Github user twalthr commented on a diff in the pull request:
https://github.com/apache/flink/pull/3456#discussion_r105648552
--- Diff:
flink-connectors/flink-hcatalog/src/main/scala/org/apache/flink/table/hive/functions/HiveSimpleUDF.scala
---
@@ -0,0 +1,87 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.flink.table.hive.functions
+
+import java.lang.reflect.Method
+import java.math.BigDecimal
+import java.util
+
+import org.apache.flink.table.functions.ScalarFunction
+import org.apache.hadoop.hive.ql.exec.{FunctionRegistry, UDF}
+import
org.apache.hadoop.hive.ql.udf.generic.GenericUDFUtils.ConversionHelper
+import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspector
+import
org.apache.hadoop.hive.serde2.objectinspector.primitive.PrimitiveObjectInspectorFactory
+import org.apache.hadoop.hive.serde2.typeinfo.{PrimitiveTypeInfo,
TypeInfo, TypeInfoFactory}
+
+import scala.annotation.varargs
+
+/**
+ * A Hive UDF Wrapper which behaves as a Flink-table ScalarFunction.
+ *
+ * This class has to have a method with @varargs annotation. For scala
will compile
+ * <code> eval(args: Any*) </code> to <code>eval(args: Seq)</code>.
+ * This will cause an exception in Janino compiler.
+ */
+class HiveSimpleUDF(className: String) extends ScalarFunction {
+
+ @transient
+ private lazy val functionWrapper = HiveFunctionWrapper(className)
+
+ @transient
+ private lazy val function = functionWrapper.createFunction[UDF]()
+
+ @transient
+ private var typeInfos: util.List[TypeInfo] = _
+
+ @transient
+ private var objectInspectors: Array[ObjectInspector] = _
+
+ @transient
+ private var conversionHelper: ConversionHelper = _
+
+ @transient
+ private var method: Method = _
+
+ @varargs
+ def eval(args: AnyRef*) : Any = {
+ if (null == typeInfos) {
+ typeInfos = new util.ArrayList[TypeInfo]()
+ args.foreach(arg => {
+
typeInfos.add(TypeInfoFactory.getPrimitiveTypeInfoFromJavaPrimitive(arg.getClass))
+ })
+ method = function.getResolver.getEvalMethod(typeInfos)
+
+ objectInspectors = new Array[ObjectInspector](typeInfos.size())
+ args.zipWithIndex.foreach { case (_, i) =>
+ objectInspectors(i) =
PrimitiveObjectInspectorFactory.getPrimitiveJavaObjectInspector(
+ typeInfos.get(i).asInstanceOf[PrimitiveTypeInfo])
+ }
+ conversionHelper = new ConversionHelper(method, objectInspectors)
+ }
+
+ val mappedArgs = args.map {
--- End diff --
Maybe it is better to throw an exception because of an unsupported type
BigDecimal type, such that the user can manually cast the BigDecimal to double.
Otherwise the user is not aware of losing precision.
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