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SPARK-37389
Check unclosed bracketed comments
Support the utils for escapse the regex for ANSI SQL: SIMILAR TO ... ESCAPE syntax
ANSI SQL: LATERAL derived table(T491)
Improve performance for last_value over unbounded preceding window frame
Improve performance for last_value over unbounded window frame
Improve performance for nth_value ignore nulls over offset window
ANALYZE command support analyze all tables in a specific database
LEAD/LAG should support [ IGNORE NULLS | RESPECT NULLS ]
Support drop column in spark also like in postgresql
Improve the performance for FIRST_VALUE
Respect ANSI standard and change FIRST_VALUE as pure window function.
Improve the performance for NTH_VALUE and Reactor the OffsetWindowFunction
Aggregation support aggregate function with multiple foldable expressions.
Eliminate filter clause in aggregate
Support grant/revoke access privileges like postgresql
Add documents information for window function.
Support (IGNORE | RESPECT) NULLS for LEAD/LAG/NTH_VALUE/FIRST_VALUE/LAST_VALUE
Spark SQL can't display bracketed comments well in generated golden files
AnalysisException that window RangeFrame not match RowFrame
ANSI SQL: LAST_VALUE function
ANSI SQL: FIRST_VALUE function
first_value/last_value window function throws ParseException
Lead/Lag window function throws AnalysisException without ORDER BY clause
[SQL] ANSI SQL: Throw exception on format invalid and overflow when casting String to IntegerType.
When there are multiple DISTINCT aggregate expressions acting on different fields, any DISTINCT aggregate expression allows the use of the FILTER clause
When one or more DISTINCT aggregate expressions operate on the same field, the DISTINCT aggregate expression allows the use of the FILTER clause
Support Filter expression allows simultaneous use of DISTINCT
Support Filter expression uses IN/EXISTS predicate sub-queries
Support Filter expression reference the outer query
ANSI-F053: Overlaps datetimes predicate support
Support dec as shorthand for decimal
Support ANSI SQL CREATE SEQUENCE
Real data type is not supported in Spark SQL which is supporting in postgresql
Test both ANSI mode and Spark mode
The exact math method should be called only when there is a corresponding function in Math
ANSI SQL: delete and update does not support in Spark
ANSI SQL: Nested bracketed comments
ANSI SQL: Collation Support
Spark should support select <columnname> into <table> from <table> where <condition> as PostgreSQL supports
ANSI SQL: unique predicate
adds support for `filter` clause
ANSI SQL: Unicode escapes in literals
ANSI SQL: OVERLAY function support byte array(T312)
ANSI SQL(E021-05): OCTET_LENGTH function
Fully support correlation names in the FROM clause
ANSI SQL: Top-level <result offset clause> in <query expression>
SELECT INTO syntax
Support ANSI SQL:member predicate
Support ANSI SQL:SIMILAR TO ... ESCAPE syntax
DIV support decimal type