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Confluent CCDAK Exam Syllabus Topics:

Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions:

1. 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) Distributed mode
B) SingleCluster mode
C) Parallel mode
D) Standalone mode

2. Which two statements about Kafka Connect Single Message Transforms (SMTs) are correct?
(Select two.)

A) Masking data is a good example of an SMT.
B) Multiple SMTs can be chained together and act on source or sink messages.
C) SMTs are often used to join multiple records from a source data system into a single Kafka record.
D) SMT functionality is included within Kafka Connect converters.

3. 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) Increase session.timeout.ms property.
C) Split consumers in different consumer groups.
D) Reduce max.poll.records property.

4. You have a Kafka client application that has real-time processing requirements.
Which Kafka metric should you monitor?

A) Aggregate incoming byte rate
B) Consumer lag between brokers and consumers
C) Consumer heartbeat rate to group coordinator
D) Total time to serve requests to replica followers

5. Which is true about topic compaction?

A) Compaction will keep exactly one message per key after compaction of inactive log segments.
B) When a client produces a new event with an existing key, the broker immediately deletes the offset of the existing event.
C) Topic compaction does not remove old events; instead, when clients consume events from a compacted topic, they store events in a hashmap that maintains the latest value.
D) When a client produces a new event with an existing key, the old value is overwritten with the new value in the compacted log segment.

Solutions: