MELOGRAPH: Multi-engine WorkfLOw graph processing
Paper i proceeding, 2016

This paper introduces MELOGRAPH, a new system that exposes in the front-end a domain specific language(DSL) for graph processing tasks and in the back-end identifies, ranks and generates source code for the top-N ranked engines. This approach lets the specialized MELOGRAPH be part of a more general multi-engine workflow optimizer. The candidate execution engines are chosen from the contemporaneous Big Data ecosystem: graph databases (e.g. Neo4j, TitanDB, OrientDB, Sparksee/DEX) and robust graph processing frameworks with Java API or packaged libraries of algorithms (e.g. Giraph, Okapi, Flink Gelly, Hama, Gremlin). As MELOGRAPH is work in progress, our current paper stresses upon the state of the art in this field, provides a general architecture and some early implementation insights.

Multi-engine workflow

Big Data ecosystem

Graph processing tasks


Camelia Elena Ciolac

Chalmers, Data- och informationsteknik

Workshops of the EDBT/ICDT 2016 Joint Conference, EDBT/ICDT 2016; Bordeaux; France; 15 March 2016

1613-0073 (ISSN)

Vol. 1558


Data- och informationsvetenskap