线上问题-kafka生产者发送消息总是失败

爱被打了一巴掌 2022-09-08 13:57 395阅读 0赞

# 问题解决过程 #

线上一个界面发现老是没有数据，排查下来时生产者没有成功发送消息所致，报错如下：

org.springframework.kafka.core.KafkaProducerException: Failed to send; nested exception is org.apache.kafka.common.errors.TimeoutException: Failed to update metadata after 0 ms.

我们发现配置里有一个很奇怪的参数

config.put(ProducerConfig.MAX_BLOCK_MS_CONFIG, 0);

我们找到相关源码：

private Future<RecordMetadata> doSend(ProducerRecord<K, V> record, Callback callback) {
            TopicPartition tp = null;
            try {
                throwIfProducerClosed();
                // first make sure the metadata for the topic is available
                ClusterAndWaitTime clusterAndWaitTime;
                try {
                // -------------------------maxBlockTimeMs最终会传入ProducerConfig.MAX_BLOCK_MS_CONFIG对应值0
                    clusterAndWaitTime = waitOnMetadata(record.topic(), record.partition(), maxBlockTimeMs);
            .......  
    
    private ClusterAndWaitTime waitOnMetadata(String topic, Integer partition, long maxWaitMs) throws InterruptedException {
           ....
            do {
                log.trace("Requesting metadata update for topic {}.", topic);
                metadata.add(topic);
                int version = metadata.requestUpdate();
                sender.wakeup();
                try {
                    metadata.awaitUpdate(version, remainingWaitMs);
                } catch (TimeoutException ex) {
                // ------------------主要是在这里报错了------------
                    // Rethrow with original maxWaitMs to prevent logging exception with remainingWaitMs
                    throw new TimeoutException("Failed to update metadata after " + maxWaitMs + " ms.");
                }
                ....

我们找到max.block.ms的作用

public static final String MAX_BLOCK_MS_CONFIG = "max.block.ms";
        private static final String MAX_BLOCK_MS_DOC = "The configuration controls how long <code>KafkaProducer.send()</code> and <code>KafkaProducer.partitionsFor()</code> will block."
                                                        + "These methods can be blocked either because the buffer is full or metadata unavailable."
                                                        + "Blocking in the user-supplied serializers or partitioner will not be counted against this timeout.";

问题很清晰了, send时发现要更新metadata，更新metadata时0ms超时报错了！

故把该值改为1000即可

config.put(ProducerConfig.MAX_BLOCK_MS_CONFIG, 1000);

# 深入思考这个问题 #

这个功能是由界面点击时触发的，但运营人员很少会去使用这个功能，故猜测太长时间没用，比如超过9分钟（connections.max.idle.ms), 导致连接关闭，下次send时需要重新拉取metadata导致，但实际是这样的吗？no

我们把connections.max.idle.ms=1000，期待1s后send失败，但实际上还是需要空闲好几分钟后send才会失败，说明connections.max.idle.ms这个参数不是报错的直接原因！

通过DEBUG日志, 我们发现超时连接断开时，会触发metadata的更新；当metadata.max.age.ms超时时也会触发metadate更新。我们再深入研究下去

调试时发现抛出报错的日志前面，有如下所示日志

[2021-08-25 22:28:15,039] [kafka-producer-network-thread | producer-1] [DEBUG] org.apache.kafka.clients.Metadata - Removing unused topic InnerProcess from the metadata list, expiryMs 1629901694499 now 1629901695039

这句话是在下面这个地方打印的

org.apache.kafka.clients.Metadata#update
    
    public static final long TOPIC_EXPIRY_MS = 5 * 60 * 1000;
    
    public synchronized void update(Cluster newCluster, Set<String> unavailableTopics, long now) {
           ....
    
    // producer默认为true，consumer默认为false
            if (topicExpiryEnabled) {
                // Handle expiry of topics from the metadata refresh set.
                for (Iterator<Map.Entry<String, Long>> it = topics.entrySet().iterator(); it.hasNext(); ) {
                    Map.Entry<String, Long> entry = it.next();
                    long expireMs = entry.getValue();
                    // 第一次需要立即更新为-1
                    if (expireMs == TOPIC_EXPIRY_NEEDS_UPDATE)
                    // 第一次设置了5分钟后失效
                        entry.setValue(now + TOPIC_EXPIRY_MS);
                    else if (expireMs <= now) {
                    // 达到失效时间后，topic就会删除，下次send需要重新更新metadata了
                        it.remove();
                        log.debug("Removing unused topic {} from the metadata list, expiryMs {} now {}", entry.getKey(), expireMs, now);
                    }
                }
            }
            .....

