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Confluent CCDAK Exam Syllabus Topics:

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

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Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q63-Q68):

NEW QUESTION # 63
Which of the following is true regarding thread safety in the Java Kafka Clients?

A. One Consumer needs to run in one thread
B. One Consumer can be safely used in multiple threads
C. One Producer needs to be run in one thread
D. One Producer can be safely used in multiple threads

Answer: A,D

Explanation:
KafkaConsumer is not thread-safe, KafkaProducer is thread safe.

NEW QUESTION # 64
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 fetch request to each Broker in the cluster
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. Get the Broker id from Zookeeper that is hosting the leader replica and send request to it

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 # 65
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. Its position in the producer's batch of messages
B. The number of bytes that overflowed beyond a producer batch of messages
C. The sequential id of the message is committed into a partition
D. The id of the partition that the message was committed to

Answer: C

NEW QUESTION # 66
Kafka is configured with following parameters - log.retention.hours = 168 log.retention.minutes = 168 log.retention.ms = 168 How long will the messages be retained for?

A. Broker will not start due to bad configuration
B. 168 ms
C. 168 minutes
D. 168 hours

Answer: B

Explanation:
If more than one similar config is specified, the smaller unit size will take precedence.

NEW QUESTION # 67
Your company has three Kafka clusters: Development, Testing, and Production.
The Production cluster is running out of storage, so you add a new node.
Which two statements about the new node are true?
(Select two.)

A. A new node will not have any partitions assigned to it unless a new topic is created or reassignment occurs.
B. A node ID will be assigned to the new node automatically.
C. A new node can be added without stopping existing cluster nodes.
D. A newly added node will have KRaft controller role by default.

Answer: A,C

Explanation:
* C is true: When a new broker is added,no partitions are assigned to itunless you create new topics or reassign existing onesusing kafka-reassign-partitions.sh.
* D is true: Kafka brokers arehot-pluggable; no need to stop the cluster when scaling.
FromKafka Operations Guide:
"A newly added broker won't be assigned partitions until reassignments or new topic creation."
"Kafka allows dynamic scaling by adding brokers without downtime."
* A is false: Broker IDs must bemanually setunless using dynamic broker registration in KRaft mode.
* B is false unless the cluster usesKRaft modeand the broker isspecifically assigneda controller role.
Reference:Kafka Operations > Adding Brokers

NEW QUESTION # 68
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