Data processing method and device based on associated data table

Abstract

The present invention provides a data processing method and device based on an associated data table, and relates to the technical field of data processing. The method divides an associated data table in a database list into a main data table and a sub data table, and associates them according to associated fields, thereby improving matching accuracy through an association process; after data query, the associated relationship between the two can also be used to associate and display, greatly improving retrieval efficiency, thereby solving the problems of high difficulty in accurate retrieval and low retrieval efficiency existing in the prior art.

Description

Technical Field

[0001] The present invention relates to the field of data processing, and in particular to a data processing method and device based on an associated data table. Background Art

[0002] For the massive amount of information obtained from social media, news websites and other platforms, it is usually stored in a database. When querying the associated data tables in the database, the search personnel need to use the fields in the database to generate specific search instructions and query the database through a specific data request interface. This type of search process is relatively complicated and requires the search personnel to be familiar with the various fields and data interfaces of the associated database. Since the data query method is mainly based on keyword matching and the correlation is low, it is difficult to perform accurate searches and the retrieval efficiency of data queries is low. Summary of the invention

[0003] In view of this, the purpose of the present invention is to provide a data processing method and device based on associated data tables, which divides the associated data tables in the database list into main data tables and sub data tables, and associates them according to associated fields, thereby improving the matching accuracy through the association process; after the data query, the associated relationship between the two can also be used to associate and display them, greatly improving the retrieval efficiency, thereby solving the problems of high difficulty in accurate retrieval and low retrieval efficiency existing in the prior art.

[0004] In a first aspect, an embodiment of the present invention provides a data processing method based on an association data table, the method comprising:

[0005] Obtain a list of associated data tables to be processed, and determine the master data table and the slave data table using weight parameters corresponding to all associated data tables in the list of associated data tables; wherein the weight parameters are used to characterize the importance of the data table;

[0006] Determine association parameters based on the association fields between the master data table and the slave data table, and perform association processing on the master data table and the slave data table according to the association parameters;

[0007] After the master data table and the slave data table that have completed the association processing are synchronously updated to the list of associated data tables, the data query strategy and the data display strategy corresponding to the list of associated data tables are determined according to the association parameters;

[0008] Perform data query processing on the associated data table list according to the data query strategy, and display the data query processing results according to the data display strategy.

[0009] In one implementation, obtaining a list of associated data tables to be processed, and determining a master data table and a slave data table using weight parameters corresponding to all associated data tables in the list of associated data tables, includes:

[0010] After sending a request instruction to the preset database interface, receiving the associated data table data responded by the preset database interface, and obtaining a list of associated data tables to be processed according to the corresponding public data tables, uploaded data tables, and shared data tables in the associated data table data;

[0011] Obtain all associated data tables contained in the associated data table list, and determine weight parameters corresponding to all associated data tables;

[0012] According to the corresponding weight value in the weight parameter, the master data table and the slave data table included in the associated data table list are determined.

[0013] In one implementation, all associated data tables included in the associated data table list are obtained, and weight parameters corresponding to all associated data tables are determined, including:

[0014] Get all related data tables contained in the related data table list;

[0015] Determine the click parameter corresponding to the associated data table according to the first data corresponding to the click field in the associated data table;

[0016] Based on the click order of the associated data table corresponding to the click parameter, a weight parameter corresponding to the associated data table is determined.

[0017] In one implementation, determining association parameters based on association fields between the master data table and the slave data table, and associating the master data table with the slave data table according to the association parameters includes:

[0018] Traverse all fields contained in the main data table and the sub-data table, and obtain condition fields and associated fields from all fields;

[0019] Determine the association parameter between the master data table and the slave data table based on the second data corresponding to the condition field and the third data corresponding to the association field;

[0020] The main data table and the sub-data table are associated with each other using the associated condition instructions corresponding to the associated parameters.

[0021] In one implementation, synchronously updating the master data table and the slave data table that have completed the association process to the list of associated data tables includes:

[0022] When it is detected that the master data table and the slave data table have completed the association process, the association mark data corresponding to the association parameter is determined;

[0023] After replacing the third data corresponding to the associated field with the associated tag data, the master data table and the slave data table are updated;

[0024] Synchronize the updated master data table and slave data table to the list of related data tables.

[0025] In one implementation, determining a data query strategy and a data display strategy corresponding to the associated data table list according to the associated parameters includes:

[0026] Determine query strategy parameters between the master data table and the slave data table using the association parameters, and determine query instructions and filter instructions for the associated data table list according to the query strategy parameters;

[0027] Determine the data query strategy corresponding to the associated data table list according to the query instruction and the filter instruction;

[0028] The display strategy parameters between the master data table and the slave data table are determined based on the data query strategy, and the data display strategy is determined according to the display strategy parameters.

[0029] In one implementation, performing data query processing on the list of associated data tables according to the data query strategy, and displaying the data query processing results according to the data display strategy, includes:

[0030] Determine the data query instruction corresponding to the associated data table list according to the data query strategy, and use the data query instruction to perform data query processing on the associated data table list;

[0031] The data query processing result corresponding to the data query instruction is obtained, and the corresponding master data table and slave data table in the data query processing result are displayed using the data display strategy.

