schema evolution triggers a CDC query exception

{code:sql}
sparkSession.sql("CREATE TABLE if not exists hudi_ut_schema_evolution (id INT, version INT, name STRING, birthDate TIMESTAMP, inc_day STRING) USING HUDI PARTITIONED BY (inc_day) TBLPROPERTIES (hoodie.table.cdc.enabled='true', type='cow', primaryKey='id')");

20231127201042503.commit:
sparkSession.sql("merge into hudi_ut_schema_evolution t using ( select 1 as id, 1 as version, 'str_1' as name, cast('2023-01-01 12:12:12.0' as timestamp) as birthDate, '2023-10-01' as inc_day) s on t.id=s.id when matched THEN UPDATE SET * WHEN NOT MATCHED THEN INSERT *; ");

20231127201113131.commit:
sparkSession.sql("ALTER TABLE hudi_ut_schema_evolution ADD COLUMNS (add1 String AFTER id); ");

20231127201124255.commit:
sparkSession.sql("merge into hudi_ut_schema_evolution t using ( select '1' as add1, 2 as id, 1 as version, 'str_1' as name, cast('2023-01-01 12:12:12.0' as timestamp) as birthDate, '2023-10-01' as inc_day) s on t.id=s.id when matched THEN UPDATE SET * WHEN NOT MATCHED THEN INSERT *; ");

20231127201146659.commit:
sparkSession.sql("ALTER TABLE hudi_ut_schema_evolution DROP COLUMN add1");

20231127201157382.commit:
sparkSession.sql("ALTER TABLE hudi_ut_schema_evolution ADD COLUMNS (add1 int)");

20231127201208532.commit:
sparkSession.sql("merge into hudi_ut_schema_evolution t using ( select 1 as add1, 3 as id, 1 as version, 'str_1' as name, cast('2023-01-01 12:12:12.0' as timestamp) as birthDate, '2023-10-01' as inc_day) s on t.id=s.id when matched THEN UPDATE SET * WHEN NOT MATCHED THEN INSERT *; ");

sparkSession.sql("select * from hudi_ut_schema_evolution").show(100, false);
+-------------------+---------------------+------------------+----------------------+-------------------------------------------------------------------------+---+-------+-----+-------------------+----+----------+
|_hoodie_commit_time|_hoodie_commit_seqno |_hoodie_record_key|_hoodie_partition_path|_hoodie_file_name |id |version|name |birthDate |add1|inc_day |
+-------------------+---------------------+------------------+----------------------+-------------------------------------------------------------------------+---+-------+-----+-------------------+----+----------+
|20231127201042503 |20231127201042503_0_0|1 |inc_day=2023-10-01 |2fe30d70-daa3-4ebc-8dab-313116e1f8f3-0_0-103-89_20231127201208532.parquet|1 |1 |str_1|2023-01-01 12:12:12|null|2023-10-01|
|20231127201124255 |20231127201124255_0_1|2 |inc_day=2023-10-01 |2fe30d70-daa3-4ebc-8dab-313116e1f8f3-0_0-103-89_20231127201208532.parquet|2 |1 |str_1|2023-01-01 12:12:12|null|2023-10-01|
|20231127201208532 |20231127201208532_0_2|3 |inc_day=2023-10-01 |2fe30d70-daa3-4ebc-8dab-313116e1f8f3-0_0-103-89_20231127201208532.parquet|3 |1 |str_1|2023-01-01 12:12:12|1 |2023-10-01|
+-------------------+---------------------+------------------+----------------------+-------------------------------------------------------------------------+---+-------+-----+-------------------+----+----------+

sparkSession.sql("select * from hudi_table_changes('hudi_ut_schema_evolution','cdc','20231127201042503','20231127201208532')").show(100, false);
exception:
org.apache.avro.AvroTypeException: Found string, expecting union
at org.apache.avro.io.ResolvingDecoder.doAction(ResolvingDecoder.java:308)
at org.apache.avro.io.parsing.Parser.advance(Parser.java:86)
at org.apache.avro.io.ResolvingDecoder.readIndex(ResolvingDecoder.java:275)
at org.apache.avro.generic.GenericDatumReader.readWithoutConversion(GenericDatumReader.java:187)
at org.apache.avro.generic.GenericDatumReader.read(GenericDatumReader.java:160)
at org.apache.avro.generic.GenericDatumReader.readField(GenericDatumReader.java:259)
at org.apache.avro.generic.GenericDatumReader.readRecord(GenericDatumReader.java:247)
at org.apache.avro.generic.GenericDatumReader.readWithoutConversion(GenericDatumReader.java:179)
at org.apache.avro.generic.GenericDatumReader.read(GenericDatumReader.java:160)
at org.apache.avro.generic.GenericDatumReader.readWithoutConversion(GenericDatumReader.java:187)
at org.apache.avro.generic.GenericDatumReader.read(GenericDatumReader.java:160)
at org.apache.avro.generic.GenericDatumReader.readField(GenericDatumReader.java:259)
at org.apache.avro.generic.GenericDatumReader.readRecord(GenericDatumReader.java:247)
at org.apache.avro.generic.GenericDatumReader.readWithoutConversion(GenericDatumReader.java:179)
at org.apache.avro.generic.GenericDatumReader.read(GenericDatumReader.java:160)
at org.apache.avro.generic.GenericDatumReader.read(GenericDatumReader.java:153)
at org.apache.hudi.common.table.log.block.HoodieAvroDataBlock$RecordIterator.next(HoodieAvroDataBlock.java:196)
at org.apache.hudi.common.table.log.block.HoodieAvroDataBlock$RecordIterator.next(HoodieAvroDataBlock.java:146)
at org.apache.hudi.common.util.collection.MappingIterator.next(MappingIterator.java:44)
at org.apache.hudi.common.util.collection.MappingIterator.next(MappingIterator.java:44)
at org.apache.hudi.common.table.log.HoodieCDCLogRecordIterator.hasNext(HoodieCDCLogRecordIterator.java:77)
at org.apache.hudi.cdc.HoodieCDCRDD$CDCFileGroupIterator.hasNextInternal(HoodieCDCRDD.scala:266)
at org.apache.hudi.cdc.HoodieCDCRDD$CDCFileGroupIterator.hasNext(HoodieCDCRDD.scala:275)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:759)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:349)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:337)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1462)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:750)
{code}

## JIRA info

- Link: https://issues.apache.org/jira/browse/HUDI-7143
- Type: Bug

Reproduce the SQL schema-evolution sequence and the hudi_table_changes query described in the issue. Start with HoodieAvroDataBlock.RecordIterator and HoodieCDCRDD, where the stack trace reports the failure, and trace the Avro decoding path. Done means the CDC query completes without the AvroTypeException for this sequence.

Written by the indexing model from the issue text.