多线程那点事—Parallel.for

先看段代码：

1 for (int i = 0; i < 10; i++)
2 {
3     Task.Factory.StartNew(()=>Console.WriteLine($"{Thread.CurrentThread.ManagedThreadId} ~ {i}"));
4 }

从代码上可以看出我们预期是打印1~10，但实际的打印结果是：

1 7 ~ 10
2 4 ~ 10
3 10 ~ 10
4 9 ~ 10
5 4 ~ 10
6 3 ~ 10
7 5 ~ 10
8 9 ~ 10
9 6 ~ 10
10 8 ~ 10

与预期的不一致，我们预期是打印数字1到10，但实际打印出来的是10次10。因为这几个lambda表达式中使用了同一个变量，并且这些匿名函数共享变量值。

再来看下面这段代码：

1 Action<int> displayNumber = n => Console.WriteLine(n);
2 int i = 5;
3 Task taskOne = Task.Factory.StartNew(() => displayNumber(i));
4 i = 7;
5 Task taskTwo = Task.Factory.StartNew(() => displayNumber(i));
6 Task.WaitAll(taskOne,taskTwo);

输出结果：

7
7

当闭包通过lambda表达式捕获可变变量时，lambda捕获变量的引用，而不是捕获该变量的当前值。因此，如果任务在变量的引用值更改后运行，则该值将是内存中最新的值，而不是捕获变量时的值。

为解决该问题，我们引入Parallel类来解决问题：

1 Parallel.For(0,10,i=>Console.WriteLine($"{Thread.CurrentThread.ManagedThreadId} ~ {i}"));

打印结果：

1 1 ~ 0
2 1 ~ 2
3
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3 ~ 1
4 3 ~ 4
5 3 ~ 7
6 3 ~ 8
7 3 ~ 9
8 1 ~ 3
9 5 ~ 5
10 4 ~ 6

