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 of the query size) for two-dimensional data.
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 …
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 robust spatial database systems and advanced geospatial data storage solutions.
We evaluate our clustering hypergraph model and recursive bipartitioning schemes on a wide range of road network datasets. The results of the conducted experiments show that the proposed model is quite effective in reducing the number of disk accesses incurred by the network operations. ... Range aggregate processing in …
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 …
spatial aggregates is devoted to mechanisms to support range queries, or box queries. Aggregate range queries perform some aggregate operation over spatial or spatiotemporal data that fall into a user speci ed area (the range or box), pos-sibly over some speci ed time window [17, 10, 13]. Such aggregation mechanisms seem to stem …
In this paper, we propose a new index structure called the Adaptively Partitioned Aggregate R-Tree (APART) and query processing algorithms to efficiently …
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 …
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 …
Range-aggregate version of point enclosure queries, 1-d segment intersection, 2-d orthogonal segment intersection (with/without distance constraint) are revisited and we improve the existing results for these problems. We also provide semidynamic (insertions) solutions to some of these problems. ... Range aggregate …
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Figure 5.1: Node accesses vs. query length qL (uniform data) - "Range aggregate processing in spatial databases"
We 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-marized information about objects in a given range rather than individual objects. Thus, a RA query returns an ag-gregation value over objects qualified for a given …
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.
Zeighami S Shahabi C Sharan V (2023) NeuroSketch: Fast and Approximate Evaluation of Range Aggregate Queries with Neural Networks Proceedings of the ACM on Management of Data 10.1145/3588954 1:1 (1-26) Online publication date: 30-May-2023
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 …
SNH [44] introduces a neural database for spatial range queries and adds DP-compliant noise to the input queries to maintain the density features of location data. More recently, NGRAM [14] has ...
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We consider variations of the standard orthogonal range searching motivated by applications in database querying and VLSI layout processing. In a generic instance of such a problem, called a range-aggregate query problem we wish to preprocess a set S of geometric objects such that given a query orthogonal range q, a certain intersection or …
Range Aggregate Processing in Spatial Databases Yufei Tao and Dimitris Papadias Abstract—A range aggregate query returns summarized information about the points …
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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 …
Large amount of uncertain data is inherent in many novel and important applications such as sensor data analysis and mobile data management. A probabilistic threshold range aggregate (PTRA) query retrieves summarized information about the uncertain objects satisfying a range query, with respect to a given probability threshold.
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 …
This paper investigates the MaxRS problem in spatial databases. Given a set O of weighted points and a rectangular region r of a given size, the goal of the MaxRS problem is to find a location of r such that the sum of the weights of all the points covered by r is maximized. This problem is useful in many location-based applications such as …
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 …
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.
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 …
Understanding Geospatial Data. To understand the world of geospatial data, we need to grasp a few basic concepts: Coordinates are geographic "addresses" using latitude and longitude.; Projections transform the Earth's 3D surface onto 2D maps, preserving various spatial attributes.; Datums are reference systems that define the …
The spatial query language support enables users to perform complex spatial operations, such as spatial join, spatial aggregate, and spatial analysis, on the stored data. Spatial database management systems are commonly used in various industries, such as agriculture, urban planning, transportation, and natural resource …