A method and system for creating batch data migration templates

Abstract

The present invention discloses a method and system for creating batch data migration templates, which provides convenience for users to create individual security reports, simplifies the steps for users to create individual security reports, and can generate different report information by configuring different templates, thereby improving the flexibility of creating individual security reports. When the system creates a report template, the user can choose to manually create a template, use a template provided by the system, and upload the report to be migrated to the system. The system will automatically identify the header of the current file according to multiple professional dimensions and generate results. It will also analyze some logical problems in the current template in real time and give corresponding prompts at the corresponding positions, greatly improving the accuracy of data when creating the report and the standardization of the report.

Description

Technical Field

[0001] The present application relates to the technical field of batch data migration template creation, and in particular to a batch data migration template creation method and system. Background Art

[0002] In the clinical drug system, when users need to batch migrate multiple case reports, they need to manually create each one individually. The existing manual migration method of case reports is time-consuming and labor-intensive, and due to manual import, there may be inaccurate migration data. In addition, due to the current variety of case report styles, in order to meet users' needs for cross-platform migration of large amounts of data, the traditional method of importing single reports is time-consuming and labor-intensive. Summary of the Invention

[0003] Based on this, in response to the above technical problems, a batch data migration template creation method and system are provided to solve the problem that the traditional single report import method is time-consuming and labor-intensive.

[0004] In a first aspect, a method for creating a batch data migration template is provided, the method comprising:

[0005] In response to the user's input for creating a template, the system receives the file to be entered, analyzes the file, and parses the file to obtain a header data set;

[0006] Determine whether the header data set field matches the system mapping field. If not, record the header data set field, use a sharding method to obtain a field value that matches the header data set, and save the field value into a processing result set;

[0007] If so, determine whether the header data set field matches multiple mapping fields. If so, take the field with the highest matching weight among the multiple mapping fields as the matching item, and take the field with the highest matching weight as the matching item. If not, save the mapping field that the header data set field matches as the matching item in the processing result set;

[0008] When all fields in all header data sets in the file have a corresponding system mapping field, a final result set is generated; and the final result set is analyzed and determined based on the E2B guideline to determine whether the final result set includes all the required fields in the E2B guideline; if not, the required fields in the final result set that do not include the E2B guideline are saved to the highest priority recommendation category in the field recommendation result set; if so, it is determined according to the E2B guideline whether the fields with logical relationships in the final result set exist at the same time; if there are fields in the final result set that do not meet the requirements for the logical relationship between fields, it is determined whether the user directly adds the corresponding field, and if so, the corresponding logical relationship field is added to the final result set in the header; if not, the fields that do not meet the requirements for the logical relationship between fields and the fields that are logically associated with the fields that do not meet the requirements for the logical relationship between fields are stored in the highest priority recommendation category in the field recommendation result set;

[0009] If the final result set contains the requirements for the logical relationship between fields, obtain the current tenant information, and obtain the system mapping fields under the current tenant according to the tenant classification, and then obtain the frequently selected field data set under the current tenant, and analyze and determine whether the final result set contains the frequently selected field data set under the current tenant;

[0010] If the final result set does not include the frequently selected field data set under the current tenant, the excluded fields are saved in a field recommendation result set with a low priority level;

[0011] If the final result set contains all the frequently selected field data sets under the current tenant, the most frequently selected field data sets in the system are obtained according to the system mapping field database, and the final result set is analyzed to determine whether the most frequently selected field data sets are included; if the final result set does not contain the field data sets most frequently selected in the system, the fields not included in the final result set are saved in a field recommendation result set with a low priority level; if the final result set contains all the field data sets most frequently selected under the current tenant, the analysis results are returned to the user, and after the user confirms, the analysis results are saved in the system mapping field database.

[0012] In the above solution, optionally, the field data set analysis rule with the most selection times in the system includes: according to the system mapping field database, the two fields before and after the current field have the highest frequency of appearance, and are considered to be the field with the most selection times.

[0013] In the above solution, further optionally, the method further includes:

[0014] In response to the user's input for creating a template, the user chooses to manually create a template. When the user clicks to save the template, the user-configured information is stored in the database, and the template information is stored in Redis under the current tenant. All template field information under the current tenant and the weight value of each field are stored by tenant classification.

