public class HashMap1.1、底层数据结构extends AbstractMap implements Map , Cloneable, Serializable { // 默认数组大小 static final int DEFAULT_INITIAL_CAPACITY = 1 << 4; // aka 16 // 默认加载因子 static final float DEFAULT_LOAD_FACTOR = 0.75f; static final Entry,?>[] EMPTY_TABLE = {}; transient Entry [] table = (Entry []) EMPTY_TABLE; transient int size; int threshold; final float loadFactor; public HashMap() { this(DEFAULT_INITIAL_CAPACITY, DEFAULT_LOAD_FACTOR); } 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; threshold = initialCapacity; init(); } public V put(K key, V value) { if (table == EMPTY_TABLE) { inflateTable(threshold); } if (key == null) return putForNullKey(value); int hash = hash(key); int i = indexFor(hash, table.length); for (Entry e = table[i]; e != null; e = e.next) { Object k; if (e.hash == hash && ((k = e.key) == key || key.equals(k))) { V oldValue = e.value; e.value = value; e.recordAccess(this); return oldValue; } } modCount++; // 修改次数 addEntry(hash, key, value, i); return null; } private void inflateTable(int toSize) { // Find a power of 2 >= toSize int capacity = roundUpToPowerOf2(toSize); threshold = (int) Math.min(capacity * loadFactor, MAXIMUM_CAPACITY + 1); table = new Entry[capacity]; initHashSeedAsNeeded(capacity); } private static int roundUpToPowerOf2(int number) { // assert number >= 0 : "number must be non-negative"; return number >= MAXIMUM_CAPACITY ? MAXIMUM_CAPACITY : (number > 1) ? Integer.highestoneBit((number - 1) << 1) : 1; } final boolean initHashSeedAsNeeded(int capacity) { boolean currentAltHashing = hashSeed != 0; boolean useAltHashing = sun.misc.VM.isBooted() && (capacity >= Holder.ALTERNATIVE_HASHING_THRESHOLD); boolean switching = currentAltHashing ^ useAltHashing; if (switching) { hashSeed = useAltHashing ? sun.misc.Hashing.randomHashSeed(this) : 0; } return switching; } private V putForNullKey(V value) { for (Entry e = table[0]; e != null; e = e.next) { if (e.key == null) { V oldValue = e.value; e.value = value; e.recordAccess(this); return oldValue; } } modCount++; addEntry(0, null, value, 0); return null; } final int hash(Object k) { int h = hashSeed; if (0 != h && k instanceof String) { return sun.misc.Hashing.stringHash32((String) k); } h ^= k.hashCode(); // This function ensures that hashCodes that differ only by // constant multiples at each bit position have a bounded // number of collisions (approximately 8 at default load factor). h ^= (h >>> 20) ^ (h >>> 12); return h ^ (h >>> 7) ^ (h >>> 4); } static int indexFor(int h, int length) { // assert Integer.bitCount(length) == 1 : "length must be a non-zero power of 2"; return h & (length-1); }
上面是HashMap的关键代码,其中Entry
static class Entryimplements Map.Entry { final K key; // 键对象 V value; // 值对象 Entry next; // 下一个Entry对象引用 int hash; ...... }
从上面的代码可以看出,HashMap底层实现数据结构(数组+链表): Entry类型的table数组 + entry类型的链式结构。
1.2、关键方法put如果底层数组table是空数组,则初始化table。
if (table == EMPTY_TABLE) { inflateTable(threshold); }
根据传入的threshold值计算刚好出比其大的2的N次方为table数组容量。
