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Confluent CCDAK Exam Syllabus Topics:

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

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Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q13-Q18):

NEW QUESTION # 13
If you enable an SSL endpoint in Kafka, what feature of Kafka will be lost?

A. Cross-cluster mirroring
B. Zero copy
C. Support for Avro format
D. Exactly-once delivery

Answer: B

Explanation:
With SSL, messages will need to be encrypted and decrypted, by being first loaded into the JVM, so you lose the zero copy optimization. See more information herehttps://twitter.com/ijuma/status/1161303431501324293?s=09

NEW QUESTION # 14
Which of the following Kafka Streams operators are stateful? (select all that apply)

A. peek
B. count
C. reduce
D. flatmap
E. joining
F. aggregate

Answer: B,C,E,F

Explanation:
Seehttps://kafka.apache.org/20/documentation/streams/developer-guide/dsl-api.html#stateful-transformations

NEW QUESTION # 15
(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 and call consumer.skip() method.
C. Log the bad record; no other action is needed.
D. Log the bad record and seek the consumer to the offset of the next record.

Answer: D

Explanation:
The Apache Kafka consumer documentation explains that when a RecordDeserializationException occurs, the consumer cannot continue polling until the problematic offset is skipped. Simply logging the error is insufficient, because the consumer will repeatedly fail on the same record.
The recommended pattern is to log the malformed record, extract its topic, partition, and offset from the exception, and then call consumer.seek() to move the consumer position to the next offset (offset + 1). This allows the application to skip the poison pill and resume processing subsequent records.
Option B is invalid because Kafka does not provide a consumer.skip() API. Option C is unnecessary if the application is designed to tolerate malformed records. Option D results in an infinite failure loop.
Therefore, seeking past the bad record after logging it is the correct and officially documented way to handle poison pill records while maintaining consumer liveness and resilience.

NEW QUESTION # 16
How do you create a topic named test with 3 partitions and 3 replicas using the Kafka CLI?

A. bin/kafka-topics-create.sh --zookeeper localhost:9092 --replication-factor 3 --partitions 3 --topic test
B. bin/kafka-topics.sh --create --bootstrap-server localhost:2181 --replication-factor 3 --partitions 3 --topic test
C. bin/kafka-topics.sh --create --broker-list localhost:9092 --replication-factor 3 --partitions 3 --topic test
D. bin/kafka-topics.sh --create --bootstrap-server localhost:9092 --replication-factor 3 --partitions 3 --topic test

Answer: D

Explanation:
As of Kafka 2.3, the kafka-topics.sh command can take --bootstrap-server localhost:9092 as an argument.
You could also use the (now deprecated) option of --zookeeper localhost:2181.

NEW QUESTION # 17
Refer to the producer code below. It features a 'Callback' class with a method called 'onCompletion()'.
In the 'on Completion*.)' method, what does the 'metadata.offset()' value represent?

producer.send(record, new MyCallback(record));

A. The id of the partition that the message was committed to
B. The sequential id of the message is committed into a partition
C. The number of bytes that overflowed beyond a producer batch of messages
D. Its position in the producer's batch of messages

Answer: B

NEW QUESTION # 18
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