[0015] In the above solution, further optionally, the method further includes:

[0016] In response to the user's input of creating a template, the user selects to use the template automatically configured by the system. When the user selects the system configuration template, if the user directly uses the system default template, after the system template is downloaded in response to the user's download button, the field data is matched;

[0017] If the user needs to modify the template, the system will jump to the details page in response to the user's editing, add, delete or adjust the order of the template fields and save them. The saved field information and the modified template id will be returned to the system, and the template information will be stored in the Redis under the current tenant. All template field information under the current tenant and the weight value of each field will be stored by tenant classification.

[0018] In the above scheme, further optionally, the response to the user's input for creating a template includes: receiving an Excel file passed in by the user, matching it according to the existing dictionary field memory points, and directly determining the mapping relationship if only one dictionary field matches the current header name; if multiple dictionary fields match the current header name, listing the matching field relationships and manually mapping other fields.

[0019] In the above scheme, further optionally, the response to the user's input for creating a template includes: template field weight analysis. Every time the user configures a template, the system will automatically record the number of times the field in the template is selected in the tenant set under the current user and store it in Redis; every time the user wants to configure a template and queries the fields that can be created for the template, the number of field selections recorded in the Redis will be obtained first, and the fields that meet a certain number of occurrences will be extracted as commonly used template field information.

[0020] In the above scheme, further optionally, the response to the user's input for creating a template includes: template field inference, based on the weight analysis of the template field, when the user selects a template field, real-time analysis is performed, and the three most common occurrences of the current field in all recorded templates under the current user's tenant are returned to the user for selection.

[0021] In a second aspect, a batch data migration template creation system is provided, the system comprising:

[0022] Receiving module: used to respond to the user's input of creating a template, receive the file to be entered, analyze the file and parse it to obtain the header data set of the file;

[0023] The first judgment module is used to judge whether the header data set field matches the system mapping field. If not, the header data set field is recorded, a field value of the header data set that matches is obtained by using a sharding method, and the field value is saved in a processing result set.

[0024] The second judgment module is used to judge whether the header data set field matches multiple mapping fields. If so, the field with the highest matching weight among the multiple mapping fields is used as a matching item, and the field with the highest matching weight is used as a matching item. If not, the mapping field matched by the header data set field is saved as a matching item in the processing result set;

[0025] The third judgment module is used to generate a final result set when all fields in all header data sets in the file have a corresponding system mapping field; and the final result set is analyzed and judged based on the E2B guideline to see whether the final result set includes all the required fields in the E2B guideline; if not, the required fields in the final result set that do not include the E2B guideline are saved to the highest priority recommendation category in the field recommendation result set; if so, whether the fields with logical relationships in the final result set exist at the same time according to the E2B guideline; if there are fields in the final result set that do not meet the requirements of the logical relationship between fields, it is judged whether the user directly adds the corresponding field, and if so, the corresponding logical relationship field is added to the final result set in the header; if not, the fields that do not meet the requirements of the logical relationship between fields and the fields that are logically associated with the fields that do not meet the requirements of the logical relationship between fields are stored in the highest priority recommendation category in the field recommendation result set;

[0026] The fourth judgment module is used to obtain the current tenant information if the final result set contains the requirements for the logical relationship between fields, obtain the system mapping fields under the current tenant according to the tenant classification, and then obtain the frequently selected field data set under the current tenant, and analyze and determine whether the final result set contains the frequently selected field data set under the current tenant; if the final result set does not contain the frequently selected field data set under the current tenant, save the excluded fields to a low priority level in the field recommendation result set;

[0027] Generation module: used for obtaining the most frequently selected field dataset in the system according to the system mapping field database if the final result set contains all the frequently selected field datasets under the current tenant, and analyzing and judging whether the final result set contains the most frequently selected field dataset; if the final result set does not contain the field dataset with the most selections in the system, saving the fields not contained in the final result set to a low priority level in the field recommendation result set; if the final result set contains all the field datasets with the most selections under the current tenant, returning the analysis result to the user, and saving the analysis result to the system mapping field database after the user confirms.

