physinet commented on code in PR #36545:
URL: https://github.com/apache/spark/pull/36545#discussion_r875099589
##########
python/pyspark/sql/session.py:
##########
@@ -570,10 +570,20 @@ def _inferSchemaFromList(
if not data:
raise ValueError("can not infer schema from empty dataset")
infer_dict_as_struct = self._jconf.inferDictAsStruct()
+ infer_array_from_first_element =
self._jconf.legacyInferArrayTypeFromFirstElement()
Review Comment:
I can see the argument for casting to the widest applicable type, but I
think that should be a separate discussion. Inferring the type of an array I
think should be analogous to inferring a type over rows, which raises an error
in this case:
```python
>>> spark.createDataFrame([{"a": "1"}, {"a": 2}])
...
TypeError: field a: Can not merge type <class
'pyspark.sql.types.StringType'> and <class 'pyspark.sql.types.LongType'>
```
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