CN117370339A

CN117370339A - Report blood edge relationship processing method and device, computer equipment and storage medium

Info

Publication number: CN117370339A
Application number: CN202311229277.7A
Authority: CN
Inventors: 毛莹; 李昂; 杨帆; 刘琦; 董宏越; 史国鹏; 李霞
Original assignee: Bank of China Ltd
Current assignee: Bank of China Ltd
Priority date: 2023-09-22
Filing date: 2023-09-22
Publication date: 2024-01-09

Abstract

The application relates to a report blood relationship processing method, a report blood relationship processing device, a report blood relationship processing computer device, a report blood relationship storage medium and a report blood relationship processing computer program product. The method comprises the following steps: responding to a blood margin analysis instruction, and acquiring report data information to be analyzed, wherein the report data information comprises the data type of the report data and the structured query language of the report data; when the data type is a multi-library report data type, determining whether an analyzed source table with source table blood-edge relation data exists in each data source table according to the information of each source table in the report data; if the analyzed source table exists, determining the blood-edge relation data of the report data according to the source table blood-edge relation data of the analyzed source table and the structured query language; and sending the blood relationship data to a data asset management platform according to the report data information. By adopting the method, the blood relationship analysis efficiency can be improved, and the analysis error rate can be reduced.

Description

Report blood edge relationship processing method and device, computer equipment and storage medium

Technical Field

The present invention relates to the field of data processing technologies, and in particular, to a report blood edge relationship processing method, apparatus, computer device, storage medium, and computer program product.

Background

With the rapid development of internet technology, banking business is gradually transferred from offline to online, and a user can realize banking business processing through front-end applications of a bank, such as a bank application program, a bank webpage and the like. When a user handles related banking business through a front-end application, corresponding business processing data are often generated, and the business processing data are often stored in a data warehouse in the form of a report form for facilitating data management.

In order to better manage the data, the blood relationship analysis of the data becomes an important management means. The blood relationship is a very important part of data management, and the complete data blood relationship can be used for carrying out data tracing, analysis of influence of table and field change, data compliance proof, data quality check and the like.

However, the prior art of blood relationship analysis is usually completed by manual analysis and entry, which not only consumes human resources, but also causes higher and higher error rate in the case of multiplied analysis amount, thereby being unfavorable for the management of data assets of banks.

Disclosure of Invention

In view of the foregoing, it is desirable to provide a report blood-edge relationship processing method, apparatus, computer device, computer-readable storage medium, and computer program product that can improve the efficiency of blood-edge relationship analysis and reduce the analysis error rate.

In a first aspect, the present application provides a report blood-edge relationship processing method, where the method includes:

responding to a blood margin analysis instruction, and acquiring report data information to be analyzed, wherein the report data information comprises the data type of report data and the structured query language of the report data;

when the data type is a multi-library report data type, determining whether an analyzed source table with source table blood-edge relation data exists in each data source table according to the source table information in the report data;

if the analyzed source table exists, determining the blood-edge relation data of the report data according to the source-table blood-edge relation data of the analyzed source table and the structured query language;

and sending the blood relationship data to a data asset management platform according to the report data information.

In one embodiment, when the data type is a multi-library report data type, determining whether an analyzed source table with source table blood edge relationship data exists in each data source table according to each source table information in the report data includes:

when the data type is a multi-library report data type, acquiring the source table information of the report data from a structured query language of the report data according to a preset source table information extraction rule;

And determining whether an analyzed source table with source table blood relationship data exists in each data source table according to the source table information.

In one embodiment, the determining whether the analyzed source table with the source table blood-edge relationship data exists in each data source table according to the source table information in the report data includes:

determining a database to which each data source table of the report data belongs according to each source table information in the report data;

obtaining blood margin relation information of each data source base, wherein the blood margin relation information comprises the corresponding relation between blood margin relation data of the data base and a data table;

and matching each data source table with each data table in the blood-edge relation information, and determining the successfully matched data source table as an analyzed source table with source-table blood-edge relation data.

In one embodiment, the determining the blood-edge relationship data of the report data according to the source-table blood-edge relationship data of the analyzed source table and the structured query language includes:

acquiring a service identifier of the report data, and determining a key information extraction rule of the report data according to the service identifier;

Extracting key information from the structured query language based on the key information extraction rule and the source table information of the analyzed source table to obtain a target structured query language of the report data;

performing blood margin relation analysis according to the target structured query language to obtain partial blood margin relation data of the report data;

and obtaining the blood edge relation data of the report data based on the partial blood edge relation data and the source table blood edge relation data.

