zozo123 commented on code in PR #58859:
URL: https://github.com/apache/spark/pull/58859#discussion_r4142818148


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core/src/main/scala/org/apache/spark/internal/config/UDF.scala:
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@@ -0,0 +1,34 @@
+/*
+ * 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.internal.config
+
+private[spark] object UDF {
+
+  val DISPATCHER_FACTORY = ConfigBuilder("spark.udf.worker.dispatcherFactory")

Review Comment:
   Agreed — I followed up in #59153. The PR removes the arbitrary factory-class 
setting and keeps dispatch Spark-owned. One refinement is that 
`UDFWorkerSpecification.worker` already generates a closed `WorkerCase` enum, 
so Spark routes from that instead of adding a second enum config that could 
disagree with the specification. `DIRECT` maps only to a hard-coded Spark 
factory; worker-specific behavior remains in the specification and outside the 
Spark JVM. I also outlined generic provisioned/indirect workers as a separate 
follow-up rather than adding backend-specific APIs here. Thank you for 
reconsidering the boundary.



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