TPL, Async & Soluto

• Introduced in .net 4.0
• Aimed to leverage multi-core processors
• Better abstractions to design concurrent applications.
• Designed to handle concurrency challenges better
  
• Synchronization - locking, dead locks, race condition
• Debugging
• Code Complexity

• Provide data structures aimed for concurrency
• ConcurrentQueue<T>, ConcurrentDictionary<T>, Lazy<T>
• Provide data-parallelism capabilities
  
• AsParallel, PLINQ...
• Partition the data
• Distribute some logic on data on multiple-threads or cores 
•  Task parallelism capabilities ...

• Break program into multiple operations
• Run operations in parallel
• Combine operations with continuation
• Schedule and keep track on ongoing operations

• TASK<T> -  represents a T that is being computed asynchronously and will be available in the future, if it isn't already

• TASK - same with task, but without return value, a bit like Task<void>

• Using Task.Run 
• Task.Run( ()=> DoOtherThing() )
• Run code on TaskScheduler (ThreadPool)
• Task.FromResult()
• From other tasks
• From promises (TaskCompletionSource)

• Wait(), Result - blocking , should be avoided in most cases.

 Task a = Task.Run( ()=> CountToTen())
 Launch(a.Result); 

• ContinueWith() - continuation, allow us to schedule a new task, that get the original resolved task as an argument.

Task a = Task.Run( ()=> CountToTen());
a.ContinueWith( t => Launch(t.Result))); 

• Task not only wrap the result, but also wrap the exception if one has occurred

 Task someTask = Task.Run(()=>doSomethingDangerous()) someTask.ContinueWith((t)=> {
    if (t.IsFaulted)        Log(t.Exception)
    else
        Launch(t.Result)
});

• Could also be written as:

 someTask.ContinueWith( t=> Log(t.Exception), TaskContinuationOptions.OnlyOnFaulted)someTask.ContinueWith( t=> Launch(t.Result), TaskContinuationOptions.OnlyOnRanToCompletion);

• Task can only resolve once, it has final state.
  

 var firstTask = Task.Run(()=>GetSomeData()) var secondTask = firstTask.ContinueWith((t) => ProcessSomeData(t.Result)) var thirdTask = secondTask.ContinueWith((t)=>sendProcessedData(t.Result))

• Tasks are passable as objects

void Click_GetDataButton(Object o, EventArgs e)
{
    GetData().ContinueWith((t)=>showMessage(t.Result))
}
Task<string> GetData()
{    Task<IDbClient> firstTask = Task.Run(()=>getDBClient())    Task<IEnumarable<String>> secondTask = firstTask.ContinueWith((t)=>t.Result.query(someQuery))

    Task<string> thirdTask = 
                       secondTask.ContinueWith((t)=> someMerge(t.Result))    return thirdTask;
}

 Task<int> firstParallelTask = Task.Run( ()=> ComputeOneThing() )
 Task<int> secondParallelTask = Task.Run( ()=> ComputeOtherThing() )

 Task<int[]> allTasks = Task.WhenAll(firstParallelTask ,secondParallelTask);

Task<int> mergeTask = allTasks.ContinuteWith( (t) => SomeMerge(t.Result[0], t.Result[1]))

return mergeTask; //wrap the result of the merge opeation

• Cancellation - We can pass a cancellation token to abort operation. Tokens can propagate along the continuation chain. (for example downloading a large file)

• Progress - IProgress interface allow us to notify the caller on progress update. (for example downloading a large file)
  

• Threads are memory expensive
• Context switches are expensive
• Using threads, we trade efficiency for responsiveness
• IO operations are long, if we create a thread per IO operation we waste lots of memory and CPU for thread management.
• And  in common web application servers, we have at least one thread per incoming request that simply wait for db.
• So, it doesn't scale that well.

Why is it the default programming model for the web?

• Web is been for years the one of lowest level of programming.
• It's simpler and safer.
• Writing asynchronous code is more difficult, and  you can easily find yourself in a callback hell.
• DB was believed to be the bottleneck in most of web applications, and the benefits we can get from this optimization was simply not worth it for most cases.
  
• Web used mainly request - response based operations,
  no long-lasting operations

• So, the idea is instead of sending an IO request and waiting for response, we put the request in some queue, and get a notification with the data when it's ready.
• We can look at it simply as callback, underlying implementation can be different based on runtime,
  OS and/or hardware drivers. 

• APM - Asynchronous Programming model
  
• BeginXXX, EndXXX, IAsyncResult, AsyncDelegate

• EAP - Event-based Asynchronous pattern
• WebClient.DownloadStringCompleted += ()...

• Introduced in .net 4.5, based entirely on Tasks
• IO classes/clients have methods with Async/TaskAsync suffix.
• All those method return task<T>.
• For example : WebClientDownloadStringTaskAsync (url)

• Tasks have final state, so you can attach continuation in any time.
• They wrap the result of the operation, making them passable as objects.
• Tasks are compos-able, as we saw, we can join tasks together, and create another tasks
• Tasks wrap exceptions, and are easier to debug
• Tasks support cancellation
• And a bit more...

