refactor(pymsg): 新增AsyncRpcQueue通用异步队列，log_client基于此重构
- pymsg新增AsyncRpcQueue：提供内存队列+后台线程+攒批处理的通用异步基础设施， 支持两种模式：简单RPC模式(client+method+serialize)和自定义handler模式 - confs/dnfs/static的log_client.py重构为基于AsyncRpcQueue的薄封装， 保持API完全向后兼容(push/info/error/warning/debug/critical + 全局logs单例) - 消除了三份log_client副本中重复的队列/线程/攒批逻辑(约150行/份)， 代码量净减少约50行 - LogClient的行为与旧版一致：逐条INSERT到db、fail-fast网络错误、队列满丢最旧
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@@ -1,13 +1,15 @@
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"""统一日志客户端 — 各服务共用（dnfs / smtp / static / confs 四份副本内容一致，改动请同步）。
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"""
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统一日志客户端 — 各服务共用（基于 pymsg.AsyncRpcQueue）。
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设计要点：
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- 通过 pymsg RPC 调用 dbv2 execute 路由，逐条 INSERT 到 Logs 表
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- 异步非阻塞：内存队列 + 后台线程批量推送，不拖慢业务
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- fail-safe：db 服务不可用时静默丢弃，绝不影响业务；后台线程任何异常都不会崩溃
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- 异步非阻塞：内存队列 + 后台线程攒批推送，不拖慢业务
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- fail-safe：db 服务不可用时静默丢弃，绝不影响业务
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- 缓冲批量：队列满 50 条或超时 2 秒时自动 flush
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- 时间戳：日志入队时即记录 ts，反映事件真实发生时间
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- 时间戳：日志入队时即记录 ts（UTC ISO 格式），反映事件真实发生时间
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- 底层复用 pymsg.AsyncRpcQueue 通用队列基础设施
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用法：
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用法（与旧版完全兼容）：
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from log_client import logs
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logs.info("dnfs", "节点新增成功 id=42")
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@@ -19,28 +21,25 @@
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import json
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import os as _os
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import sys as _sys
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import threading
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import queue
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import time
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import atexit
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from datetime import datetime, timezone
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_sys.path.insert(0, _os.path.join(_os.path.dirname(__file__), ".."))
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from pymsg import RpcClient, RpcError # noqa: E402
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from pymsg import RpcClient, RpcError, AsyncRpcQueue # noqa: E402
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# ── 配置 ──────────────────────────────────────────────────────────────
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_DBV2_ADDR = _os.environ.get('DB_HOST', '127.0.0.1')
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_DBV2_PORT = int(_os.environ.get('DB_PORT', '8005'))
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_BATCH_SIZE = 50 # 队列满 50 条时 flush
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_FLUSH_INTERVAL = 2.0 # 超时 2 秒强制 flush
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_TIMEOUT = 5 # socket 超时（秒）
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_QUEUE_MAXSIZE = 10000 # 队列上限，防止后台线程异常时内存无限增长；满则丢弃最旧条目
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_BATCH_SIZE = 50
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_FLUSH_INTERVAL = 2.0
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_TIMEOUT = 5
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_QUEUE_MAXSIZE = 10000
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def _safe_json(obj):
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"""安全序列化 extra 字段，不可序列化对象转为 repr 字符串，保证不抛异常。"""
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"""安全序列化 extra 字段，不可序列化对象转为 repr 字符串。"""
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try:
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return json.dumps(obj, ensure_ascii=False, default=str)
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except Exception:
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@@ -48,163 +47,80 @@ def _safe_json(obj):
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def _now_iso():
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"""生成当前 UTC 时间 ISO 字符串（在入队时调用，保证时间戳准确）。"""
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"""生成当前 UTC 时间 ISO 字符串（入队时调用，保证时间戳准确）。"""
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return datetime.now(timezone.utc).isoformat()
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class LogClient:
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"""异步批量日志推送客户端。"""
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"""异步批量日志推送客户端（API 与旧版完全兼容）。"""
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def __init__(self, service_name="log",
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batch_size=_BATCH_SIZE,
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flush_interval=_FLUSH_INTERVAL):
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def __init__(self, service_name: str = "log",
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batch_size: int = _BATCH_SIZE,
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flush_interval: float = _FLUSH_INTERVAL):
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self._service_name = service_name
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self._batch_size = batch_size
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self._flush_interval = flush_interval
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self._queue = queue.Queue(maxsize=_QUEUE_MAXSIZE)
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self._stop = threading.Event()
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self._flush_signal = threading.Event()
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self._flush_done = threading.Event()
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self._thread = threading.Thread(target=self._flush_loop,
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daemon=True, name='log-client')
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self._thread.start()
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atexit.register(self._shutdown)
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self._client = RpcClient(
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_DBV2_ADDR, _DBV2_PORT,
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service_name + "-log",
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timeout=_TIMEOUT,
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)
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self._queue = AsyncRpcQueue(
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handler=self._send_batch,
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batch_size=batch_size,
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flush_interval=flush_interval,
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max_queue_size=_QUEUE_MAXSIZE,
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on_error=self._on_error,
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)
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self._queue.start()
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atexit.register(self.close)
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# ── 公开接口 ────────────────────────────────────────────────────────
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def push(self, service, level, message, trace_id=None, extra=None):
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def push(self, service: str, level: str, message: str,
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trace_id: str = None, extra=None):
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"""推送一条日志（非阻塞，立即返回）。
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队列满时静默丢弃最旧条目再放入新条目，保证不阻塞业务线程、不导致 OOM。
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"""
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entry = {
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'ts': _now_iso(), # 入队时即生成时间戳，反映真实事件时间
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'ts': _now_iso(),
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'service': service,
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'level': level,
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'message': message,
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'trace_id': trace_id,
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'extra': extra,
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}
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try:
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self._queue.put_nowait(entry)
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except queue.Full:
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# 队列满：丢弃最旧的一条，再放入新条目（drop-oldest 策略）
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try:
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self._queue.get_nowait()
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except queue.Empty:
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pass
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try:
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self._queue.put_nowait(entry)
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except queue.Full:
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pass # 极端竞争下仍失败则静默丢弃
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self._queue.put(entry)
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def debug(self, service, message, **kw):
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def debug(self, service: str, message: str, **kw):
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self.push(service, 'DEBUG', message, **kw)
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def info(self, service, message, **kw):
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def info(self, service: str, message: str, **kw):
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self.push(service, 'INFO', message, **kw)
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def warning(self, service, message, **kw):
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def warning(self, service: str, message: str, **kw):
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self.push(service, 'WARNING', message, **kw)
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def error(self, service, message, **kw):
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def warn(self, service: str, message: str, **kw):
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self.push(service, 'WARNING', message, **kw)
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def error(self, service: str, message: str, **kw):
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self.push(service, 'ERROR', message, **kw)
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def critical(self, service, message, **kw):
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def critical(self, service: str, message: str, **kw):
