John Leach explains using HBase co-processors to support a full ANSI SQL RDBMS without modifying the core HBase source, showing how Hadoop/HBase can replace traditional RDBMS solutions.
This talk goes over the design motivation for Zen and describe its internals including the API, type system and HBase backend.
Jayesh Thakrar shows what can be done with irb, how to exploit JRuby-Java integration, and demonstrates how the Shell can be used in Hadoop streaming to perform complex and large volume batch jobs.
Matthias Broecheler discusses graph computing, introducing the Aurelius graph cluster enabling graph computing at scale by building on distributed systems like Cassandra, HBase, and Hadoop.
Nicolas Spiegelberg discusses Facebook Messages built on top of HBase, the systems involved and the scaling challenges for handling 500TB of new data per month.
Kumar Palaniapan and Scott Fleming present how NetApp deals with big data using Hadoop, HBase, Flume, and Solr, collecting and analyzing TBs of log data with Think Big Analytics.
Kannan Muthukkaruppan overviews HBase, explaining what Facebook Messages is and why they chose HBase to implement it, their contribution to HBase, and what they plan to use it for in the future.
Kevin Weil presents how Twitter does data analysis using Scribe for logging, base analysis with Pig/Hadoop, and specialized data analysis with HBase, Cassandra, and FlockDB.