[GitHub] [spark] ueshin commented on a diff in pull request #36640: [SPARK-39262][PYTHON] Correct the behavior of creating DataFrame from an RDD

[GitBox <gi...@apache.org>]

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 int:
   
   ```py
   >>> spark.createDataFrame(spark._sc.parallelize([0, 1]))
   ...
   TypeError: Can not infer schema for type: <class 'int'>
   ```
   
   then I think the error message for the case of 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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