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Join statement in multiple thread

I have a program that starts 2 threads and use Join.My understanding says that joins blocks the calling operation till it is finished executing .So,the below program should give 2 Million as answer since both the threads blocks till execution is completed but I am always getting the different value.This might be because first thread is completed but second thread is not run completely.
Can someone please explain the output.
Reference -Multithreading: When would I use a Join?
namespace ThreadSample
{
class Program
{
static int Total = 0;
public static void Main()
{
Thread thread1 = new Thread(Program.AddOneMillion);
Thread thread2 = new Thread(Program.AddOneMillion);
thread1.Start();
thread2.Start();
thread1.Join();
thread2.Join();
Console.WriteLine("Total = " + Total);
Console.ReadLine();
}
public static void AddOneMillion()
{
for (int i = 1; i <= 1000000; i++)
{
Total++;
}
}
}
}

When you call start method of thread, it starts immediately. hence by the time u call join on the thread1, thread2 would also have started. As a result variable 'Total' will be accessed by both threads simultaneously. Hence you will not get correct result as one thread operation is overwriting the value of 'Total' value causing data lose.
public static void Main()
{
Thread thread1 = new Thread(Program.AddOneMillion);
Thread thread2 = new Thread(Program.AddOneMillion);
thread1.Start(); //starts immediately
thread2.Start();//starts immediately
thread1.Join(); //By the time this line executes, both threads have accessed the Total varaible causing data loss or corruption.
thread2.Join();
Console.WriteLine("Total = " + Total);
Console.ReadLine();
}
Inorder to correct results either u can lock the Total variable as follows
static object _l = new object();
public static void AddOneMillion()
{
for (int i = 0; i < 1000000; i++)
{
lock(_l)
ii++;
}
}
U can use Interlocked.Increment which atomically updates the variable.
Please refer the link posted by #Emanuel Vintilă in the comment for more insight.
public static void AddOneMillion()
{
for (int i = 0; i < 1000000; i++)
{
Interlocked.Increment(ref Total);
}
}

It's because the increment operation is not done atomically. That means that each thread may hold a copy of Total and increment it. To avoid that you can use a lock or Interlock.Increment that is specific to incrementing a variable.
Clarification:
thread 1: read copy of Total
thread 2: read copy of Total
thread 1: increment and store Total
thread 2: increment and store Total (overwriting previous value)
I leave you with all possible scenarios where things could go wrong.
I would suggest avoiding explicit threading when possible and use map reduce operations that are less error prone.
You need to read about multi-threading programming and functional programming constructs available in mainstream languages. Most languages have added libraries to leverage the multicore capabilities of modern CPUs.

Thread synchronization in the Task Parallel Library (TPL)

I am learning TPL and stuck with a doubt. It is only for learning purpose and I hope people will guide me in the correct direction.
I want only one thread to access the variable sum at one time so that it does not get overwritten.
The code I have is below.
using System;
using System.Threading.Tasks;
class ThreadTest
{
private Object thisLock = new Object();
static int sum = 0;
public void RunMe()
{
lock (thisLock)
{
sum = sum + 1;
}
}
static void Main()
{
ThreadTest b = new ThreadTest();
Task t1 = new Task(()=>b.RunMe());
Task t2= new Task(() => b.RunMe());
t1.Start();
t2.Start();
Task.WaitAll(t1, t2);
Console.WriteLine(sum.ToString());
Console.ReadLine();
}
}
Question -Am i right in this code ?
Question-Can I do it without lock because I read it somewhere that it should be avoided as it does not allow task to communicate with each other.I have seen some examples with async and await but I am using .Net 4.0 .
Thanks

