Java实现kafka生产者和消费者

需要的依赖：

       <dependency>
            <groupId>org.apache.kafka</groupId>
            <artifactId>kafka-clients</artifactId>
            <version>2.7.0</version>
        </dependency>

生产者：

Properties properties = new Properties();
        //Kafka代理的地址，生产者建立连接broker的地址,如果是集群ip间用逗号隔开
        properties.put("bootstrap.servers", "127.0.0.1:9092");
        //除了all还可选0,或1。all表示复制的节点全部收到消息时，生产者才会收到一个来自服务器的成功响应
        properties.put("acks", "all");
        //用于序列化秘钥KEY对象
        properties.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
        //用于序列化值对象的类。下面的示例中，我们的值是String，因此我们可以使用StringSerializer类来序列化键。如果值是其他对象，则创建自定义序列化程序类
        properties.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer");
        //组id
        properties.put(ConsumerConfig.GROUP_ID_CONFIG, "duanjt_test");

        //创建生产者实例
        KafkaProducer<String,String> producer = new KafkaProducer<>(properties);

        //key,可以不传。key的作用是可以将同一topic的消息放到同一分区
        String topic = "test";
        //String key = "userName";
        //value可以传json字符串，消费的时候转成json解析
        String value = "cccc";
        ProducerRecord record = new ProducerRecord<String, String>(topic,  value);
        //发送记录
        producer.send(record);
        producer.close();

消费者：

		Properties properties = new Properties();
        properties.put("bootstrap.servers", "127.0.0.1:9092");
        properties.put("group.id", "jd-group1");
        properties.put("enable.auto.commit", "true");
        properties.put("auto.commit.interval.ms", "1000");
        properties.put("auto.offset.reset", "earliest");
        //设置会话响应的时间，超过这个时间kafka可以选择放弃消费或者消费下一条消息
        properties.put("session.timeout.ms", "30000");
        properties.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
        properties.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
        //设置每次拉取的数量，不设置默认是500
        //properties.put("max.poll.records",100);

        KafkaConsumer<String, String> kafkaConsumer = new KafkaConsumer<>(properties);
        kafkaConsumer.subscribe(Arrays.asList("test"));
        while (true) {
            Duration timeout = Duration.ofMillis(500);
            ConsumerRecords<String, String> records = kafkaConsumer.poll(timeout);

            records.forEach(record -> {
                System.out.println("Record Key: " + record.key());
                System.out.println("Record value: " + record.value());
                System.out.println("Record partition: " + record.partition());
                System.out.println("Record offset: " + record.offset());
                System.out.println("------------------------------");
            });
            //异步提交偏移量到服务器broker
            kafkaConsumer.commitAsync();
        }

消费过的再消费：

		Properties properties = new Properties();
        properties.put("bootstrap.servers", "127.0.0.1:9092");//xxx是服务器集群的ip
        properties.put("group.id", "jd-group1");
        properties.put("enable.auto.commit", "true");
        properties.put("auto.commit.interval.ms", "1000");
        properties.put("auto.offset.reset", "earliest");
        properties.put("session.timeout.ms", "30000");
        properties.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
        properties.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");

        KafkaConsumer<String, String> kafkaConsumer = new KafkaConsumer<>(properties);
        kafkaConsumer.subscribe(Arrays.asList("test"));

        Duration timeout1 = Duration.ofMillis(0);
        //timeout1为0则返回所有的分区信息，然后重新设置所有分区的偏移量
        ConsumerRecords<String, String> records = kafkaConsumer.poll(timeout1);
        long offset = 0;
        //TopicPartition 分区信息
        for (TopicPartition partition : kafkaConsumer.assignment()) {
            kafkaConsumer.seek(partition, offset);
        }

        //再次消费
        Duration timeout2 = Duration.ofMillis(500);
        ConsumerRecords<String, String> records_2 = kafkaConsumer.poll(timeout2);
        while (true) {
            records_2.forEach(record -> {
                System.out.println("Record Key: " + record.key());
                System.out.println("Record value: " + record.value());
                System.out.println("Record partition: " + record.partition());
                System.out.println("Record offset: " + record.offset());
                System.out.println("------------------------------");
            });
            //异步提交偏移量到服务器broker
            kafkaConsumer.commitAsync();
        }