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Confluent CCDAK Exam Syllabus Topics:

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

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Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q46-Q51):

NEW QUESTION # 46
You are building a system for a retail store selling products to customers.
Which three datasets should you model as a GlobalKTable?
(Select three.)

A. Log of payment transactions
B. All purchases at a retail store occurring in real time
C. Catalog of products
D. Customer profile information
E. Inventory of products at a warehouse

Answer: C,D,E

Explanation:
A GlobalKTable is a replicated, read-only table available in full on all instances. It's best for reference or lookup datasets such as:
Product catalog
Customer profiles
Warehouse inventory
From Kafka Streams Developer Guide:
"Use GlobalKTable when you need to perform joins using non-partition-aligned reference data that's small enough to replicate." Purchases and transactions are high-throughput, time-sensitive streams, not static reference data.
Reference: Kafka Streams Concepts > GlobalKTable

NEW QUESTION # 47
Partition leader election is done by

A. Vote amongst the brokers
B. Zookeeper
C. The consumers
D. The Kafka Broker that is the Controller

Answer: B

Explanation:
The Controller is a broker that is responsible for electing partition leaders

NEW QUESTION # 48
What is the risk of increasing max.in.flight.requests.per.connection while also enabling retries in a producer?

A. At least once delivery is not guaranteed
B. Less resilient
C. Message order not preserved
D. Reduce throughput

Answer: C

Explanation:
Some messages may require multiple retries. If there are more than 1 requests in flight, it may result in messages received out of order. Note an exception to this rule is if you enable the producer settingenable.
idempotence=true which takes care of the out of ordering case on its own. Seehttps://issues.apache.org/jira
/browse/KAFKA-5494

NEW QUESTION # 49
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 sequential id of the message is committed into a partition
C. The number of bytes that overflowed beyond a producer batch of messages
D. The id of the partition that the message was committed to

Answer: B

NEW QUESTION # 50
You are writing a producer application and need to ensure proper delivery. You configure the producer with acks=all.
Which two actions should you take to ensure proper error handling?
(Select two.)

A. Check the value of ProducerRecord.status().
B. Surround the call of producer.send() with a try/catch block to catch KafkaException.
C. Check that producer.send() returned a RecordMetadata object and is not null.
D. Use a callback argument in producer.send() where you check delivery status.

Answer: B,D

Explanation:
For proper delivery handling with acks=all:
* Usecallbackto log or act on success/failure.
* Usetry/catchto handle synchronous exceptions like serialization errors or network failures.
FromKafka Producer Documentation:
"Errors can be caught either via the returned Future<RecordMetadata> or via the callback interface. For fatal errors, use a try/catch block around the send call." Option B is incorrect because send() returns a Future, not RecordMetadata directly.
Option D is invalid - ProducerRecord has no method called status().
Reference:Kafka Producer Error Handling and Callback APIs

NEW QUESTION # 51
......

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