CCDAK Exam Dumps : Confluent Certified Developer for Apache Kafka Certification Examination

According to the official Apache Kafka Connect and Confluent JDBC Source Connector documentation, the correct connector class for a JDBC source connector is io.confluent.connect.jdbc.JdbcSourceConnector. This connector is used to read data from relational databases and publish each table as a Kafka topic.

To read all rows from a specific table, the configuration must include table.whitelist (or table.include.list in newer versions) with the table name, and a topic.prefix to determine the Kafka topic name. In this case, using topic.prefix=dbl- with table.whitelist=orders results in records being written to the dbl-orders topic, which matches the requirement.

Options A, B, and C are invalid because they reference a non-existent connector class (DdbcSourceConnector), contain unsupported properties such as topic.whitelist for a source connector, or include malformed/incorrect JDBC parameters. Additionally, blacklisting tables does not ensure that only the orders table is read.

Therefore, option D is the only configuration that is syntactically correct, uses the proper connector class, and aligns with the official Kafka Connect JDBC Source Connector documentation.

For Kafka Streams to perform joins, topics must be co-partitioned, meaning:

They have the same number of partitions (A), and

They use the same partitioning strategy (typically by key) (B)

From Kafka Streams Documentation > Joins:

“Co-partitioning is required for Kafka Streams joins. Topics must have the same number of partitions and use the same key-based partitioner.”

Value schema (C) and retention time (D) have no bearing on join compatibility.

To skip a corrupted record and avoid failing the application, you must seek past the failed offset manually using consumer.seek(). This allows the application to resume consumption from the next offset.

From Kafka Consumer Error Handling Docs:

“On deserialization failure, you can catch RecordDeserializationException, log the error, and call seek() to the next offset to skip the bad record.”

A does not prevent re-processing the bad record.

C is invalid; there's no skip() method in the Kafka consumer API.

D results in service interruption — not ideal for resiliency.