Confluent CCDAK Exam Questions (Updated 2026) 100% Real Question Answers
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The CCDAK certification is offered by Confluent, the company behind Apache Kafka. Confluent Certified Developer for Apache Kafka Certification Examination certification provides developers with a way to demonstrate their expertise in Kafka development and gain recognition from potential employers. The CCDAK certification is also a requirement for becoming a Confluent Certified Developer or Confluent Certified Administrator.
Apache Kafka has become one of the most popular open-source distributed streaming platforms used by software developers and data engineers. Kafka is used for building real-time data pipelines and streaming applications, making it a crucial component of the modern data architecture. To validate the knowledge and expertise of developers working with Kafka, Confluent has introduced the Confluent Certified Developer for Apache Kafka (CCDAK) certification exam.
NEW QUESTION # 77
What isn't an internal Kafka Connect topic?
- A. connect-jars
- B. connect-offsets
- C. connect-configs
- D. connect-status
Answer: A
Explanation:
connect-configs stores configurations, connect-status helps to elect leaders for connect, and connect-offsets store source offsets for source connectors
NEW QUESTION # 78
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. offset 45
- B. offset 643
- C. it will crash
- 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 # 79
Which statements are correct about ksqlDB SQL? (Choose 3.)
- A. Queries can run continuously.
- B. Primary key indexing is supported.
- C. It is ANSI compliant.
- D. It can do joins.
- E. It supports windowed joins.
Answer: A,D,E
NEW QUESTION # 80
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. Use Single Message Transforms to add schema and payload fields in the message
- B. Set key.converter, value.converter to AvroConverter and the schema registry url
- C. Set key.converter, value.converter to JsonConverter and the schema registry url
- D. Set key.converter.schemas.enable and value.converter.schemas.enable to false
Answer: D
Explanation:
You will need to set the schemas.enable parameters for the converter to false for plain text with no schema.
NEW QUESTION # 81
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. Create a custom partitioner
- B. Add metadata to the producer record
- 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. Define a Kafka Broker routing rule
Answer: A
Explanation:
A Custom Partitioner allows you to easily customise how the partition number gets computed from a source message.
NEW QUESTION # 82
You are building a consumer application that processes events from a Kafka topic. What is the most important metric to monitor to ensure real-time processing?
- A. BytesInPerSec
- B. UnderReplicatedPartitions
- C. MessagesInPerSec
- D. records-lag-max
Answer: D
Explanation:
This metric shows the current lag (number of messages behind the broker)
NEW QUESTION # 83
The kafka-console-consumer CLI, when used with the default options
- A. always uses the same group id
- B. uses a random group id
- C. does not use a group id
Answer: B
Explanation:
If a group is not specified, the kafka-console-consumer generates a random consumer group.
NEW QUESTION # 84
Where are the ACLs stored in a Kafka cluster by default?
- A. Inside the Zookeeper's data directory
- B. Inside the broker's data directory
- C. Under Zookeeper node /kafka-acl/
- D. In Kafka topic __kafka_acls
Answer: B
Explanation:
ACLs are stored in Zookeeper node /kafka-acls/ by default.
NEW QUESTION # 85
Which of the following is NOT a supported serialization format in ksqlDB?
- A. Avro
- B. BSON
- C. Protobuf
- D. Delimited
Answer: B
NEW QUESTION # 86
You have a consumer group of 12 consumers and when a consumer gets killed by the process management system, rather abruptly, it does not trigger a graceful shutdown of your consumer. Therefore, it takes up to 10 seconds for a rebalance to happen. The business would like to have a 3 seconds rebalance time. What should you do? (select two)
- A. increase max.poll.interval.ms
- B. Decrease session.timeout.ms
- C. decrease max.poll.interval.ms
- D. Increase session.timeout.ms
- E. Increase heartbeat.interval.ms
- F. Decrease heartbeat.interval.ms
Answer: A,B
Explanation:
session.timeout.ms must be decreased to 3 seconds to allow for a faster rebalance, and the heartbeat thread must be quicker, so we also need to decrease heartbeat.interval.ms
NEW QUESTION # 87
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:
* 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 onlyin-sync replicascan be elected as leaders. If disabled, an out-of-sync replica may become leader, potentially leading to data loss.
* replication.factor defineshow many brokerswill maintain copies of each partition, directly impacting durability and availability.
