问题一：在下面的示例代码中，为什么要使用join()方法？它的作用是什么？
在下面的示例代码中，为什么要使用join()方法？它的作用是什么？
package learning.multithreading; import java.util.Random;import java.util.concurrent.ExecutionException;import java.util.concurrent.ForkJoinPool;import java.util.concurrent.RecursiveTask; public class ParallelSumComputationUsingForkJoin { private static final int[] LARGE_ARR = largeArr(); private static final int LENGTH = LARGE_ARR.length; public static void main(String[] args) throws ExecutionException, InterruptedException { RecursiveSumTask recursiveTask = new RecursiveSumTask(0, LENGTH, LARGE_ARR); ForkJoinPool forkJoinPool = ForkJoinPool.commonPool(); long start = System.currentTimeMillis(); long sum = forkJoinPool.invoke(recursiveTask); System.out.println("The sum is : " + sum + ", Time Taken by Parallel(Fork/Join) Execution: " + (System.currentTimeMillis() - start) + " millis"); } private static int[] largeArr() { return new Random().ints(500000000, 10, 1000).toArray(); } static class RecursiveSumTask extends RecursiveTask<Long> { private static final int SEQUENTIAL_COMPUTE_THRESHOLD = 4000; private final int startIndex; private final int endIndex; private final int[] data; RecursiveSumTask(int startIndex, int endIndex, int[] data) { this.startIndex = startIndex; this.endIndex = endIndex; this.data = data; } @Override protected Long compute() { if (SEQUENTIAL_COMPUTE_THRESHOLD >= (endIndex - startIndex)) { long sum = 0; for (int i = startIndex; i < endIndex; i++) { sum += data[i]; } return sum; } int mid = startIndex + (endIndex - startIndex) / 2; RecursiveSumTask leftSumTask = new RecursiveSumTask(startIndex, mid, data); RecursiveSumTask rightSumTask = new RecursiveSumTask(mid, endIndex, data); leftSumTask.fork(); // Fork the Left Task in a Separate Execution long rightSum = rightSumTask.compute(); // Compute the Right Part long leftSum = leftSumTask.join(); // Wait for the results from the Left Part return leftSum + rightSum; // Return Both } }}/** * Output: * The sum is : 252235235953, Time Taken by Parallel(Fork/Join) Execution: 139 millis *
参考回答：
join()方法被用于等待左侧子任务的完成，并获取其结果。join()是阻塞调用，调用线程会等待左侧子任务执行完成后才继续执行，从而确保在合并结果之前，所有的子任务都已经完成。
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https://developer.aliyun.com/ask/625186
问题二：在下面的示例代码中，SEQUENTIAL_COMPUTE_THRESHOLD变量起什么作用？
在下面的示例代码中，SEQUENTIAL_COMPUTE_THRESHOLD变量起什么作用？
package learning.multithreading; import java.util.Random;import java.util.concurrent.ExecutionException;import java.util.concurrent.ForkJoinPool;import java.util.concurrent.RecursiveTask; public class ParallelSumComputationUsingForkJoin { private static final int[] LARGE_ARR = largeArr(); private static final int LENGTH = LARGE_ARR.length; public static void main(String[] args) throws ExecutionException, InterruptedException { RecursiveSumTask recursiveTask = new RecursiveSumTask(0, LENGTH, LARGE_ARR); ForkJoinPool forkJoinPool = ForkJoinPool.commonPool(); long start = System.currentTimeMillis(); long sum = forkJoinPool.invoke(recursiveTask); System.out.println("The sum is : " + sum + ", Time Taken by Parallel(Fork/Join) Execution: " + (System.currentTimeMillis() - start) + " millis"); } private static int[] largeArr() { return new Random().ints(500000000, 10, 1000).toArray(); } static class RecursiveSumTask extends RecursiveTask<Long> { private static final int SEQUENTIAL_COMPUTE_THRESHOLD = 4000; private final int startIndex; private final int endIndex; private final int[] data; RecursiveSumTask(int startIndex, int endIndex, int[] data) { this.startIndex = startIndex; this.endIndex = endIndex; this.data = data; } @Override protected Long compute() { if (SEQUENTIAL_COMPUTE_THRESHOLD >= (endIndex - startIndex)) { long sum = 0; for (int i = startIndex; i < endIndex; i++) { sum += data[i]; } return sum; } int mid = startIndex + (endIndex - startIndex) / 2; RecursiveSumTask leftSumTask = new RecursiveSumTask(startIndex, mid, data); RecursiveSumTask rightSumTask = new RecursiveSumTask(mid, endIndex, data); leftSumTask.fork(); // Fork the Left Task in a Separate Execution long rightSum = rightSumTask.compute(); // Compute the Right Part long leftSum = leftSumTask.join(); // Wait for the results from the Left Part return leftSum + rightSum; // Return Both } }}/** * Output: * The sum is : 252235235953, Time Taken by Parallel(Fork/Join) Execution: 139 millis *
参考回答：
SEQUENTIAL_COMPUTE_THRESHOLD变量在示例代码中设定了一个阈值，当需要处理的数组元素数量小于这个阈值时，任务将不再进行进一步的拆分，而是直接顺序计算。这是为了避免过度拆分任务造成的额外开销，提高计算效率。
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问题三：ForkJoinTask可以通过哪些方法来提交任务？
ForkJoinTask可以通过哪些方法来提交任务？
参考回答：
可以使用execute()、invoke()和submit()方法来提交任务。
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问题四：ForkJoinPool中任务是如何排队的？
ForkJoinPool中任务是如何排队的？
参考回答：
ForkJoinPool维护一个全局共享队列，所有提交的任务都会在这个共享队列中排队。
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https://developer.aliyun.com/ask/625190
问题五：在ForkJoinPool模型中，工作线程如何从多个来源检查任务？
在ForkJoinPool模型中，工作线程如何从多个来源检查任务？
参考回答：
工作线程会检查来自全局共享队列、本地工作窃取队列以及其他线程的工作窃取队列的任务。
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