xinrong-databricks commented on code in PR #36870:
URL: https://github.com/apache/spark/pull/36870#discussion_r902961587
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python/pyspark/sql/session.py:
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@@ -975,6 +976,17 @@ def createDataFrame( # type: ignore[misc]
if data.ndim not in [1, 2]:
raise ValueError("NumPy array input should be of 1 or 2
dimensions.")
column_names = ["value"] if data.ndim == 1 else ["_1", "_2"]
+ if schema is None and not self._jconf.arrowPySparkEnabled():
+ # Construct `schema` from `np.dtype` of the input NumPy array
+ # TODO: Apply the logic below when
self._jconf.arrowPySparkEnabled() is True
+ spark_type = _from_numpy_type(data.dtype)
+ if spark_type is not None:
+
Review Comment:
Good idea! Simplified.
As for `nullable`, shall we follow how we infer schema, as
[here](https://github.com/apache/spark/blob/b588d070ebc234280af730c8f9915e8859b1886e/python/pyspark/sql/types.py#L1348)?
Let me know if you have other concerns.
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