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Why do I seem to have so few threads

I am trying to understand some code (for performance reasons) that is processing tasks from a queue. The code is C# .NET Framework 4.8 (And I didn't write this stuff)
I have this code creating a timer that from what I can tell should use a new thread every 10 seconds
_myTimer = new Timer(new TimerCallback(OnTimerGo), null, 0, 10000 );
Inside the onTimerGo it calls DoTask() inside of DoTask() it grabs a task off a queue and then does this
System.Threading.Tasks.Task.Factory.StartNew(ProcessTask, task).ContinueWith(c => DoTask());
My reading of this is that a new thread should start running OnTimerGo every 10 seconds, and that thread should in parralel run ProcessTask on tasks as fast as it can get them from the queue.
I inserted some code to call ThreadPool.GetMaxThreads and ThreadPool.GetAvailableThreads to figure out how many threads were in use. Then I queued up 10,000 things for it to do and let it loose.
I never see more then 4 threads in use at a time. This is running on a c4.4xlarge ec2 instance... so 16 vCPU 30 gb mem. The get max and available return over 2k. So I would expect more threads. By looking at the logging I can see that a total of 50ish different threads (by thread id) end up doing the work over the course of 20 minutes. Since the timer is set to every 10 seconds, I would expect 100 threads to be doing the work (or for it to finish sooner).
Looking at the code, the only time a running thread should stop is if it asks for a task from the queue and doesn't get one. Some other logging shows that there are never more than 2 tasks running in a thread. This is probably because they work is pretty fast. So the threads shouldn't be exiting, and I can even see from the logs that many of them end up doing as many as 500 tasks over the 20 minutes.
so... what am I missing here. Are the ThreadPool.GetMaxThreads and ThreadPool.GetAvailableThreads not accurate if run from inside a thread? Is something shutting down some of the threads while letting others keep going?
EDIT: adding more code
public static void StartScheduler()
{
lock (TimerLock)
{
if (_timerShutdown == false)
{
_myTimer = new Timer(new TimerCallback(OnTimerGo), null, 0, 10 );
const int numberOfSecondsPerMinute = 60;
const int margin = 1;
var pollEventsPerMinute = (numberOfSecondsPerMinute/SystemPreferences.TaskPollingIntervalSeconds);
_numberOfTimerCallsForHeartbeat = pollEventsPerMinute - margin;
}
}
}
private static void OnTimerGo(object state)
{
try
{
_lastTimer = DateTime.UtcNow;
var currentTickCount = Interlocked.Increment(ref _timerCallCount);
if (currentTickCount == _numberOfTimerCallsForHeartbeat)
{
Interlocked.Exchange(ref _timerCallCount, 0);
MonitoringTools.SendHeartbeatMetric(Heartbeat);
}
CheckForTasks();
}
catch (Exception e)
{
Log.Warn("Scheduler: OnTimerGo exception", e);
}
}
public static void CheckForTasks()
{
try
{
if (DoTask())
_lastStart = DateTime.UtcNow;
_lastStartOrCheck = DateTime.UtcNow;
}
catch (Exception e)
{
Log.Error("Unexpected exception checking for tasks", e);
}
}
private static bool DoTask()
{
Func<DataContext, bool> a = db =>
{
var mtid = Thread.CurrentThread.ManagedThreadId;
int totalThreads = Process.GetCurrentProcess().Threads.Count;
int maxWorkerThreads;
int maxPortThreads;
ThreadPool.GetMaxThreads(out maxWorkerThreads, out maxPortThreads);
int AvailableWorkerThreads;
int AvailablePortThreads;
ThreadPool.GetAvailableThreads(out AvailableWorkerThreads, out AvailablePortThreads);
int usedWorkerThreads = maxWorkerThreads - AvailableWorkerThreads;
string usedThreadMessage = $"Thread {mtid}: Threads in Use count: {usedWorkerThreads}";
Log.Info(usedThreadMessage);
var taskTypeAndTasks = GetTaskListTypeAndTasks();
var task = GetNextTask(db, taskTypeAndTasks.Key, taskTypeAndTasks.Value);
if (_timerShutdown)
{
Log.Debug("Task processing stopped.");
return false;
}
if (task == null)
{
Log.DebugFormat("DoTask: Idle in thread {0} ({1} tasks running)", mtid, _processingTaskLock);
return false;
}
Log.DebugFormat("DoTask: starting task {2}:{0} on thread {1}", task.Id, mtid, task.Class);
System.Threading.Tasks.Task.Factory.StartNew(ProcessTask, task).ContinueWith(c => DoTask());
Log.DebugFormat("DoTask: done ({0})", mtid);
return true;
};
return DbExtensions.WithDbWrite(ctx => a(ctx));
}

