java數據結構之HashMap
1、HashMap源碼註釋java
/** * HashMap的存儲結構： * 底層是用一個數組table來存儲鍵值對的Node，table的每一個下標稱爲一個桶，經過key計算出來的hash值和table的長度計算出來下標值，鍵值對就存儲在table的該下標處的桶中 * 若是計算獲得的下標相同就會被存入到同一個桶裏面，以單鏈表的形式來進行存儲， * 若是鏈表太長就會以tree的形式來對Node進行存儲 * * * HashMap實現了Map接口，容許存儲null鍵和null值。 * HashMap和HashTable相比除了它是不一樣步的而且容許null鍵和null值外，其餘部分大體至關。 * HashMap不能保證map中元素的順序，也不能保證順序不隨着時間的變化改變 * * 若是hash函數將元素恰當的分散到各個桶中，那麼HashMap爲基本操做提供了get和put提供了常量級的時間性能。 * 迭代集合所須要的時間和桶的個數以及鍵值對的個數成正比。所以，若是很看重性能就不要將初始容量設置過高（或者負載因子設置過小） * * HashMap實例有兩個影響其性能的參數：初始容量initial capacity和負載因子load factor。 * initial capacity 就是建立HashMap時table的長度。 * load factor 負載因子 是衡量在table的長度在被自動增長以前，table能夠填多滿的度量，用來限制table填充的極限。 * 當哈希表的中的鍵值對超過負載因子和當前容量的乘積時，哈希表將會被rehash（即從新構建內部數據結構），致使table的桶數量翻倍 * * 通常來講默認的負載因子0.75在時間和空間成本之間提供了很好的權衡，較高的負載因子雖然減小了空間開銷，可是增長了查詢的成本（反映在HashMap的大多數操做上，包括put和get）。 * 在設置map的初始容量時，應該考慮map中預期的鍵值對數量以及負載因子，從而最小化rehash操做數量。 * 若是初始容量大於最大鍵值對數除以負載因子，則不會發生任何重哈希操做。 * * 若是要將許多映射存儲在HashMap實例中，那麼建立足夠大容量的哈希表來存儲映射將比讓映射根據須要執行自動哈希來增加表更有效地存儲映射。 * 注意，使用具備相同hashCode()的多個鍵確定會下降任何散列表的性能。爲了改善影響，當鍵是可比較的時，該類可使用鍵之間的比較順序來幫助下降影響。 * * 注意，HashMap不是同步的。若是多個線程同時訪問一個散列映射，而且其中至少有一個線程從結構上修改了映射，那麼它必須在外部同步。 * 這一般是經過在封裝這個map的對象上進行同步來實現的。若是不存在這樣的對象，則應該使用Collections.synchronizedMap「包裝」映射 * 方法。這最好在建立時完成，以防止意外地不一樣步地訪問這個map * Map m = Collections.synchronizedMap(new HashMap(...)); * * 這個類的全部「集合視圖方法」返回的迭代器都是快速失敗的:若是在建立迭代器以後的任什麼時候候對映射進行結構上的修改， * （除了經過迭代器本身的remove方法以外），迭代器將拋出ConcurrentModificationException。 * 所以，在面對併發修改時，迭代器會快速而乾淨地失敗，而不是在未來某個不肯定的時間冒着任意的、不肯定的行爲的風險。 * * 注意，迭代器的快速故障行爲不能獲得保證，通常來講，在存在非同步併發修改的狀況下，不可能作出任何嚴格的保證。 * 故障快速迭代器以最大的努力拋出ConcurrentModificationException。 * 所以，編寫一個依賴於此異常來判斷其正確性的程序是錯誤的:迭代器的快速故障行爲應該只用於檢測bug。 * * * @author Doug Lea * @author Josh Bloch * @author Arthur van Hoff * @author Neal Gafter */ public class HashMap<K,V> extends AbstractMap<K,V> implements Map<K,V>, Cloneable, Serializable { private static final long serialVersionUID = 362498820763181265L; /* * 注意事項： * * HashMap一般至關於裝有不少桶哈希表，可是當桶變得太大時，它們會被轉換成樹節點的桶，每一個桶的結構都相似於java.util.TreeMap中的桶。 * 大多數方法都嘗試使用普通的桶（鏈表），但在適用時中繼到TreeNode方法(只需檢查節點的instanceof)。 * 樹節點的存儲桶能夠像其餘存桶同樣被遍歷，可是能夠在鍵值對數量不少的時支持更快的查找。 * 可是，因爲正常使用的大多數桶並無過分填充，因此在表方法的過程當中可能會延遲檢查樹桶是否存在。 * * 樹型桶（其元素都是treenode的桶)主要由hashCode排序，但在tie的狀況下， * 若是兩個元素具備相同的「class C implementation Comparable」，則鍵入它們的compareTo方法來排序。 * 樹桶的額外複雜性是值得的，在提供壞的O (log n)操做，當鍵有不一樣的散列或可排序時。 * 所以,在乎外或惡意使用hashCode()方法的返回值有着不好的分佈時，以及那些許多鍵共享一個hashCode的鍵（只要它們也是可比較的），性能會優雅地降低, * (若是這兩種方法都不適用，與不採起預防措施相比，咱們可能會浪費大約兩倍的時間和空間。 * 但目前所知的惟一案例來自於糟糕的用戶編程實踐，這些實踐已經很是緩慢，以致於沒有什麼區別。) * * 由於樹節點的大小大約是普通節點的兩倍，因此咱們只在桶中包含足夠的節點以保證使用時才使用它們(請參閱TREEIFY_THRESHOLD)。 * 當它們變得過小(因爲移除或調整大小)，就會被轉換回普通的桶（鏈表）。在使用分佈良好的用戶哈希碼時，不多使用樹桶。 * 理想狀況下，在隨機哈希碼下，bin中節點的頻率遵循泊松分佈(http://en.wikipedia.org/wiki/Poisson_distribution)， * 默認調整閾值爲0.75，平均參數約爲0.5，儘管因爲調整粒度而存在較大的差別。忽略方差，列表大小k的預期出現率爲(exp(-0.5) * pow(0.5, k) / factorial(k))。 * 第一個值是: * * 0: 0.60653066 * 1: 0.30326533 * 2: 0.07581633 * 3: 0.01263606 * 4: 0.00157952 * 5: 0.00015795 * 6: 0.00001316 * 7: 0.00000094 * 8: 0.00000006 * more: less than 1 in ten million * 更多：少於千萬分之一 * * 樹桶的根節點一般是它的第一個節點，可是有時(目前僅在Iterator.remove以後)根可能在其餘地方， * 可是可以經過TreeNode.root()方法進行恢復 * * 全部適用的內部方法都接受散列代碼做爲參數(一般由公共方法提供)，容許它們在不從新計算用戶散列代碼的狀況下相互調用。大多數內部方法也接受「tab」參數， * 這一般是當前表，但在調整大小或轉換時多是新的或舊的。 * * 當桶列表被treeified、split或untreeified時，咱們將它們保持相同的相對訪問/遍歷順序 * (即爲了更好地保存局部，並稍微簡化對調用iterator.remove的分割和遍歷的處理。 * 當在插入時使用比較器時，爲了保持跨從新平衡的總順序(或儘量接近這裏的要求)，咱們將類和identityhashcode做爲鏈接符進行比較。 * * 因爲LinkedHashMap子類的存在，普通vs樹模式之間的使用和轉換變得複雜。有關定義在插入、刪除和訪問時調用的回調方法， * 請參見下面，這些方法容許LinkedHashMap內部保持獨立於這些機制。(這還要求將map實例傳遞給一些可能建立新節點的實用程序方法。) * */ /** * 默認的初始化table的大小16，必須是2的整數次冪 */ static final int DEFAULT_INITIAL_CAPACITY = 1 << 4; // aka 16 /** * 最大容量大小，必須是小於1<<30的2的整數次冪 */ static final int MAXIMUM_CAPACITY = 1 << 30; /** * 默認的加載因子 */ static final float DEFAULT_LOAD_FACTOR = 0.75f; /** * 要想桶轉化爲樹形桶，則該桶中至少要有TREEIFY_THRESHOLD個元素。這個值必需要大於2，大於等於8最好 */ static final int TREEIFY_THRESHOLD = 8; /** * 當樹桶中的元素數量小於等於UNTREEIFY_THRESHOLD時，就須要將樹桶轉化爲鏈表 */ static final int UNTREEIFY_THRESHOLD = 6; /** * 想要桶轉爲樹桶所須要的最小桶數量，這個值應至少爲4 * TREEIFY_THRESHOLD，以免調整大小和treeification閾值之間的衝突。 * 若是桶數量小於這個值，就算桶中的元素已經達到了TREEIFY_THRESHOLD值，也只是經過resize來調整表中桶的個數 */ static final int MIN_TREEIFY_CAPACITY = 64; /** * 基本的桶節點，用於大多數entries（參見下面的TreeNode子類和LinkedHashMap中的Entry子類） */ static class Node<K,V> implements Map.Entry<K,V> { final int hash; final K key; V value; Node<K,V> next; Node(int hash, K key, V value, Node<K,V> next) { this.hash = hash; this.key = key; this.value = value; this.next = next; } public final K getKey() { return key; } public final V getValue() { return value; } public final String toString() { return key + "=" + value; } public final int hashCode() { return Objects.hashCode(key) ^ Objects.hashCode(value); } public final V setValue(V newValue) { V oldValue = value; value = newValue; return oldValue; } public final boolean equals(Object o) { if (o == this) return true; if (o instanceof Map.Entry) { Map.Entry<?,?> e = (Map.Entry<?,?>)o; if (Objects.equals(key, e.getKey()) && Objects.equals(value, e.getValue())) return true; } return false; } } /* ---------------- Static utilities -------------- */ /** * 計算key的hash值 * 當key爲null時，hash值爲0,不然hash值爲key的hashcode高16位和低16位進行異或運算 * * 爲何要這樣設計？ * 由於經過hashtable計算下標的方式i = (n - 1) & hash ，n爲table的桶的個數可知hash值的後幾位參與了運算。 * 設計者權衡了speed, utility, and quality，將高16位與低16位異或來減小這種影響。 * 考慮到如今的hashCode分佈的已經很不錯了，並且當發生較大碰撞時也用樹形存儲下降了衝突。 * 僅僅異或一下，既減小了系統的開銷，也不會形成的由於高位沒有參與下標的計算(table長度比較小時)，從而引發的碰撞。 */ static final int hash(Object key) { int h; return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16); } /** * Returns x's Class if it is of the form "class C implements * Comparable<C>", else null. */ static Class<?> comparableClassFor(Object x) { if (x instanceof Comparable) { Class<?> c; Type[] ts, as; Type t; ParameterizedType p; if ((c = x.getClass()) == String.class) // bypass checks return c; if ((ts = c.getGenericInterfaces()) != null) { for (int i = 0; i < ts.length; ++i) { if (((t = ts[i]) instanceof ParameterizedType) && ((p = (ParameterizedType)t).getRawType() == Comparable.class) && (as = p.getActualTypeArguments()) != null && as.length == 1 && as[0] == c) // type arg is c return c; } } } return null; } /** * 若是x不等於null且x的類對象爲kc則返回k.compareTo(x)的值，不然返回0。其中k是篩選過的可比較的類 */ @SuppressWarnings({"rawtypes","unchecked"}) // for cast to Comparable static int compareComparables(Class<?> kc, Object k, Object x) { return (x == null || x.getClass() != kc ? 0 : ((Comparable)k).compareTo(x)); } /** * 返回最近的不小於cap的2的整數次冪 * 爲何要cap-1？是爲了防止cap自己就是2的冪，最後獲得的結果是cap的兩倍，這樣就不是最近的不小於cap的2的整數次冪 * 下面的5個惟一操做是爲了將cap的最高位的1後面的全部位都置爲1，這樣獲得的結果確定是2的冪次方減1。 * 最後若是n已經大於最大的容量MAXIMUM_CAPACITY，那麼就取MAXIMUM_CAPACITY，不然將n+1，這樣就獲得了離cap最近的2的整數次冪 */ static final int tableSizeFor(int cap) { int n = cap - 1; n |= n >>> 1; n |= n >>> 2; n |= n >>> 4; n |= n >>> 8; n |= n >>> 16; return (n < 0) ? 1 : (n >= MAXIMUM_CAPACITY) ? MAXIMUM_CAPACITY : n + 1; } /* ---------------- Fields -------------- */ /** * HashMap底層的數組 */ transient Node<K,V>[] table; /** * Holds cached entrySet(). Note that AbstractMap fields are used * for keySet() and values(). */ transient Set<Map.Entry<K,V>> entrySet; /** * HashMap中鍵值對的個數 */ transient int size; /** * HashMap結構化修改的次數 */ transient int modCount; /** * HashMap須要擴容時，HashMap中鍵值對須要達到的容量，其值等於 當前容量*加載因子 */ int threshold; /** * 加載因子 */ final float loadFactor; /* ---------------- Public operations -------------- */ /** * 指定初始化容量和加載因子來構建HashMap對象 */ public HashMap(int initialCapacity, float loadFactor) { if (initialCapacity < 0) throw new IllegalArgumentException("Illegal initial capacity: " + initialCapacity); if (initialCapacity > MAXIMUM_CAPACITY) initialCapacity = MAXIMUM_CAPACITY; if (loadFactor <= 0 || Float.isNaN(loadFactor)) throw new IllegalArgumentException("Illegal load factor: " + loadFactor); this.loadFactor = loadFactor; this.threshold = tableSizeFor(initialCapacity);//直接先將threshold的大小table的size，後面resize方法就用到了 } /** * 指定容量建立HashMap，使用默認加載因子0.75 */ public HashMap(int initialCapacity) { this(initialCapacity, DEFAULT_LOAD_FACTOR); } /** * 使用默認容量16和默認加載因子0.75來建立HashMap對象 */ public HashMap() { this.loadFactor = DEFAULT_LOAD_FACTOR; // all other fields defaulted } /** * 利用其餘map來建立HashMap對象 */ public HashMap(Map<? extends K, ? extends V> m) { this.loadFactor = DEFAULT_LOAD_FACTOR; putMapEntries(m, false); } /** * 在調用putAll或者Map的構造方法時會用到 */ final void putMapEntries(Map<? extends K, ? extends V> m, boolean evict) { int s = m.size(); if (s > 0) { if (table == null) { // pre-size float ft = ((float)s / loadFactor) + 1.0F; int t = ((ft < (float)MAXIMUM_CAPACITY) ? (int)ft : MAXIMUM_CAPACITY); if (t > threshold) threshold = tableSizeFor(t); } else if (s > threshold) resize(); for (Map.Entry<? extends K, ? extends V> e : m.entrySet()) { K key = e.getKey(); V value = e.getValue(); putVal(hash(key), key, value, false, evict); } } } /** * 返回HashMap中鍵值對的個數 */ public int size() { return size; } /** * 判斷是否爲空 */ public boolean isEmpty() { return size == 0; } /** * 經過key獲取value */ public V get(Object key) { Node<K,V> e; return (e = getNode(hash(key), key)) == null ? null : e.value; } /** * 經過key和key的 hash值來獲取Node，供get、containsKey等方法調用 * 能夠看出是經過(n - 1) & hash來肯定桶的位置 */ final Node<K,V> getNode(int hash, Object key) { Node<K,V>[] tab; Node<K,V> first, e; int n; K k; if ((tab = table) != null && (n = tab.length) > 0 && (first = tab[(n - 1) & hash]) != null) { if (first.hash == hash && //判斷桶的第一個節點就是要找的節點 ((k = first.key) == key || (key != null && key.equals(k)))) return first; if ((e = first.next) != null) {//若是第一個節點後面還有節點就往下找 if (first instanceof TreeNode)//若是第一個節點是樹節點就用樹的方式去查找 return ((TreeNode<K,V>)first).getTreeNode(hash, key); do {//若是不是樹節點，那麼就是鏈表節點，就直接循環遍歷 if (e.hash == hash && ((k = e.key) == key || (key != null && key.equals(k)))) return e; } while ((e = e.next) != null); } } return null; } /** * 判斷是否存在該key */ public boolean containsKey(Object key) { return getNode(hash(key), key) != null; } /** * 新增鍵值對，無論key是否已經存在 */ public V put(K key, V value) { return putVal(hash(key), key, value, false, true); } /** * 新增鍵值對 * hash 是key調用hash方法獲得的值 * key 是鍵 * value 是值 * onlyIfAbsent 是否只有在key不存在的狀況下覆蓋原來的value false表示覆蓋 */ final V putVal(int hash, K key, V value, boolean onlyIfAbsent, boolean evict) { Node<K,V>[] tab; Node<K,V> p; int n, i; if ((tab = table) == null || (n = tab.length) == 0)//若是table爲null或者空，調用resize方法進行初始化 n = (tab = resize()).length; //建立一個Node數組，長度爲DEFAULT_INITIAL_CAPACITY，threshold爲DEFAULT_INITIAL_CAPACITY * loadFactor if ((p = tab[i = (n - 1) & hash]) == null) //若是經過計算出來的下標處沒有節點，就建立一個節點添加到table的該下標處，p爲該下標處的第一個節點 tab[i] = newNode(hash, key, value, null); else {//該下標已經存在節點，就須要找到該節點 Node<K,V> e; K k;//e爲要找的節點，k爲要找到的節點的key if (p.hash == hash && ((k = p.key) == key || (key != null && key.equals(k))))//若是該下標的第一個節點就是要找的節點 e = p; else if (p instanceof TreeNode)//若是第一個節點是樹節點，則須要在樹裏面進行添加 e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value); else {//若是是鏈表 for (int binCount = 0; ; ++binCount) { if ((e = p.next) == null) {//若是鏈表中沒有key相同node存在，就根據key、value建立一個node，而後添加在鏈表的結尾 p.next = newNode(hash, key, value, null); if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st treeifyBin(tab, hash);//若是整個鏈表的長度大於等於8了，就須要將鏈表轉爲樹結構 break; } if (e.hash == hash && ((k = e.key) == key || (key != null && key.equals(k))))//若是找到了key相同的node結束循環。 break; p = e; } } if (e != null) { // existing mapping for key 確實找到了key相同的node V oldValue = e.value; if (!onlyIfAbsent || oldValue == null)//onlyIfAbsent == false 或者oldValue == null時對原來的 值進行覆蓋 e.value = value; afterNodeAccess(e);//提供一個回調方法沒有實現 return oldValue; } } ++modCount; if (++size > threshold)//若是添加後的元素個數大於threshold的值，則對hash表進行resize操做 resize(); afterNodeInsertion(evict);//回調方法沒有實現 return null; } /** * 初始化或者將table的大小翻倍 ，若是table爲null就按照默認的初始值DEFAULT_INITIAL_CAPACITY分配容量 * 另外、因爲咱們是將table的大小以2的冪形式進行擴展（變爲原來的兩倍），因此原來的節點必須保持在原來的索引，或者在新的 table中以2的冪偏移量移動 */ final Node<K,V>[] resize() { Node<K,V>[] oldTab = table; int oldCap = (oldTab == null) ? 0 : oldTab.length; int oldThr = threshold; int newCap, newThr = 0; if (oldCap > 0) {//若是之前的table長度大於0 if (oldCap >= MAXIMUM_CAPACITY) {//若是table長度大於等於MAXIMUM_CAPACITY,直接將存儲極限設置爲int的最大值 threshold = Integer.MAX_VALUE; return oldTab; } //若是table的長度小於MAXIMUM_CAPACITY而且大於DEFAULT_INITIAL_CAPACITY，就想table長度和存儲極限都翻倍 else if ((newCap = oldCap << 1) < MAXIMUM_CAPACITY && oldCap >= DEFAULT_INITIAL_CAPACITY) newThr = oldThr << 1; // double threshold } else if (oldThr > 0) //建立HashMap的時候若是調用的是有參構造函數，容量就爲計算的存儲極限（在有參構造方法中就直接將threshold的 值設置爲cap的值） newCap = oldThr; else {//用默認的構造方法建立HashMap，table的大小和存儲極限都爲默認值 newCap = DEFAULT_INITIAL_CAPACITY; newThr = (int)(DEFAULT_LOAD_FACTOR * DEFAULT_INITIAL_CAPACITY); } if (newThr == 0) {//因爲用有參構造函數建立的對象threshold的值實際上是cap因此要從新計算一下threshold的值 float ft = (float)newCap * loadFactor; newThr = (newCap < MAXIMUM_CAPACITY && ft < (float)MAXIMUM_CAPACITY ? (int)ft : Integer.MAX_VALUE); } threshold = newThr;//將存儲極限設置爲新值，並根據新的容量大小來建立新的table @SuppressWarnings({"rawtypes","unchecked"}) Node<K,V>[] newTab = (Node<K,V>[])new Node[newCap]; table = newTab; if (oldTab != null) {//若是原來的table已經存在，要將原來的Node從新安排位置 for (int j = 0; j < oldCap; ++j) { Node<K,V> e; if ((e = oldTab[j]) != null) { oldTab[j] = null;//先將原來的table該位置的值設置爲null if (e.next == null)//若是該下標處只有一個節點，則從新計算該節點的下標並賦值 