akka.pattern.BackoffOptions.scala Maven / Gradle / Ivy
/*
* Copyright (C) 2015-2019 Lightbend Inc.
*/
package akka.pattern
import akka.actor.{ OneForOneStrategy, Props, SupervisorStrategy }
import akka.annotation.DoNotInherit
import akka.pattern.internal.{ BackoffOnRestartSupervisor, BackoffOnStopSupervisor }
import akka.util.JavaDurationConverters._
import scala.concurrent.duration.{ Duration, FiniteDuration }
/**
* Backoff options allow to specify a number of properties for backoff supervisors.
*/
object BackoffOpts {
/**
* Back-off options for creating a back-off supervisor actor that expects a child actor to restart on failure.
*
* This explicit supervisor behaves similarly to the normal implicit supervision where
* if an actor throws an exception, the decider on the supervisor will decide when to
* `Stop`, `Restart`, `Escalate`, `Resume` the child actor.
*
* When the `Restart` directive is specified, the supervisor will delay the restart
* using an exponential back off strategy (bounded by minBackoff and maxBackoff).
*
* This supervisor is intended to be transparent to both the child actor and external actors.
* Where external actors can send messages to the supervisor as if it was the child and the
* messages will be forwarded. And when the child is `Terminated`, the supervisor is also
* `Terminated`.
* Transparent to the child means that the child does not have to be aware that it is being
* supervised specifically by this actor. Just like it does
* not need to know when it is being supervised by the usual implicit supervisors.
* The only caveat is that the `ActorRef` of the child is not stable, so any user storing the
* `sender()` `ActorRef` from the child response may eventually not be able to communicate with
* the stored `ActorRef`. In general all messages to the child should be directed through this actor.
*
* An example of where this supervisor might be used is when you may have an actor that is
* responsible for continuously polling on a server for some resource that sometimes may be down.
* Instead of hammering the server continuously when the resource is unavailable, the actor will
* be restarted with an exponentially increasing back off until the resource is available again.
*
* '''***
* This supervisor should not be used with `Akka Persistence` child actors.
* `Akka Persistence` actors shutdown unconditionally on `persistFailure()`s rather
* than throw an exception on a failure like normal actors.
* [[#onStop]] should be used instead for cases where the child actor
* terminates itself as a failure signal instead of the normal behavior of throwing an exception.
* ***'''
* You can define another
* supervision strategy by using `akka.pattern.BackoffOptions.withSupervisorStrategy` on [[akka.pattern.BackoffOnFailureOptions]].
*
* @param childProps the [[akka.actor.Props]] of the child actor that
* will be started and supervised
* @param childName name of the child actor
* @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`.
*/
def onFailure(
childProps: Props,
childName: String,
minBackoff: FiniteDuration,
maxBackoff: FiniteDuration,
randomFactor: Double): BackoffOnFailureOptions =
BackoffOnFailureOptionsImpl(childProps, childName, minBackoff, maxBackoff, randomFactor)
/**
* Java API: Back-off options for creating a back-off supervisor actor that expects a child actor to restart on failure.
*
* This explicit supervisor behaves similarly to the normal implicit supervision where
* if an actor throws an exception, the decider on the supervisor will decide when to
* `Stop`, `Restart`, `Escalate`, `Resume` the child actor.
*
* When the `Restart` directive is specified, the supervisor will delay the restart
* using an exponential back off strategy (bounded by minBackoff and maxBackoff).
*
* This supervisor is intended to be transparent to both the child actor and external actors.
* Where external actors can send messages to the supervisor as if it was the child and the
* messages will be forwarded. And when the child is `Terminated`, the supervisor is also
* `Terminated`.
* Transparent to the child means that the child does not have to be aware that it is being
* supervised specifically by this actor. Just like it does
* not need to know when it is being supervised by the usual implicit supervisors.
* The only caveat is that the `ActorRef` of the child is not stable, so any user storing the
* `sender()` `ActorRef` from the child response may eventually not be able to communicate with
* the stored `ActorRef`. In general all messages to the child should be directed through this actor.
*
* An example of where this supervisor might be used is when you may have an actor that is
* responsible for continuously polling on a server for some resource that sometimes may be down.
* Instead of hammering the server continuously when the resource is unavailable, the actor will
* be restarted with an exponentially increasing back off until the resource is available again.
*
* '''***
* This supervisor should not be used with `Akka Persistence` child actors.
* `Akka Persistence` actors shutdown unconditionally on `persistFailure()`s rather
* than throw an exception on a failure like normal actors.
