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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/26228

Title: Performing OLAP over Graph Data: Query Language, Implementation, and a Case Study
Authors: Gomez, Leticia
Kuijpers, Bart
Vaisman, Alejandro
Issue Date: 2017
Publisher: Assoc computing machinery
Citation: Chatziantoniou, Damianos; Castellanos, Malu; Chrysanthis, Panos K. (Ed.). Proceedings of the eleventh international workshop on real-time business intelligence and analytics, Assoc computing machinery,p. 1-8 (Art N° 6)
Series/Report: ACM International Conference Proceeding Series
Abstract: In current Big Data scenarios, traditional data warehousing and Online Analytical Processing (OLAP) operations on cubes are clearly not sufficient to address the current data analysis requirements. Nevertheless, OLAP operations and models can expand the possibilities of graph analysis beyond the traditional graph-based computation. In spite of this, there is not much work on the problem of taking OLAP analysis to the graph data model. In previous work we proposed a multidimensional (MD) data model for graph analysis, that considers not only the basic graph data, but background information in the form of dimension hierarchies as well. The graphs in our model are node-and edge-labelled directed multi-hypergraphs, called graphoids, defined at several different levels of granularity. In this paper we show how we implemented this proposal over the widely used Neo4J graph database, discuss implementation issues, and present a detailed case study to show how OLAP operations can be used on graphs.
Notes: Gomez, L (reprint author), Inst Tecnol Buenos Aires, Buenos Aires, DF, Argentina, lgomez@itba.edu.ar; bart.kuijpers@uhasselt.be; avaisman@itba.edu.ar
URI: http://hdl.handle.net/1942/26228
DOI: 10.1145/3129292.3129293
ISI #: 000426583400006
ISBN: 9781450354257
Category: C1
Type: Proceedings Paper
Appears in Collections: Research publications

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