- 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
cfranko
debasishg
/ gist:8172796
Last active
March 15, 2024 15:05
A collection of links for streaming algorithms and data structures
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| // Use built in or binary modules | |
| var crypto = require('crypto'); | |
| var hash = crypto.createHmac("sha1",key).update(signatureBase).digest("base64"); |
tjsingleton
/ heroku_env_logger.rb
Created
May 12, 2011 15:23
Middleware that logs heroku requests into redis.
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| require "csv" | |
| class HerokuEnvLogger | |
| PREFIX = "HerokuRequest" | |
| TIME_STEP = 1.minute * 1000 # ms | |
| EXPIRE_IN = 6.hours | |
| KEYS = %w[HTTP_X_REQUEST_START | |
| HTTP_X_HEROKU_QUEUE_WAIT_TIME | |
| HTTP_X_HEROKU_QUEUE_DEPTH | |
| HTTP_X_HEROKU_DYNOS_IN_USE] |