假设你需要有一个整数列表/数组,你需要频繁迭代,我的意思是非常频繁。原因可能各不相同,但可以说这是在一个大容量处理的最内部循环的核心。

通常情况下,人们会选择使用列表(List),因为它们在大小上具有灵活性。最重要的是,msdn文档声称列表在内部使用数组,并且应该执行得一样快(快速查看Reflector证实了这一点)。尽管如此,还是有一些开销。

有人测量过吗?在一个列表中迭代6M次是否与数组相同?


当前回答

这是一个使用字典IEnumerable的例子:

using System;
using System.Collections.Generic;
using System.Diagnostics;
using System.Linq;

static class Program
{
    static void Main()
    {
        List<int> list = new List<int>(6000000);

        for (int i = 0; i < 6000000; i++)
        {
                list.Add(i);
        }
        Console.WriteLine("Count: {0}", list.Count);

        int[] arr = list.ToArray();
        IEnumerable<int> Ienumerable = list.ToArray();
        Dictionary<int, bool> dict = list.ToDictionary(x => x, y => true);

        int chk = 0;
        Stopwatch watch = Stopwatch.StartNew();
        for (int rpt = 0; rpt < 100; rpt++)
        {
            int len = list.Count;
            for (int i = 0; i < len; i++)
            {
                chk += list[i];
            }
        }
        watch.Stop();
        Console.WriteLine("List/for: {0}ms ({1})", watch.ElapsedMilliseconds, chk);

        chk = 0;
        watch = Stopwatch.StartNew();
        for (int rpt = 0; rpt < 100; rpt++)
        {
            for (int i = 0; i < arr.Length; i++)
            {
                chk += arr[i];
            }
        }
        watch.Stop();
        Console.WriteLine("Array/for: {0}ms ({1})", watch.ElapsedMilliseconds, chk);

        chk = 0;
        watch = Stopwatch.StartNew();
        for (int rpt = 0; rpt < 100; rpt++)
        {
            foreach (int i in Ienumerable)
            {
                chk += i;
            }
        }

        Console.WriteLine("Ienumerable/for: {0}ms ({1})", watch.ElapsedMilliseconds, chk);

        chk = 0;
        watch = Stopwatch.StartNew();
        for (int rpt = 0; rpt < 100; rpt++)
        {
            foreach (int i in dict.Keys)
            {
                chk += i;
            }
        }

        Console.WriteLine("Dict/for: {0}ms ({1})", watch.ElapsedMilliseconds, chk);


        chk = 0;
        watch = Stopwatch.StartNew();
        for (int rpt = 0; rpt < 100; rpt++)
        {
            foreach (int i in list)
            {
                chk += i;
            }
        }

        watch.Stop();
        Console.WriteLine("List/foreach: {0}ms ({1})", watch.ElapsedMilliseconds, chk);

        chk = 0;
        watch = Stopwatch.StartNew();
        for (int rpt = 0; rpt < 100; rpt++)
        {
            foreach (int i in arr)
            {
                chk += i;
            }
        }
        watch.Stop();
        Console.WriteLine("Array/foreach: {0}ms ({1})", watch.ElapsedMilliseconds, chk);



        chk = 0;
        watch = Stopwatch.StartNew();
        for (int rpt = 0; rpt < 100; rpt++)
        {
            foreach (int i in Ienumerable)
            {
                chk += i;
            }
        }
        watch.Stop();
        Console.WriteLine("Ienumerable/foreach: {0}ms ({1})", watch.ElapsedMilliseconds, chk);

        chk = 0;
        watch = Stopwatch.StartNew();
        for (int rpt = 0; rpt < 100; rpt++)
        {
            foreach (int i in dict.Keys)
            {
                chk += i;
            }
        }
        watch.Stop();
        Console.WriteLine("Dict/foreach: {0}ms ({1})", watch.ElapsedMilliseconds, chk);

        Console.ReadLine();
    }
}

其他回答

很容易测量…

在少量的紧循环处理代码中,我知道长度是固定的,我使用数组来进行额外的微小优化;如果你使用索引器/ for表单,数组可以稍微快一点——但是IIRC认为这取决于数组中数据的类型。但除非你需要进行微观优化,否则尽量保持简单,使用List<T>等。

当然,这只适用于读取所有数据的情况;对于基于键的查找,字典会更快。

下面是我使用“int”的结果(第二个数字是一个校验和,以验证它们都做了相同的工作):

(修改bug)

List/for: 1971ms (589725196)
Array/for: 1864ms (589725196)
List/foreach: 3054ms (589725196)
Array/foreach: 1860ms (589725196)

