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Created a comprehensive profiling framework for dtail commands (dcat, dgrep, dmap)
to analyze CPU usage and memory allocations. The framework now prints all executed
commands to stdout for full transparency.
Key features:
- Integrated Go profiling (CPU, memory, allocations) into all three commands
- Created profile.sh bash script for analyzing pprof profiles
- Added multiple Makefile targets for different profiling scenarios
- Automated profiling scripts with command echoing
- Support for different data sizes (quick, normal, full)
- Special handling for dmap MapReduce format
All profiling commands are now echoed to stdout before execution, making it
easy to understand what the framework is doing and reproduce commands manually.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
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- Create benchmark framework to measure performance of dcat, dgrep, and dmap
- Generate test files of 10MB, 100MB, and 1GB with configurable patterns
- Support benchmarking with gzip and zstd compressed files
- Implement tool-specific benchmarks:
* DCat: Simple reading, multiple files, compressed files
* DGrep: Pattern matching, regex complexity, context lines, inverted grep
* DMap: Aggregations, group by operations, complex queries, time intervals
- Track performance metrics: throughput (MB/sec), lines/sec, memory usage
- Save results in multiple formats: JSON, CSV, and Markdown reports
- Add Makefile targets: benchmark, benchmark-quick, benchmark-full
- Support environment variables for configuration (sizes, timeouts, etc.)
- Automatically clean up temporary .tmp files after benchmarks
The framework provides consistent performance testing across the DTail toolset
and enables tracking performance regressions between commits.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
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