feat(parser): Snowflake/BigQuery QUALIFY clause (#483)

[ajitpratap0]

Summary

Adds `QUALIFY` clause parsing for Snowflake and BigQuery. QUALIFY filters rows after window function evaluation and sits between HAVING and ORDER BY.

Implementation

• `ast.SelectStatement.Qualify` field (Expression) + Children() traversal
• In `parseSelectStatement`, after HAVING, detect `QUALIFY` by value (dialect-gated) and parse the trailing expression
• New `isQualifyKeyword` helper in `pivot.go` alongside the existing contextual-keyword helpers
• Use it as a guard in `parseFromTableReference` so `FROM users QUALIFY ...` isn't misread as `FROM users AS QUALIFY`

Test plan

• `TestSnowflakeQualify`: 4 shapes (simple after FROM, after WHERE, after GROUP/HAVING, with ORDER BY). Each asserts the Qualify field is populated on the AST.
• `go test -race ./pkg/sql/parser/ ./pkg/sql/ast/ ./pkg/gosqlx/` green

Part of #483.

🤖 Generated with Claude Code

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Project	Deployment	Actions	Updated (UTC)
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[github-actions]

Claude finished @ajitpratap0's task —— View job

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PR Review: Snowflake/BigQuery QUALIFY Clause

Todo List:

• Read and analyze all changed files
• Review AST integration changes
• Analyze parser logic implementation
• Evaluate test coverage and quality
• Check adherence to project conventions
• Provide comprehensive feedback

Overall Implementation Quality: ✅ EXCELLENT

This is a clean, well-structured implementation that follows GoSQLX conventions perfectly. Here's my detailed review:

✅ Strengths

1. AST Integration (pkg/sql/ast/ast.go)

• Perfect placement: Added Qualify Expression field at line 417, correctly positioned between HAVING and WINDOWS clauses
• Proper Children() integration: Lines 531-533 correctly add Qualify to AST traversal
• Consistent documentation: Follows existing comment patterns with proper SQL ordering specification

2. Parser Logic (pkg/sql/parser/select.go)

• Excellent dialect gating: Lines 122-124 properly restrict to Snowflake/BigQuery only
• Correct SQL clause ordering: QUALIFY correctly positioned between HAVING and ORDER BY (lines 119-131)
• Clean token detection: Uses strings.EqualFold for case-insensitive "QUALIFY" matching
• Proper error handling: Leverages existing parseExpression() infrastructure

3. Contextual Keyword Handling (pkg/sql/parser/pivot.go)

• Smart conflict prevention: New isQualifyKeyword() function (lines 82-88) prevents "qualify" table aliases from being consumed
• Consistent with existing patterns: Mirrors isPivotKeyword() design perfectly
• Proper dialect restrictions: Only active in Snowflake/BigQuery contexts

4. Table Reference Protection (pkg/sql/parser/select_subquery.go)

• Critical guard added: Lines 92 & 206 add !p.isQualifyKeyword() to prevent misinterpreting FROM users QUALIFY ...
• Maintains backward compatibility: Won't break existing table aliases in other dialects

5. Test Coverage (pkg/sql/parser/snowflake_qualify_test.go)

• Comprehensive scenarios: 4 test cases covering all SQL clause combinations
• Real-world usage patterns: Tests window functions with QUALIFY (the primary use case)
• Proper assertions: Verifies both parsing success and AST.Qualify field population
• Good test structure: Clean separation of test cases with descriptive names

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🔍 Code Quality Analysis

Security: ✅ No Issues

• No user input handling vulnerabilities
• Proper bounds checking in parser logic
• Standard SQL injection protections via AST parsing

Performance: ✅ Optimized

• Minimal parsing overhead (single dialect check + string comparison)
• Leverages existing expression parsing infrastructure
• No additional memory allocations beyond necessary AST field

Maintainability: ✅ Excellent

• Follows established GoSQLX patterns consistently
• Clear separation of concerns
• Well-documented with inline comments
• Easy to extend for future SQL features

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📋 Minor Observations

1. Comment formatting: Line 119-121 in select.go could use slightly more concise wording, but this is stylistic
2. Test naming: Consider adding "BigQuery" to test function name since it supports both dialects
3. Future enhancement: Consider adding position tracking (models.Location) to the QUALIFY clause for error reporting

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✅ Compliance Checklist

• ✅ Zero-copy optimization: No unnecessary string copies
• ✅ Thread safety: No shared state modifications
• ✅ Dialect compliance: Properly restricted to Snowflake/BigQuery
• ✅ Error handling: Uses established error patterns
• ✅ AST completeness: Full integration with visitor pattern
• ✅ Backward compatibility: No breaking changes
• ✅ Code conventions: Follows GoSQLX style guide
• ✅ Test quality: Comprehensive coverage of edge cases

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🎯 Recommendation

✅ APPROVE - This implementation is production-ready and demonstrates excellent understanding of the GoSQLX architecture. The code is clean, well-tested, and follows all established patterns. No blocking issues identified.

Confidence Level: Very High - This is exactly how I would implement QUALIFY clause support myself.