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self.push(service, 'CRITICAL', message, **kw)
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def flush(self):
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"""手动 flush 队列中剩余的日志（含后台线程持有的局部 batch）。"""
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self._flush_done.clear()
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self._flush_signal.set() # 通知后台线程立即 flush 其局部 batch
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# 等待后台线程完成 flush（最多等待 flush_interval + 2 秒余量）
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self._flush_done.wait(timeout=self._flush_interval + 2.0)
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# 主线程排空队列中剩余条目
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self._drain_queue_to_db()
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"""手动 flush 队列中剩余的日志。"""
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self._queue.flush()
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def _drain_queue_to_db(self):
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"""排空主线程可见的队列中剩余条目，直接发送到 db。"""
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batch = []
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while True:
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try:
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batch.append(self._queue.get_nowait())
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if len(batch) >= self._batch_size:
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self._send(batch)
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batch = []
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except queue.Empty:
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break
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if batch:
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self._send(batch)
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def close(self):
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"""关闭客户端，flush 剩余日志。"""
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self._queue.close()
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# ── 内部实现 ────────────────────────────────────────────────────────
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def _flush_loop(self):
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"""后台线程：积攒到 batch_size 或超时 flush_interval 时发送。
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外层捕获所有异常，保证后台线程在任何情况下（网络故障、序列化错误等）
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都不会死亡，避免日志队列无限增长导致 OOM。
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"""
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batch = []
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last_flush = time.monotonic()
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while not self._stop.is_set():
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try:
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timeout = self._flush_interval - (time.monotonic() - last_flush)
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chk_timeout = max(0.1, min(timeout, 0.5))
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try:
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item = self._queue.get(timeout=chk_timeout)
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batch.append(item)
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while len(batch) < self._batch_size:
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try:
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batch.append(self._queue.get_nowait())
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except queue.Empty:
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break
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except queue.Empty:
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pass
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should_flush = (
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len(batch) >= self._batch_size or
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self._flush_signal.is_set() or
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(batch and time.monotonic() - last_flush >= self._flush_interval)
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)
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if should_flush and batch:
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try:
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self._send(batch)
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except Exception as e:
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# _send 内部已有细粒度异常处理，此处是最终安全网
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print(f"[log_client] _send 异常（已捕获，线程继续运行）: {e}",
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file=_sys.stderr)
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batch = []
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last_flush = time.monotonic()
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if self._flush_signal.is_set():
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self._flush_signal.clear()
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self._flush_done.set()
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except Exception as e:
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# 最外层安全网：任何意外异常都不应杀死日志线程
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print(f"[log_client] _flush_loop 异常（已捕获，线程继续运行）: {e}",
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file=_sys.stderr)
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time.sleep(0.5) # 防止异常风暴导致 CPU 满载
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# 退出前 flush 剩余
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if batch:
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try:
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self._send(batch)
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except Exception as e:
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print(f"[log_client] 退出时 flush 异常: {e}", file=_sys.stderr)
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self._flush_done.set()
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def _send(self, batch):
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"""通过 pymsg RPC（execute 路由）批量发送到 dbv2 Logs 表。
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整个 batch 复用一个 TCP 连接；网络错误时放弃本批剩余条目（fail-safe），
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不抛异常给调用方。
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"""
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try:
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client = RpcClient(_DBV2_ADDR, _DBV2_PORT, self._service_name + "-log")
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except Exception as e:
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print(f"[log_client] 创建 RpcClient 失败: {e}", file=_sys.stderr)
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return
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def _send_batch(self, batch: list):
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"""后台线程回调：逐条 INSERT 到 db（与旧版行为一致：网络错误放弃本批剩余）。"""
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for entry in batch:
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extra_val = entry.get("extra")
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try:
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@@ -224,21 +140,21 @@ class LogClient:
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},
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}
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try:
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client.call("execute", payload, timeout=_TIMEOUT)
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self._client.call("execute", payload, timeout=_TIMEOUT)
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except RpcError as e:
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# 业务错误（如表结构不符）：打印后继续下一条
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print(f"[log_client] INSERT 失败: {e}", file=_sys.stderr)
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except Exception as e:
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# 网络错误：db 不可用，放弃本批剩余（fail-safe）
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print(f"[log_client] 发送失败: {e}", file=_sys.stderr)
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print(f"[log_client] 发送失败（放弃本批剩余）: {e}", file=_sys.stderr)
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break
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def _shutdown(self):
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"""进程退出时 flush 剩余日志。"""
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self._stop.set()
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self.flush()
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def _on_error(self, e: Exception, batch: list):
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"""异常安全网：handler 外的异常也不会崩溃线程。"""
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print(f"[log_client] _send_batch 异常（已捕获，线程继续运行）: {e}",
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file=_sys.stderr)
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# ── 全局单例 ──────────────────────────────────────────────────────────
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# 各服务的 log_client.py 副本需将 service_name 改为自己的服务名。
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# 此文件（confs/log_client.py）的 service_name 为 "confs"。
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logs = LogClient()
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logs = LogClient(service_name="confs")
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+60
-144
@@ -1,13 +1,15 @@
|
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"""统一日志客户端 — 各服务共用（dnfs / smtp / static / confs 四份副本内容一致，改动请同步）。
|
||||
"""
|
||||
统一日志客户端 — 各服务共用（基于 pymsg.AsyncRpcQueue）。
|
||||
|
||||
设计要点：
|
||||
- 通过 pymsg RPC 调用 dbv2 execute 路由，逐条 INSERT 到 Logs 表
|
||||
- 异步非阻塞：内存队列 + 后台线程批量推送，不拖慢业务
|
||||
- fail-safe：db 服务不可用时静默丢弃，绝不影响业务；后台线程任何异常都不会崩溃
|
||||
- 异步非阻塞：内存队列 + 后台线程攒批推送，不拖慢业务
|
||||
- fail-safe：db 服务不可用时静默丢弃，绝不影响业务
|
||||
- 缓冲批量：队列满 50 条或超时 2 秒时自动 flush
|
||||
- 时间戳：日志入队时即记录 ts，反映事件真实发生时间
|
||||
- 时间戳：日志入队时即记录 ts（UTC ISO 格式），反映事件真实发生时间
|
||||
- 底层复用 pymsg.AsyncRpcQueue 通用队列基础设施
|
||||
|
||||
用法：
|
||||
用法（与旧版完全兼容）：
|
||||
from log_client import logs
|
||||
|
||||
logs.info("dnfs", "节点新增成功 id=42")
|
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@@ -19,28 +21,25 @@
|
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import json
|
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import os as _os
|
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import sys as _sys
|
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import threading
|
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import queue
|
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import time
|
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import atexit
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from datetime import datetime, timezone
|
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|
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_sys.path.insert(0, _os.path.join(_os.path.dirname(__file__), ".."))
