[GitHub] [spark] itholic commented on a diff in pull request #40382: [SPARK-42679][CONNECT][PYTHON] createDataFrame doesn't work with non-nullable schema

["itholic (via GitHub)" <gi...@apache.org>]

itholic commented on code in PR #40382:
URL: https://github.com/apache/spark/pull/40382#discussion_r1133177990


##########
python/pyspark/sql/connect/session.py:
##########
@@ -267,6 +269,10 @@ def createDataFrame(
                 [ser._create_batch([(c, t) for (_, c), t in zip(data.items(), arrow_types)])]
             )
 
+            if isinstance(schema, StructType):
+                assert arrow_schema is not None

Review Comment:
   May dumb question, but just out of curiosity: is there any change that we get `None` for `arrow_schema`??
   
   Seems like `to_arrow_schema` function always return `pyarrow.Field` since it uses `pa.field` to create the schema? 



##########
python/pyspark/sql/connect/types.py:
##########
@@ -309,9 +309,12 @@ def to_arrow_type(dt: DataType) -> "pa.DataType":
     elif type(dt) == DayTimeIntervalType:
         arrow_type = pa.duration("us")
     elif type(dt) == ArrayType:
-        arrow_type = pa.list_(to_arrow_type(dt.elementType))
+        field = pa.field("element", to_arrow_type(dt.elementType), nullable=dt.containsNull)

Review Comment:
   Oh... so we didn't pass the nullable information to `pa._list`....
   
   Thanks for fixing this!!



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