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Collections-Hashmap - 赵小黑的博客
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<a href="https://xiaohei.im/hugo-theme-pure/2019/11/sentinel/" class="title">Redis HA - 哨兵模式</a>
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<a
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>Collections-Hashmap</a
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<a href="https://xiaohei.im/hugo-theme-pure/collections/hashmap/" class="article-date">
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<a class="article-category-link" href="/hugo-theme-pure/categories/corejava/"> CoreJava </a>
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<a class="article-tag-link" href="/hugo-theme-pure/tags/collections/"> collections </a>
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<blockquote>
<p>美团的blog:<a href="https://tech.meituan.com/java_hashmap.html">https://tech.meituan.com/java_hashmap.html</a>
参考blog: <a href="https://www.tianxiaobo.com/2018/01/18/HashMap-%E6%BA%90%E7%A0%81%E8%AF%A6%E7%BB%86%E5%88%86%E6%9E%90-JDK1-8/">田小波的博客</a>
<a href="https://www.tianxiaobo.com/2018/01/11/%E7%BA%A2%E9%BB%91%E6%A0%91%E8%AF%A6%E7%BB%86%E5%88%86%E6%9E%90/">红黑树介绍</a></p>
</blockquote>
<h2 id="hashmap-hashtable-concurrenthashmap的区别">HashMap,HashTable,ConcurrentHashMap的区别?</h2>
<p><strong>HashMap</strong>是非线程安全的,<strong>HashTable</strong>和<strong>ConcurrentHashMap</strong>是线程安全的.HashTable不允许null key和null Value,HashMap允许.
ConcurrentHashMap推出之后官方推荐不要在使用HashTable作为线程安全的使用类,而是使用这个.关于<strong>ConcurrentHashMap</strong>后面再学习.
> <a href="https://juejin.im/post/5add97a46fb9a07aa212f4c0">参考blog</a></p>
<h2 id="hashmap在不同版本之间实现的区别">HashMap在不同版本之间实现的区别?</h2>
<blockquote>
<p><a href="http://linfenliang.com/hashmap/2017/08/04/HashMapInJDK-6-7-8-Differ/">区别</a></p>
</blockquote>
<h2 id="官方文档介绍">官方文档介绍:</h2>
<ol>
<li>基于<code>Map</code>接口实现的哈希表.提供了所有map可选的操作,允许key为null,value为null.<code>HashMap</code>与<code>HashTable</code>基本一致,除了<code>HashMap</code> <em>线程不安全并且允许为空</em>.
不保证有序,尤其不保证顺序一直不变(因为扩容时会rehash,基本上就顺序就重排了)</li>
<li>假设hash分布均匀的情况下,基本的操作(<code>get/put</code>)性能很不错.迭代所需要的时间与<code>buckets</code>数量与每个<code>bukets</code>下的键值对的数量之和成正比.所以官方建议如果要求hashmap的迭代性能的话,初始的<code>capacity</code>不能太高,<code>loadFactor</code>不要太高.</li>
<li><p>HashMap有两个重要的参数:<code>initial capacity</code>,<code>load factor</code>.capacity定义bucket的数量,initial capacity定义的是初始化bucket数量.load factor(中文名: <em>加载因子</em> )是判断哈希表是否需要扩容的阈值,当entries数量超过(load factor * current capacity),哈希表会触发<code>rehash</code>操作,内部数据结构会重整,buckets数量会变为之前大约两倍左右</p></li>
<li><p>通常情况下,load factor 默认<code>0.75f</code>,在时间空间上是很平衡的.值偏高时,空间减少,查找时间上升了(影响大部分的操作,get/put之类的),在设置初始容量时,需要考虑到预期的entries数量和加载因子,以便最小化rehash的数量.如果初始化的容量大于最大数量的entries除以加载因子,不会发生rehash操作.</p></li>
<li><p>如果有大量的键值对存到hashmap中,那么创建一个足够大的hashmap来存储要比让他自动rehash扩容来存储的性能要好很多.注意:具有相同hashcode的多个key肯定会影响哈希表的性能.为了改善这种影响,当key是Comparable类型时,可以通过key之间的比较顺序来打破这种关系.</p></li>
<li><p>注意hashmap是<code>Non synchronized</code>,即 <em>非线程安全</em>.如果多线程并发访问hashmap,并且至少有一个线程操作map的结构,在外部必须<code>synchronized</code>.(结构修改是指任何关于add或delte的操作,仅仅只是修改key关联的value时则不属于结构修改).通常在将object封装进map做synchronized操作</p></li>
<li><p>如果不存在上面的objects,那这个map需要被Collections.synchronizedMap包装下.最好在创建的时候就做好,防止偶然的并发访问.</p>
<pre><code class="language-java">Map m = Collections.synchronizedMap(new HashMap(...));
</code></pre></li>
<li><p>迭代器的所有方法都是<code>fail-fast</code>,如果迭代器创建后,在迭代器里的结构操作必须通过迭代器的方法来操作,否则会抛<code>ConcurrentModificationException</code>.因此,面对并发修改,迭代器会快速而干净的失败,而不是在未来的不确定时间冒任意非确定行为的风险.</p></li>
<li><p>请注意,迭代器的快速失败行为无法得到保证,因为一般来说,在存在不同步的并发修改时,不可能做出任何硬性保证. 快速失败迭代器会尽最大努力抛出ConcurrentModificationException. 因此,编写依赖于此异常的程序以确保其正确性是错误的:迭代器的快速失败行为应该仅用于检测错误.</p></li>
</ol>
<h2 id="源码">源码</h2>
<pre><code class="language-java"> /**
* The default initial capacity - MUST be a power of two.
