Low-Code Database Merging Method Based on Incremental Meta-Model Atlas

Abstract

The present invention relates to the technical field of low-code databases, and specifically discloses a low-code database merging method based on an incremental meta-model graph, including: constructing an entity structure of a development and test library meta-model graph according to the system table data of a development and test library, and constructing an entity structure of a production library meta-model graph according to the system table data of a production library; generating a development and test library meta-model graph according to the entity structure of the development and test library meta-model graph, and generating a production library meta-model graph according to the entity structure of the production library meta-model graph; performing incremental merging on the development and test library meta-model graph and the production library meta-model graph; performing meta-model synchronous merging on the system table data of the production library; and synchronously updating the business table structure in the production library. The low-code database merging method based on an incremental meta-model graph provided by the present invention can efficiently implement the merging of a low-code database in the case of isolation between a development and test environment and a production environment.

Description

Technical Field

[0001] The present invention relates to the technical field of low-code databases, and particularly to a low-code database merging method based on an incremental meta-model graph. Background Art

[0002] Due to the particularity of the complex equipment industry, the development and test environment and the production environment need to be completely physically isolated, and it is impossible to quickly release the system through the integration of DEVOPS research and development and operation and maintenance. Moreover, the deployment file can generally only be unidirectionally imported from the development and test environment to the production environment. For example, if it is exported from the production environment to the development and test environment, it requires a long approval cycle, which brings a certain time delay to the implementation and deployment of the low-code system. Therefore, the deployment of the low-code system only considers the unidirectional import condition in the isolated environment. Different from high-code systems that write various models and configurations in code files, low-code systems store business meta-models, interface models, process models, etc. in databases. Therefore, when deploying a low-code system, in addition to compiling and deploying the front-end and back-end code, it is also necessary to merge the low-code system databases.

[0003] The advantage of the low-code system is that it can respond to the urgent business requirement changes of users at any time. The implementers of the low-code system can complete the implementation by directly modifying the low-code configuration in the background management of the production environment, without going through multiple implementation links such as code development and testing in the development and test environment and then importing it into the production environment for deployment. However, this causes the models and configurations of the development and test library and the production library to be dynamically updated. When deploying the low-code system, not only do we need to synchronize various models and configuration information in the development and test library to the production library, but also we need to retain the configurations modified on-site in the production library, and merge the models and configurations of the development and test library and the production library as the new production library. Due to the physical isolation condition, the models and configurations of the two libraries are dynamically updated, so the primary key IDs and foreign key IDs of the models and configurations of the two libraries will increase respectively and may not be completely matched. The creation order of the business table fields and the insertion order of the system table data records are not exactly the same. System data such as users, organizations, and roles are referenced in the form of foreign keys in each model, and it is also possible to create them separately in the two libraries, resulting in inconsistent primary and foreign keys. Therefore, it is not possible to simply complete the database deployment and merging by exporting the business meta-model, interface model, process model, and configuration information from the development and test library to the production library.

[0004] Although there are also solutions proposed in the prior art for synchronizing the development and test libraries with the production library in a low-code system, none of them can achieve merging. For example, the technical solution for the synchronization method of the low-code multi-environment database structure only generates SQL for the table structures in the test library and executes it in the production library for table structure synchronization, without considering the synchronization of models and configuration information. Since the system tables and business tables in the development and test libraries and the production library are associated with each other through the primary key ID, when there are model and configuration modifications in both, the primary key IDs of each table increase automatically, resulting in the inability to synchronize the model and configuration data between the development and test libraries and the production library in an unchanged manner, otherwise there will be situations such as primary key ID conflicts, foreign key associations, or data association confusion. Another example is that the technical solution of the database synchronization method based on difference detection is applicable to the case where only the source database is modified and synchronized to the target database. Currently, there are also modifications in the production library, and the issue of merging the models and configurations of the two libraries needs to be considered. Therefore, the technical solutions in the prior art cannot completely solve the problem of low-code database merging in the case where both the development and test libraries and the production library are modified under the condition of one-way import in an isolated environment. For the merging of low-code databases, relatively cumbersome two-library merging methods are still adopted, as follows: One method is to take the production library as the standard, manually record all the modifications in the test and development library, and re-manually operate them in the production library. The low-code system will generate relevant models and configurations according to the internal logic rules and match them with the production library. This method is suitable for the case where there are few modifications in the test and development library. When there are a large number of modifications, it is equivalent to re-implementing, and the workload is large. Another method is to take the test and development library as the standard and adopt the method of manual merging and single-item import. Re-configure and implement the modifications in the production library in the development library, and then export the merged system table structure, system table data (including data models, interface models, process models, and system configurations), and business table structure in the development library and generate SQL, and execute this SQL in the test library for database update. When the test passes in the test library, then execute this SQL in the production library. For the situation of primary key ID conflicts, first, associate and find all the foreign keys related to this primary key ID, and replace all the same data values with the currently largest auto-incremented ID value, and then execute the SQL to perform the merge. For the system configuration information such as personnel, organization, and role referenced in the page model and process model, take the original production library as the standard and re-configure it in the production library. Both of these methods require too much manual participation and review, have high requirements for the implementation and deployment personnel, need to be very meticulous, take a long time for deployment, are prone to omissions in manual library merging, and have a certain impact on the system stability. And when synchronizing, it cannot fully ensure the correct internal logical relationship between the data of each low-code system table, and errors can only be exposed when the system is running.Common system errors include: part of the form configuration is not synchronized, the form cannot be found due to ID misalignment, the process instance cannot be found in the to-do task, the form is not fully synchronized, the changes in the production library are overwritten and lost due to restoration, the personnel organization roles of the page model and the process model cannot be found, the process model ID is inconsistent and the process cannot be initiated, etc.

[0005] Therefore, how to efficiently realize the merger of low-code databases in the case of isolation of development and testing environment and production environment has become a technical problem that needs to be urgently solved by technical personnel in this field. Summary of the invention

[0006] The present invention provides a low-code database merging method based on an incremental metamodel graph, which solves the problem in the related art that it is impossible to efficiently realize the merging of low-code databases when the development and testing environment is isolated from the production environment.

[0007] As one aspect of the present invention, a low-code database merging method of an incremental metamodel graph is provided, which includes:

[0008] Constructing the entity structure of the metamodel graph of the development and test library according to the system table data of the development and test library, and constructing the entity structure of the metamodel graph of the production library according to the system table data of the production library;

[0009] Generate a development and test library metamodel map according to the entity structure of the development and test library metamodel map, and generate a production library metamodel map according to the entity structure of the production library metamodel map;

[0010] Incrementally merging the development and test library metamodel map with the production library metamodel map to obtain an incremental metamodel map;

[0011] Performing metamodel synchronization and merging of system table data of the production library according to the incremental metamodel graph;

[0012] Synchronously updating the business table structure in the production library according to the data model metamodel map in the incremental metamodel map;

[0013] Perform SQL synchronization on the system table structure and system settings between the development and test library and the production library.

