We Keep Coding

Creating a class that runs tasks sequentially [duplicate]

I know that asynchronous programming has seen a lot of changes over the years. I'm somewhat embarrassed that I let myself get this rusty at just 34 years old, but I'm counting on StackOverflow to bring me up to speed.
What I am trying to do is manage a queue of "work" on a separate thread, but in such a way that only one item is processed at a time. I want to post work on this thread and it doesn't need to pass anything back to the caller. Of course I could simply spin up a new Thread object and have it loop over a shared Queue object, using sleeps, interrupts, wait handles, etc. But I know things have gotten better since then. We have BlockingCollection, Task, async/await, not to mention NuGet packages that probably abstract a lot of that.
I know that "What's the best..." questions are generally frowned upon so I'll rephrase it by saying "What is the currently recommended..." way to accomplish something like this using built-in .NET mechanisms preferably. But if a third party NuGet package simplifies things a bunch, it's just as well.
I considered a TaskScheduler instance with a fixed maximum concurrency of 1, but seems there is probably a much less clunky way to do that by now.
Background
Specifically, what I am trying to do in this case is queue an IP geolocation task during a web request. The same IP might wind up getting queued for geolocation multiple times, but the task will know how to detect that and skip out early if it's already been resolved. But the request handler is just going to throw these () => LocateAddress(context.Request.UserHostAddress) calls into a queue and let the LocateAddress method handle duplicate work detection. The geolocation API I am using doesn't like to be bombarded with requests which is why I want to limit it to a single concurrent task at a time. However, it would be nice if the approach was allowed to easily scale to more concurrent tasks with a simple parameter change.

To create an asynchronous single degree of parallelism queue of work you can simply create a SemaphoreSlim, initialized to one, and then have the enqueing method await on the acquisition of that semaphore before starting the requested work.
public class TaskQueue
{
private SemaphoreSlim semaphore;
public TaskQueue()
{
semaphore = new SemaphoreSlim(1);
}
public async Task<T> Enqueue<T>(Func<Task<T>> taskGenerator)
{
await semaphore.WaitAsync();
try
{
return await taskGenerator();
}
finally
{
semaphore.Release();
}
}
public async Task Enqueue(Func<Task> taskGenerator)
{
await semaphore.WaitAsync();
try
{
await taskGenerator();
}
finally
{
semaphore.Release();
}
}
}
Of course, to have a fixed degree of parallelism other than one simply initialize the semaphore to some other number.

Your best option as I see it is using TPL Dataflow's ActionBlock:
var actionBlock = new ActionBlock<string>(address =>
{
if (!IsDuplicate(address))
{
LocateAddress(address);
}
});
actionBlock.Post(context.Request.UserHostAddress);
TPL Dataflow is robust, thread-safe, async-ready and very configurable actor-based framework (available as a nuget)
Here's a simple example for a more complicated case. Let's assume you want to:
Enable concurrency (limited to the available cores).
Limit the queue size (so you won't run out of memory).
Have both LocateAddress and the queue insertion be async.
Cancel everything after an hour.
var actionBlock = new ActionBlock<string>(async address =>
{
if (!IsDuplicate(address))
{
await LocateAddressAsync(address);
}
}, new ExecutionDataflowBlockOptions
{
BoundedCapacity = 10000,
MaxDegreeOfParallelism = Environment.ProcessorCount,
CancellationToken = new CancellationTokenSource(TimeSpan.FromHours(1)).Token
});
await actionBlock.SendAsync(context.Request.UserHostAddress);

Actually you don't need to run tasks in one thread, you need them to run serially (one after another), and FIFO. TPL doesn't have class for that, but here is my very lightweight, non-blocking implementation with tests. https://github.com/Gentlee/SerialQueue
Also have #Servy implementation there, tests show it is twice slower than mine and it doesn't guarantee FIFO.
Example:
private readonly SerialQueue queue = new SerialQueue();
async Task SomeAsyncMethod()
{
var result = await queue.Enqueue(DoSomething);
}

