A Reinforcement Learning Based R-Tree for Spatial Data …
To support efficient processing of spatial queries, such as range queries and KNN queries, spatial databases have relied on delicate indices. The R-Tree [14] is arguably the most popular spatial in-dex that prunes irrelevant data for queries. R-Trees have attracted extensive research interests [1–3, 5, 7, 12, 16, 17, 21, 22, 26, 29, 31–
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Range aggregate processing in spatial databases
Range aggregate processing in spatial databases Abstract: 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).
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Efficient Aggregation Query Processing for Large-Scale
The database part stores three types of data—metadata of grids, raw data, and partial aggregation values. The buffer part temporarily keeps the data to be stored in the database, so that insertion throughput can be improved. The middleware accepts queries and controls the database and the buffer through their APIs for query processing.
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GeoSpark stands out for processing geospatial data at Scale
A spatial range query takes as input a range query window and a Spatial RDD and returns all geometries that intersect/are fully covered by the query window. Assume the user has a Spatial RDD. He or she can use the following code to issue a spatial range query on this Spatial RDD. The output format of the spatial range query …
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Approximate range–sum query answering on data cubes with
Approximate range aggregate queries are one of the most frequent and useful kinds of queries for Decision Support Systems (DSS), as they are widely used in many data analysis tasks. Traditionally, sampling-based techniques have been proposed to tackle this problem. However, their effectiveness degrade when the underlying data …
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MaaSDB: Spatial Databases in the Era of Large Language …
query processing. KEYWORDS Spatial Databases, Large Language Models, Model as a Database ... answer for range count queries. While these studies show that ML models can memorize facts from spatial data, they focus on aggregate queries. Their models output scalar values and not data records. They do not have a natural language-based user …
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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 …
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Processing Continuous k Nearest Neighbor Queries in …
Yu Gu, Ge Yu, and Xiaonan Yu. 2014. An efficient method for k nearest neighbor searching in obstructed spatial databases. Journal of Information Science and Engineering 30 (2014), 1569--1583. ... R-trees with Voronoi diagrams for efficient processing of spatial nearest neighbor queries. ... Xiaochun Yang, Bin Wang, and W. …
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[PDF] Efficient Approximate Range Aggregation Over Large-Scale Spatial
This work proposes the first-of-its-kind approximate algorithms for efficient range aggregation over spatial data federation that devise novel single-silo sampling algorithms that process queries in parallel and design a level sampling based algorithm which reduces the time complexity of local queries at each data silo. Range aggregation …
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18. Module: Using Spatial Databases in QGIS
15. Module: Database Concepts with PostgreSQL; 16. Module: Spatial Database Concepts with PostGIS; 17. The QGIS processing guide; 18. Module: Using Spatial Databases in QGIS. 18.1. Lesson: Working with Databases in the QGIS Browser; 18.2. Lesson: Using DB Manager to work with Spatial Databases in QGIS; 18.3. Lesson: …
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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 …
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Spatial Data Science
9 Large data and cloud native. 9. Large data and cloud native. Code. This chapter describes how large spatial and spatiotemporal datasets can be handled with R, with a focus on packages sf and stars. For practical use, …
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2021 IEEE 37th International Conference on Data Engineering …
FPGA for Aggregate Processing: The Good, The Bad, and The Ugly pp. 1044-1055. ... Spatial-Temporal Similarity for Trajectories with Location Noise and Sporadic Sampling pp. 1224-1235. ... DBSpinner: Making a Case for Iterative Processing in Databases pp. 2399-2410.
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On Efficient Aggregate Nearest Neighbor Query Processing in …
Yiu M L, Mamoulis N, Papadias D. Aggregate nearest neighbor queries in road networks. IEEE Transactions on Knowledge and Data Engineering, 2005, 17(6): 820–833.. Kolahdouzan M R, Shahabi C. Voronoi-based k nearest neighbor search for spatial network databases. In Proc. the 30th VLDB, Aug. 31-Sept. 3, 2004, pp. 840–851.. Zhu L, Jing Y, …
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Spatial Databases
Spatial database management systems [43, 58, 120, 119, 97, 74] aim at the effective and efficient management ... spatial query processing including point, regional, range, and nearest neighbor queries; and spatial data methods using a variety of indexes such as ... set of aggregate shapes. Cardinality is used to quantify multi-shapes. For ...
