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Construction method of visual modeling job flow scheduling engine

A scheduling engine and construction method technology, applied in the field of power grid informatization, can solve problems such as limitations in use, inability to satisfy visual modeling workflow scheduling, etc., and achieve a good reference effect

Active Publication Date: 2020-11-13
STATE GRID ZHEJIANG ELECTRIC POWER CO MARKETING SERVICE CENT +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The disadvantage is that the job scheduling engine of this patent is mainly used for hierarchical control of operation and maintenance jobs, which cannot satisfy the need for better job flow scheduling for visual modeling, and its use is relatively limited.

Method used

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  • Construction method of visual modeling job flow scheduling engine
  • Construction method of visual modeling job flow scheduling engine

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Experimental program
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Effect test

Embodiment 1

[0032] A method for constructing a visual modeling job flow scheduling engine, such as figure 1 shown, including the following steps:

[0033] Step 1, the system establishes a general definition data model according to the big data modeling and analysis process, and defines the input parameter format for job flow execution;

[0034] Step 2: The system receives job flow execution input parameters, and the system parses the semi-structured data model of job flow execution input parameters into a graph object model according to the constraints of the commonly defined data model;

[0035]Step 3, the system takes the graph object model as the input parameter of the workflow execution module, and analyzes the graph object model through the workflow execution module, so as to build and complete the visual modeling workflow scheduling engine;

[0036] In the step 2, the semi-structured data model of the job flow execution input parameter is parsed into a graph object model. Specifica...

Embodiment 2

[0069] Embodiment 2: A construction method of a visual modeling workflow scheduling engine, its principle and implementation method are basically the same as in Embodiment 1, the difference is that in the calculation of the accuracy of the prediction result of the confusion matrix, select a1, A value in b2, c3...n, if this value is greater than the sum of other values, then the accuracy rate is A=ns / nsall, where ns is a number greater than the sum of other values, and nsall is the sum of all values ​​in the column corresponding to ns and.

[0070] When a certain value is greater than the sum of the remaining other values, it means that this value is the most common result in the confusion matrix, that is, the most common result in the execution input parameters corresponding to the confusion matrix, so it is necessary to judge the accuracy rate corresponding to this value. For example, in the electric power industry, it is necessary to judge the number of normal and abnormal e...

Embodiment 3

[0071] Embodiment 3: A construction method of a visual modeling workflow scheduling engine, its principle and implementation method are basically the same as in Embodiment 1, the difference is that in the calculation of the accuracy of the prediction result of the confusion matrix, select a1, One or several values ​​in b2, c3...n, if such values ​​are smaller than the remaining values, then the accuracy rate is A=nt / ntall, where nt is one or several values ​​that are all smaller than the remaining values, and ntall is The sum of all values ​​in the column corresponding to this type of value. This design is designed flexibly according to the actual situation. For example, in the power industry, it is necessary to estimate the time of grid failure and power outage, and the time of grid failure and power outage accounts for a small amount of the total time. When analyzing the time of grid failure according to actual needs , it is necessary to judge the accuracy of predicting faul...

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Abstract

The invention discloses a construction method of a visual modeling job flow scheduling engine, which comprises the following steps that step 1, the system establishes a general definition data model by a system according to a big data modeling analysis process, and defines a job flow execution parameter entry format; step 2, the system receives a job flow execution parameter, and the system analyzes the semi-structured data model of the job flow execution parameter into a graph object model according to the constraint of the general definition data model; and step 3, the system takes the graphobject model as an input parameter of a workflow execution module, and analyzes the graph object model through the workflow execution module, thereby constructing a visual modeling workflow scheduling engine. The construction method of the visual modeling job flow scheduling engine provides a technical basis for job arrangement and scheduling in the visual modeling direction and the data ETL direction of the power industry, and has good reference significance.

Description

technical field [0001] The invention relates to the technical field of grid information technology, in particular to a method for constructing a visual modeling workflow scheduling engine. Background technique [0002] With the development of informatization construction in the power grid industry, the system has accumulated a large amount of massive data such as marketing business, electricity consumption information, customer service, and statistical reports. However, how to mine the value of massive data is the biggest challenge. Data value There is a lot of room for improvement in the application. [0003] Requirements for visual modeling tools, in a componentized and visualized manner, in accordance with the big data modeling and analysis process, provide data modeling and analysis from data reading, data cleaning, data processing, model construction, model curing, model evaluation, model deployment, etc. The whole process, an integrated closed-loop component, provides...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F8/20G06F16/84G06F16/901G06F16/25G06F16/2458G06F16/215G06Q10/04G06Q50/06
CPCG06F8/20G06Q10/04G06Q50/06G06F16/215G06F16/2465G06F16/254G06F16/86G06F16/9024
Inventor 张宏达杜蜀薇马亮陈仕军胡若云王正国裘炜浩林森叶方斌欧阳柳杨世旺金王英
Owner STATE GRID ZHEJIANG ELECTRIC POWER CO MARKETING SERVICE CENT
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