1、属性值
static final int DEFAULT_INITIAL_CAPACITY = 1 << 4; // aka 16默认的表长度
static final int MAXIMUM_CAPACITY = 1 << 30;//最大的
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;//列表长度超过8进行转换为树结构
/**
* 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;//当bin的个数小于6时由树形调整为列表
/**
* 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;//当总bin的个数大于64时,且单列bin的个数大于8时才能由列表调整为树。
transient Node
2、构造实现方式:构造只是赋值属性初始值但是不会真正初始化数组表空间,在第一次添加元素时形成数组表空间。这个和以往的jDK1.7之前的不同,1.7之前的都是在构造里初始化了table数组空间。
public HashMap() {
this.loadFactor = DEFAULT_LOAD_FACTOR; // all other fields defaulted
}
public HashMap(int initialCapacity) {
this(initialCapacity, DEFAULT_LOAD_FACTOR);
}
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);
}
3、put 元素方法:
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
if ((tab = table) == null || (n = tab.length) == 0)//判断数组表是否为空,如果为空进行表空间扩容初始化。在第一次添加元素时用到
n = (tab = resize()).length;
if ((p = tab[i = (n - 1) & hash]) == null)//和数组table的长度-1进行相与得出在数组中的位置,看位置是否为空,如果为空说明这个位置还没有元素占用,new一个Node内部类节点赋值给数组。
tab[i] = newNode(hash, key, value, null);
else {//如果在该数组位置已经有值
Node
if (p.hash == hash &&
((k = p.key) == key || (key != null && key.equals(k))))//判断原数组存储的是否同一个key元素,如果是通过变量e记录下该位置,以便在下面把该元素的value替换为新值
e = p;
else if (p instanceof TreeNode)//判断是否为树形结构如果是,通过树形结构查找或者添加
e = ((TreeNode
else {//遍历链表
for (int binCount = 0; ; ++binCount) {
if ((e = p.next) == null) {//如果找到链表尾部也没有找到相同key的元素,说明该链表没有原值进行新new一个node添加到链表
p.next = newNode(hash, key, value, null);
if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st//如果遍历的链表长度大于=8转换为树形结构
treeifyBin(tab, hash);
break;
}
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k))))//如果遍历过程中找到形同key的元素,e记录位置后跳出循环
break;
p = e;
}
}
if (e != null) { // existing mapping for key//如果e不为空说明找到原来的key,把原理node的值赋予新值
V oldValue = e.value;
if (!onlyIfAbsent || oldValue == null)
e.value = value;
afterNodeAccess(e);
return oldValue;
}
}
++modCount;
if (++size > threshold)//添加一个元素后size进行加1,如果目前存在元素大于最大容量后进行扩容,
resize();
afterNodeInsertion(evict);
return null;
}
4、容器扩容
final Node
Node
int oldCap = (oldTab == null) ? 0 : oldTab.length;//如果第一次添加元素table为null,此值为0,否则为老表的长度
int oldThr = threshold;
int newCap, newThr = 0;
if (oldCap > 0) {//判断老容量是否为最大容量
if (oldCap >= MAXIMUM_CAPACITY) {
threshold = Integer.MAX_VALUE;
return oldTab;
}
else if ((newCap = oldCap << 1) < MAXIMUM_CAPACITY &&
oldCap >= DEFAULT_INITIAL_CAPACITY)//如果原来有容量,进行把原容量扩大2倍,把table长度扩大2倍
newThr = oldThr << 1; // double threshold//实际的存储值容量也扩大为2倍
}
else if (oldThr > 0) // initial capacity was placed in threshold
newCap = oldThr;
else { // zero initial threshold signifies using defaults //第一次添加默认初始化的容量值16
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
table = newTab;
if (oldTab != null) {//如果老的容器不为空,要把老的容器值遍历放入到新的容器
for (int j = 0; j < oldCap; ++j) {
Node
if ((e = oldTab[j]) != null) {
oldTab[j] = null;
if (e.next == null)//该数组位置存储的为单个node对象没有链表,直接把该node的hash值和新的table-1进行相与取得新的存储位置
