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By becoming certified, developers can demonstrate their proficiency in Apache Kafka and differentiate themselves from their peers. Confluent Certified Developer for Apache Kafka Certification Examination certification showcases the candidate's knowledge and validates their ability to design and develop high-quality streaming applications using Kafka. Furthermore, it helps organizations to identify individuals with the necessary skills and expertise to design and build data streaming applications, which is essential for addressing business problems in real-time.
Confluent CCDAK or Confluent Certified Developer for Apache Kafka Certification Examination is a certification exam designed for developers who want to demonstrate their expertise in Apache Kafka. Apache Kafka is an open-source distributed event streaming platform that is used to build real-time data pipelines and streaming applications. Confluent Certified Developer for Apache Kafka Certification Examination certification exam is conducted by Confluent, a company that provides a complete event streaming platform built on Apache Kafka.
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The CCDAK exam is ideal for Kafka developers who are passionate about this technology and looking for new challenges. Kafka developers who pass the exam can differentiate themselves from other developers and obtain recognition as experts in Kafka-based solutions. Confluent Certified Developer for Apache Kafka Certification Examination certification can enable developers to gain new career opportunities and increase their salary. The CCDAK Exam helps organizations looking for qualified Kafka professionals identify the right candidates for their projects.
Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q42-Q47):
NEW QUESTION # 42
If you enable an SSL endpoint in Kafka, what feature of Kafka will be lost?
- A. Support for Avro format
- B. Exactly-once delivery
- C. Cross-cluster mirroring
- 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 # 43
In Java, Avro SpecificRecords classes are
- A. automatically generated from an Avro Schema
- B. automatically generated from an Avro Schema + a Maven / Gradle Plugin
- C. written manually by the programmer
Answer: B
Explanation:
SpecificRecord is created from generated record classes
NEW QUESTION # 44
You need to collect logs from a host and write them to a Kafka topic named 'logs-topic'. You decide to use Kafka Connect File Source connector for this task.
What is the preferred deployment mode for this connector?
- A. Standalone mode
- B. SingleCluster mode
- C. Distributed mode
- D. Parallel mode
Answer: A
Explanation:
Kafka Connect can run instandalone modeordistributed mode. For simple tasks likereading logs from a file on a single host,standalone modeis recommended.
FromKafka Connect User Guide:
"Standalone mode is useful when running connectors on a single machine (e.g., for development or simple deployments like log collection from a local file)." Distributed mode is preferred for scalability and fault tolerance but overkill for this use case.
Reference:Kafka Connect User Guide > Deployment Modes
NEW QUESTION # 45
Which KSQL queries write to Kafka?
- A. SHOW STREAMS and EXPLAIN <query> statements
- B. CREATE STREAM AS SELECT and CREATE TABLE AS SELECT
- C. COUNT and JOIN
- D. CREATE STREAM WITH <topic> and CREATE TABLE WITH <topic>
Answer: B,D
Explanation:
SHOW STREAMS and EXPLAIN <query> statements run against the KSQL server that the KSQL client is connected to. They don't communicate directly with Kafka. CREATE STREAM WITH <topic> and CREATE TABLE WITH <topic> write metadata to the KSQL command topic. Persistent queries based on CREATE STREAM AS SELECT and CREATE TABLE AS SELECT read and write to Kafka topics. Non-persistent queries based on SELECT that are stateless only read from Kafka topics, for example SELECT * FROM foo WHERE. Non-persistent queries that are stateful read and write to Kafka, for example, COUNT and JOIN. The data in Kafka is deleted automatically when you terminate the query with CTRL-C.
NEW QUESTION # 46
(Your application consumes from a topic configured with a deserializer.
You want the application to be resilient to badly formatted records (poison pills).
You surround the poll() call with a try/catch block for RecordDeserializationException.
You need to log the bad record, skip it, and continue processing other records.
Which action should you take in the catch block?)
- A. Log the bad record and seek the consumer to the offset of the next record.
- B. Log the bad record and call consumer.skip() method.
- C. Log the bad record; no other action is needed.
- D. Throw a runtime exception to trigger a restart of the application.
Answer: A
Explanation:
The Apache Kafka consumer documentation explains that when a RecordDeserializationException occurs, the consumer cannot continue polling until the problematic offset is skipped. Simply logging the error is insufficient, because the consumer will repeatedly fail on the same record.
The recommended pattern is to log the malformed record, extract its topic, partition, and offset from the exception, and then call consumer.seek() to move the consumer position to the next offset (offset + 1). This allows the application to skip the poison pill and resume processing subsequent records.
Option B is invalid because Kafka does not provide a consumer.skip() API. Option C is unnecessary if the application is designed to tolerate malformed records. Option D results in an infinite failure loop.
Therefore, seeking past the bad record after logging it is the correct and officially documented way to handle poison pill records while maintaining consumer liveness and resilience.
NEW QUESTION # 47
......
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