In one embodiment, the performing the blood-edge relationship analysis according to the target structured query language to obtain the partial blood-edge relationship data of the report data includes:

keyword division is carried out on the target structured query language, and an abstract syntax tree of the report data is generated according to each divided keyword;

performing field analysis on each node in the abstract syntax tree to obtain field information and field blood relationship of each node;

and based on the field information, correlating the blood-edge relations of all the fields to obtain partial blood-edge relation data of the report data.

In one embodiment, the obtaining the blood edge relationship data of the report data based on the partial blood edge relationship data and the source table blood edge relationship data includes:

Acquiring each field node in the source list blood-edge relation data;

and drawing and indicating that the connection is completed according to the source and the destination of each field node and each node in the partial blood edge relation data to obtain the blood edge relation data of the report data.

In a second aspect, the present application further provides a report blood-edge relationship processing apparatus, where the apparatus includes:

the instruction response module is used for responding to the blood margin analysis instruction, acquiring report data information to be analyzed, wherein the report data information comprises the data type of the report data and the structured query language of the report data;

the type determining module is used for determining whether an analyzed source table with source table blood-edge relation data exists in each data source table according to the source table information in the report data when the data type is a multi-library report data type;

the blood margin relation determining module is used for determining the blood margin relation data of the report data according to the source blood margin relation data of the analyzed source table and the structured query language if the analyzed source table exists;

and the relation storage module is used for sending the blood relationship data to a data asset management platform according to the report data information.

In a third aspect, the present application also provides a computer device comprising a memory storing a computer program and a processor implementing the steps of the above method when the processor executes the computer program.

In a fourth aspect, the present application also provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of the above-described method.

In a fifth aspect, the present application also provides a computer program product comprising a computer program which, when executed by a processor, implements the steps of the method described above.

The method, the device, the computer equipment, the storage medium and the computer program product for processing the blood-edge relationship of the report form are characterized in that when blood-edge analysis demands exist, the data information of the report form to be analyzed is obtained in response to the blood-edge analysis demands, the data information of the report form comprises the data type of the report form data and the structured query language of the report form data, when the data type is the multi-library report form data type, the data source table with the blood-edge relationship in the report form data can exist, whether the analyzed source table with the blood-edge relationship data of the source table exists in each data source table is determined according to the information of each source table in the report form data, if so, the blood-edge relationship data of the report form data is determined according to the blood-edge relationship data of the source table and the structured query language of the analyzed source table, and the blood-edge relationship data is sent to the data asset management platform according to the report form data information. According to the method, the blood-edge relation of the report data is automatically analyzed according to the structured query language of the report data, so that the blood-edge relation data of the report data is obtained, the accuracy and the efficiency of the blood-edge relation analysis can be possibly improved, meanwhile, the analyzed source list is screened for the report data, when an analyzed source list with the blood-edge relation data exists, the blood-edge relation data of the report data can be obtained directly according to the analyzed source list blood-edge relation data and the structured query language, the blood-edge relation analysis of the analyzed data is not required to be repeated, and the blood-edge relation analysis efficiency is further improved.

Drawings

FIG. 1 is a diagram of an application environment for a method of table blood relationship processing in one embodiment;

FIG. 2 is a flow chart of a method of processing a report blood-edge relationship in one embodiment;

FIG. 3 is a flowchart illustrating a step of determining whether an analyzed source table with source table blood relationship data exists in each data source table according to each source table information in report data in one embodiment;

FIG. 4 is a flowchart illustrating steps for determining the source table blood-edge relationship data of the report data according to the source table blood-edge relationship data of the analyzed source table and the structured query language in one embodiment;

FIG. 5 is a flowchart of a step of obtaining partial blood-edge relationship data of report data according to a target structured query language for blood-edge relationship analysis in one embodiment;

FIG. 6 is a flowchart illustrating a method of processing a report blood-edge relationship according to another embodiment;

FIG. 7 is a block diagram of an apparatus for processing a report blood relationship in one embodiment;

fig. 8 is an internal structural diagram of a computer device in one embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.

The report blood relationship processing method provided by the embodiment of the application can be applied to an application environment shown in fig. 1. Wherein the blood relationship analysis system 102 communicates with the business management terminal 104 and the data asset management platform 106 over a network. The data storage system may store data that needs to be processed by the blood relationship analysis system 102. The data storage system may be integrated on the blood relationship analysis system 102 or may be placed on the cloud or other network server. The manager generates a blood-edge relation analysis instruction for report data based on the service management terminal 104, sends the blood-edge relation analysis instruction to the blood-edge relation analysis system 102, the blood-edge relation analysis system 102 responds to the blood-edge relation analysis instruction to acquire report data information to be analyzed, the report data information comprises report data types and structured query languages of the report data, when the data types are multi-library report data types, whether analyzed source tables with source table blood-edge relation data exist in the data source tables is determined according to the source table blood-edge relation data of the analyzed source tables and the structured query languages, and if the analyzed source tables exist, the blood-edge relation data of the report data is determined according to the source table blood-edge relation data of the analyzed source tables, and the blood-edge relation data is sent to the data asset management platform 106 according to the report data information. Wherein the blood relationship analysis system 102 may be integrated on a terminal or server. The terminal may be, but is not limited to, various personal computers, notebook computers, smart phones, tablet computers, etc. The server may be implemented as a stand-alone server or as a server cluster composed of a plurality of servers.