|
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from pymsg import RpcClient, RpcError # noqa: E402
|
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from pymsg import RpcClient, RpcError, AsyncRpcQueue # noqa: E402
|
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|
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# ── 配置 ──────────────────────────────────────────────────────────────
|
||||
|
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_DBV2_ADDR = _os.environ.get('DB_HOST', '127.0.0.1')
|
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_DBV2_PORT = int(_os.environ.get('DB_PORT', '8005'))
|
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|
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_BATCH_SIZE = 50 # 队列满 50 条时 flush
|
||||
_FLUSH_INTERVAL = 2.0 # 超时 2 秒强制 flush
|
||||
_TIMEOUT = 5 # socket 超时（秒）
|
||||
_QUEUE_MAXSIZE = 10000 # 队列上限，防止后台线程异常时内存无限增长；满则丢弃最旧条目
|
||||
_BATCH_SIZE = 50
|
||||
_FLUSH_INTERVAL = 2.0
|
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_TIMEOUT = 5
|
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_QUEUE_MAXSIZE = 10000
|
||||
|
||||
|
||||
def _safe_json(obj):
|
||||
"""安全序列化 extra 字段，不可序列化对象转为 repr 字符串，保证不抛异常。"""
|
||||
"""安全序列化 extra 字段，不可序列化对象转为 repr 字符串。"""
|
||||
try:
|
||||
return json.dumps(obj, ensure_ascii=False, default=str)
|
||||
except Exception:
|
||||
@@ -48,163 +47,80 @@ def _safe_json(obj):
|
||||
|
||||
|
||||
def _now_iso():
|
||||
"""生成当前 UTC 时间 ISO 字符串（在入队时调用，保证时间戳准确）。"""
|
||||
"""生成当前 UTC 时间 ISO 字符串（入队时调用，保证时间戳准确）。"""
|
||||
return datetime.now(timezone.utc).isoformat()
|
||||
|
||||
|
||||
class LogClient:
|
||||
"""异步批量日志推送客户端。"""
|
||||
"""异步批量日志推送客户端（API 与旧版完全兼容）。"""
|
||||
|
||||
def __init__(self, service_name="log",
|
||||
batch_size=_BATCH_SIZE,
|
||||
flush_interval=_FLUSH_INTERVAL):
|
||||
def __init__(self, service_name: str = "log",
|
||||
batch_size: int = _BATCH_SIZE,
|
||||
flush_interval: float = _FLUSH_INTERVAL):
|
||||
self._service_name = service_name
|
||||
self._batch_size = batch_size
|
||||
self._flush_interval = flush_interval
|
||||
self._queue = queue.Queue(maxsize=_QUEUE_MAXSIZE)
|
||||
self._stop = threading.Event()
|
||||
self._flush_signal = threading.Event()
|
||||
self._flush_done = threading.Event()
|
||||
self._thread = threading.Thread(target=self._flush_loop,
|
||||
daemon=True, name='log-client')
|
||||
self._thread.start()
|
||||
atexit.register(self._shutdown)
|
||||
self._client = RpcClient(
|
||||
_DBV2_ADDR, _DBV2_PORT,
|
||||
service_name + "-log",
|
||||
timeout=_TIMEOUT,
|
||||
)
|
||||
self._queue = AsyncRpcQueue(
|
||||
handler=self._send_batch,
|
||||
batch_size=batch_size,
|
||||
flush_interval=flush_interval,
|
||||
max_queue_size=_QUEUE_MAXSIZE,
|
||||
on_error=self._on_error,
|
||||
)
|
||||
self._queue.start()
|
||||
atexit.register(self.close)
|
||||
|
||||
# ── 公开接口 ────────────────────────────────────────────────────────
|
||||
|
||||
def push(self, service, level, message, trace_id=None, extra=None):
|
||||
def push(self, service: str, level: str, message: str,
|
||||
trace_id: str = None, extra=None):
|
||||
"""推送一条日志（非阻塞，立即返回）。
|
||||
|
||||
队列满时静默丢弃最旧条目再放入新条目，保证不阻塞业务线程、不导致 OOM。
|
||||
"""
|
||||
entry = {
|
||||
'ts': _now_iso(), # 入队时即生成时间戳，反映真实事件时间
|
||||
'ts': _now_iso(),
|
||||
'service': service,
|
||||
'level': level,
|
||||
'message': message,
|
||||
'trace_id': trace_id,
|
||||
'extra': extra,
|
||||
}
|
||||
try:
|
||||
self._queue.put_nowait(entry)
|
||||
except queue.Full:
|
||||
# 队列满：丢弃最旧的一条，再放入新条目（drop-oldest 策略）
|
||||
try:
|
||||
self._queue.get_nowait()
|
||||
except queue.Empty:
|
||||
pass
|
||||
try:
|
||||
self._queue.put_nowait(entry)
|
||||
except queue.Full:
|
||||
pass # 极端竞争下仍失败则静默丢弃
|
||||
self._queue.put(entry)
|
||||
|
||||
def debug(self, service, message, **kw):
|
||||
def debug(self, service: str, message: str, **kw):
|
||||
self.push(service, 'DEBUG', message, **kw)
|
||||
|
||||
def info(self, service, message, **kw):
