2019/03/05 by Amine Mhedhbi, Mhedhbi, Amine, Semih Salihoğlu +1 · 5 citations
Computer Science · #Advanced Database Systems and Queries #Data Management and Algorithms #Databases (cs.DB) #FOS: Computer and information sciences #Graph Theory and Algorithms
paper · pdf · doi:10.48550/arxiv.1903.02076
openalex publication_date 2019/03/05 · openalex created_date 2022/07/29 · openalex updated_date 2026/07/28
We study the problem of optimizing subgraph queries using the new worst-case\noptimal join plans. Worst-case optimal plans evaluate queries by matching one\nquery vertex at a time using multiway intersections. The core problem in\noptimizing worst-case optimal plans is to pick an ordering of the query\nvertices to match. We design a cost-based optimizer that (i) picks efficient\nquery vertex orderings for worst-case optimal plans; and (ii) generates hybrid\nplans that mix traditional binary joins with worst-case optimal style multiway\nintersections. Our cost metric combines the cost of binary joins with a new\ncost metric called intersection-cost. The plan space of our optimizer contains\nplans that are not in the plan spaces based on tree decompositions from prior\nwork. In addition to our optimizer, we describe an adaptive technique that\nchanges the orderings of the worst-case optimal sub-plans during query\nexecution. We demonstrate the effectiveness of the plans our optimizer picks\nand adaptive technique through extensive experiments. Our optimizer is\nintegrated into the Graphflow DBMS.\n