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The CCDAK certification exam covers a wide range of topics related to Apache Kafka, including core Kafka concepts, Kafka cluster management, Kafka Streams, and Kafka Connect. CCDAK exam also includes hands-on exercises that require developers to demonstrate their ability to apply their knowledge of Kafka to real-world scenarios.

Confluent CCDAK certification exam covers a wide range of topics related to Kafka, including Kafka architecture, Kafka clusters, Kafka streams, Kafka security, and Kafka monitoring. Confluent Certified Developer for Apache Kafka Certification Examination certification exam is designed for developers who have experience with Kafka and want to validate their skills and knowledge in the field. CCDAK Exam is designed to test the understanding and expertise of developers in Kafka and related technologies.

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The CCDAK exam covers a wide range of topics, including Kafka architecture, data modeling, stream processing, and security. CCDAK examination comprises multiple-choice questions and hands-on exercises that require the candidate to demonstrate their practical knowledge of Kafka. Successful completion of the CCDAK Exam certifies that the individual has the expertise to design, build, and maintain Kafka-based solutions, making them a valuable asset to any organization that uses Kafka for data processing and messaging.

Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q61-Q66):

NEW QUESTION # 61
What is the function of Kafka Connect Converters?

Answer: A


NEW QUESTION # 62
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.)

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 # 63
Which statement is true about how exactly-once semantics (EOS) work in Kafka Streams?

Answer: C

Explanation:
Kafka Streams usestransactional producersto guaranteeexactly-once semantics (EOS). This ensures that both theoutput recordsandstate store updatesare committed atomically, avoiding duplication or partial writes.
FromKafka Streams Documentation > Processing Guarantees:
"Kafka Streams leveragesKafka's transactional APIsto commit the output records and internal state updates as a single atomic unit, thereby providing exactly-once semantics."
* Option A is incorrect because log compaction is not disabled for EOS.
* Option C incorrectly describes a checkpointing system Kafka Streams does not use.
* Option D refers to deduplication, which is not how EOS is achieved in Streams.
Reference:Kafka Streams Processing Guarantees


NEW QUESTION # 64
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?

Answer: D

Explanation:
Kafka Connect can run in standalone mode or distributed mode. For simple tasks like reading logs from a file on a single host, standalone mode is recommended.
From Kafka Connect User Guide:
"Standalone mode is useful when running connectors on a single machine (e.g., for development or simple deployments like log collection from a local file)." Distributed mode is preferred for scalability and fault tolerance but overkill for this use case.
Reference: Kafka Connect User Guide > Deployment Modes


NEW QUESTION # 65
When using plain JSON data with Connect, you see the following error messageorg.apache.kafka.connect.errors.DataExceptionJsonDeserializer with schemas.enable requires "schema" and "payload" fields and may not contain additional fields. How will you fix the error?

Answer: A

Explanation:
You will need to set the schemas.enable parameters for the converter to false for plain text with no schema.


NEW QUESTION # 66
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