Scala OverflowStrategy类代码示例

//设置package包名称以及导入依赖的类
package websocket

import akka.NotUsed
import akka.actor._
import akka.http.scaladsl.model.ws.{BinaryMessage, Message, TextMessage}
import akka.stream.scaladsl._
import akka.stream.{ActorMaterializer, OverflowStrategy}
import core.entities.AuthTokenContext
import websocket.ClientEndpoint._
import websocket.WebSocketHandler._

import scala.concurrent.ExecutionContext
import scala.concurrent.duration.FiniteDuration

class WebSocketHandler(processingRouter: ActorRef, connectedClientsStore: ActorRef, processingTimeout: FiniteDuration)
                      (implicit system: ActorSystem, mat: ActorMaterializer, apiDispatcher: ExecutionContext) {

  def clientEndpoint(ctx: AuthTokenContext): Flow[Message, Message, NotUsed] = {
    val clientEndpoint =
      system.actorOf(ClientEndpoint.props(ctx, processingRouter, connectedClientsStore, processingTimeout),
                     ClientEndpoint.name(ctx))

    val incomingMessages: Sink[Message, NotUsed] = Flow[Message]
      .map {
        case TextMessage.Strict(jsContent) => Some(IncomingMessage(jsContent))

        case ts: TextMessage.Streamed =>
          ts.textStream.runWith(Sink.ignore)
          None

        case br: BinaryMessage =>
          br.dataStream.runWith(Sink.ignore)
          None
      }
      .collect {
        case Some(message: IncomingMessage) => message
      }
      .to(Sink.actorRef[IncomingMessage](clientEndpoint, PoisonPill))

    val outgoingMessages: Source[Message, NotUsed] = Source
      .actorRef[OutgoingMessage](BUFFER_SIZE, OverflowStrategy.backpressure)
      .mapMaterializedValue { socket =>
        clientEndpoint ! Attach(socket)
        NotUsed
      }
      .map {
        case OutgoingMessage(jsContent) => TextMessage(jsContent)
      }

    Flow.fromSinkAndSource(incomingMessages, outgoingMessages)
  }
}

object WebSocketHandler {
  private val BUFFER_SIZE: Int = 10
} 

//设置package包名称以及导入依赖的类
package com.stulsoft.akka.stream

import akka.NotUsed
import akka.stream.OverflowStrategy
import akka.stream.scaladsl.{Flow, Sink, Source}
import com.typesafe.scalalogging.LazyLogging


object Flows extends App with LazyLogging {
  logger.info("start")

  // Explicitly creating and wiring up a Source, Sink and Flow
  Source(1 to 6).via(Flow[Int].map(_ * 2)).to(Sink.foreach(println(_)))

  // Starting from a Source
  val source = Source(1 to 6).map(_ * 2)
  source.to(Sink.foreach(println(_)))

  // Starting from a Sink
  val sink: Sink[Int, NotUsed] = Flow[Int].map(_ * 2).to(Sink.foreach(println(_)))
  Source(1 to 6).to(sink)

  // Broadcast to a sink inline
  val otherSink: Sink[Int, NotUsed] =
  Flow[Int].alsoTo(Sink.foreach(println(_))).to(Sink.ignore)
  Source(1 to 6).to(otherSink)

  val flowDoublingElements = Flow[Int].map(_ * 2)
  val flowFilteringOutOddElements = Flow[Int].filter(_ % 2 == 0)
  val flowBatchingElements = Flow[Int].grouped(10)
  val flowBufferingElements = Flow[String].buffer(1000, OverflowStrategy.backpressure) // back-pressures the source if the buffer is full
  logger.info("end")
} 

//设置package包名称以及导入依赖的类
package controllers

import javax.inject._

import akka.NotUsed
import akka.actor.{ActorRef, ActorSystem}
import akka.cluster.pubsub.{DistributedPubSub, DistributedPubSubMediator}
import akka.stream.OverflowStrategy
import akka.stream.scaladsl.{Flow, _}
import play.api.mvc._

