package com.fasterxml.jackson.databind.util;

import java.io.*;
import java.util.concurrent.ConcurrentHashMap;

Helper for simple bounded maps used for reusing lookup values.

Note that serialization behavior is such that contents are NOT serialized, on assumption that all use cases are for caching where persistence does not make sense. The only thing serialized is the cache size of Map.

NOTE: since version 2.4.2, this is NOT an LRU-based at all; reason being that it is not possible to use JDK components that do LRU _AND_ perform well wrt synchronization on multi-core systems. So we choose efficient synchronization over potentially more efficient handling of entries.

And yes, there are efficient LRU implementations such as concurrentlinkedhashmap; but at this point we really try to keep external deps to minimum. But perhaps a shaded variant may be used one day.

/** * Helper for simple bounded maps used for reusing lookup values. *<p> * Note that serialization behavior is such that contents are NOT serialized, * on assumption that all use cases are for caching where persistence * does not make sense. The only thing serialized is the cache size of Map. *<p> * NOTE: since version 2.4.2, this is <b>NOT</b> an LRU-based at all; reason * being that it is not possible to use JDK components that do LRU _AND_ perform * well wrt synchronization on multi-core systems. So we choose efficient synchronization * over potentially more efficient handling of entries. *<p> * And yes, there are efficient LRU implementations such as * <a href="https://code.google.com/p/concurrentlinkedhashmap/">concurrentlinkedhashmap</a>; * but at this point we really try to keep external deps to minimum. But perhaps * a shaded variant may be used one day. */
public class LRUMap<K,V> implements java.io.Serializable { private static final long serialVersionUID = 1L; protected final transient int _maxEntries; protected final transient ConcurrentHashMap<K,V> _map; public LRUMap(int initialEntries, int maxEntries) { // We'll use concurrency level of 4, seems reasonable _map = new ConcurrentHashMap<K,V>(initialEntries, 0.8f, 4); _maxEntries = maxEntries; } public V put(K key, V value) { if (_map.size() >= _maxEntries) { // double-locking, yes, but safe here; trying to avoid "clear storms" synchronized (this) { if (_map.size() >= _maxEntries) { clear(); } } } return _map.put(key, value); }
Since:2.5
/** * @since 2.5 */
public V putIfAbsent(K key, V value) { // not 100% optimal semantically, but better from correctness (never exceeds // defined maximum) and close enough all in all: if (_map.size() >= _maxEntries) { synchronized (this) { if (_map.size() >= _maxEntries) { clear(); } } } return _map.putIfAbsent(key, value); } // NOTE: key is of type Object only to retain binary backwards-compatibility public V get(Object key) { return _map.get(key); } public void clear() { _map.clear(); } public int size() { return _map.size(); } /* /********************************************************** /* Serializable overrides /********************************************************** */
Ugly hack, to work through the requirement that _value is indeed final, and that JDK serialization won't call ctor(s) if Serializable is implemented.
Since:2.1
/** * Ugly hack, to work through the requirement that _value is indeed final, * and that JDK serialization won't call ctor(s) if Serializable is implemented. * * @since 2.1 */
protected transient int _jdkSerializeMaxEntries; private void readObject(ObjectInputStream in) throws IOException { _jdkSerializeMaxEntries = in.readInt(); } private void writeObject(ObjectOutputStream out) throws IOException { out.writeInt(_jdkSerializeMaxEntries); } protected Object readResolve() { return new LRUMap<Object,Object>(_jdkSerializeMaxEntries, _jdkSerializeMaxEntries); } }