How I Can Understand the Basics of ExecutorService and the Fork/Join Framework
Tags: webdev, java, executorservice, performance
Published: 2023-10-12 04:44:37

Java is a popular programming language that offers robust support for concurrency, making it an excellent choice for developing multi-threaded applications. Two key components in Java that simplify the process of managing and executing tasks concurrently are the ExecutorService and Fork/Join Framework. In this article, we’ll explore these frameworks and explain them in a simple and beginner-friendly manner.

## ExecutorService
ExecutorService is like the manager of a group of workers (threads) that helps you execute tasks concurrently in a controlled manner. It abstracts away much of the complexity involved in managing threads. Let’s dive into a simple example to illustrate its usage.

```Java
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;

public class ExecutorServiceExample {
    public static void main(String[] args) {
        // Create an ExecutorService with a fixed pool of 4 threads
        ExecutorService executorService = Executors.newFixedThreadPool(4);

        // Submit tasks for execution
        for (int i = 0; i < 10; i++) {
            final int taskNumber = i;
            executorService.execute(() -> {
                System.out.println("Task " + taskNumber + " is running on thread " + Thread.currentThread().getName());
            });
        }

        // Shutdown the ExecutorService when done
        executorService.shutdown();
    }
}
```

### In this example, we:
1 .Create an `ExecutorService` with a fixed pool of 4 threads using `Executors.newFixedThreadPool(4)`.
2. Submit 10 tasks for execution using the execute method.
3. The `ExecutorService` manages the allocation and reuse of threads for these tasks.
4. We shut down the `ExecutorService` once we're done with it.

## Fork/Join Framework

![Fork/Join Framework](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/018ari8odbb1b18hops1.png)

The Fork/Join Framework is a more specialized tool designed for parallel processing. It is ideal for situations where you need to divide a large task into smaller sub-tasks and then combine their results. Let’s understand it with a classic example — calculating the sum of elements in an array.

```Java
import java.util.concurrent.RecursiveTask;
import java.util.concurrent.ForkJoinPool;

public class ForkJoinExample {
    public static void main(String[] args) {
        int[] data = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10};
        ForkJoinPool pool = new ForkJoinPool();

        int result = pool.invoke(new SumTask(data, 0, data.length));
        System.out.println("Sum: " + result);
    }
}

class SumTask extends RecursiveTask<Integer> {
    private int[] data;
    private int start;
    private int end;

    public SumTask(int[] data, int start, int end) {
        this.data = data;
        this.start = start;
        this.end = end;
    }

    @Override
    protected Integer compute() {
        if (end - start <= 3) { // Small enough, do the task directly
            int sum = 0;
            for (int i = start; i < end; i++) {
                sum += data[i];
            }
            return sum;
        } else {
            int mid = start + (end - start) / 2;
            SumTask leftTask = new SumTask(data, start, mid);
            SumTask rightTask = new SumTask(data, mid, end);
            leftTask.fork(); // Fork new tasks
            int rightResult = rightTask.compute(); // Compute one part
            int leftResult = leftTask.join(); // Wait for the other part
            return leftResult + rightResult;
        }
    }
}
```
### In this example, we:
1. Initialize an array of data.
2 Create a `ForkJoinPool`, which is the heart of the Fork/Join Framework.
3. Define a `SumTask` class that extends `RecursiveTask<Integer>`. This is where we specify the task to be performed.
4. The `SumTask` class breaks down the task of summing the array into smaller sub-tasks and combines the results. The framework handles task distribution and result aggregation for us.

## How the Fork/Join Framework Works
The Fork/Join Framework employs a divide-and-conquer strategy to parallelize tasks. Here’s a step-by-step breakdown of how it works:
1. The main task, in this case, the `SumTask`, is given a large problem to solve. It checks if the problem size is small enough to be solved directly (in this case, when the difference between `start` and `end` is less than or equal to 3).
2. If the problem size is small, it computes the result directly. In this example, it sums the elements in the array between `start` and `end`.
3. If the problem is too large, the main task splits it into two sub-tasks, `leftTask` and `rightTask`, to solve smaller parts of the problem.
4. The `leftTask` is then forked, which means it's submitted for parallel execution. This allows the framework to allocate separate threads for each sub-task.
5. While the `rightTask` is computed directly, the `leftTask` is allowed to execute in parallel.
6. Once both sub-tasks are complete, the `leftTask` and rightTask results are joined together, effectively combining the sub-task results to obtain the final result.

This divide-and-conquer approach continues recursively until all sub-tasks are small enough to be computed directly, and their results are combined to produce the overall result.

## Conclusion
Concurrency in Java is made simpler and more efficient with the ExecutorService and Fork/Join Framework. The ExecutorService manages threads, making it easier to execute tasks concurrently, while the Fork/Join Framework is designed for parallel processing, allowing you to divide and conquer complex tasks.

These tools are valuable additions to a Java developer’s toolbox, enabling the efficient use of multiple cores and improving application performance. By mastering these frameworks, you can build high-performance, multi-threaded Java applications with ease.

Whether you’re working on a multi-threaded server application, a data processing pipeline, or any other project that requires concurrency, understanding these concepts will undoubtedly help you make the most of Java’s powerful capabilities.

Happy coding and happy concurrent programming! 🚀👨‍💻👩‍💻