手撕HashMap源码
终于通过不屑努力,把源码中的重要部分全都看完了,每一行代码都看明白了,还写了注释
import java.lang.reflect.ParameterizedType;
import java.lang.reflect.Type;
import java.util.*;
import java.util.function.Consumer;
import java.util.function.Function;
public class MyHashMap<K, V> extends AbstractMap<K, V> implements Map<K, V> {
// 默认初始容量,必须是2的次幂
static final int DEFAULT_INITIAL_CAPACITY = 1 << 4;
// 最大容量,不能超过这个值
static final int MAXIMUM_CAPACITY = 1 << 30;
// 默认负载因子
static final float DEFAULT_LOAD_FACTOR = 0.75f;
// 链表阈值,超过这个值,需要扩容
static final int TREEIFY_THRESHOLD = 8;
// 红黑树转换为链表的阈值
static final int UNTREEIFY_THRESHOLD = 6;
// 哈希表的大小至少超过该值才将链表转换为红黑树
static final int MIN_TREEIFY_CAPACITY = 64;
static class Node<K, V> implements Map.Entry<K, V> {
// 哈希值
final int hash;
// 键
final K key;
// 值
V value;
// 下一个节点
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;
}
@Override
public K getKey() {
return key;
}
@Override
public V getValue() {
return value;
}
@Override
public V setValue(V value) {
V oldValue = this.value;
this.value = value;
return oldValue;
}
@Override
public boolean equals(Object o) {
// 判断是否是同一个对象
if (this == o)
return true;
// 判断是否是Map.Entry类
if (o instanceof Map.Entry) {
// 将对象转换为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) {
if (key == null)
return 0;
int hash = key.hashCode();
hash = hash ^ (hash >>> 16);
return hash;
}
static Class<?> comparableClassFor(Object x) {
if (x instanceof Comparable) {
Class<?> c;
Type[] ts, as;
Type t;
ParameterizedType p;
if ((c = x.getClass()) == String.class) // bypass checks
return c;
if ((ts = c.getGenericInterfaces()) != null) {
for (int i = 0; i < ts.length; ++i) {
if (((t = ts[i]) instanceof ParameterizedType) &&
((p = (ParameterizedType) t).getRawType() ==
Comparable.class) &&
(as = p.getActualTypeArguments()) != null &&
as.length == 1 && as[0] == c) // type arg is c
return c;
}
}
}
return null;
}
static int compareComparables(Class<?> kc, Object k, Object x) {
return (x == null || x.getClass() != kc ? 0 :
((Comparable) k).compareTo(x));
}
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;
}
@Override
public Set<Entry<K, V>> entrySet() {
return null;
}
// 哈希表,第一次使用的时候才会加载,必要时会重新设置大小
// 长度总是2的次幂
transient Node<K, V>[] table;
// 键值对集合
transient Set<Entry<K, V>> entrySet;
// 键值对数量
transient int size;
// modCount
transient int modCount;
// 当键值对数量达到阈值时,会进行扩容,这个阈值 = 容量 * 加载因子
int threshold;
// 加载因子
final float loadFactor;
public MyHashMap(int initialCapacity, float loadFactor) {
// 初始容量不能小于0
if (initialCapacity < 0)
throw new IllegalArgumentException("Illegal initial capacity: " + initialCapacity);
// 初始容量不能大于最大容量
if (initialCapacity > MAXIMUM_CAPACITY)
initialCapacity = MAXIMUM_CAPACITY;
// 加载因子不能小于 0
// 加载因子不能为NaN
if (loadFactor <= 0 || Float.isNaN(loadFactor)) {
throw new IllegalArgumentException("Illegal load factor: " + loadFactor);
}
this.loadFactor = loadFactor;
this.threshold = tableSizeFor(initialCapacity);
}
public MyHashMap(int initialCapacity) {
this(initialCapacity, DEFAULT_LOAD_FACTOR);
}
public MyHashMap() {
this.loadFactor = DEFAULT_LOAD_FACTOR; // all other fields defaulted
}
// 将传入的map中的键值对添加到哈希表中
public MyHashMap(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) {
int s = m.size();
if (s > 0) {
// hash表还没有初始化
if (table == null) {
// 计算哈希表的大小
float ft = ((float) s / loadFactor) + 1.0F;
int t = MAXIMUM_CAPACITY;
