CN116955366B

CN116955366B - Data import processing method, system, device and storage medium

Info

Publication number: CN116955366B
Application number: CN202311223698.9A
Authority: CN
Inventors: 周鑫; 孙华; 管剑波; 吴敦; 徐央杰; 彭轩; 李丹; 赵珏晶; 陈家乐; 吴梦雨; 傅嘉炜
Original assignee: Baolue Digital Technology Hangzhou Co ltd; Zhongtu Intelligent Technology Zhejiang Co ltd; Baolue Technology Zhejiang Co ltd
Current assignee: Baolue Digital Technology Hangzhou Co ltd; Baolue Technology Zhejiang Co ltd; Zhongtu Intelligent Technology Zhejiang Co ltd
Priority date: 2023-09-21
Filing date: 2023-09-21
Publication date: 2023-12-22
Anticipated expiration: 2043-09-21
Also published as: CN116955366A

Abstract

The application relates to a data import processing method, a system, a device and a storage medium, and relates to the technical field of data processing, wherein the method comprises the following steps: acquiring user uploading data information; according to the user uploading data information, calling the data mapping table information corresponding to the user uploading data information; analyzing and processing the data information uploaded by the user according to a preset data analysis method to form common data information and table head actual data information; according to the matching result between the header actual data information and the data mapping table information, constructing the common data information, the header actual data information and the data mapping table information to obtain structured query language information; and analyzing and acquiring the imported data information corresponding to the structured query language information according to the corresponding relation between the structured query language information and the preset imported data information, and outputting the imported data information. The method and the device have the effect of improving the modeling processing efficiency of the database field.

Description

Data import processing method, system, device and storage medium

Technical Field

The present invention relates to the field of data processing technologies, and in particular, to a data import processing method, system, device, and storage medium.

Background

Excel is office software used to more conveniently process data, and general uses of Excel include accounting-specific, budget, billing and sales, reporting, plan tracking, calendar usage, etc., so that Excel is used by more and more enterprises.

In the related art, in the process of carrying out the service by using the service system, a large amount of Excel data is often required to be imported, and manual entry is generally adopted or the Excel data is directly imported according to field correspondence of a header, so that the subsequent processing of the Excel data is facilitated.

For the related art in the above, the following drawbacks are found: because Excel data forms of users are various, the table heads have uncertainty and irregularity, in the process of processing the imported Excel data, the imported Excel data of the users are not easy to be matched with the database fields accurately, operators are required to input related data which are not matched accurately, processing efficiency of modeling the database fields is reduced, modeling of the database fields related to geographic monitoring information is taken as an example, because the geographic monitoring information relates to multi-dimensional monitoring content, excel tables with a plurality of table heads can be formed, once the situation that the imported Excel data of the users are not matched with the database fields occurs, huge time and effort are consumed by the users to input the manual information matching, and construction efficiency of modeling of the database fields related to the geographic monitoring information is delayed.

Disclosure of Invention

In order to improve the processing efficiency of database field modeling, the application provides a data import processing method, a system, a device and a storage medium.

In a first aspect, the present application provides a data import processing method, which adopts the following technical scheme:

a data import processing method includes:

acquiring user uploading data information;

analyzing and processing the data information uploaded by the user according to a preset data analysis method to form common data information and table head actual data information;

according to the user uploading data information, calling the data mapping table information corresponding to the user uploading data information;

according to the matching result between the header actual data information and the data mapping table information, constructing the common data information, the header actual data information and the data mapping table information to obtain structured query language information;

and analyzing and acquiring the imported data information corresponding to the structured query language information according to the corresponding relation between the structured query language information and the preset imported data information, and outputting the imported data information.

By adopting the technical scheme, the data information uploaded by the user is acquired, the data mapping table information is then acquired, the data information uploaded by the user is analyzed and processed through a data analysis method to form common data information and table head actual data information, the structural query language information is constructed through the matching result between the table head actual data information and the data mapping table information, the imported data information is acquired through structural query language information analysis, and the imported data information is output, so that Excel data imported by the user and the data mapping table information are accurately matched and then the imported data information is output, and further the modeling of a database field by a subsequent operator is facilitated.

