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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Reporting by Chance Townsend, Caitlin Welsh, Sam Haysom, Amanda Yeo, Shannon Connellan, Cecily Mauran, Mike Pearl, and Adam Rosenberg contributed to this article.