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Online Analysis Image and Grid Cube Data Storage Management Method and System

A data storage and management method technology, applied in the field of big data, can solve the problems of high uncertainty and low performance, and achieve the effect of improving application performance, reducing transmission and corresponding computing power consumption

Active Publication Date: 2021-09-28
FUZHOU UNIV
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Problems solved by technology

[0003] The traditional MongoDB image storage method is to put the metadata of remote sensing image data into files and store them in the fs.files of GridFS, fs.chunks store the binary files of the image, and then specify the slice key for fragmentation to support distributed storage and It supports horizontal expansion of the database and is suitable for managing large-scale remote sensing image data. When performing cube online analysis, it is necessary to retrieve relevant 2D images first, and then perform cutting and reconstruction after obtaining all required images. If relevant images are missing or have resolution, etc. The parameters are inconsistent, and intervention in the refactoring process is required, the uncertainty is large, and the performance is not high

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  • Online Analysis Image and Grid Cube Data Storage Management Method and System

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Embodiment Construction

[0014] The technical solutions of the present invention will be described in detail below with reference to the accompanying drawings.

[0015] like figure 1 As shown in the figure, an embodiment of the present invention provides an online instant analysis image and grid cube data storage method. The main processing steps include: storing the image and grid cube in the online instant analysis image with various tile segmentation schemes. Compared with MongoDB on the grid cube application service platform, each storage scheme corresponds to a configuration, obtains the index range of the cube request in the online analysis application, compares the I / O number and data size of each configuration through matching rules, and obtains the data volume conditions. The tile partitioning storage scheme with the least I / O in the next step, access the target data block of the corresponding storage partitioning scheme, and analyze the application after completion.

[0016] Store images an...

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Abstract

The invention relates to a storage management method and system for analyzing image and grid cube data online. The method includes: storing images and grid cubes in multiple tile division schemes, each storage scheme corresponds to a configuration, comparing the number of I / Os and data size of each configuration through matching rules, and obtaining the data size considering the amount of data. The tile partition storage scheme with the least I / O accesses the target data block of the corresponding tile partition storage scheme to improve the online analysis performance of the cube. The cube data storage method based on MongoDB provided by the present invention improves the access efficiency of the cube target data block under the online instant analysis application condition, reduces the transmission of invalid data blocks and the consumption of corresponding computing power, and improves the online instant analysis application performance.

Description

technical field [0001] The invention belongs to the technical field of big data, and in particular relates to a method and system for online analysis of image and grid cube data storage management. Background technique [0002] Today has entered the era of big data, especially the continuous development of earth observation applications, which puts forward new requirements for the online analysis application of multi-dimensional grids. The data volume of multi-dimensional grids increases geometrically with the increase of dimensions. Only part of the data is needed, and the full data access method of traditional images and grids wastes bandwidth and cannot meet the performance requirements of online analysis applications. With the continuous development and maturity of NoSQL database, it can better solve the application requirements of mass storage and online analysis. An important feature of the NoSQL database MongoDB is that it provides GridFS for storing files with a siz...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F3/06
CPCG06F3/061G06F3/064Y02D10/00
Inventor 余劲松弟
Owner FUZHOU UNIV