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最近看到游戏中刷排行榜的问题，是用multiset实现的，想到以前面试的时候这种问题的答案都是用堆，于是自己测试了一下，完整代码如下：
#include <fstream>
#include <iostream>
#include <iterator>
#include <set>
#include <vector>
#include <algorithm>
#include <cstdlib>
#include <cstring>
using namespace std;
void print_help()
{
cout << "top [gen|set|heap1|heap2|heap3|test]" << endl;
}
//产生count个随机数
void gen(const char *dest, int count)
{
srand(time(NULL));
std::fstream fs(dest, std::fstream::trunc | std::fstream::out);
for(int i=0; i<count; ++i)
{
fs << rand() << endl;
}
fs.close();
}
//使用multiset来获得top n
void get_top_set(int n)
{
multiset<int> top;
fstream fs("sample.txt", fstream::in);
for(int t; fs >> t;)
{
top.insert(t);
if(top.size() > n)
top.erase(top.begin());
}
fs.close();
ostream_iterator<int> out_it(std::cout, ",");
copy(top.rbegin(), top.rend(), out_it);
cout << endl;
}
/** 使用STL提供的堆相关的函数获得top n, 这里依赖库的实现方式, 实际使用前需要进行测试
或者自行实现堆算法, 参考 https://blog.csdn.net/liuyuan185442111/article/details/45920979
pop_heap的gcc实现大概是先将first和last-1位置的值互换，这样first位置的值就是不对的了，
然后调用__adjust_heap将[first, last-1)调整为堆。
所以gcc的pop_heap实际上只需要[first,last-1)是一个合法的堆。*/
void get_top_heap1(int n)
{
fstream fs("sample.txt", fstream::in);
int top[n+2];
for(int i=0; i<n+1; ++i)
{
if(!(fs >> top[i])) return;
}
make_heap(top, top+n+1, greater<int>());
while(fs >> top[n+1])
{
pop_heap(top, top+n+2, greater<int>());
}
fs.close();
pop_heap(top, top+n+1, greater<int>());
sort_heap(top, top+n, greater<int>());
ostream_iterator<int> out_it(std::cout, ",");
copy(top, top+n, out_it);
cout << endl;
}
/** 与以上相比, 使用gcc内部的__adjust_heap函数
*/
void get_top_heap2(int n)
{
fstream fs("sample.txt", fstream::in);
int top[n+1];
for(int i=0; i<n+1; ++i)
{
if(!(fs >> top[i])) return;
}
make_heap(top, top+n+1, greater<int>());
for(int t; fs >> t;)
{
//取出堆的根节点, 将t作为新的根节点, 然后进行调整
//上面直接用pop_heap的话实际上是将top[n+1]作为t的存放处
__adjust_heap(top, 0, n+1, t, greater<int>());
}
fs.close();
pop_heap(top, top+n+1, greater<int>());
sort_heap(top, top+n, greater<int>());
ostream_iterator<int> out_it(std::cout, ",");
copy(top, top+n, out_it);
cout << endl;
}
/** 将操作抽象成一个模板类, 并对样本数量小于maxsize的情况做了处理
*/
template <typename Key, int maxsize, typename Cmp = std::greater<Key> >
class TopTable
{
int top[maxsize+1];
int size;
public:
TopTable():size(0){}
void Push(const Key &key)
{
if(size < maxsize+1)
{
top[size++] = key;
if(size == maxsize+1)
make_heap(top, top+size, Cmp());
return;
}
__adjust_heap(top, 0, maxsize+1, key, Cmp());
}
void Build(std::vector<Key> &table)
{
if(size == maxsize+1)
{
pop_heap(top, top+maxsize+1, Cmp());
sort_heap(top, top+maxsize, Cmp());
table.reserve(maxsize);
table.assign(top, top+maxsize);
}
else
{
sort(top, top+size);
table.reserve(size);
table.assign(top, top+size);
}
}
};
void get_top500()
{
TopTable<int, 500> table;
fstream fs("sample.txt", fstream::in);
for(int t; fs >> t; )
{
table.Push(t);
}
fs.close();
std::vector<int> top;
table.Build(top);
ostream_iterator<int> out_it(std::cout, ",");
copy(top.begin(), top.end(), out_it);
cout << endl;
}
int main(int argc, char **argv)
{
if(argc == 2)
{
if(strcmp(argv[1], "gen") == 0)
gen("sample.txt", 10000000);
else if(strcmp(argv[1], "set") == 0)
get_top_set(500);
else if(strcmp(argv[1], "heap1") == 0)
get_top_heap1(500);
else if(strcmp(argv[1], "heap2") == 0)
get_top_heap2(500);
else if(strcmp(argv[1], "heap3") == 0)
get_top500();
else if(strcmp(argv[1], "test") == 0)
{
clock_t t = clock();
cout << t << endl;
}
else
print_help();
return 0;
}
print_help();
return 0;
}
/**test 从10million个数据中取出top 500:
[eye@centos ~]$ time ./a.out heap3 > r3
real 0m2.613s
user 0m2.579s
sys 0m0.023s
[eye@centos ~]$ time ./a.out heap2 > r2
real 0m2.532s
user 0m2.486s
sys 0m0.026s
[eye@centos ~]$ time ./a.out heap1 > r1
real 0m2.771s
user 0m2.717s
sys 0m0.029s
[eye@centos ~]$ time ./a.out set > r0
real 0m4.070s
user 0m4.030s
sys 0m0.027s
剔除从文件读取消耗的时间, 使用heap带来的效率提升有两倍
*/参考：STL之heap