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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.

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Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q21-Q26):

NEW QUESTION # 21
You are running a Kafka Streams application in a Docker container managed by Kubernetes, and upon application restart, it takes a long time for the docker container to replicate the state and get back to processing the dat a. How can you improve dramatically the application restart?

• A. Increase the number of partitions in your inputs topic
• B. Increase the number of Streams threads
• C. Reduce the Streams caching property
• D. Mount a persistent volume for your RocksDB

Answer: D

Explanation:
Although any Kafka Streams application is stateless as the state is stored in Kafka, it can take a while and lots of resources to recover the state from Kafka. In order to speed up recovery, it is advised to store the Kafka Streams state on a persistent volume, so that only the missing part of the state needs to be recovered.

 

NEW QUESTION # 22
You create a topic named loT-Data with 10 partitions and replication factor of three.
A producer sends 1 MB messages compressed with Gzip.
Which two statements are true in this scenario?
(Select two.)

• A. All compressed messages will be stored in the same topic partition.
• B. Compression type will be stored in batch attributes.
• C. By default, compression is the producer's responsibility.
• D. The message is already compressed so it will not be serialized.

Answer: B,C

Explanation:
* A:Kafka batches storecompression metadata in their headers, indicating how the batch was compressed.
* B:Compression is controlled via theproducer config compression.type, which defaults to none.
Producers explicitly set Gzip or other formats.
FromKafka Producer Docs:
"Compression is done by the producer, and the type is stored in the message batch metadata. The broker does not recompress."
* C is false: messages are serializedbeforecompression.
* D is false: messages without keys are distributed acrossmultiple partitions.
Reference:Kafka Producer Configs > compression.type

 

NEW QUESTION # 23
To enhance compression, I can increase the chances of batching by using

• A. max.message.size=10MB
• B. batch.size=65536
• C. linger.ms=20
• D. acks=all

Answer: C

Explanation:
linger.ms forces the producer to wait before sending messages, hence increasing the chance of creating batches that can be heavily compressed.

 

NEW QUESTION # 24
What is encoding and decoding of a message also known as?

• A. Scalability and fault tolerance
• B. Serialization and deserialization
• C. Aggregation and deaggregation
• D. Publish and subscribe

Answer: B

 

NEW QUESTION # 25
Your application is consuming from a topic configured with a deserializer.
It needs to be resilient to badly formatted records ("poison pills"). You surround the poll() call with a try/catch for RecordDeserializationException.
You need to log the bad record, skip it, and continue processing.
Which action should you take in the catch block?

• A. Log the bad record and call the consumer.skip() method.
• B. Log the bad record, no other action needed.
• C. Throw a runtime exception to trigger a restart of the application.
• D. Log the bad record and seek the consumer to the offset of the next record.

Answer: D

Explanation:
To skip a corrupted record and avoid failing the application, you mustseek past the failed offsetmanually using consumer.seek(). This allows the application to resume consumption from the next offset.
FromKafka Consumer Error Handling Docs:
"On deserialization failure, you can catch RecordDeserializationException, log the error, and call seek() to the next offset to skip the bad record."
* A does not prevent re-processing the bad record.
* C is invalid; there'sno skip() methodin the Kafka consumer API.
* D results in service interruption - not ideal for resiliency.
Reference:Kafka Consumer API - Exception Handling and seek()

 

NEW QUESTION # 26
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