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Confluent Certified Developer for Apache Kafka (CCDAK) certification exam is intended for developers who want to demonstrate their expertise in building and implementing applications that use Apache Kafka. CCDAK Exam is designed to test the developer's knowledge of Kafka's key concepts, architecture, and APIs. The CCDAK certification is a valuable credential that can help developers stand out in the job market and demonstrate their ability to develop robust and reliable Kafka applications.

By becoming certified, developers can demonstrate their proficiency in Apache Kafka and differentiate themselves from their peers. Confluent Certified Developer for Apache Kafka Certification Examination certification showcases the candidate's knowledge and validates their ability to design and develop high-quality streaming applications using Kafka. Furthermore, it helps organizations to identify individuals with the necessary skills and expertise to design and build data streaming applications, which is essential for addressing business problems in real-time.

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Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q71-Q76):

NEW QUESTION # 71
To get acknowledgement of writes to only the leader partition, we need to use the config...

A. acks=1
B. acks=0
C. acks=all

Answer: A

Explanation:
Producers can set acks=1 to get acknowledgement from partition leader only.

NEW QUESTION # 72
You need to consume messages from Kafka using the command-line interface (CLI).
Which command should you use?

A. kafka-consumer
B. kafka-get-messages
C. kafka-consume
D. kafka-console-consumer

Answer: D

Explanation:
The official CLI utility for consuming messages from Kafka topics is kafka-console-consumer.sh. It connects to the broker, consumes messages, and prints them to standard output.
FromKafka CLI Tools Documentation:
"kafka-console-consumer.sh is used to read data from a Kafka topic and write it to standard output." The other options are not valid Kafka CLI tools.
Reference:Apache Kafka Documentation > kafka-console-consumer.sh

NEW QUESTION # 73
In Java, Avro SpecificRecords classes are

A. written manually by the programmer
B. automatically generated from an Avro Schema + a Maven / Gradle Plugin
C. automatically generated from an Avro Schema

Answer: B

Explanation:
SpecificRecord is created from generated record classes

NEW QUESTION # 74
(A consumer application needs to use an at-most-once delivery semantic.
What is the best consumer configuration and code skeleton to avoid duplicate messages being read?)

A. auto.offset.reset=latest and enable.auto.commit=truewhile (true) {final var records = consumer.poll (POLL_TIMEOUT);for (var record : records) {// Any processing}consumer.commitAsync();}
B. auto.offset.reset=earliest and enable.auto.commit=falsewhile (true) {final var records = consumer.poll (POLL_TIMEOUT);consumer.commitAsync();for (var record : records) {// Any processing}}
C. auto.offset.reset=earliest and enable.auto.commit=truewhile (true) {final var records = consumer.poll (POLL_TIMEOUT);consumer.commitAsync();for (var record : records) {// Any processing}}
D. auto.offset.reset=earliest and enable.auto.commit=falsewhile (true) {final var records = consumer.poll (POLL_TIMEOUT);for (var record : records) {// Any processing}consumer.commitAsync();}

Answer: B

Explanation:
According to the official Apache Kafka consumer semantics documentation, at-most-once delivery means that records may be lost but must never be processed more than once. To achieve this guarantee, a consumer must commit offsets before processing records. If the application crashes after committing but before processing, messages are skipped rather than reprocessed, which satisfies at-most-once semantics.
Option B correctly implements this pattern. It disables automatic offset commits (enable.auto.commit=false) and explicitly calls commitAsync() immediately after polling and before processing records. This ensures that offsets are advanced regardless of whether processing succeeds, eliminating the possibility of duplicate processing.
Option C represents at-least-once semantics, because offsets are committed after processing, which can lead to duplicates on failure. Options A and D rely on automatic commits or incorrect ordering and do not provide strict at-most-once guarantees.
The Kafka documentation explicitly states that manual offset management with commits before processing is required for at-most-once delivery.
Therefore, Option B is the best and officially documented configuration and code skeleton to avoid duplicate message processing.

NEW QUESTION # 75
You need to explain the best reason to implement the consumer callback interface ConsumerRebalanceListener prior to a Consumer Group Rebalance.
Which statement is correct?

A. Offsets are compacted.
B. Partitions assigned to a consumer may change.
C. Previous log files are deleted.
D. Partition leaders may change.

Answer: B

Explanation:
The ConsumerRebalanceListener lets youhandle partition assignments and revocationsduring rebalances.
This is critical for managingoffsets,stateful processing, orexternal transactions.
FromKafka Consumer Rebalance Docs:
"Implementing ConsumerRebalanceListener allows your application to take action before and after partitions are reassigned."
* A is true: It lets your app react when partitionsassigned to the consumer change.
* B, C, and D are unrelated to consumer rebalancing directly.
Reference:Kafka Consumer JavaDocs > ConsumerRebalanceListener

NEW QUESTION # 76
......

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CCDAK Online Training Materials - Latest Test CCDAK Simulations

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Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q71-Q76):

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