santosh-d3vpl3x commented on code in PR #37335:
URL: https://github.com/apache/spark/pull/37335#discussion_r933285810
##########
python/pyspark/sql/dataframe.py:
##########
@@ -3244,10 +3244,14 @@ def drop(self, *cols: "ColumnOrName") -> "DataFrame":
# type: ignore[misc]
else:
raise TypeError("col should be a string or a Column")
else:
- for col in cols:
- if not isinstance(col, str):
- raise TypeError("each col in the param list should be a
string")
- jdf = self._jdf.drop(self._jseq(cols))
+ if all(isinstance(col, str) for col in cols):
+ jdf = self._jdf.drop(self._jseq(cols))
+ elif all(isinstance(col, Column) for col in cols):
+ jdf = self._jdf
+ for col in cols:
+ jdf = jdf.drop(col._jc) # type: ignore[union-attr]
Review Comment:
Welp, with that change it breaks existing `drop(col: Column)` public API for
bindings.
```
py4j.Py4JException: Method drop([class org.apache.spark.sql.Column]) does
not exist
```
I have confirmed that to be the case for both python and sparkR.
I believe, addition of `drop(col: Column, cols: Column*)` or `drop(col:
Column*)` on scala is pretty hard at the moment while trying to keep the
compatibility.
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