newTab[e.hash & (newCap - 1)] = e; else if (e instanceof TreeNode)//若是該下標的節點是樹節點 ((TreeNode<K,V>)e).split(this, newTab, j, oldCap); else { //各個節點若是是鏈表形式存儲，那麼就經過e.hash & oldCap)是否等於0來將原來的鏈表分爲兩個鏈表 //算法很是巧妙 Node<K,V> loHead = null, loTail = null; Node<K,V> hiHead = null, hiTail = null; Node<K,V> next; do { next = e.next; if ((e.hash & oldCap) == 0) { if (loTail == null) loHead = e; else loTail.next = e; loTail = e; } else { if (hiTail == null) hiHead = e; else hiTail.next = e; hiTail = e; } } while ((e = next) != null); if (loTail != null) {//其中lo這個鏈表仍是放在原來的下標處， loTail.next = null; newTab[j] = loHead; } if (hiTail != null) {//hi鏈表放在（原來的下標+原來的cap） hiTail.next = null; newTab[j + oldCap] = hiHead; } } } } } return newTab; } /** * 將桶轉化爲樹結構 */ final void treeifyBin(Node<K,V>[] tab, int hash) { int n, index; Node<K,V> e; if (tab == null || (n = tab.length) < MIN_TREEIFY_CAPACITY) resize(); else if ((e = tab[index = (n - 1) & hash]) != null) { TreeNode<K,V> hd = null, tl = null; do { TreeNode<K,V> p = replacementTreeNode(e, null); if (tl == null) hd = p; else { p.prev = tl; tl.next = p; } tl = p; } while ((e = e.next) != null); if ((tab[index] = hd) != null) hd.treeify(tab); } } /** * 將map中的全部鍵值對插入到Map中 */ public void putAll(Map<? extends K, ? extends V> m) { putMapEntries(m, true); } /** * 刪除key對應的節點 */ public V remove(Object key) { Node<K,V> e; return (e = removeNode(hash(key), key, null, false, true)) == null ? null : e.value; } /** * Map.remove 和相關方法的 實現 * hash 是key的hash值 * key 爲key * value 爲value，主要是爲了matchValue使用 * matchValue 若是爲 true則只能在value也匹配的 時候才能移除 * movable 若是爲false，移除了該Node不會移動其餘節點 * */ final Node<K,V> removeNode(int hash, Object key, Object value, boolean matchValue, boolean movable) { Node<K,V>[] tab; Node<K,V> p; int n, index;//Node用來存儲找到的節點 if ((tab = table) != null && (n = tab.length) > 0 && (p = tab[index = (n - 1) & hash]) != null) {//table 不爲null，table不爲空，而且key對應的下標也有節點存在，才進行下一步 Node<K,V> node = null, e; K k; V v; if (p.hash == hash && ((k = p.key) == key || (key != null && key.equals(k)))) node = p;//若是該桶的第一個節點就是要找的節點 else if ((e = p.next) != null) { if (p instanceof TreeNode)//若是桶爲樹結構 node = ((TreeNode<K,V>)p).getTreeNode(hash, key); else {//若是是鏈表就循環遍歷查找 do { if (e.hash == hash && ((k = e.key) == key || (key != null && key.equals(k)))) { node = e; break; } p = e; } while ((e = e.next) != null); } } if (node != null && (!matchValue || (v = node.value) == value || (value != null && value.equals(v)))) {//若是找到了該節點 if (node instanceof TreeNode)//樹形結構的刪除 ((TreeNode<K,V>)node).removeTreeNode(this, tab, movable); else if (node == p)//若是是鏈表的第一個節點 tab[index] = node.next; else//若是是鏈表的其餘節點 p.next = node.next; ++modCount; --size; afterNodeRemoval(node);//回調方法 return node; } } return null; } /** * 清空整個HashMap */ public void clear() { Node<K,V>[] tab; modCount++; if ((tab = table) != null && size > 0) { size = 0; for (int i = 0; i < tab.length; ++i) tab[i] = null; } } /** * 直接遍歷而後查找 value值是否存在 */ public boolean containsValue(Object value) { Node<K,V>[] tab; V v; if ((tab = table) != null && size > 0) { for (int i = 0; i < tab.length; ++i) { for (Node<K,V> e = tab[i]; e != null; e = e.next) { if ((v = e.value) == value || (value != null && value.equals(v))) return true; } } } return false; } /** * 返回包含HashMap中鍵的Set集合，對HashMap的修改結果會反饋到Set中，反之亦然。 * 若是在對集合進行迭代的時候修改了HashMap（除了迭代器本身的 remove操做），迭代結果是未定義的 * 迭代器不支持add和addAll操做 */ public Set<K> keySet() { Set<K> ks = keySet; if (ks == null) { ks = new KeySet(); keySet = ks; } return ks; } final class KeySet extends AbstractSet<K> { public final int size() { return size; } public final void clear() { HashMap.this.clear(); } public final Iterator<K> iterator() { return new KeyIterator(); } public final boolean contains(Object o) { return containsKey(o); } public final boolean remove(Object key) { return removeNode(hash(key), key, null, false, true) != null; } public final Spliterator<K> spliterator() { return new KeySpliterator<>(HashMap.this, 0, -1, 0, 0); } public final void forEach(Consumer<? super K> action) { Node<K,V>[] tab; if (action == null) throw new NullPointerException(); if (size > 0 && (tab = table) != null) { int mc = modCount; for (int i = 0; i < tab.length; ++i) { for (Node<K,V> e = tab[i]; e != null; e = e.next) action.accept(e.key); } if (modCount != mc) throw new ConcurrentModificationException(); } } } /** * 和上面的KeySet同樣，這個是獲取Map中全部的value集合 * 一樣對HashMap的修改也會反應到該集合上 */ public Collection<V> values() { Collection<V> vs = values; if (vs == null) { vs = new Values(); values = vs; } return vs; } final class Values extends AbstractCollection<V> { public final int size() { return size; } public final void clear() { HashMap.this.clear(); } public final Iterator<V> iterator() { return new ValueIterator(); } public final boolean contains(Object o) { return containsValue(o); } public final Spliterator<V> spliterator() { return new ValueSpliterator<>(HashMap.this, 0, -1, 0, 0); } public final void forEach(Consumer<? super V> action) { Node<K,V>[] tab; if (action == null) throw new NullPointerException(); if (size > 0 && (tab = table) != null) { int mc = modCount; for (int i = 0; i < tab.length; ++i) { for (Node<K,V> e = tab[i]; e != null; e = e.next) action.accept(e.value); } if (modCount != mc) throw new ConcurrentModificationException(); } } } /** * 返回HashMap中鍵值對集合，一樣對HashMap的改變也會反應到集合上。反之亦然。 * 若是在對集合進行迭代時修改HashMap(除了經過迭代器本身的刪除操做，或者經過迭代器返回的映射條目上的setValue操做)，迭代的結果是未定義的。 * 集合支持元素刪除，元素刪除經過迭代器.remove, set從映射中刪除對應的映射。它不支持add或addAll操做。 * */ public Set<Map.Entry<K,V>> entrySet() { Set<Map.Entry<K,V>> es; return (es = entrySet) == null ? (entrySet = new EntrySet()) : es; } final class EntrySet extends AbstractSet<Map.Entry<K,V>> { public final int size() { return size; } public final void clear() { HashMap.this.clear(); } public final Iterator<Map.Entry<K,V>> iterator() { return new EntryIterator(); } public final boolean contains(Object o) { if (!(o instanceof Map.Entry)) return false; Map.Entry<?,?> e = (Map.Entry<?,?>) o; Object key = e.getKey(); Node<K,V> candidate = getNode(hash(key), key); return candidate != null && candidate.equals(e); } public final boolean remove(Object o) { if (o instanceof Map.Entry) { Map.Entry<?,?> e = (Map.Entry<?,?