Archive for the ‘Aurelius Graph Cluster’ Category

Big Graph Data on Hortonworks Data Platform

Thursday, December 13th, 2012

Big Graph Data on Hortonworks Data Platform by Marko Rodriguez.

The Hortonworks Data Platform (HDP) conveniently integrates numerous Big Data tools in the Hadoop ecosystem. As such, it provides cluster-oriented storage, processing, monitoring, and data integration services. HDP simplifies the deployment and management of a production Hadoop-based system.

In Hadoop, data is represented as key/value pairs. In HBase, data is represented as a collection of wide rows. These atomic structures makes global data processing (via MapReduce) and row-specific reading/writing (via HBase) simple. However, writing queries is nontrivial if the data has a complex, interconnected structure that needs to be analyzed (see Hadoop joins and HBase joins). Without an appropriate abstraction layer, processing highly structured data is cumbersome. Indeed, choosing the right data representation and associated tools opens up otherwise unimaginable possibilities. One such data representation that naturally captures complex relationships is a graph (or network). This post presents Aurelius‘ Big Graph Data technology suite in concert with Hortonworks Data Platform. Moreover, for a real-world grounding, a GitHub clone is described in this context to help the reader understand how to use these technologies for building scalable, distributed, graph-based systems.

If you like graphs at all or have been looking at graph solutions, you are going to like this post.