Bitmap-Based On-Line Analytical Processing of Time Interval Data

Philipp Meisen (), Tobias Meisen, Diane Keng, Marco Recchioni and Sabina Jeschke
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Philipp Meisen: IMA/ZLW & IfU, RWTH Aachen University
Tobias Meisen: IMA/ZLW & IfU, RWTH Aachen University
Diane Keng: Santa Clara University, School of Engineering
Marco Recchioni: Inform GmbH Aachen, Airport Division
Sabina Jeschke: IMA/ZLW & IfU, RWTH Aachen University

A chapter in Automation, Communication and Cybernetics in Science and Engineering 2015/2016, 2016, pp 907-922 from Springer

Abstract: Abstract On-line analytical processing is in the focus of research over the last couple decades. Several papers dealing with summarizability problems, cube computations, query languages, fact-dimension relationships or different types of hierarchies have been published. Nowadays, analyzing time interval data became ubiquitous. Nevertheless, the use of established, reliable, and proven technologies like OLAP is desirable in this respect. In this paper, we present an OLAP system capable to process time interval data. The system is based on bitmaps, enabling performant selection and fast aggregation. Moreover, we introduce a two-step aggregation technique, which enables the calculation of relevant measures in the context of time interval data. We evaluate the performance of our system using different bitmap implementations and a real-world data set. To our knowledge, there are no other systems available enabling OLAP and providing correct results considering the summarizability of time interval data.

Keywords: Time Interval Data; Time Series; Bitmap; On-Line Analytical Processing; Two-Step Aggregation (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-42620-4_68

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DOI: 10.1007/978-3-319-42620-4_68

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