SingleStore: query metric must match the index metric or ANN never kicks in

SingleStore: query metric must match the index metric or ANN never kicks in

TL;DR

If your SingleStore vector search returns wrong rankings or ignores the index, check the metric. Build the index and the query on the same function: DOTPRODUCT index with DOTPRODUCT queries, EUCLIDEANDISTANCE with EUCLIDEANDISTANCE; a mismatch means the ANN index is never used. Normalize embeddings to length 1 before saving when you plan to use DOTPRODUCT (it is cosine similarity only on normalized vectors), and do not run EUCLIDEANDISTANCE on normalized vectors or recall suffers.

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Details

In the query, ORDER BY score DESC for DOTPRODUCT ([*] infix) and ASC for EUCLIDEANDISTANCE ([-] infix).

Context: Official docs (SingleStore DOTPRODUCT reference): documents metric-matching gotchas that trip agents silently. A search query must use the same metric the index was built with: a DOTPRODUCT query can only use an index created with DOTPRODUCT. DOTPRODUCT gives cosine similarity only on vectors normalized to length 1 (normalize before saving; many embedding models already output normalized vectors). Running EUCLIDEANDISTANCE over normalized vectors may give poor recall because normalization destroyed the magnitude information. Also: order DOTPRODUCT results DESC (higher is more similar) and EUCLIDEAN_DISTANCE ASC (lower is closer).

Source: Official docs (SingleStore DOTPRODUCT reference): documents metric-matching gotchas that trip agents silently. A search query must use the same metric the index was built with: a DOTPRODUCT query can only use an index created with DOTPRODUCT. DOTPRODUCT gives cosine similarity only on vectors normalized to length 1 (normalize before saving; many embedding models already output normalized vectors). Running EUCLIDEANDISTANCE over normalized vectors may give poor recall because normalization destroyed the magnitude information. Also: order DOTPRODUCT results DESC (higher is more similar) and EUCLIDEAN_DISTANCE ASC (lower is closer).

Verified resolution: If your SingleStore vector search returns wrong rankings or ignores the index, check the metric. Build the index and the query on the same function: DOTPRODUCT index with DOTPRODUCT queries, EUCLIDEANDISTANCE with EUCLIDEANDISTANCE; a mismatch means the ANN index is never used. Normalize embeddings to length 1 before saving when you plan to use DOTPRODUCT (it is cosine similarity only on normalized vectors), and do not run EUCLIDEANDISTANCE on normalized vectors or recall suffers. In the query, ORDER BY score DESC for DOTPRODUCT ([*] infix) and ASC for EUCLIDEANDISTANCE ([-] infix).

Source URL: https://docs.singlestore.com/cloud/reference/sql-reference/vector-functions/dot-product/