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ThearchyHelios
eddeded2a4
- 第一批（安全加固与生命周期止血）：隔离测试宿主机密钥与 .env 泄漏；修复 SQLite 取消查询挂死、:memory: 连接池报错与 EngineCache 世代竞态；补齐运行与评测删除时的 Checkpointer 线程、Artifact 磁盘文件与无主附件回收；加固三套沙箱路径越界、进程组清理与 Seatbelt 数据目录隔离，封堵 SSRF IPv4-mapped IPv6 元数据绕过与响应体 OOM；修复推理模型多轮 reasoning_content、结构化输出 Token 漏计与缓存折扣计费 - 第二批（数据库/集群/问数提速与首屏分包）：补齐核心表索引与 SQLite WAL 调优，列表接口按需 defer 大列，收敛启动扫描并打通跨进程 slot 槽位唤醒；优化跨源全局选表、哈希桶数字绑定、流式 CSV 导入及多方言分析算子；剥离首屏静态引入的 @xyflow/react 与全局样式（首屏主包降至 461.59 kB），补充流式 rAF 攒批、Store 精细订阅与表单无障碍绑定 - 第三批（架构演进与工程自动化闭环）：记录库超挂接阈值历史版本自动增量归档至单库多表（解除 SQLite 10 库 ATTACH 硬上限）；重构知识库为词面 BM25 与全集合归一化向量矩阵真·双路独立召回并支持游标分批重建；升级多方言感知 SQL 模板词法分析（E'...' / $$...$$ / q'[...]' / # / 嵌套注释）与 Decimal / bool / NaN 参数校验，消除 ledger 层对 api 路由层的反向依赖；拆分 3101 行 CaliberDrafts 页面为 7 个领域子模块，消除检查脚本本机路径硬编码并新增 GitHub Actions CI 门禁与三批回归测试套件
909 lines
43 KiB
Python
909 lines
43 KiB
Python
"""查询区间里这张表有没有数据：运行时现查（查询结果整列是 0、助手搭图自查时用）。
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**为什么要有它。** 部署上撞过：一份周报按 `event_date >= DATE_SUB(CURRENT_DATE, INTERVAL (WEEKDAY(CURRENT_DATE)+7) DAY)
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AND event_date < …` 取上周、上上周的到访人数，那张表却只存最新一天（每天整表重灌），6 列全是 0，口径卡算出一排 0 和 0%，
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周报照写「上周到访人数为 0 人」「周环比 0.00%」。这些 0 不是「没有到访」，是这段时间表里根本没有数据。剖析记过日期列的
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最小、最大值，但对滚动表不可靠（剖析那天表里是前一天的数据，运行时已经换成当天），所以要运行时现查。
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**做什么。** 两个入口共用一套：
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- result_gaps：一次查询的结果里有「整列都是 0 或空」的数值列时（结果一行都没有的不归这里管），对每个这样的列，把 SQL
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收窄到算出这一列的那一项（去掉别的选择项、分组、HAVING、排序、取行数，同双盲复算差异说明的「收窄到这一格」，这里只做
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分析、不执行），取出它用到的表和时间谓词（列、比较符、界）；
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- sql_gaps：助手搭图自查时，工具节点里写死的 SQL 还没跑、没有结果：对 SQL 里所有带时间谓词的表都查。
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界是字面量的直接解析；按运行当天现算的（不含列引用的表达式：CURRENT_DATE、DATE_SUB(…)、date('now', …)……）用同一个数据源
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跑一条 `SELECT 界1, 界2 …` 在库里算出来（Oracle 加 FROM DUAL）。这一列在这张表里的实际范围现查 `SELECT MIN(列), MAX(列)
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FROM 表`（每条探查 PROBE_TIMEOUT_S 秒）；超时或失败退回剖析、取值观察记下的范围（facts，照实标「按 X 日的剖析」），都没有
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就不判。日期按常见写法归一（DATE / DATETIME、'YYYY-MM-DD'、'YYYYMMDD'、8 位整数），认不出就不判；列是文本、界也是文本时
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两边写法要一样（'20261012' 对 '2026-10-12' 按字符串比，结果和按日期比对不上），不一样的不判。区间和实际范围完全不重叠才算
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「没有数据」；一列用到几段区间（本周减上周）时每一段都不重叠才算。
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**和 sqlcheck 一样宁可漏报。** 所有探查都走数据源查询同一道只读守卫（data/guard.check + is_write），遮罩列上的不探查、不报
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值；总耗时有上限（BUDGET_S）；解析不了、认不出、探查失败一律当没问题，出错不影响查询本身（同 tools/datasource._sql_checks）。
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"""
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from __future__ import annotations
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import asyncio
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import logging
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import re
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import time
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from collections import OrderedDict
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from collections.abc import Awaitable, Callable, Iterable, Mapping
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from dataclasses import dataclass, field
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from datetime import date, datetime, timedelta
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from typing import Any
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from app.data.names import name_key
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logger = logging.getLogger(__name__)
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#: 一次检查（一份查询结果、一条自查的 SQL）所有探查加起来最多多少秒
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BUDGET_S = 20.0
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#: 每条探查查询的时限
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PROBE_TIMEOUT_S = 10.0
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#: 一次最多探查几张表的范围、几条按运行当天现算的界：再多就是 SQL 太复杂，不为它把库查一遍
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MAX_RANGES = 8
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MAX_BOUNDS = 24
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#: 太长的 SQL 不分析（同 sqlcheck.MAX_SQL_CHARS）
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MAX_SQL_CHARS = 20_000
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#: 一条 no_data 里最多列几个结果列（计数照实）
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MAX_COLUMNS = 12
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#: 现查到的表的范围在进程里记多久（秒）：同一张表一会儿内查好几次（一张图里几个取数节点、助手自查几轮）不再全表 MIN /
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#: MAX。滚动表一天才换一次数据，几分钟的旧不影响判断；查不成的、退回剖析的不记
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LIVE_TTL_S = 300.0
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SNAPSHOT_LIVE_TTL_S = 86400.0
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_LIVE_MAX = 512
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_LIVE: OrderedDict[tuple[Any, ...], tuple[float, Any]] = OrderedDict()
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#: 现查没成功（大表全表 MIN / MAX 超时、库一时连不上）也记 LIVE_TTL_S：这段时间里同一张表直接退回剖析、取值观察，
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#: 不然取数 agent 连查几次、每次结果里有整列 0，每次都要白等 PROBE_TIMEOUT_S 秒才退回
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_PROBE_FAILED = object()
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#: 给人和模型看的说法
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NO_DATA_MESSAGE = "{columns}查的是 {window}，但 {table} 的 {column} {data}：这些 0 不代表这段时间真的是 0，是这段时间表里没有数据{basis}"
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NO_DATA_SQL_MESSAGE = "查的区间是 {window}，但 {table} 的 {column} {data}{basis}"
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BASIS_PROFILE = "（现查表的范围没有成功，按 {day} 的剖析）"
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BASIS_OBSERVED = "（现查表的范围没有成功，按 {day} 的取值观察）"
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#: 写进口径卡、写作目录、双盲复算原因的那半句
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NO_DATA_SHORT = "查询区间里这张表没有数据"
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#: (表达式的类型, 方言) → 按运行当天现算的界：不认列、不认子查询，函数、字面量、INTERVAL 都可以
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_COMPARE = {"GT": ">", "GTE": ">=", "LT": "<", "LTE": "<=", "EQ": "="}
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_FLIP = {">": "<", ">=": "<=", "<": ">", "<=": ">=", "=": "="}
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_ISO = re.compile(r"^(\d{4})-(\d{1,2})-(\d{1,2})(?:[ T](\d{1,2}):(\d{2})(?::(\d{2})(?:\.\d+)?)?)?"
