注意注意，hashmap里的红黑树的节点是node的一个子类，所以这个树节点也可以使用next，在构建数时他的next指针会保留，当需要的时候仍可以使用。
TreeNode<K,V> extends LinkedHashMap.Entry<K,V>
Entry<K,V> extends HashMap.Node<K,V>
package java.util;
import java.io.IOException;
import java.io.InvalidObjectException;
import java.io.Serializable;
import java.lang.reflect.ParameterizedType;
import java.lang.reflect.Type;
import java.util.function.BiConsumer;
import java.util.function.BiFunction;
import java.util.function.Consumer;
import java.util.function.Function;
@jdk8
jdk1.2引入
public class HashMap<K,V> extends AbstractMap<K,V> implements Map<K,V>, Cloneable, Serializable {
序列化ID
private static final long serialVersionUID = 362498820763181265L;
初始容量16
static final int DEFAULT_INITIAL_CAPACITY = 1 << 4;
最大容量2^30
static final int MAXIMUM_CAPACITY = 1 << 30;
默认负载因子(当hashmap中容量打到 负载因子当前容量时，扩容为当前容量2)
static final float DEFAULT_LOAD_FACTOR = 0.75f;
一个桶链表变换乘红黑树的临界值 不能小于2
static final int TREEIFY_THRESHOLD = 8;
红黑树退化成链表的临界值
static final int UNTREEIFY_THRESHOLD = 6;
static final int MIN_TREEIFY_CAPACITY = 64;
key value 在hashmap中的存储形式
static class Node<K,V> implements Map.Entry<K,V> {
hash值
final int hash;
key值
final K key;
value值
V value;
Node<K,V> next;
构造函数
Node(int hash, K key, V value, Node<K,V> next) {
this.hash = hash;
this.key = key;
this.value = value;
this.next = next;
}
Entry中getKey
public final K getKey() { return key; }
Entry中getValue
public final V getValue() { return value; }
public final String toString() { return key + "=" + value; }
计算哈希码 key的hash异或value的hash
public final int hashCode() { return Objects.hashCode(key) ^ Objects.hashCode(value); }
更改value，并返回原来的value
public final V setValue(V newValue) { V oldValue = value; value = newValue; return oldValue; }
先判断地址，如果地址不同判断类型和key，value
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;
}
}
？？为啥要这么算有空再查查。
static final int hash(Object key) {
int h;
return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16);
}
如果该类实现了Comparable了 返回x的class对，否则返回null
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;
}
如果x时kc 返回k.((Comparable)k).compareTo(x)) 否则返回0
@SuppressWarnings({"rawtypes","unchecked"}) // for cast to Comparable
static int compareComparables(Class<?> kc, Object k, Object x) {
return (x == null || x.getClass() != kc ? 0 :
((Comparable)k).compareTo(x));
}
用来扩容的，好巧妙啊，大神就时大神
看了半天没看懂
用了几个测试用例测试了一下
cap = -1，0 1 ---> n = 1
cap = 2 ---> n = 2
cap = 3,4 ---> n = 4
cap = 5,6,7,8 ---> 8
cap = 9,10,11,12,13,14,15,16---> 16
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;
}
这应该就是哈希"表"了吧
transient Node<K,V>[] table;
所有的entry
transient Set<Map.Entry<K,V>> entrySet;
目前的size
transient int size;
iterator中用来防止篡改的
transient int modCount;
capacity * loadfactor
int threshold;
当前负载因子
final float loadFactor;
构造函数 如果initialCapacity 不是2^n 会向上进位
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;
this.threshold = tableSizeFor(initialCapacity);
}
public HashMap(int initialCapacity) {
this(initialCapacity, DEFAULT_LOAD_FACTOR);
}
public HashMap() {
this.loadFactor = DEFAULT_LOAD_FACTOR; // all other fields defaulted
}
public HashMap(Map<? extends K, ? extends V> m) {
this.loadFactor = DEFAULT_LOAD_FACTOR;
putMapEntries(m, false);
}
将一个map加入到这个hashmap中 evict??,看看下面putVal咋实现的
final void putMapEntries(Map<? extends K, ? extends V> m, boolean evict) {
int s = m.size();
if (s > 0) {
