The Fork/Join Framework is part of thejava.util.concurrentpackage, introduced in Java 7. It is designed for tasks that can be recursively divided into smaller chunks, where each chunk can be processed independently. The framework works on the principle of divide and conquer, making it ideal for tasks like sorting, searching, and other recursive algorithms.
ForkJoinTaskis the base class for tasks that can run within the Fork/Join Framework. It provides the core operations that allow tasks to fork new subtasks and join them once they are complete.
Example:
import java.util.concurrent.RecursiveTask; public class SumTask extends RecursiveTask{ private final int[] arr; private final int start, end; public SumTask(int[] arr, int start, int end) { this.arr = arr; this.start = start; this.end = end; } @Override protected Integer compute() { if (end - start <= 10) { int sum = 0; for (int i = start; i < end; i++) { sum += arr[i]; } return sum; } else { int mid = (start + end) / 2; SumTask leftTask = new SumTask(arr, start, mid); SumTask rightTask = new SumTask(arr, mid, end); leftTask.fork(); int rightResult = rightTask.compute(); int leftResult = leftTask.join(); return leftResult + rightResult; } } }
ForkJoinPoolis the central class that manages a pool of worker threads to executeForkJoinTaskinstances. It uses a work-stealing algorithm to keep all threads busy by redistributing tasks from busy threads to idle ones.
Example:
import java.util.concurrent.ForkJoinPool; public class ForkJoinExample { public static void main(String[] args) { int[] arr = new int[100]; for (int i = 0; i < arr.length; i++) { arr[i] = i + 1; } ForkJoinPool pool = new ForkJoinPool(); SumTask task = new SumTask(arr, 0, arr.length); int result = pool.invoke(task); System.out.println("Sum: " + result); } }
RecursiveTaskis used when your task returns a result, while RecursiveAction is used when it does not return any result.
Example usingRecursiveAction:
import java.util.concurrent.RecursiveAction; public class PrintTask extends RecursiveAction { private final int[] arr; private final int start, end; public PrintTask(int[] arr, int start, int end) { this.arr = arr; this.start = start; this.end = end; } @Override protected void compute() { if (end - start <= 10) { for (int i = start; i < end; i++) { System.out.print(arr[i] + " "); } System.out.println(); } else { int mid = (start + end) / 2; PrintTask leftTask = new PrintTask(arr, start, mid); PrintTask rightTask = new PrintTask(arr, mid, end); invokeAll(leftTask, rightTask); } } }
Running theForkJoinExamplewill output the sum of the array elements. The Fork/Join Framework divides the task into smaller chunks and processes them in parallel, showing significant performance improvements, especially with large datasets.
For instance, summing up the numbers from 1 to 100:
Sum: 5050
In the case of thePrintTask, the framework divides the array printing task, executing it in parallel and outputting the segments simultaneously:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 ...
The Fork/Join Framework is a powerful tool in Java for optimizing parallel processing tasks. It excels in scenarios where tasks can be broken down into smaller subtasks, executed independently, and then combined to produce the final result. While it introduces complexity, the performance benefits in multi-core environments often outweigh the downsides, making it an excellent choice for CPU-bound and large recursive problems.
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