Asynchronous streams in direct style with and without macros

Asynchronous streams in direct style with and without macros Philipp
Haller KTH Royal Institute of Technology Stockholm, Sweden Curry On 2019 London, UK, July 15th, 2019

About myself • Associate Professor at KTH Royal Institute of
Technology in Stockholm, Sweden • Previous positions at Typesafe Inc., Stanford University, and EPFL • PhD 2010 EPFL • Creator of Scala’s ﬁrst widely-used actor library, co-author of Scala futures, Scala Async, spores, and others, Akka contributor • Research interests in programming language design and implementation, type systems, concurrency, and distributed programming

A simple task • Given an asynchronous method that returns
the day of the year as a string wrapped in a future:  def dayOfYear(): Future[String] • However, sometimes, for unknown reasons, dayOfYear completes the returned future with "", or null, or the string "nope". • Task: create a future which is completed either • with "It's <month>!" where <month> is the textual representation matching the month returned by dayOfYear, or • with "Not a date, mate!" when that's really the best we can do. "04/11" for April 11, or "06/13" for June 13

A ﬁrst solution def solution() = { val date =
"""(\d+)/(\d+)""".r dayOfYear().flatMap { dayString => dayString match { case date(month, day) => nameOfMonth(month.toInt).map(name => s"It's $name!") case _ => Future.successful("Not a date, mate!") } } }

"""(\d+)/(\d+)""".r dayOfYear().flatMap { dayString => dayString match { case date(month, day) => nameOfMonth(month.toInt).map(name => s"It's $name!") case _ => Future.successful("Not a date, mate!") } } } Returns a value of type Future[String]

"""(\d+)/(\d+)""".r dayOfYear().flatMap { dayString => dayString match { case date(month, day) => nameOfMonth(month.toInt).map(name => s"It's $name!") case _ => Future.successful("Not a date, mate!") } } } Evaluates to a value of type Future[String] which is completed with “It’s April!” when future returned by nameOfMonth(4) is completed with “April” 

"""(\d+)/(\d+)""".r dayOfYear().flatMap { dayString => dayString match { case date(month, day) => nameOfMonth(month.toInt).map(name => s"It's $name!") case _ => Future.successful("Not a date, mate!") } } } Evaluates to a value of type Future[String]

"""(\d+)/(\d+)""".r dayOfYear().flatMap { dayString => dayString match { case date(month, day) => nameOfMonth(month.toInt).map(name => s"It's $name!") case _ => Future.successful("Not a date, mate!") } } } (a) ﬂatMap returns a future f  (b) f is completed (asynchronously) as follows:  once dayOfYear() completes with value dayString, run closure { dayString => .. } which results in a future g;  when g completes with value v,  complete f with v

Scala Async • Purpose:  Simplify asynchronous programming using futures. •
Created by Jason Zaugg (Lightbend) and yours truly, ﬁrst released in 2013 • Stable releases for Scala 2.12 and 2.13

A solution using Scala Async def solution() = async {
val date = """(\d+)/(\d+)""".r await(dayOfYear()) match { case date(month, day) => s"It's ${await(nameOfMonth(month.toInt))}!" case _ => "Not a date, mate!" } } async { <body> } creates a future which is completed asynchronously with result of <body> await(f) suspends current async block until f is completed with value v which is returned A simple, sequential program!

A solution using  Scala for-comprehensions def solution() = { val
date = """(\d+)/(\d+)""".r for { dayString <- dayOfYear() response <- dayString match { case date(month, day) => for (name <- nameOfMonth(month.toInt)) yield s"It's $name!" case _ => Future.successful("Not a date, mate!") } } yield response } Readability OK not great

A solution using Scala Async def solution() = async {
val date = """(\d+)/(\d+)""".r await(dayOfYear()) match { case date(month, day) => s"It's ${await(nameOfMonth(month.toInt))}!" case _ => "Not a date, mate!" } } No need to name all intermediate results No need for explicit Future.successful() Fewer closures allocated: async {} = 1 closure

Let’s make our previous task slightly more complex! • Instead
of converting a single string "04/11" (or "06/13" etc.), "", null, or "nope", we should consume a stream of multiple such strings • Output should be a publisher which produces a stream of results