>) o; Object key = e.getKey(); Object value = e.getValue(); return removeNode(hash(key), key, value, true, true) != null; } return false; } public final Spliterator<Map.Entry<K,V>> spliterator() { return new EntrySpliterator<>(HashMap.this, 0, -1, 0, 0); } public final void forEach(Consumer<? super Map.Entry<K,V>> action) { Node<K,V>[] tab; if (action == null) throw new NullPointerException(); if (size > 0 && (tab = table) != null) { int mc = modCount; for (int i = 0; i < tab.length; ++i) { for (Node<K,V> e = tab[i]; e != null; e = e.next) action.accept(e); } if (modCount != mc) throw new ConcurrentModificationException(); } } } // Overrides of JDK8 Map extension methods 重寫JDK8的擴展方法 //返回key對應的value，若是沒有就返回defaultValue @Override public V getOrDefault(Object key, V defaultValue) { Node<K,V> e; return (e = getNode(hash(key), key)) == null ? defaultValue : e.value; } //添加鍵值對，若是key已經存在，不覆蓋 @Override public V putIfAbsent(K key, V value) { return putVal(hash(key), key, value, true, true); } //要key和value都相等纔會刪除節點，而且將後面的節點往前移動（爭對樹桶） @Override public boolean remove(Object key, Object value) { return removeNode(hash(key), key, value, true, true) != null; } //只有在key和oldValue和HashMap中的徹底相同的時候，纔會用newValue來替換oldValue @Override public boolean replace(K key, V oldValue, V newValue) { Node<K,V> e; V v; if ((e = getNode(hash(key), key)) != null && ((v = e.value) == oldValue || (v != null && v.equals(oldValue)))) { e.value = newValue; afterNodeAccess(e); return true; } return false; } //用value替換原來的值 @Override public V replace(K key, V value) { Node<K,V> e; if ((e = getNode(hash(key), key)) != null) { V oldValue = e.value; e.value = value; afterNodeAccess(e); return oldValue; } return null; } /**若是key對應的value爲null或者key不存在，就將key和用function計算出來value做爲鍵值對保存起來 * map.computeIfAbsent("12", k -> k+"a") 若是12不存在或者value爲null，就將12a做爲value */ @Override public V computeIfAbsent(K key, Function<? super K, ? extends V> mappingFunction) { if (mappingFunction == null) throw new NullPointerException(); int hash = hash(key); Node<K,V>[] tab; Node<K,V> first; int n, i; int binCount = 0; TreeNode<K,V> t = null; Node<K,V> old = null; if (size > threshold || (tab = table) == null || (n = tab.length) == 0) n = (tab = resize()).length; if ((first = tab[i = (n - 1) & hash]) != null) { if (first instanceof TreeNode) old = (t = (TreeNode<K,V>)first).getTreeNode(hash, key); else { Node<K,V> e = first; K k; do { if (e.hash == hash && ((k = e.key) == key || (key != null && key.equals(k)))) { old = e; break; } ++binCount; } while ((e = e.next) != null); } V oldValue; if (old != null && (oldValue = old.value) != null) { afterNodeAccess(old); return oldValue; } } V v = mappingFunction.apply(key); if (v == null) { return null; } else if (old != null) { old.value = v; afterNodeAccess(old); return v; } else if (t != null) t.putTreeVal(this, tab, hash, key, v); else { tab[i] = newNode(hash, key, v, first); if (binCount >= TREEIFY_THRESHOLD - 1) treeifyBin(tab, hash); } ++modCount; ++size; afterNodeInsertion(true); return v; } /** * 若是key存在（key爲null也算存在）且value值不爲null的時候，對key-value進行替換 * map.computeIfPresent("12", (k,v) -> v+"a"); */ public V computeIfPresent(K key, BiFunction<? super K, ? super V, ? extends V> remappingFunction) { if (remappingFunction == null) throw new NullPointerException(); Node<K,V> e; V oldValue; int hash = hash(key); if ((e = getNode(hash, key)) != null && (oldValue = e.value) != null) { V v = remappingFunction.apply(key, oldValue); if (v != null) { e.value = v; afterNodeAccess(e); return v; } else removeNode(hash, key, null, false, true); } return null; } /** * 無論key是否存在，也無論value是否爲null，都要替換value * hashMap.compute("13", (k,v) -> k+'a'); */ @Override public V compute(K key, BiFunction<? super K, ? super V, ? extends V> remappingFunction) { if (remappingFunction == null) throw new NullPointerException(); int hash = hash(key); Node<K,V>[] tab; Node<K,V> first; int n, i; int binCount = 0; TreeNode<K,V> t = null; Node<K,V> old = null; if (size > threshold || (tab = table) == null || (n = tab.length) == 0) n = (tab = resize()).length; if ((first = tab[i = (n - 1) & hash]) != null) { if (first instanceof TreeNode) old = (t = (TreeNode<K,V>)first).getTreeNode(hash, key); else { Node<K,V> e = first; K k; do { if (e.hash == hash && ((k = e.key) == key || (key != null && key.equals(k)))) { old = e; break; } ++binCount; } while ((e = e.next) != null); } } V oldValue = (old == null) ? null : old.value; V v = remappingFunction.apply(key, oldValue); if (old != null) { if (v != null) { old.value = v; afterNodeAccess(old); } else removeNode(hash, key, null, false, true); } else if (v != null) { if (t != null) t.putTreeVal(this, tab, hash, key, v); else { tab[i] = newNode(hash, key, v, first); if (binCount >= TREEIFY_THRESHOLD - 1) treeifyBin(tab, hash); } ++modCount; ++size; afterNodeInsertion(true); } return v; } /** * 若是key不存在或者value爲null，就將value賦值給鍵值對 * 若是key存在且value不爲null，就經過後面的表達式來計算出新的value * 若是最後U計算出來的value值爲null，就將key刪除 * map.merge("12", "b", (v1,v2) -> v1+v2) */ @Override public V merge(K key, V value, BiFunction<? super V, ? super V, ? extends V> remappingFunction) { if (value == null) throw new NullPointerException(); if (remappingFunction == null) throw new NullPointerException(); int hash = hash(key); Node<K,V>[] tab; Node<K,V> first; int n, i; int binCount = 0; TreeNode<K,V> t = null; Node<K,V> old = null; if (size > threshold || (tab = table) == null || (n = tab.length) == 0) n = (tab = resize()).length; if ((first = tab[i = (n - 1) & hash]) != null) { if (first instanceof TreeNode) old = (t = (TreeNode<K,V>)first).getTreeNode(hash, key); else { Node<K,V> e = first; K k; do { if (e.hash == hash && ((k = e.key) == key || (key != null && key.equals(k)))) { old = e; break; } ++binCount; } while ((e = e.next) != null); } } if (old != null) { V v; if (old.value != null) v = remappingFunction.apply(old.value, value); else v = value; if (v != null) { old.value = v; afterNodeAccess(old); } else removeNode(hash, key, null, false, true); return v; } if (value != null) { if (t != null) t.putTreeVal(this, tab, hash, key, value); else { tab[i] = newNode(hash, key, value, first); if (binCount >= TREEIFY_THRESHOLD - 1) treeifyBin(tab, hash); } ++modCount; ++size; afterNodeInsertion(true); } return value; } /** * 循環遍歷HashMap，而後執行括號中的方法 * map.forEach((k,v) -> System.out.println(k+"-"+v)); */ @Override public void forEach(BiConsumer<? super K, ? super V> action) { Node<K,V>[] tab; if (action == null) throw new NullPointerException(); if (size > 0 && (tab = table) != null) { int mc = modCount; for (int i = 0; i < tab.length; ++i) { for (Node<K,V> e = tab[i]; e != null; e = e.next) action.accept(e.key, e.value); } if (modCount != mc) throw new ConcurrentModificationException(); } } /** * 經過括號中的表達式來匹配鍵值對，並將返回值替換原來的value * hashMap.replaceAll((k,v) -> { * if(Integer.parseInt(k)>=10){ * v = v+"a"; * } * return v; * }); *若是k的值大於等於10，就在value後面加a */ @Override public void replaceAll(BiFunction<? super K, ? super V, ? extends