Confluent Certified Developer for Apache Kafka Certification Examination
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Exam Code
CCDAK
Exam Name
Confluent Certified Developer for Apache Kafka Certification Examination
Questions
90 Questions Answers With Explanation
Update Date
04, 30, 2026
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Confluent CCDAK Sample Question Answers
Question # 1
An ecommerce wesbite sells some custom made goods. What's the natural way of modeling this data in Kafka streams?
A. Purchase as stream, Product as stream, Customer as stream B. Purchase as stream, Product as table, Customer as table C. Purchase as table, Product as table, Customer as table D. Purchase as stream, Product as table, Customer as stream
Answer: B
Explanation:
Mostly-static data is modeled as a table whereas business transactions should be modeled as a
stream.
Question # 2
How do you create a topic named test with 3 partitions and 3 replicas using the Kafka CLI?
A. bin/kafka-topics.sh --create --broker-list localhost:9092 --replication-factor 3 --partitions 3 --topic test B. bin/kafka-topics-create.sh --zookeeper localhost:9092 --replication-factor 3 --partitions 3 --topic test C. bin/kafka-topics.sh --create --bootstrap-server localhost:9092 --replication-factor 3 --partitions 3 -- topic test D. bin/kafka-topics.sh --create --bootstrap-server localhost:2181 --replication-factor 3 --partitions 3 -- topic test
Answer: C
Explanation:
As of Kafka 2.3, the kafka-topics.sh command can take --bootstrap-server localhost:9092 as an
argument. You could also use the (now deprecated) option of --zookeeper localhost:2181.
Question # 3
Your streams application is reading from an input topic that has 5 partitions. You run 5 instances of your application, each with num.streams.threads set to 5. How many stream tasks will be created and how many will be active?
A. 5 created, 1 active B. 5 created, 5 active C. 25 created, 25 active D. 25 created, 5 active
Answer: D
Explanation:
One partition is assigned a thread, so only 5 will be active, and 25 threads (i.e. tasks) will be created
Question # 4
Your manager would like to have topic availability over consistency. Which setting do you need to change in order to enable that?
A. compression.type B. unclean.leader.election.enable C. min.insync.replicas
Answer: B
Explanation:
unclean.leader.election.enable=true allows non ISR replicas to become leader, ensuring availability
but losing consistency as data loss will occur
Question # 5
A topic has three replicas and you set min.insync.replicas to 2. If two out of three replicas are not available, what happens when a produce request with acks=all is sent to broker?
A. NotEnoughReplicasException will be returned B. Produce request is honored with single in-sync replica C. Produce request will block till one of the two unavailable partition is available again.
Answer: A
Explanation:
With this configuration, a single in-sync replica becomes read-only. Produce request will receive
NotEnoughReplicasException.
Question # 6
In Avro, removing or adding a field that has a default is a __ schema evolution
A. full B. backward C. breaking D. forward
Answer: A
Explanation:
Clients with new schema will be able to read records saved with old schema and clients with old
schema will be able to read records saved with new schema.
Question # 7
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. Add metadata to the producer record 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. Define a Kafka Broker routing rule
Answer: B
Explanation:
A Custom Partitioner allows you to easily customise how the partition number gets computed from a
source message.
Question # 8
What is the protocol used by Kafka clients to securely connect to the Confluent REST Proxy?
A. Kerberos B. SASL C. HTTPS (SSL/TLS) D. HTTP
Answer: C
Explanation:
TLS - but it is still called SSL.
Question # 9
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 session.timeout.ms B. Decrease session.timeout.ms C. Increase heartbeat.interval.ms D. decrease max.poll.interval.ms E. increase max.poll.interval.ms F. Decrease heartbeat.interval.ms
Answer: B, E
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
Question # 10
How much should be the heap size of a broker in a production setup on a machine with 256 GB of RAM, in PLAINTEXT mode?
A. 4 GB B. 128 GB C. 16 GB D. 512 MB
Answer: A
Explanation:
In Kafka, a small heap size is needed, while the rest of the RAM goes automatically to the page cache
(managed by the OS). The heap size goes slightly up if you need to enable SSL
Question # 11
What is the default port that the KSQL server listens on?
A. 9092 B. 8088 C. 8083 D. 2181
Answer: B
Explanation:
Default port of KSQL server is 8088
Question # 12
If I supply the setting compression.type=snappy to my producer, what will happen? (select two)
A. The Kafka brokers have to de-compress the data B. The Kafka brokers have to compress the data C. The Consumers have to de-compress the data D. The Consumers have to compress the data E. The Producers have to compress the data
Answer: C
Explanation:
Kafka transfers data with zero copy and no transformation. Any transformation (including
compression) is the responsibility of clients.
