SQL Parser Guide: Tokens, ASTs, Dialects, and Errors SQL 解析器：Token、AST、方言与错误诊断

What is an SQL parser?什么是 SQL 解析器？

Parsing is structural, not execution. A successful parse does not prove that a table exists, a column is unambiguous, types are compatible, a function signature is valid, permissions allow access, a query is read-only, a result is correct, or execution is affordable. Those claims require binding, semantic validation, schema context, policy analysis, planning, or controlled execution.

解析关注结构，而不是执行。解析成功不能证明表存在、列无歧义、类型兼容、函数签名有效、权限允许、查询只读、结果正确或执行成本可接受。这些声明需要绑定、语义验证、模式上下文、策略分析、规划或受控执行。

Trace the pipeline from raw text to a usable tree追踪从原始文本到可用语法树的流水线

“Parse SQL” often hides several stages. An application may normalize line endings, remove a byte-order mark, expand templates, split a script, tokenize characters, apply grammar rules, build a parse tree, transform it into an AST, attach source metadata, recover from errors, and run post-parse normalization. Each stage can change what downstream tools see.

“解析 SQL”经常隐藏多个阶段。应用可能先规范换行、移除字节序标记、展开模板、切分脚本，再把字符 Token 化、应用语法规则、构建解析树、转换为 AST、附加源码元数据、从错误恢复，并执行解析后规范化。每个阶段都会改变下游工具看到的内容。

PostgreSQL’s official parser-stage documentation distinguishes lexical recognition and grammar parsing from a later transformation process. That separation is broadly useful: a raw syntax tree and a semantically augmented query representation answer different questions and should not be labeled interchangeably.

PostgreSQL 官方的解析阶段文档区分词法识别、语法解析与后续转换过程。这种区分具有普遍价值：原始语法树与经过语义增强的查询表示回答不同问题，不应使用相同标签混淆。

Separate parsing, validation, planning, and execution claims区分解析、验证、规划与执行声明

A parser answers “Can this text be represented by this grammar?” A validator may answer “Do referenced names and types make sense in this schema and policy context?” A planner asks “How could the database execute the validated operation?” An executor performs work. Tools sometimes collapse these stages into one green check, which creates false confidence.

解析器回答“这段文本能否由该语法表示？”验证器可能回答“引用名称与类型在此模式和策略上下文中是否合理？”规划器回答“数据库如何执行已验证操作？”执行器真正完成工作。部分工具把这些阶段合并为一个绿色勾选，从而制造错误信心。

A syntax-only parser should display “parsed,” not “valid” or “safe.” If a tool enriches the tree with schema or executes a dry run, state the data source, identity, freshness, permissions, and side-effect boundary. The same-batch SQL query validator guide covers the broader validation contract.

纯语法解析器应显示“已解析”，而不是“有效”或“安全”。如果工具使用模式增强语法树或执行 dry run，应说明数据来源、身份、新鲜度、权限与副作用边界。同批次的 SQL 查询验证器指南将覆盖更广泛的验证契约。

Define the exact text and preprocessing boundary定义准确文本与预处理边界

The parser may never see the text visible to the user. Applications can expand `${variable}` placeholders, replace templated blocks, strip comments, normalize quotes, resolve notebook cells, include other files, convert named parameters, rewrite client commands, or split batches first. Parse diagnostics then refer to transformed text unless the system maintains a source map.

解析器可能从未看到用户眼中的原始文本。应用可能先展开 `${variable}` 占位符、替换模板块、删除注释、规范引号、解析笔记本单元、包含其他文件、转换命名参数、重写客户端命令或切分批次。如果系统没有维护源码映射，解析诊断就会指向转换后文本。

Preserve both raw and normalized input where policy permits, with secrets redacted. If a parser accepts pre-tokenized input, document token provenance. Diagnostics and rewrite tools cannot be trusted when source locations silently drift.