@Singleton
class Application @Inject() (system: ActorSystem) extends Controller {

  val mediator = DistributedPubSub(system).mediator

  def socket = WebSocket.accept[String, String] { request =>
    new Chat(mediator, "chat").flow
  }
}

class Chat(mediator: ActorRef, topic: String) {

  def flow: Flow[String, String, NotUsed] =
    Flow.fromSinkAndSource(
      publishToMediatorSink,
      sourceFrom)

  private def publishToMediatorSink[In]: Sink[In, NotUsed] =
    Flow[In].map(DistributedPubSubMediator.Publish(topic, _)) to
      Sink.actorRef[DistributedPubSubMediator.Publish](mediator, ())

  private def sourceFrom[Out]: Source[Out, ActorRef] =
    Source
      .actorRef[Out](5, OverflowStrategy.fail)
      .mapMaterializedValue { ref => mediator ! DistributedPubSubMediator.Subscribe(topic, ref); ref }


} 

//设置package包名称以及导入依赖的类
package org.efset

import java.util.Date
import java.util.concurrent.atomic.AtomicInteger

import akka.actor.ActorSystem
import akka.stream.scaladsl.{Flow, Sink, Source}
import akka.stream.{ActorMaterializer, OverflowStrategy}
import org.efset.ContextConfig.writeBatchSize
import org.efset.Model.{ModelDate, ModelThing}
import org.efset.readers.TestSessionCassandraDataReaderComponent
import org.efset.writer.TestSessionSolrDataWriterComponent

import scala.concurrent.ExecutionContext
import scala.concurrent.duration._

object TestSessionExporterSolr {

  def apply(query: String, maybeDateFilter: Option[Date]) = {
    val reader = new TestSessionCassandraDataReaderComponent(query).dataReader
    val writer = new TestSessionSolrDataWriterComponent().dataWriter

    implicit val system = ActorSystem("test-sessions-export")
    implicit val materializer = ActorMaterializer()
    implicit val ec = ExecutionContext.global

    def endDateFilter(thing: ModelThing, endDate: Date): Boolean = {
      val maybeField = thing.fields.find(f => f.name == "create_date")

      maybeField match {
        case Some(ModelDate(_, dt)) => dt.after(endDate)
        case _ => false
      }
    }

    val filter = Flow[ModelThing].filter(t => maybeDateFilter.forall(dt => endDateFilter(t, dt)))

    val source = Source.actorRef[ModelThing](Int.MaxValue, OverflowStrategy.fail)
    val group = Flow[ModelThing].groupedWithin(writeBatchSize, ContextConfig.groupWindow.seconds)
    val commit = Flow[Seq[ModelThing]].map { s => writer.write(s); s }
    val sink = Sink.ignore

    val total = new AtomicInteger()

    val showGroup = Flow[Seq[ModelThing]].map { testSessions =>
      println(s"Processing ${testSessions.size} items. Batch number ${total.incrementAndGet()}")
      testSessions
    }

    val flow = source.via(filter).via(group).via(showGroup).via(commit).to(sink).run()

    reader.read().foreach { thing =>
      flow ! thing
      Thread.sleep(ContextConfig.sleepLength)
    }

    println("Finished...")
  }
} 

//设置package包名称以及导入依赖的类
package org.efset

import java.util.Date
import java.util.concurrent.atomic.AtomicInteger

import akka.actor.ActorSystem
import akka.stream.scaladsl.{Flow, Sink, Source}
import akka.stream.{ActorMaterializer, OverflowStrategy}
import org.efset.ContextConfig.writeBatchSize
import org.efset.Model.{ModelDate, ModelThing}
import org.efset.readers.TestSessionCassandraDataReaderComponent
import org.efset.writer.TestSessionElasticsearchDataWriterComponent

import scala.concurrent.ExecutionContext
import scala.concurrent.duration._

object TestSessionExporter {

  def apply(query: String, maybeDateFilter: Option[Date]) = {
    val reader = new TestSessionCassandraDataReaderComponent(query).dataReader
    val writer = new TestSessionElasticsearchDataWriterComponent().dataWriter

    implicit val system = ActorSystem("test-sessions-export")
    implicit val materializer = ActorMaterializer()
    implicit val ec = ExecutionContext.global

    def endDateFilter(thing: ModelThing, endDate: Date): Boolean = {
      val maybeField = thing.fields.find(f => f.name == "create_date")

      maybeField match {
        case Some(ModelDate(_, dt)) => dt.after(endDate)
        case _ => false
      }
    }

    val filter = Flow[ModelThing].filter(t => maybeDateFilter.forall(dt => endDateFilter(t, dt)))