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);
}
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);
}
}
}
size O(1)
public int size() { return size; }
isEmpty O(1)
public boolean isEmpty() { return size == 0; }
根据key返回val 时间复杂度取决于下面的getNode
public V get(Object key) {
Node<K,V> e;
return (e = getNode(hash(key), key)) == null ? null : e.value;
}
第一个node的地址为(n - 1) & hash
首先判断第一个节点与要找的key一样不一样
- 判断的过程：先==，后equals
然后判断该桶里时红黑树还是链表，然后根据对应的规则进行搜索
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) {
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;
}
containskey通过getNode来实现
public boolean containsKey(Object key) {
return getNode(hash(key), key) != null;
}
put没啥说的调用putVal
public V put(K key, V value) {
return putVal(hash(key), key, value, false, true);
}
- 首先判断实例中是否以及存在表了，如果不存在，通过resize创建一个Node数组
- 然后通过传入的key的【hash&(n -1)】计算索引查找所在的桶内是否以及存在元素了，
- 如果没有元素在这个桶里，根据传入的kv创建桶的头结点
- ++modCount;
- size++
- 判断是够扩容
- afterNodeInsertion(evict);
- 如果桶内已经存在元素了
- 如果发现桶内的头结点key与传入的key的值地址相同，或者key equals k， 令e等于当前节点
- 如果该桶已经进化成红黑数了，利用红黑树的api进行插入或者更新 e等于返回的节点
- 否则，向链表后面走，并更新e为当前节点，如果找到了与key对应的节点 p=e，如果没找到就在最后没新建一个，此时若发现打到了进化红黑树的阀值，将此链表进化
- 如果e中val为空插入val，不为空 根据onlyIfAbsent判断是否更新，如果false---更新，true---不更新e---
- 执行 afterNodeAccess(e);
final V putVal(int hash, K key, V value, boolean onlyIfAbsent,
boolean evict) {
Node<K,V>[] tab; Node<K,V> p; int n, i;
if ((tab = table) == null || (n = tab.length) == 0)
n = (tab = resize()).length;
if ((p = tab[i = (n - 1) & hash]) == null)
tab[i] = newNode(hash, key, value, null);
else {
Node<K,V> e; K k;
if (p.hash == hash &&
((k = p.key) == key || (key != null && key.equals(k))))
e = p;
else if (p instanceof TreeNode)
e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
else {
for (int binCount = 0; ; ++binCount) {
if ((e = p.next) == null) {
p.next = newNode(hash, key, value, null);
if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st
treeifyBin(tab, hash);
break;
}
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;
}
如果之前有实例中有table已经初始化并且桶数大于8 扩容2倍后小于2^30，进行扩容,并更新thr
如果之前table为空，
- 但oldThr有值，cap = oldThr，并更新thr
- 如果oldThr等于0，cap = 0，thr = DEFAULT_LOAD_FACTOR * DEFAULT_INITIAL_CAPACITY
根据新的容量新建一个数组，原来的顺序会被打乱，甚至一个桶内的元素会被散列到不同位置去，并将老数组的每一个位置更新为null，便于垃圾回收
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;
@SuppressWarnings({"rawtypes","unchecked"})
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) {
oldTab[j] = null;
if (e.next == null)
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;
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;
}
把链表替换成红黑树，这个算法有空可以看一下
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);
}
}
将map复制到实例中，如果key存在会覆盖掉之前的值
public void putAll(Map<? extends K, ? extends V> m) { putMapEntries(m, true); }
public V remove(Object key) {
Node<K,V> e;
return (e = removeNode(hash(key), key, null, false, true)) == null ?
null : e.value;
}
基本思路与put类似，然后先找到节点，然后删除
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;
if (p.hash == hash &&
((k = p.key) == key || (key != null && key.equals(k))))
node = p;
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);
}
}
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;
}
清空实例里所以的元素
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;
}
}
判断包含value
这里有的桶里已经时红黑树了，但是仍用next去寻找
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;
}
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