Unverified50% confidenceFactExact time
In pgvector's HNSW index, the parameter m is the number of neighbor edges kept per node, and ef_construction is the size of the candidate queue during construction; together they determine the recall-latency trade-off at query time.
1
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50%
Confidence
Long-term
Relevance
10/20/2026
First Seen
Sources
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Related Claims
UnverifiedHNSW uses m to control the number of neighbors each node keeps in the graph (default 16), ef_construction determines the candidate queue size during construction (default 64), and ef_search controls the search breadth during queries.73% similarUnverifiedHNSW有两个关键超参数：M（每个节点的最大连接数）和ef_construction（索引构建时的动态候选列表大小）72% similarUnverifiedpgvector provides two index types, IVFFlat and HNSW, respectively aimed at different recall and speed trade-off scenarios.68% similarUnverifiedAccording to benchmark data provided by the project, Pg_vectorsearch surpasses pgvector's IVFFlat and HNSW in query throughput.64% similarUnverifiedSince 0.8.0, pgvector provides an iterative index scan, enabled via SET hnsw.iterative_scan = relaxed_order or strict_order, which continues expanding the scan when candidates are exhausted until enough rows for the LIMIT are collected or the hnsw.max_scan_tuples limit is reached.63% similar
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