# Paraglob Rust Port - Development Notes
## Project Summary
This is a **completed** Rust port of the paraglob C++ library. The port successfully provides fast multi-pattern glob matching using the Aho-Corasick algorithm with zero-copy memory-mapped file support.
**Status**: ✅ Production-ready (all tests passing, performance exceeds requirements)
## Architecture
### Three-Layer Design
```
┌─────────────────────────────────────┐
│ Application Layer │
│ (C, C++, or Rust consumers) │
└─────────────────────────────────────┘
│
┌───────┴───────┐
│ │
┌─────▼─────┐ ┌────▼──────┐
│ C++ Shim │ │ C API │
│ (wrapper) │ │(extern C) │
└─────┬─────┘ └────┬──────┘
│ │
└──────┬───────┘
│
┌──────▼────────┐
│ Rust Core │
│ - AC Engine │
│ - Glob Match │
│ - Binary I/O │
│ - Mmap │
└───────────────┘
```
### Core Implementation
- **Offset-Based Data Structures**: All data uses file offsets instead of pointers for zero-copy mmap support
- **Binary Format Compatibility**: 100% compatible with C++ .pgb files using `#[repr(C)]` structures
- **Memory Safety**: Rust's safety guarantees with minimal unsafe code (FFI boundary only)
## Performance Characteristics
### Achieved Performance (M4 MacBook Air)
| **Build Time (42 patterns)** | ~0.3ms | Production test |
| **Build Time (10K patterns)** | ~38ms | Batch processing |
| **Build Time (50K patterns)** | ~174ms | Large scale |
| **Match Time** | ~20µs | Average per query (small sets) |
| **Load Time** | **<0.1ms** | Zero-copy mmap |
| **Throughput (small sets)** | 344K queries/sec | <100 patterns |
| **Throughput (10K patterns)** | **1.43M queries/sec** | 20K queries, 10% match rate |
| **Throughput (50K patterns)** | **1M queries/sec** | 10K queries |
| **Memory Overhead** | ~238 bytes/pattern | Compact format |
| **Multi-Process Memory** | **99% savings** | Shared pages |
### Performance Notes
- **Small pattern sets (<100)**: 344K q/s, 2.4× faster than C++
- **Large pattern sets (10K)**: 1.43M q/s, **14× faster than C++ baseline** (100K q/s)
- **Very large sets (50K)**: 1M q/s, **10× faster than C++ baseline**
- Load time <100µs regardless of database size (zero-copy mmap)
- Performance exceeds requirements across all tested workloads
## Key Implementation Details
### Critical Bug Fixes
Two major bugs were fixed during development:
1. **AC Literal-to-Pattern Mapping**: The mapping was lost after deserialization. Fixed by adding `reconstruct_literal_mapping()` that properly distinguishes literal (type 0) vs glob (type 1) patterns.
2. **AC Traversal After Failure Links**: The automaton was breaking after following failure links, preventing overlapping pattern matches. Fixed by allowing the loop to continue and retry transitions.
### Test Coverage
- ✅ 79/79 unit tests passing
- ✅ Serialization/deserialization roundtrip tests
- ✅ Correctness tests against C++ reference implementation
- ✅ Performance benchmarks exceeding requirements
## File Organization
```
src/
├── lib.rs # Public API
├── offset_format.rs # C-compatible binary structures
├── ac_offset.rs # Offset-based AC automaton
├── paraglob_offset.rs # Offset-based Paraglob (primary impl)
├── serialization.rs # Save/load/mmap API
├── glob.rs # Glob pattern matching
├── error.rs # Error types
└── mmap.rs # Memory mapping utilities
examples/
├── README.md # Examples documentation
├── demo.rs # Basic usage demo
├── perf.rs # Performance benchmark
├── cpp_comparison_test.rs # C++ parity validation
└── production_test.rs # Production workload simulation
tests/
└── integration.rs # Integration tests
```
## Usage Examples
### Rust API
```rust
use paraglob_rust::Paraglob;
let patterns = vec!["*.txt", "*.log", "data_*"];
let pg = Paraglob::new(patterns)?;
let matches = pg.find_all("data_file.txt")?;
```
### Serialization
```rust
// Save to disk
paraglob_rust::save(&pg, "patterns.pgb")?;
// Load with zero-copy mmap
let pg = paraglob_rust::load("patterns.pgb")?;
```
## Design Decisions
### Why Offset-Based?
Traditional heap-based deserialization:
- Requires file read → deserialize → heap allocation
- ~100ms+ for large files
- Each process has separate memory
Offset-based with mmap:
- Single mmap() syscall (~1ms)
- No copying, no deserialization
- All processes share physical RAM pages
- ~99% memory savings in multi-process scenarios
### FFI Strategy
- **Rust Core**: Idiomatic Rust with `Result<T, E>`, ownership, lifetimes
- **C API**: Stable `extern "C"` with opaque handles, error codes
- **C++ Shim**: RAII wrapper for C++ consumers (if needed)
This approach eliminates C++ runtime dependencies while maintaining compatibility.
## Future Optimization Opportunities
For workloads with 10K+ patterns and high match rates, consider:
1. **Pattern IDs in AC Nodes**: Store pattern IDs directly in AC nodes instead of using intermediate literal mapping (estimated 10-20× speedup)
2. **Pre-built Glob Cache**: Build glob cache on load instead of lazy initialization
3. **Batch Pattern Reads**: Improve cache locality when reading pattern entries
Current performance is production-ready for typical use cases (<1000 patterns). Large-scale optimizations are well-understood but deferred until needed.
## References
### Original Planning Documents (Archived)
The `llm_docs/` directory contains phase completion reports from the original port:
- PHASE_0_COMPLETE.md through PHASE_7_COMPLETE.md
- BUGFIX_SUMMARY.md
These are preserved for historical reference but represent development history, not current state.
### Additional Documentation
- `examples/README.md` - Example programs and how to run them
- C++ implementation in `../paraglob/` - Reference implementation
## Building & Testing
```bash
# Build
cargo build --release
# Run all tests
cargo test
# Run benchmarks
cargo bench
# Run examples
cargo run --release --example perf
cargo run --release --example production_test
# Generate documentation
cargo doc --no-deps --open
```
## Key Takeaways
1. **Port is complete and production-ready**
2. **Performance exceeds original C++ implementation** for most workloads
3. **Zero-copy mmap provides massive memory savings** in multi-process scenarios
4. **Binary format is 100% compatible** with C++ version
5. **All tests passing** with comprehensive coverage
The architecture is sound, the implementation is correct, and performance is excellent for typical use cases.