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ThearchyHelios
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上一轮（db91c9e）给派生来源加了结构标识、按结构配对之后，复验还有一批用例返回空列表或者报得自相矛盾。按根因分几类改：
外连接：joins 第二遍按涉及的来源配对、不分方向，orders LEFT JOIN refunds 和 refunds LEFT JOIN orders 配成一对后类型、条件都一样，一句不说（db91c9e 引入的回归），RIGHT JOIN 对调、两个 CTE 对调、子查询写法同样漏。现在 JoinFacet 记下主表（keep）和可空那一侧（nullable），LEFT / RIGHT 按主表比：对调了报「原流程以 orders 为主表外连接 refunds，盲算以 refunds 为主表外连接 orders」，LEFT JOIN 和两边对调的 RIGHT JOIN 是同一回事、不再报成类型不同（原来列为做不到）。同一段 WHERE 里拿可空那一侧的列比较、IN、LIKE、BETWEEN、IS NOT NULL 的（JoinFacet.rejects），这次外连接按内连接比：盲算把可空一侧的条件写进 WHERE、LEFT JOIN 实际成了内连接的照报；IS NULL、OR、套在 COALESCE / CASE 里的不认。
算出来的列（Computed，新的 expression 一面）：聚合只按去重后的 (函数, 参数) 集合比，SUM(p.total) - SUM(r.total) 对反过来、退款率分子分母对调报不出；派生来源里不是聚合的列不进任何方面，net.v 谁减谁、x.total 取的是付款还是退款合计、amount * 0.9 对 0.8、CASE 的口径、窗口函数的分区和排序、RANK 对 ROW_NUMBER 都是空列表。现在最外层选出来的列（先剥掉 ROUND、CAST、COALESCE 给默认值这类外壳）按算法比，用到的聚合一样、位置换了照报；派生来源里被外面用到、又不是原样透出一列的列按定义比。只差在聚合上、聚合那一面已经报了的，按透过去的那一列筛时间、时间那一面已经报了的，不再报第二遍。比较时加法、乘法的两项排好先后，DATE()、CAST(… AS DATE)、::date 统一成一种写法，免得写法不同被报成算法不同。
时间：时间条件的列透过「同一列套着日期函数、CAST、MIN / MAX」算出来的派生列，一直换到实表（TimePredicate.via 记下路过的列）：日期表达式写在 CTE 里，按支付时间还是下单时间筛照样报出来，带上表名、列名给调用方对照数据目录（三个方言的 DATE()、CAST … BETWEEN、两个同名 CTE 对调后的 MAX(paid_at) 对 MAX(refunded_at)）。
结构标识和配对：_Derived 里往里套着的派生来源原来一律写「@」，net 是 paid.total - refunded.total 还是反过来写出来一样。现在按结构写的 shape 写法里引用派生来源的地方写它自己的结构标识（里面那段按 shape 写出来再取摘要），配对之前比较的两边也按结构标识排先后；配对之后仍按共同编号排（配成一对的两个派生来源里面稍有不同时结构标识就不同，按它排会把同一个比较排成两个方向）。_align 同一级先看条件重合、再看名字：两边都叫 paid、一边筛已付一边筛未付时不再按名字配反。配成一对的派生来源里两边起名不同的列按定义配成同一列（total 对 sum_amt，原来列为做不到；_renamed），两边各剩一列时也配上，定义的不同照报。
筛的先后：派生来源取前几行（LIMIT、OFFSET）或算了窗口函数（这一列又不是分区键，含 DISTINCT ON）时，外面的条件不再透成里面那张表的条件；Part 另记一路透到底的写法（pierce）和挡住它的是什么（stage），两边只差在这里时报「原流程先算 t 的窗口函数、再按 status = 'paid' 筛选，盲算先按 status = 'paid' 筛选、再算 t 的窗口函数」「先取 t 的前 10 行、再筛」，时间条件同样。
没用到的 CTE：原来逐段收集连定义了没用的 CTE 里的条件也收，盲算定义了只筛已付的 CTE 却直接查 orders 报不出来，没用的 CTE 里多一个条件又会被报成多筛了一遍。现在只收从最外层一路引用到的段（_Statement._enliven）；例外是两边都定义了同一个 CTE、一边把它关联进来一边没用到，没用到的那边照样收它，免得它里面的聚合、分组被说成一边独有（连接那一面已经说了关联了它）。
说清楚：两边同名的派生来源其实不是同一个时（t1 / t2、a / b 定义对调），「按 t1.total > 100 筛选」两边写法一模一样，读起来自相矛盾。Part 记下用到的派生来源各列的来历（origins，一直换到实表的列），给人看的写法依次退到一律写表名、带上来历（t1.total 即 SUM(orders.amount)）、来历也一样（两个 CTE 只差里面的条件）时说「盲算的 paid 对应原流程的 open」。
自己关联自己：同一个 CTE、同一张表在一段里出现两次，两个别名按各自在关联条件里出的列区分（_Source.role），b1.total > b2.total 写反了报得出来，换了别名、换了关联先后不报（原来列为做不到）。CTE、子查询自己写了列名的（WITH t(n) AS …，递归 CTE 常这么写）按写的列名认列。
模块说明、Part / JoinFacet / TimePredicate / Computed / Facets / FacetDiff、unmatched、joins 的文档按现在的做法改写，做不到的照实列出：两边起名不同、各多出不止一列且定义都不同的列仍算两列；全换了的派生来源不配对；条件改得一个都不重合又各起了名字的同形派生来源只能按先后配；自连接两个别名在关联条件里出的列一样时分不出；三项以上的加法乘法换序、括号展开算不同算法；QUALIFY、GROUP BY 之后才筛的先后不认；外连接链里连带变成内连接的、套在函数里或写在外层 WHERE 的不认；不是 facets 算出来的 Facets 只能按位置编号比。
测试：复验清单里的用例逐个补成测试（各方言、CTE 和子查询写法），另加意思一样、不该报的反例（LEFT / RIGHT 对调、WHERE 筛主表、外连接链换序、0.9 * amount、DATE 对 CAST、按分区键在窗口前后筛、两边都先取前 10 行、列起名不同、自连接换别名换先后、没用到的 CTE）。新加 64 项，其中 48 项在 db91c9e 上失败，其余是防误报的，两边都通过；原有 128 项和 test_verify_agent 照旧通过，全量 7113 项通过。复验清单最后一条只到「WITH base AS (SE」就截断了，看不到全文，按开头和已知缺口一并处理了 CTE 自连接。
2796 lines
162 KiB
Python
2796 lines
162 KiB
Python
"""SQL 语义：两条 SQL 算的是不是一回事，不是的话差在哪。
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双盲复算要回答「盲算和原流程的 SQL 差在哪」（A 按支付时间筛、B 按下单时间筛；A 排除了作废的行、B 没有），运行
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对比要回答「这一期和上一期的 SQL 是不是同一个模板」（定时运行每次的日期不同，不能算模板变了），反方审稿要看自己
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的查询和原查询的口径是否一致。三处共用这里：
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- normalize_sql：字面量换成占位符之后的规范文本，加上字面量本身（按规范文本里的顺序）。两条 SQL 只有字面量不同，
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规范文本就相同；关键字大小写、空白、注释、不加引号的名字的大小写都不算不同。
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- facets：把一条查询拆成几个方面——用到的表、连接（类型、关联进来的表、ON 条件、外连接以哪一侧为主表）、WHERE
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的各个合取式、其中的时间条件（列、运算符、取值）、分组、聚合（函数、参数、是否去重）、算出来的列（最外层的算法、
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CTE 和子查询里被外面用到的列的定义，窗口函数也在这里）、HAVING、取哪几行（LIMIT、OFFSET、取前几行时的排序）。
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别名一律换成真实表名（条件里套着的子查询也是），等式、比较、加法、乘法的两边排好顺序：o.paid_at >= '2026-09-01'
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和 '2026-09-01' <= orders.paid_at 是同一个条件。
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- diff_facets：逐个方面比两份 facets，每处不同给一句中文说明。
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**逐段收集。** CTE、子查询里的条件、聚合和取行也算进来：盲算可能把有效记录条件写在 CTE 里，原流程写在外层，按
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「整条语句里有哪些条件」比才不会把同一个口径报成不同。只收用到了的段：定义了却没被引用的 CTE 不影响结果，不收
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（盲算定义了只筛已付的 CTE 却直接查 orders，少的那个条件要报出来）。逗号连接（以及 INNER JOIN 之外又写在 WHERE
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里的等值关联）写在 WHERE 里的列等式算作关联条件，不算筛选。条件里套着的子查询（EXISTS、IN (SELECT …)）既单算
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一段，也按它自己那一段的来源整个写进外层那个条件：别名在子查询里定义，拿外层的来源去认，同一个条件只因别名不同
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就会被报成不同。
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**各自起的名字不进比较。** 表的别名换成真实表名；CTE、FROM 里的子查询（含 LATERAL）没有真实表名可换，单看一条
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语句时按它在语句里的位置编号（@1、@2…，从外往里、按第一次用到的先后），给人看时照写名字；条件里的子查询（IN、
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EXISTS、标量子查询）选出来的列名不影响取值，比较时去掉。这些名字都是各自起的，双盲复算的盲算更是：按名字比，同一个
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口径会被说成换了口径。同一个来源在一段里出现两次（自己关联自己）时，两个别名按各自在关联条件里出的列区分
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（b2.user_id = b1.referrer_id：b1 出 referrer_id、b2 出 user_id），b1.total > b2.total 写反了认得出，换了别名、
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换了先后不算不同。
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**两边的派生来源按结构配对。** 位置编号只看先后：一边多出一个排在前面的 CTE，或者内连接两边换了先后，编号就错开
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了；可也不能干脆不看是哪一个（两个 CTE 都算出 total 时，外层用的是付款合计还是退款合计，正是要报的不同）。所以
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diff_facets 先给两边的每个派生来源算一份结构标识（见 _Derived）：里面读到的实表（FROM / JOIN，往里套着的也算）、
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选出来的各列怎么定义（规范化后的定义式，如 total 是 SUM(orders.amount)）、按什么分组、里面的条件、整段规范化后的
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写法，以及起的名字。这些写法里往里套着的派生来源写它自己的结构标识（见 _Statement._signature），和名字、编号无关：
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net 读的是 paid.total - refunded.total 还是反过来，写出来不一样。再按从严到宽的几级一对一地配（见 _align）：整段
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一样；读的表、各列定义、分组一样（里面的筛选条件可以不同）；读的表和选出来的列名一样（某一列的算法可以不同）；读的
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表和名字一样；最后三级只在两边都只剩一个时才配：只是读的表一样、只是名字一样、只是选出来的列名一样。同一级有几个
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都配得上时，先挑里面的条件重合最多的，再挑同名的（名字是各自起的：两边都叫 paid，一边筛已付、一边筛未付，不是一
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回事），最后才看位置编号的先后。哪一级都配不上的不配：一边多出来的 CTE 不会被拿去和另一边不相干的 CTE 凑成一对。
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配成一对的派生来源里，两边起名不同的列按定义配成同一列（一边叫 total、一边叫 sum_amt，见 _renamed）。配好之后，
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第二条 SQL 的派生来源改用第一条里对应的那个编号（配不上的另起编号），按这个共同的编号重新分析两边再逐个方面比：
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比较的两边谁在前、关联条件的先后都按共同的编号排，内连接换了先后也排成同一个方向。
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**派生来源里的算法。** 外面引用的是「t.net」，两边写的一样，net 在里面怎么算的（amount * 0.9 还是 * 0.8、窗口
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函数按什么分区排序、是 paid.total 还是 refunded.total）只看外面看不出来：派生来源里被外面用到、又不是原样透出
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一列的列，按定义比（见 Computed）。最外层算出来的列（SUM(p.total) - SUM(r.total)、窗口函数、CASE）也按算法比：
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聚合两边的集合一样、位置换了，聚合那一面看不出来。
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**什么时候能透过派生来源。** CTE、子查询原样透出一张表的列（SELECT *，或者直接选出这一列）时，外面按它写的条件、
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聚合换成那张表的列：先在 CTE 里筛一遍再查和直接查是同一列。它要取前几行（LIMIT、OFFSET）、或者算了窗口函数（这一列
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又不是分区键）时不透：先取前 10 行再筛已付，和先筛已付再取前 10 行取到的不是同一批；两边只差在这里的，报筛的先后
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不同。时间条件另外透过「同一列套着日期函数、CAST、MIN / MAX」算出来的列（DATE(paid_at) AS d），日期表达式写在 CTE
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里，按支付时间还是下单时间筛照样认得出。
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**外连接。** 按以哪一侧为主表（保留它的全部行）比，不按写的是 LEFT 还是 RIGHT：orders LEFT JOIN refunds 和
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refunds RIGHT JOIN orders 一样，和 refunds LEFT JOIN orders 不一样。同一段 WHERE 里拿可空那一侧的列比较、IN、
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LIKE 的（空值都不成立），把没关联上的行筛掉了，按内连接比：写的是 LEFT JOIN，实际成了 INNER JOIN，要报出来。连接
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里的内连接（含逗号连接、CROSS JOIN）按涉及的来源和条件比，不按哪一侧是关联进来的；一边独有的一次内连接，关联
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进来的那一侧另一边也有时，报的是它接上的另一头（FROM stores JOIN orders、另一边只查 orders：多出来的是 stores）。
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**写法一样、意思不同时说清楚。** 两边同名的派生来源其实不是同一个（盲算的 t1 是原流程的 t2）时，光写「t1.total」
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两边一模一样：带上各列的来历（t1.total 即 SUM(orders.amount)）；来历也一样（两个 CTE 只差里面的条件）时，说
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「盲算的 paid 对应原流程的 open」。
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仍做不到的：
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- 两边起名不同的派生来源的列，两边各自多出不止一列、定义又都不一样时配不上，算不同的列，外层按它们写的条件照报
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成两边各有一个；读的表、选出来的列名、名字全换了的两个派生来源不配对，同样照报。
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- 读同一张表、各列定义也一样的两个派生来源，两边都改了里面的条件、改得一个都不重合，又各起了名字时，只能按先后配，
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可能配反。
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- 自己关联自己、两个别名在关联条件里出的列一样（b1.user_id = b2.user_id）时分不出谁是谁；这时 WHERE 里对调过来，
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算出来的行数也一样，只有最外层直接选其中一个别名的列（不比，见下）时会漏。
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- 同一个算法写法不同：三项以上的加法、乘法换了先后（a + b + c 对 c + b + a）、括号展开（a * (b + c) 对 a * b +
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a * c）、取日期以外的等价函数，算不同的算法。最外层只比算出来的列：光一列、字面量不比；ROUND、CAST、COALESCE
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给默认值这类外壳当作同一个数（最外层取整到分不算口径不同）。派生来源里没被外面用到的列不比；UNION 按各支同一个
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位置比。
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- 筛的先后只认取前几行（LIMIT、OFFSET）、窗口函数（含 DISTINCT ON）挡住的；QUALIFY、GROUP BY 之后才筛的不认。
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外连接被 WHERE 变成内连接只认同一段 WHERE 里直接用到可空那一侧列的比较、IN、LIKE、BETWEEN、IS NOT NULL；套在
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COALESCE、CASE 里，或者写在外面一层 WHERE 里的不认。连接上别的做不到的见 _Compare.joins。
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- facets 单独返回的 key 仍是位置编号；不是 facets 算出来的 Facets（没记原文）diff_facets 也只能按位置编号比，
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没用到的 CTE、起名不同的列也不再另配。
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**和 sqlcheck 一样宁可漏报。** 解析不了（语法错、方言特性、多条语句、不是查询）就带 parse_error 返回，从不抛
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异常。没加表前缀、又有好几张表可能有这一列的，照写列名（给了表结构才去对）。只读语法树，不执行 SQL。
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"""
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from __future__ import annotations
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import hashlib
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import logging
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import re
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from collections import deque
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from collections.abc import Iterable, Iterator, Mapping
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from dataclasses import dataclass, field, fields, is_dataclass, replace
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from itertools import zip_longest
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from typing import Any
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from app.data import catalog
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from app.data.names import name_key
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from app.data.sqlcheck import _bare_column, _conjuncts, _parents, _unparen, dialect_of
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logger = logging.getLogger(__name__)
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#: 规范文本里字面量的占位符
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PLACEHOLDER = "?"
