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Confluent Certified Developer for Apache Kafka (CCDAK) Certification Examination is designed for developers who wish to demonstrate their expertise in developing Apache Kafka-based applications using Confluent's platform. Confluent is a leading provider of Apache Kafka-based solutions, and the CCDAK certification confirms that developers have the necessary skills to design, develop, and troubleshoot Kafka-based applications using Confluent's platform.
The CCDAK exam covers a wide range of topics, including Kafka architecture, data modeling, stream processing, and security. CCDAK examination comprises multiple-choice questions and hands-on exercises that require the candidate to demonstrate their practical knowledge of Kafka. Successful completion of the CCDAK exam certifies that the individual has the expertise to design, build, and maintain Kafka-based solutions, making them a valuable asset to any organization that uses Kafka for data processing and messaging.
Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q160-Q165):
NEW QUESTION # 160
An ecommerce wesbite sells some custom made goods. What's the natural way of modeling this data in Kafka streams?
- A. Purchase as stream, Product as stream, Customer as stream
- B. Purchase as table, Product as table, Customer as table
- C. Purchase as stream, Product as table, Customer as table
- D. Purchase as stream, Product as table, Customer as stream
Answer: C
Explanation:
Mostly-static data is modeled as a table whereas business transactions should be modeled as a stream.
NEW QUESTION # 161
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 batches the message
- B. When a broker sends an acknowledgement to the producer
- C. When the producer puts the message into its socket buffer
- D. When a consumer sends an acknowledgement to the producer
Answer: B
NEW QUESTION # 162
If you enable an SSL endpoint in Kafka, what feature of Kafka will be lost?
- A. Cross-cluster mirroring
- B. Support for Avro format
- C. Exactly-once delivery
- D. Zero copy
Answer: D
Explanation:
With SSL, messages will need to be encrypted and decrypted, by being first loaded into the JVM, so you lose the zero copy optimization. See more information herehttps://twitter.com/ijuma/status
/1161303431501324293?s=09
NEW QUESTION # 163
When using plain JSON data with Connect, you see the following error messageorg.apache.kafka.connect.errors.DataExceptionJsonDeserializer with schemas.enable requires "schema" and "payload" fields and may not contain additional fields. How will you fix the error?
- A. Set key.converter, value.converter to AvroConverter and the schema registry url
- B. Set key.converter.schemas.enable and value.converter.schemas.enable to false
- C. Use Single Message Transforms to add schema and payload fields in the message
- D. Set key.converter, value.converter to JsonConverter and the schema registry url
Answer: B
Explanation:
You will need to set the schemas.enable parameters for the converter to false for plain text with no schema.
NEW QUESTION # 164
You use Kafka Connect with the JDBC source connector to extract data from a large database and push it into Kafka.
The database contains tens of tables, and the current connector is unable to process the data fast enough.
You add more Kafka Connect workers, but throughput doesn't improve.
What should you do next?
- A. Add more Kafka brokers to the cluster.
- B. Increase the value of the connector's property tasks.max.
- C. Modify the database schemas to enable horizontal sharding.
- D. Increase the number of Kafka partitions for the topics.
Answer: B
Explanation:
Increasingtasks.maxallows the connector to createmultiple tasks, each responsible for processing different tables or table partitions. If onlyone taskis used,adding more workers has no effect.
FromKafka Connect JDBC Connector Docs:
"Use tasks.max to configure how many tasks are created for the connector. Each task can process a subset of the data."
* A and C help only if the bottleneck is in Kafka, not Connect.
* D is a large architectural change, not the first step.
Reference:Kafka Connect JDBC Connector Configuration
NEW QUESTION # 165
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