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Confluent Certified Developer for Apache Kafka (CCDAK) certification exam is intended for developers who want to demonstrate their expertise in building and implementing applications that use Apache Kafka. CCDAK exam is designed to test the developer's knowledge of Kafka's key concepts, architecture, and APIs. The CCDAK certification is a valuable credential that can help developers stand out in the job market and demonstrate their ability to develop robust and reliable Kafka applications.
The CCDAK certification exam is ideal for developers who are looking to establish their expertise in Apache Kafka and differentiate themselves in a competitive job market. CCDAK Exam is designed to evaluate the candidate's proficiency in developing and deploying Kafka-based applications that meet the business requirements of modern data-driven organizations. Successful candidates receive a Confluent Certified Developer for Apache Kafka certificate, which demonstrates their mastery of the essential skills needed to build scalable and reliable data streaming applications using Apache Kafka.
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The CCDAK Certification is highly valued by companies that leverage Apache Kafka for their business needs. It demonstrates that the certified individual has a deep understanding of Kafka and can develop solutions that meet the requirements of modern data-driven organizations. Confluent Certified Developer for Apache Kafka Certification Examination certification also validates the candidate’s ability to work effectively in a team and collaborate with other developers and stakeholders to deliver high-quality Kafka applications.
NEW QUESTION # 86
A Zookeeper ensemble contains 3 servers. Over which ports the members of the ensemble should be able to communicate in default configuration? (select three)
Answer: B,E,F
Explanation:
2181 - client port, 2888 - peer port, 3888 - leader port
NEW QUESTION # 87
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: C
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 # 88
Which two statements are correct when assigning partitions to the consumers in a consumer group using the assign() API?
(Select two.)
Answer: A,B
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 # 89
Which configurations define which connector is deployed?
Answer: D
NEW QUESTION # 90
(You have a Kafka consumer in production actively reading from a critical topic from which multiple other applications are consuming.
You have a new requirement to update the offset of your consumer to start reading from the beginning of the topic.
Which action would you take?)
Answer: C
Explanation:
The Apache Kafka documentation states that consumer offsets are stored per consumer group and must be explicitly reset if an application needs to reprocess data from an earlier position. The officially supported and safest way to reset offsets for an existing consumer group is by using the kafka-consumer-groups CLI tool with the --reset-offsets option and the --to-earliest flag.
Setting auto.offset.reset=earliest (Option D) only applies when no committed offset exists for a partition.
Since this consumer is already running in production, offsets are already committed, making this option ineffective. Option C does not change offsets because Kafka identifies consumers by group ID, not application instance. Option B is extremely dangerous and incorrect, as setting retention.ms=0 deletes data for all consumers and impacts other applications.
Therefore, using the CLI to reset offsets for the specific consumer group ensures controlled, auditable, and targeted offset management without affecting other consumers or the topic itself. This approach is explicitly documented in Kafka's consumer group administration tools.
NEW QUESTION # 91
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