newTab[e.hash & (newCap - 1)] = e;
else if (e instanceof TreeNode)//如果为树形结构,按照树形结构遍历
((TreeNode
else { // preserve order //下面的为链表
Node
Node
Node
do {
next = e.next;
if ((e.hash & oldCap) == 0) {//这里是一个非常精妙的设计和原来的JDK1.7以前的版本差距很大,原来的都是为再hash(e.hash & (table.length - 1))判断位置,现在为(e.hash & oldCap)判断mask范围在高位多1bit是否有值,如果有值新在位置为(原索引+oldCap)否则为原索引位置,具体描述图示参加下面:链表扩容后的序列计算
if (loTail == null)
loHead = e;//找链表头
else
loTail.next = e;//指向下一个
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;//添加到原位置,指向链表头
}
if (hiTail != null) {
hiTail.next = null;
newTab[j + oldCap] = hiHead;//添加到(原位置+老表长度)位置
}
}
}
}
}
return newTab;
}
5、链表扩容后的序列计算
经过观测可以发现,我们使用的是2次幂的扩展(指长度扩为原来2倍),所以,元素的位置要么是在原位置,要么是在原位置再移动2次幂的位置。看下图可以明白这句话的意思,n为table的长度,图(a)表示扩容前的key1和key2两种key确定索引位置的示例,图(b)表示扩容后key1和key2两种key确定索引位置的示例,其中hash1是key1对应的哈希与高位运算结果。
元素在重新计算hash之后,因为n变为2倍,那么n-1的mask范围在高位多1bit(红色),因此新的index就会发生这样的变化:
因此,我们在扩充HashMap的时候,不需要像JDK1.7的实现那样重新计算hash,只需要看看原来的hash值新增的那个bit是1还是0就好了,是0的话索引没变,是1的话索引变成“原索引+oldCap”,可以看看下图为16扩充为32的resize示意图:
这个设计确实非常的巧妙,既省去了重新计算hash值的时间,而且同时,由于新增的1bit是0还是1可以认为是随机的,因此resize的过程,均匀的把之前的冲突的节点分散到新的bucket了。
6、get取值 public V get(Object key) {
Node
return (e = getNode(hash(key), key)) == null ? null : e.value;
}
/**
* Implements Map.get and related methods
*
* @param hash hash for key
* @param key the key
* @return the node, or null if none
*/
final Node
Node
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))))//table的第一个值正好是取的值
return first;
if ((e = first.next) != null) {
if (first instanceof TreeNode)//如果是树形结构通过树形方法遍历取node
return ((TreeNode
do {//如果是链表通过遍历取值
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k))))
return e;
} while ((e = e.next) != null);
}
}
return null;
}
7、remove删除node
public V remove(Object key) {
Node
return (e = removeNode(hash(key), key, null, false, true)) == null ?
null : e.value;
}
/**
* Implements Map.remove and related methods
*
* @param hash hash for key
* @param key the key
* @param value the value to match if matchValue, else ignored
* @param matchValue if true only remove if value is equal
* @param movable if false do not move other nodes while removing
* @return the node, or null if none
*/
final Node
boolean matchValue, boolean movable) {
Node
if ((tab = table) != null && (n = tab.length) > 0 &&
(p = tab[index = (n - 1) & hash]) != null) {
Node
if (p.hash == hash &&
((k = p.key) == key || (key != null && key.equals(k)))) //如果table数组为该值记录位置
node = p;
else if ((e = p.next) != null) {
if (p instanceof TreeNode)//如果树形结构
node = ((TreeNode
else {//如果链表结构
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)))) {//找到要的node位置,根据node的结构处理
if (node instanceof TreeNode)//如果为树形
((TreeNode
else if (node == p)//如果table数组为该node值记录位置
tab[index] = node.next;
else//如为链表
p.next = node.next;
++modCount;
--size;
afterNodeRemoval(node);
return node;
}
}
return null;
}
图片参考:http://www.importnew.com/20386.html