河北省网站建设_网站建设公司_Linux_seo优化

一、先回顾一下以前《手搓》线程池Case

ConcurrencyLevel设置为10

并发实现了完美的指数递进关系

当时内心还是得到了很大的满足

第一批01:58:55.832是1个并发

第二批01:58:55.944是2个并发

第三批01:58:56.054是4个并发

第四批01:58:56.165是8个并发

01:58:56.276及以后一段时间达到并发上限10个

参考笔者博文《手搓》线程池

var options = new ReduceOptions { ConcurrencyLevel = 10 };

var scheduler = new ConcurrentTaskScheduler(options);

var factory = new TaskFactory(scheduler);

var jobService = new ConcurrentJobService(scheduler, options);

jobService.Start();

Start(factory);

private void Start(TaskFactory factory)

{

for (int i = 1; i < 10; i++)

{

for (int j = 1; j < 10; j++)

{

int a = i, b = j;

factory.StartNew(() => Multiply(a, b));

}

}

}

public int Multiply(int a, int b)

{

var result = a * b;

_output.WriteLine($"{a} x {b} = {result},{DateTime.Now:HH:mm:ss.fff}");

Thread.Sleep(100);

return result;

}

// 1 x 1 = 1,01:58:55.832

// 1 x 2 = 2,01:58:55.944

// 1 x 3 = 3,01:58:55.944

// 1 x 4 = 4,01:58:56.054

// 1 x 5 = 5,01:58:56.054

// 1 x 6 = 6,01:58:56.054

// 1 x 7 = 7,01:58:56.054

// 1 x 8 = 8,01:58:56.165

// 1 x 9 = 9,01:58:56.165

// 2 x 1 = 2,01:58:56.165

// 2 x 3 = 6,01:58:56.165

// 2 x 2 = 4,01:58:56.165

// 2 x 4 = 8,01:58:56.165

// 2 x 5 = 10,01:58:56.165

// 2 x 6 = 12,01:58:56.165

// 2 x 8 = 16,01:58:56.276

// 2 x 9 = 18,01:58:56.276

// 3 x 2 = 6,01:58:56.276

// 2 x 7 = 14,01:58:56.276

// 3 x 3 = 9,01:58:56.276

// 3 x 1 = 3,01:58:56.276

// 3 x 4 = 12,01:58:56.276

// 3 x 5 = 15,01:58:56.276

// 3 x 6 = 18,01:58:56.277

// 3 x 7 = 21,01:58:56.277

// 4 x 1 = 4,01:58:56.388

// 3 x 8 = 24,01:58:56.388

// 3 x 9 = 27,01:58:56.388

// 4 x 2 = 8,01:58:56.388

// 4 x 6 = 24,01:58:56.388

// 4 x 3 = 12,01:58:56.388

// 4 x 5 = 20,01:58:56.388

// 4 x 8 = 32,01:58:56.388

// 4 x 4 = 16,01:58:56.388

// 4 x 7 = 28,01:58:56.388

// 5 x 8 = 40,01:58:56.500

// 5 x 4 = 20,01:58:56.500

// 5 x 9 = 45,01:58:56.500

// 5 x 2 = 10,01:58:56.500

// 5 x 7 = 35,01:58:56.500

// 5 x 6 = 30,01:58:56.500

// 4 x 9 = 36,01:58:56.500

// 5 x 5 = 25,01:58:56.500

// 5 x 1 = 5,01:58:56.500

// 5 x 3 = 15,01:58:56.500

// 6 x 5 = 30,01:58:56.612

// 6 x 2 = 12,01:58:56.612

// 6 x 1 = 6,01:58:56.612

// 6 x 3 = 18,01:58:56.612

// 6 x 6 = 36,01:58:56.612

// 6 x 7 = 42,01:58:56.612

// 6 x 4 = 24,01:58:56.612

// 6 x 8 = 48,01:58:56.612

// 6 x 9 = 54,01:58:56.612

// 7 x 1 = 7,01:58:56.612

// 7 x 2 = 14,01:58:56.724

// 8 x 1 = 8,01:58:56.724

// 7 x 4 = 28,01:58:56.724

// 7 x 7 = 49,01:58:56.724

// 7 x 5 = 35,01:58:56.724

// 8 x 2 = 16,01:58:56.724

// 7 x 8 = 56,01:58:56.724

// 7 x 6 = 42,01:58:56.724

// 7 x 9 = 63,01:58:56.724

// 7 x 3 = 21,01:58:56.724

// 8 x 5 = 40,01:58:56.836

// 8 x 8 = 64,01:58:56.836

// 9 x 1 = 9,01:58:56.836

// 9 x 2 = 18,01:58:56.836

// 8 x 7 = 56,01:58:56.836

// 8 x 9 = 72,01:58:56.836

// 8 x 3 = 24,01:58:56.836

// 8 x 6 = 48,01:58:56.836

// 9 x 3 = 27,01:58:56.836

// 8 x 4 = 32,01:58:56.836

// 9 x 5 = 45,01:58:56.948

// 9 x 7 = 63,01:58:56.948

// 9 x 4 = 36,01:58:56.948

// 9 x 6 = 54,01:58:56.948

// 9 x 9 = 81,01:58:56.948

// 9 x 8 = 72,01:58:56.948

二、短暂的快乐被异步并发测试给打破了

ConcurrencyLevel设置为4

一开始就是4个清晰可见的并发

一发入魂,开局即是高潮

第一感觉是bug

第二感觉是偶发事件

笔者多次测试,并反复Review代码,都没发现其中的蹊跷

参考笔者博文《手搓》TaskFactory带你安全的起飞

var options = new ReduceOptions { ConcurrencyLevel = 4 };

var factory = new ConcurrentTaskFactory(options);

_output.WriteLine($"begin {DateTime.Now:HH:mm:ss.fff}");

Stopwatch sw = Stopwatch.StartNew();

List<Task<Product>> tasks = new(100);

for (int i = 0; i < 100; i++)

{

var id = i;

var task = factory.StartTask(() => GetProductAsync(id));

tasks.Add(task);

}

var products = await Task.WhenAll(tasks);

sw.Stop();

_output.WriteLine($"end {DateTime.Now:HH:mm:ss.fff}, Elapsed {sw.ElapsedMilliseconds}");

Assert.NotNull(products);

Assert.Equal(100, products.Length);

