Suppose I\'ve got a function foo
that performs asynchronous computation and returns a Future
:
def foo(x: Int)(implicit ec: Executio
I'd probably do something like this:
final case class ExceptionsList(es: List[Throwable]) extends Throwable
def retry[T](n: Int, expr: => Future[T], exs: List[Throwable] = Nil)(implicit ec: ExecutionContext): Future[T] =
Future.unit.flatMap(_ => expr).recoverWith {
case e if n > 0 => retry(n - 1, expr, e :: exs)
case e => Future.failed(new ExceptionsList(e :: exs))
}
expr
is call-by-name since it itself could throw an exception rather than returning a failed Future. I keep the accumulated exceptions in a list, but I guess that's a taste-thing.
You can use Future's transformWith
and a little recursion to do the retrying. Using transformWith
you can pattern match on the success or failure of your future. In the success case, you just return the result of the Success
and you're done since you don't care about intermediate failures. On the failure case you make a recursive call where you decrement the retry count and append the exception to a list in your parameter list to keep track of all your failures. If n
is ever zero, you've exhausted your retries. In this case you just create a new instance of ExceptionsList
and fail the future.
The below example demonstrates the failure case when all futures throw exceptions. You can call retryFoo(3)
and you will get a failed future with three exceptions.
case class ExceptionsList(es: List[Throwable]) extends Exception
def retryFoo(n: Int, exceptions: List[Throwable] = List())(implicit ec: ExecutionContext): Future[Int] = {
if (n == 0) {
Future.failed(ExceptionsList(exceptions))
} else {
Future {
throw new Exception("fail!")
}.transformWith {
case Success(result) => Future(result)
case Failure(ex) =>
println("Retrying!")
retryFoo(n - 1, exceptions :+ ex)
}
}
}