Github user zjffdu commented on a diff in the pull request:
https://github.com/apache/spark/pull/9766#discussion_r83159493
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/UDFRegistration.scala ---
@@ -414,6 +418,84 @@ class UDFRegistration private[sql] (functionRegistry:
FunctionRegistry) extends
//////////////////////////////////////////////////////////////////////////////////////////////
/**
+ * Register a Java UDF class using reflection, for use from pyspark
+ *
+ * @param name udf name
+ * @param className fully qualified class name of udf
+ * @param returnDataType return type of udf. If it is null, spark would
try to infer
+ * via reflection.
+ */
+ def registerJava(name: String, className: String, returnDataType:
DataType): Unit = {
+
+ try {
+ val clazz = Utils.classForName(className)
+ val udfInterfaces = clazz.getGenericInterfaces
+ .filter(_.isInstanceOf[ParameterizedType])
+ .map(_.asInstanceOf[ParameterizedType])
+ .filter(e => e.getRawType.isInstanceOf[Class[_]] &&
e.getRawType.asInstanceOf[Class[_]].getCanonicalName.startsWith("org.apache.spark.sql.api.java.UDF"))
+ if (udfInterfaces.length == 0) {
+ throw new IOException(s"UDF class ${className} doesn't implement
any UDF interface")
+ } else if (udfInterfaces.length > 1) {
+ throw new IOException(s"It is invalid to implement multiple UDF
interfaces, UDF class ${className}")
+ } else {
+ try {
+ val udf = clazz.newInstance()
+ val udfReturnType = udfInterfaces(0).getActualTypeArguments.last
+ var returnType = returnDataType
+ if (returnType == null) {
+ if (udfReturnType.isInstanceOf[Class[_]]) {
+ returnType =
udfReturnType.asInstanceOf[Class[_]].getCanonicalName match {
--- End diff --
Thanks for the hintï¼ fixed
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