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Confluent CCDAK Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Kafka Connect	10-15%	- Offset Management in Connect - Connector Configuration - Single Message Transformations (SMT) - Source and Sink Connectors - Connect Architecture (Workers, Connectors, Tasks) - Converters and Transforms
Topic 2: Developing with Kafka Producers	15-20%	- Partitioning Strategies - Idempotent Producers - Producer Configuration and Tuning - Producer Interceptors - Exactly-Once Semantics - Error Handling and Retry Logic - Serialization (JSON, Avro, Protobuf)
Topic 3: Developing with Kafka Consumers	15-20%	- Consumer Groups and Rebalancing - Multi-threaded Consumers - Consumer Configuration and Tuning - Consumer Interceptors - Offset Management - Deserialization - Commit Strategies (Auto, Manual, Cooperative)
Topic 4: Schema Management	5-10%	- Protobuf and JSON Schemas - Schema Registration and Retrieval - Schema Registry Architecture - Avro Schemas - Schema Evolution and Compatibility
Topic 5: Monitoring and Operations	5-10%	- Log Compaction - Consumer Lag and Health Checks - Disaster Recovery - Cross-region Replication - Kafka Metrics and Monitoring
Topic 6: Installing and Configuring Kafka	5-10%	- Broker Configuration Parameters - ZooKeeper vs KRaft Mode - Topic Creation and Configuration - Partition Assignment Strategies
Topic 7: Kafka Streams	20-25%	- Windowed Operations (Tumbling, Hopping, Session) - Exactly-Once Processing - Interactive Queries - Testing Kafka Streams Applications - State Stores and Processors - Streams Architecture and Topology - Transformation Operations (map, filter, join, aggregate)
Topic 8: Kafka Fundamentals	10-15%	- Replication Factor and ISR - Brokers and Clusters - Log Segments and Retention - Producer and Consumer Basics - Topics, Partitions, and Offsets
Topic 9: Security	5-10%	- Authorization (ACLs) - Encryption in Transit - Securing Schema Registry - Authentication (SASL, SSL/TLS)

Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions:

Question #1

(You are implementing a Kafka Streams application to process financial transactions.
Each transaction must be processed exactly once to ensure accuracy.
The application reads from an input topic, performs computations, and writes results to an output topic.
During testing, you notice duplicate entries in the output topic, which violates the exactly-once processing requirement.
You need to ensure exactly-once semantics (EOS) for this Kafka Streams application.
Which step should you take?)

A. Set processing.guarantee=exactly_once_v2 in the Kafka Streams configuration.
B. Enable compaction on the output topic to handle duplicates.
C. Set enable.exactly_once=true in the Kafka Streams configuration.
D. Set enable.idempotence=true in the internal producer configuration of the Kafka Streams application.

Reveal Solution Discussion 0

Correct Answer: A 🗳️

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Question #2

Where are source connector offsets stored?

A. topic.offset.config
B. offset.storage.topic
C. storage.offset.topic
D. offset, storage, partitions

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Correct Answer: B 🗳️

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Question #3

An application is consuming messages from Kafka.
The application logs show that partitions are frequently being reassigned within the consumer group.
Which two factors may be contributing to this?
(Select two.)

A. An instance of the application is crashing and being restarted.
B. There is a storage issue on the broker.
C. There is a slow consumer processing application.
D. The number of partitions does not match the number of application instances.

Reveal Solution Discussion 0

Correct Answer: A,C 🗳️

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Question #4

A stream processing application is tracking user activity in online shopping carts.
You want to identify periods of user inactivity.
Which type of Kafka Streams window should you use?

A. Sliding
B. Tumbling
C. Hopping
D. Session

Reveal Solution Discussion 0

Correct Answer: D 🗳️

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Question #5

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?