[0032] In one embodiment, the data display strategy is used to display the corresponding master data table and slave data table in the data query processing result, including:

[0033] Obtain the master data table and the slave data table contained in the data query processing result, and obtain the type fields of the master data table and the slave data table;

[0034] Determine the data table types of the master data table and the slave data table according to the fourth data corresponding to the type field, and determine the data collision strategy using the data table types; wherein the data collision strategy is used to compare and display the master data table and the slave data table;

[0035] Based on the data display strategy and using the data collision strategy, the corresponding main data table and sub-data table in the data query processing results are displayed separately.

[0036] In a second aspect, an embodiment of the present invention provides a data processing device based on an association data table, the device comprising:

[0037] A data table determination module is used to obtain a list of associated data tables to be processed, and determine a master data table and a slave data table using weight parameters corresponding to all associated data tables in the associated data table list; wherein the weight parameters are used to characterize the importance of the data table;

[0038] A data table association module is used to determine association parameters based on the association fields between the master data table and the slave data table, and to associate the master data table with the slave data table according to the association parameters;

[0039] A data table update module is used to synchronously update the master data table and the slave data table that have completed the association processing to the associated data table list, and then determine the data query strategy and data display strategy corresponding to the associated data table list according to the association parameters;

[0040] The data table processing module is used to perform data query processing on the associated data table list according to the data query strategy, and display the data query processing results according to the data display strategy.

[0041] In a third aspect, an embodiment of the present invention further provides an electronic device, including a processor and a memory, wherein the memory stores computer-executable instructions that can be executed by the processor, and the processor executes the computer-executable instructions to implement the steps of the data processing method based on the associated data table provided in the first aspect.

[0042] In a fourth aspect, an embodiment of the present invention further provides a storage medium storing computer executable instructions. When the computer executable instructions are called and executed by a processor, the computer executable instructions prompt the processor to implement the steps of the data processing method based on the associated data table provided in the first aspect.

[0043] The embodiment of the present invention provides a data processing method and device based on an associated data table. In the process of querying associated data on a database, the method first obtains a list of associated data tables to be processed, and determines the master data table and the slave data table using the weight parameters corresponding to all associated data tables in the associated data table list; wherein the weight parameters are used to characterize the importance of the data table; then the associated parameters are determined based on the associated fields between the master data table and the slave data table, and the master data table and the slave data table are associated according to the associated parameters; then the master data table and the slave data table that have completed the associated processing are synchronously updated to the associated data table list, and the data query strategy and data display strategy corresponding to the associated data table list are determined according to the associated parameters; finally, the associated data table list is subjected to data query processing according to the data query strategy, and the data query processing result is displayed according to the data display strategy. The method divides the associated data tables in the database list into the master data table and the slave data table, and associates them according to the associated fields, thereby improving the matching accuracy through the association process; after the data query, the associated relationship between the two can also be used for associated display, greatly improving the retrieval efficiency, thereby solving the problems of high difficulty in accurate retrieval and low retrieval efficiency in the prior art.

[0044] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0045] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0047] Figure 1 A flowchart of a data processing method based on an association data table provided by an embodiment of the present invention;

[0048] Figure 2 A flowchart of step S101 in a data processing method based on an association data table provided in an embodiment of the present invention;

[0049] Figure 3A flowchart of step S202 in a data processing method based on an association data table provided in an embodiment of the present invention;

[0050] Figure 4 A flowchart of step S102 in a data processing method based on an association data table provided in an embodiment of the present invention;

[0051] Figure 5 A flowchart of synchronously updating a master data table and a slave data table that have completed association processing to a list of associated data tables in a data processing method based on associated data tables provided by an embodiment of the present invention;

[0052] Figure 6 A flowchart of a data query strategy and a data display strategy corresponding to an associated data table list according to associated parameters in a data processing method based on an associated data table provided by an embodiment of the present invention;

[0053] Figure 7 A flowchart of step S104 in a data processing method based on an association data table provided in an embodiment of the present invention;

[0054] Figure 8 A flowchart of a data processing method based on an associated data table provided in an embodiment of the present invention, using a data display strategy to display a corresponding master data table and a slave data table in a data query processing result;

[0055] Fig. 9 A schematic diagram of a data processing device based on an association data table provided by an embodiment of the present invention;

[0056] Fig.10 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention.

[0057] icon:

[0058] 910-data table determination module; 920-data table association module; 930-data table update module; 940-data table processing module;

[0059] 101 - processor; 102 - memory; 103 - bus; 104 - communication interface. DETAILED DESCRIPTION

[0060] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution of the present invention will be clearly and completely described in combination with the embodiments below. Obviously, the described embodiments are 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 are within the scope of protection of the present invention.

