Spring boot 卡夫卡消费者在偏移量提交后无法读取所有消息（错误=偏移量超出范围

我创建了消费者以批量接收消息， 消费者配置：

    allow.auto.create.topics = false
    auto.commit.interval.ms = 5000
    auto.offset.reset = latest
    bootstrap.servers = [localhost:9092]
    check.crcs = true
    client.dns.lookup = default
    client.id =
    client.rack =
    connections.max.idle.ms = 540000
    default.api.timeout.ms = 60000
    enable.auto.commit = false
    exclude.internal.topics = true
    fetch.max.bytes = 52428800
    fetch.max.wait.ms = 500
    fetch.min.bytes = 1
    group.id = cm-persistence-notification
    group.instance.id = null
    heartbeat.interval.ms = 3000
    interceptor.classes = []
    internal.leave.group.on.close = true
    isolation.level = read_uncommitted
    key.deserializer = class org.apache.kafka.common.serialization.StringDeserializer
    max.partition.fetch.bytes = 1048576
    max.poll.interval.ms = 300000
    max.poll.records = 1000
    metadata.max.age.ms = 300000
    metric.reporters = []
    metrics.num.samples = 2
    metrics.recording.level = INFO
    metrics.sample.window.ms = 30000
    partition.assignment.strategy = [class org.apache.kafka.clients.consumer.RangeAssignor]
    receive.buffer.bytes = 65536
    reconnect.backoff.max.ms = 1000
    reconnect.backoff.ms = 50
    request.timeout.ms = 30000
    retry.backoff.ms = 100
    sasl.client.callback.handler.class = null
    sasl.jaas.config = null
    sasl.kerberos.kinit.cmd = /usr/bin/kinit
    sasl.kerberos.min.time.before.relogin = 60000
    sasl.kerberos.service.name = null
    sasl.kerberos.ticket.renew.jitter = 0.05
    sasl.kerberos.ticket.renew.window.factor = 0.8
    sasl.login.callback.handler.class = null
    sasl.login.class = null
    sasl.login.refresh.buffer.seconds = 300
    sasl.login.refresh.min.period.seconds = 60
    sasl.login.refresh.window.factor = 0.8
    sasl.login.refresh.window.jitter = 0.05
    sasl.mechanism = GSSAPI
    security.protocol = PLAINTEXT
    send.buffer.bytes = 131072
    session.timeout.ms = 10000
    ssl.cipher.suites = null
    ssl.enabled.protocols = [TLSv1.2, TLSv1.1, TLSv1]
    ssl.endpoint.identification.algorithm = https
    ssl.key.password = null
    ssl.keymanager.algorithm = SunX509
    ssl.keystore.location = null
    ssl.keystore.password = null
    ssl.keystore.type = JKS
    ssl.protocol = TLS
    ssl.provider = null
    ssl.secure.random.implementation = null
    ssl.trustmanager.algorithm = PKIX
    ssl.truststore.location = null
    ssl.truststore.password = null
    ssl.truststore.type = JKS
    value.deserializer = class org.apache.kafka.common.serialization.StringDeserializer

Spring启动配置：

public KafkaListenerContainerFactory<ConcurrentMessageListenerContainer<String, String>> cmPersistenceListenerContainerFactory(
        KafkaProperties kafkaProperties )
    {
        ConcurrentKafkaListenerContainerFactory<String, String> containerFactory =
            new ConcurrentKafkaListenerContainerFactory<>();

        Map<String, Object> consumerProperties = kafkaProperties.buildConsumerProperties();
        consumerProperties.put( ConsumerConfig.MAX_POLL_RECORDS_CONFIG, "1000" );
        consumerProperties.put( ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG, false );
        consumerProperties.put( ConsumerConfig.ALLOW_AUTO_CREATE_TOPICS_CONFIG, false );

        containerFactory
            .setConsumerFactory(
                new DefaultKafkaConsumerFactory<>(
                    consumerProperties, new StringDeserializer(), new StringDeserializer() ) );
        containerFactory.setBatchListener( true );
       
        containerFactory.getContainerProperties().setCommitLogLevel(LogIfLevelEnabled.Level.INFO);
        
        containerFactory.getContainerProperties().setAckMode( AckMode.MANUAL_IMMEDIATE );
        
