ue7*_*e7m 4 c++ performance dictionary unordered-map vector
我写了一个小程序,用两个样本数据创建了两百万张地图的向量,然后查询一些值。
我知道我可以在此时使用数据库,但是我只是在四处探索以实现性能优化。
代码:
#include <iostream>
#include <vector>
#include <unordered_map>
#include <map>
#include <string>
#include <chrono>
using namespace std;
static int NUM_OF_MAPS = 2 * 1000 * 1000;
void buildVector(vector<unordered_map <string, int>> &maps);
void find(string key, int value, vector<unordered_map <string, int>> &maps);
int main() {
auto startPrg = chrono::steady_clock::now();
vector<unordered_map <string, int>> maps;
buildVector(maps);
for (int i = 0; i < 10; i++) {
string s(1, 'a'+ i);
find(s, i, maps);
}
auto endPrg = chrono::steady_clock::now();
cout << "program duration: " << chrono::duration_cast<chrono::microseconds>(endPrg - startPrg).count() / 1000.0 << " ms" << endl;
return 0;
}
void find(string key, int value, vector<unordered_map <string, int>> &maps) {
auto start = chrono::steady_clock::now();
int matches = 0;
for (unordered_map <string, int> &map : maps) {
unordered_map<string,int>::const_iterator got = map.find(key);
if (got != map.end() && got->second == value) {
matches++;
}
}
auto end = chrono::steady_clock::now();
cout << matches << " matches for " << key << " = " << value << " in " << chrono::duration_cast<chrono::microseconds>(end - start).count() / 1000.0 << " ms" << endl;
}
void buildVector(vector<unordered_map <string, int>> &maps) {
auto start = chrono::steady_clock::now();
maps.reserve(NUM_OF_MAPS);
int entryCounter = 0;
unordered_map <string, int> map;
for (int i = 0; i < NUM_OF_MAPS; i++) {
map["a"] = entryCounter++;
map["b"] = entryCounter++;
map["c"] = entryCounter++;
map["d"] = entryCounter++;
map["e"] = entryCounter++;
map["f"] = entryCounter++;
maps.push_back(map);
entryCounter %= 100;
}
auto end = chrono::steady_clock::now();
cout << "build vector: " << chrono::duration_cast<chrono::microseconds>(end - start).count() / 1000.0 << " ms (" << maps.size() << ")" << endl;
}
Run Code Online (Sandbox Code Playgroud)
输出:
build vector: 697.381 ms (2000000)
40000 matches for a = 0 in 67.873 ms
40000 matches for b = 1 in 64.176 ms
40000 matches for c = 2 in 60.484 ms
40000 matches for d = 3 in 68.102 ms
40000 matches for e = 4 in 62.71 ms
40000 matches for f = 5 in 65.723 ms
0 matches for g = 6 in 64.407 ms
0 matches for h = 7 in 45.401 ms
0 matches for i = 8 in 65.307 ms
0 matches for j = 9 in 64.371 ms
program duration: 1326.42 ms
Run Code Online (Sandbox Code Playgroud)
为了比较速度,我在Java中做了同样的操作,得到了以下结果:
build vector: 2536.971578 ms (2000000)
40000 matches for a = 0 in 59.293339 ms
40000 matches for b = 1 in 56.306123 ms
40000 matches for c = 2 in 53.503208 ms
40000 matches for d = 3 in 51.174979 ms
40000 matches for e = 4 in 50.967731 ms
40000 matches for f = 5 in 53.68969 ms
0 matches for g = 6 in 41.927401 ms
0 matches for h = 7 in 36.160645 ms
0 matches for i = 8 in 33.535616 ms
0 matches for j = 9 in 36.56883 ms
program duration: 3016.979919 ms
Run Code Online (Sandbox Code Playgroud)
尽管C ++创建数据的速度要快得多,但查询部分的速度却非常慢(与Java相比)。在这方面,C ++有什么办法可以击败Java?
Java代码:
static int NUM_OF_MAPS = 2 * 1000 * 1000;
public static void run() {
long startPrg = System.nanoTime();
List<Map<String,Integer>> maps = new ArrayList<>(NUM_OF_MAPS);
buildVector(maps);
for (int i = 0; i < 10; i++) {
String s = String.valueOf((char)('a' + i));
find(s, i, maps);
}
long endPrg = System.nanoTime();
System.out.println("program duration: " + (endPrg - startPrg) / 1000000.0 + " ms");
}
static void find(String key, Integer value, List<Map<String,Integer>> maps) {
long start = System.nanoTime();
int matches = 0;
for (Map<String,Integer> map : maps) {
Integer got = map.get(key);
if (got != null && got.equals(value)) {
matches++;
}
}
long end = System.nanoTime();
System.out.println(matches + " matches for " + key + " = " + value + " in " + (end - start) / 1000000.0 + " ms");
}
static void buildVector(List<Map<String,Integer>> maps) {
long start = System.nanoTime();
int entryCounter = 0;
Map<String,Integer> map = new HashMap<>();
for (int i = 0; i < NUM_OF_MAPS; i++) {
map.put("a", entryCounter++);
map.put("b", entryCounter++);
map.put("c", entryCounter++);
map.put("d", entryCounter++);
map.put("e", entryCounter++);
map.put("f", entryCounter++);
maps.add(new HashMap<>(map));
entryCounter %= 100;
}
long end = System.nanoTime();
System.out.println("build vector: " + (end - start) / 1000000.0 + " ms (" + maps.size() + ")");
}
Run Code Online (Sandbox Code Playgroud)
编辑:Sry复制了Java代码两次,而不是C ++代码。
C ++代码不是太慢。最好对Java代码进行散列优化。
unordered_map<string,int>::const_iterator got = map.find(key)
。在方面hash(string) -> int
的计算,你在C find方法++为O(NUM_OF_MAPS)
,而在Java是O(1)
。