在策略允许时保留原始与规范化输入，并去除密钥。如果解析器接受预先 Token 化输入，应记录 Token 来源。源码位置静默漂移时，诊断与重写工具都不可信。

Evaluate the lexer before judging the syntax tree评价语法树前先评价词法器

The lexer turns characters into tokens such as keywords, identifiers, quoted identifiers, string and numeric literals, parameter markers, operators, punctuation, comments, whitespace, and dialect-specific constructs. If token boundaries or kinds are wrong, the grammar receives the wrong language. Lexing is especially sensitive to quoting, escape modes, nested comments, dollar-quoted bodies, Unicode, multi-character operators, and keywords that can also act as identifiers.

词法器把字符转换为关键字、标识符、引用标识符、字符串与数字字面值、参数标记、运算符、标点、注释、空白及方言特有结构等 Token。如果边界或类别错误，语法器接收到的就是错误语言。引用、转义模式、嵌套注释、美元引用过程体、Unicode、多字符运算符，以及可同时充当标识符的关键字尤其敏感。

Expose token kind, raw slice, normalized value, quote metadata, start and end offsets, line and column, and channel or trivia status. Redact literal values only in a separate presentation layer; altering tokens before parsing changes the input.

应暴露 Token 类别、原始切片、规范值、引用元数据、起止偏移、行列与通道或附属状态。字面值脱敏应在独立展示层完成；解析前改变 Token 会改变输入。

Treat dialect configuration as part of the parse result把方言配置视为解析结果的一部分

A grammar defines valid statement forms, clause order, expression precedence, associativity, reserved words, extensions, and ambiguity resolution. “ANSI SQL” is rarely sufficient because products support different standard levels and extensions. Some parsers offer strict, lenient, or vendor conformance modes; leniency can increase coverage while hiding unsupported syntax.

语法定义有效语句形式、子句顺序、表达式优先级、结合性、保留字、扩展与歧义解决方式。“ANSI SQL”通常不够，因为产品支持不同标准级别与扩展。部分解析器提供严格、宽松或厂商一致性模式；宽松模式可以提高覆盖，却也可能隐藏不支持语法。

Apache Calcite’s official SQL language reference describes the grammar accepted by its default parser and identifies constructs allowed only at certain conformance levels. A parser result should carry this configuration so another system cannot silently reinterpret the same text under a different grammar.

Apache Calcite 官方的 SQL 语言参考描述其默认解析器接受的语法，并指出部分结构只在特定一致性级别允许。解析结果应携带这些配置，避免另一个系统在不同语法下静默重新解释相同文本。

Define what the abstract syntax tree preserves and discards定义抽象语法树保留与丢弃什么

An AST represents meaningful constructs rather than every character. Parentheses may be represented through tree shape; keywords and commas may disappear; aliases, quote flags, comments, hints, and source spans may be attached selectively; equivalent syntax may normalize to one node form. This is useful for analysis but risky for exact rewriting unless the fidelity contract is explicit.

AST 表示有意义的结构，而不是每个字符。括号可能通过树形表示；关键字与逗号可能消失；别名、引用标志、注释、Hint 与源码范围可能只选择性附加；等价语法还可能规范成一种节点形式。这有利于分析，但若没有明确保真契约，用于精确重写会有风险。

Version the AST schema independently from the parser package if other systems persist or exchange it. Adding a node kind, changing child order, normalizing aliases, or altering source-span semantics can break policies and lineage even when parsing still succeeds.

如果其他系统会持久化或交换 AST，应独立于解析器包对 AST 模式进行版本控制。新增节点类型、改变子节点顺序、规范别名或修改源码范围语义，即使解析仍成功，也可能破坏策略与血缘。

Require precise source spans for every material node为每个关键节点提供精确源码范围

Source spans connect the tree back to the text. They power diagnostics, syntax highlighting, hover details, code actions, policy findings, diffs, refactoring, and review. A node may need a full range, a name range, keyword ranges, delimiter ranges, and ranges for child lists. One coarse statement span is not enough for a safe automated edit.

