ueshin commented on code in PR #52320:
URL: https://github.com/apache/spark/pull/52320#discussion_r2345621649
##########
python/pyspark/sql/pandas/serializers.py:
##########
@@ -218,8 +218,10 @@ def load_stream(self, stream):
if i in self.table_arg_offsets:
struct = batch.column(i)
# Flatten the struct and create a RecordBatch from it
+ flattened_arrays = struct.flatten()
+ field_names = [field.name for field in struct.type]
flattened_batch = pa.RecordBatch.from_arrays(
- struct.flatten(), schema=pa.schema(struct.type)
+ flattened_arrays, names=field_names
Review Comment:
I checked the generated schema from both with pyarrow `15.0.2` and `20.0.0`:
```py
print(f"{flattened_batch.schema} <=====> {pa.schema(struct.type)}")
```
and saw from the tests:
```
id: int64 <=====> id: int64 not null
```
or
```
id: int64 <=====> id: int64
```
Seems like the original schema is more accurate?
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