[索引页]
[源码下载]
作者: webabcd
介绍
C# 4.0 的新特性之并行运算
示例
1、Parallel.For 的 Demo
Parallel/ParallelFor.aspx.cs
[源码下载]
精进不休 .NET 4.0 (5) - C# 4.0 新特性之并行运算(Parallel)
作者: webabcd
介绍
C# 4.0 的新特性之并行运算
- Parallel.For - for 循环的并行运算
- Parallel.ForEach - foreach 循环的并行运算
- Parallel.Invoke - 并行调用多个任务
- Task - 任务,基于线程池。其使我们对并行编程变得更简单,且不用关心底层是怎么实现的
- PLINQ - 用于对内存中的数据做并行运算,也就是说其只支持 LINQ to Object 的并行运算
示例
1、Parallel.For 的 Demo
Parallel/ParallelFor.aspx.cs
using System;
using System.Collections.Generic;
using System.Linq;
using System.Web;
using System.Web.UI;
using System.Web.UI.WebControls;
namespace CSharp.Parallel
{
public partial class ParallelFor : System.Web.UI.Page
{
void Page_Load() void Page_Load(object sender, EventArgs e)
{
Normal();
ParallelForDemo();
}
void Normal() void Normal()
{
DateTime dt = DateTime.Now;
for (int i = 0; i < 20; i++)
{
GetData(i);
}
Response.Write((DateTime.Now - dt).TotalMilliseconds.ToString());
Response.Write( "<br />");
Response.Write( "<br />");
}
void ParallelForDemo() void ParallelForDemo()
{
DateTime dt = DateTime.Now;
// System.Threading.Tasks.Parallel. For - for 循环的并行运算
System.Threading.Tasks.Parallel. For(0, 20, (i) => { GetData(i); });
Response.Write((DateTime.Now - dt).TotalMilliseconds.ToString());
Response.Write( "<br />");
}
int GetData() int GetData(int i)
{
System.Threading.Thread.Sleep(100);
Response.Write(i.ToString());
Response.Write( "<br />");
return i;
}
}
}
/*
运行结果:
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
2000.0514
0
13
1
19
7
12
18
6
2
8
10
14
4
16
5
3
15
17
9
11
300.0077
*/
using System.Collections.Generic;
using System.Linq;
using System.Web;
using System.Web.UI;
using System.Web.UI.WebControls;
namespace CSharp.Parallel
{
public partial class ParallelFor : System.Web.UI.Page
{
void Page_Load() void Page_Load(object sender, EventArgs e)
{
Normal();
ParallelForDemo();
}
void Normal() void Normal()
{
DateTime dt = DateTime.Now;
for (int i = 0; i < 20; i++)
{
GetData(i);
}
Response.Write((DateTime.Now - dt).TotalMilliseconds.ToString());
Response.Write( "<br />");
Response.Write( "<br />");
}
void ParallelForDemo() void ParallelForDemo()
{
DateTime dt = DateTime.Now;
// System.Threading.Tasks.Parallel. For - for 循环的并行运算
System.Threading.Tasks.Parallel. For(0, 20, (i) => { GetData(i); });
Response.Write((DateTime.Now - dt).TotalMilliseconds.ToString());
Response.Write( "<br />");
}
int GetData() int GetData(int i)
{
System.Threading.Thread.Sleep(100);
Response.Write(i.ToString());
Response.Write( "<br />");
return i;
}
}
}
/*
运行结果:
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
2000.0514
0
13
1
19
7
12
18
6
2
8
10
14
4
16
5
3
15
17
9
11
300.0077
*/
2、Parallel.ForEach 的 Demo
Parallel/ParallelForEach.aspx.cs
Parallel/ParallelForEach.aspx.cs
using System;
using System.Collections.Generic;
using System.Linq;
using System.Web;
using System.Web.UI;
using System.Web.UI.WebControls;
namespace CSharp.Parallel
{
public partial class ParallelForEach : System.Web.UI.Page
{
List<int> _data = new List<int>() List<int> _data = new List<int>();
void Page_Load() void Page_Load(object sender, EventArgs e)
{
InitData();
Normal();
ParallelForEachDemo();
}
void InitData() void InitData()
{
_data.Clear();
for (int i = 0; i < 20; i++)
{
_data.Add(i);
}
}
void Normal() void Normal()
{
DateTime dt = DateTime.Now;
