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?
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
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();
}
}
其他回答
简短的回答:
在。net List中<T>和Array<T>具有相同的速度/性能,因为在。net List中是Array的包装器。
再说一遍:List在里面是数组!在。net List中<T>是其他语言中的<T>数组列表。
详细说明在哪些情况下需要使用什么:
Array need to use: So often as possible. It's fast and takes smallest RAM range for same amount information. If you know exact count of cells needed If data saved in array < 85000 b (85000/32 = 2656 elements for integer data) If needed high Random Access speed List need to use: If needed to add cells to the end of list (often) If needed to add cells in the beginning/middle of the list (NOT OFTEN) If data saved in array < 85000 b (85000/32 = 2656 elements for integer data) If needed high Random Access speed LinkedList need to use: If needed to add cells in the beginning/middle/end of the list (often) If needed only sequential access (forward/backward) If you need to save LARGE items, but items count is low. Better do not use for large amount of items, as it's use additional memory for links. If you not sure that you need LinkedList -- YOU DON'T NEED IT. Just do not use it.
更多的细节:
更多细节:
https://stackoverflow.com/a/29263914/4423545
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();
}
}
因为我有一个类似的问题,这让我快速开始。
我的问题更具体一点,'自反数组实现的最快方法是什么'
Marc Gravell所做的测试显示了很多,但并不是确切的访问时间。他的计时还包括对数组和列表的循环。因为我还提出了第三个我想测试的方法,一个“字典”,只是为了比较,我扩展了hist测试代码。
首先,我使用一个常数进行测试,这给了我一个包括循环在内的特定时间。这是一个“裸”计时,不包括实际访问。 然后我做了一个访问主题结构的测试,这给了我和“开销包括”时间,循环和实际访问。
“裸”计时和“开销包含”计时之间的差异给了我一个“结构访问”计时的指示。
但是这个时机有多准确呢?在测试窗口期间将为shure做一些时间切片。我没有关于时间切片的信息,但我假设它在测试期间是均匀分布的,在几十毫秒的数量级,这意味着计时的准确性应该在+/- 100毫秒左右的数量级。粗略估计一下?无论如何,这是一个系统测量误差的来源。
此外,测试是在“调试”模式下进行的,没有进行优化。否则,编译器可能会更改实际的测试代码。
因此,我得到两个结果,一个是标记为“(c)”的常量,一个是标记为“(n)”的访问,而“dt”的差值告诉我实际访问所花费的时间。
结果是这样的:
Dictionary(c)/for: 1205ms (600000000)
Dictionary(n)/for: 8046ms (589725196)
dt = 6841
List(c)/for: 1186ms (1189725196)
List(n)/for: 2475ms (1779450392)
dt = 1289
Array(c)/for: 1019ms (600000000)
Array(n)/for: 1266ms (589725196)
dt = 247
Dictionary[key](c)/foreach: 2738ms (600000000)
Dictionary[key](n)/foreach: 10017ms (589725196)
dt = 7279
List(c)/foreach: 2480ms (600000000)
List(n)/foreach: 2658ms (589725196)
dt = 178
Array(c)/foreach: 1300ms (600000000)
Array(n)/foreach: 1592ms (589725196)
dt = 292
dt +/-.1 sec for foreach
Dictionary 6.8 7.3
List 1.3 0.2
Array 0.2 0.3
Same test, different system:
dt +/- .1 sec for foreach
Dictionary 14.4 12.0
List 1.7 0.1
Array 0.5 0.7
通过更好地估计时间误差(如何消除由于时间切片引起的系统测量误差?),可以对结果进行更多的讨论。
看起来List/foreach具有最快的访问速度,但它的开销非常大。
List/for和List/foreach之间的区别是奇怪的。也许涉及到兑现?
