- Lab
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Libraries: If you want this lab, consider one of these libraries.
- Cloud
Evolving an Avro Schema in a Kafka Application
Confluent Schema Registry is a useful tool for coordinating contracts between producers and consumers, as well as simplifies the process of serializing and deserializing complex data objects. However, it also provides some powerful functionality to help you manage changes to your data schemas. In this lab, you will have the opportunity to make a change to an existing schema by adding a new field. This will give you some hands-on experience with the process of evolving a schema using the Confluent Schema Registry.
Lab Info
Table of Contents
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Challenge
Clone the Starter Project and Run It to Make Sure Everything Is Working
- Clone the starter project into your
homedirectory:
cd ~/ git clone https://github.com/linuxacademy/content-ccdak-schema-evolve-lab.git- Run the code to ensure it works before modifying it:
cd content-ccdak-schema-evolve-lab ./gradlew runProducer ./gradlew runConsumerNote: The consumer should output some records that were created by the producer.
- Clone the starter project into your
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Challenge
Update the Purchase Schema to Add the `member_id` Field
- Edit the schema definition file:
vi src/main/avro/com/linuxacademy/ccdak/schemaregistry/Purchase.avsc- Add the
member_idfield with a blank default:
{ "namespace": "com.linuxacademy.ccdak.schemaregistry", "compatibility": "FORWARD", "type": "record", "name": "Purchase", "fields": [ {"name": "id", "type": "int"}, {"name": "product", "type": "string"}, {"name": "quantity", "type": "int"}, {"name": "member_id", "type": "int", "default": 0} ] } -
Challenge
Update the Producer to Set the `member_id` for the Records It Publishes
- Edit the schema definition file:
vi src/main/avro/com/linuxacademy/ccdak/schemaregistry/Purchase.avsc- Add the
member_idfield with a blank default:
{ "namespace": "com.linuxacademy.ccdak.schemaregistry", "compatibility": "FORWARD", "type": "record", "name": "Purchase", "fields": [ {"name": "id", "type": "int"}, {"name": "product", "type": "string"}, {"name": "quantity", "type": "int"}, {"name": "member_id", "type": "int", "default": 0} ] }Update the Producer to Set the
member_idfor the Records It Publishes- Edit the producer
Mainclass:
vi src/main/java/com/linuxacademy/ccdak/schemaregistry/ProducerMain.java- Implement the new
member_idfield in the producer by setting it for the records being produced:
package com.linuxacademy.ccdak.schemaregistry; import io.confluent.kafka.serializers.AbstractKafkaAvroSerDeConfig; import io.confluent.kafka.serializers.KafkaAvroSerializer; import java.util.Properties; import org.apache.kafka.clients.producer.KafkaProducer; import org.apache.kafka.clients.producer.ProducerConfig; import org.apache.kafka.clients.producer.ProducerRecord; import org.apache.kafka.common.serialization.StringSerializer; public class ProducerMain { public static void main(String[] args) { final Properties props = new Properties(); props.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092"); props.put(ProducerConfig.ACKS_CONFIG, "all"); props.put(ProducerConfig.RETRIES_CONFIG, 0); props.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, StringSerializer.class); props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, KafkaAvroSerializer.class); props.put(AbstractKafkaAvroSerDeConfig.SCHEMA_REGISTRY_URL_CONFIG, "http://localhost:8081"); KafkaProducer<String, Purchase> producer = new KafkaProducer<String, Purchase>(props); Purchase apples = new Purchase(1, "apples", 17, 77543); producer.send(new ProducerRecord<String, Purchase>("inventory_purchases", apples.getId().toString(), apples)); Purchase oranges = new Purchase(2, "oranges", 5, 56878); producer.send(new ProducerRecord<String, Purchase>("inventory_purchases", oranges.getId().toString(), oranges)); producer.close(); } }- Run the producer:
./gradlew runProducer- Run the consumer:
./gradlew runConsumer- Verify the data in the output file. We should see the new
member_iddata in the last lines of the file:
cat /home/cloud_user/output/output.txt
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