The Task.Factory.StartNew by default doesn't create a new thread. It borrows a thread from the ThreadPool instead.
The ThreadPool is intended as a small pool of reusable threads, to help amortize the cost of running frequent and lightweight operations like callbacks, continuations, event handers etc. Depleting the ThreadPool from available workers by scheduling too much work on it, results in a situation that is called saturation or starvation. And as you've already figured out, it's not a happy situation to be.
You can prevent the saturation of the ThreadPool by running your long-running work on dedicated threads instead of ThreadPool threads. This can be done by passing the TaskCreationOptions.LongRunning as argument to the Task.Factory.StartNew:
_ = Task.Factory.StartNew(ProcessTask, task, CancellationToken.None,
TaskCreationOptions.LongRunning,
TaskScheduler.Default).ContinueWith(t => DoTask(), CancellationToken.None,
TaskContinuationOptions.ExecuteSynchronously,
TaskScheduler.Default);
The above code schedules the ProcessTask(task) on a new thread, and after the invocation is completed either successfully or unsuccessfully, the DoTask will be invoked on the same thread. Finally the thread will be terminated. The discard _ signifies that the continuation Task (the task returned by the ContinueWith) is fire-and-forget. Which, to put it mildly, is architecturally suspicious. 😃
In case you are wondering why I pass the TaskScheduler.Default explicitly as argument to StartNew and ContinueWith, check out this link.

My reading of this is that a new thread should start running OnTimerGo every 10 seconds, and that thread should in parralel run ProcessTask on tasks as fast as it can get them from the queue.
Well, that is definitely not what's happening. It's a lot of uncertainty about your code, but it's clear that another DoTask is starting AFTER ProcessTask completes. And that is not parallel execution. Your line of code is this
System.Threading.Tasks.Task.Factory.StartNew(ProcessTask, task).ContinueWith(c => DoTask());
I suggest you to start another DoTask right there like this:
System.Threading.Tasks.Task.Factory.StartNew(ProcessTask, task);
DoTask();
Make sure your code is ready for parallel execution, though.

Is parallel asynchronous execution where a thread sleeps using multiple threads?

This is the code that I wrote to better understand asynchronous methods. I knew that an asynchronous method is not the same as multithreading, but it does not seem so in this particular scenario:
class Program
{
static void Main(string[] args)
{
Thread.CurrentThread.CurrentCulture = new System.Globalization.CultureInfo("en-US");
//the line above just makes sure that the console output uses . to represent doubles instead of ,
ExecuteAsync();
Console.ReadLine();
}
private static async Task ParallelAsyncMethod() //this is the method where async parallel execution is taking place
{
List<Task<string>> tasks = new List<Task<string>>();
for (int i = 0; i < 5; i++)
{
tasks.Add(Task.Run(() => DownloadWebsite()));
}
var strings = await Task.WhenAll(tasks);
foreach (var str in strings)
{
Console.WriteLine(str);
}
}
private static string DownloadWebsite() //Imitating a website download
{
Thread.Sleep(1500); //making the thread sleep for 1500 miliseconds before returning
return "Download finished";
}
private static async void ExecuteAsync()
{
var watch = Stopwatch.StartNew();
await ParallelAsyncMethod();
watch.Stop();
Console.WriteLine($"It took the machine {watch.ElapsedMilliseconds} milliseconds" +
$" or {Convert.ToDouble(watch.ElapsedMilliseconds) / 1000} seconds to complete this task");
Console.ReadLine();
}
}
//OUTPUT:
/*
Download finished
Download finished
Download finished
Download finished
Download finished
It took the machine 1537 milliseconds or 1.537 seconds to complete this task
*/
As you can see, the DownloadWebsite method waits for 1.5 seconds and then returns "a". The method called ParallelAsyncMethod adds five of these methods into the "tasks" list and then starts the parallel asynchronous execution. As you can see, I also tracked the amount of time that it takes for the ExecuteAsync method to be executed. The result is always somewhere around 1540 milliseconds. Here is my question: if the DownloadWebsite method required a thread to sleep 5 times for 1500 milliseconds, does it mean that the parallel execution of these methods required 5 different threads? If not, then how come it only took the program 1540 milliseconds to be executed and not ~7500 ms?

