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Confluent CCDAK Exam Syllabus Topics:

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

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Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q86-Q91):

NEW QUESTION # 86
You are using JDBC source connector to copy data from a table to Kafka topic. There is one connector created with max.tasks equal to 2 deployed on a cluster of 3 workers. How many tasks are launched?

Answer: D

Explanation:
JDBC connector allows one task per table.


NEW QUESTION # 87
You have a Kafka client application that has real-time processing requirements.
Which Kafka metric should you monitor?

Answer: C

Explanation:
For real-time applications, thekey metric to monitor is consumer lag- the difference between thelatest offset on the brokerand thelast committed offset by the consumer.
FromKafka Monitoring Guide:
"Consumer lag is the most important metric for real-time applications. It tells you how far behind the consumer is from the latest data in Kafka."
* B relates to replication, not client responsiveness.
* C tracks group membership stability, not data delay.
* D tracks input throughput, not processing latency.
Reference:Kafka Operations > Monitoring > Consumer Lag


NEW QUESTION # 88
If I want to send binary data through the REST proxy to topic "test_binary", it needs to be base64 encoded. A consumer connecting directly into the Kafka topic

Answer: B

Explanation:
On the producer side, after receiving base64 data, the REST Proxy will convert it into bytes and then send that bytes payload to Kafka. Therefore consumers reading directly from Kafka will receive binary data.


NEW QUESTION # 89
Compaction is enabled for a topic in Kafka by setting log.cleanup.policy=compact. What is true about log compaction?

Answer: D

Explanation:
Compaction changes the offset of messages
Explanation:
Log compaction retains at least the last known value for each record key for a single topic partition. All compacted log offsets remain valid, even if record at offset has been compacted away as a consumer will get the next highest offset.


NEW QUESTION # 90
What is the default port that the KSQL server listens on?

Answer: C

Explanation:
Default port of KSQL server is 8088


NEW QUESTION # 91
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