類 IdentityHashMap<K,V>
此類利用哈希表實現 Map 接口,比較鍵(和值)時使用引用相等性代替對象相等性。換句話說,在 IdentityHashMap 中,當且僅當 (k1 == k2) 時,才認爲兩個鍵 k1 和 k2 相等(在正常 Map 實現(如 HashMap)中,當且僅當滿足下列條件時才認爲兩個鍵 k1 和 k2 相等:(k1 == null ? k2 == null : e1.equals(e2)))。
此類不是 通用 Map 實現!此類實現 Map 接口時,它有意違反 Map 的常規協定,該協定在比較對象時強制使用 equals 方法。此類設計僅用於其中需要引用相等性語義的罕見情況。
此類的典型用法是拓撲保留對象圖形轉換,如序列化或深層複製。要執行這樣的轉換,程序必須維護用於跟蹤所有已處理對象引用的“節點表”。節點表一定不等於不同對象,即使它們偶然相等也如此。此類的另一種典型用法是維護代理對象。例如,調試設施可能希望爲正在調試程序中的每個對象維護代理對象。
此類提供所有的可選映射操作,並且允許 null 值和 null 鍵。此類對映射的順序不提供任何保證;特別是不保證順序隨時間的推移保持不變。
此類提供基本操作(get 和 put)的穩定性能,假定系統標識了將桶間元素正確分開的哈希函數 (System.identityHashCode(Object))。
此類具有一個調整參數(影響性能但不影響語義):expected maximum size。此參數是希望映射保持的鍵值映射關係最大數。在內部,此參數用於確定最初組成哈希表的桶數。未指定所期望的最大數量和桶數之間的確切關係。
如果映射的大小(鍵值映射關係數)已經超過期望的最大數量,則桶數會增加,增加桶數(“重新哈希”)可能相當昂貴,因此創建具有足夠大的期望最大數量的標識哈希映射更合算。另一方面,對 collection 視圖進行迭代所需的時間與哈希表中的桶數成正比,所以如果特別注重迭代性能或內存使用,則不宜將期望的最大數量設置得過高。
此實現不是同步的。
由所有此類的“collection 視圖方法”所返回的迭代器都是快速失敗。
實現注意事項:此爲簡單的線性探頭 哈希表,如 Sedgewick 和 Knuth 原文示例中所述。該數組交替保持鍵和值(對於大型表來說,它比使用獨立組保持鍵和值更具優勢)。對於多數 JRE 實現和混合操作,此類比 HashMap(它使用鏈 而不使用線性探頭)能產生更好的性能。
源碼
成員以及構造方法:
/**
* The initial capacity used by the no-args constructor.
* MUST be a power of two. The value 32 corresponds to the
* (specified) expected maximum size of 21, given a load factor
* of 2/3.
*/
private static final int DEFAULT_CAPACITY = 32;
/**
* The minimum capacity, used if a lower value is implicitly specified
* by either of the constructors with arguments. The value 4 corresponds
* to an expected maximum size of 2, given a load factor of 2/3.
* MUST be a power of two.
*/
private static final int MINIMUM_CAPACITY = 4;
/**
* 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<<29.
*/
private static final int MAXIMUM_CAPACITY = 1 << 29;
/**
* Constructs a new, empty identity hash map with a default expected
* maximum size (21).
*/
public IdentityHashMap() {
init(DEFAULT_CAPACITY);
}
/**
* Constructs a new, empty map with the specified expected maximum size.
* Putting more than the expected number of key-value mappings into
* the map may cause the internal data structure to grow, which may be
* somewhat time-consuming.
*
* @param expectedMaxSize the expected maximum size of the map
* @throws IllegalArgumentException if <tt>expectedMaxSize</tt> is negative
*/
public IdentityHashMap(int expectedMaxSize) {
if (expectedMaxSize < 0)
throw new IllegalArgumentException("expectedMaxSize is negative: "
+ expectedMaxSize);
init(capacity(expectedMaxSize));
}
/**
* Returns the appropriate capacity for the specified expected maximum
* size. Returns the smallest power of two between MINIMUM_CAPACITY
* and MAXIMUM_CAPACITY, inclusive, that is greater than
* (3 * expectedMaxSize)/2, if such a number exists. Otherwise
* returns MAXIMUM_CAPACITY. If (3 * expectedMaxSize)/2 is negative, it
* is assumed that overflow has occurred, and MAXIMUM_CAPACITY is returned.
*/
private int capacity(int expectedMaxSize) {
// Compute min capacity for expectedMaxSize given a load factor of 2/3
int minCapacity = (3 * expectedMaxSize)/2;
// Compute the appropriate capacity
int result;
if (minCapacity > MAXIMUM_CAPACITY || minCapacity < 0) {
result = MAXIMUM_CAPACITY;
} else {
result = MINIMUM_CAPACITY;
while (result < minCapacity)
result <<= 1;
}
return result;
}
/**
* Initializes object to be an empty map with the specified initial
* capacity, which is assumed to be a power of two between
* MINIMUM_CAPACITY and MAXIMUM_CAPACITY inclusive.
*/
private void init(int initCapacity) {
// assert (initCapacity & -initCapacity) == initCapacity; // power of 2
// assert initCapacity >= MINIMUM_CAPACITY;
// assert initCapacity <= MAXIMUM_CAPACITY;
// 閾值爲容量的2/3
threshold = (initCapacity * 2)/3;
// 內部數組的size爲容量的2倍,因爲IdentityHashMap將所有的key和value都存儲到Object[]數組table中,
// 並且key和value相鄰存儲,因此map中每一對鍵值對都要佔用兩個位置。
// 數組第一個位置存儲的是key,第二個位置存儲的是value。因此奇數位置處存儲的是key,偶數位置處存儲的是value。
table = new Object[2 * initCapacity];
}
/**
* Constructs a new identity hash map containing the keys-value mappings
* in the specified map.
*
* @param m the map whose mappings are to be placed into this map
* @throws NullPointerException if the specified map is null
*/
public IdentityHashMap(Map<? extends K, ? extends V> m) {
// Allow for a bit of growth
this((int) ((1 + m.size()) * 1.1));
putAll(m);
}
put方法:
public V put(K key, V value) {
// 若key爲null返回定義的nullkey
Object k = maskNull(key);
Object[] tab = table;
int len = tab.length;
// 獲得位置
int i = hash(k, len);
Object item;
while ( (item = tab[i]) != null) {
if (item == k) {//這裏使用==判斷key是否是同一個key
i+1的位置上存着i位置上key的對應值
V oldValue = (V) tab[i + 1];
tab[i + 1] = value;
return oldValue;
}
// 產生衝突,找到下一個爲null的位置
// 獲取下一個鍵的位置 i+2
i = nextKeyIndex(i, len);
}
// 數組中不存在這個鍵則新增
modCount++;
tab[i] = k;
tab[i + 1] = value;
// size+1後大於或等於閾值時擴容
if (++size >= threshold)
resize(len); // len == 2 * current capacity.
return null;
}
/**
* Value representing null keys inside tables.
*/
private static final Object NULL_KEY = new Object();
/**
* Use NULL_KEY for key if it is null.
*/
private static Object maskNull(Object key) {
return (key == null ? NULL_KEY : key);
}
/**
* Returns index for Object x.
*/
private static int hash(Object x, int length) {
// 使用System.identityHashCode來確定對象的哈希碼,該方法返回對象的地址。
int h = System.identityHashCode(x);
// Multiply by -127, and left-shift to use least bit as part of hash
return ((h << 1) - (h << 8)) & (length - 1);
}
/**
* Circularly traverses table of size len.
*/
private static int nextKeyIndex(int i, int len) {
return (i + 2 < len ? i + 2 : 0);
}
擴容:
private void resize(int newCapacity) {
// assert (newCapacity & -newCapacity) == newCapacity; // power of 2
int newLength = newCapacity * 2;
Object[] oldTable = table;
int oldLength = oldTable.length;
if (oldLength == 2*MAXIMUM_CAPACITY) { // can't expand any further
// 若當前數組容量已經是最大
if (threshold == MAXIMUM_CAPACITY-1)
// 閾值最大,報錯
throw new IllegalStateException("Capacity exhausted.");
// 擴大閾值
threshold = MAXIMUM_CAPACITY-1; // Gigantic map!
return;
}
// 容量已經夠用了 返回
if (oldLength >= newLength)
return;
Object[] newTable = new Object[newLength];
// newLength前邊已經乘2
threshold = newLength / 3;
for (int j = 0; j < oldLength; j += 2) {
Object key = oldTable[j];
if (key != null) {
Object value = oldTable[j+1];
oldTable[j] = null;
oldTable[j+1] = null;
// 重新計算hash值
int i = hash(key, newLength);
while (newTable[i] != null)
i = nextKeyIndex(i, newLength);
newTable[i] = key;
newTable[i + 1] = value;
}
}
table = newTable;
}
get方法:
public V get(Object key) {
// nullkey判斷
Object k = maskNull(key);
Object[] tab = table;
int len = tab.length;
// 計算位置
int i = hash(k, len);
while (true) {
// 一直到找到該key(key地址相等)或者不存在該key(位置爲null)時返回。
Object item = tab[i];
if (item == k)
return (V) tab[i + 1];
if (item == null)
return null;
// put時發生衝突會放到之後第一個爲null的位置上
i = nextKeyIndex(i, len);
}
}
remove方法:
public V remove(Object key) {
Object k = maskNull(key);
Object[] tab = table;
int len = tab.length;
int i = hash(k, len);
while (true) {
Object item = tab[i];
if (item == k) {
modCount++;
size--;
V oldValue = (V) tab[i + 1];
tab[i + 1] = null;
tab[i] = null;
// 這裏會把因爲產生衝突而後移的元素的位置都重新調整
closeDeletion(i);
return oldValue;
}
if (item == null)
return null;
i = nextKeyIndex(i, len);
}
}
private void closeDeletion(int d) {
// Adapted from Knuth Section 6.4 Algorithm R
Object[] tab = table;
int len = tab.length;
// Look for items to swap into newly vacated slot
// starting at index immediately following deletion,
// and continuing until a null slot is seen, indicating
// the end of a run of possibly-colliding keys.
Object item;
for (int i = nextKeyIndex(d, len); (item = tab[i]) != null;
i = nextKeyIndex(i, len) ) {
// The following test triggers if the item at slot i (which
// hashes to be at slot r) should take the spot vacated by d.
// If so, we swap it in, and then continue with d now at the
// newly vacated i. This process will terminate when we hit
// the null slot at the end of this run.
// The test is messy because we are using a circular table.
int r = hash(item, len);
// 將衝突元素移動到前一個衝突元素的位置
if ((i < r && (r <= d || d <= i)) || (r <= d && d <= i)) {
tab[d] = item;
tab[d + 1] = tab[i + 1];
tab[i] = null;
tab[i + 1] = null;
d = i;
}
}
}
與HashMap的比較
- 比較key時是“引用相等”。
- 支持null
- 所有的key和value都存儲到Object[]數組table中,並且key和value相鄰存儲,當出現哈希衝突時,會往下遍歷數組,直到找到一個空閒的位置。
- 加載因子爲2/3