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Finlay Thompson in the audience during "GIN in Practice" at PGCon 2007 at the University of Ottawa. A lead developer for New Zealand's electoral roll management system, Finlay Thompson presented "Developing New Zealand's Electoral Roll on PostgreSQL".
Josh Berkus presenting the "Performance Whack-a-Mole" tutorial at PGCon 2007 at the University of Ottawa. A member of the PostgreSQL core team and the PostgreSQL Lead for Sun Microsystems, Josh Berkus also co-presented "Useful Solaris Tools for PostgreSQL DBAs".
Followup on Greg's talk. Greg insisted I get a photo so that he could show off how engaged he gets people to be. ;-)
Attendees in the audience during Bruce Momjian's PGCon 2007 keynote presentation at the University of Ottawa. PGCon is a conference for users and developers of PostgreSQL.
Heikki Linnakangas in the audience during "Digesting an Open-Source Fair-Use TPC-E Implementation" at PGCon 2007 at the University of Ottawa. A PostgreSQL contributor, Heikki Linnakangas co-presented "PostgreSQL Performance Research".
Greg Sabino Mullane working on his laptop at PGCon 2007 at the University of Ottawa. Greg Sabino Mullane gave the "PL/Perl—Best of Both Worlds" tutorial, presented the "PostgreSQL Version 8 in Action" session, co-presented a PostgreSQL Lightning Talk, and hosted the PostgreSQL Palaver BOF.
Entrada do prédio do auditório, no CCUEC. Fotos das palestras ficaram
"impostáveis"...
___
Para o Projeto Fotocotidiano.
One of the leading factors for bad database performance is slow SQL queries. Slow queries directly impact database performance, which also causes many types of application performance issues. As DBAs, it is critical to monitor, find, and rectify slow queries. Addressing SQL query slow performance is one of the top tasks performed as a part of the database Optimization process. In this video, we will talk about slow queries and how to handle them for some databases. For more details, visit at www.optimizsql.com/
Tratando de explicar como crear un indexador de texto en PostgreSQL antes del partido Chilev/sArgentina.
Project powered by: Tropicana
Site Name:
Freshly Squeezed Election Tweets
"We're not red. We're not blue. We're 100% orange."
Site URL:
Launched:
This morning, when the polls opened!
Tagline:
"A place where you can compare oranges to oranges."
Overview of project:
In an online space where lots of information is streaming in, users need help making sense of what is being said and what it means
The site itself is an abstract visualization of the aggregate conversation on the popular social media platform, Twitter. It shows frequency and context of election-related terms, live as they happen. Consider it a living information graphic: the picture changes over time as the conversation develops over time.
The site will pull a continuous stream of tweets mentioning Obama and McCain. Each tweet is examined for certain key words and phrases.
We have a pre-determined list, but we will be looking out for other words appearing with significant regularity and adding them to the tool.
The data is represented as a series of interconnected half-circles. The bigger the "bubble" the more frequently the term is being used. Each bubble is colored red and blue: if the bubble is mostly red that means the term correlates more strongly with mentions of John McCain, and vice versa: the more blue, the more it's associated with Barack Obama.
Keyword bubbles are themselves connected by half-circles (solid colors only), showing relationships between them. The stronger the connection, the thicker the line.
You can make it show what you want: show only tweets about Obama or McCain, about both, or about one but not the other. If you want to compare the current conversational landscape against a full day's worth of tweets, or even three days, you can do that, too.
You can embed it and go full screen!
Technical Details
How does it work?
We take a sample from Twitter every 30 seconds and analyze them in 50-result batches for associations and term matches. They accumulate for 5 minutes and then we flush sample aggregates to the database. So the database has samples from when it started through present in 5-minute granularity. As new terms trend, they begin to populate on the X-axis.
What's under the hood?
The system back end will be implemented using a Java-based stack and PostgreSQL RDBMS. The presentation will be implemented using Flash targeted to Player 9, standards-compliant XHTML/CSS targeted to modern browser versions with significant market share (Safari 2+, Firefox 2+, IE 6+).
Source: www.AnOrangeAmerica.com