jdk1.8HashMap方法剖析
前言
HashMap是工作中常用的数据结构，网上关于HashMap源码的资料很多，但一直觉得如管中窥豹，对于HashMap的认知一直停留在表面，只知道概念而不知道过程。并且自己在看源码的过程中发现，网上部分博主的文档对源码的解析也是错误的，于是决定自己解读一次源码。
正文
HashMap属性：
//默认初始容量(注意：必须为2的幂)
static final int DEFAULT_INITIAL_CAPACITY = 1 << 4; // aka 16
//最大容量，如果任意一个带有参数的构造函数指定更高的值，则使用此最大容量。
//HashMap数组长度必须是2的幂次方且<= 1<<30
static final int MAXIMUM_CAPACITY = 1 << 30;
//在构造函数中未指定时使用的负载系数
static final float DEFAULT_LOAD_FACTOR = 0.75f;
//树化阈值：链表转成红黑树的阈值，在存储数据时，当链表长度 > 该值时，则将链表转换成红黑树
static final int TREEIFY_THRESHOLD = 8;
//树退化阈值：当在扩容（resize（））时，在重新计算存储位置后，当原有的红黑树内数量 < 6时，则将 红黑树转换成链表
static final int UNTREEIFY_THRESHOLD = 6;
//最小树形化容量阈值：即 当哈希表中的容量 > 该值时，才允许树形化链表 （即 将链表 转换成红黑树）
//否则，若桶内元素太多时，则直接扩容，而不是树形化
//为了避免进行扩容、树形化选择的冲突，这个值不能小于 4 * TREEIFY_THRESHOLD
static final int MIN_TREEIFY_CAPACITY = 64;
HashMap链表和红黑树结构：
Node
static class Node<K, V> implements Map.Entry<K, V> {
//节点的key值的hash值
final int hash;
//节点的key值
final K key;
//节点的value值
V value;
//下一个节点
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;
}
}
TreeNode
/**
* Entry for Tree bins. Extends LinkedHashMap.Entry (which in turn
* extends Node) so can be used as extension of either regular or
* linked node.
*
* 双向链表+红黑树的数据结构
*/
static final class TreeNode<K, V> extends LinkedHashMap.Entry<K, V> {
//父节点
TreeNode<K, V> parent; // red-black tree links
//左孩子节点
TreeNode<K, V> left;
//右孩子节点
TreeNode<K, V> right;
//双向链表结构下的上一个节点
TreeNode<K, V> prev; // needed to unlink next upon deletion
//节点颜色
boolean red;
//TreeNode 继承于LinkedHashMap.Entry,LinkedHashMap.Entry继承于HashMap.Node
//TreeNode还有四个属性:
// final int hash; hash值
// final K key; key值
// V value; value值
// Node next; 下一个节点
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) {
//先获取table的下标
int index = (n - 1) & root.hash;
//获取table下标的节点
TreeNode<K, V> first = (TreeNode<K, V>) tab[index];
//如果红黑树的根节点不是table[index]的节点
if (root != first) {
Node<K, V> rn;
//第一步将红黑树的根节点变成table[index]的节点
tab[index] = root;
//第二步将红黑树的根节点变成双向链表的头节点
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;
}
//验证红黑树的准确性 assert:启动参数中加 -ae 才能生效
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.
* h:寻找的key的hash值
* k:寻找的key
* kc:寻找的key的类
*/
final TreeNode<K, V> find(int h, Object k, Class<?> kc) {
//当前的节点
TreeNode<K, V> p = this;
do {
//ph:当前节点p的hash值,dir:接下来遍历的方向
int ph, dir;
//pk:当前节点p的key值
K pk;
//pl:p的左孩子节点,pr:p的右孩子节点,q:
TreeNode<K, V> pl = p.left, pr = p.right, q;
//如果p的hash值大于要寻找的key的hash值,往左边走
if ((ph = p.hash) > h)
p = pl;
//如果p的hash值小于要寻找的key的hash值,往右边走
else if (ph < h)
p = pr;
//如果遍历的p的key和寻找的key在同一个内存地址或者equals比较相等,那么直接返回p
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
//将a和b的类名来比较
|| (d = a.getClass().getName().compareTo(b.getClass().getName())) == 0)
//如果名字还相等的话...,最后进行比较hashcode
d = (System.identityHashCode(a) <= System.identityHashCode(b) ?