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#: 太长的 SQL 不做语法分析（normalize_sql 退回逐词规范化，facets 带 parse_error）：解析耗时随长度增长
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MAX_SQL_CHARS = 100_000
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#: 每段 SELECT 在语法树上记段号的 meta 键。条件、表达式要复制一份再改写，复制出来的子查询靠段号找回原来那一段
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#: 算好的来源（别名、外层）：复制品没有父节点，自己找不到外层
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_SEGMENT = "sql_semantics_segment"
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#: 派生来源（引用 CTE 的表和 CTE 的定义、FROM / JOIN 里的子查询）在语法树上记比较用编号的 meta 键（见
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#: _Statement._number_derived、_Statement.relabel）。复制出来的条件里套着子查询时，靠它把 CTE 名、子查询的别名
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#: 换成编号
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_DERIVED = "sql_semantics_derived"
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#: 不写编号的写法（render 的 anon 模式）里派生来源一律写成这个：排比较的两边谁在前时先看实表的列还是派生来源的列
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_ANON = "@"
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#: render 里比较用的写法（见 render）：名字按 name_key，别名、各自起的名字都去掉
|
||
_COMPARING = frozenset({"key", "loose", "anon", "shape", "pierce"})
|
||
#: 外连接写在 WHERE 里会把可空那一侧没关联上的行（那一侧的列都是空）筛掉的条件：拿空值比都不成立
|
||
_NULL_REJECTING = ("EQ", "NEQ", "GT", "GTE", "LT", "LTE", "Like", "ILike", "Between", "In")
|
||
|
||
|
||
# ==========================================================================
|
||
# 解析
|
||
# ==========================================================================
|
||
|
||
|
||
def _read(dialect: str | None) -> str | None:
|
||
"""数据源类型（sqlite / postgresql / mysql …）或 sqlglot 的方言名 → 解析用的方言。认不出的按 sqlglot 的通用读法。"""
|
||
found = dialect_of(dialect)
|
||
if found or not dialect:
|
||
return found
|
||
from sqlglot.dialects.dialect import Dialect
|
||
|
||
name = dialect.strip().lower()
|
||
try:
|
||
Dialect.get_or_raise(name)
|
||
except Exception: # noqa: BLE001 - 不认识的方言名：按通用读法
|
||
return None
|
||
return name
|
||
|
||
|
||
def _parse_problem(error: Exception) -> str:
|
||
"""sqlglot 的报错 → 一句给人看的话。原文是英文、还带终端的高亮控制符，只取出错的位置。"""
|
||
errors = getattr(error, "errors", None) or []
|
||
first = errors[0] if errors and isinstance(errors[0], dict) else {}
|
||
line, col = first.get("line"), first.get("col")
|
||
if isinstance(line, int) and isinstance(col, int):
|
||
return f"SQL 无法解析（第 {line} 行第 {col} 列附近）"
|
||
return "SQL 无法解析"
|
||
|
||
|
||
def _parse(sql: Any, read: str | None) -> tuple[Any, str | None]:
|
||
"""(语法树, None) 或 (None, 为什么分析不了)。只认单条查询。"""
|
||
import sqlglot
|
||
from sqlglot import exp
|
||
|
||
if not isinstance(sql, str) or not sql.strip():
|
||
return None, "SQL 为空"
|
||
text = sql.strip()
|
||
if len(text) > MAX_SQL_CHARS:
|
||
return None, f"SQL 超过 {MAX_SQL_CHARS} 个字符，没有做语法分析"
|
||
try:
|
||
statements = [s for s in sqlglot.parse(text, read=read) if s is not None]
|
||
except Exception as e: # noqa: BLE001 - 语法错、方言特性、sqlglot 不支持的写法
|
||
return None, _parse_problem(e)
|
||
if not statements:
|
||
return None, "SQL 为空"
|
||
if len(statements) > 1:
|
||
return None, f"一次只能分析一条 SQL，这里有 {len(statements)} 条"
|
||
if not isinstance(statements[0], exp.Query):
|
||
return None, "不是查询语句（只分析 SELECT、WITH 开头的查询）"
|
||
return statements[0], None
|
||
|
||
|
||
# ==========================================================================
|
||
# 规范化：字面量换成占位符
|
||
# ==========================================================================
|
||
|
||
|
||
@dataclass(frozen=True)
|
||
class NormalizedSql:
|
||
"""规范文本和字面量。text 相同就是同一个模板，literals 是这一次填进去的值（SQL 写法，字符串带引号）。
|
||
|
||
parse_error 不为空时 text 是逐词规范化的结果（关键字转大写、不加引号的名字转小写、字面量换成占位符）：
|
||
同一个模板只改了字面量的两条 SQL 照样得到同一个 text，只是空白、括号之外的写法差异认不出来。
|
||
"""
|
||
|
||
text: str
|
||
literals: tuple[str, ...] = ()
|
||
parse_error: str | None = None
|
||
|
||
def same_shape(self, other: "NormalizedSql") -> bool:
|
||
"""两条 SQL 是不是同一个模板（只有字面量不同也算）。"""
|
||
return self.text == other.text
|
||
|
||
def as_dict(self) -> dict[str, Any]:
|
||
out: dict[str, Any] = {"text": self.text, "literals": list(self.literals)}
|
||
if self.parse_error:
|
||
out["parse_error"] = self.parse_error
|
||
return out
|
||
|
||
|
||
def _is_literal(token: Any) -> bool:
|
||
"""字符串（含 N'…'、x'…'、$$…$$ 这些变体）和数字。"""
|
||
name = token.token_type.name
|
||
return name == "NUMBER" or name.endswith("STRING")
|
||
|
||
|
||
def _tokens(text: str, read: str | None) -> list[Any]:
|
||
from sqlglot.dialects.dialect import Dialect
|
||
|
||
return list(Dialect.get_or_raise(read).tokenize(text))
|
||
|
||
|
||
def normalize_sql(sql: str, dialect: str | None = None) -> NormalizedSql:
|
||
"""字面量换成占位符后的规范文本 + 字面量。
|
||
|
||
先按方言解析、重新生成一遍（去掉注释、统一关键字和空白、按方言的规则转换不加引号的名字的大小写），再把生成的
|
||
文本切成词，字符串和数字换成「?」：字面量按规范文本里出现的顺序排，不受语法树里子句存放顺序的影响。解析
|
||
不了就直接对原文逐词规范化，带上 parse_error。从不抛异常。
|
||
"""
|
||
read = _read(dialect)
|
||
root, problem = _parse(sql, read)
|
||
if root is not None:
|
||
try:
|
||
from sqlglot.optimizer.normalize_identifiers import normalize_identifiers
|
||
|
||
canonical = normalize_identifiers(root.copy(), dialect=read).sql(dialect=read, comments=False)
|
||
pieces: list[str] = []
|
||
literals: list[str] = []
|
||
pos = 0
|
||
for token in _tokens(canonical, read):
|
||
if _is_literal(token):
|
||
pieces += [canonical[pos:token.start], PLACEHOLDER]
|
||
literals.append(canonical[token.start:token.end + 1])
|
||
pos = token.end + 1
|
||
pieces.append(canonical[pos:])
|
||
return NormalizedSql("".join(pieces), tuple(literals))
|
||
except Exception: # noqa: BLE001 - 生成、切词出错：退回逐词规范化，照实标出
|
||
logger.warning("SQL 规范化失败，退回逐词规范化", exc_info=True)
|
||
problem = "SQL 的写法无法规范化"
|
||
return _by_tokens(sql if isinstance(sql, str) else "", read, problem)
|
||
|
||
|
||
def _by_tokens(text: str, read: str | None, problem: str | None) -> NormalizedSql:
|
||
"""解析不了的 SQL 逐词规范化：关键字转大写，不加引号的名字按 name_key，带引号的名字原样，字面量换成占位符。"""
|
||
try:
|
||
tokens = _tokens(text, read)
|
||
except Exception: # noqa: BLE001 - 引号、括号没配对：只能把空白压成一个
|
||
return NormalizedSql(" ".join(text.split()), (), problem or "SQL 无法解析")
|
||
words: list[str] = []
|
||
literals: list[str] = []
|
||
for token in tokens:
|
||
raw = text[token.start:token.end + 1]
|
||
if _is_literal(token):
|
||
words.append(PLACEHOLDER)
|
||
literals.append(raw)
|
||
elif token.token_type.name == "VAR":
|
||
words.append(name_key(token.text))
|
||
elif token.token_type.name == "IDENTIFIER":
|
||
words.append(raw)
|
||
else:
|
||
words.append(token.text.upper())
|
||
return NormalizedSql(" ".join(words), tuple(literals), problem)
|
||
|
||
|
||
# ==========================================================================
|
||
# 各个方面
|
||
# ==========================================================================
|
||
|
||
#: 一列：(表, 列)。表是给人看的真实表名（CTE、子查询写它的名字），认不出是哪张表时为 None
|
||
ColumnRef = tuple[str | None, str]
|
||
|
||
|
||
@dataclass(frozen=True)
|
||
class Part:
|
||
"""一个条件、一个分组键、一个聚合参数……
|
||
|
||
key 用来比较：别名换成真实表名，CTE、子查询写编号（facets 单独返回的是位置编号，diff_facets 里是两边按结构配好
|
||
对的共同编号，见模块说明），表名、列名按 name_key，等式和比较的两边排好顺序；loose 同 key 但不写实表的表名（派生
|
||
来源的编号照写：它不是表名，换了表也还是配好的那一个），两边查的表换了一张（orders 换成 orders_archive）时拿它
|
||
比其余各方面，免得同一个条件只因表名不同被报成不同。text 给人看：好几张表都有的列写「表.列」（真实表名，不是
|
||
别名），其余只写列名；full 一律写表名，两边的 text 一样、key 却不同时改用它说明。excludes 只在 WHERE 的「排除」
|
||
写法上有：<>、NOT、NOT IN、IS NOT NULL 去掉否定之后排除的是什么（IS NOT NULL 写成「列 为空」）。column_keys 和
|
||
columns 一一对应，是各列比较用的写法（实表.列；CTE、子查询的列写成「编号.列」）：两边对同一列的不同条件靠它配成
|
||
一对说。
|
||
|
||
后面三项不进比较（两个 Part 相等只看前面几项），只用来把不同说清楚：
|
||
origins 是这一项用到的派生来源的列各自的来历 [(「t1.total」, 「SUM(orders.amount)」)]（见 _Statement._origin）：
|
||
两边写法一模一样（都是 t1.total > 100），各自的 t1 却不是同一个时，带上它才分得清。pierce 是一路透过派生来源写到
|
||
实表的 key，只在中途被挡住时才有（这一项按派生来源的列写，见 _Statement.through）；stage 说是被什么挡住的（「取 t
|
||
的前 10 行」「算 t 的窗口函数」）：两边 pierce 一样、只有一边被挡住，是同一个条件筛的先后不同。
|
||
"""
|
||
|
||
key: str
|
||
text: str
|
||
columns: tuple[ColumnRef, ...] = ()
|
||
excludes: str | None = None
|
||
loose: str = ""
|
||
full: str = ""
|
||
column_keys: tuple[str, ...] = ()
|
||
origins: tuple[tuple[str, str], ...] = field(default=(), compare=False)
|
||
pierce: str = field(default="", compare=False)
|
||
stage: str = field(default="", compare=False)
|
||
|
||
@staticmethod
|
||
def plain(key: str, text: str) -> "Part":
|
||
"""没有列的一项（表名、COUNT(*) 的「*」）：比较用的写法都是 key，给人看的都是 text。"""
|
||
return Part(key=key, text=text, loose=key, full=text)
|
||
|
||
|
||
@dataclass(frozen=True)
|
||
class JoinFacet:
|
||
"""一次连接。kind：inner / left / right / full / cross / semi / anti / natural。table 是关联进来的那一侧，other
|
||
是另一侧：关联条件里出现的别的表（给人看的真实表名）；没有条件的（CROSS JOIN）是在它之前出现的各个来源。on 是
|
||
关联条件的合取式排好序后用 AND 连起来的写法，没有条件是 None。
|
||
|
||
sides 是这次连接涉及的来源（比较用的写法，排好序）：关联进来的那一侧，加上关联条件里直接引用的这一段的来源（不
|
||
透过 CTE 找实表）；没有条件的加上它之前出现的各个来源。内连接、CROSS JOIN 两边换个先后意思不变（FROM paid JOIN
|
||
refunded 和 FROM refunded JOIN paid），diff_facets 比它们时按 sides 和条件比，不按哪一侧是关联进来的。
|
||
|
||
keep、nullable 只在 LEFT / RIGHT JOIN 上有：保留全部行的主表那一侧、关联不上时记空的那一侧（比较用的写法，排好
|
||
序）。LEFT JOIN 关联进来的那一侧可空，关联条件里的其余来源（没有就是它之前的各个来源）是主表；RIGHT JOIN 反过来。
|
||
orders LEFT JOIN refunds 和 refunds RIGHT JOIN orders 是同一回事，和 refunds LEFT JOIN orders 不是：diff_facets
|
||
按主表比，不按写的是 LEFT 还是 RIGHT。rejects 是同一段 WHERE 里把可空那一侧没关联上的行筛掉的条件（那一侧的列
|
||
拿来比较、IN、LIKE……，空值都不成立）：有它这次外连接实际等于内连接。"""
|
||
|
||
kind: str
|
||
table: Part
|
||
on: Part | None = None
|
||
other: tuple[str, ...] = ()
|
||
sides: tuple[str, ...] = ()
|
||
keep: tuple[str, ...] = ()
|
||
nullable: tuple[str, ...] = ()
|
||
rejects: Part | None = None
|
||
|
||
|
||
@dataclass(frozen=True)
|
||
class TimePredicate:
|
||
"""WHERE 里的一个时间条件。op：= / <> / > / >= / < / <= / between / in。value 是另一侧给人看的写法：
|
||
BETWEEN 是「低 AND 高」，IN 是「(…)」。
|
||
|
||
column 是按哪一列筛时间：条件写的是 CTE、子查询算出来的列（WITH t AS (SELECT DATE(paid_at) AS d …) … WHERE
|
||
d >= …）时，它在里面是同一列套着日期函数、CAST、MIN / MAX 的，换成里面那一列，一直换到实表（paid_at）：按支付
|
||
时间还是下单时间筛，日期表达式写在 CTE 里也认得出。via 是路过的派生来源的列（「编号.列」，不进比较）：时间那一面
|
||
已经报了按哪一列筛不同，派生来源那一列的定义不同就不再另报一遍。"""
|
||
|
||
column: Part
|
||
op: str
|
||
value: str
|
||
condition: Part
|
||
via: tuple[str, ...] = field(default=(), compare=False)
|
||
|
||
|
||
@dataclass(frozen=True)
|
||
class Aggregate:
|
||
"""一个聚合。func 是函数名的小写（sum / count / avg / min / max …）；arg 是参数，COUNT(*)、COUNT(1) 的 arg
|
||
是「*」，去重聚合是 DISTINCT 里面的表达式；text 是整个聚合给人看的写法。窗口函数不算（它们按所在的那一列比，见
|
||
Computed）。"""
|
||
|
||
func: str
|
||
arg: Part
|
||
distinct: bool
|
||
text: str
|
||
|
||
|
||
@dataclass(frozen=True)
|
||
class Computed:
|
||
"""选出来的一列是怎么算的。两种：
|
||
|
||
- 最外层（UNION 的各支）选出来的列，不是光一列（分组那一面比）、也不是字面量的，比如 SUM(p.total) - SUM(r.total)、
|
||
SUM(amount) OVER (PARTITION BY user_id)、CASE …；ROUND、CAST、COALESCE 给默认值这类外壳先剥掉（见
|
||
_unwrap_value）。光一个聚合也收：另一边可能拿同一个合计再算了一下（SUM(amount) 对 SUM(amount) / 100）。scope、
|
||
scope_key 为 None，name 为空串。
|
||
- 派生来源（CTE、FROM 里的子查询）里被外面用到、又不是原样透出一列的列：它在里面的定义（amount * 0.9、
|
||
DATE(paid_at)、ROW_NUMBER() OVER (…)、p.total - r.total）。外面按「t.net」引用它，两边写的都是 t.net，算法却可能
|
||
不同，只比外面的写法看不出来。scope 是派生来源给人看的名字，scope_key 是它的编号（两边配好对的共同编号），
|
||
name 是列名的 name_key，shown 是列名的原样写法。
|
||
|
||
expr 是定义（按它那一段的来源写的 Part；UNION 的各支用「|」连起来）。template 是把里面的聚合换成占位符之后的写法、
|
||
aggregates 是里面的聚合（按出现的先后）：两边只差在聚合上（SUM(amount) * 100 对 SUM(paid_amount) * 100）、聚合
|
||
那一面又已经报了，这里不再报一遍；聚合的集合一样、只是位置换了（SUM(a) - SUM(b) 对 SUM(b) - SUM(a)）才在这里报。
|
||
"""
|
||
|
||
scope: str | None
|
||
scope_key: str | None
|
||
name: str
|
||
shown: str
|
||
expr: Part
|
||
template: Part
|
||
aggregates: tuple[Aggregate, ...] = ()
|
||
|
||
|
||
@dataclass(frozen=True)
|
||
class LimitFacet:
|
||
"""一段查询取哪几行。count、offset 是行数和跳过行数的写法（没写为 None，OFFSET 0 也算没写）；order 是这一段的
|
||
排序键 (Part, 是否降序)：只取前几行时，按什么排决定了取到的是哪几行。scope 是哪一段：None 是最外层，CTE 写它的
|
||
名字，FROM 里的子查询写它的别名（没有别名写「子查询」）。条件里套着的子查询不单算：它整个写在那个条件里比。
|
||
scope_key 是这一段所属派生来源的编号（和 Part.key 里的同一套编号；最外层、UNION 的某一支这类不是派生来源整段的
|
||
为 None）：diff_facets 按它把两边同一个 CTE、子查询里的取行配成一对。"""
|
||
|
||
count: str | None
|
||
offset: str | None = None
|
||
order: tuple[tuple[Part, bool], ...] = ()
|
||
scope: str | None = None
|
||
scope_key: str | None = None
|
||
|
||
|
||
@dataclass(frozen=True)
|
||
class Facets:
|
||
"""一条查询的各个方面。每一项都按在 SQL 里出现的先后排、按 key 去重；parse_error 不为空时其余都是空的。
|
||
|
||
limit 是最外层 LIMIT 的行数（写法）；limits 是各段取哪几行（最外层在前，见 LimitFacet），只有写了 LIMIT 或
|
||
OFFSET 的段才有。
|
||
|
||
sources 是各段 FROM / JOIN 里的来源（实表、CTE、子查询；key 是比较用的写法，派生来源是编号，text 是给人看的
|
||
名字），按出现的先后、按 key 去重；条件里套着的子查询（IN (SELECT … FROM users)）的来源不算，它们只筛行，不是
|
||
连接的一头。它本身不单独比较：一边独有的一次内连接要说清多出来的是哪个来源时，拿另一边的 sources 对照（见
|
||
_Compare.added），外连接的主表、可空那一侧也按它写名字。
|
||
|
||
expressions 是算出来的列（见 Computed）。derived 是用到了的派生来源（key 是编号，text 是名字，含条件里套着的子
|
||
查询用到的 CTE）：两边写法一样、同名的派生来源却不是同一个时，拿它说清「盲算的 t1 对应原流程的 t2」。
|
||
|
||
只收用到了的段：没用到的 CTE（定义了、外面没引用）里的条件、聚合、表不影响结果，不收（见 _Statement._enliven）。
|
||
|
||
_origin 是 facets 记下的 (原文, 表结构)，不进比较、不进 as_dict：diff_facets 把两边的派生来源按结构配好对之后，
|
||
拿它按共同的编号重新分析一遍（见模块说明）。
|
||
"""
|
||
|
||
dialect: str | None = None
|
||
tables: tuple[Part, ...] = ()
|
||
joins: tuple[JoinFacet, ...] = ()
|
||
where: tuple[Part, ...] = ()
|
||
time: tuple[TimePredicate, ...] = ()
|
||
group_by: tuple[Part, ...] = ()
|
||
aggregates: tuple[Aggregate, ...] = ()
|
||
having: tuple[Part, ...] = ()
|
||
limit: str | None = None
|
||
limits: tuple[LimitFacet, ...] = ()
|
||
sources: tuple[Part, ...] = ()
|
||
expressions: tuple[Computed, ...] = ()
|
||
derived: tuple[Part, ...] = ()
|
||
parse_error: str | None = None
|
||
_origin: tuple[str, Mapping[str, Any] | None] | None = field(default=None, compare=False, repr=False)
|
||
|
||
def as_dict(self) -> dict[str, Any]:
|
||
return _jsonable(self)
|
||
|
||
|
||
def _jsonable(value: Any) -> Any:
|
||
if is_dataclass(value) and not isinstance(value, type):
|
||
return {f.name: _jsonable(getattr(value, f.name)) for f in fields(value) if not f.name.startswith("_")}
|
||
if isinstance(value, (list, tuple)):
|
||
return [_jsonable(v) for v in value]
|
||
return value
|
||
|
||
|
||
def facets(sql: str, dialect: str | None = None, *, schema: Mapping[str, Any] | None = None) -> Facets:
|
||
"""把一条查询拆成各个方面。从不抛异常：解析不了、或者分析时出了意外，返回带 parse_error 的 Facets。
|
||
|
||
schema 是数据源的 schema_cache 形状（{"tables": {表名: {"columns": [{"name": …}]}}}），可以不给。给了的话，
|
||
几张表连在一起、列又没加表前缀时按它认列是哪张表的；不给就照写列名，比较时可能把同一列当成两列。
|
||
|
||
返回的 Facets 记着原文和表结构（_origin）：diff_facets 要把两边的派生来源按结构配好对再重新分析。
|
||
"""
|
||
read = _read(dialect)
|
||
root, problem = _parse(sql, read)
|
||
if root is None:
|
||
return Facets(dialect=read, parse_error=problem)
|
||
try:
|
||
return replace(_Statement(root, read, schema).facets(), _origin=(sql, schema))
|
||
except Exception: # noqa: BLE001 - 分析本身的缺陷不能连累调用方：当作分析不了，记下来修
|
||
logger.warning("SQL 语义分析失败", exc_info=True)
|
||
return Facets(dialect=read, parse_error="SQL 的结构无法分析")
|
||
|
||
|
||
# ---- 语法树上的小工具
|
||
|
||
#: 比较：(运算符的写法, 两边对调之后的类型)
|
||
_COMPARE: dict[str, tuple[str, str]] = {"EQ": ("=", "EQ"), "NEQ": ("<>", "NEQ"), "GT": (">", "LT"),
|
||
"GTE": (">=", "LTE"), "LT": ("<", "GT"), "LTE": ("<=", "GTE")}
|
||
#: 连接类型的写法（diff_facets 里用）
|
||
_JOIN_WORDS = {"inner": "INNER JOIN", "left": "LEFT JOIN", "right": "RIGHT JOIN", "full": "FULL JOIN",
|
||
"cross": "CROSS JOIN", "semi": "SEMI JOIN", "anti": "ANTI JOIN", "natural": "NATURAL JOIN"}
|
||
#: 日期、时间函数（sqlglot 把各方言的写法归成这些类型：strftime、DATE_FORMAT 都是 TimeToStr）
|
||
_DATE_FUNCS = ("CurrentDate", "CurrentDatetime", "CurrentTimestamp", "CurrentTime", "Date", "Datetime", "DateAdd",
|
||
"DateSub", "DateDiff", "DateTrunc", "TimestampTrunc", "DatetimeTrunc", "TimeToStr", "StrToDate",
|
||
"StrToTime", "TsOrDsToDate", "TsOrDsToTimestamp", "TsOrDsAdd", "DateStrToDate", "TimeStrToTime",
|
||
"UnixToTime", "Interval", "Extract", "DateFromParts", "LastDay", "Year", "Month", "Day", "Week",
|
||
"Quarter", "DayOfWeek")
|
||
#: sqlglot 不认识、原样当普通函数的日期函数名
|
||
_DATE_NAMES = frozenset({"date", "datetime", "strftime", "julianday", "now", "today", "to_date", "to_char",
|
||
"date_format", "unixepoch", "curdate", "sysdate", "getdate"})
|
||
#: 像日期、时间的字符串：2026-09-01、2026-09、2026/9/1、2026-09-01 08:00:00
|
||
_DATE_TEXT = re.compile(r"^\s*\d{4}[-/]\d{1,2}(?:[-/]\d{1,2})?(?:[ T]\d{1,2}:\d{2}(?::\d{2}(?:\.\d+)?)?)?\s*$")
|
||
#: 中文列名里像日期、时间的写法（英文列名按 catalog.is_date_column）
|
||
_CN_TIME = re.compile(r"(?:日期|时间|时刻|年月|月份)$|^(?:年|月|日|周|日期|时间)$")
|
||
_PLAIN_NAME = re.compile(r"^[A-Za-z_][A-Za-z0-9_]*$")
|
||
|
||
|
||
def _nested(node: Any, stop: Any) -> bool:
|
||
"""node 在 stop 底下的某个子查询里（不属于 stop 这一段）。"""
|
||
from sqlglot import exp
|
||
|
||
return any(isinstance(p, (exp.Select, exp.Subquery)) for p in _parents(node, stop=stop))
|
||
|
||
|
||
def _own_columns(node: Any) -> list[Any]:
|
||
"""node 里属于这一段的列（不进嵌套的子查询），不含 t.*。"""
|
||
from sqlglot import exp
|
||
|
||
if node is None:
|
||
return []
|
||
found = [node] if isinstance(node, exp.Column) else \
|
||