* [[#onStop]] should be used instead for cases where the child actor
* terminates itself as a failure signal instead of the normal behavior of throwing an exception.
* ***'''
* You can define another
* supervision strategy by using `akka.pattern.BackoffOptions.withSupervisorStrategy` on [[akka.pattern.BackoffOnFailureOptions]].
*
* @param childProps the [[akka.actor.Props]] of the child actor that
* will be started and supervised
* @param childName name of the child actor
* @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`.
*/
def onFailure(
childProps: Props,
childName: String,
minBackoff: java.time.Duration,
maxBackoff: java.time.Duration,
randomFactor: Double): BackoffOnFailureOptions =
onFailure(childProps, childName, minBackoff.asScala, maxBackoff.asScala, randomFactor)
/**
* Back-off options for creating a back-off supervisor actor that expects a child actor to stop on failure.
*
* This actor can be used to supervise a child actor and start it again
* after a back-off duration if the child actor is stopped.
*
* This is useful in situations where the re-start of the child actor should be
* delayed e.g. in order to give an external resource time to recover before the
* child actor tries contacting it again (after being restarted).
*
* Specifically this pattern is useful for persistent actors,
* which are stopped in case of persistence failures.
* Just restarting them immediately would probably fail again (since the data
* store is probably unavailable). It is better to try again after a delay.
*
* It supports exponential back-off between the given `minBackoff` and
* `maxBackoff` durations. For example, if `minBackoff` is 3 seconds and
* `maxBackoff` 30 seconds the start attempts will be delayed with
* 3, 6, 12, 24, 30, 30 seconds. The exponential back-off counter is reset
* if the actor is not terminated within the `minBackoff` duration.
*
* In addition to the calculated exponential back-off an additional
* random delay based the given `randomFactor` is added, e.g. 0.2 adds up to 20%
* delay. The reason for adding a random delay is to avoid that all failing
* actors hit the backend resource at the same time.
*
* You can retrieve the current child `ActorRef` by sending `BackoffSupervisor.GetCurrentChild`
* message to this actor and it will reply with [[akka.pattern.BackoffSupervisor.CurrentChild]]
* containing the `ActorRef` of the current child, if any.
*
* The `BackoffSupervisor`delegates all messages from the child to the parent of the
* `BackoffSupervisor`, with the supervisor as sender.
*
* The `BackoffSupervisor` forwards all other messages to the child, if it is currently running.
*
* The child can stop itself and send a [[akka.actor.PoisonPill]] to the parent supervisor
* if it wants to do an intentional stop.
*
* Exceptions in the child are handled with the default supervisionStrategy, which can be changed by using
* [[BackoffOnStopOptions#withSupervisorStrategy]] or [[BackoffOnStopOptions#withDefaultStoppingStrategy]]. A
* `Restart` will perform a normal immediate restart of the child. A `Stop` will
* stop the child, but it will be started again after the back-off duration.
*
* @param childProps the [[akka.actor.Props]] of the child actor that
* will be started and supervised
* @param childName name of the child actor
* @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`.
*/
def onStop(
childProps: Props,
childName: String,
minBackoff: FiniteDuration,
maxBackoff: FiniteDuration,
randomFactor: Double): BackoffOnStopOptions =
BackoffOnStopOptionsImpl(childProps, childName, minBackoff, maxBackoff, randomFactor)
/**
* Java API: Back-off options for creating a back-off supervisor actor that expects a child actor to stop on failure.
*
* This actor can be used to supervise a child actor and start it again
* after a back-off duration if the child actor is stopped.
*
* This is useful in situations where the re-start of the child actor should be
* delayed e.g. in order to give an external resource time to recover before the
* child actor tries contacting it again (after being restarted).
*
* Specifically this pattern is useful for persistent actors,
* which are stopped in case of persistence failures.
* Just restarting them immediately would probably fail again (since the data
* store is probably unavailable). It is better to try again after a delay.
*
* It supports exponential back-off between the given `minBackoff` and
* `maxBackoff` durations. For example, if `minBackoff` is 3 seconds and
* `maxBackoff` 30 seconds the start attempts will be delayed with
* 3, 6, 12, 24, 30, 30 seconds. The exponential back-off counter is reset
* if the actor is not terminated within the `minBackoff` duration.
*
* In addition to the calculated exponential back-off an additional
* random delay based the given `randomFactor` is added, e.g. 0.2 adds up to 20%
* delay. The reason for adding a random delay is to avoid that all failing
* actors hit the backend resource at the same time.