private void inflateTable(int toSize) { // Find a power of 2 >= toSize int capacity = roundUpToPowerOf2(toSize); threshold = (int) Math.min(capacity * loadFactor, MAXIMUM_CAPACITY + 1); table = new Entry[capacity]; initHashSeedAsNeeded(capacity); }
判断可以是否为null,如果key==null,则保存到table[0]下。
if (key == null) return putForNullKey(value);
private V putForNullKey(V value) { for (Entrye = table[0]; e != null; e = e.next) { if (e.key == null) { V oldValue = e.value; e.value = value; e.recordAccess(this); return oldValue; } } modCount++; addEntry(0, null, value, 0); return null; }
从上面的代码可以看出,key为null的entry对象是放在table[0]对象所在的第一条链表中,保存新值并返回原来的值。
然后是计算key的hash值(hash方法后面在研究):
int hash = hash(key);
根据等到的hash值,计算出table数组索引下标值:
int i = indexFor(hash, table.length);
static int indexFor(int h, int length) { // assert Integer.bitCount(length) == 1 : // "length must be a non-zero power of 2"; return h & (length-1); }
遍历table[i]下的链表,如果key存在,则替换新值替换老值,并返回老值。
for (Entrye = table[i]; e != null; e = e.next) { Object k; if (e.hash == hash && ((k = e.key) == key || key.equals(k))) { V oldValue = e.value; e.value = value; e.recordAccess(this); // hashMap中此方法为空方法 return oldValue; } }
如果key不存在于table[i]下的链表中,则以key-value为键值对创建entry对象,并保存。
addEntry(hash, key, value, i);1.3、关键方法addEntry:
void addEntry(int hash, K key, V value, int bucketIndex) { // 1、判断是否需要扩容table数组 // 条件: // 1)当前HashMap中有效entry个数 >= table数组容量 * loadFactor; // 2)当前table[bucketIndex]不为null(table[bucketIndex]存在元素) if ((size >= threshold) && (null != table[bucketIndex])) { // 扩容table数组 resize(2 * table.length); // 扩容后需要重新计算hash值和索引下标 hash = (null != key) ? hash(key) : 0; bucketIndex = indexFor(hash, table.length); } // 2、创建entry并保存为table[i]的头结点 createEntry(hash, key, value, bucketIndex); }
先来看createEntry方法:
void createEntry(int hash, K key, V value, int bucketIndex) { // 获取table[bucketIndex],即table[bucketIndex]为所在链表的头结点 Entrye = table[bucketIndex]; // 创建Entry,将之前的 头结点e 设置为新new节点的后置next节点 table[bucketIndex] = new Entry<>(hash, key, value, e); size++; }
从createEntry方法可以看出,新创建的entry节点是作为头结点放在table数组指定下标的链表中。
下面我们重点看一下addEntry方法中出现的resize(2 * table.length)代码。
从传入resize方法的参数(2 * table.length)可以看出,在扩容的时候底层table数组实际变为原先长度的2倍。
void resize(int newCapacity) { Entry[] oldTable = table; int oldCapacity = oldTable.length; // 1、如果当前table数组的长度已经是2的30次方,则不进行扩容 if (oldCapacity == MAXIMUM_CAPACITY) { threshold = Integer.MAX_VALUE; return; } Entry[] newTable = new Entry[newCapacity]; // 2、转移老table数组的元素到新table数组上(重要) transfer(newTable, initHashSeedAsNeeded(newCapacity)); table = newTable; threshold = (int)Math.min(newCapacity * loadFactor, MAXIMUM_CAPACITY + 1); }
进入transfer方法,遍历老table数组和链表中的entry,重新计算hash值和新数组table索引下标,并将entry迁移到新table数组中:
void transfer(Entry[] newTable, boolean rehash) { int newCapacity = newTable.length; for (Entrye : table) { while(null != e) { Entry next = e.next; // 是否需要重新计算hash值 if (rehash) { e.hash = null == e.key ? 0 : hash(e.key); } // 重新计算table数组索引下标 int i = indexFor(e.hash, newCapacity); e.next = newTable[i]; newTable[i] = e; e = next; } } }
以上就是hashMap的put方法的主要流程,在其中我们应该注意额外几点:
1)hashSeed的作用
transient int hashSeed = 0;
2)roundUpToPowerOf2方法的作用
private static int roundUpToPowerOf2(int number) { // assert number >= 0 : "number must be non-negative"; return number >= MAXIMUM_CAPACITY ? MAXIMUM_CAPACITY : (number > 1) ? Integer.highestoneBit((number - 1) << 1) : 1; }
3)initHashSeedAsNeeded方法的作用
final boolean initHashSeedAsNeeded(int capacity) { boolean currentAltHashing = hashSeed != 0; boolean useAltHashing = sun.misc.VM.isBooted() && (capacity >= Holder.ALTERNATIVE_HASHING_THRESHOLD); boolean switching = currentAltHashing ^ useAltHashing; if (switching) { hashSeed = useAltHashing ? sun.misc.Hashing.randomHashSeed(this) : 0; } return switching; }
4)hash方法的作用
final int hash(Object k) { int h = hashSeed; if (0 != h && k instanceof String) { return sun.misc.Hashing.stringHash32((String) k); } h ^= k.hashCode(); // This function ensures that hashCodes that differ only by // constant multiples at each bit position have a bounded // number of collisions (approximately 8 at default load factor). h ^= (h >>> 20) ^ (h >>> 12); return h ^ (h >>> 7) ^ (h >>> 4); }2、jdk1.8关键代码
public class HashMap2.1、底层数据结构extends AbstractMap implements Map , Cloneable, Serializable { static final int DEFAULT_INITIAL_CAPACITY = 1 << 4; // aka 16 // 底层table数组最大长度2的30次方 static final int MAXIMUM_CAPACITY = 1 << 30; // 默认加载因子 static final float DEFAULT_LOAD_FACTOR = 0.75f; // 链表树化的元素个数 static final int TREEIFY_THRESHOLD = 8; // 解除树化的元素个数 static final int UNTREEIFY_THRESHOLD = 6; // 树化时底层table的最小长度 static final int MIN_TREEIFY_CAPACITY = 64; // 底层数组table transient Node [] table; // 有效元素个数 transient int size; // 实际加载因子 final float loadFactor; // 默认构造器,只设置 加载因子,其他属性取默认值 public HashMap() { this.loadFactor = DEFAULT_LOAD_FACTOR; // all other fields defaulted } // put方法 public V put(K key, V value) { return putVal(hash(key), key, value, false, true); } // 计算hash值 static final int hash(Object key) { int h; return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16); } // 实际put值的方法 final V putVal(int hash, K key, V value, boolean onlyIfAbsent, boolean evict) { Node [] tab; Node p; int n, i; // 1、hash表 底层table数组为空则初始化 if ((tab = table) == null || (n = tab.length) == 0) n = (tab = resize()).length; // 2、如果计算的table数组下标的头结点为空, // 则将数据创建一个node,并设置为底层数组中table[i]链表的头结点 if ((p = tab[i = (n - 1) & hash]) == null) tab[i] = newNode(hash, key, value, null); else { Node e; K k; // 3、如果当前节点table[i]的hash值和需要新增的key的hash值相同,则替换 if (p.hash == hash && ((k = p.key) == key || (key != null && key.equals(k)))) e = p; // 4、如果 table[i]节点 是TreeNode,则执行putTreeval方法 else if (p instanceof TreeNode) e = ((TreeNode )p).putTreeval(this, tab, hash, key, value); else { // 5、无限for循环 遍历table[i]链表或树 for (int binCount = 0; ; ++binCount) { // 1)遍历到尾节点,创建Node节点并跳出循环 if ((e = p.next) == null) { p.next = newNode(hash, key, value, null); // 执行树化 if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st treeifyBin(tab, hash); break; } // 2)如果节点e的hash值和需要新增的key的hash值相同,跳出循环 if (e.hash == hash && ((k = e.key) == key || (key != null && key.equals(k)))) break; // 循环 p = e; } } // 6、如果 e 不为null,则表示key存在,则替换oldValue并返回 if (e != null) { // existing mapping for key V oldValue = e.value; if (!onlyIfAbsent || oldValue == null) e.value = value; afterNodeAccess(e); return