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Parsing SQL code in the C# .NET Core environment requires accessing its tree structure, identifying node types and classifying statements. This article explains how to achieve this using the right tools and techniques.
For Transact-SQL (T-SQL), Microsoft provides a dedicated assembly called Microsoft.SqlServer.Management.SqlParser.dll
. This assembly contains the Microsoft.SqlServer.Management.SqlParser.Parser
namespace, which allows SQL code to be parsed into tokens.
The following example method demonstrates how to use this parser to parse a T-SQL string into tokens:
<code class="language-csharp">IEnumerable<TokenInfo> ParseSql(string sql) { var parseOptions = new ParseOptions(); var scanner = new Scanner(parseOptions); int state = 0, start, end, lastTokenEnd = -1, token; bool isPairMatch, isExecAutoParamHelp; var tokens = new List<TokenInfo>(); scanner.SetSource(sql, 0); while ((token = scanner.GetNext(ref state, out start, out end, out isPairMatch, out isExecAutoParamHelp)) != (int)Tokens.EOF) { var tokenInfo = new TokenInfo { Start = start, End = end, IsPairMatch = isPairMatch, IsExecAutoParamHelp = isExecAutoParamHelp, Sql = sql.Substring(start, end - start + 1), Token = (Tokens)token, }; tokens.Add(tokenInfo); lastTokenEnd = end; } return tokens; }</code>The
TokenInfo
class encapsulates information about the parsed tag, including its start and end positions, pairing status, and associated SQL text. The Tokens
enum contains constant values representing various tag types, such as TOKEN_BEGIN
, TOKEN_COMMIT
, and TOKEN_EXISTS
.
If Microsoft SQL Parser does not meet your needs, you may consider using a regular expression library or a parser generator tool to build your own parser. Regular expressions provide a flexible way to match patterns, but can become complex when dealing with nested structures. Parser generator tools (such as ANTLR or Bison) provide a structured way to define grammar rules and automatically generate parsers based on these rules.
In summary, which method to choose depends on the specific needs and complexity of your SQL parsing task. By leveraging Microsoft SQL Parser to parse T-SQL or exploring alternative techniques for general purpose parsing, you can efficiently access the tree structure of your SQL code and identify node types.
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