emres

USER='admin'
PASS='admin'
CLUSTER='dev'
HOST=$(hostname -f):8080

function start(){
  curl -u $USER:$PASS -i -H 'X-Requested-By: ambari' -X PUT -d \
    '{"RequestInfo": {"context" :"Start '"$1"' via REST"}, "Body": {"ServiceInfo": {"state": "STARTED"}}}' \
    http://$HOST/api/v1/clusters/$CLUSTER/services/$1
}

emres

# Wes Floyd April 2015

import sys
import requests
import json
import argparse
import pprint
import time

pp = pprint.PrettyPrinter(indent=4)

emres

1. General Background and Overview

• 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