bench_any_vs_in.exs

Mix.install([
  {:benchee, "~> 1.0"},
  {:benchee_html, "~> 1.0", only: :dev}
])

minimal_size = 5
medium_size = 1000
big_size = 10_000

build_list = fn size ->
  Enum.map(1..size, fn _ -> %{attr: Enum.random(1..200_000)} end)
end

Benchee.run(
  %{
    "filter_any?" => fn %{a: list_a, b: list_b} -> 
      Enum.filter(list_a, fn el_a ->
        Enum.any?(list_b, &Kernel.==(&1.attr, el_a.attr))
      end)
    end,
    "using_in" => fn %{a: list_a, b: list_b} ->
      list_b_attrs = list_b |> Enum.map(& &1.attr) |> Enum.uniq()

      Enum.filter(list_a, fn el_a ->
        el_a.attr in list_b_attrs
      end)
    end
  },
  inputs: %{
    "minimal A, minimal B" => %{a: build_list.(minimal_size), b: build_list.(minimal_size)},
    "medium A, minimal B" => %{a: build_list.(medium_size), b: build_list.(minimal_size)},
    "big A, minimal B" => %{a: build_list.(big_size), b: build_list.(minimal_size)},
    "minimal A, medium B" => %{a: build_list.(minimal_size), b: build_list.(medium_size)},
    "medium A, medium B" => %{a: build_list.(medium_size), b: build_list.(medium_size)},
    "big A, medium B" => %{a: build_list.(big_size), b: build_list.(medium_size)},
    "minimal A, big B" => %{a: build_list.(minimal_size), b: build_list.(big_size)},
    "medium A, big B" => %{a: build_list.(medium_size), b: build_list.(big_size)},
    "big A, big B" => %{a: build_list.(big_size), b: build_list.(big_size)}
  },
  time: 10,
  formatters: [
  Benchee.Formatters.HTML,
  Benchee.Formatters.Console
]
)

results.txt

##### With input big A, big B #####
Name                  ips        average  deviation         median         99th %
using_in             9.50        0.105 s     ±8.80%        0.102 s        0.142 s
filter_any?          0.51         1.96 s     ±2.25%         1.96 s         2.01 s

Comparison: 
using_in             9.50
filter_any?          0.51 - 18.62x slower +1.85 s

##### With input big A, medium B #####
Name                  ips        average  deviation         median         99th %
using_in            96.01       10.42 ms     ±6.06%       10.29 ms       13.45 ms
filter_any?          5.07      197.17 ms     ±2.35%      196.54 ms      209.70 ms

Comparison: 
using_in            96.01
filter_any?          5.07 - 18.93x slower +186.76 ms

##### With input big A, minimal B #####
Name                  ips        average  deviation         median         99th %
using_in           3.94 K        0.25 ms    ±14.32%        0.25 ms        0.46 ms
filter_any?        0.74 K        1.36 ms    ±10.15%        1.34 ms        1.96 ms

Comparison: 
using_in           3.94 K
filter_any?        0.74 K - 5.36x slower +1.11 ms

##### With input medium A, big B #####
Name                  ips        average  deviation         median         99th %
using_in            71.99       13.89 ms    ±12.98%       14.66 ms       16.84 ms
filter_any?          5.07      197.41 ms     ±5.08%      195.10 ms      255.83 ms

Comparison: 
using_in            71.99
filter_any?          5.07 - 14.21x slower +183.52 ms

##### With input medium A, medium B #####
Name                  ips        average  deviation         median         99th %
using_in           876.37        1.14 ms     ±9.68%        1.12 ms        1.76 ms
filter_any?         50.94       19.63 ms     ±2.85%       19.58 ms       21.87 ms

Comparison: 
using_in           876.37
filter_any?         50.94 - 17.20x slower +18.49 ms

##### With input medium A, minimal B #####
Name                  ips        average  deviation         median         99th %
using_in          38.76 K       25.80 μs    ±57.78%          25 μs          53 μs
filter_any?        6.87 K      145.59 μs    ±76.39%         130 μs         316 μs

Comparison: 
using_in          38.76 K
filter_any?        6.87 K - 5.64x slower +119.79 μs

##### With input minimal A, big B #####
Name                  ips        average  deviation         median         99th %
filter_any?        1.00 K        1.00 ms    ±11.63%        0.97 ms        1.59 ms
using_in           0.48 K        2.10 ms    ±21.61%           2 ms        4.63 ms

Comparison: 
filter_any?        1.00 K
using_in           0.48 K - 2.11x slower +1.10 ms

##### With input minimal A, medium B #####
Name                  ips        average  deviation         median         99th %
filter_any?        9.99 K      100.14 μs    ±16.38%          98 μs         185 μs
using_in           7.87 K      127.09 μs    ±16.22%         122 μs         234 μs

Comparison: 
filter_any?        9.99 K
using_in           7.87 K - 1.27x slower +26.94 μs

##### With input minimal A, minimal B #####
Name                  ips        average  deviation         median         99th %
using_in           1.39 M      718.97 ns  ±5865.12%        1000 ns        1000 ns
filter_any?        1.10 M      912.17 ns  ±4369.28%        1000 ns        1000 ns

Comparison: 
using_in           1.39 M
filter_any?        1.10 M - 1.27x slower +193.20 ns