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Confluent CCDAK Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Application Observability | 13% | - Error diagnosis and troubleshooting - Logging and monitoring metrics - Tracing and performance tuning |
| Apache Kafka Streams | 12% | - Windowing and time semantics - Stream processing operations: map, filter, join, aggregation - Streams API concepts: topology, processors, state stores - Error handling and state management |
| Kafka Connect | 15% | - Data transformation and integration patterns - Source and sink connectors configuration - Connect architecture: workers, connectors, tasks, converters |
| Apache Kafka Application Development | 28% | - Producer API: configuration, serialization, partitioning, error handling - Transactional messaging and idempotence - Schema management: Confluent Schema Registry, compatibility rules, evolution - Consumer API: configuration, offset management, consumer groups, rebalancing |
| Apache Kafka Fundamentals | 23% | - Delivery semantics: at-most-once, at-least-once, exactly-once - Core concepts: brokers, topics, partitions, replicas, offsets - Kafka architecture and data flow - Configuration basics and cluster setup |
| Application Testing | 8% | - Mocking and test utilities - Unit testing producers and consumers - Integration testing and test clusters |
Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions:
1. Which configuration allows more time for the consumer poll to process records?
A) fetch.max.wait.ms
B) max.poll.interval.ms
C) session.timeout.ms
D) heartbeat.interval.ms
2. You need to correctly join data from two Kafka topics.
Which two scenarios will allow for co-partitioning?
(Select two.)
A) Both topics have the same key and partitioning strategy.
B) Both topics have the same number of partitions.
C) Both topics have the same value schema.
D) Both topics have the same retention time.
3. What is the default maximum size of a message the Apache Kafka broker can accept?
A) 1MB
B) 2MB
C) 10MB
D) 5MB
4. (You want to read messages from all partitions of a topic in every consumer instance of your application.
How do you do this?)
A) Use the assign() method using all topic-partitions of the topic as argument.
B) Use the subscribe() method with an empty consumer group name configuration.
C) Use the subscribe() method with a regular expression argument.
D) Use the assign() method with the topic name as argument.
5. Which two statements are correct about transactions in Kafka?
(Select two.)
A) Transactions guarantee at least once delivery of messages.
B) Information about producers and their transactions is stored in the _transaction_state topic.
C) All messages from a failed transaction will be deleted from a Kafka topic.
D) Transactions are only possible when writing messages to a topic with single partition.
E) Consumers can consume both committed and uncommitted transactions.
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: A,B | Question # 3 Answer: A | Question # 4 Answer: A | Question # 5 Answer: B,E |



