Open shift intro for Philly PUG

Jul 13, 2012Download as PPT, PDF0 likes523 views

This are the few slides I presented for the Philly Python User Group on 7_12 - please see the script file for the commands I used

Getting Started with
OpenShift

Steven Citron-Pousty
PaaS Dust Spreader, Red Hat

@TheSteve0

1

Looks great, but what’s the catch?
• OpenShift is free-as-in-beer & free-as-in-freedom
• Three gears – 1.5 gig RAM, 3 gig Disk (always free)
• Need more resources, just ask!
• The Catch is we are in developer preview right now

6

This document provides an agenda and overview for an OpenShift workshop on Python development. The workshop will introduce OpenShift and demonstrate how to create Python applications using the OpenShift platform-as-a-service. Attendees will learn to create applications from the command line and web console, add databases like MongoDB, and use tools like Git for version control. The document outlines assumptions about attendees' experience and what will be covered, including supported technologies, available resources, and terminology for the workshop.

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The document provides commands for adding spatial data to MongoDB. It includes steps to import coordinate data from a JSON file into a MongoDB collection called "parkpoints", build a 2D index on the "pos" field, and perform simple spatial queries and a geoNear query to find documents near a given location. It also shows how to create a new "checkin" collection, insert documents with location data, update an existing document, and query the checkin collection.

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This document summarizes a presentation about building spatial web services using MongoDB and Node.js. It includes an agenda that covers loading spatial data into MongoDB, performing queries, and sharing a code repository. The presenter assumes the audience has basic knowledge of Node.js, MongoDB, and using the command line. They then explain what OpenShift is and what resources it provides. The bulk of the presentation focuses on demonstrating how to add spatial indexing and querying capabilities to MongoDB, including indexing coordinates and performing near and containment queries. The presenter concludes by stating spatial functionality is easy to integrate with MongoDB and that attendees can now build applications like Foursquare or field data systems using these techniques.

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Mongo sf spatialmongoSteven Pousty

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