前言
从事了好长时间的开发工作，平时只注重业务代码的开发，而忽略了java本身一些基础，所以从现在开始阅读以下jdk的源代码，首先从集合开始吧！这一篇先看下HashMap的源码。
java集合架构
这一段是引用了 http://blog.csdn.net/ns_code/article/details/35564663大神文章中的内容。
Java集合工具包为于Java.util包下，包含了很多常用的数据结构，如数组、链表、栈、队列、集合、哈希表等。学习Java集合框架大致可以分为以下五个部分：List列表、Set集合、Map、迭代器(Iterator、Enumeration)、工具类(Arrays、Collections)。
Java集合类的整体框架如下：
从上图中可以看出，集合类主要分为两大类：Collection和Map。
Collection是List、Set等集合高度抽象出来的接口，它包含了这些集合的基本操作，它主要又分为两大部分：List和Set。
List接口通常表示一个列表（数组、队列、链表、栈等），其中的元素可以重复，常用实现类为ArrayList和LinkedList，另外还有不常用的Vector。另外，LinkedList还是实现了Queue接口，因此也可以作为队列使用。
Set接口通常表示一个集合，其中的元素不允许重复（通过hashcode和equals函数保证），常用实现类有HashSet和TreeSet，HashSet是通过Map中的HashMap实现的，而TreeSet是通过Map中的TreeMap实现的。另外，TreeSet还实现了SortedSet接口，因此是有序的集合（集合中的元素要实现Comparable接口，并覆写Compartor函数才行）。
我们看到，抽象类AbstractCollection、AbstractList和AbstractSet分别实现了Collection、List和Set接口，这就是在Java集合框架中用的很多的适配器设计模式，用这些抽象类去实现接口，在抽象类中实现接口中的若干或全部方法，这样下面的一些类只需直接继承该抽象类，并实现自己需要的方法即可，而不用实现接口中的全部抽象方法。
Map是一个映射接口，其中的每个元素都是一个key-value键值对，同样抽象类AbstractMap通过适配器模式实现了Map接口中的大部分函数，TreeMap、HashMap、WeakHashMap等实现类都通过继承AbstractMap来实现，另外，不常用的HashTable直接实现了Map接口，它和Vector都是JDK1.0就引入的集合类。
Iterator是遍历集合的迭代器（不能遍历Map，只用来遍历Collection），Collection的实现类都实现了iterator()函数，它返回一个Iterator对象，用来遍历集合，ListIterator则专门用来遍历List。而Enumeration则是JDK1.0时引入的，作用与Iterator相同，但它的功能比Iterator要少，它只能再Hashtable、Vector和Stack中使用。
Arrays和Collections是用来操作数组、集合的两个工具类，例如在ArrayList和Vector中大量调用了Arrays.Copyof()方法，而Collections中有很多静态方法可以返回各集合类的synchronized版本，即线程安全的版本，当然了，如果要用线程安全的结合类，首选Concurrent并发包下的对应的集合类。
HashMap简介
HashMap是基于哈希表实现的，他的底层是一个Entry链表数组，并且数组的长度是2的倍数，在执行put操作的时候，将key进行hash操作， 将hash值h跟数组长度length-1做与操作h & (length-1)，值就是key在Entry数组中下标，但是前提条件就是数组长度必须为2的倍数。当如果发生哈希碰撞(就是说key做哈希后得到的下标位置冲突)，那么判断下，在下标对应链表中是否存在当前key，如果存在那么将其对应值替换，否则，创建一个新的Entry对象放到下标位置，并且将他的下一个元素指向原来位置上的Entry。
HashTable实现了Map接口中所有的方法，并且允许key和value都为null。HashMap大致上和HashTable一样，实现了Map接口所有的方法，但是HashMap是线程不安全的，并且允许key可value为null。并且HashMap不保证集合中元素的顺序和也不保证在不同时间段集合中元素顺序是一致的。
容量(capacity)和负载因子(loadFactor)
capacity表示的是哈希表中bucket的数量，loadFactor则表示的是哈希表中bucket填满数量占哈希表总数量的百分比。当哈希表中存有extry的bucket数量大于等于capacity*loadFactor时，哈希表容量增大一倍，也就是bucket数量为当前2倍的最小2的次幂。注意，在扩容前后capacity都是2的次幂，这是因为在获取key对应hash值在哈希表中下标时公式h&(length-1)就是建立在length是2的次幂的前提下。
源码解析
import java.io.*;
public class HashMap1<K,V>
extends AbstractMap<K,V>
implements Map<K,V>, Cloneable, Serializable
{
/**
* The default initial capacity - MUST be a power of two.
默认初始化容量16， 并且容量必须是2的整数次幂
*/
static final int DEFAULT_INITIAL_CAPACITY = 1 << 4; // aka 16
/**
* The maximum capacity, used if a higher value is implicitly specified
* by either of the constructors with arguments.
* MUST be a power of two <= 1<<30.
通过参数构建HashMap时，最大容量是2的30次幂，传入容量过大时将会被这个值替换
*/
static final int MAXIMUM_CAPACITY = 1 << 30;
/**
* The load factor used when none specified in constructor.
负载因子默认值是0.75f
*/
static final float DEFAULT_LOAD_FACTOR = 0.75f;
/**
* An empty table instance to share when the table is not inflated.
哈希表没有被初始化时，先初始化为一个空表
*/
static final Entry<?,?>[] EMPTY_TABLE = {};
/**
* The table, resized as necessary. Length MUST Always be a power of two.
哈希表，有必要时会扩容，长度必须是2的整数次幂
*/
transient Entry<K,V>[] table = (Entry<K,V>[]) EMPTY_TABLE;
/**
* The number of key-value mappings contained in this map.
map中存放键值对的数量
*/
transient int size;
/**
* The next size value at which to resize (capacity * load factor).
* HashMap阈值，用于判断是否需要扩容(threshold = capacity*loadfactor)
*/
//初始化HashMap时,哈希表为空，此时threshold为容量capacity大小，
//当inflate初始化哈希表时，threshold赋值为capacity*loadfactor
int threshold;
//负载因子
final float loadFactor;
//HashMap改动的次数
transient int modCount;
/**
* The default threshold of map capacity above which alternative hashing is
* used for String keys. Alternative hashing reduces the incidence of
* collisions due to weak hash code calculation for String keys.
* <p/>
* This value may be overridden by defining the system property
* {@code jdk.map.althashing.threshold}. A property value of {@code 1}
* forces alternative hashing to be used at all times whereas
* {@code -1} value ensures that alternative hashing is never used.
*/
static final int ALTERNATIVE_HASHING_THRESHOLD_DEFAULT = Integer.MAX_VALUE;
/**
* holds values which can't be initialized until after VM is booted.
*/
private static class Holder {
/**
* Table capacity above which to switch to use alternative hashing.
*/
static final int ALTERNATIVE_HASHING_THRESHOLD;
static {
String altThreshold = java.security.AccessController.doPrivileged(
new sun.security.action.GetPropertyAction(
"jdk.map.althashing.threshold"));
int threshold;
try {
threshold = (null != altThreshold)
? Integer.parseInt(altThreshold)
: ALTERNATIVE_HASHING_THRESHOLD_DEFAULT;
// disable alternative hashing if -1
if (threshold == -1) {
threshold = Integer.MAX_VALUE;
}
if (threshold < 0) {
throw new IllegalArgumentException("value must be positive integer.");
}
} catch(IllegalArgumentException failed) {
throw new Error("Illegal value for 'jdk.map.althashing.threshold'", failed);
}
ALTERNATIVE_HASHING_THRESHOLD = threshold;
}
}
/**
* A randomizing value associated with this instance that is applied to
* hash code of keys to make hash collisions harder to find. If 0 then
* alternative hashing is disabled.
*/
transient int hashSeed = 0;
/**
* Constructs an empty <tt>HashMap</tt> with the specified initial
* capacity and load factor.
根据指定的容量和负载因子创建一个空的HashMap，在进行put操作时会判断哈希表是否为空，空就初始化哈希表
*/
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();
}
/**
* Constructs an empty <tt>HashMap</tt> with the specified initial
* capacity and the default load factor (0.75).
根据指定的容量和默认的负载因子0.75创建一个空的HashMap
*/
public HashMap(int initialCapacity) {
this(initialCapacity, DEFAULT_LOAD_FACTOR);
}
/**
* Constructs an empty <tt>HashMap</tt> with the default initial capacity
* (16) and the default load factor (0.75).
*/
public HashMap() {
this(DEFAULT_INITIAL_CAPACITY, DEFAULT_LOAD_FACTOR);
}
/**
* Constructs a new <tt>HashMap</tt> with the same mappings as the
* specified <tt>Map</tt>. The <tt>HashMap</tt> is created with
* default load factor (0.75) and an initial capacity sufficient to
* hold the mappings in the specified <tt>Map</tt>.
*
* @param m the map whose mappings are to be placed in this map
* @throws NullPointerException if the specified map is null
*/
public HashMap(Map<? extends K, ? extends V> m) {
this(Math.max((int) (m.size() / DEFAULT_LOAD_FACTOR) + 1,
DEFAULT_INITIAL_CAPACITY), DEFAULT_LOAD_FACTOR);
inflateTable(threshold);
putAllForCreate(m);
}
private static int roundUpToPowerOf2(int number) {
// assert number >= 0 : "number must be non-negative";
int rounded = number >= MAXIMUM_CAPACITY
? MAXIMUM_CAPACITY
: (rounded = Integer.highestOneBit(number)) != 0
? (Integer.bitCount(number) > 1) ? rounded << 1 : rounded
: 1;
return rounded;
}
/**
* Inflates the table.
*/
private void inflateTable(int toSize) {
// Find a power of 2 >= toSize
//找到大于toSize最小的2的整数次幂
int capacity = roundUpToPowerOf2(toSize);
threshold = (int) Math.min(capacity * loadFactor, MAXIMUM_CAPACITY + 1);
table = new Entry[capacity];
initHashSeedAsNeeded(capacity);
}
void init() {
}
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;
}
/**
* Retrieve object hash code and applies a supplemental hash function to the
* result hash, which defends against poor quality hash functions. This is
* critical because HashMap uses power-of-two length hash tables, that
* otherwise encounter collisions for hashCodes that do not differ
* in lower bits. Note: Null keys always map to hash 0, thus index 0.
*/
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);
}
/**
* 根据key对应hash值和哈希表长度获取key在哈希表中下标
*/
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);
}
/**
* 获取map中键值对数量
*/
public int size() {
return size;
}
public boolean isEmpty() {
return size == 0;
}
/**
*/
public V get(Object key) {
if (key == null)
return getForNullKey();
Entry<K,V> entry = getEntry(key);
return null == entry ? null : entry.getValue();
}
/**
* Offloaded version of get() to look up null keys. Null keys map
* to index 0. This null case is split out into separate methods
* for the sake of performance in the two most commonly used
* operations (get and put), but incorporated with conditionals in
* others.
*/
private V getForNullKey() {
if (size == 0) {
return null;
}
for (Entry<K,V> e = table[0]; e != null; e = e.next) {
if (e.key == null)
return e.value;
}
return null;
}
/**
* Returns <tt>true</tt> if this map contains a mapping for the
* specified key.
*
* @param key The key whose presence in this map is to be tested
* @return <tt>true</tt> if this map contains a mapping for the specified
* key.
*/
public boolean containsKey(Object key) {
return getEntry(key) != null;
}
/**
根据key获取entry对象，如果 没有那么返回null
整体操作就是首先根据key的哈希值获取在table中下标，然后拿到链表后遍历链表
*/
final Entry<K,V> getEntry(Object key) {
if (size == 0) {
return null;
}
int hash = (key == null) ? 0 : hash(key);
for (Entry<K,V> e = table[indexFor(hash, table.length)];
e != null;
e = e.next) {
Object k;
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k))))
return e;
}
return null;
}
//存储key-value键值对
public V put(K key, V value) {
//判断下如果table为空那么初始化哈希表
if (table == EMPTY_TABLE) {
inflateTable(threshold);
}
if (key == null)
return putForNullKey(value);
int hash = hash(key);
//获取在哈希表中下标
int i = indexFor(hash, table.length);
//拿到下标位置的Entry链表对象，遍历链表所有元素，判断链表上是否已存在key为当前插入key的Entry对象
for (Entry<K,V> e = table[i]; e != null; e = e.next) {
Object k;
//如果链表上已存在当前插入的key那么将原来value替换掉
if (e.hash == hash && ((k = e.key) == key || key.equals(k))) {
V oldValue = e.value;
e.value = value;
e.recordAccess(this);
return oldValue;
}
}
//如果链表上不存在当前key，创建Entry
modCount++;
addEntry(hash, key, value, i);
return null;
}
/**
* 插入key为null的value
*/
private V putForNullKey(V value) {
//讲key为null的键值对放到table下标为0的链表中
for (Entry<K,V> 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;
}
/**
* This method is used instead of put by constructors and
* pseudoconstructors (clone, readObject). It does not resize the table,
* check for comodification, etc. It calls createEntry rather than
* addEntry.
*/
private void putForCreate(K key, V value) {
int hash = null == key ? 0 : hash(key);
int i = indexFor(hash, table.length);
/**
* Look for preexisting entry for key. This will never happen for
* clone or deserialize. It will only happen for construction if the
* input Map is a sorted map whose ordering is inconsistent w/ equals.
*/
for (Entry<K,V> e = table[i]; e != null; e = e.next) {
Object k;
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k)))) {
e.value = value;
return;
}
}
createEntry(hash, key, value, i);
}
private void putAllForCreate(Map<? extends K, ? extends V> m) {
for (Map.Entry<? extends K, ? extends V> e : m.entrySet())
putForCreate(e.getKey(), e.getValue());
}
/**
* Rehashes the contents of this map into a new array with a
* larger capacity. This method is called automatically when the
* number of keys in this map reaches its threshold.
*
* If current capacity is MAXIMUM_CAPACITY, this method does not
* resize the map, but sets threshold to Integer.MAX_VALUE.
* This has the effect of preventing future calls.
*
* @param newCapacity the new capacity, MUST be a power of two;
* must be greater than current capacity unless current
* capacity is MAXIMUM_CAPACITY (in which case value
* is irrelevant).
*/
void resize(int newCapacity) {
Entry[] oldTable = table;
int oldCapacity = oldTable.length;
if (oldCapacity == MAXIMUM_CAPACITY) {
threshold = Integer.MAX_VALUE;
return;
}
Entry[] newTable = new Entry[newCapacity];
transfer(newTable, initHashSeedAsNeeded(newCapacity));
table = newTable;
threshold = (int)Math.min(newCapacity * loadFactor, MAXIMUM_CAPACITY + 1);
}
/**
* Transfers all entries from current table to newTable.
*/
void transfer(Entry[] newTable, boolean rehash) {
int newCapacity = newTable.length;
for (Entry<K,V> e : table) {
while(null != e) {
Entry<K,V> next = e.next;
if (rehash) {
e.hash = null == e.key ? 0 : hash(e.key);
}
int i = indexFor(e.hash, newCapacity);
e.next = newTable[i];
newTable[i] = e;
e = next;
}
}
}
/**
* Copies all of the mappings from the specified map to this map.
* These mappings will replace any mappings that this map had for
* any of the keys currently in the specified map.
*
* @param m mappings to be stored in this map
* @throws NullPointerException if the specified map is null
*/
public void putAll(Map<? extends K, ? extends V> m) {
int numKeysToBeAdded = m.size();
if (numKeysToBeAdded == 0)
return;
if (table == EMPTY_TABLE) {
inflateTable((int) Math.max(numKeysToBeAdded * loadFactor, threshold));
}
/*
* Expand the map if the map if the number of mappings to be added
* is greater than or equal to threshold. This is conservative; the
* obvious condition is (m.size() + size) >= threshold, but this
* condition could result in a map with twice the appropriate capacity,
* if the keys to be added overlap with the keys already in this map.
* By using the conservative calculation, we subject ourself
* to at most one extra resize.
*/
if (numKeysToBeAdded > threshold) {
int targetCapacity = (int)(numKeysToBeAdded / loadFactor + 1);
if (targetCapacity > MAXIMUM_CAPACITY)
targetCapacity = MAXIMUM_CAPACITY;
int newCapacity = table.length;
while (newCapacity < targetCapacity)
newCapacity <<= 1;
if (newCapacity > table.length)
resize(newCapacity);
}
for (Map.Entry<? extends K, ? extends V> e : m.entrySet())
put(e.getKey(), e.getValue());
}
/**
* Removes the mapping for the specified key from this map if present.
*
* @param key key whose mapping is to be removed from the map
* @return the previous value associated with <tt>key</tt>, or
* <tt>null</tt> if there was no mapping for <tt>key</tt>.
* (A <tt>null</tt> return can also indicate that the map
* previously associated <tt>null</tt> with <tt>key</tt>.)
*/
public V remove(Object key) {
Entry<K,V> e = removeEntryForKey(key);
return (e == null ? null : e.value);
}
/**
* Removes and returns the entry associated with the specified key
* in the HashMap. Returns null if the HashMap contains no mapping
* for this key.
*/
final Entry<K,V> removeEntryForKey(Object key) {
if (size == 0) {
return null;
}
int hash = (key == null) ? 0 : hash(key);
int i = indexFor(hash, table.length);
Entry<K,V> prev = table[i];
Entry<K,V> e = prev;
while (e != null) {
Entry<K,V> next = e.next;
Object k;
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k)))) {
modCount++;
size--;
if (prev == e)
table[i] = next;
else
prev.next = next;
e.recordRemoval(this);
return e;
}
prev = e;
e = next;
}
return e;
}
/**
* Special version of remove for EntrySet using {@code Map.Entry.equals()}
* for matching.
*/
final Entry<K,V> removeMapping(Object o) {
if (size == 0 || !(o instanceof Map.Entry))
return null;
Map.Entry<K,V> entry = (Map.Entry<K,V>) o;
Object key = entry.getKey();
int hash = (key == null) ? 0 : hash(key);
int i = indexFor(hash, table.length);
Entry<K,V> prev = table[i];
Entry<K,V> e = prev;
while (e != null) {
Entry<K,V> next = e.next;
if (e.hash == hash && e.equals(entry)) {
modCount++;
size--;
if (prev == e)
table[i] = next;
else
prev.next = next;
e.recordRemoval(this);
return e;
}
prev = e;
e = next;
}
return e;
}
/**
* Removes all of the mappings from this map.
* The map will be empty after this call returns.
*/
public void clear() {
modCount++;
Arrays.fill(table, null);
size = 0;
}
/**
* Returns <tt>true</tt> if this map maps one or more keys to the
* specified value.
*
* @param value value whose presence in this map is to be tested
* @return <tt>true</tt> if this map maps one or more keys to the
* specified value
*/
public boolean containsValue(Object value) {
if (value == null)
return containsNullValue();
Entry[] tab = table;
for (int i = 0; i < tab.length ; i++)
for (Entry e = tab[i] ; e != null ; e = e.next)
if (value.equals(e.value))
return true;
return false;
}
/**
* Special-case code for containsValue with null argument
*/
private boolean containsNullValue() {
Entry[] tab = table;
for (int i = 0; i < tab.length ; i++)
for (Entry e = tab[i] ; e != null ; e = e.next)
if (e.value == null)
return true;
return false;
}
/**
* Returns a shallow copy of this <tt>HashMap</tt> instance: the keys and
* values themselves are not cloned.
*
* @return a shallow copy of this map
*/
public Object clone() {
HashMap<K,V> result = null;
try {
result = (HashMap<K,V>)super.clone();
} catch (CloneNotSupportedException e) {
// assert false;
}
if (result.table != EMPTY_TABLE) {
result.inflateTable(Math.min(
(int) Math.min(
size * Math.min(1 / loadFactor, 4.0f),
// we have limits...
HashMap.MAXIMUM_CAPACITY),
table.length));
}
result.entrySet = null;
result.modCount = 0;
result.size = 0;
result.init();
result.putAllForCreate(this);
return result;
}
static class Entry<K,V> implements Map.Entry<K,V> {
final K key;
V value;
Entry<K,V> next;
int hash;
/**
* Creates new entry.
*/
Entry(int h, K k, V v, Entry<K,V> n) {
value = v;
next = n;
key = k;
hash = h;
}
public final K getKey() {
return key;
}
public final V getValue() {
return value;
}
public final V setValue(V newValue) {
V oldValue = value;
value = newValue;
return oldValue;
}
public final boolean equals(Object o) {
if (!(o instanceof Map.Entry))
return false;
Map.Entry e = (Map.Entry)o;
Object k1 = getKey();
Object k2 = e.getKey();
if (k1 == k2 || (k1 != null && k1.equals(k2))) {
Object v1 = getValue();
Object v2 = e.getValue();
if (v1 == v2 || (v1 != null && v1.equals(v2)))
return true;
}
return false;
}
public final int hashCode() {
return Objects.hashCode(getKey()) ^ Objects.hashCode(getValue());
}
public final String toString() {
return getKey() + "=" + getValue();
}
/**
* This method is invoked whenever the value in an entry is
* overwritten by an invocation of put(k,v) for a key k that's already
* in the HashMap.
*/
void recordAccess(HashMap<K,V> m) {
}
/**
* This method is invoked whenever the entry is
* removed from the table.
*/
void recordRemoval(HashMap<K,V> m) {
}
}
/**
* Adds a new entry with the specified key, value and hash code to
* the specified bucket. It is the responsibility of this
* method to resize the table if appropriate.
*
* Subclass overrides this to alter the behavior of put method.
*/
void addEntry(int hash, K key, V value, int bucketIndex) {
//如果哈希表大小已经达到扩容阈值，并且下标对应值不为空，那么将哈希表扩容为原来两倍
if ((size >= threshold) && (null != table[bucketIndex])) {
resize(2 * table.length);
hash = (null != key) ? hash(key) : 0;
bucketIndex = indexFor(hash, table.length);
}
createEntry(hash, key, value, bucketIndex);
}
/**
创建新的entry对象
*/
void createEntry(int hash, K key, V value, int bucketIndex) {
//首先获取哈希表中bucketIndex下标对应的Entry对象
Entry<K,V> e = table[bucketIndex];
//然后根据新传进来的key-value键值对创建一个entry对象，并且next属性指向原来bucketIndex下标位置上的entry对象，
//然后将新创建的entry对象，放到哈希表bucketIndex位置。
table[bucketIndex] = new Entry<>(hash, key, value, e);
size++;
}
private abstract class HashIterator<E> implements Iterator<E> {
Entry<K,V> next; // next entry to return
int expectedModCount; // For fast-fail
int index; // current slot
Entry<K,V> current; // current entry
HashIterator() {
expectedModCount = modCount;
if (size > 0) { // advance to first entry
Entry[] t = table;
while (index < t.length && (next = t[index++]) == null)
;
}
}
public final boolean hasNext() {
return next != null;
}
final Entry<K,V> nextEntry() {
if (modCount != expectedModCount)
throw new ConcurrentModificationException();
Entry<K,V> e = next;
if (e == null)
throw new NoSuchElementException();
if ((next = e.next) == null) {
Entry[] t = table;
while (index < t.length && (next = t[index++]) == null)
;
}
current = e;
return e;
}
public void remove() {
if (current == null)
throw new IllegalStateException();
if (modCount != expectedModCount)
throw new ConcurrentModificationException();
Object k = current.key;
current = null;
HashMap.this.removeEntryForKey(k);
expectedModCount = modCount;
}
}
private final class ValueIterator extends HashIterator<V> {
public V next() {
return nextEntry().value;
}
}
private final class KeyIterator extends HashIterator<K> {
public K next() {
return nextEntry().getKey();
}
}
private final class EntryIterator extends HashIterator<Map.Entry<K,V>> {
public Map.Entry<K,V> next() {
return nextEntry();
}
}
// Subclass overrides these to alter behavior of views' iterator() method
Iterator<K> newKeyIterator() {
return new KeyIterator();
}
Iterator<V> newValueIterator() {
return new ValueIterator();
}
Iterator<Map.Entry<K,V>> newEntryIterator() {
return new EntryIterator();
}
// Views
private transient Set<Map.Entry<K,V>> entrySet = null;
/**
* Returns a {@link Set} view of the keys contained in this map.
* The set is backed by the map, so changes to the map are
* reflected in the set, and vice-versa. If the map is modified
* while an iteration over the set is in progress (except through
* the iterator's own <tt>remove</tt> operation), the results of
* the iteration are undefined. The set supports element removal,
* which removes the corresponding mapping from the map, via the
* <tt>Iterator.remove</tt>, <tt>Set.remove</tt>,
* <tt>removeAll</tt>, <tt>retainAll</tt>, and <tt>clear</tt>
* operations. It does not support the <tt>add</tt> or <tt>addAll</tt>
* operations.
*/
public Set<K> keySet() {
Set<K> ks = keySet;
return (ks != null ? ks : (keySet = new KeySet()));
}
private final class KeySet extends AbstractSet<K> {
public Iterator<K> iterator() {
return newKeyIterator();
}
public int size() {
return size;
}
public boolean contains(Object o) {
return containsKey(o);
}
public boolean remove(Object o) {
return HashMap.this.removeEntryForKey(o) != null;
}
public void clear() {
HashMap.this.clear();
}
}
/**
* Returns a {@link Collection} view of the values contained in this map.
* The collection is backed by the map, so changes to the map are
* reflected in the collection, and vice-versa. If the map is
* modified while an iteration over the collection is in progress
* (except through the iterator's own <tt>remove</tt> operation),
* the results of the iteration are undefined. The collection
* supports element removal, which removes the corresponding
* mapping from the map, via the <tt>Iterator.remove</tt>,
* <tt>Collection.remove</tt>, <tt>removeAll</tt>,
* <tt>retainAll</tt> and <tt>clear</tt> operations. It does not
* support the <tt>add</tt> or <tt>addAll</tt> operations.
*/
public Collection<V> values() {
Collection<V> vs = values;
return (vs != null ? vs : (values = new Values()));
}
private final class Values extends AbstractCollection<V> {
public Iterator<V> iterator() {
return newValueIterator();
}
public int size() {
return size;
}
public boolean contains(Object o) {
return containsValue(o);
}
public void clear() {
HashMap.this.clear();
}
}
/**
* Returns a {@link Set} view of the mappings contained in this map.
* The set is backed by the map, so changes to the map are
* reflected in the set, and vice-versa. If the map is modified
* while an iteration over the set is in progress (except through
* the iterator's own <tt>remove</tt> operation, or through the
* <tt>setValue</tt> operation on a map entry returned by the
* iterator) the results of the iteration are undefined. The set
* supports element removal, which removes the corresponding
* mapping from the map, via the <tt>Iterator.remove</tt>,
* <tt>Set.remove</tt>, <tt>removeAll</tt>, <tt>retainAll</tt> and
* <tt>clear</tt> operations. It does not support the
* <tt>add</tt> or <tt>addAll</tt> operations.
*
* @return a set view of the mappings contained in this map
*/
public Set<Map.Entry<K,V>> entrySet() {
return entrySet0();
}
private Set<Map.Entry<K,V>> entrySet0() {
Set<Map.Entry<K,V>> es = entrySet;
return es != null ? es : (entrySet = new EntrySet());
}
private final class EntrySet extends AbstractSet<Map.Entry<K,V>> {
public Iterator<Map.Entry<K,V>> iterator() {
return newEntryIterator();
}
public boolean contains(Object o) {
if (!(o instanceof Map.Entry))
return false;
Map.Entry<K,V> e = (Map.Entry<K,V>) o;
Entry<K,V> candidate = getEntry(e.getKey());
return candidate != null && candidate.equals(e);
}
public boolean remove(Object o) {
return removeMapping(o) != null;
}
public int size() {
return size;
}
public void clear() {
HashMap.this.clear();
}
}
/**
* Save the state of the <tt>HashMap</tt> instance to a stream (i.e.,
* serialize it).
*
* @serialData The <i>capacity</i> of the HashMap (the length of the
* bucket array) is emitted (int), followed by the
* <i>size</i> (an int, the number of key-value
* mappings), followed by the key (Object) and value (Object)
* for each key-value mapping. The key-value mappings are
* emitted in no particular order.
*/
private void writeObject(java.io.ObjectOutputStream s)
throws IOException
{
// Write out the threshold, loadfactor, and any hidden stuff
s.defaultWriteObject();
// Write out number of buckets
if (table==EMPTY_TABLE) {
s.writeInt(roundUpToPowerOf2(threshold));
} else {
s.writeInt(table.length);
}
// Write out size (number of Mappings)
s.writeInt(size);
// Write out keys and values (alternating)
if (size > 0) {
for(Map.Entry<K,V> e : entrySet0()) {
s.writeObject(e.getKey());
s.writeObject(e.getValue());
}
}
}
private static final long serialVersionUID = 362498820763181265L;
/**
* Reconstitute the {@code HashMap} instance from a stream (i.e.,
* deserialize it).
*/
private void readObject(java.io.ObjectInputStream s)
throws IOException, ClassNotFoundException
{
// Read in the threshold (ignored), loadfactor, and any hidden stuff
s.defaultReadObject();
if (loadFactor <= 0 || Float.isNaN(loadFactor)) {
throw new InvalidObjectException("Illegal load factor: " +
loadFactor);
}
// set other fields that need values
table = (Entry<K,V>[]) EMPTY_TABLE;
// Read in number of buckets
s.readInt(); // ignored.
// Read number of mappings
int mappings = s.readInt();
if (mappings < 0)
throw new InvalidObjectException("Illegal mappings count: " +
mappings);
// capacity chosen by number of mappings and desired load (if >= 0.25)
int capacity = (int) Math.min(
mappings * Math.min(1 / loadFactor, 4.0f),
// we have limits...
HashMap.MAXIMUM_CAPACITY);
// allocate the bucket array;
if (mappings > 0) {
inflateTable(capacity);
} else {
threshold = capacity;
}
init(); // Give subclass a chance to do its thing.
// Read the keys and values, and put the mappings in the HashMap
for (int i = 0; i < mappings; i++) {
K key = (K) s.readObject();
V value = (V) s.readObject();
putForCreate(key, value);
}
}
// These methods are used when serializing HashSets
int capacity() { return table.length; }
float loadFactor() { return loadFactor; }
}
上面代码太多，有点乱，下面总结几点：
下面内容转载的http://blog.csdn.net/ns_code/article/details/36034955大神的文章。
1、首先要清楚HashMap的存储结构，如下图所示：
图中，紫色部分即代表哈希表table，也称为哈希数组，数组的每个元素都是一个单链表的头节点，链表是用来解决冲突的，如果不同的key映射到了数组的同一位置处，就将其放入单链表中。
2、首先看链表中节点的数据结构：
它的结构元素除了key、value、hash外，还有next，next指向下一个节点。另外，这里覆写了equals和hashCode方法来保证键值对的独一无二。
3、HashMap共有四个构造方法。构造方法中提到了两个很重要的参数：初始容量和加载因子。这两个参数是影响HashMap性能的重要参数，其中容量表示哈希表中槽的数量（即哈希数组的长度），初始容量是创建哈希表时的容量（从构造函数中可以看出，如果不指明，则默认为16），加载因子是哈希表在其容量自动增加之前可以达到多满的一种尺度，当哈希表中的条目数超出了加载因子与当前容量的乘积时，则要对该哈希表进行 resize 操作（即扩容）。
下面说下加载因子，如果加载因子越大，对空间的利用更充分，但是查找效率会降低（链表长度会越来越长）；如果加载因子太小，那么表中的数据将过于稀疏（很多空间还没用，就开始扩容了），对空间造成严重浪费。如果我们在构造方法中不指定，则系统默认加载因子为0.75，这是一个比较理想的值，一般情况下我们是无需修改的。
另外，无论我们指定的容量为多少，构造方法都会将实际容量设为不小于指定容量的2的次方的一个数，且最大值不能超过2的30次方
4、HashMap中key和value都允许为null。
5、要重点分析下HashMap中用的最多的两个方法put和get。先从比较简单的get方法着手，源码如下：
//根据key获取value
public V get(Object key) {
if (key == null)
return getForNullKey();
Entry<K,V> entry = getEntry(key);
//因为可能不存在key对应的entry对象，所以需要处理entry为null
return null == entry ? null : entry.getValue();
}
//获取key为null的值
private V getForNullKey() {
if (size == 0) {
return null;
}
//HashMap将key为null的值放在table[0]的位置的链表，但是不是定是链表的第一个位置
for (Entry<K,V> e = table[0]; e != null; e = e.next) {
if (e.key == null)
return e.value;
}
return null;
}
//根据key获取key对应的Entry对象
final Entry<K,V> getEntry(Object key) {
//如果table的size为0直接返回空
if (size == 0) {
return null;
}
//否则根据key获取哈希表中链表，遍历，获取链表中key和hash值相同的Entry的value
int hash = (key == null) ? 0 : hash(key);
for (Entry<K,V> e = table[indexFor(hash, table.length)];
e != null;
e = e.next) {
Object k;
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k))))
return e;
}
return null;
}
首先，如果key为null，则直接从哈希表的第一个位置table[0]对应的链表上查找。记住，key为null的键值对永远都放在以table[0]为头结点的链表中，当然不一定是存放在头结点table[0]中。 如果key不为null，则先求的key的hash值，根据hash值找到在table中的索引，在该索引对应的单链表中查找是否有键值对的key与目标key相等，有就返回对应的value，没有则返回null。
put方法稍微复杂些，代码如下：
如果table为EMPTY_TABLE,那么，初始化table，inflateTable的源码如下：
private void inflateTable(int toSize) {
// 设置比toSize大的2的整数次幂的值为初始化容量
int capacity = roundUpToPowerOf2(toSize);
threshold = (int) Math.min(capacity * loadFactor, MAXIMUM_CAPACITY + 1);
table = new Entry[capacity];
initHashSeedAsNeeded(capacity);
}
如果key不为null，则同样先求出key的hash值，根据hash值得出在table中的索引，而后遍历对应的单链表，如果单链表中存在与目标key相等的键值对，则将新的value覆盖旧的value，比将旧的value返回，如果找不到与目标key相等的键值对，或者该单链表为空，则将该键值对插入到改单链表的头结点位置（每次新插入的节点都是放在头结点的位置），该操作是有addEntry方法实现的，它的源码如下：
//新增entry。将key-value插入指定位置，bucketIndex是链表位置索引
void addEntry(int hash, K key, V value, int bucketIndex) {
//如果HashMap的size达到扩容阈值，并且索引所在位置链表不为空，那么扩容
if ((size >= threshold) && (null != table[bucketIndex])) {
//扩容，数组长度变为原来的两倍
resize(2 * table.length);
hash = (null != key) ? hash(key) : 0;
//获取key在新生成哈希表中位置索引
bucketIndex = indexFor(hash, table.length);
}
createEntry(hash, key, value, bucketIndex);
}
void createEntry(int hash, K key, V value, int bucketIndex) {
//保存bucketIndex位置的值到entry
Entry<K,V> e = table[bucketIndex];
//设置bucketIndex位置元素为“新Entry”，并且设置e为“新Entry”的下一个节点
table[bucketIndex] = new Entry<>(hash, key, value, e);
size++;
}
注意这里倒数第二行的构造方法，将key-value键值对赋给table[bucketIndex]，并将其next指向元素e，这便将key-value放到了头结点中，并将之前的头结点接在了它的后面。该方法也说明，每次put键值对的时候，总是将新的该键值对放在table[bucketIndex]处（即头结点处）。
两外注意addEntry方法中第一行代码，每次加入键值对时，都要判断当前已用的槽的数目是否大于等于阀值（容量*加载因子），如果大于等于，则进行扩容，将容量扩为原来容量的2倍。
6、关于扩容。上面我们看到了扩容的方法，resize方法，它的源码如下：
很明显，是新建了一个HashMap的底层数组，而后调用transfer方法，将就HashMap的全部元素添加到新的HashMap中（要重新计算元素在新的数组中的索引位置）。transfer方法的源码如下：
很明显，扩容是一个相当耗时的操作，因为它需要重新计算这些元素在新的数组中的位置并进行复制处理。因此，我们在用HashMap的时，最好能提前预估下HashMap中元素的个数，这样有助于提高HashMap的性能。
7、注意containsKey方法和containsValue方法。前者直接可以通过key的哈希值将搜索范围定位到指定索引对应的链表，而后者要对哈希数组的每个链表进行搜索。
8、我们重点来分析下求hash值和索引值的方法，这两个方法便是HashMap设计的最为核心的部分，二者结合能保证哈希表中的元素尽可能均匀地散列。
计算哈希值的方法如下：
它只是一个数学公式，IDK这样设计对hash值的计算，自然有它的好处，至于为什么这样设计，我们这里不去追究，只要明白一点，用的位的操作使hash值的计算效率很高。
由hash值找到对应索引的方法如下：
这个我们要重点说下，我们一般对哈希表的散列很自然地会想到用hash值对length取模（即除法散列法），Hashtable中也是这样实现的，这种方法基本能保证元素在哈希表中散列的比较均匀，但取模会用到除法运算，效率很低，HashMap中则通过h&(length-1)的方法来代替取模，同样实现了均匀的散列，但效率要高很多，这也是HashMap对Hashtable的一个改进。
接下来，我们分析下为什么哈希表的容量一定要是2的整数次幂。首先，length为2的整数次幂的话，h&(length-1)就相当于对length取模，这样便保证了散列的均匀，同时也提升了效率；其次，length为2的整数次幂的话，为偶数，这样length-1为奇数，奇数的最后一位是1，这样便保证了h&(length-1)的最后一位可能为0，也可能为1（这取决于h的值），即与后的结果可能为偶数，也可能为奇数，这样便可以保证散列的均匀性，而如果length为奇数的话，很明显length-1为偶数，它的最后一位是0，这样h&(length-1)的最后一位肯定为0，即只能为偶数，这样任何hash值都只会被散列到数组的偶数下标位置上，这便浪费了近一半的空间，因此，length取2的整数次幂，是为了使不同hash值发生碰撞的概率较小，这样就能使元素在哈希表中均匀地散列。