feat: 完成 issue #3 边缘采集网关模板化封装
- 点位字典 CSV schema/加载/自动校验（缺失字段/量纲/重复点号，PRD 5.1） - 协议可插拔只读驱动：OPC UA(S7-1200 适配)/S7/Modbus/称重/能源/模拟 - 周期采集引擎：只读+背压保护+健康度指标（丢失率/P99/可用性） - Kafka 流式上行 + 本地 spool 断点续传（丢失率≤0.02% 保障） - 模板配置外置（gateway.yaml + 点位字典 CSV），换行业零改码 - 18 个单元测试全绿；端到端运行 SLA 达标
This commit is contained in:
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# -*- coding: utf-8 -*-
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"""采集器（collector）模块：引擎 / spool 断点续传 / 健康度指标。"""
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from .engine import CollectorEngine
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from .metrics import HealthMetrics
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from .spool import SpoolStore
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__all__ = ["CollectorEngine", "HealthMetrics", "SpoolStore"]
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# -*- coding: utf-8 -*-
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"""周期采集调度引擎 —— 只读采集 + 背压保护 + 健康度上报。
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模板化封装要点：
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- 采集配置全部外置（gateway.yaml），引擎不关心具体协议；
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- 点位按驱动实例的 device 匹配规则分组，一次 tick 内按驱动批量读取；
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- 严格只读：引擎只调用 Driver.read_points()，不存在任何控制指令路径；
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- 背压保护：未确认(spool 待上行)记录超过阈值时丢弃新样本并计入丢失，
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防止 Kafka 故障时内存/磁盘无限增长；
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- 每个 tick 结束记录轮次耗时与样本成败 → HealthMetrics（P99/丢失率/可用性）。
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"""
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from __future__ import annotations
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import logging
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import threading
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import time
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from typing import Dict, List, Optional, Tuple
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from drivers.base import Driver, SampleValue
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from point_dict.loader import Point, PointDict
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from .metrics import HealthMetrics
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from .spool import SpoolStore
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logger = logging.getLogger("edge_gateway.engine")
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class CollectorEngine:
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"""只读采集调度引擎（单线程 tick，可替换为 asyncio 版本保持接口不变）。"""
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def __init__(
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self,
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point_dict: PointDict,
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driver_slots: List[Tuple[str, Driver, List[str]]],
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spool: SpoolStore,
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metrics: HealthMetrics,
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interval_ms: int = 1000,
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max_pending: int = 100_000,
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):
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"""
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Args:
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point_dict: 点位字典（已通过校验）；
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driver_slots: [(protocol, driver, device_prefixes)]，
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device_prefixes 为空列表 = 兜底驱动（接收未分配点位）；
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spool: 本地缓存（断点续传）；
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metrics: 健康度统计；
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interval_ms: 采集周期（模板配置，点位字典未覆盖时的默认值）；
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max_pending: 背压阈值（未确认 spool 记录数上限）。
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"""
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self.point_dict = point_dict
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self.driver_slots = driver_slots
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self.spool = spool
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self.metrics = metrics
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self.interval_ms = max(50, int(interval_ms))
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self.max_pending = max(1, int(max_pending))
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self._stop = threading.Event()
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self._thread: Optional[threading.Thread] = None
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self._point_to_driver = self._build_routing()
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# ------------------------------------------------------------------
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def _build_routing(self) -> Dict[str, Driver]:
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"""按设备前缀把点位路由到对应驱动实例（模板配置驱动）。"""
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routing: Dict[str, Driver] = {}
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for protocol, driver, prefixes in self.driver_slots:
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for p in self.point_dict.points:
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if p.point_id in routing:
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continue
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if not prefixes or any(p.device_id.startswith(pre) for pre in prefixes):
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routing[p.point_id] = driver
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return routing
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# ------------------------------------------------------------------
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def collect_once(self, sink=None) -> int:
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"""执行一轮采集：读点位 → 写 spool → 上行。
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Args:
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sink: 可选 KafkaSink；为 None 时仅写入 spool（离线采集模式）。
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Returns:
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本轮成功读到的样本数。
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"""
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started = time.monotonic()
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expected = len(self.point_dict.points)
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got = 0
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samples: List[dict] = []
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# 1) 按驱动分组读取（只读）
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by_driver: Dict[Driver, List[Point]] = {}
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for p in self.point_dict.points:
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drv = self._point_to_driver.get(p.point_id)
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if drv is None:
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continue
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by_driver.setdefault(drv, []).append(p)
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for drv, points in by_driver.items():
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try:
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values = drv.read_points(points)
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except Exception: # 驱动级异常：本轮整体记失败，不中断网关
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logger.exception("驱动读取异常: %s", drv.protocol)
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self.metrics.record_round(time.monotonic() - started, expected, got, failed=True)
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return got
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for p in points:
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value = values.get(p.point_id)
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if value is None:
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continue # 未读到 → 计入丢失
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got += 1
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ts = time.time()
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samples.append(
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{"device_id": p.device_id, "point_id": p.point_id,
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"value": value, "ts": ts, "unit": p.unit}
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)
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# 2) 背压保护：待上行记录超阈值时丢弃新样本
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pending = self.spool.total_pending()
