PlugCache

A response caching plug based on nebulex

Installation

def deps do
  [
    {:plug_cache, "~> 0.1.0-rc1"}
  ]
end

Usage

plug PlugCache

simply add the PlugCache will caches the responses in memory.

defmodule MyApp.PageController do

  plug PlugCache, ttl: 86400 when action in [:index]

  def index(conn, _params) do
    conn
    |> render(:index)
  end
end

This will caches the index action response on first time, then return cached response on next time for a day.

Cache key is based on request path and params. Request path like below produces different cache.

/v1/hello
/v1/hello?a=b

If you want to manipulate the cache manually, you can use PlugCache.Cache like this.

PlugCache.Cache.set(key, value)
PlugCache.Cache.delete(key)
PlugCache.Cache.update(key, initial, fn(x) -> x + 1 end)

Configurations

Per plug configurations

example:

plug PlugCache, ttl: 100 # cache 100 seconds
key description default example
ttl TTL for cache (second) nil (never expired) 100

Distributed Cache

If you want to distribute the cache in erlang cluster, then use PlugCache.DistCache

config :plug_cache,
  adapter: PlugCache.DistCache

By using this adapter, caches are shared in cluster.

So manual cache operation is propagated to across cluster.

Distribution requires clustering erlang processes. Tools like libcluster, peerage helps clustering erlang nodes.

Benchmark

Local Cache

Operating System: Linux
CPU Information: Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz
Number of Available Cores: 8
Available memory: 31.37 GB
Elixir 1.6.0-dev
Erlang 20.1
Benchmark suite executing with the following configuration:
warmup: 2 s
time: 5 s
parallel: 1
inputs: none specified
Estimated total run time: 7 s

Benchmarking test...
Name ips average deviation median 99th %
test 63.79 K 15.68 μs ±149.14% 14 μs 31 μs

Distributed Cache

Operating System: Linux
CPU Information: Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz
Number of Available Cores: 8
Available memory: 31.37 GB
Elixir 1.6.0-dev
Erlang 20.1
Benchmark suite executing with the following configuration:
warmup: 2 s
time: 5 s
parallel: 1
inputs: none specified
Estimated total run time: 7 s


Benchmarking test...
Name ips average deviation median 99th %
test 45.60 K 21.93 μs ±177.22% 20 μs 42 μs

Contributing

  1. Fork it
  2. Create your feature branch (git checkout -b my-new-feature)
  3. Commit your changes (git commit -am 'Add some feature')
  4. Push to the branch (git push origin my-new-feature)
  5. Create new Pull Request

License

MIT