mirror of
https://github.com/ThearchyHelios/AgentLab.git
synced 2026-11-15 22:01:58 +00:00
ThearchyHelios
1349 lines
71 KiB
Python
1349 lines
71 KiB
Python
"""数据剖析：对业务库发少量只读查询，验证数据目录里推断出来的关联关系，补上基数、覆盖率和码值候选。
|
||
|
||
**为什么要有它。** 命名推断只看列名，可能推错，也给不出基数和覆盖率；而只有 verified、confirmed 的关系才会
|
||
触发错误级的 SQL 检查。剖析拿数据说话：从子表抽一批不同的键值去父表里对，对得上、父键唯一的升为 verified
|
||
（来源记为 profile，和外键约束的 fk 分开），对不上的保持 proposed 并在备注里写明覆盖率。顺带给状态类的列
|
||
取一次取值分布（码值候选，含义留给人填），给只有一个日期列的表提议业务日期。
|
||
|
||
**这是数据目录里唯一会对业务库发查询的地方**，约束都是硬的：
|
||
|
||
- 默认关闭，按数据源在 options.catalog_profile 里开启（profile_settings）；
|
||
- 每条查询先过守卫的只读判定（不论数据源本身可写与否），再交给查询层 run_query：同一套连接、守卫和
|
||
时限，不另开连接；
|
||
- 每条查询有时限（不超过数据源自己的查询时限），每次剖析有查询次数上限和总时长上限；
|
||
- 表有多大先看数据库的统计信息，没有统计信息就数到上限为止，不做全表 COUNT；超过上限的表不做
|
||
COUNT(DISTINCT)、MIN/MAX 这类整表统计，抽样和取值分布也只看前若干行；
|
||
- 数据源设置里遮罩的列不取样，也不出现在任何一条剖析查询里；
|
||
- 只取低基数列的取值分布（最多 21 个取值），不取明细行。
|
||
"""
|
||
from __future__ import annotations
|
||
|
||
import copy
|
||
import logging
|
||
import re
|
||
import time
|
||
from collections.abc import Awaitable, Callable
|
||
from dataclasses import asdict, dataclass, field
|
||
from decimal import Decimal
|
||
from typing import Any
|
||
|
||
from sqlalchemy.dialects import mysql, oracle, postgresql, sqlite
|
||
from sqlalchemy.ext.asyncio import AsyncSession
|
||
|
||
from app.data import catalog, guard
|
||
from app.data import engine as data_engine
|
||
from app.data.engine import CATALOG_PROFILE_OPTION, QueryResult, SnapshotTampered
|
||
from app.data.guard import QueryLimits, SqlRejected
|
||
|
||
logger = logging.getLogger(__name__)
|
||
|
||
#: 数据源 options 里剖析设置的键
|
||
PROFILE_OPTION = CATALOG_PROFILE_OPTION
|
||
|
||
|
||
# ==========================================================================
|
||
# 设置
|
||
# ==========================================================================
|
||
|
||
|
||
@dataclass(frozen=True)
|
||
class ProfileSettings:
|
||
"""一个数据源的剖析设置。缺省即「关闭」：剖析会对业务库发查询，必须有人按源明确打开。"""
|
||
|
||
enabled: bool = False
|
||
#: 一次剖析最多发几条查询（读统计信息、抽样、核对都算）。用完就停，剩下的记为「查询次数用完」
|
||
max_queries: int = 60
|
||
#: 单条查询的时限（秒）。实际取它和数据源自己的查询时限中较小的一个
|
||
query_timeout_s: float = 10
|
||
#: 每条关系从子表抽多少个不同的键值去父表里对
|
||
sample_size: int = 2000
|
||
#: 行数不超过它的表才做 COUNT(DISTINCT)、MIN/MAX 这类整表统计；更大的、或者不知道多大的表只看前若干行。
|
||
#: 填 0 表示一律不做整表统计
|
||
max_scan_rows: int = 100_000
|
||
#: 一次剖析的总时长上限（秒）。接口是同步的，不能让一个请求无限地挂着
|
||
max_total_s: float = 120
|
||
|
||
def to_dict(self) -> dict[str, Any]:
|
||
return asdict(self)
|
||
|
||
|
||
#: 数值项：(中文叫法, 下限, 上限, 是否必须是整数)。叫法和数据源设置里剖析预算的标签一致（frontend/src/lib/terms.ts），
|
||
#: 报错里只写它
|
||
_NUMBER_FIELDS: dict[str, tuple[str, float, float, bool]] = {
|
||
"max_queries": ("查询次数上限", 1, 500, True),
|
||
"query_timeout_s": ("单条查询时限（秒）", 1, 60, False),
|
||
"sample_size": ("抽样键值数", 10, 10_000, True),
|
||
"max_scan_rows": ("整表统计行数上限", 0, 10_000_000, True),
|
||
"max_total_s": ("总时长上限（秒）", 10, 600, False),
|
||
}
|
||
_ENABLED_LABEL = "开启数据剖析"
|
||
_KNOWN_KEYS = frozenset({"enabled", *_NUMBER_FIELDS})
|
||
|
||
|
||
def _fmt(value: float) -> str:
|
||
return str(int(value)) if float(value).is_integer() else f"{value:g}"
|
||
|
||
|
||
def _number(value: Any, low: float, high: float, integer: bool) -> int | float | None:
|
||
"""设置里的一个数：数字和数字写成的文字都认（表单存的常是文字）。不合规返回 None。"""
|
||
if value is None or isinstance(value, bool):
|
||
return None
|
||
try:
|
||
number = float(str(value).strip())
|
||
except ValueError:
|
||
return None
|
||
if number != number or not low <= number <= high: # NaN 也在这里挡掉
|
||
return None
|
||
if number.is_integer():
|
||
return int(number)
|
||
return None if integer else number
|
||
|
||
|
||
def profile_settings(options: dict[str, Any] | None) -> ProfileSettings:
|
||
"""options → 剖析设置。读的时候宽松：库里存着的某一项不对（老数据、手改过），那一项用缺省，不报错；
|
||
开关只认 true，写成别的一律当作没开。"""
|
||
raw = (options or {}).get(PROFILE_OPTION)
|
||
if not isinstance(raw, dict):
|
||
return ProfileSettings()
|
||
values: dict[str, Any] = {"enabled": raw.get("enabled") is True}
|
||
for key, (_, low, high, integer) in _NUMBER_FIELDS.items():
|
||
number = _number(raw.get(key), low, high, integer)
|
||
if number is not None:
|
||
values[key] = number
|
||
return ProfileSettings(**values)
|
||
|
||
|
||
def profile_settings_problem(options: dict[str, Any] | None) -> str | None:
|
||
"""保存数据源时查一下剖析设置；没填、或者填对了返回 None。写的时候严格：不认识的项、超出范围的值都拒。"""
|
||
found = profile_settings_rejection(options)
|
||
return found[0] if found else None
|
||
|
||
|
||
def profile_settings_rejection(options: dict[str, Any] | None) -> tuple[str, str | None] | None:
|
||
"""同 profile_settings_problem，另给出错的是哪一项：(给人看的一句, 字段名)。字段名是 enabled 或 _NUMBER_FIELDS
|
||
的键（max_queries……），格式不对、有认不出的项时为 None。接口带着它回 422，表单不必从原话里认是哪一格。"""
|
||
raw = (options or {}).get(PROFILE_OPTION)
|
||
if raw is None:
|
||
return None
|
||
if not isinstance(raw, dict):
|
||
return "数据剖析设置的格式不正确，请在数据源设置中重新填写", None
|
||
if unknown := sorted(set(raw) - _KNOWN_KEYS):
|
||
return f"数据剖析设置中有无法识别的项「{'、'.join(map(str, unknown))}」，请删除后重试", None
|
||
if "enabled" in raw and not isinstance(raw["enabled"], bool):
|
||
return f"数据剖析的「{_ENABLED_LABEL}」只能是开启或关闭", "enabled"
|
||
for key, (label, low, high, integer) in _NUMBER_FIELDS.items():
|
||
if key in raw and _number(raw[key], low, high, integer) is None:
|
||
kind = "整数" if integer else "数"
|
||
return f"数据剖析的「{label}」需要填写 {_fmt(low)} 到 {_fmt(high)} 之间的{kind}；当前为「{raw[key]}」", key
|
||
return None
|
||
|
||
|
||
# ==========================================================================
|
||
# SQL：字面量与方言
|
||
# ==========================================================================
|
||
|
||
#: 查询层不支持参数绑定（run_query 只收一段 SQL），核对键值只能把值拼进 IN 列表。所以只拼「自己刚从库里
|
||
#: 取回的原值」，并且按类型生成字面量：整数原样写，文字加单引号、单引号写两遍。下面几种文字不拼，跳过：
|
||
#: - 带反斜杠的：MySQL 在 NO_BACKSLASH_ESCAPES 开与不开时读法不同，守卫会整条拒掉；
|
||
#: - 带「:名字」的：查询层用 SQLAlchemy 的 text() 执行，它不认引号，会把字符串里的 :b 当成绑定参数；
|
||
#: - 带控制字符的、太长的：键值不该长这样，多半不是键。
|
||
_BIND_LIKE = re.compile(r"(?<![:\w\\]):\w")
|
||
_CONTROL = re.compile(r"[\x00-\x1f\x7f]")
|
||
_INT_TEXT = re.compile(r"-?\d{1,38}")
|
||
#: 文字字面量的长度上限
|
||
MAX_LITERAL_LEN = 200
|
||
|
||
|
||
def sql_literal(value: Any, kind: str | None) -> str | None:
|
||
"""一个取回的值 → SQL 字面量；不安全或类型不支持时返回 None（调用方跳过这个值）。
|
||
|
||
kind 是查询层记下的列类型（QueryResult.column_types：number / text / date …），None 表示拿不准。
|
||
DECIMAL 经查询层已经转成了字符串（保精度），所以 number 列的整数文字原样写成数字。只认整数和文字：
|
||
非整数的数做相等比较靠不住；日期、时间的字面量各家写法不同，不猜；布尔不当键。
|
||
"""
|
||
if value is None or isinstance(value, bool):
|
||
return None
|
||
if isinstance(value, int):
|
||
return str(value)
|
||
if isinstance(value, float):
|
||
return str(int(value)) if value.is_integer() and abs(value) < 2 ** 53 else None
|
||
if isinstance(value, Decimal):
|
||
return str(int(value)) if value.is_finite() and value == value.to_integral_value() else None
|
||
if not isinstance(value, str):
|
||
return None
|
||
if kind == "number":
|
||
return value if _INT_TEXT.fullmatch(value) else None
|
||
if kind not in ("text", None):
|
||
return None
|
||
if len(value) > MAX_LITERAL_LEN or "\\" in value or _CONTROL.search(value) or _BIND_LIKE.search(value):
|
||
return None
|
||
return "'" + value.replace("'", "''") + "'"
|
||
|
||
|
||
