Kafka for Developers - Data Contracts Using Schema Registry - Date Logical Type

This lecture covers the implementation of a date logical type in an Avro schema for a coffee order system. It demonstrates creating a new field for order date, regenerating Avro classes, and updating the consumer application to handle the new schema. The process includes publishing new records and verifying the order date field in the consumer.

What is the purpose of adding a new field named 'order date' in the coffee order schema?

• To replace the existing order time field

• To demonstrate the implementation of the date logical type

• To remove the timestamp functionality

• To improve the performance of the schema

Which logical type is used for the 'order date' field in the Avro schema?

• Timestamp milliseconds

• Float

• String

• Date

What is the next step after adding the 'order date' field in the schema?

• Removing the old schema

• Updating the producer application

• Regenerating the Avro classes

• Publishing a new record

Why is it important to update the consumer before the producer when changing the schema?

• To allow the consumer to generate new fields

• To improve the consumer's performance

• To ensure the producer can publish new records

• To prevent breaking the consumer with unmatched schema

What is verified after publishing a new record with the updated schema?

• The presence of the order date field

• The compatibility of the old schema

• The removal of the order time field

• The performance of the producer