Optionally, constructing the common data information, the header actual data information and the data mapping table information to obtain the structured query language information according to a matching result between the header actual data information and the data mapping table information includes:

according to the data mapping table information, table head reference data information corresponding to the data mapping table information is called;

judging whether the actual data information of the header is matched with the reference data information of the header or not;

if yes, analyzing and processing the header reference data information and the header actual data information according to a preset selected matching field analysis method to form selected matching field information;

according to the corresponding relation between the selected matching field information, the common data information and the preset structured query matching language information, analyzing and obtaining structured query matching language information corresponding to the selected matching field information and the common data information, and taking the structured query matching language information as structured query language information;

if not, the header actual data information which is not matched with the header reference data information is taken as header reject data information, and the header reject data information is deleted.

By adopting the technical scheme, the table head reference data information is called through the data mapping table information, whether the table head actual data information is matched with the table head reference data information or not is judged, when the matching exists, the table head reference data information and the table head actual data information are analyzed and processed through the selected matching field analysis method to form selected matching field information, the structured query matching language information is obtained through analysis of the selected matching field information and the common data information, the structured query matching language information is used as the structured query language information, when the matching does not exist, the table head actual data information which is not matched with the table head reference data information is used as the table head reject data information, and the table head reject data information is deleted, so that the imported data information can be output only when the matching exists, and further, the follow-up operator can conveniently model the database field.

Optionally, the analyzing the header reference data information and the header actual data information according to the preset method for analyzing the selected matching field to form the selected matching field information includes:

analyzing and processing the header actual data information according to a preset subscript position determining method to form matched data subscript actual position points;

according to the corresponding relation between the actual position point of the matching data subscript and the preset current field type information, analyzing and obtaining the current field type information corresponding to the actual position point of the matching data subscript;

retrieving updated field information corresponding to the header reference data information according to the header reference data information;

judging whether the current field type information is preset special field type information or not;

if yes, analyzing the type information of the current field according to a preset special field determining method to form special field information, and taking the special field information as selected matching field information;

if not, analyzing the current field type information and the updated field information according to a preset common field determining method to form common field information, and taking the common field information as optional matching field information.

By adopting the technical scheme, the header actual data information is analyzed and processed through the subscript position determining method to form the actual position point of the subscript of the matched data, the current field type information is obtained through the analysis of the actual position point of the subscript of the matched data, the updated field information is called through the header reference data information, whether the current field type information is preset special field type information or not is judged, when the current field type information is the special field type information, the current field type information is analyzed and processed through the special field determining method to form the special field information, the special field information is used as the selected matched field information, when the current field type information and the updated field information are not the special field type information, the common field information is analyzed and processed through the common field determining method to form the common field information, and the common field information is used as the selected matched field information, so that the accuracy of the obtained selected matched field information is improved.

Optionally, the method further includes the steps of taking header actual data information which is not matched with the header reference data information as header reject data information, and deleting the header reject data information, specifically including the following steps:

According to the header reject data information and the header reference data information, analyzing and obtaining deviation information between the header reject data information and the header reference data information and taking the deviation information as header deviation information;

according to the corresponding relation between the header deviation information and the preset deviation degree actual value, analyzing and obtaining the deviation degree actual value corresponding to the header deviation information;

judging whether the actual deviation degree value is smaller than a preset deviation degree reference value or not;

if yes, analyzing the head reject data information according to a preset data type confirmation method to form the head reject data type information;

according to the corresponding relation between the table head reject data type information and the preset data type probability value, analyzing and obtaining the data type probability value corresponding to the table head reject data type information;

according to the corresponding relation between the data type probability value, the header discarding data information and the preset header original data information, analyzing and obtaining header original data information corresponding to the data type probability value and the header discarding data information, and sending the header original data information to a terminal held by an operator;

if not, obtaining a deviation number value;

and analyzing and acquiring deviation factor prediction information corresponding to the deviation times according to the corresponding relation between the deviation times and preset deviation factor prediction information, and sending the deviation factor prediction information to a terminal held by an operator.

