hashCode 方法是为了产生不同的 hash 值, 但是当两个对象的 hash 值一样时,会发生碰撞冲突
基本思想:当发生地址冲突的时候,按照某种方法继续探测哈希表中的其他存储单元,直到找到空位置为止;
测试代码:
public class Test1 {
//线性探测再散列
public static int[] m1(int[] arr){
if (arr==null || arr.length == 0){
return null;
}
int[] arr1 = new int[arr.length];
for (int i = 0;i<arr.length;i++){
int p = arr[i]%(arr1.length);
if (arr1[p]==0){
arr1[p] = arr[i];
}else {
for (int j = 1 ; j<5;j++){
int p1 = (p+j)%(arr1.length);
if (arr1[p1]==0){
arr1[p1] = arr[i];
}
}
}
}
return arr1;
}
//二次探测再散列
public static int[] m2(int[] arr){
if (arr==null || arr.length == 0){
return null;
}
int[] arr1 = new int[arr.length];
for (int i = 0;i<arr.length;i++){
int p = arr[i]%(arr1.length);
if (arr1[p]==0){
arr1[p] = arr[i];
}else {
for (int j = 1 ; j <= 5/2;j++){
int p1 = (p+j*j)%(arr1.length);
int p2 = (p-j*j)%(arr1.length);
if (p1<=arr.length && arr1[p1]==0){
arr1[p1] = arr[i];
}
if (p2>=0 && arr1[p2]==0){
arr1[p2] = arr[i];
}
}
}
}
return arr1;
}
//伪随机再散列
public static int[] m3(int[] arr){
if (arr==null || arr.length==0){
return null;
}
int[] arr1 = new int[arr.length];
for (int i = 0;i<arr.length;i++){
int p = arr[i]%(arr1.length);
if (arr1[p]==0){
arr1[p] = arr[i];
}else {
while (true){
int p1 = (int) ((p+arr.length*Math.random())%(arr1.length));
if (p1<=arr.length-1 && arr1[p1]==0){
arr1[p1] = arr[i];
break;
}
}
}
}
return arr1;
}
//数组输出函数
public static void arrayPrint(int[] arr){
if (arr == null){
System.out.println("数组为null");
}else {
for (int k = 0 ;k<arr.length;k++){
System.out.print(arr[k]+" ");
}
System.out.println();
}
}
public static void main(String[] args){
int[] arr = {13,45,34,56,33};
int[] arr1 = m1(arr);
int[] arr2 = m2(arr);
int[] arr3 = m3(arr);
arrayPrint(arr2);
arrayPrint(arr1);
arrayPrint(arr3);
}
}
其实 ThreadLocalMap 中的就用的开放地址法,不断的进行线性探测, 通过nextIndex()不断获取table上得槽位,直到遇到第一个为null的地方,此处也将是存放具体entry的位置。
private void set(ThreadLocal<?> key, Object value) {
// We don't use a fast path as with get() because it is at
// least as common to use set() to create new entries as
// it is to replace existing ones, in which case, a fast
// path would fail more often than not.
Entry[] tab = table;
int len = tab.length;
int i = key.threadLocalHashCode & (len-1);
for (Entry e = tab[i];
e != null;
e = tab[i = nextIndex(i, len)]) {
ThreadLocal<?> k = e.get();
if (k == key) {
e.value = value;
return;
}
if (k == null) {
replaceStaleEntry(key, value, i);
return;
}
}
tab[i] = new Entry(key, value);
int sz = ++size;
if (!cleanSomeSlots(i, sz) && sz >= threshold)
rehash();
}
所用公式 H(key) = (H(key) + di)mod m;其中i = 1、2、3.....k(k<m-1),H(key)为关键字key的直接hash地址;M为hash表的长度;
di为再次探测时的地址增量;根据di的不同取法,有不同的称呼;
基本思想:有多个不同的Hash函数,当发生冲突时,使用第二个,第三个,…,等哈希函数计算地址,直到无冲突。虽然不易发生聚集,但是增加了计算时间
基本思想:每个哈希表节点都有一个next指针,多个哈希表节点可以用next指针构成一个单向链表,被分配到同一个索引上的多个节点可以用这个单向链表连接起来 HashMap 中 hash 冲突的解决办法,就是链地址法, 如果当前桶上发生 hash 冲突,就,将当前值放到链表尾。
源码示例:
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)
n = (tab = resize()).length;
if ((p = tab[i = (n - 1) & hash]) == null)
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 {
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);
break;
}
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k))))
break;
p = e;
}
}
if (e != null) { // existing mapping for key
V oldValue = e.value;
if (!onlyIfAbsent || oldValue == null)
e.value = value;
afterNodeAccess(e);
return oldValue;
}
}
++modCount;
if (++size > threshold)
resize();
afterNodeInsertion(evict);
return null;
}
基本思想:将 hash 表为基本表和溢出表两部分,凡是和基本表冲突发生冲突的元素,一律填入溢出表。