Efficiently Pinpointing SPARQL Query Containments

被引:4
|
作者
Stadler, Claus [1 ]
Saleem, Muhammad [1 ]
Ngomo, Axel-Cyrille Ngonga [2 ]
Lehmann, Jens [3 ,4 ]
机构
[1] Univ Leipzig, Comp Sci Inst, D-04109 Leipzig, Germany
[2] Univ Paderborn, Warburger Str 100, D-33098 Paderborn, Germany
[3] Univ Bonn, Comp Sci Inst 3, Smart Data Analyt Grp, Bonn, Germany
[4] Fraunhofer IAIS, Enterprise Informat Syst Dept, D-53757 St Augustin, Germany
来源
WEB ENGINEERING, ICWE 2018 | 2018年 / 10845卷
基金
欧盟地平线“2020”;
关键词
D O I
10.1007/978-3-319-91662-0_16
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Query containment is a fundamental problem in database research, which is relevant for many tasks such as query optimisation, view maintenance and query rewriting. For example, recent SPARQL engines built on Big Data frameworks that precompute solutions to frequently requested query patterns, are conceptually an application of query containment. We present an approach for solving the query containment problem for SPARQL queries - the W3C standard query language for RDF datasets. Solving the query containment problem can be reduced to the problem of deciding whether a sub graph isomorphism exists between the normalized algebra expressions of two queries. Several state-of-the-art methods are limited to matching two queries only, as well as only giving a boolean answer to whether a containment relation holds. In contrast, our approach is fit for view selection use cases, and thus capable of efficiently enumerating all containment mappings among a set of queries. Furthermore, it provides the information about how two queries' algebra expression trees correspond under containment mappings. All of our source code and experimental results are openly available.
引用
收藏
页码:210 / 224
页数:15
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