ForkJoin并行执行任务!提高效率!大数据量! 任务的分割与合并主流程  ForkJoin特点:工作窃取 这里面维护的都是双端队列  测试代码:
public class ForkJoinDemo extends RecursiveTask<Long> {
private Long start;
private Long end;
private long temp=10000;
public ForkJoinDemo(Long start, Long end) {
this.start = start;
this.end = end;
}
@Override
protected Long compute() {
if ((end-start)<temp){
Long sum=0L;
for (Long i = start; i <= end; i++) {
sum+=i;
}
return sum;
}else{
long middle = (start + end) / 2;
ForkJoinDemo task1 = new ForkJoinDemo(start, middle);
task1.fork();
ForkJoinDemo task2 = new ForkJoinDemo(middle+1, end);
task2.fork();
return task1.join() + task2.join();
}
}
}
public class Test {
public static void main(String[] args) throws ExecutionException, InterruptedException {
}
public static void test1() {
Long sum=0L;
long start = System.currentTimeMillis();
for (int i = 1; i <= 10_0000_0000; i++) {
sum+=i;
}
long end = System.currentTimeMillis();
System.out.println("sum="+ sum + "时间:" + (end - start));
}
public static void test2() throws ExecutionException, InterruptedException {
long start = System.currentTimeMillis();
ForkJoinPool forkJoinPool=new ForkJoinPool();
ForkJoinTask<Long> task = new ForkJoinDemo(0L, 10_0000_0000L);
ForkJoinTask<Long> submit = forkJoinPool.submit(task);
Long sum = submit.get();
long end = System.currentTimeMillis();
System.out.println("sum=" + sum + "时间:" + (end - start));
}
public static void test3() {
long start = System.currentTimeMillis();
Long sum=LongStream.rangeClosed(0,10_0000_0000).parallel().reduce(0,Long::sum);
long end = System.currentTimeMillis();
System.out.println("sum=" + sum + "时间:" + (end - start));
}
}
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