|
||||
def info(self, service: str, message: str, **kw):
|
||||
self.push(service, 'INFO', message, **kw)
|
||||
|
||||
def warning(self, service, message, **kw):
|
||||
def warning(self, service: str, message: str, **kw):
|
||||
self.push(service, 'WARNING', message, **kw)
|
||||
|
||||
def error(self, service, message, **kw):
|
||||
def warn(self, service: str, message: str, **kw):
|
||||
self.push(service, 'WARNING', message, **kw)
|
||||
|
||||
def error(self, service: str, message: str, **kw):
|
||||
self.push(service, 'ERROR', message, **kw)
|
||||
|
||||
def critical(self, service, message, **kw):
|
||||
def critical(self, service: str, message: str, **kw):
|
||||
self.push(service, 'CRITICAL', message, **kw)
|
||||
|
||||
def flush(self):
|
||||
"""手动 flush 队列中剩余的日志（含后台线程持有的局部 batch）。"""
|
||||
self._flush_done.clear()
|
||||
self._flush_signal.set() # 通知后台线程立即 flush 其局部 batch
|
||||
# 等待后台线程完成 flush（最多等待 flush_interval + 2 秒余量）
|
||||
self._flush_done.wait(timeout=self._flush_interval + 2.0)
|
||||
# 主线程排空队列中剩余条目
|
||||
self._drain_queue_to_db()
|
||||
"""手动 flush 队列中剩余的日志。"""
|
||||
self._queue.flush()
|
||||
|
||||
def _drain_queue_to_db(self):
|
||||
"""排空主线程可见的队列中剩余条目，直接发送到 db。"""
|
||||
batch = []
|
||||
while True:
|
||||
try:
|
||||
batch.append(self._queue.get_nowait())
|
||||
if len(batch) >= self._batch_size:
|
||||
self._send(batch)
|
||||
batch = []
|
||||
except queue.Empty:
|
||||
break
|
||||
if batch:
|
||||
self._send(batch)
|
||||
def close(self):
|
||||
"""关闭客户端，flush 剩余日志。"""
|
||||
self._queue.close()
|
||||
|
||||
# ── 内部实现 ────────────────────────────────────────────────────────
|
||||
|
||||
def _flush_loop(self):
|
||||
"""后台线程：积攒到 batch_size 或超时 flush_interval 时发送。
|
||||
|
||||
外层捕获所有异常，保证后台线程在任何情况下（网络故障、序列化错误等）
|
||||
都不会死亡，避免日志队列无限增长导致 OOM。
|
||||
"""
|
||||
batch = []
|
||||
last_flush = time.monotonic()
|
||||
|
||||
while not self._stop.is_set():
|
||||
try:
|
||||
timeout = self._flush_interval - (time.monotonic() - last_flush)
|
||||
chk_timeout = max(0.1, min(timeout, 0.5))
|
||||
try:
|
||||
item = self._queue.get(timeout=chk_timeout)
|
||||
batch.append(item)
|
||||
while len(batch) < self._batch_size:
|
||||
try:
|
||||
batch.append(self._queue.get_nowait())
|
||||
except queue.Empty:
|
||||
break
|
||||
except queue.Empty:
|
||||
pass
|
||||
|
||||
should_flush = (
|
||||
len(batch) >= self._batch_size or
|
||||
self._flush_signal.is_set() or
|
||||
(batch and time.monotonic() - last_flush >= self._flush_interval)
|
||||
)
|
||||
if should_flush and batch:
|
||||
try:
|
||||
self._send(batch)
|
||||
except Exception as e:
|
||||
# _send 内部已有细粒度异常处理，此处是最终安全网
|
||||
print(f"[log_client] _send 异常（已捕获，线程继续运行）: {e}",
|
||||
file=_sys.stderr)
|
||||
batch = []
|
||||
last_flush = time.monotonic()
|
||||
if self._flush_signal.is_set():
|
||||
self._flush_signal.clear()
|
||||
self._flush_done.set()
|
||||
except Exception as e:
|
||||
# 最外层安全网：任何意外异常都不应杀死日志线程
|
||||
print(f"[log_client] _flush_loop 异常（已捕获，线程继续运行）: {e}",
|
||||
file=_sys.stderr)
|
||||
time.sleep(0.5) # 防止异常风暴导致 CPU 满载
|
||||
|
||||
# 退出前 flush 剩余
|
||||
if batch:
|
||||
try:
|
||||
self._send(batch)
|
||||
except Exception as e:
|
||||
print(f"[log_client] 退出时 flush 异常: {e}", file=_sys.stderr)
|
||||
self._flush_done.set()
|
||||
|
||||
def _send(self, batch):
|
||||
"""通过 pymsg RPC（execute 路由）批量发送到 dbv2 Logs 表。
|
||||
|
||||
整个 batch 复用一个 TCP 连接；网络错误时放弃本批剩余条目（fail-safe），
|
||||
不抛异常给调用方。
|
||||
"""
|
||||
try:
|
||||
client = RpcClient(_DBV2_ADDR, _DBV2_PORT, self._service_name + "-log")
|
||||
except Exception as e:
|
||||
print(f"[log_client] 创建 RpcClient 失败: {e}", file=_sys.stderr)
|
||||
return
|
||||
|
||||
def _send_batch(self, batch: list):
|
||||
"""后台线程回调：逐条 INSERT 到 db（与旧版行为一致：网络错误放弃本批剩余）。"""
|
||||
for entry in batch:
|
||||
extra_val = entry.get("extra")
|
||||
try:
|
||||
@@ -224,21 +140,21 @@ class LogClient:
|
||||
},
|
||||
}
|
||||
try:
|
||||
client.call("execute", payload, timeout=_TIMEOUT)