基于试验台:

using System;
using System.Collections.Generic;
using System.Diagnostics;
static class Program
{
    static void Main()
    {
        List<int> list = new List<int>(6000000);
        Random rand = new Random(12345);
        for (int i = 0; i < 6000000; i++)
        {
            list.Add(rand.Next(5000));
        }
        int[] arr = list.ToArray();

        int chk = 0;
        Stopwatch watch = Stopwatch.StartNew();
        for (int rpt = 0; rpt < 100; rpt++)
        {
            int len = list.Count;
            for (int i = 0; i < len; i++)
            {
                chk += list[i];
            }
        }
        watch.Stop();
        Console.WriteLine("List/for: {0}ms ({1})", watch.ElapsedMilliseconds, chk);

        chk = 0;
        watch = Stopwatch.StartNew();
        for (int rpt = 0; rpt < 100; rpt++)
        {
            for (int i = 0; i < arr.Length; i++)
            {
                chk += arr[i];
            }
        }
        watch.Stop();
        Console.WriteLine("Array/for: {0}ms ({1})", watch.ElapsedMilliseconds, chk);

        chk = 0;
        watch = Stopwatch.StartNew();
        for (int rpt = 0; rpt < 100; rpt++)
        {
            foreach (int i in list)
            {
                chk += i;
            }
        }
        watch.Stop();
        Console.WriteLine("List/foreach: {0}ms ({1})", watch.ElapsedMilliseconds, chk);

        chk = 0;
        watch = Stopwatch.StartNew();
        for (int rpt = 0; rpt < 100; rpt++)
        {
            foreach (int i in arr)
            {
                chk += i;
            }
        }
        watch.Stop();
        Console.WriteLine("Array/foreach: {0}ms ({1})", watch.ElapsedMilliseconds, chk);

        Console.ReadLine();
    }
}
static long[] longs = new long[500000];
static long[] longs2 = {};
static List<long> listLongs = new List<long> { };
static void Main(string[] args)
{
    Console.CursorVisible = false;
    Stopwatch time = new Stopwatch();

    time.Start();
    for (int f = 50000000; f < 50255000; f++)
    {
        listLongs.Add(f);
    }

    //List  Time: 1ms    Count : 255000
    Console.WriteLine("List Time: " + time.ElapsedMilliseconds + " | Count: " + listLongs.Count());

    time.Restart();
    time.Start();
    for (long i = 1; i < 500000; i++)
    {
        longs[i] = i * 200;
    }

    //Array Time: 2ms Length: 500000 (Unrealistic Data)
    Console.WriteLine("Array Time: " + time.ElapsedMilliseconds + " | Length: " + longs.Length);

    time.Restart();
    time.Start();
    for (int i = 50000000; i < 50055000; i++)
    {
        longs2 = longs2.Append(i).ToArray();
    }

    //Array Time: 17950ms Length: 55000
    Console.WriteLine("Array Append Time: " + time.ElapsedMilliseconds + " | Length: " + longs2.Length);

    Console.ReadLine();
}
Type Time Len
Array 2ms 500000
List 1ms 255000
Array Append 17950ms 55000

如果您计划不断地向数组中添加少量数据,那么list更快

这实际上取决于你将如何使用数组。

在一些简短的测试中,我发现两者的结合在我所谓的合理密集数学中会更好:

类型:<双[]>列表

时间:00:00:05.1861300

类型:列表<列表<double>>

时间:00:00:05.7941351

类型:double[行*列]

时间:00:00:06.0547118

运行代码:

int rows = 10000;
int columns = 10000;

IMatrix Matrix = new IMatrix(rows, columns);

Stopwatch stopwatch = new Stopwatch();
stopwatch.Start();


for (int r = 0; r < Matrix.Rows; r++)
    for (int c = 0; c < Matrix.Columns; c++)
        Matrix[r, c] = Math.E;

for (int r = 0; r < Matrix.Rows; r++)
    for (int c = 0; c < Matrix.Columns; c++)
        Matrix[r, c] *= -Math.Log(Math.E);


stopwatch.Stop();
TimeSpan ts = stopwatch.Elapsed;

Console.WriteLine(ts.ToString());

我真希望我们有一些顶尖的硬件加速矩阵类,就像。net团队用system . numbers . vectors类做的那样!

c#可能是最好的ML语言,只要在这方面多做一些工作!

