Wednesday, June 22, 2011

Monetizing the Web



The Revolution will not be monetized by Bob Garfield

Read that. Here are my personal notes.

Problems making money with advertising.
  Supply of too many pages with ads depresses demand.
  Click-through rate less than 1%. Nobody does it on purpose.
  Central advantage, ability to mine data, target people with relevant ads.
  People get a creepy sense of privacy invasion.
  This is being investgated.
  Facebook has a great database for knowing your interests.
  Facebook mostly gets money for third-party ads shown elsewhere.
  Google search allows for targeting interests right at the moment.
  Some hobbyist magazines have ads that readers value as much as the content.

Year 2010
= $164 billion – U.S. Ad market
= $25 billion - Online ad revenue
= $29 billion – Google revenues
> $1 billion – Facebook ad revenue
< $3 per user per year – Facebook
= $25 per user per year - Google
= 31% - of Americans' media-consuming time was on-line
= $1 per hour – print publications
= $.25 per hour – TV
< $.10 per hour – online
= 600 million users – Facebook
= 25 minutes per day per user – Facebook
= 1 billion searches per day - Google
= 2000 employees Facebook
= 26316 employees Google
= 30000 employees Google by end of year

Other time periods
= $1.65 billion Google paid for YouTube




Monday, June 20, 2011

Print button example

Print Test






Saturday, June 18, 2011

Sapphire jobs

Sapphire Technologies


JobTitleLocOpenedClosed
2D/3D Game Artist SF06/18/1106/18/11
BI ETL Developer SF06/18/1106/18/11
Business Systems Analyst SF06/18/1106/18/11
Data Analyst SF06/18/1106/18/11
Data Warehouse Developer - San Francisco, Ca SF06/18/1106/18/11
Flash Engineer SF06/18/1106/18/11
Front End Web Developer - San Francisco, Ca. SF06/18/1106/18/11
IT Quality Engineer SF06/18/1106/18/11
IT Quality Engineer - Web Services SF06/18/1106/18/11
IT Release Engineering Manager SF06/18/1106/18/11
Java Developer with PL/SQL SF06/18/1106/18/11
Mechanical Engineer SF06/18/1106/18/11
Mid-level Oracle Applications Developer SF06/18/1106/18/11
Oracle SCM developer:needed in San Francisco CA SF06/18/1106/18/11
Production Assistant SF06/18/1106/18/11
QA Automation Engineer SF06/18/1106/18/11
Senior IT Quality Engineer SF06/18/1106/18/11
Sr. Data Analyst SF06/17/1106/18/11
Ruby on Rails Developer SF06/16/1106/18/11
SAP R/3 Fi/CO Business Analyst SF06/15/1106/18/11
Database Marketing Analyst SF06/11/1106/18/11
Studio Business Analyst / Developer SF06/11/1106/18/11
Business Analyst SF06/10/1106/18/11
Senior QA Engineer SF06/10/1106/18/11
Middleware Engineer needed in San Francisco CA SF06/04/1106/18/11
Quality Engineer SF06/04/1106/18/11
IT Release Manager SF06/03/1106/18/11
Senior QA Engineer - Data Warehouse SF06/01/1106/18/11
_______________________
Technical Project Manager SF06/04/1106/09/11
Technical Writer SF06/02/1106/03/11

Thursday, June 16, 2011

My Facebook Friends

I have a small circle of friends.
I want to see most of their posts.
This table seems to say a lot about why they are in my Facebook circle



Name Introduction Friends WeeklyPosts
Andy Fahrenwald High School 20 0.1
Angel Green Hip Hop Dance 600 3
Ann B Cox Young Adulthood 200 3
Bill Nelson Sister's family 1000 3
Bron Rich Family 500 2
Carla Kincaid-Yoshikawa Job Club 20 0.1
Chia Hamilton Friend of friend 100 2
Dave Nelson Sister's family 200 3
Edith Rasmussen Partner 20 3
Floyd Dean Johnson Neighbor 50 0.2
Grenville King High School 50 0.3
James A. Nelson Sister's family 20 0.1
James Heaps-Nelson Family 100 0.5
Jarvis Rich Self 40 2
Jay Ulbricht High School 50 0.3
Jeri Jewett King High School 50 0.2
Jim McConville Young Adulthood 20 0.1
Joan Carrier High School 50 0.2
John Lee Evans Young Adulthood 50 0.1
Joyce Ringermacher Family of friend 20 0.1
Julian Roberts Young Adulthood 500 4
Karen Kaes Matteson College 50 0.1
Karen Vander Wall Dutton High School 100 3
Keith Rich Family 100 0.5
Ken Knabb Young Adulthood 100 1
Kimberleigh Miller Family 500 1
Lesley Rich Family 100 0.2
Lisa Harrison Family of friend 200 0.5
Maria Ray Friend of friend 200 4
Marilyn Heaps-Nelson Family 20 0.1
Mary Davidson Neighbor 50 5
Maya Kilmer Family of friend 200 3
Michael Lipsey High School 200 5
Oliah Kraft Friend of friend 100 3
Paprika Becky Fahrenwald Family of friend 100 2
Russ Bliss High School 100 0.1
Sara Fasy Family of friend 100 0.5
Scott Harrison Young Adulthood 100 0.1
Simon Stanfield College 50 0.2
Tina Harrison Family of friend 50 0.1
Tom Drohan Friend of friend 500 3
Tom Heaps-Nelson Family 100 0.1

Wednesday, June 15, 2011

Top 25 Web Sites

Top Sites Alexa Internet Alexa Internet http://www.alexa.com/topsites/global
The top 500 sites on the web. The sites in the top sites lists are ordered by their 1 month alexa traffic rank.

