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Confluent CCDAK Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Apache Kafka Streams	12%	- Windowing and time semantics - Streams API concepts: topology, processors, state stores - Error handling and state management - Stream processing operations: map, filter, join, aggregation
Topic 2: Apache Kafka Application Development	28%	- Transactional messaging and idempotence - Producer API: configuration, serialization, partitioning, error handling - Consumer API: configuration, offset management, consumer groups, rebalancing - Schema management: Confluent Schema Registry, compatibility rules, evolution
Topic 3: Application Testing	8%	- Mocking and test utilities - Unit testing producers and consumers - Integration testing and test clusters
Topic 4: Apache Kafka Fundamentals	23%	- Configuration basics and cluster setup - Delivery semantics: at-most-once, at-least-once, exactly-once - Kafka architecture and data flow - Core concepts: brokers, topics, partitions, replicas, offsets
Topic 5: Kafka Connect	15%	- Connect architecture: workers, connectors, tasks, converters - Source and sink connectors configuration - Data transformation and integration patterns
Topic 6: Application Observability	13%	- Tracing and performance tuning - Logging and monitoring metrics - Error diagnosis and troubleshooting

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Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q71-Q76):

NEW QUESTION # 71
If I produce to a topic that does not exist, and the broker setting auto.create.topic.enable=true, what will happen?

A. Kafka will automatically create the topic with 1 partition and 1 replication factor
B. Kafka will automatically create the topic with num.partitions=#of brokers and replication.factor=3
C. Kafka will automatically create the topic with the broker settings num.partitions and default.replication.factor
D. Kafka will automatically create the topic with the indicated producer settings num.partitions and default.replication.factor

Answer: C

Explanation:
The broker settings comes into play when a topic is auto created

NEW QUESTION # 72
You are doing complex calculations using a machine learning framework on records fetched from a Kafka topic. It takes more about 6 minutes to process a record batch, and the consumer enters rebalances even though it's still running. How can you improve this scenario?

A. Increase max.poll.interval.ms to 600000
B. Increase heartbeat.interval.ms to 600000
C. Add consumers to the consumer group and kill them right away
D. Increase session.timeout.ms to 600000

Answer: A

Explanation:
Here, we need to change the setting max.poll.interval.ms (default 300000) to its double in order to tell Kafka a consumer should be considered dead if the consumer only if it hasn't called the .poll() method in 10 minutes instead of 5.

NEW QUESTION # 73
Refer to the producer code below. It features a 'Callback' class with a method called 'onCompletion()'.
In the 'on Completion*.)' method, what does the 'metadata.offset()' value represent?

producer.send(record, new MyCallback(record));

A. Its position in the producer's batch of messages
B. The sequential id of the message is committed into a partition
C. The id of the partition that the message was committed to
D. The number of bytes that overflowed beyond a producer batch of messages

Answer: B

NEW QUESTION # 74
Select all that applies (select THREE)

A. acks is a producer setting
B. min.insync.replicas is a topic setting
C. min.insync.replicas is a producer setting
D. acks is a topic setting
E. min.insync.replicas matters regardless of the values of acks
F. min.insync.replicas only matters if acks=all

Answer: A,B,F

Explanation:
acks is a producer setting min.insync.replicas is a topic or broker setting and is only effective when acks=all

NEW QUESTION # 75
Which of these joins does not require input topics to be sharing the same number of partitions?

A. KStream-KTable join
B. KTable-KTable join
C. KStream-GlobalKTable
D. KStream-KStream join

Answer: C

Explanation:
GlobalKTables have their datasets replicated on each Kafka Streams instance and therefore no repartitioning is required

NEW QUESTION # 76
......

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