Guide to the Fork/Join Framework in Java – Java中的Fork/Join框架指南

最后修改: 2016年 4月 25日


1. Overview


Java 7 introduced the fork/join framework. It provides tools to help speed up parallel processing by attempting to use all available processor cores. It accomplishes this through a divide and conquer approach.

Java 7引入了fork/join框架。它提供了一些工具,通过尝试使用所有可用的处理器内核来帮助加速并行处理。它通过分而治之的方法实现了这一目标

In practice, this means that the framework first “forks,” recursively breaking the task into smaller independent subtasks until they are simple enough to run asynchronously.

在实践中,这意味着框架首先 “分叉”,递归地将任务分解为更小的独立子任务,直到它们简单到可以异步运行。

After that, the “join” part begins. The results of all subtasks are recursively joined into a single result. In the case of a task that returns void, the program simply waits until every subtask runs.

之后,“连接 “部分开始。所有子任务的结果被递归地连接成一个单一的结果。如果一个任务的返回结果是空的,程序只需等待,直到每个子任务都运行。

To provide effective parallel execution, the fork/join framework uses a pool of threads called the ForkJoinPool. This pool manages worker threads of type ForkJoinWorkerThread.


2. ForkJoinPool

2. ForkJoinPool

The ForkJoinPool is the heart of the framework. It is an implementation of the ExecutorService that manages worker threads and provides us with tools to get information about the thread pool state and performance.


Worker threads can execute only one task at a time, but the ForkJoinPool doesn’t create a separate thread for every single subtask. Instead, each thread in the pool has its own double-ended queue (or deque, pronounced “deck”) that stores tasks.

工作线程一次只能执行一个任务,但ForkJoinPool并不为每一个子任务创建单独的线程。相反,池中的每个线程都有自己的双端队列(或deque,发音为 “甲板”),用于存储任务。

This architecture is vital for balancing the thread’s workload with the help of the work-stealing algorithm.


2.1. Work-Stealing Algorithm


Simply put, free threads try to “steal” work from deques of busy threads.

简单地说,空闲线程试图从繁忙线程的脱机中 “偷走 “工作。

By default, a worker thread gets tasks from the head of its own deque. When it is empty, the thread takes a task from the tail of the deque of another busy thread or from the global entry queue since this is where the biggest pieces of work are likely to be located.


This approach minimizes the possibility that threads will compete for tasks. It also reduces the number of times the thread will have to go looking for work, as it works on the biggest available chunks of work first.


2.2. ForkJoinPool Instantiation


In Java 8, the most convenient way to get access to the instance of the ForkJoinPool is to use its static method commonPool(). This will provide a reference to the common pool, which is a default thread pool for every ForkJoinTask.

在 Java 8 中,获取 ForkJoinPool 实例的最便捷方式是使用其静态方法 commonPool ()。这将提供一个对公共池的引用,它是每个ForkJoinTask的默认线程池。

According to Oracle’s documentation, using the predefined common pool reduces resource consumption since this discourages the creation of a separate thread pool per task.


ForkJoinPool commonPool = ForkJoinPool.commonPool();

We can achieve the same behavior in Java 7 by creating a ForkJoinPool and assigning it to a public static field of a utility class:

在Java 7中,我们可以通过创建一个ForkJoinPool并将其分配给一个实用类的public static字段来实现同样的行为。

public static ForkJoinPool forkJoinPool = new ForkJoinPool(2);

Now we can easily access it:


ForkJoinPool forkJoinPool = PoolUtil.forkJoinPool;

With ForkJoinPool’s constructors, we can create a custom thread pool with a specific level of parallelism, thread factory and exception handler. Here the pool has a parallelism level of 2. This means that pool will use two processor cores.


3. ForkJoinTask<V>

3. ForkJoinTask<V>

ForkJoinTask is the base type for tasks executed inside ForkJoinPool. In practice, one of its two subclasses should be extended: the RecursiveAction for void tasks and the RecursiveTask<V> for tasks that return a value. They both have an abstract method compute() in which the task’s logic is defined.

ForkJoinTask是在ForkJoinPool中执行的任务的基础类型。在实践中,它的两个子类之一应该被扩展:RecursiveAction用于void任务,RecursiveTask<V>用于返回值的任务。它们都有一个抽象的方法compute() ,任务的逻辑在其中被定义。

3.1. RecursiveAction

3.1. RecursiveAction

In the example below, we use a String called workload to represent the unit of work to be processed. For demonstration purposes, the task is a nonsensical one: It simply uppercases its input and logs it.


To demonstrate the forking behavior of the framework, the example splits the task if workload.length() is larger than a specified threshold using the createSubtask() method.


The String is recursively divided into substrings, creating CustomRecursiveTask instances that are based on these substrings.