_DIALECT_MODULES = {"sqlite": sqlite, "postgres": postgresql, "postgresql": postgresql, "mysql": mysql,
|
||
"mariadb": mysql, "oracle": oracle}
|
||
|
||
|
||
class SqlDialect:
|
||
"""剖析 SQL 的方言差异：标识符怎么加引号、怎么只取前 n 行、统计信息在哪个系统视图里。只拼字符串，不连库。
|
||
|
||
标识符交给 SQLAlchemy 各方言的 identifier_preparer：需要时才加引号（memberTags 加、visits 不加），
|
||
MySQL 用反引号。Oracle 尤其不能一律加双引号：探查拿到的表名是 SQLAlchemy 规整过的小写，库里其实是
|
||
大写，"visits" 加了引号就成了另一张不存在的表；不加引号 Oracle 自己转大写才对得上。
|
||
"""
|
||
|
||
def __init__(self, kind: str | None) -> None:
|
||
self.kind = (kind or "").lower()
|
||
module = _DIALECT_MODULES.get(self.kind)
|
||
if module is None:
|
||
raise ValueError(f"不支持的数据库类型：{kind}")
|
||
self._dialect = module.dialect()
|
||
self._prep = self._dialect.identifier_preparer
|
||
self.oracle = self.kind == "oracle"
|
||
|
||
def quote(self, name: str) -> str:
|
||
return self._prep.quote(name)
|
||
|
||
def table(self, meta: dict[str, Any] | None, name: str) -> str:
|
||
"""写进 FROM 的表名：探查时指定了 schema 的带上它（Oracle 只读账号名下没有对象，全靠 schema 前缀）。"""
|
||
schema = (meta or {}).get("schema")
|
||
return f"{self._prep.quote_schema(schema)}.{self.quote(name)}" if schema else self.quote(name)
|
||
|
||
def limit(self, sql: str, n: int) -> str:
|
||
"""只取前 n 行。Oracle 11g 没有 LIMIT 也没有 FETCH FIRST，一律套一层 ROWNUM。"""
|
||
if self.oracle:
|
||
return f"SELECT * FROM ({sql}) WHERE ROWNUM <= {int(n)}"
|
||
return f"{sql} LIMIT {int(n)}"
|
||
|
||
def _first_rows(self, table: str, column: str, scan_cap: int | None) -> str:
|
||
"""FROM 子句：整张表，或者只看前 scan_cap 行非空值的子查询（大表不做整表扫描）。"""
|
||
if scan_cap is None:
|
||
return table
|
||
return f"({self.limit(f'SELECT {column} FROM {table} WHERE {column} IS NOT NULL', scan_cap)}) s"
|
||
|
||
def stats_sql(self, meta: dict[str, Any] | None, name: str) -> str | None:
|
||
"""读这张表行数估算值的查询：MySQL information_schema.TABLES.TABLE_ROWS、PostgreSQL pg_class.reltuples、
|
||
Oracle ALL_TABLES.NUM_ROWS。SQLite 没有可靠的统计信息，返回 None（改为数到上限为止）。"""
|
||
schema = (meta or {}).get("schema")
|
||
if self.kind in ("mysql", "mariadb"):
|
||
where_schema = sql_literal(schema, "text") if schema else "DATABASE()"
|
||
table = sql_literal(name, "text")
|
||
if not (where_schema and table):
|
||
return None
|
||
return (f"SELECT TABLE_ROWS FROM information_schema.TABLES "
|
||
f"WHERE TABLE_SCHEMA = {where_schema} AND TABLE_NAME = {table}")
|
||
if self.kind in ("postgres", "postgresql"):
|
||
where_schema = sql_literal(schema, "text") if schema else "current_schema()"
|
||
table = sql_literal(name, "text")
|
||
if not (where_schema and table):
|
||
return None
|
||
return ("SELECT c.reltuples FROM pg_catalog.pg_class c "
|
||
"JOIN pg_catalog.pg_namespace n ON n.oid = c.relnamespace "
|
||
f"WHERE n.nspname = {where_schema} AND c.relname = {table}")
|
||
if self.oracle:
|
||
denorm = self._dialect.denormalize_name
|
||
owner = sql_literal(denorm(schema), "text") if schema else "SYS_CONTEXT('USERENV', 'CURRENT_SCHEMA')"
|
||
table = sql_literal(denorm(name), "text")
|
||
if not (owner and table):
|
||
return None
|
||
return f"SELECT NUM_ROWS FROM ALL_TABLES WHERE OWNER = {owner} AND TABLE_NAME = {table}"
|
||
return None
|
||
|
||
def bounded_count_sql(self, table: str, cap: int) -> str:
|
||
"""数到 cap 行为止：小表得到准确行数，大表只知道「至少 cap 行」，不做全表 COUNT。"""
|
||
return f"SELECT COUNT(*) AS n FROM ({self.limit(f'SELECT 1 AS one FROM {table}', cap)}) s"
|
||
|
||
def distinct_sample_sql(self, table: str, column: str, n: int, *, scan_cap: int | None) -> str:
|
||
"""至多 n 个不同的非空键值。scan_cap 给了时只在前 scan_cap 行里找：键的取值少时 DISTINCT … LIMIT
|
||
凑不满 n 个，会一直扫到表尾。"""
|
||
if scan_cap is None:
|
||
return self.limit(f"SELECT DISTINCT {column} FROM {table} WHERE {column} IS NOT NULL", n)
|
||
return self.limit(f"SELECT DISTINCT {column} FROM {self._first_rows(table, column, scan_cap)}", n)
|
||
|
||
def match_count_sql(self, table: str, column: str, literals: list[str]) -> str:
|
||
"""被指向表里能对上这些键值的个数（去重：被指向列有重复值时不多算）。"""
|
||
return f"SELECT COUNT(DISTINCT {column}) AS n FROM {table} WHERE {column} IN ({', '.join(literals)})"
|
||
|
||
def unique_check_sql(self, table: str, column: str) -> str:
|
||
"""非空值个数和不同值个数：相等即这一列（非空部分）唯一。整表统计，只对小表用。"""
|
||
return f"SELECT COUNT({column}) AS n, COUNT(DISTINCT {column}) AS d FROM {table}"
|
||
|
||
def value_counts_sql(self, table: str, column: str, n: int, *, scan_cap: int | None) -> str:
|
||
"""取值分布：出现最多的 n 个取值和各自的行数。只拿取值和计数，不拿明细行。"""
|
||
sql = (f"SELECT {column}, COUNT(*) AS cnt FROM {self._first_rows(table, column, scan_cap)} "
|
||
f"WHERE {column} IS NOT NULL GROUP BY {column} ORDER BY cnt DESC, {column}")
|
||
return self.limit(sql, n)
|
||
|
||
def min_max_sql(self, table: str, columns: list[str]) -> str:
|
||
return f"SELECT {', '.join(f'MIN({c}), MAX({c})' for c in columns)} FROM {table}"
|
||
|
||
|
||
# ==========================================================================
|
||
# 发查询：守卫、查询次数、时限
|
||
# ==========================================================================
|
||
|
||
#: 总时长只剩这么一点时不再发新查询：发出去的时限也只剩零点几秒，白占一次查询次数
|
||
_MIN_WINDOW_S = 0.5
|
||
#: 连续失败这么多条就停：多半是连接断了、账号没有权限，再发只是一条条重复同一个错误
|
||
_MAX_CONSECUTIVE_ERRORS = 3
|
||
|
||
|
||
class _Stop(Exception):
|
||
"""整次剖析停下：budget 查询次数用完、deadline 总时长用完、failed 连续失败。剩下的检查都不再发查询。"""
|
||
|
||
def __init__(self, reason: str) -> None:
|
||
super().__init__(reason)
|
||
self.reason = reason
|
||
|
||
|
||
class _Skip(Exception):
|
||
"""这一项没查成或不查：timeout 超时、error 查询失败、rejected 未通过守卫、masked 被遮罩……记下原因，接着查别的。
|
||
|
||
carry：目录里剖析以前对这一项写的结论要不要原样留着。没查成的（超时、表太大……）留着——这次没查不等于
|
||
结论错了；被遮罩的列上取过值的结论（码值、日期范围）不留：遮罩之后，带着原值的结论也不该再给人看。
|
||
"""
|
||
|
||
def __init__(self, reason: str, detail: str, *, carry: bool = True) -> None:
|
||
super().__init__(detail)
|
||
self.reason = reason
|
||
self.detail = detail
|
||
self.carry = carry
|
||
|
||
|
||
def _brief(e: BaseException) -> str:
|
||
"""驱动报错的第一行，去掉 SQLAlchemy 加的「(模块.类名)」前缀和后面附的 SQL、文档链接。"""
|
||
lines = str(getattr(e, "orig", None) or e).strip().splitlines()
|
||
first = re.sub(r"^\([\w.]+\)\s*", "", lines[0] if lines else "")
|
||
return first[:160] or type(e).__name__
|
||
|
||
|
||
class _Runner:
|
||
"""剖析发的每一条查询都从这里走：先按只读过守卫，再交给查询层 run_query；记次数、管时限。
|
||
|
||
- 只读：不论数据源本身可写与否，先用 guard.check(readonly=True) 判一遍，再进 run_query——那里还会按
|
||
数据源自己的设置判一遍。两遍是同一个守卫，不为剖析放宽，也不另开连接。
|
||
- 查询次数：每发一条记一次（超时、失败的也算），到上限就停。没发出去的（守卫拒了）不算。
|
||
- 时限：单条取设置和数据源查询时限中较小的一个，并且不超过总时长剩下的部分。
|
||
"""
|
||
|
||
def __init__(self, source: Any, settings: ProfileSettings, dialect: SqlDialect) -> None:
|
||
self.source = source
|
||
self.settings = settings
|
||
self.kind = dialect.kind
|
||
self.timeout = min(float(settings.query_timeout_s), float(data_engine.query_timeout(source)))
|
||
self.ends = time.monotonic() + float(settings.max_total_s)
|
||
self.used = 0
|
||
self.stopped: str | None = None
|
||
self._errors = 0
|
||
|
||
def _stop(self, reason: str) -> None:
|
||
self.stopped = reason
|
||
raise _Stop(reason)
|
||
|
||
async def __call__(self, sql: str, *, max_rows: int = 1) -> QueryResult:
|
||
if self.stopped:
|
||
raise _Stop(self.stopped)
|
||
if self.used >= self.settings.max_queries:
|
||
self._stop("budget")
|
||
remaining = self.ends - time.monotonic()
|
||
