Most Recent Confluent CCDAK Exam Dumps

Prepare for the Confluent Certified Developer for Apache Kafka exam with our extensive collection of questions and answers. These practice Q&A are updated according to the latest syllabus, providing you with the tools needed to review and test your knowledge.

QA4Exam focus on the latest syllabus and exam objectives, our practice Q&A are designed to help you identify key topics and solidify your understanding. By focusing on the core curriculum, These Questions & Answers helps you cover all the essential topics, ensuring you're well-prepared for every section of the exam. Each question comes with a detailed explanation, offering valuable insights and helping you to learn from your mistakes. Whether you're looking to assess your progress or dive deeper into complex topics, our updated Q&A will provide the support you need to confidently approach the Confluent CCDAK exam and achieve success.

The questions for CCDAK were last updated on May 4, 2025.

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Question No. 1

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?

Show Answer

Correct Answer: D

min.insync.replicas does not impact producers when acks=1 (only when acks=all)

Question No. 2

What isn't an internal Kafka Connect topic?

Aconnect-status

Bconnect-offsets

Cconnect-configs

Dconnect-jars

Show Answer

Correct Answer: D

connect-configs stores configurations, connect-status helps to elect leaders for connect, and connect-offsets store source offsets for source connectors

Question No. 3

In Kafka Streams, by what value are internal topics prefixed by?

Atasks-<number>

Bapplication.id

Cgroup.id

Dkafka-streams-

Show Answer

Correct Answer: B

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)

Question No. 4

StreamsBuilder builder = new StreamsBuilder();

KStream textLines = builder.stream("word-count-input");

KTable wordCounts = textLines

.mapValues(textLine -> textLine.toLowerCase())

.flatMapValues(textLine -> Arrays.asList(textLine.split("\W+")))

.selectKey((key, word) -> word)

.groupByKey()

.count(Materialized.as("Counts"));

wordCounts.toStream().to("word-count-output", Produced.with(Serdes.String(), Serdes.Long()));

builder.build();

What is an adequate topic configuration for the topic word-count-output?

Amax.message.bytes=10000000

Bcleanup.policy=delete

Ccompression.type=lz4

Dcleanup.policy=compact

Show Answer

Correct Answer: D

Result is aggregated into a table with key as the unique word and value its frequency. We have to enable log compaction for this topic to align the topic's cleanup policy with KTable semantics.

Question No. 5

What exceptions may be caught by the following producer? (select two)

ProducerRecord record =

new ProducerRecord<>("topic1", "key1", "value1");

try {

producer.send(record);

} catch (Exception e) {

e.printStackTrace();

}

ABrokerNotAvailableException

BSerializationException

CInvalidPartitionsException

DBufferExhaustedException

Show Answer

Correct Answer: B, D

These are the client side exceptions that may be encountered before message is sent to the broker, and before a future is returned by the .send() method.

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