Am i right in this code
Implementation wise Yes, but understanding wise No, as you have mixed up the new and old world while trying to implement the logic, let me try to explain in detail.
Task t1 = new Task(()=>b.RunMe()); doesn't mean as expected as in case of Thread API a new thread every time
Task API will invoke a thread pool thread, so chances are two Task objects t1,t2, gets executed on same thread most of the times for a short running logic and there's never a race condition, which needs an explicit lock, while trying to update the shared object
Better way to prevent race condition for Sum object would be Interlocked.Increment(ref sum), which is a thread safe mechanism to do basic operations on primitive types
For the kind of operation you are doing a better API would be Parallel.For, instead of creating a separate Task, the benefit would be you can run any number of such increment operations with minimal effort, instead of creating a Separate Task and it automatically blocks the Main thread, so your code shall look like:
using System;
using System.Threading.Tasks;
class ThreadTest
{
public static int sum;
}
static void Main()
{
Parallel.For(0, 1, i =>
{
// Some thread instrumentation
Console.WriteLine("i = {0}, thread = {1}", i,
Thread.CurrentThread.ManagedThreadId);
Interlocked.Increment(ref ThreadTest.sum);
});
Console.WriteLine(ThreadTest.sum.ToString());
Console.ReadLine();
}
}
While using the Thread instrumentation you will find that chances are that for two loops, 0,1, managed thread id is same, thus obviating the need for thread safety as suggested earlier

Answer 1:
This is threadsafe for the code that you posted.
However, as Sam has pointed out, this is not currently threadsafe in the general case because the field being incremented is static, but the locking object is not static.
This means that two separate instances of ThreadTest could be created on two separate threads, and then RunMe() could be called from those threads and because each instance has a separate locking object, the locking wouldn't work.
The solution here is to make the locking object static too.
Answer 2:
You can do this without explicit locking using Interlocked.Increment():
public void RunMe()
{
Interlocked.Increment(ref sum);
}

Now to the point, as I was adding some unhappy comments about downvotes, that have no reasons:).
Your scenario is working and is classic multithreading usage.
Classic because of using system lock, that is lock are actually WinAPI locks of the OS, so in order to synchronize, the code has to manage to ring down to the OS and back and of course lose some time with switching threads as some contention may happen especially if you would access RunMe multiple times in each thread running given task or created even more concurrent tasks thank 2.
Please try look on atomic operations.
For your scenario it would work very well, Interlocked.Increment(ref sum).
From there you have to restrain yourself from directly accessing the sum, but that is not a problem, because the Increment method is returning latest result.
Another option is to use SpinLock, that is IF YOU OPERATION IS REALLY FAST.
NEVER ON something ,like Console.WriteLine or any other system operations or long running calculations etc.
Here Inrelocked examples:
using System;
using System.Threading;
using System.Threading.Tasks;
class ThreadTest
{
/// <summary> DO NOT TOUCH ME DIRECTLY </summary>
private static int sum/* = 0 zero is default*/;
private static int Add(int add) => Interlocked.Add(ref sum, add);
private static int Increment() => Interlocked.Increment(ref sum);
private static int Latest() => Interlocked.Add(ref sum, 0);
private static void RunMe() => Increment();
static void Main()
{
Task t1 = new Task(RunMe);
Task t2 = new Task(RunMe);
t1.Start();
t2.Start();
Task.WaitAll(t1, t2);
Console.WriteLine(Latest().ToString());
Console.ReadLine();
}
}

How does sequential loop run faster than Parallel loop in C#?

I tried a very minimal example:
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
using System.Threading;
using System.Collections.Concurrent;
using System.Diagnostics;
namespace TPLExample {
class Program {
static void Main(string[] args) {
int[] dataItems = new int[100];
double[] resultItems = new double[100];
for (int i = 0; i < dataItems.Length; ++i) {
dataItems[i] = i;
}
Stopwatch stopwatch = new Stopwatch();
stopwatch.Reset();
stopwatch.Start();
Parallel.For(0, dataItems.Length, (index) => {
resultItems[index] = Math.Pow(dataItems[index], 2);
});
stopwatch.Stop();
Console.WriteLine("TPL Time elapsed: {0}", stopwatch.Elapsed);
stopwatch.Reset();
stopwatch.Start();
for (int i = 0; i < dataItems.Length; ++i) {
resultItems[i] = Math.Pow(dataItems[i], 2);
}
stopwatch.Stop();
Console.WriteLine("Sequential Time elapsed: {0}", stopwatch.Elapsed);
WaitForEnterKey();
}
public static void WaitForEnterKey() {
Console.WriteLine("Press enter to finish");
Console.ReadLine();
}
public static void PrintMessage() {
Console.WriteLine("Message printed");
}
}
}
The output was:
TPL Time elapsed: 00:00:00.0010670
Sequential Time elapsed: 00:00:00.0000178
Press enter to finish
The sequential loop is way faster than TPL! How is this possible? From my understanding, calculation within the Parallel.For will be executed in parallel, so must it be faster?