In one embodiment, as shown in fig. 2, a report blood-edge relationship processing method is provided, and the method is applied to the blood-edge relationship analysis system 102 in fig. 1 for illustration, and includes the following steps:

s202, acquiring report data information to be analyzed in response to a blood margin analysis instruction, wherein the report data information comprises the data type of the report data and the structured query language of the report data.

The blood edge relation analysis instruction is an instruction for indicating to analyze the blood edge relation of the report data to be analyzed, the blood edge relation analysis instruction carries report data information to be analyzed, and the report data information comprises report data types and a structured query language of the report data.

It may be appreciated that in some embodiments, the blood-edge relationship analysis instruction may be triggered and generated by a manager based on the service management system, for example, when the service manager determines that the blood-edge relationship analysis needs to be performed on certain report data, the service manager directly opens the blood-edge relationship analysis system through the service management terminal, inputs report data information into the blood-edge relationship analysis system, clicks an analysis button, and triggers and generates the blood-edge relationship analysis instruction. In other embodiments, the blood-edge relationship analysis instruction may also be generated by self-triggering by the blood-edge relationship analysis system, for example, a designer may design an analysis period, and the blood-edge relationship analysis system may automatically obtain report data information to be analyzed in the analysis period according to the analysis period, and generate the blood-edge analysis instruction according to the report data information.

The structured query language (Structured Query Language, SQL) is a language used for accessing data and querying information stored in a database, wherein report data is composed of a plurality of source table data, and in order to better understand data information in the report data, a designer can generate the structured query language of the report data according to actual generation requirements of the report data and preset generation rules, and the structured query language can contain source table information, field information, database information and the like of the report data.

The bank can build a corresponding database according to the service types for storing the service processing data generated under the service types, and the database combination of the service types can obtain a data warehouse for storing the banking service data.

Among report data generated based on the data warehouse, the report data type is a type attribute parameter for characterizing a data composition structure of the report data. Report data types of report data may include multi-library data report types and single data report types. When the data type of the report data is a multi-database data report type, it is explained that the report data is a data set composed of report data of a plurality of databases, for example, report data X is generated by report data A1, B1 and C1 in database a, database B and database C, and then the report data X is the multi-database data report type. The report data A1, B1, and C1 may be a single data table in the corresponding database, or may be a combined data report in the corresponding database, for example, A1 is obtained by combining data of three data tables A1, a2, and a3 in the database a, and then A1 is a combined data report of the database a. When the data type of the report data is a single data report type, it is indicated that the report data is a combined data report in a database in the data warehouse, for example, A1 is the combined data report of the database a.

Specifically, the blood margin relation analysis system responds to the blood margin analysis instruction, and acquires report data information to be analyzed carried in the blood margin analysis instruction according to the blood margin analysis instruction, wherein the report data information comprises the data type of the report data and the structured query language of the report data.

S204, when the data type is the multi-library report data type, determining whether an analyzed source table with source table blood edge relation data exists in each data source table according to the source table information in the report data.

The source table information is information of a data table to which each data constituting the report data belongs, and the data table to which each data constituting the report data belongs is the source table of the report data. For example, the composition data of the report data X is derived from A1, B1 and C1, and then A1, B1 and C1 are the data source tables of the report data X, and the information of A1, B1 and C1 is the source table information of the report data.

The analyzed source table refers to a source table in which the blood-edge relationship analysis has been performed and corresponding blood-edge relationship data exists. For example, the source table A1 of the report data X is composed of the data tables A1, a2 and a3 in the database a, and A1 has been subjected to the blood-edge data analysis, and the corresponding blood-edge relationship data exists, A1 can be determined as the analyzed source table.

As can be seen from the foregoing description of the data warehouse, each warehouse in the data warehouse is used for storing service processing data of a corresponding service type, so that if the data type of the report data is a multi-database report data type, it is indicated that the current report data to be analyzed is integrated report data of a plurality of service types, and the integrated report data is used for carrying out centralized processing analysis on the service processing data of the plurality of service types.

