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Confluent CCDAK Exam Syllabus Topics:

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

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Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q12-Q17):

NEW QUESTION # 12
You want to send a message of size 3 MB to a topic with default message size configuration. How does KafkaProducer handle large messages?

A. MessageSizeTooLarge exception will be thrown, KafkaProducer will not retry and return exception immediately
B. KafkaProducer divides messages into sizes of max.request.size and sends them in order
C. KafkaProducer divides messages into sizes of message.max.bytes and sends them in order
D. MessageSizeTooLarge exception will be thrown, KafkaProducer retries until the number of retries are exhausted

Answer: A

Explanation:
MessageSizeTooLarge is not a retryable exception.

NEW QUESTION # 13
What is encoding and decoding of a message also known as?

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

Answer: C

NEW QUESTION # 14
Your application is consuming from a topic configured with a deserializer.
It needs to be resilient to badly formatted records ("poison pills"). You surround the poll() call with a try/catch for RecordDeserializationException.
You need to log the bad record, skip it, and continue processing.
Which action should you take in the catch block?

A. Log the bad record and call the consumer.skip() method.
B. Log the bad record, no other action needed.
C. Throw a runtime exception to trigger a restart of the application.
D. Log the bad record and seek the consumer to the offset of the next record.

Answer: D

Explanation:
To skip a corrupted record and avoid failing the application, you mustseek past the failed offsetmanually using consumer.seek(). This allows the application to resume consumption from the next offset.
FromKafka Consumer Error Handling Docs:
"On deserialization failure, you can catch RecordDeserializationException, log the error, and call seek() to the next offset to skip the bad record."
* A does not prevent re-processing the bad record.
* C is invalid; there'sno skip() methodin the Kafka consumer API.
* D results in service interruption - not ideal for resiliency.
Reference:Kafka Consumer API - Exception Handling and seek()

NEW QUESTION # 15
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. Send metadata request to the same broker for the topic and select the broker hosting the leader replica
B. Get the Broker id from Zookeeper that is hosting the leader replica and send request to it
C. Send fetch request to each Broker in the cluster
D. Send metadata request to Zookeeper for the topic and select the broker hosting the leader replica

Answer: A

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 # 16
What is accomplished by producing data to a topic with a message key?

A. Kafka brokers allow you to add more partitions to a given topic, without impacting the data flow for existing keys.
B. It provides a mechanism for encrypting messages at the partition level to ensure secure data transmission.
C. Messages with the same key are routed to a deterministically selected partition, enabling order guarantees within that partition.
D. Consumers can filter messages in real time based on the message key without processing unrelated messages.

Answer: C

Explanation:
When amessage keyis specified in Kafka, the producer uses apartitioner(typically the default hash-based partitioner) todeterministically map all records with the same key to the same partition. Kafka guarantees order within a partition, so this enables per-key ordering.
FromKafka Producer Concepts:
"If a key is present, the producer will always route records with the same key to the same partition. Kafka preserves the order of records within a partition." This is essential for ordered processing and join semantics.
Reference:Kafka Producer Design > Partitions and Keys

NEW QUESTION # 17
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