* min.insync.replicas determineshow many replicas must acknowledgea write when acks=all is used, enforcing write durability.
Reference:Apache Kafka Topic Configuration Documentation
NEW QUESTION # 88
In Kafka Streams, by what value are internal topics prefixed by?
- A. group.id
- B. kafka-streams-
- C. tasks-<number>
- D. application.id
Answer: D
Explanation:
In Kafka Streams, the application.id is also the underlying group.id for your consumers, and the prefix for all internal topics (repartition and state)
NEW QUESTION # 89
You want to perform table lookups against a KTable everytime a new record is received from the KStream.
What is the output of KStream-KTable join?
- A. KTable
- B. Kstream
- C. GlobalKTable
- D. You choose between KStream or KTable
Answer: B
Explanation:
Here KStream is being processed to create another KStream.
NEW QUESTION # 90
A consumer wants to read messages from a specific partition of a topic. How can this be achieved?
- A. Call subscribe() passing TopicPartition as the argument
- B. Call subscribe(String topic, int partition) passing the topic and partition number as the arguments
- C. Call assign() passing a Collection of TopicPartitions as the argument
Answer: C
Explanation:
assign() can be used for manual assignment of a partition to a consumer, in which case subscribe() must not be used. Assign() takes a collection of TopicPartition object as an argument https://kafka.apache.org/23/javadoc/org/apache/kafka/clients/consumer/KafkaConsumer.html#assign-java.util.Collection-
NEW QUESTION # 91
What is the difference between exactly once semantics (EOS) and idempotence?
- A. Idempotence sends updates multiple times and stores the first value. EOS sends updates multiple times and stores the latest value.
- B. Idempotence Is any function that can be executed several times without changing the final result beyond its first iteration. EOS sends an update once and only one time.
- C. Idempotence sends an update once and only one item. EOS is any function that can be executed several times without changing the final result beyond its first iteration
- D. Idempotence sends an update multiple times and only keeps the latest update EOS requests get sent multiple times, but only the first request is accepted.
Answer: B
NEW QUESTION # 92
By default, which replica will be elected as a partition leader? (select two)
- A. Any of the replicas
- B. Preferred leader broker if it is in-sync and auto.leader.rebalance.enable=true
- C. Preferred leader broker if it is in-sync and auto.leader.rebalance.enable=false
- D. An in-sync replica
Answer: A,D
Explanation:
Preferred leader is a broker that was leader when topic was created. It is preferred because when partitions are first created, the leaders are balanced between brokers. Otherwise, any of the in-sync replicas (ISR) will be elected leader, as long as unclean.leader.election=false (by default)
NEW QUESTION # 93
A consumer application runs once a week and reads from a Kafka topic. The last time the application ran, the last offset processed was 217. The application is configured with auto.offset.reset set to "latest". The current offsets in the topic start at 318 and end at 588.
What offset will the application start reading when it starts up for its next run?
- A. 0
- B. 1
- C. 2
- D. 3
Answer: D
NEW QUESTION # 94
Which statement is true about how exactly-once semantics (EOS) work in Kafka Streams?
- A. Kafka Streams disables log compaction on internal changelog topics to preserve all state changes for potential recovery.
- B. Kafka Streams provides EOS by periodically checkpointing state stores and replaying changelogs to recover only unprocessed messages during failure.
- C. EOS in Kafka Streams relies on transactional producers to atomically commit state updates to changelog topics and output records to Kafka.
- D. EOS in Kafka Streams is implemented by creating a separate Kafka topic for deduplication of all messages processed by the application.
Answer: C
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 # 95
Which configuration determines how many bytes of data are collected before sending messages to the Kafka broker?
- A. buffer.memory
- B. batch.size
- C. send.buffer.bytes
- D. max.block.size
Answer: B
Explanation:
Thebatch.sizeconfig sets themaximum number of bytes to batch per partitionbefore sending. This allows Kafka producers toamortize I/Oand improve throughput.
FromKafka Producer Configuration Docs:
"batch.size is the maximum amount of data per partition the producer will batch before sending."
* buffer.memory sets total memory for the producer, not per-batch.
* send.buffer.bytes is aTCP socket buffer, not a Kafka config.
* max.block.ms controls blocking time, not size.
Reference:Kafka Producer Configs > batch.size
NEW QUESTION # 96
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