源码范围把语法树重新连接到文本，为诊断、语法高亮、悬停详情、代码操作、策略发现、差异、重构与审查提供基础。一个节点可能需要完整范围、名称范围、关键字范围、分隔符范围与子列表范围。只有粗粒度语句范围不足以支持安全自动编辑。

Store offset units and indexing base in the API contract. Do not infer them from examples. Verify spans after every preprocessing step and AST normalization. A diagnostic that highlights the wrong identifier can cause a developer to “fix” valid text.

API 契约中应记录偏移单位与索引起点，不能从示例猜测。每个预处理步骤与 AST 规范化后都要验证范围。高亮错误标识符的诊断可能导致开发者“修复”原本有效的文本。

Preserve comments, hints, and whitespace according to purpose按用途保留注释、Hint 与空白

Whitespace and comments are often called trivia because they do not change the core grammar. They can still carry optimizer hints, tool directives, lineage annotations, suppression markers, ticket references, ownership notes, and review rationale. Removing them may change execution or governance even when the AST looks equivalent.

空白与注释常被称为附属文本，因为它们通常不改变核心语法。但它们仍可能包含优化器 Hint、工具指令、血缘注解、抑制标记、工单引用、归属说明与审查理由。即使 AST 看似等价，删除它们也可能改变执行或治理。

Classify hints and directives separately from ordinary prose comments. If an unparser relocates a hint, test whether the target engine still interprets it. Never claim semantic equivalence after comment removal without understanding dialect behavior.

Hint 与指令应和普通说明注释分开分类。如果反解析器移动 Hint，应测试目标引擎是否仍按原意解释。不了解方言行为时，不能在删除注释后声称语义等价。

Parse scripts with grammar-aware statement boundaries使用感知语法的边界解析脚本

Splitting on every semicolon fails when semicolons appear inside strings, comments, procedural bodies, dynamic SQL, or vendor constructs. Some clients support custom delimiters, batch separators, meta-commands, includes, or notebook cell boundaries. The script parser must distinguish server SQL from client directives and report incomplete trailing input.

简单按每个分号切分会在字符串、注释、过程体、动态 SQL 或厂商结构中失败。部分客户端支持自定义分隔符、批次分隔符、元命令、包含文件或笔记本单元边界。脚本解析器必须区分服务器 SQL 与客户端指令，并报告不完整尾部输入。

Return statement and batch ranges, delimiter metadata, client-directive nodes, and an explicit completeness flag. A formatter or policy engine must know whether it received one complete statement, a script, or a fragment.

输出应包含语句与批次范围、分隔符元数据、客户端指令节点与显式完整性标志。格式化器或策略引擎必须知道收到的是完整单语句、脚本还是片段。

Return structured diagnostics that identify cause and location返回能够识别原因与位置的结构化诊断

A useful syntax diagnostic is more than “parse failed.” It identifies an unexpected token or input region, expected token classes or grammar context, severity, stage, source range, related ranges, recovery action, and whether a tree remains usable. The human message should be derived from structured fields so interfaces can localize, sort, suppress, and test it.

有用语法诊断不只是“解析失败”，还应指出意外 Token 或输入区域、预期 Token 类别或语法上下文、严重级别、阶段、源码范围、相关范围、恢复动作，以及语法树是否仍可用。人类消息应由结构化字段生成，使界面能够本地化、排序、抑制与测试。

Do not promise the one true fix. After an unexpected token, several repairs may be valid. Offer grammar-grounded suggestions and label them as candidates. Preserve the raw parser error for debugging while presenting a concise user message.

不要承诺唯一正确修复。遇到意外 Token 后可能存在多种合法修复。建议应基于语法，并明确标为候选。保留原始解析错误用于调试，同时展示简洁用户消息。

Make recovered trees visibly different from clean trees让恢复语法树与干净语法树明显不同

Editors need partial trees while a user is typing; batch validators may prefer fail-fast behavior. Recovery strategies can insert an expected token, delete an unexpected token, skip to a synchronization point, wrap raw text in an error node, or choose one branch of an ambiguity. Recovery enables continued analysis but introduces parser-created structure not present in the source.

