LRU算法及Apache LRUMap源码实例解析
目录
- 1. 什么是LRU
- 1.1 自定义实现LRU的要求
- 1.2 Apache LRUMap示例
- 1.2.1 pom依赖
- 1.2.2 demo
- 2. 源码解析
- 2.1 设计
- 2.2 数据结构
- 2.3 方法解析put get remove
- 2.3.1 get方法
- 2.3.2 remove方法
- 2.3.3 put方法
- 3. 总结
1. 什么是LRU
LRU(least recently used) : 最近最少使用
LRU就是一种经典的算法,在容器中,对元素定义一个最后使用时间,当新的元素写入的时候,如果容器已满,则淘汰最近最少使用的元素,把新的元素写入。
1.1 自定义实现LRU的要求
比如redis,如何自己实现简易版的redis缓存。
那么我们需要一种数据结构,支持set和get操作。
1) get操作时间复杂度O(1);
2)需要支持RLU算法,空间不足时,需要将使用最少的元素移除,为新元素让空间;
3)时间失效remove(这个先不谈,比较麻烦)。
1.2 Apache LRUMap示例
1.2.1 pom依赖
<dependency> <groupId>org.apache.commons</groupId> <artifactId>commons-collections4</artifactId> <version>4.2</version> </dependency>
1.2.2 demo
LRUMap<String, String> map = new LRUMap<>(3); map.put("1", "1"); map.put("2", "2"); map.put("3", "3"); map.get("2"); System.out.println("---------------------------------"); map.forEach((k,v)-> System.out.println(k+"\t"+v) ); map.put("4", "4"); map.put("5", "5"); System.out.println("---------------------------------"); map.forEach((k,v)-> System.out.println(k+"\t"+v) ); map.put("6", "6"); System.out.println("---------------------------------"); map.forEach((k,v)-> System.out.println(k+"\t"+v) );
结果如下:
---------------------------------
1 1
3 3
2 2
---------------------------------
2 2
4 4
5 5
---------------------------------
4 4
5 5
6 6
可以看出在get("2"),2的位置挪后,然后移除的顺序就延后。
容量不足时,总是移除,使用最少的,时间最远的。
2. 源码解析
2.1 设计
public class LRUMap<K, V> extends AbstractLinkedMap<K, V> implements BoundedMap<K, V>, Serializable, Cloneable {
进一步查看AbstractLinkedMap,AbstractHashedMap
public abstract class AbstractLinkedMap<K, V> extends AbstractHashedMap<K, V> implements OrderedMap<K, V> {
public class AbstractHashedMap<K, V> extends AbstractMap<K, V> implements IterableMap<K, V> {
本质是自定义AbstractMap
我们看看HashMap LinkedHashMap
public class LinkedHashMap<K,V> extends HashMap<K,V> implements Map<K,V>
public class HashMap<K,V> extends AbstractMap<K,V> implements Map<K,V>, Cloneable, Serializable {
可以看出AbstractMap,AbstractHashedMap,LRUMap的本质其实也是HashMap。
2.2 数据结构
protected static final int DEFAULT_MAX_SIZE = 100; public LRUMap() { this(DEFAULT_MAX_SIZE, DEFAULT_LOAD_FACTOR, false); }
可以看出默认初始化容量100,最大容量也是100.
