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Ehcache is an open source, standards-based cache used to boost performance,
offload the database and simplify scalability. Ehcache is robust, proven and full-featured and
this has made it the most widely-used Java-based cache.
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package org.glassfish.hk2.utilities.cache.internal;
import java.util.Collection;
import java.util.Collections;
import java.util.Comparator;
import java.util.HashMap;
import java.util.Map;
import java.util.concurrent.ConcurrentHashMap;
import org.glassfish.hk2.utilities.cache.CacheEntry;
import org.glassfish.hk2.utilities.cache.CacheKeyFilter;
import org.glassfish.hk2.utilities.cache.LRUCache;
/**
* LRU Cache implementation that relies on entries that keep
* last hit (get/put) timestamp in order to be able to remove least recently
* accessed items when running out of cache capacity.
* Item order is not being maintained during regular cache usage (mainly reads).
* This makes pruning operation expensive in exchange
* for making reads quite cheap in a multi-threaded environment.
*
* @author Jakub Podlesak (jakub.podlesak at oracle.com)
* @param The key of the cache
* @param The values in the cache
*/
public class LRUCacheCheapRead extends LRUCache {
final Object prunningLock = new Object();
final int maxCacheSize;
Map> cache = new ConcurrentHashMap>();
/**
* Create new cache with given maximum capacity.
*
* @param maxCacheSize Maximum number of items to keep.
*/
public LRUCacheCheapRead(int maxCacheSize) {
this.maxCacheSize = maxCacheSize;
}
@Override
public V get(K key) {
final CacheEntryImpl entry = cache.get(key);
return entry != null ? entry.hit().value : null;
}
@Override
public CacheEntry put(K key, V value) {
CacheEntryImpl entry = new CacheEntryImpl(key, value, this);
synchronized (prunningLock) {
if (cache.size() + 1 > maxCacheSize) {
removeLRUItem();
}
cache.put(key, entry);
return entry;
}
}
@Override
public void releaseCache() {
cache.clear();
}
@Override
public int getMaxCacheSize() {
return maxCacheSize;
}
@Override
public void releaseMatching(CacheKeyFilter filter) {
if (filter == null) return;
for (Map.Entry> entry : (new HashMap>(cache)).entrySet()) {
if (filter.matches(entry.getKey())) {
entry.getValue().removeFromCache();
}
}
}
/**
* Remove least recently used item form the cache.
* No checks are done here. The method just tries to remove the least recently used
* cache item. An exception will be thrown if the cache is empty.
*/
private void removeLRUItem() {
final Collection> values = cache.values();
Collections.min(values, COMPARATOR).removeFromCache();
}
private static final CacheEntryImplComparator COMPARATOR = new CacheEntryImplComparator();
private static class CacheEntryImplComparator implements Comparator> {
@Override
public int compare(CacheEntryImpl first, CacheEntryImpl second) {
final long diff = first.lastHit - second.lastHit;
return diff > 0 ? 1 : diff == 0 ? 0 : -1;
}
}
private static class CacheEntryImpl implements CacheEntry {
final K key;
final V value;
final LRUCacheCheapRead parent;
long lastHit;
public CacheEntryImpl(K k, V v, LRUCacheCheapRead cache) {
this.parent = cache;
this.key = k;
this.value = v;
this.lastHit = System.nanoTime();
}
@Override
public void removeFromCache() {
parent.cache.remove(key);
}
public CacheEntryImpl hit() {
this.lastHit = System.nanoTime();
return this;
}
}
}