Question # 13
What happens if you write the following code in your producer? producer.send(producerRecord).get()
A. Compression will be increased B. Throughput will be decreased C. It will force all brokers in Kafka to acknowledge the producerRecord D. Batching will be increased
Answer: B
Explanation:
Using Future.get() to wait for a reply from Kafka will limit throughput.
Question # 14
Suppose you have 6 brokers and you decide to create a topic with 10 partitions and a replication factor of 3. The brokers 0 and 1 are on rack A, the brokers 2 and 3 are on rack B, and the brokers 4 and 5 are on rack C. If the leader for partition 0 is on broker 4, and the first replica is on broker 2, which broker can host the last replica? (select two)
A. 6 B. 1 C. 2 D. 5 E. 0 F. 3
Answer: B, E
Explanation:
When you create a new topic, partitions replicas are spreads across racks to maintain availability.
Question # 15
A kafka topic has a replication factor of 3 and min.insync.replicas setting of 2. How many brokers can go down before a producer with acks=1 can't produce?
A. 0 B. 3 C. 1 D. 2
Answer: D
Explanation:
min.insync.replicas does not impact producers when acks=1 (only when acks=all)
Question # 16
What are the requirements for a Kafka broker to connect to a Zookeeper ensemble? (select two)
A. Unique value for each broker's zookeeper.connect parameter B. Unique values for each broker's broker.id parameter C. All the brokers must share the same broker.id D. All the brokers must share the same zookeeper.connect parameter
Answer: B, D
Explanation:
Each broker must have a unique broker id and connect to the same zk ensemble and root zNode
Question # 17
Which of these joins does not require input topics to be sharing the same number of partitions?
A. KStream-KTable join B. KStream-KStream join C. KStream-GlobalKTable D. KTable-KTable join
Answer: C
Explanation:
GlobalKTables have their datasets replicated on each Kafka Streams instance and therefore no
repartitioning is required
Question # 18
What is the disadvantage of request/response communication?
A. Scalability B. Reliability C. Coupling D. Cost
Answer: C
Explanation:
Point-to-point (request-response) style will couple client to the server.
Question # 19
To produce data to a topic, a producer must provide the Kafka client with...
A. the list of brokers that have the data, the topic name and the partitions list B. any broker from the cluster and the topic name and the partitions list C. all the brokers from the cluster and the topic name D. any broker from the cluster and the topic name
Answer: D
Explanation:
All brokers can respond to a Metadata request, so a client can connect to any broker in the cluster
and then figure out on its own which brokers to send data to.
Question # 20
What is not a valid authentication mechanism in Kafka?
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. UnderReplicatedPartitions B. records-lag-max C. MessagesInPerSec D. BytesInPerSec
Answer: B
Explanation:
This metric shows the current lag (number of messages behind the broker)
Question # 22
When auto.create.topics.enable is set to true in Kafka configuration, what are the circumstances under which a Kafka broker automatically creates a topic? (select three)
A. Client requests metadata for a topic B. Consumer reads message from a topic C. Client alters number of partitions of a topic D. Producer sends message to a topic
Answer: A, B, D
Explanation:
A kafka broker automatically creates a topic under the following circumstances- When a producer
starts writing messages to the topic - When a consumer starts reading messages from the topic -
When any client requests metadata for the topic
Question # 23
When is the onCompletion() method called? private class ProducerCallback implements Callback { @Override public void onCompletion(RecordMetadata recordMetadata, Exception e) { if (e != null) { e.printStackTrace(); } } } ProducerRecord<String, String> record = new ProducerRecord<>("topic1", "key1", "value1"); producer.send(record, new ProducerCallback());
A. When the message is partitioned and batched successfully B. When message is serialized successfully C. When the broker response is received D. When send() method is called
Answer: C
Explanation:
Callback is invoked when a broker response is received.
Question # 24
Compaction is enabled for a topic in Kafka by setting log.cleanup.policy=compact. What is true about log compaction?
A. After cleanup, only one message per key is retained with the first value B. Each message stored in the topic is compressed C. Kafka automatically de-duplicates incoming messages based on key hashes D. After cleanup, only one message per key is retained with the latest value Compaction changes the offset of messages
Answer: D
Explanation:
Log compaction retains at least the last known value for each record key for a single topic partition.
All compacted log offsets remain valid, even if record at offset has been compacted away as a
consumer will get the next highest offset.
Question # 25
When using the Confluent Kafka Distribution, where does the schema registry reside?
A. As a separate JVM component B. As an in-memory plugin on your Zookeeper cluster C. As an in-memory plugin on your Kafka Brokers D. As an in-memory plugin on your Kafka Connect Workers
Answer: A
Explanation:
Schema registry is a separate application that provides RESTful interface for storing and retrieving
Avro schemas.
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