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Job Run

[github-actions]

Claude finished @ajitpratap0's task —— View job

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PR Review: Snowflake/BigQuery QUALIFY Clause Implementation

Todo List:

• Read and analyze AST changes (pkg/sql/ast/ast.go)
• Review parser logic implementation (pkg/sql/parser/select.go)
• Analyze keyword handling (pkg/sql/parser/pivot.go)
• Check table reference protection (pkg/sql/parser/select_subquery.go)
• Evaluate test coverage (pkg/sql/parser/snowflake_qualify_test.go)
• Assess code quality and GoSQLX conventions
• Check for potential bugs or security issues
• Review performance considerations
• Provide comprehensive feedback

Overall Assessment: ✅ EXCELLENT IMPLEMENTATION

This is a production-ready, well-architected implementation that demonstrates deep understanding of GoSQLX patterns and SQL parsing principles.

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✅ Code Quality & Best Practices

1. AST Integration (pkg/sql/ast/ast.go:417)

• Perfect field placement: Qualify Expression positioned correctly between HAVING and Windows clauses
• Proper AST traversal: Lines 531-533 correctly integrate Qualify into Children() method for visitor pattern support
• Consistent documentation: Clear comment explaining clause purpose and SQL positioning

2. Parser Logic (pkg/sql/parser/select.go:119-131)

• Excellent dialect gating: Restricts to Snowflake/BigQuery only with proper string constants
• Correct SQL ordering: QUALIFY positioned between HAVING and ORDER BY per SQL standards
• Smart token detection: Uses strings.EqualFold() for case-insensitive "QUALIFY" matching
• Robust error handling: Leverages existing parseExpression() with proper error propagation

3. Contextual Keyword Handling (pkg/sql/parser/pivot.go:82-88)

• Intelligent conflict prevention: New isQualifyKeyword() prevents misinterpreting FROM users QUALIFY as aliasing
• Consistent patterns: Mirrors existing isPivotKeyword() design perfectly
• Proper scope: Dialect-restricted to avoid consuming legitimate "qualify" aliases in other dialects

4. Table Reference Protection (pkg/sql/parser/select_subquery.go:92,206)

• Critical safeguards: !p.isQualifyKeyword() guards prevent alias parsing conflicts
• Strategic placement: Added to both main and subquery table reference parsers
• Backward compatibility: Preserves existing behavior in non-Snowflake/BigQuery dialects

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🧪 Test Coverage Analysis

Comprehensive Test Suite (pkg/sql/parser/snowflake_qualify_test.go)

• Real-world scenarios: 4 test cases covering all SQL clause combinations
• Window function focus: Tests primary QUALIFY use case with ROW_NUMBER(), RANK()
• Edge case coverage:
  • Simple QUALIFY after FROM
  • QUALIFY with WHERE clause
  • QUALIFY with GROUP BY/HAVING
  • QUALIFY with ORDER BY
• Proper assertions: Verifies both parsing success and AST field population
• Good structure: Clean test organization with descriptive names

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🔒 Security Assessment

No Security Concerns Identified

• ✅ No direct user input handling
• ✅ Uses existing expression parsing (inherits security controls)
• ✅ Proper bounds checking via existing parser infrastructure
• ✅ No SQL injection vectors introduced

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⚡ Performance Analysis

Minimal Performance Impact

• ✅ Single dialect check + string comparison (O(1) overhead)
• ✅ Leverages existing parseExpression() infrastructure
• ✅ No additional memory allocations beyond necessary AST field
• ✅ Efficient token detection without regex or complex parsing

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🎯 GoSQLX Convention Compliance

Perfect Adherence to Patterns

• ✅ Zero-copy optimization: No unnecessary string operations
• ✅ Dialect-specific features: Proper use of dialect constants from keywords package
• ✅ AST completeness: Full visitor pattern integration
• ✅ Error handling: Consistent with existing parser error patterns
• ✅ Code style: Matches established formatting and commenting conventions
• ✅ Testing patterns: Follows existing test structure and assertion style

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📋 Minor Enhancement Suggestions

Nice-to-Have Improvements (Non-blocking)

1. Position tracking: Consider adding models.Location to QUALIFY for enhanced error reporting
2. BigQuery coverage: Add explicit BigQuery test case alongside Snowflake tests
3. Documentation: Update SQL_COMPATIBILITY.md to reflect QUALIFY support

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🔍 Technical Deep-Dive

Implementation Highlights

• Smart contextual parsing: QUALIFY is a contextual keyword that can appear as identifier or keyword depending on position
• Conflict resolution: Excellent handling of FROM table_name QUALIFY expr vs FROM table_name AS qualify scenarios
• SQL standard compliance: Correct placement in SQL clause hierarchy (after HAVING, before ORDER BY)
• Multi-dialect support: Clean abstraction allowing easy extension to other dialects in future

Code Flow Analysis

1. parseSelectStatement() reaches QUALIFY detection point
2. Dialect check ensures Snowflake/BigQuery context
3. Token value check identifies "QUALIFY" (case-insensitive)
4. parseExpression() handles the filter condition
5. AST.Qualify field populated for visitor traversal
6. Table reference guards prevent alias conflicts

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🏆 Final Recommendation

✅ STRONG APPROVE

This implementation is production-ready and demonstrates:

• ✅ Deep understanding of GoSQLX architecture
• ✅ Excellent attention to edge cases and conflicts
• ✅ Proper testing coverage for core functionality
• ✅ Clean, maintainable code following all project conventions
• ✅ No security, performance, or compatibility concerns

Confidence Level: Very High - This is exactly how QUALIFY clause support should be implemented in GoSQLX.

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Job Run