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r"(?:Z|[+-]\d{2}(?::?\d{2})?)?$")
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_COMPACT = re.compile(r"^(\d{4})(\d{2})(\d{2})$")
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# ==========================================================================
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# 日期的归一
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# ==========================================================================
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@dataclass(frozen=True)
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class _Day:
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"""归一后的一个日期：day 是哪一天，timed 是带不带一天里的时刻（00:00:00 不算），shape 是写法（iso / compact /
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number / date：库交回的是日期类型），kind 是库交回的类型（date / datetime / text / number，字面量按它的写法）。"""
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day: date
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timed: bool
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shape: str
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kind: str
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def _as_day(value: Any, kind: str | None = None) -> _Day | None:
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"""一个值归一成日期；认不出返回 None。kind 是库交回的列类型（run_query 的 column_types），字面量不给。"""
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if isinstance(value, bool) or value is None:
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return None
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if isinstance(value, datetime):
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return _Day(value.date(), bool(value.time().replace(microsecond=0) != datetime.min.time()), "date", "datetime")
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if isinstance(value, date):
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return _Day(value, False, "date", "date")
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if isinstance(value, (int, float)):
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if isinstance(value, float) and not value.is_integer():
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return None
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found = _COMPACT.match(str(int(value)))
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day = _ymd(found.group(1), found.group(2), found.group(3)) if found else None
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return _Day(day, False, "number", kind or "number") if day else None
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if not isinstance(value, str):
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return None
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text = value.strip()
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if found := _COMPACT.match(text):
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day = _ymd(found.group(1), found.group(2), found.group(3))
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return _Day(day, False, "compact", kind or "text") if day else None
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if found := _ISO.match(text):
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day = _ymd(found.group(1), found.group(2), found.group(3))
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if day is None:
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return None
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timed = any(int(found.group(i) or 0) for i in (4, 5, 6))
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shape = "date" if kind in ("date", "datetime") else "iso"
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return _Day(day, timed, shape, kind or "text")
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return None
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def _ymd(y: str, m: str, d: str) -> date | None:
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try:
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return date(int(y), int(m), int(d))
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except ValueError:
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return None
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def _comparable(column: _Day, bound: _Day, *, bare: bool, read: str | None) -> bool:
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"""库里拿这一列和这个界比，是不是按日期在比（我们的判断才对得上）：
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- 列外面套着函数（DATE(x)、STR_TO_DATE(x, …)）：比的是函数的结果，按日期算；
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- 列本身是日期类型：库把文本的界转成日期再比；
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- 界是库算出来的日期类型（DATE_SUB(CURRENT_DATE, …)）、列是文本：MySQL 把文本转成日期再比，别的库不一定（SQLite 的
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date('now') 交回的是文本，照下一条比写法），只认 MySQL；
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- 两边都是文本、都是数：写法得一样（'20261012' 对 '2026-10-12' 按字符串比，和按日期比对不上）。"""
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if not bare or column.kind in ("date", "datetime"):
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return True
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if bound.kind in ("date", "datetime"):
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return read == "mysql" and column.kind == "text"
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if column.kind == "text" and bound.kind == "text":
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return column.shape == bound.shape
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return column.kind == bound.kind == "number" and column.shape == bound.shape == "number"
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# ==========================================================================
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# 从 SQL 里认时间谓词
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# ==========================================================================
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@dataclass
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class _Filter:
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"""一段 SELECT 里对一张实表的一列的时间条件：table / column 是 sqlglot 的节点（探查时照它写 SQL），conds 是
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[(比较符, 界的节点, 列是不是光着的)]。key 按内容认（表、列、各个条件的写法）：几列各自收窄出来的同一段条件是同一个，
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判一次。"""
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key: tuple[Any, ...]
