Spatial data storage management system based on big data storage architecture

Abstract

The invention discloses a spatial data storage management system based on a big data storage architecture. The system comprises a bottom layer big data heterogeneous storage module, a middle layer element information base and engine module and a top layer service module, wherein the underlying big data heterogeneous storage module performs storage by taking data resources as units, and a specificmedium comprises a plurality of heterogeneous storage environments; the middle layer element information base and engine module is composed of four parts of a sagittal grid data ETL, a data engine, aelement information base and a sagittal grid visualization engine. The top-layer service module is responsible for providing unified and standard services for the outside. According to the scheme, data resources are aggregated through the meta information base, heterogeneous storage is set up for different computing (application) modes on the bottom layer, data are effectively decomposed, the resources are aggregated, unified and standard services are provided for the outside, and efficient storage management of huge, heterogeneous and incremental spatial big data is achieved.

Description

technical field [0001] The invention belongs to the technical field of big data storage management, and relates to a spatial data storage management system based on a big data storage architecture. Background technique [0002] With the increasing ability of remote sensing data acquisition, the amount of data acquired in a single star day is calculated in terabytes, and these big data have the characteristics of spatial structure, that is, spatial data. Spatial data itself has a high-density value, and each data unit is associated with a spatial location, reflecting certain spatial attributes. [0003] Early spatial data storage and management methods are extremely effective heterogeneous spatial data storage management systems based on relational databases, but due to the high consistency requirements of relational databases for data, the scalability of the underlying storage is weak, and there are Data segmentation and merging are difficult problems. [0004] In the late...

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Problems solved by technology

[0006] The purpose of the present invention is to provide a spatial data storage management system based on a big data storage architecture. Aiming at the problem that the general big data architecture is still difficult to apply to spatial data storage management, a "meta information library-heterogeneous storage-computing The new architecture of "Model" aggregates data resources with the meta information base, builds heterogeneous storage for different computing (application) modes at the bottom layer, effectively decomposes data, aggregates resources, and provides unified and standard services to the outside world. Efficient storage management of huge, heterogeneous and incremental spatial big data

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