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How Can I Properly Use Asynchronous Lambda Functions with Parallel.ForEach?

Barbara Streisand
Release: 2025-02-01 03:31:08
Original
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How Can I Properly Use Asynchronous Lambda Functions with Parallel.ForEach?

Parallel Processing with Asynchronous Lambda Functions

Combining parallel processing and asynchronous lambda functions requires careful consideration. This article addresses the challenges of using async methods within Parallel.ForEach and offers effective solutions.

The Problem with Parallel.ForEach and Async Lambdas

Parallel.ForEach launches background threads that don't inherently wait for task completion. This creates problems when using await inside the lambda expression. The following example illustrates this issue:

var bag = new ConcurrentBag<object>();
Parallel.ForEach(myCollection, async item =>
{
  // some pre-processing
  var response = await GetData(item);
  bag.Add(response);
  // some post-processing
});
var count = bag.Count; // count will be 0
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The count will be 0 because the main thread continues execution before the background threads complete their asynchronous operations. Using Wait() as a workaround, as shown below, negates the benefits of await and requires explicit exception handling:

var bag = new ConcurrentBag<object>();
Parallel.ForEach(myCollection, item =>
{
  // some pre-processing
  var responseTask = GetData(item);
  responseTask.Wait();
  var response = responseTask.Result;
  bag.Add(response);
  // some post-processing
});
var count = bag.Count;
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Solution Using Task.WhenAll

A more efficient solution involves leveraging Task.WhenAll to manage the asynchronous operations:

var bag = new ConcurrentBag<object>();
var tasks = myCollection.Select(async item =>
{
  // some pre-processing
  var response = await GetData(item);
  bag.Add(response);
  // some post-processing
});
await Task.WhenAll(tasks);
var count = bag.Count; // count will be correct
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This approach allows each item to be processed asynchronously, and Task.WhenAll ensures all tasks complete before proceeding.

Advanced Solution: ForEachAsync

For more sophisticated asynchronous parallel processing, explore Stephen Toub's blog post on ForEachAsync. This provides a robust and flexible solution for handling complex scenarios.

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