HashMap（JDK8）
HashMap = 数组 + 链表 + 红黑树
一、HashMap初始化
HashMap默认容量大小为16，最大容量为1073741824（2^29）。
当链表长度大于等于8时并且Hash桶数量大于等于64时，链表转为红黑树。
当红黑树节点数量小于等于6时，红黑树转为链表。
/*** The default initial capacity - MUST be a power of two.*/static final int DEFAULT_INITIAL_CAPACITY = 1 << 4; // aka 16
?/*** The maximum capacity, used if a higher value is implicitly specified* by either of the constructors with arguments.* MUST be a power of two <= 1<<30.*/static final int MAXIMUM_CAPACITY = 1 << 30;/*** The bin count threshold for using a tree rather than list for a* bin. Bins are converted to trees when adding an element to a* bin with at least this many nodes. The value must be greater* than 2 and should be at least 8 to mesh with assumptions in* tree removal about conversion back to plain bins upon* shrinkage.*/static final int TREEIFY_THRESHOLD = 8;// 链表转为红黑树阈值
?/*** The bin count threshold for untreeifying a (split) bin during a* resize operation. Should be less than TREEIFY_THRESHOLD, and at* most 6 to mesh with shrinkage detection under removal.*/static final int UNTREEIFY_THRESHOLD = 6; // 红黑树转为链表阈值/*** The smallest table capacity for which bins may be treeified.* (Otherwise the table is resized if too many nodes in a bin.)* Should be at least 4 * TREEIFY_THRESHOLD to avoid conflicts* between resizing and treeification thresholds.*/static final int MIN_TREEIFY_CAPACITY = 64; // 链表转为红黑树Hash桶数量阈值
new HashMap（容量 initialCapacity，负载因子loadFactor）
负载因子：当前长度 > 容量 * 因子时进行扩容。负载因子过大会导致hash桶中的链表过长，查找键值对时间复杂度增高，过小会导致hash桶的数量过多，空间复杂度会增高。
threshold : 阈值
threshold = 容量 * 因子；
扩容时 threshold << 1 进行double双倍容量扩容
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);}tableSizeFor()方法会根据new HashMap(int initialCapacity, float loadFactor)传入的初始容量initialCapacity进行调整，获取最接近 2^n 次方的值。
例如传入20，那么return返回的是32
/*** Returns a power of two size for the given target capacity.*/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;}Hash桶
/*** The table, initialized on first use, and resized as* necessary. When allocated, length is always a power of two.* (We also tolerate length zero in some operations to allow* bootstrapping mechanics that are currently not needed.)*/transient Node<K,V>[] table;HashMap数组的链表结构
/*** Basic hash bin node, used for most entries. (See below for* TreeNode subclass, and in LinkedHashMap for its Entry subclass.)*/static class Node<K,V> implements Map.Entry<K,V> {final int hash;final K key;V value;Node<K,V> next;}HashMap红黑树结构
/*** 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 linksTreeNode<K,V> left;TreeNode<K,V> right;TreeNode<K,V> prev; // needed to unlink next upon deletionboolean red;TreeNode(int hash, K key, V val, Node<K,V> next) {super(hash, key, val, next);}
}二、增加元素
1、执行put方法
public V put(K key, V value) {return putVal(hash(key), key, value, false, true);
}2、先调用hash(key)方法根据hash算法将key的hash值返回。
static final int hash(Object key) {int h;return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16);
}3、接着调用putVal()方法
final V putVal(int hash, K key, V value, boolean onlyIfAbsent,boolean evict) {Node<K,V>[] tab; Node<K,V> p; int n, i;// 1、如果 table为null 或 table长度为0，那么调用resize()方法对table数组的初始化（第一次扩容）// new HashMap()创建实例后，在第一次put时对数组进行初始化操作（扩容）if ((tab = table) == null || (n = tab.length) == 0)n = (tab = resize()).length;// 2、(容量 - 1) & hash 值获取table数组的index下标，如果table[index]为null就对赋值一个新的Node链表if ((p = tab[i = (n - 1) & hash]) == null)tab[i] = newNode(hash, key, value, null);// 3、table[index]不为null，那么就进行插入操作else {Node<K,V> e; K k;// 3-1、链头 或 红黑树树顶 key相同情况if (p.hash == hash &&((k = p.key) == key || (key != null && key.equals(k))))e = p;// 3-2、判断当前table[index]是否为红黑树结构else if (p instanceof TreeNode)// 3-2-1、强转为TreeNode，执行(TreeNode)putTreeVal()方法进行添加e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);else {// 3-3、链表结构// 遍历链表for (int binCount = 0; ; ++binCount) {// 遍历到链表尾部，插入K,Vif ((e = p.next) == null) {// 链表中无相同key，直接将新节点插入到链表尾部p.next = newNode(hash, key, value, null);// 链表节点数量大于等于8时，转为红黑树结构if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st// 链表转红黑树 (数组长度小于64是不会转成红黑树的)treeifyBin(tab, hash);break;}// 如果key在链表中存在if (e.hash == hash &&((k = e.key) == key || (key != null && key.equals(k))))break;p = e;}}// 3-1-1 链表头发现key相同或红黑树树顶发现key相同 // 3-2-1 红黑树中存在key相同的节点// 3-3-1 链表中存在key相同的节点// 据onlyIfAbsent布尔值判断是否替换对应的value值if (e != null) { // existing mapping for keyV oldValue = e.value;if (!onlyIfAbsent || oldValue == null)e.value = value;afterNodeAccess(e);return oldValue;}}++modCount;// 存储容量是否大于临界值 （容量 * 负载因子）if (++size > threshold)// 扩容resize();afterNodeInsertion(evict);return null;
}红黑树的putTreeVal()
/*** 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)))// 红黑树中存在相同的key，直接返回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;// 添加叶节点TreeNode<K,V> x = map.newTreeNode(h, k, v, xpn);if (dir <= 0)xp.left = x;elsexp.right = x;xp.next = x;x.parent = x.prev = xp;if (xpn != null)((TreeNode<K,V>)xpn).prev = x;// 平衡红黑树moveRootToFront(tab, balanceInsertion(root, x));return null;}}}三、HashMap数组扩容
当数组元素大于等于阈值时，就会调用resize()方法进行数组扩容，扩容完成后数组长度为原来的两倍。
/*** Initializes or doubles table size. If null, allocates in* accord with initial capacity target held in field threshold.* Otherwise, because we are using power-of-two expansion, the* elements from each bin must either stay at same index, or move* with a power of two offset in the new table.** @return the table*/
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) {if (oldCap >= MAXIMUM_CAPACITY) {threshold = Integer.MAX_VALUE;return oldTab;}// 扩容为之前的两倍else if ((newCap = oldCap << 1) < MAXIMUM_CAPACITY &&oldCap >= DEFAULT_INITIAL_CAPACITY)// 阈值为之前的两倍newThr = oldThr << 1; // double threshold}else if (oldThr > 0) // initial capacity was placed in thresholdnewCap = oldThr;else { // zero initial threshold signifies using defaults// 阈值为0，容量和阈值使用默认值 也就是16和12newCap = DEFAULT_INITIAL_CAPACITY;newThr = (int)(DEFAULT_LOAD_FACTOR * DEFAULT_INITIAL_CAPACITY);}if (newThr == 0) {float ft = (float)newCap * loadFactor;newThr = (newCap < MAXIMUM_CAPACITY && ft < (float)MAXIMUM_CAPACITY ?(int)ft : Integer.MAX_VALUE);}// 新阈值threshold = newThr;// 新数组@SuppressWarnings({"rawtypes","unchecked"})Node<K,V>[] newTab = (Node<K,V>[])new Node[newCap];table = newTab;// 对之前的数组进行处理if (oldTab != null) {// 遍历原来的数组for (int j = 0; j < oldCap; ++j) {Node<K,V> e;if ((e = oldTab[j]) != null) {// 置nulloldTab[j] = null;// 空链表if (e.next == null)newTab[e.hash & (newCap - 1)] = e;// 红黑树else if (e instanceof TreeNode)// 拆分红黑树，拆成两颗树，然后映射都新数组中// 拆分的树节点总数如果小于等于6，就会转化为链表结构((TreeNode<K,V>)e).split(this, newTab, j, oldCap);// 链表else { // preserve orderNode<K,V> loHead = null, loTail = null;Node<K,V> hiHead = null, hiTail = null;Node<K,V> next;// 拆分链表，根据 hash & oldCap == 0 将链表拆为两个链表（低位链表、高位链表）do {next = e.next;if ((e.hash & oldCap) == 0) {if (loTail == null)loHead = e;elseloTail.next = e;loTail = e;}else {if (hiTail == null)hiHead = e;elsehiTail.next = e;hiTail = e;}} while ((e = next) != null);if (loTail != null) {loTail.next = null;// 低位链表依旧放在原来的数组下标位置上newTab[j] = loHead;}if (hiTail != null) {hiTail.next = null;// 高位链表放在对应的数组增加长度位置上 // 例如原来数组长度为16,扩容后长度为32，原来位置3，现在位置为19newTab[j + oldCap] = hiHead;}}}}}return newTab;
}扩容时红黑树拆分
/*** 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 orderTreeNode<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;// 根据hash & bit == 0，将红黑树拆成低位树和高位树if ((e.hash & bit) == 0) {if ((e.prev = loTail) == null)loHead = e;elseloTail.next = e;loTail = e;++lc;}else {if ((e.prev = hiTail) == null)hiHead = e;elsehiTail.next = e;hiTail = e;++hc;}}
?if (loHead != null) {// 红黑树节点总数小于等于6 转为链表形式 UNTREEIFY_THRESHOLD：6if (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) {// 红黑树节点总数小于等于6 转为链表形式if (hc <= UNTREEIFY_THRESHOLD)tab[index + bit] = hiHead.untreeify(map);else {tab[index + bit] = hiHead;if (loHead != null)hiHead.treeify(tab);}}
}