Specifically, when the data type of the report data is determined to be the multi-library report data type, the blood-edge relationship analysis system acquires information of each source table in the report data, and determines whether an analyzed source table with source-table blood-edge relationship data exists in each data source table of the report data according to the information of each source table in the report data.

S206, if the analyzed source table exists, determining the blood-edge relation data of the report data according to the source table blood-edge relation data of the analyzed source table and the structured query language.

Specifically, if it is determined that the analyzed source tables exist in each data source table of the report data, the source table blood-edge relationship data of the report data is obtained according to the source table blood-edge relationship data of the analyzed source tables and the structured query language of the report data.

And S208, according to the report data information, the blood-margin relation data are sent to a data asset management platform.

The data asset management platform is used for managing the bank data assets by the bank, and the bank data asset management platform can clearly know the blood-edge relationship of each report data by sending the blood-edge relationship data to the data asset management platform for storage management, so that the bank data asset management platform is convenient for carrying out management operations such as data tracing and data quality inspection on the report data.

Specifically, after the blood edge relation analysis system obtains the blood edge relation data of the report data, the blood edge relation data and the report data information are bound according to the report data information and then sent to the data asset management platform for storage. It can be understood that the data asset management platform can quickly determine the report data information corresponding to the blood-edge relationship data by performing association binding on the blood-edge relationship data and the report data information, so that subsequent management operation can be conveniently executed.

In one embodiment, the data asset management platform of the bank may be provided on a blockchain for management security of the data asset.

In the report blood-edge relationship processing method, when blood-edge analysis demands exist, the report data information to be analyzed is obtained in response to the blood-edge analysis demands, the report data information comprises the data type of the report data and the structured query language of the report data, when the data type is the multi-database report data type, the condition that the data source table with the blood-edge relationship exists in the report data at the moment is indicated, whether the analyzed source table with the source table blood-edge relationship data exists in each data source table is determined according to the information of each source table in the report data, if so, the blood-edge relationship data of the report data is determined according to the source table blood-edge relationship data of the analyzed source table and the structured query language, and the blood-edge relationship data is sent to the data asset management platform according to the report data information. According to the method, the blood-edge relation of the report data is automatically analyzed according to the structured query language of the report data, so that the blood-edge relation data of the report data is obtained, the accuracy and the efficiency of the blood-edge relation analysis can be possibly improved, meanwhile, the analyzed source list is screened for the report data, when an analyzed source list with the blood-edge relation data exists, the blood-edge relation data of the report data can be obtained directly according to the analyzed source list blood-edge relation data and the structured query language, the blood-edge relation analysis of the analyzed data is not required to be repeated, and the blood-edge relation analysis efficiency is further improved.

In one embodiment, when the data type is a multi-library report data type, determining whether an analyzed source table with source table blood relationship data exists in each data source table according to each source table information in the report data comprises:

when the data type is the multi-library report data type, extracting rules according to preset source table information, and acquiring the source table information of the report data from a structured query language of the report data. And determining whether an analyzed source table with source table blood relationship data exists in each data source table according to the source table information.

The preset source table information extraction rule is a preset rule for extracting each source table information of the report data from the structured query language, and it can be understood that when a designer generates the structured query language of the report data, each source table information corresponding to the report data is written in the structured query language of the report data according to the preset information writing rule, then the source table information extraction rule is obtained by back-pushing according to the information writing rule, and the source table information extraction rule is preconfigured in the blood-edge relationship analysis system, so that the blood-edge relationship analysis system can be conveniently called at any time.

The source table information is an information parameter for reflecting source information and attribute information of the data source table. For example, the source table information may include a database to which the data source table belongs, and a service processing type of the data source table, a generation time of the data source table, and the like.

Specifically, when the data type is a multi-library report data type, acquiring a preset source table information extraction rule, extracting information from a structured query language of report data according to the preset source table information extraction rule to obtain source table information of each data source table constituting the report data, and determining whether an analyzed source table with source table blood-edge relation data exists in each data source table constituting the report data according to each source table information.

In this embodiment, the information extraction is performed on the structured query language of the report data by the preset source table information extraction rule, so that the source table information of each data source table can be obtained, and the analyzed source table judgment is performed based on the source table information, so that the accuracy and efficiency of the analyzed source table judgment are effectively improved, and the efficiency of blood-edge relationship analysis is further improved.

Further, in one embodiment, as shown in fig. 3, determining whether an analyzed source table with source table blood edge relationship data exists in each data source table according to each source table information in report data includes:

s302, determining a database to which each data source table of the report data belongs according to the information of each source table in the report data.

