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前言 Microsoft.AspNetCore.ConcurrencyLimiter AspNetCore3.0后增加的,用于传入的请求进行排队处理,避免线程池的不足. Queue策略 添加Nuget Install-Package Microsoft.AspNetCore.ConcurrencyLimiter
public void ConfigureServices(IServiceCollection services)
{
services.AddQueuePolicy(options =>
{
//最大并发请求数
options.MaxConcurrentRequests = 2;
//请求队列长度限制
options.RequestQueueLimit = 1;
});
services.AddControllers();
}
public void Configure(IApplicationBuilder app, IWebHostEnvironment env)
{
//添加并发限制中间件
app.UseConcurrencyLimiter();
app.Run(async context =>
{
Task.Delay(100).Wait(); // 100ms sync-over-async
await context.Response.WriteAsync("Hello World!");
});
if (env.IsDevelopment())
{
app.UseDeveloperExceptionPage();
}
app.UseHttpsRedirection();
app.UseRouting();
app.UseAuthorization();
app.UseEndpoints(endpoints =>
{
endpoints.MapControllers();
});
}
通过上面简单的配置,我们就可以将他引入到我们的代码中,从而做并发量限制,以及队列的长度;那么问题来了,他是怎么实现的呢？
public static IServiceCollection AddQueuePolicy(this IServiceCollection services, Action<QueuePolicyOptions> configure)
{
services.Configure(configure);
services.AddSingleton<IQueuePolicy, QueuePolicy>();
return services;
}
QueuePolicy采用的是SemaphoreSlim信号量设计,SemaphoreSlim、Semaphore（信号量）支持并发多线程进入被保护代码,对象在初始化时会指定 最大任务数量,当线程请求访问资源,信号量递减,而当他们释放时,信号量计数又递增。
/// <summary>
/// 构造方法(初始化Queue策略)
/// </summary>
/// <param name="options"></param>
public QueuePolicy(IOptions<QueuePolicyOptions> options)
{
_maxConcurrentRequests = options.Value.MaxConcurrentRequests;
if (_maxConcurrentRequests <= 0)
{
throw new ArgumentException(nameof(_maxConcurrentRequests), "MaxConcurrentRequests must be a positive integer.");
}
_requestQueueLimit = options.Value.RequestQueueLimit;
if (_requestQueueLimit < 0)
{
throw new ArgumentException(nameof(_requestQueueLimit), "The RequestQueueLimit cannot be a negative number.");
}
//使用SemaphoreSlim来限制任务最大个数
_serverSemaphore = new SemaphoreSlim(_maxConcurrentRequests);
}
ConcurrencyLimiterMiddleware中间件
/// <summary>
/// Invokes the logic of the middleware.
/// </summary>
/// <param name="context">The <see cref="HttpContext"/>.</param>
/// <returns>A <see cref="Task"/> that completes when the request leaves.</returns>
public async Task Invoke(HttpContext context)
{
var waitInQueueTask = _queuePolicy.TryEnterAsync();
// Make sure we only ever call GetResult once on the TryEnterAsync ValueTask b/c it resets.
bool result;
if (waitInQueueTask.IsCompleted)
{
ConcurrencyLimiterEventSource.Log.QueueSkipped();
result = waitInQueueTask.Result;
}
else
{
using (ConcurrencyLimiterEventSource.Log.QueueTimer())
{
result = await waitInQueueTask;
}
}
if (result)
{
try
{
await _next(context);
}
finally
{
_queuePolicy.OnExit();
}
}
else
{
ConcurrencyLimiterEventSource.Log.RequestRejected();
ConcurrencyLimiterLog.RequestRejectedQueueFull(_logger);
context.Response.StatusCode = StatusCodes.Status503ServiceUnavailable;
await _onRejected(context);
}
}
每次当我们请求的时候首先会调用_queuePolicy.TryEnterAsync(),进入该方法后先开启一个私有lock锁,再接着判断总请求量是否≥(请求队列限制的大小+最大并发请求数),如果当前数量超出了,那么我直接抛出,送你个503状态;
if (result)
{
try
{
await _next(context);
}
finally
{
_queuePolicy.OnExit();
}
}
else
{
ConcurrencyLimiterEventSource.Log.RequestRejected();
ConcurrencyLimiterLog.RequestRejectedQueueFull(_logger);
context.Response.StatusCode = StatusCodes.Status503ServiceUnavailable;
await _onRejected(context);
}
问题来了,我这边如果说还没到你设置的大小呢,我这个请求没有给你服务器造不成压力,那么你给我处理一下吧.
lock (_totalRequestsLock)
{
if (TotalRequests >= _requestQueueLimit + _maxConcurrentRequests)
{
return false;
}
TotalRequests++;
}
//异步等待进入信号量，如果没有线程被授予对信号量的访问权限，则进入执行保护代码；否则此线程将在此处等待，直到信号量被释放为止
await _serverSemaphore.WaitAsync();
return true;
}
返回成功后那么中间件这边再进行处理,_queuePolicy.OnExit();通过该调用进行调用_serverSemaphore.Release();释放信号灯,再对总请求数递减 Stack策略 再来看看另一种方法,栈策略,他是怎么做的呢？一起来看看.再附加上如何使用的代码.
public void ConfigureServices(IServiceCollection services)
{
services.AddStackPolicy(options =>
{
//最大并发请求数
options.MaxConcurrentRequests = 2;
//请求队列长度限制
options.RequestQueueLimit = 1;
});
services.AddControllers();
}
通过上面的配置,我们便可以对我们的应用程序执行出相应的策略.下面再来看看他是怎么实现的呢
public static IServiceCollection AddStackPolicy(this IServiceCollection services, Action<QueuePolicyOptions> configure)
{
services.Configure(configure);
services.AddSingleton<IQueuePolicy, StackPolicy>();
return services;
}
可以看到这次是通过StackPolicy类做的策略.来一起来看看主要的方法
/// <summary>
/// 构造方法(初始化参数)
/// </summary>
/// <param name="options"></param>
public StackPolicy(IOptions<QueuePolicyOptions> options)
{
//栈分配
_buffer = new List<ResettableBooleanCompletionSource>();
//队列大小
_maxQueueCapacity = options.Value.RequestQueueLimit;
//最大并发请求数
_maxConcurrentRequests = options.Value.MaxConcurrentRequests;
//剩余可用空间
_freeServerSpots = options.Value.MaxConcurrentRequests;
}
当我们通过中间件请求调用,_queuePolicy.TryEnterAsync()时,首先会判断我们是否还有访问请求次数,如果_freeServerSpots＞0,那么则直接给我们返回true,让中间件直接去执行下一步,如果当前队列＝我们设置的队列大小的话,那我们需要取消先前请求;每次取消都是先取消之前的保留后面的请求;
public ValueTask<bool> TryEnterAsync()
{
lock (_bufferLock)
{
if (_freeServerSpots > 0)
{
_freeServerSpots--;
return _trueTask;
}
// 如果队列满了，取消先前的请求
if (_queueLength == _maxQueueCapacity)
{
_hasReachedCapacity = true;
_buffer[_head].Complete(false);
_queueLength--;
}
var tcs = _cachedResettableTCS ??= new ResettableBooleanCompletionSource(this);
_cachedResettableTCS = null;
if (_hasReachedCapacity || _queueLength < _buffer.Count)
{
_buffer[_head] = tcs;
}
else
{
_buffer.Add(tcs);
}
_queueLength++;
// increment _head for next time
_head++;
if (_head == _maxQueueCapacity)
{
_head = 0;
}
return tcs.GetValueTask();
}
}
当我们请求后调用_queuePolicy.OnExit();出栈,再将请求长度递减
public void OnExit()
{
lock (_bufferLock)
{
if (_queueLength == 0)
{
_freeServerSpots++;
if (_freeServerSpots > _maxConcurrentRequests)
{
_freeServerSpots--;
throw new InvalidOperationException("OnExit must only be called once per successful call to TryEnterAsync");
}
return;
}
// step backwards and launch a new task
if (_head == 0)
{
_head = _maxQueueCapacity - 1;
}
else
{
_head--;
}
//退出,出栈
_buffer[_head].Complete(true);
_queueLength--;
}
}
总结 基于栈结构的特点，在实际应用中，通常只会对栈执行以下两种操作：
队列存储结构的实现有以下两种方式：
以上就是本文的全部内容，希望对大家的学习有所帮助，也希望大家多多支持极客世界。 |
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