How to implement Future as Applicative in Scala? - scala

Suppose I need to run two concurrent computations, wait for both of them, and then combine their results. More specifically, I need to run f1: X1 => Y1 and f2: X2 => Y2 concurrently and then call f: (Y1, Y2) => Y to finally get a value of Y.
I can create future computations fut1: X1 => Future[Y1] and fut2: X2 => Future[Y2] and then compose them to get fut: (X1, X2) => Future[Y] using monadic composition.
The problem is that monadic composition implies sequential wait. In our case it implies that we wait for one future first and then we will wait for another. For instance. if it takes 2 sec. to the first future to complete and just 1 sec. to the 2nd future to fail we waste 1 sec.
Thus it looks like we need an applicative composition of the futures to wait till either both complete or at least one future fails. Does it make sense ? How would you implement <*> for futures ?

None of the methods in other answers does the right thing in case of a future that fails quickly plus a future that succeeds after a long time.
But such a method can be implemented manually:
def smartSequence[A](futures: Seq[Future[A]]): Future[Seq[A]] = {
val counter = new AtomicInteger(futures.size)
val result = Promise[Seq[A]]()
def attemptComplete(t: Try[A]): Unit = {
val remaining = counter.decrementAndGet
t match {
// If one future fails, fail the result immediately
case Failure(cause) => result tryFailure cause
// If all futures have succeeded, complete successful result
case Success(_) if remaining == 0 =>
result tryCompleteWith Future.sequence(futures)
case _ =>
}
}
futures.foreach(_ onComplete attemptComplete)
result.future
}
ScalaZ does a similar thing internally, so both f1 |#| f2 and List(f1, f2).sequence fail immediately after any of the futures fails.
Here is a quick test of the failing time for those methods:
import java.util.Date
import scala.concurrent.Future
import scala.concurrent.ExecutionContext.Implicits.global
import scalaz._, Scalaz._
object ReflectionTest extends App {
def f1: Future[Unit] = Future {
Thread.sleep(2000)
}
def f2: Future[Unit] = Future {
Thread.sleep(1000)
throw new RuntimeException("Failure")
}
def test(name: String)(
f: (Future[Unit], Future[Unit]) => Future[Unit]
): Unit = {
val start = new Date().getTime
f(f1, f2).andThen {
case _ =>
println(s"Test $name completed in ${new Date().getTime - start}")
}
Thread.sleep(2200)
}
test("monadic") { (f1, f2) => for (v1 <- f1; v2 <- f2) yield () }
test("zip") { (f1, f2) => (f1 zip f2).map(_ => ()) }
test("Future.sequence") {
(f1, f2) => Future.sequence(Seq(f1, f2)).map(_ => ())
}
test("smartSequence") { (f1, f2) => smartSequence(Seq(f1, f2)).map(_ => ())}
test("scalaz |#|") { (f1, f2) => (f1 |#| f2) { case _ => ()}}
test("scalaz sequence") { (f1, f2) => List(f1, f2).sequence.map(_ => ())}
Thread.sleep(30000)
}
And the result on my machine is:
Test monadic completed in 2281
Test zip completed in 2008
Test Future.sequence completed in 2007
Test smartSequence completed in 1005
Test scalaz |#| completed in 1003
Test scalaz sequence completed in 1005

