The Policy Hash Table has 20-30% faster linear insertion/deletion, equal performance for random insertion/deletion, and 3-10x increase for writes/reads. However, clear() is slower on a Policy Hash Table with random insertion order.
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.
Well, enough backstory, let's look at some numbers. All benchmarks below are compiled with -O2.
unordered map linear insertion: 0.816795 policy hash table linear insertion: 0.442094 unordered map linear read/write: 1.91384 policy hash table linear read/write: 0.216669 unordered map random insertion: 2.98216 policy hash table random insertion: 3.13651 unordered map random read/write: 2.12804 policy hash table random read/write: 0.356518
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.
At this point, you may still be skeptical. Benchmarks of course, don't always reflect on the real world. So here's an example of it being used to speed up a previously too slow solution.
Example problem: 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 policy hash table and rewritten to not use clears: http://codeforces.com/contest/264/submission/40574196 (AC with max time of 3180 ms)
To use this data structure:
#include <ext/pb_ds/assoc_container.hpp> using namespace __gnu_pbds; cc_hash_table<int, int> table;
From there, the API seems almost exactly the same.
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