[0014] Further, incrementally merging the development and test library metamodel map with the production library metamodel map to obtain an incremental metamodel map includes:

[0015] Construct an initial set of incremental triples;

[0016] Perform triple comparison between the developed test library meta-model graph and the production library meta-model graph to obtain the first triples that exist in the production library meta-model graph but not in the developed test library meta-model graph, and the second triples that exist in the developed test library meta-model graph but not in the production library meta-model graph;

[0017] Perform source marking and status marking on the first triples and the second triples respectively;

[0018] Add the marked first triples and second triples to the initial set of incremental triples to obtain an incremental meta-model graph.

[0019] Further, perform meta-model synchronization and merging on the system table data of the production library according to the incremental meta-model graph, including:

[0020] Compare the entities of the triples in the incremental meta-model graph with the model two-dimensional tables in the production library to determine the objects to be synchronized in the production library;

[0021] Map the entities and attributes of the triples to the objects to be synchronized;

[0022] Determine the foreign key relationships of the objects to be synchronized according to the relationships of the triples.

[0023] Further, comparing the entities of the triples in the incremental meta-model graph with the model two-dimensional tables in the production library to determine the objects to be synchronized in the production library includes:

[0024] Compare the entities of the triples in the incremental meta-model graph with the information in the model two-dimensional tables in the production library;

[0025] If there are matching record information between the model two-dimensional tables in the production library and the entities of the triples in the incremental meta-model graph, determine the model two-dimensional tables in the production library as the objects to be synchronized;

[0026] If there are record information in the model two-dimensional tables in the production library that do not match the entities of the triples in the incremental meta-model graph, determine that the model two-dimensional tables in the production library do not need to be synchronized.

[0027] Further, mapping the entities and attributes of the triples to the objects to be synchronized includes:

[0028] Map the entities of the triples in the incremental meta-model graph to the table records in the objects to be synchronized according to the direct mapping method, and realize the synchronization of entity values;

[0029] Map the attributes of the triples in the incremental meta-model graph to the columns of the table in the objects to be synchronized according to the direct mapping method, and realize the synchronization of attribute values.

[0030] Furthermore, determine the foreign key relationships of the objects to be synchronized according to the relationships of the triples, including:

[0031] Match the foreign key relationships with the objects to be synchronized according to the relationships of the triples in the incremental meta-model graph;

[0032] Judge whether there is a foreign key ID value in the production database;

[0033] If not, create a new foreign key ID value according to the foreign key ID value generator of the production database;

[0034] If it exists, use the existing foreign key ID value as the foreign key ID value of the object to be synchronized.

[0035] Furthermore, synchronously update the business table structure in the production database according to the data model meta-model graph in the incremental meta-model graph, including:

[0036] Obtain the incremental data model meta-model according to the incremental data model meta-model graph in the incremental meta-model graph;

[0037] Automatically update the business table structure in the production database according to the business table structure generation function and the incremental data model meta-model.

[0038] Furthermore, automatically update the business table structure in the production database according to the business table structure generation function and the incremental data model meta-model, including:

[0039] Determine the creation order of the business table structure in the production database according to the meta-model generation order of breadth-first search;

[0040] Automatically update the business table structure according to the business table structure generation function and the incremental data model meta-model in the creation order of the business table structure.

[0041] Furthermore, generate the development and test library meta-model graph according to the entity structure of the development and test library meta-model graph, and generate the production database meta-model graph according to the entity structure of the production database meta-model graph, including:

[0042] Extract knowledge, clean knowledge, disambiguate knowledge, and associate knowledge with the entity structures of the development and test library meta-model graph and the production database meta-model graph respectively;

[0043] Visually extract entities, attributes, and relationships from the entity structures of the development and test library meta-model graph and the production database meta-model graph respectively to form the development and test library meta-model graph triples and the production database meta-model graph triples;

[0044] Generate a development and test library meta-model graph based on the triples of the development and test library meta-model graph, and generate a production library meta-model graph based on the triples of the production library meta-model graph.

[0045] Furthermore, construct the entity structure of the development and test library meta-model graph based on the system table data of the development and test library, and construct the entity structure of the production library meta-model graph based on the system table data of the production library, including:

[0046] Determine the entity structure of the development and test library meta-model graph according to the system table structure of the development and test library, where the system table structure of the development and test library includes a development and test library data model, a development and test library page model, and a development and test library process model, and the entity structure of the development and test library meta-model graph includes a development and test library data model meta-model graph, a development and test library page model meta-model graph, and a development and test library process model meta-model graph;

[0047] Determine the entity structure of the production library meta-model graph according to the system table data structure of the production library, where the system table structure of the production library includes a production library data model, a production library page model, and a production library process model, and the entity structure of the production library meta-model graph includes a production library data model meta-model graph, a production library page model meta-model graph, and a production library process model meta-model graph.

[0048] The low-code database merging method for the incremental meta-model graph provided by the present invention realizes the merging of the low-code databases in the case of isolation between the development and test environments and the production environment by constructing an incremental meta-model graph. This method, due to constructing an incremental meta-model graph, replaces the foreign key relationship with the edge relationship of the meta-model graph. When merging the two libraries through the entity triples of the meta-model graph, the entities and entity relationships are synchronized, and the foreign key ID values are not synchronized. After merging, according to the primary key values of each table in the production library and the entity relationships of the triples, the consistent foreign key ID values are determined, effectively avoiding the error in merging the two libraries caused by the inconsistent growth of the primary key IDs in the development and test library and the production library. In addition, when merging the development and test library and the production library, the business table structure is not synchronized. Instead, the business meta-model is synchronized first, and then the business table structure is generated by the business meta-model through the low-code system rules. This can accurately ensure the consistency between the business table structure and the business meta-model, effectively preventing the situation where the business table structure is randomly modified by executing SQL statements in the low-code database, resulting in the error of inconsistency between the business table structure and the data meta-model, thereby avoiding high-risk problems such as the system being unable to normally read the business table. Therefore, the low-code database merging method for the incremental meta-model graph provided by the present invention can efficiently realize the merging of the low-code databases in the case of isolation between the development and test environments and the production environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The accompanying drawings are used to provide a further understanding of the present invention, and constitute a part of the specification. Together with the following specific implementation manners, they are used to explain the present invention, but do not constitute a limitation to the present invention.

[0050] Figure 1 It is a flowchart of the low-code database merging method for the incremental meta-model atlas provided by the present invention.

[0051] Figure 2 It is a schematic diagram of the specific implementation process of the low-code database merging of the incremental meta-model atlas provided by the present invention.

[0052] Figure 3 It is a flowchart of the generation process of the development test library meta-model atlas and the production library meta-model atlas provided by the present invention.

[0053] Figure 4 It is a flowchart of obtaining the incremental meta-model atlas provided by the present invention.

[0054] Figure 5 It is a flowchart of the meta-model synchronous merging provided by the present invention.

[0055] Figure 6 It is a flowchart of determining the objects to be synchronized in the production library provided by the present invention.

[0056] Figure 7 It is a flowchart of mapping the entities and attributes of the triple to the objects to be synchronized provided by the present invention.