* 默认的容量16 必须是2的n次方
*/
static final int DEFAULT_INITIAL_CAPACITY = 1 << 4; // aka 16
/**
* 最大的容量限制
* 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;
/**
* 默认的加载因子
* The load factor used when none specified in constructor.
*/
static final float DEFAULT_LOAD_FACTOR = 0.75f;
/**
* 大于这个值转红黑树
* 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;
/**
* 大于这个值小于 TREEIFY_THRESHOLD 不转树
* 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;
/**
* hashmap整体容量大于这个值时才能树化
* 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;
/**
* node节点
* 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() {
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中的静态方法
/**
* hash方法详解 blog:http://www.hollischuang.com/archives/2091
* 扰动算法--使hash分布更均匀
*/
static final int hash(Object key) {
int h;
return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16);
}
//取模运算,获得对象存储到bukets的下标
//实际上就是取模,一般取模使用% 但是考虑到效率问题,采用位运算
//X % 2^n = X & (2^n-1) 这也是为什么hashmap容量为2的n次方的原因
static int indexFor(int h, int length) {
return h & (length-1);
}
//返回hashmap的容量 2的n次方 很巧妙的位运算
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;
}
/**
* 参数都用transient不让序列化的原因:https://segmentfault.com/q/1010000000630486
*/
//bukets hashmap是链表加数组的结构.此为数组
transient Node<K,V>[] table;
//保存键值对的Entry
transient Set<Map.Entry<K,V>> entrySet;
//hashmap的size
transient int size;
//结构操作次数 可用于快速失败的比较条件 例如并发操作时
transient int modCount;
//resize的临界点: capacity * load factor
int threshold;
//加载因子
final float loadFactor;
//公有操作方法
//构造方法
/**
* 根据 initial capactity 和 loadFactor创建空的hashmap
* 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) {
//校验initialCapacity
if (initialCapacity < 0)
throw new IllegalArgumentException("Illegal initial capacity: " +
initialCapacity);
//容量校验
if (initialCapacity > MAXIMUM_CAPACITY)
initialCapacity = MAXIMUM_CAPACITY;
//校验loadFactor isNaN--> 是否是一个number Not-a-Number
if (loadFactor <= 0 || Float.isNaN(loadFactor))
throw new IllegalArgumentException("Illegal load factor: " +
loadFactor);
//加载因子赋值
this.loadFactor = loadFactor;
//扩容阈值赋值 2的n次方
this.threshold = tableSizeFor(initialCapacity);
}
/**
* 通过initialCapacity赋值
* 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) {
this(initialCapacity, DEFAULT_LOAD_FACTOR);
}
/**
* 根据默认容量和默认加载因子创建空的hashmap
* 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
}
/**
* 根据传进来的map创建一个新的hashMap
* initialCapacity 足以装下参数map的数量
* loadFactor使用默认值
* 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);
}
/**
* Implements Map.putAll and Map constructor
*
* @param m the map
* @param evict false when initially constructing this map, else
* true (relayed to method afterNodeInsertion).
* evict 初始化构建map时 为false 其他情况下为true
*/
final void putMapEntries(Map<? extends K, ? extends V> m, boolean evict) {
int s = m.size();
if (s > 0) {
//初次创建hashmap
if (table == null) { // pre-size
//计算m所需要的容量
float ft = ((float)s / loadFactor) + 1.0F;
//获得真实的容量
int t = ((ft < (float)MAXIMUM_CAPACITY) ?
