ccDangJianExam/src/main/java/UnitTest/kafkaConsumerTest.java

package UnitTest;

import org.apache.kafka.clients.consumer.*;
import org.apache.kafka.common.TopicPartition;
import org.apache.kafka.common.serialization.StringDeserializer;

import java.text.ParseException;
import java.text.SimpleDateFormat;
import java.util.*;

public class kafkaConsumerTest {

    /**
     * 功能：获取kafka的时间戳
     *
     * @param dateString
     * @return
     * @throws ParseException
     */
    public static long getKafkaTimeStamp(String dateString) throws ParseException {
        SimpleDateFormat sdf = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
        Date date = sdf.parse(dateString);
        long millis = date.getTime();
        long kafkaTimestamp = millis / 1000;
        return kafkaTimestamp;
    }

    protected static Properties initConfig(){
        Properties properties = new Properties();
        properties.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, "10.10.14.67:9092");
        properties.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class.getName());
        properties.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class.getName());
        properties.put(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG, "false");
        properties.put(ConsumerConfig.GROUP_ID_CONFIG,"dsideal-group");
        properties.put(ConsumerConfig.CLIENT_ID_CONFIG, "dsideal1");
        return properties;
    }

    public static void main(String[] args) throws ParseException {
        KafkaConsumer<String, String> kafkaConsumer = new KafkaConsumer<String, String>(initConfig());
        String topic="test";
        kafkaConsumer.subscribe(Arrays.asList(topic));
        //kafka的分区逻辑是在poll方法里执行的,所以执行seek方法之前先执行一次poll方法
        //获取当前消费者消费分区的情况
        Set<TopicPartition> assignment = new HashSet<>();
        while (assignment.size() == 0) {
            //如果没有分配到分区,就一直循环下去
            kafkaConsumer.poll(100L);
            assignment = kafkaConsumer.assignment();
        }
        for (TopicPartition tp : assignment) {
            //消费第当前分区的offset为10的消息
            kafkaConsumer.seek(tp, 10);
        }
        while (true) {
            ConsumerRecords<String, String> consumerRecords = kafkaConsumer.poll(2000L);
            System.out.println("本次拉取的消息数量:" + consumerRecords.count());
            System.out.println("消息集合是否为空:" + consumerRecords.isEmpty());
            for (ConsumerRecord<String, String> consumerRecord : consumerRecords) {
                System.out.println("消费到的消息key:" + consumerRecord.key() + ",value:" + consumerRecord.value() + ",offset:" + consumerRecord.offset());
            }
        }
    }
}
//https://blog.csdn.net/qq_39839075/article/details/105522855