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The CCDAK exam covers a wide range of topics, including Kafka architecture and components, data modeling and serialization, producer and consumer APIs, Kafka Connect, Kafka Streams, and security. CCDAK exam consists of 60 multiple-choice questions and must be completed within two hours. Candidates who pass the exam will receive a Confluent Certified Developer for Apache Kafka certificate, which is valid for two years. The CCDAK Certification is a rigorous exam that requires a deep understanding of Kafka's architecture and APIs, and passing it is a significant achievement for any developer.

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The CCDAK Certification Exam is an important certification for developers who want to work with Kafka and Confluent's platform. It demonstrates to employers and clients that a developer has the skills and knowledge necessary to build and manage Kafka-based applications using Confluent's platform. In addition, the certification can help developers advance their careers and increase their earning potential.

Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q18-Q23):

NEW QUESTION # 18
Consumer failed to process record # 10 and succeeded in processing record # 11. Select the course of action that you should choose to guarantee at least once processing

A. Commit offsets at 11
B. Do not commit until successfully processing the record #10
C. Commit offsets at 10

Answer: A

Explanation:
Here, you shouldn't commit offsets 11 or 10 as it would indicate that the message #10 has been processed successfully.

NEW QUESTION # 19
In Kafka, every broker... (select three)

A. is a controller
B. is a bootstrap broker
C. knows all the metadata for all topics and partitions
D. contains only a subset of the topics and the partitions
E. knows the metadata for the topics and partitions it has on its disk
F. contains all the topics and all the partitions

Answer: B,C,D

Explanation:
Kafka topics are divided into partitions and spread across brokers. Each brokers knows about all the metadata and each broker is a bootstrap broker, but only one of them is elected controller

NEW QUESTION # 20
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

Answer: D

Explanation:
Kafka Connect can run instandalone modeordistributed mode. For simple tasks likereading logs from a file on a single host,standalone modeis recommended.
FromKafka 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 # 21
What are three built-in abstractions in the Kafka Streams DSL?
(Select three.)

A. GlobalKTable
B. KStream
C. GlobalKStream
D. StreamTable
E. KTable

Answer: A,B,E

Explanation:
The Kafka Streams DSL provides three primary abstractions:
KStream: Represents an unbounded stream of records (append-only).
KTable: Represents a changelog stream where each key has the latest value (like a materialized view).
GlobalKTable: A fully replicated version of KTable across all stream instances, enabling global joins.
From Kafka Streams Developer Guide:
"Kafka Streams provides three core abstractions: KStream, KTable, and GlobalKTable, each serving different purposes in stream processing and joins." GlobalKStream and StreamTable do not exist in Kafka's API.
Reference: Kafka Streams Concepts > KStream, KTable, GlobalKTable

NEW QUESTION # 22
You have a consumer group with default configuration settings reading messages from your Kafka cluster.
You want to optimize its throughput so the consumer group processes more messages in the same amount of time.
Which changes increase the consumption throughput?

A. Decrease the session timeout of each consumer.
B. Remove some consumers from the consumer group.
C. Increase the number of bytes the consumers read with each fetch request.
D. Disable auto commit and have the consumers manually commit offsets.

Answer: C

NEW QUESTION # 23
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