编辑器在用户输入时需要部分语法树，批量验证器则可能更适合快速失败。恢复策略可以插入预期 Token、删除意外 Token、跳到同步点、把原始文本包进错误节点，或在歧义中选择一个分支。恢复使分析得以继续，却会引入源码中不存在的解析器结构。

Downstream security, lineage, and rewrite systems should default to refusing consequential conclusions from recovered regions. A formatter may print them, and an editor may navigate them, but a policy engine must not treat guessed structure as proven syntax.

下游安全、血缘与重写系统默认不应从恢复区域得出重大结论。格式化器可以打印它们，编辑器可以导航它们，但策略引擎不能把猜测结构当作已证明语法。

Measure incremental parsing by correctness before latency增量解析应先衡量正确性，再衡量延迟

Interactive tools reparse as a user types. Incremental parsers reuse unchanged tokens or subtrees, while simpler systems reparse the whole document. Reuse reduces latency but requires valid invalidation when an edit changes lexical mode, delimiter balance, statement boundary, alias scope, or dialect interpretation far from the cursor.

交互工具会在用户输入时持续重解析。增量解析器复用未变化 Token 或子树，而简单系统重解析整个文档。复用降低延迟，却要求在编辑改变词法模式、分隔符平衡、语句边界、别名作用域或远处方言解释时正确失效。

Build a differential test that applies random and recorded editor operations, compares the incremental tree and diagnostics with a fresh full parse, and checks source spans. Fast stale trees are worse than slower correct trees.

应构建差分测试：应用随机与记录的编辑操作，把增量语法树和诊断与全新完整解析比较，并检查源码范围。快速但过期的语法树比稍慢但正确的树更糟。

Preserve identifier, parameter, and literal distinctions保留标识符、参数与字面值之间的区别

Many downstream errors begin when a parser normalizes away distinctions that matter later. An identifier needs original spelling, quote style, quote escapes, case-folding status, and qualification parts. A parameter needs marker style, position or name, and source range. A literal needs raw text, literal kind, prefixes, and decoded value without losing precision or executing conversion logic unsafely.

许多下游错误始于解析器过度规范化，丢失后续重要区别。标识符需要原始拼写、引用样式、引用转义、大小写折叠状态与限定部分。参数需要标记样式、位置或名称以及源码范围。字面值需要原始文本、类型、前缀与解码值，同时不能丢失精度或不安全执行转换逻辑。

Redaction should replace literal presentation after parsing, not mutate the AST used for analysis unless the transformation is explicit and type-aware. A redacted tree is a different artifact and needs its own provenance.

脱敏应在解析后替换字面值展示，不应静默修改分析使用的 AST，除非转换显式且感知类型。脱敏语法树是不同制品，需要自己的来源记录。

Measure coverage beyond simple SELECT statements衡量简单 SELECT 之外的覆盖

A parser can advertise a dialect while supporting only common queries. Real repositories contain DDL, DML, MERGE, COPY or load commands, grants, comments, transactions, session settings, explain commands, procedural functions, triggers, dynamic SQL, scripting variables, warehouse clauses, hints, semi-structured paths, and vendor extensions. Coverage must be stated by construct and version.

解析器可能宣称支持某方言，却只支持常见查询。真实仓库还包含 DDL、DML、MERGE、COPY 或加载命令、授权、注释、事务、会话设置、执行计划命令、过程函数、触发器、动态 SQL、脚本变量、仓库子句、Hint、半结构化路径与厂商扩展。覆盖必须按结构与版本说明。

Publish unsupported constructs and fallback behavior. Returning a generic raw node can be acceptable when clearly marked; silently coercing a vendor clause into a superficially similar standard node is more dangerous because downstream tools assume understanding.

应公开不支持结构与回退行为。若明确标记，返回通用原始节点可以接受；把厂商子句静默强制成表面相似的标准节点更危险，因为下游工具会假定解析器理解其含义。

Evaluate AST traversal with scope and context在作用域与上下文中评价 AST 遍历

A tree visitor can collect every table-looking or column-looking node, but the same syntax has different roles in CTE definitions, subqueries, aliases, function arguments, windows, insert targets, update assignments, merge branches, and correlated references. Useful traversal APIs expose parent, child role, statement, clause, scope boundary, and source range.

