Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/17222#discussion_r115166927
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/UDFRegistration.scala ---
@@ -475,20 +475,42 @@ class UDFRegistration private[sql] (functionRegistry:
FunctionRegistry) extends
case 21 => register(name, udf.asInstanceOf[UDF20[_, _, _, _,
_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _]], returnType)
case 22 => register(name, udf.asInstanceOf[UDF21[_, _, _, _,
_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _]], returnType)
case 23 => register(name, udf.asInstanceOf[UDF22[_, _, _, _,
_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _]], returnType)
- case n => logError(s"UDF class with ${n} type arguments is not
supported ")
+ case n =>
+ throw new IOException(s"UDF class with ${n} type arguments
is not supported.")
}
} catch {
case e @ (_: InstantiationException | _:
IllegalArgumentException) =>
- logError(s"Can not instantiate class ${className}, please make
sure it has public non argument constructor")
+ throw new IOException(s"Can not instantiate class
${className}, please make sure it has public non argument constructor")
}
}
} catch {
- case e: ClassNotFoundException => logError(s"Can not load class
${className}, please make sure it is on the classpath")
+ case e: ClassNotFoundException => throw new IOException(s"Can not
load class ${className}, please make sure it is on the classpath")
}
}
/**
+ * Register a Java UDAF class using reflection, for use from pyspark
+ *
+ * @param name UDAF name
+ * @param className fully qualified class name of UDAF
+ */
+ private[sql] def registerJavaUDAF(name: String, className: String): Unit
= {
--- End diff --
`registerJava` accepts an optional return type, if not given, spark will
try to infer it via reflection. do we really not need to do this for udaf?
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