By adopting the technical scheme, the deviation information between the head-discarded data information and the head reference data information is obtained through analysis, the deviation information is used as the head deviation information, the actual deviation degree value is obtained through analysis of the head deviation information, whether the actual deviation degree value is smaller than a preset deviation degree reference value is judged, when the deviation degree value is smaller, the head-discarded data information is analyzed and processed through a data type confirmation method to form the head-discarded data type information, the data type probability value is obtained through analysis of the head-discarded data type information, the head original data information is obtained through analysis of the data type probability value and the head-discarded data information, the head original data information is sent to a terminal held by an operator, when the deviation degree value is not smaller, the deviation degree value is obtained through analysis of the deviation degree value, the deviation reason prediction information is sent to the terminal held by the operator, and the head-discarded data information is stored in the data mapping table information, so that when the deviation degree is smaller, the operator is prompted to know about the original data with smaller deviation, and when the deviation degree is larger, the operator is prompted to predict the reason.

Optionally, according to a correspondence between the deviation sub-value and preset deviation cause prediction information, analyzing and obtaining deviation cause prediction information corresponding to the deviation sub-value includes:

judging whether the deviation times value is smaller than a preset times reference value or not;

if yes, outputting preset uploading error prompt information, and taking the uploading error prompt information as deviation reason prediction information;

if not, according to the corresponding relation between the deviation times value and the preset frequently-used probability information, analyzing and acquiring the frequently-used probability information corresponding to the deviation times value, and taking the frequently-used probability information as deviation reason prediction information;

according to the corresponding relation between the header discarding data information and the preset field storage type information, analyzing and obtaining the field storage type information corresponding to the header discarding data information;

and storing the header discard data information in the data mapping table information according to the field storage type information.

By adopting the technical scheme, whether the deviation number value is smaller than the preset number reference value is judged, when the deviation number value is smaller than the preset number reference value, preset uploading error prompt information is output, the uploading error prompt information is used as deviation reason prediction information, when the deviation number value is not smaller than the preset number reference value, frequent use probability information is obtained through analysis of the deviation number value, the frequent use probability information is used as deviation reason prediction information, field storage type information is obtained through analysis of the table head reject data information, the table head reject data information is stored in the data mapping table information through the field storage type information, and therefore accuracy of the obtained deviation reason prediction information is improved, frequent occurrence is stored, and follow-up use is facilitated.

Optionally, according to a correspondence between the structured query language information and preset imported data information, analyzing and obtaining the imported data information corresponding to the structured query language information includes:

analyzing and acquiring the initial information of the imported data corresponding to the structured query language information according to the corresponding relation between the structured query language information and the initial information of the preset imported data;

obtaining a matched number of the header actual data information matched with the header reference data information;

judging whether the number value of the matching number is smaller than a preset number reference value or not;

if yes, directly taking the initial information of the imported data as the imported data information;

if not, analyzing and acquiring matching number influence information corresponding to the matching number according to the corresponding relation between the matching number and the preset matching number influence information;

according to the corresponding relation between the initial information of the imported data, the influence information of the matching number and the preset final information of the imported data, analyzing and obtaining the final information of the imported data corresponding to the initial information of the imported data and the influence information of the matching number, and taking the final information of the imported data as the information of the imported data.

By adopting the technical scheme, the initial information of the imported data is obtained through the analysis of the structured query language information, the matched number value of the matching of the header actual data information and the header reference data information is obtained, whether the matched number value is smaller than the preset number reference value is judged, when the number value is smaller than the preset number reference value, the initial information of the imported data is directly used as the imported data information, when the number value is not smaller than the preset number reference value, the influence information of the matched number is obtained through the analysis of the matched number value, the final information of the imported data is obtained through the analysis of the initial information of the imported data and the influence information of the matched number, and the final information of the imported data is used as the imported data information, so that the accuracy of the obtained imported data information is improved.

Optionally, the method further comprises the step of acquiring the data information uploaded by the user, wherein the step is as follows:

acquiring operator maintenance information;

according to the corresponding relation between the operator maintenance information, the data mapping table information and the preset field remark display information, analyzing and acquiring the field remark display information corresponding to the operator maintenance information and the data mapping table information, and outputting the field remark display information;

acquiring maintenance input field information;

and analyzing and acquiring mapping table modification information corresponding to the maintenance input field information according to the corresponding relation between the maintenance input field information and the preset mapping table modification information, and adding the mapping table modification information into the data mapping table information to form new data mapping table information.