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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 ...
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Range aggregate processing in spatial databases
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 …
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[PDF] Aggregate Processing of Planar Points | Semantic Scholar
It is shown that, an aggregate window query can be answered in logarithmic worst-case time by an indexing structure called the aP-tree, and efficient cost models that predict the structure size and actual query cost are proposed. Aggregate window queries return summarized information about objects that fall inside a query rectangle (e.g., the …
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Analyzing Range Queries on Spatial Data | Proceedings of the …
Analysis of range queries on spatial (multidimensional) data is both important and challenging. ... Database query processing and optimization (theory) ... Range-aggregate queries on the data cube are powerful tools for analysis in data warehouse environments. Cubetree is a technique materializing a data cube through an …
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Analyzing Range Queries on Spatial Data | Proceedings of the …
Analysis of range queries on spatial (multidimensional) data is both important and challenging. ... Database query processing and optimization (theory) ...
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A Global Feature-Rich Network Dataset of Cities and Dashboard …
Data identification, retrieval, and pre-processing. Several considerations factor into the selection of urban datasets: (1) open source; (2) use case suitability.
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Efficient Approximate Range Aggregation Over Large-Scale Spatial …
The problem is also intensively studied, under the name range-aggregate queries by the spatial database community [1,27, 22] and data warehouse community [11]. However, in this area one typically ...
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[PDF] Efficient Approximate Range Aggregation over Large-scale Spatial
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 each data silo is fixed during query processing. In this work, we propose the first-of-its-kind approximate algorithms for efficient range aggregation over spatial data ...
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Efficient Approximate Range Aggregation over Large-Scale …
In this paper, we define the Federated Range Aggregation (FRA) problem and investigate efficient solutions to range aggregation queries over large-scale spatial data federation. Observing that the underlying applications demand real-time. 2375-026X/22/$31.00 ©2022 IEEE DOI 10.1109/ICDE53745.2022.00156. response of high-frequency queries while ...
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Spatial Analytics with Oracle Database 19c
Oracle. Database provides native storage, querying, and retrieval for 3-dimensional (3D) data, including points, lines, surfaces, triangulated irregular networks (TINs), an alternative to rasters, and point clouds. Spatial R-tree indexing and SQL operators and analysis functions for 3D data are also provided.
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Spatial databases with application to GIS: | Guide books | ACM …
Range-aggregate query problems involving geometric aggregation operations, Nordic Journal of Computing, 13:4, (294-308), Online publication date: 1-Dec-2006. ... Chapter 7 continues in the same vein, extending relational query processing techniques to spatial database queries. Particular attention is given to discussion of the …
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Cyrus Shahabi Education
solving spatial range queries using k-nearest neighbor searches, GeoInformatica 13(4): 483-514 (2009). 28. A. Khoshgozaran, A. Khodaei, M. Sharifzadeh, and C., Shahabi, A Hybrid Aggregation and Compression Technique for Road Network Databases, To appear in the Journal of Knowledge and Information Systems (KAIS), ISSN 0219-1377 (Print) …
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Query processing in spatial database systems | Guide books
Query processing in spatial database systems: declustering and. 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 ...
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Approximation Techniques for Spatial Data
tance. In spatial data management, records in the database have a spatial extent, and users can pose expressive queries such as a spatial join between two relations (join all objects that overlap or are within certain distance of each other) or a range query (report all objects in a selected range, or return an aggregate over the selected objects).
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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 studies spatial indexes that solve such queries efficiently and proposes the aggregate Point-tree (aP-tree), which achieves logarithmic cost to the data set …
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