概述
HashMap 主要来存放键值对。JDK1.8 之前使用数组 + 链表的形式，JDK1.8 之后进行了改变，使用了数组 + 链表或者红黑树的形式。
小概念普及
关系运算简介
| 0 0 | 0 1 | 1 1 | |
|---|---|---|---|
| 与 & | 0 | 0 | 1 |
| 或 \ | 0 | 1 | 1 |
| 异或 ^ | 0 | 1 | 0 |
非～ ～1=0 ～0=1
成员变量
/**
* The default initial capacity - MUST be a power of two.
* 默认的初始容量，必须是 2 的次幂
*/
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.
* 最大容量
*/
static final int MAXIMUM_CAPACITY = 1 << 30;
/**
* The load factor used when none specified in constructor.
* 默认的负载因子
*/
static final float DEFAULT_LOAD_FACTOR = 0.75f;
/**
* 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.
* 红黑树阈值，链表元素个数大于等于此值则转化为红黑树
*/
static final int TREEIFY_THRESHOLD = 8;
/**
* 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.
* 普通链表阈值，红黑树元素个数小于等于此值则转化为普通链表
*/
static final int UNTREEIFY_THRESHOLD = 6;
/**
* 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.
* 桶中结构转化为红黑树对应的 table 的最小大小
*/
static final int MIN_TREEIFY_CAPACITY = 64;
/**
* 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.)
* 存储数据的桶数组，数组大小总是 2 的次幂。*/
transient Node<K,V>[] table;
/**
* Holds cached entrySet(). Note that AbstractMap fields are used
* for keySet() and values().
* 存放具体元素的 set
*/
transient Set<Map.Entry<K,V>> entrySet;
/**
* The number of key-value mappings contained in this map.
* map 中的 key-value 个数
*/
transient int size;
/**
* The number of times this HashMap has been structurally modified
* Structural modifications are those that change the number of mappings in
* the HashMap or otherwise modify its internal structure (e.g.,
* rehash). This field is used to make iterators on Collection-views of
* the HashMap fail-fast. (See ConcurrentModificationException).
* HashMap 的扩容和修改次数计数器 用于判断 fail-fast
*/
transient int modCount;
/**
* The next size value at which to resize (capacity * load factor).
* 下一次扩容的阈值，元素个数到达此阈值即扩容
* @serial
*/
// (The javadoc description is true upon serialization.
// Additionally, if the table array has not been allocated, this
// field holds the initial array capacity, or zero signifying
// DEFAULT_INITIAL_CAPACITY.)
// 此外，如果 table 还没有被分配，则此值为初始容量或者 0
int threshold;
/**
* The load factor for the hash table.
* 负载因子
* @serial
*/
final float loadFactor;
构造方法
/**
* Constructs an empty <tt>HashMap</tt> with the specified initial
* capacity and load factor.
*
* @param initialCapacity the initial capacity
* @param loadFactor the load factor
* @throws IllegalArgumentException if the initial capacity is negative
* or the load factor is nonpositive
*/
public HashMap(int initialCapacity, float loadFactor) {
// 判断初始容量是否小于 0，小于 0 则报错
if (initialCapacity < 0)
throw new IllegalArgumentException("Illegal initial capacity:" +
initialCapacity);
// 判断初始容量是否大于最大容量，大于则置为最大容量
if (initialCapacity > MAXIMUM_CAPACITY)
initialCapacity = MAXIMUM_CAPACITY;
// 判断负载因子是否小于等于 0 是否是一个数字
if (loadFactor <= 0 || Float.isNaN(loadFactor))
throw new IllegalArgumentException("Illegal load factor:" +
loadFactor);
// 为负载因子赋值
this.loadFactor = loadFactor;
// 为扩容阈值赋值（tableSizeFor 函数用于找到大于 initialCapacity 的最近的 2 的次幂）this.threshold = tableSizeFor(initialCapacity);
}
/**
* Constructs an empty <tt>HashMap</tt> with the specified initial
* capacity and the default load factor (0.75).
*
* @param initialCapacity the initial capacity.
* @throws IllegalArgumentException if the initial capacity is negative.
*/
public HashMap(int initialCapacity) {
// 参数只有初始容量，使用默认负载因子，并调用另一个构造方法
this(initialCapacity, DEFAULT_LOAD_FACTOR);
}
/**
* Constructs an empty <tt>HashMap</tt> with the default initial capacity
* (16) and the default load factor (0.75).
*/
public HashMap() {
// 无参数 则只制定默认负载因子
this.loadFactor = DEFAULT_LOAD_FACTOR; // all other fields defaulted
}
/**
* Constructs a new <tt>HashMap</tt> with the same mappings as the
* specified <tt>Map</tt>. The <tt>HashMap</tt> is created with
* default load factor (0.75) and an initial capacity sufficient to
* hold the mappings in the specified <tt>Map</tt>.
*
* @param m the map whose mappings are to be placed in this map
* @throws NullPointerException if the specified map is null
*/
public HashMap(Map<? extends K, ? extends V> m) {
this.loadFactor = DEFAULT_LOAD_FACTOR;
putMapEntries(m, false);
}
/**
* Returns a power of two size for the given target capacity.
* 根据传入的值返回一个 2 的次幂
*/
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;
}可以看出以上的所有的初始化过程都没有对 talbe 进行初始化。并且在传入 initialCapacity 的构造函数中对 threshold 进行了初始化，所以 threshold 除了记录扩容阈值之外，还在 HashMap 初始化时记录初始容量或直接置为 0。
node 的数据结构
/**
* 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;
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() {
//key 与 value 的 hashCode 进行异或
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;
}
}hash 计算方法
/**
* Computes key.hashCode() and spreads (XORs) higher bits of hash
* to lower. Because the table uses power-of-two masking, sets of
* hashes that vary only in bits above the current mask will
* always collide. (Among known examples are sets of Float keys
* holding consecutive whole numbers in small tables.) So we
* apply a transform that spreads the impact of higher bits
* downward. There is a tradeoff between speed, utility, and
* quality of bit-spreading. Because many common sets of hashes
* are already reasonably distributed (so don't benefit from
* spreading), and because we use trees to handle large sets of
* collisions in bins, we just XOR some shifted bits in the
* cheapest possible way to reduce systematic lossage, as well as
* to incorporate impact of the highest bits that would otherwise
* never be used in index calculations because of table bounds.
*/
static final int hash(Object key) {
int h;
return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16);
}put
普通的 put 方法
可见普通的 put 方法仅仅是接收了 key value 参数并调用了 putVal 方法 /**
* Associates the specified value with the specified key in this map.
* If the map previously contained a mapping for the key, the old
* value is replaced.
* 在 map 中创建 key 与 value 的对应关系，如果 map 中之前已经存在 key 的对应关系，则之前的对应关系会被替换。* @param key key with which the specified value is to be associated
* @param value value to be associated with the specified key
* @return the previous value associated with <tt>key</tt>, or
* <tt>null</tt> if there was no mapping for <tt>key</tt>.
* (A <tt>null</tt> return can also indicate that the map
* previously associated <tt>null</tt> with <tt>key</tt>.)
*/
public V put(K key, V value) {return putVal(hash(key), key, value, false, true);
}putAll 方法
putAll 是直接调用了 putMapEntries 方法 /**
* Copies all of the mappings from the specified map to this map.
* These mappings will replace any mappings that this map had for
* any of the keys currently in the specified map.
