1、kafka消费者@KafkaListener增加errorHandler属性记录consumer错误,增加properties解决数据获取子系统的消费者发来json数据无法解序列化;
2、配置文件配置consumer反序列化错误处理
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@@ -0,0 +1,33 @@
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package com.realtime.protection.configuration.kafka;
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import lombok.extern.slf4j.Slf4j;
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import org.apache.kafka.clients.consumer.Consumer;
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import org.springframework.kafka.listener.KafkaListenerErrorHandler;
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import org.springframework.kafka.listener.ListenerExecutionFailedException;
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import org.springframework.lang.NonNull;
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import org.springframework.messaging.Message;
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import org.springframework.stereotype.Component;
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@Slf4j
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@Component
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public class MyKafkaListenerErrorHandler implements KafkaListenerErrorHandler {
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@Override
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@NonNull
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public Object handleError(@NonNull Message<?> message, @NonNull ListenerExecutionFailedException exception) {
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return new Object();
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}
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@Override
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@NonNull
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public Object handleError(@NonNull Message<?> message, @NonNull ListenerExecutionFailedException exception, Consumer<?, ?> consumer) {
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log.error("消息详情:" + message);
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log.error("异常信息::" + exception.getCause());
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log.error("消费者详情::" + consumer.groupMetadata());
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log.error("监听主题::" + consumer.listTopics());
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return KafkaListenerErrorHandler.super.handleError(message, exception, consumer);
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}
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}
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@@ -12,7 +12,7 @@ import org.springframework.web.bind.annotation.*;
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public class AlertMessageController
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{
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private final AlertMessageService alertMessageService;
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public AlertMessageController(final AlertMessageService alertMessageService) {
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public AlertMessageController(AlertMessageService alertMessageService) {
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this.alertMessageService = alertMessageService;
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}
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@@ -1,6 +1,7 @@
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package com.realtime.protection.server.alertmessage.kafkaProducer;
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import com.realtime.protection.configuration.entity.alert.AlertMessage;
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import com.realtime.protection.server.alertmessage.AlertMessageService;
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import lombok.extern.slf4j.Slf4j;
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import org.springframework.kafka.annotation.KafkaListener;
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import org.springframework.kafka.support.Acknowledgment;
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@@ -9,15 +10,21 @@ import org.springframework.stereotype.Service;
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@Slf4j
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@Service
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public class KafkaConsumerService {
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@KafkaListener(topics = "${spring.kafka.consumer.topic-name}")
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public void consume(AlertMessage alerm, Acknowledgment ack) {
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try {
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log.info("消费者监听到数据:{}", alerm);
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// 手动提交
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ack.acknowledge();
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} catch (Exception e) {
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throw new RuntimeException("消费失败,数据: " + alerm, e);
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}
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private final AlertMessageService alertMessageService;
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public KafkaConsumerService(AlertMessageService alertMessageService){
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this.alertMessageService = alertMessageService;
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}
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@KafkaListener(id = "${spring.kafka.consumer.group-id}", topics = "${spring.kafka.consumer.topic-name}",
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errorHandler = "myKafkaListenerErrorHandler",
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properties = {"spring.json.value.default.type=com.realtime.protection.configuration.entity.alert.AlertMessage"})
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public void consume(AlertMessage alert, Acknowledgment ack) {
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log.info("消费者监听到数据:{}", alert);
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alertMessageService.processAlertMessage(alert);
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ack.acknowledge();
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// 手动提交
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}
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@@ -49,9 +49,9 @@ spring:
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# none:当各分区都存在已提交的offset时,从提交的offset开始消费;只要有一个分区不存在已提交的offset,则抛出异常
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auto-offset-reset: latest
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# 键的反序列化方式
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key-deserializer: org.springframework.kafka.support.serializer.JsonDeserializer
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key-deserializer: org.springframework.kafka.support.serializer.ErrorHandlingDeserializer
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# 值的反序列化方式(建议使用Json,这种序列化方式可以无需额外配置传输实体类)
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value-deserializer: org.springframework.kafka.support.serializer.JsonDeserializer
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value-deserializer: org.springframework.kafka.support.serializer.ErrorHandlingDeserializer
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# 配置消费者的 Json 反序列化的可信赖包,反序列化实体类需要
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properties:
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spring.json.trusted.packages: com.realtime.protection.configuration.entity.*
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@@ -62,8 +62,11 @@ spring:
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# 要避免出现上述问题,提前评估好处理一条消息最长需要多少时间,然后覆盖默认的max.poll.records参数
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# 注:需要开启BatchListener批量监听才会生效,如果不开启BatchListener则不会出现reBalance情况
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#max-poll-records: 3
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spring.deserializer.key.delegate.class: org.springframework.kafka.support.serializer.JsonDeserializer
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spring.deserializer.value.delegate.class: org.springframework.kafka.support.serializer.JsonDeserializer
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# properties:
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# properties:
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# # 两次poll之间的最大间隔,默认值为5分钟。如果超过这个间隔会触发reBalance
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# max:
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# poll:
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@@ -74,9 +77,6 @@ spring:
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# timeout:
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# ms: 10000
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producer:
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# 重试次数,设置大于0的值,则客户端会将发送失败的记录重新发送
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retries: 3
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