In this paper, we present a new benchmark to validate the suitability of database systems for interactive visualization workloads. While there exist proposals for evaluating database systems on interactive data exploration workloads, none rely on real user traces for database benchmarking. To this end, our long term goal is to collect user traces that represent workloads with different exploration characteristics. In this paper, we present an initial benchmark that focuses on "crossfilter"-style applications, which are a popular interaction type for data exploration and a particularly demanding scenario for testing database system performance. We make our benchmark materials, including input datasets, interaction sequences, corresponding SQL queries, and analysis code, freely available as a community resource, to foster further research in this area: https://osf.io/9xerb/?view-only=81de1a3f99d04529b6b173a3bd5b4d23.

Database Benchmarking for Supporting Real-Time Interactive Querying of Large Data / Battle, L.; Eichmann, P.; Angelini, M.; Catarci, T.; Santucci, G.; Zheng, Y.; Binnig, C.; Fekete, J. -D.; Drummer, Moritz. - (2020), pp. 1571-1587. (Intervento presentato al convegno ACM Special Interest Group on Management of Data Conference tenutosi a Portland; United States) [10.1145/3318464.3389732].

Database Benchmarking for Supporting Real-Time Interactive Querying of Large Data

Angelini M.
;
Catarci T.
;
Santucci G.
;
Zheng Y.
;
Moritz D.
2020

Abstract

In this paper, we present a new benchmark to validate the suitability of database systems for interactive visualization workloads. While there exist proposals for evaluating database systems on interactive data exploration workloads, none rely on real user traces for database benchmarking. To this end, our long term goal is to collect user traces that represent workloads with different exploration characteristics. In this paper, we present an initial benchmark that focuses on "crossfilter"-style applications, which are a popular interaction type for data exploration and a particularly demanding scenario for testing database system performance. We make our benchmark materials, including input datasets, interaction sequences, corresponding SQL queries, and analysis code, freely available as a community resource, to foster further research in this area: https://osf.io/9xerb/?view-only=81de1a3f99d04529b6b173a3bd5b4d23.
2020
ACM Special Interest Group on Management of Data Conference
interactive data exploration; visualization performance benchmarks
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Database Benchmarking for Supporting Real-Time Interactive Querying of Large Data / Battle, L.; Eichmann, P.; Angelini, M.; Catarci, T.; Santucci, G.; Zheng, Y.; Binnig, C.; Fekete, J. -D.; Drummer, Moritz. - (2020), pp. 1571-1587. (Intervento presentato al convegno ACM Special Interest Group on Management of Data Conference tenutosi a Portland; United States) [10.1145/3318464.3389732].
File allegati a questo prodotto
File Dimensione Formato  
Battle_Database_2020.pdf

solo gestori archivio

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 2.04 MB
Formato Adobe PDF
2.04 MB Adobe PDF   Contatta l'autore

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1419396
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 17
  • ???jsp.display-item.citation.isi??? 10
social impact