緩存大小動態(tài)調整適應Java線程負載變化

在Java中，動態(tài)調整緩存大小以適應線程負載變化可以通過多種方法實現。以下是一些常見的方法：

1. 使用Java內置的緩存庫

Java提供了一些內置的緩存庫，如java.util.concurrent.ConcurrentHashMap，可以用于實現動態(tài)調整緩存大小的功能。

import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.atomic.AtomicInteger;

public class DynamicCache<K, V> {
    private final ConcurrentHashMap<K, V> cache = new ConcurrentHashMap<>();
    private final AtomicInteger size = new AtomicInteger(0);
    private final int maxCapacity;

    public DynamicCache(int maxCapacity) {
        this.maxCapacity = maxCapacity;
    }

    public V get(K key) {
        return cache.get(key);
    }

    public void put(K key, V value) {
        if (cache.containsKey(key)) {
            return;
        }
        if (size.incrementAndGet() > maxCapacity) {
            evict();
        }
        cache.put(key, value);
    }

    private void evict() {
        // Implement eviction logic here, e.g., remove the least recently used item
        cache.entrySet().iterator().next().getKey();
        size.decrementAndGet();
    }
}

2. 使用第三方庫

有一些第三方庫可以幫助實現動態(tài)調整緩存大小的功能，例如Guava的CacheBuilder。

import com.google.common.cache.Cache;
import com.google.common.cache.CacheBuilder;

public class DynamicCache<K, V> {
    private final Cache<K, V> cache;

    public DynamicCache(int initialCapacity, float maxLoadFactor) {
        this.cache = CacheBuilder.newBuilder()
                .initialCapacity(initialCapacity)
                .maximumSize(Integer.MAX_VALUE) // Adjust as needed
                .loadFactor(maxLoadFactor)
                .build();
    }

    public V get(K key) {
        return cache.getIfPresent(key);
    }

    public void put(K key, V value) {
        cache.put(key, value);
    }
}

3. 自定義實現

你也可以自定義實現一個動態(tài)調整大小的緩存類。

import java.util.HashMap;
import java.util.Map;
import java.util.concurrent.Executors;
import java.util.concurrent.ScheduledExecutorService;
import java.util.concurrent.TimeUnit;

public class DynamicCache<K, V> {
    private final Map<K, V> cache = new HashMap<>();
    private final int maxCapacity;
    private final ScheduledExecutorService executor = Executors.newScheduledThreadPool(1);

    public DynamicCache(int maxCapacity) {
        this.maxCapacity = maxCapacity;
        scheduleCacheEviction();
    }

    public V get(K key) {
        return cache.get(key);
    }

    public void put(K key, V value) {
        if (cache.containsKey(key)) {
            return;
        }
        if (cache.size() >= maxCapacity) {
            evict();
        }
        cache.put(key, value);
    }

    private void scheduleCacheEviction() {
        executor.scheduleAtFixedRate(() -> {
            evict();
        }, 1, 1, TimeUnit.MINUTES); // Adjust as needed
    }

    private void evict() {
        // Implement eviction logic here, e.g., remove the least recently used item
        K keyToRemove = null;
        V valueToRemove = null;
        for (Map.Entry<K, V> entry : cache.entrySet()) {
            if (keyToRemove == null || entry.getKey().compareTo(keyToRemove) < 0) {
                keyToRemove = entry.getKey();
                valueToRemove = entry.getValue();
            }
        }
        if (keyToRemove != null) {
            cache.remove(keyToRemove);
        }
    }
}

總結

以上方法都可以實現動態(tài)調整緩存大小以適應線程負載變化。你可以根據自己的需求選擇合適的方法。如果你需要更復雜的緩存策略，可以考慮使用第三方庫，如Guava的CacheBuilder。