Use BlockingCollection<Action> to create a producer/consumer pattern with one consumer (only one thing running at a time like you want) and one or many producers.
First define a shared queue somewhere:
BlockingCollection<Action> queue = new BlockingCollection<Action>();
In your consumer Thread or Task you take from it:
//This will block until there's an item available
Action itemToRun = queue.Take()
Then from any number of producers on other threads, simply add to the queue:
queue.Add(() => LocateAddress(context.Request.UserHostAddress));

I'm posting a different solution here. To be honest I'm not sure whether this is a good solution.
I'm used to use BlockingCollection to implement a producer/consumer pattern, with a dedicated thread consuming those items. It's fine if there are always data coming in and consumer thread won't sit there and do nothing.
I encountered a scenario that one of the application would like to send emails on a different thread, but total number of emails is not that big.
My initial solution was to have a dedicated consumer thread (created by Task.Run()), but a lot of time it just sits there and does nothing.
Old solution:
private readonly BlockingCollection<EmailData> _Emails =
new BlockingCollection<EmailData>(new ConcurrentQueue<EmailData>());
// producer can add data here
public void Add(EmailData emailData)
{
_Emails.Add(emailData);
}
public void Run()
{
// create a consumer thread
Task.Run(() =>
{
foreach (var emailData in _Emails.GetConsumingEnumerable())
{
SendEmail(emailData);
}
});
}
// sending email implementation
private void SendEmail(EmailData emailData)
{
throw new NotImplementedException();
}
As you can see, if there are not enough emails to be sent (and it is my case), the consumer thread will spend most of them sitting there and do nothing at all.
I changed my implementation to:
// create an empty task
private Task _SendEmailTask = Task.Run(() => {});
// caller will dispatch the email to here
// continuewith will use a thread pool thread (different to
// _SendEmailTask thread) to send this email
private void Add(EmailData emailData)
{
_SendEmailTask = _SendEmailTask.ContinueWith((t) =>
{
SendEmail(emailData);
});
}
// actual implementation
private void SendEmail(EmailData emailData)
{
throw new NotImplementedException();
}
It's no longer a producer/consumer pattern, but it won't have a thread sitting there and does nothing, instead, every time it is to send an email, it will use thread pool thread to do it.

My lib, It can:
Run random in queue list
Multi queue
Run prioritize first
Re-queue
Event all queue completed
Cancel running or cancel wait for running
Dispatch event to UI thread
public interface IQueue
{
bool IsPrioritize { get; }
bool ReQueue { get; }
/// <summary>
/// Dont use async
/// </summary>
/// <returns></returns>
Task DoWork();
bool CheckEquals(IQueue queue);
void Cancel();
}
public delegate void QueueComplete<T>(T queue) where T : IQueue;
public delegate void RunComplete();
public class TaskQueue<T> where T : IQueue
{
readonly List<T> Queues = new List<T>();
readonly List<T> Runnings = new List<T>();
[Browsable(false), DefaultValue((string)null)]
public Dispatcher Dispatcher { get; set; }
public event RunComplete OnRunComplete;
public event QueueComplete<T> OnQueueComplete;
int _MaxRun = 1;
public int MaxRun
{
get { return _MaxRun; }
set
{
bool flag = value > _MaxRun;
_MaxRun = value;
if (flag && Queues.Count != 0) RunNewQueue();
}
}
public int RunningCount
{
get { return Runnings.Count; }
}
public int QueueCount
{
get { return Queues.Count; }
}
public bool RunRandom { get; set; } = false;
//need lock Queues first
void StartQueue(T queue)
{
if (null != queue)
{
Queues.Remove(queue);
lock (Runnings) Runnings.Add(queue);
queue.DoWork().ContinueWith(ContinueTaskResult, queue);
}
}
void RunNewQueue()
{
lock (Queues)//Prioritize
{
foreach (var q in Queues.Where(x => x.IsPrioritize)) StartQueue(q);
}
if (Runnings.Count >= MaxRun) return;//other
else if (Queues.Count == 0)
{
if (Runnings.Count == 0 && OnRunComplete != null)
{
if (Dispatcher != null && !Dispatcher.CheckAccess()) Dispatcher.Invoke(OnRunComplete);
else OnRunComplete.Invoke();//on completed
}
else return;
}
else
{
lock (Queues)
{
T queue;
if (RunRandom) queue = Queues.OrderBy(x => Guid.NewGuid()).FirstOrDefault();
else queue = Queues.FirstOrDefault();
StartQueue(queue);
}
if (Queues.Count > 0 && Runnings.Count < MaxRun) RunNewQueue();
}
}
void ContinueTaskResult(Task Result, object queue_obj) => QueueCompleted((T)queue_obj);
void QueueCompleted(T queue)
{
lock (Runnings) Runnings.Remove(queue);
if (queue.ReQueue) lock (Queues) Queues.Add(queue);
if (OnQueueComplete != null)
{
if (Dispatcher != null && !Dispatcher.CheckAccess()) Dispatcher.Invoke(OnQueueComplete, queue);
else OnQueueComplete.Invoke(queue);
}
RunNewQueue();
}
public void Add(T queue)
{
if (null == queue) throw new ArgumentNullException(nameof(queue));
lock (Queues) Queues.Add(queue);
RunNewQueue();
}
public void Cancel(T queue)
{
if (null == queue) throw new ArgumentNullException(nameof(queue));
lock (Queues) Queues.RemoveAll(o => o.CheckEquals(queue));
lock (Runnings) Runnings.ForEach(o => { if (o.CheckEquals(queue)) o.Cancel(); });
}
public void Reset(T queue)
{
if (null == queue) throw new ArgumentNullException(nameof(queue));
Cancel(queue);
Add(queue);
}
public void ShutDown()
{
MaxRun = 0;
lock (Queues) Queues.Clear();
lock (Runnings) Runnings.ForEach(o => o.Cancel());
}
}