By adopting the technical scheme, the field remark display information is obtained through the analysis of the operator maintenance information and the data mapping table information, the field remark display information is output, the maintenance input field information is obtained, the mapping table modification information is obtained through the analysis of the maintenance input field information, and the mapping table modification information is added into the data mapping table information to form new data mapping table information, so that a user can modify the data mapping table information before uploading data according to the field remark display information, and further the follow-up modeling of database fields is facilitated.

In a second aspect, the present application provides a data import processing system, which adopts the following technical scheme:

a data import processing system, comprising:

the acquisition module is used for acquiring user uploading data information, discarding reference data information, matching numerical values, operator maintenance information and maintenance input field information;

a memory for storing a program of the data import processing method according to any one of the first aspect;

a processor, a program in a memory being capable of being loaded and executed by the processor and implementing the data import processing method according to any one of the first aspects.

By adopting the technical scheme, the acquisition module is used for acquiring the user uploading data information, discarding the reference data information, matching the numerical value, the operator maintenance information and the maintenance input field information, and then the processor is used for loading and executing the program in the memory, so that the operator can conveniently model the database field.

In a third aspect, the present application provides a data import processing apparatus, which adopts the following technical scheme:

a data import processing apparatus comprising a memory and a processor, the memory storing a computer program that can be loaded by the processor and that executes the data import processing method according to any one of the first aspects.

By adopting the technical scheme, the program in the memory is loaded and executed by the processor, so that an operator can model the database field conveniently.

In a fourth aspect, the present application provides a computer storage medium, capable of storing a corresponding program, and having the characteristics of being convenient for an operator to model a database field, and adopting the following technical scheme:

a computer storage medium storing a computer program capable of being loaded by a processor and executing the data import processing method according to any one of the first aspects.

By adopting the technical scheme, the program is stored, and when needed, the program is loaded and executed by the processor, so that an operator can conveniently model the database field.

In summary, the present application includes at least one of the following beneficial technical effects:

1. the method comprises the steps of obtaining data information uploaded by a user, then calling data mapping table information, analyzing and processing the data information uploaded by the user through a data analysis method to form common data information and table head actual data information, constructing structural query language information through a matching result between the table head actual data information and the data mapping table information, analyzing and obtaining imported data information through the structural query language information, and outputting the imported data information, so that Excel data imported by the user and the data mapping table information are accurately matched and then output the imported data information, and further, modeling of database fields by a follow-up operator is facilitated;

2. The method comprises the steps of obtaining header reference data information through data mapping table information, judging whether the header actual data information and the header reference data information are matched or not, when matching exists, analyzing the header reference data information and the header actual data information through an optional matching field analysis method to form optional matching field information, obtaining structural query matching language information through analysis of the optional matching field information and common data information, taking the structural query matching language information as structural query language information, when matching does not exist, taking the header actual data information which is not matched with the header reference data information as header reject data information, deleting the header reject data information, and accordingly outputting imported data information only when matching exists, and further facilitating modeling of a database field by a subsequent operator;

3. analyzing and processing the header actual data information through a subscript position determining method to form a matched data subscript actual position point, analyzing and processing the matched data subscript actual position point to obtain current field type information, calling updated field information through header reference data information, judging whether the current field type information is preset special field type information or not, analyzing and processing the current field type information through a special field determining method to form special field information when the current field type information is the special field type information, analyzing and processing the special field information to be selected to be matched with field information when the current field type information is not the special field type information, analyzing and processing the current field type information and the updated field information through a common field determining method to form common field information, and taking the common field information to be selected to be matched with field information, so that the accuracy of the obtained selected matched field information is improved.

Drawings

Fig. 1 is a flowchart of a method of data import processing according to an embodiment of the present application.

Fig. 2 is a flowchart of a method for constructing common data information, header actual data information and data mapping table information to obtain structured query language information according to a matching result between header actual data information and data mapping table information in an embodiment of the present application.

Fig. 3 is a flowchart of a method for analyzing header reference data information and header actual data information according to a preset method for analyzing an optional matching field to form optional matching field information according to an embodiment of the present application.

Fig. 4 is a flowchart of a method of an embodiment of the present application after taking header actual data information that does not match header reference data information as header discard data information and deleting the header discard data information.

