Java多线程使用详解

多线程同步原因：共享变量、执行步骤不确定

控制共享变量

将“单对象多线程”修改为“多对象多线程”
将“全局变量”降级为“局部变量”
使用ThreadLocal

控制执行步骤

synchronized, Lock等加锁

concurrent工具包探索

阻塞队列：ArrayBlockingQueue、LinkedBlockingQueue等
信号量：Semaphore，acquire，release
屏障：CyclicBarrier，await的次数等于N的时候，大家再都开始执行，学的Unix的。可以重置
计数器：CountDownLatch，countDown方法减1，await方法等待值为0再继续。计数值不能重置，屏障可以
Executors工具类，ScheduledThreadPoolExecutor、ThreadPoolExecutor是具体的实现类，Executors通过工厂方法创建不同类型的线程池
并发的数据结构，ConcurrentHashMap, CopyOnWriteArrayList, CopyOnWriteArraySet

locks工具包探索

ReentrantLock，可以用newCondition()创建一个等待条件
ReentrantReadWriteLock

atomic工具包探索

AtomicBoolean\Integer\Long\Reference\
AtomicIntegerArray\LongArray\ReferenceArray
DoubleAccumulator\DoubleAdder\LongAccumulator\LongAdder

构造线程池

对某一端口进行监听，来请求就抛给线程池处理

import java.io.IOException;
import java.net.ServerSocket;
import java.net.Socket;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;

public class NetworkService implements Runnable {
	private final ServerSocket serverSocket;
	private final ExecutorService pool;

	public NetworkService(int port, int poolSize) throws IOException {
		serverSocket = new ServerSocket(port);
		pool = Executors.newFixedThreadPool(poolSize);
	}

	public void run() { // run the service
		try {
			for (;;) {
				pool.execute(new Handler(serverSocket.accept()));
			}
		} catch (IOException ex) {
			pool.shutdown();
		}
	}
}

class Handler implements Runnable {
	private final Socket socket;

	Handler(Socket socket) {
		this.socket = socket;
	}

	public void run() {
		// read and service request on socket
	}
}

Here is a class with a method that sets up a ScheduledExecutorService to beep every ten seconds for an hour:

 import static java.util.concurrent.TimeUnit.*;
 class BeeperControl {
   private final ScheduledExecutorService scheduler =
     Executors.newScheduledThreadPool(1);

   public void beepForAnHour() {
     final Runnable beeper = new Runnable() {
       public void run() { System.out.println("beep"); }
     };
     final ScheduledFuture<?> beeperHandle =
       scheduler.scheduleAtFixedRate(beeper, 10, 10, SECONDS);
     scheduler.schedule(new Runnable() {
       public void run() { beeperHandle.cancel(true); }
     }, 60 * 60, SECONDS);
   }
 }

ReentrantLock使用

lock()加锁之后，紧接着一个try块对临界资源进行处理

class X {
   private final ReentrantLock lock = new ReentrantLock();
   // ...

   public void m() {
     lock.lock();  // block until condition holds
     try {
       // ... method body
     } finally {
       lock.unlock()
     }
   }
 }

ReentrantReadWriteLock使用

Here is a code sketch showing how to perform lock downgrading after updating a cache (exception handling is particularly tricky when handling multiple locks in a non-nested fashion):

 class CachedData {
   Object data;
   volatile boolean cacheValid;
   final ReentrantReadWriteLock rwl = new ReentrantReadWriteLock();

   void processCachedData() {
     rwl.readLock().lock();
     if (!cacheValid) {
       // Must release read lock before acquiring write lock
       rwl.readLock().unlock();
       rwl.writeLock().lock();
       try {
         // Recheck state because another thread might have
         // acquired write lock and changed state before we did.
         if (!cacheValid) {
           data = ...
           cacheValid = true;
         }
         // Downgrade by acquiring read lock before releasing write lock
         rwl.readLock().lock();
       } finally {
         rwl.writeLock().unlock(); // Unlock write, still hold read
       }
     }

     try {
       use(data);
     } finally {
       rwl.readLock().unlock();
     }
   }
 }

ReentrantReadWriteLocks can be used to improve concurrency in some uses of some kinds of Collections. This is typically worthwhile only when the collections are expected to be large, accessed by more reader threads than writer threads, and entail operations with overhead that outweighs synchronization overhead. For example, here is a class using a TreeMap that is expected to be large and concurrently accessed.

 class RWDictionary {
   private final Map m = new TreeMap();
   private final ReentrantReadWriteLock rwl = new ReentrantReadWriteLock();
   private final Lock r = rwl.readLock();
   private final Lock w = rwl.writeLock();

   public Data get(String key) {
     r.lock();
     try { return m.get(key); }
     finally { r.unlock(); }
   }
   public String[] allKeys() {
     r.lock();
     try { return m.keySet().toArray(); }
     finally { r.unlock(); }
   }
   public Data put(String key, Data value) {
     w.lock();
     try { return m.put(key, value); }
     finally { w.unlock(); }
   }
   public void clear() {
     w.lock();
     try { m.clear(); }
     finally { w.unlock(); }
   }
 }