if (ft < (float) MAXIMUM_CAPACITY) {
t = (int) ft;
}
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);
}
}
}
/**
* 获取键值对数量
*
* @return
*/
public int size() {
return size;
}
public boolean isEmpty() {
return size == 0;
}
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;
// 经典三步走:
// 1.看桶是否为null
// 2.判断链表头和key是否相等
// 3.遍历链表(如果是红黑树去遍历红黑树)
if ((tab = table) != null && (n = tab.length) > 0 &&
(first = tab[(n - 1) & hash]) != null) {
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)
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;
}
final Node<K, V>[] resize() {
Node<K, V>[] oldTable = table;
// 获取旧数组长度
int oldCapacity = (oldTable == null) ? 0 : oldTable.length;
// 获取旧数组扩容阈值
int oldThreshold = threshold;
int newCapacity = 0;
int newThreshold = 0;
// 1.如果旧数组长度>0,那就扩容
if (oldCapacity > 0) {
// 2.容量大于最大容量,则直接返回
if (oldCapacity >= MAXIMUM_CAPACITY) {
threshold = Integer.MAX_VALUE;
return oldTable;
} else {
// 3.旧数组容量小于最大容量,则扩容。直接翻倍
if (oldCapacity >= DEFAULT_INITIAL_CAPACITY &&
(oldCapacity << 1) < MAXIMUM_CAPACITY) {
newCapacity = oldCapacity << 1;
newThreshold = oldThreshold << 1;
}
// 4.旧数组容量太大,无法翻倍
}
// 5.此时 oldCapacity == 0;
} else if (oldThreshold > 0) {
newCapacity = oldThreshold;
} else {
// oldCapacity == 0;
// oldThreshold == 0
// newCapacity = 16,newThreshold = 12
newCapacity = DEFAULT_INITIAL_CAPACITY;
newThreshold = (int) (DEFAULT_LOAD_FACTOR * DEFAULT_INITIAL_CAPACITY);
}
// newThreshold 说明没有更新阈值,自己计算新的阈值
// 可能是由于情况4,情况5
if (newThreshold == 0) {
float ft = (float) newCapacity * loadFactor;
newThreshold = (newCapacity < MAXIMUM_CAPACITY && ft < (float) MAXIMUM_CAPACITY ?
(int) ft : Integer.MAX_VALUE);
}
threshold = newThreshold;
Node<K, V>[] newTable = (Node<K, V>[]) new Node[newCapacity];
table = newTable;
if (oldTable != null) {
for (int j = 0; j < oldCapacity; j++) {
Node<K, V> e = oldTable[j];
if (e == null)
continue;
oldTable[j] = null;
if (e.next == null) {
// 该捅只有一个元素,讲该元素赋值到新的捅中
newTable[e.hash & (newCapacity - 1)] = e;
} else if (e instanceof TreeNode) {
((TreeNode<K, V>) e).split(this, newTable, j, oldCapacity);
} else {
// 原来桶上的链表,讲他们分成两个链表,放在新链表的两个桶上
// 举个例子,oldCapacity = 16
// 此时 j = 1
// 假设,现在链表上有 1、17、33、49这些元素
// 那么需要讲他们重新找到新桶,放在新桶的位置上
// 那么只会有两种结果,一种是放在1桶上,一种是放在17桶上
// 为啥源代码中会让e.hash & oldCap 是否等于0来分开链表
// 我们看下这些元素的二进制
// 1: 000001
// 17:010001
// 33:100001
// 49:110001
// 而16:010000
// 所以说只要二进制中倒数五位是1,那就说明是放在17桶上.否则就是放在1桶上
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 & oldCapacity) == 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;
newTable[j] = loHead;
}
if (hiTail != null) {
hiTail.next = null;
newTable[j + oldCapacity] = hiHead;
}
}
}
}
return newTable;
}
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 len, index;
// 如果table为空或者长度为0,表示还没有初始化,需要初始化
if ((tab = table) == null || (len = tab.length) == 0)
len = (tab = resize()).length;
// 计算keyhash后对应的捅索引,看是否为空
if ((p = tab[index = (len - 1) & hash]) == null)
tab[index] = newNode(hash, key, value, null);
else {
// 如果捅不为空,则需要遍历捅
// 检测key是否存在
Node<K, V> e;
K k;
// 如果第一个点就是要找的key
if (p.hash == hash && compareKey(key, p.key))
e = p;
// 如果第一个点不是要找的key,判断是红黑树吗
else if (p instanceof TreeNode)
e = ((TreeNode<K, V>) p).putTreeVal(this, tab, hash, key, value);
else {
// 不是红黑树,那就是链表
for (int binCount = 0; ; ++binCount) {
// 找到最后都没找到key
if ((e = p.next) == null) {
// 在链表尾部添加一个节点
