Post Processing: Add a timeseries report generator#354
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Implements the code to:
- Parse FIO time-series data into a common intermediate format for time-series data.
- Generate a plot of the time series data:
- IOPS over time
- bandwidth over time
- latency over time
- create a timeseries report in github markdown and pdf format
A common intermediate format for time-series data is analogous to the common intemediate format for hockey-stick curves prevously implemented. It allows for a single plotter to be able to handle time-series data from sevear benchmark tools.
The code uses the existing design patterns, with different axis plotter sub-classes for each plot. This allows for adding multiple data lines to a single plot if required.
Additional unit tests have been added to cover the changed code, and to extend coverage for files that were touched
Ruff, pylint, mypy and black checks all pass on the changed files
IBM Bob v1.02 and v1.03 was used to help with these changes.
Signed-off-by: Chris Harris <harriscr@uk.ibm.com>
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Purpose of Change
This PR implements a comprehensive time-series reporting capability for the CBT (Ceph Benchmarking Tool) post-processing framework. The implementation adds the ability to parse FIO time-series data, generate time-series plots (IOPS, bandwidth, and latency over time), and create reports in both GitHub markdown and PDF formats.
Key Features
Design Approach
The implementation follows existing design patterns in the codebase:
Automated Testing
Test Files Added/Modified:
test_time_series_report_generator.py(418 lines)test_time_series_plotter.py(536 lines)test_time_series_output_formatter.py(248 lines)test_time_series_formatter.py(388 lines)test_fio_log_parser.py(294 lines)test_timestamp_aligner.py(354 lines)test_fio_benchmarks.py(947 lines)test_run_result.py(462 lines)Manual Testing
A time series report was generated from a CBT RBD FIO benchmark run:
timeseries_performance_report_260602_141547.pdf
A regression test was also run, producing a comparison report and a simple report to verify the new code still produces identical reports
Additional Notes
tools/generate_timeseries_performance_report.pyfor easy report generationrequirements.txtwith necessary dependenciesRelated Documentation
post_processing/parsers/directorypost_processing/plotter/README.md