Instant Google ABC – Germany 09.09.2010

Yesterday Google launched Instant Google for logged in users.

Google Instant ABC served on from Germany 09.09.2010.

With one letter typed, first third results:

a: amazon; aol; att 
b: best buy; bank of america; bing
c: craigslist; cnn; chase
d: dictionary; droid x; dominos
e: ebay; espn; expedia
f: facebook; facebook login; firefox
g: gmail; google maps;
h: hotmail; hulu; home depot
i: ikea; imdb; itunes
j: jet blue; java; justin bieber
k: kohls; kmart; kayak
l: lowes; lost; limewire
m: mapquest; myspace; msn
n: netflix; nordstrom; nba
o: orbitz; office depot; old navy
p: pandora; paypal; pizza hut
q: quotes; qvc; quicktime
r: rei; realtor; redbox
s: sears; skype; sprint
t: target; twitter; tmz
u: usps; ups; utube;
v: verizon; verizon wireless; vlc
w: weather; walmart, white pages
x: xbox; xm radio; xkcd
y: youtube; yahoo; yahoo mail
z: zillow; zappos; zip codes


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Knowledge for every web developer: Performance optimization

We got a great introduction to Yahoo’s experience of performance optimization on their homepage by Nicholas Zakas (Yahoo! Frontend Engineer, @slicknet) at the 2010 Velocity Conference.

This is a must read for every Frontend developer:

The Cost of Customization:

– Spriting is difficult
   Hard to know which images will be on the page together
– Limited image caching
   With content constantly changing, getting images into cache doesn’t help much
– A lot more Javascript/CSS
   And very different, depending on how the user has customized the page

Areas of Focus:
– Time to interactivity
– Ajax Responsiveness
– Perceived performance

Source: Performance on the Yahoo! Homepage (24.06.2010)

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Write-Behind Caching Pattern

I have not used it before, but good to know that this exists. (Learned it today)

The latest version of open source caching framework Ehcache supports write-behind caching and transaction management using Java Transaction API (JTA). It also includes a Hibernate 3.3 caching plugin, Bulk Loading API for clustered caches, and runtime cache reconfiguration.

Source: (May 2010)

A good introduction Write Behind Cache Pattern on Webshere Extreme Scale (sorry no opensource, only commercial)

This article reviewed the write-behind caching scenario and showed how this feature is implemented with WebSphere eXtreme Scale. The write-behind caching function reduces back-end load, decreases transaction response time, and isolates the application from back-end failure. These benefits and its simple configuration make the write-behind caching a truly powerful feature.

Source: (Lan Vuong, Technical Evangelist at IBM, December 2009).

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NoSQL overview presentation for BeJUG – 17/6/2010

A short introduction to NoSQL with Hadopp and Hbase by Steven Noels (Outerthougth Belgium, @stevenn)

Source: NoSQL with Hadoop and HBase

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Performance: Dynatrace on Performance Problems taken from Zappos, Monster, Thomson and Co

A must read for every web development team:

Top 10 Performance Problems taken from Zappos, Monster, Thomson and Co

by Andreas Grabner (Dynatrace, @grabnerandi), Jun 15, 10

For a recent edition of the Swiss Computerworld Magazine we listed our Top 10 Performance Problems as we have seen them over the years when working with our clients. I hope this list is enlightening – and I’ve included follow-up links to the blogs to help better understand how to solve these problems:

#1: Too Many Database Calls

#2: Synchronized to Death

I would add three non-technical problems:

  • #11 ignoring shared nothing architecture
  • #12 missing refactoring according because people believe in ‘never touch a running system’
  • #13 re-invent the wheel what other people solved

Read more: Top 10 Performance Problems taken from Zappos, Monster, Thomson and Co

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Databases: Situations in which graphical models are beneficial

If you are a beginner on graph databases and want to read a nice introduction to graphical models, you can checkout a current article [1]

published by Marko A. Rodriguez (AT&T Interactive, @twarko) and Peter Neubauer (Neo Technology, @peterneubauer):

A graph is a data structure composed of dots (i.e. vertices) and lines (i.e. edges). The dots and lines of a graph can be organized into intricate arrangements. The ability for a graph to denote objects and their relationships to one another allow for a surprisingly large number of things to be modeled as a graph. From the dependencies that link software packages to the wood beams that provide the framing to a house, most anything has a corresponding graph representation. However, just because it is possible to represent something as a graph does not necessarily mean that its graph representation will be useful. If a modeler can leverage the plethora of tools and algorithms that store and process graphs, then such a mapping is worthwhile. This article explores the world of graphs in computing and exposes situations in which graphical models are beneficial.

This article contains also a good short description of recent database types:

  • document database
  • key/value store
  • column store
  • graph database

[1] Source: Construction form Dots and Lines (11 Jun 2010)

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Apple has a way of turning people into automatons controlled by the Borg in Cupertino.


cannot say it better:

Don’t get me wrong. I love Apple and I love Apple products. However, there is a degree of hypocrisy (or shall we call it “situational morality”) that comes into play here. There is nothing “open” about Apple products. Sure, Steve Jobs famously points out that Apple encourages the use of open web standards like HTML5, CSS3 and Javascript, but the devices are nowhere near open.

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