Many resources are needed to download a project. Please understand that we have to compensate our server costs. Thank you in advance. Project price only 1 $
You can buy this project and download/modify it how often you want.
/*
* Copyright (C) 2015-2020 Lightbend Inc.
*/
package akka.stream.scaladsl
import akka.NotUsed
import akka.stream.{ Attributes, Outlet, SourceShape }
import akka.stream.stage.{ GraphStage, OutHandler }
import scala.concurrent.duration.FiniteDuration
/**
* A RestartSource wraps a [[Source]] that gets restarted when it completes or fails.
*
* They are useful for graphs that need to run for longer than the [[Source]] can necessarily guarantee it will, for
* example, for [[Source]] streams that depend on a remote server that may crash or become partitioned. The
* RestartSource ensures that the graph can continue running while the [[Source]] restarts.
*/
object RestartSource {
/**
* Wrap the given [[Source]] with a [[Source]] that will restart it when it fails or complete using an exponential
* backoff.
*
* This [[Source]] will never emit a complete or failure, since the completion or failure of the wrapped [[Source]]
* is always handled by restarting it. The wrapped [[Source]] can however be cancelled by cancelling this [[Source]].
* When that happens, the wrapped [[Source]], if currently running will be cancelled, and it will not be restarted.
* This can be triggered simply by the downstream cancelling, or externally by introducing a [[KillSwitch]] right
* after this [[Source]] in the graph.
*
* This uses the same exponential backoff algorithm as [[akka.pattern.Backoff]].
*
* @param minBackoff minimum (initial) duration until the child actor will
* started again, if it is terminated
* @param maxBackoff the exponential back-off is capped to this duration
* @param randomFactor after calculation of the exponential back-off an additional
* random delay based on this factor is added, e.g. `0.2` adds up to `20%` delay.
* In order to skip this additional delay pass in `0`.
* @param sourceFactory A factory for producing the [[Source]] to wrap.
*/
def withBackoff[T](minBackoff: FiniteDuration, maxBackoff: FiniteDuration, randomFactor: Double)(
sourceFactory: () => Source[T, _]): Source[T, NotUsed] = {
Source.fromGraph(
new RestartWithBackoffSource(
sourceFactory,
minBackoff,
maxBackoff,
randomFactor,
onlyOnFailures = false,
Int.MaxValue))
}
/**
* Wrap the given [[Source]] with a [[Source]] that will restart it when it fails or complete using an exponential
* backoff.
*
* This [[Source]] will not emit a complete or failure as long as maxRestarts is not reached, since the completion
* or failure of the wrapped [[Source]] is handled by restarting it. The wrapped [[Source]] can however be cancelled
* by cancelling this [[Source]]. When that happens, the wrapped [[Source]], if currently running will be cancelled,
* and it will not be restarted.
* This can be triggered simply by the downstream cancelling, or externally by introducing a [[KillSwitch]] right
* after this [[Source]] in the graph.
*
* This uses the same exponential backoff algorithm as [[akka.pattern.Backoff]].
*
* @param minBackoff minimum (initial) duration until the child actor will
* started again, if it is terminated
* @param maxBackoff the exponential back-off is capped to this duration
* @param randomFactor after calculation of the exponential back-off an additional
* random delay based on this factor is added, e.g. `0.2` adds up to `20%` delay.
* In order to skip this additional delay pass in `0`.
* @param maxRestarts the amount of restarts is capped to this amount within a time frame of minBackoff.
* Passing `0` will cause no restarts and a negative number will not cap the amount of restarts.
* @param sourceFactory A factory for producing the [[Source]] to wrap.
*/
def withBackoff[T](minBackoff: FiniteDuration, maxBackoff: FiniteDuration, randomFactor: Double, maxRestarts: Int)(
sourceFactory: () => Source[T, _]): Source[T, NotUsed] = {
Source.fromGraph(
new RestartWithBackoffSource(
sourceFactory,
minBackoff,
maxBackoff,
randomFactor,
onlyOnFailures = false,
maxRestarts))
}
/**
* Wrap the given [[Source]] with a [[Source]] that will restart it when it fails using an exponential backoff.
