/** * 对外暴露的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; //如果map为空,则做初始化,table是map中存放索引的表 if ((tab = table) == null || (n = tab.length) == 0) n = (tab = resize()).length; //使用hash与数组长度减一的值进行异或得到分散的数组下标,如果这个位置上没有值,新建k-v节点存放 if ((p = tab[i = (n - 1) & hash]) == null) tab[i] = newNode(hash, key, value, null); //走到else这里说明出现了哈希冲突,需要处理哈希冲突再存放 else { Node<K,V> e; K k; //p为上面发生碰撞的那个节点,作比较后将p用临时节点e保存 if (p.hash == hash && ((k = p.key) == key || (key != null && key.equals(k)))) e = p; //如果当前节点是红黑树节点,则特殊处理,如果是树,说明碰撞已经开始,后序数据结构都是树不是链表 else if (p instanceof TreeNode) e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value); //key不存在且不是红黑树节点,则开始遍历链表 else { for (int binCount = 0; ; ++binCount) { //如果当前碰撞节点没有后序节点,则直接新建节点并追加 if ((e = p.next) == null) { p.next = newNode(hash, key, value, null); //追加的链表长度大于8,那么需要重新评估当前是扩充数组还是将链表转换为红黑树来存储 //TREEIFY_THRESHOLD等于8 if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st treeifyBin(tab, hash); break; } //找到碰撞节点,key完全相等的节点,则用新节点替换老节点 if (e.hash == hash && ((k = e.key) == key || (key != null && key.equals(k)))) break; p = e; } } //此时的e是保存的被碰撞的那个节点,即老节点 if (e != null) { // existing mapping for key V oldValue = e.value; // onlyIfAbsent是方法的调用参数,表示是否替换已存在的值, // 在默认的put方法中这个值是false,所以这里会用新值替换旧值 if (!onlyIfAbsent || oldValue == null) e.value = value; afterNodeAccess(e); return oldValue; } } // map变更性操作计数器 // 比如map结构化的变更像内容增减或者rehash,这将直接导致外部map的并发 // 迭代引起fail-fast问题,该值就是比较的基础 ++modCount; // size即map中包括k-v数量的多少 // 当map中的内容大小已经触及到扩容阈值时,则需要扩容了 if (++size > threshold) resize(); afterNodeInsertion(evict); return null; }
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; }
当存储值发生碰撞,并在当前节点已经延申到树时,将执行putTreeVal方法,里面描述了红黑树存储值的计算方法:
final TreeNode<K,V> putTreeVal(HashMap<K,V> map, Node<K,V>[] tab,int h, K k, V v) { Class<?> kc = null; boolean searched = false; TreeNode<K,V> root = (parent != null) ? root() : this; for (TreeNode<K,V> p = root;;) { int dir, ph; K pk; if ((ph = p.hash) > h) dir = -1; else if (ph < h) dir = 1; else if ((pk = p.key) == k || (k != null && k.equals(pk))) return p; else if ((kc == null && (kc = comparableClassFor(k)) == null) || (dir = compareComparables(kc, k, pk)) == 0) { if (!searched) { TreeNode<K,V> q, ch; searched = true; if (((ch = p.left) != null && (q = ch.find(h, k, kc)) != null) || ((ch = p.right) != null && (q = ch.find(h, k, kc)) != null)) return q; } dir = tieBreakOrder(k, pk); } TreeNode<K,V> xp = p; if ((p = (dir <= 0) ? p.left : p.right) == null) { Node<K,V> xpn = xp.next; TreeNode<K,V> x = map.newTreeNode(h, k, v, xpn); if (dir <= 0) xp.left = x; else xp.right = x; xp.next = x; x.parent = x.prev = xp; if (xpn != null) ((TreeNode<K,V>)xpn).prev = x; moveRootToFront(tab, balanceInsertion(root, x)); return null; } } }
在值发生碰撞并需要延续追加时,如果追加的链表长度大于8,那么需要treeifyBin()方法重新评估当前是扩充数组还是将链表转换为红黑树来存储。
final void treeifyBin(Node<K,V>[] tab, int hash) { int n, index; Node<K,V> e; if (tab == null || (n = tab.length) < MIN_TREEIFY_CAPACITY) resize(); else if ((e = tab[index = (n - 1) & hash]) != null) { 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); } }
扩充数组长度方法resize,会将整个map中的k-v对重新散列存储,会消耗性能
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) { // MAXIMUM_CAPACITY = 1 << 30 = 1073741824 // Integer.MAX_VALUE = (1 << 31) - 1 = 2147483647 // 如果已经到了最大容量了,那么就调整扩容的threshold阈值 if (oldCap >= MAXIMUM_CAPACITY) { threshold = Integer.MAX_VALUE; return oldTab; } // DEFAULT_INITIAL_CAPACITY = 1 << 4 // 否则的话,如果将目前的容量扩充2倍还在允许范围之内,则将容量 // 扩充为原来的两倍,并且阈值也为原来的两倍 else if ((newCap = oldCap << 1) < MAXIMUM_CAPACITY && oldCap >= DEFAULT_INITIAL_CAPACITY) newThr = oldThr << 1; // double threshold } // 如果原始(或者初始)容量不大于0,且之前的阈值大于0,则将容量初始化为 // 之前阈值的大小 else if (oldThr > 0) // initial capacity was placed in threshold newCap = oldThr; else { // zero initial threshold signifies using defaults // 执行这里的方法说明,初始参数中容量大小和阈值都不大于0,那么就用 // map中的缺省值 // DEFAULT_INITIAL_CAPACITY = 1 << 4 = 16 // DEFAULT_LOAD_FACTOR = 0.75f newCap = DEFAULT_INITIAL_CAPACITY; newThr = (int)(DEFAULT_LOAD_FACTOR * DEFAULT_INITIAL_CAPACITY); } // 如果新的阈值没有重新计算,那么先用加载因子计算出值 // 如果新的容量大小和阈值大小都未超过限定值,则计算出的值可用,否则 // 阈值就限定为容量真正允许的上限即Integer.MAX_VALUE 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已经是扩容好的新table了 // 老的table存在了oldTab中 table = newTab; // 以下就是一个重新散列存储的过程了 // 将老的tab中的node,按照key重新散列得到新得存储地址来存储, // 以此来完成扩充 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; }