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Confluent CCDAK Exam Syllabus Topics:

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

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Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q42-Q47):

NEW QUESTION # 42
In Kafka, every broker... (select three)

A. contains all the topics and all the partitions
B. is a controller
C. knows the metadata for the topics and partitions it has on its disk
D. contains only a subset of the topics and the partitions
E. knows all the metadata for all topics and partitions
F. is a bootstrap broker

Answer: D,E,F

Explanation:
Kafka topics are divided into partitions and spread across brokers. Each brokers knows about all the metadata and each broker is a bootstrap broker, but only one of them is elected controller

NEW QUESTION # 43
To prevent network-induced duplicates when producing to Kafka, I should use

A. max.in.flight.requests.per.connection=1
B. enable.idempotence=true
C. retries=200000
D. batch.size=1

Answer: B

Explanation:
Producer idempotence helps prevent the network introduced duplicates. More details herehttps://cwiki.apache.org/confluence/display/KAFKA/Idempotent+Producer

NEW QUESTION # 44
A producer is sending messages with null key to a topic with 6 partitions using the DefaultPartitioner. Where will the messages be stored?

A. Partition 0
B. Partition 5
C. The partition for the null key
D. Any of the topic partitions

Answer: B

Explanation:
Message with no keys will be stored with round-robin strategy among partitions.

NEW QUESTION # 45
A consumer has auto.offset.reset=latest, and the topic partition currently has data for offsets going from 45 to 2311. The consumer group never committed offsets for the topic before. Where will the consumer read from?

A. offset 2311
B. offset 45
C. it will crash
D. offset 0

Answer: A

Explanation:
Latest means that data retrievals will start from where the offsets currently end

NEW QUESTION # 46
In Kafka, what are Topics split into?

A. Chunks
B. Consumers
C. Partitions
D. Sub Topics

Answer: C

NEW QUESTION # 47
......

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