本文很長,詳細描述了HashMap源碼級別的實現原理,並討論了包括擴容,hash計算,新建HashMap的開銷等問題,同時還提供了一些外部資料。因爲內容太多,建議閱讀時結合目錄快速跳轉查看。java
Java源碼閱讀最好採用IDEA,Ctrl + N 輸入HashMap便可看到HashMap的源碼了,HashMap總共有2444行源碼 本文查看的是JDK-11.0.1的源碼node
[toc]git
我們按照源碼順序來分析HashMap,除了HashMap自己的變量和方法,HashMap中還定義了定義以下內部類:github
HashMap底層使用哈希表(數組 + 單鏈表),當鏈表過長會將鏈表轉成 紅黑樹以實現 O(logn) 時間複雜度內查找。算法
HashMap的定義爲class HashMap<K,V> extends AbstractMap<K,V> implements Map<K,V>, Cloneable, Serializable
。數組
HashMap採用的擴容策略是,每次加倍,這樣,原來位置的Entry在新擴展的數組中要麼依然在原來的位置,要麼在<原來位置+原來的容量>
的位置。緩存
hash()
函數計算hash值方法爲(key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16)
,計算出的hash值會被緩存在Node.hash
中。bash
hash值計算至關於就是將高16位與低16位進行異或,結果是高16不變,低16位變成其異或的新結果。服務器
爲何讓低16位與高16爲異或合成一個新的結果呢?是由於HashMap的容量一般比較小,在進行長度取模運算時採用的是隻取二進制最右端幾位,這樣高位的二進制信息就沒有用到,所帶來的結果就是Hash結果分佈不太均勻。而高16位與低16位異或後就可讓低位附帶高位的信息,加大低位的隨機性。具體請參考JDK 源碼中 HashMap 的 hash 方法原理是什麼? - 胖君的回答 - 知乎 微信
不明白異或結果的朋友來看下這段驗證代碼,複製此代碼運行便可明白高16位與低16位的異或的結果:
import java.util.Random;
class Scratch {
public static void main(String[] args) {
generateTestCase(41132564);
Random random = new Random();
for (int j = 0; j < 10; j++) {
generateTestCase(random.nextInt(Integer.MAX_VALUE));
}
}
/** * 顯示根據key的hashCode算出最終元素的hash值 * * @param hashCode 表明key的hashCode */
public static void generateTestCase(int hashCode) {
System.out.println("hashCode = " + hashCode + " 時");
show(hashCode);
int k = hashCode >>> 16;
show(k);
int x = hashCode ^ k;
show(x);
System.out.println();
}
/** * 顯示一個數字的二進制,按照高16位在左,低16位在右的方式顯示 */
public static void show(int n) {
String s = Integer.toBinaryString(n);
s = fillZero(s);
System.out.print(s.substring(0, 16));
System.out.print(" | ");
System.out.println(s.substring(16));
}
/** * 填充0到字符串前面使得總長32 */
public static String fillZero(String src) {
StringBuilder sb = new StringBuilder(32);
for (int i = 0; i < 32 - src.length(); i++) {
sb.append('0');
}
return sb.append(src).toString();
}
}
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這就是爲何HashMap能夠放入鍵值null,由於計算hash中爲null的hash值爲0,而後putVal插入
根據hash()獲取元素所在鏈表的位置的方法爲:tab[(n - 1) & hash]
,因爲n爲容量是2的冪,n-1的二進制形式是111111
這類二進制左邊全1的形式,因此這個方法本質是截取hash二進制相應長度的0和1,以下例。
hash: 10111101
n - 1: 00111111
result: 00111101
// hash的最左端的1沒有了,至關於只取二進制最右端幾位
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在hash計算中(上文),null的hash值爲0,而後按照正常的putVal()
插入
從源碼中(下文構造函數)咱們能夠看到:
new HashMap()開銷很是少,僅僅確認裝載因子。真正的建立table的操做盡量的日後延遲,這使得HashMap有很多操做都須要檢查table是否初始化。這種設計我猜測應該是爲了讓人們能夠不用擔憂建立HashMap的開銷,大量建立HashMap,好比ArrayList<HashMap> a = new ArrayList<>(1000)
HashMap的默認容量是16,被DEFAULT_INITIAL_CAPACITY定義。
static final int DEFAULT_INITIAL_CAPACITY = 1 << 4; // aka 16
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其最大容量爲 1073741824(2的30次方)
static final int MAXIMUM_CAPACITY = 1 << 30;
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默認裝載因子0.75
static final float DEFAULT_LOAD_FACTOR = 0.75f;
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將鏈表轉換成紅黑樹的閾值爲8,即當鏈表長度>=8時,鏈表轉換成紅黑樹
static final int TREEIFY_THRESHOLD = 8;
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將紅黑樹轉換成鏈表的閾值爲6(<6時轉換),注意,這個是在resize()的過程當中調用TreeNode.split()實現
static final int UNTREEIFY_THRESHOLD = 6;
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要樹化並不只僅是超過TREEIFY_THRESHOLD ,同時容量要超過MIN_TREEIFY_CAPACITY,若是隻是超過TREEIFY_THRESHOLD,則會進行擴容(調用resize(),由於擴容可讓鏈表變短),直到擴容>=MIN_TREEIFY_CAPACITY
static final int MIN_TREEIFY_CAPACITY = 64;
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哈希表的數組主體定義,使用時初始化,在構造函數中並不會初始化,因此在各類操做中老是要檢查其是否爲null
transient Node<K,V>[] table;
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做爲一個entrySet緩存,使用entrySet方法首先檢查其是否爲null,不爲null則使用這個緩存,不然生成一個並緩存至此。
transient Set<Map.Entry<K,V>> entrySet;
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HashMap中Entry的數量
transient int size;
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記錄修改內部結構化修改次數,用於實現fail-fast,ConcurrentModificationException就是經過檢測這個拋出
transient int modCount;
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其值=capacity * load factor,當size超過threshhold便進行一次擴容
int threshold;
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裝載因子
final float loadFactor;
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用於序列化
private static final long serialVersionUID = 362498820763181265L;
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該構造函數並不初始化transient Node<K,V>[] table;
,進行容量和裝載因子的(範圍)合法性驗證,然而並無對容量進行存儲,只是用來肯定擴容閾值threshold
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);
}
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顯然
public HashMap(int initialCapacity) {
this(initialCapacity, DEFAULT_LOAD_FACTOR);
}
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無參構造函數僅僅確認裝載因子
public HashMap() {
this.loadFactor = DEFAULT_LOAD_FACTOR; // all other fields defaulted
}
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經過Map構造HashMap時,使用默認裝載因子,並調用putMapEntries將Map裝入HashMap
public HashMap(Map<? extends K, ? extends V> m) {
this.loadFactor = DEFAULT_LOAD_FACTOR;
putMapEntries(m, false);
}
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Hash函數負責產生HashCode,計算法則爲若key爲null則返回0,不然:對key的hashCode的高16位和低16位進行異或
static final int hash(Object key) {
int h;
return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16);// >>>表示無符號右移
}
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對於一個Object,若其定義時是class X implement Comparable<X>
,則返回X,不然返回null,注意必定Comparable<X>
中的X必定得是X不能爲其子類或父類,用於紅黑樹中的比較
static Class<?> comparableClassFor(Object x) {
if (x instanceof Comparable) {
Class<?> c; Type[] ts, as; ParameterizedType p;
if ((c = x.getClass()) == String.class) // bypass checks
return c;
if ((ts = c.getGenericInterfaces()) != null) {
for (Type t : ts) {
if ((t instanceof ParameterizedType) &&
((p = (ParameterizedType) t).getRawType() ==
Comparable.class) &&
(as = p.getActualTypeArguments()) != null &&
as.length == 1 && as[0] == c) // type arg is c
return c;
}
}
}
return null;
}
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import java.lang.reflect.ParameterizedType;
import java.lang.reflect.Type;
class Scratch {
public static void main(String[] args) {
System.out.println(comparableClassFor(new C()));// class Scratch$C
System.out.println(comparableClassFor(new CS()));// null
System.out.println(comparableClassFor(new CSI()));// null
System.out.println(comparableClassFor(new CSIC()));// class Scratch$CSIC
}
static Class<?> comparableClassFor(Object x) {
if (x instanceof Comparable) {
Class<?> c; Type[] ts, as; ParameterizedType p;
if ((c = x.getClass()) == String.class) // bypass checks
return c;
if ((ts = c.getGenericInterfaces()) != null) {
for (Type t : ts) {
if ((t instanceof ParameterizedType) &&
((p = (ParameterizedType) t).getRawType() ==
Comparable.class) &&
(as = p.getActualTypeArguments()) != null &&
as.length == 1 && as[0] == c) // type arg is c
return c;
}
}
}
return null;
}
static class C implements Comparable<C> {
@Override
public int compareTo(C o) {
return 0;
}
}
static class CS extends C {}
static class CSI implements Comparable<C> {
@Override
public int compareTo(C o) {
return 0;
}
}
static class CSIC implements Comparable<CSIC> {
@Override
public int compareTo(CSIC o) {
return 0;
}
}
}
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若是x=null,返回0;若是x的類型爲kc,則返回k.compare(x);不然返回0
static int compareComparables(Class<?> kc, Object k, Object x) {
return (x == null || x.getClass() != kc ? 0 :
((Comparable)k).compareTo(x));
