[GitHub] [spark] ueshin commented on a diff in pull request #42157: [SPARK-43968][PYTHON] Improve error messages for Python UDTFs with wrong number of outputs

["ueshin (via GitHub)" <gi...@apache.org>]

ueshin commented on code in PR #42157:
URL: https://github.com/apache/spark/pull/42157#discussion_r1276759271


##########
python/pyspark/worker.py:
##########
@@ -654,6 +657,19 @@ def wrap_udtf(f, return_type):
             assert return_type.needConversion()
             toInternal = return_type.toInternal
 
+            def verify_and_convert_result(result):
+                # TODO(SPARK-44005): support returning non-tuple values
+                if result is not None and hasattr(result, "__len__"):
+                    if len(result) != len(return_type):

Review Comment:
   nit: ditto.



##########
python/pyspark/worker.py:
##########
@@ -604,8 +604,11 @@ def verify_result(result):
                         },
                     )
 
-                # Check when the dataframe has both rows and columns.
-                if not result.empty or len(result.columns) != 0:
+                # Validate the output schema when the result dataframe has either output
+                # rows or columns. Note that we avoid using `df.empty` here because the
+                # result dataframe may contain an empty row. For example, when a UDTF is
+                # defined as follows: def eval(self): yield tuple().
+                if len(result) > 0 or len(result.columns) > 0:
                     if len(result.columns) != len(return_type):

Review Comment:
   nit: We might want to have an variable for `len(return_type)` outside of `verify_result` to avoid any potential overhead.



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