* 从传入的 map 中复制所有的对应关系到当前 map，如果一个 key 值在传入的 map 和当前 map 中皆有对应关系，则可能会覆盖当前 map 中的对应关系会被覆盖。* @param m mappings to be stored in this map
* @throws NullPointerException if the specified map is null
*/
public void putAll(Map<? extends K, ? extends V> m) {putMapEntries(m, true);
} /**
* Implements Map.putAll and Map constructor
* 把传入的 map 加入本 HashMap，用于 Map.putAll 或者构造 map
* @param m the map 传入的 map
* @param evict false when initially constructing this map, else
* true (relayed to method afterNodeInsertion). 如果是初始化构造时
使用为 false，其余时候为 true
*/
final void putMapEntries(Map<? extends K, ? extends V> m, boolean evict) {
// 获取传入 map 的大小
int s = m.size();
// 如果传入的 map 有元素则进入
if (s > 0) {
// 如果本 HashMap 尚未初始化
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);
}
// 如果本 HashMap 已经初始化但是传入 map 的大小大于了当前的扩容阈值则调整 map 的大小
// 注意此处是用传入的 map 大小与当前 map 的 threshold 进行比较
// 理论上说应该用当前 map 的大小与传入 map 的大小的和与 threshold 进行比较
// 在 jdk1.7 版本中有如下一段注释来解释这个行为
/*
* Expand the map if the map if the number of mappings to be added
* is greater than or equal to threshold. This is conservative; the
* obvious condition is (m.size() + size) >= threshold, but this
* condition could result in a map with twice the appropriate capacity,
* if the keys to be added overlap with the keys already in this map.
* By using the conservative calculation, we subject ourself
* to at most one extra resize.
*/
/* 当待加入的映射关系个数大于 threshold 时对 map 进行扩容。这是一个保守的方法，很显然判断条件应该是 (m.size()+size)>=threshold，不过这个条件可能会让 map 的容量比实际需要容量大一倍, 因为在传入的 map 中可能会有和当前 map 重复的 key（重复的 key 会被覆盖，所以实际容量会比 m.size()+size 小）. 所以使用保守的计算方法，最多进行一次额外的扩容。*/
else if (s > threshold)
// 调整 map 大小
resize();
// 循环向添加当前 map 添加原 map 中数据
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 方法的最终函数 putVal
/**
* Implements Map.put and related methods
*
* @param hash hash for key
* @param key the key
* @param value the value to put
* @param onlyIfAbsent if true, don't change existing value
如果为 true 则不修改已经存在的值
* @param evict if false, the table is in creation mode.
如果为 false 则进入创建模式（初始化）* @return previous value, or null if none
*/
final V putVal(int hash, K key, V value, boolean onlyIfAbsent,
boolean evict) {Node<K,V>[] tab; Node<K,V> p; int n, i;
// 如果 table 没有初始化或者 tab 的长度为 0 则初始化 table
if ((tab = table) == null || (n = tab.length) == 0)
// 初始化 table 并取得 table 的长度
n = (tab = resize()).length;
// 取得 tab 中放入的位置的值为 p，如果 p 为 null 则 hash 没有冲突 直接放入
// n 为 2 的次幂 n- 1 为一个全 1 项 与 hash 与可得到一个小于 n 的比较均匀的分布值
// 例如 n 为 32 hash 为 40 则有如下运算
//n :00000000000000000000000000100000
//n-1:00000000000000000000000000011111
//40 :00000000000000000000000000101000
//(n-1)&40:00000000000000000000000000001000 = 8
// 故放入 table[8] 中
if ((p = tab[i = (n - 1) & hash]) == null)
tab[i] = newNode(hash, key, value, null);
// 如果放入的位置当前有值则进行链表或红黑树的插入
else {
Node<K,V> e; K k;
// 如果 key 与当前 p 中 key 相同则找到了赋值的位置，的把 p 值直接赋值给 e 以供最后统一赋值
if (p.hash == hash &&
((k = p.key) == key || (key != null && key.equals(k))))
e = p;
// 如果 p 为一个树节点 则进入树节点处理流程
else if (p instanceof TreeNode)
e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
// 如果不为树节点 则进入链表处理流程
else {
// 循环遍历链表
for (int binCount = 0; ; ++binCount) {
// 如果遍历到了链表的末尾
if ((e = p.next) == null) {
// 新建节点并插入到表尾
p.next = newNode(hash, key, value, null);
// 如果链表长度等于了树化阈值则进行树化
if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st
treeifyBin(tab, hash);
break;
}
// 判断当前节点的 key 是否与传入的 key 相同，相同则直接结束循环（找到了赋值的位置）if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k))))
break;
p = e;
}
}
// 判断 e 是否为 null 即是否是找到了 key 相同的历史映射 如果在面直接插入了新映射此处 e 应为 null
if (e != null) { // existing mapping for key
// 取得旧值
V oldValue = e.value;
// 如果 onlyIfAbsent 为 false 即修改已经存在的值 或者 oldValue 为 null 则重新赋值
if (!onlyIfAbsent || oldValue == null)
e.value = value;
//HashMap 中无用
afterNodeAccess(e);
return oldValue;
}
}
// 修改技术增加
++modCount;
// 调整 size 的值并判断是否大于了扩容阈值 如果大于扩容阈值则进行扩容
if (++size > threshold)
resize();
//HashMap 中无用
afterNodeInsertion(evict);
return null;
}get
/**
* Returns the value to which the specified key is mapped,
* or {@code null} if this map contains no mapping for the key.
