AngersZhuuuu commented on a change in pull request #29054:
URL: https://github.com/apache/spark/pull/29054#discussion_r496712280
##########
File path:
sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveSessionCatalog.scala
##########
@@ -69,49 +119,18 @@ private[sql] class HiveSessionCatalog(
// Current thread context classloader may not be the one loaded the class.
Need to switch
// context classloader to initialize instance properly.
Utils.withContextClassLoader(clazz.getClassLoader) {
- Try(super.makeFunctionExpression(name, clazz, input)).getOrElse {
- var udfExpr: Option[Expression] = None
- try {
- // When we instantiate hive UDF wrapper class, we may throw
exception if the input
- // expressions don't satisfy the hive UDF, such as type mismatch,
input number
- // mismatch, etc. Here we catch the exception and throw
AnalysisException instead.
- if (classOf[UDF].isAssignableFrom(clazz)) {
- udfExpr = Some(HiveSimpleUDF(name, new
HiveFunctionWrapper(clazz.getName), input))
- udfExpr.get.dataType // Force it to check input data types.
- } else if (classOf[GenericUDF].isAssignableFrom(clazz)) {
- udfExpr = Some(HiveGenericUDF(name, new
HiveFunctionWrapper(clazz.getName), input))
- udfExpr.get.dataType // Force it to check input data types.
- } else if
(classOf[AbstractGenericUDAFResolver].isAssignableFrom(clazz)) {
- udfExpr = Some(HiveUDAFFunction(name, new
HiveFunctionWrapper(clazz.getName), input))
- udfExpr.get.dataType // Force it to check input data types.
- } else if (classOf[UDAF].isAssignableFrom(clazz)) {
- udfExpr = Some(HiveUDAFFunction(
- name,
- new HiveFunctionWrapper(clazz.getName),
- input,
- isUDAFBridgeRequired = true))
- udfExpr.get.dataType // Force it to check input data types.
- } else if (classOf[GenericUDTF].isAssignableFrom(clazz)) {
- udfExpr = Some(HiveGenericUDTF(name, new
HiveFunctionWrapper(clazz.getName), input))
- udfExpr.get.asInstanceOf[HiveGenericUDTF].elementSchema // Force
it to check data types.
- }
- } catch {
- case NonFatal(e) =>
- val noHandlerMsg = s"No handler for UDF/UDAF/UDTF
'${clazz.getCanonicalName}': $e"
- val errorMsg =
- if (classOf[GenericUDTF].isAssignableFrom(clazz)) {
- s"$noHandlerMsg\nPlease make sure your function overrides " +
- "`public StructObjectInspector initialize(ObjectInspector[]
args)`."
- } else {
- noHandlerMsg
- }
- val analysisException = new AnalysisException(errorMsg)
- analysisException.setStackTrace(e.getStackTrace)
- throw analysisException
- }
- udfExpr.getOrElse {
- throw new AnalysisException(s"No handler for UDF/UDAF/UDTF
'${clazz.getCanonicalName}'")
- }
+ try {
+ super.makeFunctionExpression(name, clazz, input)
+ } catch {
+ case _: InvalidUDFClassException =>
+ // If `super.makeFunctionExpression` throw
`InvalidUDFClassException`, we construct
+ // Hive UDF/UDAF/UDTF with function definition.
+ makeHiveFunctionExpression(name, clazz, input)
+ case e: AnalysisException =>
Review comment:
> nit: `case e => throw e`
>
> The only exception is `InvalidUDFClassException`, where we need to try
with Hive UDF class. For other exceptions, just re-throw.
Done
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/catalog/SessionCatalog.scala
##########
@@ -1299,12 +1299,12 @@ class SessionCatalog(
// Check input argument size
if (e.inputTypes.size != input.size) {
- throw new AnalysisException(s"Invalid number of arguments for function
$name. " +
- s"Expected: ${e.inputTypes.size}; Found: ${input.size}")
+ throw new AnalysisException(s"Invalid number of arguments for " +
+ s"function $name. Expected: ${e.inputTypes.size}; Found:
${input.size}")
Review comment:
> unnecessary change
Done
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