Download Confluent CCDAK Sample Questions [Sep-2025]
Real CCDAK Exam Questions and Answers FREE
To prepare for the CCDAK certification examination, candidates must have a solid understanding of Kafka's architecture, design principles, and implementation details. They must also have experience working with Kafka in a production environment. Confluent offers a range of training courses and resources that can help candidates prepare for the exam. These courses cover topics such as Kafka architecture, Kafka Streams, Kafka Connect, and Kafka security.
NEW QUESTION # 135
What Java library is KSQL based on?
- A. Kafka Connect
- B. Kafka Streams
- C. REST Proxy
- D. Schema Registry
Answer: B
Explanation:
KSQL is based on Kafka Streams and allows you to express transformations in the SQL language that get automatically converted to a Kafka Streams program in the backend
NEW QUESTION # 136
You have a Kafka cluster and all the topics have a replication factor of 3. One intern at your company stopped a broker, and accidentally deleted all the data of that broker on the disk. What will happen if the broker is restarted?
- A. The broker will start, and won't have any data. If the broker comes leader, we have a data loss
- B. The broker will start, and won't be online until all the data it needs to have is replicated from other leaders
- C. The broker will crash
- D. The broker will start, and other topics will also be deleted as the broker data on the disk got deleted
Answer: B
Explanation:
Kafka replication mechanism makes it resilient to the scenarios where the broker lose data on disk, but can recover from replicating from other brokers. This makes Kafka amazing!
NEW QUESTION # 137
What isn't a feature of the Confluent schema registry?
- A. Store schemas
- B. Store avro data
- C. Enforce compatibility rules
Answer: B
Explanation:
Data is stored on brokers.
NEW QUESTION # 138
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 # 139
Which statement is true about how exactly-once semantics (EOS) work in Kafka Streams?
- A. EOS in Kafka Streams is implemented by creating a separate Kafka topic for deduplication of all messages processed by the application.
- B. Kafka Streams disables log compaction on internal changelog topics to preserve all state changes for potential recovery.
- C. Kafka Streams provides EOS by periodically checkpointing state stores and replaying changelogs to recover only unprocessed messages during failure.
- D. EOS in Kafka Streams relies on transactional producers to atomically commit state updates to changelog topics and output records to Kafka.
Answer: D
Explanation:
Kafka Streams usestransactional producersto guaranteeexactly-once semantics (EOS). This ensures that both theoutput recordsandstate store updatesare committed atomically, avoiding duplication or partial writes.
FromKafka Streams Documentation > Processing Guarantees:
"Kafka Streams leveragesKafka's transactional APIsto commit the output records and internal state updates as a single atomic unit, thereby providing exactly-once semantics."
* Option A is incorrect because log compaction is not disabled for EOS.
* Option C incorrectly describes a checkpointing system Kafka Streams does not use.
* Option D refers to deduplication, which is not how EOS is achieved in Streams.
Reference:Kafka Streams Processing Guarantees
NEW QUESTION # 140
When using the Confluent Kafka Distribution, where does the schema registry reside?
- A. As an in-memory plugin on your Zookeeper cluster
- B. As a separate JVM component
- C. As an in-memory plugin on your Kafka Connect Workers
- D. As an in-memory plugin on your Kafka Brokers
Answer: B
Explanation:
Schema registry is a separate application that provides RESTful interface for storing and retrieving Avro schemas.
NEW QUESTION # 141
You are composing a REST request to create a new connector in a running Connect cluster. You invoke POST /connectors with a configuration and receive a 409 (Conflict) response.
What are two reasons for this response? (Select two.)
- A. The connect cluster has reached capacity, and new connectors cannot be created without expandingthe cluster.
- B. The Connector already exists in the cluster.
- C. The connector configuration was invalid, and the response body will expand on the configuration error.
- D. The Connect cluster is in process of rebalancing.
Answer: B,D
Explanation:
A409 Conflictresponse in Kafka Connect REST API usually means:
* The connector name provided already exists (i.e., a connector with that name is already deployed).
* The Kafka Connect cluster is temporarily unavailable to accept new tasks due toa rebalance in progress.
From theConfluent Developer documentationand Kafka Connect REST API spec:
"409 - Conflict. The connector name is already in use or the worker group is in the process of rebalancing and cannot complete the request at this time." Option A is incorrect because invalid configurations return400 Bad Request, not 409.
Option B is invalid because Kafka Connect does not have a strict concept of "capacity" that prevents connector creation with a 409.
Reference:Apache Kafka Connect REST API documentation
NEW QUESTION # 142
When using plain JSON data with Connect, you see the following error messageorg.apache.kafka.connect.
errors.DataExceptionJsonDeserializer with schemas.enable requires "schema" and "payload" fields and may not contain additional fields. How will you fix the error?
- A. Set key.converter, value.converter to JsonConverter and the schema registry url
- B. Use Single Message Transforms to add schema and payload fields in the message
- C. Set key.converter.schemas.enable and value.converter.schemas.enable to false
- D. Set key.converter, value.converter to AvroConverter and the schema registry url
Answer: C
Explanation:
You will need to set the schemas.enable parameters for the converter to false for plain text with no schema.
NEW QUESTION # 143
You are using JDBC source connector to copy data from a table to Kafka topic. There is one connector created with max.tasks equal to 2 deployed on a cluster of 3 workers. How many tasks are launched?
- A. 0
- B. 1
- C. 2
- D. 3
Answer: D
Explanation:
JDBC connector allows one task per table.
