rpa*_*pax 20 c# performance datetime dayofweek micro-optimization
首先:
我问这个问题只是为了好玩和渴望学习.我不得不承认我喜欢搞微观优化(虽然他们从未在我的任何开发中导致任何显着的速度提升).
该DateTime.DayOfWeek方法并不代表我的任何应用中的瓶颈.
并且它不太可能 成为任何其他问题.如果有人认为这种方法对他的应用程序的性能有影响,他应该考虑何时进行优化,然后,他应该进行分析.
DateTime使用ILSpy 反编译类,我们了解如何DateTime.DayOfWeek实现:
[__DynamicallyInvokable]
public DayOfWeek DayOfWeek
{
[__DynamicallyInvokable, TargetedPatchingOptOut("Performance critical to inline across NGen image boundaries")]
get
{
return (DayOfWeek)((this.InternalTicks / 864000000000L + 1L) % 7L);
}
}
public long Ticks
{
[__DynamicallyInvokable, TargetedPatchingOptOut("Performance critical to inline this type of method across NGen image boundaries")]
get
{
return this.InternalTicks;
}
}
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此方法执行以下操作:
与当天相对应的刻度除以一天中现有的刻度数.
我们在前面的结果中加1,以便除数7的余数在0和6之间.
这是计算星期几的唯一方法吗?
是否有可能重新实现它以使其运行更快?
rpa*_*pax 77
我们来做一些调整.
TimeSpan.TicksPerDay (864000000000)
DayOfWeek 现在可以表达为:
public DayOfWeek DayOfWeek
{
get
{
return (DayOfWeek)(((Ticks>>14) / 52734375 + 1L) % 7L);
}
}
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我们在模7中工作,52734375 % 7它是1.所以,上面的代码等于:
public static DayOfWeek dayOfWeekTurbo(this DateTime date)
{
return (DayOfWeek)(((date.Ticks >> 14) + 1) % 7);
}
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直观地说,它有效.但是,让我们用代码来证明这一点
public static void proof()
{
DateTime date = DateTime.MinValue;
DateTime max_date = DateTime.MaxValue.AddDays(-1);
while (date < max_date)
{
if (date.DayOfWeek != date.dayOfWeekTurbo())
{
Console.WriteLine("{0}\t{1}", date.DayOfWeek, date.dayOfWeekTurbo());
Console.ReadLine();
}
date = date.AddDays(1);
}
}
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如果你愿意,你可以运行它,但我保证你工作正常.
好的,唯一剩下的就是一些基准测试.
这是一种辅助方法,以使代码更清晰:
public static IEnumerable<DateTime> getAllDates()
{
DateTime d = DateTime.MinValue;
DateTime max = DateTime.MaxValue.AddDays(-1);
while (d < max)
{
yield return d;
d = d.AddDays(1);
}
}
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我想它不需要解释.
public static void benchDayOfWeek()
{
DateTime[] dates = getAllDates().ToArray();
// for preventing the compiler doing things that we don't want to
DayOfWeek[] foo = new DayOfWeek[dates.Length];
for (int max_loop = 0; max_loop < 10000; max_loop+=100)
{
Stopwatch st1, st2;
st1 = Stopwatch.StartNew();
for (int i = 0; i < max_loop; i++)
for (int j = 0; j < dates.Length; j++)
foo[j] = dates[j].DayOfWeek;
st1.Stop();
st2 = Stopwatch.StartNew();
for (int i = 0; i < max_loop; i++)
for (int j = 0; j < dates.Length; j++)
foo[j] = dates[j].dayOfWeekTurbo();
st2.Stop();
Console.WriteLine("{0},{1}", st1.ElapsedTicks, st2.ElapsedTicks);
}
Console.ReadLine();
Console.WriteLine(foo[0]);
}
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输出:
96,28
172923452,50884515
352004290,111919170
521851120,168153321
683972846,215554958
846791857,264187194
1042803747,328459950
Monday
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如果我们使用数据创建图表,它看起来像这样:

?????????????????????????????????????????????????????????????????????????????????
? Number of iterations ? Standard DayOfWeek ? Optimized DayOfWeek ? Speedup ?
?????????????????????????????????????????????????????????????????????????????????
? 0 ? 96 ? 28 ? 3.428571429 ?
? 100 ? 172923452 ? 50884515 ? 3.398351188 ?
? 200 ? 352004290 ? 111919170 ? 3.145165301 ?
? 300 ? 521851120 ? 168153321 ? 3.103424404 ?
? 400 ? 683972846 ? 215554958 ? 3.1730787 ?
? 500 ? 846791857 ? 264187194 ? 3.205272156 ?
? 600 ? 1042803747 ? 328459950 ? 3.174827698 ?
