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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