I know this thread is old, but it seems all the present solutions are extremely onerous. The simplest way I could find uses the Linq Aggregate function to create a daisy-chained list of tasks.
var arr = new int[] { 1, 2, 3, 4, 5};
var queue = arr.Aggregate(Task.CompletedTask,
(prev, item) => prev.ContinueWith(antecedent => PerformWorkHere(item)));
The idea is to get your data into an IEnumerable (I'm using an int array), and then reduce that enumerable to a chain of tasks, starting with a default, completed, task.

How to properly delay when there is no task to wait for

I have a task that is waiting for a property to be set to true (= completed). The way I am receiving that property value change is via EventHandler (System.Diagnostics.Process.OutputDataReceived to be exact - it continuously reads the output of another process until the correct output is provided). However checking for the property all the time feels somewhat inefficiencient. I have tried adding a small delay of one tick because I believe I can allow myself such a wait if that would save CPU time, but I read .NET struggles with fractional milliseconds. Can I improve this code?
private ConcurrentBag<string> _allMessages = new ConcurrentBag<string>();
public OutputRetriever()
{
var process = new System.Diagnostics.Process();
...
process.OutputDataReceived += OutputDataReceived;
process.Start();
}
public async Task<string[]> GetAllOutput()
{
while (!IsCompleted)
{
// how to properly wait here?
// await Task.Delay(TimeSpan.FromTicks(1)); // is this ok?
}
return _allMessages.ToArray();
}
private void ConsoleDataReceived(object sender, DataReceivedEventArgs e)
{
_allMessages.Add(e?.Data);
if (e?.Data == "success")
{
IsCompleted = true;
}
}

The timers in Windows have a resolution of approx. 16 ms, so any delay below 16 ms cannot be precisely achieved. This applies to any timer - the .NET timers are just wrappers for Windows native timers.
Instead of busy-waiting in a loop, create a custom TaskCompletionSource<T> and return a Task that can be awaited.
class OutputRetriever
{
private readonly ConcurrentBag<string> _allMessages = new ConcurrentBag<string>();
private readonly TaskCompletionSource<string[]> _taskSource
= new TaskCompletionSource<string[]>();
// Note: this method is not async anymore
public Task<string[]> GetAllOutput()
{
// We just return a task that can be awaited
return _taskSource.Task;
}
void ConsoleDataReceived(object sender, DataReceivedEventArgs e)
{
_allMessages.Add(e?.Data);
if (e?.Data == "success")
{
// Here we notify that the task is completed by setting the result
_taskSource.SetResult(_allMessages.ToArray());
}
}
}
Now the clients can simply await the results as usual:
var receiver = new OutputReceiver();
string[] messages = await receiver.GetAllOutput();

Parallel processing using TPL in windows service

I have a windows service which is consuming a messaging system to fetch messages. I have also created a callback mechanism with the help of Timer class which helps me to check the message after some fixed time to fetch and process. Previously, the service is processing the message one by one. But I want after the message arrives the processing mechanism to execute in parallel. So if the first message arrived it should go for processing on one task and even if the processing is not finished for the first message still after the interval time configured using the callback method (callback is working now) next message should be picked and processed on a different task.
Below is my code:
Task.Factory.StartNew(() =>
{
Subsriber<Message> subsriber = new Subsriber<Message>()
{
Interval = 1000
};
subsriber.Callback(Process, m => m != null);
});
public static void Process(Message message)
{
if (message != null)
{
// Processing logic
}
else
{
}
}
But using the Task Factory I am not able to control the number of tasks in parallel so in my case I want to configure the number of tasks on which messages will run on the availability of the tasks?
Update:
Updated my above code to add multiple tasks
Below is the code:
private static void Main()
{
try
{
int taskCount = 5;
Task.Factory.StartNewAsync(() =>
{
Subscriber<Message> consumer = new
Subcriber<Message>()
{
Interval = 1000
};
consumer.CallBack(Process, msg => msg!=
null);
}, taskCount);
Console.ReadLine();
}
catch (Exception e)
{
Console.WriteLine(e.Message);
}
public static void StartNewAsync(this TaskFactory
target, Action action, int taskCount)
{
var tasks = new Task[taskCount];
for (int i = 0; i < taskCount; i++)
{
tasks[i] = target.StartNew(action);
}
}
public static void Process(Message message)
{
if (message != null)
{
}
else
{ }
}
}

I think what your looking for will result in quite a large sample. I'm trying just to demonstrate how you would do this with ActionBlock<T>. There's still a lot of unknowns so I left the sample as skeleton you can build off. In the sample the ActionBlock will handle and process in parallel all your messages as they're received from your messaging system
public class Processor
{
private readonly IMessagingSystem _messagingSystem;
private readonly ActionBlock<Message> _handler;
private bool _pollForMessages;
public Processor(IMessagingSystem messagingSystem)
{
_messagingSystem = messagingSystem;
_handler = new ActionBlock<Message>(msg => Process(msg), new ExecutionDataflowBlockOptions()
{
MaxDegreeOfParallelism = 5 //or any configured value
});
}
public async Task Start()
{
_pollForMessages = true;
while (_pollForMessages)
{
var msg = await _messagingSystem.ReceiveMessageAsync();
await _handler.SendAsync(msg);
}
}
public void Stop()
{
_pollForMessages = false;
}
private void Process(Message message)
{
//handle message
}
}
More Examples
And Ideas