}
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對於給定cap,計算>=cap的2的冪。用於計算table數組大小
static final int tableSizeFor(int cap) {
int n = -1 >>> Integer.numberOfLeadingZeros(cap - 1);
return (n < 0) ? 1 : (n >= MAXIMUM_CAPACITY) ? MAXIMUM_CAPACITY : n + 1;
}
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先肯定放入map時容量是否應該調整,調整好後,經過putVal一個個放入
final void putMapEntries(Map<? extends K, ? extends V> m, boolean evict) {
int s = m.size();
if (s > 0) {//放入的map的size要大於0才插入
if (table == null) { // pre-size,若是本map的table未初始化(同時沒有任何元素),就根據放入map大小以及loadfactor計算出threshold,依然不初始化table
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)//放入的map超過threshold就擴容
resize();
//到這裏容量問題解決了,就一個一個putVal插入
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);
}
}
}
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直接返回size變量的值
public int size() {
return size;
}
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判斷size是否等於0
public boolean isEmpty() {
return size == 0;
}
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經過計算hash並調用getNode找到節點Node,而後返回Node.value,找不到Node則返回null
public V get(Object key) {
Node<K,V> e;
return (e = getNode(hash(key), key)) == null ? null : e.value;
}
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若是table未初始化以及長度=0或者根據hash找到鏈表的第一個元素爲nul便返回null,不然判斷第一個節點是否爲要找的節點,不然之後的節點根據紅黑樹類型或鏈表類型採用各自的查找策略
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) {//在table初始化了,且table長度大於0而且根據hash找到鏈表第一個節點不爲null時
if (first.hash == hash && // always check first node,若是鏈表第一個節點就是要找的便返回
((k = first.key) == key || (key != null && key.equals(k))))
return first;
if ((e = first.next) != null) {
//根據節點是紅黑樹仍是鏈表類型採用不一樣的查找策略
if (first instanceof TreeNode)
return ((TreeNode<K,V>)first).getTreeNode(hash, key);
do {//鏈表類型就是順序遍歷查找
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k))))
return e;
} while ((e = e.next) != null);
}
}
return null;
}
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根據getNode是否找到節點來判斷是否存在
public boolean containsKey(Object key) {
return getNode(hash(key), key) != null;
}
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調用putVal放入節點
public V put(K key, V value) {
return putVal(hash(key), key, value, false, true);
}
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參數解釋:
先進行table初始化和0長檢查判斷是否須要擴容,以後若是key所在鏈表表頭未初始化便初始化並插入,不然根據是否樹化根據相應策略查找節點,若是onlyIfAbsent爲false則插入。插入後size++並根據threshold判斷是否擴容resize()
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未初始化或0長便調用resize()初始化
n = (tab = resize()).length;
if ((p = tab[i = (n - 1) & hash]) == null)//若是相應位置的鏈表還未建立表頭,便建立表頭
tab[i] = newNode(hash, key, value, null);
else {
Node<K,V> e; K k;
if (p.hash == hash &&
((k = p.key) == key || (key != null && key.equals(k))))
e = p;
else if (p instanceof TreeNode)
e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
else {//在鏈表中順序查找節點
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);//添加節點的過程當中若是超過樹化閾值,便執行樹化操做
break;
}
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k))))
break;
p = e;
}
}
if (e != null) { // existing mapping for key,e即是插入的key的位置
V oldValue = e.value;
if (!onlyIfAbsent || oldValue == null)
e.value = value;
afterNodeAccess(e);
return oldValue;
}
}
++modCount;
if (++size > threshold)//若是插入後超過擴容閾值便擴容
resize();
afterNodeInsertion(evict);
return null;
}
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閱讀這部分源碼應注意:
100000
這類形式,Cap-1的二進制都爲111111
這類形式。原理:
oldCap(二進制是10000的形式)& e.hash
(判斷相應位爲0仍是1)來劃分紅兩類,一類放在原位置,一類放在原位置+oldCap
位置。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) {
threshold = Integer.MAX_VALUE;
return oldTab;
}
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
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);
}
//以上代碼都是根據限制條件肯定newThr和newCap