// begin 10:20:45.317

// Thread36 GetProductAsync(0),10:20:45.487

// Thread11 GetProductAsync(2),10:20:45.487

// Thread8 GetProductAsync(3),10:20:45.487

// Thread35 GetProductAsync(1),10:20:45.487

// Thread11 GetProductAsync(6),10:20:45.614

// Thread35 GetProductAsync(4),10:20:45.614

// Thread8 GetProductAsync(7),10:20:45.614

// Thread36 GetProductAsync(5),10:20:45.614

// Thread35 GetProductAsync(9),10:20:45.742

// Thread8 GetProductAsync(8),10:20:45.742

// Thread41 GetProductAsync(11),10:20:45.742

// Thread37 GetProductAsync(10),10:20:45.742

// Thread37 GetProductAsync(12),10:20:45.869

// Thread8 GetProductAsync(14),10:20:45.869

// Thread11 GetProductAsync(13),10:20:45.869

// Thread41 GetProductAsync(15),10:20:45.869

// Thread8 GetProductAsync(18),10:20:45.997

// Thread35 GetProductAsync(17),10:20:45.997

// Thread41 GetProductAsync(19),10:20:45.997

// Thread11 GetProductAsync(16),10:20:45.997

// Thread11 GetProductAsync(20),10:20:46.125

// Thread8 GetProductAsync(22),10:20:46.125

// Thread35 GetProductAsync(21),10:20:46.125

// Thread41 GetProductAsync(23),10:20:46.125

// Thread37 GetProductAsync(27),10:20:46.253

// Thread41 GetProductAsync(26),10:20:46.253

// Thread35 GetProductAsync(25),10:20:46.253

// Thread11 GetProductAsync(24),10:20:46.253

// Thread35 GetProductAsync(29),10:20:46.381

// Thread41 GetProductAsync(28),10:20:46.381

// Thread11 GetProductAsync(31),10:20:46.381

// Thread37 GetProductAsync(30),10:20:46.381

// Thread8 GetProductAsync(32),10:20:46.507

// Thread37 GetProductAsync(34),10:20:46.507

// Thread41 GetProductAsync(35),10:20:46.507

// Thread11 GetProductAsync(33),10:20:46.507

// Thread37 GetProductAsync(39),10:20:46.635

// Thread11 GetProductAsync(37),10:20:46.635

// Thread41 GetProductAsync(36),10:20:46.635

// Thread35 GetProductAsync(38),10:20:46.635

// Thread41 GetProductAsync(40),10:20:46.763

// Thread37 GetProductAsync(41),10:20:46.763

// Thread35 GetProductAsync(42),10:20:46.763

// Thread11 GetProductAsync(43),10:20:46.763

// Thread41 GetProductAsync(47),10:20:46.891

// Thread8 GetProductAsync(44),10:20:46.891

// Thread11 GetProductAsync(46),10:20:46.891

// Thread37 GetProductAsync(45),10:20:46.891

// Thread37 GetProductAsync(51),10:20:47.018

// Thread8 GetProductAsync(49),10:20:47.018

// Thread41 GetProductAsync(48),10:20:47.018