V> function) { Node<K,V>[] tab; if (function == null) throw new NullPointerException(); if (size > 0 && (tab = table) != null) { int mc = modCount; for (int i = 0; i < tab.length; ++i) { for (Node<K,V> e = tab[i]; e != null; e = e.next) { e.value = function.apply(e.key, e.value); } } if (modCount != mc) throw new ConcurrentModificationException(); } } /* ------------------------------------------------------------ */ // Cloning and serialization /** * 淺克隆 */ @SuppressWarnings("unchecked") @Override public Object clone() { HashMap<K,V> result; try { result = (HashMap<K,V>)super.clone(); } catch (CloneNotSupportedException e) { // this shouldn't happen, since we are Cloneable throw new InternalError(e); } result.reinitialize(); result.putMapEntries(this, false); return result; } // These methods are also used when serializing HashSets final float loadFactor() { return loadFactor; } final int capacity() { return (table != null) ? table.length : (threshold > 0) ? threshold : DEFAULT_INITIAL_CAPACITY; } /** * 將HashMap寫入流中年 */ private void writeObject(java.io.ObjectOutputStream s) throws IOException { int buckets = capacity(); // Write out the threshold, loadfactor, and any hidden stuff s.defaultWriteObject(); s.writeInt(buckets); s.writeInt(size); internalWriteEntries(s); } /** * 從流中讀取HashMap對象 */ private void readObject(java.io.ObjectInputStream s) throws IOException, ClassNotFoundException { // Read in the threshold (ignored), loadfactor, and any hidden stuff s.defaultReadObject(); reinitialize(); if (loadFactor <= 0 || Float.isNaN(loadFactor)) throw new InvalidObjectException("Illegal load factor: " + loadFactor); s.readInt(); // Read and ignore number of buckets int mappings = s.readInt(); // Read number of mappings (size) if (mappings < 0) throw new InvalidObjectException("Illegal mappings count: " + mappings); else if (mappings > 0) { // (if zero, use defaults) // Size the table using given load factor only if within // range of 0.25...4.0 float lf = Math.min(Math.max(0.25f, loadFactor), 4.0f); float fc = (float)mappings / lf + 1.0f; int cap = ((fc < DEFAULT_INITIAL_CAPACITY) ? DEFAULT_INITIAL_CAPACITY : (fc >= MAXIMUM_CAPACITY) ? MAXIMUM_CAPACITY : tableSizeFor((int)fc)); float ft = (float)cap * lf; threshold = ((cap < MAXIMUM_CAPACITY && ft < MAXIMUM_CAPACITY) ? (int)ft : Integer.MAX_VALUE); @SuppressWarnings({"rawtypes","unchecked"}) Node<K,V>[] tab = (Node<K,V>[])new Node[cap]; table = tab; // Read the keys and values, and put the mappings in the HashMap for (int i = 0; i < mappings; i++) { @SuppressWarnings("unchecked") K key = (K) s.readObject(); @SuppressWarnings("unchecked") V value = (V) s.readObject(); putVal(hash(key), key, value, false, false); } } } /* ------------------------------------------------------------ */ // iterators 迭代器 abstract class HashIterator { Node<K,V> next; // next entry to return Node<K,V> current; // current entry int expectedModCount; // for fast-fail int index; // current slot HashIterator() { expectedModCount = modCount; Node<K,V>[] t = table; current = next = null; index = 0; if (t != null && size > 0) { // advance to first entry do {} while (index < t.length && (next = t[index++]) == null); } } public final boolean hasNext() { return next != null; } final Node<K,V> nextNode() { Node<K,V>[] t; Node<K,V> e = next; if (modCount != expectedModCount) throw new ConcurrentModificationException(); if (e == null) throw new NoSuchElementException(); if ((next = (current = e).next) == null && (t = table) != null) { do {} while (index < t.length && (next = t[index++]) == null); } return e; } public final void remove() { Node<K,V> p = current; if (p == null) throw new IllegalStateException(); if (modCount != expectedModCount) throw new ConcurrentModificationException(); current = null; K key = p.key; removeNode(hash(key), key, null, false, false); expectedModCount = modCount; } } final class KeyIterator extends HashIterator implements Iterator<K> { public final K next() { return nextNode().key; } } final class ValueIterator extends HashIterator implements Iterator<V> { public final V next() { return nextNode().value; } } final class EntryIterator extends HashIterator implements Iterator<Map.Entry<K,V>> { public final Map.Entry<K,V> next() { return nextNode(); } } /* ------------------------------------------------------------ */ // spliterators 用多線程來並行迭代的迭代器，將整個HashMap分割成多個部分，而後分別迭代 //下面的KeySpliterator，ValueSpliterator，EntrySpliterator同理 static class HashMapSpliterator<K,V> { final HashMap<K,V> map; Node<K,V> current; // current node int index; // current index, modified on advance/split int fence; // one past last index int est; // size estimate int expectedModCount; // for comodification checks HashMapSpliterator(HashMap<K,V> m, int origin, int fence, int est, int expectedModCount) { this.map = m; this.index = origin; this.fence = fence; this.est = est; this.expectedModCount = expectedModCount; } final int getFence() { // initialize fence and size on first use int hi; if ((hi = fence) < 0) { HashMap<K,V> m = map; est = m.size; expectedModCount = m.modCount; Node<K,V>[] tab = m.table; hi = fence = (tab == null) ? 0 : tab.length; } return hi; } public final long estimateSize() { getFence(); // force init return (long) est; } } static final class KeySpliterator<K,V> extends HashMapSpliterator<K,V> implements Spliterator<K> { KeySpliterator(HashMap<K,V> m, int origin, int fence, int est, int expectedModCount) { super(m, origin, fence, est, expectedModCount); } public KeySpliterator<K,V> trySplit() { int hi = getFence(), lo = index, mid = (lo + hi) >>> 1; return (lo >= mid || current != null) ? null : new KeySpliterator<>(map, lo, index = mid, est >>>= 1, expectedModCount); } public void forEachRemaining(Consumer<? super K> action) { int i, hi, mc; if (action == null) throw new NullPointerException(); HashMap<K,V> m = map; Node<K,V>[] tab = m.table; if ((hi = fence) < 0) { mc = expectedModCount = m.modCount; hi = fence = (tab == null) ? 