threshold = newThr;
@SuppressWarnings({"rawtypes","unchecked"})
//建立新table
Node<K,V>[] newTab = (Node<K,V>[])new Node[newCap];
table = newTab;
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;//鏈表只有一個元素則直接放入新數組
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) {//根據oldCap肯定元素hash指定位上是0仍是1來劃分放在原位置仍是原位置+oldCap位置,這裏是放在原位置
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;//放在原位置
}
if (hiTail != null) {
hiTail.next = null;
newTab[j + oldCap] = hiHead;//原位置+oldCap
}
}
}
}
}
return newTab;
}
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達到樹化閾值還須要超過MIN_TREEIFY_CAPACITY纔會樹化,不然先進行擴容操做,達到後,先將鏈表Node逐個替換成TreeNode,在調用TreeNode.treeify創建紅黑樹
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)//達到樹化閾值還須要超過MIN_TREEIFY_CAPACITY纔會樹化,不然先進行擴容操做
resize();
else if ((e = tab[index = (n - 1) & hash]) != null) {
TreeNode<K,V> hd = null, tl = null;
do {//先將鏈表Node逐個替換成TreeNode
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);//這裏進行樹化
}
}
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putAll就是調用putMapEntries
public void putAll(Map<? extends K, ? extends V> m) {
putMapEntries(m, true);
}
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remove調用removeNode移除節點後,返回節點value
public V remove(Object key) {
Node<K,V> e;
return (e = removeNode(hash(key), key, null, false, true)) == null ?
null : e.value;
}
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根據hash查找key的位置並刪除,若是matchValue爲true,則只有值也相等時才刪除,若是movable爲false,紅黑樹的刪除不移動node,而後size減少,若是沒找到key,返回null
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;//查找key的位置
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)
node = ((TreeNode<K,V>)p).getTreeNode(hash, key);
else {
do {
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)))) {//matchValue控制值也要相等才刪除
if (node instanceof TreeNode) //刪除key並減少size
((TreeNode<K,V>)node).removeTreeNode(this, tab, movable);
else if (node == p)
tab[index] = node.next;
else
p.next = node.next;
++modCount;
--size;
afterNodeRemoval(node);
return node;
}
}
return null;
}
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size置0,table每一個Node都置爲null
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;
}
}
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雙重循環查找數組+鏈表中的每一個value
public boolean containsValue(Object value) {
Node<K,V>[] tab; V v;
if ((tab = table) != null && size > 0) {
for (Node<K,V> e : tab) {
for (; e != null; e = e.next) {
if ((v = e.value) == value ||
(value != null && value.equals(v)))
return true;
}
}
}
return false;
}
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查看keySet中是否有已緩存的keySet,沒有就建立並加入緩存。值得注意的是因爲keySet採用視圖技術(沒有成員變量),因此建立開銷近乎爲0。
public Set<K> keySet() {
Set<K> ks = keySet;
if (ks == null) {
ks = new KeySet();
keySet = ks;
}
return ks;
}
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查看是否有已緩存的,沒有則建立Value()並緩存,因爲沒有成員變量,因此建立Values開銷近乎爲0
public Collection<V> values() {
Collection<V> vs = values;
if (vs == null) {
vs = new Values();
values = vs;
}
return vs;
}
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查看是否有已緩存的,沒有則建立EntrySet()並緩存,因爲沒有成員變量,因此建立開銷近乎爲0
public Set<Map.Entry<K,V>> entrySet() {
Set<Map.Entry<K,V>> es;
return (es = entrySet) == null ? (entrySet = new EntrySet()) : es;
}
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用getNode查找,找不到則返回defaultValue
@Override
public V getOrDefault(Object key, V defaultValue) {
Node<K,V> e;
return (e = getNode(hash(key), key)) == null ? defaultValue : e.value;
}
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調用putVal,並設定putVal的參數onlyIfAbsent=true。只有不存在key的時候才插入
@Override
public V putIfAbsent(K key, V value) {
return putVal(hash(key), key, value, true, true);
}
