SQL parsers convert SQL text into a structured format, usually a tree, that computers can process. They follow a clear pipeline: first, the lexer breaks the SQL string into tokens, then the parser builds a tree based on grammar rules. The Abstract Syntax Tree (AST) is the main output, representing the query's structure. Syntactic analysis checks for valid grammar, while semantic analysis requires knowledge of the database schema to ensure queries make sense. A parser can only perform syntactic checks without schema information, which limits its capabilities. The article highlights different SQL parsers, including SQLGlot, Apache Calcite, and JSqlParser, noting their various trade-offs. It explains that lexers are straightforward, handling simple character recognition, while parsers are more complex, managing structure and grammar. The discussion on column-level lineage is particularly relevant; it traces how data flows through queries and can be affected by factors like control flow, even if they don’t appear in the output. SQL dialects complicate matters further, as no database vendor fully adheres to the SQL standard, leading to variations in syntax and functionality. Overall, the piece provides a thorough breakdown of SQL parsing mechanics and considerations. It emphasizes the need for both syntactic and semantic analysis to effectively evaluate SQL queries, along with the importance of understanding lineage and dialects in database management.