object RestartFlow
A RestartFlow wraps a Flow that gets restarted when it completes or fails.
They are useful for graphs that need to run for longer than the Flow can necessarily guarantee it will, for example, for Flow streams that depend on a remote server that may crash or become partitioned. The RestartFlow ensures that the graph can continue running while the Flow restarts.
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- RestartFlow.scala
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- def onFailuresWithBackoff[In, Out](settings: RestartSettings)(flowFactory: () => Flow[In, Out, _]): Flow[In, Out, NotUsed]
Wrap the given Flow with a Flow that will restart it when it fails using an exponential backoff.
Wrap the given Flow with a Flow that will restart it when it fails using an exponential backoff. Notice that this Flow will not restart on completion of the wrapped flow.
This Flow will not emit any failure The failures by the wrapped Flow will be handled by restarting the wrapping Flow as long as maxRestarts is not reached. Any termination signals sent to this Flow however will terminate the wrapped Flow, if it's running, and then the Flow will be allowed to terminate without being restarted.
The restart process is inherently lossy, since there is no coordination between cancelling and the sending of messages. A termination signal from either end of the wrapped Flow will cause the other end to be terminated, and any in transit messages will be lost. During backoff, this Flow will backpressure.
This uses the same exponential backoff algorithm as pekko.pattern.BackoffOpts.
- settings
RestartSettings defining restart configuration
- flowFactory
A factory for producing the Flow to wrap.
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- def withBackoff[In, Out](settings: RestartSettings)(flowFactory: () => Flow[In, Out, _]): Flow[In, Out, NotUsed]
Wrap the given Flow with a Flow that will restart it when it fails or complete using an exponential backoff.
Wrap the given Flow with a Flow that will restart it when it fails or complete using an exponential backoff.
This Flow will not cancel, complete or emit a failure, until the opposite end of it has been cancelled or completed. Any termination by the Flow before that time will be handled by restarting it as long as maxRestarts is not reached. Any termination signals sent to this Flow however will terminate the wrapped Flow, if it's running, and then the Flow will be allowed to terminate without being restarted.
The restart process is inherently lossy, since there is no coordination between cancelling and the sending of messages. A termination signal from either end of the wrapped Flow will cause the other end to be terminated, and any in transit messages will be lost. During backoff, this Flow will backpressure.
This uses the same exponential backoff algorithm as pekko.pattern.BackoffOpts.
- settings
RestartSettings defining restart configuration
- flowFactory
A factory for producing the Flow to wrap.
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- def onFailuresWithBackoff[In, Out](minBackoff: FiniteDuration, maxBackoff: FiniteDuration, randomFactor: Double, maxRestarts: Int)(flowFactory: () => Flow[In, Out, _]): Flow[In, Out, NotUsed]
Wrap the given Flow with a Flow that will restart it when it fails using an exponential backoff.
Wrap the given Flow with a Flow that will restart it when it fails using an exponential backoff. Notice that this Flow will not restart on completion of the wrapped flow.
This Flow will not emit any failure The failures by the wrapped Flow will be handled by restarting the wrapping Flow as long as maxRestarts is not reached. Any termination signals sent to this Flow however will terminate the wrapped Flow, if it's running, and then the Flow will be allowed to terminate without being restarted.
The restart process is inherently lossy, since there is no coordination between cancelling and the sending of messages. A termination signal from either end of the wrapped Flow will cause the other end to be terminated, and any in transit messages will be lost. During backoff, this Flow will backpressure.
This uses the same exponential backoff algorithm as pekko.pattern.BackoffOpts.
- minBackoff
minimum (initial) duration until the child actor will started again, if it is terminated
- maxBackoff
the exponential back-off is capped to this duration
- randomFactor
after calculation of the exponential back-off an additional random delay based on this factor is added, e.g.
0.2
adds up to20%
delay. In order to skip this additional delay pass in0
.- 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.- flowFactory
A factory for producing the Flow to wrap.
- Annotations
- @deprecated
- Deprecated
(Since version Akka 2.6.10) Use the overloaded method which accepts org.apache.pekko.stream.RestartSettings instead.
- def withBackoff[In, Out](minBackoff: FiniteDuration, maxBackoff: FiniteDuration, randomFactor: Double, maxRestarts: Int)(flowFactory: () => Flow[In, Out, _]): Flow[In, Out, NotUsed]
Wrap the given Flow with a Flow that will restart it when it fails or complete using an exponential backoff.
Wrap the given Flow with a Flow that will restart it when it fails or complete using an exponential backoff.
This Flow will not cancel, complete or emit a failure, until the opposite end of it has been cancelled or completed. Any termination by the Flow before that time will be handled by restarting it as long as maxRestarts is not reached. Any termination signals sent to this Flow however will terminate the wrapped Flow, if it's running, and then the Flow will be allowed to terminate without being restarted.
The restart process is inherently lossy, since there is no coordination between cancelling and the sending of messages. A termination signal from either end of the wrapped Flow will cause the other end to be terminated, and any in transit messages will be lost. During backoff, this Flow will backpressure.
This uses the same exponential backoff algorithm as pekko.pattern.BackoffOpts.
- minBackoff
minimum (initial) duration until the child actor will started again, if it is terminated
- maxBackoff
the exponential back-off is capped to this duration
- randomFactor
after calculation of the exponential back-off an additional random delay based on this factor is added, e.g.
0.2
adds up to20%
delay. In order to skip this additional delay pass in0
.- 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.- flowFactory
A factory for producing the Flow to wrap.
- Annotations
- @deprecated
- Deprecated
(Since version Akka 2.6.10) Use the overloaded method which accepts org.apache.pekko.stream.RestartSettings instead.
- def withBackoff[In, Out](minBackoff: FiniteDuration, maxBackoff: FiniteDuration, randomFactor: Double)(flowFactory: () => Flow[In, Out, _]): Flow[In, Out, NotUsed]
Wrap the given Flow with a Flow that will restart it when it fails or complete using an exponential backoff.
Wrap the given Flow with a Flow that will restart it when it fails or complete using an exponential backoff.
This Flow will not cancel, complete or emit a failure, until the opposite end of it has been cancelled or completed. Any termination by the Flow before that time will be handled by restarting it. Any termination signals sent to this Flow however will terminate the wrapped Flow, if it's running, and then the Flow will be allowed to terminate without being restarted.
The restart process is inherently lossy, since there is no coordination between cancelling and the sending of messages. A termination signal from either end of the wrapped Flow will cause the other end to be terminated, and any in transit messages will be lost. During backoff, this Flow will backpressure.
This uses the same exponential backoff algorithm as pekko.pattern.BackoffOpts.
- minBackoff
minimum (initial) duration until the child actor will started again, if it is terminated
- maxBackoff
the exponential back-off is capped to this duration
- randomFactor
after calculation of the exponential back-off an additional random delay based on this factor is added, e.g.
0.2
adds up to20%
delay. In order to skip this additional delay pass in0
.- flowFactory
A factory for producing the Flow to wrap.
- Annotations
- @deprecated
- Deprecated
(Since version Akka 2.6.10) Use the overloaded method which accepts org.apache.pekko.stream.RestartSettings instead.