Abstract
The increasing availability and usage of Knowledge Graphs (KGs) on the Web calls for scalable and general-purpose solutions to store this type of data structures. We propose Trident, a novel storage architecture for very large KGs on centralized systems. Trident uses several interlinked data structures to provide fast access to nodes and edges, with the physical storage changing depending on the topology of the graph to reduce the memory footprint. In contrast to single architectures designed for single tasks, our approach offers an interface with few low-level and general-purpose primitives that can be used to implement tasks like SPARQL query answering, reasoning, or graph analytics. Our experiments show that Trident can handle graphs with 1011 edges using inexpensive hardware, delivering competitive performance on multiple workloads.
Original language | English |
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Title of host publication | WWW '20 |
Subtitle of host publication | Proceedings of The Web Conference 2020 |
Editors | Yennun Huang, Irwin King, Tie-Yan Liu, Maarten Steen, van |
Place of Publication | Taipei, Taiwan |
Publisher | Association for Computing Machinery, Inc |
Pages | 1761-1772 |
Number of pages | 12 |
ISBN (Electronic) | 9781450370233 |
DOIs | |
Publication status | Published - 20 Apr 2020 |
Event | 29th International World Wide Web Conference, WWW 2020 - Taipei, Taiwan, Province of China Duration: 20 Apr 2020 → 24 Apr 2020 |
Conference
Conference | 29th International World Wide Web Conference, WWW 2020 |
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Country/Territory | Taiwan, Province of China |
City | Taipei |
Period | 20/04/20 → 24/04/20 |