Abstract
With an increasing popularity of graph data and graph processing systems, the need of efficient graph processing and graph query optimization becomes more important. Subgraph isomorphism queries, one of the fundamental graph query types, rely on an accurate cardinality estimation of a single edge of a pattern for efficient query processing. State of the art approaches do not consider two important aspects for cardinality estimation of graph queries on property graphs: the existence of nodes with a high outdegree and functional dependencies between attributes. In this paper we focus on these two challenges and integrate the detection of high-outdegree nodes and functional dependency analysis into the cardinality estimation. We evaluate our approach on two real data sets and compare it against a state-of-the-art query optimizer for property graphs as implemented in Neo4j.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
We use the latest available version: Neo4j 2.3.0-M2.
References
Boldi, P., Rosa, M., Vigna, S.: HyperANF: approximating the neighbourhood function of very large graphs on a budget. In: Proceedings of the WWW 2011, pp. 625–634 (2011)
Cormode, G., Garofalakis, M., Haas, P.J., Jermaine, C.: Synopses for massive data: samples, histograms, wavelets, sketches. Found. Trends Databases 4(1–3), 1–294 (2012)
Iglewicz, B., Hoaglin, D.C.: How to Detect, Handle Outliers. ASQC Quality Press, Milwaukee (1993)
Lee, J., Han, W.-S., Kasperovics, R., Lee, J.-H.: An in-depth comparison ofsubgraph isomorphism algorithms in graph databases. In: Proceedings of the VLDB Endowment, vol. 6, pp. 133–144 (2012)
Lu, Y., Cheng, J., Yan, D., Wu, H.: Large-scale distributed graph computing systems: An experimental evaluation. Proc. VLDB Endow. 8(3), 281–292 (2014)
Martínez-Bazan, N., Águila Lorente, M.A., Muntés-Mulero, V., Dominguez-Sal, D., Gómez-Villamor, S., Larriba-Pey, J.-L.: Efficient graph management based on bitmap indices. In: Proceedings of the IDEAS 2012, pp. 110–119 (2012)
Neumann, T., Moerkotte, G., Sets, C.: Accurate cardinality estimation for RDF queries with multiple joins. In: Proceedings of the ICDE 2011, pp. 984–994 (2011)
Neumann, T., Weikum, G.: RDF-3X: A RISC-style engine for RDF. Proc. VLDB Endow. 1(1), 647–659 (2008)
Palmer, C.R., Gibbons, P.B., Faloutsos, C., ANF: a fast and scalable tool for data mining in massive graphs. In: Proceedings of the SIGKDD 2002, pp. 81–90 (2002)
Papenbrock, T., Ehrlich, J., Marten, J., Neubert, T., Rudolph, J.-P., Schönberg, M., Zwiener, J., Naumann, F.: Functional dependency discovery: an experimental evaluation of seven algorithms. Proc. VLDB Endow. 8(10), 217–228 (2015)
Paradies, M., Lehner, W., Bornhövd, C.: GRAPHITE: an extensible graph traversal framework for relational database management systems. In: Proceedings of the SSDBM 2015, pp. 29: 1–29: 12 (2015)
Paradies, M., Lemke, C., Plattner, H., Lehner, W., Sattler, K.-U., Zeier, A., Krueger, J.: How to juggle columns: an entropy-based approach for table compression. In: Proceedings of the IDEAS 2010, pp. 205–215 (2010)
Rodriguez, M.A., Neubauer, P.: Constructions from dots and lines. Bull. Am. Soc. Inf. Sci. Technol. 36(6), 35–41 (2010)
Seo, S.: A review and comparison of methods for detecting outliers in univariate data sets. Master’s thesis, Faculty of Graduate School of Public Health, University of Pittsburgh (2006)
Shang, H., Zhang, Y., Lin, X., Yu, J.X.: Taming verification hardness: an efficient algorithm for testing subgraph isomorphism. Proc. VLDB Endow. 1(1), 364–375 (2008)
Stocker, M., Seaborne, A., Bernstein, A., Kiefer, C., Reynolds, D.: SPARQL basic graph pattern optimization using selectivity estimation. In: Proceedings of the WWW 2008, pp. 595–604 (2008)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
A Evaluated Queries
A Evaluated Queries
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Paradies, M., Vasilyeva, E., Mocan, A., Lehner, W. (2016). Robust Cardinality Estimation for Subgraph Isomorphism Queries on Property Graphs. In: Wang, F., Luo, G., Weng, C., Khan, A., Mitra, P., Yu, C. (eds) Biomedical Data Management and Graph Online Querying. Big-O(Q) DMAH 2015 2015. Lecture Notes in Computer Science(), vol 9579. Springer, Cham. https://doi.org/10.1007/978-3-319-41576-5_14
Download citation
DOI: https://doi.org/10.1007/978-3-319-41576-5_14
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-41575-8
Online ISBN: 978-3-319-41576-5
eBook Packages: Computer ScienceComputer Science (R0)