我经常遇到这样的情况:我想在声明查询的地方对查询进行求值。这通常是因为我需要对它进行多次迭代，计算成本很高。例如:
string raw = "...";
var lines = (from l in raw.Split('\n')
let ll = l.Trim()
where !string.IsNullOrEmpty(ll)
select ll).ToList();
这很好。但是如果我不打算修改结果，那么我也可以调用ToArray()而不是ToList()。
然而，我想知道ToArray()是否通过首先调用ToList()来实现，因此内存效率比只调用ToList()低。
我疯了吗?我是否应该调用ToArray() -在知道内存不会被分配两次的情况下安全可靠?
当前回答
您应该根据理想的设计选择来决定使用ToList还是ToArray。如果您想要一个只能通过索引迭代和访问的集合，请选择ToArray。如果您希望以后能够轻松地从集合中添加和删除额外的功能，那么可以使用ToList(并不是说您不能添加到数组中，但这通常不是合适的工具)。
如果性能很重要，您还应该考虑哪些操作会更快。实际上，您不会调用ToList或ToArray一百万次，但可能会对获得的集合进行一百万次操作。在这方面[]更好，因为List<>是[]，有一些开销。查看这个线程的一些效率比较:List<int>或int[]
在我自己不久前的测试中，我发现ToArray更快。我不确定这些测试有多偏颇。然而，性能差异是如此微不足道，只有在循环运行这些查询数百万次时才能明显看出。
其他回答
老问题，但总是有新的提问者。
根据来源的System.Linq。可枚举，ToList只返回一个新的List(source)，而ToArray使用一个新的Buffer<T>(source).ToArray()返回一个T[]。
关于内存分配:
当运行在IEnumerable<T> only对象上时，ToArray确实比ToList多分配一次内存。但是在大多数情况下您不必关心它，因为GC将在需要时进行垃圾收集。
关于运行时效率:
那些质疑这个问题的人可以在自己的机器上运行下面的代码，然后就会得到答案。
class PersonC
{
public Guid uuid;
public string name;
public int age;
public bool sex;
public DateTime BirthDay;
public double weight;
}
struct PersonS
{
public Guid uuid;
public string name;
public int age;
public bool sex;
public DateTime BirthDay;
public double weight;
}
class PersonT<T> : IEnumerable<T>
{
private List<T> items;
public PersonT(IEnumerable<T> init)
{
items = new List<T>(init);
}
public IEnumerator<T> GetEnumerator() => items.GetEnumerator();
IEnumerator IEnumerable.GetEnumerator() => items.GetEnumerator();
}
private IEnumerable<PersonC> C(int count)
{
for (var i = 0; i < count; ++i)
{
var guid = Guid.NewGuid();
var guidBytes = guid.ToByteArray(); //16 bytes
yield return new PersonC
{
uuid = guid,
name = guid.ToString(),
age = guidBytes[0] ^ guidBytes[7],
sex = guidBytes[14] % 2 == 0,
BirthDay = DateTime.Now.AddDays(-guidBytes[11] * 18),
weight = guidBytes[12] * 100
};
}
}
private IEnumerable<PersonS> S(int count)
{
for (var i = 0; i < count; ++i)
{
var guid = Guid.NewGuid();
var guidBytes = guid.ToByteArray(); //16 bytes
yield return new PersonS
{
uuid = guid,
name = guid.ToString(),
age = guidBytes[0] ^ guidBytes[7],
sex = guidBytes[14] % 2 == 0,
BirthDay = DateTime.Now.AddDays(-guidBytes[11] * 18),
weight = guidBytes[12] * 100
};
}
}
private void MakeLog(string test, List<long> log) =>
Console.WriteLine("{0} {1} ms -> [{2}]",
test,
log.Average(),
string.Join(", ", log)
);
private void Test1(int times, int count)
{
var test = Enumerable.Range(1, times).ToArray();
MakeLog("C.ToList", test.Select(o =>
{
var sw = new Stopwatch();
GC.Collect();
sw.Start();
var ret = C(count).ToList();
sw.Stop();
return sw.ElapsedMilliseconds;
}).ToList());
MakeLog("C.ToArray", test.Select(o =>
{
var sw = new Stopwatch();
GC.Collect();
sw.Start();
var ret = C(count).ToArray();
sw.Stop();
return sw.ElapsedMilliseconds;
}).ToList());
MakeLog("S.ToList", test.Select(o =>
{
var sw = new Stopwatch();
GC.Collect();
sw.Start();
var ret = S(count).ToList();
sw.Stop();
return sw.ElapsedMilliseconds;
}).ToList());
MakeLog("S.ToArray", test.Select(o =>
{
var sw = new Stopwatch();
GC.Collect();
sw.Start();
var ret = S(count).ToArray();
sw.Stop();
return sw.ElapsedMilliseconds;
}).ToList());
}
private void Test2(int times, int count)
{
var test = Enumerable.Range(1, times).ToArray();
var dataC1 = new PersonT<PersonC>(C(count));
var dataS1 = new PersonT<PersonS>(S(count));
MakeLog("C1.ToList", test.Select(o =>
{
var sw = new Stopwatch();
GC.Collect();
sw.Start();
var ret = dataC1.ToList();
sw.Stop();
return sw.ElapsedMilliseconds;
}).ToList());
MakeLog("C1.ToArray", test.Select(o =>
{
var sw = new Stopwatch();
GC.Collect();
sw.Start();
var ret = dataC1.ToArray();
sw.Stop();
return sw.ElapsedMilliseconds;
}).ToList());
MakeLog("S1.ToList", test.Select(o =>
{
var sw = new Stopwatch();
GC.Collect();
sw.Start();