The problem is that monadic composition implies sequential wait. In our case it implies that we wait for one future first and then we will wait for another.
This is unfortunately true.
import java.util.Date
import scala.concurrent.Future
import scala.concurrent.ExecutionContext.Implicits.global
object Test extends App {
def timestamp(label: String): Unit = Console.println(label + ": " + new Date().getTime.toString)
timestamp("Start")
for {
step1 <- Future {
Thread.sleep(2000)
timestamp("step1")
}
step2 <- Future {
Thread.sleep(1000)
timestamp("step2")
}
} yield { timestamp("Done") }
Thread.sleep(4000)
}
Running this code outputs:
Start: 1430473518753
step1: 1430473520778
step2: 1430473521780
Done: 1430473521781
Thus it looks like we need an applicative composition of the futures to wait till either both complete or at least one future fails.
I am not sure applicative composition has anything to do with the concurrent strategy. Using for comprehensions, you get a result if all futures complete or a failure if any of them fails. So it's semantically the same.
Why Are They Running Sequentially
I think the reason why futures are run sequentially is because step1 is available within step2 (and in the rest of the computation). Essentially we can convert the for block as:
def step1() = Future {
Thread.sleep(2000)
timestamp("step1")
}
def step2() = Future {
Thread.sleep(1000)
timestamp("step2")
}
def finalStep() = timestamp("Done")
step1().flatMap(step1 => step2()).map(finalStep())
So the result of previous computations are available to the rest of the steps. It differs from <?> & <*> in this respect.
How To Run Futures In Parallel
#andrey-tyukin's code runs futures in parallel:
import java.util.Date
import scala.concurrent.Future
import scala.concurrent.ExecutionContext.Implicits.global
object Test extends App {
def timestamp(label: String): Unit = Console.println(label + ": " + new Date().getTime.toString)
timestamp("Start")
(Future {
Thread.sleep(2000)
timestamp("step1")
} zip Future {
Thread.sleep(1000)
timestamp("step2")
}).map(_ => timestamp("Done"))
Thread.sleep(4000)
}
Output:
Start: 1430474667418
step2: 1430474668444
step1: 1430474669444
Done: 1430474669446

Your post seems to contain two more or less independent questions.
I will address the concrete practical problem of running two concurrent computations first. The question about Applicative is answered in the very end.
Suppose you have two asynchronous functions:
val f1: X1 => Future[Y1]
val f2: X2 => Future[Y2]
And two values:
val x1: X1
val x2: X2
Now you can start the computations in multiple different ways. Let's take a look at some of them.
Starting computations outside of for (parallel)
Suppose you do this:
val y1: Future[Y1] = f1(x1)
val y2: Future[Y2] = f2(x2)
Now, the computations f1 and f2 are already running. It does not matter in which order you collect the results. You could do it with a for-comprehension:
val y: Future[(Y1,Y2)] = for(res1 <- y1; res2 <- y2) yield (res1,res2)
Using the expressions y1 and y2 in the for-comprehension does not interfere with the order of computation of y1 and y2, they are still being computed in parallel.
Starting computations inside of for (sequential)
If we simply take the definitions of y1 and y2, and plug them into the for comprehension directly, we will still get the same result, but the order of execution will be different:
val y = for (res1 <- f1(x1); res2 <- f2(x2)) yield (res1, res2)
translates into
val y = f1(x1).flatMap{ res1 => f2(x2).map{ res2 => (res1, res2) } }
in particular, the second computation starts after the first one has terminated. This is usually not what one wants to have.
Here, a basic substitution principle is violated. If there were no side-effects, one probably could transform this version into the previous one, but in Scala, one has to take care of the order of execution explicitly.
Zipping futures (parallel)
Futures respect products. There is a method Future.zip, which allows you to do this:
val y = f1(x1) zip f2(x2)
This would run both computations in parallel until both are done, or until one of them fails.
Demo
Here is a little script that demonstrates this behaviour (inspired by muhuk's post):
import scala.concurrent._
import scala.concurrent.duration._
import scala.concurrent.ExecutionContext.Implicits.global
import java.lang.Thread.sleep
import java.lang.System.{currentTimeMillis => millis}
var time: Long = 0
val x1 = 1
val x2 = 2
// this function just waits
val f1: Int => Future[Unit] = {
x => Future { sleep(x * 1000) }
}
// this function waits and then prints
// elapsed time
val f2: Int => Future[Unit] = {
x => Future {
sleep(x * 1000)
val elapsed = millis() - time
printf("Time: %1.3f seconds\n", elapsed / 1000.0)
}
}
/* Outside `for` */ {
time = millis()
val y1 = f1(x1)
val y2 = f2(x2)
val y = for(res1 <- y1; res2 <- y2) yield (res1,res2)
Await.result(y, Duration.Inf)
}
/* Inside `for` */ {
time = millis()
val y = for(res1 <- f1(x1); res2 <- f2(x2)) yield (res1, res2)
Await.result(y, Duration.Inf)
}
/* Zip */ {
time = millis()
val y = f1(x1) zip f2(x2)
Await.result(y, Duration.Inf)
}
Output:
Time: 2.028 seconds
Time: 3.001 seconds
Time: 2.001 seconds
Applicative
Using this definition from your other post:
trait Applicative[F[_]] {
def apply[A, B](f: F[A => B]): F[A] => F[B]
}
one could do something like this:
object FutureApplicative extends Applicative[Future] {
def apply[A, B](ff: Future[A => B]): Future[A] => Future[B] = {
fa => for ((f,a) <- ff zip fa) yield f(a)
}
}
However, I'm not sure what this has to do with your concrete problem, or with understandable and readable code. A Future already is a monad (this is stronger than Applicative), and there is even built-in syntax for it, so I don't see any advantages in adding some Applicatives here.

