grundprinzip commented on code in PR #38908:
URL: https://github.com/apache/spark/pull/38908#discussion_r1039348490
##########
python/pyspark/sql/connect/dataframe.py:
##########
@@ -137,7 +137,13 @@ def isEmpty(self) -> bool:
return len(self.take(1)) == 0
def select(self, *cols: "ColumnOrName") -> "DataFrame":
- return DataFrame.withPlan(plan.Project(self._plan, *cols),
session=self._session)
+ sql_expr = []
+ for element in cols:
+ if isinstance(element, str):
+ sql_expr.append(sql_expression(element))
Review Comment:
@amaliujia This approach does not work either. If I apply your approach to
my example, it fails as well:
```
s2.read.table("martin.trips").groupBy("martin.trips.pickup_zip").sum("fare_amount").select("sum(fare_amount)").show()
```
Error
```
[UNRESOLVED_COLUMN.WITH_SUGGESTION] A column or function parameter with name
`fare_amount` cannot be resolved. Did you mean one of the following?
[`sum(fare_amount)`, `spark_catalog`.`martin`.`trips`.`pickup_zip`]; line 1 pos
4;
'Project [unresolvedalias('sum('fare_amount), None)]
+- Aggregate [pickup_zip#0], [pickup_zip#0, sum(fare_amount#1) AS
sum(fare_amount)#42]
+- SubqueryAlias spark_catalog.martin.trips
+- Relation spark_catalog.martin.trips[pickup_zip#0,fare_amount#1]
parquet
```
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