Working Efficiently with Large Geodata Files using Ad-hoc Queries

Pascal Bormann, Pascal Bormann, Michel Krämer, Michel Krämer, Hendrik Würz, Hendrik Würz

2022

Abstract

Working with large geospatial data such as building models or point clouds typically requires an index structure to enable fast queries. Creating such an index is a time-consuming process. Especially in single-user explorative scenarios, as they are often found in the scientific community, creating an index or importing the data into a database management system (DBMS) might be unnecessary. In this position paper, we show through a series of experiments that modern commodity hardware is fast enough to perform many query types ad-hoc on unindexed building model and point cloud data. We show how searching in unindexed data can be sped up using simple techniques and trivial data layout adjustments. Our experiments show that ad-hoc queries often can be answered in interactive or near-interactive time without an index, sometimes even outperforming the DBMS. We believe our results provide valuable input and open up possibilities for future research.

Paper Citation

in Harvard Style

Bormann P., Krämer M. and Würz H. (2022). Working Efficiently with Large Geodata Files using Ad-hoc Queries. In Proceedings of the 11th International Conference on Data Science, Technology and Applications - Volume 1: DATA, ISBN 978-989-758-583-8, pages 438-445. DOI: 10.5220/0011291200003269

in Bibtex Style

@conference{data22,
author={Pascal Bormann and Michel Krämer and Hendrik Würz},
title={Working Efficiently with Large Geodata Files using Ad-hoc Queries},
booktitle={Proceedings of the 11th International Conference on Data Science, Technology and Applications - Volume 1: DATA,},
year={2022},
pages={438-445},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011291200003269},
isbn={978-989-758-583-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Data Science, Technology and Applications - Volume 1: DATA,
TI - Working Efficiently with Large Geodata Files using Ad-hoc Queries
SN - 978-989-758-583-8
AU - Bormann P.
AU - Krämer M.
AU - Würz H.
PY - 2022
SP - 438
EP - 445
DO - 10.5220/0011291200003269