- 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=rep1&t
# NB. This affront to reason mocks our beliefs in everything save chaos and death. | |
# May whatever you call Holy forgive you, the damned, who read further | |
# than this point. You have been warned. But if you scorn this warning, if | |
# your contempt for these my dying words is so complete that you read on, | |
# if you still believe that there is something good or right or just in this world, | |
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# black and brackish pit, the Hell below Hell, where I now go. |
Vagrant plugins currently expose the FULL POWER of Vagrant. Unfortunately, as is often the case, "full power" means "complicated" (relatively), especially for those not familiar with Ruby.
Instead, I'd like to introduce an alternative "simple" API to plugins as well that people can confidently use. Below are some examples of this. I'm not even going to describe what each plugin does because it should be simple enough from the code, that's how simple they are!
The end goal is that it should be much more common to see Vagrant projects ship with custom commands like vagrant run-tests
or vagrant start-server
, to perform common tasks that previously required SSH.
These "easy" plugins can't do everything but they will be able to do the common things. If you want more power, full (non-easy) plugins should be used.