2020/08/28 by Danila Piatov, Piatov, Danila, Sven Helmer +5
Computer Science · #Advanced Database Systems and Queries #Data Management and Algorithms #Data Mining Algorithms and Applications #Databases (cs.DB) #FOS: Computer and information sciences #H.2.4
paper · pdf · doi:10.48550/arxiv.2008.12665
openalex publication_date 2020/08/28 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We develop a family of efficient plane-sweeping interval join algorithms that can evaluate 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.