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Confluent CCDAK Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Application Testing | 8% | - Mocking and test utilities - Unit testing producers and consumers - Integration testing and test clusters |
| Topic 2: Application Observability | 13% | - Logging and monitoring metrics - Error diagnosis and troubleshooting - Tracing and performance tuning |
| Topic 3: Apache Kafka Fundamentals | 23% | - Delivery semantics: at-most-once, at-least-once, exactly-once - Core concepts: brokers, topics, partitions, replicas, offsets - Kafka architecture and data flow - Configuration basics and cluster setup |
| Topic 4: Kafka Connect | 15% | - Data transformation and integration patterns - Connect architecture: workers, connectors, tasks, converters - Source and sink connectors configuration |
| Topic 5: Apache Kafka Application Development | 28% | - Consumer API: configuration, offset management, consumer groups, rebalancing - Producer API: configuration, serialization, partitioning, error handling - Transactional messaging and idempotence - Schema management: Confluent Schema Registry, compatibility rules, evolution |
| Topic 6: Apache Kafka Streams | 12% | - Error handling and state management - Windowing and time semantics - Stream processing operations: map, filter, join, aggregation - Streams API concepts: topology, processors, state stores |
Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions:
Question #1
You use Kafka Connect with the JDBC source connector to extract data from a large database and push it into Kafka.
The database contains tens of tables, and the current connector is unable to process the data fast enough.
You add more Kafka Connect workers, but throughput doesn't improve.
What should you do next?
A. Add more Kafka brokers to the cluster.
B. Increase the value of the connector's property tasks.max.
C. Increase the number of Kafka partitions for the topics.
D. Modify the database schemas to enable horizontal sharding.
Question #2
(You are developing a Kafka Streams application with a complex topology that has multiple sources, processors, sinks, and sub-topologies.
You are working in a development environment and do not have access to a real Kafka cluster or topics.
You need to perform unit testing on your Kafka Streams application.
Which should you use?)
A. KafkaUnitTestDriver
B. TopologyTestDriver
C. TestProducer, TestConsumer
D. MockProducer, MockConsumer
Question #3
Kafka producers can batch messages going to the same partition.
Which statement is correct about producer batching?
A. Two or more broker failures will automatically disable batching on the producer.
B. Producers have a separate background thread for each batch.
C. Producers can include multiple batches in a single request to a broker.
D. Producers can only batch messages of the same size.
Question #4
(What are two stateless operations in the Kafka Streams API?
Select two.)
A. GroupBy
B. Join
C. Filter
D. Reduce
Question #5
Clients that connect to a Kafka cluster are required to specify one or more brokers in the bootstrap.servers parameter.
What is the primary advantage of specifying more than one broker?
A. It forces clients to enumerate every single broker in the cluster.
B. It provides the ability to wake up dormant brokers.
C. It provides redundancy in making the initial connection to the Kafka cluster.
D. It is the mechanism to distribute a topic's partitions across multiple brokers.
Solutions:
| Question #1 Correct Answer: B | Question #2 Correct Answer: B | Question #3 Correct Answer: C | Question #4 Correct Answer: A,C | Question #5 Correct Answer: C |


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