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To prepare for the CCDAK Certification Exam, candidates can take advantage of various training resources provided by Confluent. Confluent offers online training courses, workshops, and practice exams to help candidates prepare for the exam. Additionally, candidates can also refer to the Kafka documentation and community resources for further learning.
Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q89-Q94):
NEW QUESTION # 89
(You have a Kafka Connect cluster with multiple connectors deployed.
One connector is not working as expected.
You need to find logs related to that specific connector to investigate the issue.
How can you find the connector's logs?)
- A. Change the log level to DEBUG to include connector context information.
- B. Modify the log4j.properties file to enable connector context.
- C. Modify the log4j.properties file to add a dedicated log appender for the connector.
- D. Make no change; there is no way to isolate connector logs.
Answer: C
Explanation:
The official Apache Kafka Connect documentation explains that connectors run within the same worker JVM, and all logs are written through the worker's logging framework (Log4j or Log4j2). To isolate logs for a specific connector, Kafka Connect supports connector-specific logging contexts, which can be routed to separate log files using logging configuration.
By modifying the log4j.properties (or log4j2.xml) file to define a dedicated logger and appender for the connector's package or class name, you can direct logs from that connector to a separate file. This is the recommended and documented approach for debugging individual connectors in a shared Connect cluster.
Option A is incorrect because there is no generic "enable connector context" switch. Option B may increase verbosity but does not isolate logs per connector. Option D is false; Kafka Connect explicitly supports connector-level log separation through logging configuration.
Therefore, the correct approach is to configure a dedicated log appender for the specific connector.
NEW QUESTION # 90
You are developing a Java application using a Kafka consumer.
You need to integrate Kafka's client logs with your own application's logs using log4j2.
Which Java library dependency must you include in your project?
- A. SLF4J implementation for Log4j2 (org.apache.logging.log4j:log4j-slf4j-impl)
- B. SLF4J implementation for Log4j 1.2 (org.slf4j:slf4j-log4j12)
- C. Just the log4j2 dependency of the application
- D. None, the right dependency will be added by the Kafka client dependency by transitivity.
Answer: A
Explanation:
Kafka clients use SLF4J as a logging facade. To redirect Kafka logs to log4j2, you must include the SLF4J binding for log4j2 in your classpath:
"org.apache.logging.log4j:log4j-slf4j-impl bridges SLF4J to Log4j2 so that Kafka's logs integrate into your application's Log4j2 configuration." Option A is for Log4j 1.x, which is outdated.
Option C is incorrect; Kafka clients don't include logging bindings.
Option D is insufficient without the SLF4J bridge.
Reference: Kafka Logging Integration Practices
NEW QUESTION # 91
Which of the following is not an Avro primitive type?
- A. null
- B. int
- C. long
- D. date
- E. string
Answer: D
Explanation:
date is a logical type
NEW QUESTION # 92
You are sending messages with keys to a topic. To increase throughput, you decide to increase the number of partitions of the topic. Select all that apply.
- A. All the existing records will get rebalanced among the partitions to balance load
- B. New records with the same key will get written to the partition where old records with that key were written
- C. Old records will stay in their partitions
- D. New records may get written to a different partition
Answer: C,D
Explanation:
Increasing the number of partition causes new messages keys to get hashed differently, and breaks the guarantee "same keys goes to the same partition". Kafka logs are immutable and the previous messages are not re-shuffled
NEW QUESTION # 93
You have an existing topic t1 with four partitions.
Which statement is correct about changing the number of partitions for this topic?
- A. You may decrease the partition count if you increase the replication count.
- B. You may decrease the partition count if you change the partitioning algorithm.
- C. You may increase the partition count and Kafka will leave the existing data on the original partitions.
- D. You may increase the partition count and Kafka will ensure the message ordering remains the same.
Answer: C
NEW QUESTION # 94
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