Fork/Join framework in the Java class library: parallel task processing and work stealing
Fork/Join framework in the Java class library: parallel task processing and work stealing
introduction:
When dealing with large -scale parallel tasks, in order to make full use of computing resources and improve computing efficiency, the Java class library introduced the Fork/Join framework.This framework decompose tasks into smaller sub -tasks in a recursive way, and uses multi -threaded parallel to perform these sub -tasks.At the same time, it also introduced a work stealing mechanism, so that the free threads can obtain tasks from the task queue of other threads, and improve the load balance of the system.In this article, we will introduce the characteristics of the FORK/JOIN framework in the Java class library and its usage methods, and provide some Java code examples.
1. Force/Join framework overview:
The FORK/JOIN framework is a framework provided by the Java library to handle large -scale parallel tasks.It is based on the work-there to decompose the task into a smaller sub-task and distribute it to multiple threads to achieve the parallel execution of the task.
2. Core concept:
1. Specifications: The task in the FORK/JOIN framework adopts the division of treatment, that is, a large task is divided into multiple small tasks, and then these small tasks are dealt with recursively.Each sub -task can continue to be divided into smaller sub -tasks until it reaches a certain calculation scale.
2. Fork/Join pool: The fork/Join framework manages the thread pool and task queue through the ForkjoinPool class.Each thread in the thread pool will perform one or more sub -tasks, and obtain the task from the task queue of other threads through the work stealing algorithm.
3. Work stealing algorithm: The threads in the FORK/JOIN framework implement the load balancing through the work stealing algorithm.When the task of a thread is queue, it can get a task execution from the task queue of other threads.This can avoid thread idle and improve the utilization rate of the system.
Third, use the Fork/Join framework:
Using the FORK/JOIN framework can be divided into the following steps:
1. Define a task class that inherits from java.util.concurrent.RCURSIVETASK or java.util.concurrent.RecursiveAction, which are used in tasks with return values and no return values, respectively.
2. Implement the compute method in the task category, which is used to define the execution logic of the task.In this method, you can use the Invokeall method to submit the sub -task and obtain the results of the sub -mission through the Join method.
3. Create the forkjoinpool instance to schedule and perform tasks through it.
4. Use the invoke method of FORKJOINPOOL to submit the task and obtain the execution results of the task through it.
Below is a simple example that demonstrates how to use the FORK/JOIN framework to calculate the value of the Fibonaccis number:
import java.util.concurrent.RecursiveTask;
import java.util.concurrent.ForkJoinPool;
public class FibonacciTask extends RecursiveTask<Integer> {
private int n;
public FibonacciTask(int n) {
this.n = n;
}
@Override
protected Integer compute() {
if (n <= 1) {
return n;
} else {
FibonacciTask fib1 = new FibonacciTask(n - 1);
fib1.fork();
FibonacciTask fib2 = new FibonacciTask(n - 2);
return fib2.compute() + fib1.join();
}
}
public static void main(String[] args) {
ForkJoinPool pool = new ForkJoinPool();
FibonacciTask fibonacciTask = new FibonacciTask(10);
int result = pool.invoke(fibonacciTask);
System.out.println("Result: " + result);
pool.shutdown();
}
}
In the above example, we define a Fibonaccitask task that inherits from the recursivetask class.In the Compute method, we use recursive calls and fork/Join operations to calculate the value of the Fibonaccis.In the main function, we created a FORKJOINPOOL object and performed the task through the Invoke method, and obtained the calculation results.
Fourth, summary:
In the Java class library, the FORK/JOIN framework provides a mechanism for high -efficiency large -scale parallel tasks.Through the decomposition and parallel execution of tasks, and the application of work stealing algorithms, it can make full use of computing resources to improve computing efficiency.We can define our tasks by inheriting the recursiveTask or the RecursiveAction class, and schedule and execute the task through FORKJOINPOOL.
