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Diffstat (limited to '')
-rw-r--r-- | sqlglot/dialects/dialect.py | 32 |
1 files changed, 32 insertions, 0 deletions
diff --git a/sqlglot/dialects/dialect.py b/sqlglot/dialects/dialect.py index 0120e71..0ab584e 100644 --- a/sqlglot/dialects/dialect.py +++ b/sqlglot/dialects/dialect.py @@ -245,6 +245,11 @@ def no_tablesample_sql(self, expression): return self.sql(expression.this) +def no_pivot_sql(self, expression): + self.unsupported("PIVOT unsupported") + return self.sql(expression) + + def no_trycast_sql(self, expression): return self.cast_sql(expression) @@ -282,3 +287,30 @@ def format_time_lambda(exp_class, dialect, default=None): ) return _format_time + + +def create_with_partitions_sql(self, expression): + """ + In Hive and Spark, the PARTITIONED BY property acts as an extension of a table's schema. When the + PARTITIONED BY value is an array of column names, they are transformed into a schema. The corresponding + columns are removed from the create statement. + """ + has_schema = isinstance(expression.this, exp.Schema) + is_partitionable = expression.args.get("kind") in ("TABLE", "VIEW") + + if has_schema and is_partitionable: + expression = expression.copy() + prop = expression.find(exp.PartitionedByProperty) + value = prop and prop.args.get("value") + if prop and not isinstance(value, exp.Schema): + schema = expression.this + columns = {v.name.upper() for v in value.expressions} + partitions = [col for col in schema.expressions if col.name.upper() in columns] + schema.set( + "expressions", + [e for e in schema.expressions if e not in partitions], + ) + prop.replace(exp.PartitionedByProperty(this=prop.this, value=exp.Schema(expressions=partitions))) + expression.set("this", schema) + + return self.create_sql(expression) |