Java backend development: API parallel processing using Java ForkJoinPool

With the advent of the Internet era and the improvement of technical levels such as big data processing and high concurrency processing, Java back-end developers often need to face the need to process large amounts of data. At this time, we must consider how to use Java multi-threading technology to improve the concurrent processing capabilities of the program.

Java ForkJoinPool is a new juc (Java Util Concurrent) package in Java 7, which allows us to use Java multi-threading technology more conveniently. This article will introduce the concept and usage of Java ForkJoinPool, and how to use Java ForkJoinPool for parallel processing of API interfaces.

What is Java ForkJoinPool?

Java ForkJoinPool is a newly added thread pool in Java 7. It extends the Java Executor framework and is specially used to handle decomposable tasks. Its most important feature is that it supports parallel execution of tasks. In the era of Java multi-core CPUs, its advantages are obvious.

In Java parallel execution, the core is the splitting and merging of tasks. ForkJoinTask is the best example of this splitting and merging. It splits a large computing task into multiple small tasks, each of which can be executed independently. After execution, the results of the small tasks will be unified into one large result.

The basic principle of Java ForkJoinPool is similar to MapReduce, dividing a large task into several subtasks, and there is a collaborative relationship between the subtasks. In this way, Java ForkJoinPool can easily utilize the parallel capabilities of multi-core CPUs to achieve efficient big data processing.

Using Java ForkJoinPool for parallel processing of API interfaces

Parallel processing of API interfaces is a very practical problem. Usually, we need to call multiple API interfaces to obtain the required data. If the calling time of the API interface is relatively long, it will take a relatively long time and affect the performance of the program. At this time, we can use Java ForkJoinPool to perform parallel processing of API interfaces.

The following is a sample code for using Java ForkJoinPool for parallel processing of the API interface:

public class ApiParallelTask extends RecursiveTask { private List apiList; public ApiParallelTask(List apiList) { this.apiList = apiList; } @Override protected Integer compute() { if (apiList.size() == 1) { //执行具体的API调用 System.out.println("API Call:" + apiList.get(0)); return 1; } else { int middle = apiList.size() / 2; List leftList = apiList.subList(0, middle); List rightList = apiList.subList(middle, apiList.size()); ApiParallelTask leftTask = new ApiParallelTask(leftList); ApiParallelTask rightTask = new ApiParallelTask(rightList); leftTask.fork(); rightTask.fork(); int leftResult = leftTask.join(); int rightResult = rightTask.join(); return leftResult + rightResult; } } }

In this example, we implement the splitting and merging of tasks by inheriting RecursiveTask. Next, we create an ApiParallelTask that contains the list of APIs to be processed. If the API list has only one element, then we directly execute the API call and return the result. If the API list has multiple elements, we split the list into two parts and create two subtasks - leftTask and rightTask, to process the left and right lists respectively. After the left and right subtasks have been executed, we merge their results and return them to the parent task. This completes the parallel processing of the API interface.

The following is a sample code that uses Java ForkJoinPool to perform parallel processing of API interfaces:

public static void main(String[] args) { List apiList = new ArrayList<>(); apiList.add("API 1"); apiList.add("API 2"); apiList.add("API 3"); apiList.add("API 4"); apiList.add("API 5"); apiList.add("API 6"); ApiParallelTask apiParallelTask = new ApiParallelTask(apiList); ForkJoinPool forkJoinPool = new ForkJoinPool(); int result = forkJoinPool.invoke(apiParallelTask); System.out.println("Result:" + result); }

In this example, we first define the API list to be processed, and then create an ApiParallelTask task as root task. Next, we created a ForkJoinPool thread pool and started the root task through the invoke method. Finally, we show the processing results.

Summary

Java ForkJoinPool is a very practical concurrent processing tool in Java multi-threading technology. It can easily implement complex task division and allocation and improve program performance, which is very important in Java back-end development. In practical applications, we can use Java ForkJoinPool to perform parallel processing of API interfaces, which can not only improve the execution efficiency of the program, but also improve the user experience of the system.

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