I've read the docs about map
and flatMap
and I understand that flatMap
is used for an operation that accepts a Future
parameter and returns another Future
. What I don't fully understand is why I would want to do this. Take this example:
I understand that I would want to use a future to download the file but I have have two options re processing it:
val downloadFuture = Future {/* downloadFile */}
val processFuture = downloadFuture map {/* processFile */}
processFuture onSuccess { case r => renderResult(r) }
or
val downloadFuture = Future {/* download the file */}
val processFuture = downloadFuture flatMap { Future {/* processFile */} }
processFuture onSuccess { case r => renderResult(r) }
By adding debug statements (Thread.currentThread().getId
) I see that in both cases download, process
and render
occur in the same thread (using ExecutionContext.Implicits.global
).
Would I use flatMap
simply to decouple downloadFile
and processFile
and ensure that processFile
always runs in a Future
even if it was not mapped from downloadFile
?
If you have a future, let's say, Future[HttpResponse]
, and you want to specify what to do with that result when it is ready, such as write the body to a file, you may do something like responseF.map(response => write(response.body)
. However if write
is also an asynchronous method which returns a future, this map
call will return a type like Future[Future[Result]]
.
In the following code:
import scala.concurrent.Future
import scala.concurrent.ExecutionContext.Implicits.global
val numF = Future{ 3 }
val stringF = numF.map(n => Future(n.toString))
val flatStringF = numF.flatMap(n => Future(n.toString))
stringF
is of type Future[Future[String]]
while flatStringF
is of type Future[String]
. Most would agree, the second is more useful. Flat Map is therefore useful for composing multiple futures together.
When you use for
comprehensions with Futures, under the hood flatMap
is being used together with map
.
import scala.concurrent.{Await, Future}
import scala.concurrent.ExecutionContext.Implicits.global
import scala.concurrent.duration._
val threeF = Future(3)
val fourF = Future(4)
val fiveF = Future(5)
val resultF = for{
three <- threeF
four <- fourF
five <- fiveF
}yield{
three * four * five
}
Await.result(resultF, 3 seconds)
This code will yield 60.
Under the hood, scala translates this to
val resultF = threeF.flatMap(three => fourF.flatMap(four => fiveF.map(five => three * four * five)))