duxingchen
3286a11bc7
- 复制来源: /home/yueli/track @ 192c8ee (feature/ai-audit-update) - 组织隔离目标: LICA - 端口规划: 前端 8030 / 后端 8031 / 数据库 8032 - 已排除 deploy.sh、deploy_full.sh、docker-compose.prod.yml（IRIS 生产发布脚本） - 已排除工作区未提交改动，取干净的 192c8ee 状态
155 lines
5.0 KiB
Python
155 lines
5.0 KiB
Python
"""
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MOM 跨库查询缓存模块 — 使用本地 TTL 缓存消除冗余跨库请求
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解决的问题：
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1. _lookup_display_names 在 get_all_products 中被调用 3 次，每次都打开/关闭
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MOM 数据库连接，150 条产品的列表页 = 3 根管线查询。
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2. 同一批 username 在短时间内（用户翻页、多人同时访问）被反复查询。
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3. 旧实现用 OR 拼接 LIKE 条件，存在注入风险。
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方案：python -m 内置模块（零依赖）实现线程安全 TTL 缓存 + 参数化 ANY 查询。
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TTL: 2 小时（人员姓名不会频繁变动，可调）。
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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 app.core.mom_database import MomSessionLocal
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# ============================================================
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# 零依赖 TTL 缓存（线程安全）
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# ============================================================
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class _TTLCache:
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"""线程安全的内存 TTL 缓存，用于 MOM 只读查询结果"""
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def __init__(self, ttl_seconds: int = 7200) -> None:
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self._store: dict[str, str] = {}
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self._expiry: dict[str, float] = {}
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self._ttl = ttl_seconds
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self._lock = threading.RLock()
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def get_many(self, keys: list[str]) -> tuple[dict[str, str], list[str]]:
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"""
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批量获取 → (命中字典, 未命中 key 列表)。
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内部自动清理过期条目。
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"""
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hits: dict[str, str] = {}
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missed: list[str] = []
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now = time.monotonic()
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with self._lock:
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for k in keys:
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exp = self._expiry.get(k)
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if exp is not None and now < exp:
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hits[k] = self._store[k]
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else:
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missed.append(k)
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# 清理过期残留
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if k in self._store:
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del self._store[k]
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del self._expiry[k]
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return hits, missed
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def set_many(self, mapping: dict[str, str]) -> None:
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"""批量写入，所有 key 共享同一过期时间"""
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expiry = time.monotonic() + self._ttl
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with self._lock:
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for k, v in mapping.items():
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self._store[k] = v
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self._expiry[k] = expiry
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# ============================================================
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# 全局缓存实例（2h TTL）
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# ============================================================
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_user_name_cache = _TTLCache(ttl_seconds=7200)
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# ============================================================
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# 公开 API
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# ============================================================
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def get_display_names(user_ids: list[str]) -> dict[str, str]:
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"""
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批量查询 MOM sys_user，将 username 映射为真实姓名（带 2h TTL 缓存）。
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缓存穿透流程：
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1. 去重 → 从缓存批量读取
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2. 计算 miss 差集
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3. miss 非空时，用参数化 ANY(:user_ids) 查 MOM（1 条 SQL）
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4. 写回缓存
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5. 合并 hits + fresh 返回
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参数:
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user_ids: 短用户名列表，如 ["zhangsan01", "lisi02"]
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返回:
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{"zhangsan01": "张三", "lisi02": "李四"}
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不存在的 key 不会出现在返回字典中。
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SQL 安全:
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使用 SPLIT_PART(username, '/', 2) = ANY(:user_ids) 参数化查询，
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杜绝旧实现中 OR 拼接 LIKE 的注入风险。
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"""
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if not user_ids:
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return {}
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# 过滤特殊值 + 去重保序
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seen: set[str] = set()
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real_ids: list[str] = []
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for uid in user_ids:
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if uid and uid != "virtual_warehouse" and uid not in seen:
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seen.add(uid)
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real_ids.append(uid)
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if not real_ids:
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return {}
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# ── Step 1: 批量查缓存 ──
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hits, missed = _user_name_cache.get_many(real_ids)
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# ── Step 2: 仅对 miss 查 MOM ──
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if missed:
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db = MomSessionLocal()
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try:
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from sqlalchemy import text
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# 参数化 ANY 查询 — 安全防注入
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# SPLIT_PART('张三/zhangsan01', '/', 2) = 'zhangsan01'
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# OR username = ANY(...) 兜底无斜杠的用户名（如 admin）
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sql = text("""
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SELECT username,
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SPLIT_PART(username, '/', 1) AS display_name
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FROM sys_user
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WHERE SPLIT_PART(username, '/', 2) = ANY(:user_ids)
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OR username = ANY(:user_ids)
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""")
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result = db.execute(sql, {"user_ids": missed})
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rows = result.fetchall()
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finally:
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db.close()
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# ── Step 3: 解析结果 + 写回缓存 ──
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fresh: dict[str, str] = {}
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for row in rows:
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full_username: str = row[0]
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display_name: str = row[1]
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# "张三/zhangsan01" → short="zhangsan01"
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short = full_username.split("/")[-1] if "/" in full_username else full_username
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fresh[short] = display_name
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if fresh:
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_user_name_cache.set_many(fresh)
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# ── Step 4: 合并 ──
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hits.update(fresh)
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return hits
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