feat: support distance pushdown

[cutecutecat]

No description provided.

[cutecutecat]

Index build script:

-- Dataset Params
SET app.num_collections           TO 30;
SET app.num_assets_per_collection TO 50;
SET app.num_segments_per_asset    TO 300;

-- BUILD DATASET

-- Ensure the extension is made
DROP EXTENSION IF EXISTS vectors;
CREATE EXTENSION vectors;

-- Create the collection table
CREATE TABLE collection (
  id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
  name TEXT NOT NULL
);

-- Create the asset table with a foreign key to the collection table
CREATE TABLE asset (
  id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
  collection_id UUID REFERENCES collection(id) ON DELETE CASCADE,
  title TEXT NOT NULL
);

-- Vector Types (https://docs.pgvecto.rs/reference/vector-types.html)
-- - vecf16: FP16 vector
-- - bvector: Binary vector

-- Depending on the choice of vector type, we need to modify the following parts:
-- - `segment.embedding` dtype
-- - index creation operators (See https://docs.pgvecto.rs/reference/schema.html#list-of-operator-families)
-- - table insertion dtype casting

-- Create the segment table with a foreign key to the asset table
CREATE TABLE segment (
  id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
  asset_id UUID REFERENCES asset(id) ON DELETE CASCADE,
  embedding vector(640) NOT NULL, -- 640 dimensions
  category TEXT NOT NULL
);

-- INDEXES
-- Create index on asset's foreign key collection_id
CREATE INDEX idx_asset_collection_id ON asset(collection_id);

-- Create index on segment's foreign key asset_id
CREATE INDEX idx_segment_asset_id ON segment(asset_id);

-- Create index on segment's category column
CREATE INDEX idx_segment_category ON segment(category);


-- VECTOR INDEX
-- Ops options: https://docs.pgvecto.rs/reference/schema.html#list-of-operator-families
-- - vector_cos_ops
-- - vecf16_cos_ops
-- - veci8_cos_ops
-- - bvector_cos_ops

-- CREATE INDEX ON segment USING vectors (embedding vecf16_cos_ops);
-- CREATE INDEX ON segment USING vectors (embedding vector_cos_ops);


DO $$
DECLARE
  -- num_collections INT := 10;
  -- num_assets_per_collection INT := 100;
  -- num_segments_per_asset INT := 1500;
  num_collections INT := current_setting('app.num_collections')::INT;
  num_assets_per_collection INT := current_setting('app.num_assets_per_collection')::INT;
  num_segments_per_asset INT := current_setting('app.num_segments_per_asset')::INT;
  category_counter INTEGER;
  category TEXT;
  collection_id UUID;
  asset_id UUID;
  embedding vector;  -- May need to modify dtype

-- Dummy data
BEGIN
  -- Insert dummy data for the collection table
  FOR i IN 1..num_collections LOOP
    INSERT INTO collection (name) 
    VALUES ('Library ' || i)
    RETURNING id INTO collection_id;

    -- Insert dummy data for the asset table
    FOR j IN 1..num_assets_per_collection LOOP
      INSERT INTO asset (collection_id, title) 
      VALUES (collection_id, 'Video Asset ' || j)
      RETURNING id INTO asset_id;

      category_counter := 0;

      -- Insert dummy data for the segment table
      FOR k IN 1..num_segments_per_asset LOOP
        -- Generate a random vector embedding
        -- embedding := ARRAY(SELECT round(random()::real) FROM generate_series(1, 640))::real[]::vector::bvector;
        -- embedding := ARRAY(SELECT random()::real FROM generate_series(1, 640))::real[]::vector::vecf16;
        embedding := ARRAY(SELECT random()::real FROM generate_series(1, 640))::real[]::vector;
        category := CASE WHEN category_counter % 2 = 0 THEN 'visual' ELSE 'transcript' END;
        category_counter := category_counter + 1;

        -- Insert the segment data
        INSERT INTO segment (asset_id, embedding, category)
        VALUES (asset_id, embedding, category);
      END LOOP;
    END LOOP;
  END LOOP;
END $$;


-- BUILD HNSW INDEX w/ Cosine Ops
CREATE INDEX i ON segment USING vectors (embedding vector_cos_ops)
WITH (options = $$
optimizing.optimizing_threads = 12
[indexing.hnsw]
$$);

Query:

SELECT embedding <=> 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FROM segment
WHERE embedding < 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LIMIT 100;

[usamoi]

It's good if it's inlined. Small util functions always make code messy.

[usamoi]

It's marked resolved but not resolved. @cutecutecat

[cutecutecat]

Cleared for mistake

[usamoi]

It's marked resolved but not resolved. @cutecutecat

[usamoi]

It's marked resolved but not resolved. @cutecutecat

[usamoi]

Memory leak.