线程对象与线程的不同

标签：c语言   嵌入式   

线程的handle是指向"线程核心对象"，而不是指向线程本身。

#define WIN32_LEAN_AND_MEAN

#include <stdlib.h>
#include <stdio.h>
#include <Windows.h>

DWORD WINAPI ThreadFunc(LPVOID);

int main()
{
	HANDLE hThrd;
	DWORD threadID;
	int i;

	for ( i = 0; i < 5; i++)
	{
		hThrd = CreateThread(NULL, 0, ThreadFunc, (LPVOID)i, 0, &threadID);
		if (hThrd)
		{
			printf("Thread launched %d\n",i);
		}
	}
	Sleep(2000);

	return EXIT_SUCCESS;
}


DWORD WINAPI ThreadFunc(LPVOID n)
{
	int i;
	for( i =0; i < 10; i++)
		printf("%d%d%d%d%d%d%d%d%d%d\n",n,n,n,n,n,n,n,n,n,n);
	return 0;
}

“线程核心对象”引用到的那个线程也会令核心对象开启。

“引用计数”机制保证新的进程有个地方可以写下其返回值。这样的机制也保证就线程能够读取那个返回值----只要它没有调用CloseHandle（）。

BOOL GetExitCodeThread（

           HANDLE hthread，
           LPDWORD lpExitCode
）;

#define WIN32_LEAN_AND_MEAN


#include <stdlib.h>
#include <stdio.h>
#include <Windows.h>
#include <conio.h>


DWORD WINAPI ThreadFunc(LPVOID);


int main()
{
<span style="white-space:pre">	</span>HANDLE hThrd1;
<span style="white-space:pre">	</span>HANDLE hThrd2;
<span style="white-space:pre">	</span>DWORD exitCode1 = 0;
<span style="white-space:pre">	</span>DWORD exitCode2 = 0;
<span style="white-space:pre">	</span>DWORD threadId;


<span style="white-space:pre">	</span>hThrd1 = CreateThread(NULL,
<span style="white-space:pre">		</span>0,
<span style="white-space:pre">		</span>ThreadFunc,
<span style="white-space:pre">		</span>(LPVOID)1,
<span style="white-space:pre">		</span>0,
<span style="white-space:pre">		</span>&threadId);
<span style="white-space:pre">	</span>if (hThrd1)
<span style="white-space:pre">	</span>{
<span style="white-space:pre">		</span>printf(" Thread 1 lauched\n");
<span style="white-space:pre">	</span>}


<span style="white-space:pre">	</span>hThrd2 = CreateThread(NULL,
<span style="white-space:pre">		</span>0,
<span style="white-space:pre">		</span>ThreadFunc,
<span style="white-space:pre">		</span>(LPVOID)2,
<span style="white-space:pre">		</span>0,
<span style="white-space:pre">		</span>&threadId);


<span style="white-space:pre">	</span>if (hThrd2)
<span style="white-space:pre">	</span>{
<span style="white-space:pre">		</span>printf("Thread 2 launched\n");
<span style="white-space:pre">	</span>}


<span style="white-space:pre">	</span>for(;;)
<span style="white-space:pre">	</span>{
<span style="white-space:pre">		</span>printf(" Please any key to exit....\n");
<span style="white-space:pre">		</span>getch();


<span style="white-space:pre">		</span>GetExitCodeThread(hThrd1,&exitCode1);
<span style="white-space:pre">		</span>GetExitCodeThread(hThrd2,&exitCode2);
<span style="white-space:pre">		</span>if (exitCode1 == STILL_ACTIVE)
<span style="white-space:pre">		</span>{
<span style="white-space:pre">			</span>puts("Thread 1 is still running!\n");
<span style="white-space:pre">		</span>}


<span style="white-space:pre">		</span>if(exitCode2 == STILL_ACTIVE)
<span style="white-space:pre">		</span>{
<span style="white-space:pre">			</span>puts("Thread2 is still running!\n");
<span style="white-space:pre">		</span>}
<span style="white-space:pre">		</span>if (exitCode1 != STILL_ACTIVE && exitCode2 != STILL_ACTIVE)
<span style="white-space:pre">			</span>break;
<span style="white-space:pre">	</span>}


<span style="white-space:pre">	</span>CloseHandle(hThrd1);
<span style="white-space:pre">	</span>CloseHandle(hThrd2);


<span style="white-space:pre">	</span>printf("Thread 1 returned %d\n",exitCode1);
<span style="white-space:pre">	</span>printf("Thread 2 returned %d \n",exitCode2);


<span style="white-space:pre">	</span>return EXIT_SUCCESS;
}




DWORD WINAPI ThreadFunc(LPVOID n)
{
<span style="white-space:pre">	</span>Sleep((DWORD)n*1000*2);
<span style="white-space:pre">	</span>return (DWORD)n*10;
}

每次运行的结果都不一样，这中不确定性在多线程中是非常常见的

<img src="data:image/png;base64,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" alt="" />

<img src="data:image/png;base64,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" alt="" />

线程对象与线程的不同

标签：c语言   嵌入式   

原文地址：http://blog.csdn.net/u011046042/article/details/42044763