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- Add comprehensive PGO module in internal/tools/pgo/
- Integrate PGO into dtail-tools command with full CLI support
- Add Makefile targets for PGO workflow:
- make pgo: Full PGO workflow
- make pgo-quick: Quick PGO with smaller datasets
- make pgo-generate: Generate profiles only
- make build-pgo: Build with existing profiles
- make install-pgo: Install optimized binaries
- Add convenience functions to data generator for PGO
- Document PGO workflow in CLAUDE.md
Performance improvements observed:
- DCat: 3.8-7.0% additional improvement over turbo mode
- DGrep: Up to 19% improvement for low hit rates
- DMap: Variable impact, up to 64% for min_max on large files
Benchmarks show total performance gains (pre-turbo → turbo+PGO):
- DCat: 14-21x faster
- DGrep: 9-15x faster
- DMap: 9-29% faster
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
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This commit adds comprehensive performance benchmarking comparing DTail v4.3.0
(before turbo mode) with the current implementation that has turbo boost enabled
by default.
Performance Improvements:
- DCat: 2,535% improvement (26.3x faster)
- DGrep: 1,334-1,811% improvement (14-19x faster depending on hit rate)
- DMap: 25-55% improvement for most query types
Files added:
- benchmarks/baselines/baseline_20250704_130947_turbo-enabled.txt
New baseline with turbo mode enabled for future comparisons
- doc/turbo_performance_analysis.md
Detailed technical analysis of performance improvements including
methodology, results, and implementation details
- benchmark_comparison_report.md
Summary report comparing v4.3.0 baseline with turbo-enabled baseline
The turbo mode optimizations bypass channels for direct output operations
and use direct line processing for MapReduce in server mode, resulting in
dramatic performance improvements while maintaining compatibility.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
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- Created new baseline with turbo mode enabled (default configuration)
- Added comprehensive performance analysis comparing v4.3.0 to turbo mode
- Documented significant performance improvements:
- DCat: Up to 93% faster on large files
- DGrep: Up to 93% faster with better scaling
- DMap: 27-39% improvements across all operations
- Analysis shows turbo mode is especially effective for large files
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
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- Fixed race condition in periodicTruncateCheck by using context cancellation
- Added turbo mode support to TestDCat2 server configuration
- Removed problematic wait for pending files in readCommand.Start
- Fixed potential panic when truncate channel is closed while goroutine is running
The test now properly enables turbo mode on both client and server, preventing
the timeout issues that occurred when only the client had turbo mode enabled.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
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This major refactoring replaces all bash-based profiling and benchmarking
scripts with a unified Go tool (dtail-tools) that provides:
- Better cross-platform compatibility
- Improved error handling and reliability
- Structured data generation for test files
- Consistent command-line interface
- Easier maintenance and extensibility
Key changes:
- Created dtail-tools command with profile and benchmark subcommands
- Implemented common utilities for data generation and file operations
- Updated Makefile to use the new Go-based tools
- Maintained backward compatibility with existing make targets
- Fixed ParseSize to handle single-letter suffixes (10M, 1G, etc.)
The new tool supports all previous functionality:
- profile-quick, profile-all, profile-dmap
- benchmark creation, comparison, and management
- Test data generation with multiple formats
- Profile analysis and listing
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
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Created baseline snapshot of current performance metrics for version v4.3.0.
This baseline can be used for future performance comparisons.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
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