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by Kyle Banker
One of the challenges that comes with moving to MongoDB is figuring how to best model your data. While most developers have internalized the rules of thumb for designing schemas for RDBMSs, these rules don't always apply to MongoDB. The simple fact that documents can represent rich, schema-free data structures means that we have a lot of viable alternatives to the standard, normalized, relational model. Not only that, MongoDB has several unique features, such as atomic updates and indexed array keys, that greatly influence the kinds of schemas that make sense. Understandably, this begets good questions: Are foreign keys permissible, or is it better to represent one-to-many relations withing a single document? Are join tables necessary, or is there another technique for building out many-to-many relationships? What level of denormalization is appropriate? How do my data modeling decisions affect the efficiency of updates and queries? In this session, we'll answer these questions and more, provide a number of data modeling rules of thumb, and discuss the tradeoffs of various data modeling strategies.
by Dan Crosta
Love Django, but hate schema migrations? Need to scale to more than a few gigabytes of data? Tired of flattening your data, only to have your code rebuild the hierarchy? This talk will show you how you can leave JOINs behind and embrace MongoDB for your next Django project. MongoDB's hierarchical document-oriented design makes it a natural fit for web development, and when coupled with Python's easy-going nature, using MongoDB with Django is a breeze. In this talk, learn about MongoDB, the most popular NoSQL database; MongoEngine and friends, the Djangonic MongoDB adapter; and watch as we build a highly-scalable online game before your very eyes.
by Meghan Gill
A case study on how we built the community around MongoDB, with some lessons learned for anyone building community around open source
by Mike Dirolf
This talk will look inside the technology and architecture used at Fiesta (https://fiesta.cc), with a focus on the deployment of Python web apps, processing email, and using MongoDB in practice. The goal is to provide generic insights about the tools we've chosen, rather than information specific to our business.
by Tony Hannan
MongoDB supports asynchronous replication of data between servers for failover and redundancy. In this session, we'll introduce the different modes the replication, including master-slave and replica sets, and we'll describe how to achieve better durability by adjusting the write concern. We'll also discuss backups and provide some tips on scaling with replication alone.
This intermediate-level talk will teach you techniques using the popular NoSQL database MongoDB and the Python library Ming to write maintainable, high-performance, and scalable applications. We will cover everything you need to become an effective Ming/MongoDB developer from basic PyMongo queries to high-level object-document mapping setups in Ming.
by Dan Pasette
Mongo Monitoring System
This session is a deep dive into the implementation of sharding within MongoDB. We'll review the MongoDB's sharding architecture, which blends ideas from RDBMSes, key/value stores, and large distributed systems like BigTable. We'll then take a look under the hood to show how queries work across a sharded set up, and how data is balanced and migrated.
by David Nevins
A holographic platform will advance digital tool-making capabilities, creating opportunities to rethink interoperability, portability, ownership and security.
Some of these issues are not as new as they may seem. Precedent set 150 years ago in solving global clock simultaneity applies today in solving interoperability by means of a holographic feed, synchronizing data for rendering.
As databases get huge, resolution is reduced. 4D renderings enhance and extend the human capacity for pattern matching and act as a kind of perceptual faculty. Renderings of relationships between diverse data types make antecedents and dependencies, cause and effect, more clear.
Python is ideal because of its versatility importing data formats and outputs. Prototype in Python, Unity 3D gaming platform and MongoDB will be demo'd.
by Daniel Foreman-Mackey
The field of Observational Astrophysics is beginning to focus on huge datasets covering large portions of the sky over long time periods. This yields an immensely rich dataset but the traditional scientific workflow can no longer efficiently work on these scales. As a graduate student in Astrophysics, I will discuss the growing role of Python in our scientific research development cycle and present several case studies where MongoDB has been an integral component of the workflow.
16th–17th September 2011