Modeling and querying method for spatio-temporal data cube with flying area
A technology of spatio-temporal data and query method, applied in the field of computer program algorithm, interactive visual analysis of big data preprocessing, and visual analysis, which can solve problems such as mismatch between results and display
Pending Publication Date: 2020-10-23
ZHEJIANG UNIV OF TECH
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[0005] In order to reduce the time-consuming and memory consumption of the Nanocubes data structure preprocessing scheme during the construction process, the upper limit of the number of different values of a single category dimension is modified to solve the problem that the results of spatial polygon queries do not match the display in special scenarios, and improve the data cube. The portability of the invention is a spatio-temporal data cube modeling and query method with a flight zone, which can realize an interactive visual analysis system with the help of ECharts, and can quickly analyze the data distribution of large-scale spatio-temporal data sets
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[0042] The present invention will be further described below in conjunction with the accompanying drawings. The description of the following examples is provided only to aid the understanding of the present invention. It should be pointed out that for those skilled in the art, without departing from the principle of the present invention, some improvements and modifications can be made to the present invention, and these improvements and modifications also fall within the protection scope of the claims of the present invention.
[0043] refer to Figure 1 ~ Figure 4 , a method for modeling and querying a spatiotemporal data cube with flight zones, the method comprising a modeling process and a query process,
[0044] The modeling process includes steps one to five, as follows:
[0045] Step 1, data preparation, that is, to preprocess the original spatio-temporal data, to obtain figure 1Middle O 1 to O 6 An ordered dataset of , including latitude and longitude coordinates,...
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The invention discloses a modeling and querying method for a spatio-temporal data cube with a flying area, and the method comprises the steps of giving a spatio-temporal data cube with three dimensions: space, category and time, reducing the internal storage in a mode of sharing nodes in the structure, and enabling the category dimension to store the relation between categories and category nodesthrough an increasable mapping structure; in the spatial dimension, using a ray projection algorithm for judging whether nodes are located in a query area or not, meanwhile, by means of the design ofa spatial dimension flight area, cache of part of data can be omitted through high-level spatial nodes of a data structure, and the calculation amount during modeling is reduced; and in the query process, separating the acquisition judgment and the data aggregation calculation of the space nodes, and combining multiple threads and a communication technology among the threads. According to the invention, an interactive visual analysis system can be realized by means of ECharts, and the data distribution of a large-scale spatio-temporal data set can be quickly analyzed.
Description
technical field [0001] The present invention relates to the field of visual analysis and computer program algorithm, in particular to a method for modeling and querying a data cube structure of a data summary generated by spatio-temporal data preprocessing, and belongs to the field of interactive visual analysis of big data preprocessing. Background technique [0002] In the era of big data, the amount of data is increasing rapidly. How to quickly mine potential information from massive data has become an important challenge in the database field at this stage. In the past decade or so, visualization has been widely studied as an emerging discipline, and a large number of visualization tools and display methods have emerged. Its landmark milestone is the development from static graphics to interactive visualization. [0003] Spatio-temporal data are recorded in large quantities in the Internet era, and usually have specific categories. When the data is accumulated, operation...
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IPC IPC(8): G06F30/20G06F16/9537G06F16/29
CPCG06F30/20G06F16/9537G06F16/29
Inventor 江颉汪锴
Owner ZHEJIANG UNIV OF TECH