8e9f53a478
- perf/analysis: разбор trace (timeline_breakdown), CPU-профилей с source maps (cpuprofile_top), heap snapshots (heapdiff), циклов памяти, сравнения масштабов, ручной EXPLAIN вложенных запросов (explain_manual), API против X-DB-Time-Ms (api_split), сводка горячих точек; тесты ядра в perf/tests/test_analysis.py - perf/e2e/scenarios/hotspots.spec.ts: CPU-профиль, рендеры React, мутации DOM после фильтра, рост CSS-правил по циклам (вне run-all) - prod-сборка с source maps: PERF_SOURCEMAP=1, perf/stand.sh web-sourcemap (:8082) - perf/report-data/20261026-s1, 20261026-s2 (summary, sql, analysis, explain-manual), t5-types (иллюстрация CPU 6x) - design.md: решения T10b без обсуждения Refs #202 Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
135 lines
8.2 KiB
Python
135 lines
8.2 KiB
Python
"""Сравнение масштабов 1 и 2: скролл, фильтры, модалки (summary.json) и время ответа API по листам (api.jsonl).
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cd perf && .venv/bin/python analysis/scale_compare.py --s1 20261026-s1 --s2 20261026-s2 \
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--out report-data/20261026-s2/analysis
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Масштаб 2 снят с 1 повтором (R-4): отношение s2/s1 - оценка роста с объёмом, не точная цифра.
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Скролл: роли rf (листы, отчёты проектов) и dfip (своды); модалки - все роли. API: медиана по каждому URL; form_id
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различаются между масштабами, поэтому URL листа сводится к `<form_type>/<sheet>` по манифесту масштаба.
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Вывод: <out>/scale-compare.json и scale-compare.md.
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"""
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from __future__ import annotations
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import argparse
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import json
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import re
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import statistics
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from collections import defaultdict
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from pathlib import Path
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PERF = Path(__file__).resolve().parents[1]
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def groups(run: str) -> dict:
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d = json.loads((PERF / "report-data" / run / "summary.json").read_text())
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return {(g["scenario"], g["target"], g["role"], g["cpu_rate"]): g for g in d["groups"]}
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def med(g, k):
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m = g["metrics"].get(k) if g else None
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return m["median"] if m else None
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def api_by_sheet(run: str, scale: int) -> dict:
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man = json.loads((PERF / "report-data" / run / f"manifest-s{scale}.json").read_text())
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ft = {s["form_id"]: s["form_type"] for s in man["sheets"]}
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vals, size = defaultdict(list), {}
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for line in (PERF / "results" / run / "api.jsonl").read_text().splitlines():
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r = json.loads(line)
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path = re.sub(r"^https?://[^/]+", "", r["url"])
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m = re.match(r"/api/v1/form/(\d+)/sheet/(\w+)", path)
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if m:
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key = f"GET лист {ft.get(int(m.group(1)), '?')}/{m.group(2)}"
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elif re.match(r"/api/v1/svod/2/(\w+)/", path):
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key = "GET свод 2 " + re.match(r"/api/v1/svod/2/(\w+)/", path).group(1)
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elif re.match(r"/api/v1/svod/1/(\w+)/", path):
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key = "GET свод 1 " + re.match(r"/api/v1/svod/1/(\w+)/", path).group(1)
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elif "plan-summary" in path:
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key = "GET сводные проектов"
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elif re.match(r"/api/v1/projects/\d+/report/\d+/(\w+)", path):
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key = "GET отчёт проекта " + re.match(r"/api/v1/projects/\d+/report/\d+/(\w+)", path).group(1)
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else:
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continue
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k = (key, r["role"])
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vals[k].append(r["metrics"]["ms"])
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size[k] = max(size.get(k, 0), r["metrics"].get("bytes") or 0)
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return {k: (statistics.median(v), size[k], len(v)) for k, v in vals.items()}
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def main(argv=None):
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ap = argparse.ArgumentParser()
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ap.add_argument("--s1", required=True)
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ap.add_argument("--s2", required=True)
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ap.add_argument("--out", required=True)
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a = ap.parse_args(argv)
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out = Path(a.out)
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out.mkdir(parents=True, exist_ok=True)
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g1, g2 = groups(a.s1), groups(a.s2)
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m1 = json.loads((PERF / "report-data" / a.s1 / "manifest-s1.json").read_text())
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m2 = json.loads((PERF / "report-data" / a.s2 / "manifest-s2.json").read_text())
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rows1 = {f"{s['form_type']}/{s['sheet']}/{s['direction'] or 'null'}": s["rows"] for s in m1["sheets"] if s.get("owner", "rf") == "rf"}
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rows2 = {f"{s['form_type']}/{s['sheet']}/{s['direction'] or 'null'}": s["rows"] for s in m2["sheets"] if s.get("owner", "rf") == "rf"}
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res = {"scroll": [], "modal": [], "api": []}
