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CCDAK Latest Dumps Book | Test CCDAK Cram Review

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The CCDAK certification exam covers a wide range of topics related to Kafka development, including Kafka basics, cluster setup, producer and consumer development, Kafka Streams, and Kafka Connect. CCDAK exam is designed to test a developer’s ability to design, develop, and deploy Kafka-based applications using best practices and industry standards. CCDAK Exam is divided into multiple sections, each focusing on a specific area of Kafka development. CCDAK exam requires a deep understanding of Kafka and its related technologies, making it a valuable certification for developers who are interested in building and maintaining Kafka-based applications.

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Pass Guaranteed Quiz 2025 Confluent CCDAK: Confluent Certified Developer for Apache Kafka Certification Examination Fantastic Latest Dumps Book

The PDFVCE Confluent Certified Developer for Apache Kafka Certification Examination (CCDAK) exam dumps are being offered in three different formats. The names of these formats are PDFVCE CCDAK PDF questions file, desktop practice test software, and web-based practice test software. All these three PDFVCE CCDAK Exam Dumps formats contain the real Confluent CCDAK exam questions that will help you to streamline the CCDAK exam preparation process.

The CCDAK exam covers a range of topics related to Kafka, including Kafka architecture, configuration, and management, message producers and consumers, stream processing with Kafka Streams, and Kafka Connect. CCDAK exam is designed to test your ability to configure, develop, and manage Kafka clusters, as well as your knowledge of Kafka best practices.

Confluent CCDAK certification exam is a comprehensive exam that covers all aspects of Kafka development, including Kafka architecture, Kafka producers and consumers, Kafka Streams, Kafka Connect, Confluent Platform, and Kafka Security. CCDAK Exam is designed to test the candidate's ability to build Kafka-based applications using Confluent Platform, and their ability to troubleshoot and optimize Kafka applications.

Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q63-Q68):

NEW QUESTION # 63
You create a topic named stream-logs with:
* A replication factor of 3
* Four partitions
* Messages that are plain logs without a keyHow will messages be distributed across partitions?

A. Messages will be distributed among all the topic partitions with strict ordering.
B. All messages will be written to the same log segment.
C. The first message will always be written to partition 0.
D. Messages will be distributed round-robin among all the topic partitions.

Answer: D

Explanation:
If amessage key is not provided, Kafka's default partitioner usesround-robin distributionacross available partitions.
FromKafka Producer Design:
"If no key is provided, the default partitioner distributes messages round-robin to available partitions."
* A is incorrect - not all go to partition 0.
* C is invalid - Kafka doesn't group messages into one segment without a key.
* D is false - ordering isnot preservedacross partitions without a key.
Reference:Kafka Producer Partitioner Behavior

NEW QUESTION # 64
Refer to the producer code below. It features a 'Callback' class with a method called 'onCompletion()'. When will the 'onCompletion()' method be Invoked?

producer.send(record, new MyCallback(record));

A. When the producer puts the message into its socket buffer
B. When a broker sends an acknowledgement to the producer
C. When a consumer sends an acknowledgement to the producer
D. When the producer batches the message

Answer: B

NEW QUESTION # 65
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?

A. 512 MB
B. 4 GB
C. 16 GB
D. 128 GB

Answer: B

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 # 66
Using the Confluent Schema Registry, where are Avro schema stored?

A. In the Zookeeper node /schemas
B. In the Schema Registry embedded SQL database
C. In the _schemas topic
D. In the message bytes themselves

Answer: C

Explanation:
The Schema Registry stores all the schemas in the _schemas Kafka topic

NEW QUESTION # 67
What is a consequence of increasing the number of partitions in an existing Kafka topic?

A. The acknowledgment process will increase latency for producers using acks=all.
B. Consumers will need to process data from more partitions which will significantly increase consumer lag.
C. Records with the same key could be located in different partitions.
D. Existing data will be redistributed across the new number of partitions temporarily increasing cluster load.

Answer: B

Explanation:
Increasing partitions increasesparallelism, but also means:
* Consumers in a group may have to handlemore partitions, especially if the number of consumers is lower than the number of partitions.
* This can result inincreased lag, especially under high load.
FromKafka Topic Management Docs:
"Increasing the number of partitions increases consumer work, and if consumers can't keep up, lag can accumulate."
* A is false:existing data is not redistributed.
* B is false:records with the same key always map to the same partitionbased on hash.
* D is not directly impacted by the partition count.
Reference:Kafka Topic Management > Adding Partitions

NEW QUESTION # 68
......

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