Map
HashMap（底层是数组+链表/红黑树，无序键值对集合，非线程安全)
- 基于哈希表实现，链地址法。
- loadFactor默认为0.75，threshold（阈)为12，并创建一个大小为16的Entry数组。
- 在遍历时是无序的，如需有序，建议使用TreeMap。
- 采用数组方式存储key、value构成的Entry对象，无容量限制。
- 基于key hash寻找Entry对象存放在数组中的位置，对于hash冲突采用链表/红黑树的方式来解决。
- HashMap在插入元素时可能会扩大数组的容量，在扩大容量时需要重新计算hash，并复制对象到新的数组中。
- 是非线程安全的。
- 哈希冲突时采用链表法的类，一个哈希桶多于8个元素改为TreeNode
- 哈希冲突时采用红黑树存储的类，一个哈希桶少于6个元素改为Node
- 某个桶对应的链表过长的话搜索效率低，改为红黑树效率会提高。
- 为何按位与而不是取摸 hashmap的iterator读取时是否会读到另一个线程put的数据 红黑树；hashmap报ConcurrentModificationException的情况
- Hash冲突中链表结构的数量大于8个，则调用树化转为红黑树结构，红黑树查找稍微快些；红黑树结构的数量小于6个时，则转为链表结构
- 如果加载因子越大，对空间的利用更充分，但是查找效率会降低（链表长度会越来越长)；如果加载因子太小，那么表中的数据将过于稀疏（很多空间还没用，就开始扩容了)，对空间造成严重浪费。如果我们在构造方法中不指定，则系统默认加载因子为0.75，这是一个比较理想的值，一般情况下我们是无需修改的。
- 一般对哈希表的散列很自然地会想到用hash值对length取模（即除法散列法)，Hashtable中也是这样实现的，这种方法基本能保证元素在哈希表中散列的比较均匀，但取模会用到除法运算，效率很低，HashMap中则通过h&(length-1)的方法来代替取模，同样实现了均匀的散列，但效率要高很多，这也是HashMap对Hashtable的一个改进。
- 哈希表的容量一定要是2的整数次幂。首先，length为2的整数次幂的话，h&(length-1)就相当于对length取模，这样便保证了散列的均匀，同时也提升了效率；其次，length为2的整数次幂的话，为偶数，这样length-1为奇数，奇数的最后一位是1，这样便保证了h&(length-1)的最后一位可能为0，也可能为1（这取决于h的值)，即与后的结果可能为偶数，也可能为奇数，这样便可以保证散列的均匀性，而如果length为奇数的话，很明显length-1为偶数，它的最后一位是0，这样h&(length-1)的最后一位肯定为0，即只能为偶数，这样任何hash值都只会被散列到数组的偶数下标位置上，这便浪费了近一半的空间，因此，length取2的整数次幂，是为了使不同hash值发生碰撞的概率较小，这样就能使元素在哈希表中均匀地散列。
Map#Entry（接口)
interface Entry<K,V> {
K getKey();
V getValue();
V setValue(V value);
boolean equals(Object o);
int hashCode();
public static <K extends Comparable<? super K>, V> Comparator<Map.Entry<K,V>> comparingByKey() {
return (Comparator<Map.Entry<K, V>> & Serializable)
(c1, c2) -> c1.getKey().compareTo(c2.getKey());
}
public static <K, V extends Comparable<? super V>> Comparator<Map.Entry<K,V>> comparingByValue() {
return (Comparator<Map.Entry<K, V>> & Serializable)
(c1, c2) -> c1.getValue().compareTo(c2.getValue());
}
public static <K, V> Comparator<Map.Entry<K, V>> comparingByKey(Comparator<? super K> cmp) {
Objects.requireNonNull(cmp);
return (Comparator<Map.Entry<K, V>> & Serializable)
(c1, c2) -> cmp.compare(c1.getKey(), c2.getKey());
}
public static <K, V> Comparator<Map.Entry<K, V>> comparingByValue(Comparator<? super V> cmp) {
Objects.requireNonNull(cmp);
return (Comparator<Map.Entry<K, V>> & Serializable)
(c1, c2) -> cmp.compare(c1.getValue(), c2.getValue());
}
}
HashMap#Node（Map.Entry的实现，链表的基本元素)
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() {
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;
}
}
HashMap#TreeNode（Map.Entry的实现，红黑树的基本元素)
static final class TreeNode<K,V> extends LinkedHashMap.Entry<K,V> {
TreeNode<K,V> parent; // red-black tree links
TreeNode<K,V> left;
TreeNode<K,V> right;
TreeNode<K,V> prev; // needed to unlink next upon deletion
boolean red;
TreeNode(int hash, K key, V val, Node<K,V> next) {
super(hash, key, val, next);
}
//...
