What is the IVFFlat index in pgvector and how does it compare to HNSW?

IVFFlat (Inverted File Flat) is pgvector's other index type. It clusters vectors into lists using k-means, then searches only the closest lists to the query vector. It was the original pgvector index type but is now generally considered secondary to HNSW for most workloads.

-- Create an IVFFlat index
-- IMPORTANT: table must have data before creating the index
-- (k-means clustering needs existing vectors to learn from)

-- For L2 distance:
CREATE INDEX ON items USING ivfflat (embedding vector_l2_ops)
WITH (lists = 100);  -- number of clusters/lists

-- For cosine distance:
CREATE INDEX ON items USING ivfflat (embedding vector_cosine_ops)
WITH (lists = 100);

-- Guideline for lists parameter:
-- rows <= 1,000,000: lists = sqrt(rows)  e.g. sqrt(100000) ~ 316
-- rows >  1,000,000: lists = rows / 1000  e.g. 2000000/1000 = 2000

-- Tune QUERY recall at query time:
SET ivfflat.probes = 10;  -- number of lists to search (default 1)
-- Higher probes = better recall, slower queries
-- probes = lists gives exact search (defeats purpose of index)

SELECT id FROM items ORDER BY embedding <-> '[...]' LIMIT 5;
RESET ivfflat.probes;

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