gMark: Schema-Driven Generation of Graphs and Queries

Guillaume Bagan 1 Angela Bonifati 2, 3, * Radu Ciucanu 4, 5, * George Fletcher 6, * Aurélien Lemay 7 Nicky Advokaat 6
* Auteur correspondant
1 GOAL - Graphes, AlgOrithmes et AppLications
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
3 BD - Base de Données
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
7 LINKS - Linking Dynamic Data
Inria Lille - Nord Europe, CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
Abstract : Massive graph data sets are pervasive in contemporary application domains. Hence, graph database systems are becoming increasingly important. In the experimental study of these systems, it is vital that the research community has shared solutions for the generation of database instances and query workloads having predictable and controllable properties. In this paper, we present the design and engineering principles of gMark, a domain- and query language-independent graph instance and query workload generator. A core contribution of gMark is its ability to target and control the diversity of properties of both the generated instances and the generated workloads coupled to these instances. Further novelties include support for regular path queries, a fundamental graph query paradigm, and schema-driven selectivity estimation of queries, a key feature in controlling workload chokepoints. We illustrate the flexibility and practical usability of gMark by showcasing the framework's capabilities in generating high quality graphs and workloads, and its ability to encode user-defined schemas across a variety of application domains.
Type de document :
Article dans une revue
IEEE Transactions on Knowledge and Data Engineering, Institute of Electrical and Electronics Engineers, 2016
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https://hal.inria.fr/hal-01402575
Contributeur : Radu Ciucanu <>
Soumis le : jeudi 24 novembre 2016 - 19:31:51
Dernière modification le : mardi 16 janvier 2018 - 16:13:33

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  • HAL Id : hal-01402575, version 1

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Guillaume Bagan, Angela Bonifati, Radu Ciucanu, George Fletcher, Aurélien Lemay, et al.. gMark: Schema-Driven Generation of Graphs and Queries. IEEE Transactions on Knowledge and Data Engineering, Institute of Electrical and Electronics Engineers, 2016. 〈hal-01402575〉

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