Evaluation of Optimization Strategies for Incremental Graph Queries

  • Gábor Szárnyas
    Affiliation

    Department of Measurement and Information Systems, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, Hungary; MTA-BME Lendület Research Group on Cyber-Physical Systems, Hungary

  • János Maginecz
    Affiliation

    Department of Measurement and Information Systems, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, Hungary

  • Dániel Varró
    Affiliation

    Department of Measurement and Information Systems, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, Hungary; MTA-BME Lendület Research Group on Cyber-Physical Systems, Hungary

Abstract

The last decade brought considerable improvements in distributed storage and query technologies, known as NoSQL systems. These systems provide quick evaluation of simple retrieval operations and are able to answer certain complex queries in a scalable way, albeit not instantly. Providing scalability and quick response times at the same time for querying large data sets is still a challenging task. Evaluating complex graph queries is particularly difficult, as it requires lots of join, antijoin and filtering operations. This paper presents optimization techniques used in relational database systems and applies them on graph queries. We evaluate various query plans on multiple datasets and discuss the effect of different optimization techniques.

Keywords: graph queries, relational algebra, query optimization
Published online
2017-05-23
How to Cite
Szárnyas, G., Maginecz, J., Varró, D. “Evaluation of Optimization Strategies for Incremental Graph Queries”, Periodica Polytechnica Electrical Engineering and Computer Science, 61(2), pp. 175-192, 2017. https://doi.org/10.3311/PPee.9769
Section
Articles