TL;DR↵
------↵
The Policy Hash Table has 3-6x faster insertion/deletion and 3-10x increase for writes/reads. As far as I can tell, there are no downsides. The policy hash table (specifically the open-addressing version), beats out unordered_map in all my benchmarks.↵
[cut]↵
Background↵
------↵
I've often been irritated by how slow unordered_map is in C++. Too often, I have something that runs fast enough in terms of complexity, but the constant factor from unordered_map slows down the solution too much. Yesterday though, after using the useful order statistics tree from https://codeforces.com/blog/entry/11080, I was curious if there were any other useful data structures hiding in the Policy STL. And lo and behold, I found a hash table.↵
↵
Benchmarks↵
------------------↵
Well, enough backstory, let's look at some numbers.↵
All benchmarks below are compiled with C++14 -O2.↵
↵
~~~~~↵
unordered_maplinear insertion: 0.689846↵
cc_hash_tablelinear insertion: 0.408233↵
gp_hash_tablelinear insertion: 0.256131↵
↵
unordered_maplinear read/write: 1.69783↵
cc_hash_tablelinear read/write: 0.202474↵
gp_hash_tablelinear read/write: 0.26842↵
↵
unordered_maprandom insertion: 2.90184↵
cc_hash_tablerandom insertion: 3.15129↵
gp_hash_tablerandom insertion: 0.56553↵
↵
unordered_maprandom read/write: 2.02336↵
cc_hash_tablerandom read/write: 0.333415↵
gp_hash_tablerandom read/write: 0.403486↵
~~~~~↵
↵
While for linear insertions, the policy hash table gives modest improvements, the policy hash table blows the unordered_map out of the water when it comes to reads/writes. These are order of magnitude improvements that make hash tables usable when they previously weren't.↵
Example↵
------↵
Benchmarks of course, don't always reflect the real world. So here's an example of it allowing a solution to be accepted that TLE's with unordered_map.↵
↵
Example problem (5000 ms time limit): http://codeforces.com/contest/264/problem/C ↵
Solution with unordered_map: http://codeforces.com/contest/264/submission/40542899 (TLE on test case 8) ↵
Solution with policy hash table directly substituted in: http://codeforces.com/contest/264/submission/40573491 (TLE on test case 26) ↵
Solution with unordered_map, rewritten to not use clears:↵
http://codeforces.com/contest/264/submission/40590437 (TLE on test case 26)↵
Solution with policy hash table and rewritten to not use clears: http://codeforces.com/contest/264/submission/40574196 (AC with max time of 3180 ms) ↵
↵
Usage↵
------↵
To use this data structure:↵
↵
~~~~~↵
#include <ext/pb_ds/assoc_container.hpp>↵
using namespace __gnu_pbds;↵
gp_hash_table<int, int> table;↵
~~~~~↵
From there, the API seems almost exactly the same.↵
↵
Thanks to ~adamant,2018-07-20 for his post that revealed to me the existence of policy data structures, and thanks to ~tonynater,2018-07-20 for the discussion.↵
↵
PS: In other posts for unordered_map, I've seen people claim that reserve and max_load_factor could increase performance drastically. They didn't seem to do much for me. However, if you want to do something similar for these hash tables, use `typedef cc_hash_table<↵
int, int, hash<int>, equal_to<int>, direct_mask_range_hashing<int>,↵
hash_standard_resize_policy<hash_exponential_size_policy<>, hash_load_check_resize_trigger<true>, true>>↵
ht;`, and you should be able to resize and set load factor manually as well.↵
↵
↵
↵
↵
Code for the benchmarks can be found here: https://ideone.com/ZkNMbH↵
↵
EDIT: I realized that gp_hash_table is the way to go, not cc_hash_table. gp_hash_table sacrifices ~10% reading/writing speed to gain 3-6x in insertion/deletion/clearing. I updated the post to reflect the new numbers.
------↵
The Policy Hash Table has 3-6x faster insertion/deletion and 3-10x increase for writes/reads. As far as I can tell, there are no downsides. The policy hash table (specifically the open-addressing version), beats out unordered_map in all my benchmarks.↵
[cut]↵
Background↵
------↵
I've often been irritated by how slow unordered_map is in C++. Too often, I have something that runs fast enough in terms of complexity, but the constant factor from unordered_map slows down the solution too much. Yesterday though, after using the useful order statistics tree from https://codeforces.com/blog/entry/11080, I was curious if there were any other useful data structures hiding in the Policy STL. And lo and behold, I found a hash table.↵
↵
Benchmarks↵
------------------↵
Well, enough backstory, let's look at some numbers.↵
All benchmarks below are compiled with C++14 -O2.↵
↵
~~~~~↵
unordered_maplinear insertion: 0.689846↵
cc_hash_tablelinear insertion: 0.408233↵
gp_hash_tablelinear insertion: 0.256131↵
↵
unordered_maplinear read/write: 1.69783↵
cc_hash_tablelinear read/write: 0.202474↵
gp_hash_tablelinear read/write: 0.26842↵
↵
unordered_maprandom insertion: 2.90184↵
cc_hash_tablerandom insertion: 3.15129↵
gp_hash_tablerandom insertion: 0.56553↵
↵
unordered_maprandom read/write: 2.02336↵
cc_hash_tablerandom read/write: 0.333415↵
gp_hash_tablerandom read/write: 0.403486↵
~~~~~↵
↵
While for linear insertions, the policy hash table gives modest improvements, the policy hash table blows the unordered_map out of the water when it comes to reads/writes. These are order of magnitude improvements that make hash tables usable when they previously weren't.↵
Example↵
------↵
Benchmarks of course, don't always reflect the real world. So here's an example of it allowing a solution to be accepted that TLE's with unordered_map.↵
↵
Example problem (5000 ms time limit): http://codeforces.com/contest/264/problem/C ↵
Solution with unordered_map: http://codeforces.com/contest/264/submission/40542899 (TLE on test case 8) ↵
Solution with policy hash table directly substituted in: http://codeforces.com/contest/264/submission/40573491 (TLE on test case 26) ↵
Solution with unordered_map, rewritten to not use clears:↵
http://codeforces.com/contest/264/submission/40590437 (TLE on test case 26)↵
Solution with policy hash table and rewritten to not use clears: http://codeforces.com/contest/264/submission/40574196 (AC with max time of 3180 ms) ↵
↵
Usage↵
------↵
To use this data structure:↵
↵
~~~~~↵
#include <ext/pb_ds/assoc_container.hpp>↵
using namespace __gnu_pbds;↵
gp_hash_table<int, int> table;↵
~~~~~↵
From there, the API seems almost exactly the same.↵
↵
Thanks to ~adamant,2018-07-20 for his post that revealed to me the existence of policy data structures, and thanks to ~tonynater,2018-07-20 for the discussion.↵
↵
PS: In other posts for unordered_map, I've seen people claim that reserve and max_load_factor could increase performance drastically. They didn't seem to do much for me. However, if you want to do something similar for these hash tables, use `typedef cc_hash_table<↵
int, int, hash<int>, equal_to<int>, direct_mask_range_hashing<int>,↵
hash_standard_resize_policy<hash_exponential_size_policy<>, hash_load_check_resize_trigger<true>, true>>↵
ht;`, and you should be able to resize and set load factor manually as well.↵
↵
↵
↵
↵
Code for the benchmarks can be found here: https://ideone.com/ZkNMbH↵
↵
EDIT: I realized that gp_hash_table is the way to go, not cc_hash_table. gp_hash_table sacrifices ~10% reading/writing speed to gain 3-6x in insertion/deletion/clearing. I updated the post to reflect the new numbers.
