Method, device, equipment, medium and product for describing blood relationship of logical model

Abstract

The present invention discloses a method, device, equipment, medium and product for describing blood relationship of a logical model. The present invention relates to the field of big data technology. The method comprises: obtaining attribute information of a logical model; determining, according to the attribute information of the logical model, conversion rules between attributes with blood relationship in the attributes of the logical model; describing the conversion rules by a preset SQL language to obtain blood relationship description results. This solution solves the problems of high cost and difficult maintenance of blood relationship analysis of logical models, and can improve the accuracy of blood relationship analysis and reduce acquisition costs while standardizing the description of blood relationship of logical models.

Description

Technical Field

[0001] The present invention relates to the field of big data technology, and in particular to a method, device, equipment, medium and product for describing a logical model blood relationship. Background Art

[0002] In the current era of big data, huge and complex data information will generate new data through marriage, fusion, transformation and conversion. From its generation, processing, fusion, circulation to its final extinction, new data will have an inevitable connection with the original data before processing. These connections are blood relations. If blood relations can be analyzed in depth, it will be helpful to locate errors in the program, analyze business differences, track indicator fluctuations, greatly improve data quality, and optimize user data experience.

[0003] At present, most of the existing technologies for obtaining the blood relationship of data are to obtain the blood relationship between tables and fields, that is, the blood relationship between physical models, by analyzing ETL scripts or parsing database logs. However, there is a lack of powerful means to obtain and maintain the blood relationship between logical models, and the existing solutions are usually maintained and analyzed manually.

[0004] The existing manual maintenance of the blood relationship of the logical model is mostly obtained from the descriptive language of the source caliber of the logical model. If the source caliber is analyzed between tens of millions of tables to find the source and destination of the table data, the blood relationship analysis not only requires huge labor costs, but also easily loses the relationship, and the correctness is difficult to guarantee. Summary of the invention

[0005] The present invention provides a method, device, equipment, medium and product for describing the blood relationship of a logical model to solve the problems of high cost and difficult maintenance of the blood relationship analysis of the logical model. It can improve the accuracy of the blood relationship analysis and reduce the acquisition cost while standardizing the description of the blood relationship of the logical model.

[0006] According to one aspect of the present invention, a method for describing a blood relationship of a logical model is provided, the method comprising:

[0007] Get the attribute information of the logical model;

[0008] Determining, according to the attribute information of the logic model, a conversion rule between attributes having a blood relationship in the attributes of the logic model;

[0009] The conversion rule is described by using a preset SQL language to obtain a blood relationship description result.

[0010] According to another aspect of the present invention, there is provided a device for describing a blood relationship of a logical model, the device comprising:

[0011] An attribute information acquisition module is used to acquire the attribute information of the logical model;

[0012] A conversion rule determination module, used to determine, according to the attribute information of the logic model, a conversion rule between attributes with blood relationship in the attributes of the logic model;

[0013] The blood relationship description result generating module is used to describe the conversion rule by using a preset SQL language to obtain a blood relationship description result.

[0014] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0015] at least one processor; and

[0016] a memory communicatively connected to the at least one processor; wherein,

[0017] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for describing the blood relationship of a logical model as described in any embodiment of the present invention.

[0018] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method for describing the blood relationship of a logical model described in any embodiment of the present invention when executed.

[0019] According to another aspect of the present invention, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the method for describing the blood relationship of a logical model as described in any one of the embodiments of the present invention is implemented.

[0020] The technical solution of the embodiment of the present invention determines the conversion rules between the attributes of the logical model with blood relationship through the attribute information of the logical model. The conversion rules are described in SQL language to obtain a standardized blood relationship description result. The technical solution can solve the problems of high cost and difficult maintenance of logical model blood relationship analysis, and can improve the accuracy of blood relationship analysis and reduce acquisition costs while standardizing the description of blood relationship in the logical model.

[0021] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0023] Figure 1A is a flow chart of a method for describing a blood relationship of a logical model provided according to the first embodiment of the present invention;

[0024] Figure 1B It is a schematic diagram of blood relationship analysis of a logical model attribute table provided in an embodiment of the present invention;

[0025] Figure 2 is a flow chart of a method for describing a logical model blood relationship according to the second embodiment of the present invention;

[0026] Figure 3 is a schematic diagram of the structure of a device for describing a logical model blood relationship provided according to Embodiment 3 of the present invention;

[0027] Figure 4 It is a schematic diagram of the structure of an electronic device for implementing the method for describing the blood relationship of a logical model according to an embodiment of the present invention. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0029] 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 are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices. The acquisition, storage, use, processing, etc. of data in the technical solution of this application comply with the relevant provisions of national laws and regulations.

[0030] Embodiment 1

[0031] Figure 1A A flowchart of a method for describing a logical model blood relationship is provided for the first embodiment of the present invention. This embodiment is applicable to the description scenario of a logical model blood relationship. The method can be executed by a device for describing a logical model blood relationship. The device can be implemented in the form of hardware and / or software, and the device can be configured in an electronic device. Figure 1A As shown, the method includes:

[0032] S110: Acquire attribute information of the logical model.

[0033] This solution can be executed by a blood relationship analysis system. The blood relationship analysis system can obtain the attribute information of the logical model to be analyzed. Among them, the logical model can be a concretization of the conceptual model. Specifically, the conceptual model can be a model composed of entities that are refined based on the analysis and summary of product requirements and used to describe business needs. For example, in the sales business, there are entities such as "customers", "orders", "merchants" and "goods". The conceptual model can be an "order" signed between a "merchant" and a "customer" to purchase a "goods".

[0034] It is understandable that to realize what the conceptual model describes, a more specific demand analysis is needed, that is, the process of building a logical model. Still using the above example to illustrate, "customer" can include attribute information such as contact person, contact number and address, "product" can include attribute information such as name, specification and unit price, "order" can include attribute information such as date and time, and "merchant" can include attribute information such as business scope, contact number and address. There is a connection between the attribute information of "order" and "customer", "merchant" and "product". The business system needs to establish data tables to realize the functions to be realized by the sales business. For example, the business system can establish customer information tables, merchant information tables, product information tables and order tables. By establishing these data tables, the business system can realize functions such as customer information maintenance, merchant information maintenance, product information maintenance, and establishment of sales orders.

[0035] It should be noted that the logical model can be one, and obtaining the attribute information of the logical model can be used to analyze the data lineage relationship within the logical model. The logical model can also be multiple, and obtaining the attribute information of multiple logical models can be used to analyze the data lineage relationship within the logical model and the data lineage relationship between logical models.

[0036] S120: Determine, according to the attribute information of the logic model, a conversion rule between attributes having a blood relationship in the attributes of the logic model.

[0037] The blood relationship analysis system can determine which attributes in the logical model have blood relationships based on the attribute information of the logical model. The blood relationship is the connection between related data obtained in the process of data tracing. After finding the attributes with blood relationships, the blood relationship analysis system can further determine the conversion rules between the attributes with blood relationships, and the conversion rules can also be called the blood relationship caliber between the attributes. The conversion rules may include rules such as data extraction standards and data extraction logic. For example, to extract female customers with daily consumption below 100 yuan and age above 18 from the customer information table, the data extraction standard is to meet the constraints of daily consumption, age and gender. The data extraction logic can be to extract data based on gender first, and then extract data based on age and daily consumption in turn on the basis of the extracted data, and finally obtain the target data. The data extraction logic can also be to obtain three groups of extracted data according to daily consumption, age and gender, and then perform intersection operations on the three groups of extracted data to obtain the target data.

[0038] Figure 1B Schematic diagram of the blood relationship analysis of the logical model attribute table provided according to an embodiment of the present invention. The blood relationship analysis system can determine the conversion rules between the attribute tables according to the data source relationship between the attribute tables. Figure 1B As shown, taking attribute table F as an example, its source data table is attribute table A. The blood relationship analysis system can analyze the data retrieval standards and data retrieval logic of attribute table F in attribute table A, and then determine the conversion rules from attribute table A to attribute table F.

[0039] S130. Describe the conversion rule using a preset SQL language to obtain a blood relationship description result.

[0040] The blood relationship analysis system can allow users to use SQL language to describe conversion rules. Specifically, the blood relationship analysis system can select some SQL statements to build an SQL language description library. Users can select reasonable statements in the SQL language description library to describe the conversion rules.

