一,HashTable
哈希表,它相比于hashMap结构简单点,它没有涉及红黑树,直接使用链表的方式解决哈希冲突。
我们看它的字段,和hashMap差不多,使用table存放元素
private transient Entry<?,?>[] table;
private transient int count;
private int threshold;
private float loadFactor;
private transient int modCount = 0;
它没有常量字段,默认值是在构造方法里面直接体现的,我们看一下无参构造:
public Hashtable() {
this(11, 0.75f);
}
1.get()方法
根据key获得value
public synchronized V get(Object key) {
Entry<?,?> tab[] = table;
//计算下标
int hash = key.hashCode();
int index = (hash & 0x7FFFFFFF) % tab.length;
//遍历查找,e=e.next
for (Entry<?,?> e = tab[index] ; e != null ; e = e.next) {
if ((e.hash == hash) && e.key.equals(key)) {
return (V)e.value;
}
}
return null;
}
2.put()方法
与get()方法类似,也是遍历table,然后调用addEntry()实现添加。
public synchronized V put(K key, V value) {
if (value == null) {
throw new NullPointerException();
}
Entry<?,?> tab[] = table;
int hash = key.hashCode();
int index = (hash & 0x7FFFFFFF) % tab.length;
@SuppressWarnings("unchecked")
Entry<K,V> entry = (Entry<K,V>)tab[index];
//如果已经存在,则覆盖,返回老的值
for(; entry != null ; entry = entry.next) {
if ((entry.hash == hash) && entry.key.equals(key)) {
V old = entry.value;
entry.value = value;
return old;
}
}
//不存在,直接添加
addEntry(hash, key, value, index);
return null;
}
addEntry()
private void addEntry(int hash, K key, V value, int index) {
modCount++;
Entry<?,?> tab[] = table;
if (count >= threshold) { //大小超过阈值,要扩容
// Rehash the table if the threshold is exceeded
rehash();
tab = table;
hash = key.hashCode();
index = (hash & 0x7FFFFFFF) % tab.length;
}
//添加
@SuppressWarnings("unchecked")
Entry<K,V> e = (Entry<K,V>) tab[index];
tab[index] = new Entry<>(hash, key, value, e);
count++;
}
注意这里的手法,直接将新来的节点,放到头部,这样就可以不管后面是否存在节点,都不会出现问题
protected Entry(int hash, K key, V value, Entry<K,V> next) {
this.hash = hash;
this.key = key;
this.value = value;
this.next = next;
}
二,HashMap
1.常量字段介绍
static final int DEFAULT_INITIAL_CAPACITY = 1 << 4; // aka 16 2的四次方,初始化默认的容量
static final int MAXIMUM_CAPACITY = 1 << 30; 最大的容量值
static final float DEFAULT_LOAD_FACTOR = 0.75f; //容量 负载因子,
static final int TREEIFY_THRESHOLD = 8; //链表转换为数的阈值
static final int UNTREEIFY_THRESHOLD = 6; //树转坏为链表的阈值
static final int MIN_TREEIFY_CAPACITY = 64; //桶中的数据采用红黑树存储时,整个table的最小容量
字段:
transient Node<K,V>[] table; //存储主干,节点数组
transient Set<Map.Entry<K,V>> entrySet;
transient int size; //元素数量
transient int modCount; //修改次数
//The next size value at which to resize (capacity * load factor).
int threshold; //下一次扩容的大小,
final float loadFactor; //负载因子
2.构造函数
2.1常用的无参构造:
默认构造方法,就直接给负载因子赋值,其他没有操作,其他字段都是默认的。
// 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
}
2.2带初始化容器大小,和负载因子的构造方法:
首先要判断传入参数的正确性,然后赋值。
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);
}
2.3带集合的构造方法:
传入一个Map集合,调用put方法进行初始化。
public HashMap(Map<? extends K, ? extends V> m) {
this.loadFactor = DEFAULT_LOAD_FACTOR;
putMapEntries(m, false);
}
从上面的代码中可以看到,在构造方法中并没有初始化table,具体的table初始化是在put操作上进行的。
3.添加
3.1 put()
是一个入口方法,实际调用的是putVal()方法,其中通过hash()方法计算了key对应的 值
public V put(K key, V value) {
return putVal(hash(key), key, value, false, true);
}
//异或运算,保证存储位置尽量均匀分布。
static final int hash(Object key) {
int h;
return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16);
}
具体的putVal()方法,内容很长
final V putVal(int hash, K key, V value, boolean onlyIfAbsent,
boolean evict) {
Node<K,V>[] tab; Node<K,V> p; int n, i; //变量初始化,n表示table的长度
if ((tab = table) == null || (n = tab.length) == 0) //容器初始化
n = (tab = resize()).length; //通过resize()方法获取分配空间。
if ((p = tab[i = (n - 1) & hash]) == null) //如果新的位置是空的,则直接放入,否者要解决冲突
tab[i] = newNode(hash, key, value, null); //将value封装成新的node
else { //解决冲突
Node<K,V> e; K k;
// 注意p的赋值在 第二个if里面,它表示的是冲突位置所存放的节点。如果新传入的节点和当前node的hash和key相同,则下面再处理
if (p.hash == hash &&
((k = p.key) == key || (key != null && key.equals(k))))
e = p;
else if (p instanceof TreeNode) //基于红黑树的插入
e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
else { //基于链表的插入
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;
}
}
//更新当前传入的值到当前node中。返回之前的oldValue
if (e != null) { // existing mapping for key
V oldValue = e.value;
if (!onlyIfAbsent || oldValue == null)
e.value = value;
afterNodeAccess(e);
return oldValue;
}
}
++modCount; //修改次数+1,
if (++size > threshold) //空间大小,如果超过了阈值,要扩容
resize();
afterNodeInsertion(evict);
return null;
}
其中涉及的重点方法:resize()方法,返回新分配的空间。
final Node<K,V>[] resize() {
Node<K,V>[] oldTab = table;//获取老的table空间
int oldCap = (oldTab == null) ? 0 : oldTab.length; //获取老的容量
int oldThr = threshold; //获取老的阈值
int newCap, newThr = 0;
if (oldCap > 0) {
if (oldCap >= MAXIMUM_CAPACITY) {
threshold = Integer.MAX_VALUE;
return oldTab;
} //扩容两倍
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,构造函数指定了阈值
newCap = oldThr;
else { // 第一次初始化 oldCap=0,oldThr=0
newCap = DEFAULT_INITIAL_CAPACITY; //默认大小,16
newThr = (int)(DEFAULT_LOAD_FACTOR * DEFAULT_INITIAL_CAPACITY); //默认计算方法,16*0.75,12
}
if (newThr == 0) { //初始化阈值
float ft = (float)newCap * loadFactor;
newThr = (newCap < MAXIMUM_CAPACITY && ft < (float)MAXIMUM_CAPACITY ?
