以下是使用ForkJoinPool实现并行递归计算的完整解决方案，包含任务拆分、结果合并和性能优化：
import java.util.concurrent.*;
public class ParallelRecursiveCalculator extends RecursiveTask
private static final int THRESHOLD = 1000;
private final int[] array;
private final int start;
private final int end;
public ParallelRecursiveCalculator(int[] array, int start, int end) {
this.array = array;
this.start = start;
this.end = end;
}
@Override
protected Long compute() {
if (end - start <= THRESHOLD) {
return sequentialCompute();
}
int mid = (start + end) >>> 1;
ParallelRecursiveCalculator left = new ParallelRecursiveCalculator(array, start, mid);
ParallelRecursiveCalculator right = new ParallelRecursiveCalculator(array, mid, end);
left.fork();
Long rightResult = right.compute();
Long leftResult = left.join();
return leftResult + rightResult;
}
private Long sequentialCompute() {
long sum = 0;
for (int i = start; i < end; i++) {
sum += array[i];
}
return sum;
}
public static void main(String[] args) {
int[] data = new int[10_000_000];
Arrays.fill(data, 1);
ForkJoinPool pool = new ForkJoinPool();
long result = pool.invoke(new ParallelRecursiveCalculator(data, 0, data.length));
System.out.println("Result: " + result);
}
}
java.util.concurrent.*;
public class FibonacciTask extends RecursiveTask
private final int n;
public FibonacciTask(int n) {
this.n = n;
}
@Override
protected Long compute() {
if (n <= 10) {
return sequentialFibonacci(n);
}
FibonacciTask f1 = new FibonacciTask(n - 1);
FibonacciTask f2 = new FibonacciTask(n - 2);
f1.fork();
return f2.compute() + f1.join();
}
private long sequentialFibonacci(int n) {
if (n <= 1) return n;
return sequentialFibonacci(n - 1) + sequentialFibonacci(n - 2);
}
public static void main(String[] args) {
ForkJoinPool pool = new ForkJoinPool();
long result = pool.invoke(new FibonacciTask(30));
System.out.println("Fibonacci(30) = " + result);
}
}
代码说明：第一个示例展示数组求和的分治并行计算，第二个示例实现斐波那契数列的并行递归。两者都通过ForkJoinTask拆分任务，自动利用多核处理器资源。