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    Query Optimizations over Decentralized RDF Graphs

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    Type
    Conference Paper
    Authors
    Abdelaziz, Ibrahim cc
    Mansour, Essam
    Ouzzani, Mourad
    Aboulnaga, Ashraf
    Kalnis, Panos cc
    KAUST Department
    Computer Science Program
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Date
    2017-05-18
    Online Publication Date
    2017-05-18
    Print Publication Date
    2017-04
    Permanent link to this record
    http://hdl.handle.net/10754/625591
    
    Metadata
    Show full item record
    Abstract
    Applications in life sciences, decentralized social networks, Internet of Things, and statistical linked dataspaces integrate data from multiple decentralized RDF graphs via SPARQL queries. Several approaches have been proposed to optimize query processing over a small number of heterogeneous data sources by utilizing schema information. In the case of schema similarity and interlinks among sources, these approaches cause unnecessary data retrieval and communication, leading to poor scalability and response time. This paper addresses these limitations and presents Lusail, a system for scalable and efficient SPARQL query processing over decentralized graphs. Lusail achieves scalability and low query response time through various optimizations at compile and run times. At compile time, we use a novel locality-aware query decomposition technique that maximizes the number of query triple patterns sent together to a source based on the actual location of the instances satisfying these triple patterns. At run time, we use selectivity-awareness and parallel query execution to reduce network latency and to increase parallelism by delaying the execution of subqueries expected to return large results. We evaluate Lusail using real and synthetic benchmarks, with data sizes up to billions of triples on an in-house cluster and a public cloud. We show that Lusail outperforms state-of-the-art systems by orders of magnitude in terms of scalability and response time.
    Citation
    Abdelaziz I, Mansour E, Ouzzani M, Aboulnaga A, Kalnis P (2017) Query Optimizations over Decentralized RDF Graphs. 2017 IEEE 33rd International Conference on Data Engineering (ICDE). Available: http://dx.doi.org/10.1109/ICDE.2017.59.
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    2017 IEEE 33rd International Conference on Data Engineering (ICDE)
    Conference/Event name
    33rd IEEE International Conference on Data Engineering, ICDE 2017
    DOI
    10.1109/ICDE.2017.59
    Additional Links
    http://ieeexplore.ieee.org/document/7929955/
    ae974a485f413a2113503eed53cd6c53
    10.1109/ICDE.2017.59
    Scopus Count
    Collections
    Conference Papers; Computer Science Program; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

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