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Confluent CCDAK Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Kafka Connect | 15% | - Data transformation and integration patterns - Connect architecture: workers, connectors, tasks, converters - Source and sink connectors configuration |
| Application Testing | 8% | - Mocking and test utilities - Integration testing and test clusters - Unit testing producers and consumers |
| Apache Kafka Application Development | 28% | - Consumer API: configuration, offset management, consumer groups, rebalancing - Transactional messaging and idempotence - Producer API: configuration, serialization, partitioning, error handling - Schema management: Confluent Schema Registry, compatibility rules, evolution |
| Application Observability | 13% | - Tracing and performance tuning - Error diagnosis and troubleshooting - Logging and monitoring metrics |
| Apache Kafka Streams | 12% | - Streams API concepts: topology, processors, state stores - Windowing and time semantics - Error handling and state management - Stream processing operations: map, filter, join, aggregation |
| Apache Kafka Fundamentals | 23% | - Core concepts: brokers, topics, partitions, replicas, offsets - Delivery semantics: at-most-once, at-least-once, exactly-once - Kafka architecture and data flow - Configuration basics and cluster setup |
Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions:
1. You are writing a producer application and need to ensure proper delivery. You configure the producer with acks=all.
Which two actions should you take to ensure proper error handling?
(Select two.)
A) Use a callback argument in producer.send() where you check delivery status.
B) Check the value of ProducerRecord.status().
C) Surround the call of producer.send() with a try/catch block to catch KafkaException.
D) Check that producer.send() returned a RecordMetadata object and is not null.
2. Your application is consuming from a topic with one consumer group.
The number of running consumers is equal to the number of partitions.
Application logs show that some consumers are leaving the consumer group during peak time, triggering a rebalance. You also notice that your application is processing many duplicates.
You need to stop consumers from leaving the consumer group.
What should you do?
A) Add more consumer instances.
B) Reduce max.poll.records property.
C) Increase session.timeout.ms property.
D) Split consumers in different consumer groups.
3. You need to collect logs from a host and write them to a Kafka topic named 'logs-topic'. You decide to use Kafka Connect File Source connector for this task.
What is the preferred deployment mode for this connector?
A) Parallel mode
B) Standalone mode
C) SingleCluster mode
D) Distributed mode
4. You need to explain the best reason to implement the consumer callback interface ConsumerRebalanceListener prior to a Consumer Group Rebalance.
Which statement is correct?
A) Previous log files are deleted.
B) Offsets are compacted.
C) Partition leaders may change.
D) Partitions assigned to a consumer may change.
5. The producer code below features a Callback class with a method called onCompletion().
In the onCompletion() method, when the request is completed successfully, what does the value metadata.
offset() represent?
A) The ID of the partition to which the message was committed
B) Its position in the producer's batch of messages
C) The number of bytes that overflowed beyond a producer batch of messages
D) The sequential ID of the message committed into a partition
Solutions:
| Question # 1 Answer: A,C | Question # 2 Answer: C | Question # 3 Answer: B | Question # 4 Answer: D | Question # 5 Answer: D |