// Thread11 GetProductAsync(50),10:20:47.018

// Thread41 GetProductAsync(55),10:20:47.146

// Thread11 GetProductAsync(54),10:20:47.146

// Thread8 GetProductAsync(52),10:20:47.146

// Thread37 GetProductAsync(53),10:20:47.146

// Thread11 GetProductAsync(59),10:20:47.274

// Thread8 GetProductAsync(58),10:20:47.274

// Thread37 GetProductAsync(56),10:20:47.274

// Thread41 GetProductAsync(57),10:20:47.274

// Thread41 GetProductAsync(62),10:20:47.402

// Thread11 GetProductAsync(63),10:20:47.402

// Thread37 GetProductAsync(60),10:20:47.402

// Thread8 GetProductAsync(61),10:20:47.402

// Thread41 GetProductAsync(66),10:20:47.530

// Thread88 GetProductAsync(64),10:20:47.530

// Thread35 GetProductAsync(65),10:20:47.530

// Thread11 GetProductAsync(67),10:20:47.530

// Thread11 GetProductAsync(68),10:20:47.658

// Thread41 GetProductAsync(70),10:20:47.658

// Thread8 GetProductAsync(69),10:20:47.658

// Thread35 GetProductAsync(71),10:20:47.658

// Thread41 GetProductAsync(74),10:20:47.786

// Thread95 GetProductAsync(75),10:20:47.786

// Thread35 GetProductAsync(73),10:20:47.786

// Thread88 GetProductAsync(72),10:20:47.786

// Thread95 GetProductAsync(78),10:20:47.914

// Thread41 GetProductAsync(77),10:20:47.914

// Thread88 GetProductAsync(79),10:20:47.914

// Thread8 GetProductAsync(76),10:20:47.914

// Thread95 GetProductAsync(80),10:20:48.042

// Thread41 GetProductAsync(83),10:20:48.042

// Thread8 GetProductAsync(82),10:20:48.042

// Thread35 GetProductAsync(81),10:20:48.042

// Thread95 GetProductAsync(84),10:20:48.170

// Thread35 GetProductAsync(86),10:20:48.170

// Thread41 GetProductAsync(85),10:20:48.170

// Thread8 GetProductAsync(87),10:20:48.170

// Thread11 GetProductAsync(90),10:20:48.297

// Thread88 GetProductAsync(88),10:20:48.297

// Thread8 GetProductAsync(89),10:20:48.297

// Thread35 GetProductAsync(91),10:20:48.297

// Thread11 GetProductAsync(95),10:20:48.425

// Thread8 GetProductAsync(94),10:20:48.425

// Thread41 GetProductAsync(93),10:20:48.425

// Thread35 GetProductAsync(92),10:20:48.425

// Thread41 GetProductAsync(98),10:20:48.553

// Thread35 GetProductAsync(99),10:20:48.553

// Thread8 GetProductAsync(97),10:20:48.553

// Thread88 GetProductAsync(96),10:20:48.553

// end 10:20:48.553, Elapsed 3235

三、进一步优化的空间

傍晚在小区边的小湖散步就反复思考异步并发的问题

如果把异步线程等同同步线程,在异步线程未执行完就激活了新的线程

由于激活前这个过程足够快导致线程叠加

造成开局即是高潮的"假象"