语法树访问器可以收集每个看起来像表或列的节点，但相同语法在 CTE 定义、子查询、别名、函数参数、窗口、插入目标、更新赋值、MERGE 分支与相关引用中扮演不同角色。有用遍历 API 应暴露父节点、子角色、语句、子句、作用域边界与源码范围。

Provide typed child roles instead of relying only on list position. Visitors should be able to skip recovered or unknown subtrees, preserve traversal order, and report uncertainty. Test nested scopes and shadowed names even if the parser itself does not bind them.

应提供类型化子角色，而不是只依赖列表位置。访问器应能跳过恢复或未知子树、保持遍历顺序并报告不确定性。即使解析器本身不绑定名称，也要测试嵌套作用域与名称遮蔽。

Do not confuse table-shaped nodes with resolved catalog objects不要把表形节点与已解析目录对象混淆

The AST can say that the source contains a relation reference named orders. Without a catalog and scope rules, it cannot prove whether that name refers to a CTE, local temporary table, view, materialized view, synonym, table function, remote object, or physical table; nor which database and schema resolve an unqualified name.

AST 可以说明源码包含名为 orders 的关系引用，但没有目录与作用域规则时，无法证明它指向 CTE、本地临时表、视图、物化视图、同义词、表函数、远程对象还是物理表，也无法确定未限定名称解析到哪个数据库和模式。

Downstream APIs should name syntax references differently from resolved symbols. Preserve the original node and attach resolution separately with catalog version, scope, identity, and confidence. This prevents stale binding from being mistaken for parser truth.

下游 API 应把语法引用与已解析符号使用不同名称。保留原始节点，并把解析结果以目录版本、作用域、身份与置信信息单独附加，防止过期绑定被误认为解析器事实。

Use the AST as lineage input, not lineage proof把 AST 当作血缘输入，而不是血缘证明

Parsing reveals syntactic data flow: sources, projections, aliases, joins, expressions, insert targets, and nested statements. Complete lineage also needs name resolution, star expansion, view and routine definitions, dynamic SQL, macros, temporary objects, external tables, session defaults, policy rewrites, runtime branches, and engine-specific semantics. Recovered or unsupported syntax creates explicit gaps.

解析揭示语法数据流：来源、投影、别名、连接、表达式、插入目标与嵌套语句。完整血缘还需要名称解析、星号展开、视图与例程定义、动态 SQL、宏、临时对象、外部表、会话默认值、策略重写、运行分支与引擎特定语义。恢复或不支持语法会形成明确缺口。

Never turn an incomplete parse into a complete-looking lineage graph by omitting unknown regions. Show gaps, affected outputs, and the evidence needed to resolve them.

不能通过省略未知区域，把不完整解析转换成看似完整的血缘图。应显示缺口、受影响输出与解决缺口所需证据。

Test parse–unparse–parse at syntax and semantic levels在语法与语义层测试解析—反解析—再解析

An unparser or formatter turns a tree back into SQL. The result may intentionally normalize keyword case, indentation, parentheses, aliases, identifier quotes, or literal spelling. The critical question is which changes are allowed and whether the output reparses under the same dialect into an equivalent structure without losing hints, comments, or unsupported fragments.

反解析器或格式化器把语法树重新转换成 SQL，可能有意规范关键字大小写、缩进、括号、别名、标识符引用或字面值拼写。关键问题是允许哪些变化，以及输出能否在相同方言下重新解析为等价结构，同时不丢失 Hint、注释或不支持片段。

Structural equality needs a documented normalizer: alias omission, redundant parentheses, literal forms, commutative expressions, and clause ordering cannot be treated casually. A parser round trip proves its own representation consistency, not universal query equivalence.

