C# Program to Generate Odd Numbers in Parallel using LINQ

This article demonstrates how to generate odd numbers in parallel using LINQ in C#. LINQ (Language Integrated Query) provides a powerful way to query data from collections, arrays, and databases using a SQL-like syntax. When combined with parallel processing, LINQ can efficiently handle large datasets by distributing work across multiple CPU cores.

Syntax

Following is the syntax for generating odd numbers in parallel using LINQ

IEnumerable<int> odds = ParallelEnumerable.Range(start, count)
    .Where(x => x % 2 != 0)
    .Select(x => x);

LINQ Methods Used

Where() Method

The Where() method filters elements based on a Boolean condition (predicate). It returns only those elements for which the condition evaluates to true.

Select() Method

The Select() method projects each element of a sequence into a new form. In this case, it selects the filtered odd numbers.

Example

The following example generates odd numbers in parallel within the range 10 to 20

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

class Program {
   static void Main(string[] args) {
      // Generate odd numbers in parallel within range 10 to 20
      IEnumerable<int> oddNumbers = ParallelEnumerable.Range(10, 11)
         .Where(x => x % 2 != 0)
         .Select(x => x);
      
      Console.WriteLine("Odd numbers generated in parallel:");
      foreach (int number in oddNumbers) {
         Console.WriteLine(number);
      }
   }
}

The output of the above code is

Odd numbers generated in parallel:
11
13
15
17
19

Using AsParallel() for Existing Collections

You can also apply parallel processing to existing collections using the AsParallel() method

using System;
using System.Linq;

class Program {
   static void Main(string[] args) {
      int[] numbers = { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 };
      
      var oddNumbers = numbers.AsParallel()
         .Where(x => x % 2 != 0)
         .Select(x => x * x); // Square the odd numbers
      
      Console.WriteLine("Squared odd numbers:");
      foreach (int number in oddNumbers) {
         Console.WriteLine(number);
      }
   }
}

The output of the above code is

Squared odd numbers:
1
9
25
49
81

Performance Comparison

Conclusion

Parallel LINQ (PLINQ) in C# enables efficient processing of large datasets by distributing operations across multiple CPU cores. Using methods like ParallelEnumerable.Range(), Where(), and Select(), you can generate and filter data in parallel, significantly improving performance for computationally intensive tasks.