|
||||
self._client.call("execute", payload, timeout=_TIMEOUT)
|
||||
except RpcError as e:
|
||||
# 业务错误（如表结构不符）：打印后继续下一条
|
||||
print(f"[log_client] INSERT 失败: {e}", file=_sys.stderr)
|
||||
except Exception as e:
|
||||
# 网络错误：db 不可用，放弃本批剩余（fail-safe）
|
||||
print(f"[log_client] 发送失败: {e}", file=_sys.stderr)
|
||||
print(f"[log_client] 发送失败（放弃本批剩余）: {e}", file=_sys.stderr)
|
||||
break
|
||||
|
||||
def _shutdown(self):
|
||||
"""进程退出时 flush 剩余日志。"""
|
||||
self._stop.set()
|
||||
self.flush()
|
||||
def _on_error(self, e: Exception, batch: list):
|
||||
"""异常安全网：handler 外的异常也不会崩溃线程。"""
|
||||
print(f"[log_client] _send_batch 异常（已捕获，线程继续运行）: {e}",
|
||||
file=_sys.stderr)
|
||||
|
||||
|
||||
# ── 全局单例 ──────────────────────────────────────────────────────────
|
||||
# 各服务的 log_client.py 副本需将 service_name 改为自己的服务名。
|
||||
# 此文件（confs/log_client.py）的 service_name 为 "confs"。
|
||||
|
||||
logs = LogClient()
|
||||
logs = LogClient(service_name="dnfs")
|
||||
@@ -525,5 +525,6 @@ class MsgServer:
|
||||
|
||||
# ── JSON RPC 约定层（依赖上面的 MsgClient / MsgServer，故放在末尾导入）──
|
||||
from .rpc import RpcClient, RpcError, RpcServer # noqa: E402
|
||||
from .async_queue import AsyncRpcQueue # noqa: E402
|
||||
|
||||
__all__ += ["RpcClient", "RpcServer", "RpcError"]
|
||||
__all__ += ["RpcClient", "RpcServer", "RpcError", "AsyncRpcQueue"]
|
||||
@@ -0,0 +1,202 @@
|
||||
"""
|
||||
AsyncRpcQueue - 通用异步批量发送队列
|
||||
|
||||
提供内存队列 + 后台线程的异步批量处理机制，适用于日志上报、指标采集等
|
||||
非关键路径场景。业务线程put操作非阻塞，后台线程攒批处理，失败时通过错误回调
|
||||
通知，不影响主业务流程。
|
||||
|
||||
两种使用模式：
|
||||
|
||||
1. 简单RPC模式（指定client + method + serialize）：
|
||||
queue = AsyncRpcQueue(
|
||||
client=rpc_client,
|
||||
method='log_api.push',
|
||||
batch_size=50,
|
||||
flush_interval=2.0,
|
||||
serialize=lambda items: {'logs': json.dumps(items)},
|
||||
)
|
||||
|
||||
2. 自定义处理模式（指定handler回调）：
|
||||
def send_batch(batch):
|
||||
for item in batch:
|
||||
rpc_client.call('execute', item)
|
||||
queue = AsyncRpcQueue(
|
||||
handler=send_batch,
|
||||
batch_size=50,
|
||||
flush_interval=2.0,
|
||||
)
|
||||
"""
|
||||
|
||||
import threading
|
||||
import time
|
||||
from collections import deque
|
||||
from typing import Any, Callable, Optional
|
||||
|
||||
|
||||
class AsyncRpcQueue:
|
||||
"""通用异步批量发送队列"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
client: Any = None,
|
||||
method: str = None,
|
||||
*,
|
||||
handler: Optional[Callable[[list], None]] = None,
|
||||
batch_size: int = 100,
|
||||
flush_interval: float = 2.0,
|
||||
max_queue_size: int = 10000,
|
||||
serialize: Optional[Callable[[list], dict]] = None,
|
||||
on_error: Optional[Callable[[Exception, list], None]] = None,
|
||||
retry_on_refused: bool = False,
|
||||
retry_interval: float = 1.0,
|
||||
):
|
||||
"""
|
||||
初始化异步队列
|
||||
|
||||
Args:
|
||||
client: RpcClient实例（RPC模式必填）
|
||||
method: RPC方法名（RPC模式必填）
|
||||
handler: 自定义批量处理回调，接收一批items列表。提供此参数时
|
||||
忽略client/method/serialize/retry_on_refused。
|
||||
batch_size: 批量发送的阈值，达到此数量立即发送
|
||||
flush_interval: 定时flush间隔（秒）
|
||||
max_queue_size: 队列最大长度，超过则丢弃最旧数据
|
||||
serialize: 序列化函数，接收items列表返回RPC参数字典
|
||||
默认: lambda items: {'items': items}
|
||||
on_error: 错误回调，接收(exception, batch_items)
|
||||
retry_on_refused: 是否在连接被拒绝时重试（RPC模式，透传给client.call）
|
||||
retry_interval: 重试间隔（秒）（RPC模式，透传给client.call）
|
||||
"""
|
||||
if handler is None:
|
||||
if client is None or method is None:
|
||||
raise ValueError("必须提供 handler 或 (client + method)")
|
||||
self._handler = self._make_rpc_handler(
|
||||
client, method,
|
||||
serialize or (lambda items: {'items': items}),
|
||||
retry_on_refused, retry_interval,
|
||||
)
|
||||
else:
|
||||
self._handler = handler
|
||||
|
||||
self._batch_size = batch_size
|
||||
self._flush_interval = flush_interval
|
||||
self._max_queue_size = max_queue_size
|
||||
self._on_error = on_error
|
||||
|
||||
self._queue: deque = deque()
|
||||
self._lock = threading.Lock()
|
||||
self._wakeup = threading.Event()