Simply put: For only iterating over a hundred items and performing a small mathematical operation, spawning new threads and waiting for them to complete produces more overhead than just running through the loop would.
From my understanding, calculation within the Parallel.For will be executed in parallel, so must it be faster?
As generally happens when people make sweeping statements about computer performance, there are far more variables at play here, and you can't really make that assumption. For example, inside your for loop, you are doing nothing more than Math.Pow, which the processor can perform very quickly. If this were an I/O intensive operation, requiring each thread to wait a long time, or even if it were a series of processor-intensive operations, you would get more out of Parallel processing (assuming you have a multi-threaded processor). But as it is, the overhead of creating and synchronizing these threads is far greater than any advantage that parallelism might give you.

Parallel loop processing is beneficial when the operation performed within the loop is relatively costly. All you're doing in your example is calculating an exponent, which is trivial. The overhead of multithreading is far outweighing the gains that you're getting in this case.

This code example is practical proof really nice answers above.
I've simulated intensive processor operation by simply blocking thread by Thead.Sleep.
The output was:
Sequential Loop - 00:00:09.9995500
Parallel Loop - 00:00:03.0347901
_
class Program
{
static void Main(string[] args)
{
const int a = 10;
Stopwatch sw = new Stopwatch();
sw.Start();
//for (long i = 0; i < a; i++)
//{
// Thread.Sleep(1000);
//}
Parallel.For(0, a, i =>
{
Thread.Sleep(1000);
});
sw.Stop();
Console.WriteLine(sw.Elapsed);
Console.ReadLine();
}
}

The overhead of parallelization is far greater than simply running Math.Pow 100 times sequentially. The others have said this.
More importantly, though, the memory access is trivial in the sequential version, but with the parallel version, the threads have to share memory (resultItems) and that kind of thing will really kill you even if you have a million items.
See page 44 of this excellent Microsoft whitepaper on parallel programming:
http://www.microsoft.com/en-us/download/details.aspx?id=19222. Here is an MSDN magazine article on the subject: http://msdn.microsoft.com/en-us/magazine/cc872851.aspx

Shouldn't this fail without the use of locking? Simple producer consumer

I have a queue, a list with producer threads and a list with consumer threads.
My code looks like this
public class Runner
{
List<Thread> Producers;
List<Thread> Consumers;
Queue<int> queue;
Random random;
public Runner()
{
Producers = new List<Thread>();
Consumers = new List<Thread>();
for (int i = 0; i < 2; i++)
{
Thread thread = new Thread(Produce);
Producers.Add(thread);
}
for (int i = 0; i < 2; i++)
{
Thread thread = new Thread(Consume);
Consumers.Add(thread);
}
queue = new Queue<int>();
random = new Random();
Producers.ForEach(( thread ) => { thread.Start(); });
Consumers.ForEach(( thread ) => { thread.Start(); });
}
protected void Produce()
{
while (true)
{
int number = random.Next(0, 99);
queue.Enqueue(number);
Console.WriteLine(Thread.CurrentThread.ManagedThreadId + " Produce: " + number);
}
}
protected void Consume()
{
while (true)
{
if (queue.Any())
{
int number = queue.Dequeue();
Console.WriteLine(Thread.CurrentThread.ManagedThreadId + " Consume: " + number);
}
else
{
Console.WriteLine("No items to consume");
}
}
}
}
Shouldn't this fail miserable cause of the missing use of the lock keyword?
It failed once because it tried to dequeue when the queue was empty, using the lock keyword will fix that right?
If the lock keyword is not needed for the above code, when is it needed then?
Thank you in advance! =)

Locking is to done to eliminate aberrant behavior of an application, most specifically in multithreading. The most common goal is the elimination of a "race condition" which causes non-deterministic program behavior.
This is the behavior you saw. In one run you get an error for the queue having no items, in another run you have no issues. This is a race condition. Proper usage of locking will eliminate this scenario.

