Expand description
HNSW Neighborhood Search Algorithms
This module implements the core k-nearest neighbor (k-NN) search functionality for HNSW, including dynamic candidate lists, greedy search, and layer-by-layer navigation. These algorithms provide the search performance that makes HNSW efficient and scalable.
§Architecture
- Search Candidate: Dynamic candidate list with priority ordering
- Greedy Search: Local search within individual layers
- Layer Navigation: Multi-level search with entry point optimization
- Distance Computation: Efficient distance-based candidate selection
§Performance Characteristics
- Time Complexity: O(log N) average case for k-NN search
- Memory Usage: O(ef) candidate list size during search
- Deterministic: Predictable search results with stable sorting
- Scalable: Efficient for both small and large result sets
Structs§
- Neighborhood
Search - HNSW neighborhood search algorithms
- Search
Metrics - Search performance metrics
- Search
Result - Search result containing nearest neighbors