我们可以看到topic其实是设置了失效时间的，默认5分钟，当第一次调用send()，失效时间为-1，并且会触发更新metadata，即会修改为entry.setValue(now + TOPIC\_EXPIRY\_MS)，5分钟后失效，但5分钟后不会立即失效，若等到9分钟连接断开时，会走到上面的代码：

if (expireMs <= now) {
                    // 达到失效时间后，topic就会删除，下次send需要重新更新metadata了
                        it.remove();
                        log.debug("Removing unused topic {} from the metadata list, expiryMs {} now {}", entry.getKey(), expireMs, now);
                    }

即会将topic移除了，故9分钟后再次send时，需要更新metadata，但max.block.ms=0导致超时报错，即发送失败！

我们可以做这样的试验, 修改下面2个参数

// 在topic失效之前停掉
            config.put(ProducerConfig.CONNECTIONS_MAX_IDLE_MS_CONFIG, 4 * 60 * 1000);
            // 10小时才更新一次metadata
            config.put(ProducerConfig.METADATA_MAX_AGE_CONFIG, 10 * 60 * 60 * 1000);

然后每大于5分钟的时间间隔，send一次

@Scheduled(fixedDelay = 9 * 60 * 1000 + 10000)
        public void sendKafkaASync() {
            kafkaService.sendKafkaASync();
        }

发现除了第一次失败后，就不会失败了！！！

因此，试验下来，是由于max.block.ms设置过小，导致更新metadata超时，导致send失败；更深入的：  
1）首次发送没有topic数据，send调用时需要首先更新metadata时间不够，导致超时；  
2）后面发送失败，是因为topic已超时，并在之后，connections.max.idle.ms或metadata.max.age.ms到时间触发metadata更新，而把超时的topic移除了。topic移除后，再进行send，有需要先更新metadata，进而还是会失败；

总体上而言，send的间隔不要超过5分钟最好，超过5分钟不调用send, 存在一定的可能导致topic被移除，从而下次send需要重新拉去metadata

# 附录：相关代码 #

### pom.xml ###

<parent>
            <artifactId>spring-boot-starter-parent</artifactId>
            <groupId>org.springframework.boot</groupId>
            <version>2.1.5.RELEASE</version>
        </parent>
    
        <dependencies>
            <dependency>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-starter-web</artifactId>
                <exclusions>
                    
                    <exclusion>
                        <groupId>org.springframework.boot</groupId>
                        <artifactId>spring-boot-starter-logging</artifactId>
                    </exclusion>
                </exclusions>
            </dependency>
            <dependency>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-starter-log4j2</artifactId>
            </dependency>
            <dependency>
                <groupId>org.springframework.kafka</groupId>
                <artifactId>spring-kafka</artifactId>
                <version>2.2.5.RELEASE</version>
            </dependency>
            <dependency>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-starter-test</artifactId>
            </dependency>
    
            <dependency>
                <groupId>org.projectlombok</groupId>
                <artifactId>lombok</artifactId>
                <version>1.18.12</version>
            </dependency>
    
        </dependencies>

### log4j2.xml ###

<?xml version="1.0" encoding="UTF-8"?>
    
    
    <Configuration status="DEBUG" monitorInterval="5">
            .....
    
        <Loggers>
            <Logger name="org.springframework" level="INFO" />
            <Logger name="com.ydfind" level="DEBUG" />
            <Logger name="org.apache.kafka.clients.consumer" level="WARN"/>
            <Logger name="org.apache.kafka.clients.FetchSessionHandler" level="WARN" />
            <Logger name="org.apache.kafka.clients.producer.KafkaProducer" level="TRACE" />
        </Loggers>
    </Configuration>

### application.yml ###

logging:
      config: classpath:log4j2.xml

### KafkaConfig.java ###

package com.ydfind.config;
    
    import org.apache.kafka.clients.CommonClientConfigs;
    import org.apache.kafka.clients.consumer.ConsumerConfig;
    import org.apache.kafka.clients.producer.ProducerConfig;
    import org.apache.kafka.common.config.SaslConfigs;
    import org.apache.kafka.common.security.auth.SecurityProtocol;
    import org.apache.kafka.common.security.scram.ScramLoginModule;
    import org.apache.kafka.common.serialization.StringDeserializer;
    import org.apache.kafka.common.serialization.StringSerializer;
    import org.springframework.context.annotation.Bean;
    import org.springframework.context.annotation.Configuration;
    import org.springframework.kafka.annotation.EnableKafka;
    import org.springframework.kafka.config.ConcurrentKafkaListenerContainerFactory;
    import org.springframework.kafka.config.KafkaListenerContainerFactory;
    import org.springframework.kafka.core.DefaultKafkaConsumerFactory;
    import org.springframework.kafka.core.DefaultKafkaProducerFactory;
    import org.springframework.kafka.core.KafkaTemplate;
    import org.springframework.kafka.core.ProducerFactory;
    import org.springframework.kafka.listener.ConcurrentMessageListenerContainer;
    import org.springframework.web.context.request.FacesRequestAttributes;
    
    import java.awt.datatransfer.StringSelection;
    import java.util.HashMap;
    import java.util.Map;
    