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調用removeNode,返回是否刪除成功
@Override
public boolean remove(Object key, Object value) {
return removeNode(hash(key), key, value, true, true) != null;
}
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經過getNode尋找到Node,判斷oldValue是否與value相等,而後替換value,並有afterNodeAccess鉤子用於LinkedHashMap
@Override
public boolean replace(K key, V oldValue, V newValue) {
Node<K,V> e; V v;
if ((e = getNode(hash(key), key)) != null &&
((v = e.value) == oldValue || (v != null && v.equals(oldValue)))) {
e.value = newValue;
afterNodeAccess(e);
return true;
}
return false;
}
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經過getNode尋找到Node,而後替換value,並有afterNodeAccess鉤子用於LinkedHashMap
@Override
public V replace(K key, V value) {
Node<K,V> e;
if ((e = getNode(hash(key), key)) != null) {
V oldValue = e.value;
e.value = value;
afterNodeAccess(e);
return oldValue;
}
return null;
}
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若是查找不到key不就運行函數,並將函數返回值插入到key中。function不能更改modCount(不能修改HashMap),不然會ConcurrentModificationException
@Override
public V computeIfAbsent(K key, Function<? super K, ? extends V> mappingFunction) {
if (mappingFunction == null)
throw new NullPointerException();
int hash = hash(key);
Node<K,V>[] tab; Node<K,V> first; int n, i;
int binCount = 0;
TreeNode<K,V> t = null;
Node<K,V> old = null;
if (size > threshold || (tab = table) == null ||
(n = tab.length) == 0)
n = (tab = resize()).length;
if ((first = tab[i = (n - 1) & hash]) != null) {
if (first instanceof TreeNode)
old = (t = (TreeNode<K,V>)first).getTreeNode(hash, key);
else {
Node<K,V> e = first; K k;
do {
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k)))) {
old = e;
break;
}
++binCount;
} while ((e = e.next) != null);
}
V oldValue;
if (old != null && (oldValue = old.value) != null) {//找到後便返回並處理鉤子
afterNodeAccess(old);
return oldValue;
}
}//沒找到時
int mc = modCount;
V v = mappingFunction.apply(key);
if (mc != modCount) { throw new ConcurrentModificationException(); }
//將mappingFunction產生的返回值做爲value插入到key中,若是超過樹化閾值就樹化,size++
if (v == null) {
return null;
} else if (old != null) {
old.value = v;
afterNodeAccess(old);
return v;
}
else if (t != null)
t.putTreeVal(this, tab, hash, key, v);
else {
tab[i] = newNode(hash, key, v, first);
if (binCount >= TREEIFY_THRESHOLD - 1)
treeifyBin(tab, hash);
}
modCount = mc + 1;
++size;
afterNodeInsertion(true);
return v;
}
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若是查找到key就運行remappingFunction,並將返回值做爲value插入。function不能更改modCount(不能修改HashMap),不然會ConcurrentModificationException。若是返回值爲null,就經過removeNode刪除key
@Override
public V computeIfPresent(K key, BiFunction<? super K, ? super V, ? extends V> remappingFunction) {
if (remappingFunction == null)
throw new NullPointerException();
Node<K,V> e; V oldValue;
int hash = hash(key);
if ((e = getNode(hash, key)) != null &&
(oldValue = e.value) != null) {//
int mc = modCount;
V v = remappingFunction.apply(key, oldValue);
if (mc != modCount) { throw new ConcurrentModificationException(); }
if (v != null) {
e.value = v;
afterNodeAccess(e);
return v;
}
else
removeNode(hash, key, null, false, true);
}
return null;
}
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查找key對應的value,若是key不在map中,則value爲null,並以這兩個參數調用remappingFunction,函數返回值爲v。若是以前key不在map中而v不爲null,就插入key和v。若是key在map中:若是v爲null,就刪除key;若是v不爲null,則修改value爲v。其間還有併發檢查和訪問插入鉤子函數用於實現LRUCache
@Override
public V compute(K key, BiFunction<? super K, ? super V, ? extends V> remappingFunction) {
if (remappingFunction == null)
throw new NullPointerException();
int hash = hash(key);
Node<K,V>[] tab; Node<K,V> first; int n, i;
int binCount = 0;
TreeNode<K,V> t = null;
Node<K,V> old = null;
if (size > threshold || (tab = table) == null ||
(n = tab.length) == 0)//常規table檢查
n = (tab = resize()).length;
if ((first = tab[i = (n - 1) & hash]) != null) {//判斷hash相應鏈表是否存在,而後尋找節點
if (first instanceof TreeNode)
old = (t = (TreeNode<K,V>)first).getTreeNode(hash, key);
else {
Node<K,V> e = first; K k;
do {
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k)))) {
old = e;
break;
}
++binCount;
} while ((e = e.next) != null);
}
}
V oldValue = (old == null) ? null : old.value;
int mc = modCount;
V v = remappingFunction.apply(key, oldValue);//調用函數
if (mc != modCount) { throw new ConcurrentModificationException(); }
if (old != null) {
if (v != null) {
old.value = v;
afterNodeAccess(old);
}
else
removeNode(hash, key, null, false, true);
}
else if (v != null) {
if (t != null)
t.putTreeVal(this, tab, hash, key, v);
else {
tab[i] = newNode(hash, key, v, first);
if (binCount >= TREEIFY_THRESHOLD - 1)
treeifyBin(tab, hash);
}
modCount = mc + 1;
++size;
afterNodeInsertion(true);
}
return v;
}
複製代碼
查找key,若是key存在:map中key對應的value若是不爲null,就調用remappingFunction,返回值爲v,若是返回值爲null且調用merge的value爲null,則從map中刪除key;不然用remappingFunction的返回值插入value;若是調用merge的value不爲null,插入value。
@Override
public V merge(K key, V value, BiFunction<? super V, ? super V, ? extends V> remappingFunction) {
if (value == null)
throw new NullPointerException();
if (remappingFunction == null)
throw new NullPointerException();
int hash = hash(key);
Node<K,V>[] tab; Node<K,V> first; int n, i;
int binCount = 0;
TreeNode<K,V> t = null;
Node<K,V> old = null;
if (size > threshold || (tab = table) == null ||
(n = tab.length) == 0)//常規table檢查
n = (tab = resize()).length;
if ((first = tab[i = (n - 1) & hash]) != null) {//檢查hash後table中是否存在相應鏈表,而後尋找key
if (first instanceof TreeNode)
old = (t = (TreeNode<K,V>)first).getTreeNode(hash, key);
else {
Node<K,V> e = first; K k;
do {
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k)))) {
old = e;
break;
}
++binCount;
} while ((e = e.next) != null);
}
}
if (old != null) {
V v;
if (old.value != null) {
int mc = modCount;
v = remappingFunction.apply(old.value, value);
if (mc != modCount) {
throw new ConcurrentModificationException();
}
} else {
v = value;
}
if (v != null) {
old.value = v;
afterNodeAccess(old);
}
else
removeNode(hash, key, null, false, true);
return v;
}
if (value != null) {
if (t != null)
t.putTreeVal(this, tab, hash, key, value);
else {
tab[i] = newNode(hash, key, value, first);
if (binCount >= TREEIFY_THRESHOLD - 1)
treeifyBin(tab, hash);
}
++modCount;
++size;
afterNodeInsertion(true);
}
return value;
}
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進行基本合法性檢查,而後調用foreach循環調用actioin
@Override
public void forEach(BiConsumer<? super K, ? super V> action) {
Node<K,V>[] tab;
if (action == null)
throw new NullPointerException();
if (size > 0 && (tab = table) != null) {
int mc = modCount;
for (Node<K,V> e : tab) {
for (; e != null; e = e.next)
action.accept(e.key, e.value);
}
if (modCount != mc)
throw new ConcurrentModificationException();
}
}
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進行基本合法性檢查,而後foreach循環調用action並將返回值賦給value
@Override
public void replaceAll(BiFunction<? super K, ? super V, ? extends V> function) {
Node<K,V>[] tab;
if (function == null)
throw new NullPointerException();
if (size > 0 && (tab = table) != null) {
int mc = modCount;
for (Node<K,V> e : tab) {
for (; e != null; e = e.next) {
e.value = function.apply(e.key, e.value);
}
}
if (modCount != mc)
throw new ConcurrentModificationException();
}
}
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從新初始化,而後把當前HashMap插入到克隆的HashMap中
@Override
public Object clone() {
HashMap<K,V> result;
try {
result = (HashMap<K,V>)super.clone();
} catch (CloneNotSupportedException e) {
// this shouldn't happen, since we are Cloneable
throw new InternalError(e);
}
result.reinitialize();
result.putMapEntries(this, false);
return result;
}
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直接返回loadFactor
final float loadFactor() { return loadFactor; }
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若是table不爲null,返回table的長度,不然若是threshold大於0,返回threshol,不然返回16(即DEFAULT_INITIAL_CAPACITY)
final int capacity() {
return (table != null) ? table.length :
(threshold > 0) ? threshold :
DEFAULT_INITIAL_CAPACITY;
}
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經過ObjectOutputStream先寫入非static和非transient的變量(即threshold和loadFactor),而後寫入capacity,size,最後調用internalWriteEntries()寫入table中的鍵值對
private void writeObject(java.io.ObjectOutputStream s) throws IOException {
int buckets = capacity();
// Write out the threshold, loadfactor, and any hidden stuff
s.defaultWriteObject();
s.writeInt(buckets);
s.writeInt(size);
internalWriteEntries(s);
}
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按照writeObject相反的順序讀出變量,可是capacity會被丟棄從新計算出來。最後鍵值對讀出來再putVal進去
private void readObject(java.io.ObjectInputStream s) throws IOException, ClassNotFoundException {
// Read in the threshold (ignored), loadfactor, and any hidden stuff
s.defaultReadObject();
reinitialize();
if (loadFactor <= 0 || Float.isNaN(loadFactor))
throw new InvalidObjectException("Illegal load factor: " +
loadFactor);
s.readInt(); // Read and ignore number of buckets
int mappings = s.readInt(); // Read number of mappings (size)
if (mappings < 0)
throw new InvalidObjectException("Illegal mappings count: " +
mappings);
else if (mappings > 0) { // (if zero, use defaults)
// Size the table using given load factor only if within
// range of 0.25...4.0
float lf = Math.min(Math.max(0.25f, loadFactor), 4.0f);
float fc = (float)mappings / lf + 1.0f;
int cap = ((fc < DEFAULT_INITIAL_CAPACITY) ?
DEFAULT_INITIAL_CAPACITY :
(fc >= MAXIMUM_CAPACITY) ?
MAXIMUM_CAPACITY :
tableSizeFor((int)fc));
float ft = (float)cap * lf;
threshold = ((cap < MAXIMUM_CAPACITY && ft < MAXIMUM_CAPACITY) ?
(int)ft : Integer.MAX_VALUE);
// Check Map.Entry[].class since it's the nearest public type to
// what we're actually creating.
SharedSecrets.getJavaObjectInputStreamAccess().checkArray(s, Map.Entry[].class, cap);
@SuppressWarnings({"rawtypes","unchecked"})
Node<K,V>[] tab = (Node<K,V>[])new Node[cap];
table = tab;
// Read the keys and values, and put the mappings in the HashMap
for (int i = 0; i < mappings; i++) {
@SuppressWarnings("unchecked")
K key = (K) s.readObject();
@SuppressWarnings("unchecked")
V value = (V) s.readObject();
putVal(hash(key), key, value, false, false);
}
}
}
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3.40 newNode(int hash, K key, V value, Node<K,V> next) 顯然
Node<K,V> newNode(int hash, K key, V value, Node<K,V> next) {
return new Node<>(hash, key, value, next);
}
複製代碼
顯然
Node<K,V> replacementNode(Node<K,V> p, Node<K,V> next) {
return new Node<>(p.hash, p.key, p.value, next);
}
複製代碼
顯然
TreeNode<K,V> newTreeNode(int hash, K key, V value, Node<K,V> next) {
return new TreeNode<>(hash, key, value, next);
}
複製代碼
顯然
TreeNode<K,V> replacementTreeNode(Node<K,V> p, Node<K,V> next) {
return new TreeNode<>(p.hash, p.key, p.value, next);
}
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將除了threshold和loadFactor以外的變量所有初始化
void reinitialize() {
table = null;
entrySet = null;
keySet = null;
values = null;
modCount = 0;
threshold = 0;
size = 0;
}
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給子類(LinkedHashMap)的鉤子
void afterNodeAccess(Node<K,V> p) { }
複製代碼
給子類(LinkedHashMap)的鉤子
void afterNodeInsertion(boolean evict) { }
複製代碼
給子類(LinkedHashMap)的鉤子
void afterNodeRemoval(Node<K,V> p) { }
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雙重循環遍歷全部key同時寫入key value至序列化流中。
void internalWriteEntries(java.io.ObjectOutputStream s) throws IOException {
Node<K,V>[] tab;
if (size > 0 && (tab = table) != null) {
for (Node<K,V> e : tab) {
for (; e != null; e = e.next) {
s.writeObject(e.key);
s.writeObject(e.value);
}
}
}
}
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這裏就介紹下Node,KeySet,ValueSet和TreeNode,其它的暫且略去,也比較易懂
static class Node<K,V> implements Map.Entry<K,V> {
final int hash;
final K key;
V value;
Node<K,V> next;
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;
}
}
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Node的成員變量包括:
final int hash;
final K key;
V value;
Node<K,V> next;
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成員函數基本很明朗,就不怎麼解釋了
final class KeySet extends AbstractSet<K> {
public final int size() { return size; }
public final void clear() { HashMap.this.clear(); }
public final Iterator<K> iterator() { return new KeyIterator(); }
public final boolean contains(Object o) { return containsKey(o); }
public final boolean remove(Object key) {
return removeNode(hash(key), key, null, false, true) != null;
}
public final Spliterator<K> spliterator() {
return new KeySpliterator<>(HashMap.this, 0, -1, 0, 0);
}
public final void forEach(Consumer<? super K> action) {
Node<K,V>[] tab;
if (action == null)
throw new NullPointerException();
if (size > 0 && (tab = table) != null) {
int mc = modCount;
for (Node<K,V> e : tab) {
for (; e != null; e = e.next)
action.accept(e.key);
}
if (modCount != mc)
throw new ConcurrentModificationException();
}
}
}
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能夠看到,KeySet是經過將大部分方法委託給其它類(主要是HashMap)來實現的,foreach例外。建立KeySet沒有任何開銷(就跟new Object())同樣。
final class EntrySet extends AbstractSet<Map.Entry<K,V>> {
public final int size() { return size; }
public final void clear() { HashMap.this.clear(); }
public final Iterator<Map.Entry<K,V>> iterator() {
return new EntryIterator();
}
public final boolean contains(Object o) {
if (!(o instanceof Map.Entry))
return false;
Map.Entry<?,?> e = (Map.Entry<?,?>) o;
Object key = e.getKey();
Node<K,V> candidate = getNode(hash(key), key);
return candidate != null && candidate.equals(e);
}
public final boolean remove(Object o) {
if (o instanceof Map.Entry) {
Map.Entry<?,?> e = (Map.Entry<?,?>) o;
Object key = e.getKey();
Object value = e.getValue();
return removeNode(hash(key), key, value, true, true) != null;
}
return false;
}
public final Spliterator<Map.Entry<K,V>> spliterator() {
return new EntrySpliterator<>(HashMap.this, 0, -1, 0, 0);
}
public final void forEach(Consumer<? super Map.Entry<K,V>> action) {
Node<K,V>[] tab;
if (action == null)
throw new NullPointerException();
if (size > 0 && (tab = table) != null) {
int mc = modCount;
for (Node<K,V> e : tab) {
for (; e != null; e = e.next)
action.accept(e);
}
if (modCount != mc)
throw new ConcurrentModificationException();
}
}
}
複製代碼
能夠看到,EntrySet是經過將大部分方法委託給其它類(主要是HashMap)來實現的,foreach例外。建立EntrySet沒有任何開銷(就跟new Object())同樣。
因爲源碼太長,就不貼上來了。TreeNode主要實現了紅黑樹的全部操做,對於紅黑樹的原理,建議查找相關資料。
咱們先看下TreeNode的成員變量有哪些:
//繼承自Node
final int hash;
final K key;
V value;
Node<K,V> next;
//繼承自LinkedHashMap.Entry
Entry<K,V> before, after;
//自帶
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
複製代碼
可見,採用TreeNode在使用通常64位JVM(引用大小爲8位),則TreeNode的大小是Node的2.7倍。不過如今服務器內存愈來愈大,用內存換時間(從O(n)->O(logN))仍是划得來的。
關於利用HashMap中留下的鉤子函數,實際上是給LinkedHashMap用於實現LRUCache的,如何實現請看這篇文章:如何設計實現一個LRU Cache?
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