Scala's List has a Secret

| 3 minutes | Comments

OOP couples the “data” with the methods operating on it, and that’s considered bad in FP circles, because supposedly data outlives the functions operating on it. Also in static FP circles, dumb data structures are reusable, so it’s a good idea to make them generic, and add restrictions on the functions themselves.

Few data structures could be simpler than an immutable List definition, right? At least as far as recursive data structures go 🙂 For the standard List you’d expect the following:

sealed abstract class List[+A]

final case class :: [+A](head: A, tail: List[A])
  extends List[A]

case object Nil extends List[Nothing]

Oh boy, I’ve got news for you — this is the actual definition from Scala’s standard library:

sealed abstract class List[+A]

final case class :: [+A](
  head: A, 
  // mutable var 😱
  private[scala] var next: List[A @uncheckedVariance]) 
  extends List[A] {
  // 😱 memory barrier

case object Nil extends List[Nothing]

Yikes, that private next value is a var. They added it as a var such that ListBuffer can build a list more efficiently, because an immutable List is in essence a Stack, so to build a new list from an existing one, you’d need to do an O(n) reversal at the end.

With the pure definition, we’d build List values like this:

def map[A, B](self: List[A])(f: A => B): List[B] = {
  var buffer = List.empty[B]
  for (elem <- self) { buffer = f(elem) :: buffer  }
  // Extra O(n) tax if that list would be pure, no way around it
  // (legend has it that this is a computer science issue related to stacks)

But with ListBuffer, due to making use of that var:

def map[A, B](self: List[A])(f: A => B): List[B] = {
  val buffer = ListBuffer.empty[B]
  for (elem <- self) { buffer += f(elem)  }
  // O(1), no inefficiency

Contrary to popular opinion, this means List does not benefit from final (val in Scala) visibility guarantees by the Java Memory Model. So it might have visibility issues in a multi-threaded context (e.g. you might end up with a tail being null when it shouldn’t be). Which is probably why we see this in both the class constructor and in ListBuffer#toList:

override def toList: List[A] = {
  aliased = nonEmpty
  // We've accumulated a number of mutations to `List.tail` by this stage.
  // Make sure they are visible to threads that the client of this ListBuffer might be about
  // to share this List with.

Yikes, they are adding manual memory barriers everywhere 😲 I guess it beats an added O(n) penalty when building new lists. But this goes to show the necessity of coupling data structures with the methods operating on them.

FP developers don’t care about resources, because of the expectation that resources should be handled by the runtime, but sometimes that isn’t possible or optimal — even dumb data structures are resources and sometimes need special resource management, for efficiency reasons. In which case coupling the data with the methods operating on it is healthy 😉

I don't like manual memory barriers BTW. They are expensive and a design based on proper acquisition and release (reads and writes in volatiles) would be better, as it lets the JVM do its magic. Don't copy their design here without knowing what you're doing.

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Tags: FP | Multithreading | Scala