I knew that an asynchronous method is not the same as multi-threading
That is correct, an asynchronous method releases the current thread whilst I/O occurs, and schedules a continuation after it's completion.
Async and threads are completely unrelated concepts.
but it does not seem so in this particular scenario
That is because you explicitly run DownloadWebsite on the ThreadPool using Task.Run, which imitates asynchronous code by returning a Task after instructing the provided delegate to run.
Because you are not waiting for each Task to complete before starting the next, multiple threads can be used simultaneously.
Currently each thread is being blocked, as you have used Thread.Sleep in the implementation of DownloadWebsite, meaning you are actually running 5 synchronous methods on the ThreadPool.
In production code your DownloadWebsite method should be written asynchronously, maybe using HttpClient.GetAsync:
private static async Task<string> DownloadWebsiteAsync()
{
//...
await httpClinet.GetAsync(//...
//...
}
In that case, GetAsync returns a Task, and releases the current thread whilst waiting for the HTTP response.
You can still run multiple async methods concurrently, but as the thread is released each time, this may well use less than 5 separate threads and may even use a single thread.
Ensure that you dont use Task.Run with an asynchronous method; this simply adds unnecessary overhead:
var tasks = new List<Task<string>>();
for (int i = 0; i < 5; i++)
{
tasks.Add(DownloadWebsiteAsync()); // No need for Task.Run
}
var strings = await Task.WhenAll(tasks);
As an aside, if you want to imitate an async operation, use Task.Delay instead of Thread.Sleep as the former is non-blocking:
private static async Task<string> DownloadWebsite() //Imitating a website download
{
await Task.Delay(1500); // Release the thread for ~1500ms before continuing
return "Download finished";
}

Throttling in multithread console application

My console application opens 100 threads which do exactly the same - sends some date to host in internal network. The host is very responsive, I have checked that it can handle much bigger number of requests in every second. The console application also is quite primitive and responsive (it doesn't use database or something) - it only sends requests to host. Increasing the number of threads doesn't improve the speed. It seems something is throttling the speed of communication the app with the host. Moreover I have run three instances of the same console application in the same time, and they have made 3x time more, so it seems the limitation is one the level of application.
I have already increased DefaultConnectionLimit but with no effect.
class Program
{
static void Main(string[] args)
{
System.Net.ServicePointManager.DefaultConnectionLimit = 200;
for (var i = 1; i <= 100; i++)
{
int threadId = i;
Thread thread = new Thread(() =>
{
Testing(threadId);
});
thread.Start();
}
}
private static void Testing(int threadId)
{
//just communicate with host
}
}

The thing is that craeting more threads than you have cores in your processors is pointless.
For example you have 4 cores and create 100 threads: where do you expect 96 threads to run? They have to wait and decrease of performance is due to creating and managing unnecessary threads.
You should use ThreadPool, which will optimize number of threads created and scheduled to work.