p.next = newNode(hash, key, value, null);
// 查看链表个数是否大于等于8
if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st
// 转换为红黑树
treeifyBin(tab, hash);
break;
}
// 如果找到了,直接退出查找
if (e.hash == hash && compareKey(key, e.key))
break;
p = e;
}
}
// 表示存在要找的key
if (e != null) { // existing mapping for key
V oldValue = e.value;
if (!onlyIfAbsent || oldValue == null)
e.value = value;
// afterNodeAccess(e);
return oldValue;
}
}
++modCount;
// 如果元素个数大于阈值,则扩容
if (++size > threshold)
resize();
// afterNodeInsertion(evict);
return null;
}
final void treeifyBin(Node<K, V>[] tab, int hash) {
int len, index;
Node<K, V> e;
// 如果链表的大小超过8,但是哈希表的大小小于64,会进行扩容,等到满足了才会转换成红黑树
if (tab == null || (len = tab.length) < MIN_TREEIFY_CAPACITY)
resize();
else if ((e = tab[index = (len - 1) & hash]) != null) {
TreeNode<K, V> head = null, tail = null;
do {
// 尾插法,先将链表中的所有节点转换为树节点
TreeNode<K, V> p = replacementTreeNode(e, null);
if (tail == null)
head = p;
else {
p.prev = tail;
tail.next = p;
}
tail = p;
} while ((e = e.next) != null);
// 转换成红黑树
if ((tab[index] = head) != null)
head.treeify(tab);
}
}
public void putAll(Map<? extends K, ? extends V> m) {
putMapEntries(m, true);
}
final boolean compareKey(K k1, K k2) {
return Objects.equals(k1, k2);
}
@Override
public V remove(Object key) {
Node<K, V> e;
e = removeNode(hash(key), key, null, false, true);
if (e == null)
return null;
return e.value;
}
@Override
public boolean replace(K key, V oldValue, V newValue) {
Node<K, V> e;
V v;
if ((e = getNode(hash(key), key)) != null &&
((v = e.value) == oldValue || (v != null && v.equals(oldValue)))) {
e.value = newValue;
return true;
}
return false;
}
@Override
public V replace(K key, V value) {
Node<K, V> e;
if ((e = getNode(hash(key), key)) != null) {
V oldValue = e.value;
e.value = value;
return oldValue;
}
return null;
}
// matchValue : 是否需要比较value
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;
// 判断该key对应的桶是否有元素
if ((tab = table) != null && (n = tab.length) > 0 && (p = tab[index = (n - 1) & hash]) != null) {
// 查找到的key对应的node节点
Node<K, V> node = null;
Node<K, V> e;
K k;
V v;
// 头节点是不是
if (p.hash == hash && ((k = p.key) == key || (key != null && key.equals(k)))) {
node = p;
// 头节点不是,找下一个节点
} else if ((e = p.next) != null) {
// 如果是红黑树的话
if (p instanceof TreeNode) {
node = ((TreeNode<K, V>) p).getTreeNode(hash, key);
}
// 不是红黑树
else {
do {
if (e.hash == hash && compareKey(e.key, key)) {
node = e;
break;
}
p = e;
} while ((e = e.next) != null);
}
}
//
if (node != null && (!matchValue || (v = node.value) == value ||
(value != null && value.equals(v)))) {
// 找到的节点属于红黑树节点,从红黑树中删除
if (node instanceof TreeNode) {
((TreeNode<K, V>) node).removeTreeNode(this, tab, movable);
// node是找到的节点,p是链表头,如果node正好是链表头的话,直接删除头节点
} else if (node == p) {
tab[index] = node.next;
} else {
// 此时p是当node的上一个节点
p.next = node.next;
}
++modCount;
--size;
return node;
}
}
return null;
}
// 删除所有的元素
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;
}
}
}
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;
}
@Override
public V getOrDefault(Object key, V defaultValue) {
Node<K, V> e;
return (e = getNode(hash(key), key)) == null ? defaultValue : e.value;
}
@Override
public V putIfAbsent(K key, V value) {
// 当不存在时才添加
return putVal(hash(key), key, value, true, true);
}
// 当不存在时,执行mappingFunction方法,否则返回之前的值
@Override