    val source = Source.actorRef[ModelThing](Int.MaxValue, OverflowStrategy.fail)
    val group = Flow[ModelThing].groupedWithin(writeBatchSize, ContextConfig.groupWindow.seconds)
    val commit = Flow[Seq[ModelThing]].map { s => writer.write(s); s }
    val sink = Sink.ignore

    val total = new AtomicInteger()

    val showGroup = Flow[Seq[ModelThing]].map { testSessions =>
      println(s"Processing ${testSessions.size} items. Batch number ${total.incrementAndGet()}")
      testSessions
    }

    val flow = source.via(filter).via(group).via(showGroup).via(commit).to(sink).run()

    reader.read().foreach { thing =>
      flow ! thing
      Thread.sleep(ContextConfig.sleepLength)
    }

    println("Finished...")
  }
} 

//设置package包名称以及导入依赖的类
package org.efset

import java.util.Date
import java.util.concurrent.atomic.AtomicInteger

import akka.actor.ActorSystem
import akka.stream.scaladsl.{Flow, Sink, Source}
import akka.stream.{ActorMaterializer, OverflowStrategy}
import org.efset.ContextConfig.writeBatchSize
import org.efset.Model.{ModelDate, ModelThing}
import org.efset.readers.TestGroupCassandraDataReaderComponent
import org.efset.writer.TestGroupSolrDataWriterComponent

import scala.concurrent.ExecutionContext
import scala.concurrent.duration._

object TestGroupExporterSolr {

  def apply(query: String, maybeDateFilter: Option[Date]) = {
    val reader = new TestGroupCassandraDataReaderComponent(query).dataReader
    val writer = new TestGroupSolrDataWriterComponent().dataWriter

    implicit val system = ActorSystem("test-groups-export")
    implicit val materializer = ActorMaterializer()
    implicit val ec = ExecutionContext.global

    def endDateFilter(thing: ModelThing, endDate: Date): Boolean = {
      val maybeField = thing.fields.find(f => f.name == "create_date")

      maybeField match {
        case Some(ModelDate(_, dt)) => dt.after(endDate)
        case _ => false
      }
    }

    val filter = Flow[ModelThing].filter(t => maybeDateFilter.forall(dt => endDateFilter(t, dt)))

    val source = Source.actorRef[ModelThing](Int.MaxValue, OverflowStrategy.fail)
    val group = Flow[ModelThing].groupedWithin(writeBatchSize, ContextConfig.groupWindow.seconds)
    val commit = Flow[Seq[ModelThing]].map { s => writer.write(s); s }
    val sink = Sink.ignore

    val total = new AtomicInteger()

    val showGroup = Flow[Seq[ModelThing]].map { testGroups =>
      println(s"Processing ${testGroups.size} items. Batch number ${total.incrementAndGet()}")
      testGroups
    }

    val flow = source.via(filter).via(group).via(showGroup).via(commit).to(sink).run()

    reader.read().foreach { thing =>
      flow ! thing
      Thread.sleep(ContextConfig.sleepLength)
    }

    println("Finished...")
  }
} 

//设置package包名称以及导入依赖的类
package org.efset

import java.util.Date
import java.util.concurrent.atomic.AtomicInteger

import akka.actor.ActorSystem
import akka.stream.scaladsl.{Flow, Sink, Source}
import akka.stream.{ActorMaterializer, OverflowStrategy}
import org.efset.ContextConfig.writeBatchSize
import org.efset.Model.{ModelDate, ModelThing}
import org.efset.readers.TestGroupCassandraDataReaderComponent
import org.efset.writer.TestGroupElasticsearchDataWriterComponent

import scala.concurrent.ExecutionContext
import scala.concurrent.duration._

object TestGroupExporter {

  def apply(query: String, maybeDateFilter: Option[Date]) = {
    val reader = new TestGroupCassandraDataReaderComponent(query).dataReader
    val writer = new TestGroupElasticsearchDataWriterComponent().dataWriter

    implicit val system = ActorSystem("test-groups-export")
    implicit val materializer = ActorMaterializer()
    implicit val ec = ExecutionContext.global

    def endDateFilter(thing: ModelThing, endDate: Date): Boolean = {
      val maybeField = thing.fields.find(f => f.name == "create_date")

      maybeField match {
        case Some(ModelDate(_, dt)) => dt.after(endDate)
        case _ => false
      }
    }

    val filter = Flow[ModelThing].filter(t => maybeDateFilter.forall(dt => endDateFilter(t, dt)))

