怎么在ASP.NET Core 3.x 中實現(xiàn)并發(fā)限制？針對這個問題，這篇文章詳細(xì)介紹了相對應(yīng)的分析和解答，希望可以幫助更多想解決這個問題的小伙伴找到更簡單易行的方法。
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Queue策略
添加Nuget
Install-Package Microsoft.AspNetCore.ConcurrencyLimiter
public void ConfigureServices(IServiceCollection services)
{
services.AddQueuePolicy(options =>
{
//較大并發(fā)請求數(shù)
options.MaxConcurrentRequests = 2;
//請求隊列長度限制
options.RequestQueueLimit = 1;
});
services.AddControllers();
}
public void Configure(IApplicationBuilder app, IWebHostEnvironment env)
{
//添加并發(fā)限制中間件
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();
});
}通過上面簡單的配置,我們就可以將他引入到我們的代碼中,從而做并發(fā)量限制,以及隊列的長度;那么問題來了,他是怎么實現(xiàn)的呢？
public static IServiceCollection AddQueuePolicy(this IServiceCollection services, Action configure)
{
services.Configure(configure);
services.AddSingleton();
return services;
}
QueuePolicy采用的是SemaphoreSlim信號量設(shè)計,SemaphoreSlim、Semaphore（信號量）支持并發(fā)多線程進(jìn)入被保護(hù)代碼,對象在初始化時會指定 較大任務(wù)數(shù)量,當(dāng)線程請求訪問資源,信號量遞減,而當(dāng)他們釋放時,信號量計數(shù)又遞增。
///
/// 構(gòu)造方法(初始化Queue策略)
///
///
public QueuePolicy(IOptions 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來限制任務(wù)較大個數(shù)
_serverSemaphore = new SemaphoreSlim(_maxConcurrentRequests);
}
ConcurrencyLimiterMiddleware中間件
///
/// Invokes the logic of the middleware.
///
/// The .
/// A that completes when the request leaves.
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);
}
}
每次當(dāng)我們請求的時候首先會調(diào)用_queuePolicy.TryEnterAsync(),進(jìn)入該方法后先開啟一個私有l(wèi)ock鎖,再接著判斷總請求量是否≥(請求隊列限制的大小+較大并發(fā)請求數(shù)),如果當(dāng)前數(shù)量超出了,那么我直接拋出,送你個503狀態(tài);
if (result)
{
try
{
await _next(context);
}
finally
{
_queuePolicy.OnExit();
}
}
else
{
ConcurrencyLimiterEventSource.Log.RequestRejected();
ConcurrencyLimiterLog.RequestRejectedQueueFull(_logger);
context.Response.StatusCode = StatusCodes.Status503ServiceUnavailable;
await _onRejected(context);
}問題來了,我這邊如果說還沒到你設(shè)置的大小呢,我這個請求沒有給你服務(wù)器造不成壓力,那么你給我處理一下吧.
await _serverSemaphore.WaitAsync();異步等待進(jìn)入信號量，如果沒有線程被授予對信號量的訪問權(quán)限，則進(jìn)入執(zhí)行保護(hù)代碼；否則此線程將在此處等待，直到信號量被釋放為止
lock (_totalRequestsLock)
{
if (TotalRequests >= _requestQueueLimit + _maxConcurrentRequests)
{
return false;
}
TotalRequests++;
}
//異步等待進(jìn)入信號量，如果沒有線程被授予對信號量的訪問權(quán)限，則進(jìn)入執(zhí)行保護(hù)代碼；否則此線程將在此處等待，直到信號量被釋放為止
await _serverSemaphore.WaitAsync();
return true;
}返回成功后那么中間件這邊再進(jìn)行處理,_queuePolicy.OnExit();通過該調(diào)用進(jìn)行調(diào)用_serverSemaphore.Release();釋放信號燈,再對總請求數(shù)遞減
Stack策略
再來看看另一種方法,棧策略,他是怎么做的呢？一起來看看.再附加上如何使用的代碼.
public void ConfigureServices(IServiceCollection services)
{
services.AddStackPolicy(options =>
{
//較大并發(fā)請求數(shù)
options.MaxConcurrentRequests = 2;
//請求隊列長度限制
options.RequestQueueLimit = 1;
});
services.AddControllers();
}通過上面的配置,我們便可以對我們的應(yīng)用程序執(zhí)行出相應(yīng)的策略.下面再來看看他是怎么實現(xiàn)的呢
public static IServiceCollection AddStackPolicy(this IServiceCollection services, Action configure)
{
services.Configure(configure);
services.AddSingleton();
return services;
}
可以看到這次是通過StackPolicy類做的策略.來一起來看看主要的方法
///
/// 構(gòu)造方法(初始化參數(shù))
///
///
public StackPolicy(IOptions options)
{
//棧分配
_buffer = new List();
//隊列大小
_maxQueueCapacity = options.Value.RequestQueueLimit;
//較大并發(fā)請求數(shù)
_maxConcurrentRequests = options.Value.MaxConcurrentRequests;
//剩余可用空間
_freeServerSpots = options.Value.MaxConcurrentRequests;
}
當(dāng)我們通過中間件請求調(diào)用,_queuePolicy.TryEnterAsync()時,首先會判斷我們是否還有訪問請求次數(shù),如果_freeServerSpots＞0,那么則直接給我們返回true,讓中間件直接去執(zhí)行下一步,如果當(dāng)前隊列＝我們設(shè)置的隊列大小的話,那我們需要取消先前請求;每次取消都是先取消之前的保留后面的請求;
public ValueTask TryEnterAsync()
{
lock (_bufferLock)
{
if (_freeServerSpots > 0)
{
_freeServerSpots--;
return _trueTask;
}
// 如果隊列滿了，取消先前的請求
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();
}
}
當(dāng)我們請求后調(diào)用_queuePolicy.OnExit();出棧,再將請求長度遞減
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,出棧
_buffer[_head].Complete(true);
_queueLength--;
}
}關(guān)于怎么在ASP.NET Core 3.x 中實現(xiàn)并發(fā)限制問題的解答就分享到這里了，希望以上內(nèi)容可以對大家有一定的幫助，如果你還有很多疑惑沒有解開，可以關(guān)注創(chuàng)新互聯(lián)行業(yè)資訊頻道了解更多相關(guān)知識。
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