Confluent CCDAK Free Study Material - CCDAK Latest Study Questions

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Confluent CCDAK Exam Syllabus Topics:

SectionWeightObjectives
Apache Kafka Streams12%- Stream processing operations: map, filter, join, aggregation
- Error handling and state management
- Streams API concepts: topology, processors, state stores
- Windowing and time semantics
Kafka Connect15%- Source and sink connectors configuration
- Data transformation and integration patterns
- Connect architecture: workers, connectors, tasks, converters
Application Testing8%- Unit testing producers and consumers
- Mocking and test utilities
- Integration testing and test clusters
Application Observability13%- Tracing and performance tuning
- Error diagnosis and troubleshooting
- Logging and monitoring metrics
Apache Kafka Fundamentals23%- Delivery semantics: at-most-once, at-least-once, exactly-once
- Kafka architecture and data flow
- Configuration basics and cluster setup
- Core concepts: brokers, topics, partitions, replicas, offsets
Apache Kafka Application Development28%- Producer API: configuration, serialization, partitioning, error handling
- Schema management: Confluent Schema Registry, compatibility rules, evolution
- Consumer API: configuration, offset management, consumer groups, rebalancing
- Transactional messaging and idempotence

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Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q40-Q45):

NEW QUESTION # 40
Suppose you have 6 brokers and you decide to create a topic with 10 partitions and a replication factor of 3.
The brokers 0 and 1 are on rack A, the brokers 2 and 3 are on rack B, and the brokers 4 and 5 are on rack C.
If the leader for partition 0 is on broker 4, and the first replica is on broker 2, which broker can host the last replica? (select two)

Answer: B,D

Explanation:
When you create a new topic, partitions replicas are spreads across racks to maintain availability. Hence, the Rack A, which currently does not hold the topic partition, will be selected for the last replica


NEW QUESTION # 41
This schema excerpt is an example of which schema format?
package com.mycorp.mynamespace;
message SampleRecord {
int32 Stock = 1;
double Price = 2;
string Product_Name = 3;
}

Answer: D

Explanation:
This syntax is a clear match to Protocol Buffers (Protobuf). It defines a schema with fields, types, and tags, which is a format supported by Kafka when using Protobuf-based schema registry serialization.
From Confluent Schema Registry Docs:
"Kafka supports Protobuf serialization, where schemas are written in .proto files and include fields with tags." int32, double, and string are standard Protobuf types.
Avro uses JSON-style schema.
JSON Schema uses JSON object structure, not .proto.
YAML is unrelated.
Reference: Confluent Schema Registry for Protobuf


NEW QUESTION # 42
What data format isn't natively available with the Confluent REST Proxy?

Answer: C

Explanation:
Protocol buffers isn't a natively supported type for the Confluent REST Proxy, but you may use the binary format instead


NEW QUESTION # 43
How will you find out all the partitions where one or more of the replicas for the partition are not in-sync with the leader?

Answer: B


NEW QUESTION # 44
Which statement describes the storage location for a sink connector's offsets?

Answer: C

Explanation:
Kafka Connectsink connectorsuse thestandard Kafka consumer mechanismto track offsets, which means offsets are stored in the__consumer_offsets internal topic.
FromKafka Connect Documentation:
"Sink connectors are regular Kafka consumers and store their offsets in the __consumer_offsets topic like any other consumer."
* The other options refer tosource connectorsor worker configuration.
* offsets.storage.topic is relevant forsource connectors.
Reference:Kafka Connect Concepts > Sink Connectors and Offset Storage


NEW QUESTION # 45
......

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