Autoren:	Bouros, Panagiotis Mamoulis, Nikos Tsitsigkos, Dimitrios Terrovitis, Manolis
Titel:	In-Memory Interval Joins
Online-Publikationsdatum:	4-Jul-2022
Erscheinungsdatum:	2021
Sprache des Dokuments:	Englisch
Zusammenfassung/Abstract:	The interval join is a popular operation in temporal, spatial, and uncertain databases. The majority of interval join algorithms assume that input data reside on disk and so, their focus is to minimize the I/O accesses. Recently, an in-memory approach based on plane sweep (PS) for modern hardware was proposed which greatly outperforms previous work. However, this approach relies on a complex data structure and its parallelization has not been adequately studied. In this article, we investigate in-memory interval joins in two directions. First, we explore the applicability of a largely ignored forward scan (FS)-based plane sweep algorithm, for single-threaded join evaluation. We propose four optimizations for FS that greatly reduce its cost, making it competitive or even faster than the state-of-the-art. Second, we study in depth the parallel computation of interval joins. We design a non-partitioning-based approach that determines independent tasks of the join algorithm to run in parallel. Then, we address the drawbacks of the previously proposed hash-based partitioning and suggest a domain-based partitioning approach that does not produce duplicate results. Within our approach, we propose a novel breakdown of the partition-joins into mini-joins to be scheduled in the available CPU threads and propose an adaptive domain partitioning, aiming at load balancing. We also investigate how the partitioning phase can benefit from modern parallel hardware. Our thorough experimental analysis demonstrates the advantage of our novel partitioning-based approach for parallel computation.
DDC-Sachgruppe:	004 Informatik 004 Data processing
Veröffentlichende Institution:	Johannes Gutenberg-Universität Mainz
Organisationseinheit:	FB 08 Physik, Mathematik u. Informatik
Veröffentlichungsort:	Mainz
ROR:	https://ror.org/023b0x485
DOI:	http://doi.org/10.25358/openscience-7287
Version:	Published version
Publikationstyp:	Zeitschriftenaufsatz
Nutzungsrechte:	CC BY
Informationen zu den Nutzungsrechten:	https://creativecommons.org/licenses/by/4.0/
Zeitschrift:	The VLDB Journal 30
Seitenzahl oder Artikelnummer:	667 691
Verlag:	Springer
Verlagsort:	Berlin u.a.
Erscheinungsdatum:	2021
ISSN:	0949-877X
DOI der Originalveröffentlichung:	10.1007/s00778-020-00639-0
Enthalten in den Sammlungen:	JGU-Publikationen