Parallel 类 提供对并行循环和区域的支持， 现在我们看下Parallel.for的代码：

1 // this needs to be in try-block because it can throw in  BuggyScheduler.MaxConcurrencyLevel
2                 rootTask = new ParallelForReplicatingTask(
3                     parallelOptions,
4                     delegate
5                     {
6                         //
7                         // first thing we do upon enterying the task is to register  as a new "RangeWorker" with the
8                         // shared RangeManager instance.
9                         //
10                         // If this call returns a RangeWorker struct which wraps the  state needed by this task
11                         //
12                         // We need to call FindNewWork32() on it to see whether  there's a chunk available.
13                         //
14                         // Cache some information about the current task
15                         Task currentWorkerTask = Task.InternalCurrent;
16                         bool bIsRootTask = (currentWorkerTask == rootTask);
17                         RangeWorker currentWorker = new RangeWorker();
18                         Object savedStateFromPreviousReplica =  currentWorkerTask.SavedStateFromPreviousReplica;
19                         if (savedStateFromPreviousReplica is RangeWorker)
20                             currentWorker =  (RangeWorker)savedStateFromPreviousReplica;
21                         else
22                             currentWorker = rangeManager.RegisterNewWorker();
23                         // These are the local index values to be used in the  sequential loop.
24                         // Their values filled in by FindNewWork32
25                         int nFromInclusiveLocal;
26                         int nToExclusiveLocal;
27                         if (currentWorker.FindNewWork32(out nFromInclusiveLocal, out  nToExclusiveLocal) == false ||
28                             sharedPStateFlags.ShouldExitLoop(nFromInclusiveLocal) ==  true)
29                         {
30                             return; // no need to run
31                         }
32                         // ETW event for ParallelFor Worker Fork
33                         if (TplEtwProvider.Log.IsEnabled())
34                         {
35                             TplEtwProvider.Log.ParallelFork((currentWorkerTask != null  ? currentWorkerTask.m_taskScheduler.Id : TaskScheduler.Current.Id),  (currentWorkerTask != null ? currentWorkerTask.Id : 0),
36                                                              forkJoinContextID);
37                         }
38                         TLocal localValue = default(TLocal);
39                         bool bLocalValueInitialized = false; // Tracks whether  localInit ran without exceptions, so that we can skip localFinally if it wasn't
40                         try
41                         {
42                             // Create a new state object that references the shared  "stopped" and "exceptional" flags
43                             // If needed, it will contain a new instance of  thread-local state by invoking the selector.
44                             ParallelLoopState32 state = null;
45                             if (bodyWithState != null)
46                             {
47                                 Contract.Assert(sharedPStateFlags != null);
48                                 state = new ParallelLoopState32(sharedPStateFlags);
49                             }
50                             else if (bodyWithLocal != null)
51                             {
52                                 Contract.Assert(sharedPStateFlags != null);
53                                 state = new ParallelLoopState32(sharedPStateFlags);
54                                 if (localInit != null)
55                                 {
56                                     localValue = localInit();
57                                     bLocalValueInitialized = true;
58                                 }
59                             }
60                             // initialize a loop timer which will help us decide  whether we should exit early
61                             LoopTimer loopTimer = new  LoopTimer(rootTask.ActiveChildCount);
62                             // Now perform the loop itself.
63                             do
64                             {
65                                 if (body != null)
66                                 {
67                                     for (int j = nFromInclusiveLocal;
68                                          j < nToExclusiveLocal &&  (sharedPStateFlags.LoopStateFlags == ParallelLoopStateFlags.PLS_NONE  // fast path  check as SEL() doesn't inline
69                                                                    ||  !sharedPStateFlags.ShouldExitLoop()); // the no-arg version is used since we have  no state
70                                          j += 1)
71                                     {
72                                         body(j);
73                                     }
74                                 }
75                                 else if (bodyWithState != null)
76                                 {
77                                     for (int j = nFromInclusiveLocal;
78                                         j < nToExclusiveLocal &&  (sharedPStateFlags.LoopStateFlags == ParallelLoopStateFlags.PLS_NONE  // fast path  check as SEL() doesn't inline
79                                                                    ||  !sharedPStateFlags.ShouldExitLoop(j));
80                                         j += 1)
81                                     {
82                                         state.CurrentIteration = j;
83                                         bodyWithState(j, st
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ate);
84                                     }
85                                 }
86                                 else
87                                 {
88                                     for (int j = nFromInclusiveLocal;
89                                         j < nToExclusiveLocal &&  (sharedPStateFlags.LoopStateFlags == ParallelLoopStateFlags.PLS_NONE  // fast path  check as SEL() doesn't inline
90                                                                    ||  !sharedPStateFlags.ShouldExitLoop(j));
91                                         j += 1)
92                                     {
93                                         state.CurrentIteration = j;
94                                         localValue = bodyWithLocal(j, state,  localValue);
95                                     }
96                                 }
97                                 // Cooperative multitasking hack for AppDomain  fairness.
98                                 // Check if allowed loop time is exceeded, if so save  current state and return. The self replicating task logic
99                                 // will detect this, and queue up a replacement task.  Note that we don't do this on the root task.
100                                 if (!bIsRootTask && loopTimer.LimitExceeded())
101                                 {
102                                     currentWorkerTask.SavedStateForNextReplica =  (object)currentWorker;
103                                     break;
104                                 }
105                             }
106                             // Exit if we can't find new work, or if the loop was  stoppped.
107                             while (currentWorker.FindNewWork32(out  nFromInclusiveLocal, out nToExclusiveLocal) &&
108                                     ((sharedPStateFlags.LoopStateFlags ==  ParallelLoopStateFlags.PLS_NONE) ||
109                                        !sharedPStateFlags.ShouldExitLoop(nFromInclusiveLocal)));
110                         }
111                         catch
112                         {
113
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// if we catch an exception in a worker, we signal the  other workers to exit the loop, and we rethrow
114                             sharedPStateFlags.SetExceptional();
115                             throw;
116                         }
117                         finally
118                         {
119                             // If a cleanup function was specified, call it.  Otherwise, if the type is
120                             // IDisposable, we will invoke Dispose on behalf of the  user.
121                             if (localFinally != null && bLocalValueInitialized)
122                             {
123                                 localFinally(localValue);
124                             }
125                             // ETW event for ParallelFor Worker Join
126                             if (TplEtwProvider.Log.IsEnabled())
127                             {
128                                 TplEtwProvider.Log.Parall
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elJoin((currentWorkerTask !=  null ? currentWorkerTask.m_taskScheduler.Id : TaskScheduler.Current.Id),  (currentWorkerTask != null ? currentWorkerTask.Id : 0),
129                                                                  forkJoinContextID);
130                             }
131                         }
132                     },
133                     creationOptions, internalOptions);
134                 rootTask.RunSynchronously(parallelOptions.EffectiveTaskScheduler);  // might throw TSE
135                 rootTask.Wait();
136                 // If we made a cancellation registration, we need to clean it up  now before observing the OCE
137                 // Otherwise we could be caught in the middle of a callback, and  observe PLS_STOPPED, but oce = null
138                 if (parallelOptions.CancellationToken.CanBeCanceled)
139                 {
140                     ctr.Dispose();
141                 }
142                 // If we got through that with no exceptions, and we were canceled,  then
143                 // throw our cancellation exception
144                 if (oce != null) throw oce;

body对于迭代范围 (的每个值调用一次委托 fromInclusive ， toExclusive) 。提供两个参数：

1、一个 Int32 值，该值表示迭代次数。

2、ParallelLoopState可用于提前中断循环的实例。ParallelLoopState对象是由编译器创建的; 它不能在用户代码中实例化。

继续来看：

Parallel.For(0, 10, (i,state) =>
{
if (i > 5)
state.Break();
Console.WriteLine($"{Thread.CurrentThread.ManagedThreadId} ~ {i}");
} );

输出：

1 1 ~ 0
2 1 ~ 1
3 1 ~ 2
4 1 ~ 3
5 1 ~ 4
6 1 ~ 5
7 1 ~ 6

在上面的方法中我们使用了 break方法。

调用 Break 方法会通知 ad8 for 操作，在当前的迭代之后，无需执行迭代。不过，如果所有迭代尚未执行，则仍必须执行当前的所有迭代。

因此，调用 Break 类似于 for c# 等语言中的传统循环内的中断操作，但它并不是完美的替代方法：例如，无法保证当前的迭代不会执行。

今天就先写道这里~