It needs not be sequential. The future computation may start the moment the future is created. Of course, if the future is created by the flatMap argument (and it will necessary be so if it needs the result of the first computation), then it will be sequential. But in code such as
val f1 = Future {....}
val f2 = Future {....}
for (a1 <- f1; a2 <- f2) yield f(a1, a2)
you get concurrent execution.
So the implementation of Applicative implied by Monad is ok.

Related

How to test if futures run sequentially in Scala?

Suppose I have this methods:
def callApis(f1, f2, f3):Future[Result] {
for {
a <- Future { f1 }
b <- Future { f2 }
c <- Future { f3 }
} yield Result(a,b,c)
}
If you are familiar with scala you will know that lines in the for block will execute sequentially. More specific, a will be calculated first. Then when we have the result for a, the code will calculate b. Then when we have the result for b, the code will calculate c.
My question is, how can you write a UNIT TEST that ensures that a always be computed before calculating b, and b always be computed before calculating c? My fear is if someone doesn't know much about how futures work in scala. They can accidentally make this code to run asynchronously.
I mean people can accidentally do something like this, this makes a,b,c to be calculated asynchronously (which I don't want people to do):
def callApis(f1, f2, f3):Future[Result] {
val fut1 = Future { f1 }
val fut2 = Future { f2 }
val fut3 = Future { f3 }
for {
a <- fut1
b <- fut2
c <- fut3
} yield Result(a,b,c)
}
Perhaps try defining a single-threaded execution context and require it in blocks that should execute serially. For example,
trait SerialExecutionContext extends ExecutionContext {
val singleThreadPool = Executors.newFixedThreadPool(1, (r: Runnable) => new Thread(r, s"single-thread-pool"))
val serialEc = ExecutionContext.fromExecutor(singleThreadPool)
override def execute(runnable: Runnable): Unit = serialEc.execute(runnable)
override def reportFailure(cause: Throwable): Unit = serialEc.reportFailure(cause)
}
def callApis()(implicit ec: SerialExecutionContext): Future[Result] = {
val fut1 = Future { ...doSomething... }
val fut2 = Future { ...doSomething... }
val fut3 = Future { ...doSomething... }
for {
a <- fut1
b <- fut2
c <- fut3
} yield Result(a,b,c)
}
Now callApis can evaluate only if we can prove at compile time there exists a serial execution context. Since within the body we have only one thread available futures are forced to start only after the previous one finished.

Running sequential Futures with similar shapes using for comprehension

def func1(list : List[T]) : Future[\/[Throwable,Unit] ]
def func2(list : List[T]) : Future[List[\/[Throwable,Unit]]]
where T is just a specific type and that type will be same for both the functions. Now func2 is dependent on success of first func 's future. so func2 should run sequentially only after func completed successfully. I want a for comprehension something in a similar line as below (following isn't valid compilable code) and return Future[\/[Throwable,Unit] ]
def func3 combiner(list) : Future[\/[Throwable,Unit] ] = for{
u <- func1(list)
us <- u
d <- func2(list)
}yield
Any pointers how to go about this?
Because futures either complete with a value or an exception you won't need the Either (or do you have other reasons for using it?).
Running this code should help you (and reading the documentation on futures):
import scala.concurrent._
import ExecutionContext.Implicits.global
def f1(l: List[Int]): Future[Int] = future { println("f1"); l head }
def f2(l: List[Int]): Future[Int] = future { println("f2"); throw new Exception("bang") }
def f3(l: List[Int]): Future[Int] = future { println("f3"); l last }
val result1 = for {
x1 <- f2(List(1, 2))
x2 <- f1(List(1, 2)) // f1 is not run
} yield x2
val result2 = for {
x1 <- f1(List(1, 2))
x3 <- f3(List(1, 2))
} yield x3
result1.onComplete(res => println("result1 = " + res))
result2.onComplete(res => println("result2 = " + res))