[0057] Figure 8 It is a flowchart of determining the foreign key relationships of the objects to be synchronized provided by the present invention.

[0058] Figure 9 It is a schematic diagram of the specific process of the meta-model synchronous merging provided by the present invention.

[0059] Figure 10 It is a flowchart of synchronously updating the business table structure in the production library provided by the present invention.

[0060] Figure 11 It is a specific flowchart of automatically updating the business table structure in the production library provided by the present invention. Specific implementation manners

[0061] It should be noted that, without conflict, the embodiments in the present invention and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0062] To enable those skilled in the art to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0063] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily need to describe a specific order or sequence. It should be understood that such data used can be interchanged under appropriate circumstances for the embodiments of the present invention described herein. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products, or devices.

[0064] In this embodiment, a low-code database merging method for an incremental meta-model graph is provided. Figure 1 It is a flowchart of the low-code database merging method for an incremental meta-model graph provided according to the embodiments of the present invention, as Figure 1 shown, including:

[0065] S100. Construct the entity structure of the development and test library meta-model graph according to the system table data of the development and test library, and construct the entity structure of the production library meta-model graph according to the system table data of the production library;

[0066] Specifically, create the structure of the development and test library meta-model graph according to the data model, page model, and process model in the system table of the development and test library; and create the structure of the production library meta-model graph according to the data model, page model, and process model in the system table of the production library.

[0067] S200. Generate the development and test library meta-model graph according to the entity structure of the development and test library meta-model graph, and generate the production library meta-model graph according to the entity structure of the production library meta-model graph;

[0068] Specifically, the meta-model graph is produced according to the data model, page model, and process model in the development and test library system table. Since most of the models and configuration information of the low-code system are stored in the database, through steps such as knowledge extraction, knowledge cleaning, knowledge disambiguation, and knowledge association on the relevant information of the data model, page model, and process model in the development and test library, the entities, attributes, and relationships of the three types of models, namely the data model, page model, and process model, are visually extracted to form triples, and the data model graph, page model graph, and process model graph are constructed.

[0069] It should be understood that since the meta-model graph structure of the production library is the same as that of the development and test library, except for the different data, the triple extraction steps are the same as those of the development and test library meta-model graph, and will not be elaborated here.

[0070] S300. Incrementally merge the development and test library meta-model graph and the production library meta-model graph to obtain an incremental meta-model graph;

[0071] Specifically, the merger of the development and test library and the production library mainly extracts the parts of the meta-model that have changed in the two libraries and performs incremental merging. Since the structures of the development and test library meta-model graph and the production library meta-model graph are the same, except that the triples are inconsistent, by comparing the triples of the two graphs, an incremental meta-model graph is obtained.

[0072] S400. Synchronously merge the system table data of the production library according to the incremental meta-model graph;

[0073] Specifically, the triples of the incremental meta-model graph store the changed meta-model graph information in the development and test library and the production library, including three types: data model, process model, and interface model. For each type of model, an incremental meta-data graph, an incremental model graph, an incremental meta-data graph, and an incremental data meta-graph are constructed respectively.

[0074] Perform meta-model synchronous merging according to the incremental meta-model graph to update the meta-model and meta-data of the data model, process model, and interface model in the production library.

[0075] S500. Synchronously update the business table structure in the production library according to the data model meta-model graph in the incremental meta-model graph;

[0076] Specifically, there is a corresponding relationship between the business meta-model and the business table structure, and an extended description of the business table structure is provided. To ensure the consistency between the business meta-model and the business table structure, when merging the development test library and the production library, instead of synchronizing the business table structure, first obtain the incremental data model meta-model from the incremental data model meta-model graph, and then let the incremental data model meta-model execute the business table generation function according to the low-code system data model construction rules to automatically generate or update the business table structure.

[0077] S600, perform SQL synchronization on the system table structure and system settings between the development test library and the production library.

[0078] Specifically, since the adjustment and change of the system table structure are relatively few, and the system setting data only synchronizes business data, the parameter configuration, data dictionary, and system table structure can directly use the traditional exported SQL for synchronization. When a merge conflict occurs, make a selection based on the modification timestamp.

[0079] In summary, the low-code database merging method based on the incremental meta-model graph provided by the present invention realizes the merging of the low-code database in the case of isolation between the development test environment and the production environment by constructing the incremental meta-model graph. This method, due to constructing the incremental meta-model graph, replaces the foreign key relationship with the edge relationship of the meta-model graph. When merging the two libraries through the entity triples of the meta-model graph, it synchronizes the entities and entity relationships, and does not synchronize the foreign key ID values. After the merge, according to the primary key values of each table in the production library and the entity relationships of the triples, the consistent foreign key ID values are determined, effectively avoiding the problem of incorrect merging of the two libraries caused by the inconsistent growth of the primary key IDs of the development test library and the production library. In addition, when merging the development test library and the production library, instead of synchronizing the business table structure, first synchronize the business meta-model, and then let the business meta-model generate the business table structure through the low-code system rules, which can accurately ensure the consistency between the business table structure and the business meta-model, effectively preventing the situation of incorrect modification of the business table structure by executing SQL statements in the low-code database, resulting in the inconsistency between the business table structure and the data meta-model, and thus avoiding high-risk problems such as the system being unable to normally read the business table. Therefore, the low-code database merging method based on the incremental meta-model graph provided by the present invention can efficiently realize the merging of the low-code database in the case of isolation between the development test environment and the production environment, and this low-code database merging method based on the incremental meta-model graph can realize the low-code library merging in the case where both the development test library and the production library are modified in a physically isolated environment, effectively improving the database merging efficiency compared with the one-way database merging in the prior art where only one database is modified and the other is not.

[0080] In an embodiment of the present invention, constructing an entity structure of a development test library meta-model graph based on the system table data of the development test library, and constructing an entity structure of a production library meta-model graph based on the system table data of the production library, including:

[0081] (1) Determining the entity structure of the development test library meta-model graph according to the system table structure of the development test library, where the system table structure of the development test library includes a development test library data model, a development test library page model, and a development test library process model, and the entity structure of the development test library meta-model graph includes a development test library data model meta-model graph, a development test library page model meta-model graph, and a development test library process model meta-model graph;

[0082] In an embodiment of the present invention, creating a meta-model graph structure according to the data model, page model, and process model in the development test library system table. Specifically, it can be combined with Figure 2 As shown, various model entities in the development test library include the following:

[0083] 1) The data model meta-model graph includes four types of entities: data meta-model, data model, meta-data, and data element.

[0084] The data meta-model entity contains attributes such as the basic information, attributes, parent-child inheritance relationship, composition relationship, and dependency relationship of the meta-model; the data model entity includes attributes such as the business table name and definition constructed visually through the low-code system; the meta-data entity includes attributes such as the name, definition, value range, and type of the business table fields constructed visually through the low-code system; the data element entity includes attributes such as the definition, value range, and type of the business table fields themselves constructed visually through the low-code system.

[0085] 2) The interface model meta-model graph includes four types of entities: interface meta-model, interface model, interface meta-data, and interface data element.

[0086] The interface meta-model contains interface meta-model entities such as layout container meta-model, component interaction meta-model, navigation meta-model, and dynamic rendering meta-model; the interface model contains interface model entities such as list page model, detail page model, chart page model, and workflow page model; the interface meta-data contains interface meta-data entities such as component attribute meta-data, page configuration meta-data, component binding meta-data, and user permission meta-data; the interface data element contains interface data element entities such as basic data type element, business entity data element, calculation data element, and enumeration data element.

[0087] 3) The process model meta-model graph includes four types of entities: process meta-model, process model, process meta-data, and process data element.

[0088] The process meta-model includes process meta-model entities such as task meta-model, gateway meta-model, event meta-model, process variable meta-model, swimlane meta-model, etc.; the process model includes process model entities such as sequential process model, parallel process model, conditional branch process model, subprocess model, loop process model, etc.; the process metadata includes process metadata entities such as process definition metadata, process node metadata, process permission metadata, process monitoring metadata, etc.; the process data element includes process data element entities such as business basic data element, object data element, process status data element, associated data element, etc.

[0089] According to the actual system data in the development and test library, the entities, attributes, and relationships of the meta-model graph are constructed respectively. There are constraint relationships among the four types of entities. For example, there is an abstract and concrete relationship between the meta-model entity and the model entity, a belonging relationship between the model entity and the metadata entity, and a definition and implementation relationship between the metadata entity and the data element entity. There are also constraint relationships within the entity. For example, there are reference relationships within the data model entity and within the data model metadata entity.

[0090] (2)Determine the entity structure of the production library meta-model graph according to the system table data structure of the production library, where the system table structure of the production library includes the production library data model, the production library page model, and the production library process model, and the entity structure of the production library meta-model graph includes the production library data model meta-model graph, the production library page model meta-model graph, and the production library process model meta-model graph.

[0091] It should be understood that when constructing the production library meta-model graph according to the data model, page model, and process model in the production library system table, since the meta-model graph structure is the same except for the data, therefore, the specific content of the entity structure of the specific production library meta-model graph can refer to the content description of the entity structure of the development and test library meta-model graph in the previous text.

[0092] In the embodiment of the present invention, the models and configuration information of the low-code system are analyzed. The models of the low-code database are composed of meta-model, model, metadata, and data element, and the models are further divided into types such as data model, process model, and page model.

[0093] Specifically, the meta-model specifically represents the specification of the elements of the model and the relationships between the elements. The meta-model includes the abstract specifications of the data model and the metadata. The meta-model makes the definition and connection of the model more standardized and normalized. The low-code system meta-model includes the data model meta-model, the process model meta-model, the page model meta-model, etc. Among them, the data model meta-model defines the structure and rules of the data model, such as the composition method of the database table, the field type, the data constraint, etc. The process model meta-model is used to standardize the modeling and design of the business process, covering elements such as process nodes, transfer conditions, execution order, etc. and their mutual relationships. The page model meta-model mainly abstracts and defines the construction of the user interface, including page layout, component type, component attributes, data binding rules, etc.

[0094] The model represents the abstraction of data characteristics. A whole structure formed by arranging a number of relevant data elements in a certain order is the data model. The low-code system model includes the data model, the process model, the page model, etc. The data model describes the data structure, data operations and data constraints. The process model is used to design and execute the business process. The page model is responsible for visual page building.

[0095] Metadata represents information about the organization of data, data domains and their relationships, and is data about data. For example, the metadata of "project name" is the description of the field "project name". The low-code system metadata includes the data model metadata, the process model metadata, the page model metadata, etc. Among them, the data model metadata is the specific instance information of the data model created according to the data model meta-model, including detailed information such as the actual created database table name, field name, field length, data type, etc. The process model metadata is the relevant data of the specific business process configured and run on the basis of the process model meta-model, such as the status of the process instance, the current node, the transfer history, the approval opinion, etc. The page model metadata is the specific configuration data of the user interface constructed using the page model meta-model, including the actual attribute values of each component on the page, the specific data source and fields of data binding, the event handling functions of the components, etc.

[0096] A data element represents a data unit described by a series of attributes such as definition, identification, representation, and allowed values. The low-code system data elements include the data model data elements, the process model data elements, the page model data elements, etc. The data model data element is the digital abstraction representation of a certain characteristic or attribute of things in the real world, and is also the most basic element that constitutes the data entity. The process model data element is the abstract representation of each link, operation, condition, etc. in the business process, and is the smallest unit that constitutes the business process. The page model data element is the basic element used to describe the user interface in the page model, and is the abstract representation of the page layout, components and their interaction behaviors, etc., and is the smallest unit that constitutes the user interface.

[0097] There are interdependencies among the data model, process model, and page model. The data model is referenced in the process model and page model, and there are also mutual reference relationships between the process model and page model. There are interdependencies among the meta-model, model, metadata, and data element. There is an abstract-concrete relationship between the meta-model and the model, an ownership relationship between the model and metadata, and a definition-implementation relationship between metadata and data elements. Each model object has intricate relationships such as dependency and being dependent, reference and being referenced, class and implementation, etc., and a complex relationship network has been formed internally. The current association between data is mainly represented by the foreign key ID.

[0098] Since the model data is organized using a table structure (two-dimensional table), when representing the relationships between metadata, it is usually necessary to implement through methods such as foreign keys or joint queries, which is relatively cumbersome. Therefore, in the embodiments of the present invention, a knowledge graph is used to organize the meta-model of the low-code system. A knowledge graph is a semantic network based on a graph data structure that can represent and store low-code model knowledge in a structured manner.

[0099] The meta-model, model, metadata, and data element are all represented as entities. The relationships between entities can be represented by edges (relationships), such as the relationship between the meta-model and the model, the relationship between the model and metadata, the relationship between metadata and data elements, etc. The attributes of an entity are used to describe the detailed characteristics of the entity. For example, the attributes of the meta-model include the rules and structures it defines, the attributes of the model include the specific business logic it describes, the attributes of metadata include the name, type, etc. of the data, and the attributes of the data element include the specific value and constraint conditions of the data.

[0100] It should be understood that this graph data structure of the meta-model graph is very advantageous for handling the complex relationships between models and between data. It can clearly display the associations and dependencies between metadata, and can easily find the relationships between metadata, thereby improving the discoverability and relevance of metadata.

[0101] Since the foreign key ID values are not directly stored in the meta-model graph, but the foreign key relationship is replaced by an edge relationship, it can effectively avoid the problem that the primary key IDs of the development test library and the production library grow inconsistently. Moreover, by expanding the entity relationship through the edge relationship, more edge relationship information can be stored.

[0102] It should be noted that Figure 2 Only the situation of synchronizing the production library when the development test library is modified is shown. Those skilled in the art should understand that the low-code database merging method based on the incremental meta-model graph is also applicable when the production library needs to be modified and the development test library needs to be synchronized. Therefore, the low-code database merging method based on the incremental meta-model graph in the embodiments of the present invention can achieve the merging and generation of the low-code library in the case of both libraries being modified.

