我有一个卡夫卡处理器是这样定义的。
import org.apache.kafka.clients.consumer.ConsumerConfig
import org.apache.kafka.common.serialization.StringDeserializer
import org.slf4j.LoggerFactory
import org.springframework.context.annotation.Bean
import org.springframework.stereotype.Component
import reactor.core.publisher.Mono
import reactor.core.scheduler.Schedulers
import reactor.kafka.receiver.KafkaReceiver
import reactor.kafka.receiver.ReceiverOptions
import reactor.kafka.receiver.ReceiverRecord
import reactor.kotlin.core.publisher.toMono
import reactor.util.retry.Retry
import java.time.Duration
import java.util.*
@Component
class KafkaProcessor {
private val logger = LoggerFactory.getLogger(javaClass)
private val consumerProps = hashMapOf(
ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG to StringDeserializer::javaClass,
ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG to StringDeserializer::javaClass,
ConsumerConfig.GROUP_ID_CONFIG to "groupId",
ConsumerConfig.AUTO_OFFSET_RESET_CONFIG to "earliest",
ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG to "localhost:9092"
)
private val receiverOptions = ReceiverOptions.create<String, String>(consumerProps)
.subscription(Collections.singleton("some-topic"))
.commitInterval(Duration.ofSeconds(1))
.commitBatchSize(1000)
.maxCommitAttempts(1)
private val kafkaReceiver: KafkaReceiver<String, String> = KafkaReceiver.create(receiverOptions)
@Bean
fun processKafkaMessages(): Unit {
kafkaReceiver.receive()
.groupBy { m -> m.receiverOffset().topicPartition() }
.flatMap { partitionFlux ->
partitionFlux.publishOn(Schedulers.elastic())
.concatMap { receiverRecord ->
processRecord(receiverRecord)
.map { it.receiverOffset().acknowledge() }
}
}
.retryWhen(
Retry.backoff(3, Duration.ofSeconds(1))
.maxBackoff(Duration.ofSeconds(3))
.doBeforeRetry { rs ->
logger.warn("Retrying: ${rs.totalRetries() + 1}/3 due to ${rs.failure()}")
}
.onRetryExhaustedThrow { _, u ->
logger.error("All ${u.totalRetries() + 1} attempts failed with the last exception: ${u.failure()}")
u.failure()
}
)
.subscribe()
}
private fun processRecord(record: ReceiverRecord<String, String>): Mono<ReceiverRecord<String, String>> {
return record.toMono()
}
}
有时,我会犯这个错误。
org.apache.kafka.clients.consumer.RetriableCommitFailedException: Offset commit failed with a retriable exception. You should retry committing the latest consumed offsets.
Caused by: org.apache.kafka.common.errors.TimeoutException: The request timed out.
第一次重试看起来是这样的。
Retrying: 1/3 due to org.apache.kafka.clients.consumer.RetriableCommitFailedException: Offset commit failed with a retriable exception. You should retry committing the latest consumed offsets
第二个和第三个看起来是这样的。
Retrying: 2/3 due to reactor.core.Exceptions$ReactorRejectedExecutionException: Scheduler unavailable
Retrying: 3/3 due to reactor.core.Exceptions$ReactorRejectedExecutionException: Scheduler unavailable
一旦所有3次重试都用尽了,消息就会如下所示。
All 4 attempts failed with the last exception: reactor.core.Exceptions$ReactorRejectedExecutionException: Scheduler unavailable
当我得到该错误时,我需要重新启动应用程序,以便重新连接到Kafka broker并提交记录。
我知道,将maxCommitAttempts
设置为1
意味着一旦它到达RetriableCommitFailedException
,就不会再重试。我认为,我在retryWhen
函数末尾添加的processKafkaMessages()
子句可以完成这个任务,这样管道就可以自己恢复。
我设置maxCommitAttempts
的原因是因为它没有被讨论过的带有退避的重试,默认的100次最大提交尝试是在10 is内完成的。所以,我认为我应该写我自己的重试逻辑与退却。
问题是,对于自动提交,我应该如何使用退避进行重试?是否可以使用EmbeddedKafka
编写单元测试?
语言:Kotlin
反应堆卡夫卡库:io.projectreactor.kafka:reactor-kafka:1.2.2.RELEASE
发布于 2022-03-16 14:18:16
retryWhen()
只是尝试重新订阅。由于卡夫卡消费者处于错误状态,它将拒绝重新订阅.您需要推迟kafkaReceiver.receive()
调用,因此:
Flux.defer(() -> kafkaReceiver.receive())
.groupBy { m -> m.receiverOffset().topicPartition() }
// etc
因此,重新订阅将再次调用kafkaReceiver.receive()
并创建一个新的使用者。
https://stackoverflow.com/questions/63256984
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