1024programmer Asp.Net Have you used the parallel processing and parallel query methods in C# correctly?

Have you used the parallel processing and parallel query methods in C# correctly?

Have you used the parallel processing and parallel query methods in C# correctly?

Parallel.ForEach

Parallel.ForEach is a powerful tool for performing iterative operations on collections in parallel. It improves performance by efficiently utilizing the power of multi-core processors. Parallel.ForEach not only simplifies parallel programming, but it can provide better performance than traditional iteration when executing simple loops.

Here is a simple example that demonstrates how to use Parallel.ForEach to process a list of integers in parallel:

using System;
 using System.Collections.Generic;
 using System.Threading.Tasks;

 class Program
 {
     static void Main()
     {
         List numbers = GetNumbers();

         // Use Parallel.ForEach to process a list of integers in parallel
         Parallel.ForEach(numbers, num =>
         {
             int result = ProcessNumber(num);
             Console.WriteLine($"Processed {num} - Result: {result}");
         });

         Console.ReadLine();
     }

     static List GetNumbers()
     {
         // Get a list containing a large number of integers
         List numbers = new List();
         for (int i = 1; i <= 10000; i++)
         {
             numbers.Add(i);
         }
         return numbers;
     }

     static int ProcessNumber(int number)
     {
         // Simulate some computationally intensive operations
         return number * number;
     }
 }

In the above example, Parallel.ForEach will process each element in the numbers list in parallel and call the ProcessNumber method. Since the calculations in this example are relatively simple, parallelization may not be noticeable in performance. In fact, Parallel.ForEach is more effective when dealing with larger data sets or more complex computing tasks.

AsParallel

AsParallel is a method in LINQ that can parallelize query operations. Using AsParallel allows LINQ queries to be executed in parallel on multiple processors to improve query performance. It returns a ParallelQuery object that supports parallel execution of LINQ operations.

Here is an example showing how to use AsParallel to perform a parallel LINQ query on a list of integers:

using System;
 using System.Collections.Generic;
 using System.Linq;

 class Program
 {
     static void Main()
     {
         List numbers = GetNumbers();

         // Use AsParallel to perform a parallel LINQ query on a list of integers
         var result = numbers
             .AsParallel()
             .Where(num => num % 2 == 0) // Filter even numbers
             .Select(num => num * num) // Square even numbers
             .ToList();

         //output result
         Console.WriteLine("Parallel LINQ Result:");
         foreach (var num in result)
         {
             Console.WriteLine(num);
         }

         Console.ReadLine();
     }

     static List GetNumbers()
     {
         // Get a list containing a large number of integers
         List numbers = new List();
         for (int i = 1; i <= 10000; i++)
         {
             numbers.Add(i);
         }
         return numbers;
     }
 }

In the above example, AsParallel is used to parallelize the LINQ query. The query first filters out the even numbers in the list and then calculates the square of each even number. The end result is a list containing squared values. The example here is relatively simple, but AsParallel can significantly improve performance when working with larger or more complex data.

Differences and performance comparison

Difference:

  1. Different purposes:
  2. Parallel.ForEach is used to process elements of a collection in parallel and can be directly applied to loop iterations.
  3. AsParallel is used to parallelize LINQ queries, mainly used to implement parallel processing in LINQ queries.
  4. Different operation objects:
  5. Parallel.ForEach operates the elements of the collection and needs to provide a delegate to define the operation on each element.
  6. AsParallel operates a LINQ query, enabling operations in the query to be executed in parallel.

Performance comparison:

The relative performance depends on the specific usage scenario and data set. Generally speaking:

  • Parallel.ForEach may be more efficient in direct collection iteration operations, especially for simple computationally intensive tasks.
  • AsParallel is more suitable for parallel processing in LINQ queries.�, especially where filtering, mapping, and other complex operations are required.

In practical applications, it is recommended to select appropriate tools based on the nature of the task. If you have a simple collection iteration task, Parallel.ForEach may be more suitable. If you are performing complex query operations, AsParallel may be more suitable.

In parallel programming, the choice between using Parallel.ForEach or AsParallel depends on the nature of the task. When processing collection elements, Parallel.ForEach provides an intuitive and simple way; when performing complex LINQ queries, AsParallel provides more flexible parallel processing capabilities. In practical applications, by carefully analyzing task requirements and performance characteristics, appropriate tools can be better selected to achieve parallelization.

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author: admin

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