Advanced search
Start date
Betweenand
Related content
(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Analyzing spatial analytics systems based on Hadoop and Spark: A user perspective

Full text
Author(s):
de Carvalho Castro, Joao Pedro [1, 2] ; Chaves Carniel, Anderson [3] ; Dutra de Aguiar Ciferri, Cristina [1]
Total Authors: 3
Affiliation:
[1] Univ Sao Paulo, Dept Comp Sci, Sao Paulo - Brazil
[2] Fed Univ Minas Gerais UFMG, Comp Ctr CECOM, Belo Horizonte, MG - Brazil
[3] Fed Univ Technol Parana UTFPR, Dois Vizinhos - Brazil
Total Affiliations: 3
Document type: Journal article
Source: SOFTWARE-PRACTICE & EXPERIENCE; v. 50, n. 12, p. 2121-2144, DEC 2020.
Web of Science Citations: 1
Abstract

Spatial analytics systems (SASs) represent a technology capable of managing huge volumes of spatial data using frameworks such as Apache Hadoop and Apache Spark. An increasing number of SASs have been proposed, requiring a comparison among them. However, existing comparisons in the literature provide asystem-centricview based on performance evaluations. Thus, there is a lack of comparisons based on theuser-centricview, that is, comparisons that help users to understand how the characteristics of SASs are useful to meet the specific requirements of their spatial applications. In this article, we provide a user-centric comparison of the following SASs based on Hadoop and Spark: Hadoop-GIS, SpatialHadoop, SpatialSpark, GeoSpark, GeoMesa Spark, SIMBA, LocationSpark, STARK, Magellan, SparkGIS, and Elcano. This comparison employs an extensive set of criteria related to the general characteristics of these systems, to the aspects of spatial data handling, and to the aspects inherent to distributed systems. Based on this comparison, we introduce guidelines to help users to choose an appropriate SAS. We also describe two case studies based on real-world applications to illustrate the use of these guidelines. Finally, we discuss chronological tendencies related to SASs and identify limitations that SASs should address to improve user experience. (AU)

FAPESP's process: 18/22277-8 - Processing of OLAP and SOLAP Queries on Parallel and Distributed Environments
Grantee:Cristina Dutra de Aguiar
Support Opportunities: Regular Research Grants