2022 Fiscal Year Final Research Report
GeoFlink: A real-time and highly scalable processing framework for the spatial data streams
| Project/Area Number |
20K19806
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 60080:Database-related
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| Research Institution | National Institute of Advanced Industrial Science and Technology |
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Principal Investigator |
SHAIKH SALMAN AHMED 国立研究開発法人産業技術総合研究所, 情報・人間工学領域, 主任研究員 (30742621)
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| Project Period (FY) |
2020-04-01 – 2023-03-31
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| Keywords | GeoFlink / Scalable Processing / Spatial Stream / Continuous Queries / Spatial Indexing / Range Query / Knn Query / Join Query |
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| Outline of Final Research Achievements |
With the advancement in data collection technologies, there is an increase in spatial data. Spatial data is huge and many time requires real-time processing. This project focuses on the research and development of a scalable and real-time spatial data stream management system GeoFlink.
GeoFlink extends Apache Flink to support spatial data types, indexes and continuous queries over spatial data streams. To enable efficient processing of continuous queries and for the effective data distribution across computing cluster nodes, a gird-based index is introduced. GeoFlink supports spatial range, spatial kNN and spatial join queries on point, multi-point, line, multi-line, polygon and multi-polygon geometry types. Extensive experimental study on real spatial data streams proves that GeoFlink achieves significantly higher query throughput than ordinary Flink processing.
In this project, we published 3 conference and 1 journal papers. GeoFlink is open source and is registered as an AIST IP.
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| Free Research Field |
Data Streams and Distributed Computing
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| Academic Significance and Societal Importance of the Research Achievements |
Our proposed framework GeoFlink enables low-latency continuous queries (range, knn, and join) processing over spatial data streams. The GeoFlink, being real-time spatial data processing framework, can be used for target marketing, disaster management, autonomous driving, robots path guidance, etc.
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