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Confluent CCDAK Exam Syllabus Topics:

Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions:

1. (You are designing a stream pipeline to monitor the real-time location of GPS trackers, where historical location data is not required.
Each event has:
* Key: trackerId
* Value: latitude, longitude
You need to ensure that the latest location for each tracker is always retained in the Kafka topic.
Which topic configuration parameter should you set?)

A) retention.ms=0
B) min.cleanable.dirty.ratio=-1
C) retention.ms=infinite
D) cleanup.policy=compact

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) Split consumers in different consumer groups.
B) Reduce max.poll.records property.
C) Add more consumer instances.
D) Increase session.timeout.ms property.

3. (You create a topic with five partitions.
What can you assume about messages read from that topic by a single consumer group?)

A) Messages from one partition can be consumed by any of the consumers in a group for faster processing.
B) All messages will be read from exactly one broker by the consumer group.
C) The consumer group can only read the same number of messages from all the partitions.
D) Messages can be consumed by a maximum of five consumers in the same consumer group.

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) Partitions assigned to a consumer may change.
B) Offsets are compacted.
C) Partition leaders may change.
D) Previous log files are deleted.

5. (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) Check the value of ProducerRecord.status().
B) Surround the call to producer.send() with a try/catch block to catch KafkaException.
C) Use a callback argument in producer.send() where you check delivery status.
D) Check that producer.send() returned a RecordMetadata object and is not null.

Solutions: