11 Best Geospatial Database Systems: An In …
Teradata Geospatial is a robust solution for large-scale geospatial data management. Known for its scalability and performance, it offers a range of features that facilitate effective geographic data processing. It also provides …
Range aggregate processing in spatial databases
Figure 2.2: Representation of temporal data - "Range aggregate processing in spatial databases"
Range aggregate processing in spatial databases
A range aggregate query returns summarized information about the points falling in a hyper-rectangle (e.g., the total number of these points instead of their concrete ids). This paper …
Range Aggregate Processing in Spatial Databases
A range aggregate query returns summarized information about the points falling in a hyper-rectangle (e.g., the total number of these points instead of their concrete ids). This paper …
Analyzing the performance of NoSQL vs. SQL databases for Spatial and
Relational databases have been around for a long time and spatial databases have exploited this feature for close to two decades. The recent past has seen the development of NoSQL non-relational databases, which are now being adopted for spatial object storage and handling, too. While SQL databases face scalability and agility challenges and fail to take the advantage of …
Range aggregate processing in spatial databases
Figure 2.1: The aR-tree - "Range aggregate processing in spatial databases"
Range Aggregate Processing in Spatial Databases
4 partially intersects q (e.g., e2) and its child node is fetched to continue the search; (iii) the entry is contained in q (e.g., e3), in which case we simply add the aggregate number of the entry …
Query processing in spatial databases containing obstacles
This paper proposes efficient algorithms for the most important query types, namely, range search, nearest neighbours, e‐distance joins, closest pairs and distance semi‐joins, assuming that both data objects and obstacles are indexed by R‐trees. Despite the existence of obstacles in many database applications, traditional spatial query processing …
Range aggregate processing in spatial databases | IEEE …
A range aggregate query returns summarized information about the points falling in a hyper-rectangle (e.g., the total number of these points instead of their concrete ids). This paper studies spatial indexes that solve such queries efficiently and proposes the aggregate …
Range aggregate processing in spatial databases | IEEE …
A range aggregate query returns summarized information about the points falling in a hyper-rectangle (e.g., the total number of these points instead of their concrete ids). This paper studies spatial indexes that solve such queries efficiently and proposes the aggregate Point-tree (aP-tree), which achieves logarithmic cost to the data set cardinality (independently …
Aggregate keyword routing in spatial database
Keyword search on spatial databases. ICDE, pages 656--665, 2008. Digital Library. Google Scholar [4] K. Deng, S. Sadiq, X. Zhou, H. Xu, G. Fung, and Y. Lu. On group nearest group query processing. ... On Efficient Aggregate Nearest Neighbor Query Processing in Road Networks Journal of Computer Science and Technology 10.1007/s11390-015-1560-z 30 ...
ESTA: An Efficient Spatial-Temporal Range Aggregation …
compared with the baseline spatial-temporal range aggre-gation query processing algorithm in terms of the query delay and energy consumption. The remainder of the paper is organized as follows. Section 2summarizes the state-of-the-art in spatial-temporal range ag-gregation query processing and routing protocols for UAV net-works. The system ...
Clustering spatial networks for aggregate query processing: …
In spatial networks, clustering adjacent data to disk pages is highly likely to reduce the number of disk page accesses made by the aggregate network operations during query processing. For this purpose, different techniques based on the clustering graph model are proposed in the literature.
[PDF] Range aggregate processing in spatial databases
A range aggregate query returns summarized information about the points falling in a hyper-rectangle (e.g., the total number of these points instead of their concrete ids). ...
Range aggregate processing in spatial databases
Figure 5.3: Node accesses vs. query length qL (non-uniform) - "Range aggregate processing in spatial databases"
sbm/sbm range aggregate processing in spatial databases…
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A scalable algorithm for maximizing range sum in spatial databases
A scalable algorithm for maximizing range sum in spatial databases. A scalable algorithm for maximizing range sum in spatial databases. Chin-Wan Chung. 2012, Proceedings of the VLDB Endowment. See Full PDF Download PDF.
