大家好，我是烤鸭:
今天分享下 springboot 整合 kafka。
1. 环境参数:
windows + kafka_2.11-2.3.0 + zookeeper-3.5.6 + springboot 2.3.0
2. 下载安装zookeeper + kafka
zookeeper:
https://mirror.bit.edu.cn/apache/zookeeper/zookeeper-3.5.8/apache-zookeeper-3.5.8-bin.tar.gz
复制 zoo_sample.cfg ，改名为 zoo.cfg，增加日志路径：
dataDir=D:\xxx\env\apache-zookeeper-3.5.6-bin\data
dataLogDir=D:\xxx\env\apache-zookeeper-3.5.6-bin\log启动zk，zkServer.cmd
kafka:
https://kafka.apache.org/downloads
找 Binary downloads 下载
https://archive.apache.org/dist/kafka/2.3.0/kafka_2.12-2.3.0.tgz
修改 config/server.properties，由于zk用的默认端口 2181，所以不需要改
log.dirs=D:\\xxx\\env\\kafka\\logs
启动kafka
D:\xxx\env\kafka\bin\windows\kafka-server-start.bat D:\xxx\env\kafka\config\server.properties3. springboot 接入
pom.xml
<dependencies><dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter</artifactId></dependency><dependency><groupId>org.springframework.kafka</groupId><artifactId>spring-kafka</artifactId></dependency><dependency><groupId>org.projectlombok</groupId><artifactId>lombok</artifactId><optional>true</optional></dependency><dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-test</artifactId><scope>test</scope><exclusions><exclusion><groupId>org.junit.vintage</groupId><artifactId>junit-vintage-engine</artifactId></exclusion></exclusions></dependency><dependency><groupId>org.springframework</groupId><artifactId>spring-web</artifactId></dependency><dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-web</artifactId><version>2.3.0.RELEASE</version><scope>compile</scope></dependency></dependencies>application.yml
spring:kafka:# 指定kafka server的地址，集群配多个，中间，逗号隔开bootstrap-servers: 127.0.0.1:9092# 生产者producer:# 写入失败时，重试次数。当leader节点失效，一个repli节点会替代成为leader节点，此时可能出现写入失败，# 当retris为0时，produce不会重复。retirs重发，此时repli节点完全成为leader节点，不会产生消息丢失。retries: 0# 每次批量发送消息的数量,produce积累到一定数据，一次发送batch-size: 16384# produce积累数据一次发送，缓存大小达到buffer.memory就发送数据buffer-memory: 33554432# 指定消息key和消息体的编解码方式key-serializer: org.apache.kafka.common.serialization.StringSerializervalue-serializer: org.apache.kafka.common.serialization.StringSerializerproperties:linger.ms: 1# 消费者consumer:enable-auto-commit: falseauto-commit-interval: 100mskey-deserializer: org.apache.kafka.common.serialization.StringDeserializervalue-deserializer: org.apache.kafka.common.serialization.StringDeserializerproperties:session.timeout.ms: 15000group-id: group
server:port: 8081KafkaDemoController.java
package com.mys.mys.demo.kafka.web;import com.mys.mys.demo.kafka.service.KafkaSendService;
import org.apache.kafka.clients.admin.AdminClient;
import org.apache.kafka.clients.admin.AdminClientConfig;
import org.apache.kafka.clients.admin.NewTopic;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.kafka.core.KafkaAdmin;
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RequestParam;
import org.springframework.web.bind.annotation.RestController;import java.util.Arrays;
import java.util.HashMap;
import java.util.Map;@RestController
public class KafkaDemoController {@Autowiredprivate KafkaTemplate<String, Object> kafkaTemplate;@AutowiredKafkaSendService kafkaSendService;@GetMapping("/message/send")public boolean send(@RequestParam String message) {//默认自动创建,消费者端 allow.auto.create.topics = true//createTopic();kafkaTemplate.send("testTopic-xxx15", message);return true;}//同步@GetMapping("/message/sendSync")public boolean sendSync(@RequestParam String message){kafkaSendService.sendSync("synctopic",message);return true;}//异步示例@GetMapping("/message/sendAnsyc")public boolean sendAnsys(@RequestParam String message){kafkaSendService.sendAnsyc("ansyctopic",message);return true;}/*** @Author* @Description 创建主题* @Date 2020/5/23 19:03* @Param []* @return void**/private void createTopic() {Map<String, Object> configs = new HashMap<>();configs.put(AdminClientConfig.BOOTSTRAP_SERVERS_CONFIG,"127.0.0.1:9092");KafkaAdmin admin = new KafkaAdmin(configs);NewTopic newTopic = new NewTopic("testTopic-xxx15",1,(short)1);AdminClient adminClient = AdminClient.create(admin.getConfigurationProperties());adminClient.createTopics(Arrays.asList(newTopic));}
}KafkaSendService.java
package com.mys.mys.demo.kafka.service;import com.mys.mys.demo.kafka.handler.KafkaSendResultHandler;
