Springboot中使用kafka

注:kafka消息队列默认采用配置消息主题进行消费，一个topic中的消息只能被同一个组（groupId）的消费者中的一个消费者消费。

1.在pom.xml依赖下新添加一下kafka依赖ar包

<!--kafka-->
<dependency>
   <groupId>org.springframework.kafka</groupId>
   <artifactId>spring-kafka</artifactId>
   <version>1.1.1.RELEASE</version>
</dependency>
<dependency>
   <groupId>org.apache.kafka</groupId>
   <artifactId>kafka_2.10</artifactId>
   <version>0.10.0.1</version>
</dependency>

2.在application.properties增加配置：

#原始数据kafka读取
kafka.consumer.servers=IP:9092,IP:9092(kafka消费集群ip+port端口)
kafka.consumer.enable.auto.commit=true(是否自动提交)
kafka.consumer.session.timeout=20000(连接超时时间)
kafka.consumer.auto.commit.interval=100
kafka.consumer.auto.offset.reset=latest(实时生产，实时消费，不会从头开始消费)
kafka.consumer.topic=result(消费的topic)
kafka.consumer.group.id=test(消费组)
kafka.consumer.concurrency=10(设置消费线程数)

#协议转换后存储kafka
kafka.producer.servers=IP:9092,IP:9092(kafka生产集群ip+port端口)
kafka.producer.topic=result(生产的topic)
kafka.producer.retries=0
kafka.producer.batch.size=4096
kafka.producer.linger=1
kafka.producer.buffer.memory=40960

3.生产者配置类：

package com.mapbar.track_storage.config;

import org.apache.kafka.clients.producer.ProducerConfig;
import org.apache.kafka.common.serialization.StringSerializer;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.kafka.annotation.EnableKafka;
import org.springframework.kafka.core.DefaultKafkaProducerFactory;
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.kafka.core.ProducerFactory;

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

/**
* kafka生产配置
* @author Lvjiapeng
*
*/
@Configuration
@EnableKafka
public class KafkaProducerConfig {
@Value("${kafka.producer.servers}")
private String servers;
@Value("${kafka.producer.retries}")
private int retries;
@Value("${kafka.producer.batch.size}")
private int batchSize;
@Value("${kafka.producer.linger}")
private int linger;
@Value("${kafka.producer.buffer.memory}")
private int bufferMemory;

public Map<String, Object> producerConfigs() {
Map<String, Object> props = new HashMap<>();
props.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, servers);
props.put(ProducerConfig.RETRIES_CONFIG, retries);
props.put(ProducerConfig.BATCH_SIZE_CONFIG, batchSize);
props.put(ProducerConfig.LINGER_MS_CONFIG, linger);
props.put(ProducerConfig.BUFFER_MEMORY_CONFIG, bufferMemory);
props.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
return props;
}

public ProducerFactory<String, String> producerFactory() {
return new DefaultKafkaProducerFactory<>(producerConfigs());
}

@Bean
public KafkaTemplate<String, String> kafkaTemplate() {
return new KafkaTemplate<String, String>(producerFactory());
}
}

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