SPARTex: A Vertex-Centric Framework for RDF Data Analytics

A growing number of applications require combining SPARQL queries with generic graph search on RDF data. However, the lack of procedural capabilities in SPARQL makes it inappropriate for graph analytics. Moreover, RDF engines focus on SPARQL query evaluation whereas graph management frameworks perform only generic graph computations. In this work, we bridge the gap by introducing SPARTex, an RDF analytics framework based on the vertex-centric computation model. In SPARTex, user-defined vertex-centric programs can be invoked from SPARQL as stored procedures. SPARTex allows the execution of a pipeline of graph algorithms without the need for multiple reads/writes of input data and intermediate results. We use a cost-based optimizer for minimizing the communication cost. SPARTex evaluates queries that combine SPARQL and generic graph computations orders of magnitude faster than existing RDF engines.

coming soon

Relevant Publications:
Ibrahim Abdelaziz, Razen Harbi, Semih Salihoglu, Panos Kalnis and Nikos Mamoulis. SPARTex: A Vertex-Centric Framework for RDF Data Analytics. PVLDB 8(12): 1880-1891 (2015)‚Äč