[0041] Specifically, the description of the conversion rule by using a preset SQL language includes at least one of the following situations:

[0042] Describe the source logical model attributes of the current logical model attributes through the SELECT statement;

[0043] Describe the source logical model of the current logical model through the FROM statement;

[0044] Describe the association relationship between the source logical models of the current logical model through INNER / LEFT / RIGHT / FULL / SELF JOIN statements;

[0045] Describe the filtering relationship of the source logical model through a WHERE statement;

[0046] Describe the grouping relationship between the source logical models through a GROUP BY statement;

[0047] Describe the sorting relationship after the source logic models are combined by using an ORDER BY statement;

[0048] The parallel combination of multiple source logical relationships is described through UNION / UNION ALL statements.

[0049] It is easy to understand that the source logic model is the source model of the current logic model data. It should be noted that the above SQL statements can be used alone or in combination, and the blood relationship analysis system can introduce new SQL statements to describe the conversion rules according to actual needs. The wish relationship analysis system can also build functions that implement specific functions based on the above SQL statements to adapt to the conversion rules of complex logic.

[0050] This solution can set corresponding SQL description statements for various situations in the conversion rules, which is conducive to achieving standardized and accurate description of the conversion rules.

[0051] After all the conversion rules involved in the logical model are described in SQL language, the blood relationship analysis system can obtain the blood relationship description result of the logical model to be analyzed.

[0052] In this solution, optionally, after obtaining the blood relationship description result, the method further includes:

[0053] According to the blood relationship description result, analyzing the blood relationship link of the attribute with blood relationship in the logical model attribute;

[0054] A lineage view of the logical model is established based on the source information obtained from the lineage link; wherein the source information includes source component information, source table information and source field relationship information.

[0055] It is understandable that after obtaining the blood relationship description results of all the logical models to be analyzed, the blood relationship analysis system parses the blood relationship description results, for example, by compiling and parsing software in SQL language. Based on the parsing results, the blood relationship analysis system can generate blood relationship links between the attributes with blood relationship in the logical model attributes. The blood relationship links can be data flows between the attributes with blood relationship in a single or multiple logical models, which can show the blood relationship between the attributes in a macroscopic way. Figure 1B As shown, attribute table A -> attribute table F -> attribute table I -> attribute table is a bloodline link.

[0056] From the lineage link, the lineage relationship analysis system can obtain the source information of each attribute or each logical model, and then build the lineage view of the logical model based on the source component, source table, source field and other information. Figure 1B It can be regarded as a simple display of the bloodline view, which may be composed of multiple bloodline links and include rich bloodline relationship information.

[0057] This solution generates a blood relationship view by parsing the blood relationship description results. This solution can display the blood relationship in the form of a blood relationship view, making the blood relationship of the logical model more specific and clearer, and providing users with a more intuitive understanding of the blood relationship.

[0058] In a feasible solution, optionally, after determining the conversion rules between attributes with blood relationship in the logical model attributes, the method further includes:

[0059] The conversion rule is described by presetting a colloquial description template to obtain a colloquial description result of the blood relationship;

[0060] The colloquial description result is parsed according to preset parsing rules to generate a blood relationship description result based on SQL language.

[0061] For non-technical personnel, it is difficult to describe the conversion rules using SQL language. In order to facilitate the description of non-technical personnel, the blood relationship analysis system develops a colloquial description template according to each SQL statement. For example, for the statement SELECT field FROM table, the colloquial description can be <select> [table.field]. Specifically, the colloquial description template can be as shown in the following table:

[0062] Table 1:

[0063]

[0064]

[0065] After the colloquial description is completed, the blood relationship analysis system can parse the colloquial description result according to the pre-defined parsing rules. The parsing rules can be mapping rules between the colloquial description and the SQL language. According to the parsing rules, the blood relationship analysis system can translate the colloquial description into the SQL language description, thereby obtaining the blood relationship description result based on the SQL language.

[0066] The colloquial description template provided by this solution is user-friendly for non-technical personnel. By converting the colloquial description into SQL language description through parsing rules, the blood relationship description results based on SQL language can be generated quickly and accurately.

[0067] This technical solution determines the conversion rules between attributes with blood relations in the logical model attributes through the attribute information of the logical model. The conversion rules are described in SQL language to obtain a standardized blood relation description result. This technical solution can solve the problems of high cost and difficult maintenance of blood relation analysis of logical models, and can improve the accuracy of blood relation analysis and reduce acquisition costs while standardizing the blood relation description of logical models.

