Quiz Confluent - Authoritative CCDAK - Confluent Certified Developer for Apache Kafka Certification Examination Practice Questions

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The CCDAK certification exam is a valuable tool for both developers and organizations looking to build and maintain Kafka-based applications. With its comprehensive coverage of Kafka concepts and hands-on exercises, the exam provides a thorough evaluation of a developer's skills and knowledge, making it a highly respected and sought-after certification in the industry.

To prepare for the Confluent CCDAK Exam, developers can attend the Confluent Developer Training or take online courses, such as the Confluent Cloud Fundamentals for Developers course, which is available on Udemy. They can also refer to the official documentation and practice using Kafka clusters, producers, and consumers. There are also practice exams available online to help developers prepare for the certification exam.

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Confluent Certified Developer for Apache Kafka (CCDAK) Certification Examination is designed for developers who wish to demonstrate their expertise in developing Apache Kafka-based applications using Confluent's platform. Confluent is a leading provider of Apache Kafka-based solutions, and the CCDAK Certification confirms that developers have the necessary skills to design, develop, and troubleshoot Kafka-based applications using Confluent's platform.

Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q17-Q22):

NEW QUESTION # 17
Match the topic configuration setting with the reason the setting affects topic durability.
(You are given settings like unclean.leader.election.enable=false, replication.factor, min.insync.replicas=2)

Answer:

Explanation:

Explanation:
unclean.leader.election.enable=false # Prevents data loss by only considering in-sync replicas when rebalancing.
replication.factor # Specifies how many redundant copies of partitions are distributed across brokers.
min.insync.replicas=2 # Sets the standard for the number of partition instances that must keep up with the latest committed message.
unclean.leader.election.enable=false ensures that only in-sync replicas can be elected as leaders. If disabled, an out-of-sync replica may become leader, potentially leading to data loss.
replication.factor defines how many brokers will maintain copies of each partition, directly impacting durability and availability.
min.insync.replicas determines how many replicas must acknowledge a write when acks=all is used, enforcing write durability.
Reference: Apache Kafka Topic Configuration Documentation


NEW QUESTION # 18
You are working on a Kafka cluster with three nodes. You create a topic named orders with:
replication.factor = 3
min.insync.replicas = 2
acks = allWhat exception will be generated if two brokers are down due to network delay?

Answer: C

Explanation:
With acks=all and min.insync.replicas=2, Kafka requires at least two in-sync replicas to acknowledge a write.
If only one broker is alive, the condition fails, and NotEnoughReplicasException is thrown by the producer.
From Kafka Producer Exception Docs:
"NotEnoughReplicasException is thrown when the number of in-sync replicas is insufficient to satisfy acks=all with min.insync.replicas." NetworkException is generic and not raised here.
NotCoordinatorException is related to consumer group coordination.
NotLeaderForPartitionException is unrelated unless accessing an unassigned leader.
Reference: Kafka Producer Error Handling


NEW QUESTION # 19
You need to explain the best reason to implement the consumer callback interface ConsumerRebalanceListener prior to a Consumer Group Rebalance.
Which statement is correct?

Answer: C

Explanation:
The ConsumerRebalanceListener lets you handle partition assignments and revocations during rebalances.
This is critical for managing offsets, stateful processing, or external transactions.
From Kafka 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 partitions assigned to the consumer change.
B, C, and D are unrelated to consumer rebalancing directly.
Reference: Kafka Consumer JavaDocs > ConsumerRebalanceListener


NEW QUESTION # 20
In Kafka, what are Topics split into?

Answer: B


NEW QUESTION # 21
You are building a system for a retail store selling products to customers.
Which three datasets should you model as a GlobalKTable?
(Select three.)

Answer: A,B,E

Explanation:
AGlobalKTableis a replicated, read-only table available in full on all instances. It's best forreference or lookup datasetssuch as:
* Product catalog
* Customer profiles
* Warehouse inventory
FromKafka Streams Developer Guide:
"Use GlobalKTable when you need to perform joins using non-partition-aligned reference data that's small enough to replicate."
* Purchases and transactions are high-throughput, time-sensitive streams, not static reference data.
Reference:Kafka Streams Concepts > GlobalKTable


NEW QUESTION # 22
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