1. 《手搓》线程池核心代码

异步时_processor.Run的耗时可以忽略不计

如何能实现同步和异步同样的效果

while (true)

{

if (_processor.Run())

{

_pool.Increment();

}

else

{

await Task.Delay(_reduceTime, CancellationToken.None)

.ConfigureAwait(false);

}

if (token.IsCancellationRequested)

break;

}

2. 以上想明白后就好优化了

优化后的代码

把_processor.Run()拆分processor.TryTake(out var item)和processor.Run(ref item)

先发现任务,激活线程再执行

有人可能会说,你这代码逻辑有问题啊

发现任务也只是证明本线程有事可干,激活新线程明显浪费资源啊

这点确实应该说一下

现实经验告诉我们,如果发现1只蟑螂,很可能你家已经成为了蟑螂窝

就算激活一个线程没事可干消耗也不大,TryTake返回false就直接走线程回收逻辑了

while (true)

{

if (processor.TryTake(out var item))

{

_pool.Increment();

processor.Run(ref item);

}

else

{

await Task.Delay(_reduceTime, CancellationToken.None)

.ConfigureAwait(false);

}

if (token.IsCancellationRequested)

break;

}

3. 优化后再把第一个同步Case重跑一遍

ConcurrencyLevel设置为10

同步方法也实现了一发入魂,开局即是高潮

必需承认完美的指数递进关系很有数学美

但笔者做为一个码奴,追求程序性能才是终极目标

var options = new ReduceOptions { ConcurrencyLevel = 10 };

var scheduler = new ConcurrentTaskScheduler(options);

var factory = new TaskFactory(scheduler);

var jobService = new ConcurrentJobService(scheduler, options);

jobService.Start();

Start(factory);

private void Start(TaskFactory factory)

{

for (int i = 1; i < 10; i++)

{

for (int j = 1; j < 10; j++)

{

int a = i, b = j;

factory.StartNew(() => Multiply(a, b));

}

}

}

public int Multiply(int a, int b)

{

var result = a * b;

_output.WriteLine($"{a} x {b} = {result},{DateTime.Now:HH:mm:ss.fff}");

Thread.Sleep(100);

return result;