结构相等需要有文档的规范器：别名省略、冗余括号、字面值形式、可交换表达式与子句顺序不能随意处理。解析往返证明的是自身表示一致性，而不是普遍查询等价。

Treat dialect transpilation as a typed, lossy transformation把方言转译视为有类型且可能有损的转换

A multi-dialect parser can normalize source syntax and emit a target dialect, but syntax similarity does not guarantee semantic equivalence. Functions, types, null behavior, date arithmetic, identifier resolution, collation, regex, arrays, JSON, intervals, merge semantics, transactions, and optimizer hints may lack exact mappings. Some transformations require schema and type information unavailable to the parser.

多方言解析器可以规范源语法并输出目标方言，但语法相似不保证语义等价。函数、类型、空值行为、日期运算、标识符解析、排序规则、正则、数组、JSON、间隔、MERGE 语义、事务与优化器 Hint 可能没有精确映射。部分转换需要解析器无法获得的模式与类型信息。

The SQLGlot project documentation describes parser errors, AST inspection, custom dialects, and unsupported transpilation behavior, including cases that need schema information. Regardless of library, configure unsupported mappings to fail or surface prominently for consequential use.

SQLGlot 项目文档描述了解析错误、AST 检查、自定义方言与不支持转译行为，包括需要模式信息的情况。无论使用哪个库，重大用途都应让不支持映射失败或显著展示。

Parse untrusted SQL without turning analysis into execution解析不受信 SQL，但不能把分析变成执行

Parsing should not contact a database or execute functions, but it still processes attacker-controlled input. Deep nesting, huge token counts, pathological ambiguity, long literals, recursive grammar paths, comment nesting, generated diagnostics, AST serialization, extension hooks, and downstream visitors can consume CPU, memory, stack, disk, or logs. Dependencies and native bindings add their own attack surface.

解析不应联系数据库或执行函数，但仍会处理攻击者控制输入。深层嵌套、海量 Token、病态歧义、超长字面值、递归语法路径、嵌套注释、生成诊断、AST 序列化、扩展 Hook 与下游访问器都可能消耗 CPU、内存、栈、磁盘或日志。依赖与原生绑定还会增加攻击面。

Do not log full untrusted SQL by default. Diagnostics can include secrets or personal data in context windows. Use content hashes, bounded redacted excerpts, secure access, retention limits, and deletion procedures.

默认不要记录完整不受信 SQL。诊断上下文可能包含密钥或个人数据。应使用内容哈希、有界脱敏片段、安全访问、保留限制与删除流程。

Benchmark realistic syntax, errors, and tail latency用真实语法、错误与尾延迟进行基准测试

A benchmark of short valid SELECT statements says little about migration files, deeply nested views, procedural definitions, malformed editor buffers, multi-megabyte generated SQL, or mixed-dialect repositories. Measure throughput and latency by corpus class, input length, token count, node count, nesting, error count, recovery mode, comments, and source-map requirements.

短小合法 SELECT 基准无法代表迁移文件、深层嵌套视图、过程定义、畸形编辑缓冲区、多 MB 生成 SQL 或混合方言仓库。应按语料类别、输入长度、Token 数、节点数、嵌套、错误数、恢复模式、注释与源码映射需求衡量吞吐与延迟。

Pin runtime and hardware, warm-up policy, garbage collector, parser options, input corpus hash, and output mode. A parser that discards spans and comments should not be compared directly with one that preserves them without explaining the work difference.

固定运行时与硬件、预热策略、垃圾回收器、解析选项、输入语料哈希与输出模式。丢弃范围与注释的解析器不能在不解释工作差异时，直接与保留它们的解析器比较。

Build a layered parser test corpus构建分层解析器测试语料

Parser quality depends on breadth and adversarial depth. Golden AST snapshots are useful but can approve an incorrect tree if reviewed casually. Combine lexical fixtures, grammar examples, vendor documentation, real sanitized repositories, negative syntax cases, recovery cases, round trips, differential tests, fuzzing, metamorphic properties, and downstream behavior tests.

