文章目录
1、kafka数据传递语义
kafka发送消息时是否需要重试
仅发送一次:生产者发送消息后不重试,只发送一次 可能丢失消息 效率最高
至少一次:生产者发送消息后重试,可能重试多次 效率差
精准一次发送:生产者发送消息后无论是否重复发送 发送了多少次,在 kafka broker 中只保存一次消息,通过幂等性 + 生产者事务来实现
kafak天然支持幂等性,每个消息头中带了一个唯一的标志 kafka broker 根据此标志判断消息是否已经发送过,生产者事务可以保证数据没有最终发送成功时,消费者不可以消费,如果生产者发送消息时出现异常会自动回滚(清除之前发送的事务中的消息)
kafka天然幂等性:但是指的是生产者事务 生产消息时的幂等性,发送消息时消息中带唯一标识、broker接收到消息时如果重复不再保存,事务没提交消费者不能消费改消息
2、kafka生产者事务
一组消息要么一起成功 被消费者消息 要么一起失败都不能被消费者消费
配置ack为-1 分区所有副本均落盘成功
配置生产者重试(发送失败可以继续发送:需要保证发送失败后再次发送消息到kafka实现 精准一次发送)
需要给事务分配事务id(区分一个事务中的多条消息)
3、事务消息发送
3.1、application.yml配置
yml
复制代码
server:
port: 8110
# v1
spring:
kafka:
bootstrap-servers: 192.168.74.148:9095,192.168.74.148:9096,192.168.74.148:9097
producer: # producer 生产者
retries: 1 # 重试次数 0表示不重试
acks: -1 # 应答级别:多少个分区副本备份完成时向生产者发送ack确认(可选0、1、-1/all)
transaction-id-prefix: tx_ # 事务id前缀:配置后producer自动开启事务
batch-size: 16384 # 批次大小 单位byte
buffer-memory: 33554432 # 生产者缓冲区大小 单位byte
key-serializer: org.apache.kafka.common.serialization.StringSerializer # key的序列化器
value-serializer: org.apache.kafka.common.serialization.StringSerializer # value的序列化器
3.2、创建生产者监听器
java
复制代码
package com.atguigu.kafka.listener;
import org.apache.kafka.clients.producer.ProducerRecord;
import org.apache.kafka.clients.producer.RecordMetadata;
import org.springframework.kafka.support.ProducerListener;
@Component
public class MyKafkaProducerListener implements ProducerListener<String,String> {
//生产者 ack 配置为 0 只要发送即成功
//ack为 1 leader落盘 broker ack之后 才成功
//ack为 -1 分区所有副本全部落盘 broker ack之后 才成功
@Override
public void onSuccess(ProducerRecord<String, String> producerRecord, RecordMetadata recordMetadata) {
//ProducerListener.super.onSuccess(producerRecord, recordMetadata);
System.out.println("MyKafkaProducerListener消息发送成功:"+"topic="+producerRecord.topic()
+",partition = "+producerRecord.partition()
+",key = "+producerRecord.key()
+",value = "+producerRecord.value()
+",offset = "+recordMetadata.offset());
}
//消息发送失败的回调:监听器可以接收到发送失败的消息 可以记录失败的消息
@Override
public void onError(ProducerRecord<String, String> producerRecord, RecordMetadata recordMetadata, Exception exception) {
System.out.println("MyKafkaProducerListener消息发送失败:"+"topic="+producerRecord.topic()
+",partition = "+producerRecord.partition()
+",key = "+producerRecord.key()
+",value = "+producerRecord.value()
+",offset = "+recordMetadata.offset());
System.out.println("异常信息:" + exception.getMessage());
}
}
3.3、创建生产者拦截器
java
复制代码
package com.atguigu.kafka.interceptor;
import org.apache.kafka.clients.producer.ProducerInterceptor;
import org.apache.kafka.clients.producer.ProducerRecord;
import org.apache.kafka.clients.producer.RecordMetadata;
import org.springframework.stereotype.Component;
import java.util.Map;
//拦截器必须手动注册给kafka生产者(KafkaTemplate)
@Component
public class MyKafkaInterceptor implements ProducerInterceptor<String,String> {
//kafka生产者发送消息前执行:拦截发送的消息预处理
@Override
public ProducerRecord<String, String> onSend(ProducerRecord<String, String> producerRecord) {
System.out.println("生产者即将发送消息:topic = "+ producerRecord.topic()
+",partition:"+producerRecord.partition()
+",key = "+producerRecord.key()
+",value = "+producerRecord.value());
return null;
}
//kafka broker 给出应答后执行
@Override
public void onAcknowledgement(RecordMetadata recordMetadata, Exception e) {
//exception为空表示消息发送成功
if(e == null){
System.out.println("消息发送成功:topic = "+ recordMetadata.topic()
+",partition:"+recordMetadata.partition()
+",offset="+recordMetadata.offset()
+",timestamp="+recordMetadata.timestamp());
}
}
@Override
public void close() {
}
@Override
