Advice for properly timing Django queryset evaluation about pgvector-python

[ankane]

Hi @rsomani95, Postgres will figure out the best way to execute the query (in most situations), which involves minimizing work. You can use EXPLAIN ANALYZE to see the details.

[rsomani95]

@ankane EXPLAIN ANALYZE was helpful, thanks.
It suggests to me that the concern presented above is true i.e. the vector filter is being applied on all rows of the table.

First, here's a simplified version of the code above:

        # `embeddable_cls` is a Django Model
        # `candidate_ids` is a list of ids to limit the scope of the vector filtering

        scoped_qset = embeddable_cls.objects.filter(id__in=candidate_ids)

        queryset = (
            scoped_qset
            .annotate(distance=CosineDistance(embedding_name, embedding))
            .filter(distance__lt=query_arguments.distance)
        )

        filtered_ids = list(queryset.values_list("id", flat=True))

In this case, candidate_ids is a precomputed list of 33 ids. The entire table has 178 rows in total.
I'd expect the cosine distance to only be computed on those 33 ids, and not 178 rows. However, this is the generated SQL:

Executed SQL
SELECT "ozu_api_segment"."id"
  FROM "ozu_api_segment"
 WHERE ("ozu_api_segment"."id" IN ('36d3abe1-2cf5-4796-8445-a7529ff0c8fb'::uuid, 'f1d02d3d-7861-40c6-95ae-627e791983cf'::uuid, '32a6be12-617b-4ef8-b580-698b99628b01'::uuid, '2f7cb18d-7e09-4b6b-976a-b16db475ce2f'::uuid, '5655dd82-fe55-426d-b54e-38663e1f13a2'::uuid, '1cca49ea-e27f-40af-82f3-d37417073ffe'::uuid, '887ad098-be19-4575-ac30-679cb65a150a'::uuid, 'a48b75f2-ca12-4e52-b843-664067bf03e4'::uuid, '4c72595c-fade-4af2-84e1-723b0dc23422'::uuid, '9973b052-27d0-4378-b7ba-0c56027e3c21'::uuid, '93f1b0aa-ea42-4b85-b216-7bc2b2e15a16'::uuid, 'bb6eded5-8855-4766-b892-dcb420710ec3'::uuid, 'ea2d008f-3108-4fe1-b82b-c0c0b4784005'::uuid, '6e2609a4-4e7a-4fb1-865e-9b9d707b08a1'::uuid, 'a176518f-f7cf-4171-9802-9f191caa7d87'::uuid, '02b0ced8-490b-4ef2-9300-bdf702102843'::uuid, '62e8f839-3023-4da8-b531-59a6dd61fd25'::uuid, 'f74db32a-705f-436b-bcf0-da480e535755'::uuid, 'b8cc4c88-5f4c-4408-aea3-6bac56cd4caf'::uuid, '2825b039-2a51-45cc-83e0-51ad0c4a4af9'::uuid, '33c0bc96-57f6-4415-9b4c-38890c53332e'::uuid, 'd7b35172-d824-43ae-8a89-e1974db7d9f2'::uuid, '7b3ae0c2-6526-437a-b10e-491826d197bf'::uuid, '24a5182d-ce1c-43a8-9dc0-02b0f6fc81a0'::uuid, 'fc94f78c-6120-4efc-8512-5b89f8b85298'::uuid, '2d98b2e0-3c5f-4067-9aea-3f00472342c2'::uuid, 'eda81005-1182-40fd-b486-7d1ea9a690b7'::uuid, '62dedc3d-b2f2-414b-b2bc-6c6bf57b7cda'::uuid, '432b3a21-acc8-416f-921e-541a03eb0460'::uuid, '0ea707b5-a54a-4a59-b362-95b0383c77a5'::uuid, 'cbf00545-2ab4-48ac-bcde-3b535e36e45d'::uuid, 'cbf8e005-5197-441a-ba45-5bb450b69707'::uuid, '6ee8ee78-c360-48c2-b6f5-1bf73cddaa9d'::uuid) AND ("ozu_api_segment"."visual_cinema_clip_embedding" <=> 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< 0.6)

and this is the output of EXPLAIN ANALYZE:

QUERY PLAN
Seq Scan on ozu_api_segment  (cost=0.08..9.12 rows=11 width=16) (actual time=0.497..0.638 rows=10 loops=1)
  Filter: ((id = ANY 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AND ((visual_cinema_clip_embedding <=> 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< '0.6'::double precision))
  Rows Removed by Filter: 168
Planning Time: 0.539 ms
Execution Time: 0.685 ms

If I'm reading this correctly, 10 rows are being returned and 168 are removed, and the distance query is being run on 10 + 168 = 178 rows i.e. all rows in the table. Is that correct?

[rsomani95]

This might be the solution: https://www.postgresql.org/docs/current/queries-with.html

Will try this out and share updates.