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从分区的开始进行消费，因为kafka会定期清理历史数据，所以分区开始的位移不一定为0。seekToBeginning只是从目前保留的数据中最小的offset进行消费

package com.cisdi.dsp.modules.metaAnalysis.rest.kafka2023;import org.apache.kafka.clients.consumer.*;
import org.apache.kafka.clients.producer.ProducerConfig;
import org.apache.kafka.common.PartitionInfo;
import org.apache.kafka.common.TopicPartition;
import org.apache.kafka.common.serialization.StringDeserializer;
import org.apache.kafka.common.serialization.StringSerializer;import java.time.Duration;
import java.time.temporal.TemporalUnit;
import java.util.*;
import java.util.concurrent.TimeUnit;
/*
从分区开头进行消费; seekToBeginning)*/public class KafkaTest14 {private static Properties getProperties(){Properties properties=new Properties();properties.setProperty(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class.getName());properties.setProperty(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class.getName());properties.setProperty(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG,"xx.xx.xx.xx:9092");properties.setProperty(ConsumerConfig.GROUP_ID_CONFIG,"testGroup12");//properties.setProperty(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG,"false");return properties;}public static void main(String[] args) {KafkaConsumer<String,String> myConsumer=new KafkaConsumer<String, String>(getProperties());myConsumer.subscribe(Arrays.asList("student"));Set<TopicPartition> topicPartitionSet = new HashSet<>();while(topicPartitionSet.size() == 0){ConsumerRecords<String,String> consumerRecords=myConsumer.poll(Duration.ofMillis(5000));topicPartitionSet = myConsumer.assignment();}myConsumer.seekToBeginning(topicPartitionSet);while(true){ConsumerRecords<String, String> consumerRecords = myConsumer.poll(Duration.ofMillis(5000));for(ConsumerRecord record: consumerRecords){System.out.println(record.value());System.out.println(record.offset());}}}
}