Free PDF Confluent - CCDAK - Trustable Confluent Certified Developer for Apache Kafka Certification Examination Test Pass4sure

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Confluent CCDAK Exam Syllabus Topics:

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

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

NEW QUESTION # 71
Which actions will trigger partition rebalance for a consumer group? (select three)

A. A consumer in a consumer group shuts down
B. Remove a broker from the cluster
C. Add a broker to the cluster
D. Add a new consumer to consumer group
E. Increase partitions of a topic

Answer: A,D,E

Explanation:
Rebalance occurs when a new consumer is added, removed or consumer dies or paritions increased.

NEW QUESTION # 72
What isn't an internal Kafka Connect topic?

A. connect-jars
B. connect-status
C. connect-offsets
D. connect-configs

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

Answer: A

NEW QUESTION # 74
How would you describe a connector in ksqlDB?

A. DESCRIBE ip_sum EXTENDED;
B. DROP CONNECTOR [IF EXISTS] connector_name;
C. DESCRIBE CONNECTOR connector_name;
D. DESCRIBE connector_name CONNECTOR;

Answer: C

NEW QUESTION # 75
Kafka producers can batch messages going to the same partition.
Which statement is correct about producer batching?

A. Producers can include multiple batches in a single request to a broker.
B. Producers have a separate background thread for each batch.
C. Producers can only batch messages of the same size.
D. Two or more broker failures will automatically disable batching on the producer.

Answer: A

Explanation:
Kafka producers can group messages destined fordifferent partitionsintoseparate batches, and send multiple batches in one requestto optimize network usage.
FromKafka Producer Internals:
"The producer maintains buffers (batches) for each partition and can send multiple of these batches together in a single request to the broker."
* Message size is not a constraint for batching (A is false).
* Broker failures don't disable batching (B is false).
* There isno separate thread per batch(C is false).
Reference:Kafka Producer Architecture and Internals

NEW QUESTION # 76
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