DC Field
Value
Language
dc.contributor.author
Grasmann, Lukas
-
dc.contributor.author
Pichler, Reinhard
-
dc.contributor.author
Selzer, Alexander
-
dc.contributor.editor
Geerts, Floris
-
dc.contributor.editor
Vandevoort, Brecht
-
dc.date.accessioned
2024-02-06T16:06:15Z
-
dc.date.available
2024-02-06T16:06:15Z
-
dc.date.issued
2023
-
dc.identifier.citation
<div class="csl-bib-body"> <div class="csl-entry">Grasmann, L., Pichler, R., &#38; Selzer, A. (2023). Integration of Skyline Queries into Spark SQL. In F. Geerts &#38; B. Vandevoort (Eds.), <i>Proceedings 26th International Conference on Extending Database Technology (EDBT 2023)</i> (pp. 337–350). OpenProceedings.org. https://doi.org/10.48786/edbt.2023.27</div> </div>
-
dc.identifier.uri
http://hdl.handle.net/20.500.12708/193564
-
dc.description.abstract
Skyline queries are frequently used in data analytics and multicriteria decision support applications to filter relevant information from big amounts of data. Apache Spark is a popular framework for processing big, distributed data. The framework even provides a convenient SQL-like interface via the Spark SQL module. However, skyline queries are not natively supported and require tedious rewriting to fit the SQL standard or Spark's SQL-like language. The goal of our work is to fill this gap. We thus provide a full-fledged integration of the skyline operator into Spark SQL. This allows for a simple and easy to use syntax to input skyline queries. Moreover, our empirical results show that this integrated solution by far outperforms a solution based on rewriting into standard SQL.
en
dc.description.sponsorship
WWTF Wiener Wissenschafts-, Forschu und Technologiefonds
-
dc.description.sponsorship
FWF - Österr. Wissenschaftsfonds
-
dc.language.iso
en
-
dc.relation.ispartofseries
Advances in database technology
-
dc.rights.uri
http://creativecommons.org/licenses/by-nc-nd/4.0/
-
dc.subject
Spark SQL
en
dc.subject
Data Analytics
en
dc.subject
Skyline Queries
en
dc.subject
Solution
en
dc.subject
Apache Spark
en
dc.subject
Analyzer
en
dc.subject
Logical Plan
en
dc.subject
Algorithm
en
dc.subject
Optimizations
en
dc.title
Integration of Skyline Queries into Spark SQL
en
dc.type
Inproceedings
en
dc.type
Konferenzbeitrag
de
dc.rights.license
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
en
dc.rights.license
Creative Commons Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International
de
dc.relation.isbn
978-3-89318-093-6
-
dc.description.startpage
337
-
dc.description.endpage
350
-
dc.relation.grantno
VRG18-013
-
dc.relation.grantno
P30930-N35
-
dc.rights.holder
© 2023 Copyright held by the owner/author(s).
-
dc.type.category
Full-Paper Contribution
-
dc.relation.eissn
2367-2005
-
tuw.booktitle
Proceedings 26th International Conference on Extending Database Technology (EDBT 2023)
-
tuw.container.volume
26
-
tuw.peerreviewed
true
-
tuw.book.ispartofseries
Advances in database technology
-
tuw.relation.publisher
OpenProceedings.org
-
tuw.project.title
Scalable Reasoning in Knowledge Graphs
-
tuw.project.title
HyperTrac: hypergraph Decompositions and Tractability
-
tuw.researchTopic.id
I1
-
tuw.researchTopic.name
Logic and Computation
-
tuw.researchTopic.value
100
-
tuw.publication.orgunit
E192-02 - Forschungsbereich Databases and Artificial Intelligence
-
tuw.publisher.doi
10.48786/edbt.2023.27
-
dc.identifier.libraryid
AC17204181
-
dc.description.numberOfPages
14
-
tuw.author.orcid
0000-0002-1760-122X
-
tuw.author.orcid
0000-0002-6867-5448
-
dc.rights.identifier
CC BY-NC-ND 4.0
en
dc.rights.identifier
CC BY-NC-ND 4.0
de
tuw.editor.orcid
0000-0001-7212-4625
-
tuw.event.name
26th International Conference on Database Theory, (EDBT/ICDT 2023)
en
tuw.event.startdate
28-03-2023
-
tuw.event.enddate
31-03-2023
-
tuw.event.online
On Site
-
tuw.event.type
Event for scientific audience
-
tuw.event.place
Ioannina
-
tuw.event.country
GR
-
tuw.event.presenter
Grasmann, Lukas
-
wb.sciencebranch
Informatik
-
wb.sciencebranch
Mathematik
-
wb.sciencebranch.oefos
1020
-
wb.sciencebranch.oefos
1010
-
wb.sciencebranch.value
80
-
wb.sciencebranch.value
20
-
item.languageiso639-1
en
-
item.openairetype
conference paper
-
item.grantfulltext
open
-
item.fulltext
with Fulltext
-
item.cerifentitytype
Publications
-
item.mimetype
application/pdf
-
item.openairecristype
http://purl.org/coar/resource_type/c_5794
-
item.openaccessfulltext
Open Access
-
crisitem.author.dept
E192-02 - Forschungsbereich Databases and Artificial Intelligence
-
crisitem.author.dept
E192-02 - Forschungsbereich Databases and Artificial Intelligence
-
crisitem.author.dept
E192-02 - Forschungsbereich Databases and Artificial Intelligence
-
crisitem.author.orcid
0000-0002-1760-122X
-
crisitem.author.orcid
0000-0002-6867-5448
-
crisitem.author.parentorg
E192 - Institut für Logic and Computation
-
crisitem.author.parentorg
E192 - Institut für Logic and Computation
-
crisitem.author.parentorg
E192 - Institut für Logic and Computation
-
crisitem.project.funder
WWTF Wiener Wissenschafts-, Forschu und Technologiefonds
-
crisitem.project.funder
FWF - Österr. Wissenschaftsfonds
-
crisitem.project.grantno
VRG18-013
-
crisitem.project.grantno
P30930-N35
-
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