pralabhkumar commented on a change in pull request #35191:
URL: https://github.com/apache/spark/pull/35191#discussion_r820885856
##########
File path: python/pyspark/pandas/series.py
##########
@@ -5241,9 +5253,16 @@ def asof(self, where: Union[Any, List]) -> Union[Scalar,
"Series"]:
# The data is expected to be small so it's fine to transpose/use
default index.
with ps.option_context("compute.default_index_type", "distributed",
"compute.max_rows", 1):
- psdf: DataFrame = DataFrame(sdf)
- psdf.columns = pd.Index(where)
- return first_series(psdf.transpose()).rename(self.name)
+ if len(where) == len(set(where)) and not isinstance(index_type,
TimestampType):
+ psdf: DataFrame = DataFrame(sdf)
+ psdf.columns = pd.Index(where)
+ return first_series(psdf.transpose()).rename(self.name)
+ else:
+ # If `where` has duplicate items, leverage the pandas directly
Review comment:
@HyukjinKwon . IMHO , this may not be very uncommon case . Is there a
reason to not handle this case and throw exception
cc @itholic
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