[0068] Embodiment 2

[0069] Figure 2 1 is a flow chart of a method for describing a blood relationship of a logical model according to Embodiment 2 of the present invention. This embodiment is based on the above embodiment and is refined. Figure 2 As shown, the method includes:

[0070] S210: Obtain attribute information of the logical model.

[0071] S220: Determine, based on the attribute information of the logic model, a conversion rule between attributes having a blood relationship in the attributes of the logic model.

[0072] S230. Describe the conversion rule using a preset SQL language to obtain a blood relationship description result.

[0073] S240: If an event of establishing a non-strategy field in the physical model is detected, a conversion rule description associated with a logical model attribute corresponding to the non-strategy field is determined in the blood relationship description result.

[0074] The physical model may be a model that implements the logical model on a specific physical medium. For example, if the database uses SQL Server 2000, the physical model can be built on the database server by writing a specific SQL script. The process from the logical model to the physical model can be understood as a design and development process that is from abstract to concrete and continuously refined and improved. The establishment of the physical model is accompanied by the establishment of fields. The fields in the physical model may include policy fields and non-policy fields. The policy fields may be fields generated during the physicalization process such as creation time and creator, and the non-policy fields are fields in the physical model that have a mapping relationship with the attributes of the logical model.

[0075] When the blood relationship analysis system detects the creation event of a non-strategy field in the physical model, it indicates that the non-strategy field may have a blood relationship. The blood relationship analysis system can extract the conversion rules associated with the logical model attribute from the blood relationship description result based on the mapping relationship between the non-strategy field and the logical model attribute.

[0076] S250. Extract the entity name and attribute name of the logical model according to the parsing result described by the conversion rule; and determine the physical table name and field name in the physical model according to the mapping relationship between the attribute and the non-strategy field.

[0077] The blood relationship analysis system can parse the conversion rule description in the blood relationship description result to obtain the entity name and attribute name of the logical model. For example, by parsing the SELECT field a FROM table b, the entity name of the logical model can be obtained as b and the attribute name as a. It can be understood that there is a mapping relationship between the entity in the logical model and the table in the physical model, and there is a mapping relationship between the attribute in the logical model and the field in the physical model. Through the mapping relationship between the attribute and the non-strategy field, the blood relationship analysis system can determine the field name based on the non-strategy field in the physical model, and then determine the physical table name based on the relationship between the field and the physical table.

[0078] S260. Replace the entity name in the conversion rule description with the physical table name, and replace the attribute name in the conversion rule description with the field name, so as to obtain the conversion rule description between the non-strategy fields with blood relationship in the physical model fields.

[0079] The blood relationship analysis system can replace the entity names in the conversion rule description of the logical model with the physical table names, and replace the attribute names with the field names to obtain the conversion rule description between the non-strategy fields of the physical model. Similarly, the blood relationship analysis system can also replace the entity names in the blood relationship description results of the logical model with the physical table names, and replace the attribute names with the field names to obtain the blood relationship description results of the physical model. It should be noted that there is not only a simple one-to-one mapping relationship between the attributes in the logical model and the fields in the physical model, but also a one-to-many and other complex mapping relationships. Therefore, it is more rigorous and accurate to replace the names of the conversion rule descriptions in the blood relationship description results.

[0080] S270. Generate a blood relationship description result of the physical model according to the conversion rule description.

[0081] It is easy to understand that, similar to the blood relationship analysis process of the logical model, the blood relationship description result of the physical model can also be obtained based on the conversion rule description of the physical model.

[0082] In this solution, optionally, after obtaining the description of the conversion rule between the non-strategy fields having a blood relationship in the physical model field, the method further includes:

[0083] Determine the source physical table and source field of each non-strategy field according to the parsing result described by the conversion rule;

[0084] A lineage view of the physical model is established according to the source physical table and the source fields.

[0085] Similar to the process of building the lineage view of the logical model, the lineage relationship analysis system can obtain the source physical table and source field of each non-strategy field based on the analysis results described by the conversion rules, thereby building the lineage view of the physical model.

[0086] This solution can display the blood relationship of the physical model in the form of a blood relationship view, providing users with a more intuitive understanding of the blood relationship and facilitating the comparison of the blood relationship between the physical model and the logical model.