public V computeIfAbsent(K key, Function<? super K, ? extends V> mappingFunction) {
if (mappingFunction == null)
throw new NullPointerException();
int hash = hash(key);
Node<K, V>[] tab;
Node<K, V> first; // 头节点
int n, i; // n:tab长度,i:hash & n - 1
int binCount = 0;
TreeNode<K, V> t = null; // 红黑树的头节点
Node<K, V> old = null; // 之前的值
// 当该key对应的桶为null,重新resize
if (size > threshold || (tab = table) == null || (n = tab.length) == 0) {
n = (tab = resize()).length;
}
if ((first = tab[i = (n - 1) & hash]) != null) {
if (first instanceof TreeNode) {
old = (t = (TreeNode<K, V>) first).getTreeNode(hash, key);
} else {
Node<K, V> e = first;
K k;
// 遍历链表
do {
if (e.hash == hash &&
((k = e.key) == key) || (key != null && key.equals(k))) {
old = e;
break;
}
++binCount;
} while ((e = e.next) != null);
}
V oldValue;
if (old != null && (oldValue = old.value) != null) {
return oldValue;
}
}
// 走到这里说明该key在hash表中不存在或者对应的value不存在
V v = mappingFunction.apply(key);
if (v == null) {
return null;
// v!=null 并且 old !=null, 说明该key已经存在,但是 vlaue == null
} else if (old != null) {
old.value = v;
return v;
}
// 表示该key在哈希表中不存在
// 并且该key对应的桶是红黑树节点,那么就加入到红黑树中
else if (t != null) {
t.putTreeVal(this, tab, hash, key, v);
} else {
// 该桶是链表节点
tab[i] = newNode(hash, key, v, first);
if (binCount >= TREEIFY_THRESHOLD - 1) {
treeifyBin(tab, hash);
}
}
++modCount;
++size;
return v;
}
TreeNode<K, V> replacementTreeNode(Node<K, V> p, Node<K, V> next) {
return new TreeNode<>(p.hash, p.key, p.value, next);
}
static final class TreeNode<K, V> extends MyLinkedHashMap.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);
}
final TreeNode<K, V> root() {
TreeNode<K, V> p = this;
while (p.parent != null) {
p = p.parent;
}
return p;
}
// 将链表转换为红黑树
final void treeify(Node<K, V>[] tab) {
TreeNode<K, V> root = null;
for (TreeNode<K, V> x = this, next; x != null; x = next) {
next = (TreeNode<K, V>) x.next;
x.left = x.right = null;
// 如果根节点为空,则直接作为根节点
if (root == null) {
x.parent = null;
x.red = false;
root = x;
} else {
// 根节点不为空,则需要找到该节点在红黑树中的位置
// 找到该key在红黑树中插入的位置
K k = x.key;
int h = x.hash;
Class<?> kc = null;
TreeNode<K, V> p = root;
while (true) {
// 向左还是向右 -1 表示向左, 1表示向右
int dir;
int ph = p.hash;
K pk = p.key;
// 如果hash值小于当前节点的hash值,则向左子树查找
if (h < ph) {
dir = -1;
// 如果hash值大于当前节点的hash值,则向右子树查找
} else if (h > ph) {
dir = 1;
// 如果hash值等于当前节点的hash值,则比较key
} else if ((kc == null &&
(kc = comparableClassFor(k)) == null) ||
(dir = compareComparables(kc, k, pk)) == 0)
dir = tieBreakOrder(k, pk);
TreeNode<K, V> xp = p;
if (dir <= 0) {
p = p.left;
} else {
p = p.right;
}
if (p == null) {
x.parent = xp;
if (dir <= 0) {
xp.left = x;
} else {
xp.right = x;
}
root = balanceInsertion(root, x);
break;
}
}
}
}
moveRootToFront(tab, root);
}
// 红黑树转换为列表
final Node<K, V> untreeify(MyHashMap<K, V> map) {
Node<K, V> head = null, tail = null;
// 这里我保证是红黑树的根节点
Node<K, V> q = root();
while (q != null) {
Node<K, V> p = map.replacementNode(q, null);
if (tail == null)
head = p;
else
tail.next = p;
tail = p;
q = q.next;
}
return head;
}
// 最终裁决方法
// 1.先比较a,b的类名字符串,看返回值是不是0
// 2.仍然返回0的话,调用System.identityHashCode去比较
// System.identityHashCode会强制调用Object.hashCode()
static int tieBreakOrder(Object a, Object b) {
int d;
if (a == null || b == null ||
(d = a.getClass().getName().
compareTo(b.getClass().getName())) == 0)
d = (System.identityHashCode(a) <= System.identityHashCode(b) ?
