A method and system for generate a large graph for testing

A technology of application system and statistical information, which is applied in the field of large image generation for testing, can solve problems such as changes, and achieve more effective testing results

Active Publication Date: 2019-01-22
四川蜀天梦图数据科技有限公司 +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the graph generated by this tool is generated according to a specific data model, and its structure is still relatively fixed and cannot be changed as the application changes

Method used

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  • A method and system for generate a large graph for testing
  • A method and system for generate a large graph for testing
  • A method and system for generate a large graph for testing

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0067] The embodiment of the present invention provides a method for generating a large image for testing, such as figure 1 As shown, it specifically includes the following three steps:

[0068] Step 1, generate the first-scale graph according to the small-scale business data of the application system, and obtain the relevant statistical information of the graph after analysis and processing;

[0069] Step 2, according to the expected second scale map and the data scale of the existing first scale map, calculate the relevant expansion factor, and transform and expand the relevant statistical information;

[0070] Step 3: Generate the basic data, vertex data, and edge data of the second-scale graph according to the relevant statistical information after transformation and expansion, and then generate a second-scale graph that meets the predicted results;

[0071] Wherein, the data scale of the first-scale graph is larger than the data scale of the second-scale graph; therefore...

specific Embodiment approach

[0105] Step 334, process D' sequentially ij For each discrete point in the corresponding new discrete point set, if the g' value is greater than 0, two vertices are extracted from the ID subset to construct the edges of the graph, and the corresponding g' value is reduced by 1, and the corresponding two-tuple (ID ,v') decrement the value of v' by 1 until the value of v' or g' is 0. The specific implementation is as follows:

[0106] First, if the g' value of the current discrete point is greater than 0, extract a vertex ID with a v value other than 0 from the corresponding ID subset. For example, first for the discrete point Q 1 processing, corresponding to g 1 'The value is 90000, which means that 90000 adjacent edges need to be constructed, then a vertex ID is extracted from the corresponding subset X, such as extracting A 1 , with A 1 as a vertex of an edge;

[0107] Second, the edge object of the graph is constructed, and the other vertex ID of the edge is randomly s...

Embodiment 2

[0114] On the basis of the above-mentioned embodiment 1, the embodiment of the present invention also provides a large test image generation system, which is used to realize the method for generating a large test image described in embodiment 1, such as Figure 18 , the system includes:

[0115] The statistical fitting module 10 is used to generate a small graph according to the small-scale business data of the application system, and obtain relevant statistical information of the graph after analysis and processing;

[0116] Transformation and expansion module 20, used to calculate the relevant expansion factor according to the data scale of the expected large picture and the existing small picture, and perform transformation and expansion on the relevant statistical information;

[0117] The large graph generation module 30 is used to generate the basic data, vertex data and edge data of the large graph based on the related statistical information after transformation and ex...

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Abstract

The invention relates to the technical field of graph database testing, in particular to a method and a system for generating a large graph for testing. The method comprises the following steps: generating a first scale graph according to small-scale business data of an application system; analyzing and processing the first scale graph to obtain relevant statistical information of the graph; according to the expected scale and the scale of the first scale map, calculating the correlation expansion factor and transforming and expanding the correlation statistical information, generating a second scale map in accordance with the prediction result according to the correlation statistical information after the transformation expansion; Wherein the data scale of the first scale map is larger than that of the second scale map. The invention takes the small-scale service data of the application system as the input to restore the small-scale diagram, By analyzing and obtaining the distributionlaw of the small graph data, the large graph data can be generated after the expansion of the graph data, which is more consistent with the expected business data of the application system, so that the test of the graph database system software product has more pertinence and effectiveness, and lays the foundation for the smooth online and stable operation of the application system.

Description

【Technical field】 [0001] The invention relates to the technical field of graph database testing, in particular to a method and system for generating large graphs for testing. 【Background technique】 [0002] The rapid development of social information construction has prompted the advent of the era of big data. Traditional relational databases have been unable to support more and more complex application scenarios. In this context, graph databases are easy to handle rich relationships and intuitive data display. The method has received a high degree of attention and has been widely used in analytical systems. In a graph database, data is represented as vertices of the graph, and relationships between data are represented as edges between vertices. The effect of relational databases on storing "relational" data is not good. Using relational patterns often artificially reduces the complexity of relations and hides part of the relational information in the entity attributes of ...

Claims

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Application Information

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IPC IPC(8): G06F11/36
CPCG06F11/3684G06F11/3688
Inventor 李专李海波吕伟李鹏吕继云
Owner 四川蜀天梦图数据科技有限公司
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