• Javascript - jQuery deferred, ES6 Promises, Q...
• Java -  Future, Java 8 CompletableFuture, google Guava ListenableFuture, SettableFuture
• .Net Tasks & TaskCompletionSource
• C++ std::future, std::promise
• There are basically implementations for almost every language.
  
  http://en.wikipedia.org/wiki/Futures_and_promises

• Writing in a synchronous manner is still simpler 
• Even with continuation and named methods, async code can be still ugly, and less readable

ReadString()
.ContinueWith((t)=> ConnectToDb(t.Result)).Unwrap().ContinueWith((t)=> RetrieveData(t.Result)).Unwrap().ContinueWith((t)=> HandleResponse(t.Result))

  public Task<int> CountSomething()
  {
    Task<string> conStringTask = ReadConnectionStringAsync();
    Task<IDbProvider> dbTask = conStringTask.ContinueWith((t)=> 
ConnectToDbAsync(t.Result), TaskContinuationOption.OnlyOnRanToCompletion).Unwrap();    Task<int> queryTask = dbTask.ContinueWith((t)=>t.Result.QueryAsync("count * from something", TaskContinuationOption.OnlyOnRanToCompletion)).Unwrap();    return queryTask;
  }

• Implement continuation in a synchronized fashion using code generation.
• Simple with magic keywords, async and await.
• Same Example:
  

  public async Task<int> CountSomething()
  {
     try
     {
          string conString = await ReadConnectionStringAsync();
          IDbProvider db = await ConnectToDbAsync(conString);
     }
     catch (Exception e)
     {
        //handle exception
     }
     int someCalc = await db.QueryAsync("count * from something");
     return someCalc;
  } 

• That we can use await in that method body
• That we are going to return a Task (async void is exception)
• The task object that wraps the result is auto generated by the compiler

  Color favoriteColor = await GetUserFavoriteColorFromDb(userId)

public async Task<int> SumSomeData(key1, key2)
{   
   try
   {     string conString = await ReadConnectionStringAsync()
     IDbProvider db = await ConnectToDbAsync(conString);
   }
   catch (Exception e)
   {
      //handle exception
   }   Task<int> someDataTask = db.ReadAsync(key1);
   Task<int> otherDataTask = db.ReadAsync(key2);   // Both tasks run in parallel!
   int sum = (await someDataTask) + (await otherDataTask);
   return sum; // use var instead of explicit types in real code
}  

• async-await reduce most shortcoming related to writing async code.
• It makes flow better, and provide much easier exception handling.
• Using "async all the way" significantly improve scaleability, and performance in some cases.
• Tasks & Futures are really good abstraction for writing high-concurrent apps, and async/await plays with them perfectly.
• The only different cases are heavily optimized code, or legacy code in which migration won't produce enough benefits.

• When we are in async context, we must not use blocking code, a Task represent an async operation, and since we didn't use Task.Run, we are running on shared context with other async methods.

• Which means that instead of:
• Thread.Sleep -> use await Task.Delay() instead
• Locks -> use async-supported locking mechanism if you have to such as SemaphoreSlim
• Parallel.For/ForEach -> use await Task.WhenAll
• Lazy<T> -> use AsyncLazy<T> instead
• IO operations -> use async versions.
• MVC Filters -> WebApi async Filters
• Task.WaitAll/WaitAny -> await Task.WhenAll/WhenAny
• Any other blocking operation that doesn't have async implementation should run with await Task.Run()

• Async methods are the simplest way to create tasks
• TaskCompletionSource<T> -> can be used to translate EAP, Timer-based, or any other asynchronous mechanism to Tasks, mainly used for IO operations.
• Task.Run -> Should be used to cpu-bound operations.
  
• Task.Run -> could also be used for migrating older code as a temporary solution.

• Task objects mustn't be null.
• Remember! Async methods always return Task.

 public async Task<string> GetSomeString()
{   return null; //still return Task that wrap the value null}

• Non-async methods that return task should never return null Task.

 public Task<string> GetSomeString()
{    //return null -> don't use!    return Task.FromResult(null);}

• Don't use Task Constructor.
• Async all the way - avoid consuming tasks in a blocking way. Don't use Task.Result, Task.Wait(), Task.WaitAll(), Task.WaitAny() - in simple cases, it will result in a performance degradation, in worst case it can cause deadlocks due to SynchronizationContext.
• Unit Testing are exceptional.

• Use FakeItEasy in testing - TypeMock doesn't play well with task objects.
• Tasks can be easily faked with Result via Task.FromResult

• Or even simpler:

 int avg = await (StocksLists.Select( async () => await GetCurrentPriceAsync()).WhenAll()).Average();

• TableDataContext ->have task-based Api that wrap azure storage async method.
• LiveRole -> Queue message to agent, was turned into async to improve scalability.
• LiveStateWeb -> Check the live state of agent, created as Async asp.net mvc role, we also use TaskCompletionSource to wrap messaging async event based Api.
• AnalyticsListenerRole -> Asp.net mvc async role, aimed to handle incoming analytics event.
• Mobile View -> All mobile view endpoints were converted to async, it's still not optimal tough because of the heavily use of await Task.Run on older not task-based Api.