How to control concurrency with Java caching technology

Java caching technology plays a very important role in applications and can effectively improve application performance and response speed. However, in high-concurrency scenarios, how to control the concurrency of Java cache technology to ensure the correctness and stability of applications has become an important issue that development engineers need to face.

The following are some commonly used Java cache technology concurrency control methods:

1. Synchronization lock

Synchronization lock is the most basic Java concurrency control technology, by controlling critical resources The locking method ensures that only one thread can access the resource at the same time. In caching technology, concurrent data operation control can be achieved by locking the data structure.

For example, when using HashMap for caching, you can lock it synchronously. The code example is as follows:

Map<String, Object> cacheMap = Collections.synchronizedMap(new HashMap<>());
Object value;
synchronized (cacheMap) {
    value = cacheMap.get(key);
    if (value == null) {
        value = loadData();
        cacheMap.put(key, value);
    }
}

However, the shortcomings of synchronous locks are also obvious and may cause performance bottlenecks. and deadlock issues.

2. ConcurrentHashMap

ConcurrentHashMap is an efficient concurrent hash table. It divides the table into multiple segments and locks each segment to achieve efficient concurrent access. When using ConcurrentHashMap for caching, since it has a built-in concurrency control mechanism, locking operations can be omitted and the performance of the program can be improved.

For example, use ConcurrentHashMap for caching. The code example is as follows:

ConcurrentMap<String, Object> cacheMap = new ConcurrentHashMap<>();
Object value = cacheMap.get(key);
if (value == null) {
    value = loadData();
    cacheMap.put(key, value);
}

3. Read-write lock

The read-write lock is a special synchronization lock that can support both Multiple threads read shared resources and ensure that no other threads will read or write the resource during write operations. In caching technology, efficient read and write operations on cached data can be achieved by using read-write locks.

For example, when using LinkedHashMap for caching, you can use ReentrantReadWriteLock to control read-write locks. The code example is as follows:

Map<String, Object> cacheMap = new LinkedHashMap<String, Object>(16, 0.75f, true) {
    protected boolean removeEldestEntry(Map.Entry<String, Object> eldest) {
        return size() > CACHE_MAX_SIZE;
    }
};
ReentrantReadWriteLock lock = new ReentrantReadWriteLock();
Object value;
lock.readLock().lock();
try {
    value = cacheMap.get(key);
    if (value == null) {
        lock.readLock().unlock();
        lock.writeLock().lock();
        try {
            value = loadData();
            cacheMap.put(key, value);
        } finally {
            lock.writeLock().unlock();
        }
        lock.readLock().lock();
    }
} finally {
    lock.readLock().unlock();
}

4. Memory model

In Java The volatile keyword can ensure the visibility and orderliness of variables in a multi-threaded environment to achieve a function similar to a synchronization lock. When using caching technology, you can use the memory model to achieve concurrency control.

For example, when using double-check locking for caching, you can use the volatile keyword to ensure the visibility and orderliness of data. The code example is as follows:

volatile Map<String, Object> cacheMap;

Object value = cacheMap.get(key);
if (value == null) {
    synchronized (this) {
        value = cacheMap.get(key);
        if (value == null) {
            value = loadData();
            cacheMap.put(key, value);
        }
    }
}

The above is for Java Cache technology is a common method for concurrency control. Of course, in different scenarios, it is also necessary to flexibly choose different caching technologies and concurrency control methods according to needs. In this process, we need to continuously evaluate and optimize to ensure the performance and stability of the program.

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