Specifically, after the blood relationship analysis system obtains the source table information of each data source table, the database to which each data source table of the report data belongs is determined according to the database identifier carried in each source table information.

S304, obtaining the blood edge relation information of each data source base, wherein the blood edge relation information comprises the corresponding relation between the blood edge relation data of the data base and the data table.

The blood-edge relation information of the database is mapping information for reflecting the corresponding relation between the blood-edge relation data contained in the database and the data table in the database. It can be understood that after the blood edge relationship analysis system analyzes the blood edge relationship of the data table, the relationship identifier of the blood edge data relationship and the table identifier of the corresponding data table are bound and written into the blood edge relationship information of the database so as to facilitate the subsequent searching.

Specifically, the blood-edge relation analysis system obtains blood-edge relation information of each data source base after determining the data source base to which each data source table belongs.

S306, matching each data source table with each data table in the blood-edge relation information, and determining the successfully matched data source table as an analyzed source table with source-table blood-edge relation data.

Specifically, after obtaining the blood edge relation information of the data source database, the blood edge relation analysis system matches the source table identifier of the data source table with the table identifier of the data table in the corresponding blood edge relation information, if the table identifier successfully matched exists, the data source table is indicated to have the corresponding blood edge relation data, and the data source table is determined to be the analyzed source table with the source table blood edge relation data. If the table identification which is successfully matched does not exist, the fact that the data source table does not exist corresponding blood-edge relation data is indicated, and the blood-edge relation of the corresponding field is required to be determined according to the structured query language of the report data.

In this embodiment, by comparing each data source table with the data table in the corresponding blood-edge relationship information, it is able to quickly determine whether there is an analyzed source table from each data source table, thereby effectively improving the determination efficiency and accuracy of the analyzed source table, and further improving the efficiency of blood-edge relationship analysis.

In one embodiment, as shown in FIG. 4, determining the blood-edge relationship data of the report data from the source table blood-edge relationship data of the analyzed source table and the structured query language includes:

s402, acquiring service identifiers of the report data, and determining key information extraction rules of the report data according to the service identifiers.

The service identifier is identification information for determining a service processing type to which the report data belongs, the service processing types are different, the generation rules for generating the report data are different, and correspondingly, the generation modes of the report data structured query language are different.

The key information extraction rule refers to a preset extraction rule for extracting key information from a structured query language of report data, wherein the key information in the structured query language is report field information of the report data, and besides the key information, irrelevant contents exist in the structured query statement of the report data when script files are generated, so that the key information extraction is required to be performed through the key information extraction rule. It can be understood that the types of business processing corresponding to the report data are different, the generation rules for generating the report data are different, the report fields in the report data are also different, the corresponding key information writing modes are also different when the structured query language of the report data is generated, the designer generates the key information extraction rules according to the writing rules of the key information when the structured query language of the report data is generated, and the key information extraction rules and the business identification of the report data are bound and stored.

Specifically, the report data information also carries a service identifier of the report data, the blood relationship analysis system acquires the service identifier of the report data from the report data information, searches a mapping relationship between a preset identifier and a rule according to the service identifier, determines a key information extraction rule corresponding to the service identifier, and determines the key information extraction rule as the key information extraction rule of the report data.

S404, extracting key information from the structured query language based on the key information extraction rule and the source table information of the analyzed source table to obtain a target structured query language of the report data.

The target structured query language refers to an actual analysis language during subsequent blood margin analysis, namely, a structured query language after relevant structured query languages corresponding to the analyzed source tables are removed.

Specifically, the blood relationship analysis system extracts key information from the structured query language based on the key information extraction rule, extracts candidate information related to fields in report data from the structured query language, and then removes information corresponding to the analyzed source table from the candidate information through the source table information of the analyzed source table to obtain a target structured query language of the report data.

S406, performing blood margin relation analysis according to the target structured query language to obtain partial blood margin relation data of the report data.

Specifically, the blood-edge relation analysis system analyzes the blood-edge relation of the target structured query language to obtain partial blood-edge relation data of the report data.

S408, obtaining the blood-edge relation data of the report data based on the partial blood-edge relation data and the source table blood-edge relation data.

Specifically, the blood-edge relation analysis system combines the blood-edge relation data of the report data based on the partial blood-edge relation data and the analyzed blood-edge relation data of the source list.

In this embodiment, key information is extracted from the structured query language by using a key information extraction rule and source table information of an analyzed source table, so as to obtain a target structured query language of report data, and then, the blood-edge relationship analysis is performed based on the screened target structured query language, so that the calculated amount of the blood-edge relationship analysis can be effectively reduced, and the analysis efficiency of the blood-edge relationship analysis can be improved.

