This Ruby gem adds a parallel map method to any Enumerable (notably including any Array).
- pmap parallel map
It is implemented using Concurrent Futures so that it uses threads to run your map in parallel. All limitations of Concurrent::Future apply here.
ParallelMap was heavily inspired by pmap so a lot of credit goes to bruceadams. One small difference with pmap is that ParallelMap does not patch Enumerable by default. You need to decide if you want to patch Enumerable or only other classes like Array or Range.
# Patch Enumerable and all its descendants
ParallelMap.patch_enumerable
# Or patch any other class/module directly
ParallelMap.patch Array
Add this line to your application's Gemfile:
gem 'parallel_map'
And then execute:
$ bundle
Or install it yourself as:
$ gem install parallel_map
Paraphrasing pmap let's
suppose that we have a function get_quote
that calls out to a stock
quote service to get a current stock price. The response time for
get_quote
ranges averages 0.5 seconds.
# We will only patch Array for now
ParallelMap.patch Array
# We'll gather the stock symbols
stock_symbols = [:ibm, :goog, :appl, :msft, :hp, :orcl]
# This will take about three seconds; an eternity if you want to render a web page.
stock_quotes = stock_symbols.map { |s| get_quote(s) }
# Instead we can use pmap and this whole process will take as much as the slowest of all the calls.
stock_quotes = stock_symbols.pmap { |s| get_quote(s) }
Threading in Ruby is heavily dependent on the Ruby VM you are using. I will quote pmap on its general limitations and its usefulness.
Matz Ruby 1.8.* uses green threads. All Ruby threads are run within a single thread in a single process. A single Ruby program will never use more than a single core of a mutli-core machine.
Matz Ruby 1.9.* uses native threads. Each Ruby thread maps directly to a thread in the underlying operating system. In theory, a single Ruby program can use multpile cores. Unfortunately, there is a global interpreter lock GIL that causes single-threaded behavior.
JRuby also uses native threads. JRuby avoids the global interpreter lock, allowing a single Ruby program to really use multiple CPU cores.
Despite the Matz Ruby threading limitations, IO bound actions can greatly benefit from multi-threading. A very typical use is making multiple HTTP requests in parallel. Issuing those requests in separate Ruby threads means the requests will be issued very quickly, well before the responses start coming back. As responses come back, they will be processed as they arrive.
After checking out the repo, run bin/setup
to install dependencies. Then, run rake spec
to run the tests. You can also run bin/console
for an interactive prompt that will allow you to experiment.
To install this gem onto your local machine, run bundle exec rake install
. To release a new version, update the version number in version.rb
, and then run bundle exec rake release
, which will create a git tag for the version, push git commits and tags, and push the .gem
file to rubygems.org.
Bug reports and pull requests are welcome on GitHub at https://github.com/[USERNAME]/parallel_map. This project is intended to be a safe, welcoming space for collaboration, and contributors are expected to adhere to the Contributor Covenant code of conduct.
The gem is available as open source under the terms of the MIT License.