[0028] According to a third aspect, a computer device includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are performed:

[0029] In response to the user's input for creating a template, the system receives the file to be entered, analyzes the file, and parses the file to obtain a header data set;

[0030] Determine whether the header data set field matches the system mapping field. If not, record the header data set field, use a sharding method to obtain a field value that matches the header data set, and save the field value into a processing result set;

[0031] If so, determine whether the header data set field matches multiple mapping fields. If so, take the field with the highest matching weight among the multiple mapping fields as the matching item, and take the field with the highest matching weight as the matching item. If not, save the mapping field that the header data set field matches as the matching item in the processing result set;

[0032] When all fields in all header data sets in the file have a corresponding system mapping field, a final result set is generated; and the final result set is analyzed and determined based on the E2B guideline to determine whether the final result set includes all the required fields in the E2B guideline; if not, the required fields in the final result set that do not include the E2B guideline are saved to the highest priority recommendation category in the field recommendation result set; if so, it is determined according to the E2B guideline whether the fields with logical relationships in the final result set exist at the same time; if there are fields in the final result set that do not meet the requirements for the logical relationship between fields, it is determined whether the user directly adds the corresponding field, and if so, the corresponding logical relationship field is added to the final result set in the header; if not, the fields that do not meet the requirements for the logical relationship between fields and the fields that are logically associated with the fields that do not meet the requirements for the logical relationship between fields are stored in the highest priority recommendation category in the field recommendation result set;

[0033] If the final result set contains the requirements for the logical relationship between fields, obtain the current tenant information, and obtain the system mapping fields under the current tenant according to the tenant classification, and then obtain the frequently selected field data set under the current tenant, and analyze and determine whether the final result set contains the frequently selected field data set under the current tenant;

[0034] If the final result set does not include the frequently selected field data set under the current tenant, the excluded fields are saved in a field recommendation result set with a low priority level;

[0035] If the final result set contains all the frequently selected field data sets under the current tenant, the most frequently selected field data sets in the system are obtained according to the system mapping field database, and the final result set is analyzed to determine whether the most frequently selected field data sets are included; if the final result set does not contain the field data sets most frequently selected in the system, the fields not included in the final result set are saved in a field recommendation result set with a low priority level; if the final result set contains all the field data sets most frequently selected under the current tenant, the analysis results are returned to the user, and after the user confirms, the analysis results are saved in the system mapping field database.

[0036] In a fourth aspect, a computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, the computer program implements the following steps:

[0037] In response to the user's input for creating a template, the system receives the file to be entered, analyzes the file, and parses the file to obtain a header data set;

[0038] Determine whether the header data set field matches the system mapping field. If not, record the header data set field, use a sharding method to obtain a field value that matches the header data set, and save the field value into a processing result set;

[0039] If so, determine whether the header data set field matches multiple mapping fields. If so, take the field with the highest matching weight among the multiple mapping fields as the matching item, and take the field with the highest matching weight as the matching item. If not, save the mapping field that the header data set field matches as the matching item in the processing result set;

[0040] When all fields in all header data sets in the file have a corresponding system mapping field, a final result set is generated; and the final result set is analyzed and determined based on the E2B guideline to determine whether the final result set includes all the required fields in the E2B guideline; if not, the required fields in the final result set that do not include the E2B guideline are saved to the highest priority recommendation category in the field recommendation result set; if so, it is determined according to the E2B guideline whether the fields with logical relationships in the final result set exist at the same time; if there are fields in the final result set that do not meet the requirements for the logical relationship between fields, it is determined whether the user directly adds the corresponding field, and if so, the corresponding logical relationship field is added to the final result set in the header; if not, the fields that do not meet the requirements for the logical relationship between fields and the fields that are logically associated with the fields that do not meet the requirements for the logical relationship between fields are stored in the highest priority recommendation category in the field recommendation result set;

[0041] If the final result set contains the requirements for the logical relationship between fields, obtain the current tenant information, and obtain the system mapping fields under the current tenant according to the tenant classification, and then obtain the frequently selected field data set under the current tenant, and analyze and determine whether the final result set contains the frequently selected field data set under the current tenant;

[0042] If the final result set does not include the frequently selected field data set under the current tenant, the excluded fields are saved in a field recommendation result set with a low priority level;

[0043] If the final result set contains all the frequently selected field data sets under the current tenant, the most frequently selected field data sets in the system are obtained according to the system mapping field database, and the final result set is analyzed to determine whether the most frequently selected field data sets are included; if the final result set does not contain the field data sets most frequently selected in the system, the fields not included in the final result set are saved in a field recommendation result set with a low priority level; if the final result set contains all the field data sets most frequently selected under the current tenant, the analysis results are returned to the user, and after the user confirms, the analysis results are saved in the system mapping field database.

