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Confluent CCDAK Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Application Testing | 8% | - Integration testing and test clusters - Mocking and test utilities - Unit testing producers and consumers |
| Topic 2: Apache Kafka Application Development | 28% | - Transactional messaging and idempotence - Schema management: Confluent Schema Registry, compatibility rules, evolution - Producer API: configuration, serialization, partitioning, error handling - Consumer API: configuration, offset management, consumer groups, rebalancing |
| Topic 3: Apache Kafka Fundamentals | 23% | - Delivery semantics: at-most-once, at-least-once, exactly-once - Configuration basics and cluster setup - Kafka architecture and data flow - Core concepts: brokers, topics, partitions, replicas, offsets |
| Topic 4: Application Observability | 13% | - Error diagnosis and troubleshooting - Logging and monitoring metrics - Tracing and performance tuning |
| Topic 5: Apache Kafka Streams | 12% | - Windowing and time semantics - Stream processing operations: map, filter, join, aggregation - Error handling and state management - Streams API concepts: topology, processors, state stores |
| Topic 6: Kafka Connect | 15% | - Source and sink connectors configuration - Connect architecture: workers, connectors, tasks, converters - Data transformation and integration patterns |
Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions:
(You are writing to a Kafka topic with producer configuration acks=all.
The producer receives acknowledgements from the broker but still creates duplicate messages due to network timeouts and retries.
You need to ensure that duplicate messages are not created.
Which producer configuration should you set?)
- A. enable.auto.commit=true
- B. retries=0max.in.flight.requests.per.connection=5enable.idempotence=true
- C. retries=2147483647max.in.flight.requests.per.connection=1enable.idempotence=true
- D. retries=2147483647max.in.flight.requests.per.connection=5enable.idempotence=false
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(You want to enrich the content of a topic by joining it with key records from a second topic.
The two topics have a different number of partitions.
Which two solutions can you use?
Select two.)
- A. Use a KStream-KTable join; Kafka Streams will automatically repartition the topics to satisfy the co- partitioning constraint.
- B. Repartition one topic to a new topic with the same number of partitions as the other topic (co- partitioning constraint) and use a KStream-KTable join.
- C. Create as many Kafka Streams application instances as the maximum number of partitions of the two topics and use a KStream-KTable join.
- D. Use a GlobalKTable for one of the topics where data does not change frequently and use a KStream- GlobalKTable join.
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(An S3 source connector named s3-connector stopped running.
You use the Kafka Connect REST API to query the connector and task status.
One of the three tasks has failed.
You need to restart the connector and all currently running tasks.
Which REST request will restart the connector instance and all its tasks?)
- A. POST /connectors/s3-connector/restart?includeTasks=true
- B. POST /connectors/s3-connector/restart?includeTasks=true&onlyFailed=true
- C. POST /connectors/s3-connector/restart
- D. POST /connectors/s3-connector/tasks/0/restart
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You are experiencing low throughput from a Java producer.
Metrics show low I/O thread ratio and low I/O thread wait ratio.
What is the most likely cause of the slow producer performance?
- A. The producer code has an expensive callback function.
- B. Compression is enabled.
- C. There is a bad data link layer (layer 2) connection from the producer to the cluster.
- D. The producer is sending large batches of messages.
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What is the default maximum size of a message the Apache Kafka broker can accept?
- A. 5MB
- B. 10MB
- C. 2MB
- D. 1MB
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