    val source = Source.actorRef[ModelThing](Int.MaxValue, OverflowStrategy.fail)
    val group = Flow[ModelThing].groupedWithin(writeBatchSize, ContextConfig.groupWindow.seconds)
    val commit = Flow[Seq[ModelThing]].map { s => writer.write(s); s }
    val sink = Sink.ignore

    val total = new AtomicInteger()

    val showGroup = Flow[Seq[ModelThing]].map { testGroups =>
      println(s"Processing ${testGroups.size} items. Batch number ${total.incrementAndGet()}")
      testGroups
    }

    val flow = source.via(filter).via(group).via(showGroup).via(commit).to(sink).run()

    reader.read().foreach { thing =>
      flow ! thing
      Thread.sleep(ContextConfig.sleepLength)
    }

    println("Finished...")
  }
} 

//设置package包名称以及导入依赖的类
package wiii

import akka.actor._
import akka.stream.actor.ActorSubscriber
import akka.stream.scaladsl.{Keep, Sink, Source}
import akka.stream.{ActorMaterializer, Materializer, OverflowStrategy}
import com.softwaremill.react.kafka.{ProducerMessage, ProducerProperties, ReactiveKafka}
import twitter4j.{Status, _}


object KafkaWriter {
    def props(topic: String)(implicit mat: ActorMaterializer) = Props(new KafkaWriter(topic))
}

class KafkaWriter(topicName: String)(implicit mat: Materializer) extends Actor with ActorLogging {
    override def preStart(): Unit = initWriter()
    override def receive: Receive = {
        case _ =>
    }

    def initWriter(): Unit = {
        val subscriberProps = new ReactiveKafka().producerActorProps(ProducerProperties(
            bootstrapServers = "localhost:9092",
            topic = topicName,
            valueSerializer = TweetSerializer
        ))
        val subscriber = context.actorOf(subscriberProps)
        val (actorRef, publisher) = Source.actorRef[Status](1000, OverflowStrategy.fail).toMat(Sink.asPublisher(false))(Keep.both).run()

        val factory = new TwitterStreamFactory()
        val twitterStream = factory.getInstance()
        twitterStream.addListener(new StatusForwarder(actorRef))
        twitterStream.filter(new FilterQuery("espn"))

        Source.fromPublisher(publisher).map(s => ProducerMessage(Tweet(s.getUser.getName, s.getText)))
        .runWith(Sink.fromSubscriber(ActorSubscriber[ProducerMessage[Array[Byte], Tweet]](subscriber)))
    }
}

class StatusForwarder(publisher: ActorRef) extends StatusListener {
    def onStatus(status: Status): Unit = publisher ! status

    //\\ nop all the others for now  //\\
    def onStallWarning(warning: StallWarning): Unit = {}
    def onDeletionNotice(statusDeletionNotice: StatusDeletionNotice): Unit = {}
    def onScrubGeo(userId: Long, upToStatusId: Long): Unit = {}
    def onTrackLimitationNotice(numberOfLimitedStatuses: Int): Unit = {}
    def onException(ex: Exception): Unit = {}
} 

//设置package包名称以及导入依赖的类
package com.omearac.producers

import akka.actor.{ActorRef, ActorSystem}
import akka.kafka.ProducerSettings
import akka.kafka.scaladsl.Producer
import akka.stream.OverflowStrategy
import akka.stream.scaladsl.{Flow, Source}
import com.omearac.shared.JsonMessageConversion.Conversion
import com.omearac.shared.{AkkaStreams, EventSourcing}
import org.apache.kafka.clients.producer.ProducerRecord
import org.apache.kafka.common.serialization.{ByteArraySerializer, StringSerializer}



trait ProducerStream extends AkkaStreams with EventSourcing {
    implicit val system: ActorSystem
    def self: ActorRef

    def createStreamSource[msgType] = {
        Source.queue[msgType](Int.MaxValue,OverflowStrategy.backpressure)
    }

    def createStreamSink(producerProperties: Map[String, String]) = {
        val kafkaMBAddress = producerProperties("bootstrap-servers")
        val producerSettings = ProducerSettings(system, new ByteArraySerializer, new StringSerializer).withBootstrapServers(kafkaMBAddress)

        Producer.plainSink(producerSettings)
    }

    def createStreamFlow[msgType: Conversion](producerProperties: Map[String, String]) = {
        val numberOfPartitions = producerProperties("num.partitions").toInt -1
        val topicToPublish = producerProperties("publish-topic")
        val rand = new scala.util.Random
        val range = 0 to numberOfPartitions

