Java Language Parallel programming with Fork/Join framework

Fork/Join Tasks in Java

The fork/join framework in Java is ideal for a problem that can be divided into smaller pieces and solved in parallel. The fundamental steps of a fork/join problem are:

  • Divide the problem into multiple pieces
  • Solve each of the pieces in parallel to each other
  • Combine each of the sub-solutions into one overall solution

A ForkJoinTask is the interface that defines such a problem. It is generally expected that you will subclass one of its abstract implementations (usually the RecursiveTask) rather than implement the interface directly.

In this example, we are going to sum a collection of integers, dividing until we get to batch sizes of no more than ten.

import java.util.List;
import java.util.concurrent.RecursiveTask;

public class SummingTask extends RecursiveTask<Integer> {
    private static final int MAX_BATCH_SIZE = 10;

    private final List<Integer> numbers;
    private final int minInclusive, maxExclusive;

    public SummingTask(List<Integer> numbers) {
        this(numbers, 0, numbers.size());

    // This constructor is only used internally as part of the dividing process
    private SummingTask(List<Integer> numbers, int minInclusive, int maxExclusive) {
        this.numbers = numbers;
        this.minInclusive = minInclusive;
        this.maxExclusive = maxExclusive;

    public Integer compute() {
        if (maxExclusive - minInclusive > MAX_BATCH_SIZE) {
            // This is too big for a single batch, so we shall divide into two tasks
            int mid = (minInclusive + maxExclusive) / 2;
            SummingTask leftTask = new SummingTask(numbers, minInclusive, mid);
            SummingTask rightTask = new SummingTask(numbers, mid, maxExclusive);

            // Submit the left hand task as a new task to the same ForkJoinPool

            // Run the right hand task on the same thread and get the result
            int rightResult = rightTask.compute();

            // Wait for the left hand task to complete and get its result
            int leftResult = leftTask.join();

            // And combine the result
            return leftResult + rightResult;
        } else {
            // This is fine for a single batch, so we will run it here and now
            int sum = 0;
            for (int i = minInclusive; i < maxExclusive; i++) {
                sum += numbers.get(i);
            return sum;

An instance of this task can now be passed to an instance of ForkJoinPool.

// Because I am not specifying the number of threads
// it will create a thread for each available processor
ForkJoinPool pool = new ForkJoinPool();

// Submit the task to the pool, and get what is effectively the Future
ForkJoinTask<Integer> task = pool.submit(new SummingTask(numbers));

// Wait for the result
int result = task.join();