|
||||
self._thread: Optional[threading.Thread] = None
|
||||
self._closed = False
|
||||
self._dropped_count = 0
|
||||
|
||||
@staticmethod
|
||||
def _make_rpc_handler(client, method, serialize, retry_on_refused, retry_interval):
|
||||
"""创建RPC模式的默认handler"""
|
||||
def handler(batch: list):
|
||||
params = serialize(batch)
|
||||
client.call(
|
||||
method, params,
|
||||
retry_on_refused=retry_on_refused,
|
||||
retry_interval=retry_interval,
|
||||
)
|
||||
return handler
|
||||
|
||||
def start(self) -> None:
|
||||
"""启动后台发送线程"""
|
||||
if self._thread is not None and self._thread.is_alive():
|
||||
return
|
||||
self._closed = False
|
||||
self._thread = threading.Thread(
|
||||
target=self._run,
|
||||
name=f'AsyncRpcQueue',
|
||||
daemon=True,
|
||||
)
|
||||
self._thread.start()
|
||||
|
||||
def put(self, item: Any) -> bool:
|
||||
"""
|
||||
放入一条数据到队列（非阻塞）
|
||||
|
||||
Args:
|
||||
item: 要发送的数据项
|
||||
|
||||
Returns:
|
||||
bool: True表示放入成功，False表示队列已关闭
|
||||
"""
|
||||
if self._closed:
|
||||
return False
|
||||
with self._lock:
|
||||
if len(self._queue) >= self._max_queue_size:
|
||||
self._queue.popleft()
|
||||
self._dropped_count += 1
|
||||
self._queue.append(item)
|
||||
self._wakeup.set()
|
||||
return True
|
||||
|
||||
def flush(self) -> None:
|
||||
"""立即触发一次发送（会阻塞直到处理完成，主要用于关闭时）"""
|
||||
self._send_batch()
|
||||
|
||||
def close(self) -> None:
|
||||
"""关闭队列，flush剩余数据后停止后台线程"""
|
||||
if self._closed:
|
||||
return
|
||||
self._closed = True
|
||||
self._wakeup.set()
|
||||
if self._thread is not None:
|
||||
self._thread.join(timeout=5.0)
|
||||
self._send_batch()
|
||||
|
||||
@property
|
||||
def pending_count(self) -> int:
|
||||
"""当前队列中待发送的数据量"""
|
||||
with self._lock:
|
||||
return len(self._queue)
|
||||
|
||||
@property
|
||||
def dropped_count(self) -> int:
|
||||
"""因队列满而丢弃的数据量"""
|
||||
return self._dropped_count
|
||||
|
||||
def _run(self) -> None:
|
||||
"""后台线程主循环"""
|
||||
last_flush = time.time()
|
||||
while not self._closed:
|
||||
self._wakeup.wait(timeout=0.1)
|
||||
self._wakeup.clear()
|
||||
|
||||
now = time.time()
|
||||
should_flush = False
|
||||
with self._lock:
|
||||
if len(self._queue) >= self._batch_size:
|
||||
should_flush = True
|
||||
elif now - last_flush >= self._flush_interval and self._queue:
|
||||
should_flush = True
|
||||
if should_flush:
|
||||
self._send_batch()
|
||||
last_flush = time.time()
|
||||
|
||||
def _send_batch(self) -> None:
|
||||
"""取一批数据处理"""
|
||||
with self._lock:
|
||||
if not self._queue:
|
||||
return
|
||||
batch = list(self._queue)
|
||||
self._queue.clear()
|
||||
try:
|
||||
self._handler(batch)
|
||||
except Exception as e:
|
||||
if self._on_error:
|
||||
try:
|
||||
self._on_error(e, batch)
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
def __enter__(self):
|
||||
self.start()
|
||||
return self
|
||||
|
||||
def __exit__(self, exc_type, exc_val, exc_tb):
|
||||
self.close()
|
||||
return False
|
||||
+60
-144
@@ -1,13 +1,15 @@
|
||||
"""统一日志客户端 — 各服务共用（dnfs / smtp / static / confs 四份副本内容一致，改动请同步）。
|
||||
"""
|
||||
统一日志客户端 — 各服务共用（基于 pymsg.AsyncRpcQueue）。
|
||||
|
||||
设计要点：
|
||||
- 通过 pymsg RPC 调用 dbv2 execute 路由，逐条 INSERT 到 Logs 表
|
||||
- 异步非阻塞：内存队列 + 后台线程批量推送，不拖慢业务
|
||||
- fail-safe：db 服务不可用时静默丢弃，绝不影响业务；后台线程任何异常都不会崩溃
|
||||
- 异步非阻塞：内存队列 + 后台线程攒批推送，不拖慢业务
|
||||
- fail-safe：db 服务不可用时静默丢弃，绝不影响业务
|
||||
- 缓冲批量：队列满 50 条或超时 2 秒时自动 flush
|
||||
- 时间戳：日志入队时即记录 ts，反映事件真实发生时间
|
||||
- 时间戳：日志入队时即记录 ts（UTC ISO 格式），反映事件真实发生时间
|
||||
- 底层复用 pymsg.AsyncRpcQueue 通用队列基础设施
|
||||
|
||||
用法：
|
||||
用法（与旧版完全兼容）：
|
||||
from log_client import logs
|
||||
|
||||
logs.info("dnfs", "节点新增成功 id=42")
|
||||
@@ -19,28 +21,25 @@
|
||||
import json
|
||||
import os as _os
|
||||
import sys as _sys
|
||||
import threading
|
||||
import queue
|
||||
import time
|
||||
import atexit
|
||||
from datetime import datetime, timezone
|
||||
|
||||
_sys.path.insert(0, _os.path.join(_os.path.dirname(__file__), ".."))
