feat: performance optimizations for go-batcher

[mrz1836]

Summary

This PR introduces comprehensive performance optimizations and enhancements to the go-batcher library. Rather than adding separate optimized implementations, these improvements have been integrated directly into the core codebase, maintaining full backward compatibility while significantly improving performance.

🚀 Key Improvements

Enhanced Core Functionality

• Improved batching logic with better memory management and reduced allocations
• Enhanced deduplication performance with optimized data structures and algorithms
• Better concurrent processing with refined worker management
• Comprehensive test coverage with extensive benchmarking and edge case validation

Performance Optimizations

• Reduced memory allocations through better object reuse patterns
• Faster lookup operations with optimized data structure access patterns
• Improved batch processing efficiency with streamlined execution paths
• Enhanced deduplication speed using more efficient algorithms

Code Quality Enhancements

• Comprehensive benchmarking suite for performance validation
• Extensive integration testing covering real-world usage scenarios
• Enhanced error handling and edge case coverage
• Improved code documentation and maintainability

📊 Performance Impact

Based on comprehensive benchmarking, the optimizations deliver:

• Significant reduction in memory allocations during batch processing
• Improved throughput for high-volume data processing scenarios
• Better performance consistency under concurrent load
• Enhanced deduplication efficiency for datasets with varying duplicate rates

🔧 Technical Changes

Modified Files

• batcher.go - Core batching logic improvements and optimizations
• batcher_deduplication.go - Enhanced deduplication algorithms and data structures
• batcher_test.go - Expanded test coverage with additional edge cases
• batcher_deduplication_test.go - Comprehensive deduplication testing
• batcher_integration_test.go - Real-world usage scenario validation
• batcher_comprehensive_benchmark_test.go - Performance benchmarking suite
• benchmark_comparison_test.go - Comparative performance analysis
• README.md - Updated documentation reflecting improvements

Removed Files

• Cleaned up experimental optimization files that were consolidated into main codebase
• Removed temporary analysis and planning documents

✅ Validation

• All existing tests pass - Full backward compatibility maintained
• New benchmarks validate performance gains - Measurable improvements across key metrics
• Integration tests confirm real-world benefits - Tested under realistic usage patterns
• Code quality checks pass - Linting, formatting, and best practices verified

Usage

The improvements are completely transparent to existing users:

// Existing code continues to work exactly as before
batcher := batcher.New[Item](100, time.Second, processFn, false)

// All existing methods work with improved performance
batcher.Put(item)
batcher.TriggerBatch()

Impact

This upgrade provides immediate performance benefits for all users without requiring any code changes. The optimizations are particularly beneficial for:

• High-throughput batch processing scenarios
• Applications with significant duplicate data
• Memory-constrained environments
• Concurrent processing workloads

All improvements maintain the library's simple, reliable API while delivering measurably better performance.

[codecov]

Codecov Report

❌ Patch coverage is 97.46835% with 6 lines in your changes missing coverage. Please review.

Files with missing lines	Patch %	Lines
batcher_deduplication.go	97.20%	4 Missing and 1 partial ⚠️
batcher.go	98.27%	1 Missing ⚠️

📢 Thoughts on this report? Let us know!

[Copilot]

Pull Request Overview

This PR introduces comprehensive performance optimizations for the go-batcher library, implementing several key improvements while maintaining 100% backward compatibility. The optimizations focus on reducing memory allocations, improving deduplication performance, and enhancing throughput for high-concurrency scenarios.

• Timer reuse pattern to eliminate allocations in worker loops (70-80% fewer allocations)
• Non-blocking channel operations and sync.Pool for batch slice reuse (up to 90% reduction in memory allocations)
• Bloom filter-based deduplication and optimized search patterns for recent items (20-60% performance improvements)

Reviewed Changes

Copilot reviewed 7 out of 7 changed files in this pull request and generated 5 comments.

Show a summary per file

File	Description
plan.md	Implementation strategy and optimization plan documentation
performance_comparison_report.md	Comprehensive performance analysis with benchmark results
dedup_optimized.go	Optimized deduplication with bloom filter and reverse bucket search
benchmark_comparison_test.go	Side-by-side performance comparison benchmarks
batcher_optimized_test.go	Extensive test suite for optimized implementations
batcher_optimized.go	Core optimized implementations with timer reuse and pooling
batcher_integration_test.go	Integration tests for combined optimizations

Comments suppressed due to low confidence (2)

benchmark_comparison_test.go:316

• The BenchmarkSummary function is skipped and only prints information. Consider implementing actual benchmark validation or remove this function to avoid confusion.

	b.Log("\n=== BENCHMARK COMPARISON SUMMARY ===")

[sonarqubecloud]

Quality Gate passed

Issues
10 New issues
0 Accepted issues

Measures
0 Security Hotspots
0.0% Coverage on New Code
2.4% Duplication on New Code

See analysis details on SonarQube Cloud