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Java原始碼分析之HashMap(JDK1.8)

一、HashMap概述

  HashMap是常用的Java集合之一,是基於雜湊表的Map介面的實現。與HashTable主要區別為不支援同步和允許null作為key和value。由於HashMap不是執行緒安全的,如果想要執行緒安全,可以使用ConcurrentHashMap代替。

二、HashMap資料結構

  HashMap的底層是雜湊陣列,陣列元素為Entry。HashMap通過key的hashCode來計算hash值,當hashCode相同時,通過“拉鍊法”解決衝突,如下圖所示。

HashMap資料結構

  相比於之前的版本,jdk1.8在解決雜湊衝突時有了較大的變化,當連結串列長度大於閾值(預設為8)時,將連結串列轉化為紅黑樹,以減少搜尋時間。原本Map.Entry介面的實現類Entry改名為了Node。轉化為紅黑樹時改用另一種實現TreeNode。
  

Node類

static class Node<K,V> implements Map.Entry<K,V> {
        final int hash; // 雜湊值
        final K key;
        V value;
        Node<K,V> next; // 指向下一個節點

        Node(int hash, K key, V value, Node<K,V> next) {
            this.hash = hash;
            this.key = key;
            this
.value = value; this.next = next; } public final K getKey() { return key; } public final V getValue() { return value; } public final String toString() { return key + "=" + value; } public final int hashCode() { return Objects.hashCode(key) ^ Objects.hashCode(value); } public
final V setValue(V newValue) { V oldValue = value; value = newValue; return oldValue; } 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; } }

TreeNode類

    static final class TreeNode<K,V> extends LinkedHashMap.Entry<K,V> {
        TreeNode<K,V> parent;  // red-black tree links
        TreeNode<K,V> left;
        TreeNode<K,V> right;
        TreeNode<K,V> prev;    // needed to unlink next upon deletion
        boolean red;
        TreeNode(int hash, K key, V val, Node<K,V> next) {
            super(hash, key, val, next);
        }
    }

  HashMap就是這樣一個Entry(包括Node和TreeNode)陣列,Node物件中包含鍵、值和hash值,next指向下一個Entry,用來處理雜湊衝突。TreeNode物件包含指向父節點、子節點和前一個節點(移除物件時使用)的指標,以及表示紅黑節點的boolean標識。

三、HashMap原始碼分析

1. 主要屬性

    transient Node<K,V>[] table; // 雜湊陣列

    transient Set<Map.Entry<K,V>> entrySet; // entry快取Set

    transient int size; // 元素個數

    transient int modCount; // 修改次數

    int threshold; // 閾值,等於載入因子*容量,當實際大小超過閾值則進行擴容

    final float loadFactor; // 載入因子,預設值為0.75

2. 構造方法

  以下是HashMap的幾個構造方法。

    /**
     * 根據初始化容量和載入因子構建一個空的HashMap.
     */
    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);
    }

    /**
     * 使用初始化容量和預設載入因子(0.75).
     */
    public HashMap(int initialCapacity) {
        this(initialCapacity, DEFAULT_LOAD_FACTOR);
    }

    /**
     * 使用預設初始化大小(16)和預設載入因子(0.75).
     */
    public HashMap() {
        this.loadFactor = DEFAULT_LOAD_FACTOR; // all other fields defaulted
    }

    /**
     * 用已有的Map構造一個新的HashMap.
     */
    public HashMap(Map<? extends K, ? extends V> m) {
        this.loadFactor = DEFAULT_LOAD_FACTOR;
        putMapEntries(m, false);
    }

3. 資料存取

  • putAll方法
    public void putAll(Map<? extends K, ? extends V> m) {
        putMapEntries(m, true);
    }

