Multi-source heterogeneous spatial data flow method based on Oracle database

Abstract

The invention discloses a multi-source heterogeneous spatial data flow method based on an Oracle database. The method comprises the steps of receiving a data request; determining a database node to be accessed through a spatial data index according to the request; reading multi-source heterogeneous data, and conducting spatial data model transformation according to a spatial data conversion module; conducting simple pretreatment on the conversed data; storing the data or storing the data after processing the data. According to the multi-source heterogeneous spatial data flow method based on the Oracle database, mature relational database spatial data storage and spatial database engine technologies are combined, and by building an integrative vector and raster data storage model, optimizing a spatial data retrieval mechanism and integrating spatial data which is distributed and stored in each spatial database, and the data flow of the heterogeneous spatial data is achieved. An Oracle database data driving engine NMSDE is developed based on the multi-source heterogeneous spatial data flow method, and the tests show that both the storage efficiency and inquiring efficiency of the Oracle database data driving engine NMSDE are superior to ArcSDE.

Description

technical field [0001] The invention relates to the technical field of databases, in particular to a multi-source heterogeneous spatial data flow method based on an Oracle database. Background technique [0002] With the continuous development of spatial geographic information technology, the means of obtaining geographic spatial information have been continuously enriched. Geospatial data presents the characteristics of diverse data sources, differentiated data models, decentralized data storage, complex spatial relationships, and massive quantities. For this reason, various spatial database technologies, spatial data engine technologies, and distributed storage management technologies oriented to data and applications have emerged, which effectively solve the problem of geospatial data storage and management to a certain extent or from a certain aspect. question. [0003] For the storage, organization, management and release of multi-source heterogeneous spatial data, the...

AI Technical Summary

Problems solved by technology

Although many solutions have been proposed for spatial data management based on non-relational databases, they are not widely used in commercial applications. The reasons include: the technology of distributed vector data storage, spatial operation and distributed processing is not perfect, Further exploration and research are needed; there is still insufficient support for multi-source heterogeneous data; there is no good solution for how to integrate spatial data in existing relational databases

[0007] At present, most of the domestic database construction does not have a cloud environment, and the more widely used databases are still mainly concentrated in the two aspects of Oracle-based "extended object-relational database" and "spatial data engine". However, many years of database construction have emerged. Many GIS systems with different architectures make it difficult to share data, low data migration efficiency, difficult multi-source heterogeneous data flow, and difficult data interoperability.

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