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Fire and forget:

Sumit Rawal answered on May 31, 2023 Popularity 7/10 Helpfulness 1/10

answer Fire and forget:

Fire and forget:

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Fire and forget: Message is sent to Kafka with no effort made to verify if the message was received successfully by the Kafka broker. In most instances, the messages will be received by Kafka, since the producer has retries built-in for failures. However, this method is still prone to losing messages when retries exhaust.

public class AsyncProducerExample {

    public static void main(String[] args) throws InterruptedException {
        // Set-up mandatory properties
        Properties kafkaProps = new Properties();
        kafkaProps.put("bootstrap.servers", "localhost:9092");
        kafkaProps.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
        kafkaProps.put("value.serializer",
                "org.apache.kafka.common.serialization.StringSerializer");

        // Create an object of KafkaProducer and pass in the properties
        KafkaProducer producer = new KafkaProducer<String, String>(kafkaProps);

        // Create a record/message that we want to send to Kafka. Note, in this example we are
        // passing the topic, the key and the value. Recall, that the message key is optional.
        ProducerRecord<String, String> record = new ProducerRecord<>("datajek-topic", "my-key-async",
                "my-value-async");
        try {

            // We must pass an object of type that implements the interface
            // org.apache.kafka.clients.producer.Callback.
            producer.send(record, new ProducerCallback());
            System.out.println("Kafka message sent asynchronously.");

        } catch (Exception e) {
            System.out.println("Exception sending message asynchronously" + e.getMessage());
        } finally {
            // When you're finished producing records, you can flush the producer to ensure it has all been
            // written to Kafka and then close the producer to free its resources.
            producer.flush();
            producer.close();
        }

        // wait before exiting to hear from Kafka broker
        Thread.sleep(3000);        
    }

    private static class ProducerCallback implements Callback {
        @Override
        public void onCompletion(RecordMetadata recordMetadata, Exception e) {
            if (e != null) {
                e.printStackTrace();
            } else {
                // The RecordMetadata object contains the offset and partition for the message.
                System.out.println(String.format("Message written to partition %s with offset %s", recordMetadata.partition(),
                        recordMetadata.offset()));
            }
        }
    }
}

https://www.educative.io/courses/scalable-data-pipelines-kafka/7DPWqqp0g9w

Popularity 7/10 Helpfulness 1/10 Language java

Source: Grepper

Tags: java

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Contributed on May 31 2023

Sumit Rawal

0 Answers Avg Quality 2/10

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