BlockingQueue的使用

Usage example, based on a typical producer-consumer scenario. Note that a BlockingQueue can safely be used with multiple producers and multiple consumers.

class Producer implements Runnable {
   private final BlockingQueue queue;
   Producer(BlockingQueue q) { queue = q; }
   public void run() {
     try {
       while (true) { queue.put(produce()); }
     } catch (InterruptedException ex) { ... handle ...}
   }
   Object produce() { ... }
 }

 class Consumer implements Runnable {
   private final BlockingQueue queue;
   Consumer(BlockingQueue q) { queue = q; }
   public void run() {
     try {
       while (true) { consume(queue.take()); }
     } catch (InterruptedException ex) { ... handle ...}
   }
   void consume(Object x) { ... }
 }

 class Setup {
   void main() {
     BlockingQueue q = new SomeQueueImplementation();
     Producer p = new Producer(q);
     Consumer c1 = new Consumer(q);
     Consumer c2 = new Consumer(q);
     new Thread(p).start();
     new Thread(c1).start();
     new Thread(c2).start();
   }
 }

CountDownLatch使用

Sample usage: Here is a pair of classes in which a group of worker threads use two countdown latches: - The first is a start signal that prevents any worker from proceeding until the driver is ready for them to proceed; - The second is a completion signal that allows the driver to wait until all workers have completed.

class Driver { // ...
   void main() throws InterruptedException {
     CountDownLatch startSignal = new CountDownLatch(1);
     CountDownLatch doneSignal = new CountDownLatch(N);

     for (int i = 0; i < N; ++i) // create and start threads
       new Thread(new Worker(startSignal, doneSignal)).start();

     doSomethingElse();            // don't let run yet
     startSignal.countDown();      // let all threads proceed
     doSomethingElse();
     doneSignal.await();           // wait for all to finish
   }
 }

 class Worker implements Runnable {
   private final CountDownLatch startSignal;
   private final CountDownLatch doneSignal;
   Worker(CountDownLatch startSignal, CountDownLatch doneSignal) {
     this.startSignal = startSignal;
     this.doneSignal = doneSignal;
   }
   public void run() {
     try {
       startSignal.await();
       doWork();
       doneSignal.countDown();
     } catch (InterruptedException ex) {} // return;
   }

   void doWork() { ... }
 }

Another typical usage would be to divide a problem into N parts, describe each part with a Runnable that executes that portion and counts down on the latch, and queue all the Runnables to an Executor. When all sub-parts are complete, the coordinating thread will be able to pass through await. (When threads must repeatedly count down in this way, instead use a CyclicBarrier.)

 class Driver2 { // ...
   void main() throws InterruptedException {
     CountDownLatch doneSignal = new CountDownLatch(N);
     Executor e = ...

     for (int i = 0; i < N; ++i) // create and start threads
       e.execute(new WorkerRunnable(doneSignal, i));

     doneSignal.await();           // wait for all to finish
   }
 }

 class WorkerRunnable implements Runnable {
   private final CountDownLatch doneSignal;
   private final int i;
   WorkerRunnable(CountDownLatch doneSignal, int i) {
     this.doneSignal = doneSignal;
     this.i = i;
   }
   public void run() {
     try {
       doWork(i);
       doneSignal.countDown();
     } catch (InterruptedException ex) {} // return;
   }

   void doWork() { ... }
 }

CyclicBarrier的使用

Sample usage: Here is an example of using a barrier in a parallel decomposition design:

 class Solver {
   final int N;
   final float[][] data;
   final CyclicBarrier barrier;

   class Worker implements Runnable {
     int myRow;
     Worker(int row) { myRow = row; }
     public void run() {
       while (!done()) {
         processRow(myRow);

         try {
           barrier.await();
         } catch (InterruptedException ex) {
           return;
         } catch (BrokenBarrierException ex) {
           return;
         }
       }
     }
   }

   public Solver(float[][] matrix) {
     data = matrix;
     N = matrix.length;
     Runnable barrierAction =
       new Runnable() { public void run() { mergeRows(...); }};
     barrier = new CyclicBarrier(N, barrierAction);

     List<Thread> threads = new ArrayList<Thread>(N);
     for (int i = 0; i < N; i++) {
       Thread thread = new Thread(new Worker(i));
       threads.add(thread);
       thread.start();
     }

     // wait until done
     for (Thread thread : threads)
       thread.join();
   }
 }

This work is licensed under a CC A-S 4.0 International License.