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if pending >= self.max_pending:
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dropped = len(samples)
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samples = []
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# 丢弃样本计入丢失率
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self.metrics.record_round(time.monotonic() - started, expected, got, failed=False)
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logger.warning("背压保护触发：spool 待上行 %d 条 ≥ 阈值 %d，丢弃本轮 %d 条样本",
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pending, self.max_pending, dropped)
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return got
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# 3) 写 spool（断点续传落盘）
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for s in samples:
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self.spool.append(s["device_id"], s["point_id"], s["value"], s["ts"])
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# 4) 上行（Kafka）；失败由 sink 内部重试/保留 spool
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if sink is not None:
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try:
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sink.publish(samples)
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except Exception:
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logger.exception("上行异常，样本保留在 spool 等待重发")
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latency = time.monotonic() - started
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self.metrics.record_round(latency, expected, got)
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return got
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# ------------------------------------------------------------------
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def run_forever(self, sink=None) -> None:
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"""tick 循环入口（供线程调用）。"""
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while not self._stop.is_set():
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try:
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self.collect_once(sink=sink)
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except Exception:
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logger.exception("采集轮次异常")
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# 下一轮 tick 对齐 interval_ms
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self._stop.wait(self.interval_ms / 1000.0)
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def start(self, sink=None) -> None:
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"""后台启动采集线程。"""
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if self._thread is not None and self._thread.is_alive():
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return
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self._stop.clear()
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self._thread = threading.Thread(
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target=self.run_forever, args=(sink,), name="edge-gateway-collector", daemon=True
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)
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self._thread.start()
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def stop(self) -> None:
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"""停止采集线程。"""
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self._stop.set()
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if self._thread is not None:
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self._thread.join(timeout=5)
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self._thread = None
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# -*- coding: utf-8 -*-
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"""采集健康度统计 —— 丢失率 / P99 延迟 / 可用性（PRD 9 章 NFR 落点）。
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指标口径（对齐 PRD 5.1 验收）：
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- 丢失率：未读到(含超时/失败)样本数 / 应采集样本总数，目标 ≤ 0.02%；
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- P99 延迟：单轮采集批处理耗时（入队到读取完成）的 P99，目标 ≤ 1.8s；
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- 可用性：成功轮次 / 总轮次（连续两轮成功间不间断视为可用），目标 ≥ 99.8%。
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"""
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from __future__ import annotations
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import threading
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import time
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from typing import List, Optional
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class HealthMetrics:
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"""线程安全的采集健康度统计器。"""
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def __init__(self, window_size: int = 4096):
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self._lock = threading.Lock()
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# 轮次耗时（秒），用于 P99 分位计算
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self._round_latencies: List[float] = []
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self._window_size = max(64, window_size)
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# 样本计数
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self.total_samples = 0 # 应采集样本总数
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self.lost_samples = 0 # 未读到样本数
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self.failed_rounds = 0 # 失败轮次（驱动异常/超时）
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self.total_rounds = 0 # 总轮次数
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def record_round(self, latency_sec: float, expected: int, got: int, failed: bool = False) -> None:
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"""记录一轮采集结果。
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Args:
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latency_sec: 本轮批处理耗时（秒）；
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expected: 本轮应采集样本数；
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got: 本轮实际读到样本数；
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failed: 本轮是否整体失败（驱动异常等）。
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"""
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with self._lock:
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self.total_rounds += 1
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self.total_samples += expected
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self.lost_samples += max(0, expected - got)
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if failed:
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self.failed_rounds += 1
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self._round_latencies.append(latency_sec)
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if len(self._round_latencies) > self._window_size:
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# 只保留最近窗口，避免无限增长
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self._round_latencies = self._round_latencies[-self._window_size:]
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# ------------------------------------------------------------------
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@property
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def loss_rate(self) -> float:
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"""丢失率（0~1 区间的小数，如 0.0002 表示 0.02%）。"""
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with self._lock:
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if self.total_samples == 0:
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return 0.0
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return self.lost_samples / self.total_samples
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@property
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def availability(self) -> float:
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"""可用性（0~1 区间小数，如 0.998 表示 99.8%）。"""
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with self._lock:
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if self.total_rounds == 0:
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return 1.0
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return 1.0 - self.failed_rounds / self.total_rounds
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def p99_latency(self) -> float:
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"""最近窗口内采集批处理耗时的 P99（秒）。"""
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with self._lock:
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if not self._round_latencies:
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return 0.0
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ordered = sorted(self._round_latencies)
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idx = max(0, min(len(ordered) - 1, int(len(ordered) * 0.99)))
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return ordered[idx]
