sunchao commented on a change in pull request #35657:
URL: https://github.com/apache/spark/pull/35657#discussion_r839893300



##########
File path: 
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/TransformExpression.scala
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@@ -0,0 +1,61 @@
+/*
+ * 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.sql.connector.catalog.functions.BoundFunction
+import org.apache.spark.sql.types.DataType
+
+/**
+ * Represents a partition transform expression, for instance, `bucket`, 
`days`, `years`, etc.
+ *
+ * @param function the transform function itself. Spark will use it to decide 
whether two
+ *                 partition transform expressions are compatible.
+ * @param numBucketsOpt the number of buckets if the transform is `bucket`. 
Unset otherwise.

Review comment:
       We could, but since we don't check `children` in `isSameFunction` right 
now, we'll need to add extra logic to decide whether it is bucketing case or 
non-bucketing case, and check the literal in the children correspondingly. I 
think this is more complex than the current approach?




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