?????????????????????????????????????????????????????????????????????????????????
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快3倍.
注意:代码是使用Visual Studio 2013,Release模式编译的,并且在应用程序关闭时运行.(当然包括VS).
我在东芝Satellite C660-2JK,英特尔®酷睿™i3-2350M处理器和Windows®7家庭高级版64位中运行测试.
编辑:
正如Jon Skeet所注意到的,当这个方法不在日期边界时,它会失败.
由于Jon Skeet的评论这个答案,
dayOfWeekTurbo当它不在日期边界时会失败.例如,考虑一下new DateTime(2014, 3, 11, 21, 39, 30)- 你的方法认为它是星期五,实际上它是星期二.在"我们是在模7个工作"是南辕北辙,基本上...通过移除额外师,某一天的周变化在白天.
我决定编辑它.
如果我们改变proof()方法,
public static void proof()
{
DateTime date = DateTime.MinValue;
DateTime max_date = DateTime.MaxValue.AddSeconds(-1);
while (date < max_date)
{
if (date.DayOfWeek != date.dayOfWeekTurbo2())
{
Console.WriteLine("{0}\t{1}", date.DayOfWeek, date.dayOfWeekTurbo2());
Console.ReadLine();
}
date = date.AddSeconds(1);
}
}
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失败!
Jon Skeet是对的.让我们按照Jon Skeet的建议来应用该部门.
public static DayOfWeek dayOfWeekTurbo2(this DateTime date)
{
return (DayOfWeek)((((date.Ticks >> 14) / 52734375L )+ 1) % 7);
}
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另外,我们改变了方法getAllDates().
public static IEnumerable<DateTime> getAllDates()
{
DateTime d = DateTime.MinValue;
DateTime max = DateTime.MaxValue.AddHours(-1);
while (d < max)
{
yield return d;
d = d.AddHours(1);
}
}
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和 benchDayOfWeek()
public static void benchDayOfWeek()
{
DateTime[] dates = getAllDates().ToArray();
DayOfWeek[] foo = new DayOfWeek[dates.Length];
for (int max_loop = 0; max_loop < 10000; max_loop ++)
{
Stopwatch st1, st2;
st1 = Stopwatch.StartNew();
for (int i = 0; i < max_loop; i++)
for (int j = 0; j < dates.Length; j++)
foo[j] = dates[j].DayOfWeek;
st1.Stop();
st2 = Stopwatch.StartNew();
for (int i = 0; i < max_loop; i++)
for (int j = 0; j < dates.Length; j++)
foo[j] = dates[j].dayOfWeekTurbo2();
st2.Stop();
Console.WriteLine("{0},{1}", st1.ElapsedTicks, st2.ElapsedTicks);
}
Console.ReadLine();
Console.WriteLine(foo[0]);
}
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它会更快吗?答案是肯定的
输出:
90,26
43772675,17902739
84299562,37339935
119418847,47236771
166955278,72444714
207441663,89852249
223981096,106062643
275440586,125110111
327353547,145689642
363908633,163442675
407152133,181642026
445141584,197571786
495590201,217373350
520907684,236609850
511052601,217571474
610024381,260208969
637676317,275558318
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????????????????????????????????????????????????????????????????????????????????????
? Number of iterations ? Standard DayOfWeek ? Optimized DayOfWeek(2) ? Speedup ?
????????????????????????????????????????????????????????????????????????????????????
? 1 ? 43772675 ? 17902739 ? 2.445026708 ?
? 2 ? 84299562 ? 37339935 ? 2.257624766 ?
? 3 ? 119418847 ? 47236771 ? 2.528090817 ?
? 4 ? 166955278 ? 72444714 ? 2.304588821 ?
? 5 ? 207441663 ? 89852249 ? 2.308697504 ?
? 6 ? 223981096 ? 106062643 ? 2.111781205 ?
? 7 ? 275440586 ? 125110111 ? 2.201585338 ?
? 8 ? 327353547 ? 145689642 ? 2.246923958 ?
? 9 ? 363908633 ? 163442675 ? 2.226521519 ?
? 10 ? 407152133 ? 181642026 ? 2.241508433 ?
? 11 ? 445141584 ? 197571786 ? 2.25306251 ?
? 12 ? 495590201 ? 217373350 ? 2.279903222 ?
? 13 ? 520907684 ? 236609850 ? 2.201546909 ?
? 14 ? 511052601 ? 217571474 ? 2.348895246 ?
? 15 ? 610024381 ? 260208969 ? 2.344363391 ?
? 16 ? 637676317 ? 275558318 ? 2.314124725 ?
????????????????????????????????????????????????????????????????????????????????????
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快2倍.