Nearest Neighbor Search
The fundamental operation of vector retrieval: given a query vector, find the k vectors in the vector store with the smallest distance. Mathematically, as long as the store is non-empty, a result is necessarily returned, and no built-in no-result branch exists.
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The core mechanism of vector search is nearest-neighbor search: as long as the vector store is non-empty, it will always return a result, and there is no built-in "no result" branch.
Exact nearest neighbor search requires computing the distance between the query vector and every vector in the library one by one, with complexity growing linearly with data volume, which is unacceptable at the hundred-million scale.
All Facts (2)
The core mechanism of vector search is nearest-neighbor search: as long as the vector store is non-empty, it will always return a result, and there is no built-in "no result" branch.
50%UnverifiedExact nearest neighbor search requires computing the distance between the query vector and every vector in the library one by one, with complexity growing linearly with data volume, which is unacceptable at the hundred-million scale.
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