In the following example a std::map structure is filled with 26 values from A - Z (for key) and 0 – 26 for value. The time taken (on my system) to lookup the last entry (10000000 times) is roughly 250 ms for the vector, and 125 ms for the map. (I compiled using release mode, with O3 option turned on for g++ 4.4)
But if for some odd reason I wanted better performance than the std::map, what data structures and functions would I need to consider using?
I apologize if the answer seems obvious to you, but I haven't had much experience in the performance critical aspects of C++ programming.
UPDATE:
This example is rather trivial and hides the true complexity of what I'm trying to achieve. My real world project is a simple scripting language that uses a parser, data tree, and interpreter (instead of a VM stack system). I need to use some kind of data structure (perhaps map) to store the variables names created by script programmers. These are likely to be pretty randomly named, so I need a lookup method that can quickly find a particular key within a (probably) fairly large list of names.
#include <ctime>
#include <map>
#include <vector>
#include <iostream>
struct mystruct
{
char key;
int value;
mystruct(char k = 0, int v = 0) : key(k), value(v) { }
};
int find(const std::vector<mystruct>& ref, char key)
{
for (std::vector<mystruct>::const_iterator i = ref.begin(); i != ref.end(); ++i)
if (i->key == key) return i->value;
return -1;
}
int main()
{
std::map<char, int> mymap;
std::vector<mystruct> myvec;
for (int i = 'a'; i < 'a' + 26; ++i)
{
mymap[i] = i - 'a';
myvec.push_back(mystruct(i, i - 'a'));
}
int pre = clock();
for (int i = 0; i < 10000000; ++i)
{
find(myvec, 'z');
}
std::cout << "linear scan: milli " << clock() - pre << "\n";
pre = clock();
for (int i = 0; i < 10000000; ++i)
{
mymap['z'];
}
std::cout << "map scan: milli " << clock() - pre << "\n";
return 0;
}