Ok, sorry I'm short on time but here's the general idea/skeleton of what I was thinking as an alternative.
If I'm honest though I think the ActionBlock<T> is the better option as there's just so much done for you, with the only limit being that you can't dynamically scale the amount of work it will do it once, although I think the limit can be quite high. If you get into doing it this way you could have more control or just have a kind of dynamic amount of tasks running but you'll have to do a lot of things manually, e.g if you want to limit the amount of tasks running at a time, you'd have to implement a queueing system (something ActionBlock handles for you) and then maintain it. I guess it depends on how many messages you're receiving and how fast your process handles them.
You'll have to check it out and think of how it could apply to your direct use case as I think some of the details area a little sketchily implemented on my side around the concurrentbag idea.
So the idea behind what I've thrown together here is that you can start any number of tasks, or add to the tasks running or cancel tasks individually by using the collection.
The main thing I think is just making the method that the Callback runs fire off a thread that does the work, instead of subscribing within a separate thread.
I used Task.Factory.StartNew as you did, but stored the returned Task object in an object (TaskInfo) which also had it's CancellationTokenSource, it's Id (assigned externally) as properties, and then added that to a collection of TaskInfo which is a property on the class this is all a part of:
Updated - to avoid this being too confusing i've just updated the code that was here previously.
You'll have to update bits of it and fill in the blanks in places like with whatever you have for my HeartbeatController, and the few events that get called because they're beyond the scope of the question but the idea would be the same.
public class TaskContainer
{
private ConcurrentBag<TaskInfo> Tasks;
public TaskContainer(){
Tasks = new ConcurrentBag<TaskInfo>();
}
//entry point
//UPDATED
public void StartAndMonitor(int processorCount)
{
for (int i = 0; i <= processorCount; i++)
{
Processor task = new Processor(ProcessorId = i);
CreateProcessorTask(task);
}
this.IsRunning = true;
MonitorTasks();
}
private void CreateProcessorTask(Processor processor)
{
CancellationTokenSource cancellationTokenSource = new CancellationTokenSource();
Task taskInstance = Task.Factory.StartNew(
() => processor.Start(cancellationTokenSource.Token)
);
//bind status update event
processor.ProcessorStatusUpdated += ReportProcessorProcess;
Tasks.Add(new ProcessorInfo()
{
ProcessorId = processor.ProcessorId,
Task = taskInstance,
CancellationTokenSource = cancellationTokenSource
});
}
//this method gets called once but the HeartbeatController gets an action as a param that it then
//executes on a timer. I haven't included that but you get the idea
//This method also checks for tasks that have stopped and restarts them if the manifest call says they should be running.
//Will also start any new tasks included in the manifest and stop any that aren't included in the manifest.
internal void MonitorTasks()
{
HeartbeatController.Beat(() =>
{
HeartBeatHappened?.Invoke(this, null);
List<int> tasksToStart = new List<int>();
//this is an api call or whatever drives your config that says what tasks must be running.
var newManifest = this.GetManifest(Properties.Settings.Default.ResourceId);
//task Removed Check - If a Processor is removed from the task pool, cancel it if running and remove it from the Tasks List.
List<int> instanceIds = new List<int>();
newManifest.Processors.ForEach(x => instanceIds.Add(x.ProcessorId));
var removed = Tasks.Select(x => x.ProcessorId).ToList().Except(instanceIds).ToList();
if (removed.Count() > 0)
{
foreach (var extaskId in removed)
{
var task = Tasks.FirstOrDefault(x => x.ProcessorId == extaskId);
task.CancellationTokenSource?.Cancel();
}
}
foreach (var newtask in newManifest.Processors)
{
var oldtask = Tasks.FirstOrDefault(x => x.ProcessorId == newtask.ProcessorId);
//Existing task check
if (oldtask != null && oldtask.Task != null)
{
if (!oldtask.Task.IsCanceled && (oldtask.Task.IsCompleted || oldtask.Task.IsFaulted))
{
var ex = oldtask.Task.Exception;
tasksToStart.Add(oldtask.ProcessorId);
continue;
}
}
else //New task Check
tasksToStart.Add(newtask.ProcessorId);
}
foreach (var item in tasksToStart)
{
var taskToRemove = Tasks.FirstOrDefault(x => x.ProcessorId == item);
if (taskToRemove != null)
Tasks.Remove(taskToRemove);
var task = newManifest.Processors.FirstOrDefault(x => x.ProcessorId == item);
if (task != null)
{
CreateProcessorTask(task);
}
}
});
}
}
//UPDATED
public class Processor{
private int ProcessorId;
private Subsriber<Message> subsriber;
public Processor(int processorId) => ProcessorId = processorId;
public void Start(CancellationToken token)
{
Subsriber<Message> subsriber = new Subsriber<Message>()
{
Interval = 1000
};
subsriber.Callback(Process, m => m != null);
}
private void Process()
{
//do work
}
}
Hope this gives you an idea of how else you can approach your problem and that I didn't miss the point :).
Update
To use events to update progress or which tasks are processing, I'd extract them into their own class, which then has subscribe methods on it, and when creating a new instance of that class, assign the event to a handler in the parent class which can then update your UI or whatever you want it to do with that info.
So the content of Process() would look more like this:
Processor processor = new Processor();
Task task = Task.Factory.StartNew(() => processor.ProcessMessage(cancellationTokenSource.CancellationToken));
processor.StatusUpdated += ReportProcess;