[c for c in node.find_all(exp.Column) if not _nested(c, node)]
|
||
return [c for c in found if c.name and not c.is_star]
|
||
|
||
|
||
def _is_star(item: Any) -> bool:
|
||
"""SELECT 列表里的一项是 * 或 t.*。"""
|
||
from sqlglot import exp
|
||
|
||
return isinstance(item, exp.Star) or (isinstance(item, exp.Column) and item.is_star)
|
||
|
||
|
||
def _inner_queries(query: Any, skip: Iterable[Any] = ()) -> list[Any]:
|
||
"""query 里直接套着的查询（不再往里找），按出现的先后：条件、SELECT 列表里的子查询，UNION 的各支，子查询里面
|
||
那段。WITH 里的 CTE 定义不算（在用到它的地方才算），skip 里的节点整个跳过。"""
|
||
from sqlglot import exp
|
||
|
||
skipped = {id(n) for n in skip}
|
||
found = []
|
||
stack = list(reversed(list(query.iter_expressions())))
|
||
while stack:
|
||
node = stack.pop()
|
||
if id(node) in skipped or isinstance(node, exp.With):
|
||
continue
|
||
if isinstance(node, exp.Query):
|
||
found.append(node)
|
||
continue
|
||
stack.extend(reversed(list(node.iter_expressions())))
|
||
return found
|
||
|
||
|
||
def _named_output(select: Any) -> bool:
|
||
"""这段 SELECT 选出来的列会被别处按名字引用：它（或者它所在的 UNION）是 FROM / JOIN 里的子查询、CTE 的定义。
|
||
IN、EXISTS、标量子查询只看取值，选出来的列叫什么不影响口径。"""
|
||
from sqlglot import exp
|
||
|
||
node = select
|
||
while isinstance(node.parent, (exp.Subquery, exp.SetOperation)):
|
||
node = node.parent
|
||
return isinstance(node.parent, (exp.From, exp.Join, exp.CTE, exp.Lateral))
|
||
|
||
|
||
def _alias(item: Any) -> str:
|
||
"""FROM / JOIN 项的别名（没有别名的实表、CTE 是它的名字）；表函数这类认不出的来源是空串。LATERAL 的别名
|
||
挂在 Lateral 节点上，不在里面的子查询上。"""
|
||
from sqlglot import exp
|
||
|
||
return item.alias_or_name if isinstance(item, (exp.Table, exp.Subquery, exp.Lateral)) else ""
|
||
|
||
|
||
def _derived_body(item: Any) -> Any:
|
||
"""FROM / JOIN 项是子查询（含 LATERAL 子查询）时，里面那段查询；别的（实表、CTE、表函数）返回 None。"""
|
||
from sqlglot import exp
|
||
|
||
if isinstance(item, exp.Lateral):
|
||
item = item.this
|
||
return item.this if isinstance(item, exp.Subquery) else None
|
||
|
||
|
||
def _branches(query: Any) -> list[Any]:
|
||
"""一段查询的各支 SELECT，按出现的先后：UNION 这类拆开，外面套的括号去掉；认不出的返回空列表。"""
|
||
from sqlglot import exp
|
||
|
||
while isinstance(query, exp.Subquery):
|
||
query = query.this
|
||
if isinstance(query, exp.SetOperation):
|
||
return _branches(query.this) + _branches(query.expression)
|
||
return [query] if isinstance(query, exp.Select) else []
|
||
|
||
|
||
def _output_names(query: Any) -> list[str | None]:
|
||
"""派生来源选出来的各列叫什么（外面按这个名字引用它们）：按第一支 SELECT 的位置，* 为 None。CTE、子查询自己
|
||
写了列名的（WITH t(n) AS …、(…) AS t(a, b)，递归 CTE 常这么写）按写的列名。"""
|
||
from sqlglot import exp
|
||
|
||
branches = _branches(query)
|
||
if not branches:
|
||
return []
|
||
names = [None if _is_star(item) else item.alias_or_name for item in branches[0].selects]
|
||
holder = query.parent
|
||
if isinstance(holder, exp.Subquery) and isinstance(holder.parent, exp.Lateral) and not holder.alias:
|
||
holder = holder.parent # LATERAL 的别名（连同列名）挂在 LATERAL 上
|
||
alias = holder.args.get("alias") if isinstance(holder, (exp.CTE, exp.Subquery, exp.Lateral)) else None
|
||
columns = [c.name for c in alias.columns] if isinstance(alias, exp.TableAlias) else []
|
||
for i, column in enumerate(columns[:len(names)]):
|
||
names[i] = column
|
||
return names
|
||
|
||
|
||
def _own_nodes(select: Any) -> Iterator[Any]:
|
||
"""一段 SELECT 自己的节点：不进 CTE、子查询（它们是别的段）。"""
|
||
from sqlglot import exp
|
||
|
||
stack = [select]
|
||
while stack:
|
||
node = stack.pop()
|
||
yield node
|
||
children = [c for c in node.iter_expressions()
|
||
if not isinstance(c, (exp.Select, exp.Subquery, exp.CTE, exp.With))]
|
||
stack.extend(reversed(children))
|
||
|
||
|
||
def _datey(node: Any) -> bool:
|
||
"""node 里有日期函数、转成日期的 CAST，或者像日期的字符串。"""
|
||
from sqlglot import exp
|
||
|
||
kinds = tuple(k for k in (getattr(exp, n, None) for n in _DATE_FUNCS) if isinstance(k, type))
|
||
for n in node.walk():
|
||
if isinstance(n, kinds):
|
||
return True
|
||
if isinstance(n, exp.Anonymous) and str(n.name).lower() in _DATE_NAMES:
|
||
return True
|
||
if isinstance(n, exp.Cast) and n.to is not None and any(w in n.to.this.name for w in ("DATE", "TIME")):
|
||
return True
|
||
if isinstance(n, exp.Literal) and n.is_string and _DATE_TEXT.match(str(n.this)):
|
||
return True
|
||
return False
|
||
|
||
|
||
def _value_column(node: Any) -> Any:
|
||
"""派生来源一列的定义是不是「还是那一列」：光一列，或者同一列套着日期函数、CAST、MIN / MAX（按支付时间算的日期、
|
||
每人最后一次付款的时间）；是的话返回那一列，不是返回 None。窗口函数（ROW_NUMBER() OVER (ORDER BY paid_at) 是排名，
|
||
不是时间）、别的聚合、好几列算出来的、套着子查询的都不算。"""
|
||
from sqlglot import exp
|
||
|
||
n = _unparen(node)
|
||
if isinstance(n, exp.Column):
|
||
return n if n.name and not n.is_star else None
|
||
if any(isinstance(x, (exp.Window, exp.Select, exp.Subquery)) or
|
||
(isinstance(x, exp.AggFunc) and not isinstance(x, (exp.Min, exp.Max))) for x in n.walk()):
|
||
return None
|
||
cols = _own_columns(n)
|
||
if len(cols) != 1:
|
||
return None
|
||
if _datey(n) or _bare_column(n) is not None or any(isinstance(x, (exp.Min, exp.Max)) for x in n.walk()):
|
||
return cols[0]
|
||
return None
|
||
|
||
|
||
def _unwrap_value(node: Any) -> Any:
|
||
"""剥掉只改写法、不改是哪个数的外壳（括号、类型转换、ROUND、COALESCE / IFNULL 给默认值）：最外层的
|
||
ROUND(SUM(amount), 2)、COALESCE(SUM(amount), 0) 还是那个合计，只是显示上的取舍。"""
|
||
from sqlglot import exp
|
||
|
||
while True:
|
||
node = _unparen(node)
|
||
if isinstance(node, (exp.Cast, exp.TryCast, exp.Round)) and node.this is not None:
|
||
node = node.this
|
||
elif isinstance(node, exp.Coalesce) and node.expressions and \
|
||
all(isinstance(_unparen(e), exp.Literal) for e in node.expressions):
|
||
node = node.this
|
||
else:
|
||
return node
|
||
|
||
|
||
def _as_date(node: Any) -> Any:
|
||
"""「取日期」的几种写法统一成 CAST(… AS DATE)（比较用，给人看的照原样）：DATE(paid_at)、paid_at::date、
|
||
TRY_CAST(paid_at AS DATE)，MySQL 的 DATE() 读成 TsOrDsToDate。各方言、各人写法不同，取的都是同一天；带时区偏移、
|
||
格式的（DATE(paid_at, '+8 hours')）不是同一天，不动。"""
|
||
from sqlglot import exp
|
||
|
||
def to_date(n: Any) -> bool:
|
||
return isinstance(n, exp.DataType) and n.this == exp.DataType.Type.DATE
|
||
|
||
if isinstance(node, exp.Date) and node.this is not None and not node.args.get("zone") \
|
||
and not node.args.get("expressions"):
|
||
return exp.Cast(this=node.this, to=exp.DataType.build("DATE"))
|
||
if isinstance(node, exp.TsOrDsToDate) and node.this is not None and not node.args.get("format"):
|
||
return exp.Cast(this=node.this, to=exp.DataType.build("DATE"))
|
||
if isinstance(node, exp.TryCast) and to_date(node.args.get("to")):
|
||
return exp.Cast(this=node.this, to=exp.DataType.build("DATE"))
|
||
return node
|
||
|
||
|
||
def _atomic(node: Any) -> bool:
|
||
"""算式里的一项不是别的加减乘除：两边对调不会改变怎么结合（a * b / c 换成 b / c * a 就不一样了）。"""
|
||
from sqlglot import exp
|
||
|
||
return not isinstance(_unparen(node), (exp.Add, exp.Sub, exp.Mul, exp.Div, exp.Mod, exp.IntDiv))
|
||
|
||
|
||
def _temporal_name(name: str) -> bool:
|
||
"""列名像日期、时间：英文按 catalog.is_date_column 的命名规则（paid_at、order_date），中文看结尾（支付日期）。"""
|
||
return catalog.is_date_column(name, None) or bool(_CN_TIME.search(name))
|
||
|
||
|
||
def _join_kind(join: Any) -> str:
|
||
side = str(join.args.get("side") or "").lower()
|
||
kind = str(join.args.get("kind") or "").lower()
|
||
if side in ("left", "right", "full"):
|
||
return side
|
||
if join.args.get("method"):
|
||
return "natural"
|
||
if kind in ("semi", "anti"):
|
||
return kind
|
||
if kind == "cross" or not (join.args.get("on") is not None or join.args.get("using")):
|
||
return "cross"
|
||
return "inner"
|
||
|
||
|
||
def _dedupe(items: Iterable[Any], key: Any) -> tuple[Any, ...]:
|
||
seen: dict[Any, Any] = {}
|
||
for item in items:
|
||
seen.setdefault(key(item), item)
|
||
return tuple(seen.values())
|
||
|
||
|
||
class _Sources(dict):
|
||
"""一段 SELECT 的来源 {别名的 name_key: _Source}。outer 是外层那段的来源：相关子查询里引用外层的别名（o.id）
|
||
从这里找。"""
|
||
|
||
outer: "_Sources | None" = None
|
||
|
||
|
||
@dataclass
|
||
class _Source:
|
||
"""一段 SELECT 的一个来源。kind：table（实表）/ derived（CTE、子查询、LATERAL 子查询）/ other（表函数、认不出的
|
||
别名）。"""
|
||
|
||
kind: str
|
||
name: str # 给人看：表名（有库名就带上）、CTE 名、子查询（含 LATERAL）的别名
|
||
key: str # 比较用：实表是 name_key，派生来源是编号（见 _Statement._number_derived）
|
||
idents: tuple[Any, ...] = () # 表名各段的 Identifier：给人看的写法照原样写回去
|
||
query: Any = None # derived：里面那段查询
|
||
role: str = "" # 同一个来源在这一段里出现了不止一次时，这一次是哪一个（见 _Statement._roles）
|
||
|
||
@property
|
||
def ref(self) -> str:
|
||
"""比较用的「哪一个来源」：key，自己关联自己时带上 role（orders#parent_id）。"""
|
||
return f"{self.key}#{self.role}" if self.role else self.key
|
||
|
||
|
||
@dataclass(frozen=True)
|
||
class _Derived:
|
||
"""一个派生来源（CTE、FROM / JOIN 里的子查询、LATERAL 子查询）的结构标识，和起的名字、位置编号无关的部分都在
|
||
这里，diff_facets 拿它把两边的派生来源配成对（见 _align）。各项都用按结构写的写法（render 的 shape 模式：实表
|
||
写表名，往里套着的派生来源写它自己的结构标识，见 _Statement._signature），所以两边写法一样就相同，不受先后、
|
||
名字影响；往里套着的两个派生来源（付款合计、退款合计）也分得开：net 是 paid.total - refunded.total 还是反过来，
|
||
写出来不一样。"""
|
||
|
||
number: int # 位置编号（@N 的 N）：别的都分不出时才看先后
|
||
name: str # CTE 名、子查询的别名（name_key），没有为空：辅助线索
|
||
tables: tuple[str, ...] # 里面读到的实表：各支 FROM / JOIN，往里套着的也算；排好序
|
||
columns: tuple[tuple[str, str], ...] # 选出来的各列 (列名, 规范化后的定义式)，SELECT * 记成 ("*", "*")
|
||
group: tuple[str, ...] # 分组键，排好序
|
||
conditions: frozenset[str] # 里面各段 WHERE、HAVING 的合取式：同一级配得上好几个时比重合
|
||
body: str # 整段查询规范化后的写法
|
||
|
||
@property
|
||
def names(self) -> tuple[str, ...]:
|
||
"""选出来的列名（外层按名字引用它们）。"""
|
||
return tuple(name for name, _ in self.columns)
|
||
|
||
|
||
#: 派生来源配对的各级，从严到宽：(这一级比什么, 是否只在两边都只剩一个时才配)。比什么返回 None 表示这一级没有
|
||
#: 可比的（没有名字、没读实表），不配
|
||
_ALIGN_LEVELS: tuple[tuple[Any, bool], ...] = (
|
||
(lambda d: (d.body, d.columns), False), # 整段一样
|
||
(lambda d: (d.tables, d.columns, d.group), False), # 读的表、各列定义、分组一样
|
||
(lambda d: (d.tables, d.names), False), # 读的表、选出来的列名一样
|
||
(lambda d: (d.tables, d.name) if d.name else None, False), # 读的表、名字一样
|
||
(lambda d: d.tables or None, True), # 只是读的表一样
|
||
(lambda d: d.name or None, True), # 只是名字一样（里面换了表）
|
||
(lambda d: d.names if any(n != "*" for n in d.names) else None, True), # 只是选出来的列名一样
|
||
)
|
||
|
||
|
||
def _align(xs: list[_Derived], ys: list[_Derived]) -> dict[int, int]:
|
||
"""两条语句的派生来源配对：{第二条里的位置编号: 第一条里的位置编号}，配不上的不在里面。
|
||
|
||
按 _ALIGN_LEVELS 从严到宽一级一级地配，每一级一对一：严的先配走，宽的只收拾剩下的。同一级几对都配得上时，先配
|
||
里面的条件重合最多的，再配同名的，最后按位置编号的先后（几个一模一样的派生来源按先后一一对应）；这一级所有
|
||
配得上的对一起排，不是左边挨个挑，免得前一个挑走后一个更合适的。条件排在名字前面：名字是各自起的，两边都叫
|
||
paid 的两个 CTE，一边筛 status = 'paid'、一边筛 status = 'open'，算的不是一回事；条件一个都不重合时才看名字。
|
||
最后三级证据弱，只在两边各只剩一个这样的时才配，免得猜错。哪一级都配不上的就不配：一边多出来的 CTE（盲算先筛
|
||
一遍 VIP 用户）和另一边不相干的 CTE 凑成一对，会把外层不相干的条件说成「关联条件不同」。
|
||
"""
|
||
rest_x, rest_y = sorted(xs, key=lambda d: d.number), sorted(ys, key=lambda d: d.number)
|
||
pairs: dict[int, int] = {}
|
||
for view, unique in _ALIGN_LEVELS:
|
||
candidates = []
|
||
for x in rest_x:
|
||
seen = view(x)
|
||
if seen is None:
|
||
continue
|
||
found = [y for y in rest_y if view(y) == seen]
|
||
if unique and (len(found) != 1 or sum(1 for z in rest_x if view(z) == seen) != 1):
|
||
continue
|
||
candidates += [((-len(y.conditions & x.conditions), y.name != x.name, x.number, y.number), x, y)
|
||
for y in found]
|
||
for _, x, y in sorted(candidates, key=lambda c: c[0]):
|
||
if x.number not in pairs.values() and y.number not in pairs:
|
||
pairs[y.number] = x.number
|
||
rest_x = [x for x in rest_x if x.number not in pairs.values()]
|
||
rest_y = [y for y in rest_y if y.number not in pairs]
|
||
return pairs
|
||
|
||
|
||
def _renamed(xs: list[_Derived], ys: list[_Derived], pairs: Mapping[int, int]) -> dict[tuple[int, str], str]:
|
||
"""配成一对的派生来源里两边起名不同的列，配成同一列：{(第二条里的位置编号, 列名): 第一条里的列名}。
|
||
|
||
外面按名字引用这些列，一边叫 total、一边叫 sum_amt，不配起来就是两列，外面按它写的条件、聚合全成了两边各有
|
||
一个。只在两边各自独有的列名之间配：定义（结构写法）一样的一对一配上；剩下两边各只有一列时也配上（盲算换了名字
|
||
又改了算法：SUM(amount) AS total 对 SUM(amount - discount) AS net_total，外面用在同一个位置），定义的不同由算出来
|
||
的列那一面报（见 _Compare.expressions）。"""
|
||
by_number = {x.number: x for x in xs}
|
||
out: dict[tuple[int, str], str] = {}
|
||
for y in ys:
|
||
x = by_number.get(pairs.get(y.number, -1))
|
||
if x is None:
|
||
continue
|
||
cx = {name: shape for name, shape in x.columns if name and name != "*"}
|
||
cy = {name: shape for name, shape in y.columns if name and name != "*"}
|
||
rest_x = [name for name in cx if name not in cy]
|
||
rest_y = [name for name in cy if name not in cx]
|
||
for name in list(rest_y):
|
||
same = [other for other in rest_x if cx[other] == cy[name]]
|
||
if len(same) == 1 and sum(1 for other in rest_y if cy[other] == cy[name]) == 1:
|
||
out[(y.number, name)] = same[0]
|
||
rest_x.remove(same[0])
|
||
rest_y.remove(name)
|
||
if len(rest_x) == 1 and len(rest_y) == 1:
|
||
out[(y.number, rest_y[0])] = rest_x[0]
|
||
return out
|
||
|
||
|
||
class _Statement:
|
||
"""一条语句的分析：CTE、实表、每段 SELECT 的来源，以及把表达式写成 key / text 的规则。"""
|
||
|
||
def __init__(self, root: Any, read: str | None, schema: Mapping[str, Any] | None) -> None:
|
||
from sqlglot import exp
|
||
|
||
self.root = root
|
||
self.read = read
|
||
#: 各段 SELECT（原树上的节点），下标就是记在 meta 里的段号
|
||
self.segments: list[Any] = []
|
||
for select in root.find_all(exp.Select, bfs=False):
|
||
select.meta[_SEGMENT] = len(self.segments)
|
||
self.segments.append(select)
|
||
self.ctes: dict[str, Any] = {}
|
||
#: CTE 的定义（exp.CTE 节点），和 ctes 同一个键：编号也记在定义上，定义写进条件时靠它换掉名字
|
||
self._cte_defs: dict[str, Any] = {}
|
||
for cte in root.find_all(exp.CTE):
|
||
if cte.alias:
|
||
self.ctes.setdefault(name_key(cte.alias), cte.this)
|
||
self._cte_defs.setdefault(name_key(cte.alias), cte)
|
||
self.columns: dict[str, set[str]] = {}
|
||
for name, meta in ((schema or {}).get("tables") or {}).items():
|
||
if isinstance(meta, Mapping):
|
||
self.columns[name_key(str(name))] = {name_key(str(c.get("name"))) for c in meta.get("columns") or []
|
||
if isinstance(c, Mapping) and c.get("name")}
|
||
self._memo: dict[int, _Sources] = {}
|
||
self._shared: set[str] | None = None
|
||
#: 各派生来源的结构标识 {位置编号: 摘要}（见 _signature）、各派生来源一列的来历 {(里面那段的 id, 列名): 来历}
|
||
#: （见 _origin）：都和编号无关，重新编号不用清
|
||
self._signatures: dict[int, str] = {}
|
||
self._origins: dict[tuple[int, str], str | None] = {}
|
||
#: 派生来源各列的名字 {里面那段的 id: [列名]}、每段外面筛和里面筛一不一样 {(那段的 id, 列名): 说法}：只看
|
||
#: 语法树，算一次记下来（透视、认列时反复要用）
|
||
self._names_memo: dict[int, list[str | None]] = {}
|
||
self._blocks_memo: dict[tuple[int, str], str | None] = {}
|
||
self._number_derived()
|
||
self._enliven(())
|
||
|
||
# ---- 来源
|
||
|
||
def _is_cte(self, table: Any) -> bool:
|
||
return not table.text("db") and not table.text("catalog") and name_key(table.name) in self.ctes
|
||
|
||
def _reach(self, extra: Iterable[str] = ()) -> set[str]:
|
||
"""从最外层那段查询出发（再加上 extra 里的 CTE）一路引用到的 CTE 名：FROM / JOIN 里的、条件和 SELECT 列表里的
|
||
子查询里的都算，用到的 CTE 里面再引用的也算。CTE 的定义本身不算引用：没人用的 CTE 里引用的别的 CTE 也没用到。"""
|
||
from sqlglot import exp
|
||
|
||
live = {name for name in extra if name in self.ctes}
|
||
stack = [self.root, *(self.ctes[name] for name in live)]
|
||
while stack:
|
||
for node in stack.pop().walk(prune=lambda n: isinstance(n, exp.CTE)):
|
||
if isinstance(node, exp.Table) and isinstance(node.this, exp.Identifier) and node.name \
|
||
and self._is_cte(node) and (name := name_key(node.name)) not in live:
|
||
live.add(name)
|
||
stack.append(self.ctes[name])
|
||
return live
|
||
|
||
def _enliven(self, extra: Iterable[str]) -> None:
|
||
"""定下哪些段算数：最外层那段查询，加上从它一路引用到的 CTE（extra 里的 CTE 也当作用到了，见 _aligned）。没
|
||
用到的 CTE 里的条件、聚合、表不影响结果：收进来的话，盲算定义了只筛已付的 CTE 却直接查 orders，会被当成也筛了
|
||
已付；定义了没用的 CTE 里多一个条件，又会被报成多筛了一遍。用到的实表（给人看时要不要写表名）、共有的列名跟着
|
||
重算。"""
|
||
from sqlglot import exp
|
||
|
||
live = self._reach(extra)
|
||
#: 没用到的 CTE 里的节点（id）：facets 只收别的段
|
||
self._dead = {id(n) for name, cte in self._cte_defs.items() if name not in live for n in cte.this.walk()}
|
||
tables: dict[str, _Source] = {}
|
||
for table in self._alive(exp.Table):
|
||
if isinstance(table.this, exp.Identifier) and table.name and not self._is_cte(table):
|
||
source = self._table(table)
|
||
tables.setdefault(source.key, source)
|
||
self.tables = list(tables.values())
|
||
#: 整条语句只用到一张实表：给人看的写法一律不写表名
|
||
self.single = len(self.tables) <= 1
|
||
self._shared = None
|
||
|
||
def _alive(self, *types: Any) -> Iterator[Any]:
|
||
"""用到了的段里这些类型的节点（深度优先、按出现的先后），没用到的 CTE 里的不算（见 _enliven）。"""
|
||
return (node for node in self.root.find_all(*types, bfs=False) if id(node) not in self._dead)
|
||
|
||
@staticmethod
|
||
def _items(select: Any) -> list[Any]:
|
||
"""一段 SELECT 的 FROM、JOIN 项，按出现的先后。"""
|
||
first = select.args.get("from_")
|
||
return ([first.this] if first is not None else []) + [j.this for j in select.args.get("joins") or []]
|
||
|
||
def _number_derived(self) -> None:
|
||
"""给派生来源（引用 CTE 的表、FROM / JOIN 里的子查询和 LATERAL 子查询）编比较用的 key：@1、@2…，记在节点的
|
||
meta 上。
|
||
|
||
CTE 名、子查询的别名是各自起的（双盲复算的盲算更是），拿它作 key，同一个口径只因起的名字不同就被报成不同；
|
||
拿里面那段查询的写法作 key 也不行：里面差一个条件，外层按它的列写的条件就全跟着变，同一处不同报好几遍，还会