|
||||
from pymsg import RpcClient, RpcError # noqa: E402
|
||||
from pymsg import RpcClient, RpcError, AsyncRpcQueue # noqa: E402
|
||||
|
||||
# ── 配置 ──────────────────────────────────────────────────────────────
|
||||
|
||||
_DBV2_ADDR = _os.environ.get('DB_HOST', '127.0.0.1')
|
||||
_DBV2_PORT = int(_os.environ.get('DB_PORT', '8005'))
|
||||
|
||||
_BATCH_SIZE = 50 # 队列满 50 条时 flush
|
||||
_FLUSH_INTERVAL = 2.0 # 超时 2 秒强制 flush
|
||||
_TIMEOUT = 5 # socket 超时（秒）
|
||||
_QUEUE_MAXSIZE = 10000 # 队列上限，防止后台线程异常时内存无限增长；满则丢弃最旧条目
|
||||
_BATCH_SIZE = 50
|
||||
_FLUSH_INTERVAL = 2.0
|
||||
_TIMEOUT = 5
|
||||
_QUEUE_MAXSIZE = 10000
|
||||
|
||||
|
||||
def _safe_json(obj):
|
||||
"""安全序列化 extra 字段，不可序列化对象转为 repr 字符串，保证不抛异常。"""
|
||||
"""安全序列化 extra 字段，不可序列化对象转为 repr 字符串。"""
|
||||
try:
|
||||
return json.dumps(obj, ensure_ascii=False, default=str)
|
||||
except Exception:
|
||||
@@ -48,163 +47,80 @@ def _safe_json(obj):
|
||||
|
||||
|
||||
def _now_iso():
|
||||
"""生成当前 UTC 时间 ISO 字符串（在入队时调用，保证时间戳准确）。"""
|
||||
"""生成当前 UTC 时间 ISO 字符串（入队时调用，保证时间戳准确）。"""
|
||||
return datetime.now(timezone.utc).isoformat()
|
||||
|
||||
|
||||
class LogClient:
|
||||
"""异步批量日志推送客户端。"""
|
||||
"""异步批量日志推送客户端（API 与旧版完全兼容）。"""
|
||||
|
||||
def __init__(self, service_name="log",
|
||||
batch_size=_BATCH_SIZE,
|
||||
flush_interval=_FLUSH_INTERVAL):
|
||||
def __init__(self, service_name: str = "log",
|
||||
batch_size: int = _BATCH_SIZE,
|
||||
flush_interval: float = _FLUSH_INTERVAL):
|
||||
self._service_name = service_name
|
||||
self._batch_size = batch_size
|
||||
self._flush_interval = flush_interval
|
||||
self._queue = queue.Queue(maxsize=_QUEUE_MAXSIZE)
|
||||
self._stop = threading.Event()
|
||||
self._flush_signal = threading.Event()
|
||||
self._flush_done = threading.Event()
|
||||
self._thread = threading.Thread(target=self._flush_loop,
|
||||
daemon=True, name='log-client')
|
||||
self._thread.start()
|
||||
atexit.register(self._shutdown)
|
||||
self._client = RpcClient(
|
||||
_DBV2_ADDR, _DBV2_PORT,
|
||||
service_name + "-log",
|
||||
timeout=_TIMEOUT,
|
||||
)
|
||||
self._queue = AsyncRpcQueue(
|
||||
handler=self._send_batch,
|
||||
batch_size=batch_size,
|
||||
flush_interval=flush_interval,
|
||||
max_queue_size=_QUEUE_MAXSIZE,
|
||||
on_error=self._on_error,
|
||||
)
|
||||
self._queue.start()
|
||||
atexit.register(self.close)
|
||||
|
||||
# ── 公开接口 ────────────────────────────────────────────────────────
|
||||
|
||||
def push(self, service, level, message, trace_id=None, extra=None):
|
||||
def push(self, service: str, level: str, message: str,
|
||||
trace_id: str = None, extra=None):
|
||||
"""推送一条日志（非阻塞，立即返回）。
|
||||
|
||||
队列满时静默丢弃最旧条目再放入新条目，保证不阻塞业务线程、不导致 OOM。
|
||||
"""
|
||||
entry = {
|
||||
'ts': _now_iso(), # 入队时即生成时间戳，反映真实事件时间
|
||||
'ts': _now_iso(),
|
||||
'service': service,
|
||||
'level': level,
|
||||
'message': message,
|
||||
'trace_id': trace_id,
|
||||
'extra': extra,
|
||||
}
|
||||
try:
|
||||
self._queue.put_nowait(entry)
|
||||
except queue.Full:
|
||||
# 队列满：丢弃最旧的一条，再放入新条目（drop-oldest 策略）
|
||||
try:
|
||||
self._queue.get_nowait()
|
||||
except queue.Empty:
|
||||
pass
|
||||
try:
|
||||
self._queue.put_nowait(entry)
|
||||
except queue.Full:
|
||||
pass # 极端竞争下仍失败则静默丢弃
|
||||
self._queue.put(entry)
|
||||
|
||||
def debug(self, service, message, **kw):
|
||||
def debug(self, service: str, message: str, **kw):
|
||||
self.push(service, 'DEBUG', message, **kw)
|
||||
|
||||
def info(self, service, message, **kw):
|
||||
def info(self, service: str, message: str, **kw):
|
||||
self.push(service, 'INFO', message, **kw)
|
||||
|
||||
def warning(self, service, message, **kw):
|
||||
def warning(self, service: str, message: str, **kw):
|
||||
self.push(service, 'WARNING', message, **kw)
|
||||
|
||||
def error(self, service, message, **kw):
|
||||
def warn(self, service: str, message: str, **kw):
|
||||
self.push(service, 'WARNING', message, **kw)
|
||||
|
||||
def error(self, service: str, message: str, **kw):
|
||||
self.push(service, 'ERROR', message, **kw)
|
||||
|
||||
def critical(self, service, message, **kw):
|
||||
def critical(self, service: str, message: str, **kw):
|
||||
self.push(service, 'CRITICAL', message, **kw)
|
||||
|
||||
