spray.io

BackPressureHandling

object BackPressureHandling

Automated back-pressure handling is based on the idea that pressure is created by the consumer but experienced at the producer side. E.g. for http that means that a too big number of incoming requests is the ultimate cause of an experienced bottleneck on the response sending side.

The principle of applying back-pressure means that the best way of handling pressure is by handling it at the root cause which means throttling the rate at which work requests are coming in. That's the underlying assumption here: work is generated on the incoming network side. If that's not true, e.g. when the network stream is a truly bi-directional one (e.g. websockets) the strategy presented here won't be optimal.

How it works:

No pressure:

Pressure:

Possible improvement: (see http://doc.akka.io/docs/akka/2.2.0-RC1/scala/io-tcp.html)

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  1. case class Ack(offset: Int) extends akka.io.Tcp.Event with Product with Serializable

  2. class OutQueue extends AnyRef

    A mutable queue of outgoing write requests

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  6. object CanCloseNow extends akka.io.Tcp.Event

  7. val ProbeForEndOfWriting: Write

  8. val ProbeForWriteQueueEmpty: Write

  9. object ResumeReadingNow extends akka.io.Tcp.Event

  10. def apply(ackRate: Int, lowWatermark: Int = Int.MaxValue): PipelineStage

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