needs to determine whether this is a same-privilege or cross-privilege return, because the two cases require very different handling. Following execution order (not address order):
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对于智界来说，请一个荣耀系CEO容易，让整个组织华为化很难。在组织没有彻底变革之前，郭锐尽管有成熟的占领年轻消费者用户心智的经验，能否通过团队最终落地，还是要打一个问号。
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牛犇進一步稱，張又俠倒台令人驚訝之處在於，習近平在剷除政治腐敗團夥時，會放過圈內的高級保護人。張又俠明年二十一大後便要退休，讓他悄然退場本是輕而易舉。但習近平選擇不這樣做。