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Confluent Certified Developer for Apache Kafka Certification Examination brain dumps, CCDAK dumps pdf

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Confluent CCDAK (Confluent Certified Developer for Apache Kafka) Certification Exam is a globally recognized certification exam that tests the expertise of developers in Apache Kafka. Apache Kafka is an open-source distributed event streaming platform that is widely used by companies for building real-time data pipelines and streaming applications. The CCDAK Exam is designed to test the knowledge and skills of developers in building and managing Kafka-based applications.

Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q81-Q86):

NEW QUESTION # 81
Which of the following Kafka Streams operators are stateful? (select all that apply)

Answer: A,B,C,E

Explanation:
Seehttps://kafka.apache.org/20/documentation/streams/developer-guide/dsl-api.html#stateful-transformations


NEW QUESTION # 82
(You need to send a JSON message on the wire. The message key is a string.
How would you do this?)

Answer: D

Explanation:
According to the Apache Kafka producer documentation, serialization is configured independently for message keys and values. The key and value can use different serializers depending on their data types.
In this scenario, the message key is a string, so the producer must be configured with org.apache.kafka.
common.serialization.StringSerializer for the key. The value contains JSON, so a suitable JSON serializer must be configured for the value, such as a custom JSON serializer, a library-based serializer, or a byte-array serializer after converting the JSON to bytes.
Option B correctly reflects this separation by specifying a string serializer for the key and a JSON serializer for the value. Kafka does not automatically infer serializers, and setting a serializer to null is invalid.
Additionally, there is no built-in "JSON" serializer for keys, making Option D incorrect.
Therefore, the correct approach-fully aligned with Kafka's producer configuration model-is to explicitly configure a StringSerializer for the key and a JSON-capable serializer for the value.


NEW QUESTION # 83
A consumer wants to read messages from a specific partition of a topic. How can this be achieved?

Answer: A

Explanation:
assign() can be used for manual assignment of a partition to a consumer, in which case subscribe() must not be used. Assign() takes a collection of TopicPartition object as an argument https://kafka.apache.org/23/javadoc/org/apache/kafka/clients/consumer/KafkaConsumer.html#assign-java.util.Collection-


NEW QUESTION # 84
How often is log compaction evaluated?

Answer: A

Explanation:
Log compaction is evaluated every time a segment is closed. It will be triggered if enough data is "dirty" (see dirty ratio config)


NEW QUESTION # 85
(You are building real-time streaming applications using Kafka Streams.
Your application has a custom transformation.
You need to define custom processors in Kafka Streams.
Which tool should you use?)

Answer: A

Explanation:
The Apache Kafka Streams documentation clearly distinguishes between the Kafka Streams DSL and the Processor API. While the DSL is designed for common stream processing operations such as filtering, mapping, joining, and aggregations, it does not support fully custom processing logic.
For use cases that require custom transformations, fine-grained control over record processing, access to headers, timestamps, state stores, and punctuation, Kafka Streams provides the Processor API. This API allows developers to implement custom Processor, Transformer, or ValueTransformer classes and explicitly define the processing topology.
Option A (TopologyTestDriver) is a testing utility, not a development API. Option C (DSL) is higher-level and not suitable for advanced custom logic. Option D does not exist in Kafka.
Therefore, the correct and officially supported approach for defining custom processors in Kafka Streams is to use the Processor API.


NEW QUESTION # 86
......

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