Creation of a new Thread everytime is very expensive. You shouldn't create threads explicitly. Use task api instead to run this on threadpool:
var tasks = new Task[100];
for (var i = 0; i < 100; i++)
{
int threadId = i;
tasks[i] = Task.Run(() => Testing(threadId));
}
Task.WhenAll(tasks).GetAwaiter().GetResult();

Thread Local Storage working principle

This is an example about Thread Local Storage (TLS) from Apress parallel programming book. I know that if we have 4 cores computer 4 thread can run parallel in same time. In this example we create 10 task and we suppose that have 4 cores computer. Each Thread local storage live in on thread so when start 10 task parallel only 4 thread perform. And We have 4 TLS so 10 task try to change 4 Thread local storage object. i want to ask how Tls prevent data race problem when thread count < Task count ??
using System;
using System.Threading;
using System.Threading.Tasks;
namespace Listing_04
{
class BankAccount
{
public int Balance
{
get;
set;
}
}
class Listing_04
{
static void Main(string[] args)
{
// create the bank account instance
BankAccount account = new BankAccount();
// create an array of tasks
Task<int>[] tasks = new Task<int>[10];
// create the thread local storage
ThreadLocal<int> tls = new ThreadLocal<int>();
for (int i = 0; i < 10; i++)
{
// create a new task
tasks[i] = new Task<int>((stateObject) =>
{
// get the state object and use it
// to set the TLS data
tls.Value = (int)stateObject;
// enter a loop for 1000 balance updates
for (int j = 0; j < 1000; j++)
{
// update the TLS balance
tls.Value++;
}
// return the updated balance
return tls.Value;
}, account.Balance);
// start the new task
tasks[i].Start();
}
// get the result from each task and add it to
// the balance
for (int i = 0; i < 10; i++)
{
account.Balance += tasks[i].Result;
}
// write out the counter value
Console.WriteLine("Expected value {0}, Balance: {1}",
10000, account.Balance);
// wait for input before exiting
Console.WriteLine("Press enter to finish");
Console.ReadLine();
}
}
}

