关于c++ STL map 和 unordered_map 的效率的对比测试

本文采用在随机读取和插入的情况下测试map和unordered_map的效率

笔者的电脑是台渣机，现给出配置信息

处理器 ： Intel Pentium(R) CPU G850 @ 2.90GHz × 2

内存 ： 7.7GiB

操作系统 ： Ubuntu 20.04.2 LTS 64位(Noi Linux 2.0)

由于在数据量小的情况下二者时间差异微乎其微，测试范围从1e4开始到1e7，map unordered_map存储为 int, int二元组，int三元组

单 int测试

插入范围	查询范围	map插入时间	map查询时间	unordered_map插入时间	unordered_map查询时间
10000	10000	11.95ms	10.268ms	15.184ms	5.009ms
100000	100000	113.374ms	134.365ms	200.852ms	79.029ms
1000000	1000000	1606.66ms	1819.2ms	2603.46ms	862.877ms
10000000	10000000	21688.5ms	25461.7ms	33973.7ms	9484.45ms

#include <bits/stdc++.h>

using namespace std;

int main()
{
    for(int n = 1e4, m = 1e4; n <= 1e9, m <= 1e9; n *= 10,m *= 10)
    {
        cout << n << "|" << m ;
        srand(n);
        int t0 = clock();
        map <int ,int> M;
        for(int i = 1; i <= n; i++)
        {
            M[rand()] = i;
        }
        cout << "| " << (double)(clock() - t0) / 1000 << "ms ";
        unsigned sum = 0;
        t0 = clock();
        for(int i = 1; i <= m; i++)
        {
            sum += M[rand()];
        }
        cout << "| " << (double)(clock() - t0) / 1000 << "ms ";
        srand(n);
        unordered_map <int, int> U;
        for(int i = 1; i <= n; i++)
        {
            U[rand()] = i;
        }
        cout << "| " << (double)(clock() - t0) / 1000 << "ms ";
        sum = 0;
        t0 = clock();
        for(int i = 1; i <= m; i++)
        {
            sum += U[rand()];
        }
        cout << "| " << (double)(clock() - t0) / 1000 << "ms |" << endl;
    }
    return 0;
}

二元组测试

插入范围	查询范围	map插入时间	map查询时间	unordered_map插入时间	unordered_map查询时间
10000	10000	10.617ms	11.523ms	16.301ms	5.14ms
100000	100000	122.489ms	141.413ms	195.278ms	70.122ms
1000000	1000000	1792.69ms	2173.48ms	2879.21ms	783.437ms
10000000	10000000	25017.8ms	28777.1ms	36499.8ms	8666.73ms

#include <bits/stdc++.h>

using namespace std;
struct PII
{
    int x, y;

    bool operator ==(const PII b) const
    {
        return x == b.x && y == b.y;
    }

    bool operator <(const PII b) const
    {
        return x != b.x ? x < b.x : y < b.y;
    }

};

struct hashPII
{
    size_t operator()(const PII &p) const
    {
        return hash<int>()(p.x) ^ hash<int>()(p.y);
    }
};

int main()
{
    for(int n = 1e4, m = 1e4; n <= 1e9, m <= 1e9; n *= 10,m *= 10)
    {
        cout << n << "|" << m ;
        srand(n);
        int t0 = clock();
        map <PII ,int> M;
        for(int i = 1; i <= n; i++)
        {
            M[{rand(), rand()}] = i;
        }
        cout << "| " << (double)(clock() - t0) / 1000 << "ms ";
        unsigned sum = 0;
        t0 = clock();
        for(int i = 1; i <= m; i++)
        {
            sum += M[{rand(), rand()}];
        }
        cout << "| " << (double)(clock() - t0) / 1000 << "ms ";
        srand(n);
        unordered_map <PII, int, hashPII> U;
        for(int i = 1; i <= n; i++)
        {
            U[{rand(), rand()}] = i;
        }
        cout << "| " << (double)(clock() - t0) / 1000 << "ms ";
        sum = 0;
        t0 = clock();
        for(int i = 1; i <= m; i++)
        {
            sum += U[{rand(), rand()}];
        }
        cout << "| " << (double)(clock() - t0) / 1000 << "ms |" << endl;
    }
    return 0;
}

三元组测试

插入范围	查询范围	map插入时间	map查询时间	unordered_map插入时间	unordered_map查询时间
10000	10000	9.265ms	10.061ms	14.415ms	4.325ms
100000	100000	127.82ms	141.59ms	196.931ms	70.29ms
1000000	1000000	1700.73ms	1971.21ms	2685.96ms	782.957ms

O2

单 int测试

插入范围	查询范围	map插入时间	map查询时间	unordered_map插入时间	unordered_map查询时间
10000	10000	2.103ms	2.617ms	3.775ms	1.261ms
100000	100000	46.243ms	67.461ms	86.591ms	34.024ms
1000000	1000000	822.828ms	1056.85ms	1412.39ms	422.122ms
10000000	10000000	13690.2ms	16854.1ms	20994.4ms	4903.84ms

二元组测试

插入范围	查询范围	map插入时间	map查询时间	unordered_map插入时间	unordered_map查询时间
10000	10000	2.463ms	3.461ms	4.908ms	2.209ms
100000	100000	61.531ms	89.114ms	127.359ms	49.821ms
1000000	1000000	1301.74ms	1692.79ms	2184.67ms	585.508ms
10000000	10000000	21245.7ms	24632.5ms	30906.3ms	7312.4ms

理论复杂度

		map<int, int>	unordered_map<int, int>
插入		\(O(log( n ) )\)	\(O(log(n / m)\) m = 桶数
读取		\(O(log( n ) )\)	\(O(1) ？\)

可以发现随着数据量的增大unordered_map在插入上由于冲突，性能是不及map的插入\(O(logn)\)的，但是其优秀的\(O(1) ?\)读取具有很大的性能优势