gMark: Schema-Driven Generation of Graphs and Queries - Archive ouverte HAL Access content directly
Journal Articles IEEE Transactions on Knowledge and Data Engineering Year : 2017

gMark: Schema-Driven Generation of Graphs and Queries

(1) , (2) , (3, 4) , (5) , (6) , (5)
1
2
3
4
5
6

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.

Dates and versions

hal-01402575 , version 1 (24-11-2016)

Identifiers

Cite

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, 2017, 29 (4), pp.856-869. ⟨10.1109/TKDE.2016.2633993⟩. ⟨hal-01402575⟩
385 View
0 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More