AnishMahto commented on code in PR #56208:
URL: https://github.com/apache/spark/pull/56208#discussion_r3336413241


##########
sql/pipelines/src/main/scala/org/apache/spark/sql/pipelines/autocdc/Scd2BatchProcessor.scala:
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@@ -0,0 +1,271 @@
+/*
+ * 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.pipelines.autocdc
+
+import org.apache.spark.sql.{functions => F}
+import org.apache.spark.sql.Column
+import org.apache.spark.sql.catalyst.util.QuotingUtils
+import org.apache.spark.sql.classic.DataFrame
+import org.apache.spark.sql.types.{DataType, StructType}
+
+/**
+ * Per-microbatch processor for SCD Type 2 AutoCDC flows, complying to the 
specified
+ * [[changeArgs]] configuration.
+ *
+ * @param changeArgs The CDC flow configuration.
+ * @param resolvedSequencingType The post-analysis [[DataType]] of the 
sequencing column, derived
+ *                               from the flow's resolved DataFrame at flow 
setup time.
+ */
+case class Scd2BatchProcessor(
+    changeArgs: ChangeArgs,
+    resolvedSequencingType: DataType) {
+
+  /**
+   * Reconcile a CDC microbatch into the canonical form the auxiliary- and 
target-table merges
+   * consume.
+   *
+   * Step ordering is load-bearing: the row-extension steps reference user 
data columns that
+   * target-column selection is allowed to drop, so selection runs last. 
Unlike SCD1, no per-key
+   * deduplication step is needed - SCD2 preserves every event as part of the 
row's history.

Review Comment:
   Yeah good question, microbatch preprocessing isn't concerned about 
duplicate/redundant events at all, that will eventually be handled by a 
downstream step in reconciliation.
   
   Updated scaladoc to make it clear!



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