转载原文:http://blog.csdn.net/john8169/article/details/53228016
读写锁: 分为读锁和写锁,多个读锁不互斥,读锁和写锁互斥,这是有JVM自己控制的.如果代码只能读取数据,可以多人同时读,不能同时写,上读锁,
如果代码要修改数据,只能有一个人写,而且不能同时读取.上写锁.
线程进入写锁的前提条件:
没有其他线程的读锁和写锁;
线程进入读锁的前提条件:
没有其他线程的写锁或写请求
(a).重入方面其内部的WriteLock可以获取ReadLock，但是反过来ReadLock想要获得WriteLock则永远都不要想。
(b).WriteLock可以降级为ReadLock，顺序是：先获得WriteLock再获得ReadLock，然后释放WriteLock，这时候线程将保持Readlock的持有。反过来ReadLock想要升级为WriteLock则不可能，为什么？参看(a)，呵呵.
(c).ReadLock可以被多个线程持有并且在作用时排斥任何的WriteLock，而WriteLock则是完全的互斥。这一特性最为重要，因为对于高读取频率而相对较低写入的数据结构，使用此类锁同步机制则可以提高并发量。
(d).不管是ReadLock还是WriteLock都支持Interrupt，语义与ReentrantLock一致。
(e).WriteLock支持Condition并且与ReentrantLock语义一致，而ReadLock则不能使用Condition，否则抛出UnsupportedOperationException异常。
package com.imooc.locks; import java.util.concurrent.locks.ReadWriteLock;
import java.util.concurrent.locks.ReentrantReadWriteLock; public class Queue { private Object data = null;//共享数据,只能有一个线程写该数据,但可以多个线程读取该数据 //读写锁
ReadWriteLock rwl = new ReentrantReadWriteLock(); // 相当于读操作
public void get() {
rwl.readLock().lock();
try {
System.out.println(Thread.currentThread().getName() + " be ready to read data!");
Thread.sleep((long) (Math.random() * 1000));
System.out.println(Thread.currentThread().getName() + "have read data :" + data);
} catch (InterruptedException e) {
e.printStackTrace();
} finally {
rwl.readLock().unlock();
}
} // 相当于写操作
public void put(Object data) {
rwl.writeLock().lock();
try {
System.out.println(Thread.currentThread().getName() + " be ready to write data!");
Thread.sleep((long) (Math.random() * 1000));
this.data = data;
System.out.println(Thread.currentThread().getName() + " have write data: " + data);
} catch (InterruptedException e) {
e.printStackTrace();
} finally {
rwl.writeLock().unlock();
}
} }
package com.imooc.locks;
import java.util.Random;
public class ReadWriteLockTest {
public static void main(String[] args) {
final Queue q3 = new Queue();
for (int i = 0; i < 3; i++) {
new Thread() {
public void run() {
while (true) {
q3.get();
}
}
}.start();
new Thread() {
public void run() {
while (true) {
q3.put(new Random().nextInt(10000));
}
}
}.start();
}
}
}
Thread-0 be ready to read data!
Thread-2 be ready to read data!
Thread-4 be ready to read data!
Thread-0have read data :null
Thread-2have read data :null
Thread-4have read data :null
Thread-1 be ready to write data!
Thread-1 have write data: 3101
Thread-1 be ready to write data!
Thread-1 have write data: 8258
Thread-1 be ready to write data!
Thread-1 have write data: 7242
Thread-3 be ready to write data!
Thread-3 have write data: 4810
Thread-5 be ready to write data!
Thread-5 have write data: 7597
Thread-5 be ready to write data!
Thread-5 have write data: 8800
Thread-0 be ready to read data!
Thread-4 be ready to read data!
Thread-2 be ready to read data!
Thread-0have read data :8800
Thread-2have read data :8800
Thread-4have read data :8800
Thread-1 be ready to write data!
Thread-1 have write data: 6606
Thread-1 be ready to write data!
Thread-1 have write data: 5436
Thread-1 be ready to write data!
Thread-1 have write data: 3912
Thread-1 be ready to write data!
Thread-1 have write data: 7689
Thread-3 be ready to write data!
Thread-3 have write data: 3102
Thread-3 be ready to write data!
Thread-3 have write data: 466
Thread-3 be ready to write data!
Thread-3 have write data: 7377
Thread-3 be ready to write data!
Thread-3 have write data: 5461
Thread-3 be ready to write data!
Thread-3 have write data: 175
Thread-3 be ready to write data!
Thread-3 have write data: 8805
Thread-3 be ready to write data!
Thread-3 have write data: 8898
Thread-5 be ready to write data!
Thread-5 have write data: 8823
Thread-5 be ready to write data!
Thread-5 have write data: 5615
Thread-5 be ready to write data!
Thread-5 have write data: 8118
Thread-0 be ready to read data!
Thread-2 be ready to read data!
Thread-4 be ready to read data!
Thread-0have read data :8118
Thread-2have read data :8118
Thread-4have read data :8118
Thread-1 be ready to write data!
Thread-1 have write data: 5314
Thread-1 be ready to write data!
从打印结果可以看出:
多个线程可以同时读取数据,但是只有一个线程可以写数据;