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    final boolean doReconnect() {
        Exception failure = null;
        synchronized (reconnectMutex) {

            // First ensure we are up to date.
            doUpdateURIsFromDisk();

            if (disposed || connectionFailure != null) {
                reconnectMutex.notifyAll();
            }

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#!/bin/bash
CNT=10
SLEEP=10
function show_help {
  echo "Usage: $0 -a auth_token -h host [-c count_per_iteration] [-s sleep_after_iteration]"
}

while getopts "h:c:s:a:?" opt; do
    case "$opt" in
    \?)

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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

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package test;

import java.util.Random;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.Future;
import java.util.concurrent.ScheduledExecutorService;
import java.util.concurrent.ScheduledFuture;
import java.util.concurrent.TimeUnit;

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asd

$$a_b+a^c$$

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$ netstat -r
Routing tables

Internet:
Destination        Gateway            Flags        Refs      Use   Netif Expire
127                localhost          UCS             1        0     lo0
localhost          localhost          UH            661 308639805     lo0
192.168.59         link#10            UC              2        0 vboxnet
192.168.59.1       a:0:27:0:0:0       UHLWIi          2   319299     lo0
224.0.0            link#1             UmCS            2        0     lo0

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Internet Scale Services Checklist

A checklist for designing and developing internet scale services, inspired by James Hamilton's 2007 paper "On Desgining and Deploying Internet-Scale Services."

• http://mvdirona.com/jrh/talksandpapers/jamesrh_lisa.pdf

Basic tenets

• Does the design expect failures to happen regularly and handle them gracefully?
• Have we kept things as simple as possible?

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package com.getbase.tracing4j.spring;

import lombok.extern.slf4j.Slf4j;
import org.springframework.context.ApplicationListener;
import org.springframework.context.event.ContextRefreshedEvent;
import org.springframework.web.method.HandlerMethod;
import org.springframework.web.servlet.mvc.condition.PatternsRequestCondition;
import org.springframework.web.servlet.mvc.method.RequestMappingInfo;
import org.springframework.web.servlet.mvc.method.annotation.RequestMappingHandlerMapping;

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package io.opentracing.activation;

import java.util.List;
import java.util.Map;
import org.slf4j.MDC;


public class ActivationTest {

  interface ActiveSpanManager {

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# Cassandra storage config YAML

# NOTE:
#   See http://wiki.apache.org/cassandra/StorageConfiguration for
#   full explanations of configuration directives
# /NOTE

# The name of the cluster. This is mainly used to prevent machines in
# one logical cluster from joining another.
cluster_name: 'Test Cluster'