zhengruifeng commented on code in PR #38768:
URL: https://github.com/apache/spark/pull/38768#discussion_r1031102422
##########
python/pyspark/sql/connect/dataframe.py:
##########
@@ -51,24 +52,11 @@
class GroupingFrame(object):
Review Comment:
not related to this PR, but shall we rename it `GroupedData` to be the same
with pyspark?
##########
python/pyspark/sql/connect/dataframe.py:
##########
@@ -164,8 +156,20 @@ def selectExpr(self, *expr: Union[str, List[str]]) ->
"DataFrame":
return DataFrame.withPlan(plan.Project(self._plan, *sql_expr),
session=self._session)
- def agg(self, exprs: Optional[GroupingFrame.MeasuresType]) -> "DataFrame":
- return self.groupBy().agg(exprs)
+ def agg(self, *exprs: Union[Expression, Dict[str, str]]) -> "DataFrame":
+ if not exprs:
+ raise ValueError("Argument 'exprs' must not be empty")
+
+ if len(exprs) == 1 and isinstance(exprs[0], dict):
+ measures = []
+ for e, fun in exprs[0].items():
+ measures.append(ScalarFunctionExpression(fun, Column(e)))
Review Comment:
```suggestion
measures = [ScalarFunctionExpression(f, Column(e)) for e, f in
exprs[0].items()]
```
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