GeoFlink: A Distributed and Scalable Framework for the Real-time Processing of Spatial Streams

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Abstract

Apache Flink is an open-source system for scalable processing of batch and streaming data. Flink does not natively support efficient processing of spatial data streams, which is a requirement of many applications dealing with spatial data. Besides Flink, other scalable spatial data processing platforms including GeoSpark, Spatial Hadoop, etc. do not support streaming workloads and can only handle static/batch workloads. To fill this gap, we present GeoFlink, which extends Apache Flink to support spatial data types, indexes and continuous queries over spatial data streams. To enable efficient processing of spatial continuous queries and for the effective data distribution across Flink cluster nodes, a gird-based index is introduced. GeoFlink currently supports spatial range, spatial kNN and spatial join queries on point data type. An experimental study on real spatial data streams shows that GeoFlink achieves significantly higher query throughput than ordinary Flink processing.

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Shaikh, S. A., Mariam, K., Kitagawa, H., & Kim, K. S. (2020). GeoFlink: A Distributed and Scalable Framework for the Real-time Processing of Spatial Streams. In International Conference on Information and Knowledge Management, Proceedings (pp. 3149–3156). Association for Computing Machinery. https://doi.org/10.1145/3340531.3412761

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