JDK1.8 源码 java.util.TreeMap

前言

本章, 我们主要介绍java.util.TreeMap.

根据上述图片, 其继承关系为TreeMap -> NavigableMap -> SortedMap -> Map.

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总览

同样. 我们从成员变量和基本方法进行解读.

• 成员变量

  • private final Comparator<? super K> comparator;
    

  • private transient Entry<K,V> root;
    

  • private transient int size = 0;
    

  • private transient int modCount = 0;
    

• 基本方法
  • 构造函数
  • 比较器
  • 查询
  • 增
  • 删
  • 改

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类声明

public class TreeMap<K,V>extends AbstractMap<K,V>implements NavigableMap<K,V>, Cloneable, java.io.Serializable
{

public interface NavigableMap<K,V> extends SortedMap<K,V> {

public interface SortedMap<K,V> extends Map<K,V> {Comparator<? super K> comparator();

public interface Map<K,V> {

对于TreeMap -> NavigableMap -> SortedMap -> Map这条继承线. 这边一带而过, Comparator比较器是在SortedMap内定义的. 后面有时间再仔细讲解.

• 数据节点

    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;boolean color = BLACK;}

TreeMap的数据节点. 可以看出, 其是一个红黑树节点. 除了包括 K/V之外, 还包括了父指针/左指针/右指针和节点颜色标记.

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构造函数

• 构造函数

   public TreeMap() {comparator = null;}public TreeMap(Comparator<? super K> comparator) {this.comparator = comparator;}public TreeMap(Map<? extends K, ? extends V> m) {comparator = null;putAll(m);}public TreeMap(SortedMap<K, ? extends V> m) {comparator = m.comparator();try {buildFromSorted(m.size(), m.entrySet().iterator(), null, null);} catch (java.io.IOException cannotHappen) {} catch (ClassNotFoundException cannotHappen) {}}

其构造函数主要包括4种:

• 无参构造函数 public TreeMap()
• 带比较器构造函数 public TreeMap(Comparator<? super K> comparator)
• 普通Map构造函数 public TreeMap(Map<? extends K, ? extends V> m)
• 有序SortedMap构造函数 public TreeMap(SortedMap<K, ? extends V> m)

比较器

可以看到比较器``

    private final Comparator<? super K> comparator;

public interface Comparator<T> {int compare(T o1, T o2);boolean equals(Object obj);
}

比较器内主要需要实现的方法为compare() 方法与equals()方法.
关于Comparator接口, 我们日常使用的时候主要有3种写法. 详情可看Java 之集合排序

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查找元素

• 查询方法

   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 performanceif (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);if (cmp < 0)p = p.left;else if (cmp > 0)p = p.right;elsereturn p;}return null;}

从此处可以看到. 这就是一个二叉排序树的搜索. 从root节点开始. 如果小于, 则比较左节点; 如果大于, 则比较右节点. 至于为何能这样进行查找, 还是要看其插入和删除节点.

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插入节点

• 插入节点 public V put(K key, V value)

    public V put(K key, V value) {Entry<K,V> t = root;if (t == null) {// 没有root节点 & 即没有根节点compare(key, key); // type (and possibly null) checkroot = new Entry<>(key, value, null);size = 1;modCount++;return null;}int cmp;Entry<K,V> parent;// split comparator and comparable paths// 比较器Comparator<? super K> cpr = comparator;if (cpr != null) {// 有比较器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key相同的节点 直接覆盖return t.setValue(value);} while (t != null);}else {// 没有比较器 - 使用默认比较器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;elsereturn t.setValue(value);} while (t != null);}// 创建新节点Entry<K,V> e = new Entry<>(key, value, parent);if (cmp < 0)parent.left = e;elseparent.right = e;// fix即红黑树平衡操作fixAfterInsertion(e);size++;modCount++;return null;}

插入操作主要分为如下几种情况:

• 无root节点 - 新节点即root节点
• 找到该节点 - 更新节点内的值.
• 找到一个叶子节点. 新增节点. 随后进行红黑树平衡操作.

红黑树平衡操作

   /** From CLR */private void fixAfterInsertion(Entry<K,V> x) {x.color = RED;while (x != null && x != root && x.parent.color == RED) {if (parentOf(x) == leftOf(parentOf(parentOf(x)))) {Entry<K,V> y = rightOf(parentOf(parentOf(x)));if (colorOf(y) == RED) {setColor(parentOf(x), BLACK);setColor(y, BLACK);setColor(parentOf(parentOf(x)), RED);x = parentOf(parentOf(x));} else {if (x == rightOf(parentOf(x))) {x = parentOf(x);rotateLeft(x);}setColor(parentOf(x), BLACK);setColor(parentOf(parentOf(x)), RED);rotateRight(parentOf(parentOf(x)));}} else {Entry<K,V> y = leftOf(parentOf(parentOf(x)));if (colorOf(y) == RED) {setColor(parentOf(x), BLACK);setColor(y, BLACK);setColor(parentOf(parentOf(x)), RED);x = parentOf(parentOf(x));} else {if (x == leftOf(parentOf(x))) {x = parentOf(x);rotateRight(x);}setColor(parentOf(x), BLACK);setColor(parentOf(parentOf(x)), RED);rotateLeft(parentOf(parentOf(x)));}}}root.color = BLACK;}

