CCDAK Exam Dumps - Confluent Certified Developer Questions and Answers

Using assign() gives manual control over partition assignment. In this mode:

B is true: The application chooses partitions directly without involving the group coordinator.

C is true: Since no group coordination occurs, no rebalancing happens if a consumer dies.

From Kafka Consumer API Docs:

“assign() manually assigns a list of partitions to this consumer. No coordination takes place and no rebalancing is triggered.”

A is false: subscribe() and assign() are mutually exclusive.

D is incorrect: Partitions don't need to be equal across topics.

According to the official Apache Kafka Connect documentation, RegexRouter is the SMT specifically designed to dynamically change the destination topic name of records produced by a connector. It works by applying a regular expression to the original topic name and rewriting it to a new topic name.

This makes RegexRouter the correct choice when some records must be routed to a different topic, typically in combination with connector-level logic, predicates, or multiple connectors. It is commonly used for topic renaming, topic versioning, or routing records to alternate topics.

InsertField (Option B) only adds metadata fields (such as topic, partition, or timestamp) to the record payload and does not affect routing. TombstoneHandler (Option C) is used to manage null-value records, especially with compacted topics. HeaderFrom (Option D) copies fields into headers but does not change the target topic.

Therefore, RegexRouter is the only SMT that directly supports changing the output topic, as documented in the Kafka Connect SMT reference.

=========================

Kafka Connect can run in standalone mode or distributed mode. For simple tasks like reading logs from a file on a single host, standalone mode is recommended.

From Kafka Connect User Guide:

“Standalone mode is useful when running connectors on a single machine (e.g., for development or simple deployments like log collection from a local file).”

Distributed mode is preferred for scalability and fault tolerance but overkill for this use case.

For SASL/PLAIN authentication over SSL, the correct combination is:

security.protocol=SASL_SSL

sasl.jaas.config=...PlainLoginModule required username=... password=...

From Kafka Security Documentation:

“For SASL/PLAIN over SSL, configure security.protocol=SASL_SSL and provide login module configuration using sasl.jaas.config.”

Options B and D are incorrect because they do not pair the correct protocol with the authentication method.

To change the replication factor of an existing topic, you must perform a partition reassignment, because the replication factor is not directly modifiable via kafka-topics.sh. The kafka-reassign-partitions.sh tool is the official command-line utility to handle partition reassignments, including changing the replication factor.

This tool allows you to generate a reassignment JSON specifying new replica assignments per partition and then apply it.

From official documentation:

“To change the replication factor, use the kafka-reassign-partitions tool to assign the partitions to more or fewer brokers.”

Neither kafka-topics.sh nor kafka-reassign-topics.sh exists for this purpose, and kafka-recreate-topic.sh is not an official Kafka tool.

The ConsumerRebalanceListener lets you handle partition assignments and revocations during rebalances. This is critical for managing offsets, stateful processing, or external transactions.

From Kafka Consumer Rebalance Docs:

“Implementing ConsumerRebalanceListener allows your application to take action before and after partitions are reassigned.”

A is true: It lets your app react when partitions assigned to the consumer change.

B, C, and D are unrelated to consumer rebalancing directly.

Kafka Streams uses transactional producers to guarantee exactly-once semantics (EOS). This ensures that both the output records and state store updates are committed atomically, avoiding duplication or partial writes.

From Kafka Streams Documentation > Processing Guarantees:

“Kafka Streams leverages Kafka’s transactional APIs to commit the output records and internal state updates as a single atomic unit, thereby providing exactly-once semantics.”

Option A is incorrect because log compaction is not disabled for EOS.

Option C incorrectly describes a checkpointing system Kafka Streams does not use.

Option D refers to deduplication, which is not how EOS is achieved in Streams.