Map集合的特点
- 能够存储唯一的列的数据(唯一，不可重复) Set
- 能够存储可以重复的数据(可重复) List
- 值的顺序取决于键的顺序
- 键和值都是可以存储null元素的
TreeMap
特点
TreeMap底层就是红黑树，所以他符合红黑树所有的特点
源码分析
初始化
private final Comparator<? super K> comparator; //比较器
private transient Entry<K,V> root; //根节点
/**
* The number of entries in the tree
*/
private transient int size = 0; //大小
/**
* The number of structural modifications to the tree.
*/
private transient int modCount = 0; //防止并发状态下数据结构发生变化的校验
Entry
K key; //键
V value; //值
Entry<K,V> left; //左子节点
Entry<K,V> right; //右子节点
Entry<K,V> parent; //父节点
boolean color = BLACK; //默认黑色
无参构造
/**
* Constructs a new, empty tree map, using the natural ordering of its
* keys. All keys inserted into the map must implement the {@link
* Comparable} interface. Furthermore, all such keys must be
* <em>mutually comparable</em>: {@code k1.compareTo(k2)} must not throw
* a {@code ClassCastException} for any keys {@code k1} and
* {@code k2} in the map. If the user attempts to put a key into the
* map that violates this constraint (for example, the user attempts to
* put a string key into a map whose keys are integers), the
* {@code put(Object key, Object value)} call will throw a
* {@code ClassCastException}.
*/
public TreeMap() {
comparator = null;
}
put()
/**
* Associates the specified value with the specified key in this map.
* If the map previously contained a mapping for the key, the old
* value is replaced.
*
* @param key key with which the specified value is to be associated
* @param value value to be associated with the specified key
*
* @return the previous value associated with {@code key}, or
* {@code null} if there was no mapping for {@code key}.
* (A {@code null} return can also indicate that the map
* previously associated {@code null} with {@code key}.)
* @throws ClassCastException if the specified key cannot be compared
* with the keys currently in the map
* @throws NullPointerException if the specified key is null
* and this map uses natural ordering, or its comparator
* does not permit null keys
*/
public V put(K key, V value) {
//root = null;
//t = null;
Entry<K,V> t = root;
//第一次put会进入此判断
if (t == null) {
//校验key是否为null
compare(key, key); // type (and possibly null) check
//创建一个Entry以传入的key value作为根节点
root = new Entry<>(key, value, null);
size = 1;
modCount++;
return null;
}
//当第二次的时候 t != null进入以下逻辑
//t = <"a", 10>
int cmp;
//定义一个父节点的对象
Entry<K,V> parent;
// split comparator and comparable paths
//初始化的时候comparator = nu l l
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 {
//如果key == null就会抛异常
if (key == null)
throw new NullPointerException();
@SuppressWarnings("unchecked")
Comparable<? super K> k = (Comparable<? super K>) key;
do {
//第一次循环的时候，把根节点当作父节点
//第二次循环的时候，根据下面的t去做决定
//parent = <"a", 10>
parent = t;
//比较传入的key和父节点的key做比较
cmp = k.compareTo(t.key);
//如果传入的值小于父类就把父类做节点当作父类
if (cmp < 0)
t = t.left;
else if (cmp > 0) //如果传入的值大于父类就把父类的右节点当作父类
t = t.right;
else //如果传入的值等于当前值，那么直接就赋值就可以了
return t.setValue(value);
} while (t != null); //什么时候没有父类了就会跳出循环
}
//创建一个Entry，以传入的 key value作为键值对，parent为父类
Entry<K,V> e = new Entry<>(key, value, parent);
//如果传入的值小于他的父类 就会放到左边
if (cmp < 0)
parent.left = e;
else //如果传入的值大于他的父类 就会放到右边
parent.right = e;
//旋转 平衡
fixAfterInsertion(e);
size++;
modCount++;
return null;
}
/** From CLR */
private void fixAfterInsertion(Entry<K,V> x) {
//插入的元素 默认为红色
x.color = RED;
//插入的元素不等于null
//插入的元素不等于根节点
//插入的节点的父类的颜色等于红色
while (x != null && x != root && x.parent.color == RED) {
//父类节点在祖父节点的左节点
if (parentOf(x) == leftOf(parentOf(parentOf(x)))) {
//获取叔叔节点
Entry<K,V> y = rightOf(parentOf(parentOf(x)));
//叔叔节点是红色
if (colorOf(y) == RED) {
//父节点设置为黑色
setColor(parentOf(x), BLACK);
//叔叔节点设置为黑色
setColor(y, BLACK);
//祖父节点设置为红色
setColor(parentOf(parentOf(x)), RED);
//把祖父节点设置为当前节点
x = parentOf(parentOf(x));
} else { //叔叔节点是黑色
//当前节点是父节点的右节点
if (x == rightOf(parentOf(x))) {
//把父节点设置为当前节点
x = parentOf(x);
//父节点进行左旋
rotateLeft(x);
}
//父节点设置为黑色
setColor(parentOf(x), BLACK);
//祖父节点设置为红色
setColor(parentOf(parentOf(x)), RED);
//祖父节点右旋
rotateRight(parentOf(parentOf(x)));
}
} else { //父类节点在祖父节点的右节点
//获取叔叔节点
Entry<K,V> y = leftOf(parentOf(parentOf(x)));
//叔叔节点是红色
if (colorOf(y) == RED) {
//父节点设置为黑色
setColor(parentOf(x), BLACK);
//叔叔节点设置为黑色
setColor(y, BLACK);
//祖父节点设置为红色
setColor(parentOf(parentOf(x)), RED);
//祖父节点设置为当前节点
x = parentOf(parentOf(x));
} else { //叔叔节点是黑色
//当前节点是父节点的左节点
if (x == leftOf(parentOf(x))) {
//把父节点设置为当前节点
x = parentOf(x);
//父节点进行右旋
rotateRight(x);
}
//父节点设置为黑色
setColor(parentOf(x), BLACK);
//祖父节点设置为红色
setColor(parentOf(parentOf(x)), RED);
//祖父节点进行左旋
rotateLeft(parentOf(parentOf(x)));
}
}
}
//根节点设置为黑色
root.color = BLACK;
}
左旋
/** From CLR */
private void rotateLeft(Entry<K,V> p) {
if (p != null) {
Entry<K,V> r = p.right;
p.right = r.left;
if (r.left != null)
r.left.parent = p;
r.parent = p.parent;
if (p.parent == null)
root = r;
else if (p.parent.left == p)
p.parent.left = r;
else
p.parent.right = r;
r.left = p;
p.parent = r;
}
}
右旋
/** From CLR */
private void rotateRight(Entry<K,V> p) {
if (p != null) {
Entry<K,V> l = p.left;
p.left = l.right;
if (l.right != null) l.right.parent = p;
l.parent = p.parent;
if (p.parent == null)
root = l;
else if (p.parent.right == p)
p.parent.right = l;
else p.parent.left = l;
l.right = p;
p.parent = l;
}
}
HashMap
JDK1.7及以前，底层实现是数组 + 链表
JDK1.8之后，底层是数组 + 链表 / 数组 + 红黑树
初始化
// 数组的默认长度为16
static final int DEFAULT_INITIAL_CAPACITY = 1 << 4; // aka 16
// 数组的最大容量为10亿多
static final int MAXIMUM_CAPACITY = 1 << 30;
// 默认的扩容平衡因子
static final float DEFAULT_LOAD_FACTOR = 0.75f;
// 链表转红黑树的临界值，当链表长度大于等于8的时候转换成红黑树
static final int TREEIFY_THRESHOLD = 8;
// 红黑树转链表的临界值，当红黑树的节点小于等于6时转换成链表
static final int UNTREEIFY_THRESHOLD = 6;
// 链表转红黑树的另一个条件是，数组的长度要大于64
static final int MIN_TREEIFY_CAPACITY = 64;
// 数组结构
transient Node<K,V>[] table;
// Map集合中的元素个数
transient int size;
// 修改的次数
transient int modCount;
// 扩容的临界值
int threshold;
// 实际扩容因子