[0061] Specifically, the method can be applied to a database management system. When performing data query on an associated data table in a database in a database management system, the search personnel need to use the fields in the database to generate specific search instructions, and only through a specific data request interface can the query on the database be realized. This type of search process is relatively complicated, and the search personnel need to be familiar with the various fields and data interfaces of the associated database to be realized. Since the data query method is mainly based on keyword matching and the correlation is low, accurate retrieval is difficult and the retrieval efficiency of data query is low. Based on this, the present invention implements a data processing method and device based on an associated data table, which divides the associated data table in the database list into a main data table and a sub-data table, and associates them according to the associated fields, thereby improving the matching accuracy through the association process; after the data query, the association relationship between the two can also be used for association display, greatly improving the retrieval efficiency.

[0062] To facilitate understanding of this embodiment, a data processing method based on an associated data table disclosed in an embodiment of the present invention is first described in detail. Figure 1 As shown, including:

[0063] Step S101, obtaining a list of associated data tables to be processed, and determining a master data table and a slave data table using weight parameters corresponding to all associated data tables in the list of associated data tables; wherein the weight parameters are used to characterize the importance of the data table;

[0064] Step S102, determining association parameters based on the association fields between the master data table and the slave data table, and performing association processing on the master data table and the slave data table according to the association parameters;

[0065] Step S103, after the master data table and the slave data table that have completed the association processing are synchronously updated to the associated data table list, the data query strategy and the data display strategy corresponding to the associated data table list are determined according to the association parameters;

[0066] Step S104, performing data query processing on the list of associated data tables according to the data query strategy, and displaying the data query processing result according to the data display strategy.

[0067] The list of associated data tables is obtained from the relevant target database, and contains various types of associated data tables; these associated data tables can be divided according to their corresponding table types, upload types, sharing types, etc., and then displayed in the list of associated data tables according to the divided positions. All associated data tables in the list of associated data tables are set with corresponding weight parameters, which represent the importance of the associated data tables, and then the weight parameters can be used to distinguish whether the data table is a master data table or a slave data table.

[0068] In the list of related data tables, the weight parameter of each data table not only reflects its importance, but also determines its priority in data processing and query. Data tables with higher weight parameters usually contain core business data, so they will be given priority in operations such as data synchronization, backup and recovery. In addition, the weight parameter can also be used for relationship analysis between data tables, helping the system automatically identify and optimize the dependencies between data tables.

[0069] In order to better manage and use the list of related data tables, the database management system also provides a variety of filtering and sorting functions. Users can filter according to the weight parameters, table types, upload types, sharing types and other conditions of the data table to quickly find the required data table. At the same time, users can also sort the data tables according to the weight parameters, so that the data tables with higher importance are always in a prominent position in the list.

[0070] In actual applications, the management function of the associated data table list also includes the addition, deletion, modification and query operations of the data table. The administrator can add new associated data tables or modify and delete existing data tables through the preset user interface. The database management system will update the associated data table list in real time according to the administrator's operation to ensure that the data in the list is always up to date.

[0071] In order to improve the efficiency of using data tables, the database management system provides a preview function for data tables. Users can use the preview function to quickly understand the basic information and content summary of the data table without opening the data table. The preview function supports multiple data formats, such as text, pictures, audio and video, so that users can select the appropriate data table for operation according to actual needs.

[0072] Finally, in order to ensure the security and integrity of data, the database management system also provides permission management functions. Administrators can set different data access permissions based on the user's role and responsibilities. Through permission management, the database management system can effectively prevent unauthorized access and data leakage, and ensure the security of data tables. At the same time, the database management system will also regularly back up the list of related data tables to prevent data loss and damage, providing users with more reliable data management services.

[0073] As an example, suppose we have a list of related tables T = {T1, T2, ..., T n}, where n is the number of data tables. Each data table T i There are some characteristics that can help us determine its importance. These characteristics may include but are not limited to: the update frequency of the data table, the number of records in the data table, the degree of connection between the data table and other data tables, the completeness of the fields in the data table, and the relevance of the data table to the business goals.

[0074] Determine feature weights: First, you need to determine the weight of each feature, i.e. w j , where j represents the serial number of feature w. Feature weights can be derived based on expert opinions or historical data analysis.

[0075] Calculate feature scores: For each data table T i , calculate its score s on each feature j ij .

[0076] Calculate the total score: multiply the score of each feature by its corresponding feature weight, and then sum them up to get the data table T i Total score of S i .

[0077] Calculate the weight parameters: Finally, the data table T i Total score of S i Normalize to get the final weight parameter W i .

[0078] Assume that the data table T i There are m features, then the data table T i Total score of S i It can be calculated according to the following formula:

[0079] ;

[0080] in: represents the weight of the jth feature. Represents data table T i The score on the j-th feature.

[0081] Next, for all S i Normalization is performed to ensure that the weight parameter W i The range is between [0,1]. The normalization formula is as follows: ;

[0082] in: and Respectively represent the minimum and maximum values ​​among all the scores in the data table.

[0083] Determine the master data table and the slave data table, specifically, the master data table: weight parameter The higher data table is considered the master data table. Slave data table: Weight parameter The lower data table is considered as the slave data table.

