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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.
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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Confluent CCDAK (Confluent Certified Developer for Apache Kafka Certification Examination) Certification Exam is a globally recognized certification exam that tests the candidate's knowledge and proficiency in Apache Kafka development using Confluent platform. Confluent Certified Developer for Apache Kafka Certification Examination certification exam is designed to certify the developers who have a thorough understanding of Apache Kafka basics, Confluent platform, and building real-world applications using Kafka.
NEW QUESTION # 18
(You are writing lightweight XML messages to a Kafka topic named userinfo.
Which format should you use for the value field?)
Answer: B
Explanation:
Apache Kafka does not impose any schema or message format; it treats records as byte arrays on the wire.
Serialization is therefore the responsibility of the producer. For lightweight XML messages, the most common and recommended approach is to represent the XML as a UTF-8 encoded string and use Kafka's built-in StringSerializer.
The official Kafka producer documentation provides StringSerializer as the standard serializer for textual data formats, including XML and JSON. This serializer converts Java String objects into byte arrays using UTF-8 encoding, making it simple, efficient, and interoperable with a wide range of consumers.
Option A is incorrect because Kafka does not provide a built-in XmlSerializer. Option C (ByteSerializer) could technically work, but it would require manually converting the XML string to a byte array, which adds unnecessary complexity for lightweight XML payloads. Option D (VoidSerializer) is used only when no value is sent and is not applicable here.
Therefore, using StringSerializer for the value field is the correct and officially supported approach for sending lightweight XML messages in Kafka.
NEW QUESTION # 19
(You are designing a stream pipeline to monitor the real-time location of GPS trackers, where historical location data is not required.
Each event has:
* Key: trackerId
* Value: latitude, longitude
You need to ensure that the latest location for each tracker is always retained in the Kafka topic.
Which topic configuration parameter should you set?)
Answer: C
Explanation:
According to the official Apache Kafka documentation, log compaction is the mechanism used to retain only the latest record for each key in a topic. By setting cleanup.policy=compact, Kafka ensures that older records with the same key are eventually removed, leaving only the most recent value for each key.
This behavior is exactly suited for use cases such as tracking the current state of an entity, including GPS tracker locations, user profiles, or configuration data. In this scenario, the key (trackerId) uniquely identifies a tracker, and the value represents its most recent latitude and longitude.
Option B (retention.ms=infinite) retains all historical data, which contradicts the requirement. Option C (min.
cleanable.dirty.ratio) controls when compaction runs, not what data is retained. Option D (retention.ms=0) would immediately delete all data and is unsafe.
Therefore, setting cleanup.policy=compact is the correct and officially documented solution to always retain the latest location per tracker.
NEW QUESTION # 20
Which SMTs is used to change the data type?
Answer: C
NEW QUESTION # 21
How much should be the heap size of a broker in a production setup on a machine with 256 GB of RAM, in PLAINTEXT mode?
Answer: D
Explanation:
In Kafka, a small heap size is needed, while the rest of the RAM goes automatically to the page cache (managed by the OS). The heap size goes slightly up if you need to enable SSL
NEW QUESTION # 22
A customer has many consumer applications that process messages from a Kafka topic. Each consumer application can only process 50 MB/s. Your customer wants to achieve a target throughput of 1 GB/s. What is the minimum number of partitions will you suggest to the customer for that particular topic?
Answer: A
Explanation:
each consumer can process only 50 MB/s, so we need at least 20 consumers consuming one partition so that 50 * 20 = 1000 MB target is achieved.
NEW QUESTION # 23
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