[0087] In a feasible solution, optionally, determining the physical table name and field name in the physical model according to the mapping relationship between the attribute and the non-strategy field includes:

[0088] If the attribute has a mapping relationship with multiple non-strategy fields, the physical table name and field name in the physical model are determined according to the user selection result.

[0089] When there is a one-to-many mapping relationship between an attribute and a non-strategy field, the blood relationship analysis system can list multiple non-strategy fields for the user to select. Based on the user's selection result, the field name in the physical model is determined, and then the physical table name is determined.

[0090] This solution can accurately determine the field names and physical table names in the physical model when there is a one-to-many mapping relationship between attributes and non-strategy fields, which is conducive to obtaining reliable blood relationship description results by fitting the physical model.

[0091] In a preferred solution, after generating the blood relationship description result of the physical model, the method further includes:

[0092] Based on product demand information and development design information, the current logical model is supplemented with conversion rule descriptions between attributes with blood relationships and mapping relationships between non-strategy fields and attributes;

[0093] According to the conversion rule description and the mapping relationship, a conversion rule description between non-strategy fields with blood relationship is generated to supplement the blood relationship description result of the physical model.

[0094] The above scheme can improve the blood relationship description results of the physical model according to the original demand information and design information after the preliminary construction is completed, which is conducive to building a comprehensive and complete blood relationship and avoiding the omission of blood relationship.

[0095] This technical solution is based on the natural connection between the physical model and the logical model. In the process of establishing the physical model, the description result of the blood relationship of the physical model is obtained through the description result of the blood relationship of the logical model. This technical solution can ensure the unity of the blood relationship between the physical model and the logical model, and can reduce the workload of maintaining two blood relationships.

[0096] Embodiment 3

[0097] Figure 3 This is a schematic diagram of the structure of a device for describing the blood relationship of a logical model provided in the third embodiment of the present invention. Figure 3 As shown, the device comprises:

[0098] The attribute information acquisition module 310 is used to acquire the attribute information of the logical model;

[0099] A conversion rule determination module 320, for determining, based on the attribute information of the logic model, a conversion rule between attributes with blood relations in the attributes of the logic model;

[0100] The blood relationship description result generating module 330 is used to describe the conversion rule by using a preset SQL language to obtain a blood relationship description result.

[0101] In this solution, optionally, the blood relationship description result generating module 330 is specifically used to:

[0102] Describe the source logical model attributes of the current logical model attributes through the SELECT statement;

[0103] Describe the source logical model of the current logical model through the FROM statement;

[0104] Describe the association relationship between the source logical models of the current logical model through INNER / LEFT / RIGHT / FULL / SELF JOIN statements;

[0105] Describe the filtering relationship of the source logical model through a WHERE statement;

[0106] Describe the grouping relationship between the source logical models through a GROUP BY statement;

[0107] Describe the sorting relationship after the source logic models are combined by using an ORDER BY statement;

[0108] The parallel combination of multiple source logical relationships is described through UNION / UNION ALL statements.

[0109] In this solution, optionally, the device further includes:

[0110] A blood relationship link parsing module, used for parsing the blood relationship link of the attribute with blood relationship in the attributes of the logical model according to the blood relationship description result;

[0111] The lineage view building module is used to build the lineage view of the logical model based on the source information obtained from the lineage link; wherein the source information includes source component information, source table information and source field relationship information.

[0112] In a preferred embodiment, the device further comprises:

[0113] A colloquial description result generating module, used to describe the conversion rule by using a preset colloquial description template to obtain a colloquial description result of the blood relationship;

[0114] The colloquial description result conversion module is used to parse the colloquial description result according to preset parsing rules to generate a blood relationship description result based on the SQL language.

[0115] In a feasible solution, optionally, the device further includes:

[0116] A conversion rule description determination module is used to determine, if an establishment event of a non-strategy field in the physical model is detected, a conversion rule description associated with a logical model attribute corresponding to the non-strategy field in the blood relationship description result; wherein the non-strategy field is a field in the physical model that has a mapping relationship with the logical model attribute;

[0117] A physical table name and field name determination module, used to extract the entity name and attribute name of the logical model according to the parsing result described by the conversion rule; and determine the physical table name and field name in the physical model according to the mapping relationship between the attribute and the non-strategy field;

[0118] A conversion rule description generation module is used to replace the entity name in the conversion rule description with the physical table name, and replace the attribute name in the conversion rule description with the field name, so as to obtain the conversion rule description between the non-strategy fields with blood relationship in the physical model fields.