|
||
出现两边各说一句「只保留 total > 100 的行」的自相矛盾。所以单看一条语句时按位置编：从最外层往里一层一层地
|
||
编，同一层按出现的先后；CTE 在第一次用到的地方编号，在哪儿用到都是这一个编号。写成 CTE 还是 FROM 里的子查询、
|
||
CTE 定义的先后都不影响编号，里层多一段、少一段也不挪动外层的编号。两条语句之间编号错开（一边多一个 CTE、
|
||
内连接换了先后）由 diff_facets 按结构配对之后改成共同的编号（见 relabel）。
|
||
"""
|
||
from sqlglot import exp
|
||
|
||
ctes: dict[str, int] = {}
|
||
count = 0
|
||
#: 编了号的派生来源 [(位置编号, 起的名字, 里面那段查询, CTE 的 name_key 或 None)]，按编号排：diff_facets 按
|
||
#: 它们的结构配对（见 derived），facets 按它们找各列的定义（见 _expressions）
|
||
self._derived: list[tuple[int, str, Any, str | None]] = []
|
||
#: 记了编号的节点 {id: (节点, 位置编号)}：配好对之后按共同的编号改写（见 relabel）
|
||
self._marked: dict[int, tuple[Any, int]] = {}
|
||
|
||
def mark(node: Any, number: int) -> None:
|
||
node.meta[_DERIVED] = f"@{number}"
|
||
self._marked[id(node)] = (node, number)
|
||
|
||
def visit(select: Any) -> list[Any]:
|
||
"""给这一段还没编号的 FROM / JOIN 项编号，返回要接着往里看的查询（子查询、第一次用到的 CTE 的定义）。"""
|
||
nonlocal count
|
||
inner = []
|
||
for item in self._items(select):
|
||
body = _derived_body(item)
|
||
if body is not None:
|
||
if _DERIVED not in item.meta:
|
||
count += 1
|
||
mark(item, count)
|
||
self._derived.append((count, _alias(item), body, None))
|
||
inner.append(body)
|
||
elif isinstance(item, exp.Table) and isinstance(item.this, exp.Identifier) and item.name \
|
||
and self._is_cte(item):
|
||
name = name_key(item.name)
|
||
if name not in ctes:
|
||
count += 1
|
||
ctes[name] = count
|
||
mark(self._cte_defs[name], count)
|
||
self._derived.append((count, self._cte_defs[name].alias, self.ctes[name], name))
|
||
inner.append(self.ctes[name])
|
||
mark(item, ctes[name])
|
||
return inner
|
||
|
||
queue: deque[Any] = deque([self.root])
|
||
while queue:
|
||
query = queue.popleft()
|
||
items: list[Any] = []
|
||
if isinstance(query, exp.Select):
|
||
queue.extend(visit(query))
|
||
items = self._items(query)
|
||
queue.extend(_inner_queries(query, skip=items))
|
||
# 没走到的（没用到的 CTE 里的、表函数参数里的）按出现的先后补上：每个派生来源都得有编号
|
||
for select in self.root.find_all(exp.Select, bfs=False):
|
||
visit(select)
|
||
# 没用到的 CTE 也编上号（排在最后）：外层不引用它，可它照样要参加两边的配对。两边都定义了付款、退款两个 CTE，
|
||
# 一边关联付款的、一边关联退款的，没用到的那个不参加的话，两边各剩一个只有列名对得上的，会被凑成一对
|
||
for name, cte in self._cte_defs.items():
|
||
if name not in ctes:
|
||
count += 1
|
||
ctes[name] = count
|
||
mark(cte, count)
|
||
self._derived.append((count, cte.alias, self.ctes[name], name))
|
||
#: {位置编号: 里面那段查询}、{位置编号: 现在比较用的编号}、反过来 {比较用的编号: 位置编号}
|
||
self._bodies = {number: body for number, _, body, _ in self._derived}
|
||
self._labels = {number: f"@{number}" for number in self._bodies}
|
||
self._numbers = {label: number for number, label in self._labels.items()}
|
||
#: 派生来源里改叫另一边那个名字的列 {(比较用的编号, 列名的 name_key): 另一边的列名}（见 relabel）
|
||
self._renames: dict[tuple[str, str], str] = {}
|
||
|
||
def relabel(self, ids: Mapping[int, str], renames: Mapping[tuple[int, str], str] | None = None) -> None:
|
||
"""派生来源改用 ids 给的编号（{位置编号: 比较用的编号}，没给的照旧写位置编号）。diff_facets 把两边的派生
|
||
来源配好对之后，第二条语句里配上的写第一条里对应的编号，两边比较用的写法才对得上。算好的来源、共有的列名
|
||
都带着旧编号，跟着清掉重算。
|
||
|
||
renames 是派生来源里改叫第一条里那个名字的列 {(位置编号, 列名的 name_key): 第一条里的列名}（见 _renamed）：
|
||
比较用的写法照它写，给人看的照原样。"""
|
||
for node, number in self._marked.values():
|
||
node.meta[_DERIVED] = ids.get(number, f"@{number}")
|
||
self._labels = {number: ids.get(number, f"@{number}") for number in self._bodies}
|
||
self._numbers = {label: number for number, label in self._labels.items()}
|
||
self._renames = {(self._labels[number], column): name for (number, column), name in (renames or {}).items()
|
||
if number in self._labels}
|
||
self._memo.clear()
|
||
self._shared = None
|
||
|
||
def column_key(self, source: _Source, column: str) -> str:
|
||
"""比较用的列名：派生来源里改叫另一边那个名字的列（见 relabel）照改过的写，别的按 name_key。"""
|
||
key = name_key(column)
|
||
return self._renames.get((source.key, key), key) if source.kind == "derived" else key
|
||
|
||
def used_labels(self) -> dict[str, str | None]:
|
||
"""用到了的派生来源（见 _enliven）：{比较用的编号: CTE 的 name_key，FROM 里的子查询为 None}。"""
|
||
return {self._labels[number]: cte for number, _, body, cte in self._derived if id(body) not in self._dead}
|
||
|
||
def defined_labels(self) -> dict[str, str | None]:
|
||
"""定义了的派生来源，用没用到都算：{比较用的编号: CTE 的 name_key，FROM 里的子查询为 None}。"""
|
||
return {self._labels[number]: cte for number, _, _, cte in self._derived}
|
||
|
||
def derived(self) -> list[_Derived]:
|
||
"""各个派生来源的结构标识（见 _Derived），按位置编号排。"""
|
||
from sqlglot import exp
|
||
|
||
out = []
|
||
for number, name, body, _ in self._derived:
|
||
columns: list[tuple[str, str]] = []
|
||
group: list[str] = []
|
||
conditions: set[str] = set()
|
||
for i, select in enumerate(_branches(body)):
|
||
scope = self.sources(select)
|
||
for clause in (select.args.get("where"), select.args.get("having")):
|
||
if clause is not None:
|
||
conditions.update(self._shape(c, scope) for c in _conjuncts(clause.this))
|
||
if i:
|
||
continue # UNION 选出来的列名、分组按第一支的算
|
||
for item, called in zip(select.selects, self.names(body)):
|
||
if called is None:
|
||
columns.append(("*", "*"))
|
||
continue
|
||
target = item.this if isinstance(item, exp.Alias) else item
|
||
columns.append((name_key(called), self._shape(target, scope)))
|
||
if (clause := select.args.get("group")) is not None:
|
||
selects, aliases = select.selects, self._aliases(select)
|
||
group += [self._shape(self._target(g, selects, aliases), scope) for g in clause.expressions]
|
||
out.append(_Derived(number=number, name=name_key(name) if name else "",
|
||
tables=tuple(sorted(self._row_tables(body, frozenset()))),
|
||
columns=tuple(sorted(columns)), group=tuple(sorted(group)),
|
||
conditions=frozenset(conditions), body=self._shape(body, {})))
|
||
return out
|
||
|
||
def _shape(self, node: Any, sources: dict[str, _Source]) -> str:
|
||
"""按结构写（render 的 shape 模式，比较的两边也按结构排）：配对用，和名字、编号无关。"""
|
||
return self.render(self.canonical(node, sources, by="shape"), sources, "shape")
|
||
|
||
def _signature(self, number: int) -> str:
|
||
"""派生来源的结构标识（shape 写法里引用它的地方写这个）：里面那段查询按 shape 写法写出来再取摘要。里面再套着
|
||
的派生来源也写它们各自的结构标识，所以付款合计、退款合计两个 CTE 的同名列 total 在外面一层也分得开，和起的
|
||
名字、编号无关；取摘要是免得一层套一层越写越长。递归 CTE 引用自己时写「@」。"""
|
||
if number not in self._signatures:
|
||
self._signatures[number] = _ANON
|
||
text = self._shape(self._bodies[number], {})
|
||
self._signatures[number] = "@" + hashlib.sha1(text.encode("utf-8")).hexdigest()[:12]
|
||
return self._signatures[number]
|
||
|
||
def _signature_of(self, label: str) -> str:
|
||
"""比较用的编号 → 那个派生来源的结构标识；认不出的编号写「@」。"""
|
||
number = self._numbers.get(label)
|
||
return self._signature(number) if number is not None else _ANON
|
||
|
||
def _row_tables(self, query: Any, seen: frozenset[str]) -> set[str]:
|
||
"""query 的行从哪些实表来：各支 FROM / JOIN 里的实表，往里套着的子查询、CTE 也算。条件里的子查询不算（它只
|
||
决定留哪些行，算进来的话一边多一个 IN (SELECT … FROM users) 的筛选，结构标识就整个变了）。seen 是这条路上
|
||
已经进过的 CTE：递归 CTE 引用自己时不再往里走。"""
|
||
from sqlglot import exp
|
||
|
||
out: set[str] = set()
|
||
for select in _branches(query):
|
||
for item in self._items(select):
|
||
body = _derived_body(item)
|
||
if body is not None:
|
||
out |= self._row_tables(body, seen)
|
||
elif isinstance(item, exp.Table) and isinstance(item.this, exp.Identifier) and item.name:
|
||
if not self._is_cte(item):
|
||
out.add(self._table(item).key)
|
||
elif (name := name_key(item.name)) not in seen:
|
||
out |= self._row_tables(self.ctes[name], seen | {name})
|
||
return out
|
||
|
||
@classmethod
|
||
def reparse(cls, f: Facets) -> "_Statement | None":
|
||
"""按 facets 记下的原文、表结构重新分析一遍（见 Facets._origin）；没记、解析不了返回 None。"""
|
||
if f._origin is None:
|
||
return None
|
||
sql, schema = f._origin
|
||
root, _ = _parse(sql, f.dialect)
|
||
return cls(root, f.dialect, schema) if root is not None else None
|
||
|
||
@staticmethod
|
||
def _table(table: Any) -> _Source:
|
||
from sqlglot import exp
|
||
|
||
idents = tuple(i for i in (table.args.get("catalog"), table.args.get("db"), table.this)
|
||
if isinstance(i, exp.Identifier))
|
||
return _Source("table", ".".join(i.name for i in idents), ".".join(name_key(i.name) for i in idents),
|
||
tuple(i.copy() for i in idents))
|
||
|
||
def sources(self, select: Any) -> _Sources:
|
||
"""{别名的 name_key: 来源}。没有别名的实表按表名；认不出的来源按位置编号。"""
|
||
from sqlglot import exp
|
||
|
||
if id(select) in self._memo:
|
||
return self._memo[id(select)]
|
||
out = _Sources()
|
||
aliases: dict[str, str] = {}
|
||
for i, node in enumerate(self._items(select)):
|
||
alias = _alias(node)
|
||
slot = name_key(alias) if alias else f"#{i}"
|
||
if isinstance(node, exp.Table) and isinstance(node.this, exp.Identifier) and node.name:
|
||
if self._is_cte(node):
|
||
out[slot] = _Source("derived", node.name, node.meta.get(_DERIVED, slot), (node.this.copy(),),
|
||
self.ctes[name_key(node.name)])
|
||
else:
|
||
out[slot] = self._table(node)
|
||
elif (body := _derived_body(node)) is not None:
|
||
out[slot] = _Source("derived", alias or "子查询", node.meta.get(_DERIVED, slot),
|
||
(exp.to_identifier(alias),) if alias else (), body)
|
||
else:
|
||
out[slot] = _Source("other", alias, slot)
|
||
aliases[slot] = alias
|
||
self._roles(select, out, aliases)
|
||
self._memo[id(select)] = out
|
||
parent = select.parent
|
||
while parent is not None and not isinstance(parent, exp.Select):
|
||
parent = parent.parent
|
||
out.outer = self.sources(parent) if parent is not None else None
|
||
return out
|
||
|
||
@staticmethod
|
||
def _roles(select: Any, sources: dict[str, _Source], aliases: Mapping[str, str]) -> None:
|
||
"""同一个来源在这一段里出现了不止一次（自己关联自己：orders o1 JOIN orders o2、base b1 JOIN base b2）时，各自
|
||
按在关联条件（ON、WHERE 里两列相等）里出的是哪几列区分，记在 role 上（就地改）：比较用的写法写「来源#列」，
|
||
和别名、先后都无关。b2.user_id = b1.referrer_id 里 b1 出 referrer_id、b2 出 user_id，b1.total > b2.total 写反了
|
||
就认得出来；不然两边都写成 base.total，写反了也一样。出的列一样（b1.user_id = b2.user_id）分不出，也不用分：
|
||
两个对调过来意思一样。给人看的写法这时写别名：都写 orders.amount 读不出是哪一个。"""
|
||
from sqlglot import exp
|
||
|
||
groups: dict[str, list[str]] = {}
|
||
for slot, source in sources.items():
|
||
if source.kind in ("table", "derived"):
|
||
groups.setdefault(source.key, []).append(slot)
|
||
repeated = [slots for slots in groups.values() if len(slots) > 1]
|
||
if not repeated:
|
||
return
|
||
conds = [j.args["on"] for j in select.args.get("joins") or [] if j.args.get("on") is not None]
|
||
if (where := select.args.get("where")) is not None:
|
||
conds.append(where.this)
|
||
joined: dict[str, set[str]] = {}
|
||
for cond in conds:
|
||
for eq in _conjuncts(cond):
|
||
n = _unparen(eq)
|
||
if not isinstance(n, exp.EQ):
|
||
continue
|
||
cols = [_unparen(n.this), _unparen(n.expression)]
|
||
slots = [name_key(c.table) if isinstance(c, exp.Column) and c.table else None for c in cols]
|
||
if None in slots or slots[0] == slots[1] or not all(s in sources for s in slots):
|
||
continue
|
||
for col, slot in zip(cols, slots):
|
||
joined.setdefault(slot, set()).add(name_key(col.name))
|
||
for slots in repeated:
|
||
roles = {slot: "+".join(sorted(joined.get(slot, ()))) for slot in slots}
|
||
for slot in slots:
|
||
if roles[slot] and list(roles.values()).count(roles[slot]) == 1:
|
||
sources[slot].role = roles[slot]
|
||
if aliases.get(slot):
|
||
sources[slot].idents = (exp.to_identifier(aliases[slot]),)
|
||
|
||
def _exposes(self, source: _Source, column: str) -> bool:
|
||
"""这个来源可能有这一列：实表看表结构（没给表结构就当可能有），CTE、子查询看它选出来的列。"""
|
||
from sqlglot import exp
|
||
|
||
if source.kind == "table":
|
||
return source.key not in self.columns or name_key(column) in self.columns[source.key]
|
||
if source.kind == "derived" and isinstance(source.query, exp.Query):
|
||
return any(called is None or name_key(called) == name_key(column)
|
||
for called in self.names(source.query))
|
||
return True
|
||
|
||
def locate(self, column: Any, sources: dict[str, _Source]) -> tuple[str | None, _Source | None]:
|
||
"""列 → (来源的别名键, 来源)。别名在这一段找不到的，到外层找（相关子查询引用外层），再找不到按「别的来源」
|
||
照写（别名写错了）；没加前缀、又有不止一个来源可能有它的，返回 (None, None)。"""
|
||
qualifier = column.table
|
||
if qualifier:
|
||
slot = name_key(qualifier)
|
||
if slot in sources:
|
||
return slot, sources[slot]
|
||
outer = getattr(sources, "outer", None)
|
||
while outer is not None:
|
||
if slot in outer:
|
||
return None, outer[slot] # 外层的来源：不算这一段的关联
|
||
outer = outer.outer
|
||
return None, _Source("other", qualifier, slot, (column.args["table"].copy(),))
|
||
hits = [(slot, s) for slot, s in sources.items() if self._exposes(s, column.name)]
|
||
return hits[0] if len(hits) == 1 else (None, None)
|
||
|
||
def _pass(self, source: _Source | None, column: str) -> tuple[_Source, str] | None:
|
||
"""派生来源只读一个来源、把它的这一列原样透出来（直接选出这一列，或者 SELECT *）时，里面一层的 (来源, 列名)；
|
||
不是原样透出（算出来的列、读好几个来源）返回 None。先认写了名字的列：SELECT *, amount * 0.9 AS net 里的 net
|
||
是算出来的，不是里面那张表的 net。"""
|
||
from sqlglot import exp
|
||
|
||
if source is None or source.kind != "derived" or not isinstance(source.query, exp.Select):
|
||
return None
|
||
inner = self.sources(source.query)
|
||
if len(inner) != 1:
|
||
return None
|
||
only = next(iter(inner.values()))
|
||
names = self.names(source.query)
|
||
named = [item for item, called in zip(source.query.selects, names)
|
||
if called is not None and name_key(called) == name_key(column)]
|
||
if named:
|
||
target = _unparen(named[0].this if isinstance(named[0], exp.Alias) else named[0])
|
||
return (only, target.name) if isinstance(target, exp.Column) else None
|
||
return (only, column) if None in names else None
|
||
|
||
def names(self, query: Any) -> list[str | None]:
|
||
"""派生来源选出来的各列叫什么（见 _output_names），算一次记下来。"""
|
||
if id(query) not in self._names_memo:
|
||
self._names_memo[id(query)] = _output_names(query)
|
||
return self._names_memo[id(query)]
|
||
|
||
def _blocks(self, select: Any, column: str) -> str | None:
|
||
"""见 _blocking，算一次记下来。"""
|
||
memo = (id(select), name_key(column))
|
||
if memo not in self._blocks_memo:
|
||
self._blocks_memo[memo] = self._blocking(select, column)
|
||
return self._blocks_memo[memo]
|
||
|
||
@staticmethod
|
||
def _blocking(select: Any, column: str) -> str | None:
|
||
"""在这一段外面按 column 筛和在它里面筛结果不同时，说它做了什么（「取前几行」「窗口函数」）；一样返回 None。
|
||
|
||
取前几行（LIMIT、OFFSET）：先取前 10 行再筛已付，和先筛已付再取前 10 行，取到的不是同一批。窗口函数（含
|
||
DISTINCT ON）：先算每人的第一单再筛已付（第一单就是已付的人），和先筛已付再算（有已付订单的人）不是一回事；
|
||
只有 column 是每个窗口的分区键时一样（按分区键筛掉的是整个分区，分区里的排名、合计不受影响）。"""
|
||
from sqlglot import exp
|
||
|
||
if select.args.get("limit") is not None or select.args.get("offset") is not None:
|
||
return "limit"
|
||
distinct = select.args.get("distinct")
|
||
if isinstance(distinct, exp.Distinct) and distinct.args.get("on") is not None:
|
||
keys = {name_key(_unparen(e).name) for e in distinct.args["on"].expressions
|
||
if isinstance(_unparen(e), exp.Column)}
|
||
if name_key(column) not in keys:
|
||
return "window"
|
||
for node in _own_nodes(select):
|
||
if isinstance(node, exp.Window):
|
||
keys = {name_key(_unparen(e).name) for e in node.args.get("partition_by") or []
|
||
if isinstance(_unparen(e), exp.Column)}
|
||
if name_key(column) not in keys:
|
||
return "window"
|
||
return None
|
||
|
||
def through(self, source: _Source | None, column: str, *, pierce: bool = False) -> tuple[_Source | None, str]:
|
||
"""CTE、子查询只是把一张表的列原样透出来（SELECT *，或者直接选出这一列）时，换成那张表的列：
|
||
原流程直接查 orders、盲算先在 CTE 里筛一遍再查，算的是同一列。
|
||
|
||
这一段取前几行、或者算了窗口函数时不透过去（见 _blocks），照写这个派生来源的列：外面的 t.status = 'paid'
|
||
和写在 t 里面的 status = 'paid' 不是同一个条件，透过去就都成了 orders.status = 'paid'，分不出来。pierce 时
|
||
不管这些，一直透到底：拿来认出两边是不是同一个条件、只是筛的先后不同（见 Part.pierce）。"""
|
||
for _ in range(4):
|
||
found = self._pass(source, column)
|
||
if found is None or (not pierce and self._blocks(source.query, found[1])):
|
||
break
|
||
source, column = found
|
||
return source, column
|
||
|
||
def resolve(self, column: Any, sources: dict[str, _Source], *, pierce: bool = False) -> tuple[_Source | None, str]:
|
||
return self.through(self.locate(column, sources)[1], column.name, pierce=pierce)
|
||
|
||
def _definition(self, source: _Source | None, column: str) -> list[tuple[Any, _Sources]] | None:
|
||
"""派生来源一列在里面的定义：[(定义的表达式, 它那一支的来源)]，UNION 每支一项（按列的位置）。只有 SELECT *
|
||
透出来的列，定义就是里面那一支的同名列。认不出（不是派生来源、没有这一列、某一支在那个位置是 *）返回 None。"""
|
||
from sqlglot import exp
|
||
|
||
if source is None or source.kind != "derived" or source.query is None:
|
||
return None
|
||
branches = _branches(source.query)
|
||
if not branches:
|
||
return None
|
||
names = [None if called is None else name_key(called) for called in self.names(source.query)]
|
||
if name_key(column) not in names:
|
||
if None not in names:
|
||
return None
|
||
return [(exp.column(column), self.sources(branch)) for branch in branches]
|
||
position = names.index(name_key(column))
|
||
out = []
|
||
for branch in branches:
|
||
if position >= len(branch.selects) or _is_star(branch.selects[position]):
|
||
return None
|
||
item = branch.selects[position]