How to build processing in Scala depending on the multiple future Completion

I am new to Scala, and just start learning to use fully non-blocking nature of Scala API
I need to execute function after 2 tasks finish, curenly I do this following way:
import scala.concurrent._
import scala.util._
import scala.concurrent.duration._
val f1:Future[Int] = Future( {
Thread.sleep(800)
println(5)
5
})
val f2: Future[Int] = Future( {
Thread.sleep(500)
println(6)
6
})
val combined: Future[List[Int]] = Future.sequence(List(f1, f2))
combined.onComplete {
case Success(li) => li.foldLeft(0)((sum, x) => sum + x)
case Failure(t) => -1
}
Await.result(combined, 1 second)
Is there a more straight forward way to do this?
You can flatMap futures in for:
val f = for {
r1 <- f1
r2 <- f2
} yield (r1, r2) //any operations like `yield r1 + r2`
f.onSuccess { println }

Future[Option[Future[Option[Boolean]] Simplifying Futures and Options?

I've been trying to simplify the way I do futures in Scala. I got at one point a Future[Option[Future[Option[Boolean]] but I've simplified it further below. Is there a better way to simplify this?
Passing a future of "failed" doesn't seem like the best way to do this. i.e. in the sequential world I simply returned "FAIL!!" any time it failed rather than continuing to the end. Are there other ways?
val doSimpleWork = Future {
//Do any arbitrary work (can be a different function)
true //or false
}
val doComplexWork = Future {
//Do any arbitrary work (can be a different function)
Some("result") //or false
}
val failed = Future {
//Do no work at all!!! Just return
false
}
val fut1 = doSimpleWork
val fut2 = doSimpleWork
val fut3 = (fut1 zip fut2).map({
case (true, true) => true
case _ => false
})
val fut4 = fut3.flatMap({
case true =>
doComplexWork.flatMap({
case Some("result") =>
doSimpleWork
case None =>
failed
})
case false =>
failed
})
fut4.map({
case true =>
"SUCCESS!!!"
case _ =>
"FAIL!!"
})
Note that in your example, because you're eagerly instantiating the Futures to a val, all of them will start executing as soon as you declare them (val x = Future {...}). Using methods instead will make the Futures execute only when they're requested by the chain of execution.
One way to avoid the further computation would be to throw an exception, then handle it with onFailure:
def one = future { println("one") ; Some(1) }
def two = future { println("two") ; throw new Exception("no!"); 2 }
def three = future { println("three") ; 3 }
val f = one flatMap {
result1 => two flatMap {
result2 => three
}
}
f onFailure {
case e: Exception =>
println("failed somewhere in the chain")
}
You can see here that "three" isn't supposed to be printed out, because we fail on two. This is the case:
one
two
failed somewhere in the chain
a "Monad transformer" is a construct which lets you combine the "effects" of two monads, the scalaz project provides several different monad transformers. My suggestion is that you can use the OptionT monad transformer to simplify your code if you also make use of the fact that Option[Unit] is isomorphic to Boolean (Some(()) == true and None == false). Here's a complete example:
import scalaz._
import Scalaz._
import scala.concurrent._
import ExecutionContext.Implicits.global
import scala.concurrent.duration._
object Foo {
// We need a Monad instance for Future, here is a valid one, or you can use the implementation
