bryanck commented on code in PR #8701:
URL: https://github.com/apache/iceberg/pull/8701#discussion_r1367793002


##########
kafka-connect/kafka-connect-events/src/main/java/org/apache/iceberg/connect/events/CommitCompletePayload.java:
##########
@@ -0,0 +1,97 @@
+/*
+ * 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.iceberg.connect.events;
+
+import java.util.UUID;
+import org.apache.avro.Schema;
+import org.apache.avro.SchemaBuilder;
+
+public class CommitCompletePayload implements Payload {
+
+  private UUID commitId;
+  private Long vtts;
+  private final Schema avroSchema;
+
+  private static final Schema AVRO_SCHEMA =

Review Comment:
   I do agree it is more readable. However, this will require changes to the 
Avro encoder. For example, both GenericDataFile and GenericDelete file use the 
same Iceberg schema. The current schema converter only allows a one to one 
mapping of struct type to class name, so you can't include both data files and 
delete files in the same event.
   
   Also, it becomes cumbersome to redefine the same struct to class mapping for 
every schema, e.g. the TopicPartitionOffset mapping must be defined for both 
payloads that use it as well as for the event container, when converting the 
schema to Avro.
   
   Another downside is the extra overhead of doing the conversion. Schemas are 
sometimes constructed for each event, as the schema changes depending on the 
table and partitioning. Though that is more minor and could be solved w/ 
caching.
   
   I did updated the field IDs so they aren't all -1.



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