Elixir Pattern Matching Research

At the start of the week I started reading Metaprogramming Elixir by Chris McCord. One of the items you quickly learn is just how easy it is to programmatically create methods that can be compiled into your application. One of the examples in the book that is cited from this is how the Unicode.upcase method is delegated to down to methods that are created at compile time from a file. Here is where you can find this being used

After seeing this I began to wonder what the “performance” of matching was in the Elixir system. So I wired up some tests to begin identifying this for myself. To me it would seem that since the order of the methods is important; the best you could get was linear growth in lookup time. Meanwhile if you have a more robust data structure that can avoid doing this kind of lookup I would assume it to be faster.

These are the two different modules I put together, building both of them from my local dictionary of about ninety-nine thousand words:

defmodule PatternPerformance.Matching do
@external_resource words_file = Path.join([__DIR__, "../words.txt"])
for word <- File.stream!(words_file, [], :line) do
word = String.strip(word)
def is_word?(unquote(word)), do: true
def is_word?(_word), do: false

The PatternPerformance.Matching module creates close to 100 thousand methods where it matches literally on the word given and returns a simple true. Then at the end it has a catch all that returns false. I’m not sure how great this would be for production, but it serves for what I am testing. Some things to note about this module is it took 6 minutes and 23 seconds to compile on my Macbook Pro and the binary it generates is a little over three megabytes big.

defmodule PatternPerformance.HashDict do
@external_resource words_file = Path.join([__DIR__, "../words.txt"])
@words File.stream!(words_file, [], :line)
|> Enum.map(&String.strip(&1))
|> Enum.reduce(HashDict.new, fn word, acc ->
HashDict.put(acc, word, true)
def is_word?(word), do: HashDict.get(@words, word, false)

The PatternPerformance.HashDict module creates a HashDict structure at compile time and sets it as @words. The is_word? function defined simply references this structure, returning is value which is true, and is given false as the default value to return if the key is not found. Items to note about this module is it takes about 4 seconds to compile and is 1.6 megabytes big.

To test both of these I created the following crude module:

defmodule PatternPerformance do
defstruct slowest_time: 0,
total_time: 0,
words_tried: 0
def words do
File.read!(Path.join([__DIR__, "../words.txt"]))
|> String.split("\n")
def record_access(module) do
# "Warming" up the system
Enum.reduce(words, %PatternPerformance{}, fn word, performance ->
time =
case :timer.tc(module, :is_word?, [word]) do
{t, true} -> t
{t, false} ->
IO.puts "Word '#{word}' not found!"
%{performance |
slowest_time: max(time, performance.slowest_time),
words_tried: performance.words_tried + 1,
total_time: performance.total_time + time

After several tests there was a clear winner…

# %PatternPerformance{slowest_time: 293, total_time: 49189, words_tried: 99172}
# %PatternPerformance{slowest_time: 1835, total_time: 47322, words_tried: 99172}
# %PatternPerformance{slowest_time: 1861, total_time: 47508, words_tried: 99172}
# %PatternPerformance{slowest_time: 2049, total_time: 57061, words_tried: 99172}
# %PatternPerformance{slowest_time: 1983, total_time: 21555, words_tried: 99172}
# %PatternPerformance{slowest_time: 2147, total_time: 22174, words_tried: 99172}
# %PatternPerformance{slowest_time: 2079, total_time: 22341, words_tried: 99172}
# %PatternPerformance{slowest_time: 1584, total_time: 21110, words_tried: 99172}

The PatternPerformance.Matching was about twice as fast at coming back with the correct answer! This is not what I was suspecting, and as such I wanted to believe perhaps something was not right with the HashDict structure so I created two more test modules to try out the tried-and-true Erlang gb_trees and gb_sets.

defmodule PatternPerformance.GBSet do
@external_resource words_file = Path.join([__DIR__, "../words.txt"])
@words File.stream!(words_file, [], :line)
|> Enum.map(&String.strip(&1))
|> Enum.reduce(:gb_sets.new, fn word, acc ->
:gb_sets.insert(word, acc)
|> :gb_sets.balance
def is_word?(word), do: :gb_sets.is_member(word, @words)
defmodule PatternPerformance.GBTree do
@external_resource words_file = Path.join([__DIR__, "../words.txt"])
@words File.stream!(words_file, [], :line)
|> Enum.map(&String.strip(&1))
|> Enum.reduce(:gb_trees.empty, fn word, acc ->
:gb_trees.enter(word, true, acc)
|> :gb_trees.balance
def is_word?(word), do: :gb_trees.is_defined(word, @words)
# %PatternPerformance{slowest_time: 172, total_time: 69402, words_tried: 99172}
# %PatternPerformance{slowest_time: 116, total_time: 68816, words_tried: 99172}
# %PatternPerformance{slowest_time: 117, total_time: 68723, words_tried: 99172}
# %PatternPerformance{slowest_time: 115, total_time: 69169, words_tried: 99172}
# %PatternPerformance{slowest_time: 127, total_time: 73446, words_tried: 99172}
# %PatternPerformance{slowest_time: 117, total_time: 74925, words_tried: 99172}
# %PatternPerformance{slowest_time: 126, total_time: 75926, words_tried: 99172}
# %PatternPerformance{slowest_time: 115, total_time: 73989, words_tried: 99172}

These were even slower! Although an interesting note that their “slowest” times were way faster than the pattern matching and HashDict slowest lookup times on average. I guess for now I am left with more questions than answers; however for the time it appears compiling in a bunch of methods may be your best bet when referring to a static list of values.

If you want to tinker with this yourself I threw up all of my code in a simple mix project on my github: elixir_pattern_performance