Fig. 5 is a flowchart of a method for analyzing and obtaining deviation factor prediction information corresponding to a deviation factor value according to a correspondence between the deviation factor value and preset deviation factor prediction information in an embodiment of the present application.

Fig. 6 is a flowchart of a method for analyzing and obtaining imported data information corresponding to structured query language information according to a correspondence between the structured query language information and preset imported data information according to an embodiment of the present application.

Fig. 7 is a flowchart of a method of steps prior to obtaining user upload data information in an embodiment of the present application.

Fig. 8 is a system flowchart of a data import process according to an embodiment of the present application.

Reference numerals illustrate: 1. an acquisition module; 2. a memory; 3. a processor.

Description of the embodiments

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to fig. 1 to 8 and the embodiments. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.

The embodiment of the application discloses a data importing processing method.

Referring to fig. 1, a data import processing method includes:

step S100, obtaining user uploading data information.

The user uploading data information refers to Excel data information uploaded by a user, and the user uploading data information is obtained through inquiry after the user uploading.

Step S200, according to the preset data analysis method, the data information uploaded by the user is analyzed and processed to form common data information and table header actual data information.

The data analysis method is used for analyzing Excel data uploaded by a user, and is obtained by inquiring a database storing the data analysis method. The common data information refers to Excel common data information uploaded by a user, and the header actual data information refers to Excel header actual data information uploaded by the user.

And analyzing and processing the data information uploaded by the user through a data analysis method, so that common data information and table head actual data information are formed, and the subsequent use of the common data information and the table head actual data information is facilitated.

Step S300, according to the user uploading data information, the data mapping table information corresponding to the user uploading data information is called.

The data mapping table information refers to mapping table information which is originally stored and used for carrying out auxiliary importing on uploaded Excel data, and the data mapping table information is obtained by inquiring a database storing the data mapping table information.

And the data mapping table information is called through uploading the data information by the user, so that the data mapping table information can be conveniently used later.

Step S400, according to the matching result between the header actual data information and the data mapping table information, the common data information, the header actual data information and the data mapping table information are constructed to obtain the structured query language information.

The structured query language information is information for performing structured query, update and management on Excel data uploaded by a user.

And constructing the common data information, the header actual data information and the data mapping table information to obtain the structured query language information through a matching result between the header actual data information and the data mapping table information, so that the structured query language information is convenient to use later.

Step S500, according to the corresponding relation between the structured query language information and the preset imported data information, the imported data information corresponding to the structured query language information is obtained through analysis, and the imported data information is output.

The imported data information is data information for importing Excel data uploaded by a user, and the imported data information is obtained by inquiring a database storing the imported data information.

The imported data information is obtained through analysis of the structured query language information, and the imported data information is output, so that the imported Excel data imported by a user and the data mapping table information are accurately matched, and then the imported data information is output, and further modeling of database fields by a follow-up operator is facilitated.

In step S400 shown in fig. 1, in order to further ensure the rationality of the structured query language information, further separate analysis and calculation of the structured query language information is required, specifically, the steps shown in fig. 2 are described in detail.

Referring to fig. 2, according to a matching result between header actual data information and data mapping table information, constructing general data information, header actual data information and data mapping table information to obtain structured query language information includes the following steps:

Step S410, the header reference data information corresponding to the data mapping table information is called according to the data mapping table information.

The header reference data information refers to header reference data information for performing auxiliary importing on the uploaded Excel data, and the header reference data information is obtained by inquiring a database storing the header reference data information.

And the header reference data information is called through the data mapping table information, so that the subsequent usage of the header reference data information is facilitated.

Step S420, judging whether there is a match between the header actual data information and the header reference data information. If yes, go to step S430; if not, step S450 is performed.

And judging whether the actual header data of the Excel uploaded by the user is matched with the reference header data or not by judging whether the actual header data of the header is matched with the reference header data or not.

Step S430, according to the preset selected matching field analysis method, the header reference data information and the header actual data information are analyzed and processed to form selected matching field information.

The method for analyzing the selected matching field is used for analyzing the selected field of the header data which is successfully matched, and the method for analyzing the selected matching field is obtained by inquiring a database storing the method for analyzing the selected matching field. The entry matching field information refers to entry field information of header data of successful match.