var ret = dataS1.ToList();
sw.Stop();
return sw.ElapsedMilliseconds;
}).ToList());
MakeLog("S1.ToArray", test.Select(o =>
{
var sw = new Stopwatch();
GC.Collect();
sw.Start();
var ret = dataS1.ToArray();
sw.Stop();
return sw.ElapsedMilliseconds;
}).ToList());
}
private void Test3(int times, int count)
{
var test = Enumerable.Range(1, times).ToArray();
var dataC2 = (ICollection<PersonC>) new List<PersonC>(C(count));
var dataS2 = (ICollection<PersonS>) new List<PersonS>(S(count));
MakeLog("C2.ToList", test.Select(o =>
{
var sw = new Stopwatch();
GC.Collect();
sw.Start();
var ret = dataC2.ToList();
sw.Stop();
return sw.ElapsedMilliseconds;
}).ToList());
MakeLog("C2.ToArray", test.Select(o =>
{
var sw = new Stopwatch();
GC.Collect();
sw.Start();
var ret = dataC2.ToArray();
sw.Stop();
return sw.ElapsedMilliseconds;
}).ToList());
MakeLog("S2.ToList", test.Select(o =>
{
var sw = new Stopwatch();
GC.Collect();
sw.Start();
var ret = dataS2.ToList();
sw.Stop();
return sw.ElapsedMilliseconds;
}).ToList());
MakeLog("S2.ToArray", test.Select(o =>
{
var sw = new Stopwatch();
GC.Collect();
sw.Start();
var ret = dataS2.ToArray();
sw.Stop();
return sw.ElapsedMilliseconds;
}).ToList());
}
private void TestMain()
{
const int times = 100;
const int count = 1_000_000 + 1;
Test1(times, count);
Test2(times, count);
Test3(times, count);
}
我在我的机器上得到了这些结果:
Group1:
C.ToList 761.79 ms -> [775, 755, 759, 759, 756, 759, 765, 750, 757, 762, 759, 754, 757, 753, 763, 753, 759, 756, 768, 754, 763, 757, 757, 777, 780, 758, 754, 758, 762, 754, 758, 757, 763, 758, 760, 754, 761, 755, 764, 847, 952, 755, 747, 763, 760, 758, 754, 763, 761, 758, 750, 764, 757, 763, 762, 756, 753, 759, 759, 757, 758, 779, 765, 760, 760, 756, 760, 756, 755, 764, 759, 753, 757, 760, 752, 764, 758, 760, 758, 760, 755, 761, 751, 753, 761, 762, 761, 758, 759, 752, 765, 756, 760, 755, 757, 753, 760, 751, 755, 779]
C.ToArray 782.56 ms -> [783, 774, 771, 771, 773, 774, 775, 775, 772, 770, 771, 774, 771, 1023, 975, 772, 767, 776, 771, 779, 772, 779, 775, 771, 775, 773, 775, 771, 765, 774, 770, 781, 772, 771, 781, 762, 817, 770, 775, 779, 769, 774, 763, 775, 777, 769, 777, 772, 775, 778, 775, 771, 770, 774, 772, 769, 772, 769, 774, 775, 768, 775, 769, 774, 771, 776, 774, 773, 778, 769, 778, 767, 770, 787, 783, 779, 771, 768, 805, 780, 779, 767, 773, 771, 773, 785, 1044, 853, 775, 774, 775, 771, 770, 769, 770, 776, 770, 780, 821, 770]
S.ToList 704.2 ms -> [687, 702, 709, 691, 694, 710, 696, 698, 700, 694, 701, 719, 706, 694, 702, 699, 699, 703, 704, 701, 703, 705, 697, 707, 691, 697, 707, 692, 721, 698, 695, 700, 704, 700, 701, 710, 700, 705, 697, 711, 694, 700, 695, 698, 701, 692, 696, 702, 690, 699, 708, 700, 703, 714, 701, 697, 700, 699, 694, 701, 697, 696, 699, 694, 709, 1068, 690, 706, 699, 699, 695, 708, 695, 704, 704, 700, 695, 704, 695, 696, 702, 700, 710, 708, 693, 697, 702, 694, 700, 706, 699, 695, 706, 714, 704, 700, 695, 697, 707, 704]
S.ToArray 742.5 ms -> [742, 743, 733, 745, 741, 724, 738, 745, 728, 732, 740, 727, 739, 740, 726, 744, 758, 732, 744, 745, 730, 739, 738, 723, 745, 757, 729, 741, 736, 724, 744, 756, 739, 766, 737, 725, 741, 742, 736, 748, 742, 721, 746, 1043, 806, 747, 731, 727, 742, 742, 726, 738, 746, 727, 739, 743, 730, 744, 753, 741, 739, 746, 728, 740, 744, 734, 734, 738, 731, 747, 736, 731, 765, 735, 726, 740, 743, 730, 746, 742, 725, 731, 757, 734, 738, 741, 732, 747, 744, 721, 742, 741, 727, 745, 740, 730, 747, 760, 737, 740]
C1.ToList 32.34 ms -> [35, 31, 31, 31, 32, 31, 31, 31, 31, 31, 31, 31, 31, 31, 33, 32, 31, 31, 31, 31, 30, 32, 31, 31, 31, 31, 32, 30, 31, 31, 31, 30, 32, 31, 31, 31, 36, 31, 31, 31, 32, 30, 31, 32, 31, 31, 31, 31, 31, 32, 31, 31, 31, 31, 33, 32, 31, 32, 31, 31, 33, 31, 31, 31, 31, 31, 32, 31, 32, 31, 34, 38, 68, 42, 79, 33, 31, 31, 31, 31, 31, 30, 30, 30, 30, 31, 31, 31, 31, 32, 31, 32, 31, 31, 31, 32, 33, 33, 31, 31]
