- 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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[[constraint]] | |
name="k8s.io/apimachinery" | |
revision="1fd2e63a9a370677308a42f24fd40c86438afddf" | |
[[constraint]] | |
name="k8s.io/client-go" | |
branch="release-4.0" |
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import org.specs2._ | |
import matcher._ | |
import execute._ | |
import specification._ | |
// the "larger" context must be mixed-in last | |
class MySpec extends mutable.Specification with Db with Web { | |
// prints | |
// on the web | |
// in the db |
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import shapeless._ | |
sealed trait List[+T] | |
case class Cons[T](hd: T, tl: List[T]) extends List[T] | |
sealed trait Nil extends List[Nothing] | |
case object Nil extends Nil | |
trait Show[T] { | |
def apply(t: T): String | |
} |
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# | |
# Author:: Christopher Peplin (<[email protected]>) | |
# Copyright:: Copyright (c) 2010 Bueda, Inc. | |
# License:: Apache License, Version 2.0 | |
# | |
# Licensed under the Apache License, Version 2.0 (the "License"); | |
# you may not use this file except in compliance with the License. | |
# You may obtain a copy of the License at | |
# | |
# http://www.apache.org/licenses/LICENSE-2.0 |
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trait MyList[+A] { | |
def fold[B](k: Option[(A, B)] => B): B | |
def map[B](f: A => B): MyList[B] = sys.error("Implement me in terms of fold") | |
def flatMap[B](f: A => MyList[B]): MyList[B] = sys.error("Implement me in terms of fold") | |
def headOption: Option[B] = sys.error("Implement me in terms of fold") | |
def tailOption: Option[MyList[B]] = sys.error("Implement me in terms of fold") | |
def isEmpty = sys.error("Implement me in terms of fold") | |
def length = sys.error("Implement me in terms of fold") | |
} |
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object GOption { | |
def some[A](a: A): GOption[A] = new GOption[A] { | |
def cata[B](n: => B, s: A => B): B = sys.error("Implement me") | |
} | |
def none[A]: GOption[A] = new GOption[A] { | |
def cata[B](n: => B, s: A => B): B = sys.error("Implement me") | |
} | |
} | |
trait GOption[+A] { |