A recursive resultless ForkJoinTask. This class establishes conventions to parameterize resultless actions as Void ForkJoinTasks. Because null is the only valid value of type Void, methods such as join always return null upon completion.

Sample Usages. Here is a simple but complete ForkJoin sort that sorts a given long[] array:

 static class SortTask extends RecursiveAction {
  final long[] array; final int lo, hi;
  SortTask(long[] array, int lo, int hi) {
    this.array = array; this.lo = lo; this.hi = hi;
  }
  SortTask(long[] array) { this(array, 0, array.length); }
  protected void compute() {
    if (hi - lo < THRESHOLD)
      sortSequentially(lo, hi);
    else {
      int mid = (lo + hi) >>> 1;
      invokeAll(new SortTask(array, lo, mid),
                new SortTask(array, mid, hi));
      merge(lo, mid, hi);
    }
  }
  // implementation details follow:
  static final int THRESHOLD = 1000;
  void sortSequentially(int lo, int hi) {
    Arrays.sort(array, lo, hi);
  }
  void merge(int lo, int mid, int hi) {
    long[] buf = Arrays.copyOfRange(array, lo, mid);
    for (int i = 0, j = lo, k = mid; i < buf.length; j++)
      array[j] = (k == hi || buf[i] < array[k]) ?
        buf[i++] : array[k++];
  }
}

You could then sort anArray by creating new SortTask(anArray) and invoking it in a ForkJoinPool. As a more concrete simple example, the following task increments each element of an array:

 class IncrementTask extends RecursiveAction {
  final long[] array; final int lo, hi;
  IncrementTask(long[] array, int lo, int hi) {
    this.array = array; this.lo = lo; this.hi = hi;
  }
  protected void compute() {
    if (hi - lo < THRESHOLD) {
      for (int i = lo; i < hi; ++i)
        array[i]++;
    }
    else {
      int mid = (lo + hi) >>> 1;
      invokeAll(new IncrementTask(array, lo, mid),
                new IncrementTask(array, mid, hi));
    }
  }
}

The following example illustrates some refinements and idioms that may lead to better performance: RecursiveActions need not be fully recursive, so long as they maintain the basic divide-and-conquer approach. Here is a class that sums the squares of each element of a double array, by subdividing out only the right-hand-sides of repeated divisions by two, and keeping track of them with a chain of next references. It uses a dynamic threshold based on method getSurplusQueuedTaskCount, but counterbalances potential excess partitioning by directly performing leaf actions on unstolen tasks rather than further subdividing.

 double sumOfSquares(ForkJoinPool pool, double[] array) {
  int n = array.length;
  Applyer a = new Applyer(array, 0, n, null);
  pool.invoke(a);
  return a.result;
}

class Applyer extends RecursiveAction {
  final double[] array;
  final int lo, hi;
  double result;
  Applyer next; // keeps track of right-hand-side tasks
  Applyer(double[] array, int lo, int hi, Applyer next) {
    this.array = array; this.lo = lo; this.hi = hi;
    this.next = next;
  }

  double atLeaf(int l, int h) {
    double sum = 0;
    for (int i = l; i < h; ++i) // perform leftmost base step
      sum += array[i] * array[i];
    return sum;
  }

  protected void compute() {
    int l = lo;
    int h = hi;
    Applyer right = null;
    while (h - l > 1 && getSurplusQueuedTaskCount() <= 3) {
      int mid = (l + h) >>> 1;
      right = new Applyer(array, mid, h, right);
      right.fork();
      h = mid;
    }
    double sum = atLeaf(l, h);
    while (right != null) {
      if (right.tryUnfork()) // directly calculate if not stolen
        sum += right.atLeaf(right.lo, right.hi);
      else {
        right.join();
        sum += right.result;
      }
      right = right.next;
    }
    result = sum;
  }
}