c# data not processing correctly in multithreading

I have a product dropdown and selecting the product connects to a websocket and get the feed messages for that product. Once the (1) feed messages starts coming I have to then (2) get the order book and then (3) process the feed messages. So the first and last task would run asynchronously. For this I have written the following code:
void OnReceivingFeedMessage()
{
concurrentQueue.Enqueue(message);
if (!messageStreamStarted) // only first time get order book
{
messageStreamStarted = true;
GetOrderBookData();
}
}
private void GetOrderBookData()
{
MarketData m = new MarketData();
ProductOrderBook p = m.GetProductOrderBook(productId);
bidsList = p.bids;
asksList = p.asks;
isOrderBookUpdated = true;
Task task3 = Task.Run(() => KickStartToProcessQueue());
}
private void KickStartToProcessQueue()
{
while (threadProcessQueueExist)
{
int recordCountNew = concurrentQueue.Count();
if (recordCountNew != 0)
{
if (isOrderBookUpdated)
{
ProcessQueueMessages();
}
}
}
}
private void ProcessQueueMessages()
{
if (!concurrentQueue.IsEmpty)
{
string jsonString;
while (concurrentQueue.TryDequeue(out jsonString))
{
// have to insert the record in existing order book
}
}
}
This works perfectly for the first time. But when I change the product and reconnect the things mess up and the data is not processed properly. The code written on product selectedindex change
private void CloseAndReconnectToGetWebsocketFeed()
{
w.CloseWebsocketConnection();
messageStreamStarted = false;
isOrderBookUpdated = false;
ConcurrentQueue<string> wssMessagesQueue = new ConcurrentQueue<string>();
concurrentQueue = wssMessagesQueue;
ConnectAndGetWebsocketFeedMessages(); // this calls OnReceivingFeedMessage
}
I am new to multi-threading so not sure if I need to use lock or async/await or something else. What am I doing wrong in the above code?
It is running fine when run first time but the moment I change the product and do the same processing again it starts giving problems. Can someone please advise how can I clear all the resources before doing the same steps again and again

I think you are writing unneccesarily complicated code. I'm not 100 % sure, what your problem is, but here are some things that might help you.
Use a BlockingCollection<T>
With that class, you can stop your consumer-thread until new messages are coming in. Here's a simple example on how these things are working:
BlockingCollection<string> collection = new BlockingCollection<string>(new ConcurrentQueue<string>());
Task t = Task.Run(() =>
{
while (collection.TryTake(out string item, Timeout.Infinite))
{
Console.WriteLine($"Started reading {item}...");
Thread.Sleep(1000); //simulate intense work
Console.WriteLine($"Done reading {item}");
}
});
while (true)
{
//This could be your OnReceivingFeedMessage()
string input = Console.ReadLine();
if (input == "stop")
{
Console.WriteLine("Stopping...");
collection.CompleteAdding();
break;
}
else
{
collection.Add(input);
}
}
t.Wait();
The task t will wait until there are items in collection. When items are "received" (here simply via console input), they are added to your list.
Dispatch new tasks to work on the input
Pretty simple:
while (true)
{
string item = Console.ReadLine();
Task.Run(() =>
{
Console.WriteLine($"Started reading {item}...");
Thread.Sleep(1000); //simulate intense work
Console.WriteLine($"Done reading {item}");
});
}
This also has the advantage (or disadvantage) that the tasks are running all in parallel. That means that you can't rely on the order they are worked on, but they will process much faster.
By the way: Both of these approaches have the advantage that you don't have busy waiting. From your question:
while (threadProcessQueueExist)
{
int recordCountNew = concurrentQueue.Count();
if (recordCountNew != 0)
{
if (isOrderBookUpdated)
{
ProcessQueueMessages();
}
}
}
This code will create busy waiting as long as nothing is in your queue, meaning that one core of your processor will be at very high load without actually doing anything. It is considered to be bad practice.