-1 : 1);
return d;
}
/**
* HashMap的树化
* Forms tree of the nodes linked from this node.
*/
final void treeify(Node<K, V>[] tab) {
TreeNode<K, V> root = null;
//遍历当前链表
//treeify是TreeNode的方法,this代表当前节点
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) {
//将root声明为根节点
x.parent = null;
//红黑树根节点肯定是黑色的
x.red = false;
//刚进来时,x是双向链表的头节点,先将其做为红黑树的根节点
root = x;
} else {
//x:要插入的节点
//p:当前遍历的节点
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)
//左边走
dir = -1;
else if (ph < h)
//右边走
dir = 1;
//走到这里代表p的hash值和x的hash值相等
//给kc赋值
else if ((kc == null && (kc = comparableClassFor(k)) == null)
//走到这里说明k的类已经实现comparable接口,将k和pk进行比较大小
|| (dir = compareComparables(kc, k, pk)) == 0)
//p的hash值和x的hash值相等且x和p的key的大小相等
//最后走tieBreakOrder()确定走向
dir = tieBreakOrder(k, pk);
//<-------------------------------------------->
//确定走向时极端情况下用了三种方法:
//1.x和p的hash值比较大小
//2.(dir = compareComparables(kc, k, pk):x和p的key进行compareTo比较大小
//3.tieBreakOrder(k, pk):x和p进行getClass().getName()比较大小
// <-------------------------------------------->
TreeNode<K, V> xp = p;
if ((p = (dir <= 0) ? p.left : p.right) == null) {
//遍历走到p的left或者right为null时,将x节点进行插入
x.parent = xp;
if (dir <= 0)
xp.left = x;
else
xp.right = x;
//插入红黑树后进行调整,使其符合红黑树结构
root = balanceInsertion(root, x);
break;
}
}
}
}
//生成一个红黑树之后,要把红黑树的根节点赋值到table[index],即替换链表
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.
* map:当前的map对象
* tab:map的桶
* h:插入的key的hash值
* k:插入的key
* v:插入的value
*/
final TreeNode<K, V> putTreeVal(HashMap<K, V> map, Node<K, V>[] tab,
int h, K k, V v) {
//个人感觉逻辑类似于treeify()
//kc:插入的key的Class对象
Class<?> kc = null;
//该变量用于首次遍历时候查看整颗树是否有节点与插入的节点一致,有的话直接返回原先节点
boolean searched = false;
//root:当前红黑树的根节点
TreeNode<K, V> root = (parent != null) ? root() : this;
//此处遍历整棵红黑树,直到找到合适的插入节点 p:当前遍历的所在节点
for (TreeNode<K, V> p = root; ; ) {
//dir:遍历的左右方向 ph:当前遍历节点的hash值
int dir, ph;
//pk:当前遍历节点的key
K pk;
if ((ph = p.hash) > h)
//左边走
dir = -1;
else if (ph < h)
//右边走
dir = 1;
else if ((pk = p.key) == k || (k != null && k.equals(pk)))
//如果插入的key值和原先的key值一样,返回原先的节点
return p;
else if ((kc == null && (kc = comparableClassFor(k)) == null)
//首次遍历则初始化kc,如果的插入的key的类未实现comparable接口
//或者插入的key值和当前p节点的key值通过compareTo比较为0,则进入下面的方法
|| (dir = compareComparables(kc, k, pk)) == 0) {
if (!searched) {
TreeNode<K, V> q, ch;
searched = true;
//从p的左子节点开始遍历寻找,判断是否有节点与要插入的节点一样,有的话直接返回原先的节点
if (((ch = p.left) != null && (q = ch.find(h, k, kc)) != null)
//从p的右子节点开始遍历寻找,判断是否有节点与要插入的节点一样,有的话直接返回原先的节点
|| ((ch = p.right) != null && (q = ch.find(h, k, kc)) != null))
return q;
}
//最后的比较方法,详情看方法
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
|| (movable
&& (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.