We have 4 TLS so 10 task try to change 4 Thread local storage object
In your example, you could have anywhere between 1 and 10 TLS slots. This is because a) you are not managing your threads explicitly and so the tasks are executed using the thread pool, and b) the thread pool creates and destroys threads over time according to demand.
A loop of only 1000 iterations will completely almost instantaneously. So it's likely all ten of your tasks will get through the thread pool before the thread pool decides a work item has been waiting long enough to justify adding any new threads. But there is no guarantee of this.
Some important parts of the documentation include these statements:
By default, the minimum number of threads is set to the number of processors on a system
and
When demand is low, the actual number of thread pool threads can fall below the minimum values.
In other words, on your four-core system, the default minimum number of threads is four, but the actual number of threads active in the thread pool could in fact be less than that. And if the tasks take long enough to execute, the number of active threads could rise above that.
The biggest thing to keep in mind here is that using TLS in the context of a thread pool is almost certainly the wrong thing to do.
You use TLS when you have control over the threads, and you want a thread to be able to maintain some data private or unique to that thread. That's the opposite of what happens when you are using the thread pool. Even in the simplest case, multiple tasks can use the same thread, and so would wind up sharing TLS. And in more complicated scenarios, such as when using await, a single task could wind up executed in different threads, and so that one task could wind up using different TLS values depending on what thread is assigned to that task at that moment.
how Tls prevent data race problem when thread count < Task count ??
That depends on what "data race problem" you're talking about.
The fact is, the code you posted is filled with problems that are at the very least odd, if not outright wrong. For example, you are passing account.Balance as the initial value for each task. But why? This value is evaluated when you create the task, before it could ever be modified later, so what's the point of passing it?
And if you thought you were passing whatever the current value is when the task starts, that seems like that would be wrong too. Why would it be valid to make the starting value for a given task vary according to how many tasks had already completed and been accounted for in your later loop? (To be clear: that's not what's happening…but even if it were, it'd be a strange thing to do.)
Beyond all that, it's not clear what you thought using TLS here would accomplish anyway. When each task starts, you reinitialize the TLS value to 0 (i.e. the value of account.Balance that you've passed to the Task<int> constructor). So no thread involved ever sees a value other than 0 during the context of executing any given task. A local variable would accomplish exactly the same thing, without the overhead of TLS and without confusing anyone who reads the code and tries to figure out why TLS was used when it adds no value to the code.
So, does TLS solve some sort of "data race problem"? Not in this example, it doesn't appear to. So asking how it does that is impossible to answer. It doesn't do that, so there is no "how".
For what it's worth, I modified your example slightly so that it would report the individual threads that were assigned to the tasks. I found that on my machine, the number of threads used varied between two and eight. This is consistent with my eight-core machine, with the variation due to how much the first thread in the pool can get done before the pool has initialized additional threads and assigned tasks to them. Most commonly, I would see the first thread completing between three and five of the tasks, with the remaining tasks handled by remaining individual threads.
In each case, the thread pool created eight threads as soon as the tasks were started. But most of the time, at least one of those threads wound up unused, because the other threads were able to complete the tasks before the pool was saturated. That is, there is overhead in the thread pool just managing the tasks, and in your example the tasks are so inexpensive that this overhead allows one or more thread pool threads to finish one task before the thread pool needs that thread for another.
I've copied that version below. Note that I also added a delay between trial iterations, to allow the thread pool to terminate the threads it created (on my machine, this took 20 seconds, hence the delay time hard-coded…you can see the threads being terminated in the debugger output).
static void Main(string[] args)
{
while (_PromptContinue())
{
// create the bank account instance
BankAccount account = new BankAccount();
// create an array of tasks
Task<int>[] tasks = new Task<int>[10];
// create the thread local storage
ThreadLocal<int> tlsBalance = new ThreadLocal<int>();
ThreadLocal<(int Id, int Count)> tlsIds = new ThreadLocal<(int, int)>(
() => (Thread.CurrentThread.ManagedThreadId, 0), true);
for (int i = 0; i < 10; i++)
{
int k = i;
// create a new task
tasks[i] = new Task<int>((stateObject) =>
{
// get the state object and use it
// to set the TLS data
tlsBalance.Value = (int)stateObject;
(int id, int count) = tlsIds.Value;
tlsIds.Value = (id, count + 1);
Console.WriteLine($"task {k}: thread {id}, initial value {tlsBalance.Value}");
// enter a loop for 1000 balance updates
for (int j = 0; j < 1000; j++)
{
// update the TLS balance
tlsBalance.Value++;
}
// return the updated balance
return tlsBalance.Value;
}, account.Balance);
// start the new task
tasks[i].Start();
}
// Make sure this thread isn't busy at all while the thread pool threads are working
Task.WaitAll(tasks);
// get the result from each task and add it to
// the balance
for (int i = 0; i < 10; i++)
{
account.Balance += tasks[i].Result;
}
// write out the counter value
Console.WriteLine("Expected value {0}, Balance: {1}", 10000, account.Balance);
Console.WriteLine("{0} thread ids used: {1}",
tlsIds.Values.Count,
string.Join(", ", tlsIds.Values.Select(t => $"{t.Id} ({t.Count})")));
System.Diagnostics.Debug.WriteLine("done!");
_Countdown(TimeSpan.FromSeconds(20));
}
}
private static void _Countdown(TimeSpan delay)
{
System.Diagnostics.Stopwatch sw = System.Diagnostics.Stopwatch.StartNew();
TimeSpan remaining = delay - sw.Elapsed,
sleepMax = TimeSpan.FromMilliseconds(250);
int cchMax = $"{delay.TotalSeconds,2:0}".Length;
string format = $"\r{{0,{cchMax}:0}}", previousText = null;
while (remaining > TimeSpan.Zero)
{
string nextText = string.Format(format, remaining.TotalSeconds);
if (previousText != nextText)
{
Console.Write(format, remaining.TotalSeconds);
previousText = nextText;
}
Thread.Sleep(remaining > sleepMax ? sleepMax : remaining);
remaining = delay - sw.Elapsed;
}
Console.Write(new string(' ', cchMax));
Console.Write('\r');
}
private static bool _PromptContinue()
{
Console.Write("Press Esc to exit, any other key to proceed: ");
try
{
return Console.ReadKey(true).Key != ConsoleKey.Escape;
}
finally
{
Console.WriteLine();
}
}