def flush(self):
|
||||
"""手动 flush 队列中剩余的日志（含后台线程持有的局部 batch）。"""
|
||||
self._flush_done.clear()
|
||||
self._flush_signal.set() # 通知后台线程立即 flush 其局部 batch
|
||||
# 等待后台线程完成 flush（最多等待 flush_interval + 2 秒余量）
|
||||
self._flush_done.wait(timeout=self._flush_interval + 2.0)
|
||||
# 主线程排空队列中剩余条目
|
||||
self._drain_queue_to_db()
|
||||
"""手动 flush 队列中剩余的日志。"""
|
||||
self._queue.flush()
|
||||
|
||||
def _drain_queue_to_db(self):
|
||||
"""排空主线程可见的队列中剩余条目，直接发送到 db。"""
|
||||
batch = []
|
||||
while True:
|
||||
try:
|
||||
batch.append(self._queue.get_nowait())
|
||||
if len(batch) >= self._batch_size:
|
||||
self._send(batch)
|
||||
batch = []
|
||||
except queue.Empty:
|
||||
break
|
||||
if batch:
|
||||
self._send(batch)
|
||||
def close(self):
|
||||
"""关闭客户端，flush 剩余日志。"""
|
||||
self._queue.close()
|
||||
|
||||
# ── 内部实现 ────────────────────────────────────────────────────────
|
||||
|
||||
def _flush_loop(self):
|
||||
"""后台线程：积攒到 batch_size 或超时 flush_interval 时发送。
|
||||
|
||||
外层捕获所有异常，保证后台线程在任何情况下（网络故障、序列化错误等）
|
||||
都不会死亡，避免日志队列无限增长导致 OOM。
|
||||
"""
|
||||
batch = []
|
||||
last_flush = time.monotonic()
|
||||
|
||||
while not self._stop.is_set():
|
||||
try:
|
||||
timeout = self._flush_interval - (time.monotonic() - last_flush)
|
||||
chk_timeout = max(0.1, min(timeout, 0.5))
|
||||
try:
|
||||
item = self._queue.get(timeout=chk_timeout)
|
||||
batch.append(item)
|
||||
while len(batch) < self._batch_size:
|
||||
try:
|
||||
batch.append(self._queue.get_nowait())
|
||||
except queue.Empty:
|
||||
break
|
||||
except queue.Empty:
|
||||
pass
|
||||
|
||||
should_flush = (
|
||||
len(batch) >= self._batch_size or
|
||||
self._flush_signal.is_set() or
|
||||
(batch and time.monotonic() - last_flush >= self._flush_interval)
|
||||
)
|
||||
if should_flush and batch:
|
||||
try:
|
||||
self._send(batch)
|
||||
except Exception as e:
|
||||
# _send 内部已有细粒度异常处理，此处是最终安全网
|
||||
print(f"[log_client] _send 异常（已捕获，线程继续运行）: {e}",
|
||||
file=_sys.stderr)
|
||||
batch = []
|
||||
last_flush = time.monotonic()
|
||||
if self._flush_signal.is_set():
|
||||
self._flush_signal.clear()
|
||||
self._flush_done.set()
|
||||
except Exception as e:
|
||||
# 最外层安全网：任何意外异常都不应杀死日志线程
|
||||
print(f"[log_client] _flush_loop 异常（已捕获，线程继续运行）: {e}",
|
||||
file=_sys.stderr)
|
||||
time.sleep(0.5) # 防止异常风暴导致 CPU 满载
|
||||
|
||||
# 退出前 flush 剩余
|
||||
if batch:
|
||||
try:
|
||||
self._send(batch)
|
||||
except Exception as e:
|
||||
print(f"[log_client] 退出时 flush 异常: {e}", file=_sys.stderr)
|
||||
self._flush_done.set()
|
||||
|
||||
def _send(self, batch):
|
||||
"""通过 pymsg RPC（execute 路由）批量发送到 dbv2 Logs 表。
|
||||
|
||||
整个 batch 复用一个 TCP 连接；网络错误时放弃本批剩余条目（fail-safe），
|
||||
不抛异常给调用方。
|
||||
"""
|
||||
try:
|
||||
client = RpcClient(_DBV2_ADDR, _DBV2_PORT, self._service_name + "-log")
|
||||
except Exception as e:
|
||||
print(f"[log_client] 创建 RpcClient 失败: {e}", file=_sys.stderr)
|
||||
return
|
||||
|
||||
def _send_batch(self, batch: list):
|
||||
"""后台线程回调：逐条 INSERT 到 db（与旧版行为一致：网络错误放弃本批剩余）。"""
|
||||
for entry in batch:
|
||||
extra_val = entry.get("extra")
|
||||
try:
|
||||
@@ -224,21 +140,21 @@ class LogClient:
|
||||
},
|
||||
}
|
||||
try:
|
||||
client.call("execute", payload, timeout=_TIMEOUT)
|
||||
self._client.call("execute", payload, timeout=_TIMEOUT)
|
||||
except RpcError as e:
|
||||
# 业务错误（如表结构不符）：打印后继续下一条
|
||||
print(f"[log_client] INSERT 失败: {e}", file=_sys.stderr)
|
||||
except Exception as e:
|
||||
# 网络错误：db 不可用，放弃本批剩余（fail-safe）
|
||||
print(f"[log_client] 发送失败: {e}", file=_sys.stderr)
|
||||
print(f"[log_client] 发送失败（放弃本批剩余）: {e}", file=_sys.stderr)
|
||||
break
|
||||
|
||||
def _shutdown(self):
|
||||
"""进程退出时 flush 剩余日志。"""
|
||||
self._stop.set()
|
||||
self.flush()
|
||||
def _on_error(self, e: Exception, batch: list):
|
||||
"""异常安全网：handler 外的异常也不会崩溃线程。"""
|
||||
print(f"[log_client] _send_batch 异常（已捕获，线程继续运行）: {e}",
|
||||
file=_sys.stderr)
|
||||
|
||||
|
||||
# ── 全局单例 ──────────────────────────────────────────────────────────
|
||||
# 各服务的 log_client.py 副本需将 service_name 改为自己的服务名。
|
||||
# 此文件（confs/log_client.py）的 service_name 为 "confs"。
|
||||
|
||||
logs = LogClient()
|
||||
logs = LogClient(service_name="static")
|
||||
Reference in new issue
Block a user