Spatial Databases
This research has produced a taxonomy of models for space, conceptual models, spatial query languages and query processing, spatial file organization and indexes, and spatial data mining. However, emerging needs for spatial database systems include the handling of 3-D spatial data, temporal dimension with spatial data, and spatial data ...
A Scalable Algorithm for Maximizing Range Sum in …
spatial preference queries. In this paper, we solve the maximizing range sum (MaxRS) problem in spatial databases. Given a set O of weighted points (a.k.a. objects) and a rectangle r of a given size, the goal of the MaxRS problem is to find a location of r which maximizes the sum of the weights of all the objects covered by r.
[PDF] Efficient Approximate Range Aggregation over Large …
Yet they also challenge the conventional implementation of range aggregation queries because the raw data cannot be shared within the federation and the data partition at …
Approximately processing aggregate range queries on remote spatial
Processing aggregate range queries on remote spatial databases suffers from accessing huge and/or large number of databases that operate autonomously and simple and/or restrictive web API interfaces. To overcome these difficulties, this paper applies a revised version of regular polygon-based search algorithm (RPSA) to approximately search aggregate range …
A Scalable Algorithm for Maximizing Range Sum in Spatial Databases
W e first review the range aggregate processing methods. in spatial databases. The range aggregate (RA) query was. proposed for the scenario where users are interested in sum-
Progressive approximate aggregate queries with a multi …
This work presents an algorithm for answering aggregate queries in multi-dimensional databases, using selective traversal of a Multi-Resolution Aggregate (MRA) tree structure storing point data, and shows that even for exact answering the proposed data structure and algorithm are very fast. Answering aggregate queries like SUM, COUNT, MIN, MAX, AVG …
Authenticated indexing for outsourced spatial databases
The MR-tree is introduced, a space-efficient ADS that supports fast query processing and verification and the MR*-tree, a modified version of the MR- tree, which significantly reduces the VO size through a novel embedding technique. In spatial database outsourcing, a data owner delegates its data management tasks to a location-based service …
Spatial database services for location-aware applications
Spatial databases have been an active area of research for over a decade, addressing the growing data management and analysis needs of spatial applications such as Geographic Information Systems (GIS). ... (range and join queries), parallel processing, etc., which are available for non-spatial data. ... applications can aggregate the location ...
Analyzing the performance of NoSQL vs. SQL databases for Spatial …
Initial results suggest that MongoDB performs better by an average factor of 10x-25x which increases exponentially as the data size increases in both indexed and non-indexed operations, and NoSQL databases may be better suited for simultaneous multiple-user query systems including Web-GIS and mobile-GIS. : Relational databases have been around for a long time …
A Scalable Algorithm for Maximizing Range Sum in …
spatial preference queries . In this paper, we solve the maximizing range sum (MaxRS ) problem in spatial databases. Given a set O of weighted points (a.k.a. objects) and a rectangle r of a given size, the goal of the MaxRS problem is to nd a location of r which maximizes the sum of the weights of all the objects covered by r.
Indexing range sum queries in spatio-temporal databases
The R-tree is known to be one of the most popular index structures to efficiently process window queries in spatial databases. Intuitively, the aggregate R-tree (aR-tree) [7], [10] improves the R-tree's performance in range sum queries by storing, in each intermediate entry, pre-aggregated sums of the objects in the subtree. Fig. 1 shows an example of an aR-tree.
Approximate search algorithm for aggregate k-nearest …
Sato H Narita R (2018) Approximately processing aggregate range queries on remote spatial databases International Journal of Knowledge and Web Intelligence 10.1504/IJKWI.2013.060275 4:4 (314-335) Online publication date: 13-Dec-2018
Query processing in spatial database systems | Guide books
The research question in this thesis concerns how to parallelize the spatial range and join query processing in order to support a high performance spatial database application. Data partitioning for the range query operation involves declustering of spatial data, while data partitioning for the spatial join involves clustering of spatial data.