        return containerFactory;
    }


    @Bean
    public KafkaAdmin kafkaAdmin( KafkaProperties kafkaProperties )
    {
        return new KafkaAdmin( kafkaProperties.buildAdminProperties() );
    }

public KafkaListenerContainerFactory cmPersistenceListenerContainerFactory(
卡夫卡财产（卡夫卡财产）
{
ConcurrentKafkaListenerContainerFactory容器工厂=
新的ConcurrentKafkaListenerContainerFactory（）；
Map consumerProperties=kafkaProperties.buildConsumerProperties（）；
consumerProperties.put（ConsumerConfig.MAX_POLL_RECORDS_CONFIG，“1000”）；
consumerProperties.put（ConsumerConfig.ENABLE\u AUTO\u COMMIT\u CONFIG，false）；
consumerProperties.put（ConsumerConfig.ALLOW\u AUTO\u CREATE\u TOPICS\u CONFIG，false）；
集装箱厂
.setConsumerFactory(
新卡夫卡消费工厂(
consumerProperties、new StringDeserializer（）、new StringDeserializer（））；
containerFactory.setBatchListener（true）；
containerFactory.getContainerProperties（）.setCommitLogLevel（logifleveEnabled.Level.INFO）；
containerFactory.getContainerProperties（）.setAckMode（AckMode.MANUAL_立即）；
返回集装箱工厂；
}
@豆子
公共卡夫卡德明卡夫卡德明（卡夫卡不动产卡夫卡不动产）
{
返回新的KafkaAdmin（kafkaProperties.buildAdminProperties（））；
}

侦听器类：

@KafkaListener( id = "batch-listener-0", topics = "topic1", groupId = "test", containerFactory = KafkaConsumerConfiguration.CONTAINER_FACTORY_NAME )
    public void receive(
        @Payload List<String> messages,
        @Header( KafkaHeaders.RECEIVED_MESSAGE_KEY ) List<String> keys,
        @Header( KafkaHeaders.RECEIVED_PARTITION_ID ) List<Integer> partitions,
        @Header( KafkaHeaders.RECEIVED_TOPIC ) List<String> topics,
        @Header( KafkaHeaders.OFFSET ) List<Long> offsets,
        Acknowledgment ack )
    {
        long startTime = System.currentTimeMillis();

        handleNotifications( messages ); // will take more than 5s to process all messages

        long endTime = System.currentTimeMillis();

        long timeElapsed = endTime - startTime;

        LOGGER.info( "Execution Time :{}", timeElapsed );

        ack.acknowledge();

        
        LOGGER.info( "Acknowledgment Success" );

    }

@KafkaListener（id=“batch-listener-0”，topics=“topic1”，groupId=“test”，containerFactory=KafkaConsumerConfiguration.CONTAINER\u FACTORY\u NAME）
公共无效接收(
@有效载荷列表消息，
@标题（KafkaHeaders.RECEIVED_MESSAGE_KEY）列表键，
@标题（KafkaHeaders.RECEIVED_PARTITION_ID）列出分区，
@标题（KafkaHeaders.u主题）列出主题，
@标题（KafkaHeaders.OFFSET）列表偏移，
确认（确认）
{
long startTime=System.currentTimeMillis（）；
handleNotifications（messages）；//处理所有邮件需要5秒以上的时间
long-endTime=System.currentTimeMillis（）；
长时间经过=结束时间-开始时间；
info（“执行时间：{}”，timepassed）；
确认（）；
LOGGER.info（“确认成功”）；
}

我在处理消息后使用手动确认

我找到一些调试日志：

在上面的调试日志中，****fetch offset发生在offset commit之前，该offset未提交，因此它返回offset\u OUT\u超出范围，消费者在此之后无法接收任何消息，是否有任何方法在消费者代码中处理此错误，或者如何仅在提交后提取offset***

获得答案：

---

分区日志文件在删除一段时间后仍在删除，但消费者仍在寻找已删除的日志文件，

这是可复制的吗？如果是，您可以共享一个完整的、小的、显示此行为的项目吗？对于循环生产者连续发送消息，计数1000000可以在消费者控制台中接收所有消息，但无法接收in java在consumer中，我需要接收消息并执行db操作，因此这需要一些时间，因此我正在手动提交偏移量。有时能够接收和更新db，这是一个偶发故障生产者代码：consumer code:log。保留期为24小时，因此消息在kafka中可用