Async Producer/Consumer

I have a instance of a class that is accessed from several threads. This class take this calls and add a tuple into a database. I need this to be done in a serial manner, as due to some db constraints, parallel threads could result in an inconsistent database.
As I am new to parallelism and concurrency in C#, I did this:
private BlockingCollection<Task> _tasks = new BlockingCollection<Task>();
public void AddDData(string info)
{
Task t = new Task(() => { InsertDataIntoBase(info); });
_tasks.Add(t);
}
private void InsertWorker()
{
Task.Factory.StartNew(() =>
{
while (!_tasks.IsCompleted)
{
Task t;
if (_tasks.TryTake(out t))
{
t.Start();
t.Wait();
}
}
});
}
The AddDData is the one who is called by multiple threads and InsertDataIntoBase is a very simple insert that should take few milliseconds.
The problem is that, for some reason that my lack of knowledge doesn't allow me to figure out, sometimes a task is been called twice! It always goes like this:
T1
T2
T3
T1 <- PK error.
T4
...
Did I understand .Take() completely wrong, am I missing something or my producer/ consumer implementation is really bad?
Best Regards,
Rafael
UPDATE:
As suggested, I made a quick sandbox test implementation with this architecture and as I was suspecting, it does not guarantee that a task will not be fired before the previous one finishes.
So the question remains: how to properly queue tasks and fire them sequentially?
UPDATE 2:
I simplified the code:
private BlockingCollection<Data> _tasks = new BlockingCollection<Data>();
public void AddDData(Data info)
{
_tasks.Add(info);
}
private void InsertWorker()
{
Task.Factory.StartNew(() =>
{
while (!_tasks.IsCompleted)
{
Data info;
if (_tasks.TryTake(out info))
{
InsertIntoDB(info);
}
}
});
}
Note that I got rid of Tasks as I'm relying on synced InsertIntoDB call (as it is inside a loop), but still no luck... The generation is fine and I'm absolutely sure that only unique instances are going to the queue. But no matter I try, sometimes the same object is used twice.

I think this should work:
private static BlockingCollection<string> _itemsToProcess = new BlockingCollection<string>();
static void Main(string[] args)
{
InsertWorker();
GenerateItems(10, 1000);
_itemsToProcess.CompleteAdding();
}
private static void InsertWorker()
{
Task.Factory.StartNew(() =>
{
while (!_itemsToProcess.IsCompleted)
{
string t;
if (_itemsToProcess.TryTake(out t))
{
// Do whatever needs doing here
// Order should be guaranteed since BlockingCollection
// uses a ConcurrentQueue as a backing store by default.
// http://msdn.microsoft.com/en-us/library/dd287184.aspx#remarksToggle
Console.WriteLine(t);
}
}
});
}
private static void GenerateItems(int count, int maxDelayInMs)
{
Random r = new Random();
string[] items = new string[count];
for (int i = 0; i < count; i++)
{
items[i] = i.ToString();
}
// Simulate many threads adding items to the collection
items
.AsParallel()
.WithDegreeOfParallelism(4)
.WithExecutionMode(ParallelExecutionMode.ForceParallelism)
.Select((x) =>
{
Thread.Sleep(r.Next(maxDelayInMs));
_itemsToProcess.Add(x);
return x;
}).ToList();
}
This does mean that the consumer is single threaded, but allows for multiple producer threads.

From your comment
"I simplified the code shown here, as the data is not a string"
I assume that info parameter passed into AddDData is a mutable reference type. Make sure that the caller is not using the same info instance for multple calls since that reference is captured in Task lambda .

Based on the trace that you provided the only logical possibility is that you have called InsertWorker twice (or more). There are thus two background threads waiting for items to appear in the collection and occasionally they both manage to grab an item and begin executing it.