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LocationSpark: In-memory Distributed Spatial Query Processing and Optimization [PDF]
Frontiers in Big Data, 2020 Due to the ubiquity of spatial data applications and the large amounts of spatial data that these applications generate and process, there is a pressing need for scalable spatial query processing.
Mingjie Tang +5 more
doaj +4 more sources
SparkGIS: Resource Aware Efficient In-Memory Spatial Query Processing. [PDF]
Proc ACM SIGSPATIAL Int Conf Adv Inf, 2017 Much effort has been devoted to support high performance spatial queries on large volumes of spatial data in distributed spatial computing systems, especially in the MapReduce paradigm.
Baig F, Vo H, Kurc T, Saltz J, Wang F.
europepmc +2 more sources
QUASII: QUery-Aware Spatial Incremental Index. [PDF]
International Conference on Extending Database Technology, 2018 With large-scale simulations of increasingly detailed models and improvement of data acquisition technologies, massive amounts of data are easily and quickly created and collected.
Ailamaki, A +3 more
core +3 more sources
Energy-Efficient Spatial Query-Centric Geographic Routing Protocol in Wireless Sensor Networks [PDF]
Sensors, 2019 In data-centric wireless sensor networks (WSNs), sensing data have a high time–space correlation. Most queries are spatial and used to obtain data in a defined region.
Xing Wang +4 more
doaj +2 more sources
iSPEED: an Efficient In-Memory Based Spatial Query System for Large-Scale 3D Data with Complex Structures. [PDF]
Proc ACM SIGSPATIAL Int Conf Adv Inf, 2017 Liang Y, Kong J, Vo H, Wang F.
europepmc +2 more sources
On Generalizing Collective Spatial Keyword Queries [PDF]
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data, 2018 With the proliferation of spatial-textual data such as location-based services and geo-tagged websites, spatial keyword queries are ubiquitous in real life.
Chan, Harry Kai-Ho +2 more
core +3 more sources
SLBRIN: A Spatial Learned Index Based on BRIN
ISPRS International Journal of Geo-Information, 2023 The spatial learned index constructs a spatial index by learning the spatial distribution, which performs a lower cost of storage and query than the spatial indices.
Lijun Wang +6 more
doaj +1 more source
A PID-Based kNN Query Processing Algorithm for Spatial Data
Sensors, 2022 As a popular spatial operation, the k-Nearest Neighbors (kNN) query is widely used in various spatial application systems. How to efficiently process a kNN query on spatial big data has always been an important research topic in the field of spatial data
Baiyou Qiao +3 more
doaj +1 more source
Efficient Group K Nearest-Neighbor Spatial Query Processing in Apache Spark
ISPRS International Journal of Geo-Information, 2021 Aiming at the problem of spatial query processing in distributed computing systems, the design and implementation of new distributed spatial query algorithms is a current challenge.
Panagiotis Moutafis +3 more
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A SPARK BASED COMPUTING FRAMEWORK FOR SPATIAL DATA [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2017 In this paper, a novel Apache Spark-based framework for spatial data processing is proposed, which includes 4 layers: spatial data storage, spatial RDDs, spatial operations, and spatial query language.
F. Xiao
doaj +1 more source