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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/25092

Title: Performing OLAP over Graph Data: Query Language, Implementation, and a Case Study
Authors: Gómez, Letizia
Kuijpers, Bart
Vaisman, Alejandro
Issue Date: 2017
Publisher: ACM
Citation: Chatziantoniou, Damianos; Castellanos, Malú; Chrysanthis, Panos K. (Ed.). BIRTE '17 Proceedings of the International Workshop on Real-Time Business Intelligence and Analytics, ACM,p. 6:1-6:8 (Art N° 6)
Series/Report: ACM International Conference Proceeding Series
Series/Report no.: 01533
Abstract: In current Big Data scenarios, traditional data warehousing and On- line Analytical Processing (OLAP) operations on cubes are clearly not su cient to address the current data analysis requirements. Nev- ertheless, 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 pro- posed a multidimensional (MD) data model for graph analysis, that considers not only the basic graph data, but background informa- tion in the form of dimension hierarchies as well. The graphs in our model are node- and edge-labelled directed multi-hypergraphs, called graphoids, de ned at several di erent 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.
URI: http://hdl.handle.net/1942/25092
DOI: 10.1145/3129292.3129293
ISBN: 9781450354257
Category: C1
Type: Proceedings Paper
Appears in Collections: Research publications

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