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! 🚀
Enhanced MQ publishers to utilize the new logical types:
- Updated convertToRecordValue() to use TimestampValue instead of string RFC3339
- Added DateValue support for birth_date field (days since epoch)
- Added DecimalValue support for precise_amount field with configurable precision/scale
- Enhanced UserEvent struct with PreciseAmount and BirthDate fields
- Added convertToDecimal() helper using big.Rat for precise decimal conversion
- Updated test data generator to produce varied birth dates (1970-2005) and precise amounts
Publishers now generate structured data with proper logical types:
- ✅ TIMESTAMP: Microsecond precision UTC timestamps
- ✅ DATE: Birth dates as days since Unix epoch
- ✅ DECIMAL: Precise amounts with 18-digit precision, 4-decimal scale
Successfully tested with PostgreSQL integration - all topics created with logical type data.
Added support for Parquet logical types in SeaweedFS message queue schema:
- TIMESTAMP: UTC timestamp in microseconds since epoch with timezone flag
- DATE: Date as days since Unix epoch (1970-01-01)
- DECIMAL: Arbitrary precision decimal with configurable precision/scale
- TIME: Time of day in microseconds since midnight
These types enable advanced analytics features:
- Time-based filtering and window functions
- Date arithmetic and year/month/day extraction
- High-precision numeric calculations
- Proper time zone handling for global deployments
Regenerated protobuf Go code with new scalar types and value messages.
- Remove github.com/pganalyze/pg_query_go/v6 dependency to avoid CGO requirement
- Implement lightweight SQL parser for basic SELECT, SHOW, and DDL statements
- Fix operator precedence in WHERE clause parsing (handle AND/OR before comparisons)
- Support INTEGER, FLOAT, and STRING literals in WHERE conditions
- All SQL engine tests passing with new parser
- PostgreSQL integration tests can now build without CGO
The lightweight parser handles the essential SQL features needed for the
SeaweedFS query engine while maintaining compatibility and avoiding CGO
dependencies that caused Docker build issues.
The pg_query_go library requires CGO to be enabled as it wraps the libpg_query C library.
Added gcc and musl-dev dependencies to the Docker build for proper compilation.
