Kafka for Developers - Data Contracts Using Schema Registry - Publish and Consume "Key" as an AVRO Record

This lecture covers how to use Avro records for both keys and values in Kafka. It explains creating an Avro schema, configuring producers and consumers to use Avro serializers and deserializers, and handling schema changes. The lecture also addresses schema incompatibility issues and demonstrates publishing and validating records in a Kafka environment.

What is the purpose of using an Avro record for the key in Kafka?

• To ensure the key is always a string

• To allow the key to have a complex structure

• To make the key and value identical

• To reduce the size of the key

What file needs to be modified to include the Avro schema in a Maven project?

• settings.xml

• application.properties

• build.gradle

• pom.xml

Which class is used for deserializing Avro records in Kafka consumers?

• KafkaStringDeserializer

• KafkaJsonDeserializer

• KafkaBinaryDeserializer

• KafkaAvroDeserializer

What is a common issue when changing the schema in a Kafka setup?

• Increased memory usage

• Network latency

• Schema incompatibility

• Data duplication

How can you resolve schema incompatibility issues in a local Kafka setup?

• By updating the consumer code

• By restarting the Kafka environment

• By changing the producer configuration

• By clearing the cache

What command is used to bring down the Docker environment in Kafka?

• docker-compose stop

• docker-compose down

• docker-compose halt

• docker-compose terminate

What does the Schema Registry track in Kafka?

• Neither key nor value schemas

• Only the key schema

• Both key and value schemas

• Only the value schema