C1.ToArray 56.32 ms -> [57, 56, 59, 54, 54, 55, 56, 57, 54, 54, 55, 55, 57, 56, 59, 57, 56, 58, 56, 56, 54, 56, 57, 55, 55, 55, 57, 58, 57, 58, 55, 55, 56, 55, 57, 56, 56, 59, 56, 56, 56, 56, 58, 56, 57, 56, 56, 57, 56, 55, 56, 56, 56, 59, 56, 56, 56, 55, 55, 54, 55, 54, 57, 56, 56, 56, 55, 55, 56, 56, 56, 59, 56, 56, 57, 56, 57, 56, 56, 56, 56, 62, 55, 56, 56, 56, 69, 57, 58, 56, 57, 58, 56, 57, 56, 56, 56, 56, 56, 56]
S1.ToList 88.69 ms -> [96, 90, 90, 89, 91, 88, 89, 90, 96, 89, 89, 89, 90, 90, 90, 89, 90, 90, 89, 90, 89, 91, 89, 91, 89, 91, 89, 90, 90, 89, 87, 88, 87, 88, 87, 87, 87, 87, 88, 88, 87, 87, 89, 87, 87, 87, 91, 88, 87, 86, 89, 87, 90, 89, 89, 90, 89, 87, 87, 87, 86, 87, 88, 90, 88, 87, 87, 92, 87, 87, 88, 88, 88, 86, 86, 87, 88, 87, 87, 87, 89, 87, 89, 87, 90, 89, 89, 89, 91, 89, 90, 89, 90, 88, 90, 90, 90, 88, 89, 89]
S1.ToArray 143.26 ms -> [130, 129, 130, 131, 133, 130, 131, 130, 135, 137, 130, 136, 132, 131, 130, 131, 132, 130, 132, 136, 130, 131, 157, 153, 194, 364, 176, 189, 203, 194, 189, 192, 183, 140, 142, 147, 145, 134, 159, 158, 142, 167, 130, 143, 145, 144, 160, 154, 156, 153, 153, 164, 142, 145, 137, 134, 145, 143, 142, 135, 133, 133, 135, 134, 134, 139, 139, 133, 134, 141, 133, 132, 133, 132, 133, 131, 135, 132, 133, 132, 128, 128, 130, 132, 129, 129, 129, 129, 129, 128, 134, 129, 129, 129, 129, 128, 128, 137, 130, 131]
C2.ToList 3.25 ms -> [5, 3, 3, 3, 3, 4, 3, 4, 3, 4, 3, 3, 3, 4, 4, 3, 3, 3, 4, 3, 3, 3, 3, 4, 3, 4, 3, 4, 3, 3, 4, 4, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 3, 4, 3, 3, 3, 3, 3, 4, 3, 4, 3, 3, 3, 4, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 3, 4, 3, 4, 3, 3, 3, 4, 3, 3, 4, 3, 3, 3, 4, 3, 3, 3, 3, 3]
C2.ToArray 3.37 ms -> [4, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 3, 4, 3, 5, 4, 9, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 3, 3, 3, 3, 3, 4, 4, 3, 3, 4, 4, 3, 3, 3, 4, 3, 3, 3, 3, 4, 3, 3, 3, 3, 3, 4, 4, 3, 4, 4, 3, 3, 4, 3, 3, 4, 3, 4, 4, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 3, 3, 4, 3, 3, 3, 3, 3, 4, 4, 3, 3, 3, 3, 3, 4, 3, 4, 3, 3, 3]
S2.ToList 37.72 ms -> [38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 40, 38, 38, 39, 39, 38, 38, 38, 38, 37, 37, 37, 37, 39, 37, 37, 39, 38, 37, 37, 37, 37, 39, 38, 37, 37, 38, 37, 38, 37, 37, 38, 37, 37, 37, 38, 37, 37, 36, 37, 38, 37, 39, 37, 39, 38, 37, 38, 38, 38, 38, 38, 38, 37, 38, 38, 38, 38, 38, 37, 38, 37, 37, 38, 37, 37, 39, 41, 37, 38, 38, 37, 37, 37, 37, 38, 37, 37, 37, 40, 37, 37, 37, 37, 39, 38]
S2.ToArray 38.86 ms -> [39, 37, 39, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 39, 38, 38, 38, 38, 38, 38, 38, 38, 39, 39, 38, 38, 38, 39, 37, 38, 38, 38, 38, 38, 37, 37, 38, 37, 37, 38, 38, 40, 38, 38, 38, 38, 38, 39, 38, 38, 39, 38, 38, 39, 38, 38, 40, 38, 39, 38, 38, 39, 38, 38, 38, 38, 38, 39, 38, 38, 38, 39, 39, 37, 38, 38, 39, 71, 78, 37, 37, 37, 39, 38, 38, 39, 38, 38, 38, 38, 38, 39, 38, 38, 38, 39, 38, 38, 38]
Group2上:
C.ToList 756.81 ms
C.ToArray 774.21 ms
S.ToList 709.7 ms
S.ToArray 753.51 ms
C1.ToList 32.06 ms
C1.ToArray 56.58 ms
S1.ToList 89.43 ms
S1.ToArray 132.85 ms
C2.ToList 3.45 ms
C2.ToArray 3.36 ms
S2.ToList 41.43 ms
S2.ToArray 40.84 ms
Group3:
C.ToList 756.64 ms
C.ToArray 771.56 ms
S.ToList 705.42 ms
S.ToArray 749.59 ms
C1.ToList 31.45 ms
C1.ToArray 57.03 ms
S1.ToList 91.26 ms
S1.ToArray 129.77 ms
C2.ToList 3.26 ms
C2.ToArray 3.29 ms
S2.ToList 41.57 ms
S2.ToArray 40.69 ms
Group4:
C.ToList 729.65 ms -> [749, 730, 721, 719, 723, 743, 721, 724, 727, 722, 716, 725, 723, 726, 718, 722, 731, 722, 723, 725, 723, 722, 728, 726, 728, 718, 726, 1088, 788, 737, 729, 710, 730, 728, 717, 723, 728, 721, 722, 728, 722, 736, 723, 729, 732, 724, 726, 727, 728, 728, 726, 726, 725, 727, 725, 728, 728, 718, 724, 725, 726, 724, 726, 729, 727, 722, 722, 725, 725, 728, 724, 727, 738, 717, 726, 723, 725, 725, 727, 724, 720, 726, 726, 723, 727, 730, 723, 721, 725, 727, 727, 733, 720, 722, 722, 725, 722, 725, 728, 726]
C.ToArray 788.36 ms -> [748, 740, 742, 797, 1090, 774, 781, 787, 784, 786, 786, 782, 781, 781, 784, 783, 783, 781, 783, 787, 783, 784, 775, 789, 784, 785, 778, 774, 781, 783, 786, 781, 780, 788, 778, 785, 777, 781, 786, 782, 781, 787, 782, 787, 784, 773, 783, 782, 781, 777, 783, 781, 785, 788, 777, 776, 784, 784, 783, 789, 778, 781, 791, 768, 779, 783, 781, 787, 786, 781, 784, 781, 785, 781, 780, 809, 1155, 780, 790, 789, 783, 776, 785, 783, 786, 787, 782, 782, 787, 777, 779, 784, 783, 776, 786, 775, 782, 779, 784, 784]
S.ToList 705.54 ms -> [690, 705, 709, 708, 702, 707, 703, 696, 703, 702, 700, 703, 700, 707, 705, 699, 697, 703, 695, 698, 707, 697, 711, 710, 699, 700, 708, 707, 693, 710, 704, 691, 702, 700, 703, 700, 705, 700, 703, 695, 709, 705, 698, 699, 709, 700, 699, 704, 691, 705, 703, 700, 708, 1048, 710, 706, 706, 692, 702, 705, 695, 701, 710, 697, 698, 706, 705, 707, 707, 695, 698, 704, 698, 699, 705, 698, 703, 702, 701, 697, 702, 702, 704, 703, 699, 707, 703, 705, 701, 717, 698, 695, 713, 696, 708, 705, 697, 699, 700, 698]
S.ToArray 745.01 ms -> [751, 743, 727, 734, 736, 745, 739, 750, 739, 750, 758, 739, 744, 738, 730, 744, 745, 739, 744, 750, 733, 735, 743, 731, 749, 748, 727, 746, 749, 731, 737, 803, 1059, 756, 769, 748, 740, 745, 741, 746, 749, 732, 741, 742, 732, 744, 746, 737, 742, 739, 733, 744, 741, 729, 746, 760, 725, 741, 764, 739, 750, 751, 727, 745, 738, 727, 735, 741, 720, 736, 740, 733, 741, 746, 731, 749, 756, 740, 738, 736, 732, 741, 741, 733, 741, 744, 736, 742, 742, 735, 743, 746, 729, 748, 765, 743, 734, 742, 728, 749]
C1.ToList 32.27 ms -> [36, 31, 31, 32, 31, 32, 31, 30, 32, 30, 30, 30, 34, 32, 31, 31, 31, 31, 31, 31, 31, 32, 38, 51, 68, 57, 35, 30, 31, 31, 30, 30, 33, 30, 31, 34, 31, 34, 32, 31, 31, 31, 31, 32, 30, 30, 31, 30, 31, 31, 32, 31, 31, 31, 32, 31, 31, 31, 32, 31, 33, 31, 31, 32, 30, 30, 30, 30, 30, 33, 30, 33, 32, 31, 30, 31, 31, 32, 32, 31, 35, 31, 34, 31, 31, 32, 31, 31, 32, 31, 32, 31, 31, 35, 31, 31, 31, 31, 31, 32]
C1.ToArray 56.72 ms -> [58, 56, 57, 57, 59, 58, 58, 57, 56, 59, 57, 55, 55, 54, 56, 55, 56, 56, 57, 59, 56, 55, 58, 56, 55, 55, 55, 55, 58, 58, 55, 57, 57, 56, 57, 57, 57, 57, 59, 59, 56, 57, 56, 57, 57, 56, 57, 59, 58, 56, 57, 57, 57, 58, 56, 56, 59, 56, 59, 57, 57, 57, 57, 59, 57, 56, 57, 56, 58, 56, 57, 56, 57, 59, 55, 58, 55, 55, 56, 56, 56, 56, 56, 56, 56, 56, 56, 57, 56, 56, 57, 56, 56, 57, 58, 57, 57, 57, 57, 57]
S1.ToList 90.72 ms -> [95, 90, 90, 89, 89, 89, 91, 89, 89, 87, 91, 89, 89, 89, 91, 89, 89, 89, 90, 89, 89, 90, 88, 89, 88, 90, 89, 90, 89, 89, 90, 90, 89, 89, 90, 91, 89, 91, 89, 90, 89, 89, 90, 91, 89, 89, 89, 89, 89, 89, 90, 89, 89, 89, 90, 89, 90, 89, 91, 89, 90, 89, 90, 89, 90, 89, 96, 89, 90, 89, 89, 89, 89, 89, 90, 89, 89, 89, 90, 87, 89, 90, 90, 91, 89, 91, 89, 89, 90, 91, 90, 89, 93, 144, 149, 90, 90, 89, 89, 89]
S1.ToArray 131.4 ms -> [130, 128, 127, 134, 129, 129, 130, 136, 131, 130, 132, 132, 133, 131, 132, 131, 133, 132, 130, 131, 132, 131, 130, 133, 133, 130, 130, 131, 131, 131, 132, 134, 131, 131, 132, 131, 132, 131, 134, 131, 131, 130, 131, 131, 130, 132, 129, 131, 131, 131, 132, 131, 133, 134, 131, 131, 132, 132, 131, 133, 131, 131, 130, 133, 131, 130, 134, 132, 131, 132, 132, 131, 131, 134, 131, 131, 132, 132, 131, 130, 138, 130, 130, 131, 132, 132, 130, 134, 131, 131, 132, 131, 130, 132, 133, 131, 131, 131, 130, 131]
