This project loads the MusciBrainz database into MongoDB and denormalizes it into a smaller set of useful collections. The intention is to develop reasonable aggregation framework examples that are non-trivial and computationally significant. These examples can be used to test performance and optimizations for the mongo-gpu project as we track GPU computing. We also hope that general-purpose tools for denomalization will emerge.
\curl -sSL https://get.rvm.io | bash -s stable # install RVM - https://rvm.io/
rvm install 2.1.1
rvm --default use 2.1.1
bundle install
rake
The output of rake outlines the ordered steps for the project.
"Big Data Aggregation" writeup, notes, and discussion can be found in the wiki.