(int)ft : MAXIMUM_CAPACITY);
//如果比默认的阈值大则计算该 t 对应的capacity
if (t > threshold)
threshold = tableSizeFor(t);
}
else if (s > threshold) // 如果是table不为null 即是后续往map中添加 如果s > 阈值就要重置map了
resize();//resize操作 后面介绍
//确定容量后put操作
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);//
}
}
}
/*主要调用 putVal */
public V put(K key, V value) {
return putVal(hash(key), key, value, false, true);
}
/**
* put 操作
* 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 不存在才put<D-[>
* @param evict if false, the table is in creation mode.
* @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;
//若是新建map的情况下 resize创建指定长度的table
if ((tab = table) == null || (n = tab.length) == 0)
n = (tab = resize()).length;
//取模计算该key对应的数组下标 并判断该坐标下的对象是否为null
//为null时创建一个新node存入tab[i]
if ((p = tab[i = (n - 1) & hash]) == null)
tab[i] = newNode(hash, key, value, null);
else {//tab[i] != null
Node<K,V> e; K k;
//如果p与存入的key完全相同
if (p.hash == hash &&
((k = p.key) == key || (key != null && key.equals(k))))
e = p;
else if (p instanceof TreeNode)
//如果是红黑树节点 调用putTreeVal
e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
else {
//普通的put
//binCount记录了链表的长度
for (int binCount = 0; ; ++binCount) {
//如果当前node的next==null说明就可以往该链上添加一个节点
if ((e = p.next) == null) {
//新建node接到p.next下面
p.next = newNode(hash, key, value, null);
//如果binCount大于设定的红黑树化阈值
if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st
treeifyBin(tab, hash);//红黑树化
break;
}
//如果key与链表中的任意node完全相同break
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k))))
break;
p = e;
}
}
//如果存在该key
if (e != null) { // existing mapping for key
V oldValue = e.value;//获得旧值
if (!onlyIfAbsent || oldValue == null)//若没有设置不存在才put或者oldValue=null
e.value = value;//赋新值
afterNodeAccess(e);//LinkedHashMap操作
return oldValue;//返回旧值
}
}
++modCount;
if (++size > threshold)//是否需要扩容
resize();
afterNodeInsertion(evict);//LinkedHashMap操作
return null;
}
/**
* 扩容操作
* 若是初始化则根据initialCapacity创建一个table
* 否则,扩容为2的n次方倍
* 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.
*
* @return the table
*/
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) {
//超过最大值不会再扩容了
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 扩成两倍
}
else if (oldThr > 0) // initial capacity was placed in threshold
newCap = oldThr;
else { // 默认配置 zero initial threshold signifies using defaults
newCap = DEFAULT_INITIAL_CAPACITY;
newThr = (int)(DEFAULT_LOAD_FACTOR * DEFAULT_INITIAL_CAPACITY);
}
if (newThr == 0) {
//计算新的阈值
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) {
//把old buket 移到新的bukets里
for (int j = 0; j < oldCap; ++j) {
Node<K,V> e;
if ((e = oldTab[j]) != null) {
oldTab[j] = null;
if (e.next == null)//直接添加
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;
//这个取模很精辟 请结合美团的blog resize 1.8优化学习
//因为扩容是2倍扩容,二进制中相当于左移一位
/**
* 假设一次扩容
* 扩容前 oldCap = 00010000 oldCap - 1 = 00001111
* 扩容后 newCap = 00100000 newCap - 1 = 00011111
* 可以看出扩容后 newCap-1 在高位多了1
* 计算index时 hash & n-1 = 原位置 + oldCap
* 所以只需要判断hash & oldCap是否为1
* 为1则把该node的位置移到 oldCap+原位置
* 为 0 还在原位置
*/
if ((e.hash & oldCap) == 0) {//为0说明位置没有变
if (loTail == null)//第一次添加时loHead=e
loHead = e;
else
loTail.next = e;//直接往后插入
loTail = e;
}
else {//为1 说明位置会+oldCap长度
if (hiTail == null)
hiHead = e;//头节点初始化
else
hiTail.next = e;//直接插入
hiTail = e;
}
} while ((e = next) != null);
if (loTail != null) {//放在原位置上
loTail.next = null;
newTab[j] = loHead;
}
if (hiTail != null) {//放在原位置+oldCap上
hiTail.next = null;
newTab[j + oldCap] = hiHead;
}
}
}
}
}
return newTab;
}
/**
* get操作
* 为null时返回null 这个要注意下
*/
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
* get方法
* 主要是 key相等 或者 key equals的比较