-1 : 1);
return d;
}
final TreeNode<K, V> putTreeVal(MyHashMap<K, V> map, Node<K, V>[] tab,
int h, K k, V v) {
Class<?> kc = null;
// 是否找到key
boolean searched = false;
// 找到该红黑树的根节点
TreeNode<K, V> root = root();
TreeNode<K, V> p = root;
while (true) {
int dir;
int ph = p.hash;
K pk = p.key;
if (h < ph) {
dir = -1;
} else if (h > ph) {
dir = 1;
} else if (pk == 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;
ch = p.left;
// 从左子树中找
if (ch != null && (q = ch.find(h, k, kc)) != null) {
return q;
}
ch = p.right;
// 从右子树中找
if (ch != null && (q = ch.find(h, k, kc)) != null) {
return q;
}
}
dir = tieBreakOrder(k, pk);
}
TreeNode<K, V> xp = p;
if (dir <= 0)
p = p.left;
else
p = p.right;
if (p == 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 = xp;
x.prev = xp;
if (xpn != null) {
((TreeNode<K, V>) xpn).prev = x;
}
root = balanceInsertion(root, x);
moveRootToFront(tab, root);
return null;
}
}
}
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;
// 比较hash值
// 给定hash小于当前节点的hash值,则向左子树查找
if ((ph = p.hash) > h)
p = pl;
// 给定hash大于当前节点的hash值,则向右子树查找
else if (ph < h)
p = pr;
// 如果hash相等,则比较key,如果key也相等,那直接返回
else if ((pk = p.key) == k || (k != null && k.equals(pk)))
return p;
// 如果hash相等,但是key不相等,说明还需要继续往下找
// 这个节点可能在左子树也可能在右子树
// 如果当前节点的左子树为空,则向右子树查找
else if (pl == null)
p = pr;
else if (pr == null)
p = pl;
// 左子树和右子树都不为空
// 看这个插入的类是不是可比较的
// 如果不是
else if ((kc != null ||
(kc = comparableClassFor(k)) != null) &&
(dir = compareComparables(kc, k, pk)) != 0)
p = (dir < 0) ? pl : pr;
// 如果k是不可比较类型,那这里有什么作用呢?
// TODO: 待补充
else if ((q = pr.find(h, k, kc)) != null)
return q;
// 如果确定不了,那就从左子树开始找
else
p = pl;
} while (p != null);
return null;
}
final TreeNode<K, V> getTreeNode(int h, Object k) {
TreeNode<K, V> p = root();
return p.find(h, k, null);
}
static <K, V> void moveRootToFront(Node<K, V>[] tab, TreeNode<K, V> root) {
if (root == null || tab == null || tab.length == 0)
return;
int len = tab.length;
int index = root.hash & (len - 1);
TreeNode<K, V> first = (TreeNode<K, V>) tab[index];
// 如果根节点不是第一个节点,则需要将根节点放到链表第一个位置
if (root != first) {
tab[index] = root;
TreeNode<K, V> rp = root.prev;
TreeNode<K, V> rn = (TreeNode<K, V>) root.next;
if (rn != null)
rn.prev = rp;
if (rp != null)
rp.next = rn;
if (first != null)
first.prev = root;
root.next = first;
root.prev = null;
}
}
final void split(MyHashMap<K, V> map, Node<K, V>[] tab, int index, int bit) {
// bit : oldCapacity
TreeNode<K, V> b = this;
TreeNode<K, V> loHead = null, loTail = null;
TreeNode<K, V> hiHead = null, hiTail = null;
int lc = 0, hc = 0;
for (TreeNode<K, V> e = b, next; e != null; e = next) {
next = (TreeNode<K, V>) e.next;
e.next = null;
if ((e.hash & bit) == 0) {
if ((e.prev = loTail) == null) {
loHead = e;
} else {
loTail.next = e;
}
loTail = e;
++lc;
} else {
if ((e.prev = hiTail) == null) {