*
* 将红黑树中的节点拆分为上下部分的红黑树，如果拆分后太小，则取消树化。
*
* @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) {
// pp是祖父结点
// p是待旋转结点
// r是p的右孩子结点
// rl是r的左孩子结点
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) {
//新节点默认为红色
x.red = true;
//xp:x的父节点,xpp:x的祖父节点,xpp1:xpp的左孩子节点,xppr:xpp的右孩子节点
for (TreeNode<K, V> xp, xpp, xppl, xppr; ; ) {
//如果x没有父节点,则x就是根节点,根节点为黑色
if ((xp = x.parent) == null) {
x.red = false;
return x;
}
//如果父节点不是红色(也就是黑色),或者没有祖父节点,那么说明x是第二层的节点,父节点为根节点
else if (!xp.red || (xpp = xp.parent) == null)
//直接返回
return root;
//能走到这里说明x的父节点是红色
//如果x的父节点是祖父节点的左孩子节点
if (xp == (xppl = xpp.left)) {
//祖父节点的右孩子(叔叔节点)不为空,且为红色
if ((xppr = xpp.right) != null && xppr.red) {
//走到这里说明父节点和叔叔节点都是红色
//此时将叔叔节点和父亲节点变为黑色,祖父节点变成红色
//(此时祖父节点,父节点,叔叔节点,本身的节点已经调整完毕,祖父节点变成红色,要继续往上调整)
//将x替换为祖父节点,进入下一个递归
xppr.red = false;
xp.red = false;
xpp.red = true;
x = xpp;
}
//如果叔叔节点为空,或者是黑色
else {
//如果x节点为xp的右孩子
if (x == xp.right) {
//进行左旋,把x替换成xp进行递归,左旋过程中产生新的root节点
root = rotateLeft(root, x = xp);
//x替换后,修改xp和xpp
xpp = (xp = x.parent) == null ? null : xp.parent;
}
if (xp != null) {
xp.red = false;
if (xpp != null) {
xpp.red = true;
root = rotateRight(root, xpp);
}
}
}
}
//如果x的父节点是祖父节点的右孩子节点
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;
}
}
方法剖析：
get()
HashMap的get(Object key)本质上是调用了getNode(int hash, Object key)
public V get(Object key) {
Node<K, V> e;
return (e = getNode(hash(key), key)) == null ? null : e.value;
}
final Node<K, V> getNode(int hash, Object key) {
Node<K, V>[] tab;
Node<K, V> first, e;
int n;
K k;
//table初始化且长度大于0,&运算之后的下标得出第一个节点不为空
if ((tab = table) != null && (n = tab.length) > 0 &&
(first = tab[(n - 1) & hash]) != null) {
//判断第一个节点是否就是要要检索的key,如果是的话返回第一个节点
if (first.hash == hash && // always check first node
((k = first.key) == key || (key != null && key.equals(k))))
return first;
//第一个节点不是,遍历之后的节点
if ((e = first.next) != null) {
//判断节点的数据结构是否是双向链表+红黑树结构
if (first instanceof TreeNode)
return ((TreeNode<K, V>) first).getTreeNode(hash, key);
do {
//链表结构,用do{...}while(...)遍历链表,直到便利结束或者找到节点
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k))))
return e;
} while ((e = e.next) != null);
}
}
return null;
}
put()
HashMap的put(K key, V value)本质上是调用了putVal(int hash, K key, V value, boolean onlyIfAbsent, boolean evict)
public V put(K key, V value) {
return putVal(hash(key), key, value, false, true);
}
final V putVal(int hash, K key, V value, boolean onlyIfAbsent,
boolean evict) {
//tab:hashmap的桶
Node<K, V>[] tab;
//p:链表结构时为链表的头节点,红黑树结构时为根节点
Node<K, V> p;
int n, i;
//table为null,进行初始化
if ((tab = table) == null || (n = tab.length) == 0)
n = (tab = resize()).length;
//通过&的方式,算出下标.