When the header actual data information is matched with the header reference data information, the fact that the Excel actual header data uploaded by the user is matched to the reference header data at the moment is indicated, so that the header reference data information and the header actual data information are analyzed and processed through an entry matching field analysis method, entry matching field information is formed, and the entry matching field information is convenient to use subsequently.

Step S440, according to the corresponding relation between the selected matching field information, the common data information and the preset structured query matching language information, the structured query matching language information corresponding to the selected matching field information and the common data information is obtained through analysis, and the structured query matching language information is used as the structured query language information.

The structured query matching language information refers to information used for carrying out structured query, update and management on Excel data uploaded by a user after successful matching, and is obtained by querying from a database storing the structured query matching language information.

The structured query matching language information is obtained through analyzing the selected matching field information and the common data information, and the structured query matching language information is used as the structured query language information, so that the structured query language information can be generated only after the matching is successful, and the accuracy of the obtained structured query language information is improved.

In step S450, header actual data information which is not matched with the header reference data information is used as header discard data information, and the header discard data information is deleted.

The header discard data information refers to header data information that needs to be discarded and deleted during the import process.

When the header actual data information is not matched with the header reference data information, the fact that the Excel actual header data uploaded by the user is not matched with the reference header data at the moment is indicated, so that the header actual data information which is not matched with the header reference data information is used as header reject data information, and the header reject data information is deleted, so that the accuracy of the obtained structured query language information is improved, and the influence of the header reject data information on the subsequent steps is reduced.

In step S430 shown in fig. 2, in order to further ensure the rationality of the entry matching field information, further individual analysis calculation of the entry matching field information is required, specifically, the detailed description will be given by the steps shown in fig. 3.

Referring to fig. 3, according to a preset method for analyzing an entry matching field, the method for analyzing header reference data information and header actual data information to form entry matching field information includes the following steps:

In step S431, the header actual data information is analyzed according to the preset subscript position determining method to form the actual position point of the matching data subscript.

The method for determining the position of the lower label is a method for determining the position of the lower label in the actual table head of Excel uploaded by a user, and the method for determining the position of the lower label is obtained by inquiring a database storing the method for determining the position of the lower label. The actual position point of the matched data index is the actual position point of the matched data index.

The header actual data information is analyzed and processed through the index position determining method, so that the index actual position point of the matched data is formed, and the index actual position point of the matched data is convenient to use subsequently.

Step S432, according to the corresponding relation between the actual position point of the matching data index and the preset current field type information, analyzing and obtaining the current field type information corresponding to the actual position point of the matching data index.

The current field type information refers to field type information of a current field corresponding to the successfully matched data, and the current field type information is obtained by inquiring a database storing the current field type information.

And analyzing and acquiring the current field type information through the actual position points of the matched data subscripts, so that the current field type information can be conveniently used later.

Step S433, retrieving updated field information corresponding to the header reference data information according to the header reference data information.

The updated field information refers to updated field information in header reference data, and the updated field information is obtained by inquiring a database storing the updated field information.

And the updated field information is called through the header reference data information, so that the updated field information is convenient to use subsequently.

In step S434, it is determined whether the current field type information is preset special field type information. If yes, go to step S435; if not, step S436 is performed.

The special field type information refers to special type information such as special characters or null data of a current field, and the special field type information is obtained by inquiring a database storing the special field type information.

Judging whether the current field type information is the preset special field type information or not, so as to judge whether the current field type is the special type such as special characters or null data.

In step S435, the current field type information is analyzed according to the preset special field determining method to form special field information, and the special field information is used as the selected matching field information.

The special field determining method is a determining method for determining a special field, and the special field determining method is obtained by inquiring a database storing the special field determining method. The special field information refers to field information when the field is special.

If the current field type information is the preset special field type information, the current field type is the special type such as special characters or null data, so that the special field type information is analyzed and processed through a special field determining method, the special field information is formed, the special field information is used as the selected matching field information, and the accuracy of the acquired selected matching field information is improved.

Step S436, analyzing the current field type information and the updated field information according to the preset common field determining method to form common field information, and using the common field information as the optional matching field information.

The common field determining method is a determining method for determining a common field, and the common field determining method is obtained by inquiring a database storing the common field determining method. The normal field information refers to field information when the field is normal.