[0044] The present invention has at least the following beneficial effects:

[0045] The present invention is based on further analysis and research of existing technical problems and recognizes that in clinical drug systems, when users need to batch migrate multiple individual case reports, they need to manually create individual reports. The existing manual migration of individual case reports is time-consuming and labor-intensive, and due to manual import, there will be inaccurate migration data. In addition, due to the current variety of individual case report styles, in order to meet the needs of users to achieve large-scale cross-platform migration, the traditional method of importing individual reports is time-consuming and labor-intensive. The present invention provides convenience for users to create individual case safety reports, simplifies the steps for users to create individual case safety reports, and can generate different report information by configuring different templates, thereby improving the flexibility of creating individual case safety reports. When the system creates a report template, users can choose to manually create a template, use a template provided by the system, and upload the report to be migrated to the system. The system will automatically identify the header of the current file according to multiple professional dimensions and generate results. It will also analyze some logical problems in the current template in real time and give corresponding prompts in the corresponding positions, greatly improving the accuracy of data when creating reports and the standardization of reports. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 A schematic diagram of a process for creating a batch data migration template according to an embodiment of the present invention;

[0047] Figure 2 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0048] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0049] This application provides a method for creating a batch data migration template, such as Figure 1 As shown, the following steps are included:

[0050] In response to the user's input for creating a template, the system receives the file to be entered, analyzes the file, and parses the file to obtain a header data set;

[0051] Determine whether the header data set field matches the system mapping field. If not, record the header data set field, use a sharding method to obtain a field value that matches the header data set, and save the field value into a processing result set;

[0052] If so, determine whether the header data set field matches multiple mapping fields. If so, take the field with the highest matching weight among the multiple mapping fields as the matching item, and take the field with the highest matching weight as the matching item. If not, save the mapping field that the header data set field matches as the matching item in the processing result set;

[0053] When all fields in all header data sets in the file have a corresponding system mapping field, a final result set is generated; and the final result set is analyzed and determined based on the E2B guideline to determine whether the final result set includes all the required fields in the E2B guideline; if not, the required fields in the final result set that do not include the E2B guideline are saved to the highest priority recommendation category in the field recommendation result set; if so, it is determined according to the E2B guideline whether the fields with logical relationships in the final result set exist at the same time; if there are fields in the final result set that do not meet the requirements for the logical relationship between fields, it is determined whether the user directly adds the corresponding field, and if so, the corresponding logical relationship field is added to the final result set in the header; if not, the fields that do not meet the requirements for the logical relationship between fields and the fields that are logically associated with the fields that do not meet the requirements for the logical relationship between fields are stored in the highest priority recommendation category in the field recommendation result set;

[0054] If the final result set contains the requirements for the logical relationship between fields, obtain the current tenant information, and obtain the system mapping fields under the current tenant according to the tenant classification, and then obtain the frequently selected field data set under the current tenant, and analyze and determine whether the final result set contains the frequently selected field data set under the current tenant;

[0055] If the final result set does not include the frequently selected field data set under the current tenant, the excluded fields are saved in a field recommendation result set with a low priority level;

[0056] If the final result set contains all the frequently selected field data sets under the current tenant, the most frequently selected field data sets in the system are obtained according to the system mapping field database, and the final result set is analyzed to determine whether the most frequently selected field data sets are included; if the final result set does not contain the field data sets most frequently selected in the system, the fields not included in the final result set are saved in a field recommendation result set with a low priority level; if the final result set contains all the field data sets most frequently selected under the current tenant, the analysis results are returned to the user, and after the user confirms, the analysis results are saved in the system mapping field database.

[0057] In one embodiment, the most frequently selected field data set analysis rule in the system includes: according to the system mapping field database, the two fields before and after the current field appear with the highest frequency, and the field is considered to be the most frequently selected field.

[0058] In one embodiment, the method further comprises:

[0059] In response to the user's input for creating a template, the user chooses to manually create a template. When the user clicks to save the template, the user-configured information is stored in the database, and the template information is stored in Redis under the current tenant. All template field information under the current tenant and the weight value of each field are stored by tenant classification.

