Akka Streams is using asynchronous message passing between Actors to implement stream processing stages. Passing data across an asynchronous boundary has an overhead that you are seeing here: your computation seems to take only about 160ns (derived from the single-threaded measurement) while the streaming solution takes roughly 1µs per element, which is dominated by the … Read more
You need a Flow: import akka.stream.OverflowStrategy.fail import akka.stream.scaladsl.Source import akka.stream.scaladsl.{Sink, Flow} case class Weather(zip : String, temp : Double, raining : Boolean) val weatherSource = Source.actorRef[Weather](Int.MaxValue, fail) val sunnySource = weatherSource.filter(!_.raining) val ref = Flow[Weather] .to(Sink.ignore) .runWith(sunnySource) ref ! Weather(“02139”, 32.0, true) Remember this is all experimental and may change!
There are three ways this can be achieved: 1. Post Materialization with SourceQueue You can use Source.queue that materializes the Flow into a SourceQueue: case class Weather(zipCode : String, temperature : Double, raining : Boolean) val bufferSize = 100 //if the buffer fills up then this strategy drops the oldest elements //upon the arrival of … Read more