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/*
* Copyright (C) 2019-2020 Lightbend Inc.
*/
package akka.stream.javadsl
import java.util.Optional
import akka.annotation.ApiMayChange
import akka.japi.Pair
import akka.stream.scaladsl
import akka.util.JavaDurationConverters._
import scala.compat.java8.OptionConverters._
object RetryFlow {
/**
* API may change!
*
* Allows retrying individual elements in the stream with an exponential backoff.
*
* The retry condition is controlled by the `decideRetry` function. It takes the originally emitted
* element and the response emitted by `flow`, and may return a request to be retried.
*
* The implementation of the `RetryFlow` requires that `flow` follows one-in-one-out semantics,
* the [[akka.stream.javadsl.Flow Flow]] may not filter elements,
* nor emit more than one element per incoming element. The `RetryFlow` will fail if two elements are
* emitted from the `flow`, it will be stuck "forever" if nothing is emitted. Just one element will
* be emitted into the `flow` at any time. The `flow` needs to emit an element before the next
* will be emitted to it.
*
* @param minBackoff minimum duration to backoff between issuing retries
* @param maxBackoff maximum duration to backoff between issuing retries
* @param randomFactor adds jitter to the retry delay. Use 0 for no jitter
* @param flow a flow to retry elements from
* @param decideRetry retry condition decision function
*/
@ApiMayChange(issue = "https://github.com/akka/akka/issues/27960")
def withBackoff[In, Out, Mat](
minBackoff: java.time.Duration,
maxBackoff: java.time.Duration,
randomFactor: Double,
maxRetries: Int,
flow: Flow[In, Out, Mat],
decideRetry: akka.japi.function.Function2[In, Out, Optional[In]]): Flow[In, Out, Mat] =
scaladsl.RetryFlow
.withBackoff[In, Out, Mat](minBackoff.asScala, maxBackoff.asScala, randomFactor, maxRetries, flow.asScala) {
(in, out) =>
decideRetry.apply(in, out).asScala
}
.asJava
/**
* API may change!
*
* Allows retrying individual elements in the stream with an exponential backoff.
*
* The retry condition is controlled by the `decideRetry` function. It takes the originally emitted
* element with its context, and the response emitted by `flow`, and may return a request to be retried.
*
* The implementation of the `RetryFlow` requires that `flow` follows one-in-one-out semantics,
* the [[akka.stream.javadsl.FlowWithContext FlowWithContext]] may not filter elements,
* nor emit more than one element per incoming element. The `RetryFlow` will fail if two elements are
* emitted from the `flow`, it will be stuck "forever" if nothing is emitted. Just one element will
* be emitted into the `flow` at any time. The `flow` needs to emit an element before the next
* will be emitted to it.
*
* The wrapped `flow` and `decideRetry` take the additional context parameters which can be a context,
* or used to control retrying with other information.
*
* @param minBackoff minimum duration to backoff between issuing retries
* @param maxBackoff maximum duration to backoff between issuing retries
* @param randomFactor adds jitter to the retry delay. Use 0 for no jitter
* @param flow a flow to retry elements from
* @param decideRetry retry condition decision function
*/
@ApiMayChange(issue = "https://github.com/akka/akka/issues/27960")
def withBackoffAndContext[In, InCtx, Out, OutCtx, Mat](
minBackoff: java.time.Duration,
maxBackoff: java.time.Duration,
randomFactor: Double,
maxRetries: Int,
flow: FlowWithContext[In, InCtx, Out, OutCtx, Mat],
decideRetry: akka.japi.function.Function2[Pair[In, InCtx], Pair[Out, OutCtx], Optional[Pair[In, InCtx]]])
: FlowWithContext[In, InCtx, Out, OutCtx, Mat] =
scaladsl.RetryFlow
.withBackoffAndContext[In, InCtx, Out, OutCtx, Mat](
minBackoff.asScala,
maxBackoff.asScala,
randomFactor,
maxRetries,
flow.asScala) { (in, out) =>
decideRetry.apply(Pair(in._1, in._2), Pair(out._1, out._2)).asScala.map(_.toScala)
}
.asJava[In, InCtx, Out, OutCtx, Mat]
}
