前言
java集合架构
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
容量(capacity)和负载因子(loadFactor)
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:
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++;
}
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。