NEW QUESTION # 144
In the Kafka consumer metrics it is observed that fetch-rate is very high and each fetch is small. What steps will you take to increase throughput?
- A. Increase fetch.max.wait
- B. Increase fetch.min.bytes
- C. Decrease fetch.min.bytes
- D. Increase fetch.max.bytes
- E. Decrease fetch.max.bytes
Answer: B
Explanation:
This will allow consumers to wait and receive more bytes in each fetch request.
NEW QUESTION # 145
When running a ksqlDB for connectors, what does the IF NOT EXISTS clause do?
- A. Prevent the statement from executing if a connector with the supplied name does not exist.
- B. Update the connector properties if a connector with the supplied name exists.
- C. Prevent the statement from failing if a connector with the supplied name already exists.
- D. Fail if the specified connector does not exist.
Answer: C
NEW QUESTION # 146
A Kafka cluster has four brokers with a topic t1 with eight partitions. A client application has just one broker specified in the bootstrap URL.
Brokers:
b1.host.domain.com
b2.host.domain.com
b3.host.domain.com
b4.host.domain.com
Bootstrap URL:
b2.host.domain.com
What would be the impact of such configuration?
- A. Consumers and producers will not be able to consume or produce any messages.
- B. Consumers and producers will work as expected as long as broker b2 is available.
- C. Consumers and producers will get NotEnoughReplicasException.
- D. Consumers and producers will only be able to consume and produce from partitions on broker b2.
Answer: B
NEW QUESTION # 147
There are 3 brokers in the cluster. You want to create a topic with a single partition that is resilient to one broker failure and one broker maintenance. What is the replication factor will you specify while creating the topic?
- A. 0
- B. 1
- C. 2
- D. 3
Answer: B
Explanation:
1 is not possible as it doesn't provide resilience to failure, 2 is not enough as if we take a broker down for maintenance, we cannot tolerate a broker failure, and 6 is impossible as we only have 3 brokers (RF cannot be greater than the number of brokers). Here the correct answer is 3
NEW QUESTION # 148
The kafka-console-consumer CLI, when used with the default options
- A. does not use a group id
- B. uses a random group id
- C. always uses the same group id
Answer: B
Explanation:
If a group is not specified, the kafka-console-consumer generates a random consumer group.
NEW QUESTION # 149
How do Kafka brokers ensure great performance between the producers and consumers? (select two)
- A. It compresses the messages as it writes to the disk
- B. It transforms the messages into a binary format
- C. It leverages zero-copy optimisations to send data straight from the page-cache
- D. It does not transform the messages
- E. It buffers the messages on disk, and sends messages from the disk reads
Answer: C,D
Explanation:
Kafka transfers data with zero-copy and sends the raw bytes it receives from the producer straight to the consumer, leveraging the RAM available as page cache
NEW QUESTION # 150
If you enable an SSL endpoint in Kafka, what feature of Kafka will be lost?
- A. Cross-cluster mirroring
- B. Exactly-once delivery
- C. Zero copy
- D. Support for Avro format
Answer: C
Explanation:
With SSL, messages will need to be encrypted and decrypted, by being first loaded into the JVM, so you lose the zero copy optimization. See more information herehttps://twitter.com/ijuma/status
/1161303431501324293?s=09
NEW QUESTION # 151
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 seek the consumer to the offset of the next record.
- B. Log the bad record, no other action needed.
- C. Log the bad record and call the consumer.skip() method.
- D. Throw a runtime exception to trigger a restart of the application.
Answer: A
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 # 152
ksqIDB Lambda functions must be used inside what type of designated functions?
- A. Deployment
- B. Stafcc
- C. Invocation
- D. Application
Answer: B
NEW QUESTION # 153
A consumer starts and has auto.offset.reset=latest, and the topic partition currently has data for offsets going from 45 to 2311. The consumer group has committed the offset 643 for the topic before. Where will the consumer read from?
- A. it will crash
- B. offset 643
- C. offset 45
- D. offset 2311
Answer: B
Explanation:
The offsets are already committed for this consumer group and topic partition, so the property auto.offset.reset is ignored
NEW QUESTION # 154
You want to send a message of size 3 MB to a topic with default message size configuration. How does KafkaProducer handle large messages?
- A. MessageSizeTooLarge exception will be thrown, KafkaProducer will not retry and return exception immediately
- B. KafkaProducer divides messages into sizes of max.request.size and sends them in order
- C. MessageSizeTooLarge exception will be thrown, KafkaProducer retries until the number of retries are exhausted
- D. KafkaProducer divides messages into sizes of message.max.bytes and sends them in order
Answer: A
Explanation:
MessageSizeTooLarge is not a retryable exception.
NEW QUESTION # 155
A stream processing application is tracking the user activity of online shopping carts. The application tracks items added to the cart, items removed from the cart, and items ordered from the cart throughout the day for each user.
You need to capture the data to identify possible periods of user inactivity.
Which type of Kafka Streams window should you use?
- A. Tumbling
- B. Session
- C. Sliding
- D. Hopping
Answer: B
NEW QUESTION # 156
How does a consumer commit offsets in Kafka?
- A. It interacts with the Group Coordinator broker
- B. It directly commits the offsets in Zookeeper
- C. It directly sends a message to the __consumer_offsets topic
Answer: A
Explanation:
Consumers do not directly write to the __consumer_offsets topic, they instead interact with a broker that has been elected to manage that topic, which is the Group Coordinator broker
NEW QUESTION # 157
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