Code works but seems to run synchronously not asynchronously

static void Main(string[] args)
{
// do async method for each stock in the list
Task<IEnumerable<string>> symbols = Helper.getStockSymbols("amex", 0);
List<Task> tasks = new List<Task>();
try
{
for (int i = 0; i < symbols.Result.Count(); i++)
{
if (i < symbols.Result.Count())
{
string symbol = symbols.Result.ElementAtOrDefault(i);
Task t = Task.Run(() => getCalculationsDataAsync(symbol, "amex"));
tasks.Add(t);
Task e = t.ContinueWith((d) => getThreadStatus(tasks));
}
}
// don't exit until they choose to
while (args.FirstOrDefault() != "exit")
{
// do nothing
}
}
catch (Exception ex)
{
Console.WriteLine(ex.Message);
}
}
public static void getThreadStatus(List<Task> taskList)
{
int count = 0;
foreach (Task t in taskList)
{
if (t.Status == TaskStatus.Running)
{
count += 1;
}
}
Console.WriteLine(count + " threads are running.");
}
public static async Task getCalculationsDataAsync(string symbol, string market)
{
// do calculation here
}
What I'm trying to do in my code is run a new task for each stock in my list and run them all at the same time. I have a 4 core processor and I believe that means I can only run 4 tasks at once. I tried testing how many tasks were running by inserting the continuewith method that you see in my code that will tell me how many tasks are running. When I run this code, it tells me that 0 tasks are running so my questions are:
How can I complete my objective by running these tasks at the same exact time?
Why is it telling me that 0 tasks are running? I can only assume this is because the current task is finished and it hasn't started a new one yet if the tasks are running one after the other.

I am not sure why you are seeing no task running. Are you sure your Task.Run() is being hit? That is to say is i < symbols.Result.Count() satisfied?
Regardless of the above, let us try and achieve what you want. Firstly, no, it is not correct to say that because your machine has four physical cores/'threads', that you can use a maximum of four Threads. These are not the same things. A Google on this subject will bring a plethora of information your way about this.
Basically starting a thread the way you have will start background threads on a thread pool, and this thread pool can hold/govern numerous threads see Threading in C# by J. Albahari for more information. Whenever you start a thread, a few hundred microseconds are spent organizing such things as a fresh private local variable stack. Each thread also consumes (by default) around 1 MB of memory. The thread pool cuts these overheads by sharing and recycling threads, allowing multithreading to be applied at a very granular level without a performance penalty. This is useful when leveraging multicore processors to execute computationally intensive code in parallel in “divide-and-conquer” style.
The thread pool also keeps a lid on the total number of worker threads it will run simultaneously. Too many active threads throttle the operating system with administrative burden and render CPU caches ineffective. Once a limit is reached, jobs queue up and start only when another finishes.
Okay, now for your code. Let us say we have a list of stock types
List<string> types = new List<string>() { "AMEX", "AMEC", "BP" };
To dispatch multiple threads to do for for each of these (not using async/await), you could do something like
foreach (string t in types)
{
Task.Factory.StartNew(() => DoSomeCalculationForType(t));
}
This will fire of three background thread pool threads and is non-blocking, so this code will return to caller almost immediately.
If you want to set up post processing you can do this via continuations and continuation chaining. This is all described in the Albahari link I provided above.
I hope this helps.
--
Edit. to address comments:
Beginning with the .NET Framework version 4, the default size of the thread pool for a process depends on several factors, such as the size of the virtual address space. A process can call the GetMaxThreads method to determine the number of threads.
However, there's something else at play: the thread pool doesn't immediately create new threads in all situations. In order to cope with bursts of small tasks, it limits how quickly it creates new threads. IIRC, it will create one thread every 0.5 seconds if there are outstanding tasks, up to the maximum number of threads. I can't immediately see that figure documented though, so it may well change. I strongly suspect that's what you're seeing though. Try queuing a lot of items and then monitor the number of threads over time.
Basically let the thread pool dispatch what it wants, its optimizer will do the best job for your circumstance.

