Elixir Today: Combining a List of Map via Specific Field
And how to use Benchee as your benchmark tool in Elixir
References
Intro
Recently, I've been working on a similar question about How to combine a list of map via specific field
.
I looked at the elixir forum and gladly I found something. I saw that one of the answers there is using Enum.group_by
+ Enum.map
.
Given my curiosity, How can I come up with a solution using Enum.reduce
?
Curiosity Kicks In
So I started working out using Enum.reduce
.
@list [
%{id: 1, list: [1]},
%{id: 1, list: [2]},
%{id: 2, list: [1]},
%{id: 3, list: [1]},
%{id: 1, list: [3, 4, 5]},
%{id: 2, list: [2, 3]},
%{id: 3, list: [2, 3, 4, 5]},
%{id: 4, list: [2, 3, 4, 5]},
%{id: 4, list: [1]}
]
@list
|> Enum.reverse()
|> Enum.reduce(%{}, fn %{id: id, list: _list} = f, acc ->
case acc do
%{^id => existing} -> Map.put(acc, id, [f | existing])
%{} -> Map.put(acc, id, [f])
end
end)
|> Enum.map(fn {id, list} -> %{id: id, list: Enum.flat_map(list, & &1.list)} end)
In this way, I created a sample list with specific id and their list.
I reverse the order of the list
I used Enum.reduce to sort out and combine the list of the ids accordingly.
Finally, used
Enum.map
to transform the data.
Benchmarking!
I started to compare the result between using group_by
and reduce
. In order to that, I used Benchee.
To install, add benchee to your dependencies.
{:benchee, "~> 1.0", only: :dev}
Given the setup
@list [
%{id: 1, list: [1]},
%{id: 1, list: [2]},
%{id: 2, list: [1]},
%{id: 3, list: [1]},
%{id: 1, list: [3, 4, 5]},
%{id: 2, list: [2, 3]},
%{id: 3, list: [2, 3, 4, 5]},
%{id: 4, list: [2, 3, 4, 5]},
%{id: 4, list: [1]}
]
def groupby(list) do
Enum.group_by(list, & &1.id)
|> Enum.map(fn {id, list} -> %{id: id, list: Enum.flat_map(list, & &1.list)} end)
end
def reduce(list) do
list
|> Enum.reverse()
|> Enum.reduce(%{}, fn %{id: id, list: _list} = f, acc ->
case acc do
%{^id => existing} -> Map.put(acc, id, [f | existing])
%{} -> Map.put(acc, id, [f])
end
end)
|> Enum.map(fn {id, list} -> %{id: id, list: Enum.flat_map(list, & &1.list)} end)
end
Then run
Benchee.run(
%{
"groupby_enum_map" => fn -> PracticeElixir.groupby(@list) end,
"reduce_enum_map" => fn -> PracticeElixir.reduce(@list) end
},
print: [fast_warning: false]
)
Benchmark Result
Given my dev environment, here is the result.
available_memory: "16 GB",
cpu_speed: "Intel(R) Core(TM) i9-9880H CPU @ 2.30GHz",
elixir: "1.12.3",
erlang: "24.0.6",
num_cores: 16,
os: :macOS
Benchmark suite executing with the following configuration:
warmup: 2 s
time: 5 s
memory time: 0 ns
reduction time: 0 ns
parallel: 1
inputs: none specified
Estimated total run time: 14 s
Benchmarking groupby_enum_map ...
Benchmarking reduce_enum_map ...
Name ips average deviation median 99th %
reduce_enum_map 1.08 M 0.93 μs ±208.21% 0.80 μs 5 μs
groupby_enum_map 0.97 M 1.03 μs ±251.03% 0.90 μs 4 μs
Comparison:
reduce_enum_map 1.08 M
groupby_enum_map 0.97 M - 1.12x slower +0.109 μs
You can view the full implementation here!
Happy Coding!