The key lesson of this session, presented by Lino Ramirez, is that it’s all about empowering people. Perl gives us the power to empower people.

I really enjoyed the video of a tae kwon do match as a real-world analog of software development. Try one technique, see the result (get hit); try another technique, see the result (get knocked down); ad infinitum.

There are three phases: preparation, modeling, and implementation. These phases are not linear in nature. One moves between phases as necessary to design the solution.

PDL was demonstrated in the modeling phase. Brad was pretty happy when one of the slides contained a web site address for information on PDL, which happened to be a web server at his job.

As he delved into the case studies, I started to zone out, so I have little to say about his examples of machine learning and Perl in action. I wanted to enjoy this session more, since I’ve often wanted to get back into using neural networks and other machine learning techniques in my code. Unfortunately, I just found it too difficult to follow his case studies. Still, I have some good pointers for packages that will help me sprinkle some machine learning goodness in my code.

I like his conclusion: “Perl excels at empowering people in all three phases of the development of a machine learning application.” Perl is awesome for rapid application development, which in turn gets solutions to people who need them faster.

Lunch is over and I’m sitting in the first of two mid-afternoon sessions I’ve chosen on Perl technologies. The first one with Tim Bunce, the extremely knowledgeable author of DBI. He’s presenting DBD::Gofer, a stateless proxy driver for DBI.

This session is very much like other sessions I’ve attended. It’s essentially a brain dump of as many features Tim can squeeze into the alloted time as possible. It’s almost too much to follow. It’s certainly too much to take notes. Fortunately, he’s told us the slides will be available on-line.

From the description of the session, I had hoped DBD::Gofer would scratch an itch we have at work. Essentially, we need to ensure data finds its way into a database, even if the database may not be available. We have a custom solution at the moment, but it would be great if we could replace it with a packaged, maintained module. However, it appears that, while DBD::Gofer makes an excellent proxy, it wouldn’t fit our needs.

Examples have included connection pooling and load balancing, often to reduce load on the main database server. It’s apparent from the use cases that this module was developed for use by heavily trafficked web sites (its development was sponsored by Shopzilla.com). It’s design is modular, so perhaps it can be extended to do what we want. I won’t know until I’ve had a chance to look at the distribution.

Some interesting things for the future are HTTP caching and JSON, effectively turning DBI into a web service. This is cool. I can see this opening up a lot of possibilities as more applications are constructed from individual services, complete in their own right.