进一步跟踪
public LRUMap(final int maxSize, final float loadFactor, final boolean scanUntilRemovable) { this(maxSize, maxSize, loadFactor, scanUntilRemovable); } /** * Constructs a new, empty map with the specified max / initial capacity and load factor. * * @param maxSize the maximum size of the map * @param initialSize the initial size of the map * @param loadFactor the load factor * @param scanUntilRemovable scan until a removeable entry is found, default false * @throws IllegalArgumentException if the maximum size is less than one * @throws IllegalArgumentException if the initial size is negative or larger than the maximum size * @throws IllegalArgumentException if the load factor is less than zero * @since 4.1 */ public LRUMap(final int maxSize, final int initialSize, final float loadFactor, final boolean scanUntilRemovable) { super(initialSize, loadFactor); if (maxSize < 1) { throw new IllegalArgumentException("LRUMap max size must be greater than 0"); } if (initialSize > maxSize) { throw new IllegalArgumentException("LRUMap initial size must not be greather than max size"); } this.maxSize = maxSize; this.scanUntilRemovable = scanUntilRemovable; }
跟踪super(initialSize, loadFactor);
public abstract class AbstractLinkedMap<K, V> extends AbstractHashedMap<K, V> implements OrderedMap<K, V> { protected AbstractLinkedMap(final int initialCapacity, final float loadFactor) { super(initialCapacity, loadFactor); } //又super,再上一层追踪 public class AbstractHashedMap<K, V> extends AbstractMap<K, V> implements IterableMap<K, V> { //定义一些基本初始化数据 /** The default capacity to use */ protected static final int DEFAULT_CAPACITY = 16; /** The default threshold to use */ protected static final int DEFAULT_THRESHOLD = 12; /** The default load factor to use */ protected static final float DEFAULT_LOAD_FACTOR = 0.75f; /** The maximum capacity allowed */ protected static final int MAXIMUM_CAPACITY = 1 << 30; /** Load factor, normally 0.75 */ transient float loadFactor; /** The size of the map */ transient int size; /** Map entries */ transient HashEntry<K, V>[] data; /** Size at which to rehash */ transient int threshold; /** Modification count for iterators */ transient int modCount; /** Entry set */ transient EntrySet<K, V> entrySet; /** Key set */ transient KeySet<K> keySet; /** Values */ transient Values<V> values; protected AbstractHashedMap(int initialCapacity, final float loadFactor) { super(); if (initialCapacity < 0) { throw new IllegalArgumentException("Initial capacity must be a non negative number"); } if (loadFactor <= 0.0f || Float.isNaN(loadFactor)) { throw new IllegalArgumentException("Load factor must be greater than 0"); } this.loadFactor = loadFactor; initialCapacity = calculateNewCapacity(initialCapacity); this.threshold = calculateThreshold(initialCapacity, loadFactor); this.data = new HashEntry[initialCapacity]; init(); } /** * Initialise subclasses during construction, cloning or deserialization. */ protected void init() { //没有任何逻辑,仅用于子类构造 }
DEFAULT_LOAD_FACTOR = 0.75f; 负载因子0.75
可以看出LRUMap的本质,HashEntry数组。
上面的init方法没有实现逻辑,但是在他的子类中AbstractLinkedMap有相关的定义。
/** Header in the linked list */ transient LinkEntry<K, V> header; /** * Creates an entry to store the data. * <p> * This implementation creates a new LinkEntry instance. * * @param next the next entry in sequence * @param hashCode the hash code to use * @param key the key to store * @param value the value to store * @return the newly created entry */ @Override protected LinkEntry<K, V> createEntry(final HashEntry<K, V> next, final int hashCode, final K key, final V value) { return new LinkEntry<>(next, hashCode, convertKey(key), value); } protected static class LinkEntry<K, V> extends HashEntry<K, V> { /** The entry before this one in the order */ protected LinkEntry<K, V> before; /** The entry after this one in the order */ protected LinkEntry<K, V> after; /** * Constructs a new entry. * * @param next the next entry in the hash bucket sequence * @param hashCode the hash code * @param key the key * @param value the value */ protected LinkEntry(final HashEntry<K, V> next, final int hashCode, final Object key, final V value) { super(next, hashCode, key, value); } } /** * Initialise this subclass during construction. * <p> * NOTE: As from v3.2 this method calls * {@link #createEntry(HashEntry, int, Object, Object)} to create * the map entry object. */ @Override protected void init() { header = createEntry(null, -1, null, null); header.before = header.after = header; }
这个很关键。可以看出LRUMap是持有LinkEntry header,的双链表结构,初始header为null,前后节点都是自身。将HashEntry转成LinkEntry。
解析HashEntry
transient HashEntry<K, V>[] data; //构造初始化 this.data = new HashEntry[initialCapacity];
再跟踪
protected static class HashEntry<K, V> implements Map.Entry<K, V>, KeyValue<K, V> { /** The next entry in the hash chain */ protected HashEntry<K, V> next; /** The hash code of the key */ protected int hashCode; /** The key */ protected Object key; /** The value */ protected Object value;
key,value,next单链表。
public int hashCode() { return (getKey() == null ? 0 : getKey().hashCode()) ^ (getValue() == null ? 0 : getValue().hashCode()); }
hashCode方法可以看出是key的hash与value的hash按位^运算。
在此我们看透LRU的本质了,数组+单链表。同时是持有头结点的双链表结构(怎么看就是LinkedHashMap的结构,只是有尾节点)。
public class LinkedHashMap<K,V> extends HashMap<K,V> implements Map<K,V> { /** * The head (eldest) of the doubly linked list. */ transient LinkedHashMap.Entry<K,V> head; /** * The tail (youngest) of the doubly linked list. */ transient LinkedHashMap.Entry<K,V> tail;
那么LRUMap是如何实现LRU算法的?
