Workshop Abstract: Distributed processing of graph data with Neo4j and Apache Spark.In this hands-on session first the main concepts behind graph models and querying of graph data will be introduced by means of both Neo4j’s graph querying language Cypher and Apache Spark’s API for graphs GraphX. Attendees will learn the essential toolbox for analysing unstructured but related data, focusing on relations. Then we will focus on bringing the power of both tools together for smooth processing of your linked data.
Prerequisites: Basic knowledge of graph theory and algorithms would be helpful but not crucial. Some coding experience is also required.
I have updated my training plan to use cloud-based environment, so no installations will be necessary.
Bio: Passionate graphista, co-organiser of Graph Database NRW meetup: https://www.meetup.com/de-DE/G
Experience: IT-Consultant / Software Engineer, PRODYNA AG, Düsseldorf, Germany, (March 2013 to present)
Involved in different projects based on graph models and graph databases for customers of PRODYNA AG (https://www.prodyna.com/neo4j
Python Software Developer, University Library TU München, Germany (June 2012 to February 2013)
Development and maintenance of mediaTUM: https://mediatum.ub.tum.de/604
Education: B. Sc. Mathematics, FernUniversität in Hagen
Bachelor Thesis in graph theory “Vertex-Ranking on Cographs”
Mathematical Technical Software Developer (IHK), Technische Universität München
Talent Award for Trainees (Förderpreis für Auszubildende)