As a result, the method returns a List<CustomRecursiveAction>.


The list is submitted to the ForkJoinPool using the invokeAll() method:


public class CustomRecursiveAction extends RecursiveAction {

    private String workload = "";
    private static final int THRESHOLD = 4;

    private static Logger logger = 

    public CustomRecursiveAction(String workload) {
        this.workload = workload;

    protected void compute() {
        if (workload.length() > THRESHOLD) {
        } else {

    private List<CustomRecursiveAction> createSubtasks() {
        List<CustomRecursiveAction> subtasks = new ArrayList<>();

        String partOne = workload.substring(0, workload.length() / 2);
        String partTwo = workload.substring(workload.length() / 2, workload.length());

        subtasks.add(new CustomRecursiveAction(partOne));
        subtasks.add(new CustomRecursiveAction(partTwo));

        return subtasks;

    private void processing(String work) {
        String result = work.toUpperCase();"This result - (" + result + ") - was processed by " 
          + Thread.currentThread().getName());

We can use this pattern to develop our own RecursiveAction classes. To do this, we create an object that represents the total amount of work, chose a suitable threshold, define a method to divide the work and define a method to do the work.


3.2. RecursiveTask<V>

3.2. RecursiveTask<V>

For tasks that return a value, the logic here is similar.


The difference is that the result for each subtask is united in a single result:


public class CustomRecursiveTask extends RecursiveTask<Integer> {
    private int[] arr;

    private static final int THRESHOLD = 20;

    public CustomRecursiveTask(int[] arr) {
        this.arr = arr;

    protected Integer compute() {
        if (arr.length > THRESHOLD) {
            return ForkJoinTask.invokeAll(createSubtasks())
        } else {
            return processing(arr);

    private Collection<CustomRecursiveTask> createSubtasks() {
        List<CustomRecursiveTask> dividedTasks = new ArrayList<>();
        dividedTasks.add(new CustomRecursiveTask(
          Arrays.copyOfRange(arr, 0, arr.length / 2)));
        dividedTasks.add(new CustomRecursiveTask(
          Arrays.copyOfRange(arr, arr.length / 2, arr.length)));
        return dividedTasks;

    private Integer processing(int[] arr) {
          .filter(a -> a > 10 && a < 27)
          .map(a -> a * 10)

In this example, we use an array stored in the arr field of the CustomRecursiveTask class to represent the work. The createSubtasks() method recursively divides the task into smaller pieces of work until each piece is smaller than the threshold. Then the invokeAll() method submits the subtasks to the common pool and returns a list of Future.


To trigger execution, the join() method is called for each subtask.


We’ve accomplished this here using Java 8’s Stream API. We use the sum() method as a representation of combining sub results into the final result.

我们在这里使用Java 8的Stream API完成了这个任务。我们使用sum()方法来表示将子结果合并为最终结果。

4. Submitting Tasks to the ForkJoinPool


We can use a few approaches to submit tasks to the thread pool.


Let’s start with the submit() or execute() method (their use cases are the same):

让我们从submit() execute()方法开始(它们的使用情况是一样的)。

int result = customRecursiveTask.join();

The invoke() method forks the task and waits for the result, and doesn’t need any manual joining:


int result = forkJoinPool.invoke(customRecursiveTask);

The invokeAll() method is the most convenient way to submit a sequence of ForkJoinTasks to the ForkJoinPool. It takes tasks as parameters (two tasks, var args or a collection), forks and then returns a collection of Future objects in the order in which they were produced.

invokeAll()方法是向ForkJoinPool提交ForkJoinTasks序列的最方便方式。它将任务作为参数(两个任务、var args或一个集合),进行分叉,然后按照产生的顺序返回一个Future对象的集合。

Alternatively, we can use separate fork() and join() methods. The fork() method submits a task to a pool, but it doesn’t trigger its execution. We must use the join() method for this purpose.


In the case of RecursiveAction, the join() returns nothing but null; for RecursiveTask<V>, it returns the result of the task’s execution:


result = customRecursiveTaskLast.join();

Here we used the invokeAll() method to submit a sequence of subtasks to the pool. We can do the same job with fork() and join(), though this has consequences for the ordering of the results.


To avoid confusion, it is generally a good idea to use invokeAll() method to submit more than one task to the ForkJoinPool.


5. Conclusion


Using the fork/join framework can speed up processing of large tasks, but to achieve this outcome, we should follow some guidelines:


  • Use as few thread pools as possible. In most cases, the best decision is to use one thread pool per application or system.
  • Use the default common thread pool if no specific tuning is needed.
  • Use a reasonable threshold for splitting ForkJoinTask into subtasks.
  • Avoid any blocking in ForkJoinTasks.

The examples used in this article are available in the linked GitHub repository.