import org.apache.kafka.clients.producer.ProducerRecord;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.kafka.support.SendResult;
import org.springframework.stereotype.Service;
import org.springframework.util.concurrent.ListenableFuture;
import org.springframework.util.concurrent.ListenableFutureCallback;import java.util.concurrent.ExecutionException;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.TimeoutException;@Service
public class KafkaSendService {@Autowiredprivate KafkaTemplate<String,Object> kafkaTemplate;@Autowiredprivate KafkaSendResultHandler producerListener;/*** 异步示例* */public void sendAnsyc(final String topic,final String message){//统一监听处理kafkaTemplate.setProducerListener(producerListener);ListenableFuture<SendResult<String, Object>> future = kafkaTemplate.send(topic,message);//具体业务的写自己的监听逻辑future.addCallback(new ListenableFutureCallback<SendResult<String, Object>>() {@Overridepublic void onSuccess(SendResult<String, Object> result) {System.out.println("发送消息成功：" + result);}@Overridepublic void onFailure(Throwable ex) {System.out.println("发送消息失败："+ ex.getMessage());}});}/*** 同步示例* */public void sendSync(final String topic,final String message){ProducerRecord<String, Object> producerRecord = new ProducerRecord<>(topic, message);try {kafkaTemplate.send(producerRecord).get(10, TimeUnit.SECONDS);System.out.println("发送成功");}catch (ExecutionException e) {System.out.println("发送消息失败："+ e.getMessage());}catch (TimeoutException | InterruptedException e) {System.out.println("发送消息失败："+ e.getMessage());}}
}CustomerListener.java
package com.mys.mys.demo.kafka.consumer;import org.springframework.kafka.annotation.KafkaListener;
import org.springframework.stereotype.Component;@Component
public class CustomerListener {@KafkaListener(topics="testTopic")public void onMessage(String message){System.out.println("消费="+message);}@KafkaListener(topics="testTopic-xxx14")public void onMessage1(String message){System.out.println("消费="+message);}@KafkaListener(topics="testTopic-xxx15")public void onMessage15(String message){System.out.println("消费="+message);}
}KafkaSendResultHandler.java(用于接收异步的返回值)
package com.mys.mys.demo.kafka.handler;import org.apache.kafka.clients.producer.ProducerRecord;
import org.apache.kafka.clients.producer.RecordMetadata;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.kafka.support.ProducerListener;
import org.springframework.stereotype.Component;@Component
public class KafkaSendResultHandler implements ProducerListener {private static final Logger log = LoggerFactory.getLogger(KafkaSendResultHandler.class);@Overridepublic void onSuccess(ProducerRecord producerRecord, RecordMetadata recordMetadata) {log.info("Message send success : " + producerRecord.toString());}@Overridepublic void onError(ProducerRecord producerRecord, Exception exception) {log.info("Message send error : " + producerRecord.toString());}
}
4. 效果和部分源码分析
看一下项目启动的日志，消费者监听到的分区和队列名称。另外如果kafka没有这个队列，在调用send方法时自动创建,看以下这个配置。
auto.create.topics.enable ,默认为 true。
访问路径：http://localhost:8081/message/send?message=1234
输出结果。
可以看下 ProducerRecord 这个类，方法先不贴了，看这几个属性。
public class ProducerRecord<K, V> {//队列名称private final String topic;//分区名称,如果没有指定,会按照key的hash值分配。如果key也没有,按照循环的方式分配。private final Integer partition;//请求头,用来存放k、v以外的信息,默认是只读的private final Headers headers;//key-valueprivate final K key;private final V value;//时间戳，如果不传，默认按服务器时间来private final Long timestamp;
}再看下 Producer,重点看下 send方法,kafka支持同步或异步接收消息发送的结果,实现都是靠Future,只是异步的时候future执行了回调方法，支持拦截器方式。
/*** The interface for the {@link KafkaProducer}* @see KafkaProducer* @see MockProducer*/
public interface Producer<K, V> extends Closeable {/*** See {@link KafkaProducer#send(ProducerRecord)}*/Future<RecordMetadata> send(ProducerRecord<K, V> record);/*** See {@link KafkaProducer#send(ProducerRecord, Callback)}*/Future<RecordMetadata> send(ProducerRecord<K, V> record, Callback callback);
}
更详细的看这篇文章说的很好：
https://www.cnblogs.com/dingwpmz/p/12153036.html
简单总结一下：
Producer的send方法并不会直接像broker发送数据，而是计算消息长度是否超限，是否开启事务，如果当前缓存区已写满或创建了一个新的缓存区，则唤醒 Sender(消息发送线程)，将缓存区中的消息发送到 broker 服务器，以队列的形式(每个topic+每个partition维护一个双端队列)，即 ArrayDeque，内部存放的元素为 ProducerBatch，即代表一个批次，即 Kafka 消息发送是按批发送的。
