Java 源码:数据结构 Map

Posted by danner on August 24, 2019

HashMap

HashMap 底层的数据结构主要是:数组 + 单链表 + 红黑树;其中当链表的长度大于等于8时,并且整个数组大小大于64,链表会转化成红黑树,当红黑树大小小于等于6时,红黑树会转化成链表。

底层是 Node 数组 + 链表/红黑数,键值hash 后按位与上(数组长度 - 1) 就是数组序列号, key 可为空。HashMap 的存储过程:

  • key hash得到 hash 值
  • 根据hash 值找到在map 数组中的下标,查看当前数组下标是否有 node
  • 如果没有node,直接新建node 赋值;
  • 如果有node 表示 hash 冲突,则需要链表/红黑树来存储相同 hash 不同key 的node
  • 查看 node 数组是否需要扩容
transient Node<K,V>[] table;
Node(int hash, K key, V value, Node<K,V> next) {
    this.hash = hash;
    this.key = key;
    this.value = value;
    this.next = next;
}

空构造函数

public HashMap() {
	this.loadFactor = DEFAULT_LOAD_FACTOR; // all other fields defaulted
}
// 空 map 新增一个自动增长为 16
static final int DEFAULT_INITIAL_CAPACITY = 1 << 4; // aka 16

put

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;
    // 找到 hash 对应的 数组下标 i 和 node p
    if ((p = tab[i = (n - 1) & hash]) == null)
        // p 为空直接添加
        tab[i] = newNode(hash, key, value, null);
    else {
        // p 不为空,表示有node,存在hash 冲突
        Node<K,V> e; K k;
        if (p.hash == hash &&
            ((k = p.key) == key || (key != null && key.equals(k))))
            // hash 、key 都相同,说明键值是一样,根据onlyIfAbsent 是否直接覆盖
            e = p;
        else if (p instanceof TreeNode)
            // 红黑树插入
            e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
        else {
            // 单链表直接插入到最后
            // 如果中间找到相同key 的 node,根据onlyIfAbsent 是否直接覆盖
            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)
                // onlyIfAbsent = false 表示覆盖
                e.value = value;
            afterNodeAccess(e);
            return oldValue;
        }
    }
    ++modCount;
     // 扩容
    if (++size > threshold)
        resize();
    afterNodeInsertion(evict);
    return null;
}

 // 扩容
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) {
            // size 已经大于 1<<30 ,不能再扩容,加大 threshold
            threshold = Integer.MAX_VALUE;
            return oldTab;
        }
        // 在可扩容的范围下 size *2,threshold*2
        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
        // 原本为0,扩容成16,threshold  = 16*0.75=12
        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) {
        // node 数组增大后,hash 得到的 数组 index 变了,涉及 node 复制
        ......
    }
    return newTab;
}
  • 空值,size 增长到 16
  • 有值,size < (1« 30)
    • (size 2) < (1« 30),size >= 16 : size * 2 直接翻倍,threshold2
    • (size 2) < (1« 30),size < 16 : size * 2 直接翻倍,threshold = size * 20.75
    • (size *2) >= (1« 30),size * 2 直接翻倍,threshold=Integer.MAX_VALUE
  • 有值,size >= (1« 30),不扩容,但增大 threshold=Integer.MAX_VALUE

get

public V get(Object key) {
    Node<K,V> e;
    // 由 key 得到 hash ,去查询
    return (e = getNode(hash(key), key)) == null ? null : e.value;
}
final Node<K,V> getNode(int hash, Object key) {
    Node<K,V>[] tab; Node<K,V> first, e; int n; K k;
    // map 不为空,且tab[hash] 上有 node
    if ((tab = table) != null && (n = tab.length) > 0 &&
        (first = tab[(n - 1) & hash]) != null) {
        // 找到对应node 的条件是 key 相同
        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)
                // 红黑树查找
                return ((TreeNode<K,V>)first).getTreeNode(hash, key);
            do {
                // 普通链表查找
                if (e.hash == hash &&
                    ((k = e.key) == key || (key != null && key.equals(k))))
                    return e;
            } while ((e = e.next) != null);
        }
    }
    return null;
}