2.3 方法解析put get remove
2.3.1 get方法
public V get(final Object key) { return get(key, true); } public V get(final Object key, final boolean updateToMRU) { final LinkEntry<K, V> entry = getEntry(key); if (entry == null) { return null; } if (updateToMRU) { moveToMRU(entry); } return entry.getValue(); } //父类方法获取值entry protected HashEntry<K, V> getEntry(Object key) { key = convertKey(key); final int hashCode = hash(key); HashEntry<K, V> entry = data[hashIndex(hashCode, data.length)]; // no local for hash index while (entry != null) { if (entry.hashCode == hashCode && isEqualKey(key, entry.key)) { return entry; } entry = entry.next; } return null; }
下面看不一样的moveToMRU(entry);
/** * Moves an entry to the MRU position at the end of the list. * <p> * This implementation moves the updated entry to the end of the list. * * @param entry the entry to update */ protected void moveToMRU(final LinkEntry<K, V> entry) { if (entry.after != header) { modCount++; // remove if(entry.before == null) { throw new IllegalStateException("Entry.before is null." + " Please check that your keys are immutable, and that you have used synchronization properly." + " If so, then please report this to dev@commons.apache.org as a bug."); } entry.before.after = entry.after; entry.after.before = entry.before; // add first entry.after = header; entry.before = header.before; header.before.after = entry; header.before = entry; } else if (entry == header) { throw new IllegalStateException("Can't move header to MRU" + " (please report this to dev@commons.apache.org)"); } }
看出LRU的一个本质,每次get方法拨动指针,将get的元素移动到header的前一个位置。
2.3.2 remove方法
remove方法使用的父类的方法
/** * Removes the specified mapping from this map. * * @param key the mapping to remove * @return the value mapped to the removed key, null if key not in map */ @Override public V remove(Object key) { key = convertKey(key); final int hashCode = hash(key); final int index = hashIndex(hashCode, data.length); HashEntry<K, V> entry = data[index]; HashEntry<K, V> previous = null; while (entry != null) { if (entry.hashCode == hashCode && isEqualKey(key, entry.key)) { final V oldValue = entry.getValue(); removeMapping(entry, index, previous); return oldValue; } previous = entry; entry = entry.next; } return null; } /** * Removes a mapping from the map. * <p> * This implementation calls <code>removeEntry()</code> and <code>destroyEntry()</code>. * It also handles changes to <code>modCount</code> and <code>size</code>. * Subclasses could override to fully control removals from the map. * * @param entry the entry to remove * @param hashIndex the index into the data structure * @param previous the previous entry in the chain */ protected void removeMapping(final HashEntry<K, V> entry, final int hashIndex, final HashEntry<K, V> previous) { modCount++; removeEntry(entry, hashIndex, previous); size--; destroyEntry(entry); } protected void removeEntry(final HashEntry<K, V> entry, final int hashIndex, final HashEntry<K, V> previous) { if (previous == null) { data[hashIndex] = entry.next; } else { previous.next = entry.next; } } protected void destroyEntry(final HashEntry<K, V> entry) { entry.next = null; entry.key = null; entry.value = null; }
这里并没有移除header双链表的数据。
2.3.3 put方法
/** * Puts a key-value mapping into this map. * * @param key the key to add * @param value the value to add * @return the value previously mapped to this key, null if none */ @Override public V put(final K key, final V value) { final Object convertedKey = convertKey(key); final int hashCode = hash(convertedKey); final int index = hashIndex(hashCode, data.length); HashEntry<K, V> entry = data[index]; //仅在元素存在才循环,更新updateEntry,header前一个位置 while (entry != null) { if (entry.hashCode == hashCode && isEqualKey(convertedKey, entry.key)) { final V oldValue = entry.getValue(); updateEntry(entry, value); return oldValue; } entry = entry.next; } addMapping(index, hashCode, key, value); return null; }
updateEntry(entry, value);
/** * Updates an existing key-value mapping. * <p> * This implementation moves the updated entry to the end of the list * using {@link #moveToMRU(AbstractLinkedMap.LinkEntry)}. * * @param entry the entry to update * @param newValue the new value to store */ @Override protected void updateEntry(final HashEntry<K, V> entry, final V newValue) { moveToMRU((LinkEntry<K, V>) entry); // handles modCount entry.setValue(newValue); }
moveToMRU((LinkEntry<K, V>) entry); // handles modCount
上面get方法有讲,更新了链表的指针,新添加的元素在双链表的header前一个位置,仅在元素存在的时候,while循环才生效。
那么新增的元素呢?
