并行学习小结，直接上源代码
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using
System;
using
System.Collections.Generic;
using
System.Linq;
using
System.Web;
using
System.Web.UI;
using
System.Web.UI.WebControls;
using
System.Threading.Tasks;
using
System.Threading;
using
System.Diagnostics;
using
System.Collections.Concurrent;
public
partial
class
test : System.Web.UI.Page
{ protected
void
Page_Load(object
sender, EventArgs e)
{
UseParallel();
UsePLINQ();
}
/// <summary>
/// PLINQ的基本方法应用集合
/// </summary>
private
void
UsePLINQ()
{
#region 并行集合运算，Environment.ProcessorCount - 1 给一个处理器出来处理其他任务
ConcurrentDictionary<int, string> cds = new
ConcurrentDictionary<int, string>();//并行考虑用的集合
Parallel.For(0, 3000, i =>
{
cds.TryAdd(i, Math.Sqrt(i).ToString());
});
var
q1 = from
c in
cds.Values.AsParallel().WithDegreeOfParallelism(Environment.ProcessorCount - 1)
select
c;//直接获取该集合,Environment.ProcessorCount - 1 给一个处理器出来处理其他任务
#endregion
#region 并行常用的运算
ConcurrentBag<int> bags = new
ConcurrentBag<int>();//线程安全的集合
var
list = ParallelEnumerable.Range(0,3000);//生成并行集合
list.ForAll(i => {
bags.Add(i);
});
Response.Write("bags长度："
+ bags.Count+"<br/>");
Response.Write("list整数和："
+ list.Sum() + "<br/>");
Response.Write("list最大值："
+ list.Max() + "<br/>");
Response.Write("list最小值："
+ list.Min() + "<br/>");
Response.Write("list平均值："
+ list.Average() + "<br/>");
Response.Write("list默认值："
+ list.FirstOrDefault() + "<br/>");
#endregion
#region 先并行分组，在对每组并行查询统计
List<Student> list2 = new
List<Student>()
{
new
Student()
{
ID = 1,
Name = "jack",
Age = 20
},
new
Student()
{
ID = 1,
Name = "mary",
Age = 25
},
new
Student()
{
ID = 1,
Name = "joe",
Age = 29
},
new
Student()
{
ID = 1,
Name = "Aaron",
Age = 25
}
};
var
map = list2.AsParallel().ToLookup(i => i.Age,count=>1);//化简统计
var
reduce = from
IGrouping<int, int> singleMap
in
map.AsParallel()
select
new {
Age = singleMap.Key,
Count = singleMap.Count()
};
reduce.ForAll(i =>{
Response.Write(string.Format("当前Age={0}的人数有:{1}人<br/>", i.Age, i.Count));
});
#endregion
foreach
(var
o in
q1)
{
Response.Write(o + "<br/>");
}
}
/// <summary>
/// Parallel的基本使用方法集合
/// </summary>
private
void
UseParallel()
{
#region 并行查询和并行输出
List<string> lists = new
List<string>();
for
(int
i = 0; i < 1000; i++)
{
lists.Add(i.ToString());
}
var
q1 = from
p in
lists.AsParallel()
where
Convert.ToInt32(p) > 100
select
p;// 并行查询
q1.ForAll<string>(p =>
{
Response.Write(p + "<br/>");//并行输出，注意观察输出结果不是有序的
});
#endregion
#region 串行执行任务
Stopwatch sw = new
Stopwatch();
sw.Start();
Run1();
Run2();
Response.Write("串行执行时间:"
+ sw.ElapsedMilliseconds + "<br/>");
#endregion
#region 并行执行任务
sw.Restart();
Parallel.Invoke(Run1, Run2);
Response.Write("并行执行时间:"
+ sw.ElapsedMilliseconds + "<br/>");
#endregion
#region 并行赋值
List<int> mylist = new
List<int>();
Parallel.ForEach(Partitioner.Create(0, 5000), i =>
{
for
(int
m = i.Item1; m < i.Item2; m++)
{
mylist.Add(m);
}
});
#endregion
#region 并行 退出循环 Break和Stop
List<int> mylist2 = new
List<int>();
Parallel.For(0, 5000, (i, state) =>
{
if
(mylist2.Count == 50)
{
state.Break();
return;
}
mylist2.Add(i);
});
#endregion
#region 并行抛出异常处理
try
{
Parallel.Invoke(Run1, Run2, Run3);
}
catch
(AggregateException ex)
{
foreach
(var
single in
ex.InnerExceptions)
{
Response.Write(single.Message + "<br/>");
}
}
#endregion
}
private
void
Run1()
{
Thread.Sleep(3000);
}
private
void
Run2()
{
Thread.Sleep(5000);
}
private
void
Run3()
{
Thread.Sleep(1000);
}
private
void
Run4(int
ms)
{
Thread.Sleep(ms * 100);
}
}public
class
Student {
public
int
ID { get; set; }
public
string
Name { get; set; }
public
int
Age { get; set; }
public
DateTime CreateTime { get; set; }
} |