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Confluent CCDAK Exam Syllabus Topics:

Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions:

Question 1

(Which configuration is valid for deploying a JDBC Source Connector to read all rows from the orders table and write them to the dbl-orders topic?)

A. {"name": "jdbc-source","connector.class": "io.confluent.connect.jdbc.JdbcSourceConnector","tasks.
max": "1","connection.url": "jdbc:mysql://mysql:3306/dbl?user=user&password=pas","topic.prefix":
"dbl-","table.whitelist": "orders"}
B. {"name": "orders-connect","connector.class": "io.confluent.connect.jdbc.DdbcSourceConnector","tasks.
max": "1","connection.url": "jdbc:mysql://mysql:3306/dbl","topic.whitelist": "orders","auto.create":
"true"}
C. {"name": "dbl-orders","connector.class": "io.confluent.connect.jdbc.DdbcSourceConnector","tasks.
max": "1","connection.url": "jdbc:mysql://mysql:3306/dbl?user=user&password=pas","topic.prefix":
"dbl-","table.blacklist": "ord*"}
D. {"name": "jdbc-source","connector.class": "io.confluent.connect.jdbc.DdbcSourceConnector","tasks.
max": "1","connection.url": "jdbc:mysql://mysql:3306/dbl?user=user&useAutoAuth=true","topic.
prefix": "dbl-","table.whitelist": "orders"}

Question 2

The producer code below features a Callback class with a method called onCompletion().
In the onCompletion() method, when the request is completed successfully, what does the value metadata.
offset() represent?

A. The sequential ID of the message committed into a partition
B. Its position in the producer's batch of messages
C. The number of bytes that overflowed beyond a producer batch of messages
D. The ID of the partition to which the message was committed

Question 3

(A stream processing application tracks user activity in online shopping carts, including items added, removed, and ordered throughout the day for each user.
You need to capture data to identify possible periods of user inactivity.
Which type of Kafka Streams window should you use?)

A. Sliding
B. Session
C. Tumbling
D. Hopping

Question 4

You are creating a Kafka Streams application to process retail data.
Match the input data streams with the appropriate Kafka Streams object.

Question 5

(You want to enrich the content of a topic by joining it with key records from a second topic.
The two topics have a different number of partitions.
Which two solutions can you use?
Select two.)

A. Use a GlobalKTable for one of the topics where data does not change frequently and use a KStream- GlobalKTable join.
B. Create as many Kafka Streams application instances as the maximum number of partitions of the two topics and use a KStream-KTable join.
C. Use a KStream-KTable join; Kafka Streams will automatically repartition the topics to satisfy the co- partitioning constraint.
D. Repartition one topic to a new topic with the same number of partitions as the other topic (co- partitioning constraint) and use a KStream-KTable join.

Solutions: