- 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
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from __future__ import print_function | |
from random import shuffle, seed | |
from itertools import product | |
from collections import Counter | |
#seed(100) | |
ranks = list('23456789TJQKA') | |
alt_ranks = list('A23456789TJQK') | |
suits = list('CSHD') | |
new_deck = list(product(ranks, suits)) |
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#!/bin/sh | |
# Converts a mysqldump file into a Sqlite 3 compatible file. It also extracts the MySQL `KEY xxxxx` from the | |
# CREATE block and create them in separate commands _after_ all the INSERTs. | |
# Awk is choosen because it's fast and portable. You can use gawk, original awk or even the lightning fast mawk. | |
# The mysqldump file is traversed only once. | |
# Usage: $ ./mysql2sqlite mysqldump-opts db-name | sqlite3 database.sqlite | |
# Example: $ ./mysql2sqlite --no-data -u root -pMySecretPassWord myDbase | sqlite3 database.sqlite |