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BLOCK: Efficient Execution of Spatial Range Queries in Main-Memory.

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Title: BLOCK: Efficient Execution of Spatial Range Queries in Main-Memory.
Authors: Olma, M
Tauheed, F
Heinis, T
Ailamaki, A
Item Type: Conference Paper
Abstract: The execution of spatial range queries is at the core of many applications, particularly in the simulation sciences but also in many other domains. Although main memory in desktop and supercomputers alike has grown considerably in recent years, most spatial indexes supporting the efficient execution of range queries are still only optimized for disk access (minimizing disk page reads). Recent research has primarily focused on the optimization of known disk-based approaches for memory (through cache alignment etc.) but has not fundamentally revisited index structures for memory. In this paper we develop BLOCK, a novel approach to execute range queries on spatial data featuring volumetric objects in main memory. Our approach is built on the key insight that in-memory approaches need to be optimized to reduce the number of intersection tests (between objects and query but also in the index structure). Our experimental results show that BLOCK outperforms known in-memory indexes as well as in-memory implementations of disk-based spatial indexes up to a factor of 7. The experiments show that it is more scalable than competing approaches as the data sets become denser.
Issue Date: 27-Jun-2017
Date of Acceptance: 1-Jun-2017
URI: http://hdl.handle.net/10044/1/59772
DOI: https://dx.doi.org/10.1145/3085504.3085519
ISBN: 978-1-4503-5282-6
Publisher: ACM
Journal / Book Title: SSDBM '17 Proceedings of the 29th International Conference on Scientific and Statistical Database Management
Copyright Statement: © 2017 ACM. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in SSDBM '17 Proceedings of the 29th International Conference on Scientific and Statistical Database Management Article No. 15
Sponsor/Funder: Engineering & Physical Science Research Council (E
European Research Office
Funder's Grant Number: EP/N023242/1
720270
Conference Name: SSDBM '17 Proceedings of the 29th International Conference on Scientific and Statistical Database Management
Publication Status: Published
Start Date: 2017-06-27
Finish Date: 2017-06-29
Conference Place: Chicago
Online Publication Date: 2017-06-27
Appears in Collections:Computing
Faculty of Engineering