DOC-009: Performance Tuning Guide

[ajitpratap0]

Summary

Create comprehensive performance tuning guide with profiling walkthroughs, optimization techniques, and benchmark-driven optimization.

Problem

Performance docs mention pooling but lack detailed tuning guidance for production workloads.

Action Items

Create PERFORMANCE_TUNING.md with:

1. Profiling Walkthrough

   • CPU profiling with pprof
   • Memory profiling
   • Interpreting profiles
   • Finding bottlenecks

2. Memory Optimization

   • Object pool configuration
   • Pool hit rate optimization
   • Memory leak detection
   • GC tuning considerations

3. Concurrent Processing Patterns

   • Worker pool patterns
   • Batch processing
   • Scaling to multiple cores
   • Load balancing

4. Caching Strategies

   • AST caching for repeated queries
   • Token caching
   • Query result caching

5. Benchmark-Driven Optimization

   • Writing effective benchmarks
   • Comparing alternatives
   • Regression detection
   • Performance budgets

6. Pool Configuration

   • Pool sizing
   • Hit rate optimization
   • Reuse patterns

7. Input Size Considerations

   • Small vs large queries
   • Batch processing
   • Streaming for large files

Acceptance Criteria

• Comprehensive tuning guide with code examples
• Profiling examples with pprof screenshots
• Before/after benchmarks showing improvements
• Trade-off analysis for different optimizations
• Production deployment checklist

Technical Details

Priority: Medium
Effort: Small (16h)
Phase: Phase 3 - UX & Documentation
Dependencies: None

Related

Supports production claim: "1.38M+ operations/second sustained"