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table: Any
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table_name: str
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column: Any
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column_name: str
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conds: list[tuple[str, Any, bool]] = field(default_factory=list)
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def _read(kind: str | None) -> str | None:
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from app.data.sqlcheck import dialect_of
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return dialect_of(kind)
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def _parse(sql: str, read: str | None) -> Any:
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import sqlglot
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from sqlglot import exp
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if not isinstance(sql, str) or not sql.strip() or len(sql) > MAX_SQL_CHARS or "{{" in sql:
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return None
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try:
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statements = [s for s in sqlglot.parse(sql, read=read) if s is not None]
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except Exception: # noqa: BLE001 - 解析不了就不判
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return None
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if len(statements) != 1 or not isinstance(statements[0], exp.Query):
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return None
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return statements[0]
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def _output_name(item: Any, read: str | None) -> str:
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from sqlglot import exp
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if isinstance(item, exp.Alias):
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return item.alias
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if isinstance(item, exp.Column):
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return item.name
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return item.sql(dialect=read)
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def _same_name(a: str, b: str) -> bool:
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return "".join(a.split()).lower() == "".join(b.split()).lower()
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def narrowed(tree: Any, column: str, read: str | None) -> Any:
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"""收窄到算出 column 这一列的那一项：最外层 SELECT 只留它，分组、HAVING、排序、取行数去掉（只拿来认时间谓词，不执行，
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不用像双盲复算那样按这一行的分组值补等值条件）。认不准的（不是一段 SELECT、SELECT *、对不上或对上好几项）交回整条。"""
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from sqlglot import exp
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if not isinstance(tree, exp.Select):
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return tree
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items = list(tree.expressions)
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if any(isinstance(i, exp.Star) or (isinstance(i, exp.Column) and isinstance(i.this, exp.Star)) for i in items):
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return tree
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hits = [i for i in items if _same_name(_output_name(i, read), column)]
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if len(hits) != 1:
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return tree
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out = tree.copy()
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out.set("expressions", [hits[0].copy()])
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for arg in ("group", "having", "order", "limit", "offset", "qualify"):
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out.set(arg, None)
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return out
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def _columns_in(node: Any) -> list[Any]:
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from sqlglot import exp
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return [c for c in node.find_all(exp.Column) if not isinstance(c.this, exp.Star)]
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def _plain_bound(node: Any) -> bool:
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"""界里没有列、子查询、聚合、窗口：字面量，或者按运行当天现算的表达式。"""
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from sqlglot import exp
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return not _columns_in(node) and not any(
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isinstance(n, (exp.Select, exp.Subquery, exp.AggFunc, exp.Window, exp.Placeholder, exp.Parameter))
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for n in node.walk())
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def _timeish(subject: Any, column: Any, bounds: list[Any]) -> bool:
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"""像是时间条件：列名像日期、时间，或者列套着日期函数、界里有日期函数、像日期的常量、按运行当天现算的写法。"""
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from app.data import sql_semantics as ss
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name = str(column.name or "")
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return bool(ss._temporal_name(name) or ss._timeish_name(name) or ss._datey(subject)
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or any(ss._datey(b) or ss._date_like_literal(b) or ss._now_based(b) for b in bounds))
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def _condition(cond: Any) -> tuple[Any, Any, list[tuple[str, Any]], bool] | None:
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"""一个条件是不是「一列 比 界」：(列, 列那一侧的表达式, [(比较符, 界)], 列是不是光着的)。BETWEEN、IN（常量列表）
