- 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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import asyncio | |
from concurrent import futures | |
import functools | |
import inspect | |
import threading | |
from grpc import _server | |
def _loop_mgr(loop: asyncio.AbstractEventLoop): |
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"""Download Dash User Docsets and install them in Zeal""" | |
import configparser | |
import json | |
import tarfile | |
import urllib.request | |
from pathlib import Path | |
from sys import platform | |
import easygui |
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// Provides a C++11 implementation of a multi-producer, multi-consumer lock-free queue. | |
// An overview, including benchmark results, is provided here: | |
// http://moodycamel.com/blog/2014/a-fast-general-purpose-lock-free-queue-for-c++ | |
// The full design is also described in excruciating detail at: | |
// http://moodycamel.com/blog/2014/detailed-design-of-a-lock-free-queue | |
// Simplified BSD license: | |
// Copyright (c) 2013-2015, Cameron Desrochers. | |
// All rights reserved. |
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/* | |
* Random-Number Utilities (randutil) | |
* Addresses common issues with C++11 random number generation. | |
* Makes good seeding easier, and makes using RNGs easy while retaining | |
* all the power. | |
* | |
* The MIT License (MIT) | |
* | |
* Copyright (c) 2015-2022 Melissa E. O'Neill | |
* |
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### MATPLOTLIBRC FORMAT | |
# This is a sample matplotlib configuration file - you can find a copy | |
# of it on your system in | |
# site-packages/matplotlib/mpl-data/matplotlibrc. If you edit it | |
# there, please note that it will be overridden in your next install. | |
# If you want to keep a permanent local copy that will not be | |
# over-written, place it in HOME/.matplotlib/matplotlibrc (unix/linux | |
# like systems) and C:\Documents and Settings\yourname\.matplotlib | |
# (win32 systems). |