}
LinkedHashMap#Entry
static class Entry<K,V> extends HashMap.Node<K,V> {
Entry<K,V> before, after;
Entry(int hash, K key, V value, Node<K,V> next) {
super(hash, key, value, next);
}
}
成员变量
/**
* The default initial capacity - MUST be a power of two.
*/
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.
*/
static final int MAXIMUM_CAPACITY = 1 << 30;
/**
* The load factor used when none specified in constructor.
*/
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.
*/
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.
*/
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.
*/
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.)
*/
transient Node<K,V>[] table;
/**
* Holds cached entrySet(). Note that AbstractMap fields are used
* for keySet() and values().
*/
transient Set<Map.Entry<K,V>> entrySet;
/**
* The number of key-value mappings contained in this map.
*/
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).
*/
transient int modCount;
/**
* The next size value at which to resize (capacity * load factor).
*
* @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.)
// HashMap的阈值，用于判断是否需要调整HashMap的容量（threshold = 容量*装载因子)
int threshold;
/**
* The load factor for the hash table.
*
* @serial
*/
final float loadFactor;
构造方法
注意哪怕是指定了初始容量，也不会直接初始化table，而是在第一次put时调用resize来初始化table，resize里会将threshold视为初始容量。
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;
// 阈值为不小于容量的2的幂次
this.threshold = tableSizeFor(initialCapacity);
}
public HashMap(int initialCapacity) {
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() {
this.loadFactor = DEFAULT_LOAD_FACTOR; // all other fields defaulted
}
tableSizeFor（找到大于等于initialCapacity的最小的2的幂次以及原因)
/**
* Returns a power of two size for the given target capacity.
*/
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;
}
hash（hash算法，算法比较高效、均匀)
- static final int hash(Object key) {
int h;
return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16);
}
- key的hash值高16位不变，低16位与高16位异或作为key的最终hash值。（h >>> 16，表示无符号右移16位，高位补0，任何数跟0异或都是其本身，因此key的hash值高16位不变。)
- 保证了对象的hashCode的高16位的变化能反应到低16位中，
hash to index
- 如何根据hash值计算index？（put和get中的代码)
- n = table.length;
- index = (n-1)& hash;
- 当n总是2的n次方时，hash & (n-1)运算等价于h%n，但是&比%具有更高的效率。
put
public V put(K key, V value) {
return putVal(hash(key), key, value, false, true);
}
- onlyIfAbsent如果为true，只有在hashmap没有该key的时候才添加
- evict如果为false，hashmap为创建模式；只有在使用Map集合作为构造器创建LinkedHashMap或HashMap时才会为false。
- 这两个参数均为实现java8的新接口而设置
Node<K,V> newNode(int hash, K key, V value, Node<K,V> next) {
return new Node<>(hash, key, value, next);
}
final V putVal(int hash, K key, V value, boolean onlyIfAbsent,
boolean evict) {
Node<K,V>[] tab; // table
Node<K,V> p; // node pointer
int n, i; // n 为length, i 为 node index
if ((tab = table) == null || (n = tab.length) == 0)
n = (tab = resize()).length;
// index处没有元素，则直接放入新节点
if ((p = tab[i = (n - 1) & hash]) == null)
tab[i] = newNode(hash, key, value, null);
else {
// index处有元素
