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How to: Use Parallel.Invoke to Execute Parallel Operations

This example shows how to parallelize operations by using ParallelInvoke() in the Task Parallel Library. Three operations are performed on a shared data source. Because none of the operations modifies the source, they can be executed in parallel in a straightforward manner.


This documentation uses lambda expressions to define delegates in TPL. If you are not familiar with lambda expressions in C# or Visual Basic, see Lambda Expressions in PLINQ and TPL.

namespace ParallelTasks
    using System;
    using System.IO;
    using System.Linq;
    using System.Text;
    using System.Threading;
    using System.Threading.Tasks;
    using System.Net;

    class ParallelInvoke
        static void Main()
            // Retrieve Darwin's "Origin of the Species" from Gutenberg.org.
            string[] words = CreateWordArray(@"http://www.gutenberg.org/files/2009/2009.txt");

            #region ParallelTasks
            // Perform three tasks in parallel on the source array
            Parallel.Invoke(() =>
                                 Console.WriteLine("Begin first task...");
                             },  // close first Action

                             () =>
                                 Console.WriteLine("Begin second task...");
                             }, //close second Action

                             () =>
                                 Console.WriteLine("Begin third task...");
                                 GetCountForWord(words, "species");
                             } //close third Action
                         ); //close parallel.invoke

            Console.WriteLine("Returned from Parallel.Invoke");

            Console.WriteLine("Press any key to exit");

        #region HelperMethods
        private static void GetCountForWord(string[] words, string term)
            var findWord = from word in words
                           where word.ToUpper().Contains(term.ToUpper())
                           select word;

            Console.WriteLine(@"Task 3 -- The word ""{0}"" occurs {1} times.",
                term, findWord.Count());

        private static void GetMostCommonWords(string[] words)
            var frequencyOrder = from word in words
                                 where word.Length > 6
                                 group word by word into g
                                 orderby g.Count() descending
                                 select g.Key;

            var commonWords = frequencyOrder.Take(10);

            StringBuilder sb = new StringBuilder();
            sb.AppendLine("Task 2 -- The most common words are:");
            foreach (var v in commonWords)
                sb.AppendLine("  " + v);

        private static string GetLongestWord(string[] words)
            var longestWord = (from w in words
                               orderby w.Length descending
                               select w).First();

            Console.WriteLine("Task 1 -- The longest word is {0}", longestWord);
            return longestWord;

        // An http request performed synchronously for simplicity.
        static string[] CreateWordArray(string uri)
            Console.WriteLine("Retrieving from {0}", uri);

            // Download a web page the easy way.
            string s = new WebClient().DownloadString(uri);

            // Separate string into an array of words, removing some common punctuation.
            return s.Split(
                new char[] { ' ', '\u000A', ',', '.', ';', ':', '-', '_', '/' },

    /* Output (May vary on each execution):
        Retrieving from http://www.gutenberg.org/dirs/etext99/otoos610.txt
        Response stream received.
        Begin first task...
        Begin second task...
        Task 2 -- The most common words are:

        Begin third task...
        Task 1 -- The longest word is characteristically
        Task 3 -- The word "species" occurs 1927 times.
        Returned from Parallel.Invoke
        Press any key to exit  

Note that with Invoke(), you simply express which actions you want to run concurrently, and the runtime handles all thread scheduling details, including scaling automatically to the number of cores on the host computer.

This example parallelizes the operations, not the data. As an alternate approach, you can parallelize the LINQ queries by using PLINQ and run the queries sequentially. Alternatively, you could parallelize the data by using PLINQ. Another option is to parallelize both the queries and the tasks. Although the resulting overhead might degrade performance on host computers with relatively few processors, it would scale much better on computers with many processors.

  • Copy and paste the entire example into a Microsoft Visual Studio 2010 project and press F5.