The 1 month rank is calculated using a combination of average daily visitors and pageviews over the past month. The site with the highest combination of visitors and pageviews is ranked #1.


Rank Company Link Note
1 Google http://google.com Enables users to search the world's information, including webpages, images, and videos. Offers...
2 Facebook http://facebook.com A social utility that connects people, to keep up with friends, upload photos, share links and ...
3 YouTube http://youtube.com YouTube is a way to get your videos to the people who matter to you. Upload, tag and share your...
4 Yahoo! http://yahoo.com A major internet portal and service provider offering search results, customizable content, cha...
5 Blogger.com http://blogspot.com Free, automated weblog publishing tool that sends updates to a site via FTP.
6 Baidu.com http://baidu.com The leading Chinese language search engine, provides "simple and reliable" search exp...
7 Wikipedia http://wikipedia.org A free encyclopedia built collaboratively using wiki software. (Creative Commons Attribution-Sh...
8 Windows Live http://live.com Search engine from Microsoft.
9 Twitter http://twitter.com Social networking and microblogging service utilising instant messaging, SMS or a web interface..
10 QQ.COM http://qq.com China's largest and most used Internet service portal owned by Tencent, Inc founded in Nov 1998...
11 MSN http://msn.com Portal for shopping, news and money, e-mail, search, and chat.
12 Yahoo! Japan http://yahoo.co.jp Japanese version of popular portal site.
13 淘宝网 http://taobao.com 包括电脑通讯、数码、男装、女装、童装、化妆品、书籍音像、运动用品、游戏装备等各种商品的买卖,...
14 Google India http://google.co.in Indian version of this popular search engine. Search the whole web or only webpages from India....
15 LinkedIn http://linkedin.com A networking tool to find connections to recommended job candidates, industry experts and busin...
16 新浪新闻中心 http://sina.com.cn 包括即日的国内外不同类型的新闻与评论,人物专题,图库。
17 Amazon.com http://amazon.com Amazon.com seeks to be Earth's most customer-centric company, where customers can find and disc...
18 WordPress.com http://wordpress.com Free blogs managed by the developers of the WordPress software. Includes custom design template …
19 Google谷歌 http://google.com.hk 谷歌搜索在中国的官方网站。
20 Google http://google.de Suche im gesamten Web, in deutschsprachigen sowie in deutschen Seiten. Zusätzlich ist eine Bild...
21 Bing http://bing.com Search engine developed by Microsoft. Features web, image, video, local, news, and product search.ch.
22 Google UK http://google.co.uk The local version of this pre-eminent search engine, offering UK-specific pages as well as worl...
23 eBay http://ebay.com International person to person auction site, with products sorted into categories.
24 Яндекс http://yandex.ru Поиск информации в интернете с учетом русской морфологии, возможность регионального уточнения.
25 网易 Http://163.com 中国最大的网络社区和门户网站
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Tuesday, June 14, 2011

Scalable Datastores


Personal notes on

"10 Rules for Scalable performance in 'Simple Operation' Datastores"
By Michael Stonebraker and Rick Cattell.
From
JUNE 2011 VOL. 54 NO.6 COMMUNICATIONS OF THE ACM 75


The Dominant data storage systems all look about the same today but many new ones are coming.


Systems - Link

Asterdata  http://asterdata.com
BigTable  http://labs.google.com/papers/bigtable.html 
Clustrix  http://clustrix.com
CouchDB  http://couchdb.apache.org
DB2  http://ibm.com/software/data/db2
Dynamo  http://portal.acm.org/citation.cfm?id=1294281
Exadata  http://oracle.com/exadata
Greenplum  http://greenplum.com
HBase  http://hbase.apache.org
HyperTable  http://hypertable.org
MongoDB  http://mongodb.org
MySQL  http://mysql.com/products/enterprise
MySQL Cluster  http://mysql.com/ products/database/cluster
Netezza  http://netezza.com
NimbusDB  http://nimbusdb.com
Oracle  http://oracle.com
Oracle RAC  http://oracle.com/rac
Paraccel  http://paraccel.com
PNUTs  http://research.yahoo.com/pub/2304
PostgreSQL  http://postgresql.org
Riak  http://basho.com/Riak.html
Scalaris  http://code.google.com/p/scalaris
SimpleDB  http://amazon.corn/sirnpledb
SQL Server  http://microsoftcom/sqlserver
Teradata  http://teradata.com
Terrastore  http://code.google.com/p/terrastore
Tokyo Cabinet  http://1978th.net/tokyocabinet
Vertica  http://vertica.com
Voldemort  http://project-voldemort.com
VoltDB  http://voltdb.com


New kinds of stores for simple-operation (SO) databases

Key-value Stores - each object has a key and a payload
Dynamo
Voldemort

Document Stores - objects with a variable number of attributes
CouchDB
MongoDB

Extensible Record Stores
  - variable width record sets, partitioned vertically and horizontally
BigTable
Cassandra

SQL DBMSs - retain SQL and ACID (Atomicity, Consistency, Isolation, Durability
MySQL Cluster


Ten Rules

Look for shared-nothing scalability
High level languages are good and need not hurt performance
Plan to carefully leverage main memory databases
High availability and automatic recovery are essential
Online everything
Avoid multi-node operations
Don't try to build ACID consistency yourself
Look for administrative simplicity
Pay attention to node performance
Open source gives you more control over your future