C2.ToList 3.21 ms -> [4, 3, 3, 3, 4, 3, 4, 4, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 3, 3, 3, 3, 4, 3, 3, 3, 3, 3, 4, 3, 4, 3, 3, 3, 3, 3, 4, 3, 3, 4, 3, 3, 3, 3, 3, 3, 3, 4, 3, 3, 4, 3, 3, 3, 3, 3, 3, 4, 3, 4, 3, 3, 4, 4, 4, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 3, 3, 3, 4, 4, 3, 3, 3, 3, 3, 4, 3, 3, 3]
C2.ToArray 3.22 ms -> [4, 3, 3, 3, 3, 3, 3, 3, 3, 3, 5, 4, 3, 3, 3, 4, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 3, 3, 3, 3, 3, 3, 4, 3, 4, 3, 3, 3, 4, 3, 4, 3, 3, 3, 4, 4, 3, 3, 3, 3, 3, 3, 3, 3, 4, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 3, 3, 3, 4, 3, 4, 3, 3, 3, 3, 3, 4, 3, 3, 3, 4, 3, 4, 3, 3, 3, 3, 4]
S2.ToList 41.46 ms -> [42, 40, 41, 40, 42, 40, 40, 40, 40, 40, 40, 40, 40, 41, 40, 40, 41, 40, 40, 40, 39, 41, 41, 39, 40, 40, 43, 40, 39, 40, 40, 40, 40, 40, 40, 41, 40, 40, 40, 43, 40, 43, 75, 76, 47, 39, 40, 40, 40, 40, 42, 40, 41, 40, 40, 40, 44, 41, 40, 42, 42, 40, 41, 41, 41, 41, 41, 40, 41, 41, 41, 41, 42, 41, 40, 41, 41, 42, 42, 41, 40, 41, 41, 41, 41, 41, 40, 42, 40, 42, 41, 41, 41, 43, 41, 41, 41, 41, 42, 41]
S2.ToArray 41.14 ms -> [42, 41, 41, 40, 40, 40, 40, 41, 41, 42, 41, 42, 41, 41, 41, 42, 41, 41, 42, 41, 41, 41, 41, 41, 42, 40, 41, 40, 42, 40, 42, 41, 40, 42, 41, 41, 43, 42, 41, 41, 41, 41, 41, 41, 41, 41, 41, 41, 40, 40, 41, 41, 41, 40, 42, 41, 41, 41, 41, 41, 40, 41, 41, 42, 41, 41, 41, 42, 41, 41, 41, 41, 41, 41, 42, 42, 42, 41, 45, 46, 41, 40, 41, 41, 42, 41, 41, 41, 41, 41, 41, 40, 41, 43, 40, 40, 40, 40, 43, 41]
Group5:
C.ToList 757.06 ms -> [770, 752, 752, 751, 778, 763, 761, 763, 747, 758, 748, 747, 754, 749, 752, 753, 756, 762, 750, 753, 756, 749, 755, 757, 755, 756, 755, 744, 753, 758, 747, 751, 759, 751, 761, 755, 746, 752, 752, 749, 746, 752, 753, 755, 752, 755, 754, 754, 966, 937, 749, 759, 748, 747, 754, 749, 755, 750, 746, 754, 757, 752, 753, 745, 758, 755, 761, 753, 751, 755, 755, 752, 746, 756, 755, 746, 742, 751, 751, 749, 752, 751, 756, 756, 755, 742, 749, 754, 749, 756, 753, 751, 754, 752, 751, 754, 753, 749, 755, 756]
C.ToArray 772.8 ms -> [766, 772, 755, 763, 758, 767, 763, 762, 761, 768, 769, 763, 770, 757, 765, 760, 766, 759, 764, 761, 760, 777, 1102, 881, 759, 765, 758, 762, 772, 761, 758, 757, 765, 769, 769, 761, 762, 762, 763, 760, 770, 764, 760, 768, 758, 766, 763, 770, 769, 761, 764, 761, 761, 767, 761, 762, 764, 757, 765, 766, 767, 771, 753, 762, 769, 768, 759, 764, 764, 760, 763, 763, 763, 763, 763, 767, 761, 771, 760, 765, 760, 758, 768, 770, 751, 771, 767, 771, 765, 763, 760, 765, 765, 769, 767, 767, 1193, 774, 767, 764]
S.ToList 704.73 ms -> [682, 708, 705, 699, 705, 704, 695, 703, 702, 699, 701, 708, 699, 702, 703, 701, 701, 699, 701, 707, 707, 700, 701, 705, 700, 697, 706, 702, 701, 706, 699, 692, 702, 697, 707, 704, 697, 698, 699, 699, 702, 703, 698, 697, 702, 703, 702, 704, 694, 697, 707, 695, 711, 710, 700, 693, 703, 699, 699, 706, 698, 701, 703, 704, 698, 706, 700, 704, 701, 699, 702, 705, 694, 698, 709, 736, 1053, 704, 694, 700, 698, 696, 701, 700, 700, 706, 706, 692, 698, 707, 703, 695, 703, 699, 694, 708, 695, 694, 706, 695]
S.ToArray 744.17 ms -> [746, 740, 725, 740, 739, 731, 746, 760, 735, 738, 740, 734, 744, 748, 737, 744, 745, 727, 736, 738, 728, 743, 745, 735, 748, 760, 739, 748, 762, 742, 741, 747, 733, 746, 758, 742, 742, 741, 724, 744, 747, 727, 740, 740, 729, 742, 757, 741, 740, 742, 726, 739, 746, 1133, 749, 737, 730, 740, 747, 733, 747, 752, 731, 747, 742, 730, 741, 749, 731, 749, 743, 730, 747, 742, 731, 737, 745, 734, 739, 735, 727, 743, 752, 731, 744, 742, 729, 740, 746, 731, 739, 746, 733, 745, 743, 733, 739, 742, 727, 737]
C1.ToList 31.71 ms -> [35, 32, 32, 30, 31, 33, 31, 32, 32, 31, 31, 32, 32, 33, 32, 31, 31, 32, 31, 32, 32, 32, 31, 32, 33, 32, 31, 31, 31, 32, 31, 34, 31, 31, 32, 33, 32, 32, 31, 32, 34, 32, 31, 32, 33, 31, 32, 32, 31, 32, 32, 32, 32, 32, 32, 31, 31, 32, 31, 33, 30, 31, 32, 30, 30, 33, 32, 32, 34, 31, 31, 31, 31, 32, 31, 31, 31, 31, 32, 31, 31, 33, 31, 32, 32, 32, 33, 32, 31, 31, 31, 31, 31, 32, 32, 33, 32, 31, 31, 32]
C1.ToArray 59.53 ms -> [63, 57, 58, 58, 57, 59, 59, 57, 60, 131, 127, 67, 58, 56, 59, 56, 57, 58, 58, 58, 57, 59, 60, 57, 57, 59, 60, 57, 57, 57, 58, 58, 58, 58, 57, 57, 61, 57, 58, 57, 57, 57, 57, 57, 58, 58, 58, 58, 57, 58, 59, 57, 58, 57, 57, 59, 58, 58, 59, 57, 59, 57, 56, 56, 59, 56, 56, 59, 57, 58, 58, 58, 57, 58, 59, 59, 58, 57, 58, 62, 65, 57, 57, 57, 58, 60, 59, 58, 59, 57, 58, 57, 58, 59, 58, 58, 58, 59, 60, 58]
S1.ToList 82.78 ms -> [87, 82, 83, 83, 82, 82, 83, 84, 82, 83, 84, 84, 84, 82, 82, 84, 82, 84, 83, 84, 82, 82, 82, 81, 83, 83, 83, 84, 84, 82, 82, 83, 83, 83, 82, 83, 85, 83, 82, 82, 84, 82, 82, 83, 83, 83, 82, 82, 82, 83, 82, 83, 82, 84, 82, 83, 82, 83, 82, 82, 82, 84, 82, 83, 82, 82, 86, 83, 83, 82, 83, 83, 83, 82, 84, 82, 83, 81, 82, 82, 82, 82, 83, 83, 83, 82, 83, 84, 83, 82, 83, 83, 83, 82, 83, 84, 82, 82, 83, 83]
S1.ToArray 122.3 ms -> [122, 119, 119, 120, 119, 120, 120, 121, 119, 119, 122, 120, 120, 120, 122, 120, 123, 120, 120, 120, 121, 123, 120, 120, 120, 121, 120, 121, 122, 120, 123, 119, 121, 118, 121, 120, 120, 120, 119, 124, 119, 121, 119, 120, 120, 120, 120, 120, 122, 121, 123, 230, 203, 123, 119, 119, 122, 119, 120, 120, 120, 122, 120, 121, 120, 121, 120, 121, 120, 121, 120, 120, 120, 121, 122, 121, 123, 119, 119, 119, 119, 121, 120, 120, 120, 122, 121, 122, 119, 120, 120, 121, 121, 120, 121, 120, 121, 118, 118, 118]
C2.ToList 3.43 ms -> [5, 3, 4, 4, 4, 3, 4, 4, 4, 4, 4, 3, 3, 3, 4, 3, 3, 3, 4, 3, 4, 3, 4, 3, 4, 4, 3, 3, 3, 3, 4, 3, 3, 3, 4, 3, 4, 3, 3, 3, 4, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 3, 3, 6, 4, 4, 3, 3, 4, 3, 3, 4, 3, 3, 3, 3, 3, 3, 3, 4, 3, 3, 3, 3, 3, 3, 4, 3, 4, 4, 4, 3, 4, 4, 3, 4, 4, 4, 4, 4, 4, 3, 3, 3, 4, 4, 3, 3, 3, 3]
C2.ToArray 3.48 ms -> [3, 3, 3, 3, 4, 4, 3, 4, 4, 4, 3, 4, 3, 3, 4, 3, 3, 4, 3, 4, 3, 3, 3, 4, 3, 3, 3, 4, 3, 3, 3, 3, 4, 3, 4, 3, 3, 4, 3, 4, 3, 3, 3, 3, 4, 3, 3, 3, 3, 4, 3, 4, 3, 3, 4, 3, 3, 4, 3, 3, 4, 4, 3, 3, 4, 3, 4, 4, 3, 4, 4, 4, 4, 4, 3, 3, 3, 4, 4, 3, 4, 4, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 4, 4, 4, 4, 3]
S2.ToList 41.47 ms -> [41, 41, 49, 67, 82, 41, 41, 40, 40, 40, 40, 40, 41, 40, 40, 40, 40, 40, 41, 40, 42, 42, 40, 40, 41, 41, 41, 40, 41, 40, 41, 40, 41, 40, 42, 41, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 41, 41, 41, 41, 41, 42, 41, 41, 41, 42, 40, 41, 40, 40, 40, 42, 40, 41, 42, 41, 42, 41, 42, 40, 41, 41, 41, 41, 41, 41, 41, 41, 40, 41, 40, 41, 41, 41, 40, 41, 41, 40, 40, 41, 41, 41, 41, 41, 43, 40, 40, 41, 42, 41]
S2.ToArray 40.62 ms -> [42, 41, 44, 40, 40, 40, 40, 41, 41, 40, 41, 41, 41, 40, 41, 41, 40, 41, 41, 40, 41, 40, 40, 41, 42, 41, 41, 41, 40, 40, 40, 40, 40, 41, 41, 42, 40, 41, 41, 41, 41, 41, 40, 42, 40, 40, 41, 41, 41, 40, 41, 40, 40, 40, 40, 40, 41, 40, 40, 41, 40, 40, 40, 40, 41, 40, 41, 41, 41, 40, 41, 41, 40, 41, 40, 41, 42, 40, 41, 41, 42, 41, 41, 40, 41, 40, 41, 40, 41, 41, 40, 40, 40, 41, 41, 40, 40, 40, 40, 40]
由于stackoverflow对应答的字符数有限制，因此省略了Group2和Group3的示例列表。
如您所见，在大多数情况下使用ToList或ToArry并不重要。
在处理运行时计算的IEnumerable<T>对象时，如果计算带来的负载比ToList和ToArray的内存分配和复制操作重，则差异不显著(C.ToList vs .ToArray, S.ToList vs .ToArray)。
The difference can be observed only on non-runtime-calculated IEnumerable<T> only objects (C1.ToList vs C1.ToArray and S1.ToList vs S1.ToArray). But the absolute difference (<60ms) is still acceptable on an one million small object IEnumerable<T>. In fact, the difference is decided by the implementation of Enumerator<T> of IEnumerable<T>. So, if your program is really really really sensitive on this, you do have to profile, profile, profile! At last you'll probably find that the bottleneck is not on ToList or ToArray, but the detail of enumerators.
C2的结果。ToList vs C2。ToArray和S2。ToList vs S2。ToArray表明，您真的不需要关心非运行时计算的ICollection<T>对象上的ToList或ToArray。
当然，这只是在我的机器上的结果，这些操作在不同机器上的实际花费时间是不一样的，你可以在你的机器上使用上面的代码来发现。
你需要做出选择的唯一原因是，你在List<T>或T[]上有特定的需求，正如@Jeppe Stig Nielsen的回答所描述的那样。
如果在IEnumerable<T>(例如，来自ORM)上使用ToList()，则通常是首选。如果序列的长度在开始时不知道，ToArray()会创建动态长度的集合(如List)，然后将其转换为数组，这将花费额外的时间。
内存总是会被分配两次——或者类似的情况。由于不能调整数组的大小，这两种方法都将使用某种机制在不断增长的集合中收集数据。(好吧，这个名单本身就是一个不断增长的集合。)
List使用数组作为内部存储，并在需要时将容量增加一倍。这意味着平均2/3的项目至少被重新分配过一次，其中一半至少被重新分配过两次，一半至少被重新分配过三次，以此类推。这意味着每个项目平均被重新分配了1.3次，这并不是很大的开销。
还要记住，如果你在收集字符串，集合本身只包含对字符串的引用，字符串本身不会被重新分配。
这是一个老问题了——但是为了方便无意中发现它的用户，还有一种“Memoizing”Enumerable的替代方案——它具有缓存和停止Linq语句的多个枚举的效果，这就是ToArray()和ToList()经常被使用的原因，即使列表或数组的集合属性从未被使用。
Memoize在RX/System中可用。交互式库，并在这里解释: 更多LINQ与系统。互动
(摘自Bart De 's met的博客，如果你经常使用Linq to Objects，强烈推荐你阅读)
编辑2:(这是对原始答案的更正)
使用基准。NET，我们可以通过性能测量来确认，公认的答案实际上是正确的:ToList在一般情况下更快，因为它不需要从已分配的缓冲区中修剪空空间。ToArray可能会执行额外的分配和复制操作，以使缓冲区的大小精确到元素的数量。
为了确认这一点，使用下面的基准测试。
[MemoryDiagnoser]
[ShortRunJob]
public class Benchmarks
{
[Params(0, 1, 6, 10, 42, 100, 1337, 10000)]
public int Count { get; set; }
public IEnumerable<int> Items => Enumerable.Range(0, Count).Where(i => i > 0);
[Benchmark(Baseline = true)]
public int[] ToArray() => Items.ToArray();
[Benchmark]
public List<int> ToList() => Items.ToList();
}
结果证实，在大多数情况下，ToList要快10% - 15%。
BenchmarkDotNet=v0.13.1, OS=Windows 10.0.22000
Intel Core i9-10885H CPU 2.40GHz, 1 CPU, 16 logical and 8 physical cores
.NET SDK=6.0.302
[Host] : .NET 6.0.7 (6.0.722.32202), X64 RyuJIT
DefaultJob : .NET 6.0.7 (6.0.722.32202), X64 RyuJIT
| Method | Count | Mean | Error | StdDev | Ratio | RatioSD | Gen 0 | Gen 1 | Allocated |
|-------- |------ |-------------:|-----------:|-----------:|------:|--------:|--------:|-------:|----------:|
| ToArray | 0 | 29.73 ns | 0.546 ns | 0.536 ns | 1.00 | 0.00 | 0.0067 | - | 56 B |
| ToList | 0 | 31.51 ns | 0.485 ns | 0.405 ns | 1.06 | 0.02 | 0.0105 | - | 88 B |
| | | | | | | | | | |
| ToArray | 1 | 37.36 ns | 0.314 ns | 0.294 ns | 1.00 | 0.00 | 0.0114 | - | 96 B |
| ToList | 1 | 36.75 ns | 0.605 ns | 0.537 ns | 0.98 | 0.01 | 0.0153 | - | 128 B |
| | | | | | | | | | |
| ToArray | 6 | 100.05 ns | 1.522 ns | 1.349 ns | 1.00 | 0.00 | 0.0286 | - | 240 B |
| ToList | 6 | 85.16 ns | 0.808 ns | 0.756 ns | 0.85 | 0.01 | 0.0267 | - | 224 B |
| | | | | | | | | | |
| ToArray | 10 | 137.20 ns | 2.766 ns | 2.452 ns | 1.00 | 0.00 | 0.0372 | - | 312 B |
| ToList | 10 | 123.05 ns | 2.198 ns | 1.949 ns | 0.90 | 0.01 | 0.0372 | - | 312 B |
| | | | | | | | | | |
| ToArray | 42 | 398.25 ns | 6.583 ns | 5.836 ns | 1.00 | 0.00 | 0.0877 | - | 736 B |
| ToList | 42 | 352.04 ns | 4.976 ns | 4.411 ns | 0.88 | 0.02 | 0.0887 | - | 744 B |
| | | | | | | | | | |
| ToArray | 100 | 730.80 ns | 6.501 ns | 6.081 ns | 1.00 | 0.00 | 0.1488 | - | 1,248 B |
| ToList | 100 | 705.49 ns | 9.947 ns | 9.305 ns | 0.97 | 0.01 | 0.1526 | - | 1,280 B |
| | | | | | | | | | |
| ToArray | 1337 | 8,023.57 ns | 147.388 ns | 137.867 ns | 1.00 | 0.00 | 1.6785 | 0.0458 | 14,056 B |
| ToList | 1337 | 7,980.27 ns | 138.469 ns | 122.749 ns | 1.00 | 0.02 | 1.9989 | 0.1221 | 16,736 B |
| | | | | | | | | | |
| ToArray | 10000 | 57,037.19 ns | 510.492 ns | 452.538 ns | 1.00 | 0.00 | 12.6343 | 1.7700 | 106,280 B |
| ToList | 10000 | 57,728.15 ns | 583.353 ns | 517.127 ns | 1.01 | 0.01 | 15.5640 | 5.1270 | 131,496 B |
作为参考，下面是原始答案，不幸的是，它只在一个非常特殊的情况下执行基准测试，避免了中间的调整大小和复制操作。
最初的回答:
现在已经是2020年了，每个人都在使用。net Core 3.1，所以我决定用Benchmark.NET运行一些基准测试。
TL;DR: ToArray()在性能方面更好，如果不打算改变集合，则可以更好地传达意图。
编辑:从注释中可以看出，这些基准测试可能不是指示性的，因为Enumerable.Range(…)返回一个IEnumerable<T>，其中包含关于序列大小的信息，随后在ToArray()的优化中使用它来预分配正确大小的数组。考虑为您的具体场景手动测试性能。
[MemoryDiagnoser]
public class Benchmarks
{
[Params(0, 1, 6, 10, 39, 100, 666, 1000, 1337, 10000)]
public int Count { get; set; }
public IEnumerable<int> Items => Enumerable.Range(0, Count);
[Benchmark(Description = "ToArray()", Baseline = true)]
public int[] ToArray() => Items.ToArray();
[Benchmark(Description = "ToList()")]
public List<int> ToList() => Items.ToList();
public static void Main() => BenchmarkRunner.Run<Benchmarks>();
}
结果如下:
BenchmarkDotNet=v0.12.0, OS=Windows 10.0.14393.3443 (1607/AnniversaryUpdate/Redstone1)
Intel Core i5-4460 CPU 3.20GHz (Haswell), 1 CPU, 4 logical and 4 physical cores
Frequency=3124994 Hz, Resolution=320.0006 ns, Timer=TSC
.NET Core SDK=3.1.100
[Host] : .NET Core 3.1.0 (CoreCLR 4.700.19.56402, CoreFX 4.700.19.56404), X64 RyuJIT
DefaultJob : .NET Core 3.1.0 (CoreCLR 4.700.19.56402, CoreFX 4.700.19.56404), X64 RyuJIT
| Method | Count | Mean | Error | StdDev | Median | Ratio | RatioSD | Gen 0 | Gen 1 | Gen 2 | Allocated |
|---------- |------ |--------------:|------------:|------------:|--------------:|------:|--------:|--------:|------:|------:|----------:|
| ToArray() | 0 | 7.357 ns | 0.2096 ns | 0.1960 ns | 7.323 ns | 1.00 | 0.00 | - | - | - | - |
| ToList() | 0 | 13.174 ns | 0.2094 ns | 0.1958 ns | 13.084 ns | 1.79 | 0.05 | 0.0102 | - | - | 32 B |
| | | | | | | | | | | | |
| ToArray() | 1 | 23.917 ns | 0.4999 ns | 0.4676 ns | 23.954 ns | 1.00 | 0.00 | 0.0229 | - | - | 72 B |
| ToList() | 1 | 33.867 ns | 0.7350 ns | 0.6876 ns | 34.013 ns | 1.42 | 0.04 | 0.0331 | - | - | 104 B |
| | | | | | | | | | | | |
| ToArray() | 6 | 28.242 ns | 0.5071 ns | 0.4234 ns | 28.196 ns | 1.00 | 0.00 | 0.0280 | - | - | 88 B |
| ToList() | 6 | 43.516 ns | 0.9448 ns | 1.1949 ns | 42.896 ns | 1.56 | 0.06 | 0.0382 | - | - | 120 B |
| | | | | | | | | | | | |
| ToArray() | 10 | 31.636 ns | 0.5408 ns | 0.4516 ns | 31.657 ns | 1.00 | 0.00 | 0.0331 | - | - | 104 B |
| ToList() | 10 | 53.870 ns | 1.2988 ns | 2.2403 ns | 53.415 ns | 1.77 | 0.07 | 0.0433 | - | - | 136 B |
| | | | | | | | | | | | |
| ToArray() | 39 | 58.896 ns | 0.9441 ns | 0.8369 ns | 58.548 ns | 1.00 | 0.00 | 0.0713 | - | - | 224 B |
| ToList() | 39 | 138.054 ns | 2.8185 ns | 3.2458 ns | 138.937 ns | 2.35 | 0.08 | 0.0815 | - | - | 256 B |
| | | | | | | | | | | | |
| ToArray() | 100 | 119.167 ns | 1.6195 ns | 1.4357 ns | 119.120 ns | 1.00 | 0.00 | 0.1478 | - | - | 464 B |
| ToList() | 100 | 274.053 ns | 5.1073 ns | 4.7774 ns | 272.242 ns | 2.30 | 0.06 | 0.1578 | - | - | 496 B |
| | | | | | | | | | | | |
| ToArray() | 666 | 569.920 ns | 11.4496 ns | 11.2450 ns | 571.647 ns | 1.00 | 0.00 | 0.8688 | - | - | 2728 B |
| ToList() | 666 | 1,621.752 ns | 17.1176 ns | 16.0118 ns | 1,623.566 ns | 2.85 | 0.05 | 0.8793 | - | - | 2760 B |
| | | | | | | | | | | | |
| ToArray() | 1000 | 796.705 ns | 16.7091 ns | 19.8910 ns | 796.610 ns | 1.00 | 0.00 | 1.2951 | - | - | 4064 B |
| ToList() | 1000 | 2,453.110 ns | 48.1121 ns | 65.8563 ns | 2,460.190 ns | 3.09 | 0.10 | 1.3046 | - | - | 4096 B |
| | | | | | | | | | | | |
| ToArray() | 1337 | 1,057.983 ns | 20.9810 ns | 41.4145 ns | 1,041.028 ns | 1.00 | 0.00 | 1.7223 | - | - | 5416 B |
| ToList() | 1337 | 3,217.550 ns | 62.3777 ns | 61.2633 ns | 3,203.928 ns | 2.98 | 0.13 | 1.7357 | - | - | 5448 B |
| | | | | | | | | | | | |
| ToArray() | 10000 | 7,309.844 ns | 160.0343 ns | 141.8662 ns | 7,279.387 ns | 1.00 | 0.00 | 12.6572 | - | - | 40064 B |
| ToList() | 10000 | 23,858.032 ns | 389.6592 ns | 364.4874 ns | 23,759.001 ns | 3.26 | 0.08 | 12.6343 | - | - | 40096 B |
// * Hints *
Outliers
Benchmarks.ToArray(): Default -> 2 outliers were removed (35.20 ns, 35.29 ns)
Benchmarks.ToArray(): Default -> 2 outliers were removed (38.51 ns, 38.88 ns)
Benchmarks.ToList(): Default -> 1 outlier was removed (64.69 ns)
Benchmarks.ToArray(): Default -> 1 outlier was removed (67.02 ns)
Benchmarks.ToArray(): Default -> 1 outlier was removed (130.08 ns)
Benchmarks.ToArray(): Default -> 1 outlier was detected (541.82 ns)
Benchmarks.ToArray(): Default -> 1 outlier was removed (7.82 us)
// * Legends *
Count : Value of the 'Count' parameter
Mean : Arithmetic mean of all measurements
Error : Half of 99.9% confidence interval
StdDev : Standard deviation of all measurements
Median : Value separating the higher half of all measurements (50th percentile)
Ratio : Mean of the ratio distribution ([Current]/[Baseline])
RatioSD : Standard deviation of the ratio distribution ([Current]/[Baseline])
Gen 0 : GC Generation 0 collects per 1000 operations
Gen 1 : GC Generation 1 collects per 1000 operations
Gen 2 : GC Generation 2 collects per 1000 operations
Allocated : Allocated memory per single operation (managed only, inclusive, 1KB = 1024B)
1 ns : 1 Nanosecond (0.000000001 sec)
