本文深入解析了HashMap的工作原理，包括其内部结构、初始化过程、扩容机制、数据存储与查找流程等核心内容。通过源代码分析，揭示了HashMap如何利用数组加链表的方式存储数据，以及在不同场景下其性能表现。
先贴上源代码
使用的JDK版本：1.7.0_13
/*
* Copyright (c) 1997, 2010, Oracle and/or its affiliates. All rights reserved.
* ORACLE PROPRIETARY/CONFIDENTIAL. Use is subject to license terms.
*/
import java.io.*;
import java.util.AbstractCollection;
import java.util.AbstractSet;
import java.util.Collection;
import java.util.ConcurrentModificationException;
import java.util.Iterator;
import java.util.Map;
import java.util.NoSuchElementException;
import java.util.Set;
public class HashMap<K,V> extends AbstractMap<K,V> implements Map<K,V>, Cloneable, Serializable {
// 默认初始大小
static final int DEFAULT_INITIAL_CAPACITY = 16;
// 最大大小
static final int MAXIMUM_CAPACITY = 1 << 30;
// 默认加载因子，加载因子是一个比例，当HashMap的数据大小>=容量*加载因子时，HashMap会将容量扩容
static final float DEFAULT_LOAD_FACTOR = 0.75f;
// 表数据，如果需要可以扩展大小，长度是2的倍数
transient Entry<K,V>[] table;
// 当前map的大小，【transient】关键字表示不参与序列化
transient int size;
//当实际数据大小超过threshold时，HashMap会将容量扩容，threshold＝容量*加载因子，标示是否需要扩容
int threshold;
/**
* The load factor for the hash table.
*/
final float loadFactor;
// 标示该Map被修改了多少次
transient int modCount;
static final int ALTERNATIVE_HASHING_THRESHOLD_DEFAULT = Integer.MAX_VALUE;
/**
* holds values which can't be initialized until after VM is booted.
*/
private static class Holder {
// Unsafe mechanics
/**
* Unsafe utilities
*/
static final sun.misc.Unsafe UNSAFE;
/**
* Offset of "final" hashSeed field we must set in readObject() method.
*/
static final long HASHSEED_OFFSET;
/**
* Table capacity above which to switch to use alternative hashing.
*/
static final int ALTERNATIVE_HASHING_THRESHOLD;
static {
String altThreshold = java.security.AccessController.doPrivileged(
new sun.security.action.GetPropertyAction(
"jdk.map.althashing.threshold"));
int threshold;
try {
threshold = (null != altThreshold)
? Integer.parseInt(altThreshold)
: ALTERNATIVE_HASHING_THRESHOLD_DEFAULT;
// disable alternative hashing if -1
if (threshold == -1) {
threshold = Integer.MAX_VALUE;
}
if (threshold < 0) {
throw new IllegalArgumentException("value must be positive integer.");
}
} catch(IllegalArgumentException failed) {
throw new Error("Illegal value for 'jdk.map.althashing.threshold'", failed);
}
ALTERNATIVE_HASHING_THRESHOLD = threshold;
try {
UNSAFE = sun.misc.Unsafe.getUnsafe();
HASHSEED_OFFSET = UNSAFE.objectFieldOffset(
HashMap.class.getDeclaredField("hashSeed"));
} catch (NoSuchFieldException | SecurityException e) {
throw new Error("Failed to record hashSeed offset", e);
}
}
}
/**
* If {@code true} then perform alternative hashing of String keys to reduce
* the incidence of collisions due to weak hash code calculation.
*/
transient boolean useAltHashing;
/**
* A randomizing value associated with this instance that is applied to
* hash code of keys to make hash collisions harder to find.