[0103] In an embodiment of the present invention, a development and test library meta-model graph is generated according to the entity structure of the development and test library meta-model graph, and a production library meta-model graph is generated according to the entity structure of the production library meta-model graph. As Figure 3 shown, it includes:

[0104] S210. Perform knowledge extraction, knowledge cleaning, knowledge disambiguation, and knowledge association on the entity structures of the development and test library meta-model graph and the production library meta-model graph respectively;

[0105] S220. Visually extract entities, attributes, and relationships from the entity structures of the development and test library meta-model graph and the production library meta-model graph respectively to form a development and test library meta-model graph triple and a production library meta-model graph triple;

[0106] S230. Generate a development and test library meta-model graph according to the development and test library meta-model graph triple, and generate a production library meta-model graph according to the production library meta-model graph triple.

[0107] Specifically, meta-model graph production is performed according to the data model, page model, and process model in the development and test library system table. Since most of the models and configuration information of the low-code system are stored in the database, through steps such as knowledge extraction, knowledge cleaning, knowledge disambiguation, and knowledge association on the information related to the data model, page model, and process model in the development and test library, the entities, attributes, and relationships of the three types of models, namely the data model, page model, and process model, are visually extracted to form triples, and a data model graph, a page model graph, and a process model graph are constructed.

[0108] When mapping the meta-model data in the test development library to the knowledge graph, a "direct mapping" process is required. The table is mapped to a triple RDF class, the columns of the table are mapped to triple RDF attributes, and each row of data is mapped to a resource or entity. In the current process of merging the two libraries, errors in merging the two libraries often occur due to the confusion of foreign key IDs. The most effective method is to avoid foreign key IDs during synchronization. Replace the foreign key ID value with the identifier IRI of the entity it points to. When querying the relationships between entities in the knowledge graph, there is no need to rely on the foreign key ID value, and the association between entities can be represented and queried through the relationship path. Even without storing the foreign key ID value, by defining and applying various constraints and rules, using ontology languages such as RDFS or OWL to define the attributes and relationships of entities and the constraints between them, the consistency and integrity of the data can be maintained. Among them, the data required for generating the meta-model graph is shown in Table 1 below.

[0109] Table 1 Data tables required for meta-model graph production

[0110]

[0111] It should be noted that the data model, page model, and process model in the production library system table are used to construct the production library meta-model graph. Since the meta-model graph structure is the same except for the data, the triple extraction steps are the same as those for generating the development and test library meta-model graph, and will not be elaborated here.

[0112] In the embodiment of the present invention, the development and test library meta-model graph and the production library meta-model graph are incrementally merged to obtain an incremental meta-model graph, as Figure 4 shown, including:

[0113] S310. Construct an initial set of incremental triples;

[0114] Specifically, the set SET is selected to assist the operation and is used to store the triples in the two graphs respectively. Traverse the two knowledge graphs respectively, and add the triples therein to the created sets in sequence.

[0115] S320. Compare the triples of the development and test library meta-model graph with those of the production library meta-model graph to obtain the first triples that exist in the production library meta-model graph but do not exist in the development and test library meta-model graph and the second triples that exist in the development and test library meta-model graph but do not exist in the production library meta-model graph;

[0116] Specifically, the different triples are obtained by taking the difference set of the two sets. For example, let set A store the triples of the development and test library graph, and set B store the triples of the production library graph. Then, the different triples that only exist in the development and test library graph can be obtained through A - B, and the different triples that only exist in the production library graph can be obtained through B - A.

[0117] S330. Respectively perform source marking and status marking on the first triples and the second triples;

[0118] Specifically, mark the source (from the development and test library meta-model graph or the production library meta-model graph) and status (newly added, modified, deleted) of the triples.

[0119] S340. Add the marked first triples and second triples to the initial set of incremental triples to obtain an incremental meta-model graph.

[0120] Specifically, by adding the marked triples to the initial set of incremental triples, the incremental meta-model set is (B - A) U (A - B), and then the set is converted into an incremental meta-model graph.

[0121] It should be noted that since there are modifications in both the development test library and the production library, when the same triple is modified in both libraries, the triple in the production library shall prevail. When the triple cannot be matched with other triples in the incremental meta-model graph, such as when the corresponding entity cannot be found, the triple in the development test library shall prevail. And the triple in the production library shall be marked for subsequent use in test verification after synchronization.

[0122] In the embodiment of the present invention, the meta-model synchronization and merging of the system table data of the production library is performed according to the incremental meta-model graph, as Figure 5 shown, including:

[0123] S410. Compare the entities of the triples in the incremental meta-model graph with the model two-dimensional table in the production library to determine the objects to be synchronized in the production library;

[0124] In the embodiment of the present invention, the triples in the incremental meta-model graph store the changed meta-model graph information in the development test library and the production library, including three categories: data model, process model, and interface model. For each category of model, an incremental meta-data graph, an incremental model graph, an incremental meta-data graph, and an incremental data element graph are respectively constructed. According to the incremental meta-model graph, the meta-model synchronization and merging are performed to update the meta-model and meta-data of the data model, process model, and interface model in the production library.

[0125] Specifically, compare the entities of the triples in the incremental meta-model graph with the information in the model two-dimensional table in the production library to determine the objects to be synchronized in the production library, as Figure 6 shown, including:

[0126] S411. Compare the entities of the triples in the incremental meta-model graph with the information in the model two-dimensional table in the production library;

[0127] S412. If there are matching record information between the model two-dimensional table in the production library and the entities of the triples in the incremental meta-model graph, determine that the model two-dimensional table in the production library is the object to be synchronized;

[0128] S413. If there are record information in the model two-dimensional table in the production library that do not match the entities of the triples in the incremental meta-model graph, determine that the model two-dimensional table in the production library does not need to be synchronized.

[0129] It should be understood that in the embodiments of the present invention, an incremental meta-model graph entity is compared with a model two-dimensional table in a production library. For example, the metadata objects to be synchronized are determined by comparing the data model incremental metadata graph with the data model metadata system table in the production library. When there is record information in the model two-dimensional table of the production library that cannot be matched with the graph entity, it is considered that the model information has not been modified in the test development library and does not need to be synchronized.

[0130] S420. Map the entity and attributes of the triple to the object to be synchronized;

[0131] In the embodiments of the present invention, through the direct mapping method, the entity of the triple is mapped to the table record, and the attribute of the triple is mapped to the column of the table.

[0132] Specifically, map the entity and attributes of the triple to the object to be synchronized, as Figure 7 shown, including:

[0133] S421. Map the entity of the triple in the incremental meta-model graph to the table record in the object to be synchronized according to the direct mapping method, and realize the synchronization of the entity value;

[0134] S422. Map the attribute of the triple in the incremental meta-model graph to the column of the table in the object to be synchronized according to the direct mapping method, and realize the synchronization of the attribute value.

