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Confluent CCDAK Exam Overview:

Certification Vendor:	Confluent
Exam Name:	Confluent Certified Developer for Apache Kafka Certification Examination
Exam Number:	CCDAK
Exam Price:	$150 USD
Certificate Validity Period:	2 years
Available Languages:	English
Related Certifications:	Confluent Cloud Certified Operator (CCAC) Confluent Certified Administrator for Apache Kafka (CCAAK)
Exam Duration:	90 minutes
Real Exam Qty:	60
Exam Format:	Multiple-choice, Matching, List order
Passing Score:	Pass / Fail
Recommended Training:	Confluent Documentation Confluent Developer Training for Apache Kafka
Exam Registration:	Confluent Certification Portal
Sample Questions:	Confluent CCDAK Sample Questions
Exam Way:	Remote proctored online exam; requires webcam, microphone, Google Chrome browser
Pre Condition:	No mandatory prerequisites; recommended experience: 6+ months developing applications with Apache Kafka
Official Syllabus URL:	https://www.confluent.io/certification/

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Confluent Certified Developer for Apache Kafka (CCDAK) Certification Examination is an industry-recognized certification that enables professionals to demonstrate their understanding of Apache Kafka and its ecosystem. CCDAK examination is developed and administered by Confluent, a leading provider of Apache Kafka-based solutions. The CCDAK Certification is designed for developers who work with Apache Kafka and want to validate their skills and knowledge of the platform.

Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q50-Q55):

NEW QUESTION # 50
Which of the following is a push query?

A. SELECT windowstart, windowend, item_id, SUM(quantity)
FROM orders
WINDOW TUMBLING (SIZE 20 SECONDS)
GROUP BY item_id
EMIT CHANGES;
B. SELECT *
FROM NUMBER_OF_TESTS
WHERE ID='10';
C. CREATE TABLE LEFT_TABLE (ID BIGINT PRIMARY KEY, NAME varchar, VALUE bigint) WITH (kafka_topic='left_topic', value_format='JSON', partitions=4);
D. CREATE STREAM STUDENTS (ID STRING KEY, SCORE INT)
WITH (kafka_topic='students_topic', value_format='JSON', partitions=4);

Answer: A

NEW QUESTION # 51
If I produce to a topic that does not exist, and the broker setting auto.create.topic.enable=true, what will happen?

A. Kafka will automatically create the topic with num.partitions=#of brokers and replication.factor=3
B. Kafka will automatically create the topic with 1 partition and 1 replication factor
C. Kafka will automatically create the topic with the broker settings num.partitions and default.replication.
factor
D. Kafka will automatically create the topic with the indicated producer settings num.partitions and default.
replication.factor

Answer: C

Explanation:
The broker settings comes into play when a topic is auto created

NEW QUESTION # 52
There are five brokers in a cluster, a topic with 10 partitions and replication factor of 3, and a quota of producer_bytes_rate of 1 MB/sec has been specified for the client. What is the maximum throughput allowed for the client?

A. 10 MB/s
B. 5 MB/s
C. 1 MB/s
D. 0.33 MB/s

Answer: B

Explanation:
Each producer is allowed to produce @ 1MB/s to a broker. Max throughput 5 * 1MB, because we have 5 brokers.

NEW QUESTION # 53
When using the Confluent Kafka Distribution, where does the schema registry reside?

A. As an in-memory plugin on your Zookeeper cluster
B. As a separate JVM component
C. As an in-memory plugin on your Kafka Connect Workers
D. As an in-memory plugin on your Kafka Brokers

Answer: B

Explanation:
Schema registry is a separate application that provides RESTful interface for storing and retrieving Avro schemas.

NEW QUESTION # 54
(You have a Kafka consumer in production actively reading from a critical topic from which multiple other applications are consuming.
You have a new requirement to update the offset of your consumer to start reading from the beginning of the topic.
Which action would you take?)

A. Temporarily configure the topic's retention.ms parameter to 0 to empty the topic.
B. Start a new consumer application with the same consumer group id.
C. Update the consumer configuration by setting the auto.offset.reset property to earliest.
D. Update the consumer group's offset to the earliest position using the kafka-consumer-groups CLI tool.

Answer: D

Explanation:
The Apache Kafka documentation states that consumer offsets are stored per consumer group and must be explicitly reset if an application needs to reprocess data from an earlier position. The officially supported and safest way to reset offsets for an existing consumer group is by using the kafka-consumer-groups CLI tool with the --reset-offsets option and the --to-earliest flag.
Setting auto.offset.reset=earliest (Option D) only applies when no committed offset exists for a partition.
Since this consumer is already running in production, offsets are already committed, making this option ineffective. Option C does not change offsets because Kafka identifies consumers by group ID, not application instance. Option B is extremely dangerous and incorrect, as setting retention.ms=0 deletes data for all consumers and impacts other applications.
Therefore, using the CLI to reset offsets for the specific consumer group ensures controlled, auditable, and targeted offset management without affecting other consumers or the topic itself. This approach is explicitly documented in Kafka's consumer group administration tools.

NEW QUESTION # 55
......

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