bskaggs

FROM python:3.7-alpine3.8

RUN apk add --no-cache \
            build-base \
            cmake \
            bash \
            jemalloc-dev \
            boost-dev \
            autoconf \
            zlib-dev \

anubhavsinha

sudo yum update
sudo yum install -y tar wget
# Install Mesos dependencies
sudo wget http://repos.fedorapeople.org/repos/dchen/apache-maven/epel-apache-maven.repo -O /etc/yum.repos.d/epel-apache-maven.repo
#sudo vi /etc/yum.repos.d/wandisco-svn.repo and add the following content
#[WANdiscoSVN]
#name=WANdisco SVN Repo 1.9
#enabled=1
#baseurl=http://opensource.wandisco.com/centos/7/svn-1.9/RPMS/$basearch/
#gpgcheck=1

debasishg

General Background and Overview

1. 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.
2. Models and Issues in Data Stream Systems
3. 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
4. Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
5. [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep=rep1&t

Xorlev

package storm.examples;

import backtype.storm.task.OutputCollector;
import backtype.storm.task.TopologyContext;
import backtype.storm.topology.OutputFieldsDeclarer;
import backtype.storm.topology.base.BaseRichBolt;
import backtype.storm.tuple.Fields;
import backtype.storm.tuple.Tuple;
import backtype.storm.tuple.Values;
import java.util.Map;

r4vi

(defn words [text] (re-seq #"[a-z]+" (.toLowerCase text)))
 
(defn train [features]
  (reduce (fn [model f] (assoc model f (inc (get model f 1)))) {} features))
 
(def *nwords* (train (words (slurp "big.txt"))))
 
(defn edits1 [word]
  (let [alphabet "abcdefghijklmnopqrstuvwxyz", n (count word)]
    (distinct (concat

omnisis

class StrategyRunner {
	
Map strategyMap = [:]

interface IStrategy {
	boolean apply(arg)
};

def addStrategy(String name, Closure cl) {