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Confluent CCDAK Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Apache Kafka Application Development	28%	- Producer API: configuration, serialization, partitioning, error handling - Transactional messaging and idempotence - Schema management: Confluent Schema Registry, compatibility rules, evolution - Consumer API: configuration, offset management, consumer groups, rebalancing
Topic 2: Apache Kafka Streams	12%	- Streams API concepts: topology, processors, state stores - Windowing and time semantics - Stream processing operations: map, filter, join, aggregation - Error handling and state management
Topic 3: Application Observability	13%	- Logging and monitoring metrics - Tracing and performance tuning - Error diagnosis and troubleshooting
Topic 4: Kafka Connect	15%	- Connect architecture: workers, connectors, tasks, converters - Data transformation and integration patterns - Source and sink connectors configuration
Topic 5: 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
Topic 6: Application Testing	8%	- Mocking and test utilities - Unit testing producers and consumers - Integration testing and test clusters

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Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q76-Q81):

NEW QUESTION # 76
How would you describe a connector in ksqlDB?

A. DESCRIBE ip_sum EXTENDED;
B. DESCRIBE connector_name CONNECTOR;
C. DESCRIBE CONNECTOR connector_name;
D. DROP CONNECTOR [IF EXISTS] connector_name;

Answer: C

NEW QUESTION # 77
You create a topic with five partitions.
What can be assumed about messages read from that topic by a single consumer group?

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

Answer: D

NEW QUESTION # 78
What data format isn't natively available with the Confluent REST Proxy?

A. json
B. avro
C. binary
D. protobuf

Answer: D

Explanation:
Protocol buffers isn't a natively supported type for the Confluent REST Proxy, but you may use the binary format instead

NEW QUESTION # 79
You create a topic named loT-Data with 10 partitions and replication factor of three.
A producer sends 1 MB messages compressed with Gzip.
Which two statements are true in this scenario?
(Select two.)

A. Compression type will be stored in batch attributes.
B. All compressed messages will be stored in the same topic partition.
C. By default, compression is the producer's responsibility.
D. The message is already compressed so it will not be serialized.

Answer: A,C

Explanation:
A: Kafka batches store compression metadata in their headers, indicating how the batch was compressed.
B: Compression is controlled via the producer config compression.type, which defaults to none. Producers explicitly set Gzip or other formats.
From Kafka Producer Docs:
"Compression is done by the producer, and the type is stored in the message batch metadata. The broker does not recompress." C is false: messages are serialized before compression.
D is false: messages without keys are distributed across multiple partitions.
Reference: Kafka Producer Configs > compression.type

NEW QUESTION # 80
You have a topic t1 in a Kafka cluster. A producer running on host A can successfully write messages to t1.
Then, you move that producer code to run on host B, but it fails writing messages to t1.
What is a likely reason for that failure?

A. The producer is connecting to a different broker in the same cluster.
B. Another producer started writing to t1.
C. Topic T1 no longer exists in the same environment as host B.
D. Kafka ACLs are not configured to allow host B's IP address.

Answer: D

NEW QUESTION # 81
......

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