I think the problem is that the tasks have a status of Running either very briefly or can skip that status all together and go straight from WaitingForActivation to RanToCompletion.
I modified your program slightly and i can see the tasks starting and completing but they don't appear to be in the Running state whenever I check.
static void Main(string[] args)
{
// do async method for each stock in the list
Task<IEnumerable<string>> symbols = Task.FromResult(Enumerable.Range(1, 5).Select (e => e.ToString()));
List<Task> tasks = new List<Task>();
try
{
for (int i = 0; i < symbols.Result.Count(); i++)
{
string symbol = symbols.Result.ElementAtOrDefault(i);
Task t = getCalculationsDataAsync(symbol, "amex", tasks);
tasks.Add(t);
}
Console.WriteLine("Tasks Count:"+ tasks.Count());
Task.WaitAll(tasks.ToArray());
}
catch (Exception ex)
{
Console.WriteLine(ex.Message);
}
}
public static void getThreadStatus(List<Task> taskList)
{
int count = 0;
foreach (Task t in taskList)
{
Console.WriteLine("Status " + t.Status);
if (t.Status == TaskStatus.Running)
{
count += 1;
Console.WriteLine("A task is running");
}
}
//Console.WriteLine(count + " threads are running.");
}
public static async Task getCalculationsDataAsync(string symbol, string market, List<Task> tasks)
{
Console.WriteLine("Starting task");
var delay = new Random((int)DateTime.Now.Ticks).Next(5000);
Console.WriteLine("Delay:" + delay);
await Task.Delay(delay);
Console.WriteLine("Finished task");
getThreadStatus(tasks);
}
Output
Starting task
Delay:1784
Starting task
Delay:2906
Starting task
Delay:2906
Starting task
Delay:2906
Starting task
Delay:2906
Tasks Count:5
Finished task
Status WaitingForActivation
Status WaitingForActivation
Status WaitingForActivation
Status WaitingForActivation
Status WaitingForActivation
Finished task
Finished task
Finished task
Status RanToCompletion
Status RanToCompletion
Status WaitingForActivation
Status WaitingForActivation
Status RanToCompletion
Status WaitingForActivation
Status WaitingForActivation
Status WaitingForActivation
Status WaitingForActivation
Status WaitingForActivation
Status WaitingForActivation
Status WaitingForActivation
Status WaitingForActivation
Status WaitingForActivation
Status WaitingForActivation
Finished task
Status RanToCompletion
Status RanToCompletion
Status RanToCompletion
Status RanToCompletion
Status WaitingForActivation

As I describe on my blog, there are two kinds of tasks: Delegate Tasks and Promise Tasks. Only Delegate Tasks ever actually run. Promise Tasks only complete. The task returned by Task.Run is a Promise Task, not a Delegate Task; this is necessary so that Task.Run can understand async code and only complete when the async code is completed.
So, checking for TaskStatus.Running is not going to work the way you want. Instead, you can create a counter:
private static int _count;
static void Main(string[] args)
{
...
for (int i = 0; i < symbols.Result.Count(); i++)
{
if (i < symbols.Result.Count())
{
string symbol = symbols.Result.ElementAtOrDefault(i);
Task t = Task.Run(() => getCalculationsDataWithCountAsync(symbol, "amex"));
tasks.Add(t);
}
}
...
}
public static async Task getCalculationsDataWithCountAsync(string symbol, string market)
{
Console.WriteLine(Interlocked.Increment(ref _count) + " threads are running.");
try
{
await getCalculationsDataAsync(symbol, market);
}
finally
{
Console.WriteLine(Interlocked.Decrement(ref _count) + " threads are running.");
}
}
Note that I used a separate async "wrapper" method instead of messing with ContinueWith. Code using await instead of ContinueWith more correctly handles a number of edge cases, and IMO is clearer to read.
Also, remember that async and await free up threads while they're "awaiting." So, you can potentially have hundreds of (asynchronous) tasks going simultaneously; this does not imply that there are that many threads.