        Flow[msgType].map { msg =>
            val partition = range(rand.nextInt(range.length))
            val stringJSONMessage = Conversion[msgType].convertToJson(msg)
            new ProducerRecord[Array[Byte], String](topicToPublish, partition, null, stringJSONMessage)
        }
    }
} 

//设置package包名称以及导入依赖的类
package im.actor.botkit

import java.net.URLEncoder

import akka.stream.scaladsl.{ Sink, Source }
import akka.stream.{ ActorMaterializer, OverflowStrategy }
import akka.util.Timeout
import im.actor.bots.BotMessages
import im.actor.concurrent.ActorFutures
import upickle.default._

import scala.concurrent.duration._

object RemoteBot {
  val DefaultEndpoint = "wss://api.actor.im"

  private object StreamComplete
}

abstract class RemoteBot(token: String, endpoint: String) extends BotBase with ActorFutures {

  import BotMessages._
  import RemoteBot._

  override protected implicit val timeout: Timeout = Timeout(30.seconds)
  private implicit val mat = ActorMaterializer()

  initFlow()

  def onReceive(message: Object): Unit = {}

  def receive: Receive = internalReceive orElse {
    case message ?
      onReceive(message.asInstanceOf[Object])
  }

  override protected def onStreamFailure(cause: Throwable): Unit = {
    log.error(cause, "Stream failure")
    initFlow()
  }

  private final def internalReceive: Receive = workingBehavior.orElse({
    case StreamComplete ?
      log.warning("Disconnected, reinitiating flow")
      initFlow()
  })

  private def initFlow(): Unit = {
    val (wsSource, wsSink) = WebsocketClient.sourceAndSink(s"$endpoint/v1/bots/${URLEncoder.encode(token, "UTF-8")}")

    wsSource.map(read[BotMessageOut]).to(Sink.actorRef(self, StreamComplete)).run()

    val rqSource = Source.actorRef(bufferSize = 100, overflowStrategy = OverflowStrategy.fail)
      .map(write[BotRequest])
      .to(wsSink)
      .run()

    setRqSource(rqSource)
  }
} 

//设置package包名称以及导入依赖的类
package net.flatmap.vscode.languageserver
import akka.NotUsed
import akka.stream.OverflowStrategy
import akka.stream.scaladsl._
import cats.data.Xor
import io.circe.{Decoder, Json}

trait Configuration[T] extends LanguageServer {
  private var configQueues = Set.empty[SourceQueueWithComplete[Json]]

  def configChanges(implicit decoder: Decoder[T]): Source[T,NotUsed] =
    Source.queue[Json](1024,OverflowStrategy.dropTail).mapMaterializedValue {
      case queue =>
        configQueues += queue
        NotUsed
    }.map(decoder.decodeJson).collect {
      case Xor.Right(t) => t
    }

  override def didChangeConfiguration(settings: Json): Unit = {
    configQueues.foreach(_.offer(settings))
  }
} 

//设置package包名称以及导入依赖的类
package rest.client

import akka.actor.ActorSystem
import akka.http.scaladsl.Http
import akka.http.scaladsl.model.{HttpRequest, HttpResponse}
import akka.stream.scaladsl.{Flow, Keep, Sink, Source}
import akka.stream.{ActorMaterializer, OverflowStrategy, QueueOfferResult}
import rest.client.HttpRequestQueue._

import scala.concurrent.{ExecutionContext, Future, Promise}
import scala.util.{Failure, Success, Try}

trait HttpRequestQueue {

  implicit val system: ActorSystem
  implicit val mat: ActorMaterializer
  implicit val ec: ExecutionContext

  val QueueSize: Int

  val poolClientFlow: Flow[(HttpRequest, Promise[HttpResponse]),
                           (Try[HttpResponse], Promise[HttpResponse]),
                           Http.HostConnectionPool]

  private val queue =
    Source
      .queue[(HttpRequest, Promise[HttpResponse])](QueueSize, OverflowStrategy.backpressure)
      .via(poolClientFlow)
      .toMat(Sink.foreach({
        case ((Success(httpResponse), promisedResponse)) => promisedResponse.success(httpResponse)
        case ((Failure(throwable), promisedResponse))    => promisedResponse.failure(throwable)
      }))(Keep.left)
      .run()