[0060] In one embodiment, the method further comprises:

[0061] In response to the user's input of creating a template, the user selects to use the template automatically configured by the system. When the user selects the system configuration template, if the user directly uses the system default template, after the system template is downloaded in response to the user's download button, the field data is matched;

[0062] If the user needs to modify the template, the system will jump to the details page in response to the user's editing, add, delete or adjust the order of the template fields and save them. The saved field information and the modified template id will be returned to the system, and the template information will be stored in the Redis under the current tenant. All template field information under the current tenant and the weight value of each field will be stored by tenant classification.

[0063] In one embodiment, the response to the user's input for creating a template includes: receiving an Excel file input by the user, matching according to existing dictionary field memory points, and directly determining the mapping relationship if only one dictionary field matches the current header name; if multiple dictionary fields match the current header name, listing the matching field relationships and manually mapping other fields.

[0064] In one embodiment, the response to the user's input for creating a template includes: template field weight analysis. Every time the user configures a template, the system will automatically record the number of times the field in the template is selected in the tenant set under the current user and store it in Redis; every time the user wants to configure a template and queries the fields that can be created for the template, the number of field selections recorded in the Redis will be obtained first, and the fields that meet a certain number of occurrences will be extracted as commonly used template field information.

[0065] In one embodiment, the response to the user's input for creating a template includes: template field speculation, based on the weight analysis of the template field, when the user selects a template field, real-time analysis, among all the recorded templates under the current user's tenant, the three that appear the most times with the current field, and return them to the user for selection.

[0066] The above-mentioned batch data migration template creation method provides convenience for users to create individual security reports, simplifies the steps for users to create individual security reports, and can generate different report information by configuring different templates, thereby improving the flexibility of creating individual security reports. When the system creates a report template, users can choose to manually create a template, use a template provided by the system, and upload the report to be migrated into the system. The system will automatically identify the header of the current file based on multiple professional dimensions and generate results. It will also analyze some logical problems in the current template in real time and give corresponding prompts at the corresponding locations. This greatly improves the accuracy of data when creating reports and the standardization of reports. It is convenient for users to quickly match data with system fields when migrating data across platforms and generating individual reports in batches.

[0067] It should be understood that although Figure 1 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. In addition, Figure 1 At least part of the steps may include multiple steps or multiple stages. These steps or stages are not necessarily performed at the same time, but can be performed at different times. The order of execution of these steps or stages is not necessarily one by one, but can be performed in turn or alternately with other steps or at least part of the steps or stages in other steps.

[0068] In one embodiment, a batch data migration template creation system is provided, comprising the following program modules:

[0069] Receiving module: used to respond to the user's input of creating a template, receive the file to be entered, analyze the file and parse it to obtain the header data set of the file;

[0070] The first judgment module is used to judge whether the header data set field matches the system mapping field. If not, the header data set field is recorded, a field value of the header data set that matches is obtained by using a sharding method, and the field value is saved in a processing result set.

[0071] The second judgment module is used to judge whether the header data set field matches multiple mapping fields. If so, the field with the highest matching weight among the multiple mapping fields is used as a matching item, and the field with the highest matching weight is used as a matching item. If not, the mapping field matched by the header data set field is saved as a matching item in the processing result set;

[0072] The third judgment module is used to generate a final result set when all fields in all header data sets in the file have a corresponding system mapping field; and the final result set is analyzed and judged based on the E2B guideline to see whether the final result set includes all the required fields in the E2B guideline; if not, the required fields in the final result set that do not include the E2B guideline are saved to the highest priority recommendation category in the field recommendation result set; if so, whether the fields with logical relationships in the final result set exist at the same time according to the E2B guideline; if there are fields in the final result set that do not meet the requirements of the logical relationship between fields, it is judged whether the user directly adds the corresponding field, and if so, the corresponding logical relationship field is added to the final result set in the header; if not, the fields that do not meet the requirements of the logical relationship between fields and the fields that are logically associated with the fields that do not meet the requirements of the logical relationship between fields are stored in the highest priority recommendation category in the field recommendation result set;