if remaining <= _MIN_WINDOW_S:
|
||
self._stop("deadline")
|
||
try:
|
||
guard.check(sql, readonly=True, source_name=getattr(self.source, "name", ""), dialect=self.kind)
|
||
except SqlRejected as e:
|
||
raise _Skip("rejected", f"剖析查询未通过安全守卫：{e}") from e
|
||
self.used += 1
|
||
cut = remaining < self.timeout
|
||
seconds = round(min(self.timeout, remaining), 3)
|
||
limits = QueryLimits(max_rows=max(1, int(max_rows)), timeout_seconds=seconds)
|
||
try:
|
||
result = await data_engine.run_query(self.source, sql, limits=limits)
|
||
except SqlRejected as e:
|
||
# 上面已经按只读过了同一个守卫，查询层再拒只可能是时限到了
|
||
if cut:
|
||
self.stopped = "deadline"
|
||
raise _Skip("timeout", f"查询超时：超过 {_fmt(seconds)} 秒被中断，已跳过") from e
|
||
except SnapshotTampered:
|
||
raise
|
||
except Exception as e: # noqa: BLE001 - 一条查询失败不该拖垮整次剖析，原因照实记下
|
||
self._errors += 1
|
||
if self._errors >= _MAX_CONSECUTIVE_ERRORS:
|
||
self.stopped = "failed"
|
||
raise _Skip("error", f"查询失败：{_brief(e)}") from e
|
||
self._errors = 0
|
||
return result
|
||
|
||
|
||
# ==========================================================================
|
||
# 表有多大
|
||
# ==========================================================================
|
||
|
||
|
||
@dataclass(frozen=True)
|
||
class TableSize:
|
||
"""一张表的行数。rows 为 None 表示不知道（没有统计信息、也没数）或者超过了整表统计的上限。"""
|
||
|
||
rows: int | None
|
||
#: stats 数据库的统计信息（估算值）；count 数到上限为止；unknown 没能得到
|
||
method: str
|
||
#: 数到上限也没数完：至少这么多行
|
||
at_least: int | None = None
|
||
|
||
def within(self, limit: int) -> bool:
|
||
"""行数已知且不超过 limit：可以做整表统计。不知道多大的表按大表对待。"""
|
||
return self.rows is not None and self.rows <= limit
|
||
|
||
def to_dict(self) -> dict[str, Any]:
|
||
return {"rows": self.rows, "method": self.method, "at_least": self.at_least}
|
||
|
||
|
||
def _first(result: QueryResult) -> Any:
|
||
return result.rows[0][0] if result.rows and result.rows[0] else None
|
||
|
||
|
||
def _as_int(value: Any) -> int | None:
|
||
if value is None or isinstance(value, bool):
|
||
return None
|
||
try:
|
||
number = float(str(value))
|
||
except ValueError:
|
||
return None
|
||
return int(number) if number == number and abs(number) != float("inf") else None
|
||
|
||
|
||
async def estimate_size(run: _Runner, dialect: SqlDialect, meta: dict[str, Any], name: str, *,
|
||
max_scan_rows: int) -> tuple[TableSize, list[_Skip]]:
|
||
"""先读统计信息；读不到（SQLite、没分析过的表）再数到 max_scan_rows + 1 行为止。
|
||
|
||
统计信息为 0 或负数（PostgreSQL 没分析过的表是 -1，MySQL 的估算值可能是 0）当作不知道：一张其实很大的表
|
||
要是被当成空表，后面就会对它做整表统计。返回 (行数, 途中没查成的几条)。查询次数、总时长用完时抛 _Stop。
|
||
"""
|
||
skips: list[_Skip] = []
|
||
sql = dialect.stats_sql(meta, name)
|
||
if sql:
|
||
try:
|
||
rows = _as_int(_first(await run(sql)))
|
||
except _Skip as e:
|
||
skips.append(e)
|
||
else:
|
||
if rows is not None and rows > 0:
|
||
return TableSize(rows, "stats"), skips
|
||
if max_scan_rows <= 0:
|
||
return TableSize(None, "unknown"), skips
|
||
cap = max_scan_rows + 1
|
||
try:
|
||
counted = _as_int(_first(await run(dialect.bounded_count_sql(dialect.table(meta, name), cap))))
|
||
except _Skip as e:
|
||
skips.append(e)
|
||
return TableSize(None, "unknown"), skips
|
||
if counted is None:
|
||
return TableSize(None, "unknown"), skips
|
||
if counted <= max_scan_rows:
|
||
return TableSize(counted, "count"), skips
|
||
return TableSize(None, "count", at_least=cap), skips
|
||
|
||
|
||
# ==========================================================================
|
||
# 一次剖析：上下文、结果
|
||
# ==========================================================================
|
||
|
||
#: 不指定表时剖析几张：目录里有要核对的关系的表，还有待核实（推断）关系的在前，再按使用次数；确知是空表的跳过
|
||
PROFILE_DEFAULT_TABLES = 10
|
||
#: 不指定表时，为跳过空表最多先估几张候选表的行数；估行数的查询最多用掉查询次数上限的一半，免得都花在挑表上
|
||
PROFILE_PROBE_TABLES = 30
|
||
#: IN 列表每批最多几个值：Oracle 的 IN 列表不能超过 1000 项（ORA-01795），各家统一按它分批
|
||
IN_CHUNK = 1000
|
||
#: 剖析写的备注都以它开头（「数据剖析：」）：人工确认过的关系，只覆盖剖析自己写的备注，不碰人写的（认的时候连
|
||
#: 升级前带日期的「数据剖析（日期）：」一起认，catalog.is_profile_note）。不写日期，时间看这一项的 updated_at
|
||
NOTE_PREFIX = catalog.PROFILE_NOTE_PREFIX
|
||
#: 整次剖析停下的原因 → 剩下没查的项的说明
|
||
_STOP_DETAIL = {
|
||
"budget": "本次剖析的查询次数已用完（上限 {max_queries} 条），未检查",
|
||
"deadline": "本次剖析的总时长已用完（上限 {max_total_s} 秒），未检查",
|
||
"failed": "连续多条查询失败，已停止剖析，未检查",
|
||
}
|
||
|
||
|
||
class ProfileDisabled(Exception):
|
||
"""这个数据源没有开启数据剖析，或者数据源停用了。message 给人看；code 是接口回 409 时带的机读码
|
||
（api/coded.py：profile_disabled / datasource_inactive）。"""
|
||
|
||
def __init__(self, message: str, code: str = "profile_disabled") -> None:
|
||
super().__init__(message)
|
||
self.code = code
|
||
|
||
|
||
class ProfileBusy(Exception):
|
||
"""这个数据源正在剖析。message 给人看。"""
|
||
|
||
|
||
@dataclass
|
||
class ProfileSkip:
|
||
"""没做的一项和原因。
|
||
|
||
kind：relation 关系、codes 码值、date 日期列、row_estimate 行数估算、table 整张表。
|
||
reason：budget 查询次数用完、deadline 总时长用完、failed 连续失败、timeout 超时、error 查询失败、
|
||
rejected 未通过守卫、masked 字段被遮罩、too_large 表太大、view 视图、unsupported 暂不支持、
|
||
no_data 没有数据、missing 表结构里没有、high_cardinality 取值太多（不像码值）。detail 是给人看的整句。
|
||
"""
|
||
|
||
kind: str
|
||
target: str
|
||
reason: str
|
||
detail: str
|
||
path: str | None = None
|
||
|
||
def to_dict(self) -> dict[str, Any]:
|
||
return {"kind": self.kind, "target": self.target, "path": self.path, "reason": self.reason,
|
||
"detail": self.detail}
|
||
|
||
|
||
@dataclass
|
||
class TableProfile:
|
||
"""一张表这次剖析的结果。findings 是写进目录的发现（给界面看，形状见 _finding_*）。"""
|
||
|
||
table: str
|
||
queries: int = 0
|
||
row_estimate: TableSize | None = None
|
||
findings: list[dict[str, Any]] = field(default_factory=list)
|
||
skipped: list[ProfileSkip] = field(default_factory=list)
|
||
#: 日期类列的取值范围（MIN、MAX）。只有一个日期列时它还写进了业务日期的备注；多个时只在这里
|
||
date_ranges: list[dict[str, Any]] = field(default_factory=list)
|
||
added: int = 0
|
||
updated: int = 0
|
||
removed: int = 0
|
||
version: int = 0
|
||
#: 这张表没剖析（表结构里没有）或结果没写进去（写入一直冲突）
|
||
error: str | None = None
|
||
|
||
|
||
@dataclass
|
||
class ProfileReport:
|
||
"""一次剖析的结果。stopped：整次剖析中途停下的原因（budget / deadline / failed），做完了为 None。"""
|
||
|
||
profiled_at: str
|
||
settings: ProfileSettings
|
||
tables: list[TableProfile] = field(default_factory=list)
|
||
queries_used: int = 0
|
||
stopped: str | None = None
|
||
#: 不指定表时，挑表途中估过行数、确知是空表而跳过的表（表结构顺序）。估行数的查询算在 queries_used 里
|
||
empty_tables: list[str] = field(default_factory=list)
|
||
|
||
|
||
@dataclass
|
||
class _RelationOutcome:
|
||
"""一条关系核对完的结论。写不写、怎么写由 _apply 按写入时目录里那条关系的状态决定。"""
|
||
|
||
rid: str
|
||
target: str
|
||
#: 外键关系不抽样（外键已保证引用完整），没有覆盖率
|
||
coverage: float | None
|
||
cardinality: str | None
|
||
holds: bool
|
||
sample: int
|
||
matched: int
|
||
note: str
|
||
#: 基数是用数据核实的：子表一侧是否唯一有了定论（主键、唯一约束，或数过 COUNT 和 COUNT(DISTINCT)）。
|
||
#: 子表太大、没数成的按多对一记，但不算核实——SQL 检查据此不把一对多关联后的重复计算报成错误
|
||
cardinality_checked: bool = False
|
||
|
||
|
||
@dataclass
|
||
class _CodesOutcome:
|
||
"""一列的取值分布：[(码值, 行数)]，按行数从多到少。complete：看的是全表（没有只看前若干行），取到的就是
|
||
这一列的全部取值，码值项标「已列全」，SQL 检查才拿它判断某个值「不在码值表里」。"""
|
||
|
||
column: str
|
||
values: list[tuple[str, int]]
|
||
rows: int
|
||
note: str
|
||
complete: bool = False
|
||
|
||
|
||
@dataclass
|
||
class _DateOutcome:
|
||
"""表里唯一一个日期类列，提议作为业务日期。"""
|
||
|
||
column: str
|
||
low: str
|
||
high: str
|
||
note: str
|