删除

public V remove(Object key) {
    Node<K,V> e;
    return (e = removeNode(hash(key), key, null, false, true)) == null ?
        null : e.value;
}
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) {
        // key hash 得到 数组 index
        Node<K,V> node = null, e; K k; V v;
        if (p.hash == hash &&
            ((k = p.key) == key || (key != null && key.equals(k))))
            // 直接在 node 数组上取到
            node = p;
        else if ((e = p.next) != null) {
            if (p instanceof TreeNode)
                // 红黑树中获取
                node = ((TreeNode<K,V>)p).getTreeNode(hash, key);
            else {
                do {
                    // 链表中获取
                    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)
                // 红黑树删除
                ((TreeNode<K,V>)node).removeTreeNode(this, tab, movable);
            else if (node == p)
                // 链表删除,直接删表头
                tab[index] = node.next;
            else
                // 删表中间
                p.next = node.next;
            ++modCount;
            --size;
            afterNodeRemoval(node);
            return node;
        }
    }
    return null;
}

删除 node,并不会涉及到删除 node数组

链表 -> 红黑树的条件是长度大于8:链表查询复杂度是 O(n),红黑树查询复杂度是O(lon(n));在数据不多时,链表也是很快;当数据增多时转化为红黑树,但红黑树需要消耗空间是链表2倍。如果长度大于8 说明 hash 算法可能是有问题的,而且遇到大于8 的概率是很低很低,一般不会使用到红黑树。

TreeMap

treemap 按key 有序排列, 底层就是红黑树,利用红黑树左小右大的特性,可以实现按 key 大小存储。

// key 大小比较器
private final Comparator<? super K> comparator;
private transient Entry<K,V> root;
private transient int size = 0;
private transient int modCount = 0;
// 每个节点数据结构,包含KV,父节点,子左节点,子右节点
static final class Entry<K,V> implements Map.Entry<K,V> {
    K key;
    V value;
    Entry<K,V> left;
    Entry<K,V> right;
    Entry<K,V> parent;

构造函数

public TreeMap() {
    comparator = null;
}
// 传入自定义的比较器
public TreeMap(Comparator<? super K> comparator) {
    this.comparator = comparator;
}
// 可以使用传入的比较器 or 使用key 自带的比较
final int compare(Object k1, Object k2) {
    return comparator==null ? ((Comparable<? super K>)k1).compareTo((K)k2)
        : comparator.compare((K)k1, (K)k2);
}

put

public V put(K key, V value) {
    Entry<K,V> t = root;
    if (t == null) {
        // 空map 直接新建 entry 当 root 节点
        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) {
        // 利用 comparator 比较key 大小找到新增节点在那个parent下
        do {
            parent = t;
            cmp = cpr.compare(key, t.key);
            if (cmp < 0)
                t = t.left;
            else if (cmp > 0)
                t = t.right;
            else
                // 找到相同key,直接覆盖 value 返回
                return t.setValue(value);
        } while (t != null);
    }
    else {
        // 同上面一样,只是比较器用 key 自带
        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);
    }
    // 在 parent 下新建 Entry 添加
    Entry<K,V> e = new Entry<>(key, value, parent);
    if (cmp < 0)
        parent.left = e;
    else
        parent.right = e;
    // 红黑树着色,平衡二叉树为了最坏的检索效率也是高效的,看参考资料三
    fixAfterInsertion(e);
    size++;
    modCount++;
    return null;
}
  • TreeMap 键值不能为 null
  • Node 结构没有扩容概念
  • put 返回的之前key 的value,若没有则为null