[0073] The fourth judgment module is used to obtain the current tenant information if the final result set contains the requirements for the logical relationship between fields, obtain the system mapping fields under the current tenant according to the tenant classification, and then obtain the frequently selected field data set under the current tenant, and analyze and determine whether the final result set contains the frequently selected field data set under the current tenant; if the final result set does not contain the frequently selected field data set under the current tenant, save the excluded fields to a low priority level in the field recommendation result set;

[0074] Generation module: used for obtaining the most frequently selected field dataset in the system according to the system mapping field database if the final result set contains all the frequently selected field datasets under the current tenant, and analyzing and judging whether the final result set contains the most frequently selected field dataset; if the final result set does not contain the field dataset with the most selections in the system, saving the fields not contained in the final result set to a low priority level in the field recommendation result set; if the final result set contains all the field datasets with the most selections under the current tenant, returning the analysis result to the user, and saving the analysis result to the system mapping field database after the user confirms.

[0075] The specific limitations of the batch data migration template creation system can be found in the limitations of the batch data migration template creation method described above and will not be further elaborated here. Each module in the aforementioned batch data migration template creation system may be implemented in whole or in part via software, hardware, or a combination thereof. Each of these modules may be embedded in or independent of a processor within a computer device in hardware form, or may be stored in a computer device memory in software form, allowing the processor to call and execute the corresponding operations of each module.

[0076] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 2 As shown. The computer device includes a processor, a memory, a communication interface, a display screen and an input system connected via a system bus. The processor of the computer device is used 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 and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a method for creating a batch data migration template is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input system of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad provided on the computer device housing, or an external keyboard, touchpad or mouse.

[0077] Those skilled in the art will understand that Figure 2 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0078] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, which involves all or part of the processes in the above-mentioned embodiment method.

[0079] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, which involves all or part of the processes in the above-mentioned embodiment method.

[0080] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0081] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0082] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art could make various modifications and improvements without departing from the spirit of the present application, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present patent application shall be determined by the appended claims.

Claims

1. A method for creating a batch data migration template, characterized in that: The method comprises: In response to the user's input for creating a template, the system receives the file to be entered, analyzes the file, and parses the file to obtain a header data set; Determine whether the header data set field matches the system mapping field. If not, record the header data set field, use a sharding method to obtain a field value that matches the header data set, and save the field value into a processing result set; If so, determine whether the header data set field matches multiple mapping fields. If so, take the field with the highest matching weight among the multiple mapping fields as the matching item, and take the field with the highest matching weight as the matching item. If not, save the mapping field that the header data set field matches as the matching item in the processing result set; When all fields in all header data sets in the file have a corresponding system mapping field, a final result set is generated; and the final result set is analyzed and determined based on the E2B guideline to determine whether the final result set includes all the required fields in the E2B guideline; if not, the required fields in the final result set that do not include the E2B guideline are saved to the highest priority recommendation category in the field recommendation result set; if so, it is determined according to the E2B guideline whether the fields with logical relationships in the final result set exist at the same time; if there are fields in the final result set that do not meet the requirements for the logical relationship between fields, it is determined whether the user directly adds the corresponding field, and if so, the corresponding logical relationship field is added to the final result set in the header; if not, the fields that do not meet the requirements for the logical relationship between fields and the fields that are logically associated with the fields that do not meet the requirements for the logical relationship between fields are stored in the highest priority recommendation category in the field recommendation result set; If the final result set contains the requirements for the logical relationship between fields, obtain the current tenant information, and obtain the system mapping fields under the current tenant according to the tenant classification, and then obtain the frequently selected field data set under the current tenant, and analyze and determine whether the final result set contains the frequently selected field data set under the current tenant; If the final result set does not include the frequently selected field dataset under the current tenant, the excluded fields are saved in a field recommendation result set with a lower priority level; If the final result set contains all the frequently selected field data sets under the current tenant, the most frequently selected field data sets in the system are obtained according to the system mapping field database, and the analysis is performed to determine whether the final result set contains the most frequently selected field data sets; if the final result set does not contain the field data sets most frequently selected in the system, the fields not contained in the final result set are saved in a field recommendation result set with a low priority level; if the final result set contains all the field data sets most frequently selected under the current tenant, the analysis results are returned to the user, and after the user confirms, the analysis results are saved in the system mapping field database.

2. The method according to claim 1, characterized in that The analysis rule of the field data set with the most selection times in the system includes: according to the system mapping field database, the two fields before and after the current field have the highest frequency of appearance, and are considered to be the fields with the most selection times.

