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Confluent CCDAK Exam Syllabus Topics:

Section	Objectives
Kafka Ecosystem and Confluent Platform	- Schema Registry 1. Avro, Protobuf, JSON Schema usage - ksqlDB and connectors 1. Kafka Connect basics 2. Stream querying concepts
Kafka Producers and Consumers	- Consumer API 1. Rebalancing and offset commits 2. Consumer groups - Producer API 1. Reliability and acknowledgments 2. Serialization and partitioning strategies
Kafka Fundamentals	- Data flow in Kafka 1. Offset management 2. Producer and consumer model - Kafka architecture and core concepts 1. Brokers, topics, partitions 2. Replication and fault tolerance
Kafka Streams and Processing	- Kafka Streams API 1. Stateful vs stateless processing 2. Stream processing fundamentals - Event processing patterns 1. Exactly-once semantics 2. Windowing and aggregation

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Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q10-Q15):

NEW QUESTION # 10
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. Reduce max.poll.records property.
D. Split consumers in different consumer groups.

Answer: B

Explanation:
If the consumer fails to send heartbeats in time (due to being slow under load), it is considereddead, causing a rebalance. Increasing session.timeout.ms gives the consumermore time to process messages and send heartbeats, preventing premature removal.
FromKafka Docs > Heartbeats and Failures:
"If the consumer does not send a heartbeat in session.timeout.ms, it is considered dead and the group coordinator will trigger a rebalance." Reducing max.poll.records mightslow consumption further. More consumers won't help since each partition already has a dedicated consumer.
Reference:Apache Kafka Consumer Configs > session.timeout.ms

NEW QUESTION # 11
A kafka topic has a replication factor of 3 and min.insync.replicas setting of 2. How many brokers can go down before a producer with acks=all can't produce?

A. 0
B. 1
C. 2
D. 3

Answer: D

Explanation:
acks=all and min.insync.replicas=2 means we must have at least 2 brokers up for the partition to be available

NEW QUESTION # 12
You want to send a message of size 3 MB to a topic with default message size configuration. How does KafkaProducer handle large messages?

A. MessageSizeTooLarge exception will be thrown, KafkaProducer retries until the number of retries are exhausted
B. KafkaProducer divides messages into sizes of max.request.size and sends them in order
C. MessageSizeTooLarge exception will be thrown, KafkaProducer will not retry and return exception immediately
D. KafkaProducer divides messages into sizes of message.max.bytes and sends them in order

Answer: C

Explanation:
MessageSizeTooLarge is not a retryable exception.

NEW QUESTION # 13
What is the disadvantage of request/response communication?

A. Scalability
B. Coupling
C. Cost
D. Reliability

Answer: B

Explanation:
Point-to-point (request-response) style will couple client to the server.

NEW QUESTION # 14
How will you find out all the partitions where one or more of the replicas for the partition are not in-sync with the leader?

A. kafka-topics.sh --bootstrap-server localhost:9092 --describe --unavailable- partitions
B. kafka-topics.sh --zookeeper localhost:2181 --describe --under-replicated-partitions
C. kafka-topics.sh --broker-list localhost:9092 --describe --under-replicated-partitions
D. kafka-topics.sh --zookeeper localhost:2181 --describe --unavailable- partitions

Answer: B

NEW QUESTION # 15
......

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