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删除节点

• remove(Object key)

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

• deleteEntry()

   private void deleteEntry(Entry<K,V> p) {modCount++;size--;// If strictly internal, copy successor's element to p and then make p// point to successor.// 有左右节点if (p.left != null && p.right != null) {// 获取中序后续节点Entry<K,V> s = successor(p);p.key = s.key;p.value = s.value;p = s;} // p has 2 children// Start fixup at replacement node, if it exists.// 注意 如果之前有左右节点. 前面的更新后 左右子树都是null.Entry<K,V> replacement = (p.left != null ? p.left : p.right);if (replacement != null) {// Link replacement to parentreplacement.parent = p.parent;if (p.parent == null)// 只有一个节点root = replacement;else if (p == p.parent.left)// 只有左节点p.parent.left  = replacement;else// 只有右节点p.parent.right = replacement;// Null out links so they are OK to use by fixAfterDeletion.p.left = p.right = p.parent = null;// Fix replacementif (p.color == BLACK)fixAfterDeletion(replacement);} else if (p.parent == null) { // return if we are the only node.// 	只有一个节点 即根节点root = null;} else { //  No children. Use self as phantom replacement and unlink.// 是叶节点if (p.color == BLACK)fixAfterDeletion(p);if (p.parent != null) {// 更新<叶节点p>的<parent节点>的指针if (p == p.parent.left)p.parent.left = null;else if (p == p.parent.right)p.parent.right = null;p.parent = null;}}}

删除的逻辑主要如下所示:

• 删除的节点为叶子节点：直接删除. 平衡红黑树. (红黑树的特性是叶子节点都是BLACK.)

• 删除的节点只有左节点, 或者右节点. 将左或右节点与父节点交换. 随后删除.

• 删除的节点有左右子节点.

  • 寻找节点的中序后续节点. successor方法. 即左边最左, 或者右边最右节点. 随后进行替换.
  • 替换后删除节点值. 并将节点指针指向叶子节点.
  • 删除父亲节点指针. parent.left=null 或者parent.right=null.
  • 平衡二叉树.

• successor 寻找中序后续节点

 /*** Returns the successor of the specified Entry, or null if no such.*/static <K,V> TreeMap.Entry<K,V> successor(Entry<K,V> t) {if (t == null)return null;else if (t.right != null) {Entry<K,V> p = t.right;while (p.left != null)p = p.left;return p;} else {Entry<K,V> p = t.parent;Entry<K,V> ch = t;while (p != null && ch == p.right) {ch = p;p = p.parent;}return p;}}

• fixAfterDeletion 删除后的红黑树平衡策略

   /** From CLR */private void fixAfterDeletion(Entry<K,V> x) {while (x != root && colorOf(x) == BLACK) {if (x == leftOf(parentOf(x))) {Entry<K,V> sib = rightOf(parentOf(x));if (colorOf(sib) == RED) {setColor(sib, BLACK);setColor(parentOf(x), RED);rotateLeft(parentOf(x));sib = rightOf(parentOf(x));}if (colorOf(leftOf(sib))  == BLACK &&colorOf(rightOf(sib)) == BLACK) {setColor(sib, RED);x = parentOf(x);} else {if (colorOf(rightOf(sib)) == BLACK) {setColor(leftOf(sib), BLACK);setColor(sib, RED);rotateRight(sib);sib = rightOf(parentOf(x));}setColor(sib, colorOf(parentOf(x)));setColor(parentOf(x), BLACK);setColor(rightOf(sib), BLACK);rotateLeft(parentOf(x));x = root;}} else { // symmetricEntry<K,V> sib = leftOf(parentOf(x));if (colorOf(sib) == RED) {setColor(sib, BLACK);setColor(parentOf(x), RED);rotateRight(parentOf(x));sib = leftOf(parentOf(x));}if (colorOf(rightOf(sib)) == BLACK &&colorOf(leftOf(sib)) == BLACK) {setColor(sib, RED);x = parentOf(x);} else {if (colorOf(leftOf(sib)) == BLACK) {setColor(rightOf(sib), BLACK);setColor(sib, RED);rotateLeft(sib);sib = leftOf(parentOf(x));}setColor(sib, colorOf(parentOf(x)));setColor(parentOf(x), BLACK);setColor(leftOf(sib), BLACK);rotateRight(parentOf(x));x = root;}}}setColor(x, BLACK);}

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遍历

To be continue.

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小结

• TreeMap是一种使用红黑树存储,来实现Map类型的结构.
• 优点: 有序. 可以按照想要的顺序进行排序. 一定数据规模的情况下查询比较快.
• 缺点: 缺点也很明显. 那就是删除和新增节点都需要平衡红黑树.

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Reference

[1]. JDK1.8源码(十一)——java.util.TreeMap类