This lecture covers the internals of Avro serialization and deserialization, focusing on how data and schema are transmitted together in Kafka. It highlights the challenges of bulky messages and inefficient network usage due to schema transmission. The lecture introduces the Schema Registry as a solution, which allows sending schema IDs instead of full schemas, reducing message size and improving efficiency. A practical example demonstrates the impact of schema on message size, and the lecture concludes with a preview of future topics.

What is the primary benefit of using binary encoded Avro data?

• It increases the size of the data.

• It eliminates the need for a schema.

• It results in smaller serialized data.

• It includes type information and field names.

Why is sending the schema with every Avro event considered inefficient?

• It eliminates the need for a Schema Registry.

• It simplifies the deserialization process.

• It leads to inefficient network bandwidth usage.

• It reduces the size of the message.

What solution is proposed to avoid sending the schema with every Avro event?

• Eliminating the use of schemas entirely.

• Using a different serialization format.

• Utilizing a Schema Registry.

• Sending the schema as a whole.

How does sending the schema with Avro payloads affect the message size?

• It reduces the message size by half.

• It doubles the message size.

• It triples the message size.

• It has no effect on the message size.

What is the ultimate goal in optimizing Avro communication between producers and consumers?

• To increase the size of Avro messages.

• To use schema IDs for retrieving schemas.

• To send the full schema with every message.

• To eliminate the use of Avro serialization.