HyukjinKwon commented on code in PR #39041:
URL: https://github.com/apache/spark/pull/39041#discussion_r1051834536
##########
python/pyspark/sql/functions.py:
##########
@@ -2341,6 +2415,7 @@ def approx_count_distinct(col: "ColumnOrName", rsd:
Optional[float] = None) -> C
return _invoke_function("approx_count_distinct", _to_java_column(col),
rsd)
+@try_remote_functions
def broadcast(df: DataFrame) -> DataFrame:
Review Comment:
Here too. The whole logic would look like:
```python
def broadcast(df: PySparkDataFrame) -> PySparkDataFrame:
if is_remote():
return typing.cast(PySparkDataFrame, connect.broadcast(df))
else:
return pyspark.boradcast(cast(ConnectDataFrame, df))
```
And, we will just use the existing type annotations so users codes won't
need to change their type annotations.
##########
python/pyspark/sql/functions.py:
##########
@@ -2341,6 +2415,7 @@ def approx_count_distinct(col: "ColumnOrName", rsd:
Optional[float] = None) -> C
return _invoke_function("approx_count_distinct", _to_java_column(col),
rsd)
+@try_remote_functions
def broadcast(df: DataFrame) -> DataFrame:
Review Comment:
Here too. The whole logic would look like:
```python
def broadcast(df: PySparkDataFrame) -> PySparkDataFrame:
if is_remote():
return typing.cast(PySparkDataFrame,
connect.broadcast(cast(ConnectDataFrame, df)))
else:
return pyspark.boradcast(df)
```
And, we will just use the existing type annotations so users codes won't
need to change their type annotations.
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