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Confluent CCDAK Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Security | 5-10% | - Encryption in Transit - Securing Schema Registry - Authentication (SASL, SSL/TLS) - Authorization (ACLs) |
| Schema Management | 5-10% | - Schema Evolution and Compatibility - Protobuf and JSON Schemas - Avro Schemas - Schema Registration and Retrieval - Schema Registry Architecture |
| Kafka Connect | 10-15% | - Offset Management in Connect - Single Message Transformations (SMT) - Connector Configuration - Connect Architecture (Workers, Connectors, Tasks) - Converters and Transforms - Source and Sink Connectors |
| Kafka Fundamentals | 10-15% | - Brokers and Clusters - Topics, Partitions, and Offsets - Producer and Consumer Basics - Replication Factor and ISR - Log Segments and Retention |
| Installing and Configuring Kafka | 5-10% | - Topic Creation and Configuration - Broker Configuration Parameters - Partition Assignment Strategies - ZooKeeper vs KRaft Mode |
| Developing with Kafka Producers | 15-20% | - Producer Configuration and Tuning - Serialization (JSON, Avro, Protobuf) - Idempotent Producers - Exactly-Once Semantics - Error Handling and Retry Logic - Producer Interceptors - Partitioning Strategies |
| Monitoring and Operations | 5-10% | - Kafka Metrics and Monitoring - Cross-region Replication - Disaster Recovery - Consumer Lag and Health Checks - Log Compaction |
| Kafka Streams | 20-25% | - State Stores and Processors - Testing Kafka Streams Applications - Transformation Operations (map, filter, join, aggregate) - Exactly-Once Processing - Streams Architecture and Topology - Windowed Operations (Tumbling, Hopping, Session) - Interactive Queries |
| Developing with Kafka Consumers | 15-20% | - Commit Strategies (Auto, Manual, Cooperative) - Consumer Interceptors - Deserialization - Consumer Groups and Rebalancing - Multi-threaded Consumers - Offset Management - Consumer Configuration and Tuning |
Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions:
You are working on a Kafka cluster with three nodes. You create a topic named orders with:
replication.factor = 3
min.insync.replicas = 2
acks = allWhat exception will be generated if two brokers are down due to network delay?
- A. NotLeaderForPartitionException
- B. NotEnoughReplicasException
- C. NotCoordinatorException
- D. NetworkException
Correct Answer: B 🗳️
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You are developing a Java application using a Kafka consumer.
You need to integrate Kafka's client logs with your own application's logs using log4j2.
Which Java library dependency must you include in your project?
- A. None, the right dependency will be added by the Kafka client dependency by transitivity.
- B. SLF4J implementation for Log4j2 (org.apache.logging.log4j:log4j-slf4j-impl)
- C. SLF4J implementation for Log4j 1.2 (org.slf4j:slf4j-log4j12)
- D. Just the log4j2 dependency of the application
Correct Answer: B 🗳️
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Match the topic configuration setting with the reason the setting affects topic durability.
(You are given settings like unclean.leader.election.enable=false, replication.factor, min.insync.replicas=2)
Correct Answer:
Explanation:
unclean.leader.election.enable=false # Prevents data loss by only considering in-sync replicas when rebalancing.
replication.factor # Specifies how many redundant copies of partitions are distributed across brokers.
min.insync.replicas=2 # Sets the standard for the number of partition instances that must keep up with the latest committed message.
unclean.leader.election.enable=false ensures that only in-sync replicas can be elected as leaders. If disabled, an out-of-sync replica may become leader, potentially leading to data loss.
replication.factor defines how many brokers will maintain copies of each partition, directly impacting durability and availability.
min.insync.replicas determines how many replicas must acknowledge a write when acks=all is used, enforcing write durability.
Reference: Apache Kafka Topic Configuration Documentation
(You deploy a Kafka Streams application with five application instances.
Kafka Streams stores application metadata using internal topics.
Auto-topic creation is disabled in the Kafka cluster.
Which statement about this scenario is true?)
- A. The application will continue to work and internal topics will be created, even if auto-topic creation is disabled.
- B. The application will work, but application metadata will not be stored.
- C. The application will be on hold until internal topics are created manually.
- D. The application will terminate with a non-retriable exception.
Correct Answer: D 🗳️
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Which configuration determines how many bytes of data are collected before sending messages to the Kafka broker?
- A. max.block.size
- B. send.buffer.bytes
- C. buffer.memory
- D. batch.size
Correct Answer: D 🗳️
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Viewing questions 1-5 out of 92 questions.
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