sangohan

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sangohan

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

sangohan

abstract ArrayRead<T>(Array<T>) from Array<T> {
    @:arrayAccess inline function get(i:Int):T return this[i];
    public var length(get,never):Int;
    inline function get_length() return this.length;
}

sangohan

import haxe.macro.Context;
import haxe.macro.Expr;

using haxe.macro.ExprTools;

class Main
{
    inline static var QUOTED_FIELD_PREFIX = "@$__hx__";

    static function main()

sangohan

    // Live video stream management for HTML5 video. Uses FFMPEG to connect to H.264 camera stream, 
    // Camera stream is remuxed to a MP4 stream for HTML5 video compatibility and segments are recorded for later playback
var liveStream = function (req, resp) {                                            // handle each client request by instantiating a new FFMPEG instance
    // For live streaming, create a fragmented MP4 file with empty moov (no seeking possible).

    var reqUrl = url.parse(req.url, true)
    var cameraName = typeof reqUrl.pathname === "string" ? reqUrl.pathname.substring(1) : undefined;
    if (cameraName) {
        try {
            cameraName = decodeURIComponent(cameraName);

sangohan

#!/bin/sh

# Alot of these configs have been taken from the various places
# on the web, most from here
# https://github.com/mathiasbynens/dotfiles/blob/master/.osx

# Set the colours you can use
black='\033[0;30m'
white='\033[0;37m'
red='\033[0;31m'

sangohan

# bourne shell functions below take 1 argument, the file_to_hash.  
# prints hex digest on stdout

md5() {
  perl -MDigest::MD5=md5_hex -le'print md5_hex(<> or die)' "$1"
  # ruby   -rdigest/md5 -e"puts Digest::MD5.file'/dev/null'"
  # python -sBc "import hashlib;print hashlib.md5(open('$1','rb').read()).hexdigest()"
  # md5 "$1"|cut -d' ' -f4    # mac
  # md5sum "$1"|cut -d' ' -f1 # linux
  # openssl md5 "$1" | grep -o '[[:xdigit:]][[:xdigit:]]*$' | cat

sangohan

# bourne shell functions below take 1 argument, the file_to_hash.  
# prints hex digest on stdout

md5() {
  perl -MDigest::MD5=md5_hex -le'print md5_hex(<> or die)' "$1"
  # ruby   -rdigest/md5 -e"puts Digest::MD5.file'/dev/null'"
  # python -sBc "import hashlib;print hashlib.md5(open('$1','rb').read()).hexdigest()"
  # md5 "$1"|cut -d' ' -f4    # mac
  # md5sum "$1"|cut -d' ' -f1 # linux
  # openssl md5 "$1" | grep -o '[[:xdigit:]][[:xdigit:]]*$' | cat

sangohan

-- show running queries (pre 9.2)
SELECT procpid, age(query_start, clock_timestamp()), usename, current_query 
FROM pg_stat_activity 
WHERE current_query != '<IDLE>' AND current_query NOT ILIKE '%pg_stat_activity%' 
ORDER BY query_start desc;

-- show running queries (9.2)
SELECT pid, age(query_start, clock_timestamp()), usename, query 
FROM pg_stat_activity 
WHERE query != '<IDLE>' AND query NOT ILIKE '%pg_stat_activity%' 

sangohan