(int)ft : Integer.MAX_VALUE);
}
threshold = newThr; //将新计算出来的值,赋值
@SuppressWarnings({"rawtypes","unchecked"})
Node<K,V>[] newTab = (Node<K,V>[])new Node[newCap]; //重新分配空间。
table = newTab; //扩容后的空间赋值(此时,空间还是空的)
if (oldTab != null) { //如果老的空间,不是空的,那么需要元素转移
for (int j = 0; j < oldCap; ++j) { //遍历进行转移
Node<K,V> e;
if ((e = oldTab[j]) != null) { //将元数取出来
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;
}
4.Node结构
static class Node<K,V> implements Map.Entry<K,V> {
final int hash; //节点的hash值
final K key; //存入的key值
V value; //存放的值
Node<K,V> next; //下一个节点
....
}
注意hashMap和LinkedList的区别,后者是双向的,而hashMap中的Node是单向的。
5.get()操作
public V get(Object key) {
Node<K,V> e;
return (e = getNode(hash(key), key)) == null ? null : e.value; //代码内容在这里
}
调用getNode()方法,计算hash(key)值,通过Hash来获得node
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) {
//第一个 检测数组中的hash定位获得第一个Node
if (first.hash == hash &&((k = first.key) == key || (key != null && key.equals(k))))
return first;
//第一个不是,那么就是后续节点中,可能是链表形式,可能是红黑树
if ((e = first.next) != null) {
if (first instanceof TreeNode) //如果是红黑树,通过getTreeNode()方法获得
return ((TreeNode<K,V>)first).getTreeNode(hash, key);
//链表形式,直接循环遍历获得。
do {
if (e.hash == hash &&((k = e.key) == key || (key != null && key.equals(k))))
return e;
} while ((e = e.next) != null);
}
}
return null;
}
链表形式的获取比较简单,红黑树的获得,我们放在下面红黑树单独进行介绍。
三,TreeMap
TreeMap和之前的两个map就不同了,它没有使用哈希表,而是直接使用红黑树解决,它的字段只保存了根节点
private final Comparator<? super K> comparator; //排序比较器
private transient Entry<K,V> root; //根节点
private transient int size = 0;
private transient int modCount = 0;
1.get()
public V get(Object key) {
Entry<K,V> p = getEntry(key);
return (p==null ? null : p.value);
}
getEntry()
final Entry<K,V> getEntry(Object key) {
// Offload comparator-based version for sake of performance
if (comparator != null)
return getEntryUsingComparator(key);
if (key == null)
throw new NullPointerException();
@SuppressWarnings("unchecked")
Comparable<? super K> k = (Comparable<? super K>) key;
Entry<K,V> p = root;
while (p != null) {
int cmp = k.compareTo(p.key);
//左右分流
if (cmp < 0)
p = p.left;
else if (cmp > 0)
p = p.right;
else
return p;
}
return null;
}
**2.put() **涉及红黑树的操作,所以代码比较长
public V put(K key, V value) {
Entry<K,V> t = root;
if (t == null) {
compare(key, key); // type (and possibly null) check
root = new Entry<>(key, value, null);
size = 1;
modCount++;
return null;
}
int cmp;
Entry<K,V> parent;
// split comparator and comparable paths
Comparator<? super K> cpr = comparator;
if (cpr != null) {
do {
parent = t;
cmp = cpr.compare(key, t.key);
if (cmp < 0)
t = t.left;
else if (cmp > 0)
t = t.right;
else
return t.setValue(value);
} while (t != null);
}
else {
if (key == null)
throw new NullPointerException();
@SuppressWarnings("unchecked")
Comparable<? super K> k = (Comparable<? super K>) key;
do {
parent = t;
cmp = k.compareTo(t.key);
if (cmp < 0)
t = t.left;
else if (cmp > 0)
t = t.right;
else
return t.setValue(value);
} while (t != null);
}
Entry<K,V> e = new Entry<>(key, value, parent);
if (cmp < 0)
parent.left = e;
else
parent.right = e;
fixAfterInsertion(e);
size++;
modCount++;
return null;
}
3.remove()
public V remove(Object key) {
Entry<K,V> p = getEntry(key);
if (p == null)
return null;
V oldValue = p.value;
deleteEntry(p); //实际方法
return oldValue;
}
总结:
HashMap表现得更像TreeMap和HashTable的结合体。
最后
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来源:oschina
链接:https://my.oschina.net/u/4516827/blog/4450777