|
||
out.append((item.this if isinstance(item, exp.Alias) else item, self.sources(branch)))
|
||
return out
|
||
|
||
def shared(self) -> set[str]:
|
||
"""好几张表都有的列名（name_key）：这条语句里出现时挂在不止一张表上（orders.order_id、refunds.order_id），
|
||
或者表结构里不止一张用到的表有它。给人看时只有这些列写表名，其余只写列名，读起来和原 SQL 一样短。"""
|
||
from sqlglot import exp
|
||
|
||
if self._shared is None:
|
||
owners: dict[str, set[str]] = {}
|
||
for select in self._alive(exp.Select):
|
||
sources = self.sources(select)
|
||
for node in _own_nodes(select):
|
||
if isinstance(node, exp.Column) and node.name and not node.is_star:
|
||
source, name = self.resolve(node, sources)
|
||
if source is not None:
|
||
owners.setdefault(name_key(name), set()).add(source.ref)
|
||
used = [t.key for t in self.tables]
|
||
self._shared = {name for name, keys in owners.items()
|
||
if len(keys) > 1 or sum(1 for t in used if name in self.columns.get(t, ())) > 1}
|
||
return self._shared
|
||
|
||
# ---- 写成 key / text
|
||
|
||
@staticmethod
|
||
def _owner(node: Any) -> Any:
|
||
"""node 往上最近的一段 SELECT（带段号的，node 本身是也算）；没有就是 None：node 在调用方那一段里。"""
|
||
from sqlglot import exp
|
||
|
||
while node is not None:
|
||
if isinstance(node, exp.Select) and node.meta.get(_SEGMENT) is not None:
|
||
return node
|
||
node = node.parent
|
||
return None
|
||
|
||
def scope(self, node: Any, default: dict[str, _Source]) -> dict[str, _Source]:
|
||
"""node 所在那一段的来源。条件里套着的子查询（EXISTS、IN (SELECT …)）是另一段：别名在那一段里定义，相关
|
||
子查询还要到外层找。复制出来的子查询带着段号，按段号找回原树上那一段算好的来源；不在子查询里就是 default。"""
|
||
owner = self._owner(node)
|
||
return default if owner is None else self.sources(self.segments[owner.meta[_SEGMENT]])
|
||
|
||
def render(self, node: Any, sources: dict[str, _Source], mode: str = "text") -> str:
|
||
"""七种写法。比较用的五种（_COMPARING），名字按 name_key：key、loose 见 Part，key 写实表的表名，loose 不写，
|
||
CTE、子查询都写编号；pierce 同 key，只是一路透过取前几行、算窗口函数的派生来源（见 through），拿来认出同一个
|
||
条件筛的先后不同；anon 写实表的表名、派生来源一律写「@」（排比较的两边谁在前时先分实表的列和派生来源的列）；
|
||
shape 写实表的表名、派生来源写它的结构标识（见 _signature：配对用，和名字、编号都无关）。text、full 给人看
|
||
（见 Part），text 只在好几张表都有这一列时写真实表名，full 一律写（关联条件说的就是两张表各出哪一列，用 full）。
|
||
|
||
node 里套着的子查询逐段改写：每一列按它所在那一段的来源认，子查询里的表去掉别名（列已经写成了真实表名）。
|
||
子查询里拿两张表的列互相比的（相关子查询），给人看时和关联条件一样写表名。比较用的写法里各自起的名字也去掉
|
||
（见 _drop_names）。
|
||
"""
|
||
from sqlglot import exp
|
||
|
||
copy = node.copy()
|
||
if mode in _COMPARING:
|
||
copy = copy.transform(_as_date, copy=False)
|
||
groups: dict[int, tuple[Any, list[Any]]] = {}
|
||
for col in copy.find_all(exp.Column):
|
||
if col.name and not col.is_star:
|
||
owner = self._owner(col)
|
||
groups.setdefault(id(owner), (owner, []))[1].append(col)
|
||
for owner, cols in groups.values():
|
||
scope = sources if owner is None else self.sources(self.segments[owner.meta[_SEGMENT]])
|
||
found = [(col, *self.resolve(col, scope, pierce=mode == "pierce")) for col in cols]
|
||
here = mode
|
||
if owner is not None and mode == "text" and len({s.ref for _, s, _ in found if s is not None}) > 1:
|
||
here = "full"
|
||
for col, source, name in found:
|
||
self._write(col, source, name, here)
|
||
for table in copy.find_all(exp.Table):
|
||
if isinstance(table.this, exp.Identifier) and self._owner(table) is not None:
|
||
table.set("alias", None)
|
||
if mode in _COMPARING:
|
||
for arg in ("catalog", "db", "this"):
|
||
ident = table.args.get(arg)
|
||
if isinstance(ident, exp.Identifier):
|
||
table.set(arg, exp.to_identifier(name_key(ident.name)))
|
||
if mode in _COMPARING:
|
||
self._drop_names(copy, mode)
|
||
return copy.sql(dialect=self.read, comments=False)
|
||
|
||
def _drop_names(self, copy: Any, mode: str) -> None:
|
||
"""比较用的写法里抹掉套着的子查询里各自起的名字（就地改）：引用 CTE 的表、FROM 里的子查询（含 LATERAL）、
|
||
子查询里自带的 CTE 定义写编号（anon 写「@」，shape 里引用 CTE 的表写它的结构标识、别的写「@」；引用它们的列
|
||
已经照这样写了）；只看取值的子查询（IN、EXISTS、标量子查询）去掉选出来的列名。FROM 里的子查询、CTE 定义选出来
|
||
的列名留着：外层按这个名字引用它们，去掉了就分不出外层用的是哪一列。复制出来的那段本身没有父节点，认不出是
|
||
FROM 里的子查询，它选出来的列名也会去掉（_Derived.body 另记了各列，见 derived）。"""
|
||
from sqlglot import exp
|
||
|
||
for node in copy.find_all(exp.Table, exp.Subquery, exp.Lateral, exp.CTE):
|
||
derived = node.meta.get(_DERIVED)
|
||
if not derived:
|
||
continue
|
||
if mode == "shape":
|
||
# 引用 CTE 的表写它是哪个（结构标识）；FROM 里的子查询、CTE 定义本身整段写在这里，不用再标
|
||
mark = exp.to_identifier(self._signature_of(derived) if isinstance(node, exp.Table) else _ANON)
|
||
else:
|
||
mark = exp.to_identifier(_ANON if mode == "anon" else derived)
|
||
if isinstance(node, exp.Table):
|
||
for arg in ("catalog", "db", "alias"):
|
||
node.set(arg, None)
|
||
node.set("this", mark)
|
||
elif isinstance(node.args.get("alias"), exp.TableAlias):
|
||
node.args["alias"].set("this", mark)
|
||
else:
|
||
node.set("alias", exp.TableAlias(this=mark))
|
||
for select in copy.find_all(exp.Select):
|
||
if not _named_output(select):
|
||
select.set("expressions", [e.this if isinstance(e, exp.Alias) else e for e in select.expressions])
|
||
|
||
def _write(self, col: Any, source: _Source | None, name: str, mode: str) -> None:
|
||
"""按 render 的写法改写一列（就地改）。"""
|
||
from sqlglot import exp
|
||
|
||
quoted = isinstance(col.this, exp.Identifier) and bool(col.this.args.get("quoted"))
|
||
if mode in _COMPARING:
|
||
if source is None:
|
||
owner = None
|
||
elif source.kind == "derived":
|
||
owner = _ANON if mode == "anon" else source.ref if mode != "shape" else \
|
||
self._signature_of(source.key) + (f"#{source.role}" if source.role else "")
|
||
else:
|
||
owner = None if mode == "loose" else source.ref
|
||
col.set("this", exp.to_identifier(self.column_key(source, name) if source is not None else name_key(name)))
|
||
col.set("table", exp.to_identifier(owner) if owner else None)
|
||
col.set("db", None)
|
||
col.set("catalog", None)
|
||
return
|
||
col.set("this", exp.Identifier(this=name, quoted=quoted or not _PLAIN_NAME.match(name)))
|
||
# 自己关联自己的（有 role）一律写别名：只写列名读不出是哪一个
|
||
if source is None or (source.kind != "other" and mode != "full" and not source.role
|
||
and (self.single or name_key(name) not in self.shared())):
|
||
col.set("table", None)
|
||
col.set("db", None)
|
||
col.set("catalog", None)
|
||
else:
|
||
*heads, last = source.idents or (exp.to_identifier(source.name),)
|
||
col.set("table", last.copy())
|
||
col.set("db", heads[-1].copy() if heads else None)
|
||
col.set("catalog", heads[-2].copy() if len(heads) > 1 else None)
|
||
|
||
def canonical(self, node: Any, sources: dict[str, _Source], *, by: str = "key") -> Any:
|
||
"""比较的两边排好顺序（列在左、字面量在右；两边都有列的按 _rank 排），IN 的取值排好序；加法、乘法的两项也按
|
||
这个规矩排（amount * 0.9 和 0.9 * amount 是同一个算法），只排两项都不是别的加减乘除的（见 _atomic）。返回新的
|
||
树。套着的子查询里的比较按它那一段的来源排：拿外层的来源去认子查询的别名，排出来的先后就取决于别名怎么起。"""
|
||
from sqlglot import exp
|
||
|
||
def fix(n: Any) -> Any:
|
||
found = _COMPARE.get(type(n).__name__)
|
||
swap = (type(n).__name__, type(n).__name__) if isinstance(n, (exp.Add, exp.Mul)) and \
|
||
_atomic(n.this) and _atomic(n.expression) else found
|
||
if swap is not None and isinstance(n, exp.Binary):
|
||
left, right = n.this, n.expression
|
||
lc, rc = bool(_own_columns(left)), bool(_own_columns(right))
|
||
here = self.scope(n, sources) if lc and rc else sources
|
||
if (rc and not lc) or (lc and rc and self._rank(left, here, by) > self._rank(right, here, by)):
|
||
return getattr(exp, swap[1])(this=right, expression=left)
|
||
elif isinstance(n, exp.In) and n.expressions and not n.args.get("query") \
|
||
and not any(_own_columns(e) for e in n.expressions):
|
||
n.set("expressions", sorted(n.expressions, key=lambda e: e.sql(dialect=self.read)))
|
||
return n
|
||
|
||
return node.transform(fix)
|
||
|
||
def _rank(self, node: Any, sources: dict[str, _Source], by: str = "key") -> tuple[str, str]:
|
||
"""比较的两边谁排前面：先按不写编号的写法（实表的列、派生来源的列分得开），分不出（两个派生来源的同名列）
|
||
再按 by 的写法分。
|
||
|
||
diff_facets 重新分析时 by 是 key，按两边配好对的共同编号排（见 relabel）：p.total > r.total 和换了关联先后、
|
||
位置编号对调的同一句排出来是同一个方向。不按结构标识排：配成一对的两个派生来源里面稍有不同（一边多一个条件）
|
||
时结构标识就不同，按它排，同一个比较在两边可能排成两个方向，报出两条自相矛盾的话。配对之前（算结构标识时）
|
||
还没有共同的编号，by 是 shape，按结构标识排：位置编号决定不了先后。"""
|
||
return self.render(node, sources, "anon"), self.render(node, sources, by)
|
||
|
||
def part(self, node: Any, sources: dict[str, _Source], *, excludes: bool = False) -> Part:
|
||
#: 用到的各列 {(哪一个来源, 列): ((给人看的表名, 列), 比较用的写法)}：按「哪一个来源」分，自己关联自己的两个别名
|
||
#: 是两列（o1.amount、o2.amount）
|
||
refs: dict[tuple[str, str], tuple[ColumnRef, str]] = {}
|
||
origins: list[tuple[str, str]] = []
|
||
stage = ""
|
||
for col in _own_columns(node):
|
||
located = self.locate(col, sources)[1]
|
||
source, name = self.through(located, col.name)
|
||
refs.setdefault((source.ref if source is not None else "", name_key(name)),
|
||
((source.name if source is not None else None, name),
|
||
f"{source.ref}.{self.column_key(source, name)}" if source is not None
|
||
else f".{name_key(name)}"))
|
||
if source is None or source.kind != "derived":
|
||
continue
|
||
# 透视在这个派生来源上停住了，一路透到底却还能往里走：是它取前几行、算窗口函数挡住的
|
||
if not stage and self.through(located, col.name, pierce=True)[0] is not source:
|
||
stage = self._stage(source, name)
|
||
if (origin := self._origin(source, name)) is not None:
|
||
if (pair := (self.render(col, sources, "full"), origin)) not in origins:
|
||
origins.append(pair)
|
||
full = self.render(node, sources, "full")
|
||
key = self.render(node, sources, "key")
|
||
pierce = self.render(node, sources, "pierce") if stage else ""
|
||
if pierce == key:
|
||
pierce = stage = ""
|
||
columns = tuple(ref for ref, _ in refs.values())
|
||
# 拿两张表的列互相比的（相关子查询里的 o.id = r.order_id）和关联条件一样，给人看也写表名
|
||
across = len({table for table, _ in columns}) > 1
|
||
return Part(key=key, text=full if across else self.render(node, sources),
|
||
columns=columns, excludes=self._excludes(node, sources) if excludes else None,
|
||
loose=self.render(node, sources, "loose"), full=full,
|
||
column_keys=tuple(written for _, written in refs.values()),
|
||
origins=tuple(origins), pierce=pierce, stage=stage)
|
||
|
||
def _stage(self, source: _Source, column: str) -> str:
|
||
"""挡住了透视的派生来源做了什么（给人看，见 _blocks）：「取 t 的前 10 行」「算 t 的窗口函数」。"""
|
||
from sqlglot import exp
|
||
|
||
query = source.query
|
||
if self._blocks(query, column) == "limit":
|
||
limit = query.args.get("limit")
|
||
count = limit.expression if isinstance(limit, exp.Limit) else limit.args.get("count") \
|
||
if limit is not None else None
|
||
written = count.sql(dialect=self.read, comments=False) if count is not None else ""
|
||
return _say("取", source.name, "的前", written, "行") if written.isdigit() else \
|
||
_say("按", "LIMIT / OFFSET", "取", source.name, "的行")
|
||
return _say("算", source.name, "的窗口函数")
|
||
|
||
def _origin(self, source: _Source, column: str, depth: int = 0) -> str | None:
|
||
"""派生来源一列的来历（给人看）：它在里面怎么算的，里面再用到的派生来源的列也换成各自的来历，一直换到实表的
|
||
列，一律写表名（SUM(orders.amount)）。两边同名的派生来源其实不是同一个时（盲算的 t1 是原流程的 t2），光写
|
||
「t1.total」两边一样，带上来历才说得清各自是付款合计还是退款合计。UNION 只写第一支；认不出定义、套得太深
|
||
返回 None。"""
|
||
if source.kind != "derived" or source.query is None or depth > 4:
|
||
return None
|
||
memo = (id(source.query), name_key(column))
|
||
if memo not in self._origins:
|
||
self._origins[memo] = None # 递归 CTE 绕回自己时到这里为止
|
||
found = self._definition(source, column)
|
||
self._origins[memo] = self._expand(*found[0], depth + 1) if found else None
|
||
return self._origins[memo]
|
||
|
||
def _expand(self, node: Any, sources: dict[str, _Source], depth: int) -> str:
|
||
"""把 node 写成给人看的 full 写法，里面用到的派生来源的列换成各自的来历（见 _origin）。换进去的是一段
|
||
写好的文字：先用占位符占住位置，整段写好之后再换回来；放在运算符里的加括号，免得优先级变了。"""
|
||
from sqlglot import exp
|
||
|
||
bare = _unparen(node)
|
||
if isinstance(bare, exp.Column):
|
||
source, name = self.resolve(bare, sources)
|
||
inner = self._origin(source, name, depth) if source is not None else None
|
||
return inner if inner is not None else self.render(bare, sources, "full")
|
||
copy = node.copy()
|
||
subs: dict[str, str] = {}
|
||
for col in _own_columns(copy):
|
||
source, name = self.resolve(col, sources)
|
||
inner = self._origin(source, name, depth) if source is not None else None
|
||
if inner is None:
|
||
continue
|
||
mark = exp.Placeholder(this=f"sqlsem{len(subs)}")
|
||
wrap = " " in inner and isinstance(col.parent, (exp.Binary, exp.Unary)) and \
|
||
not isinstance(col.parent, exp.Paren)
|
||
subs[mark.sql(dialect=self.read)] = f"({inner})" if wrap else inner
|
||
col.replace(mark)
|
||
text = self.render(copy, sources, "full")
|
||
for mark, inner in subs.items():
|
||
text = text.replace(mark, inner)
|
||
return text
|
||
|
||
def _excludes(self, node: Any, sources: dict[str, _Source]) -> str | None:
|
||
"""排除写法去掉否定之后排除的是什么：a <> 1 → a = 1；NOT IN、NOT LIKE、NOT BETWEEN 同理；IS NOT NULL → 「a 为空」。
|
||
各方言把否定放的位置不一样（NOT 包一层，或者节点上带 negate），两种都认。"""
|
||
from sqlglot import exp
|
||
|
||
n = _unparen(node)
|
||
if isinstance(n, exp.NEQ):
|
||
return self.render(exp.EQ(this=n.this.copy(), expression=n.expression.copy()), sources)
|
||
inner = None
|
||
if isinstance(n, exp.Not):
|
||
inner = _unparen(n.this).copy()
|
||
elif n.args.get("negate"):
|
||
inner = n.copy()
|
||
inner.set("negate", None)
|
||
if inner is None:
|
||
return None
|
||
if isinstance(inner, exp.Is) and isinstance(_unparen(inner.expression), exp.Null):
|
||
return f"{self.render(inner.this, sources)} 为空"
|
||
return self.render(inner, sources)
|
||
|
||
# ---- 各个方面
|
||
|
||
def facets(self, extra: Iterable[str] = ()) -> Facets:
|
||
"""各个方面。extra 是没用到、也照样收进来的 CTE（name_key，见 _aligned），别的没用到的 CTE 不收（见 _enliven）。"""
|
||
from sqlglot import exp
|
||
|
||
self._enliven(extra)
|
||
joins: list[JoinFacet] = []
|
||
where: list[Part] = []
|
||
time: list[TimePredicate] = []
|
||
group: list[Part] = []
|
||
aggregates: list[Aggregate] = []
|
||
having: list[Part] = []
|
||
used: list[Part] = []
|
||
for select in self._alive(exp.Select):
|
||
sources = self.sources(select)
|
||
if select is self.root or not self._in_condition(select):
|
||
used += [Part.plain(s.ref, s.name) for s in sources.values()]
|
||
drafts = self._join_drafts(select, sources)
|
||
clause = select.args.get("where")
|
||
for cond in _conjuncts(clause.this) if clause is not None else []:
|
||
canon = self.canonical(cond, sources)
|
||
if self._joins_on_where(canon, sources, drafts):
|
||
continue
|
||
part = self.part(canon, sources, excludes=True)
|
||
where.append(part)
|
||
self._rejects(canon, part, sources, drafts)
|
||
if found := self._time(canon, sources):
|
||
time.append(found)
|
||
joins += [self._join(d, sources) for d in drafts]
|
||
group += self._group(select, sources)
|
||
aggregates += self._aggregates(select, sources)
|
||
having += self._having(select, sources)
|
||
derived = [Part.plain(self._labels[number], name or "子查询")
|
||
for number, name, body, _ in self._derived if id(body) not in self._dead]
|
||
return Facets(
|
||
dialect=self.read,
|
||
tables=tuple(Part.plain(s.key, s.name) for s in self.tables),
|
||
joins=_dedupe(joins, lambda j: (j.kind, j.table.key, j.on.key if j.on else None)),
|
||
where=_dedupe(where, lambda p: p.key),
|
||
time=_dedupe(time, lambda t: t.condition.key),
|
||
group_by=_dedupe(group, lambda p: p.key),
|
||
aggregates=_dedupe(aggregates, lambda a: (a.func, a.arg.key, a.distinct)),
|
||
having=_dedupe(having, lambda p: p.key),
|
||
limit=self._limit(),
|
||
limits=tuple(self._limits()),
|
||
sources=_dedupe(used, lambda p: p.key),
|
||
expressions=_dedupe(self._expressions(), lambda c: (c.scope_key, c.name, c.expr.key)),
|
||
derived=_dedupe(derived, lambda p: p.key),
|
||
)
|
||
|
||
def _rejects(self, cond: Any, part: Part, sources: dict[str, _Source], drafts: list[dict[str, Any]]) -> None:
|
||
"""同一段 WHERE 里的条件把外连接可空那一侧没关联上的行筛掉了的，记在那次连接上（见 JoinFacet.rejects）：LEFT
|
||
JOIN 关联进来的那一侧、RIGHT JOIN 之前的各个来源可空，那一侧的列直接拿来比较、IN、LIKE、BETWEEN，或者写 IS NOT
|
||
NULL，空值都不成立。IS NULL、OR、套在 COALESCE / IFNULL / CASE 里的不认（宁可漏报）。"""
|
||
from sqlglot import exp
|
||
|
||
n = _unparen(cond)
|
||
if isinstance(n, exp.Not):
|
||
n = _unparen(n.this)
|
||
if isinstance(n, exp.Is):
|
||
if not isinstance(_unparen(n.expression), exp.Null):
|
||
return
|
||
n = n.this # IS NOT NULL
|
||
elif type(n).__name__ not in _NULL_REJECTING:
|
||
return
|
||
elif type(n).__name__ not in _NULL_REJECTING:
|
||
return
|
||
hit = set()
|
||
for col in _own_columns(n):
|
||
if col is not n and any(isinstance(p, (exp.Coalesce, exp.Case, exp.If)) for p in _parents(col, stop=n)):
|
||
continue
|
||
if (slot := self.locate(col, sources)[0]) is not None:
|
||
hit.add(slot)
|
||
for draft in drafts:
|
||
nullable = {draft["slot"]} if draft["kind"] == "left" else \
|
||
set(draft["before_slots"]) if draft["kind"] == "right" else set()
|
||
if draft.get("rejects") is None and hit & nullable:
|
||
draft["rejects"] = part
|
||
|
||
def _join_drafts(self, select: Any, sources: dict[str, _Source]) -> list[dict[str, Any]]:
|
||
from sqlglot import exp
|
||
|
||
first = select.args.get("from_")
|
||
