# BigGrep Rust Architecture Research Plan

## Task Overview
Design the Rust implementation architecture for BigGrep as a Cargo workspace with shared library crate and CLI binaries.

## Task Type: Architecture Design
**Focus**: System architecture and implementation planning for high-performance text processing system

## Research Objectives
1. **Rust Workspace Best Practices**
   - [ ] Cargo workspace organization patterns
   - [ ] Shared library crate design principles
   - [ ] Binary crate separation strategies
   - [ ] Dependency management in workspaces

2. **Big Data Processing Architecture**
   - [ ] Memory-mapped file processing patterns
   - [ ] Streaming and chunking strategies
   - [ ] Concurrent processing architectures
   - [ ] Performance optimization techniques

3. **N-gram Indexing Systems**
   - [ ] N-gram data structures and storage formats
   - [ ] Index building algorithms
   - [ ] Search optimization strategies
   - [ ] Memory vs speed trade-offs

4. **Rust Performance Optimization**
   - [ ] Zero-copy data structures
   - [ ] SIMD and parallel processing
   - [ ] Memory allocation strategies
   - [ ] I/O optimization patterns

## Implementation Components to Design
- [ ] 1. Workspace structure and layout
- [ ] 2. Shared library crate (`biggrep-core`) architecture
- [ ] 3. CLI binary crates: rs-bgindex, rs-bgsearch, rs-bgparse, rs-bgverify, rs-bgextractfile
- [ ] 4. N-gram index data structures
- [ ] 5. Metadata storage and retrieval systems
- [ ] 6. Performance optimization strategies
- [ ] 7. Error handling and logging patterns
- [ ] 8. Testing and benchmarking framework

## Deliverables
- [ ] Comprehensive architecture document at `docs/rust_design/rust_biggrep_design.md`
- [ ] Cargo workspace structure specification
- [ ] Data structure specifications
- [ ] Performance optimization recommendations
- [ ] Implementation roadmap

## Research Status
- [x] Phase 1: Rust workspace and performance research
- [x] Phase 2: Big data processing architecture research
- [x] Phase 3: N-gram indexing system research
- [x] Phase 4: Architecture synthesis and document creation
- [x] Phase 5: Final review and validation

### Research Findings Summary:
- **Cargo Workspace Patterns**: Discovered 5 advanced patterns for scaling large Rust codebases
- **Memory Mapping**: Found performance improvements up to 10x for big data processing
- **N-gram Systems**: Identified Elias-Fano Trie as optimal data structure with 2.6 bytes/gram compression
- **Performance Optimization**: Collected SIMD, parallel processing, and zero-copy techniques
- **Architecture Design**: Completed comprehensive design document covering all requirements

### Sources Added**:
- Advanced Cargo workspace patterns and dependency management
- Memory mapping for high-performance file processing
- tongrams-rs N-gram indexing library architecture
- Performance optimization strategies and patterns
- Rust code optimization techniques

### Final Deliverables Completed**:
- [x] Comprehensive architecture document at `docs/rust_design/rust_biggrep_design.md`
- [x] Cargo workspace structure specification
- [x] Data structure specifications (N-gram storage, index formats)
- [x] Performance optimization recommendations
- [x] Implementation roadmap with phases
- [x] Error handling and testing framework design
- [x] File processing and I/O optimization strategies
- [x] Benchmarking and profiling recommendations