SLURP: An Interactive SPARQL Query Planner

被引:0
|
作者
Dresselhaus, Jannik [1 ]
Filippov, Ilya [1 ]
Gengenbach, Johannes [1 ]
Heling, Lars [1 ]
Kaefer, Tobias [1 ]
机构
[1] Karlsruhe Inst Technol, Inst AIFB, Karlsruhe, Germany
来源
关键词
COST;
D O I
10.1007/978-3-030-80418-3_3
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Triple Pattern Fragments (TPFs) allow for querying large RDF graphs with high availability by offering triple pattern-based access to the graphs. The limited expressivity of TPFs leads to higher client-side querying and communication costs with potentially many intermediate results that need to be transferred. Thus, the challenge of devising efficient query plans when evaluating SPARQL queries lies in minimizing these costs. Different heuristics and cost-based query planning approaches have been proposed to obtain such efficient query plans. However, we also require means to visualize, manually modify, and execute alternative query plans, to better understand the differences between existing planning approaches and their potential limitations. To this end, we propose Slurp (https://people.aifb.kit.edu/zg2916/slurp/), an interactive SPARQL query planner that assists RDF data consumers to visualize, modify, and compare the performance of different query execution plans over TPFs.
引用
收藏
页码:15 / 20
页数:6
相关论文
共 50 条
  • [41] RDF partitioning for scalable SPARQL query processing
    Wang, Xiaoyan
    Yang, Tao
    Chen, Jinchuan
    He, Long
    Du, Xiaoyong
    FRONTIERS OF COMPUTER SCIENCE, 2015, 9 (06) : 919 - 933
  • [42] ViziQuer: A Tool to Explore and Query SPARQL Endpoints
    Zviedris, Martins
    Barzdins, Guntis
    SEMANTIC WEB: RESEARCH AND APPLICATIONS, PT II, 2011, 6644 : 441 - 445
  • [43] Solving the SPARQL query containment problem with SpeCS
    Spasic, Mirko
    Janicic, Milena Vujosevic
    JOURNAL OF WEB SEMANTICS, 2023, 76
  • [44] Provenance-Based SPARQL Query Formulation
    Amsterdamer, Yael
    Callen, Yehuda
    DATABASE AND EXPERT SYSTEMS APPLICATIONS, DEXA 2022, PT I, 2022, 13426 : 116 - 129
  • [45] An analytical study of large SPARQL query logs
    Angela Bonifati
    Wim Martens
    Thomas Timm
    The VLDB Journal, 2020, 29 : 655 - 679
  • [46] Ranking the Results of DBpedia Retrieval with SPARQL Query
    Ichinose, Shiori
    Kobayashi, Ichiro
    Iwazume, Michiaki
    Tanaka, Kouji
    SEMANTIC TECHNOLOGY, 2014, 8388 : 306 - 319
  • [47] Effective SPARQL Query on SSD based RDBMS
    Kim, Seokhyun
    Kang, Woon-hak
    Lee, Sang-Won
    PROCEEDINGS OF 2010 3RD IEEE INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND INFORMATION TECHNOLOGY (ICCSIT 2010), VOL 6, 2010, : 575 - 578
  • [48] An Analytical Study of Large SPARQL Query Logs
    Bonifati, Angela
    Martens, Wim
    Timm, Thomas
    PROCEEDINGS OF THE VLDB ENDOWMENT, 2017, 11 (02): : 149 - 161
  • [49] SPARQL Query Answering over OWL Ontologies
    Kollia, Ilianna
    Glimm, Birte
    Horrocks, Ian
    SEMANTIC WEB: RESEARCH AND APPLICATIONS, PT I, 2011, 6643 : 382 - 396
  • [50] Query Results Clustering by Extending SPARQL with CLUSTER BY
    Lawrynowicz, Agnieszka
    ON THE MOVE TO MEANINGFUL INTERNET SYSTEMS: OTM 2009 WORKSHOPS, 2009, 5872 : 826 - 835