for (int i = 0; i < 20; i++)
{
GetData(i);
}
Response.Write((DateTime.Now - dt).TotalMilliseconds.ToString());
Response.Write( "<br />");
Response.Write( "<br />");
}
void ParallelForEachDemo() void ParallelForEachDemo()
{
DateTime dt = DateTime.Now;
// System.Threading.Tasks.Parallel.ForEach - foreach 循环的并行运算
System.Threading.Tasks.Parallel.ForEach(_data, (index) => { GetData(index); });
Response.Write((DateTime.Now - dt).TotalMilliseconds.ToString());
Response.Write( "<br />");
}
int GetData() int GetData(int i)
{
System.Threading.Thread.Sleep(100);
Response.Write(i.ToString());
Response.Write( "<br />");
return i;
}
}
}
/*
运行结果:
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
2000.0514
0
6
12
18
1
2
7
13
19
4
3
8
14
9
5
15
10
16
11
17
600.0154
*/
using System.Collections.Generic;
using System.Linq;
using System.Web;
using System.Web.UI;
using System.Web.UI.WebControls;
namespace CSharp.Parallel
{
public partial class ParallelForEach : System.Web.UI.Page
{
List<int> _data = new List<int>() List<int> _data = new List<int>();
void Page_Load() void Page_Load(object sender, EventArgs e)
{
InitData();
Normal();
ParallelForEachDemo();
}
void InitData() void InitData()
{
_data.Clear();
for (int i = 0; i < 20; i++)
{
_data.Add(i);
}
}
void Normal() void Normal()
{
DateTime dt = DateTime.Now;
for (int i = 0; i < 20; i++)
{
GetData(i);
}
Response.Write((DateTime.Now - dt).TotalMilliseconds.ToString());
Response.Write( "<br />");
Response.Write( "<br />");
}
void ParallelForEachDemo() void ParallelForEachDemo()
{
DateTime dt = DateTime.Now;
// System.Threading.Tasks.Parallel.ForEach - foreach 循环的并行运算
System.Threading.Tasks.Parallel.ForEach(_data, (index) => { GetData(index); });
Response.Write((DateTime.Now - dt).TotalMilliseconds.ToString());
Response.Write( "<br />");
}
int GetData() int GetData(int i)
{
System.Threading.Thread.Sleep(100);
Response.Write(i.ToString());
Response.Write( "<br />");
return i;
}
}
}
/*
运行结果:
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
2000.0514
0
6
12
18
1
2
7
13
19
4
3
8
14
9
5
15
10
16
11
17
600.0154
*/
3、Parallel.Invoke 的 Demo
Parallel/ParallelInvoke.aspx.cs
Parallel/ParallelInvoke.aspx.cs
using System;
using System.Collections.Generic;
using System.Linq;
using System.Web;
using System.Web.UI;
using System.Web.UI.WebControls;
using System.Threading;
namespace CSharp.Parallel
{
public partial class ParallelInvoke : System.Web.UI.Page
{
void Page_Load() void Page_Load(object sender, EventArgs e)
{
var tasks = new Action[] { () => Task1(), () => Task2(), () => Task3() };
// System.Threading.Tasks.Parallel.Invoke - 并行调用多个任务
System.Threading.Tasks.Parallel.Invoke(tasks);
}
void Task1() void Task1()
{
Thread.Sleep(3000);
Response.Write( "Task1 - " + "ThreadId:" + Thread.CurrentThread.ManagedThreadId.ToString() + " - "+ DateTime.Now.ToString( "HH:mm:ss"));
Response.Write( "<br />");
}
void Task2() void Task2()
{
System.Threading.Thread.Sleep(3000);
Response.Write( "Task2 - " + "ThreadId:" + Thread.CurrentThread.ManagedThreadId.ToString() + " - "+ DateTime.Now.ToString( "HH:mm:ss"));
Response.Write( "<br />");
}
void Task3() void Task3()
{
System.Threading.Thread.Sleep(3000);
Response.Write( "Task3 - " + "ThreadId:" + Thread.CurrentThread.ManagedThreadId.ToString() + " - "+ DateTime.Now.ToString( "HH:mm:ss"));
