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Confluent CCDAK Exam Syllabus Topics:

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

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Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q46-Q51):

NEW QUESTION # 46
You have a topic with four partitions. The application reads from it using two consumers in a single consumer group.
Processing is CPU-bound, and lag is increasing.
What should you do?

A. Add more partitions to the topic to increase the level of parallelism of the processing.
B. Decrease the max.poll.records property of consumers.
C. Increase the max.poll.records property of consumers.
D. Add more consumers to increase the level of parallelism of the processing.

Answer: D

Explanation:
If the application is CPU-bound and lagging, adding more consumers to the group will allow better parallel processing, especially since the topic has 4 partitions, allowing up to 4 active consumers.
From Kafka Consumer Group Docs:
"Kafka achieves parallelism by distributing partitions across consumers in a group. Adding consumers helps reduce lag if partitions are underutilized." B may help but requires repartitioning and coordination.
C or D affects how much data is polled, not how fast it's processed.
Reference: Kafka Consumer Concepts > Parallelism and Scaling

NEW QUESTION # 47
What is encoding and decoding of a message also known as?

A. Scalability and fault tolerance
B. Aggregation and deaggregation
C. Serialization and deserialization
D. Publish and subscribe

Answer: C

NEW QUESTION # 48
A client connects to a broker in the cluster and sends a fetch request for a partition in a topic. It gets an exception Not Leader For Partition Exception in the response. How does client handle this situation?

A. Get the Broker id from Zookeeper that is hosting the leader replica and send request to it
B. Send metadata request to the same broker for the topic and select the broker hosting the leader replica
C. Send metadata request to Zookeeper for the topic and select the broker hosting the leader replica
D. Send fetch request to each Broker in the cluster

Answer: B

Explanation:
In case the consumer has the wrong leader of a partition, it will issue a metadata request. The Metadata request can be handled by any node, so clients know afterwards which broker are the designated leader for the topic partitions. Produce and consume requests can only be sent to the node hosting partition leader.

NEW QUESTION # 49
What is a generic unique id that I can use for messages I receive from a consumer?

A. topic + partition + timestamp
B. topic + timestamp
C. topic + partition + offset

Answer: C

Explanation:
(Topic,Partition,Offset) uniquely identifies a message in Kafka

NEW QUESTION # 50
Which actions will trigger partition rebalance for a consumer group? (select three)

A. Add a new consumer to consumer group
B. A consumer in a consumer group shuts down
C. Increase partitions of a topic
D. Add a broker to the cluster
E. Remove a broker from the cluster

Answer: A,B,C

Explanation:
Rebalance occurs when a new consumer is added, removed or consumer dies or paritions increased.

NEW QUESTION # 51
......

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