CODEWITHSUNDEEP
c++dictionaryhashmapunordered-map
hythloday
hythloday

Reputation: 103

Why hash_map and unordered_map on my machine are extremely slow?

I tested them with this code (on Visual Studio 2010 sp1):

#include <ctime>
#include <iostream>
#include <map>
#include <unordered_map>
#include <hash_map>

int main()
{ 
    clock_t time;
    int LOOP = (1 << 16);
    std::map<int, int> my_map;
    std::unordered_map<int, int> map_unordered_map;
    std::hash_map<int, int> my_hash_map;

    time = clock();
    for (int i = 0; i != LOOP; ++i)
    {
        my_map[i] = i;
    }
    std::cout << "map: " << ((double)(clock() - time) / CLOCKS_PER_SEC) << std::endl;

    time = clock();
    for (int i = 0; i != LOOP; ++i)
    {
        map_unordered_map[i] = i;
    }
    std::cout << "unordered_map: " << ((double)(clock() - time) / CLOCKS_PER_SEC) << std::endl;

    time = clock();
    for (int i = 0; i != LOOP; ++i)
    {
        my_hash_map[i] = i;
    }
    std::cout << "hash_map: " << ((double)(clock() - time) / CLOCKS_PER_SEC) << std::endl;

    system("PAUSE");
    return EXIT_SUCCESS;
}

And the result are so strange:

In DEBUG: map: 0.289 unordered_map: 10.738 hash_map: 10.58 Press any key to continue . . .

In RELEASE: map: 0.101 unordered_map: 0.463 hash_map: 0.429 Press any key to continue . . .

Upvotes: 4

Views: 2080

Answers (2)

Jens Agby
Jens Agby

Reputation: 410

This is an example of the amortized vs worst case cost of an algorithm.

std::map uses a red-black tree that has a O(logN) insert complexity.
std::hash_map uses a hash table that has a O(1) amortized insert complexity.

However, the hash table has a worst case complexity of O(N) when it has to resize the table and rehash the table.

In your case you end up doing a lot of rehashing, so the hash table insert is hitting it's worst case enough that the tree insert becomes faster - O(N) > O(logN).

If you init the hash_map with a large enough table then the hash table will never hit it's worst case and it will be faster then the tree - O(1) < O(logN).

Upvotes: 1

Jerry Coffin
Jerry Coffin

Reputation: 490048

  1. You're only inserting 65536 items in each map -- not large enough for the difference between O(log N) and O(1) to mean a whole lot.
  2. You're only inserting items, not doing any searching afterwards.
  3. Your keys are all contiguous integers in increasing order -- doesn't fit how any map will typically be used.

Bottom line: this isn't likely to tell you much about the data structures in question.

Upvotes: 6

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