*/
transient final int hashSeed = sun.misc.Hashing.randomHashSeed(this);
//HashMap的初始化方法，初始化容量大小和加载因子
public HashMap(int initialCapacity, float loadFactor) {
//初始容量大于0
if (initialCapacity < 0)
throw new IllegalArgumentException("Illegal initial capacity: " + initialCapacity);
//如果初始最大大小大于默认最大大小，则加载默认
if (initialCapacity > MAXIMUM_CAPACITY)
initialCapacity = MAXIMUM_CAPACITY;
//加载因子位于0-1之间
if (loadFactor <= 0 || Float.isNaN(loadFactor))
throw new IllegalArgumentException("Illegal load factor: " + loadFactor);
//强制设置容量为2的倍数
int capacity = 1;
while (capacity < initialCapacity)
capacity <<= 1;
this.loadFactor = loadFactor;
//计算什么时候该扩容
threshold = (int)Math.min(capacity * loadFactor, MAXIMUM_CAPACITY + 1);
//创建一个默认大小的Entry数组
table = new Entry[capacity];
// useAltHashing = sun.misc.VM.isBooted() && (capacity >= Holder.ALTERNATIVE_HASHING_THRESHOLD);
init();
}
public HashMap(int initialCapacity) {
this(initialCapacity, DEFAULT_LOAD_FACTOR);
}
public HashMap() {
this(DEFAULT_INITIAL_CAPACITY, DEFAULT_LOAD_FACTOR);
}
//如果用Map初始化，则构建一个已当前大小和默认容量大小相比较，较大的容器和默认加载因子
public HashMap(Map<? extends K, ? extends V> m) {
this(Math.max((int) (m.size() / DEFAULT_LOAD_FACTOR) + 1,DEFAULT_INITIAL_CAPACITY), DEFAULT_LOAD_FACTOR);
putAllForCreate(m);
}
// internal utilities
void init() {
}
final int hash(Object k) {
int h = 0;
if (useAltHashing) {
if (k instanceof String) {
return sun.misc.Hashing.stringHash32((String) k);
}
h = hashSeed;
}
h ^= k.hashCode();
h ^= (h >>> 20) ^ (h >>> 12);
return h ^ (h >>> 7) ^ (h >>> 4);
}
// 求hash值和length的摸h%length，计算放置元素的位置（index）
//当数组长度为2的n次幂的时候，不同的key算得得index相同的几率较小，那么数据在数组上分布就比较均匀，也就是说碰撞的几率小，相对的，查询的时候就不用遍历某个位置上的链表，这样查询效率也就较高了
static int indexFor(int h, int length) {
return h & (length-1);
}
public int size() {
return size;
}
public boolean isEmpty() {
return size == 0;
}
//根据key值获取value
public V get(Object key) {
if (key == null)
return getForNullKey();
Entry<K,V> entry = getEntry(key);
return null == entry ? null : entry.getValue();
}
//返回key为null的值，null放置table的第0个位置
private V getForNullKey() {
for (Entry<K,V> e = table[0]; e != null; e = e.next) {
if (e.key == null)
return e.value;
}
return null;
}
public boolean containsKey(Object key) {
return getEntry(key) != null;
}
final Entry<K,V> getEntry(Object key) {
//先依据key计算哈希值
int hash = (key == null) ? 0 : hash(key);
//遍历第i个位置的链表，如果找到（同时判断hash值相同和key值相同，此处该链表所有的hash值应该都相同），在返回该Entry
for (Entry<K,V> e = table[indexFor(hash, table.length)];
e != null;
e = e.next) {
Object k;
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k))))
return e;
}
return null;
}
//放入
/**
* 这里有一个误区，网上好多教程都说hashMap数组的里面的链表的HashCode相同，
* 其实是不相同的，只是对length求模后值相同，即indexFor(hash, table.length)
*
* ***因此，HashMap在扩容后，需要将所有数据全部重新计算index，
* ***不仅table数组位置发生变化，链表结构也被打破！
*/
public V put(K key, V value) {
//key为null，放入null‘位置，即：table[0]
if (key == null)
return putForNullKey(value);
//计算哈希值
int hash = hash(key);
//找到数组放置位置
int i = indexFor(hash, table.length);
//遍历数组处的该链表，如果存在，则替换
for (Entry<K,V> e = table[i]; e != null; e = e.next) {
Object k;
if (e.hash == hash && ((k = e.key) == key || key.equals(k))) {
V oldValue = e.value;
e.value = value;
e.recordAccess(this);
return oldValue;
}
}
modCount++;
//没找到，则创建新的，此处应该有两种保存策略，一种是hash值相同，一种hash值不同（key都不相同）
addEntry(hash, key, value, i);
return null;
}
/**
* Offloaded version of put for null keys
*/
private V putForNullKey(V value) {