In one embodiment, as shown in fig. 5, performing a blood-edge relationship analysis according to a target structured query language to obtain partial blood-edge relationship data of report data, including:

S502, dividing keywords of the target structured query language, and generating an abstract syntax tree of report data according to each divided keyword.

Wherein the abstract syntax tree (Abstract syntax code, AST) is a tree representing the syntax structure of the program consisting of a stream of lexical units converted into a nest of elements.

Specifically, the blood relationship analysis system divides keywords in the target structured query language according to a preset grammar rule to obtain keywords in the target structured query language, then carries out keyword identification on each keyword, and uses the structured query language corresponding to each identified keyword as a node to generate an abstract grammar tree of report data.

S504, carrying out field analysis on each node in the abstract syntax tree to obtain field information of each node and field blood relationship.

Specifically, the blood-edge relation analysis system gives syntactic meaning to the structured query language corresponding to each node in the abstract syntax tree, so as to realize field analysis on each node and obtain field information and field blood-edge relation of each node. The field information is specific content of the field, and the field blood relationship is relationship data of a target source library, a target source table and a target source field to which the field belongs.

S506, based on the field information, correlating the blood-edge relations of the fields to obtain partial blood-edge relation data of the report data.

Specifically, after obtaining the field information of each node and the blood-edge relationship of each field, the blood-edge relationship analysis system correlates the blood-edge relationship of each field according to the field information to obtain partial blood-edge relationship data of the report data. The analysis efficiency and accuracy of the blood-edge relationship analysis can be effectively improved by carrying out the blood-edge relationship analysis through the abstract grammar tree.

Further, in one embodiment, obtaining the blood-edge relationship data of the report data based on the partial blood-edge relationship data and the source table blood-edge relationship data includes:

and acquiring each field node in the source list blood-edge relation data. And drawing and indicating that the connection line is completed according to the source and the destination of each field node and each node in the partial blood-edge relationship data, and obtaining the blood-edge relationship data of the report data.

Specifically, after obtaining source table blood edge relation data, the blood edge relation analysis system obtains field nodes from the source table blood edge relation data, matches each field node with each node in partial blood edge relation data, determines the source and the destination of each field node with each node in partial blood edge relation data, and draws indicating connection line to complete data association according to the source and the destination between each node, so as to obtain the blood edge relation data of report data. The source list blood-edge relation data and part of the blood-edge relation data are associated through the indication connecting line, so that the blood-edge relation of the report data can be visualized and displayed, and the source and the destination of each field data in the report data can be conveniently determined.

In one embodiment, after the blood-edge relation analysis system obtains the blood-edge relation data of the report data, a blood-edge relation file is generated according to the blood-edge relation data and the report data related information, and the blood-edge relation file is sent to the data dictionary platform for warehousing, so that subsequent inquiry is facilitated. The blood relationship file needs to include report target table related information, target table field information, report metadata processing logic and the like, and the report target table related information includes database information, table names, batch numbers and the like. Target table field information, including a target table field, a source table field of the target table field, and a mapping rule, e.g., a field in target table a, derived from B field in source table B.

In one embodiment, if the blood-lineage query needs to be continued, the user may call the query structure based on the service management terminal to display the blood-lineage information on the management terminal page, so as to facilitate development, query and management. The blood relationship result is stored in GBASE library, and after the front page clicks the 'query' button, the background interface is mobilized for query through the online interface.

In one embodiment, as shown in fig. 6, a report blood-edge relationship processing method is provided, and the method specifically includes the following steps:

Firstly, a blood margin relation analysis system responds to a blood margin analysis instruction, and according to the blood margin analysis instruction, report data information to be analyzed carried in the blood margin analysis instruction is obtained, wherein the report data information comprises the data type of report data and the structured query language of the report data. When the data type of the report data is a multi-library report data type, according to a preset source table information extraction rule, acquiring each source table information of the report data from a structured query language of the report data.

After the source table information of each data source table is obtained, determining the database to which each data source table of the report data belongs according to the database identification carried in each source table information, and obtaining the blood edge relation information of each data source table. And matching the source table identifier of the data source table with the table identifier of the data table in the corresponding blood-edge relation information, if the table identifier successfully matched exists, indicating that the data source table has the corresponding blood-edge relation data, and determining the data source table as an analyzed source table with the source table blood-edge relation data. If the table identification which is successfully matched does not exist, the fact that the data source table does not exist corresponding blood-edge relation data is indicated, and the blood-edge relation of the corresponding field is required to be determined according to the structured query language of the report data.

The blood relationship analysis system acquires the business identifier of the report data from the report data information, searches the mapping relation between the preset identifier and the rule according to the business identifier, determines the key information extraction rule corresponding to the business identifier, and determines the key information extraction rule as the key information extraction rule of the report data. And extracting key information from the structured query language based on the key information extraction rule, extracting candidate information related to fields in the report data from the structured query language, and then removing information corresponding to the analyzed source table in the candidate information through the source table information of the analyzed source table to obtain the target structured query language of the report data.

The blood relationship analysis system divides keywords in the target structured query language according to a preset grammar rule to obtain keywords in the target structured query language, then carries out keyword identification on each keyword, and takes the structured query language corresponding to each identified keyword as a node to generate an abstract grammar tree of report data. The method comprises the steps of endowing a syntactic meaning to a structured query language corresponding to each node in an abstract syntax tree, realizing field analysis to each node, obtaining field information of each node and field blood-edge relations, and associating each field blood-edge relation according to the field information to obtain partial blood-edge relation data of report data.

After the blood edge relation analysis system acquires the blood edge relation data of the source table, acquiring each field node from the blood edge relation data of the source table, matching each field node with each node in part of the blood edge relation data, determining the source and the destination of each field node with each node in part of the blood edge relation data, and drawing the data association of the indicating connection according to the source and the destination between each node to obtain the blood edge relation data of the report data.

It should be understood that, although the steps in the flowcharts related to the embodiments described above are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.

Based on the same inventive concept, the embodiment of the application also provides a report blood-edge relationship processing device for realizing the report blood-edge relationship processing method. The implementation scheme of the solution to the problem provided by the device is similar to the implementation scheme recorded in the method, so the specific limitation of the embodiment of the report blood edge relationship processing device or embodiments provided below can be referred to the limitation of the report blood edge relationship processing method hereinabove, and will not be repeated here.

In one embodiment, as shown in fig. 7, a report blood-edge relationship processing apparatus 700 is provided, including: an instruction response module 701, a type determination module 702, a blood relationship determination module 703, and a relationship storage module 704, wherein:

the instruction response module 701 is configured to obtain report data information to be analyzed in response to a blood-margin analysis instruction, where the report data information includes a data type of the report data and a structured query language of the report data.

The type determining module 702 is configured to determine, when the data type is a multi-library report data type, whether an analyzed source table with source table blood-edge relationship data exists in each data source table according to each source table information in the report data.

The blood relationship determining module 703 is configured to determine blood relationship data of the report data according to the source table blood relationship data of the analyzed source table and the structured query language if the analyzed source table exists.

And the relation storage module 704 is used for sending the blood relationship data to the data asset management platform according to the report data information.

When there is a need for blood-edge analysis, the report data information to be analyzed is obtained in response to the blood-edge analysis instruction, the report data information comprises the data type of the report data and the structured query language of the report data, when the data type is a multi-database report data type, the report data is indicated to have a data source table with blood-edge relation at the moment, whether the analyzed source table with the source-table blood-edge relation data exists in each data source table is determined according to the information of each source table in the report data, if so, the blood-edge relation data of the report data is determined according to the source-table blood-edge relation data of the analyzed source table and the structured query language, and the blood-edge relation data is sent to the data asset management platform according to the report data information. According to the method, the blood-edge relation of the report data is automatically analyzed according to the structured query language of the report data, so that the blood-edge relation data of the report data is obtained, the accuracy and the efficiency of the blood-edge relation analysis can be possibly improved, meanwhile, the analyzed source list is screened for the report data, when an analyzed source list with the blood-edge relation data exists, the blood-edge relation data of the report data can be obtained directly according to the analyzed source list blood-edge relation data and the structured query language, the blood-edge relation analysis of the analyzed data is not required to be repeated, and the blood-edge relation analysis efficiency is further improved.

In one embodiment, the type determination module is further to: when the data type is a multi-library report data type, acquiring the source table information of the report data from a structured query language of the report data according to a preset source table information extraction rule; and determining whether an analyzed source table with source table blood relationship data exists in each data source table according to the source table information.

In one embodiment, the type determination module is further to: determining a database to which each data source table of the report data belongs according to the information of each source table in the report data; obtaining blood edge relation information of each data source base, wherein the blood edge relation information comprises the corresponding relation between the blood edge relation data of the data base and the data table; and matching each data source table with each data table in the blood-edge relation information, and determining the successfully matched data source table as an analyzed source table with the blood-edge relation data of the source table.

In one embodiment, the blood relationship determination module is further to: acquiring a service identifier of the report data, and determining a key information extraction rule of the report data according to the service identifier; based on the key information extraction rule and the source table information of the analyzed source table, extracting key information from the structured query language to obtain a target structured query language of report data; performing blood margin relation analysis according to the target structured query language to obtain partial blood margin relation data of the report data; and obtaining the blood-edge relation data of the report data based on the partial blood-edge relation data and the source table blood-edge relation data.

