10:40am–11:20am Wednesday, 07/18/2012
The Apache Hadoop project is becoming the de-facto big-data platform. The community is gearing up the first major release of Hadoop in over 2 years. This talk will cover the major highlights of the release and also the mechanics of what it takes to deliver a major Hadoop release. Arun C Murthy is VP, Apache Hadoop at ASF and the Release Manager for this release.
2:30pm–3:10pm Wednesday, 07/18/2012
This talk will include a review of the breadth of ZooKeeper features and use cases in low latency systems like ad platforms, high latency WAN environment and high throughput deployments. The talk will also include the future roadmap for ZooKeeper.
11:30am–12:10pm Thursday, 07/19/2012
For more than a decade, people have imagined a future where the sequencing of a person's DNA would be as routine a medical practice as a visit to the doctor. We now stand on the cusp of this future, but the volume and complexity of the data exceed our ability to interpret it. Within this challenge lies a major opportunity for software to make a difference in the future of medicine.
10:00am–10:40am Friday, 07/20/2012
In this session, two case studies will be presented on leveraging Big Data and an open source Big Data processing platform to detect relationships at levels not previously detected. This session will give a behind-the-scenes look at how to program rapid data delivery queries with Big Data to solve real world problems along with anecdotal examples from the field.
2:30pm–3:10pm Thursday, 07/19/2012
Advanced 3D visualization has long been relegated to powerful workstations or supercomputers. Recent efforts have extended the open source, scientific computing tools VTK and ParaView to run on the popular Android and iOS mobile platforms. This proposal shows how to run and interact with Big Data on mobile platforms, as well as perform advanced visualization directly on the mobile device.
1:30pm–5:00pm Monday, 07/16/2012
Social media has become the true mirror of the society & no doubt, Twitter is silver behind the glass. An understanding of the underlying network models reflected by the tweets & associated metadata enables one to infer and predict. In this tutorial, we will derive domain metrics like Cliques and Brand Rank by applying SNA principles via Twitter APIs.