//如果有，则替换，此处貌似不用循环吧？key为null的
for (Entry<K,V> e = table[0]; e != null; e = e.next) {
if (e.key == null) {
V oldValue = e.value;
e.value = value;
e.recordAccess(this);
return oldValue;
}
}
modCount++;
addEntry(0, null, value, 0);
return null;
}
private void putForCreate(K key, V value) {
//依据key计算hash值
int hash = null == key ? 0 : hash(key);
int i = indexFor(hash, table.length);
//先根据index找到该链表，遍历链表，如果找到hash值相同并且key值相同，则替换该元素
for (Entry<K,V> e = table[i]; e != null; e = e.next) {
Object k;
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k)))) {
e.value = value;
return;
}
}
//找不到已存在的，则在i位置的链表中插入该Entry
createEntry(hash, key, value, i);
}
// 把传入进来的Map值全部放入当前Map中
private void putAllForCreate(Map<? extends K, ? extends V> m) {
for (Map.Entry<? extends K, ? extends V> e : m.entrySet())
putForCreate(e.getKey(), e.getValue());
}
//扩容
void resize(int newCapacity) {
Entry[] oldTable = table;
int oldCapacity = oldTable.length;
//如果已达到最大大小，则无法扩容
if (oldCapacity == MAXIMUM_CAPACITY) {
threshold = Integer.MAX_VALUE;
return;
}
//创建新的数组
Entry[] newTable = new Entry[newCapacity];
boolean oldAltHashing = useAltHashing;
useAltHashing |= sun.misc.VM.isBooted() &&
(newCapacity >= Holder.ALTERNATIVE_HASHING_THRESHOLD);
boolean rehash = oldAltHashing ^ useAltHashing;
//把老的table数据复制到新的数组中
transfer(newTable, rehash);
table = newTable;
//计算下一个扩容点
threshold = (int)Math.min(newCapacity * loadFactor, MAXIMUM_CAPACITY + 1);
}
/**
* 扩容时，把table中所有现有的数据转移到新的table中
*
* 数据迁移时，需要遍历整个Map，全部重新放置，包括数组和链表
*/
void transfer(Entry[] newTable, boolean rehash) {
int newCapacity = newTable.length;
for (Entry<K,V> e : table) {
while(null != e) {
Entry<K,V> next = e.next;
if (rehash) {
e.hash = null == e.key ? 0 : hash(e.key);
}
int i = indexFor(e.hash, newCapacity);
//下面三行代码从新组成链表
e.next = newTable[i];
newTable[i] = e;
e = next;
}
}
}
//把另外的map中值全部转移到当前map中
public void putAll(Map<? extends K, ? extends V> m) {
//要转移的map的大小
int numKeysToBeAdded = m.size();
if (numKeysToBeAdded == 0)
return;
//如果要转移的map大小大于扩容点，需要扩容
if (numKeysToBeAdded > threshold) {
int targetCapacity = (int)(numKeysToBeAdded / loadFactor + 1);
if (targetCapacity > MAXIMUM_CAPACITY)
targetCapacity = MAXIMUM_CAPACITY;
int newCapacity = table.length;
while (newCapacity < targetCapacity)
newCapacity <<= 1;
if (newCapacity > table.length)
resize(newCapacity);
}
//遍历转移数据
for (Map.Entry<? extends K, ? extends V> e : m.entrySet())
put(e.getKey(), e.getValue());
}
//移除key值
public V remove(Object key) {
Entry<K,V> e = removeEntryForKey(key);
return (e == null ? null : e.value);
}
//移除key值
final Entry<K,V> removeEntryForKey(Object key) {
int hash = (key == null) ? 0 : hash(key);
int i = indexFor(hash, table.length);
Entry<K,V> prev = table[i];
Entry<K,V> e = prev;
while (e != null) {
//e指向链表的当前对象，next指向当前的下一个对象
Entry<K,V> next = e.next;
Object k;
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k)))) {
modCount++;
size--;
if (prev == e)//如果链表的表头就是该元素，则将table的该元组指向当前元素的下一个元素，否则prev的next指向当前元素的next，prev会随着链表遍历依次后移，指向该元素的父元素
table[i] = next;
else
prev.next = next;
e.recordRemoval(this);
return e;
}
prev = e;
e = next;
}
return e;
}
//依据Entry移除一个对象
final Entry<K,V> removeMapping(Object o) {
if (!(o instanceof Map.Entry))
return null;
Map.Entry<K,V> entry = (Map.Entry<K,V>) o;
Object key = entry.getKey();
//此处和上面的removeEntryForKey(key)唯一不同的是：匹配时，e.equals(entry)整个对象匹配，上面只匹配了key，调用该方法value值不相同也无法移除，为私有方法更好些（个人意见）
