parallel.foreach

I have some code to process several million data rows in my own R-like C# DataFrame class. There's a number of Parallel.ForEach calls for iterating over the data rows in parallel. This code has been running for over a year using VS2013 and .NET 4.5 without issues. I have two dev machines (A and B) and recently upgraded machine A to VS2015. I started noticing a strange intermittent freeze in my code about half the time. Letting it run for a long time, it turns out that the code does eventually finish. It just takes 15-120 minutes instead of 1-2 minutes. Attempts to Break All using the VS2015

How do I break out of an parallel.for loop? I have a pretty complex statement which looks like the following: Parallel.ForEach<ColorIndexHolder>(ColorIndex.AsEnumerable(), new Action<ColorIndexHolder>((ColorIndexHolder Element) => { if (Element.StartIndex <= I && Element.StartIndex + Element.Length >= I) { Found = true; break; } })); Using parallel class, I can optimize this process by far. However; I cannot figure out how to break the parallel loop? The break; statement throws following syntax error: No enclosing loops out of which to break or continue Use the ParallelLoopState.Break method:

I would like to handle a collection in parallel, but I'm having trouble implementing it and I'm therefore hoping for some help. The trouble arises if I want to call a method marked async in C#, within the lambda of the parallel loop. For example: var bag = new ConcurrentBag<object>(); Parallel.ForEach(myCollection, async item => { // some pre stuff var response = await GetData(item); bag.Add(response); // some post stuff } var count = bag.Count; The problem occurs with the count being 0, because all the threads created are effectively just background threads and the Parallel.ForEach call doesn

I am using Parallel.ForEach and I am doing some database updates, now without setting MaxDegreeOfParallelism , a dual core processor machine results in sql client timeouts, where else quad core processor machine somehow does not timeout. Now I have no control over what kind of processor cores are available where my code runs, but is there some settings I can change with MaxDegreeOfParallelism that will probably run less operations simultaneously and not result in timeouts? I can increase timeouts but it isnt a good solution, if on lower CPU I can process less operations simultaneously, that

Here is the code: using (var context = new AventureWorksDataContext()) { IEnumerable<Customer> _customerQuery = from c in context.Customers where c.FirstName.StartsWith("A") select c; var watch = new Stopwatch(); watch.Start(); var result = Parallel.ForEach(_customerQuery, c => Console.WriteLine(c.FirstName)); watch.Stop(); Debug.WriteLine(watch.ElapsedMilliseconds); watch = new Stopwatch(); watch.Start(); foreach (var customer in _customerQuery) { Console.WriteLine(customer.FirstName); } watch.Stop(); Debug.WriteLine(watch.ElapsedMilliseconds); } The problem is, Parallel.ForEach takes about

I had such method: public async Task<MyResult> GetResult() { MyResult result = new MyResult(); foreach(var method in Methods) { string json = await Process(method); result.Prop1 = PopulateProp1(json); result.Prop2 = PopulateProp2(json); } return result; } Then I decided to use Parallel.ForEach : public async Task<MyResult> GetResult() { MyResult result = new MyResult(); Parallel.ForEach(Methods, async method => { string json = await Process(method); result.Prop1 = PopulateProp1(json); result.Prop2 = PopulateProp2(json); }); return result; } But now I've got an error: An asynchronous module or