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拆成几项；NOT、子查询、两边都有列的不算。"""
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from sqlglot import exp
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from app.data.sqlcheck import _bare_column, _unparen
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n = _unparen(cond)
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if n.args.get("negate"):
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return None
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if isinstance(n, exp.Between):
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subject, pairs = n.this, [(">=", n.args.get("low")), ("<=", n.args.get("high"))]
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elif isinstance(n, exp.In) and n.expressions and not n.args.get("query"):
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subject, pairs = n.this, [("in", e) for e in n.expressions]
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elif type(n).__name__ in _COMPARE and isinstance(n, exp.Binary):
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op = _COMPARE[type(n).__name__]
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left, right = n.this, n.expression
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if _columns_in(left) and not _columns_in(right):
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subject, pairs = left, [(op, right)]
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elif _columns_in(right) and not _columns_in(left):
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subject, pairs = right, [(_FLIP[op], left)]
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else:
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return None
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else:
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return None
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if subject is None or any(b is None or not _plain_bound(b) for _, b in pairs):
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return None
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cols = _columns_in(subject)
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if len(cols) != 1 or any(isinstance(x, (exp.AggFunc, exp.Select, exp.Window)) for x in subject.walk()):
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return None
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return cols[0], subject, pairs, _bare_column(subject) is not None
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def _real_tables(select: Any, ctes: set[str]) -> dict[str, Any]:
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"""这一段 FROM / JOIN 里的实表：{别名或表名的 name_key: 表节点}。CTE、子查询不算。"""
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from sqlglot import exp
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sources = [select.args.get("from_") or select.args.get("from")] + list(select.args.get("joins") or [])
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out: dict[str, Any] = {}
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for source in sources:
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table = getattr(source, "this", None)
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if isinstance(table, exp.Table) and table.name and name_key(table.name) not in ctes:
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out[name_key(table.alias_or_name)] = table
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return out
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def _schema_columns(schema: Mapping[str, Any] | None, table: Any) -> set[str] | None:
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"""表结构里这张表的列（name_key）；表结构里没有这张表为 None。"""
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tables = (schema or {}).get("tables") if isinstance(schema, Mapping) else None
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if not isinstance(tables, Mapping):
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return None
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for name, meta in tables.items():
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if name_key(str(name).rsplit(".", 1)[-1]) == name_key(table.name) and isinstance(meta, Mapping):
|
||
return {name_key(str(c.get("name"))) for c in meta.get("columns") or [] if isinstance(c, Mapping)}
|
||
return None
|
||
|
||
|
||
def filters(tree: Any, schema: Mapping[str, Any] | None = None) -> list[_Filter]:
|
||
"""语法树里各段 SELECT 的 WHERE 中，对实表的一列的时间条件，按（段、表、列）归在一起。"""
|
||
from sqlglot import exp
|
||
|
||
from app.data.sqlcheck import _conjuncts
|
||
|
||
ctes = {name_key(c.alias_or_name) for c in tree.find_all(exp.CTE) if c.alias_or_name}
|
||
found: dict[tuple[int, str, str], _Filter] = {}
|
||
for index, select in enumerate(tree.find_all(exp.Select)):
|
||
where = select.args.get("where")
|
||
if where is None:
|
||
continue
|
||
tables = _real_tables(select, ctes)
|
||
if not tables:
|
||
continue
|
||
for cond in _conjuncts(where.this):
|
||
parsed = _condition(cond)
|
||
if parsed is None:
|
||
continue
|
||
column, subject, pairs, bare = parsed
|
||
if not _timeish(subject, column, [b for _, b in pairs]):
|
||
continue
|
||
if column.table:
|
||
table = tables.get(name_key(column.table))
|
||
elif len(tables) == 1:
|
||
table = next(iter(tables.values()))
|
||
else:
|
||
owners = [t for t in tables.values()
|
||
if name_key(column.name) in (_schema_columns(schema, t) or set())]
|
||
table = owners[0] if len(owners) == 1 else None
|
||
if table is None:
|
||
continue
|
||
shown = ".".join(p for p in (table.catalog, table.db, table.name) if p)
|
||
group = (index, name_key(shown), name_key(column.name))
|
||
entry = found.setdefault(group, _Filter(group, table, shown, column, str(column.name)))
|
||
entry.conds.extend((op, bound, bare) for op, bound in pairs)
