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Updated binary vectors section [skip ci]

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Andrew Kane
2024-04-03 23:36:43 -07:00
parent 61e803a4dc
commit 7e5df3c9fe
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README.md
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@@ -421,9 +421,7 @@ CREATE TABLE items (embedding vector(3), category_id int) PARTITION BY LIST(cate
## Binary Vectors ## Binary Vectors
*Unreleased* Use the `bit` type to store binary vectors ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/hash_image_search.py))
Use the `bit` type to store binary vectors
```sql ```sql
CREATE TABLE items (id bigserial PRIMARY KEY, embedding bit(3)); CREATE TABLE items (id bigserial PRIMARY KEY, embedding bit(3));
@@ -432,6 +430,12 @@ INSERT INTO items (embedding) VALUES ('000'), ('111');
Get the nearest neighbors by Hamming distance Get the nearest neighbors by Hamming distance
```sql
SELECT * FROM items ORDER BY bit_count(embedding # '101') LIMIT 5;
```
Or (unreleased)
```sql ```sql
SELECT * FROM items ORDER BY embedding <~> '101' LIMIT 5; SELECT * FROM items ORDER BY embedding <~> '101' LIMIT 5;
``` ```
@@ -678,18 +682,6 @@ and query with:
SELECT * FROM items ORDER BY embedding::vector(3) <-> '[3,1,2]' LIMIT 5; SELECT * FROM items ORDER BY embedding::vector(3) <-> '[3,1,2]' LIMIT 5;
``` ```
#### Are binary vectors supported?
You can store binary vectors and perform exact nearest neighbor search by Hamming distance in Postgres without an extension ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/hash_image_search.py)).
```tsql
CREATE TABLE items (id bigserial PRIMARY KEY, embedding bit(3));
INSERT INTO items (embedding) VALUES ('000'), ('111');
SELECT * FROM items ORDER BY bit_count(embedding # '101') LIMIT 5;
```
Indexing is not currently supported.
#### Do indexes need to fit into memory? #### Do indexes need to fit into memory?
No, but like other index types, you’ll likely see better performance if they do. You can get the size of an index with: No, but like other index types, you’ll likely see better performance if they do. You can get the size of an index with: