Graph Analytics: Simpler than we think?
Graph analytics are all the rage today with companies rushing to build new software platforms that target just graph analytics all the time. But, are they really that different than many types of iterative data processing? Here we argue that for iterative graph processing, it is not. In fact, one can map BSP-style computation to the good-old relational algebra, with a few extensions for user-defined functions and the ability to express a loop. How can this be done? Consider the common BSP style vertex-centric computation. The canonical graph analytics computation loop looks like this: We can map this generic BSP computation to relational algebra using the following recipe. First, store the graph data in two relational tables, a nodes table (with one tuple for each node), and an edges table (with one edge tuple for each edge in the graph). Then, use the table below to map the BSP computation to relational algebra. Essentially in the relational system, one e