0 : tab.length; } else mc = expectedModCount; if (tab != null && tab.length >= hi && (i = index) >= 0 && (i < (index = hi) || current != null)) { Node<K,V> p = current; current = null; do { if (p == null) p = tab[i++]; else { action.accept(p.key); p = p.next; } } while (p != null || i < hi); if (m.modCount != mc) throw new ConcurrentModificationException(); } } public boolean tryAdvance(Consumer<? super K> action) { int hi; if (action == null) throw new NullPointerException(); Node<K,V>[] tab = map.table; if (tab != null && tab.length >= (hi = getFence()) && index >= 0) { while (current != null || index < hi) { if (current == null) current = tab[index++]; else { K k = current.key; current = current.next; action.accept(k); if (map.modCount != expectedModCount) throw new ConcurrentModificationException(); return true; } } } return false; } public int characteristics() { return (fence < 0 || est == map.size ? Spliterator.SIZED : 0) | Spliterator.DISTINCT; } } static final class ValueSpliterator<K,V> extends HashMapSpliterator<K,V> implements Spliterator<V> { ValueSpliterator(HashMap<K,V> m, int origin, int fence, int est, int expectedModCount) { super(m, origin, fence, est, expectedModCount); } public ValueSpliterator<K,V> trySplit() { int hi = getFence(), lo = index, mid = (lo + hi) >>> 1; return (lo >= mid || current != null) ? null : new ValueSpliterator<>(map, lo, index = mid, est >>>= 1, expectedModCount); } public void forEachRemaining(Consumer<? super V> action) { int i, hi, mc; if (action == null) throw new NullPointerException(); HashMap<K,V> m = map; Node<K,V>[] tab = m.table; if ((hi = fence) < 0) { mc = expectedModCount = m.modCount; hi = fence = (tab == null) ? 0 : tab.length; } else mc = expectedModCount; if (tab != null && tab.length >= hi && (i = index) >= 0 && (i < (index = hi) || current != null)) { Node<K,V> p = current; current = null; do { if (p == null) p = tab[i++]; else { action.accept(p.value); p = p.next; } } while (p != null || i < hi); if (m.modCount != mc) throw new ConcurrentModificationException(); } } public boolean tryAdvance(Consumer<? super V> action) { int hi; if (action == null) throw new NullPointerException(); Node<K,V>[] tab = map.table; if (tab != null && tab.length >= (hi = getFence()) && index >= 0) { while (current != null || index < hi) { if (current == null) current = tab[index++]; else { V v = current.value; current = current.next; action.accept(v); if (map.modCount != expectedModCount) throw new ConcurrentModificationException(); return true; } } } return false; } public int characteristics() { return (fence < 0 || est == map.size ? Spliterator.SIZED : 0); } } static final class EntrySpliterator<K,V> extends HashMapSpliterator<K,V> implements Spliterator<Map.Entry<K,V>> { EntrySpliterator(HashMap<K,V> m, int origin, int fence, int est, int expectedModCount) { super(m, origin, fence, est, expectedModCount); } public EntrySpliterator<K,V> trySplit() { int hi = getFence(), lo = index, mid = (lo + hi) >>> 1; return (lo >= mid || current != null) ? null : new EntrySpliterator<>(map, lo, index = mid, est >>>= 1, expectedModCount); } public void forEachRemaining(Consumer<? super Map.Entry<K,V>> action) { int i, hi, mc; if (action == null) throw new NullPointerException(); HashMap<K,V> m = map; Node<K,V>[] tab = m.table; if ((hi = fence) < 0) { mc = expectedModCount = m.modCount; hi = fence = (tab == null) ? 0 : tab.length; } else mc = expectedModCount; if (tab != null && tab.length >= hi && (i = index) >= 0 && (i < (index = hi) || current != null)) { Node<K,V> p = current; current = null; do { if (p == null) p = tab[i++]; else { action.accept(p); p = p.next; } } while (p != null || i < hi); if (m.modCount != mc) throw new ConcurrentModificationException(); } } public boolean tryAdvance(Consumer<? super Map.Entry<K,V>> action) { int hi; if (action == null) throw new NullPointerException(); Node<K,V>[] tab = map.table; if (tab != null && tab.length >= (hi = getFence()) && index >= 0) { while (current != null || index < hi) { if (current == null) current = tab[index++]; else { Node<K,V> e = current; current = current.next; action.accept(e); if (map.modCount != expectedModCount) throw new ConcurrentModificationException(); return true; } } } return false; } public int characteristics() { return (fence < 0 || est == map.size ? Spliterator.SIZED : 0) | Spliterator.DISTINCT; } } /* ------------------------------------------------------------ */ // LinkedHashMap support 對於LinkedHashMapde 支持 /* * 如下受包保護的方法被設計爲可由LinkedHashMap覆蓋，但不被任何其餘子類覆蓋。 * 幾乎全部其餘內部方法也受包保護，但都聲明爲final，因此LinkedHashMap、視圖類和HashSet均可以使用這些方法 * */ // Create a regular (non-tree) node Node<K,V> newNode(int hash, K key, V value, Node<K,V> next) { return new Node<>(hash, key, value, next); } // For conversion from TreeNodes to plain nodes Node<K,V> replacementNode(Node<K,V> p, Node<K,V> next) { return new Node<>(p.hash, p.key, p.value, next); } // Create a tree bin node TreeNode<K,V> newTreeNode(int hash, K key, V value, Node<K,V> next) { return new TreeNode<>(hash, key, value, next); } // For treeifyBin TreeNode<K,V> replacementTreeNode(Node<K,V> p, Node<K,V> next) { return new TreeNode<>(p.hash, p.key, p.value, next); } /** * Reset to initial default state. Called by clone and readObject. */ void reinitialize() { table = null; entrySet = null; keySet = null; values = null; modCount = 0; threshold = 0; size = 0; } // Callbacks to allow LinkedHashMap post-actions void afterNodeAccess(Node<K,V> p) { } void afterNodeInsertion(boolean evict) { } void afterNodeRemoval(Node<K,V> p) { } // Called only from writeObject, to ensure compatible ordering. void internalWriteEntries(java.io.ObjectOutputStream s) throws IOException { Node<K,V>[] tab; if (size > 0 && (tab = table) != null) { for (int i = 0; i < tab.length; ++i) { for (Node<K,V> e = tab[i]; e != null; e = e.next) { s.writeObject(e.key); s.writeObject(e.value); } } } } /* ------------------------------------------------------------ */ // Tree bins 下面的是樹結點相關的一些代碼，比較難懂，之後再分析 /** * Entry for Tree bins. Extends LinkedHashMap.Entry (which in turn * extends Node) so can be used as extension of either regular or * linked node. */ static final class TreeNode<K,V> extends LinkedHashMap.Entry<K,V> { TreeNode<K,V> parent; // red-black tree links TreeNode<K,V> left; TreeNode<K,V> right; TreeNode<K,V> prev; // needed to unlink next upon deletion boolean red; TreeNode(int hash, K key, V val, Node<K,V> next) { super(hash, key, val, next); } /** * Returns root of tree containing this node. */ final TreeNode<K,V> root() { for (TreeNode<K,V> r = this, p;;) { if ((p = r.parent) == null) return r; r = p; } } /** * Ensures that the given root is the first node of its bin. */ static <K,V> void moveRootToFront(Node<K,V>[] tab, TreeNode<K,V> root) { int n; if (root != null && tab != null && (n = tab.length) > 0) { int index = (n - 1) & root.hash; TreeNode<K,V> first = (TreeNode<K,V>)tab[index]; if (root != first) { Node<K,V> rn; tab[index] = root; TreeNode<K,V> rp = root.prev; if ((rn = root.next) != null) ((TreeNode<K,V>)rn).prev = rp; if (rp != null) rp.next = rn; if (first != null) first.prev = root; root.next = first; root.prev = null; } assert checkInvariants(root); } } /** * Finds the node starting at root p with the given hash and key. * The kc argument caches comparableClassFor(key) upon first use * comparing keys. */ final TreeNode<K,V> find(int h, Object k, Class<?