Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/20934#discussion_r178446367
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/JavaUDF.scala
---
@@ -0,0 +1,135 @@
+/*
+ * 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.spark.sql.catalyst.expressions
+
+import org.apache.spark.SparkException
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.catalyst.expressions.codegen.{CodegenContext,
CodeGenerator, ExprCode}
+import org.apache.spark.sql.types.DataType
+
+/*
+ Discussion: the ctor arg `function` need to support both scala and java.
+ so I think the style `(Any, Any, ...) => Any` is easier to use
+ Java function can be passed in using the value `javaFunction.call(_:Any,
...)`
+ */
+private[sql] case class JavaUDF (
--- End diff --
yes, almost the same for now, but the PR will change later after more
discussion. (including interface and implementation), no worry!
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