Using Queue without locks is not thread safe indeed. But better than using locks you may try ConcurrentQueue. Google for "C# ConcurrentQueue" and you will find quite a lot of examples, e.g. this one compares the use and performance of Queue with a lock and ConcurrentQueue.

To clarify the existing answers, if you have a multithreading problem (such as a race condition) then it isn't guaranteed to always fail - it may fail, in a very unpredictable manner.
The reason is that two (or more) threads that are accessing a resource may try to access it at different times - precisely when each of them tries to access it will depend on many factors (how fast your CPU is, how many processor cores it has available, what other programs are running at the time, whether you are running a release or debug build, or running under a debugger, etc). You could run it many times without the failure showing up, and then have it suddenly and "inexplicably" fail - this can make these errors extremely hard to track down because they don't often show up while you're writing the faulty code, but more often when you are writing a different unrelated piece of code.
If you are going to use multithreading it is vital that you read up on the subject and gain an understanding of what can go wrong, when, and how to handle it properly - bad use of locking can be just as dangerous (if not more so) than not using locks at all (locking can cause deadlocks where your program simply "locks up"). This are aof programming must be approached carefully!

Yes this code will fail. The queue needs to support multi-threading. Use a ConcurrentQueue. See http://msdn.microsoft.com/en-us/library/dd267265.aspx

By running your code I received InvalidOperationException - "Collection was modified after the enumerator was instantiated." It means that you modify data while using several threads.
You can use the lock every time you Enqueue or Dequeue - because you modify the queue from several threads. A far better option is to use ConcurentQueues as it is thread safe and lock-free concurrent collection. It also provides better performance.

Yep, you would definitely to synchronize access to the Queue to make it thread-safe. But, you have another problem. There is no mechanism which keeps the consumers from spinning wildly around the loop. Synchronizing access to the Queue or using ConcurrentQueue will not fix that problem.
The simplest way to implement the producer-consumer pattern is to use a blocking queue. Fortunately, .NET 4.0 provides the BlockingCollection which is, despite the name, an implementation of a blocking queue.
public class Runner
{
private BlockingCollection<int> queue = new BlockingCollection<int>();
private Random random = new Random();
public Runner()
{
for (int i = 0; i < 2; i++)
{
var thread = new Thread(Produce);
thread.Start();
}
for (int i = 0; i < 2; i++)
{
var thread = new Thread(Consume);
thread.Start();
}
}
protected void Produce()
{
while (true)
{
int number = random.Next(0, 99);
queue.Add(number);
Console.WriteLine(Thread.CurrentThread.ManagedThreadId + " Produce: " + number);
}
}
protected void Consume()
{
while (true)
{
int number = queue.Take();
Console.WriteLine(Thread.CurrentThread.ManagedThreadId + " Consume: " + number);
}
}
}

How do Tasks in the Task Parallel Library affect ActivityID?

Before using the Task Parallel Library, I have often used CorrelationManager.ActivityId to keep track of tracing/error reporting with multiple threads.
ActivityId is stored in Thread Local Storage, so each thread get's its own copy. The idea is that when you fire up a thread (activity), you assign a new ActivityId. The ActivityId will be written to the logs with any other trace information, making it possible to single out the trace information for a single 'Activity'. This is really useful with WCF as the ActivityId can be carried over to the service component.
Here is an example of what I'm talking about:
static void Main(string[] args)
{
ThreadPool.QueueUserWorkItem(new WaitCallback((o) =>
{
DoWork();
}));
}
static void DoWork()
{
try
{
Trace.CorrelationManager.ActivityId = Guid.NewGuid();
//The functions below contain tracing which logs the ActivityID.
CallFunction1();
CallFunction2();
CallFunction3();
}
catch (Exception ex)
{
Trace.Write(Trace.CorrelationManager.ActivityId + " " + ex.ToString());
}
}
Now, with the TPL, my understanding is that multiple Tasks share Threads. Does this mean that ActivityId is prone to being reinitialized mid-task (by another task)? Is there a new mechanism to deal with activity tracing?

