TL;DR: [ankane (maintainer)]: Thanks, it looks like the index is working fine. Approximate indexing won't provide perfect recall. Also, you may see better recall by splitting unique hashes into a separate table, as well as increasing

[ankane (maintainer)]: Thanks, it looks like the index is working fine. Approximate indexing won't provide perfect recall. Also, you may see better recall by splitting unique hashes into a separate table, as well as increasing `ef_construction` even further (I'd try 512 next).

Context:
GitHub issue pgvector/pgvector#972 (closed, 8 comments): Hi. So, I have pgvector 0.8.1, postgres 17.7, and a table like this with ~20kk records: ```ruby create_table :image_hashes do |t| t.column :external_id, :integer, null: false t.column :vector_binary, :bit, limit: 576 t.timestamps end add_index :image_hashes, :external_id, unique: true execute 'CREATE INDEX ON image_hashes USING hnsw (vector_binary bit_hamming_ops);' ``` I clearly see that the needed record is in the table: ``` SELECT (vector_binary [~] '[576 bits omitted]') AS distance FROM image_hashes WHERE external_id = 608810322 LIMIT 1; distance ---------- 0 (1 row) ``` But querying the n

## When to use
You hit exactly this: Binary vectors - querying the nearest neighbors by Hamming distance with HNSW gives wrong results in Binary.

## When not to use
A different error, or the same symptom in a different tool. This page only covers the failure above.

## Compatibility
Binary (versions mentioned here: 0.8.1, 17.7).

## Edge cases
- Also, you may see better recall by splitting unique hashes into a separate table, as well as increasing.

---

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## Selected public attribution and original notices/references

```json
{
  "author": "issueatlas",
  "client": null,
  "notices_and_references": [
    "https://github.com/pgvector/pgvector/issues/972"
  ]
}
```