Github user HyukjinKwon commented on a diff in the pull request:
https://github.com/apache/spark/pull/18444#discussion_r128134072
--- Diff: python/pyspark/sql/types.py ---
@@ -938,12 +1016,17 @@ def _infer_type(obj):
return MapType(_infer_type(key), _infer_type(value), True)
else:
return MapType(NullType(), NullType(), True)
- elif isinstance(obj, (list, array)):
+ elif isinstance(obj, list):
for v in obj:
if v is not None:
return ArrayType(_infer_type(obj[0]), True)
else:
return ArrayType(NullType(), True)
+ elif isinstance(obj, array):
+ if obj.typecode in _array_type_mappings:
+ return ArrayType(_array_type_mappings[obj.typecode](), False)
+ else:
+ raise TypeError("not supported type: array(%s)" % obj.typecode)
--- End diff --
Okay. Either way is fine to me (falling back to type inference or
disallowing unmappable type). Please let me know if any reviewer thinks
differently.
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at [email protected] or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