I ran some experiments and it turns out the assumption in my question is incorrect - multiple tasks created with the TPL do not run on the same thread at the same time.
ThreadLocalStorage is safe to use with TPL in .NET 4.0, since a thread can only be used by one task at a time.
The assumption that tasks can share threads concurrently was based on an interview I heard about c# 5.0 on DotNetRocks (sorry, I can't remember which show it was) - so my question may (or may not) become relevant soon.
My experiment starts a number of tasks, and records how many tasks ran, how long they took, and how many threads were consumed. The code is below if anyone would like to repeat it.
class Program
{
static void Main(string[] args)
{
int totalThreads = 100;
TaskCreationOptions taskCreationOpt = TaskCreationOptions.None;
Task task = null;
Stopwatch stopwatch = new Stopwatch();
stopwatch.Start();
Task[] allTasks = new Task[totalThreads];
for (int i = 0; i < totalThreads; i++)
{
task = Task.Factory.StartNew(() =>
{
DoLongRunningWork();
}, taskCreationOpt);
allTasks[i] = task;
}
Task.WaitAll(allTasks);
stopwatch.Stop();
Console.WriteLine(String.Format("Completed {0} tasks in {1} milliseconds", totalThreads, stopwatch.ElapsedMilliseconds));
Console.WriteLine(String.Format("Used {0} threads", threadIds.Count));
Console.ReadKey();
}
private static List<int> threadIds = new List<int>();
private static object locker = new object();
private static void DoLongRunningWork()
{
lock (locker)
{
//Keep a record of the managed thread used.
if (!threadIds.Contains(Thread.CurrentThread.ManagedThreadId))
threadIds.Add(Thread.CurrentThread.ManagedThreadId);
}
Guid g1 = Guid.NewGuid();
Trace.CorrelationManager.ActivityId = g1;
Thread.Sleep(3000);
Guid g2 = Trace.CorrelationManager.ActivityId;
Debug.Assert(g1.Equals(g2));
}
}
The output (of course this will depend on the machine) was:
Completed 100 tasks in 23097 milliseconds
Used 23 threads
Changing taskCreationOpt to TaskCreationOptions.LongRunning gave different results:
Completed 100 tasks in 3458 milliseconds
Used 100 threads

