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Preparing for the CCDAK exam requires a deep understanding of Apache Kafka architecture, programming languages, and Kafka APIs. Developers can prepare for the exam by taking courses and training programs offered by Confluent, reading Kafka documentation, and practicing with sample applications. Passing the CCDAK Exam will validate a developer's proficiency in developing Kafka-based applications and open up new career opportunities in the growing field of real-time data processing.

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The Confluent CCDAK certification is on trending nowadays, and many Confluent aspirants are trying to get it. Success in the CCDAK test helps you land well-paying jobs. Additionally, the CCDAK certification exam is also beneficial to get promotions in your current company. But the main problem that every applicant faces while preparing for the CCDAK Certification test is not finding updated Confluent Certified Developer for Apache Kafka Certification Examination (CCDAK) practice questions.

Confluent CCDAK exam is a performance-based exam that tests the developer’s ability to create and manage Kafka clusters, design and develop Kafka producers and consumers, and configure Kafka security. CCDAK Exam consists of 60 multiple-choice and multiple-response questions that need to be completed in 90 minutes. CCDAK exam is conducted online and can be taken from anywhere in the world.

Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q59-Q64):

NEW QUESTION # 59
You are receiving orders from different customer in an "orders" topic with multiple partitions. Each message has the customer name as the key. There is a special customer named ABC that generates a lot of orders and you would like to reserve a partition exclusively for ABC. The rest of the message should be distributed among other partitions. How can this be achieved?

A. Define a Kafka Broker routing rule
B. Create a custom partitioner
C. All messages with the same key will go the same partition, but the same partition may have messages with different keys. It is not possible to reserve
D. Add metadata to the producer record

Answer: B

Explanation:
A Custom Partitioner allows you to easily customise how the partition number gets computed from a source message.

NEW QUESTION # 60
In Avro, removing a field that does not have a default is a __ schema evolution

A. breaking
B. backward
C. forward
D. full

Answer: B

Explanation:
Clients with new schema will be able to read records saved with old schema.

NEW QUESTION # 61
A producer is sending messages with null key to a topic with 6 partitions using the DefaultPartitioner. Where will the messages be stored?

A. The partition for the null key
B. Any of the topic partitions
C. Partition 0
D. Partition 5

Answer: D

Explanation:
Message with no keys will be stored with round-robin strategy among partitions.

NEW QUESTION # 62
A consumer wants to read messages from partitions 0 and 1 of a topic topic1. Code snippet is shown below.
consumer.subscribe(Arrays.asList("topic1"));
List<TopicPartition> pc = new ArrayList<>();
pc.add(new PartitionTopic("topic1", 0));
pc.add(new PartitionTopic("topic1", 1));
consumer.assign(pc);

A. This works fine. subscribe() will subscribe to the topic and assign() will assign partitions to the consumer.
B. Throws IllegalStateException

Answer: B

Explanation:
subscribe() and assign() cannot be called by the same consumer, subscribe() is used to leverage the consumer group mechanism, while assign() is used to manually control partition assignment and reads assignment

NEW QUESTION # 63
To prevent network-induced duplicates when producing to Kafka, I should use

A. retries=200000
B. enable.idempotence=true
C. batch.size=1
D. max.in.flight.requests.per.connection=1

Answer: B

Explanation:
Producer idempotence helps prevent the network introduced duplicates. More details herehttps://cwiki.apache.org/confluence/display/KAFKA/Idempotent+Producer

NEW QUESTION # 64
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