CCDAK Exam Quiz, CCDAK Test Vce

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Confluent CCDAK Certification Exam is designed to be challenging and covers a variety of topics, including Kafka core concepts, Kafka ecosystem, developing Kafka producers and consumers, Kafka Connect, Kafka Streams, and several other application development and testing topics. Candidates who pass the certification exam will have demonstrated proficiency in working with the Confluent platform to develop and deploy Kafka-based applications, creating and using Avro schemas, and leveraging various Kafka tools and frameworks.

By passing the CCDAK Certification Exam, developers can demonstrate their proficiency in working with Apache Kafka and gain recognition for their skills in the industry. Confluent Certified Developer for Apache Kafka Certification Examination certification can help developers advance their careers and increase their earning potential, as well as help organizations identify and hire qualified Kafka developers.

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The CCDAK certification exam is a hands-on exam that tests the candidate's ability to apply their technical knowledge to real-world scenarios. CCDAK exam covers topics such as Kafka installation and configuration, producer and consumer development, stream processing, and Kafka security. Candidates must demonstrate their ability to design, develop, and deploy Kafka-based solutions in a distributed environment. The CCDAK Certification is an excellent way for developers to demonstrate their expertise in Apache Kafka and advance their career in Kafka-based application development.

Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q48-Q53):

NEW QUESTION # 48
A bank uses a Kafka cluster for credit card payments. What should be the value of the property unclean.leader.election.enable?

Answer: A

Explanation:
Setting unclean.leader.election.enable to true means we allow out-of-sync replicas to become leaders, we will lose messages when this occurs, effectively losing credit card payments and making our customers very angry.


NEW QUESTION # 49
Which two statements are correct about transactions in Kafka?
(Select two.)

Answer: C,D

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
# C. Consumers can consume both committed and uncommitted transactions.By default, Kafka consumers only read committed messages if they are configured with isolation.level=read_committed. However, if configured as read_uncommitted, they can also consume uncommitted (potentially aborted) transactional messages.
From Kafka Documentation:
"The isolation.level setting controls whether the consumer will read only committed messages or all messages, including uncommitted messages from ongoing or aborted transactions."
# D. Information about producers and their transactions is stored in the _transaction_state topic.Kafka uses an internal topic named __transaction_state to maintain metadata about producer transactions. This topic is essential for tracking the transaction lifecycle, fencing, and recovery.
From Kafka Internals:
"Kafka stores the state of active and completed transactions in an internal topic called __transaction_state."


NEW QUESTION # 50
You create a topic with five partitions.
What can be assumed about messages read from that topic by a single consumer group?

Answer: D


NEW QUESTION # 51
You use Kafka Connect with the JDBC source connector to extract data from a large database and push it into Kafka.
The database contains tens of tables, and the current connector is unable to process the data fast enough.
You add more Kafka Connect workers, but throughput doesn't improve.
What should you do next?

Answer: D

Explanation:
Increasing tasks.max allows the connector to create multiple tasks, each responsible for processing different tables or table partitions. If only one task is used, adding more workers has no effect.
From Kafka Connect JDBC Connector Docs:
"Use tasks.max to configure how many tasks are created for the connector. Each task can process a subset of the data." A and C help only if the bottleneck is in Kafka, not Connect.
D is a large architectural change, not the first step.
Reference: Kafka Connect JDBC Connector Configuration


NEW QUESTION # 52
What happens when broker.rack configuration is provided in broker configuration in Kafka cluster?

Answer: C

Explanation:
Partitions for newly created topics are assigned in a rack alternating manner, this is the only change broker.rack does


NEW QUESTION # 53
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