Method and system for constructing visual component model data and electronic equipment

Abstract

The invention relates to a visual component model data construction method and system and electronic equipment. The scheme comprises the following steps: initializing model data; initializing filtering parameters; traversing the node data, and distributing the node ID of each node; establishing a set membership of nodes through connecting line data in the model data; traversing the node data; screening out correct root nodes and output nodes; analyzing and verifying all the nodes and adding analysis results to the corresponding nodes; storing and converting the successfully analyzed data and then returning the data to the front end; enabling the front end to verify the returned data; if verification fails, prompting the user to continue to modify the model; if verification succeeds, running the analyzed model. The method has the advantages that a multi-component, multi-data-source and large-data-volume query scene is supported, and model data constructed by the front-end component is correctly, efficiently and easily processed and analyzed into executable SQL statements.

Description

technical field [0001] The invention relates to the technical field of data processing, in particular to a method, system and electronic equipment for constructing visual component model data. Background technique [0002] Visual modeling (VISUALMODELING) is a way of thinking about problems by organizing models around realistic ideas. Models are useful for understanding the problem, communicating with everyone involved in the project (clients, industry experts, analysts, designers, etc.), simulating business processes, preparing documents, designing programs and databases. Modeling facilitates a better understanding of requirements, cleaner designs, and easier-to-maintain systems. Visual modeling is the process of graphically describing the developed system. Visual modeling allows you to bring up the necessary details of a complex problem and filter out unnecessary details. It also provides a mechanism for looking at the system being developed from different perspectives....

AI Technical Summary

Problems solved by technology

[0003] At present, many types of relational databases, such as MySQL, Oracle, SQLServer, etc., these databases follow the SQL standard. Usually, developers and technicians use this type of database to operate the database through some database management tools such as Navicat, PLSQL, etc., but for business technicians In general, without a certain professional knowledge base, it is difficult to use tools to operate the database or directly write SQL statements. Therefore, the visual component modeling system was born, which is spliced ​​and assembled into a database query by dragging and connecting components. model, the front end converts it into xml data and transmits it to the back end, and the back end needs to parse the data into complete SQL statements to query the corresponding database. How to parse the modeling data becomes a problem here, and in the big data scenario, For the visual modeling system, a variety of scenarios must be considered, so there are many components and data sources that need to be supported. When processing and analyzing model data, it is necessary to consider supporting enough components and being easy to expand. At the same time, it must also support Concurrent query of large amount of data

None of the prior art can solve the above technical problems well

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