||
|
||
|
||
@dataclass
|
||
class _TableOutcome:
|
||
"""一张表所有检查的结论，以及没查成、要原样保留旧结论的槽位。"""
|
||
|
||
relations: list[_RelationOutcome] = field(default_factory=list)
|
||
codes: list[_CodesOutcome] = field(default_factory=list)
|
||
business_date: _DateOutcome | None = None
|
||
#: 没查成的项：目录里剖析以前写的结论原样留着（不然会被 covered={"profile"} 当成「这次没有」删掉）
|
||
keep_relations: set[str] = field(default_factory=set)
|
||
keep_codes: set[str] = field(default_factory=set)
|
||
keep_business_date: bool = False
|
||
|
||
|
||
@dataclass
|
||
class _Context:
|
||
source: Any
|
||
settings: ProfileSettings
|
||
dialect: SqlDialect
|
||
run: _Runner
|
||
tables: dict[str, Any]
|
||
#: 遮罩的列（小写）。遮罩按列名生效、不分大小写、不分表，和证据面板的比法一致
|
||
masked: set[str]
|
||
sizes: dict[str, TableSize] = field(default_factory=dict)
|
||
|
||
async def size(self, table: str, result: TableProfile) -> TableSize:
|
||
"""表有多大，一次剖析里每张表只估一次。途中没查成的记进 result（行数估算这一项）。"""
|
||
if table not in self.sizes:
|
||
size, skips = await estimate_size(self.run, self.dialect, self.tables[table], table,
|
||
max_scan_rows=self.settings.max_scan_rows)
|
||
self.sizes[table] = size
|
||
result.skipped += [ProfileSkip("row_estimate", table, s.reason, s.detail) for s in skips]
|
||
return self.sizes[table]
|
||
|
||
async def size_with_data(self, table: str, result: TableProfile) -> TableSize:
|
||
"""同 size，但确知是空表时直接跳过这一项（抛 _Skip），不再为它发查询。"""
|
||
size = await self.size(table, result)
|
||
if size.rows == 0:
|
||
raise _Skip("no_data", f"{table} 是空表，无法剖析")
|
||
return size
|
||
|
||
def is_masked(self, column: str) -> bool:
|
||
return column.lower() in self.masked
|
||
|
||
def scan_cap(self, size: TableSize) -> int | None:
|
||
"""大表（或不知道多大）抽样、取值分布只看前多少行；小表整表看，返回 None。"""
|
||
if size.within(self.settings.max_scan_rows):
|
||
return None
|
||
return max(self.settings.sample_size, self.settings.max_scan_rows)
|
||
|
||
|
||
def _column(meta: dict[str, Any], name: str) -> str | None:
|
||
"""表结构里这一列的写法（目录里的列名大小写可能和表结构不同）；没有返回 None。"""
|
||
lowered = name.lower()
|
||
return next((str(c["name"]) for c in meta.get("columns") or []
|
||
if isinstance(c, dict) and str(c.get("name", "")).lower() == lowered), None)
|
||
|
||
|
||
def _constraint(meta: dict[str, Any], column: str) -> str | None:
|
||
"""这一列单独是主键或某个唯一约束时返回「主键」/「唯一约束」，否则 None。"""
|
||
wanted = [column.lower()]
|
||
if [c.lower() for c in meta.get("primary_key") or []] == wanted:
|
||
return "主键"
|
||
for group in meta.get("unique") or []:
|
||
if isinstance(group, list) and [str(c).lower() for c in group] == wanted:
|
||
return "唯一约束"
|
||
return None
|
||
|
||
|
||
def _percent(ratio: float) -> str:
|
||
"""覆盖率写成百分数：整数不带小数，其余留一位；不到 100% 的不四舍五入成 100%。"""
|
||
text = f"{ratio * 100:.1f}".rstrip("0").rstrip(".")
|
||
return "99.9%" if text == "100" and ratio < 1 else f"{text}%"
|
||
|
||
|
||
def _relation_target(rel: dict[str, Any]) -> str:
|
||
left = ", ".join(rel.get("columns") or [])
|
||
right = ", ".join(f"{rel.get('to_table')}.{c}" for c in rel.get("to_columns") or [])
|
||
return f"{left} → {right}"
|
||
|
||
|
||
# ==========================================================================
|
||
# 检查：关联关系
|
||
# ==========================================================================
|
||
|
||
|
||
def _relation_candidates(notes: dict[str, Any] | None) -> list[dict[str, Any]]:
|
||
"""要核对的关系：没被驳回的。人工确认过的也核对，只补覆盖率和基数。
|
||
|
||
外键约束来的也核对，但只核对基数：外键保证了引用完整（不必抽样算覆盖率），却只保证被指向的键唯一，
|
||
子表一侧每个键是一行还是多行要看数据。以前跳过外键关系，外键来的一对多永远拿不到「用数据核实过」，
|
||
扇出检查只能报 warning——最常见的「订单关联明细后对订单金额求和」在受管发布时也挡不住。"""
|
||
return [r for r in (notes or {}).get("relations") or []
|
||
if isinstance(r, dict) and r.get("id") and r.get("status") != "rejected"]
|
||
|
||
|
||
async def _unique(cx: _Context, table: str, meta: dict[str, Any], column: str,
|
||
result: TableProfile) -> tuple[bool | None, str]:
|
||
"""这一列（非空部分）唯一吗：(True / False / None 不知道, 依据)。有主键或唯一约束直接认；否则只对行数不超过
|
||
整表统计上限的表数一次 COUNT 和 COUNT(DISTINCT)，大表不扫。"""
|
||
how = _constraint(meta, column)
|
||
if how:
|
||
return True, how
|
||
size = await cx.size(table, result)
|
||
if not size.within(cx.settings.max_scan_rows):
|
||
return None, "too_large"
|
||
d = cx.dialect
|
||
res = await cx.run(d.unique_check_sql(d.table(meta, table), d.quote(column)))
|
||
row = res.rows[0] if res.rows else [None, None]
|
||
total, distinct = _as_int(row[0]), _as_int(row[1])
|
||
if total is None or distinct is None:
|
||
return None, "count"
|
||
return total == distinct, "count"
|
||
|
||
|
||
def _fk_note(child: tuple[bool | None, str]) -> str:
|
||
"""外键关系的剖析备注：只说子表一侧唯不唯一、依据是什么。不写日期（同 _relation_note）。"""
|
||
unique, how = child
|
||
if unique is None:
|
||
why = "子表太大，没有整表统计" if how == "too_large" else "没能数清子表的取值"
|
||
return f"{catalog.PROFILE_NOTE_PREFIX}外键约束已保证引用完整，未抽样核对覆盖率；{why}，基数未用数据核实"
|
||
basis = "按主键或唯一约束" if how not in ("count", "too_large") else "整表数过取值"
|
||
shape = "每个键只有一行（一对一）" if unique else "同一个键有多行（一对多）"
|
||
return f"{catalog.PROFILE_NOTE_PREFIX}外键约束已保证引用完整，未抽样核对覆盖率；子表一侧{basis}：{shape}"
|
||
|
||
|
||
def _relation_note(*, sample: int, matched: int, coverage: float, scan_cap: int | None,
|
||
skipped_values: int, parent: tuple[bool | None, str], child: tuple[bool | None, str] | None,
|
||
holds: bool) -> str:
|
||
"""关系的剖析备注：抽样规模、覆盖率、父键和子键唯一的依据。人据此判断这条结论有多可靠。
|
||
不写日期：什么时候剖析的看这一项的 updated_at（界面按本地时间显示）。"""
|
||
parts: list[str] = []
|
||
low = coverage < catalog.PROFILE_VERIFY_COVERAGE
|
||
if low:
|
||
parts.append(f"抽样覆盖率 {_percent(coverage)}，可能不是这条关系")
|
||
scope = f"（只看前 {scan_cap} 行）" if scan_cap else ""
|
||
sampled = f"子表抽样 {sample} 个不同键值{scope}，父表对上 {matched} 个"
|
||
parts.append(sampled if low else f"{sampled}，覆盖率 {_percent(coverage)}")
|
||
if skipped_values:
|
||
parts.append(f"另有 {skipped_values} 个键值的类型不支持核对，未计入")
|
||
unique, how = parent
|
||
if unique is True:
|
||
parts.append(f"被指向列是{how}" if how in ("主键", "唯一约束") else "被指向列经计数核对唯一")
|
||
elif unique is False:
|
||
parts.append("被指向列有重复值，不能作为关联的被指向键")
|
||
elif how == "too_large":
|
||
parts.append("被指向的表超过整表统计的行数上限，未核对被指向列是否唯一")
|
||
else:
|
||
parts.append("未能核对被指向列是否唯一")
|
||
if child is not None:
|
||
child_unique, child_how = child
|
||
if child_unique is True:
|
||
basis = child_how if child_how in ("主键", "唯一约束") else "计数核对"
|
||
parts.append(f"子表一侧也唯一（{basis}），一对一")
|
||
elif child_unique is False:
|
||
parts.append("子表一侧有重复值，多对一")
|
||
elif child_how == "too_large":
|
||
parts.append("子表超过整表统计的行数上限，未核对子表一侧是否唯一，按多对一记")
|
||
else:
|
||
parts.append("未能核对子表一侧是否唯一，按多对一记")
|
||
if not holds and not low:
|
||
parts.append("暂不升为有确证")
|
||
return NOTE_PREFIX + "；".join(parts) + "。"
|
||
|
||
|
||
async def _check_relation(cx: _Context, table: str, rel: dict[str, Any], out: _TableOutcome,
|
||
result: TableProfile) -> None:
|
||
"""从子表取至多 sample_size 个不同的非空键值，去父表里数对上几个，得到覆盖率；再看父键、子键唯不唯一。"""
|
||
cols, to_cols = list(rel.get("columns") or []), list(rel.get("to_columns") or [])
|
||
to_table = str(rel.get("to_table") or "")
|
||
if len(cols) != 1 or len(to_cols) != 1:
|
||
raise _Skip("unsupported", "多列组成的关联关系暂不剖析")
|
||
meta = cx.tables[table]
|
||
parent = to_table if to_table in cx.tables else catalog.resolve_table_name({"tables": cx.tables}, to_table)
|
||
