Unverified50% confidenceFactExact time
Approximate nearest neighbor search (ANN) uses algorithms such as HNSW or IVF, trading a small loss in recall for millisecond-level response, returning the semantically nearest candidate set rather than the factually most relevant documents.
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50%
Confidence
Long-term
Relevance
10/19/2026
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Unverified确定性索引保证同一查询必然返回同一结果，而ANN算法（如HNSW、IVF-PQ）以牺牲精确性换取毫秒级检索，结果本质上是概率性的72% similarUnverifiedApproximate nearest neighbor (ANN) index structures (such as HNSW and IVF) need to be rebuilt or tuned after the data distribution changes, otherwise recall will decline.71% similarUnverifiedFull-text search typically relies on inverted index technology to achieve millisecond-level retrieval response.67% similarUnverifiedThe hnswlib documentation states that a higher ef makes search more accurate and slower, and that it cannot be less than k; this description can basically be carried over to understanding pgvector's hnsw.ef_search.66% similarUnverifiedDuring HNSW queries, the upper-layer search uses ef = 1, keeping only one candidate and performing pure greedy descent; the bottom layer uses a beam search of size ef.66% similar
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