What are the common concurrency patterns and designs in Java concurrent programming?

Java concurrent programming provides a variety of patterns and designs, including locks, atomic variables, semaphores, barriers, and publish-subscribe, to help write robust, scalable, and performant concurrent applications. Concurrency design includes thread pools, concurrent collections, lock-free data structures, reactive programming, and distributed locks to optimize concurrent processing. A practical case is using thread pools and concurrent queues to handle a large number of requests. This example demonstrates how to use the Java concurrency API to optimize request processing efficiency.

Common Concurrency Patterns and Designs in Java Concurrent Programming

Concurrent programming involves writing code so that multiple programs can run at the same time task. Java provides a variety of concurrency patterns and designs that help developers design robust, scalable, and performant concurrent applications.

Concurrency mode

1. Lock - Ensure exclusive access to shared data and prevent race conditions.

2. Atomic variables - Provide thread-safe variables to prevent different threads from modifying the same value at the same time.

3. Semaphore - Limit the number of threads that can access shared resources at the same time.

4. Barrier - Synchronize threads to ensure they all reach a certain point before continuing execution.

5. Publish-Subscribe - Allows publishers to publish events asynchronously, and subscribers to receive these events as needed.

Concurrency design

1. Thread pool - Manages the creation and destruction of threads to improve performance and scalability.

2. Concurrent Collections - Provides thread-safe collections, allowing safe storage and retrieval of data in a multi-threaded environment.

3. Lock-free data structure - Use atomic operations to achieve thread safety and avoid the overhead of using locks.

4. Reactive Programming - Focus on processing asynchronous event streams instead of using blocking I/O.

5. Distributed lock - Coordinates concurrent access in distributed systems and is used to manage shared resources across multiple servers.

Practical Case: Using Thread Pools and Concurrent Queues

Consider an application that handles a large number of requests. We can use thread pools and concurrent queues to optimize concurrent request processing:

import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.LinkedBlockingQueue;
import java.util.concurrent.TimeUnit;

public class ThreadPoolExample {

    public static void main(String[] args) throws InterruptedException {
        // 创建一个固定大小为 4 的线程池
        ExecutorService executorService = Executors.newFixedThreadPool(4);

        // 创建一个无界的并发队列
        LinkedBlockingQueue<Runnable> queue = new LinkedBlockingQueue<>();

        // 向队列中添加请求任务
        for (int i = 0; i < 10; i++) {
            queue.offer(() -> {
                // 执行请求处理
                System.out.println("执行请求：" + i);
            });
        }

        // 提交队列中的任务到线程池
        executorService.submit(queue);

        // 在 5 秒后关闭线程池
        executorService.shutdown();
        executorService.awaitTermination(5, TimeUnit.SECONDS);
    }
}

In the example, we created a thread pool with 4 threads. Tasks are stored in a concurrent queue and the thread pool fetches tasks from the queue and executes them in parallel. This makes request processing more efficient because the thread does not have to wait for a task to complete before starting to process the next task.

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