oldValue; } } ++modCount; // 7、如果hash表中的有效元素个数 > threshold,就重新挑战底层数组table的数组 if (++size > threshold) resize(); afterNodeInsertion(evict); return null; } // 创建Node节点 Node newNode(int hash, K key, V value, Node next) { return new Node<>(hash, key, value, next); } // 树化方法 final void treeifyBin(Node [] tab, int hash) { int n, index; Node e; if (tab == null || (n = tab.length) < MIN_TREEIFY_CAPACITY) resize(); else if ((e = tab[index = (n - 1) & hash]) != null) { TreeNode hd = null, tl = null; do { TreeNode 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); } } // 树化后put方法 final TreeNode putTreeval(HashMap map, Node [] tab, int h, K k, V v) { Class> kc = null; boolean searched = false; TreeNode root = (parent != null) ? root() : this; for (TreeNode 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 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 xp = p; if ((p = (dir <= 0) ? p.left : p.right) == null) { Node xpn = xp.next; TreeNode 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 )xpn).prev = x; moveRootToFront(tab, balanceInsertion(root, x)); return null; } } } // 扩容底层table数组 final Node [] resize() { Node [] oldTab = table; int oldCap = (oldTab == null) ? 0 : oldTab.length; int oldThr = threshold; int newCap, newThr = 0; if (oldCap > 0) {// 如果 底层table数组长度 大于 0 if (oldCap >= MAXIMUM_CAPACITY) {// 如果 底层table数组长度 大于等于2的30次方 threshold = Integer.MAX_VALUE; return oldTab; } // 如果 底层table数组长度 在 2的4次方到2的29次方之间,则扩容为原来的2倍 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 { // 1、当底层数组table还是空时,给hashMap对象的元素容量和扩容阈值赋值 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; // 2、按照 新容量(oldCap << 1,即原来容量的2倍) 来创建 新的底层数组table Node [] newTab = (Node [])new Node[newCap]; table = newTab; if (oldTab != null) { for (int j = 0; j < oldCap; ++j) { Node 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 )e).split(this, newTab, j, oldCap); else { // preserve order Node loHead = null, loTail = null; Node hiHead = null, hiTail = null; Node 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; } ...... }
从关键代码上看,底层数据结构依旧是table数组(transient Node
put方法执行的表象:put一个键值对k-v到hashMap中,如果k不存在于map中则添加进去返回null,如果k存在于map中则用新v替换老v并返回老v。
具体代码逻辑如下:
// put方法 public V put(K key, V value) { return putVal(hash(key), key, value, false, true); }
先调用hash方法计算hash值:
// 计算hash值 static final int hash(Object key) { int h; return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16); }
然后将关键put的参数传入putVal方法:
// 实际put值的方法 final V putVal(int hash, K key, V value, boolean onlyIfAbsent, boolean evict) { Node[] tab; Node p; int n, i; // 1、hash表 底层table数组为空则初始化 if ((tab = table) == null || (n = tab.length) == 0) n = (tab = resize()).length; // 2、如果计算的table[i]链表为空, // 则将数据创建一个node,并设置为底层数组中table[i]链表的头结点 if ((p = tab[i = (n - 1) & hash]) == null) tab[i] = newNode(hash, key, value, null); else { Node e; K k; // 3、如果当前节点table[i]的hash值和需要新增的key的hash值相同,则替换 if (p.hash == hash && ((k = p.key) == key || (key != null && key.equals(k)))) e = p; // 4、如果 table[i]节点 是TreeNode,则执行putTreeval方法 else if (p instanceof TreeNode) e = ((TreeNode )p).putTreeval(this, tab, hash, key, value); else { // 5、无限for循环 遍历table[i]链表或树 for (int binCount = 0; ; ++binCount) { // 1)遍历到尾节点,创建Node节点并跳出循环 if ((e = p.next) == null) { p.next = newNode(hash, key, value, null); // 执行树化 if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st treeifyBin(tab, hash); break; } // 2)如果节点e的hash值和需要新增的key的hash值相同,跳出循环 if (e.hash == hash && ((k = e.key) == key || (key != null && key.equals(k)))) break; // 循环 p = e; } } // 6、如果 e 不为null,则表示key存在,则替换oldValue并返回 if (e != null) { // existing mapping for key V oldValue = e.value; if (!onlyIfAbsent || oldValue == null) e.value = value; afterNodeAccess(e); return oldValue; } } ++modCount; // 7、如果hash表中的有效元素个数 > threshold,就重新挑战底层数组table的数组 if (++size > threshold) resize(); afterNodeInsertion(evict); return null; }
putVal方法需要详细介绍一下执行逻辑:
1)底层table数组(hash表)为空则初始化(默认底层table数组长度为16,扩容阈值为12);
// 1、hash表 底层table数组为空则初始化 if ((tab = table) == null || (n = tab.length) == 0) n = (tab = resize()).length;
// 扩容底层table数组 final Node[] resize() { Node [] oldTab = table; // 底层table数组为空 容量和扩容阈值都为0 int oldCap = (oldTab == null) ? 0 : oldTab.length; int oldThr = threshold; int newCap, newThr = 0; if (oldCap > 0) {// 如果 底层table数组长度 大于 0 ...... 无关代码 } else if (oldThr > 0) // initial capacity was placed in threshold ......无关代码 else { // 1、当底层数组table还是空时,给hashMap对象的元素容量和扩容阈值赋值 newCap = DEFAULT_INITIAL_CAPACITY; newThr = (int)(DEFAULT_LOAD_FACTOR * DEFAULT_INITIAL_CAPACITY); } ...... 无关代码 threshold = newThr; // 2、按照 新容量(oldCap << 1,即原来容量的2倍) 来创建 新的底层数组table Node [] newTab = (Node [])new Node[newCap]; table = newTab; ...... 无关代码 return newTab; }
2)如果当前定位的table[i]链表为空, 则将数据创建一个node,并设置为底层数组中table[i]链表的头结点;
// 2、如果计算的table[i]链表为空, // 则将数据创建一个node,并设置为底层数组中table[i]链表的头结点 if ((p = tab[i = (n - 1) & hash]) == null) tab[i] = newNode(hash, key, value, null);
NodenewNode(int hash, K key, V value, Node next) { return new Node<>(hash, key, value, next); }
3)如果当前定位的table[i]链表不为空,则进行下面复杂逻辑;
else { Nodee; K k; // 3、如果当前table[i]链表的头结点的key和新增的key相等,则替换 if (p.hash == hash && ((k = p.key) == key || (key != null && key.equals(k)))) e = p; // 4、如果 table[i]节点 是TreeNode,则执行putTreeval方法 else if (p instanceof TreeNode) e = ((TreeNode )p).putTreeval(this, tab, hash, key, value); else { // 5、无限for循环 遍历table[i]链表或树 for (int binCount = 0; ; ++binCount) { // 1)遍历到尾节点,创建Node节点并跳出循环 if ((e = p.next) == null) { p.next = newNode(hash, key, value, null); // 执行树化 if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st treeifyBin(tab, hash); break; } // 2)如果节点e的hash值和需要新增的key的hash值相同,跳出循环 if (e.hash == hash && ((k = e.key) == key || (key != null && key.equals(k)))) break; // 循环 p = e; } } // 6、如果 e 不为null,则表示key存在,则替换oldValue并返回 if (e != null) { // existing mapping for key V oldValue = e.value; if (!onlyIfAbsent || oldValue == null) e.value = value; afterNodeAccess(e); return oldValue; } }
我们先来关注其中无限for循环部分
// 5、无限for循环 遍历table[i]链表或树 for (int binCount = 0; ; ++binCount) { // 1)遍历到尾节点,创建Node节点并跳出循环 if ((e = p.next) == null) { // 创建新node节点 p.next = newNode(hash, key, value, null); // 执行树化 if (binCount >= TREEIFY_THRESHOLD - 1) // bitCount >= 7 treeifyBin(tab, hash); break; } // 2)如果节点e的key和新增的key相等,跳出循环 if (e.hash == hash && ((k = e.key) == key || (key != null && key.equals(k)))) break; // 3)循环 p = e; }
注意:bitCount是一个标识计数,当bitCount自增8次(即链表的长度为8就开始进行链表的树化),执行treeifyBin(tab, hash)方法逻辑。
// 6、如果 e 不为null,则表示key存在,则替换oldValue并返回 if (e != null) { // existing mapping for key V oldValue = e.value; if (!onlyIfAbsent || oldValue == null) e.value = value; afterNodeAccess(e); return oldValue; }
上面的代码显示,如果key已经存在于HashMap中,则用value替换oldValue,并返回oldValue。
4)修改计数+1,有效个数+,判断底层table数组是否需要扩容,如果需要则执行resize方法扩容。
++modCount; if (++size > threshold) resize(); afterNodeInsertion(evict); return null;
final Node[] resize() { Node [] oldTab = table; int oldCap = (oldTab == null) ? 0 : oldTab.length; int oldThr = threshold; int newCap, newThr = 0; if (oldCap > 0) { ...... 无关代码 // 1、如果当前底层table数组的长度在2的4次方与2的29次方之间,则扩容2倍 else if ((newCap = oldCap << 1) < MAXIMUM_CAPACITY && oldCap >= DEFAULT_INITIAL_CAPACITY) newThr = oldThr << 1; // double threshold } else if (oldThr > 0) ...... 无关代码 else { ...... 无关代码 } if (newThr == 0) { ...... 无关代码 } threshold = newThr; Node [] newTab = (Node [])new Node[newCap]; table = newTab; // 2、如果底层table数组不为null,则遍历底层table数组和其下的链表,进行扩容相关 *** 作 if (oldTab != null) { // 遍历底层table数组 for (int j = 0; j < oldCap; ++j) { Node e; // 如果table[j]链表存在,则遍历链表 if ((e = oldTab[j]) != null) { oldTab[j] = null; // 如果只有1个元素,则直接重新计算在新table数组的位置并保存 if (e.next == null) newTab[e.hash & (newCap - 1)] = e; // 如果已经是树节点 else if (e instanceof TreeNode) ((TreeNode )e).split(this, newTab, j, oldCap); else { // preserve order Node loHead = null, loTail = null; Node hiHead = null, hiTail = null; Node next; // 开始遍历链表 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; }
5)具体需要介绍一下treeifyBin方法:
final void treeifyBin(Node[] tab, int hash) { int n, index; Node e; // 1、如果 底层table数组为null或者长度小于64,则不进行树化,直接进行扩容 *** 作 if (tab == null || (n = tab.length) < MIN_TREEIFY_CAPACITY) resize(); // 2、获取table[index]链表头结点,开始遍历替换节点类型为TreeNode, else if ((e = tab[index = (n - 1) & hash]) != null) { TreeNode hd = null, tl = null; do { TreeNode p = replacementTreeNode(e, null); if (tl == null) hd = p; else { p.prev = tl; tl.next = p; } tl = p; } while ((e = e.next) != null); // 3、将链表进行树化 if ((tab[index] = hd) != null) hd.treeify(tab); } } // 树化 final void treeify(Node [] tab) { TreeNode root = null; // 遍历链表,其中this是链表的头结点 for (TreeNode x = this, next; x != null; x = next) { next = (TreeNode )x.next; x.left = x.right = null; // 红黑树的根为空,则设置为根节点 if (root == null) { x.parent = null; x.red = false; root = x; } else { K k = x.key; int h = x.hash; Class> kc = null; // 遍历 红黑树 for (TreeNode p = root;;) { int dir, ph; K pk = p.key; if ((ph = p.hash) > h) dir = -1; else if (ph < h) dir = 1; else if ((kc == null && (kc = comparableClassFor(k)) == null) || (dir = compareComparables(kc, k, pk)) == 0) dir = tieBreakOrder(k, pk); TreeNode xp = p; if ((p = (dir <= 0) ? p.left : p.right) == null) { x.parent = xp; if (dir <= 0) xp.left = x; else xp.right = x; root = balanceInsertion(root, x); break; } } } } moveRootToFront(tab, root); }
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