选择键值,冲突的时候采取不同的策略
散列函数:
简单的散列函数:
1 int hash(const string & key,int tableSize)
2 {
3 int hashVal = 0;
4 for(int i = 0; i < key.length();++i)
5 {
6 hashVal + = key[i];
7 }
8 return hashVal % tableSize;
9 }
比较好的散列函数:
1 int hash( const string & key,int tableSize )
2 {
3 int hashVal = 0;
4 for(int i = 0; i <key.length();++i)
5 {
6 hashVal = 37*hashVal + key[i];
7 }
8 hashVal %= tableSize;
9 if(hashVal < 0)
10 hashVal +=tableSize;
11
12 return hashVal;
13 }
键的长度和性质 影响选择。
分离链接法
分离链接散列表的类构架
1 template <typename HashedObj>
2 class HashTable
3 {
4 public:
5 explicit HashTable( int size = 101);
6 bool contains (const HashedObj & x) const;
7 void makeEmpty();
8 void insert(const HashedObj & x);
9 void remove(const HashedObj & x);
10 private:
11 vector<list<HashedObj> > theLists;
12 int currentSize;
13 void rehash();
14 int myhash( const HashedObj & x) const;
15 };
16 int hash(const string & key);
17 int hash(int key);
散列表myhash的成员函数:
1 int myhash(const HashedObj & x) const
2 {
3 int hashVal = hash(x);
4 hashVal %= theLists.size();
5 if(hashVal < 0)
6 hashVal += theLists.size();
7 return hashVal;
8 }
使用name成员为键,提供的散列函数实例:
1 class Employee
2 {
3 public:
4 const string & getName() const
5 {
6 return name;
7 }
8 bool operator==( const Employee & rhs ) const
9 {
10 return getName() == rhs.getName();
11 }
12 bool operator!=(const Employee & rhs) const
13 {
14 return !(*this == rhs);
15 }
16 private:
17 string name;
18 double salary;
19 int seniority;
20 };
21 int hash(const Employee & item)
22 {
23 return hash(item.getName());
24 }
实现makeEmpty contains remove:
1 void makeEmpty()
2 {
3 for(int i =0;i<theLists.size();i++)
4 theLists[i].clear();
5 }
6 bool contains(const HashedObj & x) const
7 {
8 const list<HashedObj> & whichList = theLists[myhash(x)];
9 return find(whichList.begin(),whichList.end(),x)!=whichList.end();
10 }
11 bool remove(const HashedObj & x) const
12 {
13 list<HashedObj> & whichList = theLists[myhash(x)];
14 list<HashedObj>::iterator itr = find(whichList.begin(),whichList.end(),x);
15
16 if(itr == whichList.end())
17 return false;
18
19 whichList.erase(itr);
20 --currentSize;
21 return true;
22 }
分离散列表的insert实例
1 bool insert(const HashedObj & x)
2 {
3 list<HashedObj> & whichList = theLists[myhash(x)];
4 if(find(whichList.begin(),whichList.end(),x)!=whichList.end())
5 return false;
6 whichList.push_back(x);
7 if(++currentSize > theLists.size())
8 rehash();
9
10 return true;
11 }
装填因子:散列表中的元素个数 与 散列表大小的 比值
执行一次查找所需的时间:计算散列函数值所需要的常数时间加上遍历表所用的时间
不使用链表的散列表:
当冲突发生时,直接寻找下一单元
<线性探测>
<平方探测>
使用探测策略的散列表的类接口
1 template <typename HashedObj>
2 class HashedObj
3 {
4 public:
5 explicit HashTable(int size = 101);
6 bool contains(const HashedObj & x) const;
7 void makeEmpty();
8 bool insert(const HashedObj & x);
9 bool remove(const HashedObj & x);
10 enum EntryType{ACTIVE,EMPTY,DELETED};
11 private:
12 struct HashEntry
13 {
14 HashedObj element;
15 EntryType info;
16
17 HashEntry(const HashedObj & e = HashedObj(),EntryType i = EMPTY):element(e),info(i){}
18 };
19 vector<HashEntry> array;
20 int currentSize;
21 bool isActive(int currentPos) const;
22 int findPos(const HashedObj & x) const;
23 void rehash();
24 int myhash(const HashedObj & x) const;
25 };
初始化平方探测散列表
1 explicit HashTable(int size = 101):array(nextPrime(size))
2 {
3 makeEmpty();
4 }
5 void makeEmpty()
6 {
7 currentSize = 0;
8 for(int i = 0 ; i < array.size(); i++)
9 array[i].info = EMPTY;
10 }
使用平方探测进行散列的contains findPos isActive
1 bool contains(const HashedObj & x) const
2 {
3 return isActive(findPos(x));
4 }
5 int findPos(const HashedObj & x) const
6 {
7 int offset = 1;
8 int currentPos = myhash(x);
9
10 while(array[currentPos].info != EMPTY && array[currentPos].element != x)
11 {
12 currentPos += offset;
13 offset += 2;
14 if(currentPos >= array.size())
15 currentPos -= array.size();
16 }
17 return currentPos;
18 }
19 bool isActive(int currentPos) const
20 {
21 return array[currentPos].info == ACTIVE;
22 }
使用平方探测的insert remove
bool insert( const HashedObj & x)
{
int currentPos = findPos(x);
if(isActive( currentPos ))
return false;
array[currentPos] = HashEntry(x,ACTIVE);
if(++currnetSize>array.size()/2)
rehash();
}
bool remove(const HashedObj & x)
{
int currentPos = findPos(x);
if(!isActive(currentPos))
return false;
array[currentPos].info = DELETED;
return true;
}
<双散列>
对分离散列表的再散列
1 void rehash()
2 {
3 vector<HashEntry> oldArray = array;
4 array.size(nextPrime(2*oldArray.size()));
5 for(int j = 0; j < array.size(); j++)
6 {
7 array[j].info = EMPTY;
8 }
9 currentSize = 0;
10 for(int i = 0; i < array.size(); i++)
11 {
12 if(oldArray[i].info == ACTIVE)
13 insert(oldArray[i].element);
14 }
15 }
对探测散列表的再散列
1 void rehash()
2 {
3 vector<list<HashedObj> > oldLists = theLists;
4 theLists.resize( nextPrime( 2*theLists.size() ) );
5 for(int j = 0; j < theLists.size(); j++)
6 {
7 theLists[j].clear();
8 }
9 currentSize = 0;
10 for(int i = 0; i < oldLists.size(); i++)
11 {
12 list<HashedObj>::iterator itr = oldLists[i].begin();
13 while( itr != oldLists[i].end( ) )
14 insert(*itr++);
15 }
16 }
作者:xingoo