用线程安全随机数解决Random在多线程中随机性重复的问题

在.NET中,随机数一般是用Random来获取,但是当在多任务的并行化编程时,问题就出现了。因为Random是基于时间作为种子来生成伪随机数的,而如果程序在多核并行时,在同一时间内的多个核中取到的时间是一样的,这样一来,生成的伪随机数就有可能会有一样的。如果业务需求中需要不可重复的随机数,那么这后果将会相当严重,所以必须采取一种新的方式来获取线程安全的伪随机数。下面是摘自《.NET Parallel Extensions》中的一段关于线程安全随机数生成的类,也可参看http://code.msdn.microsoft.com/Samples-for-Parallel-b4b76364/sourcecode?fileId=44488&pathId=1352203765

 public class ThreadSafeRandom : Random
    {
        //This is the seed provider
        private static readonly RNGCryptoServiceProvider _global = new RNGCryptoServiceProvider();

        //This is the provider of randomness.
        //There is going to be one instance of Random per thread
        //because it is  declared as ThreadLocal<Random>
        private ThreadLocal<Random> _local = new ThreadLocal<Random>(() =>
        {
            //This is the valueFactory function
            //This code will run for each thread to initialize each independent instance of Random.
            var buffer = new byte[4];
            //Calls the GetBytes method for RNGCryptoServiceProvider because this class is thread-safe
            //for this usage.
            _global.GetBytes(buffer);
            //Return the new thread-local Random instance initialized with the generated seed.
            return new Random(BitConverter.ToInt32(buffer, 0));
        });

        public override int Next()
        {
            return _local.Value.Next();
        }

        public override int Next(int maxValue)
        {
            return _local.Value.Next(maxValue);
        }

        public override int Next(int minValue, int maxValue)
        {
            return _local.Value.Next(minValue, maxValue);
        }

        public override double NextDouble()
        {
            return _local.Value.NextDouble();
        }

        public override void NextBytes(byte[] buffer)
        {
            _local.Value.NextBytes(buffer);
        }
    }
这个类ThreadSafeRandom继承自Random,所以可以像Random一样使用。

这里边关键用到了几个技术点:

1、RNGCryptoServiceProvider的加密随机生成器,再用其中的强随机序列的方法GetBytes来实现随机。

2、使用ThreadLocal来懒惰初使化(Lazy-Initialize)随机数的实例。因为ThreadLocal是针对于每一个线程的线程安全类,是线程的本地存储形式。如果同一个线程多次初始化ThreadLocal,那么得到的实例将会是一样的。因为如果一个线程已经初始化了该实例之后( ThreadSafeRandom safeRandom = new ThreadSafeRandom()),该线程后面继续初始化(再次调用 ThreadSafeRandom safeRandom = new ThreadSafeRandom())是不会再初始化一次,而是会返回之前的实例(有点像单件模式)。不过,这也带来了另一个问题,如果就是要在线程中不断产生新的实例时,这种做法就变的不合适了,不悉采用变通或者其他做法。

下面是关于Random和ThreadSafeRandom测试的实例

using System;
using System.Collections.Generic;
using System.Diagnostics;
using System.Linq;
using System.Text;
using System.Threading.Tasks;

namespace Chapter11_Console
{
    public class RadomTest
    {
        #region Run Function
        public static void Run()
        {
            Console.WriteLine("Started!");

            var sw = Stopwatch.StartNew();
            int normalRandomSameCount = randomSerial(generateNormalRadoms);
            Console.WriteLine("Normal Random Same Count:{0}, Consume Time:{1}", normalRandomSameCount, sw.Elapsed.ToString());

            sw.Restart();
            int threadSafeRandomSameCount = randomSerial(generateThreadSafeRadoms);
            Console.WriteLine("Thread Safe Random Same Count:{0}, Consume Time:{1}", threadSafeRandomSameCount, sw.Elapsed.ToString());

            Console.WriteLine("Completed!");
            Console.ReadLine();
        }

        private static int randomSerial(Func<int, List<int>> generateRadoms)
        {
            int randomCount = 100000;
            Task<List<int>>[] tasks = new Task<List<int>>[2];
            for (int i = 0; i < tasks.Length; i++)
            {
                tasks[i] = Task.Factory.StartNew(() =>
                {
                    return generateRadoms(randomCount);
                });
            }
            Task.WaitAll(tasks);
            int sameCount = 0;
            Task finalTask = Task.Factory.StartNew(() =>
            {
                for (int i = 0; i < randomCount; i++)
                {
                    if (tasks[0].Result[i] == tasks[1].Result[i])
                    {
                        sameCount++;
                    }
                }
            });
            finalTask.Wait();
            return sameCount;
        }

        private static List<int> generateNormalRadoms(int randomCount)
        {
            List<int> randoms = new List<int>();
            for (int i = 0; i < randomCount; i++)
            {
                Random random = new Random();
                randoms.Add(random.Next());
            }
            return randoms;
        }

        private static List<int> generateThreadSafeRadoms(int randomCount)
        {
            List<int> randoms = new List<int>();
            for (int i = 0; i < randomCount; i++)
            {
                ThreadSafeRandom safeRandom = new ThreadSafeRandom();
                randoms.Add(safeRandom.Next());
            }
            return randoms;
        }
        #endregion
    }
}

运行结果如下图



多运行几次会发现,有的时候Normal Random Same Count也有为0的时候,有的时候会很小,有的时候会很大,具体多少是随机性的。

注意:

   1、测试时必须是多核的。以上程序是在双核上运行的,如果有四核或更多的核,可以将任务数加大。

   2、线程安全虽然确保了随机数的安全性,但是会消耗更多时间。

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posted @ 2013-11-27 10:37  _学而时习之  阅读(1495)  评论(0编辑  收藏  举报