[0135] It should be understood that for the entity value synchronization, according to the two-dimensional table name obtained from the entity, it is judged whether there is such a table record in the production library through the entity value (generally the entity unique identification value). If not, insert it; if so, modify it. For the attribute value synchronization, according to the determined two-dimensional table, match the table fields. And modify the field values corresponding to the table record.

[0136] S430. Determine the foreign key relationship of the object to be synchronized according to the relationship of the triple.

[0137] In the embodiments of the present invention, since the incremental meta-model graph represents the meta-model association through relationships, there is no comparison of foreign key ID values when synchronizing the incremental meta-model graph.

[0138] Specifically, determine the foreign key relationship of the object to be synchronized according to the relationship of the triple, as Figure 8 shown, including:

[0139] S431. Match the relationship of the triple in the incremental meta-model graph with the object to be synchronized for the foreign key relationship;

[0140] S432. Judge whether there is a foreign key ID value in the production library;

[0141] S433. If it does not exist, create a new foreign key ID value according to the production database foreign key ID value generator;

[0142] S434. If it exists, use the existing foreign key ID value as the foreign key ID value of the object to be synchronized.

[0143] It should be understood that for the synchronization process of foreign key values, specifically as Figure 9 shown, first perform foreign key relationship matching in the model two-dimensional table determined in the first step according to the relationship of triples in the incremental meta-model graph. Then, judge whether there is a foreign key ID value in the production database. If not, create a new foreign key ID value through the production database foreign key ID value generator. If so, use this ID value as the foreign key ID value. In this way, there is no need to consider the problem of inconsistent primary and foreign keys caused by the auto-increment of foreign key ID values, and the foreign key ID of the development test database and the production database will not be misaligned.

[0144] In the embodiment of the present invention, synchronously update the business table structure in the production database according to the data model meta-model graph in the incremental meta-model graph, as Figure 10 shown, including:

[0145] S510. Obtain the incremental data model meta-model according to the incremental data model meta-model graph in the incremental meta-model graph;

[0146] S520. Automatically update the business table structure in the production database according to the business table structure generation function and the incremental data model meta-model.

[0147] In the embodiment of the present invention, for the traditional method of exporting the business table structure from the development test database and then synchronizing it in the production database, since when the low-code system synchronizes the business library structure, it not only needs to synchronize the table structure, but also needs to construct an auto-increment ID generator corresponding to the business table, and at the same time needs to be consistent with the data meta-model. Therefore, in the embodiment of the present invention, in order to make the business meta-model consistent with the business table structure, when the development test database and the production database are merged, the business table structure is not synchronized. Instead, first obtain the incremental data model meta-model based on the incremental data model meta-model graph, and then the incremental data model meta-model executes the business table generation function according to the low-code system data model construction rules to automatically generate or update the business table structure, and automatically set the auto-increment primary key ID.

[0148] Therefore, this method in the embodiment of the present invention can effectively prevent the situation where the business table structure is randomly modified by executing SQL statements in the low-code database, resulting in inconsistent errors between the business table structure and the data meta-model, thereby avoiding high-risk problems such as the system being unable to read the business table normally.

[0149] More specifically, the business table structure in the production database is automatically updated according to the business table structure generation function and the incremental data model metamodel, as Figure 11 shown, including:

[0150] 1) Determine the creation order of the business table structure in the production database according to the generation order of the breadth-first search metamodel;

[0151] 2) Automatically update the business table structure according to the business table structure generation function and the incremental data model metamodel in the creation order of the business table structure.

[0152] Specifically, during the business table generation process, it is necessary to judge the creation order of the business tables to avoid errors due to the non-existence of foreign key constraints and related references. Therefore, in the embodiments of the present invention, the order of reference relationships can be found through the metamodel graph. Taking the currently existing entities as the starting point for sorting out the reference relationships, through the method of the generation order of the breadth-first search metamodel, starting from a given graph entity, along its relationship path with other entities, trace up or down step by step, and gradually find the bottommost reference relationship. According to the reverse order method, first judge the entity missing. When an entity is missing, give priority to supplementing the entity, then create the business table structure of the bottom reference relationship, and then check whether there are business tables to be created level by level according to the parent nodes, so as to avoid the failure of business table structure synchronization due to the missing reference entity and the missing foreign key constraint.

[0153] More specifically, the specific implementation steps are as follows:

[0154] 1) The metamodel graph is represented as G=(V, E), where V is the vertex set (representing business table entities), and E is the edge set (representing foreign key constraint relationships). For any two entities u, v ∈ V, if table u has a foreign key pointing to table v, then (u, v) ∈ E.

[0155] 2) Determine the search starting node. Based on the currently existing entities and reference relationships, select one or more business table entities from the metamodel graph as the search starting nodes. Let V0 ⊆ V be the set of starting nodes. V0 can be those entities that do not have foreign key references to other tables, that is, V0 = {v ∈ V|∄u ∈ V, (u, v) ∈ E}.

[0156] 3) Perform breadth-first search. First, initialize a queue Q, and add the nodes in the starting node set V0 to the queue Q. Then traverse the nodes in the queue Q, take out a node v from the queue Q, and process this node. The processing process is as follows:

[0157] (1) Check whether the entity exists, and judge whether the business table entity represented by the current node v already exists. If the entity is missing, it is necessary to supplement this entity first.

[0158] (2) If the entity exists or has been supplemented, add it to the list L of the business table creation order.

[0159] (3) Find all adjacent nodes u of the current node v (i.e., other entities connected by foreign key constraint relationships), and add these adjacent nodes u to the queue Q for subsequent processing.

[0160] (4) Repeat the above process of traversing nodes until the queue Q is empty, that is, all nodes have been processed.

[0161] (5) Generate the business table creation order. Reverse the recorded business table creation order list L to obtain the final creation order list L'. This can ensure that when creating business tables, the underlying entities referenced by other tables are created first, and then the parent node entities are created level by level.

[0162] (6) Create business tables. Create the business table structures in the order L' after reverse sorting. After all tables are created, enable foreign key constraints to ensure that all reference relationships can work properly.

[0163] Therefore, through the method of generating the order of the meta-model based on breadth-first search in the embodiments of the present invention, by tracing up or down step by step through the meta-model graph, the dependency order relationship of business tables is found. Creating the business table structure reversely according to this dependency order relationship can effectively determine the creation order of business tables, avoid the problem of business table structure synchronization failure caused by missing reference entities and missing foreign key constraints during the process of synchronizing business table structures, and ensure the integrity and consistency of the database structure.

[0164] The following takes the scientific research contract management function of a specific scientific research project management system as an example to illustrate the merging of the development test library and the production library. Through the construction of scientific research contract management, the whole process management of businesses such as preparation before contract signing, contract signing, contract performance, and contract filing can be realized, and the recording of the contract execution process and the control of the contract execution status can be strengthened. There are direct or indirect association relationships between scientific research contracts and plans, projects, quality, finance, equipment and materials, etc. The scientific research contract management database includes a scientific research contract information table, a contract party table, a work node table, a contract fund payment table, etc.

