一、该篇博客使用技术版本
SpringBoot：1.5.9.RELEASE
zookeeper：zookeeper-3.4.5
kafka：kafka_2.10-0.10.2.1
二、SpringBoot集成Kafka
1、首先修改kafka的server.properties
root@VM-0-3-ubuntu:/usr/local/kafka_2.10-0.10.2.1/config# vi server.properties
找到配置文件中的advertised.listeners，将自己服务器的ip加入
advertised.listeners=PLAINTEXT://这里是服务器的ip:9092
重启zk，kafka服务，开启kafka生产者、消费者
2、集成编码
建SpringBoot项目
目录如下，其中测试下的kafka包是测试kafka生产消费，该篇博客不做阐述
application.properties
server.port=6097
spring.application.name=linjieadmin
#kafka
kafka.consumer.zookeeper.connect=启动zookeeper服务器的ip:2181
kafka.consumer.servers=启动kafka服务器的ip:9092
#消费完成自动提交
kafka.consumer.enable.auto.commit=true
kafka.consumer.session.timeout=6000
kafka.consumer.auto.commit.interval=100
#消费策略
kafka.consumer.auto.offset.reset=latest
kafka.consumer.topic=wingcloud
kafka.consumer.group.id=wingcloud
kafka.consumer.concurrency=10
kafka.producer.servers=启动kafka服务器的ip:9092
kafka.producer.retries=0
kafka.producer.batch.size=4096
kafka.producer.linger=1
kafka.producer.buffer.memory=40960
DsInfoSJservice.java
package com.example.flinkdemo.controller;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.http.HttpStatus;
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.stereotype.Controller;
import org.springframework.web.bind.annotation.RequestBody;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RequestMethod;
import javax.servlet.http.HttpServletRequest;
import javax.servlet.http.HttpServletResponse;
import java.io.IOException;
import java.io.OutputStream;
import java.io.PrintWriter;
@RequestMapping("DsInfoSJservice")
public class DsInfoSJservice {
@Autowired
private KafkaTemplate kafkaTemplate;
@RequestMapping(value = "webInfoSJService",method = RequestMethod.POST)
public void webInfoSJService(@RequestBody String jsonstr, HttpServletRequest request, HttpServletResponse response){
System.out.println("hello"+jsonstr);
//业务开始
kafkaTemplate.send("wingcloud","key",jsonstr);
//业务结束
PrintWriter printWriter = getWriter(response);
response.setStatus(HttpStatus.OK.value());
printWriter.write("success");
closeprintwriter(printWriter);
}
private PrintWriter getWriter(HttpServletResponse response){
response.setCharacterEncoding("utf-8");
response.setContentType("application/json");
OutputStream out = null;
PrintWriter printWriter = null;
try {
out = response.getOutputStream();
printWriter = new PrintWriter(out);
} catch (IOException e) {
e.printStackTrace();
}
return printWriter;
}
private void closeprintwriter(PrintWriter printWriter){
printWriter.flush();
printWriter.close();
}
}
KafkaProducerConfig.java
package com.example.flinkdemo.controller;
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;
@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<String, String>(producerConfigs());
}
@Bean
public KafkaTemplate<String,String> kafkaTemplate(){
return new KafkaTemplate<String, String>(producerFactory());
}
}
DsClienttest.java
package com.example.flinkdemo;
import java.io.*;
import java.net.HttpURLConnection;
import java.net.URL;
public class DsClienttest {
public static void main(String[] args){
String message = "kafkatest";
String adrress = "http://localhost:6097/DsInfoSJservice/webInfoSJService";
try {
URL url = new URL(adrress);
HttpURLConnection conn = (HttpURLConnection) url.openConnection();
conn.setRequestMethod("POST");//使用post
conn.setDoInput(true);
conn.setDoOutput(true);
conn.setAllowUserInteraction(true);//允许重定向
conn.setUseCaches(false);//关缓存
conn.setReadTimeout(6*1000);//超时时间6秒
//这里写自己浏览器的User-Agent
conn.setRequestProperty("User-Agent","这里写自己浏览器的User-Agent");
conn.setRequestProperty("Content-Type","application/json");
conn.connect();
OutputStream outputStream = conn.getOutputStream();
BufferedOutputStream out = new BufferedOutputStream(outputStream);
out.write(message.getBytes());
out.flush();
String temp = "";
InputStream in = conn.getInputStream();
byte[] tempbytes = new byte[1024];
while (in.read(tempbytes,0,1024) != -1){
temp+=new String(tempbytes);
}
System.out.println(conn.getResponseCode());
System.out.println(temp);
} catch (Exception e) {
e.printStackTrace();
}
}
}
好了，编码这些类即可
启动FlinkdemoApplication.java
运行DsClienttest类下的main方法
可以在其控制台下看到200，success。并且在FlinkdemoApplication.java控制台下看到相关配置信息表示集成成功
最后可以在之前开启的kafka消费者终端上看到打印了：kafkatest