ueshin commented on code in PR #36640:
URL: https://github.com/apache/spark/pull/36640#discussion_r887134684
##########
python/pyspark/sql/session.py:
##########
@@ -611,8 +611,8 @@ def _inferSchema(
:class:`pyspark.sql.types.StructType`
"""
first = rdd.first()
- if not first:
- raise ValueError("The first row in RDD is empty, " "can not infer
schema")
+ if first is None:
Review Comment:
That's fine, but I feel the error messages are pretty inconsistent:
1. for the case the first value is `None`:
```py
>>> spark.createDataFrame(spark._sc.parallelize([None, None]))
...
TypeError: Can not infer schema for type: <class 'NoneType'>
```
should be:
```py
ValueError: The first row in RDD is empty, can not infer schema
```
?
2. if the first value is an int or a non-empty string:
```py
>>> spark.createDataFrame(spark._sc.parallelize([0, 1]))
...
TypeError: Can not infer schema for type: <class 'int'>
>>> spark.createDataFrame(spark._sc.parallelize(["a", "b"]))
...
TypeError: Can not infer schema for type: <class 'str'>
```
then I think the error message for the case of an empty string:
```py
>>> spark.createDataFrame(spark._sc.parallelize(["", "a"]))
...
ValueError: The first row in RDD is empty, can not infer schema
```
should be:
```py
TypeError: Can not infer schema for type: <class 'str'>
```
?
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