//当n为2次方幂时,(n-1)&hash = hash%n,不直接取模的原因是位运算比取模运算速度更快
if ((p = tab[i = (n - 1) & hash]) == null)
//桶下标的对象为空,直接存入
tab[i] = newNode(hash, key, value, null);
else {
Node<K, V> e;
K k;
if (p.hash == hash &&
((k = p.key) == key || (key != null && key.equals(k))))
//存入的值和原先的值相同
e = p;
else if (p instanceof TreeNode)
//下标的节点类型是红黑树结构
e = ((TreeNode<K, V>) p).putTreeVal(this, tab, hash, key, value);
else {
//下标的节点类型是链表
for (int binCount = 0; ; ++binCount) {
//开始遍历链表
//将e初始化为p的下一个节点,并判空
if ((e = p.next) == null) {
//遍历到最后进行插入:所以jdk1.8链表是尾插法
p.next = newNode(hash, key, value, null);
//binCount>=7(链表长度大于等于8)
//插入第8个的时候,binCount还是6,此时已经break了,所以网上说的链表长度达到8就转换红黑树其实是错误的...
//也就是下标对应的链表,在存入第9个节点的之后,会调用treeifyBin函数，当桶的大小长度大于64时,将链表转换为红黑树。
if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st
treeifyBin(tab, hash);
break;
}
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k))))
//存入的值和原先的值相同,不操作,跳出循环
break;
//以上条件都不满足,将p替换为e(即:p.next),继续遍历
p = e;
}
}
if (e != null) {
// EXISTING MAPPING FOR KEY
V oldValue = e.value;
//此处判断主要用于HashMap的put()和putIfAbsent()
//所以put()会直接替换原有的值,返回原有的值,而putIfAbsent()不会替换原有的值,返回原有的值
if (!onlyIfAbsent || oldValue == null)
e.value = value;
afterNodeAccess(e);
return oldValue;
}
}
//走到这里说明没有找到原先的oldValue
//修改次数+1
++modCount;
if (++size > threshold)
//判断是否需要扩容
resize();
//HashMap里此方法为空
afterNodeInsertion(evict);
return null;
}
在putVal()引申出treeifyBin(Node
treeifyBin()
/**
* Replaces all linked nodes in bin at index for given hash unless
* table is too small, in which case resizes instead.
* 链表转红黑树之前的初始化工作,先转换成双向链表
*
*/
final void treeifyBin(Node<K, V>[] tab, int hash) {
int n, index;
Node<K, V> e;
//HashMap的桶为空,或者桶的大小长度小于64,直接进行扩容,不会树化.
if (tab == null || (n = tab.length) < MIN_TREEIFY_CAPACITY)
resize();
else if ((e = tab[index = (n - 1) & hash]) != null) {
//此处操作是在树化之前将链表转换为双向链表
//定义头节点和尾节点
TreeNode<K, V> hd = null, tl = null;
do {
//将当前节点转换为树节点
TreeNode<K, V> p = replacementTreeNode(e, null);
if (tl == null)
//首次遍历t1肯定为null,将t1初始化为头节点
hd = p;
else {
//之后开始遍历,组成双向链表
p.prev = tl;
tl.next = p;
}
tl = p;
} while ((e = e.next) != null);
if ((tab[index] = hd) != null)
//做一层判空,开始进行真正的树化
hd.treeify(tab);
}
}
resize()
final Node<K, V>[] resize() {
Node<K, V>[] oldTab = table;
//原先数组的长度
int oldCap = (oldTab == null) ? 0 : oldTab.length;
//原先hashmap进行resize的阈值
int oldThr = threshold;
//新数组长度,新数组resize阈值
int newCap, newThr = 0;
//老数组的长度>0
if (oldCap > 0) {
if (oldCap >= MAXIMUM_CAPACITY) {
threshold = Integer.MAX_VALUE;
return oldTab;
}
//新数组的长度为老数组的两倍
else if ((newCap = oldCap << 1) < MAXIMUM_CAPACITY &&
oldCap >= DEFAULT_INITIAL_CAPACITY)
//新数组resize阈值为老数组resize阈值的两倍
newThr = oldThr << 1; // double threshold
} else if (oldThr > 0)
// initial capacity was placed in threshold 初始容量置于阈值
newCap = oldThr;
else {
// zero initial threshold signifies using defaults 零初始阈值表示使用默认值(初始化)
newCap = DEFAULT_INITIAL_CAPACITY;
newThr = (int) (DEFAULT_LOAD_FACTOR * DEFAULT_INITIAL_CAPACITY);
}
if (newThr == 0) {
//如果走到这里新数组的扩容阈值还是0,那么进行初始化
float ft = (float) newCap * loadFactor;
newThr = (newCap < MAXIMUM_CAPACITY && ft < (float) MAXIMUM_CAPACITY ?