public void configure(Map<String, ?> map) {
}
}
3.4、发送消息测试
java
复制代码
package com.atguigu.kafka.producer;
import com.atguigu.kafka.interceptor.MyKafkaInterceptor;
import jakarta.annotation.PostConstruct;
import jakarta.annotation.Resource;
import org.junit.jupiter.api.Test;
import org.springframework.boot.test.context.SpringBootTest;
import org.springframework.kafka.core.KafkaTemplate;
import java.io.IOException;
@SpringBootTest
class KafkaProducerApplicationTests {
//装配kafka模板类: springboot启动时会自动根据配置文初始化kafka模板类对象注入到容器中
@Resource
KafkaTemplate kafkaTemplate;
@Resource
MyKafkaInterceptor myKafkaInterceptor;
@PostConstruct
public void init() {
kafkaTemplate.setProducerInterceptor(myKafkaInterceptor);
}
@Test
void contextLoads() throws IOException {
kafkaTemplate.send("my_topic1", "spring-kafka-生产者监听器");
//回调是等kafka,ack以后才执行,需要阻塞
System.in.read();
}
//kafka事务支持spring-tx的事务注解
//单元测试中的事务会自动回滚
@Test
void testTransaction() throws IOException {
//多个消息的发送在一个事务中执行
kafkaTemplate.executeInTransaction((var1) -> {
//通过一个事务中的operations对象来发送消息,执行事务操作
var1.send("my_topic1",0,"", "spring-kafka-事务1");
var1.send("my_topic1",0,"", "spring-kafka-事务2");
int i = 1/0;
var1.send("my_topic1",0,"", "spring-kafka-事务3");
return "发送消息失败";
});
System.in.read();
}
}
3.5、使用Java代码创建主题分区副本
java
复制代码
package com.atguigu.kafka.config;
import org.apache.kafka.clients.admin.NewTopic;
import org.springframework.context.annotation.Bean;
import org.springframework.kafka.config.TopicBuilder;
import org.springframework.stereotype.Component;
@Component
public class KafkaTopicConfig {
@Bean
public NewTopic myTopic1() {
//相同名称的主题 只会创建一次,后面创建的主题名称相同配置不同可以做增量更新(分区、副本数)
return TopicBuilder.name("my_topic1")//主题名称
.partitions(3)//主题分区
.replicas(3)//主题分区副本数
.build();//创建
}
}
3.6、屏蔽 kafka debug 日志 logback.xml
xml
复制代码
<configuration>
<!-- 如果觉得idea控制台日志太多,src\main\resources目录下新建logback.xml
屏蔽kafka debug -->
<logger name="org.apache.kafka.clients" level="debug" />
</configuration>
3.7、引入spring-kafka依赖
xml
复制代码
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 https://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<parent>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-parent</artifactId>
<version>3.0.5</version>
<relativePath/> <!-- lookup parent from repository -->
</parent>
<!-- Generated by https://start.springboot.io -->
<!-- 优质的 spring/boot/data/security/cloud 框架中文文档尽在 => https://springdoc.cn -->
<groupId>com.atguigu.kafka</groupId>
<artifactId>kafka-producer</artifactId>
<version>0.0.1-SNAPSHOT</version>
<name>kafka-producer</name>
<description>kafka-producer</description>
<properties>
<java.version>17</java.version>
</properties>
<dependencies>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-test</artifactId>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.springframework.kafka</groupId>
<artifactId>spring-kafka</artifactId>
</dependency>
</dependencies>
<build>
<plugins>
<plugin>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-maven-plugin</artifactId>
</plugin>
</plugins>
</build>
</project>
3.8、控制台日志
clike
复制代码
生产者即将发送消息:topic = my_topic1,partition:0,key = ,value = spring-kafka-事务1
生产者即将发送消息:topic = my_topic1,partition:0,key = ,value = spring-kafka-事务2
MyKafkaProducerListener消息发送失败:topic=my_topic1,partition = 0,key = ,value = spring-kafka-事务1,offset = -1
异常信息:Failing batch since transaction was aborted
MyKafkaProducerListener消息发送失败:topic=my_topic1,partition = 0,key = ,value = spring-kafka-事务2,offset = -1
异常信息:Failing batch since transaction was aborted
java.lang.ArithmeticException: / by zero