Building an efficient storage model of spatial-temporal information based on HBase. Issue 2 (4th May 2019)

• Record Type: Journal Article
• Authors: Wang, Ke; Liu, Guolin; Zhai, Min; Wang, Zhiwei; Zhou, Chuanyi
• Is Part Of: Journal of spatial science. Volume 64:Issue 2(2019)
• Page Start: 301
• Page End: 317
• Publication Date: 2019-05-04
• Subjects: HBase -- semantic constraint principle -- spatial-temporal information -- meta-semantic object -- query time; Geographic information systems -- Periodicals; Cartography -- Periodicals; Surveying -- Periodicals; Geodesy -- Periodicals; Photogrammetry -- Periodicals; Cartography; Geodesy; Geographic information systems; Photogrammetry; Surveying; Periodicals; 526.05
• DOI: 10.1080/14498596.2018.1440648
• Languages: English
• ISSNs: 1449-8596

Abstract

Abstract: Geographic space is abstracted into a meta-semantic object (MSO), which is regarded as the smallest storage unit according to the semantic constraint principle and the characteristics of spatial-temporal information. An efficient organization and storage method is proposed by adopting the strong expansibility and real-time reading and writing characteristics of HBase through the encapsulation of MSO spatial-temporal information. This paper focuses on the classification and abstraction of geographic spatial-temporal information. The HBase platform is used as a carrier for the storage of massive spatial-temporal data. An HBase storage model is built by constructing a spatial-temporal data table and designing the physical structure of the MSO. By comparing the query time of the proposed model with that of the traditional spatial-temporal data model, the experimental results show that the query speed of the proposed model is higher. This provides a new idea for the organization and storage of massive spatial-temporal data.