In the following situation
trait T {
@tailrec
def consume[A](as: Stream[A]): Unit = {
if (as.isEmpty) ()
else consume(as.tail)
}
}
object O extends T
calling O.consume(Range(1, N).toStream)
with N
big enough, the program will run out of memory, or at least will consume O(N) instead of the needed O(1).
The tail-recursive method is generated for the trait. The method entry in the extender of the trait (here O
) forwards the call to the method of the trait, but while doing so, it keeps a reference to the head of the Stream.
Thus the method is tail-recursive, but memory still can't be released. Remedy: Don't define Stream functions in traits, just directly in objects.
An alternative is scalaz's EphemeralStream
, which holds weak references to the stream head and tail, and recomputes them on demand.
There is a simple workaround. Just wrap your tail recursive stream consumer in another function that receives the stream via a by-name parameter:
import scala.annotation.tailrec
trait T {
def consume[A](as: => Stream[A]): Unit = {
@tailrec
def loop[A](as: Stream[A]): Unit = {
if (as.isEmpty) ()
else loop(as.tail)
}
loop(as)
}
}
object O extends T {
def main(args: Array[String]): Unit =
O.consume(Range(1, 1000000000).toStream)
}
The forwarder method will hold a reference to a function computing an expression the result of which is a stream:
public final class O$ implements T {
public static final MODULE$;
// This is the forwarder:
public <A> void consume(Function0<Stream<A>> as) {
T.class.consume(this, as);
}
. . .
public void main(String[] args) {
consume(new AbstractFunction0() {
public final Stream<Object> apply() {
return package..MODULE$.Range().apply(1, 1000000000).toStream();
}
});
}
}
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