一、测试代码

public class XY_ThreadData

{

private static Integer data = 0;

private static Map<Thread, Integer> map = new HashMap<Thread, Integer>();

private static ThreadLocal<Integer> local = new ThreadLocal<Integer>();

public static void setData(Integer value)

{

 data = value;

}

public static Integer getData()

{

 System.out.println("ThreadName:" + Thread.currentThread() + " data value:" + data);

 return data;

}

public static void setMapData(Integer value)

{

 map.put(Thread.currentThread(), value);

}

public static Integer getMapData()

{

 Object obj = map.get(Thread.currentThread());

 System.out.println("ThreadName:" + Thread.currentThread() + "map value:" + obj);

 return Integer.parseInt(obj.toString());

}

public static void setThreadLocalData(Integer value)

{

 local.set(value);

}

public static Integer getThreadLocalData()

{

 Object obj = local.get();

 System.out.println("ThreadName:" + Thread.currentThread() + "threadlocal value:" + obj);

 return Integer.parseInt(obj.toString());

}

}

public class XY_ThreadData_Test

{

public static void main(String[] args)

{

 for (int i = 0; i < 10; i++)

 {

  new Thread(new Runnable() {

   public void run()

   {

    final int value = new Random().nextInt(); // 每个线程自己创建的变量  

    XY_ThreadData.setData(value);

    XY_ThreadData.getData();

   }

  }).start();

 }

}

}

ThreadName:Thread[Thread-3,5,main] data value:1046062244

ThreadName:Thread[Thread-6,5,main] data value:-879673875

ThreadName:Thread[Thread-2,5,main] data value:-125397465

ThreadName:Thread[Thread-4,5,main] data value:-1546413071

ThreadName:Thread[Thread-0,5,main] data value:754770101

ThreadName:Thread[Thread-8,5,main] data value:-1666786926

ThreadName:Thread[Thread-5,5,main] data value:-1666786926

ThreadName:Thread[Thread-9,5,main] data value:1046062244

ThreadName:Thread[Thread-1,5,main] data value:269410746

ThreadName:Thread[Thread-7,5,main] data value:269410746

分析:可以看到以下两个线程中data的值时一样的,没有做到各个线程变量独一份

ThreadName:Thread[Thread-8,5,main] data value:-1666786926

ThreadName:Thread[Thread-5,5,main] data value:-1666786926


public class XY_ThreadData_Test

{

public static void main(String[] args)

{

 for (int i = 0; i < 10; i++)

 {

  new Thread(new Runnable() {

   public void run()

   {

    final int value = new Random().nextInt();  

    XY_ThreadData.setMapData(value);

    XY_ThreadData.getMapData();

   }

  }).start();

 }

}

}

ThreadName:Thread[Thread-0,5,main]map value:-1138167111

ThreadName:Thread[Thread-4,5,main]map value:-1545929782

ThreadName:Thread[Thread-6,5,main]map value:-1612385717

ThreadName:Thread[Thread-3,5,main]map value:-1390594683

ThreadName:Thread[Thread-8,5,main]map value:518506934

ThreadName:Thread[Thread-2,5,main]map value:1583239372

ThreadName:Thread[Thread-5,5,main]map value:995578601

ThreadName:Thread[Thread-1,5,main]map value:-916627474

ThreadName:Thread[Thread-7,5,main]map value:-960206804

ThreadName:Thread[Thread-9,5,main]map value:-1187504747

分析:模拟线程变量独一份,无重复


public class XY_ThreadData_Test

{

public static void main(String[] args)

{

 for (int i = 0; i < 10; i++)

 {

  new Thread(new Runnable() {

   public void run()

   {

    final int value = new Random().nextInt();

    XY_ThreadData.setThreadLocalData(value);

    XY_ThreadData.getThreadLocalData();

   }

  }).start();

 }

}

}

ThreadName:Thread[Thread-1,5,main]threadlocal value:935024745

ThreadName:Thread[Thread-4,5,main]threadlocal value:1207176846

ThreadName:Thread[Thread-7,5,main]threadlocal value:-1503260374

ThreadName:Thread[Thread-9,5,main]threadlocal value:-1538563684

ThreadName:Thread[Thread-6,5,main]threadlocal value:955259906

ThreadName:Thread[Thread-8,5,main]threadlocal value:894428541

ThreadName:Thread[Thread-3,5,main]threadlocal value:730986356

ThreadName:Thread[Thread-2,5,main]threadlocal value:-540225655

ThreadName:Thread[Thread-5,5,main]threadlocal value:-2003809947

ThreadName:Thread[Thread-0,5,main]threadlocal value:1917431015

分析:线程变量独一份,无重复


二、ThreadLocal分析

要点1

ThreadLocal不是用来解决共享对象的多线程访问问题的,一般情况下通过ThreadLocal.set()到线程中的对象是该线程自己使用的对象,其他线程是不需要访问的,也访问不到的。各个线程中访问的是不同的对象。


要点2

说ThreadLocal使得各线程能够保持各自独立的一个对象,并不是通过ThreadLocal.set()来实现的,而是通过每个线程中的new对象的操作来创建的对象,每个线程创建一个,不是什么对象的拷贝或副本。通ThreadLocal.set()将这个新创建的对象的引用保存到各线程的自己的一个map中,每个线程都有这样一个map,执行ThreadLocal.get()时,各线程从自己的map中取出放进去的对象,因此取出来的是各自自己线程中的对象,ThreadLocal实例是作为map的key来使用的。


要点3

如果ThreadLocal.set()进去的东西本来就是多个线程共享的同一个对象,那么多个线程的ThreadLocal.get()取得的还是这个共享对象本身,还是有并发访问问题。


更多关于ThreadLocal信息请参看:http://www.iteye.com/topic/103804