这篇博客深入解析了HashMap的数据结构，重点探讨了其在扩容、元素添加及删除过程中的核心逻辑。HashMap基于数组+链表实现，当链表长度超过阈值时，会考虑转换为红黑树。但在实际操作中，若数组长度小于64，会选择先扩容而非直接转为红黑树。虽然未深入讲解红黑树，但整体代码清晰易懂，有助于理解HashMap的工作原理。
首先要记住核心, HashMap的底层是数组+单向链表, 超过THRESHOLD设定的值 对应的数组下标下的链表会转换成红黑树(但是将链表转换成红黑树前会判断，如果当前数组的长度小于 64，那么会选择先进行数组扩容，而不是转换为红黑树）
没有深入了解红黑树 但是不影响看代码 有关tree的就是涉及到红黑树的
删了很多的简单的代码. 总体看下来官方代码就是清晰,认真看完一个其他发现其实也差不多
一定要根据数据结构去看
public class HashMap<K,V> extends AbstractMap<K,V>
implements Map<K,V>, Cloneable, Serializable {
private static final long serialVersionUID = 362498820763181265L;
//初始容量
static final int DEFAULT_INITIAL_CAPACITY = 1 << 4; // aka 16
// 最大值 超过20亿
static final int MAXIMUM_CAPACITY = 1 << 30;
// 超过容量* LOAD_FACTOR 就会扩容 (16 和 0.75 肯定是经过大量计算得出的)
static final float DEFAULT_LOAD_FACTOR = 0.75f;
//单个链表长超过就会转换成红黑树
static final int TREEIFY_THRESHOLD = 8;
//从树转换回来
static final int UNTREEIFY_THRESHOLD = 6;
//hashMap中元素数量大于64时，也会转为红黑树结构。
static final int MIN_TREEIFY_CAPACITY = 64;
//就是链表中的每个节点
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 int hashCode() {
return Objects.hashCode(key) ^ Objects.hashCode(value);
}
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 final int hash(Object key) {
int h;
return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16);
}
//返回最接近的2的幂次方
static final int tableSizeFor(int cap) {
}
//就是存储节点和链表的数组(数据存放的地方)
transient Node<K,V>[] table;
//用于转换进行迭代
transient Set<Map.Entry<K,V>> entrySet;
//元素的数量
transient int size;
//结构改变的次数
transient int modCount;
// 决定何时绝定扩容
int threshold;
final float loadFactor;
//四种构造方法
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);
}
public HashMap(int initialCapacity) {
this(initialCapacity, DEFAULT_LOAD_FACTOR);
}
public HashMap() {
this.loadFactor = DEFAULT_LOAD_FACTOR; // all other fields defaulted
}
public HashMap(Map<? extends K, ? extends V> m) {
this.loadFactor = DEFAULT_LOAD_FACTOR;
putMapEntries(m, false);
}
//将Map集合放入
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)//判断是否扩容
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);
}
}
}
// 查找对应的key的value
public V get(Object key) {
Node<K,V> e;
return (e = getNode(hash(key), key)) == null ? null : e.value;
}
//查找key对应的node
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) { // 盲猜通过tab[(n - 1) & hash]找到是哪个数组下标
if (first.hash == hash && // always check first node
((k = first.key) == key || (key != null && key.equals(k))))
return first;
if ((e = first.next) != null) {
if (first instanceof TreeNode)//如果是树节点就按照红黑树查找
return ((TreeNode<K,V>)first).getTreeNode(hash, key);
do {
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k))))
return e;
} while ((e = e.next) != null);
}
}
return null;
}
public V put(K key, V value) {
return putVal(hash(key), key, value, false, true);
}
// 放入节点值或者更新节点值的方法
//第四个参数表示如果该key存在值，如果为null的话，则插入新的value
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)
n = (tab = resize()).length;
if ((p = tab[i = (n - 1) & hash]) == null)// 对应的数组下标没有值才插入 否则p就是对应的下标的头结点
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))))
e = p;
else if (p instanceof TreeNode)//去红黑树的方法进行更新
e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
else {
for (int binCount = 0; ; ++binCount) {
if ((e = p.next) == null) {
p.next = newNode(hash, key, value, null);
if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st
treeifyBin(tab, hash);//判断是否需要进行转换成红黑树了
break;
}
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k))))
break;
p = e;
}
}
if (e != null) { // existing mapping for key
V oldValue = e.value;
