Said front
Working processes described herein containing a handwritten generic HashMap <K, V> is a simplified version, only the HashMap appreciated get () and put () method, the non-Java source code.
get (K key) principle
- First calculate the hash value of the key corresponding to
int hash = key.hashCode(); //此处的 hashCode() 方法为 Object对象 所属方法，默认都有 //自定义的类需要覆写该方法 - Hash value is out of range of the array for processing
hash = (hash >>> 16)^hash;//java内部自做的优化，为了使hash值更加均衡，减少冲突 int index = hash & (table.length - 1);//对下标进行合理化，以免下标越界 //这样做可以使index在数组长度范围内的原因或者一个前提是，这里的数组的长度一定是2的n次方， //这样table.length - 1 在二进制情况下，除最高位，其余低位为一定是1，用hash与这样的一个数进行与操作 //即只保留了hash的二进制的低位，就会使hash的范围一定小于数组长度 - Linked list to find the first node is located according to the correct hash value (index value)
Entry<K,V> node = table[index]; - Traverse the list, if the key values are equal, the value corresponding to the return value, otherwise null
while(node != null){
if(node.key.equals(key)){
return node.value;
}
node = node.next;
}-
Concrete realization of get (K key)
@Override
public V get(K key) {
int hash = key.hashCode();
hash = (hash >>> 16)^hash;//java内部自做的优化，为了使hash值更加均衡
int index = hash & (table.length - 1);
Entry<K,V> node = table[index];
while(node != null){
if(node.key.equals(key)){
return node.value;
}
node = node.next;
}
return null;
}put(K key,V value) 原理
- First calculate the hash value of the key corresponding to
- Hash value is out of range of the array for processing
- Linked list to find the first node is located according to the correct hash value (index value)
- If the first node == null, a new node is directly assigned to the array position
Entry<K,V> newNode = new Entry<>(key,value); table[index] = newNode; - Otherwise, traverse the list to find the node is equal to the key, and the value of the replacement value, returns the old value value
Entry<K,V> pre = null;//用来追踪该段链表的最后一个结点，为尾插做准备，如果采用头插法，则不需要 while(node != null){ if(node.key.equals(key)){ V oldValue = node.value; node.value = value; return oldValue; } pre = node; node = node.next; } - If not found, interpolation using the tail (1.8) / interpolation head (1.7) and create a new node is inserted into the list
pre.next = new Entry<>(key,value); - The number of memory elements +1 !!!
- Check whether the capacity is needed (to be completely re-calculated hash value, because the array length changes)
1) Expansion reasons: To reduce hash conflicts, reduce the collision rate (when inserting a new key, encounter probability of collisions)
2) load length factor = the number of all the key / array
3) conflict and load factor positively correlated! Therefore, in order to reduce the collision rate, length of the array may be changed!
4) do: and by calculating a load factor of 0.75) and expansion factor (compared predeterminedif((double) size / table.length >= 0.75 ){ resize(); }
private void resize(){
/**
* 1.创造新数组，长度为原数组的2倍
* 2.遍历原数组，找到每一条链表的头节点
* 3.遍历每一条链表，新建结点并将节点采用头插法插入到新数组中
*
*/
Entry<K,V>[] newTable = new Entry[table.length * 2];
for(int i = 0; i < table.length; i++){
Entry<K,V> node = table[i];
while(node != null){
Entry<K,V> newNode = new Entry<>(node.key,node.value);
int hash = node.key.hashCode();
hash = (hash >>> 16) ^ hash;
int index = hash ^ (newTable.length - 1);
//使用头插，尾插也可以
newNode.next = newTable[index];
newTable[index] = newNode;
node = node.next;
}
}
}-
Embodied put (K key, V value)
@Override
public V put(K key, V value) {
int hash = key.hashCode();
hash = (hash >>> 16)^hash;//java内部自做的优化语句，为了使hash值更加均衡
int index = hash & (table.length - 1);
Entry<K,V> node = table[index];
if(node == null){
Entry<K,V> newNode = new Entry<>(key,value);
table[index] = newNode;
}else{
Entry<K,V> pre = null;
while(node != null){
if(node.key.equals(key)){
V oldValue = node.value;
node.value = value;
return oldValue;
}
pre = node;
node = node.next;
}
pre.next = new Entry<>(key,value);
}
size++;
if((double) size / table.length >= LOAD_FACTOR_THRESHOLD ){
resize();
}
return null;
}Embodied HashMap <K, V>
package advance_ds.hashmap;
//接口
public interface Map<K,V> {
V get(K key);
V put(K key,V value);
}
/**
* @author Maria
* @program JavaDaily
* @date 2020/3/21 14:51
*/
public class HashMap<K,V> implements Map<K,V> {
//链表的节点类
private static class Entry<K,V>{
K key;
V value;
Entry<K,V> next;
public Entry(K key,V value){
this.key = key;
this.value = value;
}
}
//基本存储方式：数组
private Entry<K,V>[] table = new Entry[16];
//存储的元素的个数
private int size = 0;
//扩容因子
private static final double LOAD_FACTOR_THRESHOLD = 0.75;
@Override
public V get(K key) {
/**
* 1.先计算出key对应的hash值
* 2.对超出数组范围的hash值进行处理
* 3.根据正确的hash值（下标值）找到所在的链表的头结点
* 4.遍历链表，如果key值相等，返回对应的value值,否则返回null
*/
int hash = key.hashCode();
hash = (hash >>> 16)^hash;//java内部自做的优化，为了使hash值更加均衡
int index = hash & (table.length - 1);
Entry<K,V> node = table[index];
while(node != null){
if(node.key.equals(key)){
return node.value;
}
node = node.next;
}
return null;
}
@Override
public V put(K key, V value) {
/**
* 1.先计算出key对应的hash值
* 2.对超出数组范围的hash值进行处理
* 3.根据正确的hash值（下标值）找到所在的链表的头结点
* 4.如果头结点==null，直接将新结点赋值给数组的该位置
* 5.否则，遍历链表，找到key相等的节点，并进行value值的替换，返回旧的value值
* 6.如果没有找到，采用尾插法（1.8）/头插法（1.7）创建新结点并插入到链表中
* 7.将存储元素数量+1
* 8.校验是否需要扩容(需要全部重新计算hash值，因为数组长度改变了)
* 扩容原因：为了减少hash冲突，冲突率：插入一个新的key时，会遇到冲突的概率
* 负载因子=所有key的数量/数组的长度
* 冲突率和负载因子成正相关！因此为了降低冲突率，可改变数组的长度！
* 具体操作：通过计算负载因子并与扩容因子进行比较
*/
int hash = key.hashCode();
hash = (hash >>> 16)^hash;//java内部自做的优化语句，为了使hash值更加均衡
int index = hash & (table.length - 1);
Entry<K,V> node = table[index];
if(node == null){
Entry<K,V> newNode = new Entry<>(key,value);
table[index] = newNode;
}else{
Entry<K,V> pre = null;
while(node != null){
if(node.key.equals(key)){
V oldValue = node.value;
node.value = value;
return oldValue;
}
pre = node;
node = node.next;
}
pre.next = new Entry<>(key,value);
}
size++;
if((double) size / table.length >= LOAD_FACTOR_THRESHOLD ){
resize();
}
return null;
}
private void resize(){
/**
* 1.创造新数组，长度为原数组的2倍
* 2.遍历原数组，找到每一条链表的头节点
* 3.遍历每一条链表，新建结点并将节点采用头插法插入到新数组中
*
*/
Entry<K,V>[] newTable = new Entry[table.length * 2];
for(int i = 0; i < table.length; i++){
Entry<K,V> node = table[i];
while(node != null){
Entry<K,V> newNode = new Entry<>(node.key,node.value);
int hash = node.key.hashCode();
hash = (hash >>> 16) ^ hash;
int index = hash ^ (newTable.length - 1);
//使用头插，尾插也可以
newNode.next = newTable[index];
newTable[index] = newNode;
node = node.next;
}
}
}
}
Write a class to test the code
package advance_ds.hashmap;
import java.util.Objects;
/**
* @author Maria
* @program JavaDaily
* @date 2020/3/21 21:29
*/
public class Person {
private String name;
private int age;
private int gender;
//自动生成的
@Override
public boolean equals(Object o) {
if (this == o) return true;
if (o == null || getClass() != o.getClass()) return false;
Person person = (Person) o;
return age == person.age &&
Objects.equals(name, person.name) &&
Objects.equals(gender, person.gender);
}
//自动生成的
@Override
public int hashCode() {
return Objects.hash(name, age, gender);
}
public static void main(String[] args) {
Person p1 = new Person();
p1.name = "p1";
p1.age = 18;
p1.gender = 0;
Person p2 = new Person();
p2.name = "p1";
p2.age = 18;
p2.gender = 0;
HashMap<Person,Integer> map = new HashMap<>();
map.put(p1,108);
System.out.println(map.get(p2));//结果为108，成功取出！因为key对应的hash相等
}
}