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Confluent CCDAK Exam Syllabus Topics:

SectionWeightObjectives
Apache Kafka Application Development28%- Consumer API: configuration, offset management, consumer groups, rebalancing
- Producer API: configuration, serialization, partitioning, error handling
- Transactional messaging and idempotence
- Schema management: Confluent Schema Registry, compatibility rules, evolution
Apache Kafka Fundamentals23%- Core concepts: brokers, topics, partitions, replicas, offsets
- Kafka architecture and data flow
- Configuration basics and cluster setup
- Delivery semantics: at-most-once, at-least-once, exactly-once
Apache Kafka Streams12%- Streams API concepts: topology, processors, state stores
- Windowing and time semantics
- Stream processing operations: map, filter, join, aggregation
- Error handling and state management
Application Testing8%- Mocking and test utilities
- Unit testing producers and consumers
- Integration testing and test clusters
Kafka Connect15%- Source and sink connectors configuration
- Connect architecture: workers, connectors, tasks, converters
- Data transformation and integration patterns
Application Observability13%- 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 (Q68-Q73):

NEW QUESTION # 68
You have a Kafka cluster and all the topics have a replication factor of 3. One intern at your company stopped a broker, and accidentally deleted all the data of that broker on the disk. What will happen if the broker is restarted?

Answer: A

Explanation:
Kafka replication mechanism makes it resilient to the scenarios where the broker lose data on disk, but can recover from replicating from other brokers. This makes Kafka amazing!


NEW QUESTION # 69
Which producer exceptions are examples of the class RetriableException? (Choose 2.)

Answer: A,C


NEW QUESTION # 70
You have a Kafka Connect cluster with multiple connectors.
One connector is not working as expected.
How can you find logs related to that specific connector?

Answer: D

Explanation:
To isolate logs for a specific connector, you can configurea separate logger and appenderin theConnect worker's log4j.propertiesfile, using the connector's name as the logging context.
FromKafka Connect Logging Docs:
"Kafka Connect loggers use hierarchical logger names. You can configure per-connector log levels and output files by extending log4j.properties."
* A and C change verbosity but don't separate logs.
* D is false; targeted logging is possible.
Reference:Kafka Connect > Logging and Debugging


NEW QUESTION # 71
(You have a topic with four partitions. The application reading this topic is using a consumer group with two consumers.
Throughput is smoothly distributed among partitions, but application lag is increasing.
Application monitoring shows that message processing is consuming all available CPU resources.
Which action should you take to resolve this issue?)

Answer: C

Explanation:
According to the Apache Kafka consumer and scalability documentation, parallelism in message processing is primarily determined by the number of partitions and the number of consumers within a consumer group.
Each partition can be assigned to only one consumer at a time. In this scenario, the topic already has four partitions, but only two consumers are processing them, meaning only two partitions are actively consumed in parallel.
Since monitoring indicates that message processing is CPU-bound, the bottleneck is not Kafka I/O but application-side processing. Adding more consumers (up to the number of partitions) allows Kafka to rebalance the partitions and distribute them across more consumer instances, increasing CPU parallelism and reducing lag.
Option A (adding more partitions) can increase parallelism but is more intrusive and may require repartitioning considerations for keys and downstream systems. Option B increases batch size, which can worsen CPU pressure. Option D may reduce per-poll workload but does not increase parallel processing capacity.
Therefore, the correct and recommended action per Kafka documentation is to add more consumers to the consumer group.


NEW QUESTION # 72
Which statements are correct about ksqlDB SQL? (Choose 3.)

Answer: C,D,E


NEW QUESTION # 73
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