此外,对于数组的访问,使用for循环还是foreach循环并不重要。计时结果及其准确性使结果具有“可比性”。
到目前为止,使用字典是最慢的,我认为它只是因为在左边(索引器)我有一个稀疏的整数列表,而不是在这个测试中使用的范围。
下面是修改后的测试代码。
Dictionary<int, int> dict = new Dictionary<int, int>(6000000);
List<int> list = new List<int>(6000000);
Random rand = new Random(12345);
for (int i = 0; i < 6000000; i++)
{
int n = rand.Next(5000);
dict.Add(i, n);
list.Add(n);
}
int[] arr = list.ToArray();
int chk = 0;
Stopwatch watch = Stopwatch.StartNew();
for (int rpt = 0; rpt < 100; rpt++)
{
int len = dict.Count;
for (int i = 0; i < len; i++)
{
chk += 1; // dict[i];
}
}
watch.Stop();
long c_dt = watch.ElapsedMilliseconds;
Console.WriteLine(" Dictionary(c)/for: {0}ms ({1})", c_dt, chk);
chk = 0;
watch = Stopwatch.StartNew();
for (int rpt = 0; rpt < 100; rpt++)
{
int len = dict.Count;
for (int i = 0; i < len; i++)
{
chk += dict[i];
}
}
watch.Stop();
long n_dt = watch.ElapsedMilliseconds;
Console.WriteLine(" Dictionary(n)/for: {0}ms ({1})", n_dt, chk);
Console.WriteLine("dt = {0}", n_dt - c_dt);
watch = Stopwatch.StartNew();
for (int rpt = 0; rpt < 100; rpt++)
{
int len = list.Count;
for (int i = 0; i < len; i++)
{
chk += 1; // list[i];
}
}
watch.Stop();
c_dt = watch.ElapsedMilliseconds;
Console.WriteLine(" List(c)/for: {0}ms ({1})", c_dt, chk);
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();
n_dt = watch.ElapsedMilliseconds;
Console.WriteLine(" List(n)/for: {0}ms ({1})", n_dt, chk);
Console.WriteLine("dt = {0}", n_dt - c_dt);
chk = 0;
watch = Stopwatch.StartNew();
for (int rpt = 0; rpt < 100; rpt++)
{
for (int i = 0; i < arr.Length; i++)
{
chk += 1; // arr[i];
}
}
watch.Stop();
c_dt = watch.ElapsedMilliseconds;
Console.WriteLine(" Array(c)/for: {0}ms ({1})", c_dt, 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();
n_dt = watch.ElapsedMilliseconds;
Console.WriteLine("Array(n)/for: {0}ms ({1})", n_dt, chk);
Console.WriteLine("dt = {0}", n_dt - c_dt);
chk = 0;
watch = Stopwatch.StartNew();
for (int rpt = 0; rpt < 100; rpt++)
{
foreach (int i in dict.Keys)
{
chk += 1; // dict[i]; ;
}
}
watch.Stop();
c_dt = watch.ElapsedMilliseconds;
Console.WriteLine("Dictionary[key](c)/foreach: {0}ms ({1})", c_dt, chk);
chk = 0;
watch = Stopwatch.StartNew();
for (int rpt = 0; rpt < 100; rpt++)
{
foreach (int i in dict.Keys)
{
chk += dict[i]; ;
}
}
watch.Stop();
n_dt = watch.ElapsedMilliseconds;
Console.WriteLine("Dictionary[key](n)/foreach: {0}ms ({1})", n_dt, chk);
Console.WriteLine("dt = {0}", n_dt - c_dt);
chk = 0;
watch = Stopwatch.StartNew();
for (int rpt = 0; rpt < 100; rpt++)
{
foreach (int i in list)
{
chk += 1; // i;
}
}
watch.Stop();
c_dt = watch.ElapsedMilliseconds;
Console.WriteLine(" List(c)/foreach: {0}ms ({1})", c_dt, chk);
chk = 0;
watch = Stopwatch.StartNew();
for (int rpt = 0; rpt < 100; rpt++)
{
foreach (int i in list)
{
chk += i;
}
}
watch.Stop();
n_dt = watch.ElapsedMilliseconds;
Console.WriteLine(" List(n)/foreach: {0}ms ({1})", n_dt, chk);
Console.WriteLine("dt = {0}", n_dt - c_dt);
chk = 0;
watch = Stopwatch.StartNew();
for (int rpt = 0; rpt < 100; rpt++)
{
foreach (int i in arr)
{
chk += 1; // i;
}
}
watch.Stop();
c_dt = watch.ElapsedMilliseconds;
Console.WriteLine(" Array(c)/foreach: {0}ms ({1})", c_dt, chk);
chk = 0;
watch = Stopwatch.StartNew();
for (int rpt = 0; rpt < 100; rpt++)
{
foreach (int i in arr)
{
chk += i;
}
}
watch.Stop();
n_dt = watch.ElapsedMilliseconds;
Console.WriteLine("Array(n)/foreach: {0}ms ({1})", n_dt, chk);
Console.WriteLine("dt = {0}", n_dt - c_dt);
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。
[另见此问题]
我修改了Marc的答案,使用实际的随机数,在所有情况下都做同样的工作。
结果:
for foreach Array : 1575ms 1575ms (+0%) List : 1630ms 2627ms (+61%) (+3%) (+67%) (Checksum: -1000038876)
在VS 2008 SP1下编译为发行版。在Q6600@2.40GHz、. net 3.5 SP1上运行而不进行调试。
代码:
class Program
{
static void Main(string[] args)
{
List<int> list = new List<int>(6000000);
Random rand = new Random(1);
for (int i = 0; i < 6000000; i++)
{
list.Add(rand.Next());
}
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++)
{
int len = arr.Length;
for (int i = 0; i < len; 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.WriteLine();
Console.ReadLine();
}
}