[0084] Assume that there are two features: the number of records in the data table w1 and the degree of association between the data table and other data tables w2, and their weights are given as 0.6 and 0.4 respectively. For data table T1, the number of records has a score of 80 and the degree of association has a score of 70; for data table T2, the number of records has a score of 60 and the degree of association has a score of 80.

[0085] The total scores of T1 and T2 are: S1=0.6×80+0.4×70=48+28=76; S2=0.6×60+0.4×80=36+32=68;

[0086] Assuming that the maximum value of S1 and S2 is 76 and the minimum value is 68, the normalized weight parameters are: W1=(76-68) / (76-68)=1; W2=(68-68) / (76-68)=0.

[0087] Therefore, the weight parameter of data table T1 is 1, and it is regarded as the master data table; the weight parameter of data table T2 is 0, and it is regarded as the slave data table.

[0088] In layman's terms, the master data table can be understood as the master table, and the slave data table is the associated table of the master table. The association between the two is realized through the built-in association fields in each table. Specifically, the association parameters are determined by the data corresponding to the association fields, and then the master data table and the slave data table are associated using the association parameters. After the association processing, the master data table and the slave data table can realize data association processing at the field level, so as to realize the association operation in the subsequent data query and display process.

[0089] After the association processing, the master data table and the slave data table need to be re-synchronized to the associated data table list so that the associated data table list can implement the association operation in the subsequent data query processing. The association operation needs to consider two levels: data query and data display. Therefore, after the associated data table list is synchronously updated, the data query strategy and data display strategy are determined according to the association parameters, which are used for subsequent data query and associated display on the associated data table list.

[0090] Since the associated data table list has completed the associated update for the main data table and the sub-data table, in the subsequent query process, the associated data table list is subjected to data query processing according to the data query strategy, and the obtained data query processing results are associated and displayed according to the data display strategy.

[0091] In one embodiment, a list of associated data tables to be processed is obtained, and step S101 of determining the master data table and the slave data table is performed using weight parameters corresponding to all associated data tables in the associated data table list. Figure 2 As shown, including:

[0092] Step S201, after sending a request instruction to a preset database interface, receiving the associated data table data responded by the preset database interface, and obtaining a list of associated data tables to be processed according to the corresponding public data tables, uploaded data tables, and shared data tables in the associated data table data;

[0093] Step S202, obtaining all associated data tables included in the associated data table list, and determining weight parameters corresponding to all associated data tables;

[0094] Step S203: determining the master data table and the slave data table included in the associated data table list according to the corresponding weight value in the weight parameter.

[0095] The list of associated data tables is obtained from the relevant target database. By sending a request instruction to the preset database interface, the associated data table data in response to the preset database interface can be received. These associated data table data contain various types of associated data tables, which can be divided according to their corresponding table types, upload types, sharing types, etc., and then displayed in the associated data table list according to the divided positions. For example, two left and right areas can be set in the relevant page. The display area on the left displays all data tables including public tables, personal uploads, and shared data tables. Users can click on the data table to expand the display.

[0096] The associated data table is provided with a corresponding weight parameter, which represents the importance of the associated data table, and then distinguishes whether the data table is a master data table or a slave data table according to the corresponding weight value in the weight parameter. In one embodiment, all associated data tables included in the associated data table list are obtained, and step S202 of determining the weight parameters corresponding to all associated data tables is as follows: Figure 3 As shown, including:

[0097] Step S301, obtaining all associated data tables included in the associated data table list;

[0098] Step S302, determining the click parameter corresponding to the associated data table according to the first data corresponding to the click field in the associated data table;

[0099] Step S303: determining a weight parameter corresponding to the associated data table based on the click order of the associated data table corresponding to the click parameter.

[0100] Specifically, the weight parameter can be generated in conjunction with the user click event. The click parameter corresponding to the associated data table is determined by the first data corresponding to the click field in the associated data table, and then the weight parameter corresponding to the associated data table is determined according to the click order of the associated data table corresponding to the click parameter. For example, when the user clicks on the first table, the weight parameter corresponding to the table is set to make it the master data table, and the other data tables are associated tables of the master data table, that is, slave data tables.

[0101] In one implementation, the step S102 of determining association parameters based on the association fields between the master data table and the slave data table, and associating the master data table with the slave data table according to the association parameters is as follows: Figure 4 As shown, including:

[0102] Step S401, traverse all fields included in the master data table and the slave data table, and obtain condition fields and associated fields from all fields;

[0103] Step S402, determining the association parameter between the master data table and the slave data table based on the second data corresponding to the condition field and the third data corresponding to the association field;

[0104] Step S403: using the association condition instruction corresponding to the association parameter, the master data table is associated with the slave data table.

[0105] The conditional field and the associated field ultimately determine the associated parameters, and then generate the corresponding associated conditional instructions. In the actual scenario, two left and right areas are set in the relevant page. The display area on the left displays all associated data tables; the display area on the right is used to set the corresponding associated parameters. At this time, the associated parameters are realized by adding the corresponding associated conditions. By setting the associated conditions in the page, and then saving them in the associated fields corresponding to the master data table and the slave data table, the setting of the associated parameters is realized. Subsequently, the associated conditional instructions corresponding to the associated parameters are used to associate the master data table with the slave data table.