Intermezzo: Reactive Streams • a.k.a. java.util.concurrent.Flow (since JDK 9) •
Interfaces: j.u.c.Flow.{Publisher, Subscriber, Subscription} • Some key prior work: • Observer design pattern (Gamma et al. 1994)1 • Reactive Extensions (Meijer 2012)2 • Key innovation of Reactive Streams: backpressure control 2Erik Meijer, Your mouse is a database, Commun. ACM 55(5) (2012) 66–73. 1Gamma, Erich, Richard Helm, Ralph Johnson, and John Vlissides, Design Patterns:  Elements of Reusable Object Oriented Software, Addison-Wesley Professional, 1994 Composition of observable streams using higher-order functions

Publisher • A Flow.Publisher<T> produces events of type T which
are received by subscribers if they have expressed interest. public static interface Flow.Publisher<T> { void subscribe(Flow.Subscriber<? super T> subscriber); }

Subscriber • A Flow.Subscriber<T> s consumes events of type T
from publishers to which s has subscribed and from which s has requested to receive (a certain number of) events. public static interface Flow.Subscriber<T> { void onSubscribe(Flow.Subscription subscription); void onNext(T item); void onError(Throwable throwable); void onComplete(); }

Subscription • A Flow.Subscription enables subscribers to control the ﬂow
of events received from publishers. public static interface Flow.Subscription { void request(long n); void cancel(); }

Reactive Extensions • Libraries building on basic interfaces for publishers,
subscribers etc. • Key: higher-order functions for composing publishers • Implementations for many languages available

TextChanges(input) .Select(word => Completions(word)) .Switch() .Subscribe(ObserveChanges(output)); Example from (Meĳer 2012)
Image source: Erik Meijer, Your mouse is a database, Commun. ACM 55(5) (2012) 66–73.  https://queue.acm.org/detail.cfm?id=2169076

Challenges • Often need diagrams to understand semantics (cf. “marble
diagrams” used to document Reactive Extensions) • Creation of combinators challenging • Stateful combinators in particular • Inversion of control

Back to our task • Instead of converting a single
string "04/11" (or "06/13" etc.), "", null, or "nope", we should consume a stream of multiple such strings • Output should be a publisher which produces a stream of results • Problem: • await only takes futures as arguments, but we need to await stream events! • async creates a future, but we need to create a stream publisher which yields multiple events instead of producing just one result We can’t use async/await! :-(

scala-async + Flow = scala-async-ﬂow Extension of async/await model which:
• Provides a variant of async { … } which creates a stream publisher:  rasync { … } • Generalizes await from futures to stream events: next, done, error • Provides additional methods for yielding events:  yieldNext, yieldError, yieldDone

Generalizing await • Previously: await the completion of futures  def
await[T](future: Future[T]): T • Now: await events produced by diﬀerent asynchronous objects  (Future[T], Flow.Publisher[T], etc.) • An asynchronous object must provide the following methods: def getCompleted: Try[T] def onComplete[S](handler: Try[T] => S) given (executor: ExecutionContext)

Solution using scala-async-ﬂow val stream = rasync[String] { var dateOpt
= await(dateStream) while (dateOpt.nonEmpty) { dateOpt.get match { case date(month, day) => yieldNext(s"It's ${await(nameOfMonth(month.toInt))}!") case _ => yieldNext("Not a date, mate!") } dateOpt = await(dateStream) } yieldDone() } Type of stream: Flow.Publisher[String] Here, we are awaiting a future!

Implementing scala-async-ﬂow Some alternatives: 1. Extension of Scala Async (macro
for Scala 2.12 and 2.13) 2. Direct compiler support 3. Build on top of continuations or ﬁbers

Library Component def rasync[T](body: given Flow[T] => T): Flow.Publisher[T] =
{ delegate for Flow[T] = new Flow[T] ... } def await[T, S](a: Async[T]) given (flow: Flow[S], executor: ExecutionContext): T def yieldNext[T](event: T) given (flow: Flow[T]) = { flow.yieldNext(event) } Implicit function type3 3Odersky, Martin, Olivier Blanvillain, Fengyun Liu, Aggelos Biboudis, Heather Miller, and Sandro Stucki. Simplicitly: Foundations and applications of implicit function types. PACMPL 2(POPL): 42:1-42:29 (2018)

Implicit Function Types def rasync[T](body: given Flow[T] => T): Flow.Publisher[T]
= .. Usage: rasync[Int] { expr yieldNext(5) 3 } rasync[Int] { given ($f: Flow[Int]) => expr yieldNext(5) given $f 3 } Expands to: def yieldNext[T](event: T) given (flow: Flow[T]) = { flow.yieldNext(event) } yieldNext, yieldDone, etc. have implicit parameters:

Library Component def rasync[T](body: given Flow[T] => T): Flow.Publisher[T] =
{ delegate for Flow[T] = new Flow[T] ... } def await[T, S](a: Async[T]) given (flow: Flow[S], executor: ExecutionContext): T def yieldNext[T](event: T) given (flow: Flow[T]) = { flow.yieldNext(event) }

Macro-based implementation Example program: def fwd(s: Flow.Publisher[Int]) = rasync {
var x: Option[Int] = None x = await(s) x.get }

class StateMachine(flow: Flow[Int]) { var state = 0 val result
= Promise[Int]() var x: Option[Int] = _ def apply(tr: Try[Int]): Unit = state match { case 0 => x = None val sub = flow.pubToSub(s) val completed = sub.getCompleted if (completed == null) { state = 2 sub.onComplete(evt => apply(evt)) } else if (completed.isFailure) { result.complete(completed) } else { x = completed.get state = 1 apply(null) } case 1 => result.complete(x.get) case 2 => if (tr.isFailure) { result.complete(tr) } else { x = tr.get state = 1 apply(null) } }} Generated state machine

Alternative: more powerful execution environment • OpenJDK Project Loom •
Goal:  JVM features for supporting lightweight, high-throughput concurrency constructs • Key features: • Delimited continuations • Fibers (“user-mode threads”) • Project under active development • Sponsored by OpenJDK HotSpot Group • Talk by Ron Pressler today at 16:15!

Continuations in Project Loom • A continuation turns a task
into a suspendable computation • Suspend and resume <body> at yield points • Transfer values into and out of <body> using higher-level abstractions val cont = new Continuation(SCOPE, new Runnable { def run(): Unit = { <body> } })

var continue = false val cont = new Continuation(SCOPE, new
Runnable { def run(): Unit = { println("hello from continuation") while (!continue) { println("suspending") Continuation.`yield`(SCOPE) println("resuming") } println("all the way to the end") } }) cont.run() println("isDone: " + cont.isDone()) continue = true cont.run() println("isDone: " + cont.isDone()) hello from continuation suspending isDone: false resuming all the way to the end isDone: true Output: Example

def rasync[T](body: given Flow[T] => T): Flow.Publisher[T] = { delegate
flow for Flow[T] = new Flow[T] ... val cont = new Continuation(SCOPE, new Runnable { def run(): Unit = { try { val v = body flow.emitNext(v) flow.emitComplete() } catch { case NonFatal(error) => flow.emitError(error) } } }) ... flow }

def await[T, S](a: Async[T]) given (flow: Flow[S], executor: ExecutionContext): T
= { val res = a.getCompleted if (res eq null) { a.onComplete(x => flow.resume(x)) flow.suspend() a.getCompleted.get } else { res.get } }

Theoretical foundations Paper:  P. Haller and H. Miller: A reduction
semantics for direct-style asynchronous observables.  Journal of Logical and Algebraic Methods in Programming 105 (2019) 75–111  https://doi.org/10.1016/j.jlamp.2019.03.002 • Formalization of programming model • Type soundness proof • Proof of protocol conformance • Describes macro-based implementation Example: a stream created with rasync { … } never emits a next event after emitting a done event

Two More Issues • Issue 1: Data races due to
variable capture    Idea: constrain variable capturing of closures. See:  H. Miller, P. Haller, M. Odersky:  Spores: A Type-Based Foundation for Closures in the Age of  Concurrency and Distribution. ECOOP 2014 • Issue 2: Data races due to top-level singleton objects    Idea: ensure object-capability safety of objects created within rasync blocks. See:  P. Haller, A. Loiko:  LaCasa: lightweight aﬃnity and object capabilities in Scala. OOPSLA 2016 Example: var x = 5 rasync[Int] { x = 10 yieldNext(5) 3 } val y = x + 1

Open Issues • “Blue and red functions” problem • Calling
a suspendible method (given Flow[T]) requires the caller to be suspendible, too • Need two variants for each higher-order function: regular and suspendible • Loom continuations don’t suﬀer from that problem; can suspend as long as there is an active continuation • Relaxing need for Flow[T] capabilities may be feasible

Resources • Prototype implementation:  https://github.com/phaller/scala-async-ﬂow  Branch “cont” makes use of
Project Loom continuations and Scala 3 • Papers and more:  http://www.csc.kth.se/~phaller/ • Twitter: @philippkhaller Thank you!

Asynchronous streams in direct style with and w...

Asynchronous streams in direct style with and without macros

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