Spark Streaming实时流处理项目实战笔记——Kafka Consumer Java API编程

kafka-console-producer.sh --broker-list hadoop2:9092 --topic zz
>hello world

import java.util.Arrays;
import java.util.Properties;
import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.apache.kafka.clients.consumer.ConsumerRecords;
import org.apache.kafka.clients.consumer.KafkaConsumer;
public class CustomNewConsumer {
    public static void main(String[] args) {
        Properties props = new Properties();
        // 定义kakfa 服务的地址，不需要将所有broker指定上
        props.put("bootstrap.servers", "hadoop2:9092");
        // 制定consumer group
        props.put("group.id", "test");
        // 是否自动确认offset
        props.put("enable.auto.commit", "true");
        // 自动确认offset的时间间隔
        props.put("auto.commit.interval.ms", "1000");
        // key的序列化类
        props.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
        // value的序列化类
        props.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
        // 定义consumer
        KafkaConsumer<String, String> consumer = new KafkaConsumer<String, String>(props);
        // 消费者订阅的topic, 可同时订阅多个
        consumer.subscribe(Arrays.asList("zz"));
        while (true) {
            // 读取数据，读取超时时间为100ms
            ConsumerRecords<String, String> records = consumer.poll(100);
            for (ConsumerRecord<String, String> record : records)
                System.out.printf("offset = %d, key = %s, value = %s%n", record.offset(), record.key(), record.value());
        }
    }
}