|
||
for entry in found.values():
|
||
entry.key = (name_key(entry.table_name), name_key(entry.column_name),
|
||
tuple(sorted((op, bound.sql(), bare) for op, bound, bare in entry.conds)))
|
||
return list(found.values())
|
||
|
||
|
||
# ==========================================================================
|
||
# 探查
|
||
# ==========================================================================
|
||
|
||
|
||
async def _probe(source: Any, sql: str) -> tuple[list[Any], list[str | None]] | None:
|
||
"""在数据源上跑一条探查查询：第一行的值、各列的类型（按位置）。走数据源查询同一道只读守卫；写语句、出错、超时都交回
|
||
None。"""
|
||
from app.data.engine import run_query
|
||
from app.data.guard import QueryLimits, SqlRejected, check, is_write
|
||
|
||
kind = (getattr(source, "kind", None) or "").lower()
|
||
try:
|
||
statement = check(sql, readonly=True, source_name=getattr(source, "name", ""), dialect=kind)
|
||
if is_write(statement, dialect=kind):
|
||
return None
|
||
result = await run_query(source, statement, limits=QueryLimits(timeout_seconds=PROBE_TIMEOUT_S, max_rows=2))
|
||
except (SqlRejected, Exception): # noqa: BLE001 - 探查失败就当不知道
|
||
logger.info("覆盖检查的探查查询没有成功（数据源 %s）", getattr(source, "name", ""), exc_info=True)
|
||
return None
|
||
if not result.rows:
|
||
return None
|
||
types = result.column_types or {}
|
||
return list(result.rows[0]), [types.get(c) for c in result.columns]
|
||
|
||
|
||
def _select_sql(items: list[str], read: str | None) -> str:
|
||
return f"SELECT {', '.join(items)}" + (" FROM DUAL" if read == "oracle" else "")
|
||
|
||
|
||
@dataclass
|
||
class Cache:
|
||
"""同一个数据源上探查过的：表里那一列的范围、按运行当天现算的界。助手自查一轮里查好几次，不重复查库。"""
|
||
|
||
ranges: dict[tuple[str, str, str], Any] = field(default_factory=dict)
|
||
bounds: dict[tuple[str, str], Any] = field(default_factory=dict)
|
||
|
||
|
||
@dataclass
|
||
class _Range:
|
||
"""这一列在这张表里的范围。low / high 为 None 的是不知道那一头；empty 是表里这一列一个值都没有（现查出来的）。"""
|
||
|
||
low: _Day | None
|
||
high: _Day | None
|
||
basis: str
|
||
day: str | None = None
|
||
empty: bool = False
|
||
|
||
|
||
#: 剖析事实（catalog_profile_jobs.last_facts 的一项）：表名 → 那一份，取不到为 None
|
||
Facts = Callable[[str], Awaitable[Mapping[str, Any] | None]]
|
||
|
||
|
||
async def _range(source: Any, flt: _Filter, read: str | None, cache: Cache, facts: Facts | None) -> _Range | None:
|
||
"""这一列在这张表里的范围：现查 MIN / MAX（同一个数据源、同一张表、同一列查一次），查不成退回剖析、取值观察（facts）。"""
|
||
from sqlglot import exp
|
||
|
||
key = (str(getattr(source, "name", "")), name_key(flt.table_name), name_key(flt.column_name))
|
||
if key in cache.ranges:
|
||
return cache.ranges[key]
|
||
snapshot_id = getattr(source, "snapshot_id", None)
|
||
live = (getattr(source, "id", None), snapshot_id, *key)
|
||
held = _LIVE.get(live)
|
||
failed_before = False
|
||
if held is not None:
|
||
if held[0] > time.monotonic():
|
||
_LIVE.move_to_end(live)
|
||
if held[1] is not _PROBE_FAILED:
|
||
cache.ranges[key] = held[1]
|
||
return held[1]
|
||
failed_before = True
|
||
else:
|
||
_LIVE.pop(live, None)
|
||
table = flt.table.copy()
|
||
table.set("alias", None)
|
||
ident = flt.column.this.copy() if isinstance(flt.column.this, exp.Identifier) \
|
||
else exp.to_identifier(flt.column_name)
|
||
column = exp.Column(this=ident)
|
||
sql = (f"SELECT {exp.Min(this=column.copy()).sql(dialect=read)} AS lo, "
|
||
f"{exp.Max(this=column.copy()).sql(dialect=read)} AS hi FROM {table.sql(dialect=read)}")
|
||
found = None if failed_before else await _probe(source, sql)
|
||
out: _Range | None = None
|
||
if found is not None:
|
||
values, kinds = found
|
||
low_raw, high_raw = (values + [None, None])[:2]
|
||
kinds = (kinds + [None, None])[:2]
|
||
if low_raw is None and high_raw is None:
|
||
out = _Range(None, None, "live", empty=True)
|
||
else:
|
||
low, high = _as_day(low_raw, kinds[0]), _as_day(high_raw, kinds[1])
|
||
out = _Range(low, high, "live") if low is not None and high is not None else None
|
||
elif facts is not None:
|
||
out = await _fallback(flt, facts)
|
||
cache.ranges[key] = out
|
||
if found is None and not failed_before:
|
||
_remember(live, _PROBE_FAILED, ttl=LIVE_TTL_S)
|
||
elif out is not None and out.basis == "live":
|
||
ttl = SNAPSHOT_LIVE_TTL_S if snapshot_id else LIVE_TTL_S
|
||
_remember(live, out, ttl=ttl)
|
||
return out
|
||
|
||
|
||
def _remember(live: tuple[Any, ...], value: Any, *, ttl: float = LIVE_TTL_S) -> None:
|
||
_LIVE.pop(live, None)
|
||
while len(_LIVE) >= _LIVE_MAX:
|
||
_LIVE.popitem(last=False)
|
||
_LIVE[live] = (time.monotonic() + ttl, value)
|
||
|
||
|
||
async def _fallback(flt: _Filter, facts: Facts) -> _Range | None:
|
||
"""现查不成：退回剖析记下的范围（date_ranges），再不然取值观察的最新日期（freshness，只知道最晚那一头）。"""
|
||
try:
|
||
found = await facts(flt.table_name)
|
||
except Exception: # noqa: BLE001
|
||
return None
|
||
return _facts_range(found, flt.column_name)
|
||
|
||
|
||
def _facts_range(found: Any, column: str) -> _Range | None:
|
||
"""剖析事实（last_facts 的一项）里这一列的范围：先剖析的 date_ranges，再取值观察的最新日期。"""
|
||
if not isinstance(found, Mapping):
|
||
return None
|
||
wanted = name_key(column)
|
||
for item in found.get("date_ranges") or []:
|
||
if isinstance(item, Mapping) and name_key(str(item.get("column") or "")) == wanted:
|
||
lo, hi = _as_day(item.get("min")), _as_day(item.get("max"))
|
||
if lo is not None and hi is not None:
|
||
return _Range(lo, hi, "profile", day=str(found.get("at") or "")[:10] or None)
|
||
observed = found.get("observed") if isinstance(found.get("observed"), Mapping) else {}
|
||
for item in observed.get("freshness") or []:
|
||
if isinstance(item, Mapping) and name_key(str(item.get("column") or "")) == wanted:
|
||
hi = _as_day(item.get("max"))
|
||
if hi is not None:
|
||
return _Range(None, hi, "observed", day=str(item.get("at") or "")[:10] or None)
|
||
return None
|
||
|
||
|
||
def _literal_day(node: Any) -> _Day | None:
|
||
from sqlglot import exp
|
||
|
||
from app.data.sqlcheck import _unparen
|
||
|
||
node = _unparen(node)
|
||
negative = False
|
||
if isinstance(node, exp.Neg):
|
||
node, negative = _unparen(node.this), True
|
||
if not isinstance(node, exp.Literal) or negative:
|
||
return None
|
||
if node.is_string:
|
||
return _as_day(str(node.this))
|
||
try:
|
||
value = int(str(node.this))
|
||
except ValueError:
|
||
return None
|
||
return _as_day(value)
|
||
|
||
|
||
def _is_literal(node: Any) -> bool:
|
||
from sqlglot import exp
|
||
|
||
from app.data.sqlcheck import _unparen
|
||
|
||
node = _unparen(node)
|
||
if isinstance(node, exp.Neg):
|
||
node = _unparen(node.this)
|
||
return isinstance(node, exp.Literal)
|
||
|
||
|
||
async def _bounds(source: Any, nodes: list[Any], read: str | None, cache: Cache) -> dict[int, _Day | None]:
|
||
"""各个界归一成日期：字面量直接解析，别的（按运行当天现算的表达式）一条 SELECT 在库里算出来。{id(节点): 日期}。"""
|
||
out: dict[int, _Day | None] = {}
|
||
pending: dict[str, list[int]] = {}
|
||
name = str(getattr(source, "name", ""))
|
||
for node in nodes:
|
||
if _is_literal(node):
|
||
out[id(node)] = _literal_day(node)
|
||
continue
|
||
try:
|
||
text = node.sql(dialect=read)
|
||
except Exception: # noqa: BLE001
|
||
out[id(node)] = None
|
||
continue
|
||
if (name, text) in cache.bounds:
|
||
out[id(node)] = cache.bounds[(name, text)]
|
||
else:
|
||
pending.setdefault(text, []).append(id(node))
|
||
texts = list(pending)[:MAX_BOUNDS]
|
||
found = await _probe(source, _select_sql([f"{t} AS b{i}" for i, t in enumerate(texts)], read)) if texts else None
|
||
for i, text in enumerate(pending):
|
||
day = None
|
||
if found is not None and i < len(texts):
|
||
values, kinds = found
|
||
day = _as_day(values[i], kinds[i]) if i < len(values) and i < len(kinds) else None
|
||
if i < len(texts):
|
||
cache.bounds[(name, text)] = day
|
||
for ident in pending[text]:
|
||
out[ident] = day
|
||
return out
|
||
|
||
|
||
@dataclass(frozen=True)
|
||
class Window:
|
||
"""一段时间条件的范围（按天，两头都含）。start / end 为 None 的是那一头没有限制。"""
|
||
|
||
start: date | None
|
||
end: date | None
|
||
|
||
|
||
def _window(conds: list[tuple[str, Any, bool]], days: Mapping[int, _Day | None], data: _Range,
|
||
read: str | None) -> Window | None:
|
||
"""几个条件合成一段：下界取最晚的、上界取最早的；IN 列表取最早到最晚（中间没列到的日子也算进去，宁可判成有重叠）。
|
||
有一个界认不出、或者和列比不起来，整段不判（None）。「>」「<」的界不带时刻时按天挪一天（> 2026-10-11 从 10-12 算起）；
|
||
带时刻的不挪（那一天里还可能有数据，宁可判成有重叠）。"""
|
||
lows: list[date] = []
|
||
highs: list[date] = []
|
||
points: list[date] = []
|
||
sample = data.high or data.low
|
||
for op, node, bare in conds:
|
||
day = days.get(id(node))
|
||
if day is None or (sample is not None and not _comparable(sample, day, bare=bare, read=read)):
|
||
return None
|
||
if op == "in":
|
||
points.append(day.day)
|
||
continue
|
||
if op in (">=", "="):
|
||
lows.append(day.day)
|
||
elif op == ">":
|
||
lows.append(day.day if day.timed else day.day + timedelta(days=1))
|
||
if op in ("<=", "="):
|
||
highs.append(day.day)
|
||
elif op == "<":
|
||
highs.append(day.day if day.timed else day.day - timedelta(days=1))
|
||
if points:
|
||
lows.append(min(points))
|
||
highs.append(max(points))
|
||
start = max(lows) if lows else None
|
||
end = min(highs) if highs else None
|
||
if start is None and end is None:
|
||
return None
|
||
if start is not None and end is not None and start > end:
|
||
return None
|
||
return Window(start, end)
|
||
|
||
|
||
def _disjoint(window: Window, data: _Range) -> bool:
|
||
"""区间和表里的范围完全不重叠（表里这一列一个值都没有也算）。"""
|
||
if data.empty:
|
||
return True
|
||
if window.end is not None and data.low is not None and window.end < data.low.day:
|
||
return True
|
||
return window.start is not None and data.high is not None and window.start > data.high.day
|
||
|
||
|
||
# ==========================================================================
|
||
# 说法
|
||
# ==========================================================================
|
||
|
||
|
||
def _window_text(window: Window) -> str:
|
||
if window.start is not None and window.end is not None:
|
||
return window.start.isoformat() if window.start == window.end \
|
||
else f"{window.start.isoformat()} 到 {window.end.isoformat()}"
|
||
if window.start is not None:
|
||
return f"{window.start.isoformat()} 起"
|
||
return f"{window.end.isoformat()} 及以前" # type: ignore[union-attr]
|
||
|
||
|
||
def _data_text(data: _Range) -> str:
|
||
if data.empty:
|
||
return "一个值都没有"
|
||
if data.low is not None and data.high is not None:
|
||
if data.low.day == data.high.day:
|
||
return f"只有 {data.low.day.isoformat()} 这一天的数据"
|
||
return f"只有 {data.low.day.isoformat()} 到 {data.high.day.isoformat()} 的数据"
|
||
return f"最新只到 {data.high.day.isoformat()}" # type: ignore[union-attr]
|
||
|
||
|
||
def _basis_text(data: _Range) -> str:
|
||
if data.basis == "profile":
|
||
return BASIS_PROFILE.format(day=data.day or "上次")
|
||
if data.basis == "observed":
|
||
return BASIS_OBSERVED.format(day=data.day or "上次")
|
||
return ""
|
||
|
||
|
||
def _columns_text(columns: list[str]) -> str:
|
||
head = f"「{columns[0]}」"
|
||
return f"{head}等 {len(columns)} 列" if len(columns) > 1 else head
|
||
|
||
|
||
def _range_dict(data: _Range) -> list[str | None] | None:
|
||
if data.empty:
|
||
return None
|
||
return [data.low.day.isoformat() if data.low else None, data.high.day.isoformat() if data.high else None]
|
||
|
||
|
||
def _window_dict(window: Window) -> list[str | None]:
|
||
return [window.start.isoformat() if window.start else None, window.end.isoformat() if window.end else None]
|
||
|
||
|
||
# ==========================================================================
|
||
# 入口
|
||
# ==========================================================================
|
||
|
||
|
||
def zero_columns(payload: Mapping[str, Any]) -> list[str]:
|
||
"""查询结果里「整列都是 0 或空」的数值列（按 column_types 是数的、或者没记类型却全是数和空值的）。一行都没有的结果
|
||
返回空列表：那归「没有查到」管，不归这里。"""
|
||
from app.engine.expressions import numeric_text