*
* <p>More formally, if this map contains a mapping from a key
* {@code k} to a value {@code v} such that {@code (key==null ? k==null :
* key.equals(k))}, then this method returns {@code v}; otherwise
* it returns {@code null}. (There can be at most one such mapping.)
*
* <p>A return value of {@code null} does not <i>necessarily</i>
* indicate that the map contains no mapping for the key; it's also
* possible that the map explicitly maps the key to {@code null}.
* The {@link #containsKey containsKey} operation may be used to
* distinguish these two cases.
*
* @see #put(Object, Object)
*/
public V get(Object key) {
Node<K,V> e;
return (e = getNode(hash(key), key)) == null ? null : e.value;
}
/**
* Implements Map.get and related methods
*
* @param hash hash for key
* @param key the key
* @return the node, or null if none
*/
final Node<K,V> getNode(int hash, Object key) {Node<K,V>[] tab; Node<K,V> first, e; int n; K k;
// 如果 table 被初始化并且长度大于 0 且 key 中有值则进入判断否则返回 null
if ((tab = table) != null && (n = tab.length) > 0 &&
(first = tab[(n - 1) & hash]) != null) {
// 如果 table 中的值的 key 与传入的 key 相同则直接返回
if (first.hash == hash && // always check first node
((k = first.key) == key || (key != null && key.equals(k))))
return first;
// 如果 table 中的值 key 与传入的 key 不同则进入后续的数据结构进行判断
if ((e = first.next) != null) {if (first instanceof TreeNode)
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;
}扩容
/**
* 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.
* 初始化 table 大小或者对 table 大小进行翻倍。如果 table 为 null，则按照 threshold
字段中保存的初始容量进行分配。如果 table 不为 null，由于使用的是翻倍增加策略，则对
table 容量进行翻倍。并且之前在 table 中的元素应呆在原处或者移动到 2 倍位置处。* @return the table
*/
final Node<K,V>[] resize() {
// 缓存当前 table 为 oldTab
Node<K,V>[] oldTab = table;
// 获取 oldTab 的大小，为 oldCap
int oldCap = (oldTab == null) ? 0 : oldTab.length;
// 获取当前的扩容阈值
int oldThr = threshold;
// 初始化新的 table 大小与阈值为 0
int newCap, newThr = 0;
// 如果 oldCap 大于 0，即当前 map 中的 table 存有值
if (oldCap > 0) {
// 判断 oldCap 是否大于等于最大容量
if (oldCap >= MAXIMUM_CAPACITY) {
// 如果 oldCap 大于等于了最大容量则把扩容阈值赋为 int 的最大值
// 给一个足够大的值，以后尽量不再触发扩容
threshold = Integer.MAX_VALUE;
// 由于 oldCap 已经是最大值，故不再扩容 直接返回原 table
return oldTab;
}
