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Confluent CCDAK Exam Syllabus Topics:

Section	Objectives
Topic 1: Kafka Ecosystem and Confluent Platform	- Schema Registry 1. Avro, Protobuf, JSON Schema usage - ksqlDB and connectors 1. Kafka Connect basics 2. Stream querying concepts
Topic 2: Kafka Streams and Processing	- Kafka Streams API 1. Stream processing fundamentals 2. Stateful vs stateless processing - Event processing patterns 1. Windowing and aggregation 2. Exactly-once semantics
Topic 3: Kafka Fundamentals	- Data flow in Kafka 1. Producer and consumer model 2. Offset management - Kafka architecture and core concepts 1. Brokers, topics, partitions 2. Replication and fault tolerance
Topic 4: Kafka Producers and Consumers	- Consumer API 1. Rebalancing and offset commits 2. Consumer groups - Producer API 1. Serialization and partitioning strategies 2. Reliability and acknowledgments

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Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q16-Q21):

NEW QUESTION # 16
A kafka topic has a replication factor of 3 and min.insync.replicas setting of 2. How many brokers can go down before a producer with acks=1 can't produce?

A. 0
B. 1
C. 2
D. 3

Answer: C

Explanation:
min.insync.replicas does not impact producers when acks=1 (only when acks=all)

NEW QUESTION # 17
Which configuration determines how many bytes of data are collected before sending messages to the Kafka broker?

A. send.buffer.bytes
B. buffer.memory
C. max.block.size
D. batch.size

Answer: D

Explanation:
The batch.size config sets the maximum number of bytes to batch per partition before sending. This allows Kafka producers to amortize I/O and improve throughput.
From Kafka Producer Configuration Docs:
"batch.size is the maximum amount of data per partition the producer will batch before sending." buffer.memory sets total memory for the producer, not per-batch.
send.buffer.bytes is a TCP socket buffer, not a Kafka config.
max.block.ms controls blocking time, not size.
Reference: Kafka Producer Configs > batch.size

NEW QUESTION # 18
A consumer application needs to use an "at most once" delivery semantic.
What is the best consumer configuration lo avoid duplicate messages being read?

A. auto.offset.reset=earliest and enable auto commit=true
B. auto.offset.reset=latest and enable.auto.commit=true
C. auto.offset.reset-latest and enable auto commit-false
D. auto.offset.reset=eariiest and enable.auto.commit=false

Answer: B

NEW QUESTION # 19
To prevent network-induced duplicates when producing to Kafka, I should use

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

Answer: A

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

NEW QUESTION # 20
Which two statements are correct when assigning partitions to the consumers in a consumer group using the assign() API?
(Select two.)

A. All topics must have the same number of partitions to use assign() API.
B. It is mandatory to subscribe to a topic before calling assign() to assign partitions.
C. The consumer group will not be rebalanced if a consumer leaves the group.
D. The consumer chooses which partition to read without any assignment from brokers.

Answer: C,D

Explanation:
Using assign() givesmanual controlover partition assignment. In this mode:
* B is true: The applicationchooses partitionsdirectly without involving the group coordinator.
* C is true: Since no group coordination occurs,no rebalancinghappens if a consumer dies.
FromKafka Consumer API Docs:
"assign() manually assigns a list of partitions to this consumer. No coordination takes place and no rebalancing is triggered."
* A is false: subscribe() and assign() aremutually exclusive.
* D is incorrect: Partitions don't need to be equal across topics.
Reference:Kafka Consumer Java API > assign() and subscribe()

NEW QUESTION # 21
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