Log Compaction Practice

The video tutorial explains the concept of log compaction in Kafka, starting with a theoretical overview and moving into practical implementation. It covers setting up a Kafka topic with specific configurations to enable log compaction, followed by the setup of a Kafka consumer and producer. The tutorial demonstrates how messages are processed and compacted, showing how duplicate keys are handled. The session concludes with a demonstration of the compaction process and a summary of the key points.

What is the primary purpose of log compaction in Kafka?

• To increase the speed of data processing

• To ensure only the latest value for each key is retained

• To reduce the size of the Kafka cluster

• To improve data encryption

What is the significance of setting the cleanup policy to 'compact' in Kafka?

• It allows for data replication

• It triggers log compaction

• It increases the number of partitions

• It enables data encryption

Why is it important to have a single partition for the 'employee salary' topic?

• To ensure all messages are processed in parallel

• To make log compaction easier

• To allow multiple consumers to read simultaneously

• To increase the replication factor

What does the 'print key equals true' property do in a Kafka consumer?

• It prints the timestamp of the message

• It prints the key of the message

• It prints the value of the message

• It prints both key and value

How does the Kafka producer ensure that keys are sent to the topic?

• By setting the 'print key equals true' property

• By using a JSON format

• By increasing the partition count

• By setting the 'parse key equals true' property

What happens to duplicate keys during log compaction?

• All values are retained

• Only the first value is retained

• Only the last value is retained

• All values are deleted

Why might log compaction not occur immediately after a message update?

• Because the topic has multiple partitions

• Because the producer is not sending messages

• Because the consumer is not running

• Because log compaction is not triggered predictably