|
||
|
||
columns = [str(c) for c in payload.get("columns") or []]
|
||
rows = payload.get("rows") or []
|
||
if not columns or not isinstance(rows, list) or not rows:
|
||
return []
|
||
types = payload.get("column_types") if isinstance(payload.get("column_types"), Mapping) else {}
|
||
out: list[str] = []
|
||
for index, column in enumerate(columns):
|
||
if types.get(column) not in (None, "number"):
|
||
continue
|
||
values = [row[index] if isinstance(row, (list, tuple)) and index < len(row)
|
||
else (row.get(column) if isinstance(row, Mapping) else None) for row in rows]
|
||
|
||
def zero(value: Any) -> bool:
|
||
if value is None:
|
||
return True
|
||
if isinstance(value, bool):
|
||
return False
|
||
if isinstance(value, (int, float)):
|
||
return value == 0
|
||
number = numeric_text(value) if isinstance(value, str) else None
|
||
return number is not None and number == 0
|
||
|
||
if all(zero(v) for v in values):
|
||
out.append(column)
|
||
return out
|
||
|
||
|
||
async def _judge(source: Any, flts: list[_Filter], read: str | None, cache: Cache, facts: Facts | None,
|
||
masked: set[str], deadline: float) -> dict[tuple[int, str, str], tuple[str, Window | None, _Range | None]]:
|
||
"""每段时间条件判一下：none（区间里表里没有数据）/ some（有重叠）/ unknown（判断不了），带上区间和范围。"""
|
||
out: dict[tuple[int, str, str], tuple[str, Window | None, _Range | None]] = {}
|
||
ranges: dict[tuple[str, str], _Range | None] = {}
|
||
usable = [f for f in flts if name_key(f.column_name) not in masked]
|
||
for flt in flts:
|
||
if flt not in usable:
|
||
out[flt.key] = ("unknown", None, None)
|
||
for flt in usable:
|
||
if time.monotonic() > deadline:
|
||
out[flt.key] = ("unknown", None, None)
|
||
continue
|
||
rkey = (name_key(flt.table_name), name_key(flt.column_name))
|
||
if rkey not in ranges:
|
||
ranges[rkey] = await _range(source, flt, read, cache, facts) if len(ranges) < MAX_RANGES else None
|
||
data = ranges[rkey]
|
||
if data is None:
|
||
out[flt.key] = ("unknown", None, None)
|
||
continue
|
||
days = await _bounds(source, [node for _, node, _ in flt.conds], read, cache)
|
||
window = _window(flt.conds, days, data, read)
|
||
if window is None:
|
||
out[flt.key] = ("unknown", None, data)
|
||
else:
|
||
out[flt.key] = ("none" if _disjoint(window, data) else "some", window, data)
|
||
return out
|
||
|
||
|
||
async def result_gaps(source: Any, sql: str, payload: Mapping[str, Any], *, facts: Facts | None = None,
|
||
masked: Iterable[str] = (), cache: Cache | None = None,
|
||
budget: float = BUDGET_S) -> list[dict[str, Any]]:
|
||
"""一份查询结果里，整列是 0 或空、而查询区间里这张表没有数据的那几列：[{columns, table, column, window, data_range,
|
||
basis, basis_at?, message}]，同一张表、同一列、同一段区间的几列并成一条。没有问题（或者判断不了）返回空列表。从不抛异常。"""
|
||
try:
|
||
return await asyncio.wait_for(_result_gaps(source, sql, payload, facts, set(masked), cache or Cache(), budget),
|
||
timeout=budget + PROBE_TIMEOUT_S)
|
||
except asyncio.TimeoutError:
|
||
logger.warning("覆盖检查超过时限，本次跳过（数据源 %s）", getattr(source, "name", ""))
|
||
except Exception: # noqa: BLE001 - 检查不能让一次成功的查询变成失败
|
||
logger.exception("覆盖检查出错，本次跳过（数据源 %s）", getattr(source, "name", ""))
|
||
return []
|
||
|
||
|
||
async def _result_gaps(source: Any, sql: str, payload: Mapping[str, Any], facts: Facts | None, masked: set[str],
|
||
cache: Cache, budget: float) -> list[dict[str, Any]]:
|
||
zeros = zero_columns(payload)
|
||
if not zeros:
|
||
return []
|
||
read = _read(getattr(source, "kind", None))
|
||
tree = _parse(sql, read)
|
||
if tree is None:
|
||
return []
|
||
masked = {m.strip().lower() for m in masked if isinstance(m, str) and m.strip()}
|
||
schema = getattr(source, "schema_cache", None)
|
||
per_column = {c: filters(narrowed(tree, c, read), schema) for c in zeros if c.lower() not in masked}
|
||
every = {f.key: f for flts in per_column.values() for f in flts}
|
||
if not every:
|
||
return []
|
||
judged = await _judge(source, list(every.values()), read, cache, facts, masked, time.monotonic() + budget)
|
||
groups: dict[tuple[Any, ...], dict[str, Any]] = {}
|
||
for column, flts in per_column.items():
|
||
verdicts = [judged.get(f.key) for f in flts]
|
||
if not flts or any(v is None or v[0] != "none" for v in verdicts):
|
||
continue
|
||
for flt, (_, window, data) in zip(flts, verdicts):
|
||
gkey = (name_key(flt.table_name), name_key(flt.column_name), window, data.basis if data else None)
|
||
group = groups.setdefault(gkey, {"flt": flt, "window": window, "data": data, "columns": []})
|
||
if column not in group["columns"]:
|
||
group["columns"].append(column)
|
||
out = []
|
||
for group in groups.values():
|
||
flt, window, data, columns = group["flt"], group["window"], group["data"], group["columns"]
|
||
out.append({
|
||
"columns": columns[:MAX_COLUMNS], "table": flt.table_name, "column": flt.column_name,
|
||
"window": _window_dict(window), "data_range": _range_dict(data), "basis": data.basis,
|
||
**({"basis_at": data.day} if data.day else {}),
|
||
"message": NO_DATA_MESSAGE.format(columns=_columns_text(columns), window=_window_text(window),
|
||
table=flt.table_name, column=flt.column_name,
|
||
data=_data_text(data), basis=_basis_text(data)),
|
||
})
|
||
return out
|
||
|
||
|
||
async def sql_gaps(source: Any, sql: str, *, facts: Facts | None = None, masked: Iterable[str] = (),
|
||
cache: Cache | None = None, budget: float = BUDGET_S) -> list[dict[str, Any]]:
|
||
"""还没执行的一条 SQL（助手自查）：SQL 里每一段时间条件，区间和表里的范围完全不重叠的那几段：[{table, column,
|
||
window, data_range, basis, basis_at?, message}]，同一张表、同一列、同一段区间只算一条。从不抛异常。"""
|
||
try:
|
||
return await asyncio.wait_for(_sql_gaps(source, sql, facts, set(masked), cache or Cache(), budget),
|
||
timeout=budget + PROBE_TIMEOUT_S)
|
||
except asyncio.TimeoutError:
|
||
logger.warning("自查的覆盖检查超过时限，本次跳过（数据源 %s）", getattr(source, "name", ""))
|
||
except Exception: # noqa: BLE001
|
||
logger.exception("自查的覆盖检查出错，本次跳过（数据源 %s）", getattr(source, "name", ""))
