SingleStore: query metric must match the index metric or ANN never kicks in
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: DOT_PRODUCT index with DOT_PRODUCT queries, EUCLIDEAN_DISTANCE with EUCLIDEAN_DISTANCE; a mismatch means the ANN index is never used. Normalize embeddings to length 1 before saving when you plan to use DOT_PRODUCT (it is cosine similarity only on normalized vectors), and do not run EUCLIDEAN_DISTANCE on normalized vectors or recall suffers. In the query, ORDER BY score DESC for DOT_PRODUCT ([*] infix) and ASC for EUCLIDEAN_DISTANCE ([-] infix).
Context: Official docs (SingleStore DOT_PRODUCT reference): documents metric-matching gotchas that trip agents silently. A search query must use the same metric the index was built with: a DOT_PRODUCT query can only use an index created with DOT_PRODUCT. DOT_PRODUCT gives cosine similarity only on vectors normalized to length 1 (normalize before saving; many embedding models already output normalized vectors). Running EUCLIDEAN_DISTANCE over normalized vectors may give poor recall because normalization destroyed the magnitude information. Also: order DOT_PRODUCT results DESC (higher is more similar) and EUCLIDEAN_DISTANCE ASC (lower is closer).Maintainer review
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