// in the scalaz-contrib project, see http://typelevel.org
implicit def futureMonad(implicit executor: ExecutionContext): Monad[Future] = new Monad[Future] {
override def bind[A, B](fa: Future[A])(f: A ⇒ Future[B]) = fa flatMap f
override def point[A](a: ⇒ A) = Future(a)
override def map[A, B](fa: Future[A])(f: A ⇒ B) = fa map f
}
// OptionT allows you to combine the effects of the Future and Option monads
// to more easily work with a Future[Option[A]]
val doSimpleWork : OptionT[Future,Unit] = OptionT(Future {
// Option[Unit] is isomorphic to Boolean
Some(()) //or None
})
val simpleFail : OptionT[Future,Unit] = OptionT(Future {
None
})
val doComplexWork: OptionT[Future,String] = OptionT(Future {
Some("result") //or None
})
val f1 = doSimpleWork
val f2 = doSimpleWork
val f3 = doComplexWork
val f4 = doSimpleWork
def main(argv: Array[String]) {
val result = for {
_ <- f1
// we don't get here unless both the future succeeded and the result was Some
_ <- f2
_ <- f3
r <- f4
} yield(r)
result.fold((_ => println("SUCCESS!!")),println("FAIL!!"))
// "run" will get you to the Future inside the OptionT
Await.result(result.run, 1 second)
}
}
You could try something like this, using for comprehensions to clean up the code a bit:
def doSimpleWork = Future{
//do some simple work
true
}
def doComplexWork = Future{
//do something complex here
Some("result")
}
val fut1 = doSimpleWork
val fut2 = doSimpleWork
val fut = for{
f1Result <- fut1
f2Result <- fut2
if (f1Result && f2Result)
f3Result <- doComplexWork
if (f3Result.isDefined)
f4Result <- doSimpleWork
} yield "success"
fut onComplete{
case Success(value) => println("I succeeded")
case Failure(ex) => println("I failed: " + ex.getMessage)
}
And if you really just wanted to print out "success" or "failed" at the end, you could change that last piece of code to:
fut.recover{case ex => "failed"} onSuccess{
case value => println(value)
}
Now, to explain what's going on. For starters, we've defined two functions that return Futures that are doing some async work. The doSimpleWork function will do some simple work and return a boolean success/fail indicator. The doComplexWork function will do something more complex (and time consuming) and return an Option[String] representing a result. We then kick off two parallel invocations of doSimpleWork before entering the for comprehension. In for for comp, we get the results of fut1 and fut2 (in that order) before checking if they were both successful. If not, we would stop here, and the fut val would be failed with a NoSuchElementException which is what you get when a condition like this fails in a for comp. If both were successful, we would continue on and invoke the doComplexWork function and wait for its result. We would then check its result and if it was Some, we would kick off one last invocation of doSimpleWork. If that succeeds, we would yield the string "success". If you check the type of the fut val, its of type Future[String].
From there, we use one of the async callback functions to check if the whole sequence of calls either made it all the way through (the Success case), or failed somewhere in the process (the Failure case), printing out something related to which case it hit. In the alternate final code block, we recover from any possible failure by returning the String "failed" "and then use just the onSuccess callback which will print either "success" or "failed" depending on what happened.