Node<K,V> e;
if (p.hash == hash &&
((k = p.key) == key || (key != null && key.equals(k))))
// 假如key是相同的，那么替换value即可
e = p;
else if (p instanceof TreeNode)
// key不同，但如果p是红黑树根节点，那么将新节点放入红黑树
e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
else {
// key不同，但如果p是链表头节点，那么判断链表中是否有该节点，如没有，则将新节点插入到链表尾部
for (int binCount = 0; ; ++binCount) {
if ((e = p.next) == null) {
p.next = newNode(hash, key, value, null);
// 插入后如果发现已经链表长度已经适合转为红黑树了，则转换
if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st
treeifyBin(tab, hash);
break;
}
// 链表中某元素key和key相同，则替换value即可
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 resize
- 扩容函数，如果hash桶为空，初始化默认大小，否则双倍扩容
- 注意！！因为扩容为2的倍数，根据hash桶的计算方法，元素哈希值不变
- 所以元素在新的hash桶的下标，要不跟旧的hash桶下标一致，要不增加1倍。
- cap：capacity
- thr：threshold
- 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;
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) {
- j位置原本元素存在
oldTab[j] = null;
if (e.next == null)
- 如果该位置没有形成链表，则再次计算index，放入新table
- 假设扩容前的table大小为2的N次方，有上述put方法解析可知，元素的table索引为其hash值的后N位确定
- 那么扩容后的table大小即为2的N+1次方，则其中元素的table索引为其hash值的后N+1位确定，比原来多了一位
- 因此，table中的元素只有两种情况：
- 元素hash值第N+1位为0：不需要进行位置调整
- 元素hash值第N+1位为1：调整至原索引的两倍位置
newTab[e.hash & (newCap - 1)] = e;
else if (e instanceof TreeNode)
- 如果该位置形成了红黑树，则split
((TreeNode<K,V>)e).split(this, newTab, j, oldCap);
else { // preserve order
- 如果该位置形成了链表，则分成两个链表，分别放在0~oldCap,oldCap~oldCap*2位置处
Node<K,V> loHead = null, loTail = null;
Node<K,V> hiHead = null, hiTail = null;
Node<K,V> next;
do {
next = e.next;
// 用于确定元素hash值第N+1位是否为0：
// 若为0，则使用loHead与loTail，将元素移至新table的原索引处
// 若不为0，则使用hiHead与hiHead，将元素移至新table的两倍索引处
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;
}
get（O(logn))
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;
if ((tab = table) != null && (n = tab.length) > 0 &&
(first = tab[(n - 1) & hash]) != null) {
// table不为空，且hash对应index元素不为空
// 如果index位置就是我们要找的key，则直接返回
if (first.hash == hash && // always check first node
((k = first.key) == key || (key != null && key.equals(k))))
return first;
// 如果不是，则从链表或红黑树的角度继续找
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;
}
remove
public V remove(Object key) {
Node<K,V> e;
return (e = removeNode(hash(key), key, null, false, true)) == null ?
null : e.value;
}
// value=null,matchValue=false,movable=true
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;
// 1) 如果hash 对应index即为我们要找的key，则找到
if (p.hash == hash &&
((k = p.key) == key || (key != null && key.equals(k))))
node = p;
// 2) 从链表或红黑树的角度继续找
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);
}
}
// 找到后，根据找到的位置不同 相应地进行删除
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);
return node;
}
}
return null;
}
containsKey
public boolean containsKey(Object key) {
return getNode(hash(key), key) != null;
}
containsValue
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;
}
a)链表转红黑树 treeifyBin
/**
* Replaces all linked nodes in bin at index for given hash unless
* table is too small, in which case resizes instead.
