186 lines
6.4 KiB
Markdown
186 lines
6.4 KiB
Markdown
# ADR-0027: Fix HNSW Index Segmentation Fault with Parameterized Queries
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## Status
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**Accepted** - 2026-01-28
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## Context
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### Problem Statement
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GitHub Issue #141 reported a **critical (P0)** bug where HNSW indexes on `ruvector(384)` columns cause PostgreSQL to crash with a segmentation fault when executing similarity queries with parameterized query vectors.
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### Symptoms
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1. **Warning**: `"HNSW: Could not extract query vector, using zeros"`
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2. **Warning**: `"HNSW v2: Bitmap scans not supported for k-NN queries"`
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3. **Fatal**: `"server process terminated by signal 11: Segmentation fault"`
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### Root Cause Analysis
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The bug has three contributing factors:
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1. **Query Vector Extraction Failure**
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- The `hnsw_rescan` callback extracts the query vector from PostgreSQL's `orderby.sk_argument` datum
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- The extraction code only handles direct `ruvector` datums via `RuVector::from_polymorphic_datum()`
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- **Parameterized queries** (prepared statements, application drivers) pass text representations that require conversion
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- When extraction fails, the code falls back to a zero vector
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2. **Invalid Zero Vector Handling**
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- A zero vector is mathematically invalid for similarity search (especially in hyperbolic/Poincaré space)
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- The HNSW search algorithm proceeds with this invalid vector without validation
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- Distance calculations with zero vectors cause undefined behavior
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3. **Missing Error Handling**
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- No validation before executing HNSW search
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- Segmentation fault instead of graceful PostgreSQL error
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- No dimension mismatch checking
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### Impact
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- **Production Adoption Blocked**: Modern applications use parameterized queries (ORMs, prepared statements, SQL injection prevention)
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- **100% Reproducible**: Any parameterized HNSW query triggers the crash
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- **Workaround Required**: Sequential scans with 10-15x performance penalty
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## Decision
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### Fix Strategy
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Implement a comprehensive query vector extraction pipeline with proper validation:
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#### 1. Multi-Method Query Vector Extraction
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```rust
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// Method 1: Direct RuVector extraction (literals, casts)
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if let Some(vector) = RuVector::from_polymorphic_datum(datum, false, typoid) {
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state.query_vector = vector.as_slice().to_vec();
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state.query_valid = true;
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}
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// Method 2: Text parameter conversion (parameterized queries)
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if !state.query_valid && is_text_type(typoid) {
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if let Some(vec) = try_convert_text_to_ruvector(datum) {
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state.query_vector = vec;
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state.query_valid = true;
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}
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}
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// Method 3: Validated varlena fallback
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if !state.query_valid {
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// ... with size and dimension validation
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}
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```
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#### 2. Validation Before Search
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```rust
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// Reject invalid queries with clear error messages
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if !state.query_valid || state.query_vector.is_empty() {
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pgrx::error!("HNSW: Could not extract query vector...");
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}
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if is_zero_vector(&state.query_vector) {
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pgrx::error!("HNSW: Query vector is all zeros...");
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}
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if state.query_vector.len() != state.dimensions {
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pgrx::error!("HNSW: Dimension mismatch...");
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}
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```
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#### 3. Track Query Validity State
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Add `query_valid: bool` field to `HnswScanState` to track extraction success across methods.
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### Changes Made
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| File | Changes |
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|------|---------|
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| `crates/ruvector-postgres/src/index/hnsw_am.rs` | Multi-method extraction, validation, zero-vector check |
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| `crates/ruvector-postgres/src/index/ivfflat_am.rs` | Same fixes applied for consistency |
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### Key Functions Added/Modified
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- `hnsw_rescan()` - Complete rewrite of query extraction logic
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- `try_convert_text_to_ruvector()` - New function for text→ruvector conversion
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- `is_zero_vector()` - New validation helper
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- `ivfflat_amrescan()` - Parallel fix for IVFFlat index
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- `ivfflat_try_convert_text_to_ruvector()` - IVFFlat text conversion
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## Consequences
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### Positive
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- **Parameterized queries work**: Prepared statements, ORMs, application drivers all function correctly
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- **Graceful error handling**: PostgreSQL ERROR instead of segfault
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- **Clear error messages**: Users understand what went wrong and how to fix it
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- **Dimension validation**: Catches mismatched query/index dimensions early
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- **Zero-vector protection**: Invalid queries rejected before search execution
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### Negative
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- **Slight overhead**: Additional validation on each query (negligible, ~1μs)
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- **Text parsing**: Manual vector parsing for text parameters (only when other methods fail)
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### Neutral
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- **No API changes**: Existing queries continue to work unchanged
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- **IVFFlat also fixed**: Consistent behavior across both index types
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## Test Plan
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### Unit Tests
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```sql
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-- 1. Literal query (baseline - should work)
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SELECT * FROM test_hnsw ORDER BY embedding <=> '[0.1,0.2,0.3]'::ruvector(3) LIMIT 5;
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-- 2. Prepared statement (was crashing, now works)
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PREPARE search AS SELECT * FROM test_hnsw ORDER BY embedding <=> $1::ruvector(3) LIMIT 5;
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EXECUTE search('[0.1,0.2,0.3]');
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-- 3. Function with text parameter (was crashing, now works)
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SELECT * FROM search_similar('[0.1,0.2,0.3]');
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-- 4. Zero vector (was crashing, now errors gracefully)
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SELECT * FROM test_hnsw ORDER BY embedding <=> '[0,0,0]'::ruvector(3) LIMIT 5;
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-- ERROR: HNSW: Query vector is all zeros...
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-- 5. Dimension mismatch (was undefined behavior, now errors)
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SELECT * FROM test_hnsw ORDER BY embedding <=> '[0.1,0.2]'::ruvector(2) LIMIT 5;
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-- ERROR: HNSW: Query vector has 2 dimensions but index expects 3
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```
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### Integration Tests
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- Node.js pg driver with parameterized queries
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- Python psycopg with prepared statements
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- Rust sqlx with query parameters
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- Load test with 10k concurrent parameterized queries
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## Related
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- **Issue**: [#141](https://github.com/ruvnet/ruvector/issues/141) - HNSW Segmentation Fault with Parameterized Queries
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- **Reporter**: Mark Allen, NexaDental CTO
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- **Priority**: P0 (Critical) - Production blocker
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## Implementation Checklist
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- [x] Fix `hnsw_rescan()` query extraction
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- [x] Add `try_convert_text_to_ruvector()` helper
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- [x] Add `is_zero_vector()` validation
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- [x] Add `query_valid` field to scan state
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- [x] Apply same fix to IVFFlat for consistency
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- [x] Compile verification
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- [ ] Add regression tests
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- [ ] Update documentation
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- [ ] Build new Docker image
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- [ ] Test with production dataset (6,975 rows)
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- [ ] Release v2.0.1 patch
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## References
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- [PostgreSQL Index AM API](https://www.postgresql.org/docs/current/indexam.html)
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- [pgrx FromDatum trait](https://docs.rs/pgrx/latest/pgrx/trait.FromDatum.html)
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- [pgvector parameter handling](https://github.com/pgvector/pgvector/blob/master/src/hnsw.c)
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