# Hash-Based Skewed-Distribution Random-Integer `find` Find Timing Test

## Description

This test inserts a number of values with a markedly non-uniform i.i.d. integer keys into a container, then performs a series of finds using `find` . It measures the average time for `find` as a function of the number of values in the containers. The keys are generated as follows. First, a uniform integer is created; it is then shifted left 8 bits.

(The test was executed with `hash_zlob_random_int_find_timing_test` 200 200 2100)

## Purpose

The test checks the effect of different range-hashing functions and trigger policies (see Design::Associative Containers::Hash-Based Containers::Hash Policies and Design::Associative Containers::Hash-Based Containers::Resize Policies).

## Results

Figures NHG, NHM, and NHL show the results for various hash-based associative-containers in g++, MSVC++, and local, respectively.

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NHG: Skewed-distribution random int find timing test using `find` - g++

In the above figure, the names in the legends have the following meaning:

1. cc_hash_mask_exp_nea_lc_1div8_1div1_nsth_map- `cc_hash_table` with `Comb_Hash_Fn` = `direct_mask_range_hashing` , and `Resize_Policy` = `hash_standard_resize_policy` with `Size_Policy` = `hash_exponential_size_policy` , and `Trigger_Policy` = `hash_load_check_resize_trigger` with αmin = 1/8 and αmax = 1/1
2. gp_hash_mod_quadp_prime_nea_lc_1div8_1div2_nsth_map- `gp_hash_table` with `Comb_Hash_Fn` = `direct_mod_range_hashing` , `Resize_Policy` = `hash_standard_resize_policy` with `Size_Policy` = `hash_prime_size_policy` , and `Trigger_Policy` = `hash_load_check_resize_trigger` with αmin = 1/8 and αmax = 1/2, and `Probe_Fn` = `quadratic_probe_fn`
3. n_hash_map_ncah- `std::tr1::unordered_map` with `cache_hash_code` = `false`
4. cc_hash_mod_prime_nea_lc_1div8_1div1_nsth_map- `cc_hash_table` with `Comb_Hash_Fn` = `direct_mod_range_hashing` , and `Resize_Policy` = `hash_standard_resize_policy` with `Size_Policy` = `hash_prime_size_policy` , and `Trigger_Policy` = `hash_load_check_resize_trigger` with αmin = 1/8 and αmax = 1/1

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NHM: Skewed-distribution random int find timing test using `find` - msvc++

In the above figure, the names in the legends have the following meaning:

1. n_hash_map_ncah- `stdext::hash_map`
2. cc_hash_mask_exp_nea_lc_1div8_1div1_nsth_map- `cc_hash_table` with `Comb_Hash_Fn` = `direct_mask_range_hashing` , and `Resize_Policy` = `hash_standard_resize_policy` with `Size_Policy` = `hash_exponential_size_policy` , and `Trigger_Policy` = `hash_load_check_resize_trigger` with αmin = 1/8 and αmax = 1/1
3. gp_hash_mod_quadp_prime_nea_lc_1div8_1div2_nsth_map- `gp_hash_table` with `Comb_Hash_Fn` = `direct_mod_range_hashing` , `Resize_Policy` = `hash_standard_resize_policy` with `Size_Policy` = `hash_prime_size_policy` , and `Trigger_Policy` = `hash_load_check_resize_trigger` with αmin = 1/8 and αmax = 1/2, and `Probe_Fn` = `quadratic_probe_fn`
4. cc_hash_mod_prime_nea_lc_1div8_1div1_nsth_map- `cc_hash_table` with `Comb_Hash_Fn` = `direct_mod_range_hashing` , and `Resize_Policy` = `hash_standard_resize_policy` with `Size_Policy` = `hash_prime_size_policy` , and `Trigger_Policy` = `hash_load_check_resize_trigger` with αmin = 1/8 and αmax = 1/1

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NHL: Skewed-distribution random int find timing test using `find` - local

## Observations

In this setting, the keys' distribution is so skewed that the unerlying hash-table type affects performance marginally. (This is in contrast with Hash-Based Text `find` Find Timing Test , Hash-Based Random-Integer `find` Find Timing Test , Hash-Based Random-Integer Subscript Find Timing Test and Hash-Based Random-Integer Subscript Insert Timing Test .)

The range-hashing scheme affects performance dramatically. A mask-based range-hashing scheme effectively maps all values into the same bucket. Access degenerates into a search within an unordered linked-list. In Figures NHG and NHM , it should be noted that `std::tr1::unordered_map` and `stdext::hash_map` are hard-wired currently to mod-based and mask-based schemes, respectively.

When observing the settings of this test, it is apparent that the keys' distribution is far from natural. One might ask if the test is not contrived to show that, in some cases, mod-based range hashing does better than mask-based range hashing. This is, in fact just the case. We did not encounter a more natural case in which mod-based range hashing is better. In our opnion, real-life key distributions are handled better with an appropriate hash function and a mask-based range-hashing function. (`shift_mask.cc` shows an example of handling this a-priori known skewed distribution with a mask-based range-hashing function). If hash performance is bad, a Χ2 test can be used to check how to transform it into a more uniform distribution.

For this reason, `pb_ds`'s default range-hashing function is mask-based.

Observations::Hash-Based Container Types summarizes some observations on hash-based containers; Observations::Hash-Based Containers' Policies summarizes some observations on hash-based containers' policies.