背景:
最近处理的单个文件,大概有13GB,数量条数约5000万。一次性读人到内存需要选择合适的数据结构对其进行存储。本文对比boost::unordered_map 和 std::map
这两种数据结构在该使用情景下的效率。
代码:
#include "boost/unordered_map.hpp"
#include <iostream>
#include <map>
#include "time.h"
using namespace std;
int main()
{
{
time_t first_time = time(0);
boost::unordered_map<int, int> test_hash;
for (int i = 0; i < 50000000; i++)
{
test_hash.insert(std::pair<int, int>(i, i));
}
cout << test_hash.size() << endl;
time_t second_time = time(0);
cout << "The insert operate cost: " << second_time - first_time << endl;
for (int i = 0; i< 50000001; ++i)
{
boost::unordered_map<int, int>::iterator iter = test_hash.find(i);
if (iter == test_hash.end())
{
cout << "unordered map find the end!" << endl;
}
}
time_t third_time = time(0);
cout << "The find operate cost: " << third_time - second_time << endl;
}
{
time_t first_time = time(0);
std::map<int, int> test_hash;
for (int i = 0; i < 50000000; i++)
{
test_hash.insert(std::pair<int, int>(i, i));
}
cout << test_hash.size() << endl;
time_t second_time = time(0);
cout << "The insert operate cost: " << second_time - first_time << endl;
for (int i = 0; i< 50000001; ++i)
{
std::map<int, int>::iterator iter = test_hash.find(i);
if (iter == test_hash.end())
{
cout << "map find the end!" << endl;
}
}
time_t third_time = time(0);
cout << "The find operate cost: " << third_time - second_time << endl;
}
return 0;
}
运行结果如下所示:
50000000
The insert operate cost: 34
unordered map find the end!
The find operate cost: 15
50000000
The insert operate cost: 49
map find the end!
The find operate cost: 23
效率上:
boost::unordered_map (34s)插入比map(49s)快。
boost::unordered_map (15s)查找操作比map(23s)快。
内存空间占用上:
boost::unordered_map 内存占用26%。7.6GB*0.26=1.976GB。
map内存占用29%。7.6GB*0.29=2.2GB。
所以,在效率和内存占用上面,boost::unordered_map 都更具有优势。
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版权声明:本文为CSDN博主「JasonLiu1919」的原创文章,遵循CC 4.0 BY-SA版权协议,转载请附上原文出处链接及本声明。
原文链接:https://blog.csdn.net/ljp1919/article/details/50463761