[jira] [Created] (SPARK-24735) Improve exception when mixing pandas_udf types

["Bryan Cutler (JIRA)" <ji...@apache.org>]

Bryan Cutler created SPARK-24735:
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             Summary: Improve exception when mixing pandas_udf types
                 Key: SPARK-24735
                 URL: https://issues.apache.org/jira/browse/SPARK-24735
             Project: Spark
          Issue Type: Improvement
          Components: PySpark, SQL
    Affects Versions: 2.3.0
            Reporter: Bryan Cutler


From the discussion here https://github.com/apache/spark/pull/21650#discussion_r199203674, mixing up Pandas UDF types, like using GROUPED_MAP as a SCALAR {{foo = pandas_udf(lambda x: x, 'v int', PandasUDFType.GROUPED_MAP)}} produces an exception which is hard to understand.  It should tell the user that the UDF type is wrong.  This is the full output:

{code}
>>> foo = pandas_udf(lambda x: x, 'v int', PandasUDFType.GROUPED_MAP)
>>> df.select(foo(df['v'])).show()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/icexelloss/workspace/upstream/spark/python/pyspark/sql/dataframe.py", line 353, in show
    print(self._jdf.showString(n, 20, vertical))
  File "/Users/icexelloss/workspace/upstream/spark/python/lib/py4j-0.10.7-src.zip/py4j/java_gateway.py", line 1257, in __call__
  File "/Users/icexelloss/workspace/upstream/spark/python/pyspark/sql/utils.py", line 63, in deco
    return f(*a, **kw)
  File "/Users/icexelloss/workspace/upstream/spark/python/lib/py4j-0.10.7-src.zip/py4j/protocol.py", line 328, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o257.showString.
: java.lang.UnsupportedOperationException: Cannot evaluate expression: <lambda>(input[0, bigint, false])
	at org.apache.spark.sql.catalyst.expressions.Unevaluable$class.doGenCode(Expression.scala:261)
	at org.apache.spark.sql.catalyst.expressions.PythonUDF.doGenCode(PythonUDF.scala:50)
	at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$genCode$2.apply(Expression.scala:108)
	at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$genCode$2.apply(Expression.scala:105)
	at scala.Option.getOrElse(Option.scala:121)
        ...
{code}



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