**Problem:**
- CURRENT_TIMESTAMP test had timing race condition that could cause flaky failures
- CURRENT_DATE test could fail if run exactly at midnight boundary
- Tests were too strict about timing precision without accounting for system variations
**Root Cause:**
- Test captured before/after timestamps and expected function result to be exactly between them
- No tolerance for clock precision differences, NTP adjustments, or system timing variations
- Date boundary race condition around midnight transitions
**Solution:**
✅ **CURRENT_TIMESTAMP test**: Added 100ms tolerance buffer to account for:
- Clock precision differences between time.Now() calls
- System timing variations and NTP corrections
- Microsecond vs nanosecond precision differences
✅ **CURRENT_DATE test**: Enhanced to handle midnight boundary crossings:
- Captures date before and after function call
- Accepts either date value in case of midnight transition
- Prevents false failures during overnight test runs
**Testing:**
- Verified with repeated test runs (5x iterations) - all pass consistently
- Full test suite passes - no regressions introduced
- Tests are now robust against timing edge cases
**Impact:**
🚀 **Eliminated flaky test failures** while maintaining function correctness validation
🔧 **Production-ready testing** that works across different system environments
⚡ **CI/CD reliability** - tests won't fail due to timing variations
- Implement comprehensive DATE_TRUNC function supporting:
- Time precisions: microsecond, millisecond, second, minute, hour
- Date precisions: day, week, month, quarter, year, decade, century, millennium
- Support both singular and plural forms (e.g., 'minute' and 'minutes')
- Enhanced date/time parsing with proper timezone handling:
- Assume local timezone for non-timezone string formats
- Support UTC formats with explicit timezone indicators
- Consistent behavior between parsing and truncation
- Comprehensive test suite with 11 test cases covering:
- All supported precisions from microsecond to year
- Multiple input types (TimestampValue, string dates)
- Edge cases (null values, invalid precisions)
- Timezone consistency validation
All tests passing ✅
- Implement CURRENT_DATE returning YYYY-MM-DD format
- Add CURRENT_TIMESTAMP returning TimestampValue with microseconds
- Add CURRENT_TIME returning HH:MM:SS format
- Add NOW() as alias for CURRENT_TIMESTAMP
- Implement comprehensive EXTRACT function supporting:
- YEAR, MONTH, DAY, HOUR, MINUTE, SECOND
- QUARTER, WEEK, DOY (day of year), DOW (day of week)
- EPOCH (Unix timestamp)
- Support multiple input formats:
- TimestampValue (microseconds)
- String dates (multiple formats)
- Unix timestamps (int64 seconds)
- Comprehensive test suite with 15+ test cases covering:
- All date/time constants
- Extract from different value types
- Error handling for invalid inputs
- Timezone handling
All tests passing ✅
- Implement ROUND with optional precision parameter
- Add CEIL function for rounding up to nearest integer
- Add FLOOR function for rounding down to nearest integer
- Add ABS function for absolute values with type preservation
- Support all numeric types (int32, int64, float32, double)
- Comprehensive test suite with 20+ test cases covering:
- Positive/negative numbers
- Integer/float type preservation
- Precision handling for ROUND
- Null value error handling
- Edge cases (zero, large numbers)
All tests passing ✅
- Implement EvaluateArithmeticExpression with support for all basic operators
- Handle type conversions between int, float, string, and boolean
- Add proper error handling for division/modulo by zero
- Include 14 comprehensive test cases covering all edge cases
- Support mixed type arithmetic (int + float, string numbers, etc.)
All tests passing ✅
Added comprehensive foundation for SQL window functions with timestamp analytics:
Core Window Function Types:
- WindowSpec with PartitionBy and OrderBy support
- WindowFunction struct for ROW_NUMBER, RANK, LAG, LEAD
- OrderByClause for timestamp-based ordering
- Extended SelectStatement to support WindowFunctions field
Timestamp Analytics Functions:
✅ ApplyRowNumber() - ROW_NUMBER() OVER (ORDER BY timestamp)
✅ ExtractYear() - Extract year from TIMESTAMP logical type
✅ ExtractMonth() - Extract month from TIMESTAMP logical type
✅ ExtractDay() - Extract day from TIMESTAMP logical type
✅ FilterByYear() - Filter records by timestamp year
Foundation for Advanced Window Functions:
- LAG/LEAD for time-series access to previous/next values
- RANK/DENSE_RANK for temporal ranking
- FIRST_VALUE/LAST_VALUE for window boundaries
- PARTITION BY support for grouped analytics
This enables sophisticated time-series analytics like:
- SELECT *, ROW_NUMBER() OVER (ORDER BY timestamp) FROM user_events WHERE EXTRACT(YEAR FROM timestamp) = 2024
- Trend analysis over time windows
- Session analytics with LAG/LEAD functions
- Time-based ranking and percentiles
Ready for production time-series analytics with proper timestamp logical type support! 🚀
chrislu
Chris Lu