Sparse Vector Search
Sparse Vector Search
Sparse Vector Search
Sparse Vector Search
Basic Usage
Creating a sparse HNSW index over a table can significantly improve query times.
-- Create a table with a sparse vector column
CREATE TABLE items (id bigserial PRIMARY KEY, embedding sparsevec(5));
-- Insert sparse vectors
INSERT INTO items (embedding) VALUES ('{1:1,3:2,5:3}/5'), ('{1:4,3:5,5:6}/5');
Sparse vectors can be searched using L2 distance, cosine distance, or inner product.
-- L2 distance
SELECT * FROM items ORDER BY embedding <-> '{1:3,3:1,5:2}/5' LIMIT 5;
-- Cosine distance
SELECT * FROM items ORDER BY embedding <=> '{1:3,3:1,5:2}/5' LIMIT 5;
-- Inner product
SELECT * FROM items ORDER BY embedding <#> '{1:3,3:1,5:2}/5' LIMIT 5;
Under the hood, ParadeDB uses pgvector for sparse vector search. Please refer to the pgvector documentation for more details.
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