*
* You can retrieve the current child `ActorRef` by sending `BackoffSupervisor.GetCurrentChild`
* message to this actor and it will reply with [[akka.pattern.BackoffSupervisor.CurrentChild]]
* containing the `ActorRef` of the current child, if any.
*
* The `BackoffSupervisor`delegates all messages from the child to the parent of the
* `BackoffSupervisor`, with the supervisor as sender.
*
* The `BackoffSupervisor` forwards all other messages to the child, if it is currently running.
*
* The child can stop itself and send a [[akka.actor.PoisonPill]] to the parent supervisor
* if it wants to do an intentional stop.
*
* Exceptions in the child are handled with the default supervisionStrategy, which can be changed by using
* [[BackoffOnStopOptions#withSupervisorStrategy]] or [[BackoffOnStopOptions#withDefaultStoppingStrategy]]. A
* `Restart` will perform a normal immediate restart of the child. A `Stop` will
* stop the child, but it will be started again after the back-off duration.
*
* @param childProps the [[akka.actor.Props]] of the child actor that
* will be started and supervised
* @param childName name of the child actor
* @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`.
*/
def onStop(
childProps: Props,
childName: String,
minBackoff: java.time.Duration,
maxBackoff: java.time.Duration,
randomFactor: Double): BackoffOnStopOptions =
onStop(childProps, childName, minBackoff.asScala, maxBackoff.asScala, randomFactor)
}
/**
* Not for user extension
*/
@DoNotInherit
private[akka] sealed trait ExtendedBackoffOptions[T <: ExtendedBackoffOptions[T]] {
/**
* Returns a new BackoffOptions with automatic back-off reset.
* The back-off algorithm is reset if the child does not crash within the specified `resetBackoff`.
*
* @param resetBackoff The back-off is reset if the child does not crash within this duration.
*/
def withAutoReset(resetBackoff: FiniteDuration): T
/**
* Returns a new BackoffOptions with manual back-off reset. The back-off is only reset
* if the child sends a `BackoffSupervisor.Reset` to its parent (the backoff-supervisor actor).
*/
def withManualReset: T
/**
* Returns a new BackoffOptions with the supervisorStrategy.
*
* @param supervisorStrategy the supervisorStrategy that the back-off supervisor will use.
* The default supervisor strategy is used as fallback if the specified supervisorStrategy (its decider)
* does not explicitly handle an exception. As the BackoffSupervisor creates a separate actor to handle the
* backoff process, only a [[OneForOneStrategy]] makes sense here.
* Note that changing the strategy will replace the previously defined maxNrOfRetries.
*/
def withSupervisorStrategy(supervisorStrategy: OneForOneStrategy): T
/**
* Returns a new BackoffOptions with a maximum number of retries to restart the child actor.
* By default, the supervisor will retry infinitely.
* With this option, the supervisor will terminate itself after the maxNoOfRetries is reached.
*
* @param maxNrOfRetries the number of times a child actor is allowed to be restarted.
* If negative, the value is unbounded, otherwise the provided
* limit is used. If the limit is exceeded the child actor will be stopped.
*/
def withMaxNrOfRetries(maxNrOfRetries: Int): T
/**
* Returns a new BackoffOptions with a constant reply to messages that the supervisor receives while its
* child is stopped. By default, a message received while the child is stopped is forwarded to `deadLetters`.
* With this option, the supervisor will reply to the sender instead.
*
* @param replyWhileStopped The message that the supervisor will send in response to all messages while
* its child is stopped.
*/
def withReplyWhileStopped(replyWhileStopped: Any): T
/**
* Returns the props to create the back-off supervisor.
*/
private[akka] def props: Props
}
@DoNotInherit
sealed trait BackoffOnStopOptions extends ExtendedBackoffOptions[BackoffOnStopOptions] {
/**
* Returns a new BackoffOptions with a default `SupervisorStrategy.stoppingStrategy`.
* The default supervisor strategy is used as fallback for throwables not handled by `SupervisorStrategy.stoppingStrategy`.
*/
def withDefaultStoppingStrategy: BackoffOnStopOptions
/**
* Predicate evaluated for each message, if it returns true and the supervised actor is
* stopped then the supervisor will stop its self. If it returns true while
* the supervised actor is running then it will be forwarded to the supervised actor and
* when the supervised actor stops its self the supervisor will stop its self.