hiHead = e;
} else {
hiTail.next = e;
}
hiTail = e;
++hc;
}
}
if (loHead != null) {
// 如果链表个数小于等于6,退化成链表
if (lc <= UNTREEIFY_THRESHOLD) {
tab[index] = loHead.untreeify(map);
} else {
tab[index] = loHead;
// 如果hiHead != null,说明分成了两个红黑树。
// 那么就需要重新构建红黑树
if (hiHead != null) {
loHead.treeify(tab);
}
}
}
if (hiHead != null) {
if (hc <= UNTREEIFY_THRESHOLD) {
tab[index + bit] = hiHead.untreeify(map);
} else {
tab[index + bit] = hiHead;
if (loHead != null) {
hiHead.treeify(tab);
}
}
}
}
static <K, V> TreeNode<K, V> rotateLeft(TreeNode<K, V> root, TreeNode<K, V> p) {
if (p == null || p.right == null)
return root;
TreeNode<K, V> pp = p.parent; // 父节点
TreeNode<K, V> pr = p.right; // 右孩子
TreeNode<K, V> prl = pr.left;// 右孩子的左孩子
p.right = prl;
if (prl != null) {
prl.parent = p;
}
pr.parent = pp;
if (pp == null) {
root = pr;
root.red = false;
} else if (p == pp.left) {
pp.left = pr;
} else {
pp.right = pr;
}
pr.left = p;
p.parent = pr;
return root;
}
static <K, V> TreeNode<K, V> rotateRight(TreeNode<K, V> root, TreeNode<K, V> p) {
if (p == null || p.left == null)
return root;
TreeNode<K, V> pp = p.parent;
TreeNode<K, V> pl = p.left;
TreeNode<K, V> plr = pl.left;
p.left = plr;
if (plr != null) {
plr.parent = p;
}
// 更新旋转节点的父节点
pl.parent = pp;
if (pp == null) {
root = pl;
root.red = false;
} else if (p == pp.left) {
pp.left = pl;
} else {
pp.right = pl;
}
pl.right = p;
p.parent = pl;
return root;
}
static <K, V> TreeNode<K, V> balanceInsertion(TreeNode<K, V> root,
TreeNode<K, V> x) {
// x 为插入节点,将其颜色设置为null
x.red = true;
TreeNode<K, V> xp, xpp, xppl, xppr;
while (true) {
xp = x.parent;
// 1.如果插入节点的父亲为null,则它是根节点
// 并将其设置成黑色
if (xp == null) {
x.red = false;
return x;
// 如果父亲节点为黑色,那么插入一个红色节点不会影响平衡,直接返回
} else if (!xp.red) {
return root;
} else {
// TODO: 如果父亲节点是根节点的话,那不应该是黑色嘛
xpp = xp.parent;
if (xpp == null) {
return root;
}
}
// 此时父亲肯定是红色
xppl = xpp.left;
xppr = xpp.right;
if (xp == xppl) {
if (xppr != null && xppr.red) {
xppr.red = false;
xp.red = false;
xpp.red = true;
// 将爷爷节点设置为插入节点,因为爷爷节点变成了红色,
// 可能会破坏平衡,所以需要重新走一遍平衡
x = xpp;
} else {
// 到这里,证明它的叔叔节点为空或者为黑色
// 如果插入节点是父亲节点的右孩子
if (x == xp.right) {
// 先将父节点左旋
x = xp;
root = rotateLeft(root, x);
xp = x.parent;
xpp = xp == null ? null : xp.parent;
}
// 如果有父节点
if (xp != null) {
// 父节点设置成黑色
xp.red = false;
if (xpp != null) {
// 爷爷节点设置成红色
xpp.red = true;
// 将爷爷节点右旋
root = rotateRight(root, xpp);
}
}
}
} else {
if (xppl != null && xppl.red) {
xppl.red = false;
xp.red = false;
xpp.red = true;
x = xpp;
} else {
if (x == xp.left) {
x = xp;
root = rotateRight(root, x);
xp = x.parent;
xpp = xp == null ? null : xp.parent;
}
if (xp != null) {
xp.red = false;
if (xpp != null) {
xpp.red = true;
root = rotateLeft(root, xpp);
}
}
}
}
}
}
final void removeTreeNode(MyHashMap<K, V> map, Node<K, V>[] tab,
boolean movable) {
/**