In one embodiment, the blood relationship determination module is further to: dividing keywords of the target structured query language, and generating an abstract syntax tree of report data according to each divided keyword; performing field analysis on each node in the abstract syntax tree to obtain field information of each node and a field blood relationship; and based on the field information, correlating the blood-edge relations of all the fields to obtain partial blood-edge relation data of the report data.

In one embodiment, the blood relationship determination module is further to: acquiring each field node in the source list blood-edge relation data; and drawing and indicating that the connection line is completed according to the source and the destination of each field node and each node in the partial blood-edge relationship data, and obtaining the blood-edge relationship data of the report data.

All or part of the modules in the report blood-edge relation processing device can be realized by software, hardware and a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.

In one embodiment, a computer device is provided, which may be a blood relationship analysis system, the internal structure of which may be as shown in FIG. 8. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer equipment is used for storing report data information, source table information, blood relationship data and other data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program, when executed by the processor, implements a report blood-edge relationship processing method.

It will be appreciated by those skilled in the art that the structure shown in fig. 8 is merely a block diagram of some of the structures associated with the present application and is not limiting of the computer device to which the present application may be applied, and that a particular computer device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.

In one embodiment, a computer device is provided comprising a memory and a processor, the memory having stored therein a computer program, the processor when executing the computer program performing the steps of:

responding to a blood margin analysis instruction, and acquiring report data information to be analyzed, wherein the report data information comprises the data type of the report data and the structured query language of the report data;

when the data type is a multi-library report data type, determining whether an analyzed source table with source table blood-edge relation data exists in each data source table according to the information of each source table in the report data;

if the analyzed source table exists, determining the blood-edge relation data of the report data according to the source table blood-edge relation data of the analyzed source table and the structured query language;

In one embodiment, the processor when executing the computer program further performs the steps of:

determining a database to which each data source table of the report data belongs according to the information of each source table in the report data;

obtaining blood edge relation information of each data source base, wherein the blood edge relation information comprises the corresponding relation between the blood edge relation data of the data base and the data table;

and matching each data source table with each data table in the blood-edge relation information, and determining the successfully matched data source table as an analyzed source table with the blood-edge relation data of the source table.

based on the key information extraction rule and the source table information of the analyzed source table, extracting key information from the structured query language to obtain a target structured query language of report data;

and obtaining the blood-edge relation data of the report data based on the partial blood-edge relation data and the source table blood-edge relation data.

dividing keywords of the target structured query language, and generating an abstract syntax tree of report data according to each divided keyword;

performing field analysis on each node in the abstract syntax tree to obtain field information of each node and a field blood relationship;

acquiring each field node in the source list blood-edge relation data;

and drawing and indicating that the connection line is completed according to the source and the destination of each field node and each node in the partial blood-edge relationship data, and obtaining the blood-edge relationship data of the report data.

In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:

In one embodiment, the computer program when executed by the processor further performs the steps of:

acquiring each field node in the source list blood-edge relation data;

In one embodiment, a computer program product is provided comprising a computer program which, when executed by a processor, performs the steps of:

acquiring each field node in the source list blood-edge relation data;

It should be noted that, user information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, presented data, etc.) referred to in the present application are information and data authorized by the user or sufficiently authorized by each party.

Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the various embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like. The databases referred to in the various embodiments provided herein may include at least one of relational databases and non-relational databases. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic units, quantum computing-based data processing logic units, etc., without being limited thereto.

The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.

The above examples only represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the present application. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application shall be subject to the appended claims.

Claims

1. A report blood relationship processing method is characterized by comprising the following steps:

2. The method of claim 1, wherein when the data type is a multi-library report data type, determining whether an analyzed source table with source table blood relationship data exists in each data source table according to each source table information in the report data comprises:

3. The method according to claim 1 or 2, wherein determining whether an analyzed source table having source table blood relationship data exists in each data source table according to each source table information in the report data comprises:

4. The method of claim 1, wherein the determining the report data based on the source table blood-edge relationship data of the analyzed source table and the structured query language comprises:

5. The method of claim 4, wherein the performing a blood relationship analysis according to the target structured query language to obtain partial blood relationship data of the report data comprises:

6. The method according to claim 4 or 5, wherein the obtaining the report data based on the partial blood-edge relationship data and the source table blood-edge relationship data includes:

acquiring each field node in the source list blood-edge relation data;

7. A report blood relationship processing apparatus, the apparatus comprising:

8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 6 when the computer program is executed.

9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.

10. A computer program product comprising a computer program, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.