int hash = (key == null) ? 0 : hash(key);
int i = indexFor(hash, table.length);
Entry<K,V> prev = table[i];
Entry<K,V> e = prev;
while (e != null) {
Entry<K,V> next = e.next;
if (e.hash == hash && e.equals(entry)) {
modCount++;
size--;
if (prev == e)
table[i] = next;
else
prev.next = next;
//该行代码什么都没干，看着挺恐怖的
e.recordRemoval(this);
return e;
}
prev = e;
e = next;
}
return e;
}
//清空map所有值
public void clear() {
modCount++;
Entry[] tab = table;
for (int i = 0; i < tab.length; i++)
tab[i] = null;
size = 0;
}
//判断是否包含值，需要循环遍历数组和链表，效率相比key不高
public boolean containsValue(Object value) {
if (value == null)
return containsNullValue();
Entry[] tab = table;
for (int i = 0; i < tab.length ; i++)
for (Entry e = tab[i] ; e != null ; e = e.next)
if (value.equals(e.value))
return true;
return false;
}
//判断是否包含有值为null的value，找到一个就退出，循环遍历
private boolean containsNullValue() {
Entry[] tab = table;
for (int i = 0; i < tab.length ; i++)
for (Entry e = tab[i] ; e != null ; e = e.next)
if (e.value == null)
return true;
return false;
}
//对象的复制
public Object clone() {
HashMap<K,V> result = null;
try {
result = (HashMap<K,V>)super.clone();
} catch (CloneNotSupportedException e) {
// assert false;
}
result.table = new Entry[table.length];
result.entrySet = null;
result.modCount = 0;
result.size = 0;
result.init();
result.putAllForCreate(this);
return result;
}
//此处的静态内部类定义了HashMap的单个元素存放方式
static class Entry<K,V> implements Map.Entry<K,V> {
//四个关键变量
final K key;
V value;
Entry<K,V> next;
int hash;
/**
* Creates new entry.
*/
Entry(int h, K k, V v, Entry<K,V> n) {
value = v;
next = n;
key = k;
hash = h;
}
public final K getKey() {
return key;
}
public final V getValue() {
return value;
}
public final V setValue(V newValue) {
V oldValue = value;
value = newValue;
return oldValue;
}
public final boolean equals(Object o) {
if (!(o instanceof Map.Entry))
return false;
Map.Entry e = (Map.Entry)o;
Object k1 = getKey();
Object k2 = e.getKey();
if (k1 == k2 || (k1 != null && k1.equals(k2))) {
Object v1 = getValue();
Object v2 = e.getValue();
if (v1 == v2 || (v1 != null && v1.equals(v2)))
return true;
}
return false;
}
public final int hashCode() {
return (key==null ? 0 : key.hashCode()) ^
(value==null ? 0 : value.hashCode());
}
public final String toString() {
return getKey() + "=" + getValue();
}
/**
* This method is invoked whenever the value in an entry is
* overwritten by an invocation of put(k,v) for a key k that's already
* in the HashMap.
*/
void recordAccess(HashMap<K,V> m) {
}
/**
* This method is invoked whenever the entry is
* removed from the table.
*/
void recordRemoval(HashMap<K,V> m) {
}
}
void addEntry(int hash, K key, V value, int bucketIndex) {
//判断是否需要调整大小，如果hash值不相同，则需要占用table的一个元素，需要从新判断是否需要扩容
if ((size >= threshold) && (null != table[bucketIndex])) {
resize(2 * table.length);
hash = (null != key) ? hash(key) : 0;
bucketIndex = indexFor(hash, table.length);
}
//创建新元素
createEntry(hash, key, value, bucketIndex);
}
void createEntry(int hash, K key, V value, int bucketIndex) {
//此处e为i位置当前链表
Entry<K,V> e = table[bucketIndex];
//创建新的链表，并把当前链表元素的next指向已存在的链表，若原先不存在链表，则next指向null
table[bucketIndex] = new Entry<>(hash, key, value, e);
size++;
}
//构建一个HashIterator用于KeyIterator，ValueIterator和EntryIterator，便于遍历HashMap
// 由他的迭代器可以看出，HashMap放入时，依据Hash值决定放入的位置，因此是无序的，
// 但是遍历时，遵循table自左向右，链表自上而下的顺序，是有序的，
// 因此，对于构建好的hashMap，每次遍历出来的结果顺序应该是固定的!!!
