LSQB: A large-scale subgraph query benchmark

Amine Mhedhbi, Matteo Lissandrini, Laurens Kuiper, Jack Waudby, Gábor Szárnyas

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

10 Citationer (Scopus)
61 Downloads (Pure)

Abstract

We introduce LSQB, a new large-scale subgraph query benchmark. LSQB tests the performance of database management systems on an important class of subgraph queries overlooked by existing benchmarks. Matching a labelled structural graph pattern, referred to as subgraph matching, is the focus of LSQB. In relational terms, the benchmark tests DBMSs' join performance as a choke-point since subgraph matching is equivalent to multi-way joins between base Vertex and base Edge tables on ID attributes. The benchmark focuses on read-heavy workloads by relying on global queries which have been ignored by prior benchmarks. Global queries, also referred to as unseeded queries, are a type of queries that are only constrained by labels on the query vertices and edges. LSQB contains a total of nine queries and leverages the LDBC social network data generator for scalability. The benchmark gained both academic and industrial interest and is used internally by 5+ different vendors.

OriginalsprogEngelsk
TitelGRADES-NDA '21 : Proceedings of the 4th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences and Systems and Network Data Analytics, GRADES-NDA 2021
RedaktørerVasiliki Kalavri, Nikolay Yakovets
Antal sider11
UdgivelsesstedNew York
ForlagAssociation for Computing Machinery
Publikationsdato20 jun. 2021
Sider8:1-8:11
Artikelnummer8
ISBN (Elektronisk)9781450384773
DOI
StatusUdgivet - 20 jun. 2021
Begivenhed4th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences and Systems and Network Data Analytics, GRADES-NDA 2021 - Virtual, Online, Kina
Varighed: 6 jun. 2021 → …

Konference

Konference4th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences and Systems and Network Data Analytics, GRADES-NDA 2021
Land/OmrådeKina
ByVirtual, Online
Periode06/06/2021 → …
SponsorAlibaba, IBM, Neo4j Inc., SAP, SIGMOD, TigerGraph
NavnProceedings of the 4th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences and Systems and Network Data Analytics, GRADES-NDA 2021

Bibliografisk note

Publisher Copyright:
© 2021 Owner/Author.

Fingeraftryk

Dyk ned i forskningsemnerne om 'LSQB: A large-scale subgraph query benchmark'. Sammen danner de et unikt fingeraftryk.

Citationsformater