Gautam Rege
5c07bd3a48ed2565bf1b872620bca3e9?d=retro
Ranked 40 in Phase 1 with 51 unique views, 17 counted upvotes and 9 counted downvotes

About the author

Gautam is the co-founder of Josh Software - one of India's premiere Ruby companies. He is also the author of "Ruby and MongoDB Web development" and is currently authoring "Using Mongoid".

For the past 6 years, all he and his company do is eat, sleep and breathe Ruby. When is not organizing Ruby events locally (RubyConf India, Pune Rails Meetup, Pune Startups ) and not coding on some project or on some open-source idea, he loves to give 'gyaan' on entrepreneurship and life, universe and everything!

He has earlier presented at Lone Star Ruby Conf, Red Dot Ruby Conf, RubyConf India and talks at a host of other meetups. He writes about his research on the Josh Software Blog and his twitter handle is @gautamrege

Pushing Mongoid to the limit

Mongoid (especially 3.x) has become a very popular choice as an ODM for Rails applications. But did you know that Mongoid goes way beyond acting as just as an ODM in Rails? It can be used with any Ruby application and can be used to its full potential. This talk is about how we can push mongoid (and in turn MongoDB) to its limit.

  • Mongoid introduced Origin and Moped. This talk discusses about the origins of Origin and Moped, why they were introduced and how they can even be used independently.
  • We see what mongoize is and how its used for custom field types and their serialization.
  • We see how querying has improved with Origin and peek into its DSL. For example, we shall see what goes on under the covers for a call like :created_at.lte and how Symbol class is enhanced for better querying. We see how .or and .and operations can be done easily without any MongoDB specific syntax.
  • We see how to leverage field aliasing for better storage and compound indexing.
  • We learn how 2dsphere indexes improve geo-spatial searches and how hashed indexes are awesome for sharding.
  • How often do we hit a problem where we need aggregated data from multiple collections? This talks discusses simulating "joins" using map re-reduce.
  • Full text search indexing is now an experimental features of MongoDB 2.4. We take on text indexes, their pros and cons and compare it with indexing engines like ElasticSearch and IndexTank.

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Suggestions

  • The proposal author responded 8 months ago

    Thanks!

    This talk is actually supposed to be only in Ruby realm! I have changed the intro to ensure the Ruby aspect is highlighted and not Rails.

  • D87dddeb300217e6c6574f5ffae220be?d=retro Nikos Dimitrakopoulos suggested 8 months ago

    Very well written outline - kudos! My suggestion would also be to relate it as much as you can with ruby and not only rails.