object RetryFlow
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- RetryFlow.scala
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- RetryFlow
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- def withBackoff[In, Out, Mat](minBackoff: FiniteDuration, maxBackoff: FiniteDuration, randomFactor: Double, maxRetries: Int, flow: Flow[In, Out, Mat])(decideRetry: (In, Out) => Option[In]): Flow[In, Out, Mat]
API may change!
API may change!
Allows retrying individual elements in the stream with an exponential backoff.
The retry condition is controlled by the
decideRetryfunction. It takes the originally emitted element and the response emitted byflow, and may return a request to be retried.The implementation of the
RetryFlowrequires thatflowfollows strict first-in-first-out and one-in-one-out semantics, i.e., the Flow may neither filter elements, nor emit more than one element per incoming element. TheRetryFlowwill fail if two elements are emitted for one incoming element. Any sort of batching, grouping, or filtering will make it hang forever.Just one element will be emitted into the
flowat any time. Let's say the flow is handling an element, either first-time executing some calculation, or retrying. The next element won't be emitted into the flow until the current element has been finished processing. By finished, it means either succeed the very first attempt, succeed after a few attempts, or get dropped after using up maxRetries retries.- minBackoff
minimum duration to backoff between issuing retries
- maxBackoff
maximum duration to backoff between issuing retries
- randomFactor
adds jitter to the retry delay. Use 0 for no jitter
- maxRetries
total number of allowed retries, when reached the last result will be emitted even if unsuccessful
- flow
a flow to retry elements from
- decideRetry
retry condition decision function
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- @ApiMayChange()
- def withBackoffAndContext[In, CtxIn, Out, CtxOut, Mat](minBackoff: FiniteDuration, maxBackoff: FiniteDuration, randomFactor: Double, maxRetries: Int, flow: FlowWithContext[In, CtxIn, Out, CtxOut, Mat])(decideRetry: ((In, CtxIn), (Out, CtxOut)) => Option[(In, CtxIn)]): FlowWithContext[In, CtxIn, Out, CtxOut, Mat]
API may change!
API may change!
Allows retrying individual elements in the stream with an exponential backoff.
The retry condition is controlled by the
decideRetryfunction. It takes the originally emitted element with its context, and the response emitted byflow, and may return a request to be retried.The implementation of the
RetryFlowrequires thatflowfollows one-in-one-out semantics, the FlowWithContext may not filter elements, nor emit more than one element per incoming element. TheRetryFlowwill fail if two elements are emitted from theflow, it will be stuck "forever" if nothing is emitted. Just one element will be emitted into theflowat any time. Theflowneeds to emit an element before the next will be emitted to it.The wrapped
flowanddecideRetrytake the additional context parameters which can be a context, or used to control retrying with other information.- minBackoff
minimum duration to backoff between issuing retries
- maxBackoff
maximum duration to backoff between issuing retries
- randomFactor
adds jitter to the retry delay. Use 0 for no jitter
- maxRetries
total number of allowed retries, when reached the last result will be emitted even if unsuccessful
- flow
a flow with context to retry elements from
- decideRetry
retry condition decision function
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- @ApiMayChange()