Scala - calculate average of SomeObj.double in a List[SomeObj] - scala

Question

I'm on my second evening of scala, and I'm resisting the urge to write things in scala how I used to do them in java and trying to learn all of the idioms. In this case I'm looking to just compute an average using such things as closures, mapping, and perhaps list comprehension. Irrespective of whether this is the best way to compute an average, I just want to know how to do these things in scala for learning purposes only
Here's an example: the average method below is left pretty much unimplemented. I've got a couple of other methods for looking up the rating an individual userid gave that uses the find method of TraversableLike (I think), but nothing more that is scala specific, really. How would I compute an average given a List[RatingEvent] where RatingEvent.rating is a double value that I'd to compute an average of across all values of that List in a scala-like manner?.
package com.brinksys.liftnex.model
class Movie(val id : Int, val ratingEvents : List[RatingEvent]) {
def getRatingByUser(userId : Int) : Int = {
return getRatingEventByUserId(userId).rating
}
def getRatingEventByUserId(userId : Int) : RatingEvent = {
var result = ratingEvents find {e => e.userId == userId }
return result.get
}
def average() : Double = {
/*
fill in the blanks where an average of all ratingEvent.rating values is expected
*/
return 3.8
}
}
How would a seasoned scala pro fill in that method and use the features of scala to make it as concise as possible? I know how I would do it in java, which is what I want to avoid.
If I were doing it in python, I assume the most pythonic way would be:
sum([re.rating. for re in ratingEvents]) / len(ratingEvents)
or if I were forcing myself to use a closure (which is something I at least want to learn in scala):
reduce(lambda x, y : x + y, [re.rating for re in ratingEvents]) / len(ratingEvents)
It's the usage of these types of things I want to learn in scala.
Your suggestions? Any pointers to good tutorials/reference material relevant to this are welcome :D

Answer 1

If you're going to be doing math on things, using List is not always the fastest way to go because List has no idea how long it is--so ratingEvents.length takes time proportional to the length. (Not very much time, granted, but it does have to traverse the whole list to tell.) But if you're mostly manipulating data structures and only occasionally need to compute a sum or whatever, so it's not the time-critical core of your code, then using List is dandy.
Anyway, the canonical way to do it would be with a fold to compute the sum:
(0.0 /: ratingEvents){_ + _.rating} / ratingEvents.length
// Equivalently, though more verbosely:
// ratingEvents.foldLeft(0.0)(_ + _.rating) / ratingEvents.length
or by mapping and then summing (2.8 only):
ratingEvents.map(_.rating).sum / ratingEvents.length
For more information on maps and folds, see this question on that topic.

Answer 2

You might calculate sum and length in one go, but I doubt that this helps except for very long lists. It would look like this:
val (s,l) = ratingEvents.foldLeft((0.0, 0))((t, r)=>(t._1 + r.rating, t._2 + 1))
val avg = s / l
I think for this example Rex' solution is much better, but in other use cases the "fold-over-tuple-trick" can be essential.

Answer 3

Since mean and other descriptive statistics like standard deviation or median are needed in different contexts, you could also use a small reusable implicit helper class to allow for more streamlined chained commands:
implicit class ImplDoubleVecUtils(values: Seq[Double]) {
def mean = values.sum / values.length
}
val meanRating = ratingEvents.map(_.rating).mean
It even seems to be possible to write this in a generic fashion for all number types.

Answer 4

Tail recursive solution can achieve both single traversal and avoid high memory allocation rates
def tailrec(input: List[RatingEvent]): Double = {
#annotation.tailrec def go(next: List[RatingEvent], sum: Double, count: Int): Double = {
next match {
case Nil => sum / count
case h :: t => go(t, sum + h.rating, count + 1)
}
}
go(input, 0.0, 0)
}
Here are jmh measurements of approaches from above answers on a list of million elements:
[info] Benchmark Mode Score Units
[info] Mean.foldLeft avgt 0.007 s/op
[info] Mean.foldLeft:·gc.alloc.rate avgt 4217.549 MB/sec
[info] Mean.foldLeft:·gc.alloc.rate.norm avgt 32000064.281 B/op
...
[info] Mean.mapAndSum avgt 0.039 s/op
[info] Mean.mapAndSum:·gc.alloc.rate avgt 1690.077 MB/sec
[info] Mean.mapAndSum:·gc.alloc.rate.norm avgt 72000009.575 B/op
...
[info] Mean.tailrec avgt 0.004 s/op
[info] Mean.tailrec:·gc.alloc.rate avgt ≈ 10⁻⁴ MB/sec
[info] Mean.tailrec:·gc.alloc.rate.norm avgt 0.196 B/op

Answer 5

I can suggest 2 ways:
def average(x: Array[Double]): Double = x.foldLeft(0.0)(_ + _) / x.length
def average(x: Array[Double]): Double = x.sum / x.length
Both are fine, but in 1 case when using fold you can not only make "+" operation, but as well replace it with other (- or * for example)