A hierarchical indexing strategy for optimizing Apache Spark with HDFS to efficiently query big geospatial raster data

A hierarchical indexing strategy for optimizing Apache Spark with HDFS to efficiently query big geospatial raster data

Earth observations and model simulations are generating big multidimensional array-based raster data. However, it is difficult to efficiently query these big raster data due to the inconsistency among the geospatial raster data model, distributed physical data storage model, and the data pipeline in...

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Bibliographic Details
Main Authors: Fei Hu, Chaowei Yang, Yongyao Jiang, Yun Li, Weiwei Song, Daniel Q. Duffy, John L. Schnase, Tsengdar Lee
Format: Article
Language:English
Published: Taylor & Francis Group 2020-03-01
Series:International Journal of Digital Earth
Subjects:
big data
hierarchical indexing
multi-dimensional
apache spark
hdfs
distributed computing
gis
Online Access:http://dx.doi.org/10.1080/17538947.2018.1523957

Internet

http://dx.doi.org/10.1080/17538947.2018.1523957

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