fdc8ecb2a3
Сетевой лог сценариев, bench запросов, pg_stat_statements и EXPLAIN, aggregate исключает трассировочные повторы (O-9). Refs #202 Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
94 lines
3.4 KiB
Python
94 lines
3.4 KiB
Python
"""Агрегатор: python -m perfkit.aggregate <run_dir> -> perf/report-data/<run_id>/summary.{json,md}."""
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from __future__ import annotations
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import json
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import math
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import sys
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from pathlib import Path
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from . import REPORT_DATA_DIR
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from .results import read_all
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GROUP_KEYS = ("scenario", "target", "role", "scale", "cpu_rate")
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def _p95(sorted_vals):
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"""Nearest-rank."""
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k = math.ceil(0.95 * len(sorted_vals))
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return sorted_vals[max(k, 1) - 1]
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def _median(s):
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n = len(s)
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return s[n // 2] if n % 2 else (s[n // 2 - 1] + s[n // 2]) / 2
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def _num(v):
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return isinstance(v, (int, float)) and not isinstance(v, bool)
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def summarize(run_dir) -> dict:
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run_dir = Path(run_dir)
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groups: dict[tuple, dict] = {}
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for r in read_all(run_dir):
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key = tuple(r[k] for k in GROUP_KEYS)
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g = groups.setdefault(key, {"vals": {}, "n": 0, "incomplete_n": 0, "traced_n": 0})
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if r["metrics"].get("traced") == 1:
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# повтор под трассировкой (O-9): искажён накладными расходами trace, в статистику не входит
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g["traced_n"] += 1
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continue
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if r.get("incomplete"):
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g["incomplete_n"] += 1
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continue
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g["n"] += 1
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for m, v in r["metrics"].items():
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if m != "traced" and _num(v):
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g["vals"].setdefault(m, []).append(v)
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out = []
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for key in sorted(groups, key=lambda k: tuple(str(x) for x in k)):
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g = groups[key]
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metrics = {}
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for m, vals in sorted(g["vals"].items()):
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s = sorted(vals)
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metrics[m] = {"median": _median(s), "p95": _p95(s), "min": s[0], "max": s[-1], "n": len(s)}
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out.append({**dict(zip(GROUP_KEYS, key)), "n": g["n"], "incomplete_n": g["incomplete_n"], "traced_n": g["traced_n"], "metrics": metrics})
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return {"run_id": run_dir.name, "groups": out}
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def _fmt(x):
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return f"{x:.1f}" if isinstance(x, float) and not x.is_integer() else str(int(x)) if isinstance(x, float) else str(x)
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def render_md(summary: dict) -> str:
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lines = [f"# Summary: {summary['run_id']}", ""]
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for g in summary["groups"]:
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lines.append(f"## {g['scenario']} | target={g['target']} | role={g['role']} | scale={g['scale']} | cpu_rate={g['cpu_rate']}")
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lines.append("")
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lines.append(f"Замеров: {g['n']}, незавершённых: {g['incomplete_n']}" + (f", исключено трассировочных: {g['traced_n']}" if g.get("traced_n") else ""))
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lines.append("")
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lines.append("| metric | median | p95 | min | max | n |")
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lines.append("|---|---|---|---|---|---|")
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for m, s in g["metrics"].items():
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lines.append(f"| {m} | {_fmt(s['median'])} | {_fmt(s['p95'])} | {_fmt(s['min'])} | {_fmt(s['max'])} | {s['n']} |")
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lines.append("")
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return "\n".join(lines)
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def main(argv=None) -> int:
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argv = sys.argv[1:] if argv is None else argv
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if len(argv) != 1:
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print("usage: python -m perfkit.aggregate <run_dir>", file=sys.stderr)
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return 2
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run_dir = Path(argv[0])
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s = summarize(run_dir)
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out = REPORT_DATA_DIR / s["run_id"]
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out.mkdir(parents=True, exist_ok=True)
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(out / "summary.json").write_text(json.dumps(s, ensure_ascii=False, indent=2), encoding="utf-8")
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(out / "summary.md").write_text(render_md(s), encoding="utf-8")
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print(out)
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return 0
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if __name__ == "__main__":
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raise SystemExit(main())
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