[0165] In the actual system development and implementation process, the system completes function development in the development test environment and is deployed to the production environment. Subsequently, according to user requirement changes, function modification and adjustment are carried out in the development test environment. At the same time, due to urgent user requirement changes, function adjustment is directly carried out in the production environment by modifying the system low-code configuration.

[0166] To realize the normal deployment of the scientific research contract management function, in addition to compiling and deploying the front-end and back-end codes, system database merging is also required.

[0167] First, sort out the contract management data model, including the contract management data element model, contract management data model, contract management metadata, and contract management data elements. For example, the contract management data element model includes basic information such as the name, attributes, and primary key of the data element model, as well as relationships such as inheritance and aggregation between models.

[0168] The contract management data model includes table structures, field definitions, indexes, and other physical storage structures such as the scientific research contract information table, contract party table, work node table, contract fund payment table, etc., including details such as the selection of the database, the creation of tables, and the types and lengths of fields.

[0169] The scientific research contract metadata includes table names, table comments, field lists, field attributes, etc. Such as the table structures of the scientific research contract information table, contract party table, etc., such as table fields such as contract number, contract name, project number, contract confidentiality level, contract amount, and funding unit.

[0170] The scientific research contract data elements include the definitions, value ranges, types, etc. of the fields in the contract information table itself. Such as the types of each field, column names, meanings, data types, and whether they are non-null.

[0171] (1) Creation of the data model meta-model graph structure. Define the scientific research contract entities according to the scientific research contract business tables, mainly including the scientific research contract information entity, contract party entity, contract work node entity, contract fund payment entity, and qualified supplier entity, and define the system configuration entities, including user entities, organization entities, and role entities. Also define the scientific research plan entity, scientific research project entity, scientific research quality entity, scientific research finance entity, scientific research equipment and materials entity, etc. that are related to the scientific research contract.

[0172] Define the attributes of the scientific research contract entities according to the fields of the scientific research contract business tables, and at the same time define the entity relationships according to the foreign key relationships of the tables. For example, the scientific research contract information entity has a subordinate relationship with the contract party entity, contract work node entity, contract fund payment entity, and qualified supplier entity. The user entity, organization entity, role entity, scientific research plan entity, scientific research project entity, scientific research quality entity, scientific research finance entity, and scientific research equipment and materials entity have a reference relationship with the scientific research contract information entity.

[0173] (2)Development and production of the meta-model graph of the data model in the development and test library. Through steps such as knowledge extraction, knowledge cleaning, knowledge disambiguation, and knowledge association on the information related to the data model in the development and test library, the entities, attributes, and relationships of the data model are visually extracted to form triples, and a data model graph is constructed. Through the "direct mapping" process, tables are mapped to triple RDF classes, columns of tables are mapped to triple RDF attributes, and the foreign key ID values are replaced with the identifiers IRI of the entities they point to. For example, in the entity of scientific research contract information, the affiliated project, qualified supplier, handling unit, and handler are not associated through foreign key IDs, but directly point to the entities of scientific research projects, qualified suppliers, organizational entities, and user entities. The foreign key ID of the affiliated scientific research contract in the entities of scientific research plan, scientific research project, scientific research quality, scientific research finance, and scientific research equipment and materials that reference the scientific research contract information entity is also changed to directly point to the scientific research contract information entity.

[0174] (3)Production of the meta-model graph of the data model in the production library. In the production environment, since the structure of the meta-model graph is the same, only the triple data is different, so the extraction of the data model triples in the production library is carried out according to the steps of "development and production of the meta-model graph of the data model in the development and test library". Similarly, the foreign key ID values are replaced with the identifiers IRI of the entities they point to.

[0175] (4)Generation of the meta-model graph of the incremental data model. Extract the parts of the meta-model that have changed in the two libraries for incremental merging. Form entities such as the scientific research contract information entity, contract party entity, contract work node entity, contract funds payment entity, and qualified supplier entity with incremental changes.

[0176] (5)Synchronization of the meta-model graph of the incremental data model. Through the "direct mapping" method, the entities of the triples, including the scientific research contract information entity, contract party entity, contract work node entity, contract funds payment entity, and qualified supplier entity, are mapped to table records, and the attributes of the triples are mapped to the columns of the tables. For the foreign key ID values, the production library is taken as the standard. If not, a new foreign key ID value is recreated.

[0177] (6)Automatic generation and synchronization of the business table structure based on the meta-model graph of the data model. Obtain the incremental data model meta-model according to the incremental meta-model graph, and call the system business table structure generation function to automatically generate the business table structure and related configurations according to the low-code meta-model logic rules. For example, add the "contract nature" field to the scientific research contract information table and delete the "whether reviewed" field from the contract work node table.

[0178] (7) Synchronize the system table structure and system settings. During the implementation of the contract management function, the system table structure was not adjusted, but the financial account information referenced by the "reported subject" field in the "contract fund payment" business table was updated, adding a first-level "material cost" and its subordinate subjects. These system setting adjustments were synchronized through the SQL synchronization method.

[0179] In summary, the low-code database merging method for the incremental meta-model graph provided by the present invention has the following advantages:

[0180] 1) In view of the problem that the prior art uses a table structure (two-dimensional table) to organize low-code system model data, and when representing the relationships between metadata, it usually needs to be implemented through foreign keys or joint queries, etc., which is relatively cumbersome. The embodiments of the present invention use the meta-model graph method to represent and store the knowledge of the low-code system data model, page model, and process model, clearly showing the associations and dependencies between metadata, and being able to easily find the relationships between metadata, thereby improving the discoverability and relevance of metadata.

[0181] 2) In view of the situation in the prior art that due to the synchronous modification of the development test library and the production library, the models and configurations of the two libraries will have their own growth of primary key IDs and foreign key IDs, resulting in primary key ID conflicts, foreign key associations, or data association chaos when the two libraries are merged. The embodiments of the present invention adopt the incremental meta-model graph synchronization method to construct three types of meta-model graphs for the low-code system data model, page model, and process model, including four entities: meta-model, data model, metadata, and data element. The edge relationship of the meta-model graph is used to replace the foreign key relationship, and the foreign key ID value is replaced with the identifier IRI of the entity it points to. When merging the two libraries through the entity triples of the meta-model graph, the entities and entity relationships are synchronized, and the foreign key ID values are not synchronized. After the merge, according to the primary key values of each table in the production library and the entity relationships of the triples, the consistent foreign key ID values are determined. It effectively avoids the error in merging the two libraries caused by the inconsistent growth of the primary key IDs of the development test library and the production library.

[0182] 3) In the embodiment of the present invention, the business meta-model of the low-code system is stored in the system table. When merging the development test library and the production library, if the business table synchronization is performed by executing the SQL statement of the business table structure, there may be an omission in the synchronization of the configuration information related to the business table, and it is also possible that the business table is modified outside the low-code system, resulting in an error situation where the business table structure is inconsistent with the data meta-model. In the embodiment of the present invention, when merging the development test library and the production library, the business table structure synchronization is not performed. Instead, the business meta-model is synchronized first, and then the business table structure is generated by the business meta-model through the rules of the low-code system. This can accurately ensure the consistency between the business table structure and the business meta-model, and at the same time can automatically construct the business table configuration, such as the self-increasing ID generator. It effectively prevents the situation where the business table structure is randomly modified by executing SQL statements in the low-code database, resulting in an error situation where the business table structure is inconsistent with the data meta-model, thus avoiding high-risk problems such as the system being unable to normally read the business table.

