Github user yhuai commented on a diff in the pull request:
https://github.com/apache/spark/pull/8800#discussion_r39882820
--- Diff: sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUDFs.scala
---
@@ -59,19 +59,52 @@ private[hive] class HiveFunctionRegistry(underlying:
analysis.FunctionRegistry)
val functionClassName = functionInfo.getFunctionClass.getName
- if (classOf[UDF].isAssignableFrom(functionInfo.getFunctionClass)) {
- HiveSimpleUDF(new HiveFunctionWrapper(functionClassName), children)
- } else if
(classOf[GenericUDF].isAssignableFrom(functionInfo.getFunctionClass)) {
- HiveGenericUDF(new HiveFunctionWrapper(functionClassName),
children)
- } else if (
-
classOf[AbstractGenericUDAFResolver].isAssignableFrom(functionInfo.getFunctionClass))
{
- HiveGenericUDAF(new HiveFunctionWrapper(functionClassName),
children)
- } else if
(classOf[UDAF].isAssignableFrom(functionInfo.getFunctionClass)) {
- HiveUDAF(new HiveFunctionWrapper(functionClassName), children)
- } else if
(classOf[GenericUDTF].isAssignableFrom(functionInfo.getFunctionClass)) {
- HiveGenericUDTF(new HiveFunctionWrapper(functionClassName),
children)
- } else {
- sys.error(s"No handler for udf ${functionInfo.getFunctionClass}")
+ try {
+ // Based on the class of the function, we create corresponding the
Hive function.
+ // To trigger any error like arguments are not valid, we call the
dataType method
+ // to make sure internal Hive function resolver gets created
without any issue.
+ // The only exception at here is GenericUDTF, because it does not
support dataType
+ // method, we call elementTypes instead.
+ val resolvedHiveFunction =
+ if
(classOf[UDF].isAssignableFrom(functionInfo.getFunctionClass)) {
+ val func = HiveSimpleUDF(new
HiveFunctionWrapper(functionClassName), children)
+ // We actually only need func.dataType. Assigning the returned
value to a val
+ // is just to make the compiler happy.
+ val notUsed = func.dataType
--- End diff --
hmm, it is not really safe to call `dataType` to trigger the evaluation of
those lazy vals.
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