jodd.cache.LRUCache Maven / Gradle / Ivy
// Copyright (c) 2003-present, Jodd Team (http://jodd.org)
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package jodd.cache;
import java.util.LinkedHashMap;
import java.util.Map;
import java.util.Iterator;
/**
* LRU (least recently used) cache.
*
*
* Items are added to the cache as they are accessed; when the cache is full, the least recently used item is ejected.
* This type of cache is typically implemented as a linked list, so that an item in cache, when it is accessed again,
* can be moved back up to the head of the queue; items are ejected from the tail of the queue. Cache access overhead
* is again constant time. This algorithm is simple and fast, and it has a significant advantage over FIFO in being
* able to adapt somewhat to the data access pattern; frequently used items are less likely to be
* ejected from the cache. The main disadvantage is that it can still get filled up with items that are
* unlikely to be reaccessed soon; in particular, it can become useless in the face of scanning type accesses.
* Nonetheless, this is by far the most frequently used caching algorithm.
*
* Implementation note: unfortunately, it was not possible to have onRemove callback method,
* since LinkedHashMap has its removal methods private.
*
* Summary for LRU: fast, adaptive, not scan resistant.
*/
public class LRUCache extends AbstractCacheMap {
public LRUCache(final int cacheSize) {
this(cacheSize, 0);
}
/**
* Creates a new LRU cache.
*/
public LRUCache(final int cacheSize, final long timeout) {
this.cacheSize = cacheSize;
this.timeout = timeout;
cacheMap = new LinkedHashMap>(cacheSize + 1, 1.0f, true) {
@Override
protected boolean removeEldestEntry(final Map.Entry eldest) {
return LRUCache.this.removeEldestEntry(size());
}
};
}
/**
* Removes the eldest entry if current cache size exceed cache size.
*/
protected boolean removeEldestEntry(final int currentSize) {
if (cacheSize == 0) {
return false;
}
return currentSize > cacheSize;
}
// ---------------------------------------------------------------- prune
/**
* Prune only expired objects, LinkedHashMap will take care of LRU if needed.
*/
@Override
protected int pruneCache() {
if (!isPruneExpiredActive()) {
return 0;
}
int count = 0;
Iterator> values = cacheMap.values().iterator();
while (values.hasNext()) {
CacheObject co = values.next();
if (co.isExpired()) {
values.remove();
onRemove(co.key, co.cachedObject);
count++;
}
}
return count;
}
}