* 链表的处理
*/
int n;
// 如果当前哈希表为空直接返回
if (tab == null || (n = tab.length) == 0)
return;
// 计算当前节点在hash表的索引位置
int index = (n - 1) & hash;
// fisrt : t头节点
TreeNode<K, V> first = (TreeNode<K, V>) tab[index];
// 如果索引位置的红黑树为空
if (first == null) {
return;
}
// root:根节点
TreeNode<K, V> root = first;
// rl : root的左节点
TreeNode<K, V> rl;
// succ:节点的后继节点
TreeNode<K, V> succ = (TreeNode<K, V>) next;
// pred:节点的前驱节点
TreeNode<K, V> pred = prev;
// 如果根节点为空,则当前节点就是头节点,直接删除
if (pred == null) {
first = succ;
tab[index] = succ;
// 根节点不为空,当前节点为中间某个节点,删除中间节点
} else {
// 前驱的后继
pred.next = succ;
}
// 后继的前驱
if (succ != null) {
succ.prev = pred;
}
// 如果root的父节点不为空,说明该节点并不是真正的红黑树根节点,需要重新查找根节点
if (root.parent != null) {
root = root.parent;
}
// 通过root节点来判断此红黑树是否太小, 如果是太小了则调用untreeify方法转为链表节点并返回
// (转链表后就无需再进行下面的红黑树处理)
// 太小的判定依据:根节点为null,或者根的右节点为null,或者根的左节点为null,或者根的左节点的左节点为null
// 这里并没有遍历整个红黑树去统计节点数是否小于等于阈值6,而是直接判断这几种情况,
// 来决定要不要转换为链表,因为这几种情况一般就涵盖了节点数小于6的情况,这样执行效率也会变高
if (root == null || root.right == null ||
(rl = root.left) == null || rl.left == null) {
tab[index] = first.untreeify(map); // too small
return;
}
/**
* 红黑树的处理
*/
TreeNode<K, V> p = this;
TreeNode<K, V> pl = left;
TreeNode<K, V> pr = right;
// replacement:替换节点
TreeNode<K, V> replacement;
if (pl != null && pr != null) {
// 找到当前节点的后继
TreeNode<K, V> s = pr;
TreeNode<K, V> sl = s.left;
while (sl != null) {
s = sl;
sl = s.left;
}
// 交换p和s的颜色
boolean c = s.red;
s.red = p.red;
p.red = c;
TreeNode<K, V> sr = s.right;
TreeNode<K, V> pp = p.parent;
// 如果p的后继节点s恰好是p的右节点,那说明pr没有左节点
// 那么就可以直接将pr替换为p
if (s == pr) {
// 先处理p
p.parent = s;
p.left = null;
p.right = sr;
if (sr != null) {
sr.parent = p;
}
// 处理s
s.right = p;
s.left = pl;
pl.parent = s;
s.parent = pp;
if (pp == null) {
root = s;
} else if (p == pp.left) {
pp.left = s;
} else {
pp.right = s;
}
} else {
// 将p和s互换
TreeNode<K, V> sp = s.parent;
p.parent = sp;
if (s == sp.left) {
sp.left = p;
} else {
sp.right = p;
}
p.left = null;
p.right = sr;
if (sr != null) {
sr.parent = p;
}
s.parent = pp;
if (pp == null) {
root = s;
} else if (p == pp.left) {
pp.left = s;
} else {
pp.right = s;
}
s.left = pl;
s.right = pr;
pr.parent = s;
}
// 如果sr不等于null,那需要p和sr替换掉
if (sr != null) {
replacement = sr;
// 如果sr等于null,此时p无子树,直接删掉就可以
} else {
replacement = p;
}
// 走到这里说明pr为null,pl不为null
} else if (pl != null) {
replacement = pl;
// 走到这里说明pl为null,pr不为null
} else if (pr != null) {
replacement = pr;
}
// 到这里,说明p的左右节点都为null
else {
replacement = p;
}
// 删掉当前节点p
if (replacement != p) {
TreeNode<K, V> pp = replacement.parent = p.parent;
// 当p只有一个子树的时候,p的父节点可能为null
if (pp == null) {
root = replacement;
} else if (p == pp.left) {
pp.left = replacement;
} else {
pp.right = replacement;
}
// 删掉p节点
p.left = p.right = p.parent = null;
}
// 如果p节点是红色,那不影响树的结构
TreeNode<K, V> r = p.red ? root : balanceDeletion(root, replacement);