下面看重点 addMapping(index, hashCode, key, value); 这句代码定义了,容量满了的处理策略。
/** * Adds a new key-value mapping into this map. * <p> * This implementation checks the LRU size and determines whether to * discard an entry or not using {@link #removeLRU(AbstractLinkedMap.LinkEntry)}. * <p> * From Commons Collections 3.1 this method uses {@link #isFull()} rather * than accessing <code>size</code> and <code>maxSize</code> directly. * It also handles the scanUntilRemovable functionality. * * @param hashIndex the index into the data array to store at * @param hashCode the hash code of the key to add * @param key the key to add * @param value the value to add */ @Override protected void addMapping(final int hashIndex, final int hashCode, final K key, final V value) { //容量是否已满 if (isFull()) { LinkEntry<K, V> reuse = header.after; boolean removeLRUEntry = false; //默认是false if (scanUntilRemovable) { //这里不知道干啥,难道是以后扩展? while (reuse != header && reuse != null) { //removeLRU一定返回true,很奇怪,估计以后扩展用 if (removeLRU(reuse)) { removeLRUEntry = true; break; } reuse = reuse.after; } if (reuse == null) { throw new IllegalStateException( "Entry.after=null, header.after" + header.after + " header.before" + header.before + " key=" + key + " value=" + value + " size=" + size + " maxSize=" + maxSize + " Please check that your keys are immutable, and that you have used synchronization properly." + " If so, then please report this to dev@commons.apache.org as a bug."); } } else { //一定返回true removeLRUEntry = removeLRU(reuse); } if (removeLRUEntry) { if (reuse == null) { throw new IllegalStateException( "reuse=null, header.after=" + header.after + " header.before" + header.before + " key=" + key + " value=" + value + " size=" + size + " maxSize=" + maxSize + " Please check that your keys are immutable, and that you have used synchronization properly." + " If so, then please report this to dev@commons.apache.org as a bug."); } reuseMapping(reuse, hashIndex, hashCode, key, value); } else { super.addMapping(hashIndex, hashCode, key, value); } } else { super.addMapping(hashIndex, hashCode, key, value); } } protected boolean removeLRU(final LinkEntry<K, V> entry) { return true; }
先判断容量
public boolean isFull() { return size >= maxSize; }
未满就直接添加
super.addMapping(hashIndex, hashCode, key, value);
protected void addMapping(final int hashIndex, final int hashCode, final K key, final V value) { modCount++; final HashEntry<K, V> entry = createEntry(data[hashIndex], hashCode, key, value); addEntry(entry, hashIndex); size++; checkCapacity(); }
//这里调用了AbstractLinkedMap的方法
addEntry(entry, hashIndex);
/** * Adds an entry into this map, maintaining insertion order. * <p> * This implementation adds the entry to the data storage table and * to the end of the linked list. * * @param entry the entry to add * @param hashIndex the index into the data array to store at */ @Override protected void addEntry(final HashEntry<K, V> entry, final int hashIndex) { final LinkEntry<K, V> link = (LinkEntry<K, V>) entry; link.after = header; link.before = header.before; header.before.after = link; header.before = link; data[hashIndex] = link; }
放在header的前一个位置,最早的元素链接到header。
双向环回链表。
如果容量满了,执行LRU算法 reuseMapping(reuse, hashIndex, hashCode, key, value);
/** * Reuses an entry by removing it and moving it to a new place in the map. * <p> * This method uses {@link #removeEntry}, {@link #reuseEntry} and {@link #addEntry}. * * @param entry the entry to reuse * @param hashIndex the index into the data array to store at * @param hashCode the hash code of the key to add * @param key the key to add * @param value the value to add */ protected void reuseMapping(final LinkEntry<K, V> entry, final int hashIndex, final int hashCode, final K key, final V value) { // find the entry before the entry specified in the hash table // remember that the parameters (except the first) refer to the new entry, // not the old one try { //要干掉的元素下标 