How to wait for several Futures?

Suppose I have several futures and need to wait until either any of them fails or all of them succeed.
For example: Let there are 3 futures: f1, f2, f3.
If f1 succeeds and f2 fails I do not wait for f3 (and return failure to the client).
If f2 fails while f1 and f3 are still running I do not wait for them (and return failure)
If f1 succeeds and then f2 succeeds I continue waiting for f3.
How would you implement it?
You could use a for-comprehension as follows instead:
val fut1 = Future{...}
val fut2 = Future{...}
val fut3 = Future{...}
val aggFut = for{
f1Result <- fut1
f2Result <- fut2
f3Result <- fut3
} yield (f1Result, f2Result, f3Result)
In this example, futures 1, 2 and 3 are kicked off in parallel. Then, in the for comprehension, we wait until the results 1 and then 2 and then 3 are available. If either 1 or 2 fails, we will not wait for 3 anymore. If all 3 succeed, then the aggFut val will hold a tuple with 3 slots, corresponding to the results of the 3 futures.
Now if you need the behavior where you want to stop waiting if say fut2 fails first, things get a little trickier. In the above example, you would have to wait for fut1 to complete before realizing fut2 failed. To solve that, you could try something like this:
val fut1 = Future{Thread.sleep(3000);1}
val fut2 = Promise.failed(new RuntimeException("boo")).future
val fut3 = Future{Thread.sleep(1000);3}
def processFutures(futures:Map[Int,Future[Int]], values:List[Any], prom:Promise[List[Any]]):Future[List[Any]] = {
val fut = if (futures.size == 1) futures.head._2
else Future.firstCompletedOf(futures.values)
fut onComplete{
case Success(value) if (futures.size == 1)=>
prom.success(value :: values)
case Success(value) =>
processFutures(futures - value, value :: values, prom)
case Failure(ex) => prom.failure(ex)
}
prom.future
}
val aggFut = processFutures(Map(1 -> fut1, 2 -> fut2, 3 -> fut3), List(), Promise[List[Any]]())
aggFut onComplete{
case value => println(value)
}
Now this works correctly, but the issue comes from knowing which Future to remove from the Map when one has been successfully completed. As long as you have some way to properly correlate a result with the Future that spawned that result, then something like this works. It just recursively keeps removing completed Futures from the Map and then calling Future.firstCompletedOf on the remaining Futures until there are none left, collecting the results along the way. It's not pretty, but if you really need the behavior you are talking about, then this, or something similar could work.
You can use a promise, and send to it either the first failure, or the final completed aggregated success:
def sequenceOrBailOut[A, M[_] <: TraversableOnce[_]](in: M[Future[A]] with TraversableOnce[Future[A]])(implicit cbf: CanBuildFrom[M[Future[A]], A, M[A]], executor: ExecutionContext): Future[M[A]] = {
val p = Promise[M[A]]()
// the first Future to fail completes the promise
in.foreach(_.onFailure{case i => p.tryFailure(i)})
// if the whole sequence succeeds (i.e. no failures)
// then the promise is completed with the aggregated success
Future.sequence(in).foreach(p trySuccess _)
p.future
}
Then you can Await on that resulting Future if you want to block, or just map it into something else.
The difference with for comprehension is that here you get the error of the first to fail, whereas with for comprehension you get the first error in traversal order of the input collection (even if another one failed first). For example:
val f1 = Future { Thread.sleep(1000) ; 5 / 0 }
val f2 = Future { 5 }
val f3 = Future { None.get }
Future.sequence(List(f1,f2,f3)).onFailure{case i => println(i)}
// this waits one second, then prints "java.lang.ArithmeticException: / by zero"
// the first to fail in traversal order
And:
val f1 = Future { Thread.sleep(1000) ; 5 / 0 }
val f2 = Future { 5 }
val f3 = Future { None.get }
sequenceOrBailOut(List(f1,f2,f3)).onFailure{case i => println(i)}
// this immediately prints "java.util.NoSuchElementException: None.get"
// the 'actual' first to fail (usually...)
// and it returns early (it does not wait 1 sec)
Here is a solution without using actors.
import scala.util._
import scala.concurrent._
import java.util.concurrent.atomic.AtomicInteger
// Nondeterministic.
// If any failure, return it immediately, else return the final success.
def allSucceed[T](fs: Future[T]*): Future[T] = {
val remaining = new AtomicInteger(fs.length)
val p = promise[T]
fs foreach {
_ onComplete {
case s # Success(_) => {
if (remaining.decrementAndGet() == 0) {
// Arbitrarily return the final success
p tryComplete s
}
}
case f # Failure(_) => {
p tryComplete f
}
}
}
p.future
}
You can do this with futures alone. Here's one implementation. Note that it won't terminate execution early! In that case you need to do something more sophisticated (and probably implement the interruption yourself). But if you just don't want to keep waiting for something that isn't going to work, the key is to keep waiting for the first thing to finish, and stop when either nothing is left or you hit an exception:
import scala.annotation.tailrec
import scala.util.{Try, Success, Failure}
import scala.concurrent._
import scala.concurrent.duration.Duration
import ExecutionContext.Implicits.global
#tailrec def awaitSuccess[A](fs: Seq[Future[A]], done: Seq[A] = Seq()):
Either[Throwable, Seq[A]] = {
val first = Future.firstCompletedOf(fs)
Await.ready(first, Duration.Inf).value match {
case None => awaitSuccess(fs, done) // Shouldn't happen!
case Some(Failure(e)) => Left(e)
case Some(Success(_)) =>
val (complete, running) = fs.partition(_.isCompleted)
val answers = complete.flatMap(_.value)
answers.find(_.isFailure) match {
case Some(Failure(e)) => Left(e)
case _ =>
if (running.length > 0) awaitSuccess(running, answers.map(_.get) ++: done)
else Right( answers.map(_.get) ++: done )
}
}
}
Here's an example of it in action when everything works okay:
scala> awaitSuccess(Seq(Future{ println("Hi!") },
Future{ Thread.sleep(1000); println("Fancy meeting you here!") },
Future{ Thread.sleep(2000); println("Bye!") }
))
Hi!
Fancy meeting you here!
Bye!
res1: Either[Throwable,Seq[Unit]] = Right(List((), (), ()))
But when something goes wrong:
scala> awaitSuccess(Seq(Future{ println("Hi!") },
Future{ Thread.sleep(1000); throw new Exception("boo"); () },
Future{ Thread.sleep(2000); println("Bye!") }
))
Hi!
res2: Either[Throwable,Seq[Unit]] = Left(java.lang.Exception: boo)
scala> Bye!
For this purpose I would use an Akka actor. Unlike the for-comprehension, it fails as soon as any of the futures fail, so it's a bit more efficient in that sense.
class ResultCombiner(futs: Future[_]*) extends Actor {
var origSender: ActorRef = null
var futsRemaining: Set[Future[_]] = futs.toSet
override def receive = {
case () =>
origSender = sender
for(f <- futs)
f.onComplete(result => self ! if(result.isSuccess) f else false)
case false =>
origSender ! SomethingFailed
case f: Future[_] =>
futsRemaining -= f
if(futsRemaining.isEmpty) origSender ! EverythingSucceeded
}
}
sealed trait Result
case object SomethingFailed extends Result
case object EverythingSucceeded extends Result
Then, create the actor, send a message to it (so that it will know where to send its reply to) and wait for a reply.
val actor = actorSystem.actorOf(Props(new ResultCombiner(f1, f2, f3)))
try {
val f4: Future[Result] = actor ? ()
implicit val timeout = new Timeout(30 seconds) // or whatever
Await.result(f4, timeout.duration).asInstanceOf[Result] match {
case SomethingFailed => println("Oh noes!")
case EverythingSucceeded => println("It all worked!")
}
} finally {
// Avoid memory leaks: destroy the actor
actor ! PoisonPill
}
This question has been answered but I am posting my value class solution (value classes were added in 2.10) since there isn't one here. Please feel free to criticize.
implicit class Sugar_PimpMyFuture[T](val self: Future[T]) extends AnyVal {
def concurrently = ConcurrentFuture(self)
}
case class ConcurrentFuture[A](future: Future[A]) extends AnyVal {
def map[B](f: Future[A] => Future[B]) : ConcurrentFuture[B] = ConcurrentFuture(f(future))
def flatMap[B](f: Future[A] => ConcurrentFuture[B]) : ConcurrentFuture[B] = concurrentFutureFlatMap(this, f) // work around no nested class in value class
}
def concurrentFutureFlatMap[A,B](outer: ConcurrentFuture[A], f: Future[A] => ConcurrentFuture[B]) : ConcurrentFuture[B] = {
val p = Promise[B]()
val inner = f(outer.future)
inner.future onFailure { case t => p.tryFailure(t) }
outer.future onFailure { case t => p.tryFailure(t) }
inner.future onSuccess { case b => p.trySuccess(b) }
ConcurrentFuture(p.future)
}
ConcurrentFuture is a no overhead Future wrapper that changes the default Future map/flatMap from do-this-then-that to combine-all-and-fail-if-any-fail. Usage:
def func1 : Future[Int] = Future { println("f1!");throw new RuntimeException; 1 }
def func2 : Future[String] = Future { Thread.sleep(2000);println("f2!");"f2" }
def func3 : Future[Double] = Future { Thread.sleep(2000);println("f3!");42.0 }
val f : Future[(Int,String,Double)] = {
for {
f1 <- func1.concurrently
f2 <- func2.concurrently
f3 <- func3.concurrently
} yield for {
v1 <- f1
v2 <- f2
v3 <- f3
} yield (v1,v2,v3)
}.future
f.onFailure { case t => println("future failed $t") }
In the example above, f1,f2 and f3 will run concurrently and if any fail in any order the future of the tuple will fail immediately.
You might want to checkout Twitter's Future API. Notably the Future.collect method. It does exactly what you want: https://twitter.github.io/scala_school/finagle.html
The source code Future.scala is available here:
https://github.com/twitter/util/blob/master/util-core/src/main/scala/com/twitter/util/Future.scala
You can use this:
val l = List(1, 6, 8)
val f = l.map{
i => future {
println("future " +i)
Thread.sleep(i* 1000)
if (i == 12)
throw new Exception("6 is not legal.")
i
}
}
val f1 = Future.sequence(f)
f1 onSuccess{
case l => {
logInfo("onSuccess")
l.foreach(i => {
logInfo("h : " + i)
})
}
}
f1 onFailure{
case l => {
logInfo("onFailure")
}