*/
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)
resize();
else if ((e = tab[index = (n - 1) & hash]) != null) {
TreeNode<K,V> hd = null, tl = null;
do {
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);
}
}
红黑树转链表 TreeNode#untreeify
// 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;
}
### c)红黑树 查找
final TreeNode<K,V> getTreeNode(int h, Object k) {
return ((parent != null) ? root() : this).find(h, k, null);
}
/**
- Finds the node starting at root p with the given hash and key.
- The kc argument caches comparableClassFor(key) upon first use
- comparing keys.
*/
final TreeNode<K,V> find(int h, Object k, Class<?> kc) {
TreeNode<K,V> p = this;
do {
int ph, dir; K pk;
TreeNode<K,V> pl = p.left, pr = p.right, q;
if ((ph = p.hash) > h)
p = pl;
else if (ph < h)
p = pr;
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;
}
### d)红黑树 添加
- final TreeNode<K,V> putTreeVal(HashMap<K,V> map, Node<K,V>[] tab,
int h, K k, V v) {
Class<?> kc = null;
boolean searched = false;
TreeNode<K,V> root = (parent != null) ? root() : this;
for (TreeNode<K,V> p = root;;) {
int dir, ph; K pk;
if ((ph = p.hash) > h)
dir = -1;
else if (ph < h)
dir = 1;
else if ((pk = p.key) == k || (k != null && k.equals(pk)))
return p;
else if ((kc == null &&
(kc = comparableClassFor(k)) == null) ||
(dir = compareComparables(kc, k, pk)) == 0) {
if (!searched) {
TreeNode<K,V> q, ch;
searched = true;
if (((ch = p.left) != null &&
(q = ch.find(h, k, kc)) != null) ||
((ch = p.right) != null &&
(q = ch.find(h, k, kc)) != null))
return q;
}
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;
}
}
}
e)红黑树 删除
/**
* 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 || 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);
}
f)红黑树 遍历
遍历（先迭代table，再迭代bucket->链表/红黑树)
keySet
keySet().iterator()
public Set<K> keySet() {
Set<K> ks = keySet;
if (ks == null) {
ks = new KeySet();
keySet = ks;
}
return ks;
}
final class KeySet extends AbstractSet<K> {
public final Iterator<K> iterator() { return new KeyIterator(); }
}
KeyIterator实现了Iterator接口，并继承了HashIterator。前者仅适用于KeySet的迭代，后者适合所有基于HashMap的迭代。
HashMap#HashIterator
abstract class HashIterator {
Node<K,V> next; // next entry to return
Node<K,V> current; // current entry
int expectedModCount; // for fast-fail
int index; // current slot
HashIterator() {
expectedModCount = modCount;
Node<K,V>[] t = table;
current = next = null;
index = 0;
if (t != null && size > 0) { // advance to first entry
do {} while (index < t.length && (next = t[index++]) == null);
}
}
public final boolean hasNext() {
return next != null;
}
final Node<K,V> nextNode() {
Node<K,V>[] t;
Node<K,V> e = next;
if (modCount != expectedModCount)
throw new ConcurrentModificationException();
if (e == null)
throw new NoSuchElementException();
// next的next为空的话，则继续遍历table，否则就返回next的next（链表或红黑树的下一个节点)
if ((next = (current = e).next) == null && (t = table) != null) {
do {} while (index < t.length && (next = t[index++]) == null);
}
return e;
}
public final void remove() {
Node<K,V> p = current;
if (p == null)
throw new IllegalStateException();
if (modCount != expectedModCount)
throw new ConcurrentModificationException();
current = null;
K key = p.key;
removeNode(hash(key), key, null, false, false);
expectedModCount = modCount;
}
}
HashMap#KeyIterator
final class KeyIterator extends HashIterator
implements Iterator<K> {