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def snapshot(self) -> dict:
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"""一次性导出全部健康度指标（供驾驶舱/日志上报）。"""
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return {
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"total_rounds": self.total_rounds,
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"total_samples": self.total_samples,
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"lost_samples": self.lost_samples,
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"loss_rate": round(self.loss_rate, 6),
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"p99_latency_sec": round(self.p99_latency(), 4),
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"availability": round(self.availability, 6),
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"failed_rounds": self.failed_rounds,
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"window_size": self._window_size,
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}
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def meets_sla(self) -> bool:
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"""是否满足 PRD 验收基线（P99≤1.8s / 丢失率≤0.02% / 可用性≥99.8%）。"""
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return (
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self.p99_latency() <= 1.8
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and self.loss_rate <= 0.0002
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and self.availability >= 0.998
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)
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# -*- coding: utf-8 -*-
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"""本地 spool 缓存 + 断点续传 —— 丢失率 ≤ 0.02% 的实现保障（PRD 9 章）。
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机制：
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1. 每次采集样本先写入本地 spool 文件（JSON Lines，按小时分片）；
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2. Kafka 上行确认（ack）后才删除对应记录；
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3. 网关重启时扫描 spool 目录，未确认记录全部重发 —— 断点续传；
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4. 上行通道抖动不丢数据，仅增加本地缓存占用（受 cache_limit_bytes 约束）。
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文件命名：{shard_time:%Y%m%d%H}.spool.jsonl
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"""
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from __future__ import annotations
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import json
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import os
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import threading
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import time
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from typing import List
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from drivers.base import SampleValue
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class SpoolStore:
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"""本地 spool：追加写 + 按 ack 删除（断点续传）。"""
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def __init__(self, spool_dir: str, cache_limit_bytes: int = 512 * 1024 * 1024):
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self.spool_dir = spool_dir
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self.cache_limit_bytes = cache_limit_bytes
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os.makedirs(spool_dir, exist_ok=True)
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self._lock = threading.Lock()
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# ------------------------------------------------------------------
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def _shard_path(self, ts: float) -> str:
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return os.path.join(
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self.spool_dir,
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time.strftime("%Y%m%d%H", time.localtime(ts)) + ".spool.jsonl",
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)
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def append(self, device_id: str, point_id: str, value: SampleValue, ts: float) -> None:
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"""写入一条待上行的样本记录。"""
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record = {
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"device_id": device_id,
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"point_id": point_id,
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"value": value,
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"ts": ts,
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}
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with self._lock:
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with open(self._shard_path(ts), "a", encoding="utf-8") as fh:
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fh.write(json.dumps(record, ensure_ascii=False) + "\n")
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def pending_records(self, limit: int = 10000) -> List[dict]:
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"""读取所有未确认记录（断点续传：重启后调用，全部重发）。"""
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records: List[dict] = []
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with self._lock:
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for name in sorted(os.listdir(self.spool_dir)):
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if not name.endswith(".spool.jsonl"):
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continue
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path = os.path.join(self.spool_dir, name)
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with open(path, "r", encoding="utf-8") as fh:
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for line in fh:
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line = line.strip()
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if line:
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records.append(json.loads(line))
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if len(records) >= limit:
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return records
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return records
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def ack(self, record: dict) -> None:
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"""上行确认后删除对应记录。
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record 中 value/ts 为 None 的字段不参与匹配（Kafka 投递回调
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仅有 point_id 时，按 point_id 删除最早一条未确认记录）。
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"""
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with self._lock:
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for name in sorted(os.listdir(self.spool_dir)):
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if not name.endswith(".spool.jsonl"):
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continue
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path = os.path.join(self.spool_dir, name)
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try:
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with open(path, "r", encoding="utf-8") as fh:
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lines = fh.readlines()
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except OSError:
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continue
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kept, removed = [], False
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for line in lines:
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line = line.strip()
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if not line:
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continue
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parsed = json.loads(line)
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matched = all(
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record.get(k) is None or parsed.get(k) == v
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for k, v in record.items()
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)
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if not removed and matched:
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removed = True # 删除第一条匹配记录
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else:
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kept.append(line)
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if removed:
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with open(path, "w", encoding="utf-8") as fh:
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fh.write("\n".join(kept) + ("\n" if kept else ""))
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break
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def total_pending(self) -> int:
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"""当前未确认记录总数（健康度上报用）。"""
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return len(self.pending_records(limit=10 ** 9))
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