在c# / VB.NET/。哪个循环运行得更快,for还是foreach?
自从很久以前我读到for循环比foreach循环工作得快,我就认为它适用于所有集合、泛型集合、所有数组等。
我搜索了谷歌,找到了几篇文章,但大多数都是不确定的(阅读文章评论),而且是开放式的。
理想的情况是列出每种情况以及最佳解决方案。
例如(这只是一个例子):
用于迭代1000+的数组
字符串- for比foreach好
对于迭代IList(非泛型)字符串- foreach更好
比
在网上找到了一些相同的参考资料:
由Emmanuel Schanzer撰写的原创文章
CodeProject FOREACH Vs. FOR
博客——去博客还是不去博客,这是个问题
ASP。NET论坛- NET 1.1 c# for vs foreach
(编辑)
除了可读性之外,我对事实和数据真的很感兴趣。在某些应用中,最后一英里的性能优化确实很重要。
我发现foreach循环迭代列表更快。下面是我的测试结果。在下面的代码中,我分别迭代一个大小为100、10000和100000的数组,使用for和foreach循环来测量时间。
private static void MeasureTime()
{
var array = new int[10000];
var list = array.ToList();
Console.WriteLine("Array size: {0}", array.Length);
Console.WriteLine("Array For loop ......");
var stopWatch = Stopwatch.StartNew();
for (int i = 0; i < array.Length; i++)
{
Thread.Sleep(1);
}
stopWatch.Stop();
Console.WriteLine("Time take to run the for loop is {0} millisecond", stopWatch.ElapsedMilliseconds);
Console.WriteLine(" ");
Console.WriteLine("Array Foreach loop ......");
var stopWatch1 = Stopwatch.StartNew();
foreach (var item in array)
{
Thread.Sleep(1);
}
stopWatch1.Stop();
Console.WriteLine("Time take to run the foreach loop is {0} millisecond", stopWatch1.ElapsedMilliseconds);
Console.WriteLine(" ");
Console.WriteLine("List For loop ......");
var stopWatch2 = Stopwatch.StartNew();
for (int i = 0; i < list.Count; i++)
{
Thread.Sleep(1);
}
stopWatch2.Stop();
Console.WriteLine("Time take to run the for loop is {0} millisecond", stopWatch2.ElapsedMilliseconds);
Console.WriteLine(" ");
Console.WriteLine("List Foreach loop ......");
var stopWatch3 = Stopwatch.StartNew();
foreach (var item in list)
{
Thread.Sleep(1);
}
stopWatch3.Stop();
Console.WriteLine("Time take to run the foreach loop is {0} millisecond", stopWatch3.ElapsedMilliseconds);
}
更新
在@jgauffin建议后,我使用了@johnskeet代码,发现使用数组的for循环比下面的更快,
Foreach循环与数组。
For带列表的循环。
Foreach循环与列表。
请看下面我的测试结果和代码,
private static void MeasureNewTime()
{
var data = new double[Size];
var rng = new Random();
for (int i = 0; i < data.Length; i++)
{
data[i] = rng.NextDouble();
}
Console.WriteLine("Lenght of array: {0}", data.Length);
Console.WriteLine("No. of iteration: {0}", Iterations);
Console.WriteLine(" ");
double correctSum = data.Sum();
Stopwatch sw = Stopwatch.StartNew();
for (int i = 0; i < Iterations; i++)
{
double sum = 0;
for (int j = 0; j < data.Length; j++)
{
sum += data[j];
}
if (Math.Abs(sum - correctSum) > 0.1)
{
Console.WriteLine("Summation failed");
return;
}
}
sw.Stop();
Console.WriteLine("For loop with Array: {0}", sw.ElapsedMilliseconds);
sw = Stopwatch.StartNew();
for (var i = 0; i < Iterations; i++)
{
double sum = 0;
foreach (double d in data)
{
sum += d;
}
if (Math.Abs(sum - correctSum) > 0.1)
{
Console.WriteLine("Summation failed");
return;
}
}
sw.Stop();
Console.WriteLine("Foreach loop with Array: {0}", sw.ElapsedMilliseconds);
Console.WriteLine(" ");
var dataList = data.ToList();
sw = Stopwatch.StartNew();
for (int i = 0; i < Iterations; i++)
{
double sum = 0;
for (int j = 0; j < dataList.Count; j++)
{
sum += data[j];
}
if (Math.Abs(sum - correctSum) > 0.1)
{
Console.WriteLine("Summation failed");
return;
}
}
sw.Stop();
Console.WriteLine("For loop with List: {0}", sw.ElapsedMilliseconds);
sw = Stopwatch.StartNew();
for (int i = 0; i < Iterations; i++)
{
double sum = 0;
foreach (double d in dataList)
{
sum += d;
}
if (Math.Abs(sum - correctSum) > 0.1)
{
Console.WriteLine("Summation failed");
return;
}
}
sw.Stop();
Console.WriteLine("Foreach loop with List: {0}", sw.ElapsedMilliseconds);
}
一种强大而精确的测量时间的方法是使用BenchmarkDotNet库。
在下面的示例中,我在for/foreach上对1,000,000,000个整数记录进行了循环,并使用BenchmarkDotNet进行了测量:
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
public class Program
{
public static void Main()
{
BenchmarkRunner.Run<LoopsBenchmarks>();
}
}
[MemoryDiagnoser]
public class LoopsBenchmarks
{
private List<int> arr = Enumerable.Range(1, 1_000_000_000).ToList();
[Benchmark]
public void For()
{
for (int i = 0; i < arr.Count; i++)
{
int item = arr[i];
}
}
[Benchmark]
public void Foreach()
{
foreach (int item in arr)
{
}
}
}
结果如下:
结论
在上面的例子中,我们可以看到for循环比foreach循环略快。我们还可以看到两者使用相同的内存分配。