tidaldb/tidal/docs/planning/milestone-5/phase-2/OVERVIEW.md

m5p2: Hybrid Fusion (RRF)

Delivers

Reciprocal Rank Fusion combining BM25 ranked lists with ANN ranked lists into a single scored result set. The starting point is RRF with k=60; the architecture supports upgrading to tuned linear combination when relevance labels exist. Handles the three retrieval modes: text-only, vector-only, and hybrid. A RetrievalMode enum and route_results() function encapsulate the decision logic that the m5p3 SearchExecutor will call.

Dependencies

• m5p1 COMPLETE: TextIndex, AllScoresCollector, TextQueryParser — BM25 search that returns Vec<(EntityId, f32)>
• m2p1 COMPLETE: VectorIndex trait, VectorSearchResult { id: VectorId, distance: f32 }, EmbeddingSlotRegistry — ANN search

Research References

• docs/research/tantivy.md — Section "Start with Reciprocal Rank Fusion": RRF formula, k=60, Cormack et al. SIGIR 2009, production system comparison, upgrade path to linear combination

Acceptance Criteria (Phase Level)

• HybridFusion struct with k: u32 field (default 60) in tidal/src/query/fusion.rs
• HybridFusion::fuse(bm25_results: &[(EntityId, f32)], ann_results: &[(EntityId, f32)], k: u32) -> Vec<(EntityId, f64)> implements RRF
• RRF formula: score(d) = 1.0 / (k + rank_bm25(d)) + 1.0 / (k + rank_ann(d)), ranks are 1-based (rank 1 = best)
• Documents in only one list contribute only their single-list term; the missing-list term is zero
• Results sorted descending by fused score
• RetrievalMode enum: TextOnly, VectorOnly, Hybrid
• RetrievalMode::determine(has_text: bool, has_vector: bool) -> Option<RetrievalMode> returns the correct mode
• route_results() converts single-mode results to Vec<(EntityId, f64)> and calls HybridFusion::fuse() for hybrid
• Pure BM25 path: results passed through as Vec<(EntityId, f64)> without fusion overhead
• Pure ANN path: VectorSearchResult list converted to Vec<(EntityId, f64)> (score = 1.0 / (k + rank))
• k parameter configurable; default 60
• Fusion adds < 1ms to query time for 1000 candidates from each list (Criterion benchmarked)
• Property test: for any pair of ranked lists, RRF output is the union of both input document sets; scores computed correctly to 6 decimal places

Task Execution Order

task-01 (RRF Implementation)
    |
    v
task-02 (Retrieval Mode Router)

Both tasks are sequential. Task 02 depends on HybridFusion from Task 01.

Module Location

New module: tidal/src/query/fusion.rs

• HybridFusion — RRF computation struct
• RetrievalMode — enum for text-only / vector-only / hybrid
• route_results() — routes pre-retrieved result lists through the appropriate path

Add pub mod fusion; to tidal/src/query/mod.rs.

Notes

• RRF uses rank position only — the input f32 scores are used only for ordering, not for the fusion formula itself
• BM25 results: (EntityId, f32) where higher score = better → sort descending, rank 1 = index 0
• ANN results: VectorSearchResult { id, distance } where lower distance = better → sort ascending, rank 1 = index 0
• For the ANN-only path, convert VectorSearchResult { id, distance } to (EntityId, score) where score = 1.0 / (k + rank) to produce a consistent f64 output
• The rrf crate exists on crates.io but we implement from scratch to avoid a dependency and maintain full control over the algorithm
• No unsafe code — pure indexing arithmetic