}

// 1 x 6 = 6,09:15:35.332

// 1 x 3 = 3,09:15:35.332

// 1 x 2 = 2,09:15:35.332

// 1 x 4 = 4,09:15:35.332

// 1 x 5 = 5,09:15:35.332

// 1 x 9 = 9,09:15:35.333

// 1 x 7 = 7,09:15:35.333

// 1 x 8 = 8,09:15:35.333

// 1 x 1 = 1,09:15:35.332

// 2 x 1 = 2,09:15:35.333

// 2 x 6 = 12,09:15:35.443

// 2 x 3 = 6,09:15:35.443

// 2 x 7 = 14,09:15:35.443

// 2 x 4 = 8,09:15:35.443

// 2 x 8 = 16,09:15:35.443

// 2 x 5 = 10,09:15:35.443

// 2 x 2 = 4,09:15:35.443

// 2 x 9 = 18,09:15:35.443

// 3 x 1 = 3,09:15:35.443

// 3 x 2 = 6,09:15:35.444

// 4 x 3 = 12,09:15:35.554

// 3 x 4 = 12,09:15:35.554

// 3 x 5 = 15,09:15:35.554

// 3 x 3 = 9,09:15:35.554

// 3 x 7 = 21,09:15:35.554

// 3 x 9 = 27,09:15:35.554

// 4 x 1 = 4,09:15:35.554

// 3 x 8 = 24,09:15:35.554

// 3 x 6 = 18,09:15:35.554

// 4 x 2 = 8,09:15:35.554

// 4 x 6 = 24,09:15:35.666

// 5 x 4 = 20,09:15:35.666

// 4 x 8 = 32,09:15:35.666

// 4 x 9 = 36,09:15:35.666

// 4 x 7 = 28,09:15:35.666

// 5 x 3 = 15,09:15:35.666

// 4 x 4 = 16,09:15:35.666

// 5 x 2 = 10,09:15:35.666

// 5 x 1 = 5,09:15:35.666

// 4 x 5 = 20,09:15:35.666

// 5 x 6 = 30,09:15:35.777

// 6 x 1 = 6,09:15:35.777

// 6 x 5 = 30,09:15:35.777

// 6 x 4 = 24,09:15:35.777

// 5 x 9 = 45,09:15:35.777

// 5 x 5 = 25,09:15:35.777

// 6 x 2 = 12,09:15:35.777

// 5 x 8 = 40,09:15:35.777

// 5 x 7 = 35,09:15:35.777

// 6 x 3 = 18,09:15:35.777

// 6 x 9 = 54,09:15:35.888

// 6 x 8 = 48,09:15:35.888

// 7 x 1 = 7,09:15:35.888

// 6 x 7 = 42,09:15:35.888

// 6 x 6 = 36,09:15:35.888

// 7 x 6 = 42,09:15:35.888

// 7 x 4 = 28,09:15:35.888

// 7 x 3 = 21,09:15:35.888

// 7 x 5 = 35,09:15:35.888

// 7 x 2 = 14,09:15:35.888

// 7 x 8 = 56,09:15:36.000

// 7 x 7 = 49,09:15:36.000

// 7 x 9 = 63,09:15:36.000

// 8 x 1 = 8,09:15:36.000

// 8 x 7 = 56,09:15:36.000

// 8 x 2 = 16,09:15:36.000

// 8 x 3 = 24,09:15:36.000

// 8 x 5 = 40,09:15:36.000

// 8 x 6 = 48,09:15:36.000

// 8 x 4 = 32,09:15:36.000

// 8 x 8 = 64,09:15:36.112

// 8 x 9 = 72,09:15:36.112

// 9 x 2 = 18,09:15:36.112

// 9 x 1 = 9,09:15:36.112

// 9 x 3 = 27,09:15:36.112

// 9 x 4 = 36,09:15:36.112

// 9 x 5 = 45,09:15:36.112

// 9 x 7 = 63,09:15:36.112

// 9 x 6 = 54,09:15:36.112

// 9 x 8 = 72,09:15:36.112

// 9 x 9 = 81,09:15:36.223

4. 线程池执行同步方法开局即是高潮重要吗

当然重要,这就是冷启动的速度问题

如果用TaskFactory对同步方法做并发操作就更显得重要了

GetProduct同步方法执行1次耗时0.1秒

ConcurrencyLevel设置为7

现在优化后获取7条只要0.1秒

如果冷启动按指数递进关系至少要0.3秒多

这就快了3倍

如果ConcurrencyLevel越大,效果就越明显

var options = new ReduceOptions { ConcurrencyLevel = 7 };

var factory = new ConcurrentTaskFactory(options);

_output.WriteLine($"begin {DateTime.Now:HH:mm:ss.fff}");

Stopwatch sw = Stopwatch.StartNew();

List<Task<Product>> tasks = new(7);

for (int i = 0; i < 7; i++)

{

var id = i;

var task = factory.StartNew(() => GetProduct(id));

tasks.Add(task);

}

var products = await Task.WhenAll(tasks);

sw.Stop();

_output.WriteLine($"end {DateTime.Now:HH:mm:ss.fff}, Elapsed {sw.ElapsedMilliseconds}");

internal Product GetProduct(int id)

{

Thread.Sleep(100);

_output.WriteLine($"Thread{Environment.CurrentManagedThreadId} GetProductAsync({id}),{DateTime.Now:HH:mm:ss.fff}");

return new(id);

}

// begin 09:52:02.916

// Thread36 GetProductAsync(5),09:52:03.079

// Thread32 GetProductAsync(1),09:52:03.079

// Thread33 GetProductAsync(2),09:52:03.079

// Thread37 GetProductAsync(6),09:52:03.079

// Thread34 GetProductAsync(3),09:52:03.079

// Thread35 GetProductAsync(4),09:52:03.079

// Thread8 GetProductAsync(0),09:52:03.079

// end 09:52:03.079, Elapsed 162