    /**
     * Implements Map.putAll and Map constructor
     *
     * @param m the map
     * @param evict false when initially constructing this map, else
     * true (relayed to method afterNodeInsertion).
     */
    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); // put核心方法
            }
        }
    }
  • put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<K,V>[] tab; Node<K,V> p; int n, i;
        if ((tab = table) == null || (n = tab.length) == 0) // table為空或length為0
            n = (tab = resize()).length; // 初始化
        if ((p = tab[i = (n - 1) & hash]) == null) // 如果hash所在位置為null,直接put
            tab[i] = newNode(hash, key, value, null);
        else { // tab[i]有元素,遍歷節點後新增
            Node<K,V> e; K k;
            // 如果hash、key都相等,直接覆蓋
            if (p.hash == hash &&
                ((k = p.key) == key || (key != null && key.equals(k))))
                e = p;
            else if (p instanceof TreeNode) // 紅黑樹新增節點
                e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
            else { // 連結串列
                for (int binCount = 0; ; ++binCount) {
                    if ((e = p.next) == null) { // 找到連結串列最後一個節點,插入新節點
                        p.next = newNode(hash, key, value, null);
                        // 連結串列節點大於閾值8,呼叫treeifyBin方法,當tab.length大於64將連結串列改為紅黑樹
                        // 如果tab.length < 64或tab為null,則呼叫resize方法重構連結串列.
                        if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st
                            treeifyBin(tab, hash);
                        break;
                    }
                    // hash、key都相等,此時節點即要更新節點
                    if (e.hash == hash &&
                        ((k = e.key) == key || (key != null && key.equals(k))))
                        break;
                    p = e;
                }
            }
            // 當前節點e = p.next不為null,表示連結串列中原本存在相同的key,則返回oldValue
            if (e != null) { // existing mapping for key
                V oldValue = e.value;
                // onlyIfAbsent值為false,引數主要決定存在相同key時是否執行替換
                if (!onlyIfAbsent || oldValue == null)
                    e.value = value;
                afterNodeAccess(e);
                return oldValue;
            }
        }
        ++modCount;
        if (++size > threshold) // 檢查是否超過閾值
            resize();
        afterNodeInsertion(evict);
        return null; // 原HashMap中不存在相同的key,插入鍵值對後返回null
    }
  • get方法
    public V get(Object key) {
        Node<K,V> e;
        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<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) // 紅黑樹
                    return ((TreeNode<K,V>)first).getTreeNode(hash, key);
                // 連結串列
                do {
                    if (e.hash == hash &&
                        ((k = e.key) == key || (key != null && key.equals(k))))
                        return e;
                } while ((e = e.next) != null);
            }
        }
        return null;
    }

    // 遍歷紅黑樹搜尋節點
    /**
     * Calls find for root node.
     */
    final TreeNode<K,V> getTreeNode(int h, Object k) {
        return ((parent != null) ? root() : this).find(h, k, null);
    }

    /**
     * Returns root of tree containing this node.
     */
    final TreeNode<K,V> root() {
        for (TreeNode<K,V> r = this, p;;) {
            if ((p = r.parent) == null)
                return r;
            r = p;
        }
    }

    /**
     * Finds the node starting at root p with the given hash and key.
     * The kc argument caches comparableClassFor(key) upon first use
     * comparing keys.
     */
    final TreeNode<K,V> find(int h, Object k, Class<?> kc) {
        TreeNode<K,V> p = this;
        do {
            int ph, dir; K pk;
            TreeNode<K,V> pl = p.left, pr = p.right, q;
            if ((ph = p.hash) > h) // 當前節點hash大
                p = pl; // 查左子樹
            else if (ph < h) // 當前節點hash小
                p = pr; // 查右子樹
            else if ((pk = p.key) == k || (k != null && k.equals(pk)))
                return p; // hash、key都相等,即找到,返回當前節點
            else if (pl == null) // hash相等,key不等,左子樹為null,查右子樹
                p = pr;
            else if (pr == null)
                p = pl;
            else if ((kc != null ||
                      (kc = comparableClassFor(k)) != null) &&
                     (dir = compareComparables(kc, k, pk)) != 0)
                p = (dir < 0) ? pl : pr;
            else if ((q = pr.find(h, k, kc)) != null)
                return q;
            else
                p = pl;
        } while (p != null);
        return null;
    }
  • remove方法
    public V remove(Object key) {
        Node<K,V> e;
        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<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;
            // 直接命中
            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) // 在紅黑樹中查詢
                    node = ((TreeNode<K,V>)p).getTreeNode(hash, key);
                else { // 在連結串列中查詢
                    do {
                        if (e.hash == hash &&
                            ((k = e.key) == key ||
                             (key != null && key.equals(k)))) {
                            node = e;
                            break;
                        }
                        p = e;
                    } while ((e = e.next) != null);
                }
            }
            // 命中後刪除
            if (node != null && (!matchValue || (v = node.value) == value ||
                                 (value != null && value.equals(v)))) {
                if (node instanceof TreeNode) // 在紅黑樹中刪除節點
                    ((TreeNode<K,V>)node).removeTreeNode(this, tab, movable);
                else if (node == p) // 連結串列首節點刪除
                    tab[index] = node.next;
                else // 多節點連結串列刪除
                    p.next = node.next;
                ++modCount;
                --size;
                afterNodeRemoval(node);
                return node;
            }
        }
        return null;
    }
  • clear方法
    /**
     * Removes all of the mappings from this map.
     * The map will be empty after this call returns.
     */
    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; // 把雜湊陣列中所有位置都賦為null
        }
    }

四、總結

  本文從原始碼入手,簡單地分析了HashMap底層的結構和實現。在原始碼分析部分主要分析了常用的幾個方法,還有一些方法比如調整雜湊表大小的resize、將連結串列轉化為紅黑樹的treeify以及逆操作untreeify等,在此不再詳細分析。紅黑樹部分的程式碼只理解了大概,實現細節上還有待進一步閱讀分析。