private abstract class HashIterator<E> implements Iterator<E> {
Entry<K,V> next; // next entry to return
int expectedModCount; // For fast-fail
int index; // current slot
Entry<K,V> current; // current entry
HashIterator() {
expectedModCount = modCount;
if (size > 0) { // advance to first entry
Entry[] t = table;
//此处执行完后，next指向table的下一个不为null的链表的头元素，初始化后指向table的第一个不为null的链表的头元素
while (index < t.length && (next = t[index++]) == null)
;
}
}
public final boolean hasNext() {
return next != null;
}
final Entry<K,V> nextEntry() {
if (modCount != expectedModCount)
throw new ConcurrentModificationException();
//取出当前元素，并将next指针向后移动
Entry<K,V> e = next;
if (e == null)
throw new NoSuchElementException();
//先判断该链表是否有后续，如果有后续，则next为当前元素的后续元素（同一个链表内，向后移）
if ((next = e.next) == null) {
Entry[] t = table;
//如果当前元素链表结构只有一个元素，则在table中向后移动，next指向table的下一个不为null的链表的头元素
while (index < t.length && (next = t[index++]) == null)
;
}
current = e;
return e;
}
public void remove() {
if (current == null)
throw new IllegalStateException();
if (modCount != expectedModCount)
throw new ConcurrentModificationException();
Object k = current.key;
current = null;
HashMap.this.removeEntryForKey(k);
expectedModCount = modCount;
}
}
//此处定义了三个游标
private final class ValueIterator extends HashIterator<V> {
public V next() {
return nextEntry().value;
}
}
private final class KeyIterator extends HashIterator<K> {
public K next() {
return nextEntry().getKey();
}
}
private final class EntryIterator extends HashIterator<Map.Entry<K,V>> {
public Map.Entry<K,V> next() {
return nextEntry();
}
}
//实例化三个游标
Iterator<K> newKeyIterator() {
return new KeyIterator();
}
Iterator<V> newValueIterator() {
return new ValueIterator();
}
Iterator<Map.Entry<K,V>> newEntryIterator() {
return new EntryIterator();
}
// Views
private transient Set<Map.Entry<K,V>> entrySet = null;
public Set<K> keySet() {
Set<K> ks = keySet;
return (ks != null ? ks : (keySet = new KeySet()));
}
//key集
private final class KeySet extends AbstractSet<K> {
public Iterator<K> iterator() {
//返回一个key游标
return newKeyIterator();
}
public int size() {
return size;
}
public boolean contains(Object o) {
return containsKey(o);
}
public boolean remove(Object o) {
return HashMap.this.removeEntryForKey(o) != null;
}
public void clear() {
HashMap.this.clear();
}
}
public Collection<V> values() {
Collection<V> vs = values;
return (vs != null ? vs : (values = new Values()));
}
private final class Values extends AbstractCollection<V> {
public Iterator<V> iterator() {
return newValueIterator();
}
public int size() {
return size;
}
public boolean contains(Object o) {
return containsValue(o);
}
public void clear() {
HashMap.this.clear();
}
}
public Set<Map.Entry<K,V>> entrySet() {
return entrySet0();
}
private Set<Map.Entry<K,V>> entrySet0() {
Set<Map.Entry<K,V>> es = entrySet;
return es != null ? es : (entrySet = new EntrySet());
}
private final class EntrySet extends AbstractSet<Map.Entry<K,V>> {
public Iterator<Map.Entry<K,V>> iterator() {
return newEntryIterator();
}
public boolean contains(Object o) {
if (!(o instanceof Map.Entry))
return false;
Map.Entry<K,V> e = (Map.Entry<K,V>) o;
Entry<K,V> candidate = getEntry(e.getKey());
return candidate != null && candidate.equals(e);
}
public boolean remove(Object o) {
return removeMapping(o) != null;
}
public int size() {
return size;
}
public void clear() {
HashMap.this.clear();
}
}
private void writeObject(java.io.ObjectOutputStream s)
throws IOException
{
Iterator<Map.Entry<K,V>> i =
(size > 0) ? entrySet0().iterator() : null;
// Write out the threshold, loadfactor, and any hidden stuff
s.defaultWriteObject();
// Write out number of buckets
s.writeInt(table.length);
// Write out size (number of Mappings)
s.writeInt(size);
// Write out keys and values (alternating)
if (size > 0) {
for(Map.Entry<K,V> e : entrySet0()) {
s.writeObject(e.getKey());
s.writeObject(e.getValue());
}
}
}
private static final long serialVersionUID = 362498820763181265L;
/**
* Reconstitute the {@code HashMap} instance from a stream (i.e.,
* deserialize it).
*/
private void readObject(java.io.ObjectInputStream s)
throws IOException, ClassNotFoundException
{
// Read in the threshold (ignored), loadfactor, and any hidden stuff
s.defaultReadObject();
if (loadFactor <= 0 || Float.isNaN(loadFactor))
throw new InvalidObjectException("Illegal load factor: " +
loadFactor);
// set hashSeed (can only happen after VM boot)
Holder.UNSAFE.putIntVolatile(this, Holder.HASHSEED_OFFSET,
sun.misc.Hashing.randomHashSeed(this));
// Read in number of buckets and allocate the bucket array;
s.readInt(); // ignored
// Read number of mappings
int mappings = s.readInt();
if (mappings < 0)
throw new InvalidObjectException("Illegal mappings count: " +
mappings);
int initialCapacity = (int) Math.min(
// capacity chosen by number of mappings
// and desired load (if >= 0.25)
mappings * Math.min(1 / loadFactor, 4.0f),
// we have limits...
HashMap.MAXIMUM_CAPACITY);
int capacity = 1;
// find smallest power of two which holds all mappings
while (capacity < initialCapacity) {
capacity <<= 1;
}
table = new Entry[capacity];
threshold = (int) Math.min(capacity * loadFactor, MAXIMUM_CAPACITY + 1);
useAltHashing = sun.misc.VM.isBooted() &&
(capacity >= Holder.ALTERNATIVE_HASHING_THRESHOLD);
init(); // Give subclass a chance to do its thing.
// Read the keys and values, and put the mappings in the HashMap
for (int i=0; i<mappings; i++) {
K key = (K) s.readObject();
V value = (V) s.readObject();
putForCreate(key, value);
}
}
// These methods are used when serializing HashSets
int capacity() { return table.length; }
float loadFactor() { return loadFactor; }
}
上面的源代码注释已经对HashMap进行了详细的剖析，从上面可以看出：
- HashMap的具体实现是由数组加链表模式，数组的大小初始化为16，默认扩容因子为0.75，也就是说元素个数达到12个时，就开始扩容。
- 放入时（put操作），先通过key值计算hash值，如果通过hash值hash%length计算直接求得数组中放置位置，遍历该位置的链表，如果有则替换，没有则新加（新的元素处于链表头部）。
- 取出时（get操作），和放入遍历方式类似
- 由此可得出结论，HashMap放入时，如果元素个数正好达到扩容点，此时需要创建新数组，并将旧数组数据全部复制过去，时间消耗增大，或者发生哈希碰撞，hash值相同，需要存入链表中，如果链表过长，时间消耗也会增大，最坏的情况所有元素全部发生碰撞，此时如果元素个数较多，则get的时候需要遍历整个链表，性能下降，此外，由放入规则可知，最后放入的元素检索速度最快。
- 扩容因子对HashMap放入和访问时间和空间两方面的影响：
由上面可以知道，table放入位置是由：hash%length计算出来的，扩容因子越大，length就越小（在table很满的情况下才去扩容，当然length变小了）hash%length的值也就越小（如23400%16=8，23400%1024=872），数据都保存在链表中，会使得检索效率降低，时间消耗增大，空间利用率变高。扩容因子越小，则相反，检索速度变快，效率高，但空间利用率下降，table中有好多空值。默认取0.75 - HashMap的链表中，hash值不一定相同，只是hash值和length求模后得到index，因此在扩容时，需要遍历整个Map，重新决定放置位置，同时链表结构也会随之改变，而不是简单地内存复制。
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