if parent is None:
|
||
raise _Skip("missing", f"表结构里没有被指向的表 {to_table}，请先重新探查结构")
|
||
pmeta = cx.tables[parent]
|
||
col, pcol = _column(meta, cols[0]), _column(pmeta, to_cols[0])
|
||
if col is None or pcol is None:
|
||
missing = f"{table}.{cols[0]}" if col is None else f"{parent}.{to_cols[0]}"
|
||
raise _Skip("missing", f"表结构里没有列 {missing}，请先重新探查结构")
|
||
if pmeta.get("is_view"):
|
||
raise _Skip("view", f"被指向的 {parent} 是视图，不剖析")
|
||
for name, owner in ((col, table), (pcol, parent)):
|
||
if cx.is_masked(name):
|
||
raise _Skip("masked", f"{owner}.{name} 在数据源设置中被遮罩，不取样", carry=True)
|
||
|
||
if rel.get("source") == "fk":
|
||
await cx.size_with_data(table, result)
|
||
child = await _unique(cx, table, meta, col, result)
|
||
cardinality = None if child[0] is None else ("one_to_one" if child[0] else "many_to_one")
|
||
out.relations.append(_RelationOutcome(rid=str(rel["id"]), target=_relation_target(rel), coverage=None,
|
||
cardinality=cardinality, holds=cardinality is not None, sample=0,
|
||
matched=0, note=_fk_note(child), cardinality_checked=child[0] is not None))
|
||
return
|
||
|
||
d, s = cx.dialect, cx.settings
|
||
size = await cx.size_with_data(table, result)
|
||
scan_cap = cx.scan_cap(size)
|
||
child_table, parent_table = d.table(meta, table), d.table(pmeta, parent)
|
||
res = await cx.run(d.distinct_sample_sql(child_table, d.quote(col), s.sample_size, scan_cap=scan_cap),
|
||
max_rows=s.sample_size)
|
||
kind = (res.column_types or {}).get(res.columns[0]) if res.columns else None
|
||
values = [row[0] for row in res.rows if row]
|
||
literals = list(dict.fromkeys(lit for v in values if (lit := sql_literal(v, kind)) is not None))
|
||
if not values:
|
||
raise _Skip("no_data", f"{table}.{col} 没有非空值，无法核对")
|
||
if not literals:
|
||
raise _Skip("unsupported", f"{table}.{col} 的取值类型不支持核对（只核对整数和文字）")
|
||
matched = 0
|
||
for start in range(0, len(literals), IN_CHUNK):
|
||
sql = d.match_count_sql(parent_table, d.quote(pcol), literals[start:start + IN_CHUNK])
|
||
matched += _as_int(_first(await cx.run(sql))) or 0
|
||
matched = min(matched, len(literals))
|
||
coverage = round(matched / len(literals), 4)
|
||
|
||
parent_unique = await _unique(cx, parent, pmeta, pcol, result)
|
||
child_unique = await _unique(cx, table, meta, col, result) if parent_unique[0] else None
|
||
cardinality = None
|
||
if child_unique is not None:
|
||
cardinality = "one_to_one" if child_unique[0] is True else "many_to_one"
|
||
holds = coverage >= catalog.PROFILE_VERIFY_COVERAGE and cardinality is not None
|
||
note = _relation_note(sample=len(literals), matched=matched, coverage=coverage, scan_cap=scan_cap,
|
||
skipped_values=len(values) - len(literals), parent=parent_unique, child=child_unique,
|
||
holds=holds)
|
||
checked = child_unique is not None and child_unique[0] is not None
|
||
out.relations.append(_RelationOutcome(rid=str(rel["id"]), target=_relation_target(rel), coverage=coverage,
|
||
cardinality=cardinality, holds=holds, sample=len(literals),
|
||
matched=matched, note=note, cardinality_checked=checked))
|
||
|
||
|
||
# ==========================================================================
|
||
# 检查：码值候选、日期列
|
||
# ==========================================================================
|
||
|
||
#: 码值候选最多几个取值。查询取 CODES_MAX + 1 个：取满了说明不是低基数列
|
||
CODES_MAX = 20
|
||
#: 码值的长度上限。更长的不像状态码，像说明文字
|
||
MAX_CODE_LEN = 64
|
||
#: 像状态、类型、渠道的列名里会有的词
|
||
_CODE_WORDS = frozenset({"status", "state", "type", "kind", "category", "channel", "level", "method", "mode",
|
||
"reason", "stage", "phase", "grade", "flag", "source", "result"})
|
||
#: 以这些词结尾的列不是码值：标识、名称、说明、时间、金额、数量（channel_id、level_name、status_time……）
|
||
_NOT_CODE_TAILS = frozenset({"id", "no", "num", "number", "name", "desc", "description", "text", "remark", "note",
|
||
"at", "date", "time", "on", "amount", "price", "count", "qty", "rate", "url"})
|
||
#: 像日期的取值：2026-07-01、2026/07/01，后面可以跟时间
|
||
_DATE_TEXT = re.compile(r"^\d{4}[-/]\d{2}[-/]\d{2}")
|
||
|
||
|
||
def _code_type_ok(type_name: str | None) -> bool:
|
||
"""整数，或者短文字（定长不超过 MAX_CODE_LEN；SQLite 的 TEXT 不带长度，也算）。"""
|
||
t = (type_name or "").upper()
|
||
if not t or any(k in t for k in ("CLOB", "BLOB", "BINARY", "JSON", "DATE", "TIME", "INTERVAL", "REAL", "FLOAT",
|
||
"DOUBLE", "BOOL")):
|
||
return False
|
||
if "INT" in t:
|
||
return True
|
||
size = re.search(r"\(\s*(\d+)\s*(?:,\s*(\d+)\s*)?\)", t)
|
||
if any(k in t for k in ("NUMBER", "NUMERIC", "DECIMAL")):
|
||
return size is None or not size.group(2) or int(size.group(2)) == 0
|
||
if any(k in t for k in ("CHAR", "TEXT", "STRING")):
|
||
return size is None or int(size.group(1)) <= MAX_CODE_LEN
|
||
return False
|
||
|
||
|
||
def _looks_like_code(name: str) -> bool:
|
||
words = catalog.name_words(name)
|
||
return bool(words) and words[-1] not in _NOT_CODE_TAILS and any(w in _CODE_WORDS for w in words)
|
||
|
||
|
||
def _code_columns(meta: dict[str, Any], notes: dict[str, Any]) -> list[str]:
|
||
"""要取值分布的列：目录里度量类型记为状态的、剖析以前提过码值候选的（再核一次）、或者类型和命名像状态、
|
||
类型、渠道的整数或短文字列。主键、唯一约束列、关系里的键列不算；码值人工确认或驳回过的不再取。
|
||
被遮罩的列也列出来，由检查记为「被遮罩」跳过——要让人看得见为什么它没有码值。"""
|
||
pk = [c.lower() for c in meta.get("primary_key") or []]
|
||
unique = {str(g[0]).lower() for g in meta.get("unique") or [] if isinstance(g, list) and len(g) == 1}
|
||
keys = {str(c).lower() for r in notes.get("relations") or [] if isinstance(r, dict) for c in r.get("columns") or []}
|
||
described = notes.get("columns") if isinstance(notes.get("columns"), dict) else {}
|
||
out: list[str] = []
|
||
for col in meta.get("columns") or []:
|
||
name = str(col.get("name") or "")
|
||
items = described.get(name) if isinstance(described.get(name), dict) else {}
|
||
codes, measure = items.get("codes"), items.get("measure")
|
||
if isinstance(codes, dict) and codes.get("status") in ("confirmed", "rejected"):
|
||
continue
|
||
status_measure = (isinstance(measure, dict) and measure.get("value") == "status"
|
||
and measure.get("status") != "rejected")
|
||
profiled = isinstance(codes, dict) and codes.get("source") == "profile"
|
||
if not (status_measure or profiled or _looks_like_code(name)):
|
||
continue
|
||
lowered = name.lower()
|
||
if (pk == [lowered]) or lowered in unique or lowered in keys or not _code_type_ok(col.get("type")):
|
||
continue
|
||
out.append(name)
|
||
return out
|
||
|
||
|
||
def _code_key(value: Any) -> str | None:
|
||
"""取值分布里的一个取值 → 码值（文字）。只认整数和不太长的文字。"""
|
||
if value is None or isinstance(value, bool):
|
||
return None
|
||
if isinstance(value, int):
|
||
return str(value)
|
||
if isinstance(value, float):
|
||
return str(int(value)) if value.is_integer() else None
|
||
if isinstance(value, str) and value.strip() and len(value) <= MAX_CODE_LEN and not _CONTROL.search(value):
|
||
return value
|
||
return None
|
||
|
||
|
||
def _share(count: int, total: int) -> str:
|
||
if total <= 0:
|
||
return "0%"
|
||
ratio = count / total
|
||
return "不足 1%" if 0 < ratio < 0.01 else f"{round(ratio * 100)}%"
|
||
|
||
|
||
async def _check_codes(cx: _Context, table: str, column: str, out: _TableOutcome, result: TableProfile) -> None:
|
||
"""GROUP BY 取出现最多的 CODES_MAX + 1 个取值：不超过 CODES_MAX 个就是码值候选（值有了，含义等人填）。"""