解析器质量取决于覆盖广度与对抗深度。黄金 AST 快照有用，但如果审查随意，也可能批准错误语法树。应组合词法夹具、语法示例、厂商文档、真实脱敏仓库、负面语法案例、恢复案例、往返、差分测试、模糊测试、蜕变性质与下游行为测试。

Keep corpus provenance, dialect and version, expected support level, sanitization method, license, and failure history. Add every production parser defect as a minimal regression plus the original sanitized case.

保留语料来源、方言与版本、预期支持级别、脱敏方法、许可证与失败历史。每个生产解析缺陷都应加入最小回归案例与原始脱敏案例。

Use parsing as the first structural gate for generated SQL把解析作为生成 SQL 的第一道结构门

AI-generated SQL should be parsed under the intended dialect before any database interaction. The AST can identify statement count and type, nested mutations, relation-shaped references, functions, joins, predicates, limits, comments, unsupported syntax, parameters, and recovered regions. Those findings support policy and review, but they remain syntactic until enriched with a trusted schema and engine semantics.

AI 生成 SQL 在任何数据库交互前，应按预期方言解析。AST 可以识别语句数量与类型、嵌套变更、关系形引用、函数、连接、条件、限制、注释、不支持语法、参数与恢复区域。这些发现支持策略与审查，但在可信模式与引擎语义增强前仍属于语法层。

Score an SQL parser with observable evidence用可观察证据评价 SQL 解析器

Parser choice should follow use cases. An editor needs recovery, incremental correctness, spans, and low tail latency; a migration analyzer needs script and DDL coverage; a policy engine needs strict dialect behavior and explicit unknown nodes; a formatter needs round-trip fidelity; a transpiler needs typed context and loss reporting. Set nonnegotiable gates before weighting convenience.

解析器选择应依据用途。编辑器需要恢复、增量正确性、范围与低尾延迟；迁移分析器需要脚本与 DDL 覆盖；策略引擎需要严格方言行为与显式未知节点；格式化器需要往返保真；转译器需要类型上下文与损失报告。便利性加权前先定义不可妥协门槛。

Score 0–4: absent, claimed, demonstrated once, repeatably verified, or enforced and monitored. Weighting cannot rescue a failed gate. Store corpus hashes, parser and runtime versions, options, output schemas, test results, owners, and dates.

按 0–4 评分：缺失、仅声明、单次演示、可重复验证、强制并监控。加权不能挽救失败门槛。保存语料哈希、解析器与运行时版本、选项、输出模式、测试结果、负责人与日期。

Use a twelve-step trustworthy parsing workflow使用十二步可信解析工作流

Stop consequential analysis when the dialect is unknown, input transformation cannot be mapped, the tree contains unbounded recovered or unknown regions, source spans fail checks, required constructs are unsupported, resource bounds are absent, or downstream logic treats syntax references as resolved facts.

如果方言未知、输入转换无法映射、语法树包含无边界恢复或未知区域、源码范围检查失败、必要结构不支持、缺少资源边界，或下游把语法引用当作已解析事实，就应停止重大分析。

Avoid common SQL parser failure patterns避免常见 SQL 解析器失败模式

Continue with a related guide继续阅读相关指南

Use these related guides to continue the workflow while keeping each search intent and validation task distinct.可继续阅读以下相关指南，在保持搜索意图与验证任务清晰分离的前提下推进工作流。

• SQL query validatorSQL 查询验证器
• SQL query examplesSQL 查询示例
• Query builder guide查询构建器指南

Frequently asked questions about SQL parsers关于 SQL 解析器的常见问题

Final SQL parser readiness checklistSQL 解析器最终就绪清单

A trustworthy SQL parser does not merely produce a tree. It tells downstream systems exactly which language it recognized, which source regions support each node, where it recovered or guessed, what it intentionally discarded, what it cannot understand, and which claims still require schema or runtime evidence.

可信 SQL 解析器不只是生成一棵树，还会告诉下游：识别了哪种语言、每个节点由哪些源码区域支持、在哪里恢复或猜测、主动丢弃了什么、无法理解什么，以及哪些声明仍需要模式或运行时证据。