[0119] Based on the above solution, optionally, the device further includes:

[0120] A source physical table and source field determination module, used to determine the source physical table and source field of each non-strategy field according to the parsing result described by the conversion rule;

[0121] The physical model lineage view building module is used to build the lineage view of the physical model according to the source physical table and the source field.

[0122] In this solution, optionally, the physical table name and field name determination module is specifically used to:

[0123] If the attribute has a mapping relationship with multiple non-strategy fields, the physical table name and field name in the physical model are determined according to the user selection result.

[0124] Optionally, the device further comprises:

[0125] The physical model blood relationship description result generation module is used to generate the blood relationship description result of the physical model according to the conversion rule description.

[0126] Based on the above solution, optionally, the device further includes:

[0127] A mapping relationship supplement module is used to supplement the conversion rule description and mapping relationship between non-strategy fields and attributes in the logical model attributes that have blood relationships based on product demand information and development design information on the basis of the current logical model;

[0128] The blood relationship description result supplementing module is used to generate a conversion rule description between non-strategy fields with blood relationship according to the conversion rule description and the mapping relationship, so as to supplement the blood relationship description result of the physical model.

[0129] The device for describing the blood relationship of a logical model provided in the embodiment of the present invention can execute the method for describing the blood relationship of a logical model provided in any embodiment of the present invention, and has the functional modules and beneficial effects corresponding to the execution method.

[0130] Embodiment 4

[0131] Figure 4 A schematic diagram of an electronic device 410 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0132] like Figure 4As shown, the electronic device 410 includes at least one processor 411, and a memory connected to the at least one processor 411 in communication, such as a read-only memory (ROM) 412, a random access memory (RAM) 413, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 411 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 412 or the computer program loaded from the storage unit 418 to the random access memory (RAM) 413. In the RAM 413, various programs and data required for the operation of the electronic device 410 can also be stored. The processor 411, the ROM 412, and the RAM 413 are connected to each other via a bus 414. An input / output (I / O) interface 415 is also connected to the bus 414.

[0133] Multiple components in the electronic device 410 are connected to the I / O interface 415, including: an input unit 416, such as a keyboard, a mouse, etc.; an output unit 417, such as various types of displays, speakers, etc.; a storage unit 418, such as a disk, an optical disk, etc.; and a communication unit 419, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 419 allows the electronic device 410 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0134] The processor 411 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 411 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 411 executes the various methods and processes described above, such as the description method of the logical model blood relationship.

[0135] In some embodiments, the method for describing the logical model lineage relationship may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 418. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 410 via the ROM 412 and / or the communication unit 419. When the computer program is loaded into the RAM 413 and executed by the processor 411, one or more steps of the method for describing the logical model lineage relationship described above may be performed. Alternatively, in other embodiments, the processor 411 may be configured to execute the method for describing the logical model lineage relationship in any other appropriate manner (e.g., by means of firmware).

[0136] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0137] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0138] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0139] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0140] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0141] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0142] Embodiment 5

[0143] An embodiment of the present invention also provides a computer program product, including a computer program, which, when executed by a processor, implements a method for describing the blood relationship of a logical model as provided in any embodiment of the present application.

[0144] In the process of implementation, the computer program product can be written in one or more programming languages ​​or a combination thereof to perform the computer program code of the present invention, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0145] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0146] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for describing the blood relationship of a logical model, characterized in that: The method comprises: Get the attribute information of the logical model; Determining, according to the attribute information of the logic model, a conversion rule between attributes having a blood relationship in the attributes of the logic model; The conversion rule is described by using a preset SQL language to obtain a blood relationship description result; The blood relationship is the connection between related data obtained in the process of data tracing; the conversion rules include data acquisition standards and data acquisition logic rules; The description of the conversion rule by using a preset SQL language includes at least one of the following situations: Describe the source logical model attributes of the current logical model attributes through the SELECT statement; Describe the source logical model of the current logical model through the FROM statement; Describe the association relationship between the source logical models of the current logical model through INNER / LEFT / RIGHT / FULL / SELF JOIN statements; Describe the filtering relationship of the source logical model through a WHERE statement; Describe the grouping relationship between the source logical models through a GROUP BY statement; Describe the sorting relationship after the source logic models are combined by using an ORDER BY statement; The parallel combination of multiple source logical relationships is described through UNION / UNION ALL statements.