*
* This [[Source]] will never emit a failure, since the failure of the wrapped [[Source]] is always handled by
* restarting. The wrapped [[Source]] can be cancelled by cancelling this [[Source]].
* When that happens, the wrapped [[Source]], if currently running will be cancelled, and it will not be restarted.
* This can be triggered simply by the downstream cancelling, or externally by introducing a [[KillSwitch]] right
* after this [[Source]] in the graph.
*
* This uses the same exponential backoff algorithm as [[akka.pattern.Backoff]].
*
* @param minBackoff minimum (initial) duration until the child actor will
* started again, if it is terminated
* @param maxBackoff the exponential back-off is capped to this duration
* @param randomFactor after calculation of the exponential back-off an additional
* random delay based on this factor is added, e.g. `0.2` adds up to `20%` delay.
* In order to skip this additional delay pass in `0`.
* @param sourceFactory A factory for producing the [[Source]] to wrap.
*
*/
def onFailuresWithBackoff[T](minBackoff: FiniteDuration, maxBackoff: FiniteDuration, randomFactor: Double)(
sourceFactory: () => Source[T, _]): Source[T, NotUsed] = {
Source.fromGraph(
new RestartWithBackoffSource(
sourceFactory,
minBackoff,
maxBackoff,
randomFactor,
onlyOnFailures = true,
Int.MaxValue))
}
/**
* Wrap the given [[Source]] with a [[Source]] that will restart it when it fails using an exponential backoff.
*
* This [[Source]] will not emit a complete or failure as long as maxRestarts is not reached, since the completion
* or failure of the wrapped [[Source]] is handled by restarting it. The wrapped [[Source]] can however be cancelled
* by cancelling this [[Source]]. When that happens, the wrapped [[Source]], if currently running will be cancelled,
* and it will not be restarted.
* This can be triggered simply by the downstream cancelling, or externally by introducing a [[KillSwitch]] right
* after this [[Source]] in the graph.
*
* This uses the same exponential backoff algorithm as [[akka.pattern.Backoff]].
*
* @param minBackoff minimum (initial) duration until the child actor will
* started again, if it is terminated
* @param maxBackoff the exponential back-off is capped to this duration
* @param randomFactor after calculation of the exponential back-off an additional
* random delay based on this factor is added, e.g. `0.2` adds up to `20%` delay.
* In order to skip this additional delay pass in `0`.
* @param maxRestarts the amount of restarts is capped to this amount within a time frame of minBackoff.
* Passing `0` will cause no restarts and a negative number will not cap the amount of restarts.
* @param sourceFactory A factory for producing the [[Source]] to wrap.
*
*/
def onFailuresWithBackoff[T](
minBackoff: FiniteDuration,
maxBackoff: FiniteDuration,
randomFactor: Double,
maxRestarts: Int)(sourceFactory: () => Source[T, _]): Source[T, NotUsed] = {
Source.fromGraph(
new RestartWithBackoffSource(
sourceFactory,
minBackoff,
maxBackoff,
randomFactor,
onlyOnFailures = true,
maxRestarts))
}
}
private final class RestartWithBackoffSource[T](
sourceFactory: () => Source[T, _],
minBackoff: FiniteDuration,
maxBackoff: FiniteDuration,
randomFactor: Double,
onlyOnFailures: Boolean,
maxRestarts: Int)
extends GraphStage[SourceShape[T]] { self =>
val out = Outlet[T]("RestartWithBackoffSource.out")
override def shape = SourceShape(out)
override def createLogic(inheritedAttributes: Attributes) =
new RestartWithBackoffLogic(
"Source",
shape,
inheritedAttributes,
minBackoff,
maxBackoff,
randomFactor,
onlyOnFailures,
maxRestarts) {
override protected def logSource = self.getClass
override protected def startGraph() = {
val sinkIn = createSubInlet(out)
sourceFactory().runWith(sinkIn.sink)(subFusingMaterializer)
if (isAvailable(out)) {
sinkIn.pull()
}
}
override protected def backoff() = {
setHandler(out, new OutHandler {
override def onPull() = ()
})
}
backoff()
}
}
