在一个约定点同步任务(Synchronizing tasks in a common point)
Java 并发API中提供了一个同步工具CyclicBarrier类可以使多个线程在约定点进行任务同步,该类和CountDownLatch类有点类似,CountDownLatch是等待多个并发事件,在上节有解释;
CyclicBarrier类初始化有两个参数,第一个是要同步的线程个数,第二个要同步的任务(该参数实现了Runnable接口);当这些要同步的线程到达到了这个约定的同步点,它将调用await()方法进入睡眠状态,当所有要同步的线程都到达了这个约定的点后,CyclicBarrier将会唤醒所有睡眠的这些线程,然后执行要同步的任务(传入的第二个参数);
CyclicBarrier最好的就是它可以传入一个实现了Runnable接口的对象,在所有线程到达约定点后,在执行这个对象;这个特性非常适合分治算法 的思想;
再接下来的例子中,简单的使用CyclicBarrier模拟一个简单的分治算法;
问题:即模拟一个矩阵,从该矩阵中查找一个给定的数,并统计该数值在该矩阵中出现的次数;
解决思路:
开启多个线程,每个线程负责查找若干行,并把每一行该数值出现的次数放置到一个数组中,作为结果,每行对应与该数组的索引;在所有线程都查找完成后,执行同步任务,这里仅仅简单的输出最终的结果;
动手实现
1.辅助类,用来模拟矩阵
public class MatrixMock {
private int data[][];
public MatrixMock(int rows,int cols,int number){
int counter=0;
data=new int[rows][cols];
Random random=new Random();
for (int i = 0; i < rows; i++) {
for(int j=0;j<cols;j++){
data[i][j]=random.nextInt(10);
if (data[i][j] == number) {
counter++;
}
}
}
System.out.printf("Mock: There are %d occurrence of %d in generated data.\n",counter,number);
}
public int[] getRow(int row) {
if ((row >= 0) && (row < data.length)) {
return data[row];
}
return null;
}
}
2.辅助类,用来放置每个线程处理结果,索引对应矩阵行数,列对应每行查找到指定数值的次数
public class Result {
private int data[];
public Result(int size) {
this.data = new int[size];
}
public void setData(int position,int value){
data[position]=value;
}
public int[] getData(){
return data;
}
}
3.用来执行计算的线程
public class Searcher implements Runnable {
private int firstRow;
private int lastRow;
private MatrixMock mock;
private Result result;
private int number;
private final CyclicBarrier barrier;
public Searcher(int firstRow, int lastRow, MatrixMock mock, Result result,
int number, CyclicBarrier barrier) {
this.firstRow = firstRow;
this.lastRow = lastRow;
this.mock = mock;
this.result = result;
this.number = number;
this.barrier = barrier;
}
@Override
public void run() {
int counter;
System.out.printf("%s: Processing lines from %d to %d.\n",
Thread.currentThread().getName(), firstRow, lastRow);
for (int i = firstRow; i < lastRow; i++) {
int row[] = mock.getRow(i);
counter = 0;
for (int j = 0; j < row.length; j++) {
if (row[j] == number) {
counter++;
}
}
result.setData(i, counter);
}
System.out.printf("%s: Lines processed.\n", Thread.currentThread().getName());
try {
barrier.await();
} catch (BrokenBarrierException | InterruptedException e) {
e.printStackTrace();
}
}
}
4.同步任务,当所有线程完成之后执行,类似于分治算法中的
结果合并;
public class Grouper implements Runnable {
private Result result;
public Grouper(Result result) {
this.result = result;
}
@Override
public void run() {
int finalResult=0;
System.out.printf("Grouper: Processing results...\n");
int data[]=result.getData();
for(int number:data){
finalResult+=number;
}
System.out.printf("Grouper: Total result: %d.\n",finalResult);
}
}
5.Main
public class Main {
public static void main(String[] args) {
final int rows=10000;
final int cols=1000;
final int search=5;
final int participants=5;
final int linesParticipant=2000;
MatrixMock mock=new MatrixMock(rows, cols,search);
Result result=new Result(rows);
Grouper grouper=new Grouper(result);
CyclicBarrier barrier=new CyclicBarrier(participants,grouper);
Searcher searchers[]=new Searcher[participants];
for (int i=0; i<participants; i++){
// Every searching thread searches 2000 rows
searchers[i]=new Searcher(i*linesParticipant,
(i*linesParticipant) + linesParticipant, mock, result, 5,barrier);
Thread thread=new Thread(searchers[i]);
thread.start();
}
System.out.printf("Main: The main thread has finished.\n");
}
}
一次运行结果:
Mock: There are 1001252 occurrence of 5 in generated data.
Main: The main thread has finished.
Thread-0: Processing lines from 0 to 2000.
Thread-4: Processing lines from 8000 to 10000.
Thread-1: Processing lines from 2000 to 4000.
Thread-3: Processing lines from 6000 to 8000.
Thread-2: Processing lines from 4000 to 6000.
Thread-1: Lines processed.
Thread-3: Lines processed.
Thread-2: Lines processed.
Thread-0: Lines processed.
Thread-4: Lines processed.
Grouper: Processing results...
Grouper: Total result: 1001252.
要点
1.CyclicBarrier还提供了getNumberWaiting()方法,用来获取当前被阻塞的线程个数;
2.利用该类执行分治任务是一个很不错的选择;