|
||
return []
|
||
|
||
|
||
async def _sql_gaps(source: Any, sql: str, facts: Facts | None, masked: set[str], cache: Cache,
|
||
budget: float) -> list[dict[str, Any]]:
|
||
read = _read(getattr(source, "kind", None))
|
||
tree = _parse(sql, read)
|
||
if tree is None:
|
||
return []
|
||
masked = {m.strip().lower() for m in masked if isinstance(m, str) and m.strip()}
|
||
flts = filters(tree, getattr(source, "schema_cache", None))
|
||
if not flts:
|
||
return []
|
||
judged = await _judge(source, flts, read, cache, facts, masked, time.monotonic() + budget)
|
||
out: list[dict[str, Any]] = []
|
||
seen: set[tuple[Any, ...]] = set()
|
||
for flt in flts:
|
||
verdict, window, data = judged.get(flt.key, ("unknown", None, None))
|
||
key = (name_key(flt.table_name), name_key(flt.column_name), window)
|
||
if verdict != "none" or window is None or data is None or key in seen:
|
||
continue
|
||
seen.add(key)
|
||
out.append({"table": flt.table_name, "column": flt.column_name, "window": _window_dict(window),
|
||
"data_range": _range_dict(data), "basis": data.basis, **({"basis_at": data.day} if data.day else {}),
|
||
"message": NO_DATA_SQL_MESSAGE.format(window=_window_text(window), table=flt.table_name,
|
||
column=flt.column_name, data=_data_text(data),
|
||
basis=_basis_text(data))})
|
||
return out
|
||
|
||
|
||
# ==========================================================================
|
||
# 读快照里记下的
|
||
# ==========================================================================
|
||
|
||
|
||
def no_data_of(snapshot: Any, column: Any) -> dict[str, Any] | None:
|
||
"""查询快照里记着 column 这一列「查询区间里这张表没有数据」的那一条（no_data）；没有为 None。按列名认（不分大小写、
|
||
不计空白）。"""
|
||
if not isinstance(snapshot, Mapping) or not isinstance(column, str):
|
||
return None
|
||
for item in snapshot.get("no_data") or []:
|
||
if isinstance(item, Mapping) and any(isinstance(c, str) and _same_name(c, column)
|
||
for c in item.get("columns") or []):
|
||
return dict(item)
|
||
return None
|
||
|
||
|
||
# ==========================================================================
|
||
# 给分析的可比性检查用的几个小函数（app/analysis/comparable.py、probe.py：窗口长度、整期）。读法、写法、探查都和上面同一套，
|
||
# 只是把中间结果交出去：分析结论要把现查的范围、在库里算出的界记下来，复算时用记下的值
|
||
# ==========================================================================
|
||
|
||
|
||
def parse_sql(sql: Any, read: str | None) -> Any:
|
||
"""一条查询解析成语法树（同覆盖检查：太长、带模板占位、不止一条、不是查询的为 None）。"""
|
||
return _parse(sql, read)
|
||
|
||
|
||
def as_day(value: Any, kind: str | None = None) -> _Day | None:
|
||
"""一个值归一成日期（DATE / DATETIME、'YYYY-MM-DD'、'YYYYMMDD'、8 位整数）；认不出为 None。"""
|
||
return _as_day(value, kind)
|
||
|
||
|
||
def literal_bound(node: Any) -> tuple[bool, _Day | None]:
|
||
"""时间条件的一个界：(是不是字面量, 字面量归一成的日期)。不是字面量的是按运行当天现算的，要在库里算。"""
|
||
return (True, _literal_day(node)) if _is_literal(node) else (False, None)
|
||
|
||
|
||
def window_of(conds: list[tuple[str, Any, bool]], days: Mapping[int, _Day | None]) -> Window | None:
|
||
"""几个条件合成一段区间（同 _window：下界取最晚、上界取最早，「>」「<」的界不带时刻时按天挪一天）。days 是
|
||
{id(界的节点): 日期}。不核对列和界的写法比不比得起来：分析结论里表的范围只记了日期。"""
|
||
return _window(conds, days, _Range(None, None, "none"), None)
|
||
|
||
|
||
def _range_out(data: _Range | None) -> dict[str, Any] | None:
|
||
if data is None:
|
||
return None
|
||
return {"min": data.low.day.isoformat() if data.low else None,
|
||
"max": data.high.day.isoformat() if data.high else None,
|
||
"basis": data.basis, "at": data.day, "empty": data.empty}
|
||
|
||
|
||
def facts_range(found: Any, column: str) -> dict[str, Any] | None:
|
||
"""剖析事实（catalog_profile_jobs.last_facts 的一项）里这一列的范围，形状同 column_range；没有为 None。"""
|
||
return _range_out(_facts_range(found, column))
|
||
|
||
|
||
async def column_range(source: Any, table: str, column: str, *, facts: Facts | None = None,
|
||
cache: Cache | None = None) -> dict[str, Any] | None:
|
||
"""这一列在这张表里的实际范围：现查 MIN / MAX（只读守卫、PROBE_TIMEOUT_S 秒、同一张表 LIVE_TTL_S 秒内不重查），查不成
|
||
退回剖析、取值观察（facts）。{min, max, basis, at, empty}：min / max 是 ISO 日期（不知道的那一头为 None），basis 是 live /
|
||
profile / observed，at 是剖析、观察的日期（现查为 None），表里这一列一个值都没有时 empty 为真。都没有为 None。从不抛异常。"""
|
||
from sqlglot import exp
|
||
|
||
try:
|
||
parts = [p for p in str(table).split(".") if p]
|
||
node = exp.Table(this=exp.to_identifier(parts[-1]),
|
||
**({"db": exp.to_identifier(parts[-2])} if len(parts) > 1 else {}))
|
||
flt = _Filter((), node, str(table), exp.column(str(column)), str(column))
|
||
return _range_out(await _range(source, flt, _read(getattr(source, "kind", None)), cache or Cache(), facts))
|
||
except Exception: # noqa: BLE001 - 探查失败就当不知道
|
||
logger.info("可比性检查的范围探查没有成功（数据源 %s）", getattr(source, "name", ""), exc_info=True)
|
||
return None
|
||
|
||
|
||
async def bound_values(source: Any, texts: list[str]) -> list[Any] | None:
|
||
"""按运行当天现算的几个界（SQL 表达式，按这个数据源的方言写）在库里算出来：一条 SELECT 界1, 界2 …（Oracle 加 FROM
|
||
DUAL），走只读守卫和 PROBE_TIMEOUT_S。交回各个值（日期、时刻按 ISO 写，其余照库里交回的）；查不成为 None。从不抛异常。"""
|
||
if not texts:
|
||
return []
|
||
read = _read(getattr(source, "kind", None))
|
||
try:
|
||
found = await _probe(source, _select_sql([f"{t} AS b{i}" for i, t in enumerate(texts)], read))
|
||
except Exception: # noqa: BLE001
|
||
return None
|
||
if found is None:
|
||
return None
|
||
values = list(found[0]) + [None] * len(texts)
|
||
out: list[Any] = []
|
||
for value in values[:len(texts)]:
|
||
if isinstance(value, datetime):
|
||
out.append(value.isoformat(sep=" ", timespec="seconds"))
|
||
elif isinstance(value, date):
|
||
out.append(value.isoformat())
|
||
else:
|
||
out.append(value)
|
||
return out
|
||
|
||
|
||
__all__ = ["BUDGET_S", "Cache", "NO_DATA_SHORT", "PROBE_TIMEOUT_S", "Window", "as_day", "bound_values", "column_range",
|
||
"facts_range", "filters", "literal_bound", "narrowed", "no_data_of", "parse_sql", "result_gaps", "sql_gaps",
|
||
"window_of", "zero_columns"]
|