Response.Write( "<br />");
}
}
}
/*
运行结果:
Task2 - ThreadId:26 - 09:11:58
Task1 - ThreadId:25 - 09:11:58
Task3 - ThreadId:24 - 09:11:58
*/
using System.Collections.Generic;
using System.Linq;
using System.Web;
using System.Web.UI;
using System.Web.UI.WebControls;
using System.Threading;
namespace CSharp.Parallel
{
public partial class ParallelInvoke : System.Web.UI.Page
{
void Page_Load() void Page_Load(object sender, EventArgs e)
{
var tasks = new Action[] { () => Task1(), () => Task2(), () => Task3() };
// System.Threading.Tasks.Parallel.Invoke - 并行调用多个任务
System.Threading.Tasks.Parallel.Invoke(tasks);
}
void Task1() void Task1()
{
Thread.Sleep(3000);
Response.Write( "Task1 - " + "ThreadId:" + Thread.CurrentThread.ManagedThreadId.ToString() + " - "+ DateTime.Now.ToString( "HH:mm:ss"));
Response.Write( "<br />");
}
void Task2() void Task2()
{
System.Threading.Thread.Sleep(3000);
Response.Write( "Task2 - " + "ThreadId:" + Thread.CurrentThread.ManagedThreadId.ToString() + " - "+ DateTime.Now.ToString( "HH:mm:ss"));
Response.Write( "<br />");
}
void Task3() void Task3()
{
System.Threading.Thread.Sleep(3000);
Response.Write( "Task3 - " + "ThreadId:" + Thread.CurrentThread.ManagedThreadId.ToString() + " - "+ DateTime.Now.ToString( "HH:mm:ss"));
Response.Write( "<br />");
}
}
}
/*
运行结果:
Task2 - ThreadId:26 - 09:11:58
Task1 - ThreadId:25 - 09:11:58
Task3 - ThreadId:24 - 09:11:58
*/
4、Task 的 Demo
Parallel/ParallelTask.aspx.cs
Parallel/ParallelTask.aspx.cs
/*
Task - 任务,基于线程池。其使我们对并行编程变得更简单,且不用关心底层是怎么实现的
*/
using System;
using System.Collections.Generic;
using System.Linq;
using System.Web;
using System.Web.UI;
using System.Web.UI.WebControls;
using System.Threading;
using System.Threading.Tasks;
namespace CSharp.Parallel
{
public partial class ParallelTask : System.Web.UI.Page
{
void Page_Load() void Page_Load(object sender, EventArgs e)
{
/*
* CancellationTokenSource - 取消任务的操作需要用到的一个类
* Token - 一个 CancellationToken 类型的对象,用于通知取消指定的操作
* IsCancellationRequested - 是否收到了取消操作的请求
* Cancel() - 结束任务的执行
* ParallelOptions - 并行运算选项
* CancellationToken - 设置一个 Token,用于取消任务时的相关操作
* MaxDegreeOfParallelism - 指定一个并行循环最多可以使用多少个线程
*/
CancellationTokenSource cts = new CancellationTokenSource();
ParallelOptions pOption = new ParallelOptions() { CancellationToken = cts.Token };
pOption.MaxDegreeOfParallelism = 10;
Response.Write( "开始执行,3.5 秒后结束");
Response.Write( "<br />");
/*
* Task - 任务类
* Factory.StartNew() - 创建并开始一个或一批新任务
* ContinueWith() - 此任务完成后执行指定的另一个任务
* AsyncState - 此任务的上下文对象
* Wait() - 阻塞,直到任务完成
*/
Task task0 = Task.Factory.StartNew(() =>
{
Thread.Sleep(3500);
cts.Cancel();
Response.Write( "结束");
Response.Write( "<br />");
});
// 通过 System.Threading.Tasks.Parallel.Invoke 执行任务的时候,可以加入 ParallelOptions 参数,用于对此并行运算做一些配置
System.Threading.Tasks.Parallel.Invoke(pOption,
() => Task1(pOption.CancellationToken),
() => Task2(pOption.CancellationToken));
/*
* 一个 Task 内可以包含多个 Task
Task tasks = new Task(() =>
{
Task.Factory.StartNew(() => Method());
Task.Factory.StartNew(() => Method2());
Task.Factory.StartNew(() => Method3());
});
tasks.Start();
// 阻塞,直到整个任务完成
tasks.Wait();
*/
/*
* 带返回值的 Task
Func<object, long> fun = delegate(object state)
{
return 1.0;
};
Task<long> tsk = new Task<long>(fun, "state");
tsk.Start();
Response.Write(tsk.Result.ToString());
*/
}