if (replacement == p) {
TreeNode<K, V> pp = p.parent;
p.parent = null;
if (pp != null) {
if (p == pp.left) {
pp.left = null;
} else {
pp.right = null;
}
}
}
}
static <K, V> TreeNode<K, V> balanceDeletion(TreeNode<K, V> root,
TreeNode<K, V> x) {
TreeNode<K, V> xp, xpl, xpr;
while (true) {
// 如果x为null或者是根节点,说明已经删除完了
if (x == null || x == root) {
return root;
// 父节点为null,说明是根节点
} else if ((xp = x.parent) == null) {
x.red = false;
return x;
// 如果x是红色的,那么直接让它变成黑色的就行了
// 因为父节点是黑色的,x节点直接代替他成为黑色的就行了
// 这对应情景1.1或情景2
} else if (x.red) {
x.red = false;
return root;
// x既不是根节点,也不是红色
// x是父亲的左节点
} else if ((xpl = xp.left) == x) {
// 此时对应于情景1.2.1,父兄换色,然后对x在进行一次平衡
if ((xpr = xp.right) != null && xpr.red) {
xpr.red = false;
xp.red = true;
root = rotateLeft(root, xp);
xpr = (xp = x.parent) == null ? null : xp.right;
}
if (xpr == null) {
// TODO: 这里应该不可能出现
System.out.println("..........");
x = xp;
} else {
TreeNode<K, V> sl = xpr.left, sr = xpr.right;
// 此时xpr只能是黑色
// 这里if判断成功的可能条件:
// 1.sl == null,sr == null (对应情景1.2.2.3)
// 2.sl == null,sr == black (不可能)
// 3.sl == black,sr == null (不可能)
// 4.sl == black,sr == black (不可能)
if ((sr == null || !sr.red) &&
(sl == null || !sl.red)) {
// 对应情景1.2.2.3
xpr.red = true;
x = xp;
} else {
// 进入这里的可能条件
// 1.sl == null,sr == red (对应情景1.2.2.1)
// 2.sl == red,sr == null (对应情景1.2.2.2)
// 3.sl == red,sr == red (对应情景1.2.2.1)
// 4.sl == black,sr == red (不存在)
// 4.sl == red,sr == black (不存在)
// 条件2
if (sr == null) {
// 情景1.2.2.2
sl.red = false;
xpr.red = true;
root = rotateRight(root, xpr);
xpr = (xp = x.parent) == null ? null : xp.right;
}
// 此时就变成了场景1.2.2.1
if (xpr != null) {
// 父兄换色
xpr.red = xp.red;
if ((sr = xpr.right) != null) {
sr.red = false;
}
}
if (xp != null) {
xp.red = false;
root = rotateLeft(root, xp);
}
x = root;
}
}
} else {
// 如果xpl为红色,那xp和xpl的孩子肯定为黑色
if (xpl != null && xpl.red) {
xpl.red = false;
xp.red = true;
root = rotateRight(root, xp);
xpl = (xp = x.parent) == null ? null : xp.left;
}
if (xpl == null) {
x = xp;
} else {
TreeNode<K, V> sl = xpl.left, sr = xpl.right;
if ((sl == null || !sl.red) && (sr == null || !sr.red)) {
xpl.red = true;
x = xp;
} else {
if (sl == null) {
sr.red = false;
xpl.red = true;
root = rotateLeft(root, xpl);
xpl = (xp = x.parent) == null ?
null : xp.left;
}
if (xpl != null) {
xpl.red = xp.red;
if ((sl = xpl.left) != null)
sl.red = false;
}
if (xp != null) {
xp.red = false;
root = rotateRight(root, xp);
}
x = root;
}
}
}
}
}
}
TreeNode<K, V> newTreeNode(int hash, K key, V value, Node<K, V> next) {
return new TreeNode<>(hash, key, value, next);
}
Node<K, V> replacementNode(Node<K, V> p, Node<K, V> next) {
return new Node<>(p.hash, p.key, p.value, next);
}
Node<K, V> newNode(int hash, K key, V value, Node<K, V> next) {
return new Node<>(hash, key, value, next);
}
}