|
||
if cx.is_masked(column):
|
||
raise _Skip("masked", f"{table}.{column} 在数据源设置中被遮罩，不取值", carry=False)
|
||
d, meta = cx.dialect, cx.tables[table]
|
||
size = await cx.size_with_data(table, result)
|
||
scan_cap = cx.scan_cap(size)
|
||
res = await cx.run(d.value_counts_sql(d.table(meta, table), d.quote(column), CODES_MAX + 1, scan_cap=scan_cap),
|
||
max_rows=CODES_MAX + 1)
|
||
if not res.rows:
|
||
raise _Skip("no_data", f"{table}.{column} 没有非空值，无法取值分布")
|
||
if len(res.rows) > CODES_MAX:
|
||
raise _Skip("high_cardinality", f"{table}.{column} 的取值超过 {CODES_MAX} 个，不作为码值候选", carry=False)
|
||
values: list[tuple[str, int]] = []
|
||
for row in res.rows:
|
||
key = _code_key(row[0])
|
||
if key is None:
|
||
raise _Skip("unsupported", f"{table}.{column} 的取值不是整数或短文字，不作为码值候选", carry=False)
|
||
values.append((key, _as_int(row[1]) or 0))
|
||
if len(values) >= 3 and all(n == 1 for _, n in values):
|
||
# 每个取值只出现一次（票种编码 T01…T09）：这是一列标识，不是状态码
|
||
raise _Skip("high_cardinality", f"{table}.{column} 的取值各不相同，像标识而不是码值，不作为码值候选",
|
||
carry=False)
|
||
rows = sum(n for _, n in values)
|
||
scope = f"按前 {scan_cap} 行统计" if scan_cap else "统计全表"
|
||
spread = "、".join(f"{k}（{_share(n, rows)}）" for k, n in values)
|
||
note = f"{NOTE_PREFIX}{scope}，{rows} 行非空值共 {len(values)} 个取值：{spread}。"
|
||
out.codes.append(_CodesOutcome(column=column, values=values, rows=rows, note=note, complete=scan_cap is None))
|
||
|
||
|
||
def _is_date_column(col: dict[str, Any]) -> bool:
|
||
"""日期类列（catalog.is_date_column：和 SQL 检查认时间列是同一个判断）。"""
|
||
return catalog.is_date_column(str(col.get("name") or ""), col.get("type"))
|
||
|
||
|
||
async def _check_dates(cx: _Context, table: str, columns: list[str], total: int, out: _TableOutcome,
|
||
result: TableProfile) -> None:
|
||
"""日期类列的 MIN、MAX，作为业务日期的参考。整表统计，只对行数不超过上限的表做。表里只有一个日期类列
|
||
（total 是表结构里日期类列的个数，含被遮罩的）时提议它作为业务日期。"""
|
||
d, meta = cx.dialect, cx.tables[table]
|
||
size = await cx.size_with_data(table, result)
|
||
if not size.within(cx.settings.max_scan_rows):
|
||
raise _Skip("too_large", f"{table} 的行数超过整表统计的行数上限（{cx.settings.max_scan_rows} 行），"
|
||
"不取日期列的最小值和最大值")
|
||
res = await cx.run(d.min_max_sql(d.table(meta, table), [d.quote(c) for c in columns]))
|
||
row = res.rows[0] if res.rows else []
|
||
for i, column in enumerate(columns):
|
||
low, high = (row[2 * i], row[2 * i + 1]) if len(row) >= 2 * i + 2 else (None, None)
|
||
if low is None or high is None or not (_DATE_TEXT.match(str(low)) and _DATE_TEXT.match(str(high))):
|
||
continue
|
||
result.date_ranges.append({"column": column, "min": str(low), "max": str(high)})
|
||
if total != 1:
|
||
return
|
||
if not result.date_ranges:
|
||
raise _Skip("no_data", f"{table}.{columns[0]} 没有可识别的日期值")
|
||
found = result.date_ranges[0]
|
||
note = (f"{NOTE_PREFIX}表里只有这一个日期类列，取值从 {str(found['min'])[:19]} 到 "
|
||
f"{str(found['max'])[:19]}，可作为业务日期的参考。")
|
||
out.business_date = _DateOutcome(column=found["column"], low=found["min"], high=found["max"], note=note)
|
||
|
||
|
||
# ==========================================================================
|
||
# 结论进目录
|
||
# ==========================================================================
|
||
|
||
|
||
def _relation_finding(o: _RelationOutcome, rel: dict[str, Any], *, status: str, confirmed: bool) -> dict[str, Any]:
|
||
"""一条关系的核实结论。previous_status 是剖析之前目录里这条关系的状态：报告按它说「升为已验证」还是「仍为已验证」
|
||
（重新剖析、目录没变时不能说升了）；cardinality_checked：基数是不是用数据核实的（子表一侧数过是否唯一），
|
||
报告据此写「已用数据核实」，不从说明的原话里认。"""
|
||
previous = rel.get("status")
|
||
if rel.get("source") == "fk":
|
||
summary = ("外键约束，" + ("子表每个键只有一行（一对一）" if o.cardinality == "one_to_one"
|
||
else "子表同一个键有多行（一对多）") + "，基数已用数据核实") \
|
||
if o.cardinality_checked else "外键约束，子表太大或没能数清，基数未用数据核实"
|
||
elif confirmed:
|
||
summary = "已人工确认，只补充覆盖率和基数"
|
||
elif status == "verified":
|
||
summary = f"覆盖率 {_percent(o.coverage)}，" + ("仍为有确证" if previous == "verified" else "升为有确证")
|
||
elif o.coverage < catalog.PROFILE_VERIFY_COVERAGE:
|
||
summary = f"抽样覆盖率 {_percent(o.coverage)}，保持推断"
|
||
else:
|
||
summary = "被指向列未核实唯一，保持推断"
|
||
return {"kind": "relation", "path": f"relations.{o.rid}", "target": o.target,
|
||
"columns": list(rel.get("columns") or []), "to_table": rel.get("to_table"),
|
||
"to_columns": list(rel.get("to_columns") or []), "status": status, "confirmed": confirmed,
|
||
"previous_status": previous, "coverage": o.coverage, "cardinality": o.cardinality,
|
||
"cardinality_checked": o.cardinality_checked, "sample": o.sample, "matched": o.matched, "summary": summary}
|
||
|
||
|
||
def _codes_value(c: _CodesOutcome, item: dict[str, Any] | None) -> dict[str, str]:
|
||
"""码值候选的值：观察到的取值，含义先空着。原来有别的来源（模型起草、数据库注释）写过含义的，对得上的取值
|
||
沿用它的含义；它写了、数据里没出现的取值也留着——码值是「可能的取值」，没出现不等于不存在。"""
|
||
old = item.get("value") if isinstance(item, dict) and isinstance(item.get("value"), dict) else {}
|
||
value = {key: str(old.get(key) or "") for key, _ in c.values}
|
||
for key, meaning in old.items():
|
||
if key not in value and isinstance(meaning, str) and meaning.strip():
|
||
value[key] = meaning
|
||
return value
|
||
|
||
|
||
def _codes_finding(c: _CodesOutcome, value: dict[str, str]) -> dict[str, Any]:
|
||
"""码值候选的结论。pending：写进目录的码值里还有几个含义空着（别的来源写过的含义会沿用），报告按它说
|
||
「N 个含义待填写」，不从 summary 的原话里认。"""
|
||
pending = sum(1 for v in value.values() if not v.strip())
|
||
summary = f"{len(c.values)} 个取值" + (f"，{pending} 个含义待填写" if pending else "")
|
||
return {"kind": "codes", "path": f"columns.{c.column}.codes", "column": c.column,
|
||
"values": [{"value": k, "rows": n} for k, n in c.values], "rows": c.rows, "status": "proposed",
|
||
"pending": pending, "summary": summary}
|
||
|
||
|
||
def _patch_confirmed(rel: dict[str, Any], o: _RelationOutcome, at: str) -> bool:
|
||
"""人工确认过的关系只补覆盖率和基数：覆盖率是测量值，照新的写；基数只在原来没有时补，不改人定的；
|
||
备注只在原来为空、或者是剖析自己写的时候换成新的（只是日期变了不换）。状态、来源不动。返回改没改。"""
|
||
changed = False
|
||
if rel.get("coverage") != o.coverage:
|
||
rel["coverage"] = o.coverage
|
||
changed = True
|
||
if rel.get("cardinality") is None and o.cardinality is not None:
|
||
rel["cardinality"] = o.cardinality
|
||
if o.cardinality_checked:
|
||
rel["cardinality_checked"] = True
|
||
changed = True
|
||
note = rel.get("note")
|
||
if (not note or catalog.is_profile_note(note)) and not catalog.same_profile_note(note, o.note):
|
||
rel["note"] = o.note
|
||
changed = True
|
||
if changed:
|
||
rel["updated_at"] = at
|
||
return changed
|
||
|
||
|
||
def _patch_fk(rel: dict[str, Any], o: _RelationOutcome, at: str) -> bool:
|
||
"""外键关系只补基数和「用数据核实过」：外键结构推的多对一可能其实是一对一，数据说了算。来源、状态、
|
||
覆盖率都不动；备注同 _patch_confirmed（只是旧备注的日期不同不换）。返回改没改。"""
|
||
changed = False
|
||
if o.cardinality_checked:
|
||
if rel.get("cardinality") != o.cardinality:
|
||
rel["cardinality"] = o.cardinality
|
||
changed = True
|
||
if rel.get("cardinality_checked") is not True:
|
||
rel["cardinality_checked"] = True
|
||
changed = True
|
||
note = rel.get("note")
|
||
if (not note or catalog.is_profile_note(note)) and not catalog.same_profile_note(note, o.note):
|
||
rel["note"] = o.note
|
||
changed = True
|
||
if changed:
|
||
rel["updated_at"] = at
|
||
return changed
|
||
|
||
|
||