Please forgive my posting this as an answer as it is not really answer to your question, however, it is related to your question since it deals with CorrelationManager behavior and threads/tasks/etc. I have been looking at using the CorrelationManager's LogicalOperationStack (and StartLogicalOperation/StopLogicalOperation methods) to provide additional context in multithreading scenarios.
I took your example and modified it slightly to add the ability to perform work in parallel using Parallel.For. Also, I use StartLogicalOperation/StopLogicalOperation to bracket (internally) DoLongRunningWork. Conceptually, DoLongRunningWork does something like this each time it is executed:
DoLongRunningWork
StartLogicalOperation
Thread.Sleep(3000)
StopLogicalOperation
I have found that if I add these logical operations to your code (more or less as is), all of the logical operatins remain in sync (always the expected number of operations on stack and the values of the operations on the stack are always as expected).
In some of my own testing I found that this was not always the case. The logical operation stack was getting "corrupted". The best explanation I could come up with is that the "merging" back of the CallContext information into the "parent" thread context when the "child" thread exits was causing the "old" child thread context information (logical operation) to be "inherited" by another sibling child thread.
The problem might also be related to the fact that Parallel.For apparently uses the main thread (at least in the example code, as written) as one of the "worker threads" (or whatever they should be called in the parallel domain). Whenever DoLongRunningWork is executed, a new logical operation is started (at the beginning) and stopped (at the end) (that is, pushed onto the LogicalOperationStack and popped back off of it). If the main thread already has a logical operation in effect and if DoLongRunningWork executes ON THE MAIN THREAD, then a new logical operation is started so the main thread's LogicalOperationStack now has TWO operations. Any subsequent executions of DoLongRunningWork (as long as this "iteration" of DoLongRunningWork is executing on the main thread) will (apparently) inherit the main thread's LogicalOperationStack (which now has two operations on it, rather than just the one expected operation).
It took me a long time to figure out why the behavior of the LogicalOperationStack was different in my example than in my modified version of your example. Finally I saw that in my code I had bracketed the entire program in a logical operation, whereas in my modified version of your test program I did not. The implication is that in my test program, each time my "work" was performed (analogous to DoLongRunningWork), there was already a logical operation in effect. In my modified version of your test program, I had not bracketed the entire program in a logical operation.
So, when I modified your test program to bracket the entire program in a logical operation AND if I am using Parallel.For, I ran into exactly the same problem.
Using the conceptual model above, this will run successfully:
Parallel.For
DoLongRunningWork
StartLogicalOperation
Sleep(3000)
StopLogicalOperation
While this will eventually assert due to an apparently out of sync LogicalOperationStack:
StartLogicalOperation
Parallel.For
DoLongRunningWork
StartLogicalOperation
Sleep(3000)
StopLogicalOperation
StopLogicalOperation
Here is my sample program. It is similar to yours in that it has a DoLongRunningWork method that manipulates the ActivityId as well as the LogicalOperationStack. I also have two flavors of kicking of DoLongRunningWork. One flavor uses Tasks one uses Parallel.For. Each flavor can also be executed such that the whole parallelized operation is enclosed in a logical operation or not. So, there are a total of 4 ways to execute the parallel operation. To try each one, simply uncomment the desired "Use..." method, recompile, and run. UseTasks, UseTasks(true), and UseParallelFor should all run to completion. UseParallelFor(true) will assert at some point because the LogicalOperationStack does not have the expected number of entries.
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Diagnostics;
using System.Threading;
using System.Threading.Tasks;
namespace CorrelationManagerParallelTest
{
class Program
{
static void Main(string[] args)
{
//UseParallelFor(true) will assert because LogicalOperationStack will not have expected
//number of entries, all others will run to completion.
UseTasks(); //Equivalent to original test program with only the parallelized
//operation bracketed in logical operation.
////UseTasks(true); //Bracket entire UseTasks method in logical operation
////UseParallelFor(); //Equivalent to original test program, but use Parallel.For
//rather than Tasks. Bracket only the parallelized
//operation in logical operation.
////UseParallelFor(true); //Bracket entire UseParallelFor method in logical operation
}
private static List<int> threadIds = new List<int>();
private static object locker = new object();
private static int mainThreadId = Thread.CurrentThread.ManagedThreadId;
private static int mainThreadUsedInDelegate = 0;
// baseCount is the expected number of entries in the LogicalOperationStack
// at the time that DoLongRunningWork starts. If the entire operation is bracketed
