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Confluent CCDAK Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Kafka Streams | 20-25% | - Testing Kafka Streams Applications - State Stores and Processors - Interactive Queries - Exactly-Once Processing - Transformation Operations (map, filter, join, aggregate) - Windowed Operations (Tumbling, Hopping, Session) - Streams Architecture and Topology |
| Topic 2: Kafka Connect | 10-15% | - Single Message Transformations (SMT) - Connector Configuration - Connect Architecture (Workers, Connectors, Tasks) - Converters and Transforms - Source and Sink Connectors - Offset Management in Connect |
| Topic 3: Monitoring and Operations | 5-10% | - Cross-region Replication - Log Compaction - Kafka Metrics and Monitoring - Disaster Recovery - Consumer Lag and Health Checks |
| Topic 4: Security | 5-10% | - Authorization (ACLs) - Encryption in Transit - Securing Schema Registry - Authentication (SASL, SSL/TLS) |
| Topic 5: Installing and Configuring Kafka | 5-10% | - Partition Assignment Strategies - Topic Creation and Configuration - ZooKeeper vs KRaft Mode - Broker Configuration Parameters |
| Topic 6: Schema Management | 5-10% | - Schema Evolution and Compatibility - Avro Schemas - Protobuf and JSON Schemas - Schema Registration and Retrieval - Schema Registry Architecture |
| Topic 7: Developing with Kafka Producers | 15-20% | - Idempotent Producers - Partitioning Strategies - Producer Configuration and Tuning - Error Handling and Retry Logic - Producer Interceptors - Exactly-Once Semantics - Serialization (JSON, Avro, Protobuf) |
| Topic 8: Developing with Kafka Consumers | 15-20% | - Consumer Groups and Rebalancing - Offset Management - Consumer Configuration and Tuning - Multi-threaded Consumers - Deserialization - Consumer Interceptors - Commit Strategies (Auto, Manual, Cooperative) |
| Topic 9: Kafka Fundamentals | 10-15% | - Producer and Consumer Basics - Brokers and Clusters - Log Segments and Retention - Topics, Partitions, and Offsets - Replication Factor and ISR |
Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions:
1. Which is true about topic compaction?
A) Compaction will keep exactly one message per key after compaction of inactive log segments.
B) Topic compaction does not remove old events; instead, when clients consume events from a compacted topic, they store events in a hashmap that maintains the latest value.
C) When a client produces a new event with an existing key, the old value is overwritten with the new value in the compacted log segment.
D) When a client produces a new event with an existing key, the broker immediately deletes the offset of the existing event.
2. (You are developing a Java application that includes a Kafka consumer.
You need to integrate Kafka client logs with your own application logs.
Your application is using the Log4j2 logging framework.
Which Java library dependency must you include in your project?)
A) SLF4J implementation for Log4j 1.2 (org.slf4j:slf4j-log4j12)
B) SLF4J implementation for Log4j2 (org.apache.logging.log4j:log4j-slf4j-impl)
C) Just the Log4j2 dependency of the application
D) None, the correct dependency will be added transitively by the Kafka client
3. (A consumer application runs once every two weeks and reads from a Kafka topic.
The last time the application ran, the last offset processed was 217.
The application is configured with auto.offset.reset=latest.
The current offsets in the topic start at 318 and end at 588.
Which offset will the application start reading from when it starts up for its next run?)
A) 589
B) 318
C) 218
D) 0
4. (Your application consumes from a topic configured with a deserializer.
You want the application to be resilient to badly formatted records (poison pills).
You surround the poll() call with a try/catch block for RecordDeserializationException.
You need to log the bad record, skip it, and continue processing other records.
Which action should you take in the catch block?)
A) Throw a runtime exception to trigger a restart of the application.
B) Log the bad record; no other action is needed.
C) Log the bad record and seek the consumer to the offset of the next record.
D) Log the bad record and call consumer.skip() method.
5. What is the default maximum size of a message the Apache Kafka broker can accept?
A) 10MB
B) 5MB
C) 2MB
D) 1MB
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: B | Question # 3 Answer: A | Question # 4 Answer: C | Question # 5 Answer: D |
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