def _apply(existing: dict[str, Any] | None, out: _TableOutcome, *,
|
||
at: str) -> tuple[dict[str, Any], list[dict[str, Any]], catalog.MergeStats]:
|
||
"""把一张表的结论并进写入时的目录：(新目录, 写进去的发现, 计数)。纯函数，写入冲突重来时再调一次。
|
||
|
||
- 没被确认、驳回的关系：记为 source=profile，覆盖率够、父键唯一的 verified，否则 proposed；按 merge_notes
|
||
的规则并入（剖析顶得掉命名推断、模型起草，顶不掉外键和人工）。
|
||
- 人工确认过的关系：只补覆盖率和基数（_patch_confirmed）。
|
||
- 外键约束来的关系：只补基数和「用数据核实过」（_patch_fk），来源、状态、覆盖率都不动。
|
||
- 码值候选：profile / proposed，含义沿用别的来源写过的（_codes_value）；整表统计得到的标「已列全」，只看了
|
||
前若干行的不标；人工确认、驳回过的码值不碰。
|
||
- 业务日期：只有一个日期类列时提议，profile / proposed；已有别的来源定的业务日期不顶掉。
|
||
- covered={"profile"}：这次完整检查过、却没再得出的剖析结论删掉（比如取值变多、不再像码值的列，列被遮罩
|
||
之后它的码值）；没查成的检查（超时、预算用完……）把剖析以前写的结论原样带上，不因为这次没查成就删。
|
||
"""
|
||
existing = existing or {}
|
||
current = {str(r["id"]): r for r in existing.get("relations") or [] if isinstance(r, dict) and r.get("id")}
|
||
relations: list[dict[str, Any]] = []
|
||
confirmed: dict[str, _RelationOutcome] = {}
|
||
foreign: dict[str, _RelationOutcome] = {}
|
||
findings: list[dict[str, Any]] = []
|
||
for o in out.relations:
|
||
rel = current.get(o.rid)
|
||
if rel is None or rel.get("status") == "rejected":
|
||
continue # 核对期间被删、被驳回了：不写
|
||
if rel.get("source") == "fk":
|
||
foreign[o.rid] = o
|
||
findings.append(_relation_finding(o, rel, status=str(rel.get("status")), confirmed=False))
|
||
continue
|
||
if rel.get("status") == "confirmed":
|
||
confirmed[o.rid] = o
|
||
findings.append(_relation_finding(o, rel, status="confirmed", confirmed=True))
|
||
continue
|
||
status = "verified" if o.holds else "proposed"
|
||
relations.append({"id": o.rid, "columns": list(rel["columns"]), "to_table": rel["to_table"],
|
||
"to_columns": list(rel["to_columns"]), "cardinality": o.cardinality,
|
||
"coverage": o.coverage, "source": "profile", "status": status, "note": o.note,
|
||
# 只在基数用数据核实过时有这个键：没核实的关系和以前一字不差
|
||
**({"cardinality_checked": True} if o.cardinality_checked else {})})
|
||
findings.append(_relation_finding(o, rel, status=status, confirmed=False))
|
||
for rid in out.keep_relations:
|
||
rel = current.get(rid)
|
||
if rel is not None and rel.get("source") == "profile":
|
||
relations.append(copy.deepcopy(rel))
|
||
draft: dict[str, Any] = {"relations": relations} if relations else {}
|
||
|
||
described = existing.get("columns") if isinstance(existing.get("columns"), dict) else {}
|
||
columns: dict[str, dict[str, Any]] = {}
|
||
for c in out.codes:
|
||
item = (described.get(c.column) or {}).get("codes") if isinstance(described.get(c.column), dict) else None
|
||
if isinstance(item, dict) and item.get("status") in ("confirmed", "rejected"):
|
||
continue
|
||
columns[c.column] = {"codes": catalog.make_item(_codes_value(c, item), "profile", "proposed", note=c.note,
|
||
complete=c.complete)}
|
||
findings.append(_codes_finding(c, columns[c.column]["codes"]["value"]))
|
||
for column in out.keep_codes:
|
||
item = (described.get(column) or {}).get("codes") if isinstance(described.get(column), dict) else None
|
||
if isinstance(item, dict) and item.get("source") == "profile":
|
||
columns[column] = {"codes": copy.deepcopy(item)}
|
||
if columns:
|
||
draft["columns"] = columns
|
||
|
||
current_date = existing.get("business_date") if isinstance(existing.get("business_date"), dict) else None
|
||
ours = current_date is None or (current_date.get("source") == "profile"
|
||
and current_date.get("status") not in ("confirmed", "rejected"))
|
||
if out.business_date is not None and ours:
|
||
# 已有别的来源（模型起草、人工）定的业务日期不顶掉：按来源的可信程度剖析排得更前，但它只知道
|
||
# 「表里只有这一个日期列」，不比写了规则和时区的那条更懂业务
|
||
b = out.business_date
|
||
draft["business_date"] = catalog.make_item({"column": b.column}, "profile", "proposed", note=b.note)
|
||
findings.append({"kind": "business_date", "path": "business_date", "column": b.column, "min": b.low,
|
||
"max": b.high, "status": "proposed", "summary": f"提议按 {b.column} 作为业务日期"})
|
||
elif out.keep_business_date and current_date is not None and current_date.get("source") == "profile":
|
||
draft["business_date"] = copy.deepcopy(current_date)
|
||
|
||
merged, stats = catalog.merge_notes(existing, draft, covered={"profile"}, at=at)
|
||
for rel in merged.get("relations") or []:
|
||
rid = str(rel.get("id"))
|
||
o = foreign.get(rid)
|
||
if o is not None and rel.get("source") == "fk":
|
||
if _patch_fk(rel, o, at):
|
||
stats += catalog.MergeStats(updated=1)
|
||
continue
|
||
o = confirmed.get(rid)
|
||
if o is not None and rel.get("status") == "confirmed" and _patch_confirmed(rel, o, at):
|
||
stats += catalog.MergeStats(updated=1)
|
||
return merged, findings, stats
|
||
|
||
|
||
# ==========================================================================
|
||
# 入口
|
||
# ==========================================================================
|
||
|
||
#: 正在剖析的数据源。检查和登记之间没有 await，在一个事件循环里是原子的；服务端是单进程部署，
|
||
#: 多进程部署时要换成库里的锁
|
||
_RUNNING: set[str] = set()
|
||
|
||
|
||
@dataclass
|
||
class _Check:
|
||
kind: str
|
||
target: str
|
||
path: str | None
|
||
run: Callable[[], Awaitable[None]]
|
||
#: 没查成时调用：把目录里剖析以前对这一项写的结论标记为原样保留
|
||
keep: Callable[[], None]
|
||
|
||
|
||
def _plan(cx: _Context, table: str, notes: dict[str, Any], out: _TableOutcome,
|
||
result: TableProfile) -> list[_Check]:
|
||
"""这张表要做的检查，按价值排：关系、码值、日期。先列全再执行：中途停下时，没做的每一项都要记下原因。"""
|
||
meta = cx.tables[table]
|
||
checks: list[_Check] = []
|
||
for rel in _relation_candidates(notes):
|
||
rid = str(rel["id"])
|
||
checks.append(_Check("relation", _relation_target(rel), f"relations.{rid}",
|
||
lambda rel=rel: _check_relation(cx, table, rel, out, result),
|
||
lambda rid=rid: out.keep_relations.add(rid)))
|
||
for column in _code_columns(meta, notes):
|
||
checks.append(_Check("codes", column, f"columns.{column}.codes",
|
||
lambda column=column: _check_codes(cx, table, column, out, result),
|
||
lambda column=column: out.keep_codes.add(column)))
|
||
dates = [str(c["name"]) for c in meta.get("columns") or [] if isinstance(c, dict) and _is_date_column(c)]
|
||
for column in dates:
|
||
if cx.is_masked(column):
|
||
result.skipped.append(ProfileSkip("date", column, "masked",
|
||
f"{table}.{column} 在数据源设置中被遮罩，不取最小值和最大值"))
|
||
usable = [c for c in dates if not cx.is_masked(c)]
|
||
if usable:
|
||
checks.append(_Check("date", "、".join(usable), "business_date" if len(dates) == 1 else None,
|
||
lambda: _check_dates(cx, table, usable, len(dates), out, result),
|
||
lambda: setattr(out, "keep_business_date", True)))
|
||
return checks
|
||
|
||
|
||
async def _profile_table(cx: _Context, table: str, notes: dict[str, Any], result: TableProfile) -> _TableOutcome:
|
||
out = _TableOutcome()
|
||
if cx.tables[table].get("is_view"):
|
||
result.skipped.append(ProfileSkip("table", table, "view", "视图没有统计信息，剖析可能触发整个视图的计算，已跳过"))
|
||
return out
|
||
checks = _plan(cx, table, notes, out, result)
|
||
for i, check in enumerate(checks):
|
||
try:
|
||
await check.run()
|
||
except _Skip as e:
|
||
result.skipped.append(ProfileSkip(check.kind, check.target, e.reason, e.detail, check.path))
|
||
if e.carry:
|
||
check.keep()
|
||
except _Stop as e:
|
||
detail = _STOP_DETAIL[e.reason].format(max_queries=cx.settings.max_queries,
|
||
max_total_s=_fmt(cx.settings.max_total_s))