(int) ft : Integer.MAX_VALUE);
}
threshold = newThr;
@SuppressWarnings({
"rawtypes", "unchecked"})
Node<K, V>[] newTab = (Node<K, V>[]) new Node[newCap];
table = newTab;
if (oldTab != null) {
for (int j = 0; j < oldCap; ++j) {
//开始遍历hashMap(扩容前)的桶
Node<K, V> e;
if ((e = oldTab[j]) != null) {
oldTab[j] = null;
//判断桶对应下标的头节点的是否还有下一个节点
if (e.next == null)
//桶对应下标的头节点没有下一个节点,直接&运算得出新的下标位置
//思考:为什么e可以直接做为hash之后得出的下标的头节点?
//扩容只是左位移1位,假设原先下标为index,那么新的hash之后的下标只能为index或者index+oldCap
//并且e没有下一个节点,所以不需要考虑链表情况下冲突的问题,直接插入即可.
newTab[e.hash & (newCap - 1)] = e;
else if (e instanceof TreeNode)
//如果e是红黑树结构的一个节点,执行红黑树插入的方法
((TreeNode<K, V>) e).split(this, newTab, j, oldCap);
else {
// preserve order
//走到这里代表e是链表结构
Node<K, V> loHead = null, loTail = null;
Node<K, V> hiHead = null, hiTail = null;
Node<K, V> next;
do {
next = e.next;
//oldCap是2的N次幂,所以e.hash & oldCap 的结果只有0或者oldCap,跟定位下标e.hash & (oldCap-1)还是有所不同的
//扩容通过算出原先链表下所有节点的hash&oldCap的结果,来拆分成两条链表,再分别插入下标为j和j+oldCap中
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;
}
//遍历到整条链表的尾节点
} while ((e = next) != null);
//插入前判空
if (loTail != null) {
loTail.next = null;
newTab[j] = loHead;
}
if (hiTail != null) {
hiTail.next = null;
newTab[j + oldCap] = hiHead;
}
}
}
}
}
return newTab;
}
remove()
public V remove(Object key) {
Node<K, V> e;
return (e = removeNode(hash(key), key, null, false, true)) == null ?
null : e.value;
}
remove(Object key)内部实现是removeNode(int hash, Object key, Object value,boolean matchValue, boolean movable)
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;
if ((tab = table) != null && (n = tab.length) > 0 &&
(p = tab[index = (n - 1) & hash]) != null) {
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;
else if ((e = p.next) != null) {
if (p instanceof TreeNode)
node = ((TreeNode<K, V>) p).getTreeNode(hash, key);
else {
do {
if (e.hash == hash &&
((k = e.key) == key ||
(key != null && key.equals(k)))) {
node = e;
break;
}
p = e;
} while ((e = e.next) != null);
}
}
//以上方法与getNode（）类似
if (node != null && (!matchValue || (v = node.value) == value ||
(value != null && value.equals(v)))) {
//如果是红黑树结构,移除
if (node instanceof TreeNode)
((TreeNode<K, V>) node).removeTreeNode(this, tab, movable);
//如果是first节点,替换first节点
else if (node == p)
tab[index] = node.next;
//直接指向node的下一个节点
else
p.next = node.next;
++modCount;
--size;
afterNodeRemoval(node);
return node;
}
}
return null;
}