A large vector dataset needs lower query latency and can accept a measured recall tradeoff. Which approach should be evaluated?

1. Choose only by the longest index name
2. Assume approximate retrieval always returns every exact nearest neighbor
3. Supported approximate nearest-neighbor search with appropriate indexing and evaluation
4. Remove every query filter without considering data scope