[0106] In one implementation, the master data table and the slave data table that have completed the association process are synchronously updated to the associated data table list, such as Figure 5 As shown, including:

[0107] Step S501, when it is detected that the master data table and the slave data table have completed the association process, determining the association mark data corresponding to the association parameter;

[0108] Step S502, after replacing the third data corresponding to the associated field with the associated mark data, the master data table and the slave data table are updated;

[0109] Step S503: Synchronize the updated master data table and slave data table to the associated data table list.

[0110] After the master data table and the slave data table complete the association process, they need to be resynchronized to the list of associated data tables so that the associated data table list can implement the association operation in the subsequent data query process. In the specific processing process, the corresponding associated tag data is first determined using the association parameters, and then the third data corresponding to the associated field is replaced with the above-mentioned associated tag data, thereby updating the associated fields in the master data table and the slave data table. After the master data table and the slave data table are updated, they are synchronized and updated to the list of associated data tables.

[0111] In one implementation, the data query strategy and data display strategy corresponding to the associated data table list are determined according to the associated parameters, such as Figure 6 As shown, including:

[0112] Step S601, determining query strategy parameters between the master data table and the slave data table using the association parameters, and determining query instructions and screening instructions for the associated data table list according to the query strategy parameters;

[0113] Step S602, determining a data query strategy corresponding to the associated data table list according to the query instruction and the filter instruction;

[0114] Step S603: determining display strategy parameters between the master data table and the slave data table based on the data query strategy, and determining the data display strategy according to the display strategy parameters.

[0115] The association operation needs to consider two aspects: data query and data display. It is implemented through data query strategy and data display strategy. Specifically, the query strategy parameters between the master data table and the slave data table are first determined using the association parameters. The query strategy parameters characterize the subsequent data query process for the associated data table list. The query process follows the associated query of the master data table and the slave data table. Therefore, the query instructions and filtering instructions of the associated data table list can be determined through the query strategy parameters.

[0116] The query instruction and the filter instruction correspond to the data query process. Therefore, the data query strategy corresponding to the associated data table list can be determined through the query instruction and the filter instruction of the associated data table list, thereby realizing the associated query process, and the query result is displayed based on the data display strategy. Specifically, the data display strategy is determined by the display strategy parameters, and the data query strategy is determined based on the display strategy parameters between the master data table and the slave data table.

[0117] In one embodiment, the data query processing is performed on the list of associated data tables according to the data query strategy, and the step S104 of displaying the data query processing result according to the data display strategy is as follows: Figure 7 As shown, including:

[0118] Step S701, determining a data query instruction corresponding to the associated data table list according to a data query strategy, and performing data query processing on the associated data table list using the data query instruction;

[0119] Step S702: obtaining a data query processing result corresponding to the data query instruction, and displaying the corresponding master data table and slave data table in the data query processing result by using a data display strategy.

[0120] Since the list of associated data tables has completed the associated update for the master data table and the slave data table, the associated data table list is processed according to the data query strategy in the subsequent query process, and the obtained data query processing results are displayed in association according to the data display strategy. In the specific implementation process, firstly, the data query instruction corresponding to the data table list is determined according to the data query strategy, and the data query instruction is used to perform data query processing on the associated data table list; then the data query processing result corresponding to the data query instruction is obtained, and the master data table and the slave data table corresponding to the data query processing result are displayed using the data display strategy, thereby realizing the data association display of the master data table and the slave data table.

[0121] In one implementation, the data display strategy is used to display the corresponding master data table and slave data table in the data query processing result, such as Figure 8 As shown, including:

[0122] Step S801, obtaining the master data table and the slave data table contained in the data query processing result, and obtaining the type fields in the master data table and the slave data table;

[0123] Step S802, determining the data table types of the master data table and the slave data table according to the fourth data corresponding to the type field, and determining a data collision strategy using the data table types; wherein the data collision strategy is used to compare and display the master data table and the slave data table;

[0124] Step S803: Based on the data display strategy and using the data collision strategy, the corresponding master data table and the slave data table in the data query processing result are displayed respectively.

[0125] The data display process can be achieved through data collision. In layman's terms, data collision is to compare multiple tables and display the comparison results of each data table. In the specific implementation process, first obtain the type field in the master data table and the slave data table, and then determine the data table type of the master data table and the slave data table based on the fourth data corresponding to the type field, so as to determine the corresponding data collision strategy based on the data table type. After the data collision strategy is determined, based on the data display strategy and data expansion strategy, the corresponding master data table and slave data table in the data query processing results are respectively associated and displayed. For example, data collision requires that there must be at least one personal table, and then the data of these two tables are not associated with each other, but are displayed separately by multiple SQL queries, and finally the comparison results of each data table are achieved.

