MattBelle commented on code in PR #28979:
URL: https://github.com/apache/flink/pull/28979#discussion_r3856302875
##########
flink-python/pyflink/dataframe/dataframe.py:
##########
@@ -412,96 +331,210 @@ def __getitem__(
return self.filter(key)
raise TypeError("key must be a string, list, tuple, or Expression")
- # ======================== Conversion ========================
+ def _validate_subset(self, subset: Optional[List[str]]) -> List[str]:
+ """
+ Validate and normalize the subset parameter.
+
+ :param subset: Column names to validate, or None for all columns.
+ :return: Validated list of column names.
+ :raises ValueError: If subset is empty or contains invalid column
names.
+ :raises TypeError: If subset is not a list of strings.
+ """
+ schema = self._table.get_schema()
+ all_columns = schema.get_field_names()
+
+ if subset is None:
+ return all_columns
+
+ if not isinstance(subset, list):
+ raise TypeError("subset must be a list of strings")
+
+ if not subset:
+ raise ValueError("subset cannot be empty")
Review Comment:
Addressed. I updated `drop_null()` to treat empty subset as a no-op (returns
DataFrame unchanged), aligning with Pandas/Polars behavior and matching the
existing behavior in `fill_null()` and `fill_nan()`.
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