if (!onlyIfAbsent || oldValue == null)
e.value = value;
afterNodeAccess(e);
return oldValue;
}
}
++modCount;
if (++size > threshold)
resize();
afterNodeInsertion(evict);
return null;
}
//扩容函数
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) {// 扩容为int的最大或者扩容两倍
if (oldCap >= MAXIMUM_CAPACITY) {
threshold = Integer.MAX_VALUE;
return oldTab;
}
else if ((newCap = oldCap << 1) < MAXIMUM_CAPACITY &&
oldCap >= DEFAULT_INITIAL_CAPACITY)
newThr = oldThr << 1; // double threshold 扩容因子也变为两倍
}
else if (oldThr > 0) // 如果扩容因子被初始化了就更换
newCap = oldThr;
else { // 代表使用默认的
newCap = 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);
}
threshold = newThr;//根据上面不同的情况判断后进行跟新
@SuppressWarnings({"rawtypes","unchecked"})
Node<K,V>[] newTab = (Node<K,V>[])new Node[newCap];//扩容
table = newTab;
//把就数组遍历到新的数组中 并把旧数组置为null 释放内存
if (oldTab != null) {
for (int j = 0; j < oldCap; ++j) {
Node<K,V> e;
if ((e = oldTab[j]) != null) {
oldTab[j] = null;
if (e.next == null)
newTab[e.hash & (newCap - 1)] = e;
else if (e instanceof TreeNode)
((TreeNode<K,V>)e).split(this, newTab, j, oldCap);
else { // preserve order 把对应数组下的链表更新过去
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) {
loTail.next = null;
newTab[j] = loHead;
}
if (hiTail != null) {
hiTail.next = null;
newTab[j + oldCap] = hiHead;
}
}
}
}
}
return newTab;
}
// 进行扩容或者 更换转换成树
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)//扩容
resize();
else if ((e = tab[index = (n - 1) & hash]) != null) {//转换成红黑树
TreeNode<K,V> hd = null, tl = null;
do {
//循环链表, 把节点转换成树叶子
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);
}
}
public V remove(Object key) {
Node<K,V> e;
return (e = removeNode(hash(key), key, null, false, true)) == null ?
null : e.value;
}
// value为值代表可以直接删除,不然需要先进行查找 match表示只有value相等时才能删除, movable表示删除后是否移动节点
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) { //找到要删除key节点对应的数组下标
Node<K,V> node = null, e; K k; V v;
if (p.hash == hash &&
((k = p.key) == key || (key != null && key.equals(k))))//先看头结点是否满足
node = p;
else if ((e = p.next) != null) {
if (p instanceof TreeNode) // 检查是否是树叶子
node = ((TreeNode<K,V>)p).getTreeNode(hash, key);
else {//遍历进行查找
do {
if (e.hash == hash &&
((k = e.key) == key ||
(key != null && key.equals(k)))) {
node = e; // node是要删除的节点
break;
}
p = e; //p是要删除的节点的上一个节点
} while ((e = e.next) != null);
}
}
//正常!matchvalue表示不用判断值
if (node != null && (!matchValue || (v = node.value) == value ||
(value != null && value.equals(v)))) {
if (node instanceof TreeNode)
((TreeNode<K,V>)node).removeTreeNode(this, tab, movable);
else if (node == p)
tab[index] = node.next;
else
p.next = node.next;
++modCount;
--size;
afterNodeRemoval(node);//此方法在hashMap中是为了让子类去实现，主要是对删除结点后的链表关系进行处理
return node;
}
}
return null;
}
/**
* Removes all of the mappings from this map.
* The map will be empty after this call returns.
*/
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;
}
}
/**
* Returns <tt>true</tt> if this map maps one or more keys to the
* specified value.
*
* @param value value whose presence in this map is to be tested
* @return <tt>true</tt> if this map maps one or more keys to the
* specified value
*/
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;
}
//这三个方法表示的是在访问、插入、删除某个节点之后，进行一些处理，它们在LinkedHashMap都有各自的实现(就是子类会根据需要进行设计)
// Callbacks to allow LinkedHashMap post-actions
void afterNodeAccess(Node<K,V> p) { }
void afterNodeInsertion(boolean evict) { }
void afterNodeRemoval(Node<K,V> p) { }
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