Kafka客户端基础使用

依赖

引入以下依赖

        <!-- https://mvnrepository.com/artifact/org.apache.kafka/kafka-clients -->
        <dependency>
            <groupId>org.apache.kafka</groupId>
            <artifactId>kafka-clients</artifactId>
            <version>4.1.0</version>
        </dependency>

生产者

• 文档： https://kafka.apache.org/documentation/#producerapi

1. 设置服务配置，例如序列化，IP端口等

        final Properties props = new Properties() {{
            // 服务IP端口配置
            put(BOOTSTRAP_SERVERS_CONFIG, "study.fedora01.com:9092,study.fedora02.com:9092,study.fedora03.com:9092");

            // 序列化
            put(KEY_SERIALIZER_CLASS_CONFIG, StringSerializer.class.getCanonicalName());
            put(VALUE_SERIALIZER_CLASS_CONFIG, StringSerializer.class.getCanonicalName());
        }};

2. 发送消息
   2.1 单向发送，不关心是否发送成功

        try (final Producer<String, String> producer = new KafkaProducer<>(props)) {
            final Random rnd = new Random();
            final int numMessages = 10;
            for (int i = 0; i < numMessages; i++) {
                String user = users[rnd.nextInt(users.length)];
                String item = items[rnd.nextInt(items.length)];


                // 单向发送, 不关心是否发送成功
                producer.send(
                        new ProducerRecord<>(topic, user, item));
            System.out.printf("%s events were produced to topic %s%n", numMessages, topic);
        }

2.2 同步发送, 发送完成后获取服务端发送情况，如果一直未发送成功那么就会进行阻塞

     try (final Producer<String, String> producer = new KafkaProducer<>(props)) {
            final Random rnd = new Random();
            final int numMessages = 10;
            for (int i = 0; i < numMessages; i++) {
                String user = users[rnd.nextInt(users.length)];
                String item = items[rnd.nextInt(items.length)];

                // 同步发送, 发送完成后获取服务端发送情况，如果一直未发送成功那么就会进行阻塞
                RecordMetadata recordMetadata = producer.send(
                        new ProducerRecord<>(topic, user, item),
                        (event, ex) -> {
                            if (ex != null)
                                ex.printStackTrace();
                            else
                                System.out.printf("Produced event to topic %s: key = %-10s value = %s%n", topic, user, item);
                        }).get();
            }

2.3 异步发送, 回调函数处理异步响应信息

      try (final Producer<String, String> producer = new KafkaProducer<>(props)) {
            final Random rnd = new Random();
            final int numMessages = 10;
            for (int i = 0; i < numMessages; i++) {
                String user = users[rnd.nextInt(users.length)];
                String item = items[rnd.nextInt(items.length)];
                // 异步发送, 回调函数处理异步响应信息
                producer.send(
                        new ProducerRecord<>(topic, user, item),
                        (event, ex) -> {
                            if (ex != null)
                                ex.printStackTrace();
                            else
                                System.out.printf("Produced event to topic %s: key = %-10s value = %s%n", topic, user, item);
                        });

            }
            System.out.printf("%s events were produced to topic %s%n", numMessages, topic);
        }

消费者

• 文档: https://kafka.apache.org/documentation/#consumerapi

1. 设置配置信息

        String topic = "producer-topic";

        Properties props = new Properties();
        // 设置服务地址
        props.put("bootstrap.servers", "study.fedora01.com:9092,study.fedora02.com:9092,study.fedora03.com:9092");
        // 消费者端需要设置一个group id来消费信息
        props.put("group.id", "test-group-2"); 
        // 序列化
        props.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
        props.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");

        Consumer<String, String> consumer = new KafkaConsumer<>(props);

2. 监听topic

        consumer.subscribe(Collections.singletonList(topic));

        System.out.println("开始消费topic: " + topic);

3. 处理消息，每隔1000毫秒拉取一次

        while (true) {
            ConsumerRecords<String, String> records = consumer.poll(Duration.ofMillis(1000));
            if (records.isEmpty()) {
                System.out.println("还没有读取到消息...");
            }
            for (ConsumerRecord<String, String> record : records) {
                System.out.printf("Key=%s, Value=%s, Partition=%d, Offset=%d%n",
                        record.key(), record.value(), record.partition(), record.offset());
            }
        }