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 (opens new window) is the interface that defines such a problem. It is generally expected that you will subclass one of its abstract implementations (usually the RecursiveTask (opens new window)) 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;
    }

    @Override
    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
            leftTask.fork();

            // 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 (opens new window).

// 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();