[0126] Assume that the data contains a master data table and a detail data table, where: the master data table (M) contains basic information of employees, such as name, employee number, department, etc. The detail data table (F) contains performance evaluation records of employees, such as score, evaluation date, etc. The type field involved is the type field, which is used to identify the type of data table. The fourth data corresponds to the data of the field type_data, which is used to store additional information, for example, it can be employee or evaluation in this case. The data collision strategy can use color coding to highlight the differences between the master data table and the detail data table.

[0127] The sample data is as follows:

[0128] The master data table (M) is as follows:

[0129] ID: 1, Name: "Alice", Employee No.: 1001, Department: "HR"

[0130] ID: 2, Name: "Bob", Employee No.: 1002, Department: "IT"

[0131] From the data table (F) specifically:

[0132] Employee No.: 1001, Score: 4.5, Evaluation Date: "2024-07-15"

[0133] Employee No.: 1002, Score: 3.8, Evaluation Date: "2024-07-16"

[0134] In step S801, the master data table and the slave data table are obtained as follows: M={(1,"Alice",1001,"HR"),(2,"Bob",1002,"IT")}; F={(1001,4.5,"2024-07-15"),(1002,3.8,"2024-07-16")}; the type field is obtained as follows: type M ="employee"; type F ="evaluation".

[0135] The data table type determined in step S802 is:

[0136] type_data M = "employee";

[0137] type_data F = "evaluation".

[0138] When determining the data collision strategy, if the data in the master and detail tables do not match, the differences are highlighted in different colors. For example, if the employee ID number in the master table is inconsistent with the detail table, then those rows are highlighted in red. If the performance score is below a certain threshold, then the score is highlighted in yellow.

[0139] Step S803 is based on the data display strategy and uses the data collision strategy to display, which is as follows:

[0140] The master data table (M) is displayed as:

[0141] ID: 1, Name: "Alice", Employee No.: 1001, Department: "HR";

[0142] ID: 2, Name: "Bob", Employee No.: 1002, Department: "IT".

[0143] From the data table (F) it is shown as:

[0144] Employee No.: 1001, Score: 4.5, Evaluation Date: "2024-07-15".

[0145] Employee No.: 1002, Score: 3.8, Evaluation Date: "2024-07-16".

[0146] During the application of the data collision strategy, we check the consistency of the data in the master and detail tables for Employee No. 1001 and 1002. Since all the data is consistent, no color highlighting is used. If there is an inconsistency, such as employee Bob's employee number is mistakenly marked as 1003 in the detail table, Bob's row will be marked red to draw attention. If Bob's performance score is below a certain threshold (such as 4.0), the score of 3.8 will be marked yellow to draw attention.

[0147] The master data table and detail data table are displayed in table form, and data collision strategies are applied to highlight potential problems or important information. In this way, users can clearly see the consistency of the data and potential problem points. This display strategy helps data analysts or administrators quickly identify anomalies in the data and take corresponding measures.

[0148] In actual scenarios, the master data table and the slave data table need to be managed accordingly. Data management is to upload the user's own data files, document files, etc. to create tables to facilitate data query, sharing and other functions. In specific implementation, the data uploaded by the user for table creation is approved by the auditor, and the operation and maintenance personnel assist in table creation and complete the data upload. For the personal data that has been created, you can download the data template to assist in uploading the data, and associate the template with the corresponding data table. Finally, the data is updated after the auditor completes the review.

[0149] When a data file does not have a corresponding data table, you need to execute the data table creation process. During the data table creation process, you need to upload data files in specific formats, such as CSV, xlsx (xls), txt, etc. Data table creation can be divided into public data tables and personal data tables. The difference between public data tables and personal data tables lies in the file format. The file format of public data tables uniformly uses the db identifier. You can filter by adding time, table creation time, data status, keywords, and file format. There are two data statuses: completed and waiting for database creation.

[0150] After the data is accessed, it will be displayed in the table on the corresponding page, where the data status is divided into: Under review, Approved, Rejected, To be created, and Completed. Specifically:

[0151] Under review: After the user uploads the task, the task status is "under review" and is waiting for review by the auditor;

[0152] Passed: The data type is "Data Table Update" or "Document Upload". The status changes to Passed after the reviewer approves it.

[0153] Rejected: The auditor did not approve it;

[0154] Table to be created: The data type is "Data table creation". After the auditor passes, while waiting for the operation and maintenance personnel to create the table, the status is "Table to be created";

[0155] Completed: The data type is "Data table creation". After the auditor approves it and the operation and maintenance personnel complete the table creation, the status is Completed.

[0156] Data table creation can be achieved by setting corresponding buttons. Click the Edit button in the data table creation to jump to the table creation details. The page specifically contains the following function buttons:

[0157] Theme: Themes set in system management are displayed here in the order in which they are set in system management;

[0158] Download volume: The maximum download volume supported by the table in single-table query and data collision;

[0159] Sharing: Supports adding sharers by searching by name or key number, supports adding multiple sharers at a time, and supports deleting sharers;

[0160] Is it a key field? It is the display field in the query result list in the single table query data collision. The default setting for key fields is No.

