1.整型哈希函数的设计
小范围正整数直接使用
小范围负整数整体进行偏移
大整数,通常做法是"模一个素数"
2.浮点型哈希函数的设计
转成整型进行处理
3.字符串哈希函数的设计
转成整型进行处理
![](https://img.haomeiwen.com/i14384674/bab58042a35ae7e7.png)
简单变形优化
![](https://img.haomeiwen.com/i14384674/ae17ba69896a13b0.png)
防止整型溢出优化
![](https://img.haomeiwen.com/i14384674/d6d0f39014f07842.png)
具体代码实现
![](https://img.haomeiwen.com/i14384674/d8fa9c70a97d2b17.png)
复合类型哈希函数的设计
转成整型进行处理
![](https://img.haomeiwen.com/i14384674/e021b123c195f7cb.png)
哈希函数的设计原则
![](https://img.haomeiwen.com/i14384674/98942f97c363547a.png)
哈希冲突的处理
链地址法
![](https://img.haomeiwen.com/i14384674/3a58ba1221e46b8a.png)
开放地址法之线性探测
![](https://img.haomeiwen.com/i14384674/a9797250251ead97.png)
开放地址法之平方探测
![](https://img.haomeiwen.com/i14384674/c8170151067c6bc2.png)
开放地址法之二次哈希
![](https://img.haomeiwen.com/i14384674/5c926b3b0eff58e3.png)
哈希表的动态空间处理
![](https://img.haomeiwen.com/i14384674/0aae9d8ee5546ed2.png)
实现哈希表的业务逻辑
import java.util.TreeMap;
public class HashTable<K, V> {
private final int[] capacity
= {53, 97, 193, 389, 769, 1543, 3079, 6151, 12289, 24593,
49157, 98317, 196613, 393241, 786433, 1572869, 3145739, 6291469, 12582917,
25165843, 50331653, 100663319, 201326611, 402653189, 805306457, 1610612741};
private static final int upperTol = 10;
private static final int lowerTol = 2;
private int capacityIndex = 0;
private TreeMap<K, V>[] hashTable;
private int M;
private int size;
public HashTable() {
this.M = capacity[capacityIndex];
this.size = 0;
hashTable = new TreeMap[M];
for (int i = 0; i < M; i++) {
hashTable[i] = new TreeMap<>();
}
}
private int hash(K key) {
return key.hashCode() & 0x7fffffff % M;
}
public void add(K key, V value) {
TreeMap<K, V> map = hashTable[hash(key)];
if (map.containsKey(key)) {
map.put(key, value);
} else {
map.put(key, value);
size++;
if (size >= upperTol * M && capacityIndex + 1 < capacity.length) {
capacityIndex++;
resize(capacity[capacityIndex]);
}
}
}
public V remove(K key) {
TreeMap<K, V> map = hashTable[hash(key)];
V ret = null;
if (map.containsKey(key)) {
ret = map.remove(key);
size--;
if (size < lowerTol * M && capacityIndex - 1 >= 0) {
capacityIndex--;
resize(capacity[capacityIndex]);
}
}
return ret;
}
public void set(K key, V value) {
TreeMap<K, V> map = hashTable[hash(key)];
if (!map.containsKey(key)) {
throw new IllegalArgumentException(key + "doesn't exist.");
} else {
map.put(key, value);
}
}
public boolean contains(K key) {
return hashTable[hash(key)].containsKey(key);
}
public V get(K key) {
return hashTable[hash(key)].get(key);
}
private void resize(int newM) {
TreeMap<K, V>[] newHashTable = new TreeMap[newM];
for (int i = 0; i < newM; i++) {
newHashTable[i] = new TreeMap<>();
}
int oldM = M;
M = newM;
for (int i = 0; i < oldM; i++) {
TreeMap<K, V> map = hashTable[i];
for (K key : map.keySet()) {
newHashTable[hash(key)].put(key, map.get(key));
}
}
this.hashTable = newHashTable;
}
}
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