chitchcock

Stevey's Google Platforms Rant

I was at Amazon for about six and a half years, and now I've been at Google for that long. One thing that struck me immediately about the two companies -- an impression that has been reinforced almost daily -- is that Amazon does everything wrong, and Google does everything right. Sure, it's a sweeping generalization, but a surprisingly accurate one. It's pretty crazy. There are probably a hundred or even two hundred different ways you can compare the two companies, and Google is superior in all but three of them, if I recall correctly. I actually did a spreadsheet at one point but Legal wouldn't let me show it to anyone, even though recruiting loved it.

I mean, just to give you a very brief taste: Amazon's recruiting process is fundamentally flawed by having teams hire for themselves, so their hiring bar is incredibly inconsistent across teams, despite various efforts they've made to level it out. And their operations are a mess; they don't real

ragingwind

Backend Architectures

Twitter

ror, scala, jetty, erlang, thrift, mongrel, comet server, my-sql, memchached, varnish, kestrel(mq), starling, gizzard, cassandra, hadoop, vertica, munin, nagios, awstats

• Introduce Gizzard of Twitter - 트위터의 새로운 분산 관리 라이브러리 Gizzard를 소개합니다.
• The Architecture Twitter Uses to Deal with 150M Active Users, 300K QPS, a 22 MB/S Firehose, and Send Tweets in Under 5 Seconds
• Scaling Twitter: Making Twitter 10000 Percent Faster

higebu

#!/bin/bash

# You need to install overlayroot
# sudo apt-get install overlayroot

LANG=C

set -e
set -x

dannguyen

Using Python 3 + Google Cloud Vision API's OCR to extract text from photos and scanned documents

Just a quickie test in Python 3 (using Requests) to see if Google Cloud Vision can be used to effectively OCR a scanned data table and preserve its structure, in the way that products such as ABBYY FineReader can OCR an image and provide Excel-ready output.

The short answer: No. While Cloud Vision provides bounding polygon coordinates in its output, it doesn't provide it at the word or region level, which would be needed to then calculate the data delimiters.

On the other hand, the OCR quality is pretty good, if you just need to identify text anywhere in an image, without regards to its physical coordinates. I've included two examples:

####### 1. A low-resolution photo of road signs

staaldraad

# Gawk version
# Remote
grep -v "rem_address" /proc/net/tcp  | awk  '{x=strtonum("0x"substr($3,index($3,":")-2,2)); for (i=5; i>0; i-=2) x = x"."strtonum("0x"substr($3,i,2))}{print x":"strtonum("0x"substr($3,index($3,":")+1,4))}'

# Local
grep -v "rem_address" /proc/net/tcp | awk  '{x=strtonum("0x"substr($2,index($2,":")-2,2)); for (i=5; i>0; i-=2) x = x"."strtonum("0x"substr($2,i,2))}{print x":"strtonum("0x"substr($2,index($2,":")+1,4))}'

# No Gawk
# Local
grep -v "rem_address" /proc/net/tcp  | awk 'function hextodec(str,ret,n,i,k,c){

staaldraad

awk -F: 'END {print "uid:"u" gid:"g" groups:"gg}{if($1=="Uid"){split($2,a," ");u=a[1]}if($1=="Gid"){split($2,a," ");g=a[1]}if($1=="Groups"){gg=$2}}' /proc/self/status