SimpleMapReduce

This is a MapReduce distributed framework written in Ruby. This project is an experimental project. So all the specifications will be changed suddenly.

Installation

Add this line to your application's Gemfile:

gem 'simple_map_reduce'

And then execute:

$ bundle

Or install it yourself as:

$ gem install simple_map_reduce

Quick start in local environment with minio

1. Start minio server

$ docker run -p 9000:9000 -p 9001:9001  \
-e "MINIO_ROOT_USER=MINIO_ACCESS_KEY" -e "MINIO_ROOT_PASSWORD=MINIO_SECRET_KEY" -e "MINIO_REGION=us-east-1" \
minio/minio server /data --console-address :9001

2. Start job tracker

$ bundle exec simple_map_reduce run_job_tracker! \
  --job-tracker-url=http://job_tracker:4567 \
  --server-port=4567 \
  --s3_config=access_key_id:'MINIO_ACCESS_KEY' \
              secret_access_key:'MINIO_SECRET_KEY' \
              endpoint:'http://127.0.0.1:9000' \
              region:'us-east-1' \
              force_path_style:true

3. Start job worker(s)

$ bundle exec simple_map_reduce run_job_worker! \
  --job-tracker-url=http://localhost:4567 \
  --job-worker-url=http://localhost:4568 \
  --server-port=4568 \
  --s3_config=access_key_id:'MINIO_ACCESS_KEY' \
              secret_access_key:'MINIO_SECRET_KEY' \
              endpoint:'http://127.0.0.1:9000' \
              region:'us-east-1' \
              force_path_style:true

4. Generate and upload test data

$ bundle exec simple_map_reduce generate_lorem_text_data --upload=true

5. Execute word count job

$ bundle exec simple_map_reduce execute_word_count

Quick start in Docker Compose

• You can setup a simple_map_reduce cluster by docker compose.

$ clone [email protected]:serihiro/simple_map_reduce.git
$ cd simple_map_reduce
$ docker compose up

• You can execute word count sample by executing following commands

$ docker compose exec job_tracker bundle exec simple_map_reduce generate_lorem_text_data --upload=true
$ docker compose exec job_tracker bundle exec simple_map_reduce execute_word_count

Motivation of this project

I would have liked to lean the theory of distributed systems, big data processing, and MapReduce algorhythm. In my experiences, I believed that an implementation of them is the best way to learn them. So I decided to create an experimental implementation, and keep adding new features in order to get an practical experiences of the theories.

Development

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.

Contributing

Bug reports and pull requests are welcome on GitHub at https://github.com/[USERNAME]/simple_map_reduce. 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.

License

The gem is available as open source under the terms of the MIT License.

Code of Conduct

Everyone interacting in the SimpleMapReduce project’s codebases, issue trackers, chat rooms and mailing lists is expected to follow the code of conduct.