我担心在其他答案中发布的基准测试仍然会为编译器留下优化,消除或合并循环的空间,所以我写了一个:

使用不可预测的输入(随机) 运行计算结果并将结果打印到控制台 每次重复修改输入数据

结果是,直接数组的性能比访问封装在IList中的数组要好250%:

10亿次数组访问:4000毫秒 10亿次列表访问:10000毫秒 1亿个数组访问:350毫秒 1亿次列表访问:1000毫秒

代码如下:

static void Main(string[] args) {
  const int TestPointCount = 1000000;
  const int RepetitionCount = 1000;

  Stopwatch arrayTimer = new Stopwatch();
  Stopwatch listTimer = new Stopwatch();

  Point2[] points = new Point2[TestPointCount];
  var random = new Random();
  for (int index = 0; index < TestPointCount; ++index) {
    points[index].X = random.NextDouble();
    points[index].Y = random.NextDouble();
  }

  for (int repetition = 0; repetition <= RepetitionCount; ++repetition) {
    if (repetition > 0) { // first repetition is for cache warmup
      arrayTimer.Start();
    }
    doWorkOnArray(points);
    if (repetition > 0) { // first repetition is for cache warmup
      arrayTimer.Stop();
    }

    if (repetition > 0) { // first repetition is for cache warmup
      listTimer.Start();
    }
    doWorkOnList(points);
    if (repetition > 0) { // first repetition is for cache warmup
      listTimer.Stop();
    }
  }

  Console.WriteLine("Ignore this: " + points[0].X + points[0].Y);
  Console.WriteLine(
    string.Format(
      "{0} accesses on array took {1} ms",
      RepetitionCount * TestPointCount, arrayTimer.ElapsedMilliseconds
    )
  );
  Console.WriteLine(
    string.Format(
      "{0} accesses on list took {1} ms",
      RepetitionCount * TestPointCount, listTimer.ElapsedMilliseconds
    )
  );

}

private static void doWorkOnArray(Point2[] points) {
  var random = new Random();

  int pointCount = points.Length;

  Point2 accumulated = Point2.Zero;
  for (int index = 0; index < pointCount; ++index) {
    accumulated.X += points[index].X;
    accumulated.Y += points[index].Y;
  }

  accumulated /= pointCount;

  // make use of the result somewhere so the optimizer can't eliminate the loop
  // also modify the input collection so the optimizer can merge the repetition loop
  points[random.Next(0, pointCount)] = accumulated;
}

private static void doWorkOnList(IList<Point2> points) {
  var random = new Random();

  int pointCount = points.Count;

  Point2 accumulated = Point2.Zero;
  for (int index = 0; index < pointCount; ++index) {
    accumulated.X += points[index].X;
    accumulated.Y += points[index].Y;
  }

  accumulated /= pointCount;

  // make use of the result somewhere so the optimizer can't eliminate the loop
  // also modify the input collection so the optimizer can merge the repetition loop
  points[random.Next(0, pointCount)] = accumulated;
}

我想表演会很相似。 在使用List和Array时所涉及的开销是,恕我直言,当您向列表中添加项时,当列表必须增加它在内部使用的数组的大小时,当数组的容量达到时。

假设你有一个容量为10的List,那么一旦你想添加第11个元素,List就会增加它的容量。 可以通过将列表的Capacity初始化为它将容纳的项数来减少性能影响。

但是,为了弄清楚遍历List是否与遍历数组一样快,为什么不对其进行基准测试呢?

int numberOfElements = 6000000;

List<int> theList = new List<int> (numberOfElements);
int[] theArray = new int[numberOfElements];

for( int i = 0; i < numberOfElements; i++ )
{
    theList.Add (i);
    theArray[i] = i;
}

Stopwatch chrono = new Stopwatch ();

chrono.Start ();

int j;

 for( int i = 0; i < numberOfElements; i++ )
 {
     j = theList[i];
 }

 chrono.Stop ();
 Console.WriteLine (String.Format("iterating the List took {0} msec", chrono.ElapsedMilliseconds));

 chrono.Reset();

 chrono.Start();

 for( int i = 0; i < numberOfElements; i++ )
 {
     j = theArray[i];
 }

 chrono.Stop ();
 Console.WriteLine (String.Format("iterating the array took {0} msec", chrono.ElapsedMilliseconds));

 Console.ReadLine();

在我的系统上;遍历数组需要33msec;遍历列表花费了66msec。

说实话,我没想到变化会这么大。 所以,我把我的迭代放在一个循环中:现在,我执行了1000次迭代。 结果如下:

迭代List需要67146毫秒 迭代数组需要40821毫秒

现在,变化不再那么大了,但仍然……

因此,我已经启动了。net Reflector, List类的索引器的getter看起来像这样:

public T get_Item(int index)
{
    if (index >= this._size)
    {
        ThrowHelper.ThrowArgumentOutOfRangeException();
    }
    return this._items[index];
}

如您所见,当您使用List的索引器时,List会执行一次检查,检查您是否没有超出内部数组的边界。这种额外的检查是有成本的。