Semergence

• Binary marble adding machine
  A six bit adding machine, storing state with marbles.
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• TrimJunction
  A javascript clone of Ruby on Rails.
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As I continue to tinker with Scala, I was wondering about the performance differences between an Array and List. This post will detail what I’ve found, but as always YMMV and I could be doing it all wrong. If there’s a better (in this case, better == faster) way to do this in Scala, please let me know.

My application performs a lot of collection iteration as it combines the values of two collections into a new collection by addition. For instance, I need to combine [1,2] and [3,4] into [4,6]. I wanted to find out if the collections should be an Array or List.

Intuition tells me that the Array will perform better, but this is Scala, and Lists reign supreme. So we’ll go head to head.

For each test, I wanted to write a function that combined the two collections using tail recursion.

Test One - Two Lists Into a Third

First up, I am adding two lists together while forming a third. One problem here is, due to the way the algorithm is structured, the resulting list is built backwards. So there’s a call to reverse at the end. (Question: How to rewrite this using normal List methods such as :: without having to call reverse at the end?)

  def add(x: List[Long], y: List[Long],
             agg: List[Long]): List[Long] = x match {
    case Nil => agg.reverse
    case x1 :: xs => y match {
      case y1 :: ys => add(xs, ys,  x1 + y1 :: agg)
    }
  }

To call it:

add(List(1,2), List(3,4), Nil)

Test Two - Two Arrays Into a List

Next up, I add two Arrays into a List. The guess here is that accessing the arrays by index will help speed it up.

  def add2(x: Array[Long], y: Array[Long], agg: List[Long],
               counter: Int): List[Long] = {
    if (counter == 0) agg
    else add2(x, y, x(counter-1) + y(counter-1) :: agg, counter-1)
  }

To call it:

add2(Array(1,2), Array(3,4), Nil, 2)

Test Three - Two Arrays Into a Third Array

This should be the fastest.

  def add3(x: Array[Long], y: Array[Long], agg: Array[Long],
               i: Int): Array[Long] = {
    if (i == x.length) agg
    else {
      agg(i) = x(i) + y(i)
      add3(x, y, agg, i+1)
    }
  }

To call it:

add3(Array(1,2), Array(3,4), new Array(2), 0)

Methodology

I ran each function 1 million times and captured the times with System.currentTimeMillis. I ran the entire test suite five times to generate an average. I am running Scala 2.5.1 on Java 1.6 on Windows XP. I have a Pentium 4 2.8GHz with 2GB RAM.

Results

The results are in, and sure enough, on average, the third option (pure Arrays) is the fastest.

* Test 1 - 1172 ms
* Test 2 - 781 ms
* Test 3 - 687 ms

So, for my purposes, using Arrays results in faster execution. However, if you are looking to do traditional functional programming, you should write your methods to create zero side effects. Using Arrays like this seems anti-functional programming.

• The Sarcastic Gamer: Twisted Trailers: MS Surface
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Now, this has to have a built-in somewhere in Scala, because it just seems too common. So, how to convert an Array to a List in Scala?

Why do I need this? I needed to drop to Java for some functionality, which in this case returns an Array. I wanted to get that Array into a List to practice my functional programming skillz.

**Update**: I figured out how to convert Arrays to Lists the Scala way. Turns out it’s a piece of cake.

val myList = List.fromArray(Array(”one”, “two”, “three”))

or

val myList = Array(”one”,”two”,”three”).elements.toList

The call to elements returns an Iterator, and from there you can convert to a List via toList. Nice.

Because my first version wasn’t actually tail recursive, what follows is a true tail recursive solution, if I were to implement this by hand. The above, built in mechanism is much better, though.

object ArrayUtil {
  def toList[a](array: Array[a]): List[a] = {
    def convert(arr: Array[a], aggregator: List[a]): List[a] = {
      if (arr == null || arr.length == 0) aggregator
      else convert(arr.slice(0, arr.length-1), arr(arr.length-1) :: aggregator)
    }
	convert(array, Nil)
  }
}

The above code is interesting because it demonstrates a nested function. The convert function is nested inside toList. Scala encourages the decomposition of your problem into smaller and smaller functions.

*What follows is my original attempt.* Left here for a historical, “what not to do” perspective.

Here’s my implementation of it, but if you know if there’s a built-in function already implemented, please let me know.

object ArrayUtil {
  def toList[a](array: Array[a]): List[a] = {
    if (array == null || array.length == 0) Nil
    else if (array.length == 1) List(array(0))
    else array(0) :: toList(array.slice(1, array.length))
  }
}

To quickly explain this, an object in Scala is a singleton instance of its class. The method toList is parameterized with type a. This is similar to generics in Java. Lastly, the :: operator (pronouned cons in Scala) creates a new List from a single item (the head, on the left) and another List (the tail, on the right). Oh, and Nil represents an empty List.

As I continue to explore Scala, I wondered just how many (react based) actors I could create in a single JVM. The answer, apparently, is a lot.

Before I canceled it, the count was up to 13,500,000 actors. This is on an old Centrino laptop running the Sun 1.6 JVM. I did have to turn up the memory limit a bit, but I never saw memory go above 20MB. Also, I wasn’t doing anything inside the Actors.

Still, that’s enough for me to not have to worry about it.

Scala: It’s as if Java and Erlang had a baby. Fun stuff.

• Mapping Between Java and Scala
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• First Steps to Scala
  In this article, you’ll follow twelve steps that are designed to help you understand and gain some basic skills in the Scala programming language.
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the future belongs to those who take the present for granted.

• Chinese Room Argument [Internet Encyclopedia of Philosophy]
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RESTify DayTrader, in which Joe Gregorio converts a real world J2EE application’s interface into a REST interface.

Perfect example of how to do REST with real life requirements.