    @Configuration
    @EnableKafka
    public class KafkaConfig {
    
        @Bean
        public KafkaTemplate<String, String> kafkaTemplate() {
            return new KafkaTemplate<>(producerFactory());
        }
    
        private ProducerFactory<String, String> producerFactory() {
            return new DefaultKafkaProducerFactory<>(producerConfigs());
        }
    
        private Map<String, Object> producerConfigs() {
            Map<String, Object> config = new HashMap<>();
            config.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092");
            config.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
            config.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
    //
    //        config.put(CommonClientConfigs.SECURITY_PROTOCOL_CONFIG, SecurityProtocol.SASL_PLAINTEXT.name);
    //        config.put(SaslConfigs.SASL_JAAS_CONFIG, "org.apache.kafka.common.security.scram.ScramLoginModule required username=\"xxx\" password=\"xxx\"");
    //        config.put(SaslConfigs.SASL_MECHANISM, "SCRAM-SHA-256");
    
            config.put(ProducerConfig.MAX_BLOCK_MS_CONFIG, 0);
    //        config.put(ProducerConfig.CONNECTIONS_MAX_IDLE_MS_CONFIG, 1 * 60 * 1000);
    //        config.put(ProducerConfig.METADATA_MAX_AGE_CONFIG, 30 * 60 * 1000);
    
    //        config.put(ProducerConfig.CONNECTIONS_MAX_IDLE_MS_CONFIG, 100 * 60 * 1000);
    //        config.put(ProducerConfig.METADATA_MAX_AGE_CONFIG, 1 * 60 * 1000);
    
    
            // ----貌似下面会10小时内都成功！！！！---------------------------
            // 4min时connect断掉，5min时topic失效，6min时send()成功，10min时把topic失效时间弄从15min！！！！！
            // 是send()导致entry.getValue() == TOPIC_EXPIRY_NEEDS_UPDATE，还是connect断开的更新topic导致呢！！！
            // topics.put(topic, TOPIC_EXPIRY_NEEDS_UPDATE)-------------send时会把topic的失效时间弄成-1----相当于续命，不会失效
    
            // 在topic失效之前停掉
            config.put(ProducerConfig.CONNECTIONS_MAX_IDLE_MS_CONFIG, 4 * 60 * 1000);
            // 10小时才更新一次metadata
            config.put(ProducerConfig.METADATA_MAX_AGE_CONFIG, 10 * 60 * 60 * 1000);
            return config;
        }
    }

### KafkaService ###

package com.ydfind.service;
    
    import lombok.extern.slf4j.Slf4j;
    import org.springframework.beans.factory.annotation.Autowired;
    import org.springframework.kafka.core.KafkaTemplate;
    import org.springframework.kafka.support.SendResult;
    import org.springframework.stereotype.Component;
    import org.springframework.util.concurrent.ListenableFuture;
    
    import java.util.concurrent.ExecutionException;
    import java.util.concurrent.atomic.AtomicInteger;
    
    @Component
    @Slf4j
    public class KafkaService {
    
        @Autowired
        private KafkaTemplate<String, String> kafkaTemplate;
    
        public String sendKafkaSync() {
            ListenableFuture<SendResult<String, String>> send = kafkaTemplate.send("InnerProcess", "sendKafkaSync");
            String msg = "";
            try {
                SendResult<String, String> stringStringSendResult = send.get();
                msg += stringStringSendResult.getRecordMetadata().offset();
            } catch (InterruptedException e) {
                e.printStackTrace();
                return e.getMessage();
            } catch (ExecutionException e) {
                e.printStackTrace();
                return e.getMessage();
            }
            return msg;
        }
    
        private AtomicInteger total = new AtomicInteger();
        private AtomicInteger success = new AtomicInteger();
    
        public void sendKafkaASync() {
            ListenableFuture<SendResult<String, String>> send = kafkaTemplate.send("InnerProcess", "sendKafkaSync");
            send.completable().whenCompleteAsync((n, e) -> {
                total.getAndIncrement();
                if (null != e) {
                    e.printStackTrace();
                } else {
                    success.getAndIncrement();
                }
                log.info("\n-------------------total = {}, success = {}", total.get(), success.get());
            });
        }
    }

### MainApp.java ###

package com.ydfind;
    
    
    import com.ydfind.service.KafkaService;
    import org.springframework.beans.factory.annotation.Autowired;
    import org.springframework.boot.SpringApplication;
    import org.springframework.boot.autoconfigure.SpringBootApplication;
    import org.springframework.scheduling.annotation.EnableScheduling;
    import org.springframework.scheduling.annotation.Scheduled;
    import org.springframework.web.bind.annotation.GetMapping;
    import org.springframework.web.bind.annotation.RestController;
    
    @SpringBootApplication
    @RestController
    @EnableScheduling
    public class MainApp {
    
        public static void main(String[] args) {
            SpringApplication.run(MainApp.class, args);
        }
    
        @Autowired
        private KafkaService kafkaService;
    
        @GetMapping("sendKafka")
        public String sendKafka() {
            return kafkaService.sendKafkaSync();
        }
    
        @Scheduled(fixedDelay = 9 * 60 * 1000 + 10000)
        public void sendKafkaASync() {
            kafkaService.sendKafkaASync();
        }
    }