allisonwang-db commented on code in PR #47835:
URL: https://github.com/apache/spark/pull/47835#discussion_r1731803830
##########
python/pyspark/sql/dataframe.py:
##########
@@ -4595,6 +4597,8 @@ def dropDuplicates(self, *subset: Union[str, List[str]])
-> "DataFrame":
subset : list of column names, optional
List of columns to use for duplicate comparison (default All
columns).
+ subset_varargs : optional arguments used for supporting
variable-length argument.
Review Comment:
nit: let's also add supported version for this parameter
##########
python/pyspark/sql/dataframe.py:
##########
@@ -4627,11 +4631,22 @@ def dropDuplicates(self, *subset: Union[str,
List[str]]) -> "DataFrame":
+-----+---+------+
|Alice| 5| 80|
+-----+---+------+
+
+ Deduplicate values on 'name' and 'height' columns.
+
+ >>> df.dropDuplicates(subset=['name', 'height']).show()
+ +-----+---+------+
+ | name|age|height|
+ +-----+---+------+
+ |Alice| 5| 80|
+ +-----+---+------+
Review Comment:
Hmm this example is exactly the same as the above one. It can be confusing
to users whether they should use `dropDuplicates(subset=['name', 'height'])` or
directly use `dropDuplicates('name', 'height')`
##########
python/pyspark/sql/dataframe.py:
##########
@@ -4681,6 +4698,10 @@ def dropDuplicatesWithinWatermark(self, *subset:
Union[str, List[str]]) -> "Data
Deduplicate values on 'value' columns.
>>> df.dropDuplicatesWithinWatermark('value') # doctest: +SKIP
+
+ Deduplicate values on 'value' columns.
+
+ >>> df.dropDuplicatesWithinWatermark(subset=['value']) # doctest:
+SKIP
Review Comment:
ditto
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