Kafka connect and schema registry in a high-volume environment example in java

Category : Apache Kafka | Sub Category : Apache Kafka | By Prasad Bonam Last updated: 2023-08-03 01:09:58 Viewed : 381

Kafka connect and schema registry in a high-volume environment example in java:

lets walk through an example of how to use Kafka Connect and Schema Registry in a high-volume environment using Java. For this example, we`ll assume that you have already set up Apache Kafka, Kafka Connect, and Schema Registry in your environment.

Step 1: Create a Kafka Connect Source Connector In this example, we`ll create a custom source connector that generates random data and sends it to a Kafka topic. we`ll use Avro as the serialization format, so we`ll also define the Avro schema for our data.

javaCopy code
import org.apache.kafka.connect.data.Schema;
import org.apache.kafka.connect.data.SchemaBuilder;
import org.apache.kafka.connect.source.SourceConnector;
import org.apache.kafka.connect.source.SourceRecord;

import java.util.*;

public class HighVolumeSourceConnector extends SourceConnector {

    private String topic;
    private Random random = new Random();
    private static final Schema VALUE_SCHEMA = SchemaBuilder.struct()
            .field("id", Schema.INT32_SCHEMA)
            .field("data", Schema.STRING_SCHEMA)
            .build();

    @Override
    public void start(Map<String, String> props) {
        // Read configuration properties here
        topic = props.get("kafka.topic");
    }

    @Override
    public Class<? extends Task> taskClass() {
        return HighVolumeSourceTask.class;
    }

    @Override
    public List<Map<String, String>> taskConfigs(int maxTasks) {
        List<Map<String, String>> configs = new ArrayList<>();
        for (int i = 0; i < maxTasks; i++) {
            Map<String, String> config = new HashMap<>();
            // Assign any necessary configurations to the task here
            configs.add(config);
        }
        return configs;
    }

    @Override
    public void stop() {
        // Perform any cleanup tasks here
    }

    @Override
    public ConfigDef config() {
        return null;
    }

    @Override
    public String version() {
        return "1.0";
    }
}

Step 2: Create a Kafka Connect Source Task Next, we`ll create the task that will run for each connector instance. The task will generate random data and send it to the Kafka topic using the Schema Registry to ensure proper serialization.

javaCopy code
import org.apache.kafka.connect.data.Schema;
import org.apache.kafka.connect.data.Struct;
import org.apache.kafka.connect.source.SourceRecord;
import org.apache.kafka.connect.source.SourceTask;

import java.util.Map;

public class HighVolumeSourceTask extends SourceTask {

    private String topic;
    private int recordId = 0;

    @Override
    public void start(Map<String, String> props) {
        // Read configuration properties here
        topic = props.get("kafka.topic");
    }

    @Override
    public void stop() {
        // Perform any cleanup tasks here
    }

    @Override
    public String version() {
        return "1.0";
    }

    @Override
    public List<SourceRecord> poll() throws InterruptedException {
        // Generate random data and send it to Kafka topic
        int id = recordId++;
        String data = "Random data for record " + id;

        Schema valueSchema = HighVolumeSourceConnector.VALUE_SCHEMA;
        Struct value = new Struct(valueSchema)
                .put("id", id)
                .put("data", data);

        return Collections.singletonList(new SourceRecord(null, null, topic, null, valueSchema, value));
    }
}

Step 3: Build and Deploy the Connector Build your custom connector and task classes into a JAR file. Then, deploy the JAR file to the Kafka Connects plugin path. Update your Kafka Connect configuration to include the new connector class:

propertiesCopy code
# kafka-connect.properties
...
# Add the custom source connector class to the list of plugins
plugin.path=/path/to/your/custom/connector.jar
...

Step 4: Configure and Run Kafka Connect Create a properties file to configure your connector, including the necessary Kafka, Schema Registry, and custom connector properties:

propertiesCopy code
# high-volume-connector.properties
name=high-volume-connector
connector.class=com.example.HighVolumeSourceConnector
tasks.max=1
kafka.topic=my-topic
# Add any other required configurations 
....

Finally, start Kafka Connect using the properties file:

bashCopy code
$ kafka/bin/connect-standalone.sh kafka/config/connect-standalone.properties high-volume-connector.properties

The custom source connector will now start generating random data and sending it to the specified Kafka topic using the Avro schema managed by the Schema Registry.

Please note that this is a simplified example to illustrate how to use Kafka Connect and Schema Registry in a high-volume environment. In a real-world scenario, you would need to handle various optimizations, error handling, and configuration tuning based on your specific use case and requirements.