* @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;
if ((tab = table) != null && (n = tab.length) > 0 &&
(first = tab[(n - 1) & hash]) != null) {//获得节点
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)//树节点
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;
}
</code></pre>
<h2 id="1-8红黑树化源码解析">1.8红黑树化源码解析</h2>
<pre><code class="language-java"> /**
* TreeNode extends LinkedHashMap.Entry
* LinkedHashMap.Entry extends HashMap.Node
*/
static final class TreeNode<K,V> extends LinkedHashMap.Entry<K,V> {
TreeNode<K,V> parent; // red-black tree links 红黑树父节点
TreeNode<K,V> left;
TreeNode<K,V> right;
TreeNode<K,V> prev; // needed to unlink next upon deletion 删除的时候用来连接前后
boolean red;//红还是黑
TreeNode(int hash, K key, V val, Node<K,V> next) {
super(hash, key, val, next);
}
}
/**树化
* putVal里有用到
* 将链表重置为红黑树并放到该hash映射的tab下,如果tab过下则resize
* 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)//小于最小树化的容量时不树化而resize capacity为64,
resize();
else if ((e = tab[index = (n - 1) & hash]) != null) {
TreeNode<K,V> hd = null, tl = null;//头尾节点
do {
TreeNode<K,V> p = replacementTreeNode(e, null);//这个就是返回一个新建的TreeNode对象,内容为e
if (tl == null)//确定是头结点
hd = p;//标记头结点
else {//非头结点就首尾连接
p.prev = tl;
tl.next = p;
}
tl = p;//尾节点一直为p
} while ((e = e.next) != null);//遍历链表 其实此时形成也还算是个链表
if ((tab[index] = hd) != null)//将该treeNode挂到table下
hd.treeify(tab);//完成红黑树化
}
}
/**
* Forms tree of the nodes linked from this node.
* @return root of tree
*/
final void treeify(Node<K,V>[] tab) {
TreeNode<K,V> root = null;
for (TreeNode<K,V> x = this, next; x != null; x = next) {//x 从当前节点开始(从treeifyBin里调用看是头结点)
next = (TreeNode<K,V>)x.next;//获取下个节点
x.left = x.right = null;
if (root == null) {//设置root节点并给他黑色
x.parent = null;
x.red = false;
root = x;
}
else {
K k = x.key;
int h = x.hash;
Class<?> kc = null;
//遍历所有节点与当前节点x比较 调整位置 有点像冒泡排序
for (TreeNode<K,V> p = root;;) {
int dir, ph;
K pk = p.key;
//比较hash值
if ((ph = p.hash) > h)
dir = -1;
else if (ph < h)
dir = 1;
else if ((kc == null &&
(kc = comparableClassFor(k)) == null) ||
(dir = compareComparables(kc, k, pk)) == 0)
dir = tieBreakOrder(k, pk);
//根据dir判断x是p的左孩子 还是 右孩子
TreeNode<K,V> xp = p;
if ((p = (dir <= 0) ? p.left : p.right) == null) {
x.parent = xp;
if (dir <= 0)
xp.left = x;
else
xp.right = x;
//平衡节点
root = balanceInsertion(root, x);
break;
}
}
}
}
moveRootToFront(tab, root);
}
/**
* Returns a list of non-TreeNodes replacing those linked from
* this node.
*/
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;
}
/**
* 红黑树版put操作
* Tree version of putVal.
*/
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;//每次从根节点遍历
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)))
//如果当前节点key相同或equals 返回
return p;
else if ((kc == null &&
(kc = comparableClassFor(k)) == null) ||
(dir = compareComparables(kc, k, pk)) == 0) {
//hash值如果相等 但类不相同,只能挨个对比左右孩子
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;
}
//哈希值相等 但键无法比较 只能通过其他方法比较
dir = tieBreakOrder(k, pk);
}
//得到两个节点的大小关系 即dir的值时
//并判断只有在左孩子或右孩子不能
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;
//平衡二叉树
moveRootToFront(tab, balanceInsertion(root, x));
return null;
}
}
}
/** 查找操作 传入 hash值 和 key值
* Calls find for root node.
*/
final TreeNode<K,V> getTreeNode(int h, Object k) {
return ((parent != null) ? root() : this).find(h, k, null);//判断从当前节点还是root节点开始查找
}
/**
* 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;
//根据hash值查找 当前节点hash值大于h则 查左孩子 否则右孩子 当key相等或者equal时返回
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)//不相等则从子树继续查找
return q;
else
p = pl;
} while (p != null);
return null;
}
</code></pre>
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