Proposal: Introducing FastExcel Benchmark Performance Testing Module

Background & Project Positioning

FastExcel is positioned as a high-performance Java tool for Excel file processing, with core value propositions:

• High Performance: Significantly reduced memory consumption compared to traditional Excel processing libraries
• Stream Operations: Memory-friendly processing for large-scale data (millions of rows)
• Simplicity: Intuitive API design for easy integration

However, as the project evolves and user base grows, we face several challenges:

1. Lack of Quantified Performance Validation: While we claim FastExcel outperforms traditional libraries (e.g., Apache POI), we lack systematic benchmark data to support these claims
2. Increasing Regression Risk: Each code change may impact performance, but we currently lack automated performance monitoring mechanisms
3. Insufficient User Scenario Coverage: Cannot ensure performance across various data scales and usage scenarios
4. Difficult Competitive Assessment: Lack of objective performance comparison data with similar products

Necessity of Benchmark Module

1. Validate Core Value Proposition

• Verify FastExcel's performance advantages over Apache POI through scientific microbenchmarks
• Provide quantified memory efficiency data to support "significantly reduced memory consumption" claims
• Establish performance baselines to provide users with reliable performance expectations

2. Ensure Development Quality

• Provide data-driven decision support for code optimization
• Establish historical tracking of performance evolution
• Enable systematic performance analysis across different scenarios

3. Enhance User Confidence

• Provide transparent performance test reports to build user trust
• Offer objective performance comparison data for user selection decisions
• Demonstrate best practices and performance across different scenarios

Technical Solution Design

Key Test Scenario Design

1. Microbenchmarks

   • Data converter performance
   • Event processing chain efficiency
   • Memory allocation pattern analysis

2. Large Data Scenario Testing

   Data Scale: SMALL(1K) → MEDIUM(10K) → LARGE(100K) → EXTRA_LARGE(1M+)
   File Formats: XLSX, XLS, CSV
   Operation Types: Read, Write, Fill, Streaming
   

3. Memory Efficiency Specialized Testing

   • Streaming read memory usage patterns
   • Bulk write memory growth curves
   • GC pressure analysis

4. Comparative Benchmarks

   • FastExcel vs Apache POI performance comparison
   • Memory usage efficiency comparison
   • Performance across different data scales

Implementation Status

The benchmark module has been fully implemented with the following components:

• JMH Integration: Complete Maven configuration with JMH dependencies
• Comprehensive Test Suites: Comparison benchmarks, memory efficiency tests, streaming benchmarks
• Automated Execution: Multi-profile support with configurable dataset sizes
• Advanced Features: Interactive CLI, memory profiling, reports