Ravi Magham mravi

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

	//==================================================================
	// SPARK INSTRUMENTATION
	//==================================================================

	import com.codahale.metrics.{MetricRegistry, Meter, Gauge}
	import org.apache.spark.{SparkEnv, Accumulator}
	import org.apache.spark.metrics.source.Source
	import org.joda.time.DateTime
	import scala.collection.mutable

	#! /usr/bin/env python

	import redis
	import random
	import pylibmc
	import sys

	r = redis.Redis(host = 'localhost', port = 6389)
	mc = pylibmc.Client(['localhost:11222'])