*/
def withFinalStopMessage(isFinalStopMessage: Any => Boolean): BackoffOnStopOptions
}
@DoNotInherit
sealed trait BackoffOnFailureOptions extends ExtendedBackoffOptions[BackoffOnFailureOptions]
private final case class BackoffOnStopOptionsImpl[T](
childProps: Props,
childName: String,
minBackoff: FiniteDuration,
maxBackoff: FiniteDuration,
randomFactor: Double,
reset: Option[BackoffReset] = None,
supervisorStrategy: OneForOneStrategy = OneForOneStrategy()(SupervisorStrategy.defaultStrategy.decider),
replyWhileStopped: Option[Any] = None,
finalStopMessage: Option[Any => Boolean] = None)
extends BackoffOnStopOptions {
private val backoffReset = reset.getOrElse(AutoReset(minBackoff))
// default
def withAutoReset(resetBackoff: FiniteDuration) = copy(reset = Some(AutoReset(resetBackoff)))
def withManualReset = copy(reset = Some(ManualReset))
def withSupervisorStrategy(supervisorStrategy: OneForOneStrategy) = copy(supervisorStrategy = supervisorStrategy)
def withReplyWhileStopped(replyWhileStopped: Any) = copy(replyWhileStopped = Some(replyWhileStopped))
def withMaxNrOfRetries(maxNrOfRetries: Int) =
copy(supervisorStrategy = supervisorStrategy.withMaxNrOfRetries(maxNrOfRetries))
// additional
def withDefaultStoppingStrategy =
copy(
supervisorStrategy =
OneForOneStrategy(supervisorStrategy.maxNrOfRetries)(SupervisorStrategy.stoppingStrategy.decider))
def withFinalStopMessage(action: Any => Boolean) = copy(finalStopMessage = Some(action))
def props: Props = {
require(minBackoff > Duration.Zero, "minBackoff must be > 0")
require(maxBackoff >= minBackoff, "maxBackoff must be >= minBackoff")
require(0.0 <= randomFactor && randomFactor <= 1.0, "randomFactor must be between 0.0 and 1.0")
backoffReset match {
case AutoReset(resetBackoff) =>
require(minBackoff <= resetBackoff && resetBackoff <= maxBackoff)
case _ => // ignore
}
Props(
new BackoffOnStopSupervisor(
childProps,
childName,
minBackoff,
maxBackoff,
backoffReset,
randomFactor,
supervisorStrategy,
replyWhileStopped,
finalStopMessage))
}
}
private final case class BackoffOnFailureOptionsImpl[T](
childProps: Props,
childName: String,
minBackoff: FiniteDuration,
maxBackoff: FiniteDuration,
randomFactor: Double,
reset: Option[BackoffReset] = None,
supervisorStrategy: OneForOneStrategy = OneForOneStrategy()(SupervisorStrategy.defaultStrategy.decider),
replyWhileStopped: Option[Any] = None)
extends BackoffOnFailureOptions {
private val backoffReset = reset.getOrElse(AutoReset(minBackoff))
// default
def withAutoReset(resetBackoff: FiniteDuration) = copy(reset = Some(AutoReset(resetBackoff)))
def withManualReset = copy(reset = Some(ManualReset))
def withSupervisorStrategy(supervisorStrategy: OneForOneStrategy) = copy(supervisorStrategy = supervisorStrategy)
def withReplyWhileStopped(replyWhileStopped: Any) = copy(replyWhileStopped = Some(replyWhileStopped))
def withMaxNrOfRetries(maxNrOfRetries: Int) =
copy(supervisorStrategy = supervisorStrategy.withMaxNrOfRetries(maxNrOfRetries))
def props: Props = {
require(minBackoff > Duration.Zero, "minBackoff must be > 0")
require(maxBackoff >= minBackoff, "maxBackoff must be >= minBackoff")
require(0.0 <= randomFactor && randomFactor <= 1.0, "randomFactor must be between 0.0 and 1.0")
backoffReset match {
case AutoReset(resetBackoff) =>
require(minBackoff <= resetBackoff && resetBackoff <= maxBackoff)
case _ => // ignore
}
Props(
new BackoffOnRestartSupervisor(
childProps,
childName,
minBackoff,
maxBackoff,
backoffReset,
randomFactor,
supervisorStrategy,
replyWhileStopped))
}
}
private[akka] sealed trait BackoffReset
private[akka] final case object ManualReset extends BackoffReset
private[akka] final case class AutoReset(resetBackoff: FiniteDuration) extends BackoffReset
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