> kc) { TreeNode<K,V> p = this; do { int ph, dir; K pk; TreeNode<K,V> pl = p.left, pr = p.right, q; if ((ph = p.hash) > h) p = pl; else if (ph < h) p = pr; else if ((pk = p.key) == k || (k != null && k.equals(pk))) return p; else if (pl == null) p = pr; else if (pr == null) p = pl; else if ((kc != null || (kc = comparableClassFor(k)) != null) && (dir = compareComparables(kc, k, pk)) != 0) p = (dir < 0) ? pl : pr; else if ((q = pr.find(h, k, kc)) != null) return q; else p = pl; } while (p != null); return null; } /** * Calls find for root node. */ final TreeNode<K,V> getTreeNode(int h, Object k) { return ((parent != null) ? root() : this).find(h, k, null); } /** * Tie-breaking utility for ordering insertions when equal * hashCodes and non-comparable. We don't require a total * order, just a consistent insertion rule to maintain * equivalence across rebalancings. Tie-breaking further than * necessary simplifies testing a bit. */ static int tieBreakOrder(Object a, Object b) { int d; if (a == null || b == null || (d = a.getClass().getName(). compareTo(b.getClass().getName())) == 0) d = (System.identityHashCode(a) <= System.identityHashCode(b) ? -1 : 1); return d; } /** * Forms tree of the nodes linked from this node. * @return root of tree */ final void treeify(Node<K,V>[] tab) { TreeNode<K,V> root = null; for (TreeNode<K,V> x = this, next; x != null; x = next) { next = (TreeNode<K,V>)x.next; x.left = x.right = null; if (root == null) { x.parent = null; x.red = false; root = x; } else { K k = x.key; int h = x.hash; Class<?> kc = null; for (TreeNode<K,V> p = root;;) { int dir, ph; K pk = p.key; if ((ph = p.hash) > h) dir = -1; else if (ph < h) dir = 1; else if ((kc == null && (kc = comparableClassFor(k)) == null) || (dir = compareComparables(kc, k, pk)) == 0) dir = tieBreakOrder(k, pk); TreeNode<K,V> xp = p; if ((p = (dir <= 0) ? p.left : p.right) == null) { x.parent = xp; if (dir <= 0) xp.left = x; else xp.right = x; root = balanceInsertion(root, x); break; } } } } moveRootToFront(tab, root); } /** * Returns a list of non-TreeNodes replacing those linked from * this node. */ final Node<K,V> untreeify(HashMap<K,V> map) { Node<K,V> hd = null, tl = null; for (Node<K,V> q = this; q != null; q = q.next) { Node<K,V> p = map.replacementNode(q, null); if (tl == null) hd = p; else tl.next = p; tl = p; } return hd; } /** * Tree version of putVal. */ final TreeNode<K,V> putTreeVal(HashMap<K,V> map, Node<K,V>[] tab, int h, K k, V v) { Class<?> kc = null; boolean searched = false; TreeNode<K,V> root = (parent != null) ? root() : this; for (TreeNode<K,V> p = root;;) { int dir, ph; K pk; if ((ph = p.hash) > h) dir = -1; else if (ph < h) dir = 1; else if ((pk = p.key) == k || (k != null && k.equals(pk))) return p; else if ((kc == null && (kc = comparableClassFor(k)) == null) || (dir = compareComparables(kc, k, pk)) == 0) { if (!searched) { TreeNode<K,V> q, ch; searched = true; if (((ch = p.left) != null && (q = ch.find(h, k, kc)) != null) || ((ch = p.right) != null && (q = ch.find(h, k, kc)) != null)) return q; } dir = tieBreakOrder(k, pk); } TreeNode<K,V> xp = p; if ((p = (dir <= 0) ? p.left : p.right) == null) { Node<K,V> xpn = xp.next; TreeNode<K,V> x = map.newTreeNode(h, k, v, xpn); if (dir <= 0) xp.left = x; else xp.right = x; xp.next = x; x.parent = x.prev = xp; if (xpn != null) ((TreeNode<K,V>)xpn).prev = x; moveRootToFront(tab, balanceInsertion(root, x)); return null; } } } /** * Removes the given node, that must be present before this call. * This is messier than typical red-black deletion code because we * cannot swap the contents of an interior node with a leaf * successor that is pinned by "next" pointers that are accessible * independently during traversal. So instead we swap the tree * linkages. If the current tree appears to have too few nodes, * the bin is converted back to a plain bin. (The test triggers * somewhere between 2 and 6 nodes, depending on tree structure). */ final void removeTreeNode(HashMap<K,V> map, Node<K,V>[] tab, boolean movable) { int n; if (tab == null || (n = tab.length) == 0) return; int index = (n - 1) & hash; TreeNode<K,V> first = (TreeNode<K,V>)tab[index], root = first, rl; TreeNode<K,V> succ = (TreeNode<K,V>)next, pred = prev; if (pred == null) tab[index] = first = succ; else pred.next = succ; if (succ != null) succ.prev = pred; if (first == null) return; if (root.parent != null) root = root.root(); if (root == null || root.right == null || (rl = root.left) == null || rl.left == null) { tab[index] = first.untreeify(map); // too small return; } TreeNode<K,V> p = this, pl = left, pr = right, replacement; if (pl != null && pr != null) { TreeNode<K,V> s = pr, sl; while ((sl = s.left) != null) // find successor s = sl; boolean c = s.red; s.red = p.red; p.red = c; // swap colors TreeNode<K,V> sr = s.right; TreeNode<K,V> pp = p.parent; if (s == pr) { // p was s's direct parent p.parent = s; s.right = p; } else { TreeNode<K,V> sp = s.parent; if ((p.parent = sp) != null) { if (s == sp.left) sp.left = p; else sp.right = p; } if ((s.right = pr) != null) pr.parent = s; } p.left = null; if ((p.right = sr) != null) sr.parent = p; if ((s.left = pl) != null) pl.parent = s; if ((s.parent = pp) == null) root = s; else if (p == pp.left) pp.left = s; else pp.right = s; if (sr != null) replacement = sr; else replacement = p; } else if (pl != null) replacement = pl; else if (pr != null) replacement = pr; else replacement = p; if (replacement != p) { TreeNode<K,V> pp = replacement.parent = p.parent; if (pp == null) root = replacement; else if (p == pp.left) pp.left = replacement; else pp.right = replacement; p.left = p.right = p.parent = null; } TreeNode<K,V> r = p.red ? root : balanceDeletion(root, replacement); if (replacement == p) { // detach TreeNode<K,V> pp = p.parent; p.parent = null; if (pp != null) { if (p == pp.left) pp.left = null; else if (p == pp.right) pp.right = null; } } if (movable) moveRootToFront(tab, r); } /** * Splits nodes in a tree bin into lower and upper tree bins, * or untreeifies if now too small. Called only from resize; * see above discussion about split bits and indices. * * @param map the map * @param tab the table for recording bin heads * @param index the index of the table being split * @param bit the bit of hash to split on */ final void split(HashMap<K,V> map, Node<K,V>[] tab, int index, int bit) { TreeNode<K,V> b = this; // Relink into lo and hi lists, preserving