Tim Berglund
Greater Maryland Software Symposium
Columbia · July 13 - 14, 2012
VP Developer Relations at Confluent
Tim is a teacher, author, and technology leader with Confluent, where he serves as the Vice President of Developer Relations. He is a regular speaker at conferences and a presence on YouTube explaining complex technology topics in an accessible way. He tweets as @tlberglund, blogs every few years at http://timberglund.com. He has three grown children and two grandchildren, a fact about which he is rather excited.
Presentations
NoSQL Smackdown 2012
Alternative databases continue to establish their role in the technology stack of the future—and for many, the technology stack of the present. Making mature engineering decisions about when to adopt new products is not easy, and requires that we learn about them both from an abstract perspective and from a very concrete one as well. If you are going to recommend a NoSQL database for a new project, you're going to have to look at code.
Connected Data with Neo4j
Neo4j is an open-source, enterprise-class database with a conventional feature set and a very unconventional data model. Like the databases we're already used to, it offers support for Java, ACID transactions, and a feature-rich query language. But before you get too comfortable, you have to wrap your mind around its most important feature: Neo4j is a graph database, built precisely to store graphs efficiently and traverse them more performantly than relational, document, or key/value databases ever could.
Git Workshop (Bring A Laptop)
Git is a version control system you may have been hearing a bit about lately. But simply hearing more about it may not be enough to convince you of its value. Getting hands on experience is what really counts. In this workshop, you'll bring your Windows, Mac or Linux laptop and walk through downloading, installing, and using Git in a collaborative fashion.
Hadoop
When you want to measure fractions of a millimeter, you get a micrometer. When you want to measure centimeters, you get a ruler. When you want to measure kilometers, you might use a laser beam. The abstract task is the same in all cases, but the tools differ significantly based on the size of the measurement.
Likewise, there are some computations that can be done quickly on data structures that fit into memory. Some can't fit into memory, but will fit on the direct-attached disk of a single computer. But when you've got many terabytes or even petabytes of data, you need tooling adapted to the scale of the task. Enter Hadoop.
Gradle Workshop (Bring a Laptop)
Gradle. Another build tool? Come on! But before you say that, take a look at the one you are already using.
Whether your current tool is Make, Rake, Ant, or Maven, Gradle has a lot to offer. It leverages a strong object model like Maven, but a mutable, not predetermined one. Gradle relies on a directed acyclic graph (DAG) lifecycle like Maven, but one that can be customized. Gradle offers imperative build scripting when you need it (like Ant), but declarative build approaches by default (like Maven). In short, Gradle believes that conventions are great – as long as they are headed in the same direction you need to go. When you need to customize something in your build, your build tool should facilitate that with a smile, not a slap in the face. And customizations should be in a low-ceremony language like Groovy. Is all this too much to ask?