haiyangsun-db commented on code in PR #55611:
URL: https://github.com/apache/spark/pull/55611#discussion_r3168730507


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sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/externalUDF/MapPartitionExternalUDF.scala:
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@@ -0,0 +1,49 @@
+/*
+ * 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.plans.logical.externalUDF
+
+import org.apache.spark.annotation.Experimental
+import org.apache.spark.sql.catalyst.expressions.{Attribute, 
ExternalUDFExpression}
+import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan
+import org.apache.spark.udf.worker.UDFWorkerSpecification
+import org.apache.spark.udf.worker.core.WorkerSessionFactory
+
+/**
+ * :: Experimental ::
+ * Logical plan node for mapPartitions-style UDF execution in an
+ * external worker process.
+ *
+ * @param workerSpec       Specification describing the UDF worker.
+ * @param sessionFactory   Factory for creating worker sessions.
+ * @param functionExpr     The UDF expression describing the function.
+ * @param resultAttributes Output attributes produced by the UDF.
+ * @param child            Input relation whose partitions are processed.
+ */
+@Experimental
+case class MapPartitionExternalUDF(
+    workerSpec: UDFWorkerSpecification,
+    sessionFactory: WorkerSessionFactory,
+    functionExpr: ExternalUDFExpression,

Review Comment:
   A typical mapPartitions takes just a function, rather than an expression. 
The difference is that:
   1. In udf expressions: select some_udf(col + 1), some_udf2(col2 + col3), we 
have two UDF expressions, each expression is mapped to one function, and has 
its inputs from other expressions.
   2. for mapPartitions, it's usually input rows as whole and output rows as 
whole, it usually looks like
   df.mapInArrow(some_func), df.mapPartitions(some_lambda). It directly relies 
on one udf function, rather than depending on an expression.



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