Skip to main content

Task.Yield(...), Task.Delay(...)

I think that a lot of person already heard about these new methods. In this post I want to clarify some things about these new methods that I saw that are not very clear.
We will start with Task.Yield(). The book definition of this method is: “Creates an awaitable that asynchronously yields back to the current context when awaited”. Let see what does it means in reality.
Yield gives us the possibility to leave the current async code (method or lambda expression) and allow other code to run in the underlying thread. Usually this is used when we have long running code that is executed in events (on main UI thread for example). In this case we want to allow other code to be executed on the UI thread. For this purpose the Yield method can be called. The rest of the function that need to be executed is posted back and will be executed after other messages that were waiting were executed.
For example we can have a for in an event handler that process items for a list. To permit the UI to execute not only our code we can use Yield.
public async void StartButton_Click(...)
{
    for( int i=0; i < list.Count; i++)
    {
        Process(list[i]);
        await Task.Yield();
    }
}
We use await in front of the Yield() because we want to wait until the other messages are processed. On the other side, we can use this method when our application uses threads from ThreadPool. If an action execute for long time, you don’t want other thread to block and wait for that current action. In this situation, using Yield() can permit other actions from the queue to be executed. In this way all the actions will be executed.
In background this method resumes the current action. We can compare this method to be something similar to a pause. When Yield() is called, the remaining action is posted back to the current context (it can be the TaskScheduler.Default or SynchronizationContext). After the rest of the code is executed, the rest of our action is resumed.
When you are working with tasks, especially when you want to simulate some behavior you will need a method to put a task to sleep. Thread.Sleep cannot be found anymore (for Metro style app). This method would put the thread on sleep, but we don’t want to freeze the UI thread or block another thread. Other actions could be executed on this thread.
For this purpose Task.Delay(…) was introduce. We can specify a delay time when the task will be suspended. Other tasks will be able to be executed on that read. In this way all the resources will be used at maximum. Optionally, you can specify a cancelation token that will be used if the task is canceled and stop the delay.

Comments

  1. Do not rely on await Task.Yield() to keep a UI responsive!
    http://msdn.microsoft.com/en-us/library/system.threading.tasks.task.yield.aspx

    ReplyDelete

Post a Comment

Popular posts from this blog

Windows Docker Containers can make WIN32 API calls, use COM and ASP.NET WebForms

After the last post , I received two interesting questions related to Docker and Windows. People were interested if we do Win32 API calls from a Docker container and if there is support for COM. WIN32 Support To test calls to WIN32 API, let’s try to populate SYSTEM_INFO class. [StructLayout(LayoutKind.Sequential)] public struct SYSTEM_INFO { public uint dwOemId; public uint dwPageSize; public uint lpMinimumApplicationAddress; public uint lpMaximumApplicationAddress; public uint dwActiveProcessorMask; public uint dwNumberOfProcessors; public uint dwProcessorType; public uint dwAllocationGranularity; public uint dwProcessorLevel; public uint dwProcessorRevision; } ... [DllImport("kernel32")] static extern void GetSystemInfo(ref SYSTEM_INFO pSI); ... SYSTEM_INFO pSI = new SYSTEM_INFO(

Azure AD and AWS Cognito side-by-side

In the last few weeks, I was involved in multiple opportunities on Microsoft Azure and Amazon, where we had to analyse AWS Cognito, Azure AD and other solutions that are available on the market. I decided to consolidate in one post all features and differences that I identified for both of them that we should need to take into account. Take into account that Azure AD is an identity and access management services well integrated with Microsoft stack. In comparison, AWS Cognito is just a user sign-up, sign-in and access control and nothing more. The focus is not on the main features, is more on small things that can make a difference when you want to decide where we want to store and manage our users.  This information might be useful in the future when we need to decide where we want to keep and manage our users.  Feature Azure AD (B2C, B2C) AWS Cognito Access token lifetime Default 1h – the value is configurable 1h – cannot be modified

What to do when you hit the throughput limits of Azure Storage (Blobs)

In this post we will talk about how we can detect when we hit a throughput limit of Azure Storage and what we can do in that moment. Context If we take a look on Scalability Targets of Azure Storage ( https://azure.microsoft.com/en-us/documentation/articles/storage-scalability-targets/ ) we will observe that the limits are prety high. But, based on our business logic we can end up at this limits. If you create a system that is hitted by a high number of device, you can hit easily the total number of requests rate that can be done on a Storage Account. This limits on Azure is 20.000 IOPS (entities or messages per second) where (and this is very important) the size of the request is 1KB. Normally, if you make a load tests where 20.000 clients will hit different blobs storages from the same Azure Storage Account, this limits can be reached. How we can detect this problem? From client, we can detect that this limits was reached based on the HTTP error code that is returned by HTTP