[0161] Is it a display field: When you click to view details after querying, the fields that can be viewed, the default selection for display fields is yes;

[0162] Is it a cascade query field: When you click to view details after querying, if it is a cascade query field, you can click the field content to jump to the smart search for retrieval. The default selection for cascade fields is No;

[0163] The list supports drag-and-drop sorting and input-based sorting. The fields selected as key fields are automatically displayed at the top. It also supports secondary sorting by dragging and inputting.

[0164] After creating a table, you cannot edit the table name, field name, field comment, field type, or length when editing it again.

[0165] The query process includes the business scenario of single-table query. Single-table query supports configuring query fields for a single form to perform search queries. Click the table name in the associated data list and automatically import the table fields by setting the query conditions. The operation function is similar to data collision, except that this function can only query a single data table.

[0166] It can be seen from the data processing method based on the associated data table in the above embodiment that this method divides the associated data table in the database list into a main data table and a sub data table, and associates them according to the associated fields, thereby improving the matching accuracy through the association process; after the data query, the associated relationship between the two can also be used to associate and display them, greatly improving the retrieval efficiency, thereby solving the problems of high difficulty in accurate retrieval and low retrieval efficiency existing in the prior art.

[0167] For the data processing method based on the associated data table provided in the above embodiment, the embodiment of the present invention provides a data processing device based on the associated data table, such as Fig. 9 As shown, the device comprises:

[0168] The data table determination module 910 is used to obtain a list of associated data tables to be processed, and determine the master data table and the slave data table using weight parameters corresponding to all associated data tables in the associated data table list; wherein the weight parameters are used to represent the importance of the data table;

[0169] The data table association module 920 is used to determine association parameters based on the association fields between the master data table and the slave data table, and to associate the master data table with the slave data table according to the association parameters;

[0170] The data table updating module 930 is used to synchronously update the master data table and the slave data table that have completed the association processing to the associated data table list, and then determine the data query strategy and data display strategy corresponding to the associated data table list according to the association parameters;

[0171] The data table processing module 940 is used to perform data query processing on the associated data table list according to the data query strategy, and display the data query processing result according to the data display strategy.

[0172] From the data processing device based on associated data tables mentioned in the above embodiments, it can be seen that the device divides the associated data tables in the database list into primary data tables and secondary data tables, and associates them according to associated fields, thereby improving the matching accuracy through the association process; after the data query, the associated relationship between the two can also be used to associate and display them, greatly improving the retrieval efficiency, thereby solving the problems of high difficulty in accurate retrieval and low retrieval efficiency existing in the prior art.

[0173] The data processing device based on the associated data table provided in the embodiment of the present invention has the same implementation principle and technical effects as those of the aforementioned data processing method embodiment based on the associated data table. For the sake of brief description, for matters not mentioned in the device embodiment, reference can be made to the corresponding contents in the aforementioned data processing method embodiment based on the associated data table.

[0174] This embodiment also provides an electronic device. The structural diagram of the electronic device is as follows: Fig.10 As shown, the device includes a processor 101 and a memory 102; wherein the memory 102 is used to store one or more computer instructions, and the one or more computer instructions are executed by the processor to implement the steps of the above-mentioned data processing method based on the associated data table.

[0175] Fig.10 The electronic device shown further includes a bus 103 and a communication interface 104 , and the processor 101 , the communication interface 104 and the memory 102 are connected via the bus 103 .

[0176] The memory 102 may include a high-speed random access memory (RAM), and may also include a non-volatile memory, such as at least one disk storage. The bus 103 may be an ISA bus, a PCI bus, or an EISA bus. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Fig.10 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0177] The communication interface 104 is used to connect to at least one user terminal and other network units through a network interface, and send the encapsulated IPv4 message or IPv6 message to the user terminal through the network interface.

[0178] The processor 101 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit or software instructions in the processor 101. The above processor 101 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The disclosed methods, steps and logic block diagrams in the embodiments of the present disclosure can be implemented or executed. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in conjunction with the embodiments of the present disclosure can be directly embodied as a hardware decoding processor for execution, or a combination of hardware and software modules in the decoding processor for execution. The software module may be located in a storage medium mature in the art, such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory 102, and the processor 101 reads the information in the memory 102 and completes the steps of the method of the above embodiment in combination with its hardware.

[0179] An embodiment of the present invention further provides a storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the data processing method based on the associated data table in the above embodiment are executed.

[0180] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0181] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0182] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0183] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that can be executed by a processor. Based on this understanding, the technical solution of the present invention can essentially or in other words, the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0184] Finally, it should be noted that the above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The protection scope of the present invention is not limited thereto. Although the present invention is described in detail with reference to the above-described embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-described embodiments within the technical scope disclosed by the present invention, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A data processing method based on an associated data table, It is characterized in that include: Obtaining a list of associated data tables to be processed, and determining a master data table and a slave data table using weight parameters corresponding to all associated data tables in the list of associated data tables; wherein the weight parameters are used to characterize the importance of the data tables; Determine association parameters based on association fields between the master data table and the slave data table, and perform association processing on the master data table and the slave data table according to the association parameters; After synchronously updating the master data table and the slave data table that have completed the association processing to the associated data table list, determining the data query strategy corresponding to the associated data table list according to the association parameters; Performing data query processing on the associated data table list according to the data query strategy; Determining association parameters based on association fields between the master data table and the slave data table, and associating the master data table with the slave data table according to the association parameters, including: Traversing all fields contained in the master data table and the slave data table, and acquiring condition fields and associated fields from all the fields; Determine the association parameter between the master data table and the slave data table based on the second data corresponding to the condition field and the third data corresponding to the association field; The master data table and the slave data table are associated with each other using the associated condition instruction corresponding to the associated parameter.