[0183] 4) In view of the fact that there are foreign key constraint relationships in the business table in the prior art, the traditional method of batch creating the business table structure is to disable all constraints first, and then enable the constraints after all imports. Although all imports have been completed, there may be a situation of missing references, resulting in the failure to enable successfully. In the embodiment of the present invention, by the method of the meta-model generation order based on breadth-first search, the dependency order relationship of the business table is found by gradually tracing up or down through the meta-model graph. The business table structure is created reversely according to the dependency order relationship, thus avoiding the failure of the business table structure synchronization caused by the missing reference entity and the missing foreign key constraint.

[0184] It can be understood that the above embodiments are only exemplary embodiments adopted to illustrate the principle of the present invention. However, the present invention is not limited thereto. For those of ordinary skill in the art, various modifications and improvements can be made without departing from the spirit and essence of the present invention, and these modifications and improvements are also regarded as the protection scope of the present invention.

Claims

1. A low-code database merging method for an incremental meta-model atlas, characterized in that, Including: Constructing the entity structure of the development and test library meta-model graph based on the system table data of the development and test library, and constructing the entity structure of the production library meta-model graph based on the system table data of the production library; Generating the development and test library meta-model graph according to the entity structure of the development and test library meta-model graph, and generating the production library meta-model graph according to the entity structure of the production library meta-model graph; Performing incremental merging on the development and test library meta-model graph and the production library meta-model graph to obtain an incremental meta-model graph; Performing meta-model synchronous merging on the system table data of the production library according to the incremental meta-model graph; Synchronously updating the business table structure in the production library according to the data model meta-model graph in the incremental meta-model graph; Performing SQL synchronization on the system table structure and system settings between the development and test library and the production library; Synchronously updating the business table structure in the production library according to the data model meta-model graph in the incremental meta-model graph, including: Obtaining the incremental data model meta-model according to the incremental data model meta-model graph in the incremental meta-model graph; Automatically updating the business table structure in the production library according to the business table structure generation function and the incremental data model meta-model; Automatically updating the business table structure in the production library according to the business table structure generation function and the incremental data model meta-model, including: Determining the creation order of the business table structure in the production library according to the meta-model generation order of breadth-first search; Automatically updating the business table structure according to the business table structure generation function and the incremental data model meta-model in the creation order of the business table structure.

2. The low-code database merging method for the incremental meta-model graph spectrum according to claim 1, wherein Performing incremental merging on the development and test library meta-model graph and the production library meta-model graph to obtain an incremental meta-model graph, including: Constructing an initial set of incremental triples; Performing triple comparison on the development and test library meta-model graph and the production library meta-model graph to obtain a first triple that exists in the production library meta-model graph but does not exist in the development and test library meta-model graph and a second triple that exists in the development and test library meta-model graph but does not exist in the production library meta-model graph; Performing source marking and status marking on the first triple and the second triple respectively; Adding the marked first triple and second triple to the initial set of incremental triples to obtain an incremental meta-model graph.

3. The low-code database merging method for the incremental meta-model atlas according to claim 1, characterized in that Performing meta-model synchronous merging on the system table data of the production library according to the incremental meta-model graph, including: Comparing the entities of the triples in the incremental meta-model graph with the model two-dimensional table in the production library to determine the objects to be synchronized in the production library; Mapping the entities and attributes of the triples to the objects to be synchronized; Determining the foreign key relationships of the objects to be synchronized according to the relationships of the triples.

4. The low-code database merging method for the incremental meta-model graph according to claim 3, wherein Comparing the entities of the triples in the incremental meta-model graph with the model two-dimensional table in the production library to determine the objects to be synchronized in the production library, including: Comparing the entities of the triples in the incremental meta-model graph with the information in the model two-dimensional table in the production library; If there are record information that all match between the model two-dimensional table in the production database and the entities of the triples in the incremental meta-model graph, determine the model two-dimensional table in the production database as the object to be synchronized; If there is record information in the model two-dimensional table in the production database that does not match the entities of the triples in the incremental meta-model graph, determine that the model two-dimensional table in this production database does not need to be synchronized.

5. The low-code database merging method for the incremental meta-model atlas according to claim 3, characterized in that Mapping the entities and attributes of the triples to the object to be synchronized includes: Mapping the entities of the triples in the incremental meta-model graph to the table records in the object to be synchronized according to the direct mapping method, and realizing the synchronization of entity values; Mapping the attributes of the triples in the incremental meta-model graph to the columns of the table in the object to be synchronized according to the direct mapping method, and realizing the synchronization of attribute values.

6. The low-code database merging method for the incremental meta-model atlas according to claim 3, characterized in that, Determining the foreign key relationships of the object to be synchronized according to the relationships of the triples includes: Matching the foreign key relationships with the object to be synchronized according to the relationships of the triples in the incremental meta-model graph; Judging whether there is a foreign key ID value in the production database; If not, create a new foreign key ID value according to the production database foreign key ID value generator; If it exists, use the existing foreign key ID value as the foreign key ID value of the object to be synchronized.

7. The low-code database merging method for the incremental meta-model graph spectrum according to any one of claims 1 to 6, characterized in that Generating the development and test library meta-model graph according to the entity structure of the development and test library meta-model graph, and generating the production library meta-model graph according to the entity structure of the production library meta-model graph includes: Performing knowledge extraction, knowledge cleaning, knowledge disambiguation, and knowledge association on the entity structures of the development and test library meta-model graph and the production library meta-model graph respectively; Visually extracting entities, attributes, and relationships from the entity structures of the development and test library meta-model graph and the production library meta-model graph respectively to form the development and test library meta-model graph triples and the production library meta-model graph triples; Generating the development and test library meta-model graph according to the development and test library meta-model graph triples, and generating the production library meta-model graph according to the production library meta-model graph triples.

8. The low-code database merging method for the incremental meta-model atlas according to any one of claims 1 to 6, characterized in that Constructing the entity structure of the development and test library meta-model graph according to the system table data of the development and test library, and constructing the entity structure of the production library meta-model graph according to the system table data of the production library includes: Determining the entity structure of the development and test library meta-model graph according to the system table structure of the development and test library, where the system table structure of the development and test library includes the development and test library data model, the development and test library page model, and the development and test library process model, and the entity structure of the development and test library meta-model graph includes the development and test library data model meta-model graph, the development and test library page model meta-model graph, and the development and test library process model meta-model graph; Determining the entity structure of the production library meta-model graph according to the system table data structure of the production library, where the system table structure of the production library includes the production library data model, the production library page model, and the production library process model, and the entity structure of the production library meta-model graph includes the production library data model meta-model graph, the production library page model meta-model graph, and the production library process model meta-model graph.

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