简介

• HashMap用来存放键值对，是基于哈希表的Map接口的实现
• HashMap继承自AbstractMap，实现了Map，Cloneable，Serializable接口
• Cloneable，Serializable都是标志接口，接口内没有任何内容。Cloneable标志着HashMap重写了Object类的clone方法实现拷贝，而Serializable则标志HashMap支持序列化

核心源码

基本参数

public class HashMap<K,V> extends AbstractMap<K,V>
implements Map<K,V>, Cloneable, Serializable {
private static final long serialVersionUID = 362498820763181265L;
// 默认初始容量
static final int DEFAULT_INITIAL_CAPACITY = 1 << 4; // aka 16
// 最大容量
static final int MAXIMUM_CAPACITY = 1 << 30;
// 默认负载因子
static final float DEFAULT_LOAD_FACTOR = 0.75f;
// 转化为树的阈值
static final int TREEIFY_THRESHOLD = 8;
// 从树转化为链表的阈值
static final int UNTREEIFY_THRESHOLD = 6;
// 树的最小容量
static final int MIN_TREEIFY_CAPACITY = 64;
// 存储元素的数组，总是2的幂次方倍
transient Node<K,V>[] table;
// 存放具体元素的集
transient Set<Map.Entry<K,V>> entrySet;
// 存放元素的数量，不等于数组的长度
transient int size;
// 每次扩容和更改map结构的计数器
transient int modCount;
// 临界值，实际大小（容量*负载因子）超过此值触发扩容
int threshold;
// 实际负载因子
final float loadFactor;

构造方法

	// 默认构造，定义负载因子
public HashMap() {
this.loadFactor = DEFAULT_LOAD_FACTOR; // all other fields defaulted
}
// 有参构造，指定初始容量和默认负载因子
public HashMap(int initialCapacity) {
this(initialCapacity, DEFAULT_LOAD_FACTOR);
}
// 有参构造，指定初始容量和负载因子
public HashMap(int initialCapacity, float loadFactor) {
// 边界限定
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);
}
// 有参构造，传入一个Map进行构造
public HashMap(Map<? extends K, ? extends V> m) {
this.loadFactor = DEFAULT_LOAD_FACTOR;
putMapEntries(m, false);
}
final void putMapEntries(Map<? extends K, ? extends V> m, boolean evict) {
// 获取插入的map的size
int s = m.size();
// 判断该map的size大小
if (s > 0) {
// 判断表是否为空表
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);
}
}
}

put方法（重要）

	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) {
Node<K,V>[] tab; Node<K,V> p; int n, i;
// 判断表是否为空表
if ((tab = table) == null || (n = tab.length) == 0)
n = (tab = resize()).length;
// (n - 1) & hash确定位置并判断此位置有无节点
if ((p = tab[i = (n - 1) & hash]) == null)
// 无节点，直接插入
tab[i] = newNode(hash, key, value, null);
else {
// 有节点
Node<K,V> e; K k;
// 判断hash和key是否相等
if (p.hash == hash &&
((k = p.key) == key || (key != null && key.equals(k))))
// 相等，直接替换
e = p;
// 判断是否为红黑树节点
else if (p instanceof TreeNode)
e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
// 为链表节点，遍历链表
else {
for (int binCount = 0; ; ++binCount) {
if ((e = p.next) == null) {
// 节点为空，直接插入
p.next = newNode(hash, key, value, null);
// 判断是否到达红黑树转化阈值（8）
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))))
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;
// 判断实际容量是否大于阈值（是否需要扩容）
if (++size > threshold)
resize();
// 访问回调
afterNodeInsertion(evict);
return null;
}

resize扩容方法（重要）

	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;
}
else if ((newCap = oldCap << 1) < MAXIMUM_CAPACITY &&
oldCap >= DEFAULT_INITIAL_CAPACITY)
newThr = oldThr << 1; // double threshold
}
else if (oldThr > 0) // initial capacity was placed in threshold
newCap = oldThr;
else {
// zero initial threshold signifies using defaults
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;
@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) {
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
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;
}

总结

• HashMap维护的是键值对，jdk1.8是用数组+链表+红黑树存储的，相较于1.7数组+链表，避免了极端情况下退化为链表查询的问题
• 重写了Object的hash方法，通过传入key的hash来确定存放（替换）位置
• 最影响性能的是扩容方法，知晓需要存入的数据的长度，应在构造时设置好HashMap的容量(若不知道具体长度也应在构造时给予构造初值16)，减少扩容提高效率

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参考：https://snailclimb.gitee.io/javaguide/#/java/collection/HashMap

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