Pyneapple-G: Scalable Spatial Grouping Queries

Laila Abdelhafeez, Andres Calderon-Romero, Amr Magdy, Vassilis J. Tsotras

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1 Cita (Scopus)

Resumen

This paper demonstrates Pynapple-G, an open-source library for scalable spatial grouping queries based on Apache Sedona (formerly known as GeoSpark). We demonstrate two modules, namely, SGPAC and DDCEL, that support grouping points, grouping lines, and polygon overlays. The SGPAC module provides a large-scale grouping of spatial points by highly complex polygon boundaries. The grouping results aggregate the number of spatial points within the boundaries of each polygon. The DDCEL module provides the first parallelized algorithm to group spatial lines into a DCEL data structure and discovers planar polygons from scattered line segments. Exploiting the scalable DCEL, we support scalable overlay operations over multiple polygon layers to compute the layers’ intersection, union, or difference. To showcase Pyneapple-G, we have developed a frontend web application that enables users to interact with these modules, select their data layers or data points, and view results on an interactive map. We also provide interactive notebooks demonstrating the superiority and simplicity of Pyneapple-G to help social scientists and developers explore its full potential.

Idioma originalInglés
Páginas (desde-hasta)4469-4472
Número de páginas4
PublicaciónProceedings of the VLDB Endowment
Volumen17
N.º12
DOI
EstadoPublicada - 2024
Publicado de forma externa
Evento50th International Conference on Very Large Data Bases, VLDB 2024 - Guangzhou, China
Duración: 24 ago. 202429 ago. 2024

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