final float loadFactor;
put()
public V put(K key, V value) {
//hash(key) 以key为参数获取hash值
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 n, i;
// 第一次table = null
// tab：数组结构 tab = null
if ((tab = table) == null || (n = tab.length) == 0)
// n：数组长度，n = 16
// 第一次进来的时候resize()代表初始数组
n = (tab = resize()).length;
// 根据hash值找到的数组的下标里面没有值得话，就直接赋值
if ((p = tab[i = (n - 1) & hash]) == null)
tab[i] = newNode(hash, key, value, null);
else {
// 根据hash值找到的数组下标里面有值的话，走下面的步骤
Node<K,V> e; K k;
// 根据hash值找到的hash值与传的key转换的hash值相当的话 或者 根据hash值找到的key等于传入的key 就直接覆盖
if (p.hash == hash &&
((k = p.key) == key || (key != null && key.equals(k))))
e = p;
else if (p instanceof TreeNode) //根据hash值找到的数组位置是红黑树的话，就直接插入
e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
else {
// 表示节点是普通的链表
// 循环链表
for (int binCount = 0; ; ++binCount) {
// 直至循环到尾节点指向的next是null
if ((e = p.next) == null) {
// 就把当前的值插入到链表的最底部
p.next = newNode(hash, key, value, null);
// 当链表的长度大于等于7的时候，进行转换红黑树的判断
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;
}
final Node<K,V>[] resize() {
// table = null
// oldTab = null
Node<K,V>[] oldTab = table;
// oldCap = 0
int oldCap = (oldTab == null) ? 0 : oldTab.length;
// oldThr = 0
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 = 16
newCap = DEFAULT_INITIAL_CAPACITY;
// newThr = 12
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);
}
// 更新了扩容临界值
// threshold = 12
threshold = newThr;
@SuppressWarnings({"rawtypes","unchecked"})
// 创建了一个容量为16的数组
Node<K,V>[] newTab = (Node<K,V>[])new Node[newCap];
// 当前数组结构就是一个容量为16的数组
//table = [16]{}
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;
}
final void treeifyBin(Node<K,V>[] tab, int hash) {
int n, index; Node<K,V> e;
// 如果tab = null 或者
// 数组结构的长度赋值为n，n < 64的话继续扩容
if (tab == null || (n = tab.length) < MIN_TREEIFY_CAPACITY)
// 扩容
resize();
else if ((e = tab[index = (n - 1) & hash]) != null) { // 取出当前下标下的链表数据
// 下面就是链表转红黑树的逻辑
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);
}
}
动态扩容resize()
final Node<K,V>[] resize() {
// oldTab = table = {e,e,e,e,e,e,e,e,e,e,e,null,null,null,null,null} length = 16
Node<K,V>[] oldTab = table;
// oldCap = 16
int oldCap = (oldTab == null) ? 0 : oldTab.length;
// oldThr = 12
int oldThr = threshold;
int newCap, newThr = 0;
if (oldCap > 0) {
if (oldCap >= MAXIMUM_CAPACITY) {
threshold = Integer.MAX_VALUE;
return oldTab;
}
// newCap = oldCap = 32
else if ((newCap = oldCap << 1) < MAXIMUM_CAPACITY &&
oldCap >= DEFAULT_INITIAL_CAPACITY)
// newThr = 24
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 = 24
threshold = newThr;
@SuppressWarnings({"rawtypes","unchecked"})
// 创建一个数组的长度为32
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)
// 数组中的元素就一个的话就直接找到元素在新的数组中的位置 直接赋值
newTab[e.hash & (newCap - 1)] = e;
else if (e instanceof TreeNode) // 如果数组中的元素是数的话 就整体移动红黑树
((TreeNode<K,V>)e).split(this, newTab, j, oldCap);
else { // preserve order
// 下面是链表的移动
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;
}