public final K next() { return nextNode().key; }
}
entrySet
public Set<Map.Entry<K,V>> entrySet() {
Set<Map.Entry<K,V>> es;
return (es = entrySet) == null ? (entrySet = new EntrySet()) : es;
}
final class EntryIterator extends HashIterator
implements Iterator<Map.Entry<K,V>> {
public final Map.Entry<K,V> next() { return nextNode(); }
}
多线程环境下的问题
if ((e = p.next) == null) {
p.next = newNode(hash, key, value, null);
}
Hashtable
- Hashtable同样是基于哈希表实现的，同样每个元素是一个key-value对，其内部也是通过单链表解决冲突问题，容量不足（超过了阈值)时，同样会自动增长。
- Hashtable也是JDK1.0引入的类，是线程安全的，能用于多线程环境中。
- Hashtable同样实现了Serializable接口，它支持序列化，实现了Cloneable接口，能被克隆。
- Hashtable#Entry
private static class Entry<K,V> implements Map.Entry<K,V> {
final int hash;
final K key;
V value;
Entry<K,V> next;
protected Entry(int hash, K key, V value, Entry<K,V> next) {
this.hash = hash;
this.key = key;
this.value = value;
this.next = next;
}
@SuppressWarnings("unchecked")
protected Object clone() {
return new Entry<>(hash, key, value,
(next==null ? null : (Entry<K,V>) next.clone()));
}
// Map.Entry Ops
public K getKey() {
return key;
}
public V getValue() {
return value;
}
public V setValue(V value) {
if (value == null)
throw new NullPointerException();
V oldValue = this.value;
this.value = value;
return oldValue;
}
public boolean equals(Object o) {
if (!(o instanceof Map.Entry))
return false;
Map.Entry<?,?> e = (Map.Entry<?,?>)o;
return (key==null ? e.getKey()==null : key.equals(e.getKey())) &&
(value==null ? e.getValue()==null : value.equals(e.getValue()));
}
public int hashCode() {
return hash ^ Objects.hashCode(value);
}
public String toString() {
return key.toString()+"="+value.toString();
}
}
成员变量
/**
* The hash table data.
*/
private transient Entry<?,?>[] table;
/**
* The total number of entries in the hash table.
*/
private transient int count;
/**
* The table is rehashed when its size exceeds this threshold. (The
* value of this field is (int)(capacity * loadFactor).)
*
* @serial
*/
private int threshold;
/**
* The load factor for the hashtable.
*
* @serial
*/
private float loadFactor;
/**
* The number of times this Hashtable has been structurally modified
* Structural modifications are those that change the number of entries in
* the Hashtable or otherwise modify its internal structure (e.g.,
* rehash). This field is used to make iterators on Collection-views of
* the Hashtable fail-fast. (See ConcurrentModificationException).
*/
private transient int modCount = 0;
构造方法
public Hashtable(int initialCapacity, float loadFactor) {
if (initialCapacity < 0)
throw new IllegalArgumentException("Illegal Capacity: "+
initialCapacity);
if (loadFactor <= 0 || Float.isNaN(loadFactor))
throw new IllegalArgumentException("Illegal Load: "+loadFactor);
if (initialCapacity==0)
initialCapacity = 1;
this.loadFactor = loadFactor;
table = new Entry<?,?>[initialCapacity];
threshold = (int)Math.min(initialCapacity * loadFactor, MAX_ARRAY_SIZE + 1);
}
/**
* Constructs a new, empty hashtable with the specified initial capacity
* and default load factor (0.75).
*
* @param initialCapacity the initial capacity of the hashtable.
* @exception IllegalArgumentException if the initial capacity is less
* than zero.
*/
public Hashtable(int initialCapacity) {
this(initialCapacity, 0.75f);
}
/**
* Constructs a new, empty hashtable with a default initial capacity (11)
* and load factor (0.75).
