Scala Saturday – The reduce Method

If you have a collection of numbers that you want to sum or multiply together, Scala’s collection classes all define both a sum operation and a product operation:

ScalaDocs for Scala Collection sum and product Methods

Array	sum	product
List	sum	product
Seq	sum	product
Set	sum	product

But what if, for some reason, you want to implement sum or product yourself? Well, it turns out that sum and product are both just special cases of a more general operation that the collection modules also define: reduce. The reduce operation takes all the elements in a collection and combines them in some way to produce a single value. It uses a binary operation to combine the first two values. Then it takes the result of that first combination and combines it with the next element in the collection, and then the next, and so on through the end of the collection.

Here’s an illustration of how to use reduce to implement a product operation:

The code looks like this:

val product = List(2,5,3,6) reduce {
  (x,y) => x * y
}
// product: Int = 180

You can be even more succinct by employing the underscore, Scala’s shorthand for the lambda’s input arguments:

val product = List(2,5,3,6).reduce(_*_)
// product: Int = 180

Another special case of reduce is mkString, e.g., List.mkString—also known as a join operation—which allows you to concatenate a sequence of values together into a string with a separator between each value. Here’s how it works:

See how similar it is to the product operation above? If you should want to implement mkString yourself, you could use reduce like this:

val joined =
  List("do","mi","sol","do") reduce {
    (x,y) => x + "-" + y
  }
// joined: String = do-mi-sol-do

Or again, with the shorthand:

val joined =
  List("do","mi","sol","do").
    reduce(_ + "-" + _)
// joined: String = do-mi-sol-do

Here is the documentation on reduce in each of the collection classes:

• Array.reduce
• List.reduce
• Seq.reduce
• Set.reduce

Now a few of caveats about reduce:

• You cannot use reduce on an empty collection. You will get an exception if you do, so make sure you check to make sure your collection is not empty before you pass it to reduce. (Scala provides an alternative, reduceOption, that does not throw an exception, but represents the result as an Option.)

• The result of a reduce operation is always the same type as the elements in the collection. In other words, you can only reduce a collection of type A to a value of type A. You cannot reduce a collection of type A to a value of type B.

• Finally, order matters if the order of your binary operation matters. In other words, with addition and multiplication, order does not matter. That is, a + b is the same as b + a. (Mathematicians say that such a function is commutative.) But with something like subtraction, order does matter. In other words, a − b does not necessarily produce the same result as b − a. So make sure that your binary operation applies the reduction to its operands in the correct order.

Having noted these caveats, next week, we will cover the fold operation. It operates almost the same way as reduce in that it walks a collection, applying a binary operation to each element. The fold operation cannot help us with that last point—order still matters—but it can handle an empty collection and, if necessary, produce a result that is of a type different from the type of the source collection’s elements.