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1. General Background and Overview

• Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
• Models and Issues in Data Stream Systems
• Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
• Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
• [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep

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require 'formula'

class ScalaDocs < Formula
  homepage 'http://www.scala-lang.org/'
  url 'http://www.scala-lang.org/downloads/distrib/files/scala-docs-2.9.3.zip'
  sha1 '633a31ca2eb87ce5b31b4f963bdfd1d4157282ad'
end

class ScalaCompletion < Formula
  homepage 'http://www.scala-lang.org/'

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Make it real

Ideas are cheap. Make a prototype, sketch a CLI session, draw a wireframe. Discussions around concrete examples, not handy-waving abstractions. Don't say you did something, provide a URL that proves it.

Ship it

Nothing is real until it's being used by a real user. This doesn't mean you make a prototype in the morning and blog about it in the evening. It means you find one person you believe your product will help and try to get them to use it.

Do it with style

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All of the categories!

I wrote a really simple JavaScript script that uses jQuery to extract all the categories from Facebook's "Create a page" page.

Instructions

1. Navigate to the Create a page page.
2. jQuerify the page.
3. Open up your JavaScript console of choice and run the following script: