itholic commented on code in PR #42798:
URL: https://github.com/apache/spark/pull/42798#discussion_r1314651862
##########
python/pyspark/pandas/groupby.py:
##########
@@ -3534,7 +3534,12 @@ def _reduce_for_stat_function(
for label in psdf._internal.column_labels:
psser = psdf._psser_for(label)
input_scol = psser._dtype_op.nan_to_null(psser).spark.column
- output_scol = sfun(input_scol)
+ if sfun.__name__ == "sum" and isinstance(
+ psdf._internal.spark_type_for(label), StringType
+ ):
+ output_scol = F.concat_ws("", F.collect_list(input_scol))
Review Comment:
We should use combination of `concat_ws` and `collect_list` instead of `sum`
to match the behavior with Pandas for string summation as below:
```python
>>> import pyspark.sql.functions as sf
>>> sdf.show()
+---+
| A|
+---+
| a|
| b|
| c|
+---+
# Using `sum` over string type column returns `NULL` which is not matched
with pandas.
>>> sdf.select(sf.sum(sdf.A)).show()
+------+
|sum(A)|
+------+
| NULL|
+------+
# Using combination of `concat_ws` and `collect_list` to match the pandas
behavior
>>> sdf.select(sf.concat_ws("", sf.collect_list(sdf.A))).show()
+----------------------------+
|concat_ws(, collect_list(A))|
+----------------------------+
| abc|
+----------------------------+
```
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