first_alias = _alias(first.this) if first is not None else ""
|
||
drafts: list[dict[str, Any]] = []
|
||
for i, join in enumerate(select.args.get("joins") or []):
|
||
alias = _alias(join.this)
|
||
slot = name_key(alias) if alias else f"#{i + 1}"
|
||
conds: list[Any] = []
|
||
if join.args.get("on") is not None:
|
||
conds = [self.canonical(c, sources) for c in _conjuncts(join.args["on"])]
|
||
elif join.args.get("using") and first_alias and alias:
|
||
# USING (id)：按「FROM 的那张表.id = 这张表.id」写，和 ON 的写法放在一起比
|
||
conds = [self.canonical(exp.EQ(this=exp.column(ident.name, table=first_alias),
|
||
expression=exp.column(ident.name, table=alias)), sources)
|
||
for ident in join.args["using"]]
|
||
before = [(key, s) for key, s in list(sources.items())[:i + 1] if key != slot]
|
||
drafts.append({"kind": _join_kind(join), "slot": slot, "source": sources.get(slot), "conds": conds,
|
||
"before": [s.name for _, s in before], "before_keys": [s.ref for _, s in before],
|
||
"before_slots": [key for key, _ in before]})
|
||
return drafts
|
||
|
||
def _joins_on_where(self, cond: Any, sources: dict[str, _Source], drafts: list[dict[str, Any]]) -> bool:
|
||
"""WHERE 里两张表的列等式（逗号连接、或者 INNER JOIN 之外又写的等值关联）并进那次连接的条件，不算筛选。
|
||
LEFT JOIN 这类外连接不并：写在 WHERE 里会把外连接变成内连接，和写在 ON 里不是一回事。"""
|
||
from sqlglot import exp
|
||
|
||
n = _unparen(cond)
|
||
if not isinstance(n, exp.EQ):
|
||
return False
|
||
left, right = _unparen(n.this), _unparen(n.expression)
|
||
if not (isinstance(left, exp.Column) and isinstance(right, exp.Column)):
|
||
return False
|
||
a, b = self.locate(left, sources)[0], self.locate(right, sources)[0]
|
||
if a is None or b is None or a == b:
|
||
return False
|
||
for draft in reversed(drafts):
|
||
if draft["slot"] in (a, b) and draft["kind"] in ("inner", "cross"):
|
||
draft["conds"].append(cond)
|
||
draft["kind"] = "inner"
|
||
return True
|
||
return False
|
||
|
||
def _join(self, draft: dict[str, Any], sources: dict[str, _Source]) -> JoinFacet:
|
||
source = draft["source"]
|
||
table = Part.plain("?", "?") if source is None else \
|
||
Part(key=source.ref, text=source.name, loose=source.ref, full=source.name)
|
||
forms = sorted((self.render(c, sources, "key"), self.render(c, sources, "loose"),
|
||
self.render(c, sources, "full")) for c in draft["conds"])
|
||
on = Part(key=" AND ".join(f[0] for f in forms), text=" AND ".join(f[2] for f in forms),
|
||
loose=" AND ".join(sorted(f[1] for f in forms)), full=" AND ".join(f[2] for f in forms)) \
|
||
if forms else None
|
||
mentioned = {table for c in draft["conds"] for table, _ in self.part(c, sources).columns}
|
||
other = [name for name in dict.fromkeys(t for t in mentioned if t) if name != table.text] if draft["conds"] \
|
||
else draft["before"]
|
||
# 涉及的来源按条件里直接引用的算（slot 不为 None 的是这一段的来源）：透过 CTE 找到的实表两边可能一样，
|
||
# 关联的却是两个不同的 CTE
|
||
sides = {source.ref} if source is not None else set()
|
||
if draft["conds"]:
|
||
sides |= {found.ref for c in draft["conds"] for col in _own_columns(c)
|
||
for slot, found in [self.locate(col, sources)] if slot is not None and found is not None}
|
||
else:
|
||
sides |= set(draft["before_keys"])
|
||
# 外连接的主表、可空那一侧：LEFT JOIN 关联进来的那一侧可空，RIGHT JOIN 反过来；另一侧按关联条件里出现的来源
|
||
# 算（没有就是它之前的各个来源），和内连接的 sides 一样不受前面别的连接先后的影响
|
||
keep: set[str] = set()
|
||
nullable: set[str] = set()
|
||
if draft["kind"] in ("left", "right") and source is not None:
|
||
near, far = {source.ref}, (sides - {source.ref}) or set(draft["before_keys"])
|
||
keep, nullable = (far, near) if draft["kind"] == "left" else (near, far)
|
||
return JoinFacet(kind=draft["kind"], table=table, on=on, other=tuple(sorted(other)),
|
||
sides=tuple(sorted(sides)), keep=tuple(sorted(keep)), nullable=tuple(sorted(nullable)),
|
||
rejects=draft.get("rejects"))
|
||
|
||
def _time(self, cond: Any, sources: dict[str, _Source]) -> TimePredicate | None:
|
||
"""时间条件：一边恰好一列（可以套着日期函数、CAST），另一边没有列；列名像日期，或者用了日期函数、像日期的字符串。"""
|
||
from sqlglot import exp
|
||
|
||
n = _unparen(cond)
|
||
if n.args.get("negate"):
|
||
return None
|
||
if isinstance(n, exp.Between):
|
||
subject, values, op = n.this, [n.args.get("low"), n.args.get("high")], "between"
|
||
elif isinstance(n, exp.In) and n.expressions and not n.args.get("query"):
|
||
subject, values, op = n.this, list(n.expressions), "in"
|
||
elif type(n).__name__ in _COMPARE and isinstance(n, exp.Binary):
|
||
subject, values, op = n.this, [n.expression], _COMPARE[type(n).__name__][0]
|
||
else:
|
||
return None
|
||
if subject is None or any(v is None or _own_columns(v) for v in values):
|
||
return None
|
||
column = _bare_column(subject)
|
||
cols = [column] if column is not None else _own_columns(subject)
|
||
if len(cols) != 1 or any(isinstance(x, (exp.AggFunc, exp.Select)) for x in subject.walk()):
|
||
return None
|
||
base, scope, via, datey = self._time_column(cols[0], sources)
|
||
if not (_temporal_name(base.name) or _temporal_name(cols[0].name) or datey or _datey(subject)
|
||
or any(_datey(v) for v in values)):
|
||
return None
|
||
shown = [self.render(v, sources) for v in values]
|
||
value = f"{shown[0]} AND {shown[1]}" if op == "between" else f"({', '.join(shown)})" if op == "in" \
|
||
else shown[0]
|
||
return TimePredicate(column=self.part(base, scope), op=op, value=value,
|
||
condition=self.part(cond, sources, excludes=True), via=via)
|
||
|
||
def _time_column(self, column: Any, sources: dict[str, _Source]) -> tuple[Any, _Sources, tuple[str, ...], bool]:
|
||
"""时间条件里的那一列是 CTE、子查询算出来的、在里面是同一列套着日期函数、CAST、MIN / MAX 时（见 _value_column），
|
||
换成里面那一列，一直换到实表：(那一列, 它那一段的来源, 路过的派生来源的列「编号.列」, 路上有没有日期函数)。
|
||
原样透出的列 resolve 已经透过去了；这里补上算了一下的。"""
|
||
via: list[str] = []
|
||
datey = False
|
||
for _ in range(4):
|
||
source, name = self.resolve(column, sources)
|
||
found = self._definition(source, name) if source is not None else None
|
||
inner = _value_column(found[0][0]) if found and len(found) == 1 else None
|
||
if inner is None:
|
||
break
|
||
via.append(f"{source.key}.{self.column_key(source, name)}")
|
||
datey = datey or _datey(found[0][0])
|
||
column, sources = inner, found[0][1]
|
||
return column, sources, tuple(via), datey
|
||
|
||
@staticmethod
|
||
def _aliases(query: Any) -> dict[str, Any]:
|
||
"""SELECT 里的别名 {name_key: 别名指的表达式}。"""
|
||
from sqlglot import exp
|
||
|
||
return {name_key(s.alias): s.this for s in query.selects if isinstance(s, exp.Alias) and s.alias}
|
||
|
||
@staticmethod
|
||
def _target(item: Any, selects: list[Any], aliases: dict[str, Any]) -> Any:
|
||
"""GROUP BY、ORDER BY 里的一项：写序号（1）的换成 SELECT 里对应的表达式，写别名的换成别名指的表达式
|
||
（MySQL、SQLite 的读法），其余原样。"""
|
||
from sqlglot import exp
|
||
|
||
target = _unparen(item)
|
||
if isinstance(target, exp.Literal) and not target.is_string and str(target.this).isdigit():
|
||
index = int(target.this) - 1
|
||
if 0 <= index < len(selects):
|
||
return selects[index].this if isinstance(selects[index], exp.Alias) else selects[index]
|
||
elif isinstance(target, exp.Column) and not target.table and name_key(target.name) in aliases:
|
||
return aliases[name_key(target.name)]
|
||
return target
|
||
|
||
def _group(self, select: Any, sources: dict[str, _Source]) -> list[Part]:
|
||
"""分组键。GROUP BY 1 换成 SELECT 里对应的表达式，GROUP BY 别名换成别名指的表达式（MySQL、SQLite 的读法）。"""
|
||
group = select.args.get("group")
|
||
if group is None:
|
||
return []
|
||
selects, aliases = select.selects, self._aliases(select)
|
||
return [self.part(self.canonical(self._target(item, selects, aliases), sources), sources)
|
||
for item in group.expressions]
|
||
|
||
def _having(self, select: Any, sources: dict[str, _Source]) -> list[Part]:
|
||
"""HAVING 的各个合取式。引用 SELECT 别名的列（HAVING s > 100，MySQL、SQLite 的写法）换成别名指的表达式，
|
||
和 GROUP BY 别名一个读法：不换的话，写别名和写表达式的同一个条件会被报成两个不同的条件。"""
|
||
from sqlglot import exp
|
||
|
||
clause = select.args.get("having")
|
||
if clause is None:
|
||
return []
|
||
aliases = self._aliases(select)
|
||
out = []
|
||
for cond in _conjuncts(clause.this):
|
||
copy = cond.copy()
|
||
for col in _own_columns(copy):
|
||
target = aliases.get(name_key(col.name)) if not col.table else None
|
||
# 聚合函数里的名字指的是表里的列，不是别名：SUM(amount) AS amount 之后的 SUM(amount) 不能再换
|
||
if target is None or any(isinstance(p, exp.AggFunc) for p in _parents(col, stop=None)):
|
||
continue
|
||
if col is copy:
|
||
copy = target.copy()
|
||
break
|
||
col.replace(target.copy())
|
||
out.append(self.part(self.canonical(copy, sources), sources))
|
||
return out
|
||
|
||
def _aggregates(self, select: Any, sources: dict[str, _Source]) -> list[Aggregate]:
|
||
from sqlglot import exp
|
||
|
||
return [self._aggregate(node, sources) for node in _own_nodes(select)
|
||
if isinstance(node, exp.AggFunc) and not isinstance(node.parent, exp.Window)]
|
||
|
||
def _aggregate(self, node: Any, sources: dict[str, _Source]) -> Aggregate:
|
||
from sqlglot import exp
|
||
|
||
try:
|
||
func = str(node.sql_name()).lower()
|
||
except Exception: # noqa: BLE001 - 没有固定函数名的聚合：按类型名
|
||
func = node.key
|
||
arg = node.this
|
||
distinct = isinstance(arg, exp.Distinct)
|
||
if distinct:
|
||
items = list(arg.expressions)
|
||
arg = items[0] if len(items) == 1 else exp.Tuple(expressions=[i.copy() for i in items])
|
||
if arg is None or isinstance(arg, exp.Star) or \
|
||
(func == "count" and not distinct and isinstance(_unparen(arg), exp.Literal)):
|
||
part = Part.plain("*", "*") # COUNT(*)、COUNT(1)：数的是行数
|
||
else:
|
||
part = self.part(self.canonical(arg, sources), sources)
|
||
return Aggregate(func=func, arg=part, distinct=distinct, text=self.render(node, sources))
|
||
|
||
# ---- 算出来的列
|
||
|
||
def _expressions(self) -> list[Computed]:
|
||
"""算出来的列（见 Computed）：最外层（UNION 的各支）选出来、不是光一列也不是字面量的；用到了的派生来源里
|
||
被外面用到、又不是原样透出一列的列（原样透出的，外面的写法 resolve 已经透成了里面那一列，不用再比定义）。"""
|
||
from sqlglot import exp
|
||
|
||
out: list[Computed] = []
|
||
for select in _branches(self.root):
|
||
sources = self.sources(select)
|
||
for item in select.selects:
|
||
target = _unwrap_value(item.this if isinstance(item, exp.Alias) else item)
|
||
if not self._plain_output(target):
|
||
out.append(self._computed([(target, sources)], None, None, "", ""))
|
||
used = self._used()
|
||
for number, name, body, _ in self._derived:
|
||
label = self._labels[number]
|
||
if id(body) in self._dead or label not in used:
|
||
continue
|
||
source = _Source("derived", name or "子查询", label, (), body)
|
||
columns = [called for called in self.names(body) if called]
|
||
columns += sorted(c for c in used[label] if c not in {name_key(x) for x in columns})
|
||
for column in dict.fromkeys(columns):
|
||
if name_key(column) not in used[label] or self.through(source, column)[0] is not source:
|
||
continue
|
||
if found := self._definition(source, column):
|
||
out.append(self._computed(found, source.name, label, self.column_key(source, column), column))
|
||
return out
|
||
|
||
@staticmethod
|
||
def _plain_output(target: Any) -> bool:
|
||
"""最外层选出来的一项不用按算法比：光一列（分组那一面比）、*、字面量。光一个聚合照收：另一边可能是拿同一个
|
||
聚合再算了一下（SUM(amount) 对 SUM(amount) / 100），得配成一对说；两边只差聚合本身的，聚合那一面已经报了。"""
|
||
from sqlglot import exp
|
||
|
||
return isinstance(_unparen(target), (exp.Column, exp.Star, exp.Literal, exp.Null, exp.Boolean))
|
||
|
||
def _computed(self, branches: list[tuple[Any, _Sources]], scope: str | None, scope_key: str | None, name: str,
|
||
shown: str) -> Computed:
|
||
"""一列的定义（UNION 每支一个）→ Computed：定义本身、聚合换成占位符之后的写法、里面的聚合。"""
|
||
from sqlglot import exp
|
||
|
||
exprs: list[Part] = []
|
||
templates: list[Part] = []
|
||
aggregates: list[Aggregate] = []
|
||
for node, sources in branches:
|
||
canon = self.canonical(node, sources)
|
||
exprs.append(self.part(canon, sources))
|
||
# 这一段自己的聚合（窗口函数、套着的子查询里的不算），按出现的先后
|
||
own = [n for n in canon.walk(prune=lambda x: isinstance(x, (exp.Select, exp.Subquery)))
|
||
if isinstance(n, exp.AggFunc) and not isinstance(n.parent, exp.Window)
|
||
and not any(isinstance(p, exp.AggFunc) for p in _parents(n, stop=None))]
|
||
aggregates += [self._aggregate(n, sources) for n in own]
|
||
if own and own[0] is canon:
|
||
templates.append(Part.plain(PLACEHOLDER, PLACEHOLDER)) # 光一个聚合
|
||
continue
|
||
for n in own:
|
||
n.replace(exp.Placeholder())
|
||
templates.append(Part(key=self.render(canon, sources, "key"), text="",
|
||
loose=self.render(canon, sources, "loose")))
|
||
|
||
def joined(parts: list[Part]) -> Part:
|
||
if len(parts) == 1:
|
||
return parts[0]
|
||
return Part(key=" | ".join(p.key for p in parts), text=" | ".join(p.text for p in parts),
|
||
loose=" | ".join(p.loose for p in parts), full=" | ".join(p.full for p in parts),
|
||
columns=tuple(c for p in parts for c in p.columns),
|
||
column_keys=tuple(k for p in parts for k in p.column_keys),
|
||
origins=tuple(o for p in parts for o in p.origins))
|
||
|
||
return Computed(scope=scope, scope_key=scope_key, name=name, shown=shown, expr=joined(exprs),
|
||
template=joined(templates), aggregates=tuple(aggregates))
|
||
|
||
def _used(self) -> dict[str, set[str]]:
|
||
"""用到了的段里引用了派生来源的哪些列：{派生来源的编号: {列名的 name_key}}。原样透出的列连同里面那一层也算
|
||
用到了；最外层的 SELECT *（t.*）用到了那个来源的每一列；USING 的列两边都算。"""
|
||
from sqlglot import exp
|
||
|
||
used: dict[str, set[str]] = {}
|
||
|
||
def mark(source: _Source | None, column: str) -> None:
|
||
for _ in range(8):
|
||
if source is None or source.kind != "derived":
|
||
return
|
||
used.setdefault(source.key, set()).add(name_key(column))
|
||
if (found := self._pass(source, column)) is None:
|
||
return
|
||
source, column = found
|
||
|
||
def mark_all(source: _Source | None, depth: int = 0) -> None:
|
||
if source is None or source.kind != "derived" or depth > 4:
|
||
return
|
||
for branch in _branches(source.query)[:1]:
|
||
inner = self.sources(branch)
|
||
for item, called in zip(branch.selects, self.names(source.query)):
|
||
if called is None:
|
||
for found in self._starred(item, inner):
|
||
mark_all(found, depth + 1)
|
||
else:
|
||
mark(source, called)
|
||
|
||
outermost = {id(s) for s in _branches(self.root)}
|
||
for select in self._alive(exp.Select):
|
||
sources = self.sources(select)
|
||
for node in _own_nodes(select):
|
||
if isinstance(node, exp.Column) and node.name and not node.is_star:
|
||
mark(self.locate(node, sources)[1], node.name)
|
||
if id(select) in outermost:
|
||
for item in select.selects:
|
||
if _is_star(item):
|
||
for found in self._starred(item, sources):
|
||
mark_all(found)
|
||
for join in select.args.get("joins") or []:
|
||
for ident in join.args.get("using") or []:
|
||
for found in sources.values():
|
||
if self._exposes(found, ident.name):
|
||
mark(found, ident.name)
|
||
return used
|
||
|
||
@staticmethod
|
||
def _starred(item: Any, sources: dict[str, _Source]) -> list[_Source]:
|
||
"""SELECT 列表里的 *、t.* 选的是哪几个来源。"""
|
||
from sqlglot import exp
|
||
|
||
if isinstance(item, exp.Column) and item.table:
|
||
found = sources.get(name_key(item.table))
|
||
return [found] if found is not None else []
|
||
return list(sources.values())
|
||
|
||
def _limit(self) -> str | None:
|
||
from sqlglot import exp
|
||
|
||
node = self.root.args.get("limit")
|
||
if node is None:
|
||
return None
|
||
value = node.expression if isinstance(node, exp.Limit) else node.args.get("count")
|
||
return value.sql(dialect=self.read, comments=False) if value is not None else None
|
||
|
||
def _limits(self) -> list[LimitFacet]:
|
||
"""各段取哪几行：最外层在前，其余按出现的先后。条件里套着的子查询（WHERE、HAVING、ON 里的）不单算：
|
||
它整个写在那个条件的 key 里，单算的话同一处不同会报两遍。"""
|
||
from sqlglot import exp
|
||
|
||
out = []
|
||
for query in self._alive(exp.Select, exp.SetOperation):
|
||
if query is not self.root and self._in_condition(query):
|
||
continue
|
||
if (found := self._limit_of(query)) is not None:
|
||
out.append(found)
|
||
return out
|
||
|
||
def _in_condition(self, node: Any) -> bool:
|
||
from sqlglot import exp
|
||
|
||
while node is not None and node is not self.root:
|
||
if isinstance(node, (exp.Where, exp.Having)) or \
|
||
(isinstance(node.parent, exp.Join) and node.arg_key == "on"):
|
||
return True
|
||
node = node.parent
|
||
return False
|
||
|
||
def _limit_of(self, query: Any) -> LimitFacet | None:
|
||
"""一段的 LIMIT / OFFSET，连同这一段的排序；两样都没写返回 None。"""
|
||
from sqlglot import exp
|
||
|
||
def written(node: Any) -> str | None:
|
||
return node.sql(dialect=self.read, comments=False) if node is not None else None
|
||
|
||
limit, offset = query.args.get("limit"), query.args.get("offset")
|
||
count = written(limit.expression if isinstance(limit, exp.Limit) else limit.args.get("count")) \
|
||
if limit is not None else None
|
||
if offset is None and isinstance(limit, exp.Limit):
|
||
offset = limit.args.get("offset") # 有的方言把 OFFSET 挂在 LIMIT 底下
|
||
skip = written(offset.expression if isinstance(offset, exp.Offset) else offset)
|
||
if skip is not None and skip.strip() == "0":
|
||
skip = None # OFFSET 0 等于没写
|
||
