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Moving forward, we still see meaningful headroom to optimize our Top K performance by pruning work earlier in the execution pipeline. One direction is index partitioning and segment-level ordering, where data is physically grouped or sorted by commonly queried dimensions (such as time ranges or coarse score buckets). With this layout, entire segments whose maximum possible score or ordering value cannot beat the current Top K threshold can be skipped.

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22 - #[feature(specialization)]​

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孙亮,独立研究员,专注于数据分析与市场趋势研究,多篇文章获得业内好评。

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