*/
public Hashtable() {
this(11, 0.75f);
}
Hashtable 的容量增加逻辑是乘2+1，保证奇数。
在应用数据分布在等差数据集合(如偶数)上时，如果公差与桶容量有公约数n，则至少有(n-1)/n数量的桶是利用不到的。
hash to index
- int hash = key.hashCode();
int index = (hash & 0x7FFFFFFF) % tab.length; - 取与之后一定是一个非负数
- 0x7FFFFFFF is 0111 1111 1111 1111 1111 1111 1111 1111 : all 1 except the sign bit.
- (hash & 0x7FFFFFFF) will result in a positive integer.
- (hash & 0x7FFFFFFF) % tab.length will be in the range of the tab length.
put（有锁)
public synchronized V put(K key, V value) {
// Make sure the value is not null
if (value == null) {
throw new NullPointerException();
}
// Makes sure the key is not already in the hashtable.
Entry<?,?> tab[] = table;
int hash = key.hashCode();
int index = (hash & 0x7FFFFFFF) % tab.length;
@SuppressWarnings("unchecked")
Entry<K,V> entry = (Entry<K,V>)tab[index];
for(; entry != null ; entry = entry.next) {
if ((entry.hash == hash) && entry.key.equals(key)) {
V old = entry.value;
entry.value = value;
return old;
}
}
addEntry(hash, key, value, index);
return null;
}
private void addEntry(int hash, K key, V value, int index) {
modCount++;
Entry<?,?> tab[] = table;
if (count >= threshold) {
// Rehash the table if the threshold is exceeded
rehash();
tab = table;
hash = key.hashCode();
index = (hash & 0x7FFFFFFF) % tab.length;
}
// Creates the new entry.
@SuppressWarnings("unchecked")
Entry<K,V> e = (Entry<K,V>) tab[index];
tab[index] = new Entry<>(hash, key, value, e);
count++;
}
扩容 rehash
protected void rehash() {
int oldCapacity = table.length;
Entry<?,?>[] oldMap = table;
// overflow-conscious code
int newCapacity = (oldCapacity << 1) + 1;
if (newCapacity - MAX_ARRAY_SIZE > 0) {
if (oldCapacity == MAX_ARRAY_SIZE)
// Keep running with MAX_ARRAY_SIZE buckets
return;
newCapacity = MAX_ARRAY_SIZE;
}
Entry<?,?>[] newMap = new Entry<?,?>[newCapacity];
modCount++;
threshold = (int)Math.min(newCapacity * loadFactor, MAX_ARRAY_SIZE + 1);
table = newMap;
for (int i = oldCapacity ; i-- > 0 ;) {
for (Entry<K,V> old = (Entry<K,V>)oldMap[i] ; old != null ; ) {
Entry<K,V> e = old;
old = old.next;
// 所有元素重新散列
int index = (e.hash & 0x7FFFFFFF) % newCapacity;
e.next = (Entry<K,V>)newMap[index];
newMap[index] = e;
}
}
}
get（有锁)
public synchronized V get(Object key) {
Entry<?,?> tab[] = table;
int hash = key.hashCode();
int index = (hash & 0x7FFFFFFF) % tab.length;
for (Entry<?,?> e = tab[index] ; e != null ; e = e.next) {
if ((e.hash == hash) && e.key.equals(key)) {
return (V)e.value;
}
}
return null;
}
remove（有锁)
public synchronized V remove(Object key) {
Entry<?,?> tab[] = table;
int hash = key.hashCode();
int index = (hash & 0x7FFFFFFF) % tab.length;
@SuppressWarnings("unchecked")
Entry<K,V> e = (Entry<K,V>)tab[index];
for(Entry<K,V> prev = null ; e != null ; prev = e, e = e.next) {
if ((e.hash == hash) && e.key.equals(key)) {
modCount++;
if (prev != null) {
prev.next = e.next;
} else {
tab[index] = e.next;
}
count--;
V oldValue = e.value;
e.value = null;
return oldValue;
}
}
return null;
}
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