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The relationship between Java multithreading and GC

Apr 11, 2024 pm 02:21 PM
java Multithreading java multithreading concurrent access Synchronization mechanism gc

Multiple threads affect GC, causing memory visibility problems and affecting GC efficiency. In order to mitigate the impact, the following measures can be taken: use synchronization mechanisms to ensure the security of concurrent access to shared data; reduce the amount of shared data and reduce the possibility of memory visibility problems; use concurrent data structures to handle concurrent access.

The relationship between Java multithreading and GC

The relationship between Java multi-threading and GC

The impact of multi-threading on GC

Multiple threads can cause memory visibility problems, which may affect the efficiency of GC. When multiple threads access shared data concurrently, without proper synchronization, the following problems may result:

  • Dirty read: One thread reads something that another thread has not written yet Enter the completed data.
  • Dirty write: One thread writes data that is being read by another thread.
  • Deadlock: Two or more threads wait for each other to release the lock.

These problems may cause the GC to reference incorrect or invalid objects, causing application instability or even crash.

How to reduce the impact of multi-threading on GC

In order to reduce the impact of multi-threading on GC, you can take the following measures:

  • Use synchronization mechanism: Use the synchronized keyword or the classes in the java.util.concurrent package to ensure that concurrent access to shared data is safe.
  • Reduce the amount of shared data: Minimize the amount of data shared between threads to reduce the possibility of memory visibility problems.
  • Use concurrent data structures: Use data structures designed for concurrency, such as ConcurrentHashMap, to handle concurrent access.

Practical case

The following is a practical case showing the impact of multi-threading on GC:

class SharedCounter {
    private int count = 0;

    public int getCount() {
        return count;
    }

    public void increment() {
        count++;
    }
}

public class MultithreadedCounter {

    public static void main(String[] args) {
        final SharedCounter counter = new SharedCounter();

        // 创建 10 个线程并发地增加计数器
        Thread[] threads = new Thread[10];
        for (int i = 0; i < threads.length; i++) {
            threads[i] = new Thread(() -> {
                for (int j = 0; j < 100000; j++) {
                    counter.increment();
                }
            });
        }

        // 启动所有线程
        for (Thread thread : threads) {
            thread.start();
        }

        // 等待所有线程完成
        for (Thread thread : threads) {
            try {
                thread.join();
            } catch (InterruptedException e) {
                e.printStackTrace();
            }
        }

        // 打印计数器的值
        System.out.println("Final count: " + counter.getCount());
    }
}
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Expected output :

Final count: 1000000
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Explanation:

This example creates a shared counter object that is incremented concurrently by 10 threads. Since no synchronization mechanism is used, threads may write different values ​​to the count field concurrently, which may cause dirty write issues. In this case, the expected output should be 1000000, but the actual output may vary depending on thread scheduling and GC behavior.

By adding a synchronization block, you can ensure that concurrent access to the count field is safe, thus avoiding dirty write problems. The updated code is as follows:

class SharedCounter {
    private int count = 0;

    public synchronized int getCount() {
        return count;
    }

    public synchronized void increment() {
        count++;
    }
}
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