void Task1() void Task1(CancellationToken token)
{
// 每隔 1 秒执行一次,直到此任务收到了取消的请求
// 注意:虽然此处是其他线程要向主线程(UI线程)上输出信息,但因为使用了 Task ,所以不用做任何处理
while (!token.IsCancellationRequested)
{
Response.Write( "Task1 - " + "ThreadId: " + Thread.CurrentThread.ManagedThreadId.ToString());
Response.Write( "<br />");
Thread.Sleep(1000);
}
}
void Task2() void Task2(CancellationToken token)
{
while (!token.IsCancellationRequested)
{
Response.Write( "Task2 - " + "ThreadId: " + Thread.CurrentThread.ManagedThreadId.ToString());
Response.Write( "<br />");
Thread.Sleep(1000);
}
}
}
}
/*
运行结果:
开始执行,3.5 秒后结束
Task2 - ThreadId: 6
Task1 - ThreadId: 48
Task1 - ThreadId: 48
Task2 - ThreadId: 6
Task2 - ThreadId: 6
Task1 - ThreadId: 48
Task2 - ThreadId: 6
Task1 - ThreadId: 48
结束
*/
Task - 任务,基于线程池。其使我们对并行编程变得更简单,且不用关心底层是怎么实现的
*/
using System;
using System.Collections.Generic;
using System.Linq;
using System.Web;
using System.Web.UI;
using System.Web.UI.WebControls;
using System.Threading;
using System.Threading.Tasks;
namespace CSharp.Parallel
{
public partial class ParallelTask : System.Web.UI.Page
{
void Page_Load() void Page_Load(object sender, EventArgs e)
{
/*
* CancellationTokenSource - 取消任务的操作需要用到的一个类
* Token - 一个 CancellationToken 类型的对象,用于通知取消指定的操作
* IsCancellationRequested - 是否收到了取消操作的请求
* Cancel() - 结束任务的执行
* ParallelOptions - 并行运算选项
* CancellationToken - 设置一个 Token,用于取消任务时的相关操作
* MaxDegreeOfParallelism - 指定一个并行循环最多可以使用多少个线程
*/
CancellationTokenSource cts = new CancellationTokenSource();
ParallelOptions pOption = new ParallelOptions() { CancellationToken = cts.Token };
pOption.MaxDegreeOfParallelism = 10;
Response.Write( "开始执行,3.5 秒后结束");
Response.Write( "<br />");
/*
* Task - 任务类
* Factory.StartNew() - 创建并开始一个或一批新任务
* ContinueWith() - 此任务完成后执行指定的另一个任务
* AsyncState - 此任务的上下文对象
* Wait() - 阻塞,直到任务完成
*/
Task task0 = Task.Factory.StartNew(() =>
{
Thread.Sleep(3500);
cts.Cancel();
Response.Write( "结束");
Response.Write( "<br />");
});
// 通过 System.Threading.Tasks.Parallel.Invoke 执行任务的时候,可以加入 ParallelOptions 参数,用于对此并行运算做一些配置
System.Threading.Tasks.Parallel.Invoke(pOption,
() => Task1(pOption.CancellationToken),
() => Task2(pOption.CancellationToken));
/*
* 一个 Task 内可以包含多个 Task
Task tasks = new Task(() =>
{
Task.Factory.StartNew(() => Method());
Task.Factory.StartNew(() => Method2());
Task.Factory.StartNew(() => Method3());
});
tasks.Start();
// 阻塞,直到整个任务完成
tasks.Wait();
*/
/*
* 带返回值的 Task
Func<object, long> fun = delegate(object state)
{
return 1.0;
};
Task<long> tsk = new Task<long>(fun, "state");
tsk.Start();
Response.Write(tsk.Result.ToString());
*/
}
void Task1() void Task1(CancellationToken token)
{
// 每隔 1 秒执行一次,直到此任务收到了取消的请求
// 注意:虽然此处是其他线程要向主线程(UI线程)上输出信息,但因为使用了 Task ,所以不用做任何处理
while (!token.IsCancellationRequested)
{
Response.Write( "Task1 - " + "ThreadId: " + Thread.CurrentThread.ManagedThreadId.ToString());
Response.Write( "<br />");
Thread.Sleep(1000);
}
}
void Task2() void Task2(CancellationToken token)
{
while (!token.IsCancellationRequested)
{
Response.Write( "Task2 - " + "ThreadId: " + Thread.CurrentThread.ManagedThreadId.ToString());
Response.Write( "<br />");
Thread.Sleep(1000);
}
}
}
}
/*
运行结果:
开始执行,3.5 秒后结束
Task2 - ThreadId: 6
Task1 - ThreadId: 48
Task1 - ThreadId: 48
Task2 - ThreadId: 6
Task2 - ThreadId: 6
Task1 - ThreadId: 48
Task2 - ThreadId: 6
Task1 - ThreadId: 48
结束
*/
5、PLINQ 的 Demo