final int removeIndex = hashIndex(entry.hashCode, data.length); final HashEntry<K, V>[] tmp = data; // may protect against some sync issues HashEntry<K, V> loop = tmp[removeIndex]; HashEntry<K, V> previous = null; //避免已经被删除 while (loop != entry && loop != null) { previous = loop; loop = loop.next; } //如果被其他线程删除,抛异常 if (loop == null) { throw new IllegalStateException( "Entry.next=null, data[removeIndex]=" + data[removeIndex] + " previous=" + previous + " key=" + key + " value=" + value + " size=" + size + " maxSize=" + maxSize + " Please check that your keys are immutable, and that you have used synchronization properly." + " If so, then please report this to dev@commons.apache.org as a bug."); } // reuse the entry modCount++; //双链表移除旧元素,AbstractHashedMap移除旧元素 removeEntry(entry, removeIndex, previous); //复用移除的对象,减少创建对象和GC;增加AbstractHashedMap单链表next指向 reuseEntry(entry, hashIndex, hashCode, key, value); //复用的元素加AbstractLinkedMap双链表和AbstractHashedMap单链表 addEntry(entry, hashIndex); } catch (final NullPointerException ex) { throw new IllegalStateException( "NPE, entry=" + entry + " entryIsHeader=" + (entry==header) + " key=" + key + " value=" + value + " size=" + size + " maxSize=" + maxSize + " Please check that your keys are immutable, and that you have used synchronization properly." + " If so, then please report this to dev@commons.apache.org as a bug."); } }
/** * Removes an entry from the map and the linked list. * <p> * This implementation removes the entry from the linked list chain, then * calls the superclass implementation. * * @param entry the entry to remove * @param hashIndex the index into the data structure * @param previous the previous entry in the chain */ @Override protected void removeEntry(final HashEntry<K, V> entry, final int hashIndex, final HashEntry<K, V> previous) { final LinkEntry<K, V> link = (LinkEntry<K, V>) entry; link.before.after = link.after; link.after.before = link.before; link.after = null; link.before = null; super.removeEntry(entry, hashIndex, previous); } /** * Removes an entry from the chain stored in a particular index. * <p> * This implementation removes the entry from the data storage table. * The size is not updated. * Subclasses could override to handle changes to the map. * * @param entry the entry to remove * @param hashIndex the index into the data structure * @param previous the previous entry in the chain */ protected void removeEntry(final HashEntry<K, V> entry, final int hashIndex, final HashEntry<K, V> previous) { if (previous == null) { data[hashIndex] = entry.next; } else { previous.next = entry.next; } } /** * Reuses an existing key-value mapping, storing completely new data. * <p> * This implementation sets all the data fields on the entry. * Subclasses could populate additional entry fields. * * @param entry the entry to update, not null * @param hashIndex the index in the data array * @param hashCode the hash code of the key to add * @param key the key to add * @param value the value to add */ protected void reuseEntry(final HashEntry<K, V> entry, final int hashIndex, final int hashCode, final K key, final V value) { entry.next = data[hashIndex]; entry.hashCode = hashCode; entry.key = key; entry.value = value; } /** * Adds an entry into this map, maintaining insertion order. * <p> * This implementation adds the entry to the data storage table and * to the end of the linked list. * * @param entry the entry to add * @param hashIndex the index into the data array to store at */ @Override protected void addEntry(final HashEntry<K, V> entry, final int hashIndex) { final LinkEntry<K, V> link = (LinkEntry<K, V>) entry; link.after = header; link.before = header.before; header.before.after = link; header.before = link; data[hashIndex] = link; }
3. 总结
LRU的本质了,数组+单链表。同时是持有头结点的环回双链表结构
LRU最新使用的元素放在双链表的header的前一个位置,如果,新增元素容量已满就会移除header的后一个元素。
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