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Robust query processing for linked data fragments

Heling, Lars 1; Acosta, Maribel
1 Institut für Angewandte Informatik und Formale Beschreibungsverfahren (AIFB), Karlsruher Institut für Technologie (KIT)

Abstract:

Linked Data Fragments (LDFs) refer to interfaces that allow for publishing and querying Knowledge Graphs on the Web. These interfaces primarily differ in their expressivity and allow for exploring different trade-offs when balancing the workload between clients and servers in decentralized SPARQL query processing. To devise efficient query plans, clients typically rely on heuristics that leverage the metadata provided by the LDF interface, since obtaining fine-grained statistics from remote sources is a challenging task. However, these heuristics are prone to potential estimation errors based on the metadata which can lead to inefficient query executions with a high number of requests, large amounts of data transferred, and, consequently, excessive execution times. In this work, we investigate robust query processing techniques for Linked Data Fragment clients to address these challenges. We first focus on robust plan selection by proposing CROP, a query plan optimizer that explores the cost and robustness of alternative query plans. Then, we address robust query execution by proposing a new class of adaptive operators: Polymorphic Join Operators. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000148684
Veröffentlicht am 14.07.2022
Originalveröffentlichung
DOI: 10.3233/SW-212888
Scopus
Zitationen: 5
Web of Science
Zitationen: 3
Dimensions
Zitationen: 6
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Angewandte Informatik und Formale Beschreibungsverfahren (AIFB)
Publikationstyp Zeitschriftenaufsatz
Publikationsdatum 31.05.2022
Sprache Englisch
Identifikator ISSN: 2210-4968, 1570-0844
KITopen-ID: 1000148684
Erschienen in Semantic Web
Verlag IOS Press
Band 13
Heft 4
Seiten 623–657
Nachgewiesen in Web of Science
Scopus
Dimensions
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