3. The method according to claim 1, characterized in that The method further comprises: In response to the user's input for creating a template, the user chooses to manually create a template. When the user clicks to save the template, the user-configured information is stored in the database, and the template information is stored in Redis under the current tenant. All template field information under the current tenant and the weight value of each field are stored by tenant classification.

4. The method according to claim 1, wherein The method further comprises: In response to the user's input of creating a template, the user selects to use the template automatically configured by the system. When the user selects the system configuration template, if the user directly uses the system default template, after the system template is downloaded in response to the user's download button, the field data is matched; If the user needs to modify the template, the system will jump to the details page in response to the user's editing, add, delete or adjust the order of the template fields and save them. The saved field information and the modified template id will be returned to the system, and the template information will be stored in the Redis under the current tenant. All template field information under the current tenant and the weight value of each field will be stored by tenant classification.

5. The method according to claim 1, wherein The response to the user's input for creating a template includes: receiving an Excel file passed in by the user, matching it according to the existing dictionary field memory points, and directly determining the mapping relationship if only one dictionary field matches the current header name; if multiple dictionary fields match the current header name, listing the matching field relationships and manually mapping other fields.

6. The method according to claim 1, characterized in that The response to the user's template creation input includes: template field weight analysis. Every time the user configures a template, the system will automatically record the number of times the field in the template is selected in the tenant set under the current user and store it in Redis; every time the user wants to configure a template and queries the fields that can be created for the template, the number of field selections recorded in the Redis will be obtained first, and the fields that meet a certain number of occurrences will be extracted as commonly used template field information.

7. The method according to claim 6, characterized in that The response to the user's input for creating a template includes: template field speculation, based on the weight analysis of the template field, when the user selects a template field, real-time analysis, among all the recorded templates under the current user's tenant, the three that appear the most times with the current field, and return them to the user for selection.

8. A batch data migration template creation system, characterized in that: The system comprises: Receiving module: used to respond to the user's input of creating a template, receive the file to be entered, analyze the file and parse it to obtain the header data set of the file; The first judgment module is used to judge whether the header data set field matches the system mapping field. If not, the header data set field is recorded, a field value of the header data set that matches is obtained by using a sharding method, and the field value is saved in a processing result set. The second judgment module is used to judge whether the header data set field matches multiple mapping fields. If so, the field with the highest matching weight among the multiple mapping fields is used as a matching item, and the field with the highest matching weight is used as a matching item. If not, the mapping field matched by the header data set field is saved as a matching item in the processing result set; The third judgment module is used to generate a final result set when all fields in all header data sets in the file have a corresponding system mapping field; and the final result set is analyzed and judged based on the E2B guideline to see whether the final result set includes all the required fields in the E2B guideline; if not, the required fields in the final result set that do not include the E2B guideline are saved to the highest priority recommendation category in the field recommendation result set; if so, whether the fields with logical relationships in the final result set exist at the same time according to the E2B guideline; if there are fields in the final result set that do not meet the requirements of the logical relationship between fields, it is judged whether the user directly adds the corresponding field, and if so, the corresponding logical relationship field is added to the final result set in the header; if not, the fields that do not meet the requirements of the logical relationship between fields and the fields that are logically associated with the fields that do not meet the requirements of the logical relationship between fields are stored in the highest priority recommendation category in the field recommendation result set; The fourth judgment module is used to obtain the current tenant information if the final result set contains the requirements for the logical relationship between fields, obtain the system mapping fields under the current tenant according to the tenant classification, and then obtain the frequently selected field data set under the current tenant, and analyze and determine whether the final result set contains the frequently selected field data set under the current tenant; if the final result set does not contain the frequently selected field data set under the current tenant, save the excluded fields to a low priority level in the field recommendation result set; Generation module: used to obtain the most frequently selected field dataset in the system according to the system mapping field database if the final result set contains all the frequently selected field datasets under the current tenant, and analyze and determine whether the final result set contains the most frequently selected field dataset; if the final result set does not contain the field dataset with the most selections in the system, save the fields not included in the final result set to a low priority level in the field recommendation result set; if the final result set contains all the field datasets with the most selections under the current tenant, return the analysis result to the user, and after the user confirms, save the analysis result to the system mapping field database.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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