[GitHub] [spark] bjornjorgensen commented on a diff in pull request #37233: [SPARK-39823][SQL][PYTHON] Rename Dataset.as as Dataset.to and add DataFrame.to in PySpark

[GitBox <gi...@apache.org>]

bjornjorgensen commented on code in PR #37233:
URL: https://github.com/apache/spark/pull/37233#discussion_r929953507


##########
python/pyspark/sql/dataframe.py:
##########
@@ -1422,6 +1422,56 @@ def colRegex(self, colName: str) -> Column:
         jc = self._jdf.colRegex(colName)
         return Column(jc)
 
+    def to(self, schema: StructType) -> "DataFrame":
+        """
+        Returns a new :class:`DataFrame` where each row is reconciled to match the specified
+        schema.
+
+        Notes
+        -----
+        1, Reorder columns and/or inner fields by name to match the specified schema.
+
+        2, Project away columns and/or inner fields that are not needed by the specified schema.
+        Missing columns and/or inner fields (present in the specified schema but not input
+        DataFrame) lead to failures.
+
+        3, Cast the columns and/or inner fields to match the data types in the specified schema,
+        if the types are compatible, e.g., numeric to numeric (error if overflows), but not string
+        to int.
+
+        4, Carry over the metadata from the specified schema, while the columns and/or inner fields
+        still keep their own metadata if not overwritten by the specified schema.
+
+        5, Fail if the nullability are not compatible. For example, the column and/or inner field

Review Comment:
   Fail if the nullability are not compatible. 
   Change to:
   Fail if the nullability is not compatible.



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