springboot 配置kafka批量消费，并发消费

bash 复制代码

 @KafkaListener(id = "id0",groupId = "forest_fire_ql_firecard_test_info3",
            topicPartitions = {@TopicPartition(topic = CommonConstants.KafkaTop.personnelCardRealTimeRecord,partitions = {"0"})},
            containerFactory = "batchFactory")
    public void listener0(List<String> record, Consumer<String,String> consumer){
        consumer.commitSync();
        try {
          //业务处理
        } catch (Exception e) {
            log.error(e.toString());
        }
    }


    @KafkaListener(id = "id1",groupId = "forest_fire_ql_firecard_test_info3",
            topicPartitions = {@TopicPartition(topic = CommonConstants.KafkaTop.personnelCardRealTimeRecord,partitions = {"1"})},
            containerFactory = "batchFactory")
    public void listener1(List<String> record, Consumer<String,String> consumer){
        consumer.commitSync();
        try {
            //业务处理
        } catch (Exception e) {
            log.error(e.toString());
        }
    }


    @KafkaListener(id = "id2",groupId = "forest_fire_ql_firecard_test_info3",
            topicPartitions = {@TopicPartition(topic = CommonConstants.KafkaTop.personnelCardRealTimeRecord,partitions = {"2"})},
            containerFactory = "batchFactory")
    public void listener2(List<String> record, Consumer<String,String> consumer){
        consumer.commitSync();
        try {
            //业务处理
        } catch (Exception e) {
            log.error(e.toString());
        }
    }


    @KafkaListener(id = "id3",groupId = "forest_fire_ql_firecard_test_info3",
            topicPartitions = {@TopicPartition(topic = CommonConstants.KafkaTop.personnelCardRealTimeRecord,partitions = {"3"})},
            containerFactory = "batchFactory")
    public void listener3(List<String> record, Consumer<String,String> consumer){
        consumer.commitSync();
        try {
            //业务处理
        } catch (Exception e) {
            log.error(e.toString());
        }
    }

java 复制代码

import lombok.extern.slf4j.Slf4j;
import org.apache.kafka.clients.consumer.ConsumerConfig;
import org.apache.kafka.common.serialization.StringDeserializer;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.boot.autoconfigure.kafka.KafkaProperties;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.kafka.config.ConcurrentKafkaListenerContainerFactory;
import org.springframework.kafka.config.KafkaListenerContainerFactory;
import org.springframework.kafka.core.DefaultKafkaConsumerFactory;
import org.springframework.kafka.listener.ConcurrentMessageListenerContainer;

import java.util.HashMap;
import java.util.Map;


@Slf4j
@Configuration
public class KafkaConsumerConfig {


    @Value("${spring.kafka.bootstrap-servers}")
    private String bootstrapServersConfig;





    public Map<String,Object> consumerConfigs(){
        Map<String,Object> props = new HashMap<>();
        props.put(ConsumerConfig.GROUP_ID_CONFIG, "forest_fire_ql_firecard_test_info3");
        log.info("bootstrapServersConfig:自定义配置="+ bootstrapServersConfig);
        props.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, bootstrapServersConfig);
        props.put(ConsumerConfig.MAX_POLL_RECORDS_CONFIG,3);
        props.put(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG,false);
        props.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG,"earliest");
        props.put(ConsumerConfig.AUTO_COMMIT_INTERVAL_MS_CONFIG,"100");
        props.put(ConsumerConfig.MAX_POLL_INTERVAL_MS_CONFIG,"20000");
        props.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);
        props.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);
        return props;
    }

    @Bean
    public KafkaListenerContainerFactory<ConcurrentMessageListenerContainer<String, Object>> batchFactory(KafkaProperties properties) {
        //Map<String, Object> consumerProperties = properties.buildConsumerProperties();
        ConcurrentKafkaListenerContainerFactory<String, Object> factory = new ConcurrentKafkaListenerContainerFactory<>();
        factory.setConsumerFactory(new DefaultKafkaConsumerFactory<>(consumerConfigs()));
        //并发数量
        factory.setConcurrency(3);
        //开启批量监听,消费
        factory.setBatchListener(true);
        //factory.set
        return factory;
    }

}

按照以上配置内容即可，可以达到kafka批量消费的能力。

但是，要特别需要注意的一个点是：并发量根据实际的分区数量决定，必须小于等于分区数，否则会有线程一直处于空闲状态。

下面是创建4个分区的命令写法

bash 复制代码

bin/kafka-topics.sh --create --bootstrap-server localhost:9092 --topic   personnel_card_real_time_recordinfo    --partitions 4 --replication-factor 1