order TreeNode<K,V> loHead = null, loTail = null; TreeNode<K,V> hiHead = null, hiTail = null; int lc = 0, hc = 0; for (TreeNode<K,V> e = b, next; e != null; e = next) { next = (TreeNode<K,V>)e.next; e.next = null; if ((e.hash & bit) == 0) { if ((e.prev = loTail) == null) loHead = e; else loTail.next = e; loTail = e; ++lc; } else { if ((e.prev = hiTail) == null) hiHead = e; else hiTail.next = e; hiTail = e; ++hc; } } if (loHead != null) { if (lc <= UNTREEIFY_THRESHOLD) tab[index] = loHead.untreeify(map); else { tab[index] = loHead; if (hiHead != null) // (else is already treeified) loHead.treeify(tab); } } if (hiHead != null) { if (hc <= UNTREEIFY_THRESHOLD) tab[index + bit] = hiHead.untreeify(map); else { tab[index + bit] = hiHead; if (loHead != null) hiHead.treeify(tab); } } } /* ------------------------------------------------------------ */ // Red-black tree methods, all adapted from CLR static <K,V> TreeNode<K,V> rotateLeft(TreeNode<K,V> root, TreeNode<K,V> p) { TreeNode<K,V> r, pp, rl; if (p != null && (r = p.right) != null) { if ((rl = p.right = r.left) != null) rl.parent = p; if ((pp = r.parent = p.parent) == null) (root = r).red = false; else if (pp.left == p) pp.left = r; else pp.right = r; r.left = p; p.parent = r; } return root; } static <K,V> TreeNode<K,V> rotateRight(TreeNode<K,V> root, TreeNode<K,V> p) { TreeNode<K,V> l, pp, lr; if (p != null && (l = p.left) != null) { if ((lr = p.left = l.right) != null) lr.parent = p; if ((pp = l.parent = p.parent) == null) (root = l).red = false; else if (pp.right == p) pp.right = l; else pp.left = l; l.right = p; p.parent = l; } return root; } static <K,V> TreeNode<K,V> balanceInsertion(TreeNode<K,V> root, TreeNode<K,V> x) { x.red = true; for (TreeNode<K,V> xp, xpp, xppl, xppr;;) { if ((xp = x.parent) == null) { x.red = false; return x; } else if (!xp.red || (xpp = xp.parent) == null) return root; if (xp == (xppl = xpp.left)) { if ((xppr = xpp.right) != null && xppr.red) { xppr.red = false; xp.red = false; xpp.red = true; x = xpp; } else { if (x == xp.right) { root = rotateLeft(root, x = xp); xpp = (xp = x.parent) == null ? null : xp.parent; } if (xp != null) { xp.red = false; if (xpp != null) { xpp.red = true; root = rotateRight(root, xpp); } } } } else { if (xppl != null && xppl.red) { xppl.red = false; xp.red = false; xpp.red = true; x = xpp; } else { if (x == xp.left) { root = rotateRight(root, x = xp); xpp = (xp = x.parent) == null ? null : xp.parent; } if (xp != null) { xp.red = false; if (xpp != null) { xpp.red = true; root = rotateLeft(root, xpp); } } } } } } static <K,V> TreeNode<K,V> balanceDeletion(TreeNode<K,V> root, TreeNode<K,V> x) { for (TreeNode<K,V> xp, xpl, xpr;;) { if (x == null || x == root) return root; else if ((xp = x.parent) == null) { x.red = false; return x; } else if (x.red) { x.red = false; return root; } else if ((xpl = xp.left) == x) { if ((xpr = xp.right) != null && xpr.red) { xpr.red = false; xp.red = true; root = rotateLeft(root, xp); xpr = (xp = x.parent) == null ? null : xp.right; } if (xpr == null) x = xp; else { TreeNode<K,V> sl = xpr.left, sr = xpr.right; if ((sr == null || !sr.red) && (sl == null || !sl.red)) { xpr.red = true; x = xp; } else { if (sr == null || !sr.red) { if (sl != null) sl.red = false; xpr.red = true; root = rotateRight(root, xpr); xpr = (xp = x.parent) == null ? null : xp.right; } if (xpr != null) { xpr.red = (xp == null) ? false : xp.red; if ((sr = xpr.right) != null) sr.red = false; } if (xp != null) { xp.red = false; root = rotateLeft(root, xp); } x = root; } } } else { // symmetric if (xpl != null && xpl.red) { xpl.red = false; xp.red = true; root = rotateRight(root, xp); xpl = (xp = x.parent) == null ? null : xp.left; } if (xpl == null) x = xp; else { TreeNode<K,V> sl = xpl.left, sr = xpl.right; if ((sl == null || !sl.red) && (sr == null || !sr.red)) { xpl.red = true; x = xp; } else { if (sl == null || !sl.red) { if (sr != null) sr.red = false; xpl.red = true; root = rotateLeft(root, xpl); xpl = (xp = x.parent) == null ? null : xp.left; } if (xpl != null) { xpl.red = (xp == null) ? false : xp.red; if ((sl = xpl.left) != null) sl.red = false; } if (xp != null) { xp.red = false; root = rotateRight(root, xp); } x = root; } } } } } /** * Recursive invariant check */ static <K,V> boolean checkInvariants(TreeNode<K,V> t) { TreeNode<K,V> tp = t.parent, tl = t.left, tr = t.right, tb = t.prev, tn = (TreeNode<K,V>)t.next; if (tb != null && tb.next != t) return false; if (tn != null && tn.prev != t) return false; if (tp != null && t != tp.left && t != tp.right) return false; if (tl != null && (tl.parent != t || tl.hash > t.hash)) return false; if (tr != null && (tr.parent != t || tr.hash < t.hash)) return false; if (t.red && tl != null && tl.red && tr != null && tr.red) return false; if (tl != null && !checkInvariants(tl)) return false; if (tr != null && !checkInvariants(tr)) return false; return true; } } }
2、HashMap源碼分析node
一、HashMap的存儲結構？算法
HashMap底層是用一個數組table來存儲鍵值對的Node，table的每一個下標稱爲一個桶，經過key計算出來的hash值和table的長度計算出來下標值，鍵值對就存儲在table的該下標處的桶中若是計算獲得的下標相同就會被存入到同一個桶裏面，以單鏈表的形式來進行存儲，若是鏈表太長就會以tree的形式來對Node進行存儲。編程
二、HashMap的初始容量、最大容量和擴容因子是多少？數組
若是使用默認的構造函數建立對象，那初始容量爲16，默認的擴容因子爲0.75。HashMap的容量必須是2的整數次冪。安全
/** * 默認的初始化table的大小16，必須是2的整數次冪 */ static final int DEFAULT_INITIAL_CAPACITY = 1 << 4; // aka 16 /** * 最大容量大小，必須是小於1<<30的2的整數次冪 */ static final int MAXIMUM_CAPACITY = 1 << 30; /** * 默認的加載因子 */ static final float DEFAULT_LOAD_FACTOR = 0.75f;
三、HashMap在什麼狀況下會擴容？擴大到多少？數據結構
經過構造函數建立HashMap的對象的時候，底層是數組table爲null。在加入第一個鍵值對的時候會調用resize（）方法來利用DEFAULT_INITIAL_CAPACITY 和DEFAULT_LOAD_FACTOR 或者本身傳入的 參數來建立一Node數組。若是是無參構造函數，那麼該數組的大小就是DEFAULT_INITIAL_CAPACITY 。存儲的極限就是DEFAULT_INITIAL_CAPACITY * DEFAULT_LOAD_FACTOR 。多線程
若是不是第一次加入鍵值對，若是加入鍵值對後的鍵值對數量size大於存儲的極限threshold（當前容量*當前加載因子），那麼也須要調用resize（）方法來進行擴容。此時會將容量和存儲極限擴展爲原來的兩倍。也就是建立新的數組，而後將原來的鍵值對從新分配位置。併發
第三種狀況就是若是有的桶中的Node數量已經大於等於TREEIFY_THRESHOLD（8）時，可是整個HashMap的桶數量尚未達到MIN_TREEIFY_CAPACITY（64）時，就調用resize（）方法來進行擴容。app
四、HashMap是如何肯定新加入的鍵值對要存儲的位置的？
經過hash方法來獲取key的hash值，而後(n - 1) & hash來獲取key對應的下標值，其中n爲當前table的大小。這樣就能找到當前鍵值對須要加入的桶，若是該桶是鏈表結構就直接加載鏈表的結尾。
若是該桶是樹形結構，就須要對hash值進行比較來肯定鍵值對的位置，若是hash值相同就比較key之間是可比較的，若是是不可比較的就比較當前節點和指定節點key的類名，就這樣一步步的肯定key鎖對應的位置。
static final int hash(Object key) { int h; return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16); }
五、何時會將桶由鏈表結構變爲樹形結構，又什麼時候變回來
在桶中的Node數量大於等於TREEIFY_THRESHOLD且table大於等於MIN_TREEIFY_CAPACITY的時候就會轉爲樹結構。當桶中的節點數量小於等於MIN_TREEIFY_CAPACITY時，就須要將樹型轉化爲鏈表結構。
六、線程安全問題、是否能夠存null鍵和null值
HashMap是線程不安全的，因此在多線程環境下使用的時候要當心。它和HashTable不一樣，它能夠存儲null鍵和null值。
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