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148 lines
5.0 KiB
Python
148 lines
5.0 KiB
Python
# -*- coding: utf-8 -*-
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r'''塌陷窗口分析器：专门看"连接总数 <= 3"的那些窗口里发生了什么。
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== 为什么需要专门看窗口 ==
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总体中位数两次都会被稳态主导（都是 61 秒 / 1.2 秒），区分不出 A/B 好坏。
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真正的差别只在 QUIC 塌陷的那几分钟里体现：
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A 组 quic8+h2 2：塌陷时只剩 2 条在扛
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B 组 quic6+h2 4：塌陷时还有 4 条
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所以核心指标是：
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* 「连接总数 <= 3」的采样占比（= 风险暴露时间）
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* 这些窗口里公网可用率
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用法:
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python _build/rp_collapse.py <标签> <conns文件> <health文件>
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'''
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from __future__ import annotations
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import sys
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from datetime import datetime
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from pathlib import Path
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# 塌陷判定：总连接数 <= 这个值就算"容量很薄"
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COLLAPSE_TOTAL = 3
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def parse_ts(path: str, cols: int):
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rows = []
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for line in Path(path).read_text(encoding="utf-8", errors="replace").splitlines():
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parts = line.split("\t")
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if len(parts) < cols:
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continue
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try:
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t = datetime.strptime(parts[0].strip(), "%Y-%m-%d %H:%M:%S")
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except ValueError:
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continue
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rows.append((t, parts))
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return rows
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def main() -> int:
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if len(sys.argv) < 4:
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print("用法: rp_collapse.py <标签> <conns> <health>")
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return 2
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label, conns_path, health_path = sys.argv[1], sys.argv[2], sys.argv[3]
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conns = parse_ts(conns_path, 3)
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health = parse_ts(health_path, 3)
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if not conns:
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print(" %s: 连接采样为空" % label)
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return 1
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# ---- 连接数统计 ----
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samples = []
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for t, p in conns:
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try:
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q = int(p[1])
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except ValueError:
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q = None
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try:
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h = int(p[2])
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except ValueError:
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h = None
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samples.append((t, q, h))
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valid = [(t, q, h) for t, q, h in samples if q is not None and h is not None]
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if not valid:
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print(" %s: 没有有效的连接采样" % label)
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return 1
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span = (valid[-1][0] - valid[0][0]).total_seconds()
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total_list = [q + h for _t, q, h in valid]
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collapse = [(t, q, h) for t, q, h in valid if q + h <= COLLAPSE_TOTAL]
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collapse_secs = len(collapse) * 60.0 # 每 60 秒一个采样
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collapse_pct = len(collapse) * 100.0 / len(valid)
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print("=" * 62)
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print(" %s" % label)
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print(" 采样窗口 %.0f 分钟（%d 个连接采样）" % (span / 60, len(valid)))
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print("=" * 62)
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print()
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print(" 连接数分布:")
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from collections import Counter
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cnt = Counter(total_list)
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for k in sorted(cnt, reverse=True):
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bar = "#" * min(cnt[k], 50)
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print(" 总数 %2d : %3d 次 %s" % (k, cnt[k], bar))
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print()
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print(" 平均连接数: %.2f" % (sum(total_list) / len(total_list)))
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print()
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# ---- 塌陷窗口 ----
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print(" ── 塌陷窗口（连接总数 <= %d）──" % COLLAPSE_TOTAL)
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print(" 出现 %d 次采样 = 约 %.0f 秒 = 占窗口的 %.1f%%"
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% (len(collapse), collapse_secs, collapse_pct))
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if collapse:
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print(" 明细:")
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for t, q, h in collapse:
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print(" %s quic=%s http2=%s 合计=%d"
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% (t.strftime("%H:%M:%S"), q, h, q + h))
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# ---- 塌陷窗口内的公网可用率 ----
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print()
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print(" ── 塌陷窗口内的公网可用率 ──")
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if not collapse or not health:
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print(" （窗口内没有健康样本）")
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else:
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# 把塌陷时刻扩展成 ±60 秒的窗口，再取落在里面的健康样本
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windows = [(t.timestamp() - 60, t.timestamp() + 60) for t, _q, _h in collapse]
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inside = []
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for t, p in health:
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ts = t.timestamp()
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if any(a <= ts <= b for a, b in windows):
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inside.append((t, p[1]))
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if inside:
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ok = sum(1 for _t, c in inside if c == "200")
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print(" 窗口覆盖到 %d 个健康样本，成功 %d = %.1f%%"
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% (len(inside), ok, ok * 100.0 / len(inside)))
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bad = [(t, c) for t, c in inside if c != "200"]
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if bad:
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print(" 失败明细:")
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for t, c in bad:
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print(" %s 码=%s" % (t.strftime("%H:%M:%S"), c))
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else:
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print(" （窗口内没有健康样本）")
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# ---- 总体可用率 ----
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if health:
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ok = sum(1 for _t, p in health if p[1] == "200")
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print()
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print(" ── 总体公网可用率（对照）──")
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print(" %d/%d = %.2f%%" % (ok, len(health), ok * 100.0 / len(health)))
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# ---- 一句话结论 ----
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print()
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print(" ── 一句话 ──")
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print(" 风险暴露（总数<=%d）: %.1f%% 窗口内可用率: %s"
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% (COLLAPSE_TOTAL, collapse_pct,
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("%.1f%%" % (sum(1 for _t, c in inside if c == "200") * 100.0 / len(inside))
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if collapse and health and inside else "无数据")))
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return 0
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if __name__ == "__main__":
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sys.exit(main())
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