// externally by Start/StopLogicalOperation, then baseCount will be 1. Otherwise,
// it will be 0.
private static void DoLongRunningWork(int baseCount)
{
lock (locker)
{
//Keep a record of the managed thread used.
if (!threadIds.Contains(Thread.CurrentThread.ManagedThreadId))
threadIds.Add(Thread.CurrentThread.ManagedThreadId);
if (Thread.CurrentThread.ManagedThreadId == mainThreadId)
{
mainThreadUsedInDelegate++;
}
}
Guid lo1 = Guid.NewGuid();
Trace.CorrelationManager.StartLogicalOperation(lo1);
Guid g1 = Guid.NewGuid();
Trace.CorrelationManager.ActivityId = g1;
Thread.Sleep(3000);
Guid g2 = Trace.CorrelationManager.ActivityId;
Debug.Assert(g1.Equals(g2));
//This assert, LogicalOperation.Count, will eventually fail if there is a logical operation
//in effect when the Parallel.For operation was started.
Debug.Assert(Trace.CorrelationManager.LogicalOperationStack.Count == baseCount + 1, string.Format("MainThread = {0}, Thread = {1}, Count = {2}, ExpectedCount = {3}", mainThreadId, Thread.CurrentThread.ManagedThreadId, Trace.CorrelationManager.LogicalOperationStack.Count, baseCount + 1));
Debug.Assert(Trace.CorrelationManager.LogicalOperationStack.Peek().Equals(lo1), string.Format("MainThread = {0}, Thread = {1}, Count = {2}, ExpectedCount = {3}", mainThreadId, Thread.CurrentThread.ManagedThreadId, Trace.CorrelationManager.LogicalOperationStack.Peek(), lo1));
Trace.CorrelationManager.StopLogicalOperation();
}
private static void UseTasks(bool encloseInLogicalOperation = false)
{
int totalThreads = 100;
TaskCreationOptions taskCreationOpt = TaskCreationOptions.None;
Task task = null;
Stopwatch stopwatch = new Stopwatch();
stopwatch.Start();
if (encloseInLogicalOperation)
{
Trace.CorrelationManager.StartLogicalOperation();
}
Task[] allTasks = new Task[totalThreads];
for (int i = 0; i < totalThreads; i++)
{
task = Task.Factory.StartNew(() =>
{
DoLongRunningWork(encloseInLogicalOperation ? 1 : 0);
}, taskCreationOpt);
allTasks[i] = task;
}
Task.WaitAll(allTasks);
if (encloseInLogicalOperation)
{
Trace.CorrelationManager.StopLogicalOperation();
}
stopwatch.Stop();
Console.WriteLine(String.Format("Completed {0} tasks in {1} milliseconds", totalThreads, stopwatch.ElapsedMilliseconds));
Console.WriteLine(String.Format("Used {0} threads", threadIds.Count));
Console.WriteLine(String.Format("Main thread used in delegate {0} times", mainThreadUsedInDelegate));
Console.ReadKey();
}
private static void UseParallelFor(bool encloseInLogicalOperation = false)
{
int totalThreads = 100;
Stopwatch stopwatch = new Stopwatch();
stopwatch.Start();
if (encloseInLogicalOperation)
{
Trace.CorrelationManager.StartLogicalOperation();
}
Parallel.For(0, totalThreads, i =>
{
DoLongRunningWork(encloseInLogicalOperation ? 1 : 0);
});
if (encloseInLogicalOperation)
{
Trace.CorrelationManager.StopLogicalOperation();
}
stopwatch.Stop();
Console.WriteLine(String.Format("Completed {0} tasks in {1} milliseconds", totalThreads, stopwatch.ElapsedMilliseconds));
Console.WriteLine(String.Format("Used {0} threads", threadIds.Count));
Console.WriteLine(String.Format("Main thread used in delegate {0} times", mainThreadUsedInDelegate));
Console.ReadKey();
}
}
}
This whole issue of if LogicalOperationStack can be used with Parallel.For (and/or other threading/Task constructs) or how it can be used probably merits its own question. Maybe I will post a question. In the meantime, I wonder if you have any thoughts on this (or, I wonder if you had considered using LogicalOperationStack since ActivityId appears to be safe).
[EDIT]
See my answer to this question for more information about using LogicalOperationStack and/or CallContext.LogicalSetData with some of the various Thread/ThreadPool/Task/Parallel contstructs.
See also my question here on SO about LogicalOperationStack and Parallel extensions:
Is CorrelationManager.LogicalOperationStack compatible with Parallel.For, Tasks, Threads, etc
Finally, see also my question here on Microsoft's Parallel Extensions forum:
http://social.msdn.microsoft.com/Forums/en-US/parallelextensions/thread/7c5c3051-133b-4814-9db0-fc0039b4f9d9
In my testing it looks like Trace.CorrelationManager.LogicalOperationStack can become corrupted when using Parallel.For or Parallel.Invoke IF you start a logical operation in the main thread and then start/stop logical operations in the delegate. In my tests (see either of the two links above) the LogicalOperationStack should always have exactly 2 entries when DoLongRunningWork is executing (if I start a logical operation in the main thread before kicking of DoLongRunningWork using various techniques). So, by "corrupted" I mean that the LogicalOperationStack will eventually have many more than 2 entries.
From what I can tell, this is probably because Parallel.For and Parallel.Invoke use the main thread as one of the "worker" threads to perform the DoLongRunningWork action.
Using a stack stored in CallContext.LogicalSetData to mimic the behavior of the LogicalOperationStack (similar to log4net's LogicalThreadContext.Stacks which is stored via CallContext.SetData) yields even worse results. If I am using such a stack to maintain context, it becomes corrupted (i.e. does not have the expected number of entries) in almost all of the scenarios where I have a "logical operation" in the main thread and a logical operation in each iteration/execution of the DoLongRunningWork delegate.