How to implement a custom Akka Stream flow that handles backpressure with a finite source of data?
I've been banging my head against this for hours. I'm working on a project and hit a roadblock... I'm reviewing some code and I'm trying to create an Akka Stream that consumes data from a finite source, processes it with some complex transformations, and emits results to a sink. However, I'm facing challenges in correctly implementing backpressure when the downstream processing is slower than the upstream data generation. I'm using Akka Streams version 2.6.18 and Scala 2.13.6. Here's a simplified version of what I've attempted: ```scala import akka.actor.ActorSystem import akka.stream.scaladsl.{Sink, Source, Flow} import akka.stream.{ActorMaterializer, OverflowStrategy} implicit val system = ActorSystem("BackpressureExample") implicit val materializer = ActorMaterializer() val source = Source(1 to 100) .throttle(1, 1.second) // Simulates the upstream data generation rate val slowProcessingFlow = Flow[Int] .map { num => Thread.sleep(1000) // Simulates slow processing num * 2 } val sink = Sink.foreach[Int](result => println(s"Processed result: $result")) source.via(slowProcessingFlow).to(sink).run() ``` The issue I'm encountering is that the source can generate all 100 elements quickly, but the flow struggles to keep up due to the `Thread.sleep`. This leads to a `BufferOverflowException` because the default buffer size is overwhelmed when the downstream is slow. I tried adding an `overflowStrategy` to the `Source`, but it doesn't seem to help in this case. I would like to know the best practices for managing backpressure in such a scenario, especially when dealing with limited data sources. Any insights on how to adjust the flow to handle backpressure effectively would be greatly appreciated! This is for a REST API running on Linux. Is there a better approach? I'm using Scala LTS in this project. I'm coming from a different tech stack and learning Scala. This is my first time working with Scala 3.10.