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Confluent CCDAK or Confluent Certified Developer for Apache Kafka Certification Examination is an industry-recognized certification credential for developers who want to demonstrate their expertise in using Apache Kafka to build and operate data streaming applications. CCDAK examination is designed to validate the developers' knowledge, skills, and abilities in designing, developing, and managing enterprise-grade streaming applications using Apache Kafka.

Confluent CCDAK (Confluent Certified Developer for Apache Kafka Certification Examination) Certification Exam is a valuable certification for developers who work with Kafka. CCDAK exam tests the skills and knowledge of developers in various aspects of Kafka, and passing it demonstrates proficiency in working with Kafka. Candidates can prepare for the exam by gaining theoretical knowledge and practical experience, and there are many resources available to help them do so.

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The CCDAK exam is a comprehensive assessment of a developer's knowledge of the Kafka ecosystem and its various components, such as Kafka Connect, Kafka Streams, and Schema Registry. CCDAK exam covers a broad range of topics, including Kafka architecture, data modeling, event-driven design, and security. Developers who pass the CCDAK exam will have demonstrated their ability to develop Kafka-based applications that are scalable, reliable, and secure, and they will be recognized as experts in the Kafka ecosystem. The CCDAK Certification is an essential credential for developers who wish to work with Kafka and Confluent's platform and is highly valued by organizations that use Kafka as their messaging and streaming platform.

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

NEW QUESTION # 76
What is a consequence of increasing the number of partitions in an existing Kafka topic?

A. Existing data will be redistributed across the new number of partitions temporarily increasing cluster load.
B. Records with the same key could be located in different partitions.
C. The acknowledgment process will increase latency for producers using acks=all.
D. Consumers will need to process data from more partitions which will significantly increase consumer lag.

Answer: D

Explanation:
Increasing partitions increasesparallelism, but also means:
* Consumers in a group may have to handlemore partitions, especially if the number of consumers is lower than the number of partitions.
* This can result inincreased lag, especially under high load.
FromKafka Topic Management Docs:
"Increasing the number of partitions increases consumer work, and if consumers can't keep up, lag can accumulate."
* A is false:existing data is not redistributed.
* B is false:records with the same key always map to the same partitionbased on hash.
* D is not directly impacted by the partition count.
Reference:Kafka Topic Management > Adding Partitions

NEW QUESTION # 77
When running a ksqlDB for connectors, what does the IF NOT EXISTS clause do?

A. Prevent the statement from executing if a connector with the supplied name does not exist.
B. Update the connector properties if a connector with the supplied name exists.
C. Fail if the specified connector does not exist.
D. Prevent the statement from failing if a connector with the supplied name already exists.

Answer: D

NEW QUESTION # 78
Which message delivery semantic is guaranteed by Kafka Connect?

A. At most once
B. At least once
C. Exactly once

Answer: B

NEW QUESTION # 79
A Kafka producer application wants to send log messages to a topic that does not include any key. What are the properties that are mandatory to configure for the producer configuration? (select three)

A. value
B. key.serializer
C. value.serializer
D. bootstrap.servers
E. key
F. partition

Answer: B,C,D

Explanation:
Both key and value serializer are mandatory.

NEW QUESTION # 80
You have a topic t1 with six partitions. You use Kafka Connect to send data from topic t1 in your Kafka cluster to Amazon S3. Kafka Connect is configured for two tasks.
How many partitions will each task process?

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

Answer: D

Explanation:
When using Kafka Connect with sink connectors (like S3 Sink),each task is assigned one or more topic partitions. Thetotal number of partitions (6)isevenly distributedacross the available tasks (2). Thus, each task will handle3 partitions.
FromKafka Connect Documentation:
"Kafka Connect divides the topic partitions among available tasks. For example, a topic with six partitions and two tasks results in each task handling three partitions." Reference:Kafka Connect Concepts > Tasks and Partitions

NEW QUESTION # 81
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