2. The method according to claim 1, characterized in that After obtaining the blood relationship description result, the method further includes: According to the blood relationship description result, analyzing the blood relationship link of the attribute with blood relationship in the logical model attribute; A lineage view of the logical model is established based on the source information obtained from the lineage link; wherein the source information includes source component information, source table information and source field relationship information.

3. The method according to claim 1, characterized in that After determining the conversion rules between the attributes having blood relations in the logical model attributes, the method further includes: The conversion rule is described by presetting a colloquial description template to obtain a colloquial description result of the blood relationship; The colloquial description result is parsed according to preset parsing rules to generate a blood relationship description result based on SQL language.

4. The method according to claim 1, characterized in that: After obtaining the blood relationship description result, the method further includes: If an event of establishing a non-strategy field in the physical model is detected, a conversion rule description associated with a logical model attribute corresponding to the non-strategy field is determined in the blood relationship description result; wherein the non-strategy field is a field in the physical model that has a mapping relationship with the logical model attribute; According to the parsing result described by the conversion rule, the entity name and attribute name of the logical model are extracted; and according to the mapping relationship between the attribute and the non-strategy field, the physical table name and field name in the physical model are determined; The entity name in the conversion rule description is replaced by the physical table name, and the attribute name in the conversion rule description is replaced by the field name, so as to obtain the conversion rule description between the non-strategy fields with blood relationship in the physical model fields.

5. The method according to claim 4, characterized in that After obtaining the description of the conversion rules between the non-strategy fields having blood relations in the physical model fields, the method further includes: Determine the source physical table and source field of each non-strategy field according to the parsing result described by the conversion rule; A lineage view of the physical model is established according to the source physical table and the source fields.

6. The method according to claim 4, characterized in that Determining the physical table name and field name in the physical model according to the mapping relationship between the attribute and the non-strategy field includes: If the attribute has a mapping relationship with multiple non-strategy fields, the physical table name and field name in the physical model are determined according to the user selection result.

7. The method according to claim 4, characterized in that After obtaining the description of the conversion rules between the non-strategy fields having blood relations in the physical model fields, the method further includes: According to the conversion rule description, a blood relationship description result of the physical model is generated.

8. The method according to claim 7, characterized in that After generating the blood relationship description result of the physical model, the method further includes: Based on product demand information and development design information, the current logical model is supplemented with conversion rule descriptions between attributes with blood relationships and mapping relationships between non-strategy fields and attributes; According to the conversion rule description and the mapping relationship, a conversion rule description between non-strategy fields with blood relationship is generated to supplement the blood relationship description result of the physical model.

9. A device for describing the blood relationship of a logical model, characterized in that: The device comprises: An attribute information acquisition module is used to acquire the attribute information of the logical model; A conversion rule determination module, used to determine, according to the attribute information of the logic model, a conversion rule between attributes with blood relationship in the attributes of the logic model; A blood relationship description result generating module is used to describe the conversion rule by using a preset SQL language to obtain a blood relationship description result; The blood relationship is the connection between related data obtained in the process of data tracing; the conversion rules include data acquisition standards and data acquisition logic rules; The blood relationship description result generating module is specifically used for: Describe the source logical model attributes of the current logical model attributes through the SELECT statement; Describe the source logical model of the current logical model through the FROM statement; Describe the association relationship between the source logical models of the current logical model through INNER / LEFT / RIGHT / FULL / SELF JOIN statements; Describe the filtering relationship of the source logical model through a WHERE statement; Describe the grouping relationship between the source logical models through a GROUP BY statement; Describe the sorting relationship after the source logic models are combined by using an ORDER BY statement; The parallel combination of multiple source logical relationships is described through UNION / UNION ALL statements.

10. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for describing the blood relationship of a logical model according to any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method for describing the logical model blood relationship described in any one of claims 1-8 when executed.

12. A computer program product, characterized in that The computer program product comprises a computer program, which, when executed by a processor, implements the method for describing the logical model blood relationship according to any one of claims 1-8.

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