2. The data processing method based on the associated data table according to claim 1, It is characterized in that Obtaining a list of associated data tables to be processed, and determining a master data table and a slave data table using weight parameters corresponding to all associated data tables in the list of associated data tables, including: After sending a request instruction to a preset database interface, receiving the associated data table data responded by the preset database interface, and obtaining the associated data table list to be processed according to the corresponding public data table, uploaded data table, and shared data table in the associated data table data; Acquire all associated data tables included in the associated data table list, and determine the weight parameters corresponding to all the associated data tables; The master data table and the slave data table included in the associated data table list are determined according to the corresponding weight value in the weight parameter.

3. The data processing method based on the associated data table according to claim 2, It is characterized in that Acquiring all associated data tables included in the associated data table list and determining the weight parameters corresponding to all the associated data tables includes: Obtain all the associated data tables included in the associated data table list; Determine the click parameter corresponding to the associated data table according to the first data corresponding to the click field in the associated data table; The weight parameter corresponding to the associated data table is determined based on the click order of the associated data table corresponding to the click parameter.

4. The data processing method based on the associated data table according to claim 1, It is characterized in that The method further comprises: Determine the data display strategy corresponding to the associated data table list according to the associated parameters; After performing data query processing on the associated data table list according to the data query strategy, the data query processing result is displayed according to the data display strategy.

5. The data processing method based on the associated data table according to claim 4, It is characterized in that Synchronously updating the master data table and the slave data table that have completed the association process to the associated data table list, including: When it is detected that the master data table and the slave data table have completed the association process, determining the association mark data corresponding to the association parameter; After replacing the third data corresponding to the associated field with the associated mark data, updating the master data table and the slave data table; The updated master data table and the slave data table are synchronized to the associated data table list.

6. The data processing method based on the associated data table according to claim 1, It is characterized in that Determining a data query strategy corresponding to the associated data table list according to the associated parameters includes: Determine query strategy parameters between the master data table and the slave data table using the association parameters, and determine query instructions and screening instructions for the associated data table list according to the query strategy parameters; A data query strategy corresponding to the associated data table list is determined according to the query instruction and the screening instruction.

7. The data processing method based on the associated data table according to claim 4, It is characterized in that After performing data query processing on the associated data table list according to the data query strategy, displaying the data query processing result according to the data display strategy includes: Determine a data query instruction corresponding to the associated data table list according to the data query strategy, and perform data query processing on the associated data table list using the data query instruction; The data query processing result corresponding to the data query instruction is obtained, and the master data table and the slave data table corresponding to the data query processing result are displayed using the data display strategy.

8. The data processing method based on the associated data table according to claim 7, It is characterized in that Using the data display strategy to display the master data table and the slave data table corresponding to the data query processing result includes: Acquire the master data table and the slave data table contained in the data query processing result, and acquire the type field in the master data table and the slave data table; Determining data table types of the master data table and the slave data table according to fourth data corresponding to the type field, and determining a data collision strategy using the data table types; wherein the data collision strategy is used to compare and display the master data table and the slave data table; Based on the data display strategy and using the data collision strategy, the master data table and the slave data table corresponding to the data query processing result are displayed respectively.

9. A data processing device based on an associated data table, It is characterized in that include: A data table determination module is used to obtain a list of associated data tables to be processed, and determine a master data table and a slave data table using weight parameters corresponding to all associated data tables in the associated data table list; wherein the weight parameters are used to characterize the importance of the data table; A data table association module, used to determine association parameters based on the association fields between the master data table and the slave data table, and to associate the master data table with the slave data table according to the association parameters; A data table updating module, configured to synchronously update the master data table and the slave data table that have completed the association processing to the associated data table list, and then determine a data query strategy corresponding to the associated data table list according to the association parameters; A data table processing module, used for performing data query processing on the associated data table list according to the data query strategy; The data table association module is also used to: traverse all fields contained in the main data table and the slave data table, and obtain condition fields and association fields from all the fields; determine the association parameters between the main data table and the slave data table based on the second data corresponding to the condition field and the third data corresponding to the association field; and use the association condition instructions corresponding to the association parameters to associate the main data table with the slave data table.

10. An electronic device, It is characterized in that The method comprises a processor and a memory, wherein the memory stores computer executable instructions that can be executed by the processor, and the processor executes the computer executable instructions to implement the steps of the data processing method based on the associated data table according to any one of claims 1 to 8.

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