get

public V get(Object key) {
    Entry<K,V> p = getEntry(key);
    return (p==null ? null : p.value);
}
final Entry<K,V> getEntry(Object key) {
    // Offload comparator-based version for sake of performance
    if (comparator != null)
        return getEntryUsingComparator(key);
    // key 不能为 null
    if (key == null)
        throw new NullPointerException();
    @SuppressWarnings("unchecked")
    Comparable<? super K> k = (Comparable<? super K>) key;
    Entry<K,V> p = root;
    while (p != null) {
        // 二叉树查找
        int cmp = k.compareTo(p.key);
        if (cmp < 0)
            p = p.left;
        else if (cmp > 0)
            p = p.right;
        else
            return p;
    }
    return null;
}

remove

public V remove(Object key) {
    Entry<K,V> p = getEntry(key);
    if (p == null)
        return null;
	// 删除 Entry
    V oldValue = p.value;
    deleteEntry(p);
    return oldValue;
}

LinkedHashMap

HashMap 是无序的, TreeMap 是按 key 排序,而 LinkedHashMap 是使用迭代器时是按插入顺序。

// 继承 HashMap,可以简单理解是把 LinkedList中元素换成 HashMap.Node 就成了LinkedHashMap,但只可以单向访问
public class LinkedHashMap<K,V> extends HashMap<K,V>
// 头尾节点,
transient LinkedHashMap.Entry<K,V> head;
transient LinkedHashMap.Entry<K,V> tail;
static class Entry<K,V> extends HashMap.Node<K,V> {
    Entry<K,V> before, after;
    Entry(int hash, K key, V value, Node<K,V> next) {
        super(hash, key, value, next);
    }
}
// 访问控制,对于迭代器而言
// false 时,迭代器访问按插入顺序
// true 时,经常访问的key 放到末尾,看 afterNodeAccess
final boolean accessOrder;

put

// put 先调用父类 HashMap.put,但覆写 newNode 方法
Node<K,V> newNode(int hash, K key, V value, Node<K,V> e) {
    LinkedHashMap.Entry<K,V> p =
        new LinkedHashMap.Entry<K,V>(hash, key, value, e);
    linkNodeLast(p);
    return p;
}
// 新节点插在末尾,迭代时保证插入顺序
private void linkNodeLast(LinkedHashMap.Entry<K,V> p) {
    LinkedHashMap.Entry<K,V> last = tail;
    tail = p;
    if (last == null)
        head = p;
    else {
        p.before = last;
        last.after = p;
    }
}

迭代器

final LinkedHashMap.Entry<K,V> nextNode() {
    LinkedHashMap.Entry<K,V> e = next;
    if (modCount != expectedModCount)
        throw new ConcurrentModificationException();
    if (e == null)
        throw new NoSuchElementException();
    // 插入顺序访问
    current = e;
    next = e.after;
    return e;
}

get

// 除了afterNodeAccess ,其他与 HashMap 相同
public V get(Object key) {
    Node<K,V> e;
    if ((e = getNode(hash(key), key)) == null)
        return null;
    if (accessOrder)
        afterNodeAccess(e);
    return e.value;
}
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;
}
void afterNodeAccess(Node<K,V> e) { // move node to last
    LinkedHashMap.Entry<K,V> last;
    // accessOrder = false 直接退出
    if (accessOrder && (last = tail) != e) {
        // accessOrder = true,把当前访问的节点移动到最后 tail
        LinkedHashMap.Entry<K,V> p =
            (LinkedHashMap.Entry<K,V>)e, b = p.before, a = p.after;
        p.after = null;
        if (b == null)
            head = a;
        else
            b.after = a;
        if (a != null)
            a.before = b;
        else
            last = b;
        if (last == null)
            head = p;
        else {
            p.before = last;
            last.after = p;
        }
        tail = p;
        ++modCount;
    }
}

LinkedHashMapHashMap 基础上增加链表操作后新增访问控制(迭代器)

  • 按插入顺序访问(后插入排在后面)
  • 按使用次数访问(用的最多排在末尾)

参考资料

JDK8

面试官系统精讲Java 源码及大厂真题

Java提高篇(二七)—–TreeMap