|
||
for rest in checks[i:]:
|
||
result.skipped.append(ProfileSkip(rest.kind, rest.target, e.reason, detail, rest.path))
|
||
rest.keep()
|
||
break
|
||
if table in cx.sizes:
|
||
result.row_estimate = cx.sizes[table]
|
||
return out
|
||
|
||
|
||
async def _write(session: AsyncSession, source_id: str, table: str, out: _TableOutcome, result: TableProfile, *,
|
||
at: str, actor: str | None) -> None:
|
||
"""并入并写入（乐观锁）。撞上别人刚改过就重读重并，最多三次。"""
|
||
for _attempt in range(3):
|
||
entry = await catalog.read_entry(session, source_id, table)
|
||
version = entry.version if entry else 0
|
||
notes, findings, stats = _apply(entry.notes if entry else {}, out, at=at)
|
||
result.findings = findings
|
||
result.added, result.updated, result.removed = stats.added, stats.updated, stats.removed
|
||
result.version = version
|
||
if entry is None and not notes:
|
||
return # 什么也没得出，不建空目录
|
||
try:
|
||
written = await catalog.write_entry(session, source_id, table, notes, if_version=version, actor=actor)
|
||
except catalog.CatalogConflict:
|
||
continue
|
||
result.version = written.version
|
||
return
|
||
result.error = "这张表的数据目录正被其他人修改，剖析结果未能写入，请稍后重新剖析"
|
||
result.findings = []
|
||
result.added = result.updated = result.removed = 0
|
||
|
||
|
||
async def _pick_tables(session: AsyncSession, source: Any, tables: list[str] | None,
|
||
entries: dict[str, catalog.CatalogEntry], report: ProfileReport) -> list[str]:
|
||
cache = getattr(source, "schema_cache", None) or {}
|
||
all_tables = cache.get("tables") or {}
|
||
if tables:
|
||
picked: list[str] = []
|
||
for name in dict.fromkeys(str(t) for t in tables):
|
||
key = catalog.resolve_table_name(cache, name)
|
||
if key is None:
|
||
report.tables.append(TableProfile(table=name, error=f"表结构里没有 {name}，请先重新探查结构"))
|
||
elif key not in picked:
|
||
picked.append(key)
|
||
return picked
|
||
usage = await catalog.table_usage(session, source)
|
||
order = {name: i for i, name in enumerate(all_tables)}
|
||
candidates = [name for name, meta in all_tables.items()
|
||
if not (meta or {}).get("is_view") and name in entries
|
||
and _relation_candidates(entries[name].notes)]
|
||
# 还有待核实（推断）关系的表排在前面：剖析就是来核实它们的；关系都核实过、人工确认过的再剖析只是补覆盖率。
|
||
# 同样待核实的按使用次数，再按表结构顺序。返回全部候选，空表由 _skip_empty 估过行数再跳过
|
||
return sorted(candidates, key=lambda n: (not _pending(entries[n].notes), -usage.get(n, 0), order[n]))
|
||
|
||
|
||
def _pending(notes: dict[str, Any] | None) -> bool:
|
||
"""这张表还有没有待核实的关系：要核对的关系里有还是推断（proposed）的。"""
|
||
return any(r.get("status") == "proposed" for r in _relation_candidates(notes))
|
||
|
||
|
||
async def _skip_empty(cx: _Context, candidates: list[str], report: ProfileReport) -> list[TableProfile]:
|
||
"""不指定表时：按顺序估候选表的行数，确知是空表的跳过（记进 report.empty_tables），凑够 PROFILE_DEFAULT_TABLES
|
||
张为止。以前不估，所有表使用次数都是 0 时按表结构顺序取前 10 张，结果大半是空表、一条关系都核实不了。
|
||
|
||
估行数的查询算进这张表的查询数，行数留在 cx.sizes 里，剖析时不再查。最多估 PROFILE_PROBE_TABLES 张、最多用掉
|
||
查询次数上限的一半；超过了、或者整次剖析已经停下，剩下的候选不估、照顺序排上（真是空表的，剖析时各项检查会
|
||
记下「空表，无法剖析」）。
|
||
"""
|
||
picked: list[TableProfile] = []
|
||
probed = 0
|
||
for name in candidates:
|
||
if len(picked) >= PROFILE_DEFAULT_TABLES:
|
||
break
|
||
result = TableProfile(table=name)
|
||
if (cx.run.stopped is None and probed < PROFILE_PROBE_TABLES
|
||
and cx.run.used < cx.settings.max_queries // 2):
|
||
probed += 1
|
||
before = cx.run.used
|
||
try:
|
||
size = await cx.size(name, result)
|
||
except _Stop:
|
||
size = None
|
||
result.queries = cx.run.used - before
|
||
if size is not None and size.rows == 0:
|
||
report.empty_tables.append(name)
|
||
continue
|
||
picked.append(result)
|
||
return picked
|
||
|
||
|
||
async def profile_catalog(session: AsyncSession, row: Any, source: Any, *, tables: list[str] | None = None,
|
||
actor: str | None = None, settings: ProfileSettings | None = None) -> ProfileReport:
|
||
"""剖析这些表并把结论写进数据目录，同步完成。
|
||
|
||
- row：数据源记录（开关、遮罩按它的 options）；source：用来查询和读表结构的源（上传源是绑定当前快照的视图）。
|
||
- settings 不给就按 row.options 读；没开启抛 ProfileDisabled，这个源正在剖析抛 ProfileBusy。
|
||
- tables 为空时按使用次数取前 PROFILE_DEFAULT_TABLES 张目录里有待核实关系的表。
|
||
- 每张表做完就写入，后面的表停下（预算、总时长）不影响前面已经写进去的。
|
||
"""
|
||
settings = ensure_enabled(row, settings)
|
||
if source.id in _RUNNING:
|
||
raise ProfileBusy(f"数据源「{getattr(row, 'name', '')}」正在进行数据剖析，请等待完成后再试")
|
||
_RUNNING.add(source.id)
|
||
try:
|
||
return await _profile(session, row, source, tables, actor, settings)
|
||
finally:
|
||
_RUNNING.discard(source.id)
|
||
|
||
|
||
def ensure_enabled(row: Any, settings: ProfileSettings | None = None) -> ProfileSettings:
|
||
"""这个数据源能不能剖析：数据源停用了、或者没开启数据剖析，抛 ProfileDisabled（message 给人看）。
|
||
返回要用的设置（不给就按 row.options 读）。接口在做别的检查之前先调它：开关是第一道门。"""
|
||
settings = settings or profile_settings(getattr(row, "options", None))
|
||
name = getattr(row, "name", "") or ""
|
||
if getattr(row, "enabled", True) is False:
|
||
raise ProfileDisabled(f"数据源「{name}」已停用，无法进行数据剖析。请先在数据源设置中启用", code="datasource_inactive")
|
||
if not settings.enabled:
|
||
raise ProfileDisabled(f"数据源「{name}」未开启数据剖析。剖析会对业务库发查询，请先在数据源设置中开启数据剖析")
|
||
return settings
|
||
|
||
|
||
async def _profile(session: AsyncSession, row: Any, source: Any, tables: list[str] | None, actor: str | None,
|
||
settings: ProfileSettings) -> ProfileReport:
|
||
at = catalog.now_iso()
|
||
report = ProfileReport(profiled_at=at, settings=settings)
|
||
dialect = SqlDialect(source.kind)
|
||
run = _Runner(source, settings, dialect)
|
||
cx = _Context(source=source, settings=settings, dialect=dialect, run=run,
|
||
tables=(getattr(source, "schema_cache", None) or {}).get("tables") or {},
|
||
masked={c.lower() for c in data_engine.masked_columns(getattr(row, "options", None))})
|
||
entries = await catalog.read_catalog(session, source.id)
|
||
picked = await _pick_tables(session, source, tables, entries, report)
|
||
results = [TableProfile(table=t) for t in picked] if tables else await _skip_empty(cx, picked, report)
|
||
for result in results:
|
||
table = result.table
|
||
report.tables.append(result)
|
||
if run.stopped:
|
||
detail = _STOP_DETAIL[run.stopped].format(max_queries=settings.max_queries,
|
||
max_total_s=_fmt(settings.max_total_s))
|
||
result.skipped.append(ProfileSkip("table", table, run.stopped, detail))
|
||
continue
|
||
before = run.used
|
||
entry = entries.get(table)
|
||
out = await _profile_table(cx, table, entry.notes if entry else {}, result)
|
||
result.queries += run.used - before
|
||
await _write(session, source.id, table, out, result, at=at, actor=actor)
|
||
report.queries_used = run.used
|
||
report.stopped = run.stopped
|
||
logger.info("数据剖析 源=%s 表=%s 查询=%d 停止=%s 署名=%s", source.id,
|
||
",".join(t.table for t in report.tables), run.used, run.stopped, actor)
|
||
return report
|
||
|
||
|
||
__all__ = ["CODES_MAX", "IN_CHUNK", "MAX_CODE_LEN", "MAX_LITERAL_LEN", "NOTE_PREFIX", "PROFILE_DEFAULT_TABLES",
|
||
"PROFILE_OPTION", "PROFILE_PROBE_TABLES", "ProfileBusy", "ProfileDisabled", "ProfileReport",
|
||
"ProfileSettings", "ProfileSkip", "SqlDialect", "TableProfile", "TableSize", "ensure_enabled",
|
||
"estimate_size", "profile_catalog", "profile_settings", "profile_settings_problem", "profile_settings_rejection",
|
||
"sql_literal"]
|