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Spatial data management in apache spark: the GeoSpark perspective and beyond / Jia Yu in Geoinformatica, vol 23 n° 1 (January 2019)
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Titre : Spatial data management in apache spark: the GeoSpark perspective and beyond Type de document : Article/Communication Auteurs : Jia Yu, Auteur ; Zongsi Zhang, Auteur ; Mohamed Sarwat, Auteur Année de publication : 2019 Article en page(s) : pp 37 - 78 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] analyse comparative
[Termes IGN] Apache (serveur)
[Termes IGN] arbre k-d
[Termes IGN] arbre quadratique
[Termes IGN] arbre-R
[Termes IGN] données massives
[Termes IGN] Hadoop
[Termes IGN] index spatial
[Termes IGN] performance
[Termes IGN] Spark
[Termes IGN] traitement répartiRésumé : (auteur) The paper presents the details of designing and developing GeoSpark, which extends the core engine of Apache Spark and SparkSQL to support spatial data types, indexes, and geometrical operations at scale. The paper also gives a detailed analysis of the technical challenges and opportunities of extending Apache Spark to support state-of-the-art spatial data partitioning techniques: uniform grid, R-tree, Quad-Tree, and KDB-Tree. The paper also shows how building local spatial indexes, e.g., R-Tree or Quad-Tree, on each Spark data partition can speed up the local computation and hence decrease the overall runtime of the spatial analytics program. Furthermore, the paper introduces a comprehensive experiment analysis that surveys and experimentally evaluates the performance of running de-facto spatial operations like spatial range, spatial K-Nearest Neighbors (KNN), and spatial join queries in the Apache Spark ecosystem. Extensive experiments on real spatial datasets show that GeoSpark achieves up to two orders of magnitude faster run time performance than existing Hadoop-based systems and up to an order of magnitude faster performance than Spark-based systems. Numéro de notice : A2019-225 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10707-018-0330-9 Date de publication en ligne : 22/10/2018 En ligne : http://dx.doi.org/10.1007/s10707-018-0330-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92621
in Geoinformatica > vol 23 n° 1 (January 2019) . - pp 37 - 78[article]Index-supported pattern matching on tuples of time-dependent values / Fabio Valdés in Geoinformatica, vol 21 n° 3 (July - September 2017)
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Titre : Index-supported pattern matching on tuples of time-dependent values Type de document : Article/Communication Auteurs : Fabio Valdés, Auteur ; Ralf Hartmut Güting, Auteur Année de publication : 2017 Article en page(s) : pp 429 - 458 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] appariement de données localisées
[Termes IGN] appariement de modèles conceptuels de données
[Termes IGN] attribut sémantique
[Termes IGN] base de données orientée objet
[Termes IGN] données géologiques
[Termes IGN] données maillées
[Termes IGN] données spatiotemporelles
[Termes IGN] index spatial
[Termes IGN] objet mobile
[Termes IGN] reconstruction d'itinéraire ou de trajectoire
[Termes IGN] Rome
[Termes IGN] trace GPS
[Termes IGN] traitement de données localisées
[Termes IGN] transport routierRésumé : (Auteur) Lately, the amount of mobility data recorded by GPS-enabled (and other) devices has increased drastically, entailing the necessity of efficient processing and analysis methods. In many cases, not only the geographic position, but also additional time-dependent information are traced and/or generated, according to the purpose of the evaluation. For example, in the field of animal behavior research, besides the position of the monitored animal, biologists are interested in further data like the altitude or the temperature at every measuring point. Other application domains comprise the names of streets, places of interest, or transportation modes that can be recorded along with the geographic position of a person. In this paper, we present in detail a framework for analyzing datasets with arbitrarily many time-dependent attributes. This can be considered as a major extension of our previous work, a comprehensive framework for pattern matching on symbolic trajectories with index support. For an efficient processing of different data types, a variable number of indexes of four different types that correspond to the data types of the attributes are applied. We demonstrate the expressiveness and efficiency of our approach by querying a real dataset representing taxi trips in Rome and, particularly, with a broad series of experiments using trajectories generated by BerlinMOD combined with geological raster data. Numéro de notice : A2017-377 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-016-0286-6 En ligne : https://doi.org/10.1007/s10707-016-0286-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85809
in Geoinformatica > vol 21 n° 3 (July - September 2017) . - pp 429 - 458[article]Spatial query based virtual reality GIS analysis platform / Weixi Wang in Neurocomputing, vol (2017)
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Titre : Spatial query based virtual reality GIS analysis platform Type de document : Article/Communication Auteurs : Weixi Wang, Auteur ; Zhihan Lv, Auteur ; Xiaoming Li, Auteur ; et al., Auteur Année de publication : 2017 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] données massives
[Termes IGN] globe virtuel
[Termes IGN] index spatial
[Termes IGN] réalité virtuelle
[Termes IGN] requête spatiale
[Termes IGN] scène virtuelle
[Termes IGN] visualisation 3D
[Termes IGN] WebSIG
[Vedettes matières IGN] GéovisualisationRésumé : (auteur) A virtual reality GIS analysis platform based on spatial query is proposed in this paper. The proposed platform serves 3D digital city and supports integrated VRGIS functions including 3D spatial analysis functions and 3D visualization functions for spatial process. The 3D analysis and visualization of the concerned city massive information are conducted on the platform. The amount of information that can be visualized through this platform is overwhelming, and the GIS-based navigational scheme allows great flexibility in accessing different available data sources. A multi-level mixed three-dimensional space index is built for the virtual scene. Multi-task parallel scheduling and pre-scheduling algorithms are designed to support the distribution and query of spatial data. Experiment result indicates that the designed query algorithm improves the performance of the proposed system. Numéro de notice : A2017-148 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.neucom.2016.06.099 Date de publication en ligne : 11/04/2017 En ligne : http://doi.org/10.1016/j.neucom.2016.06.099 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84643
in Neurocomputing > vol (2017)[article]Finding dense locations in symbolic indoor tracking data: modeling, indexing, and processing / Tanvir Ahmed in Geoinformatica, vol 21 n° 1 (January - March 2017)
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Titre : Finding dense locations in symbolic indoor tracking data: modeling, indexing, and processing Type de document : Article/Communication Auteurs : Tanvir Ahmed, Auteur ; Toren Bach Pedersen, Auteur ; Hua Lu, Auteur Année de publication : 2017 Article en page(s) : pp 119 - 150 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] données spatiotemporelles
[Termes IGN] géolocalisation
[Termes IGN] index spatial
[Termes IGN] positionnement en intérieur
[Termes IGN] requête spatiale
[Termes IGN] système de gestion de bases de données relationnellesRésumé : (auteur) Finding the dense locations in large indoor spaces is very useful for many applications such as overloaded area detection, security control, crowd management, indoor navigation, and so on. Indoor tracking data can be enormous and are not immediately ready for finding dense locations. This paper presents two graph-based models for constrained and semi-constrained indoor movement, respectively, and then uses the models to map raw tracking records into mapping records that represent object entry and exit times in particular locations. Subsequently, an efficient indexing structure called Hierarchical Dense Location Time Index (HDLT-Index) is proposed for indexing the time intervals of the mapping table, along with index construction, query processing, and pruning techniques. The HDLT-Index supports very efficient aggregate point, interval, and duration queries as well as dense location queries. A comprehensive experimental study with both real and synthetic data shows that the proposed techniques are efficient and scalable and outperforms RDBMSs significantly. Numéro de notice : A2017-026 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-016-0276-8 En ligne : http://dx.doi.org/10.1007/s10707-016-0276-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83977
in Geoinformatica > vol 21 n° 1 (January - March 2017) . - pp 119 - 150[article]The direction-constrained k nearest neighbor query dealing with spatio-directional objects / Min-Joong Lee in Geoinformatica, vol 20 n° 3 (July - September 2016)
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Titre : The direction-constrained k nearest neighbor query dealing with spatio-directional objects Type de document : Article/Communication Auteurs : Min-Joong Lee, Auteur ; Dong-Wan Choi, Auteur ; SangYeon Kim, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 471 – 502 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] analyse coût-avantage
[Termes IGN] classification barycentrique
[Termes IGN] données massives
[Termes IGN] index spatial
[Termes IGN] objet géographique
[Termes IGN] plus proche voisin, algorithme du
[Termes IGN] requête spatialeRésumé : (auteur) Finding k nearest neighbor objects in spatial databases is a fundamental problem in many geospatial systems and the direction is one of the key features of a spatial object. Moreover, the recent tremendous growth of sensor technologies in mobile devices produces an enormous amount of spatio-directional (i.e., spatially and directionally encoded) objects such as photos. Therefore, an efficient and proper utilization of the direction feature is a new challenge. Inspired by this issue and the traditional k nearest neighbor search problem, we devise a new type of query, called the direction-constrained k nearest neighbor (DCkNN) query. The DCkNN query finds k nearest neighbors from the location of the query such that the direction of each neighbor is in a certain range from the direction of the query. We develop a new index structure called MULTI, to efficiently answer the DCkNN query with two novel index access algorithms based on the cost analysis. Furthermore, our problem and solution can be generalized to deal with spatio-circulant dimensional (such as a direction and circulant periods of time such as an hour, a day, and a week) objects. Experimental results show that our proposed index structure and access algorithms outperform two adapted algorithms from existing kNN algorithms. Numéro de notice : A2016-378 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-016-0245-2 En ligne : http://dx.doi.org/10.1007/s10707-016-0245-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81145
in Geoinformatica > vol 20 n° 3 (July - September 2016) . - pp 471 – 502[article]The TM-RTree: an index on generic moving objects for range queries / Jianqiu Xu in Geoinformatica, vol 19 n° 3 (July - September 2015)
PermalinkGMOBench: Benchmarking generic moving objects / Jianqiu Xu in Geoinformatica, vol 19 n° 2 (April - June 2015)
PermalinkMapping large spatial flow data with hierarchical clustering / Xi Zhu in Transactions in GIS, vol 18 n° 3 (June 2014)
PermalinkA parcel shape index for use in land consolidation planning / Demetris Demetriou in Transactions in GIS, vol 17 n° 6 (December 2013)
PermalinkDevelopment of a 3-D urbanization index using digital terrain models for surface urban heat island effects / Chih-Da Wu in ISPRS Journal of photogrammetry and remote sensing, vol 81 (July 2013)
PermalinkIndex-based query processing on distributed multidimensional data / George Tsatsanifos in Geoinformatica, vol 17 n° 3 (July 2013)
PermalinkThe SB-index and the HSB-index: efficient indices for spatial data warehouses / Thiago Luís Lopes Siqueira in Geoinformatica, vol 16 n° 1 (January 2012)
PermalinkPermalinkPostGIS pour les néophytes (3ème partie) : Géométries, création de tables et opérateurs élémentaires / Anonyme in Géomatique expert, n° 79 (01/03/2011)
PermalinkExploiting geographic references of documents in a geographical information retrieval system using an ontology-based index / N. Brisaboa in Geoinformatica, vol 14 n° 3 (July 2010)
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