itholic commented on a change in pull request #33214:
URL: https://github.com/apache/spark/pull/33214#discussion_r664993005
##########
File path: python/pyspark/sql/types.py
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@@ -1020,14 +1020,22 @@ def _infer_type(obj):
return dataType()
if isinstance(obj, dict):
- for key, value in obj.items():
- if key is not None and value is not None:
- return MapType(_infer_type(key), _infer_type(value), True)
- return MapType(NullType(), NullType(), True)
+ if infer_dict_as_struct:
+ struct = StructType()
+ for key, value in obj.items():
+ if key is not None and value is not None:
+ struct.add(key, _infer_type(value, infer_dict_as_struct),
True)
+ return struct
+ else:
+ for key, value in obj.items():
+ if key is not None and value is not None:
+ return MapType(_infer_type(key, infer_dict_as_struct),
+ _infer_type(value, infer_dict_as_struct),
True)
+ return MapType(NullType(), NullType(), True)
Review comment:
Thanks for the comment! :)
Actually PySpark merging one only handles null cases only (that's called out
here) at
https://github.com/apache/spark/blob/52a9a70fa3e5b720b41e2ff4e9177a5d201b471f/python/pyspark/sql/types.py#L1096-L1133
It actually fails for different types (unlike JSON or CSV type inference).
I am not sure what's the ideal behavior for the null case pointed out here
though.
Let me separate it from this PR in any event if you're fine.
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