Parallel/ParallelPLINQ.aspx.cs
Parallel/ParallelPLINQ.aspx.cs
/*
PLINQ - 用于对内存中的数据做并行运算,也就是说其只支持 LINQ to Object 的并行运算
*/
using System;
using System.Collections.Generic;
using System.Linq;
using System.Web;
using System.Web.UI;
using System.Web.UI.WebControls;
namespace CSharp.Parallel
{
public partial class ParallelPLINQ : System.Web.UI.Page
{
void Page_Load() void Page_Load(object sender, EventArgs e)
{
List<int> list = new List<int>();
for (int i = 0; i < 100; i++)
{
list.Add(i);
}
// AsParallel() - 并行运算
// AsSequential() - 串行运算
// AsOrdered() - 保持数据的原有顺序(AsSequential()指的是串行运算;AsOrdered()指的是如果在并行运算的前提下,它会把结果先缓存,然后排序,最后再把排序后的数据做输出)
// AsUnordered() - 可以不必保持数据的原有顺序
// WithDegreeOfParallelism() - 明确地指出需要使用多少个线程来完成工作
// WithCancellation( new CancellationTokenSource().Token) - 指定一个 CancellationToken 类型的参数
ParallelQuery nums = from num in list.AsParallel<int>().AsOrdered<int>()
where num % 10 == 0
select num;
foreach (var num in nums)
{
Response.Write(num.ToString());
Response.Write( "<br />");
}
// 聚合方法也可以做并行运算
Response.Write(list.AsParallel().Average().ToString());
Response.Write( "<br />");
// 自定义聚合方法做并行运算的 Demo(实现一个取集合的平均值的功能)
double myAggregateResult = list.AsParallel().Aggregate(
// 聚合变量的初始值
0d,
// 在每个数据分区上,计算此分区上的数据
// 第一个参数:对应的数据分区的计算结果;第二个参数:对应的数据分区的每个数据项
(value, item) =>
{
double result = value + item;
return result;
},
// 根据每个数据分区上的计算结果,再次做计算
// 第一个参数:全部数据的计算结果;第二个参数:每个数据分区上的计算结果
(value, data) =>
{
double result = value + data;
return result;
},
// 根据全部数据的计算结果再次计算,得到最终的聚合结果
(result) => result / list.Count
);
Response.Write(myAggregateResult.ToString());
}
}
}
/*
运行结果:
0
10
20
30
40
50
60
70
80
90
49.5
49.5
*/
PLINQ - 用于对内存中的数据做并行运算,也就是说其只支持 LINQ to Object 的并行运算
*/
using System;
using System.Collections.Generic;
using System.Linq;
using System.Web;
using System.Web.UI;
using System.Web.UI.WebControls;
namespace CSharp.Parallel
{
public partial class ParallelPLINQ : System.Web.UI.Page
{
void Page_Load() void Page_Load(object sender, EventArgs e)
{
List<int> list = new List<int>();
for (int i = 0; i < 100; i++)
{
list.Add(i);
}
// AsParallel() - 并行运算
// AsSequential() - 串行运算
// AsOrdered() - 保持数据的原有顺序(AsSequential()指的是串行运算;AsOrdered()指的是如果在并行运算的前提下,它会把结果先缓存,然后排序,最后再把排序后的数据做输出)
// AsUnordered() - 可以不必保持数据的原有顺序
// WithDegreeOfParallelism() - 明确地指出需要使用多少个线程来完成工作
// WithCancellation( new CancellationTokenSource().Token) - 指定一个 CancellationToken 类型的参数
ParallelQuery nums = from num in list.AsParallel<int>().AsOrdered<int>()
where num % 10 == 0
select num;
foreach (var num in nums)
{
Response.Write(num.ToString());
Response.Write( "<br />");
}
// 聚合方法也可以做并行运算
Response.Write(list.AsParallel().Average().ToString());
Response.Write( "<br />");
// 自定义聚合方法做并行运算的 Demo(实现一个取集合的平均值的功能)
double myAggregateResult = list.AsParallel().Aggregate(
// 聚合变量的初始值
0d,
// 在每个数据分区上,计算此分区上的数据
// 第一个参数:对应的数据分区的计算结果;第二个参数:对应的数据分区的每个数据项
(value, item) =>
{
double result = value + item;
return result;
},
// 根据每个数据分区上的计算结果,再次做计算
// 第一个参数:全部数据的计算结果;第二个参数:每个数据分区上的计算结果
(value, data) =>
{
double result = value + data;
return result;
},
// 根据全部数据的计算结果再次计算,得到最终的聚合结果
(result) => result / list.Count
);
Response.Write(myAggregateResult.ToString());
}
}
}
/*
运行结果:
0
10
20
30
40
50
60
70
80
90
49.5
49.5
*/
本文转自webabcd 51CTO博客,原文链接:http://blog.51cto.com/webabcd/341286,如需转载请自行联系原作者