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You have a topic with four partitions. The application reads from it using two consumers in a single consumer group.
Processing is CPU-bound, and lag is increasing.
What should you do?

• A. Add more partitions to the topic to increase the level of parallelism of the processing.
• B. Increase the max.poll.records property of consumers.
• C. Add more consumers to increase the level of parallelism of the processing.
• D. Decrease the max.poll.records property of consumers.

(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. 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.
• 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. Use a GlobalKTable for one of the topics where data does not change frequently and use a KStream- GlobalKTable join.

You need to correctly join data from two Kafka topics.
Which two scenarios will allow for co-partitioning?
(Select two.)

• A. Both topics have the same retention time.
• B. Both topics have the same key and partitioning strategy.
• C. Both topics have the same value schema.
• D. Both topics have the same number of partitions.

You have a Kafka consumer in production actively reading from a critical topic.
You need to update the offset of your consumer to start reading from the beginning of the topic.
Which action should you take?

• A. Temporarily configure the topic's retention.ms parameter to 0 to empty the topic.
• B. Start a new consumer application with the same consumer group id.
• C. Update the consumer configuration by setting auto.offset.reset=earliest.
• D. Update the consumer group's offset to the earliest position using the kafka-consumer-groups CLI tool.

(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": "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*"}
• C. {"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"}
• 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"}