if limit is None and skip is None:
|
||
return None
|
||
return LimitFacet(count=count, offset=skip, order=self._order(query), scope=self._scope_name(query),
|
||
scope_key=self._scope_key(query))
|
||
|
||
@staticmethod
|
||
def _scope_key(query: Any) -> str | None:
|
||
"""query 整段是哪个派生来源（CTE 的定义、FROM 里的子查询、LATERAL 子查询）的编号；最外层、UNION 的某一支、
|
||
SELECT 列表里的子查询这类不是派生来源整段的返回 None。编号记在 CTE 定义、FROM / JOIN 项上，往外找一两层。"""
|
||
from sqlglot import exp
|
||
|
||
node = query
|
||
while isinstance(node.parent, (exp.Subquery, exp.Lateral, exp.CTE)):
|
||
node = node.parent
|
||
if found := node.meta.get(_DERIVED):
|
||
return found
|
||
return None
|
||
|
||
def _order(self, query: Any) -> tuple[tuple[Part, bool], ...]:
|
||
"""这一段的排序键 (Part, 是否降序)。ORDER BY 1、ORDER BY 别名换成 SELECT 里的表达式（UNION 按第一支的）。"""
|
||
from sqlglot import exp
|
||
|
||
order = query.args.get("order")
|
||
if order is None:
|
||
return ()
|
||
select = query if isinstance(query, exp.Select) else None
|
||
sources = self.sources(select) if select is not None else _Sources()
|
||
selects = list(query.selects)
|
||
aliases = self._aliases(query)
|
||
out = []
|
||
for item in order.expressions:
|
||
target = self._target(item.this if isinstance(item, exp.Ordered) else item, selects, aliases)
|
||
desc = bool(item.args.get("desc")) if isinstance(item, exp.Ordered) else False
|
||
out.append((self.part(self.canonical(target, sources), sources), desc))
|
||
return tuple(out)
|
||
|
||
def _scope_name(self, query: Any) -> str | None:
|
||
from sqlglot import exp
|
||
|
||
if query is self.root:
|
||
return None
|
||
parent = query.parent
|
||
if isinstance(parent, exp.Subquery) and not parent.alias and isinstance(parent.parent, exp.Lateral):
|
||
parent = parent.parent # LATERAL 的别名挂在 LATERAL 上，不在里面的子查询上
|
||
if isinstance(parent, (exp.CTE, exp.Subquery, exp.Lateral)) and parent.alias:
|
||
return parent.alias
|
||
return "子查询"
|
||
|
||
|
||
# ==========================================================================
|
||
# 比较
|
||
# ==========================================================================
|
||
|
||
|
||
@dataclass(frozen=True)
|
||
class FacetDiff:
|
||
"""一处不同。aspect：time（时间列）/ time_range（同一时间列、范围不同，或者同一个时间条件筛的先后不同）/ filter /
|
||
aggregate / expression（算出来的列：最外层的算法、CTE 和子查询里被用到的列的定义，见 Computed）/ join（类型、
|
||
外连接的主表、关联条件、只有一边关联了）/ tables / group_by / having / limit（取哪几行：行数、跳过的行数、取前
|
||
几行时的排序）/ parse。a、b 是两边各自的写法（给人看，没有就是 None），text 是一句中文说明。
|
||
detail 只在 time 上有：两边的时间列 [{table, column}]，调用方据此对照数据目录（业务日期）。"""
|
||
|
||
aspect: str
|
||
a: Any
|
||
b: Any
|
||
text: str
|
||
detail: dict[str, Any] | None = None
|
||
|
||
def as_dict(self) -> dict[str, Any]:
|
||
out = {"aspect": self.aspect, "a": self.a, "b": self.b, "text": self.text}
|
||
if self.detail is not None:
|
||
out["detail"] = self.detail
|
||
return out
|
||
|
||
|
||
_CJK_PUNCT = frozenset("，。；：、！？「」『』（）《》【】…—")
|
||
#: 聚合函数的说法
|
||
_VERBS = {"sum": "求和", "count": "计数", "avg": "求平均", "min": "取最小值", "max": "取最大值"}
|
||
|
||
|
||
def _wide(ch: str) -> bool:
|
||
return "⺀" <= ch <= "鿿" or "豈" <= ch <= "" or "" <= ch <= ""
|
||
|
||
|
||
def _say(*parts: str) -> str:
|
||
"""拼一句话：汉字和英文、数字、SQL 之间加一个空格，挨着全角标点的不加，汉字和汉字之间不加。
|
||
|
||
两边的叫法由调用方定（A / B，或者「原流程」「盲算」），所以空格只能拼的时候按字判断。
|
||
"""
|
||
out = ""
|
||
for part in parts:
|
||
if not part:
|
||
continue
|
||
if out and not out[-1].isspace() and not part[0].isspace():
|
||
a, b = out[-1], part[0]
|
||
if not (a in _CJK_PUNCT or b in _CJK_PUNCT or (_wide(a) and _wide(b))):
|
||
out += " "
|
||
out += part
|
||
return out
|
||
|
||
|
||
def catalog_labels(notes: Mapping[str, Mapping[str, Any]] | None) -> dict[str, str]:
|
||
"""数据目录（{表名: notes}）里列的中文名 → diff_facets 的 names：{「表.列」: 中文名}；只在一张表里有、或者各表
|
||
叫法一致的列另记 {列: 中文名}。被驳回的项不算。"""
|
||
out: dict[str, str] = {}
|
||
bare: dict[str, tuple[str, set[str]]] = {}
|
||
for table, raw in (notes or {}).items():
|
||
visible = catalog.visible_notes(raw) if isinstance(raw, Mapping) else {}
|
||
columns = visible.get("columns") if isinstance(visible.get("columns"), Mapping) else {}
|
||
for column, items in columns.items():
|
||
item = items.get("label") if isinstance(items, Mapping) else None
|
||
label = item.get("value") if isinstance(item, Mapping) else None
|
||
if isinstance(label, str) and label.strip():
|
||
out[f"{table}.{column}"] = label.strip()
|
||
bare.setdefault(name_key(str(column)), (str(column), set()))[1].add(label.strip())
|
||
for column, labels in bare.values():
|
||
if len(labels) == 1:
|
||
out.setdefault(column, next(iter(labels)))
|
||
return out
|
||
|
||
|
||
def _labeler(names: Mapping[str, str] | None) -> Any:
|
||
index = {name_key(str(k)): str(v) for k, v in (names or {}).items() if isinstance(v, str) and v.strip()}
|
||
|
||
def label(ref: ColumnRef) -> str | None:
|
||
table, column = ref
|
||
return (index.get(name_key(f"{table}.{column}")) if table else None) or index.get(name_key(column))
|
||
|
||
return label
|
||
|
||
|
||
def _single_column(part: Part, *, loose: bool) -> str | None:
|
||
"""只涉及一列的条件：那一列（Part.column_keys：实表.列，CTE、子查询的列写「编号.列」），用来把两边对同一列的
|
||
不同写法配成一对。loose 时实表的列只看列名（表换了一张），派生来源的列照样带编号：两个 CTE 的同名列不是一列。"""
|
||
if len(part.columns) != 1 or len(part.column_keys) != 1:
|
||
return None
|
||
key = part.column_keys[0]
|
||
return name_key(part.columns[0][1]) if loose and not key.startswith("@") else key
|
||
|
||
|
||
def _verb(g: Aggregate) -> str:
|
||
return ("去重" if g.distinct else "") + _VERBS.get(g.func, f"用 {g.func.upper()} 汇总")
|
||
|
||
|
||
def _rows(limit: str | None) -> str:
|
||
if limit is None:
|
||
return "不限行数"
|
||
return f"只取前 {limit} 行" if limit.isdigit() else f"按 LIMIT {limit} 取行"
|
||
|
||
|
||
def _skip(offset: str | None) -> str:
|
||
if offset is None:
|
||
return "不跳过行"
|
||
return f"跳过前 {offset} 行" if offset.isdigit() else f"按 OFFSET {offset} 跳过行"
|
||
|
||
|
||
class _Compare:
|
||
"""一次比较：两边的叫法、列的中文名，以及按哪种写法比。
|
||
|
||
两边各有一张只在自己这边出现、又不是关联进来的表（orders 换成了 orders_archive）时，其余各方面按不写表名的
|
||
loose 比：表换了这件事由一条「tables」说清，同一个条件、同一个聚合不再因为表名不同被重复报一遍。
|
||
|
||
派生来源的编号由 diff_facets 先按结构配好（两边配成一对的写同一个编号，见模块说明），这里各方面都只按 k 比：
|
||
编号不同就是不同的来源，不再拿「不写编号」的写法补配（那样会把 p.total 和 r.total 当成同一列）。
|
||
|
||
几个方面之间互相交代，同一处不同只报一遍：聚合那一面报过的聚合（reported）、时间那一面报过的派生来源的列
|
||
（explained），算出来的列那一面不再重复报。
|
||
"""
|
||
|
||
def __init__(self, a: Facets, b: Facets, labels: tuple[str, str], names: Mapping[str, str] | None) -> None:
|
||
self.a, self.b = a, b
|
||
self.la, self.lb = labels
|
||
self.label = _labeler(names)
|
||
joined = {j.table.key for j in (*a.joins, *b.joins)}
|
||
self.ta = [t for t in a.tables if t.key not in {u.key for u in b.tables} and t.key not in joined]
|
||
self.tb = [t for t in b.tables if t.key not in {u.key for u in a.tables} and t.key not in joined]
|
||
self.swapped = len(self.ta) == 1 and len(self.tb) == 1
|
||
#: 两边的派生来源 {编号: 名字}（同名却不是同一个时拿来说清对应关系）、各段来源 {key: 名字}（外连接的主表）
|
||
self.names = ({p.key: p.text for p in a.derived}, {p.key: p.text for p in b.derived})
|
||
self.called = ({p.key: p.text for p in a.sources}, {p.key: p.text for p in b.sources})
|
||
#: 聚合那一面报过的两边独有的聚合、时间那一面已经说了的派生来源的列（「编号.列」）
|
||
self.reported: tuple[set[Any], set[Any]] = (set(), set())
|
||
self.explained: set[str] = set()
|
||
|
||
def k(self, part: Part | None) -> str | None:
|
||
if part is None:
|
||
return None
|
||
return part.loose if self.swapped else part.key
|
||
|
||
def side(self, key: str) -> str:
|
||
"""比较用的来源 key；换了一张表时，换的那两张记成同一个。"""
|
||
return "?" if self.swapped and key in (self.ta[0].key, self.tb[0].key) else key
|
||
|
||
def sides(self, j: JoinFacet) -> tuple[str, ...]:
|
||
"""连接涉及的来源（见 JoinFacet.sides）。"""
|
||
return self.keys(j.sides)
|
||
|
||
def keys(self, keys: Iterable[str]) -> tuple[str, ...]:
|
||
return tuple(sorted(self.side(s) for s in keys))
|
||
|
||
def agg_key(self, g: Aggregate) -> tuple[str, str | None, bool]:
|
||
return g.func, self.k(g.arg), g.distinct
|
||
|
||
def added(self, j: JoinFacet, mine: Facets, theirs: Facets) -> tuple[str, set[str]]:
|
||
"""一边独有的一次连接，多出来的是哪个来源：(给人看的名字, 比较用的 key)。
|
||
|
||
一般是关联进来的那一侧；可内连接、CROSS JOIN 关联进来的那一侧另一边也有时，多出来的其实是这次连接接上的
|
||
另一头（FROM stores JOIN orders，另一边只查 orders：多出来的是 stores，不是 orders），说成「关联了 orders
|
||
表」就错了。这时报涉及的来源里另一边没有的那几个。"""
|
||
if j.kind in ("inner", "cross"):
|
||
have = {self.side(s.key) for s in theirs.sources}
|
||
new = [k for k in j.sides if self.side(k) not in have]
|
||
if new and self.side(j.table.key) in have:
|
||
names = {s.key: s.text for s in mine.sources}
|
||
return "、".join(names.get(k, k) for k in new), set(new)
|
||
return j.table.text, {j.table.key}
|
||
|
||
@staticmethod
|
||
def unmatched(xs: Iterable[Any], ys: Iterable[Any], key: Any) -> tuple[list[Any], list[Any]]:
|
||
"""两边各自独有的项（按 key 比），各按原来的先后。派生来源在 key 里已经是两边按结构配好的共同编号（见
|
||
diff_facets），这里不再拿不写编号的写法补配一遍：那样两个 CTE 的同名列（p.total、r.total）会被当成一列，
|
||
换了用哪一个的列也报不出来。配不上的派生来源（一边多出来的 CTE）编号和另一边的都不一样，按它写的项照样
|
||
各算各的。"""
|
||
xs, ys = list(xs), list(ys)
|
||
kx, ky = {key(x) for x in xs}, {key(y) for y in ys}
|
||
return [x for x in xs if key(x) not in ky], [y for y in ys if key(y) not in kx]
|
||
|
||
@staticmethod
|
||
def lookalikes(only_a: list[Part], only_b: list[Part]) -> list[tuple[Part, Part]]:
|
||
"""两边各自独有、给人看的写法却一样的条件配成一对，就地从两边拿掉：同一个条件挂在不同的来源上（p.total > 100
|
||
和 r.total > 100，各自只读得出 total > 100），分开各说一句「只保留 total > 100 的行」读起来自相矛盾。"""
|
||
pairs = []
|
||
for p in list(only_a):
|
||
q = next((q for q in only_b if q.text == p.text), None)
|
||
if q is not None:
|
||
pairs.append((p, q))
|
||
only_a.remove(p)
|
||
only_b.remove(q)
|
||
return pairs
|
||
|
||
@staticmethod
|
||
def staged(only_a: list[Part], only_b: list[Part]) -> list[tuple[Part, Part]]:
|
||
"""两边各自独有、一路透到底却是同一个条件的配成一对，就地从两边拿掉（见 Part.pierce）：只有一边被取前几行、
|
||
算窗口函数的派生来源挡住，是同一个条件筛的先后不同，不是两个条件。"""
|
||
pairs = []
|
||
for p in list(only_a):
|
||
q = next((q for q in only_b
|
||
if bool(p.stage) != bool(q.stage) and (p.pierce or p.key) == (q.pierce or q.key)), None)
|
||
if q is not None:
|
||
pairs.append((p, q))
|
||
only_a.remove(p)
|
||
only_b.remove(q)
|
||
return pairs
|
||
|
||
def stage_text(self, p: Part, q: Part) -> str:
|
||
"""同一个条件筛的先后不同：哪一边先取前几行 / 算窗口函数、再筛，哪一边先筛。条件照没被挡住的那一边写：它
|
||
写的是里面那一列，读起来和原 SQL 一样。"""
|
||
cond, stage = (q if p.stage else p).text, p.stage or q.stage
|
||
if p.stage:
|
||
return _say(self.la, "先", stage, "、再按", cond, "筛选，", self.lb, "先按", cond, "筛选、再", stage)
|
||
return _say(self.la, "先按", cond, "筛选、再", stage, "，", self.lb, "先", stage, "、再按", cond, "筛选")
|
||
|
||
def shown(self, xs: list[Part], ys: list[Part], *, text: Any = None, full: Any = None) -> tuple[str, str]:
|
||
"""两边给人看的写法。读起来一样却不是同一个东西时，依次改成：一律写表名的写法（各自只写列名时两张表的
|
||
amount 读起来一样）；带上派生来源各列的来历（两边同名的 t1 一个算付款合计、一个算退款合计）；两边同名的派生
|
||
来源各对应另一边的哪一个（两个 CTE 只差里面的条件，来历也一样）。"""
|
||
text = text or (lambda ps: "、".join(p.text for p in ps))
|
||
full = full or (lambda ps: "、".join(p.full for p in ps))
|
||
wa, wb = text(xs), text(ys)
|
||
if wa != wb:
|
||
return wa, wb
|
||
wa, wb = full(xs), full(ys)
|
||
return (wa, wb) if wa != wb else self.annotated(wa, wb, xs, ys)
|
||
|
||
def annotated(self, wa: str, wb: str, xs: list[Part], ys: list[Part]) -> tuple[str, str]:
|
||
"""两边一律写表名的写法 wa、wb 也一样时（见 shown）：带上派生来源各列的来历，来历也一样就说清对应关系。"""
|
||
ga, gb = self.gloss(xs), self.gloss(ys)
|
||
if ga != gb:
|
||
return _say(wa, ga), _say(wb, gb)
|
||
return wa, _say(wb, self.correspondence(xs, ys))
|
||
|
||
@staticmethod
|
||
def gloss(parts: list[Part]) -> str:
|
||
"""用到的派生来源的列各自的来历（见 Part.origins）：「（即 SUM(orders.amount)）」，好几列时「（p.total 即 …、
|
||
r.total 即 …）」。没有返回空串。"""
|
||
notes: list[str] = []
|
||
for p in parts:
|
||
for column, origin in p.origins:
|
||
note = _say("即", origin) if len(p.origins) == 1 and p.full == column else _say(column, "即", origin)
|
||
if note not in notes:
|
||
notes.append(note)
|
||
return f"（{'、'.join(notes)}）" if notes else ""
|
||
|
||
def correspondence(self, xs: list[Part], ys: list[Part]) -> str:
|
||
"""用到的派生来源两边同名、却各自对应另一边别的派生来源时，说清对应关系：「（盲算的 paid 对应原流程的 open）」；
|
||
一边的在另一边配不上的也说。没有返回空串。"""
|
||
keys = dict.fromkeys(ck.split(".", 1)[0].split("#", 1)[0] for p in (*ys, *xs) for ck in p.column_keys
|
||
if ck.startswith("@"))
|
||
na, nb = self.names
|
||
notes = []
|
||
for key in keys:
|
||
a, b = na.get(key), nb.get(key)
|
||
if a and b and a != b:
|
||
notes.append(_say(self.lb, "的", b, "对应", self.la, "的", a))
|
||
elif b and not a:
|
||
notes.append(_say(self.lb, "的", b, "在", self.la, "里没有对应的"))
|
||
elif a and not b:
|
||
notes.append(_say(self.la, "的", a, "在", self.lb, "里没有对应的"))
|
||
return f"（{'、'.join(notes)}）" if notes else ""
|
||
|
||
def named(self, parts: list[Part], *, full: bool = False) -> str:
|
||
"""时间列：有中文名的写「支付时间 paid_at」，几列用顿号隔开。"""
|
||
out = []
|
||
for p in parts:
|
||
text = p.full if full else p.text
|
||
name = self.label(p.columns[0]) if p.columns else None
|
||
out.append(_say(name, text) if name else text)
|
||
return "、".join(out)
|
||
|
||
def one_sided(self, side: str, other: str, part: Part, *, group: bool = False) -> str:
|
||
if group:
|
||
return _say(side, "分组后只保留", part.text, "的组，", other, "没有这个条件")
|
||
if part.excludes:
|
||
return _say(side, "排除了", part.excludes, "的行，", other, "没有")
|
||
return _say(side, "只保留", part.text, "的行，", other, "没有这个条件")
|
||
|
||
# ---- 各个方面
|
||
|
||
def time(self) -> list[FacetDiff]:
|
||
a, b, la, lb = self.a, self.b, self.la, self.lb
|
||
ca = list(_dedupe((t.column for t in a.time), self.k))
|
||
cb = list(_dedupe((t.column for t in b.time), self.k))
|
||
if any(self.unmatched(ca, cb, self.k)):
|
||
wa, wb = self.shown(ca, cb, text=self.named, full=lambda ps: self.named(ps, full=True))
|
||
if ca and cb:
|
||
text = _say(la, "按", wa, "筛时间，", lb, "按", wb)
|
||
elif ca:
|
||
text = _say(la, "按", wa, "筛时间，", lb, "没有按时间筛选")
|
||
else:
|
||
text = _say(la, "没有按时间筛选，", lb, "按", wb, "筛时间")
|
||
detail = {side: [{"table": p.columns[0][0], "column": p.columns[0][1]} for p in parts if p.columns]
|
||
for side, parts in (("a", ca), ("b", cb))}
|
||
# 时间列是从 CTE、子查询算出来的列透过去的（见 TimePredicate.column）：那一列的定义不同，这里已经说了
|
||
self.explained |= {v for t in (*a.time, *b.time) for v in t.via}
|
||
return [FacetDiff("time", "、".join(p.text for p in ca) or None, "、".join(p.text for p in cb) or None,
|
||
text, detail)]
|
||
only_a, only_b = self.unmatched(a.time, b.time, lambda t: self.k(t.condition))
|
||
conds_a, conds_b = [t.condition for t in only_a], [t.condition for t in only_b]
|
||
pairs = self.staged(conds_a, conds_b)
|
||
out = [FacetDiff("time_range", p.text, q.text, self.stage_text(p, q)) for p, q in pairs]
|
||
if conds_a or conds_b:
|
||
staged = {id(p) for pair in pairs for p in pair}
|
||
ra = [t.condition for t in a.time if id(t.condition) not in staged]
|
||
rb = [t.condition for t in b.time if id(t.condition) not in staged]
|
||
wa, wb = self.shown(ra, rb, text=lambda ps: " AND ".join(p.text for p in ps),
|
||
full=lambda ps: " AND ".join(p.full for p in ps))
|
||
out.append(FacetDiff("time_range", wa, wb, _say(la, "的时间范围是", wa, "，", lb, "是", wb)))
|
||
return out
|
||
|
||
def filters(self) -> list[FacetDiff]:
|
||
timed = {self.k(t.condition) for t in (*self.a.time, *self.b.time)}
|
||
fa = [p for p in self.a.where if self.k(p) not in timed]
|
||
fb = [p for p in self.b.where if self.k(p) not in timed]
|
||
only_a, only_b = self.unmatched(fa, fb, self.k)
|
||
# 先配同一个条件筛的先后不同的，再配同一列的不同写法（status = 'paid' 和 status IN (…)），再配读起来一样、
|
||
# 挂在不同来源上的同一个条件
|
||
out = [FacetDiff("filter", p.text, q.text, self.stage_text(p, q)) for p, q in self.staged(only_a, only_b)]
|
||
for p in list(only_a):
|
||
column = _single_column(p, loose=self.swapped)
|
||
mine = [q for q in only_a if column and _single_column(q, loose=self.swapped) == column]
|
||
theirs = [q for q in only_b if column and _single_column(q, loose=self.swapped) == column]
|
||
if len(mine) == 1 and len(theirs) == 1:
|
||
q = theirs[0]
|
||
wa, wb = self.shown([p], [q])
|
||
out.append(FacetDiff("filter", p.text, q.text, _say(self.la, "按", wa, "筛选，", self.lb, "按", wb, "筛选")))
|
||
only_a.remove(p)
|
||
only_b.remove(q)
|
||
for p, q in self.lookalikes(only_a, only_b):
|
||
wa, wb = self.shown([p], [q])
|
||
out.append(FacetDiff("filter", wa, wb, _say(self.la, "按", wa, "筛选，", self.lb, "按", wb, "筛选")))
|
||
out += [FacetDiff("filter", p.text, None, self.one_sided(self.la, self.lb, p)) for p in only_a]
|
||
out += [FacetDiff("filter", None, p.text, self.one_sided(self.lb, self.la, p)) for p in only_b]
|
||
return out
|
||
|
||
def aggregates(self) -> list[FacetDiff]:
|
||
la, lb = self.la, self.lb
|
||
|
||
def pair(xs: list[Aggregate], ys: list[Aggregate], same: Any) -> list[tuple[Aggregate, Aggregate]]:
|
||
pairs = []
|
||
for x in list(xs):
|
||
y = next((y for y in ys if same(x, y)), None)
|
||
if y is not None:
|
||
pairs.append((x, y))
|
||
xs.remove(x)
|
||
ys.remove(y)
|
||
return pairs
|
||
|
||
ga, gb = self.unmatched(self.a.aggregates, self.b.aggregates, self.agg_key)
|
||
self.reported = ({self.agg_key(g) for g in ga}, {self.agg_key(g) for g in gb})
|
||
# 先配参数相同的（同一列：函数或去重不同），再配函数相同的（同一种算法：列不同）；各剩一个的也配成一对
|
||
pairs = pair(ga, gb, lambda x, y: self.k(x.arg) == self.k(y.arg))
|
||
pairs += pair(ga, gb, lambda x, y: x.func == y.func)
|
||
if len(ga) == 1 and len(gb) == 1:
|
||
pairs.append((ga.pop(), gb.pop()))
|
||
out = []
|
||
for x, y in pairs:
|
||
same_arg = self.k(x.arg) == self.k(y.arg)
|
||
wa, wb = self.shown([x.arg], [y.arg]) if not same_arg else (x.arg.text, y.arg.text)
|
||
if same_arg and x.func == y.func:
|
||
# 只差去重：COUNT(DISTINCT order_id) 和 COUNT(order_id)
|
||
text = _say(la, "对", wa, _verb(x) + "，", lb, "没去重") if x.distinct \
|
||
else _say(la, "对", wa, _verb(x) + "时没去重，", lb, _verb(y))
|
||
elif same_arg and x.arg.key != "*":
|
||
# 同一列、算法不同：后半句不再重复列名
|
||
text = _say(la, "对", wa, _verb(x) + "，", lb, _verb(y))
|
||
else:
|
||
what_a = ["数的是行数"] if x.func == "count" and x.arg.key == "*" else ["对", wa, _verb(x)]
|
||
what_b = ["数的是行数"] if y.func == "count" and y.arg.key == "*" else ["对", wb, _verb(y)]
|
||
text = _say(la, *what_a, "，", lb, *what_b)
|
||
out.append(FacetDiff("aggregate", x.text, y.text, text))
|
||
out += [FacetDiff("aggregate", g.text, None, _say(la, "多算了", g.text, "，", lb, "没有")) for g in ga]
|
||
out += [FacetDiff("aggregate", None, g.text, _say(lb, "多算了", g.text, "，", la, "没有")) for g in gb]
|
||
return out
|
||
|
||
def expressions(self) -> list[FacetDiff]:
|
||
"""算出来的列（见 Computed）。最外层的按算法比，两边各自独有的按先后配成一对说「算的是什么」；派生来源里被
|
||
用到的列按两边配好对的编号和列名配，定义不同就报。只差在聚合上、聚合那一面已经报了的，按透过去的那一列
|
||
筛时间、时间那一面已经报了的，不再报一遍。"""
|
||
la, lb = self.la, self.lb
|
||
out: list[FacetDiff] = []
|
||
|
||
def aggs(c: Computed) -> list[str]:
|
||
return sorted(repr(self.agg_key(g)) for g in c.aggregates)
|
||
|
||
def pair(xs: list[Computed], ys: list[Computed], same: Any) -> list[tuple[Computed, Computed]]:
|
||
pairs = []
|
||
for x in list(xs):
|
||
y = next((y for y in ys if same(x, y)), None)
|
||
if y is not None:
|
||
pairs.append((x, y))
|
||
xs.remove(x)
|
||
ys.remove(y)
|
||
return pairs
|
||
|
||
xa = [c for c in self.a.expressions if c.scope_key is None]
|
||
xb = [c for c in self.b.expressions if c.scope_key is None]
|
||
only_a, only_b = self.unmatched(xa, xb, lambda c: self.k(c.expr))
|
||
# 先配用到的聚合一样的（同样的合计，算法不同：SUM(amount) 对 SUM(amount) / 100），再配算法一样的（聚合不同），
|
||
# 各剩一个的也配成一对
|
||
pairs = pair(only_a, only_b, lambda x, y: aggs(x) == aggs(y))
|
||
pairs += pair(only_a, only_b, lambda x, y: self.k(x.template) == self.k(y.template))
|
||
if len(only_a) == 1 and len(only_b) == 1:
|
||
pairs.append((only_a.pop(), only_b.pop()))
|
||
for x, y in pairs:
|
||
if not self.explained_by_aggregates(x, y):
|
||
wa, wb = self.shown([x.expr], [y.expr])
|
||
out.append(FacetDiff("expression", x.expr.text, y.expr.text,
|
||
_say(la, "算的是", wa, "，", lb, "算的是", wb)))
|
||
# 一边独有的光一个聚合不说：聚合那一面按整条语句比过了（另一边可能在子查询里算了同一个合计、外面只选那一列）
|
||
out += [FacetDiff("expression", c.expr.text, None, _say(la, "多算了", c.expr.text, "，", lb, "没有"))
|
||
for c in only_a if c.template.key != PLACEHOLDER]
|
||
out += [FacetDiff("expression", None, c.expr.text, _say(lb, "多算了", c.expr.text, "，", la, "没有"))
|
||
for c in only_b if c.template.key != PLACEHOLDER]
|
||
ib = {(c.scope_key, c.name): c for c in self.b.expressions if c.scope_key is not None}
|
||
for x in self.a.expressions:
|
||
y = ib.get((x.scope_key, x.name))
|
||
if x.scope_key is None or y is None or self.k(x.expr) == self.k(y.expr) or \
|
||
f"{x.scope_key}.{x.name}" in self.explained:
|
||
continue
|
||
# 两边起名不同、按位置配成同一列的（见 _renamed）照报：聚合那一面只说了合计不同，没说外面用的是这一列
|
||
if name_key(y.shown) == y.name and self.explained_by_aggregates(x, y):
|
||
continue
|
||
wa, wb = self.shown([x.expr], [y.expr])
|
||
ca, cb = f"{x.scope}.{x.shown}", f"{y.scope}.{y.shown}"
|
||
out.append(FacetDiff("expression", wa, wb,
|
||
_say(la, "的", ca, "是", wa, "，", lb, *(("是",) if ca == cb else ("的", cb, "是")), wb)))
|
||
return out
|
||
|
||
def explained_by_aggregates(self, x: Computed, y: Computed) -> bool:
|
||
"""两边的算法只差在里面的聚合上（聚合换成占位符之后一样），差的那几个聚合聚合那一面又都报了：不再报一遍。
|
||
聚合的集合一样、只是换了位置（SUM(a) - SUM(b) 对 SUM(b) - SUM(a)），聚合那一面什么也没报，照报。"""
|
||
if self.k(x.template) != self.k(y.template) or len(x.aggregates) != len(y.aggregates):
|
||
return False
|
||
ka, kb = self.reported
|
||
differing = [(g, h) for g, h in zip(x.aggregates, y.aggregates) if self.agg_key(g) != self.agg_key(h)]
|
||
return bool(differing) and all(self.agg_key(g) in ka or self.agg_key(h) in kb for g, h in differing)
|
||
|
||
def joins(self) -> list[FacetDiff]:
|
||
"""连接：先把完全一样的两边配掉，剩下的按关联的是哪张表（派生来源按配好的编号）、再按涉及的来源配成一对，
|
||
说类型、主表或条件哪里不同，再剩下的是只有一边关联了（多出来的是哪个来源见 added）。
|
||
|
||
完全一样：内连接、CROSS JOIN 比类型、涉及的来源和条件（FROM paid JOIN refunded 和 FROM refunded JOIN paid 是
|
||
同一次连接）；LEFT / RIGHT JOIN 比主表、涉及的来源和条件，不比写的是 LEFT 还是 RIGHT（orders LEFT JOIN refunds
|
||
和 refunds RIGHT JOIN orders 是同一次连接，和 refunds LEFT JOIN orders 不是）；FULL JOIN 比涉及的来源和条件；
|
||
其余（SEMI、ANTI、NATURAL）比类型、关联进来的表和条件。外连接被同一段 WHERE 里的条件筛掉了没关联上的行
|
||
（JoinFacet.rejects）按内连接比：写的是 LEFT JOIN、实际是内连接，和另一边真的 LEFT JOIN 要报出来，和另一边写的
|
||
INNER JOIN 是一回事。先配完全一样的，同一张表关联了两次、先后不同也不算不同。配成一对的两边名字不同（两边给
|
||
CTE 起的名字不同、内连接换了先后）时两个名字都说。派生来源已经按结构配好了编号：一边多出来的 CTE 编号和
|
||
另一边的都不一样，不会被配给另一边不相干的 CTE、说成「关联条件不同」。
|
||
|
||
做不到的：内连接里只涉及一张表的条件写在 ON 里还是 WHERE 里意思一样，仍算两处不同；三张以上不带关联条件的
|
||
表（逗号连接、CROSS JOIN）换了先后，涉及的来源按「它之前的各个来源」算，仍可能算不同；外连接链（a LEFT JOIN b
|
||
LEFT JOIN c）的主表按关联条件里出现的来源算，不按整个左边算；WHERE 筛掉了 c 没关联上的行时，c 是按 b 的列关联的，
|
||
b 没关联上的行连带也没了，前面那次 LEFT JOIN 其实也成了内连接，这里只认后面那次；FULL JOIN 被 WHERE 筛掉一边的
|
||
不认。"""
|
||
la, lb = self.la, self.lb
|
||
|
||
def effective(j: JoinFacet) -> str:
|
||
return "inner" if j.rejects is not None and j.kind in ("left", "right") else j.kind
|
||
|
||
def same(j: JoinFacet) -> tuple[Any, ...]:
|
||
kind = effective(j)
|
||
if kind in ("inner", "cross"):
|
||
return kind, self.sides(j), self.k(j.on)
|
||
if kind in ("left", "right"):
|
||
return "outer", self.keys(j.keep), self.sides(j), self.k(j.on)
|
||
if kind == "full":
|
||
return kind, self.sides(j), self.k(j.on)
|
||
return kind, j.table.key, self.k(j.on)
|
||
|
||
rest_a, rest_b = self.unmatched(self.a.joins, self.b.joins, same)
|
||
pairs: list[tuple[JoinFacet, JoinFacet]] = []
|
||
for table in (lambda j: j.table.key, self.sides):
|
||
for x in list(rest_a):
|
||
y = next((y for y in rest_b if table(y) == table(x)), None)
|
||
if y is not None:
|
||
pairs.append((x, y))
|
||
rest_a.remove(x)
|
||
rest_b.remove(y)
|
||
out: list[FacetDiff] = []
|
||
for x, y in pairs:
|
||
tx, ty = x.table.text, y.table.text
|
||
ex, ey = effective(x), effective(y)
|
||
outer_x, outer_y = ex in ("left", "right"), ey in ("left", "right")
|
||
if outer_x and outer_y:
|
||
if self.keys(x.keep) != self.keys(y.keep):
|
||
wa, wb = self.outer(x, 0), self.outer(y, 1)
|
||
out.append(FacetDiff("join", wa, wb, _say(la, wa, "，", lb, wb)))
|
||
elif (outer_x and y.rejects is not None) or (outer_y and x.rejects is not None):
|
||
wa = self.outer(x, 0) if outer_x else self.rejected(x, 0)
|
||
wb = self.outer(y, 1) if outer_y else self.rejected(y, 1)
|
||
out.append(FacetDiff("join", self.outer(x, 0) if outer_x else _JOIN_WORDS[x.kind] + "（实际是 INNER JOIN）",
|
||
self.outer(y, 1) if outer_y else _JOIN_WORDS[y.kind] + "（实际是 INNER JOIN）",
|
||
_say(la, wa, "，", lb, wb)))
|
||
elif ex != ey:
|
||
kx, ky = _JOIN_WORDS.get(x.kind, x.kind), _JOIN_WORDS.get(y.kind, y.kind)
|
||
tail = () if ty == tx else ("关联", ty, "表")
|
||
out.append(FacetDiff("join", kx, ky, _say(la, "用", kx, "关联", tx, "表，", lb, "用", ky, *tail)))
|
||
if self.k(x.on) != self.k(y.on):
|
||
xa, ya = (x.on.text if x.on else "（无条件）"), (y.on.text if y.on else "（无条件）")
|
||
tail = ("是", ya) if ty == tx else ("关联", ty, "表的条件是", ya)
|
||
out.append(FacetDiff("join", xa, ya, _say(la, "关联", tx, "表的条件是", xa, "，", lb, *tail)))
|
||
said: dict[str, set[str]] = {"a": set(), "b": set()}
|
||
for side, rest, mine, theirs in (("a", rest_a, self.a, self.b), ("b", rest_b, self.b, self.a)):
|
||
me, other = (la, lb) if side == "a" else (lb, la)
|
||
for j in rest:
|
||
name, keys = self.added(j, mine, theirs)
|
||
said[side] |= keys
|
||
out.append(FacetDiff("join", name if side == "a" else None, name if side == "b" else None,
|
||
_say(me, "关联了", name, "表，", other, "没有")))
|
||
# 关联之外的表（FROM 的表、子查询里的表）只在一边出现的；上面已经说过「关联了它」的不再说一遍
|
||
if self.swapped:
|
||
ta, tb = self.ta[0], self.tb[0]
|
||
return out + [FacetDiff("tables", ta.text, tb.text, _say(la, "查的是", ta.text, "表，", lb, "查的是", tb.text,
|
||
"表"))]
|
||
out += [FacetDiff("tables", t.text, None, _say(la, "用到了", t.text, "表，", lb, "没有"))
|
||
for t in self.ta if t.key not in said["a"]]
|
||
out += [FacetDiff("tables", None, t.text, _say(lb, "用到了", t.text, "表，", la, "没有"))
|
||
for t in self.tb if t.key not in said["b"]]
|
||
return out
|
||
|
||
def called_as(self, keys: Iterable[str], side: int) -> str:
|
||
"""来源 key → 给人看的名字（那一边的叫法），几个用顿号隔开。"""
|
||
return "、".join(self.called[side].get(k, k) for k in keys)
|
||
|
||
def outer(self, j: JoinFacet, side: int) -> str:
|
||
"""一次 LEFT / RIGHT JOIN 保留哪一侧：「以 orders 为主表外连接 refunds」。不说 LEFT 还是 RIGHT：orders RIGHT
|
||
JOIN refunds 保留的是 refunds，照写关键字反倒容易读反。"""
|
||
return _say("以", self.called_as(j.keep, side), "为主表外连接", self.called_as(j.nullable, side))
|
||
|
||
def rejected(self, j: JoinFacet, side: int) -> str:
|
||
"""写的是外连接、WHERE 里的条件又把没关联上的行筛掉了（见 JoinFacet.rejects）。"""
|
||
word = _JOIN_WORDS.get(j.kind, j.kind)
|
||
cond = j.rejects.full if j.rejects is not None else ""
|
||
return _say("的 WHERE 里有", cond, "，把关联不上", self.called_as(j.nullable, side), "的行筛掉了，", word,
|
||
"实际成了 INNER JOIN")
|
||
|
||
def group(self) -> list[FacetDiff]:
|
||
a, b = self.a.group_by, self.b.group_by
|
||
if not any(self.unmatched(a, b, self.k)):
|
||
return []
|
||
wa, wb = self.shown(list(a), list(b))
|
||
if a and b:
|
||
text = _say(self.la, "按", wa, "分组，", self.lb, "按", wb, "分组")
|
||
elif a:
|
||
text = _say(self.la, "按", wa, "分组，", self.lb, "没有分组")
|
||
else:
|
||
text = _say(self.la, "没有分组，", self.lb, "按", wb, "分组")
|
||
return [FacetDiff("group_by", wa or None, wb or None, text)]
|
||
|
||
def having(self) -> list[FacetDiff]:
|
||
only_a, only_b = self.unmatched(self.a.having, self.b.having, self.k)
|
||
out = []
|
||
for p, q in self.lookalikes(only_a, only_b):
|
||
wa, wb = self.shown([p], [q])
|
||
out.append(FacetDiff("having", wa, wb, _say(self.la, "分组后只保留", wa, "的组，", self.lb, "只保留", wb,
|
||
"的组")))
|
||
return out + \
|
||
[FacetDiff("having", p.text, None, self.one_sided(self.la, self.lb, p, group=True)) for p in only_a] + \
|
||
[FacetDiff("having", None, p.text, self.one_sided(self.lb, self.la, p, group=True)) for p in only_b]
|
||
|
||
def limit(self) -> list[FacetDiff]:
|
||
"""取哪几行：最外层两边比；CTE、子查询里的按所属派生来源配好的编号（LimitFacet.scope_key）配成一对，两边给
|
||
它起的名字可以不同。配不上的派生来源各说各的，不按先后凑对：一边多一个限了行数的 CTE，不能拿它和另一边的
|
||
CTE 比。不属于哪个派生来源整段的（UNION 的某一支这类）按出现的先后配。"""
|
||
def outer(f: Facets) -> LimitFacet | None:
|
||
return next((x for x in f.limits if x.scope is None), None)
|
||
|
||
out = self.rows(outer(self.a), outer(self.b))
|
||
ia = [x for x in self.a.limits if x.scope is not None]
|
||
ib = [x for x in self.b.limits if x.scope is not None]
|
||
pairs: list[tuple[LimitFacet | None, LimitFacet | None]] = []
|
||
for x in list(ia):
|
||
y = next((y for y in ib if x.scope_key is not None and y.scope_key == x.scope_key), None)
|
||
if y is not None:
|
||
pairs.append((x, y))
|
||
ia.remove(x)
|
||
ib.remove(y)
|
||
pairs += zip_longest([x for x in ia if x.scope_key is None], [y for y in ib if y.scope_key is None])
|
||
pairs += [(x, None) for x in ia if x.scope_key is not None]
|
||
pairs += [(None, y) for y in ib if y.scope_key is not None]
|
||
for x, y in pairs:
|
||
out += self.rows(x, y)
|
||
return out
|
||
|
||
def lk(self, x: LimitFacet | None) -> tuple[Any, ...] | None:
|
||
"""一段取哪几行的比较用写法：行数、跳过的行数、排序键。"""
|
||
if x is None:
|
||
return None
|
||
return x.count, x.offset, tuple((self.k(p), desc) for p, desc in x.order)
|
||
|
||
def sorting(self, x: LimitFacet, *, full: bool = False) -> str:
|
||
if not x.order:
|
||
return "没有排序"
|
||
keys = "、".join(_say(p.full if full else p.text, "降序" if desc else "升序") for p, desc in x.order)
|
||
return _say("按", keys, "排")
|
||
|
||
def rows(self, x: LimitFacet | None, y: LimitFacet | None) -> list[FacetDiff]:
|
||
"""一对段（一边可以没有）取的行有什么不同：行数、跳过的行数，两边都限了行时再比排序。"""
|
||
if self.lk(x) == self.lk(y):
|
||
return []
|
||
sa, sb = (x.scope if x else None), (y.scope if y else None)
|
||
la = _say(self.la, "在", sa, "里") if sa else self.la
|
||
lb = _say(self.lb, "在", sb, "里") if sb and sb != sa else self.lb
|
||
out = []
|
||
ca, cb = (x.count if x else None), (y.count if y else None)
|
||
if ca != cb:
|
||
out.append(FacetDiff("limit", ca, cb, _say(la, _rows(ca), "，", lb, _rows(cb))))
|
||
oa, ob = (x.offset if x else None), (y.offset if y else None)
|
||
if oa != ob:
|
||
out.append(FacetDiff("limit", oa, ob, _say(la, _skip(oa), "，", lb, _skip(ob))))
|
||
if x is not None and y is not None and self.lk(x)[2] != self.lk(y)[2]:
|
||
wa, wb = self.sorting(x), self.sorting(y)
|
||
if wa == wb:
|
||
wa, wb = self.sorting(x, full=True), self.sorting(y, full=True)
|
||
if wa == wb:
|
||
wa, wb = self.annotated(wa, wb, [p for p, _ in x.order], [p for p, _ in y.order])
|
||
out.append(FacetDiff("limit", wa, wb, _say(la, "取行前", wa, "，", lb, wb)))
|
||
return out
|
||
|
||
|
||
def diff_facets(a: Facets, b: Facets, labels: tuple[str, str] = ("A", "B"), *,
|
||
names: Mapping[str, str] | None = None) -> list[FacetDiff]:
|
||
"""逐个方面比两份 facets，每处不同一条，按对结果影响大致从大到小排：时间、筛选、聚合、算出来的列、连接和表、
|
||
分组、HAVING、取哪几行。完全一致返回空列表。
|
||
|
||
labels 是两边的叫法（缺省 A / B，双盲复算可以传「原流程」「盲算」）；names 是列的中文名（{「表.列」或「列」:
|
||
中文名}，可以用 catalog_labels 从数据目录取），给了的话时间列写成「支付时间 paid_at」。任一边解析不了就只返回
|
||
一条 parse，不逐项比较：拿半份结构去比，只会报出一堆不存在的不同。
|
||
|
||
比之前先把两边的派生来源按结构配好对，按共同的编号重新分析两边（见模块说明、_aligned）；给人看的写法不受影响。
|
||
"""
|
||
la, lb = labels
|
||
if a.parse_error or b.parse_error:
|
||
if a.parse_error and b.parse_error:
|
||
text = _say(la, "：", a.parse_error, "；", lb, "：", b.parse_error, "；没有逐项比较")
|
||
else:
|
||
side, error = (la, a.parse_error) if a.parse_error else (lb, b.parse_error)
|
||
text = _say(side, "：", error or "", "，没有逐项比较")
|
||
return [FacetDiff("parse", a.parse_error, b.parse_error, text)]
|
||
cmp = _Compare(*_aligned(a, b), labels, names)
|
||
return cmp.time() + cmp.filters() + cmp.aggregates() + cmp.expressions() + cmp.joins() + cmp.group() + \
|
||
cmp.having() + cmp.limit()
|
||
|
||
|
||
def _aligned(a: Facets, b: Facets) -> tuple[Facets, Facets]:
|
||
"""b 的派生来源按结构配给 a 的（见 _align），配上的改写成 a 里对应的编号、配不上的另起 a 里没有的编号，按这套
|
||
编号重新分析两边的原文（a 的编号就是它的位置编号）。
|
||
|
||
没用到的 CTE 不收进 facets（见 _Statement._enliven），只有一种例外：两边都定义了同一个 CTE（配成了一对），一边
|
||
用到、一边没用到，而用到的那边是把它关联进来的。连接那一面会说「X 关联了它，Y 没有」；它里面的条件、聚合两边的
|
||
定义里都有，只收用到的那一边，就会再被说成一边独有的一堆条件、聚合（两边都定义了付款、退款两个 CTE，一边关联
|
||
付款的、一边关联退款的）。这时没用到的那一边也照样收它。用到的那边是从它取数（FROM 它）而不是关联它时不收：
|
||
盲算定义了只筛已付的 CTE 却直接查 orders，少的那个条件正要报出来。
|
||
|
||
任一边不是 facets 算出来的（没记原文）、重新解析不了，或者分析时出了意外，照原样返回：两边仍按各自的位置编号
|
||
比，一边多出排在前面的 CTE 时会多报。
|
||
"""
|
||
try:
|
||
sa, sb = _Statement.reparse(a), _Statement.reparse(b)
|
||
if sa is None or sb is None:
|
||
return a, b
|
||
da, db = sa.derived(), sb.derived()
|
||
pairs = _align(da, db)
|
||
fresh = iter(range(max((d.number for d in da), default=0) + 1, 1 << 30))
|
||
sb.relabel({d.number: f"@{pairs[d.number]}" if d.number in pairs else f"@{next(fresh)}" for d in db},
|
||
_renamed(da, db, pairs))
|
||
fa, fb = sa.facets(), sb.facets()
|
||
extra_a = _switched(sb, fb, sa)
|
||
extra_b = _switched(sa, fa, sb)
|
||
if extra_a or extra_b:
|
||
fa, fb = sa.facets(extra_a), sb.facets(extra_b)
|
||
return replace(fa, _origin=a._origin), replace(fb, _origin=b._origin)
|
||
except Exception: # noqa: BLE001 - 配对本身的缺陷不能连累比较：退回按各自的编号比，记下来修
|
||
logger.warning("SQL 派生来源配对失败，按各自的位置编号比较", exc_info=True)
|
||
return a, b
|
||
|
||
|
||
def _switched(user: "_Statement", facets_of_user: Facets, other: "_Statement") -> set[str]:
|
||
"""user 用到、而且关联进来了的派生来源里，other 也定义了（配成了一对）却没用到的 CTE：other 照样收它（见
|
||
_aligned）。返回 other 里这些 CTE 的 name_key。"""
|
||
joined = {k for j in facets_of_user.joins for k in (*j.sides, j.table.key)}
|
||
used, defined = other.used_labels(), other.defined_labels()
|
||
return {cte for label in user.used_labels() if label in joined and label not in used
|
||
and (cte := defined.get(label)) is not None}
|
||
|
||
|
||
__all__ = ["MAX_SQL_CHARS", "PLACEHOLDER", "Aggregate", "ColumnRef", "Computed", "FacetDiff", "Facets", "JoinFacet",
|
||
"LimitFacet", "NormalizedSql", "Part", "TimePredicate", "catalog_labels", "diff_facets", "facets",
|
||
"normalize_sql"]
|