  def queueRequest(request: HttpRequest): Future[HttpResponse] = {
    val responsePromise = Promise[HttpResponse]()
    queue
      .offer(request -> responsePromise)
      .map {
        case QueueOfferResult.Enqueued    => responsePromise
        case QueueOfferResult.Dropped     => responsePromise.failure(new RuntimeException(QUEUE_OVERFLOW))
        case QueueOfferResult.QueueClosed => responsePromise.failure(new RuntimeException(QUEUE_CLOSED))
        case QueueOfferResult.Failure(ex) => responsePromise.failure(ex)
      }
      .flatMap(_.future)
  }
}

object HttpRequestQueue {
  private val QUEUE_OVERFLOW: String = "Queue overflowed. Try again later."
  private val QUEUE_CLOSED: String   = "Queue was closed (pool shut down) while running the request. Try again later."
} 

//设置package包名称以及导入依赖的类
package eu.svez.backpressuredemo.A_local

import akka.NotUsed
import akka.pattern.after
import akka.stream.OverflowStrategy
import akka.stream.scaladsl.{Flow, Sink, Source}
import eu.svez.backpressuredemo.StreamDemo
import kamon.Kamon

import scala.concurrent.Future
import scala.concurrent.duration._

object HelloWorldBackpressured extends StreamDemo {

  sourceRate.send(5)
  sinkRate.send(5)

  def valve[T](rate: => Int): Flow[T, T, NotUsed] =
    Flow[T].mapAsync(1) { x =>
      after(1.second / rate, system.scheduler)(Future.successful(x))
    }

  def meter[T](name: String): Flow[T, T, NotUsed] = {
    val msgCounter = Kamon.metrics.counter(name)

    Flow[T].map { x =>
      msgCounter.increment()
      x
    }
  }

  Source.repeat("Hello world!")
    .via(valve(sourceRate.get))
    .via(meter("source"))

    .buffer(100, OverflowStrategy.backpressure)
    .via(valve(sinkRate.get))
    .via(meter("sink"))
    .runWith(Sink.ignore)



  readRatesFromStdIn()
} 

//设置package包名称以及导入依赖的类
package com.packt.chapter8

import akka.actor.{ActorSystem, Props}
import akka.stream.{ActorMaterializer, OverflowStrategy}
import akka.stream.scaladsl._
import akka.pattern.ask
import akka.util.Timeout
import com.packt.chapter8.SinkActor.{AckSinkActor, CompletedSinkActor, InitSinkActor}

import scala.concurrent.duration._

object IntegratingWithActorsApplication extends App {

  implicit val actorSystem = ActorSystem("IntegratingWithActors")
  implicit val actorMaterializer = ActorMaterializer()

  implicit val askTimeout = Timeout(5 seconds)
  val stringCleaner = actorSystem.actorOf(Props[StringCleanerActor])
  val sinkActor = actorSystem.actorOf(Props[SinkActor])

  val source = Source.queue[String](100, OverflowStrategy.backpressure)
  val sink = Sink.actorRefWithAck[String](sinkActor, InitSinkActor, AckSinkActor, CompletedSinkActor)
  val queue = source
    .mapAsync(parallelism = 5)(elem => (stringCleaner ? elem).mapTo[String])
    .to(sink)
    .run()

  actorSystem.actorOf(SourceActor.props(queue))
} 

//设置package包名称以及导入依赖的类
package dao

import akka.NotUsed
import akka.stream.{Materializer, OverflowStrategy, QueueOfferResult}
import akka.stream.scaladsl.{Flow, Keep, Sink, Source, SourceQueueWithComplete}
import org.reactivestreams.Publisher
import play.api.libs.json.{Format, JsSuccess, Json}

import scala.concurrent.Future

abstract class EventDao[Event](
    implicit val mat: Materializer,
    format: Format[Event]) {

  def store(str: Event): Future[QueueOfferResult] =
    in.offer(str)

  val (
    in: SourceQueueWithComplete[Event],
    out: Publisher[Event]
  ) =
    Source
      .queue[Event](3, OverflowStrategy.backpressure)
      .map(Json.toJson(_))
      .map(Json.stringify)
      .via(eventStore)
      .map(Json.parse)
      .map(Json.fromJson[Event])
      .collect { case JsSuccess(event, _) => event }
      .toMat(Sink.asPublisher(fanout = true))(Keep.both)
      .run()

  protected def eventStore: Flow[String, String, NotUsed]
}