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Cache-efficient sweeping-based interval joins for extended Allen relation predicates

Danila Piatov, Sven Helmer, Anton Dignös, Fabio Persia

2021The VLDB Journal20 citationsDOIOpen Access PDF

Abstract

Abstract We develop a family of efficient plane-sweeping interval join algorithms for evaluating a wide range of interval predicates such as Allen’s relationships and parameterized relationships. Our technique is based on a framework, components of which can be flexibly combined in different manners to support the required interval relation. In temporal databases, our algorithms can exploit a well-known and flexible access method, the Timeline Index, thus expanding the set of operations it supports even further. Additionally, employing a compact data structure, the gapless hash map, we utilize the CPU cache efficiently. In an experimental evaluation, we show that our approach is several times faster and scales better than state-of-the-art techniques, while being much better suited for real-time event processing.

Topics & Concepts

Computer scienceJoinsInterval (graph theory)Hash functionCacheRelation (database)Event (particle physics)Set (abstract data type)Parameterized complexityParallel computingTheoretical computer scienceRange (aeronautics)TimelineAlgorithmDatabaseProgramming languageMathematicsCombinatoricsStatisticsPhysicsMaterials scienceQuantum mechanicsComposite materialData Management and AlgorithmsAdvanced Database Systems and QueriesData Mining Algorithms and Applications
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