// 如果 oldCap 小于最大容量（即不满足上一个判断条件）// 把 oldCap 的翻倍值赋给 newCap 并判断 newCap 的容量是否小于最大容量（此处 newCap 可能大于最大容量）// 如果 newCap 小于最大容量并且 oldCap 大于等于初始容量则把阈值翻倍
//todo 此处有个问题 为什么 oldCap 小于默认初始容量不行
else if ((newCap = oldCap << 1) < MAXIMUM_CAPACITY &&
oldCap >= DEFAULT_INITIAL_CAPACITY)
// 此处因为容量翻了一倍，阈值是容量 * 负载因子 所以阈值翻一倍即可（为了减少计算进行的性能优化，不然其实可以放到下面进行统一的阈值计算）newThr = oldThr << 1; // double threshold
}
// 如果 oldCap 等于 0，则证明 table 未初始化
// 此时如果 oldThr 大于 0 则证明 threshold 中存储的是 table 的初始化长度（详情参见构造方法部分，带有 initialCapacity 的构造方法会把 initialCapacity 赋给 threshold 进行缓存）else if (oldThr > 0) // initial capacity was placed in threshold
// 把 oldThr 存的初始长度赋给 newCap
newCap = oldThr;
// 如果 oldCap 为 0 并且 oldThr 为 0 则当前 map 使用不带参数的构造方法创建，且未进行过 put 和 get 操作（因为使用过则 table 会被初始化）else { // zero initial threshold signifies using defaults
// 新容量为初始化容量
newCap = DEFAULT_INITIAL_CAPACITY;
// 新阈值为初始化容量 * 负载因子
newThr = (int)(DEFAULT_LOAD_FACTOR * DEFAULT_INITIAL_CAPACITY);
}
// 如果新阈值为 0
// 表示在上面的第一个判断中 newCap 大于了最大容量或者 oldCap 小于了 DEFAULT_INITIAL_CAPACITY
// 即不满足如下的条件：else if ((newCap = oldCap << 1) < MAXIMUM_CAPACITY && oldCap >= DEFAULT_INITIAL_CAPACITY)
// 或者进入了上面的第二个判断（else if (oldThr > 0)）if (newThr == 0) {
// 计算新的阈值
float ft = (float)newCap * loadFactor;
// 如果新容量小于最大容量并且计算的阈值小于最大容量则使用计算后的负载因子
// 如果新容量大于等于了最大容量或者计算得到的阈值大于了最大容量则新阈值置为 int 的最大值（给一个足够大的值，以后尽量不再触发扩容）newThr = (newCap < MAXIMUM_CAPACITY && ft < (float)MAXIMUM_CAPACITY ?
(int)ft : Integer.MAX_VALUE);
}
// 更新当前 map 的扩容阈值
threshold = newThr;
// 以下是 table 扩容并重新赋值的逻辑
@SuppressWarnings({"rawtypes","unchecked"})
// 首先根据 newCap 创建新的 table
Node<K,V>[] newTab = (Node<K,V>[])new Node[newCap];
// 把当前 map 的 table 置为新创建的 table
table = newTab;
// 如果之前的 table 被初始化过（table 可能存有值）if (oldTab != null) {
// 遍历 oldTab
for (int j = 0; j < oldCap; ++j) {
Node<K,V> e;
// 把当前位置的 node 赋给 e，如果 e 不为 null，表示当前 node 中有值
if ((e = oldTab[j]) != null) {
// 把旧 table 中值置为 null（防止内存泄露）oldTab[j] = null;
// 如果 e.next 是 null 表示当前桶中只有一个值，把当前值放入相应位置即可
if (e.next == null)
newTab[e.hash & (newCap - 1)] = e;
// 如果 e 为树节点则进入树节点重分配相关函数
else if (e instanceof TreeNode)
((TreeNode<K,V>)e).split(this, newTab, j, oldCap);
// 进入链表节点重分配逻辑
else { // preserve order
// 当前节点的链表
Node<K,V> loHead = null, loTail = null;
// 偏移后的链表
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;
}