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for key, a1 in sorted(g1.items()):
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sc, target, role, cpu = key
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if cpu != 1 or sc not in ("scroll", "modal"):
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continue
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if sc == "scroll" and not ((role == "rf" and not target.startswith("svod/")) or (role == "dfip" and target.startswith("svod/"))):
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continue
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b = g2.get(key)
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if sc == "scroll":
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base = target.split("@")[0]
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r = {"target": target, "role": role, "rows_s1": rows1.get(base), "rows_s2": rows2.get(base),
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"mt_per_step_s1": med(a1, "main_thread_ms_per_step"), "mt_per_step_s2": med(b, "main_thread_ms_per_step"),
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"mt_s1": med(a1, "main_thread_ms"), "mt_s2": med(b, "main_thread_ms"),
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"mb_s1": (med(a1, "json_bytes_sheet") or 0) / 1e6, "mb_s2": (med(b, "json_bytes_sheet") or 0) / 1e6,
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"n_s1": a1["n"], "n_s2": b["n"] if b else 0, "inc_s2": b["incomplete_n"] if b else None}
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res["scroll"].append(r)
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else:
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res["modal"].append({"target": target, "role": role, "ms_s1": med(a1, "click_to_visible_ms"), "ms_s2": med(b, "click_to_visible_ms"),
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"mt_s1": med(a1, "main_thread_ms"), "mt_s2": med(b, "main_thread_ms")})
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a1, a2 = api_by_sheet(a.s1, 1), api_by_sheet(a.s2, 2)
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for k in sorted(a1, key=lambda k: -a1[k][0]):
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if k in a2:
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res["api"].append({"endpoint": k[0], "role": k[1], "ms_s1": round(a1[k][0], 1), "ms_s2": round(a2[k][0], 1),
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"mb_s1": round(a1[k][1] / 1e6, 2), "mb_s2": round(a2[k][1] / 1e6, 2)})
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# незавершённые записи s2 (scroll_incomplete: упёрлись в PERF_MAX_STEPS) в summary не входят - берём из сырого jsonl
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res["incomplete_s2"] = []
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for line in (PERF / "results" / a.s2 / "scroll.jsonl").read_text().splitlines():
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r = json.loads(line)
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if r.get("incomplete") and r.get("skip_reason") == "scroll_incomplete":
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m = r["metrics"]
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res["incomplete_s2"].append({"target": r["target"], "role": r["role"], "steps": m.get("steps"),
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"mt_per_step": round(m.get("main_thread_ms_per_step", 0), 1),
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"duration_s": round(m.get("duration_ms", 0) / 1000), "mb": round(m.get("json_bytes_sheet", 0) / 1e6, 2)})
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(out / "scale-compare.json").write_text(json.dumps(res, ensure_ascii=False, indent=1))
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def ratio(x, y):
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return f"{y / x:.2f}" if x and y else "—"
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def f(x, nd=1):
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return "—" if x is None else f"{x:.{nd}f}"
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md = [f"# Масштаб 1 ({a.s1}) против масштаба 2 ({a.s2}, 1 повтор - оценка)", "",
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"## Скролл: main thread на шаг колеса 200 px, мс (медиана; s2 - один замер)", "",
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"| target | роль | строк s1 → s2 | мс/шаг s1 | мс/шаг s2 | × | main thread s1, мс | s2, мс | ответ s1 → s2, МБ |", "|---|---|---|---|---|---|---|---|---|"]
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for r in res["scroll"]:
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inc = " (s2 incomplete)" if r["inc_s2"] else ""
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md.append(f"| {r['target']} | {r['role']} | {r['rows_s1'] or ''} → {r['rows_s2'] or ''} | {f(r['mt_per_step_s1'])} | {f(r['mt_per_step_s2'])}{inc} | "
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f"{ratio(r['mt_per_step_s1'], r['mt_per_step_s2'])} | {f(r['mt_s1'], 0)} | {f(r['mt_s2'], 0)} | {r['mb_s1']:.2f} → {r['mb_s2']:.2f} |")
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md += ["", "Незавершённые на s2 (скролл упёрся в PERF_MAX_STEPS=5000 шагов вперёд, обратного прохода нет; в summary не входят):", ""]
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md += [f"- {r['target']} {r['role']}: {r['steps']} шагов, {r['mt_per_step']} мс/шаг, {r['duration_s']} с, ответ {r['mb']} МБ" for r in res["incomplete_s2"]]
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md += ["", "## Модалки: клик → кадр с модалкой, мс (медиана)", "", "| модалка | роль | s1 | s2 | × | main thread s1 | s2 |", "|---|---|---|---|---|---|---|"]
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for r in res["modal"]:
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md.append(f"| {r['target']} | {r['role']} | {f(r['ms_s1'], 0)} | {f(r['ms_s2'], 0)} | {ratio(r['ms_s1'], r['ms_s2'])} | {f(r['mt_s1'], 0)} | {f(r['mt_s2'], 0)} |")
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md += ["", "## API (bench, медиана 20 повторов по каждому URL; размер - распакованный ответ)", "",
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"| запрос | роль | s1, мс | s2, мс | × | s1, МБ | s2, МБ |", "|---|---|---|---|---|---|---|"]
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for r in res["api"]:
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md.append(f"| {r['endpoint']} | {r['role']} | {r['ms_s1']} | {r['ms_s2']} | {ratio(r['ms_s1'], r['ms_s2'])} | {r['mb_s1']} | {r['mb_s2']} |")
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(out / "scale-compare.md").write_text("\n".join(md) + "\n")
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print("\n".join(md))
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if __name__ == "__main__":
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main()
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