If the current field type information is not the preset special field type information, the current field type is not the special type such as special characters or null data, so that the current field type information and the updated field information are analyzed and processed through a common field determining method, common field information is formed, the common field information is used as the selected matching field information, and the accuracy of the acquired selected matching field information is improved.

After step S450 shown in fig. 2, in order to further secure the rationality after the header-discarding data information is deleted, further separate analysis calculation is required after the header-discarding data information is deleted, specifically, the steps shown in fig. 4 will be described in detail.

Referring to fig. 4, the steps after taking header actual data information which is not matched to the header reference data information as header discard data information and deleting the header discard data information include the steps of:

step S451 analyzes and acquires offset information between the header discard data information and the header reference data information as header offset information based on the header discard data information and the header reference data information.

The header deviation information refers to deviation information when a deviation occurs between header data to be discarded and deleted and header reference data in the process.

And analyzing and acquiring deviation information between the header discard data information and the header reference data information through the header discard data information and the header reference data information, and taking the deviation information between the header discard data information and the header reference data information as header deviation information, so that the subsequent use of the header deviation information is facilitated.

Step S452, analyzing and obtaining the actual deviation degree value corresponding to the header deviation information according to the corresponding relation between the header deviation information and the actual preset deviation degree value.

The actual deviation degree value refers to an actual deviation degree value when the header data which is required to be discarded and deleted in the process generates deviation, and the actual deviation degree value is obtained by inquiring a database storing the actual deviation degree value.

The actual value of the deviation degree is obtained through the header deviation information analysis, so that the subsequent use of the actual value of the deviation degree is convenient.

In step S453, it is determined whether the actual deviation degree value is smaller than a preset deviation degree reference value. If yes, go to step S454; if not, step S457 is executed.

The deviation degree reference value refers to a reference deviation degree value when the header data which is required to be discarded and deleted in the process generates deviation, and the deviation degree reference value is inquired and obtained from a database storing the deviation degree reference value.

And judging whether the actual deviation degree value is smaller than a preset deviation degree reference value or not, so as to judge whether larger deviation exists when the header data which is required to be discarded and deleted in the importing process is deviated or not.

Step S454, according to the preset data type confirmation method, analyzing the header-discarding data information to form header-discarding data type information.

The data type confirming method is used for confirming the data type, and is obtained by inquiring a database storing the data type confirming method. The header discard data type information refers to type information of header data that needs to be discarded and deleted in the process.

When the actual value of the deviation degree is smaller than the preset reference value of the deviation degree, the fact that the header data which needs to be discarded and deleted in the importing process has no larger deviation when the deviation occurs is indicated, so that the header discarded data information is analyzed and processed through a data type confirmation method, the header discarded data type information is formed, and the subsequent use of the header discarded data type information is facilitated.

In step S455, according to the correspondence between the header-dropping data type information and the preset data type probability value, the data type probability value corresponding to the header-dropping data type information is obtained.

The data type probability value refers to a probability value when data consistent with the header data type to be discarded and deleted generates deviation, and the data type probability value is inquired and acquired from a database storing the data type probability value.

And analyzing and acquiring the data type probability value through the table head discarding data type information, so that the subsequent use of the data type probability value is facilitated.

Step S456, according to the corresponding relation between the data type probability value, the header discard data information and the preset header original data information, analyzing and obtaining the header original data information corresponding to the data type probability value and the header discard data information, and sending the header original data information to the terminal held by the operator.

The header original data information refers to header original data information which needs to be discarded and deleted, and the header original data information is inquired and obtained from a database storing the header original data information.

And analyzing and acquiring the original data information of the header through the probability value of the data type and the information of the header discard data, and sending the original data information of the header to a terminal held by an operator, so that the operator can know the original data of the header which needs discard deletion in time conveniently.

Step S457, obtain the deviation times value.

The deviation sub-value refers to an actual sub-value when the header data which is required to be discarded and deleted in the process generates deviation, and the deviation sub-value is obtained by inquiring a database when the deviation is generated.

When the actual value of the deviation degree is not smaller than the preset reference value of the deviation degree, the fact that the header data which needs to be discarded and deleted in the importing process generates a larger deviation is indicated, so that the deviation number value is acquired, and the subsequent use of the deviation number value is facilitated.

Step S458, according to the corresponding relation between the deviation times and the preset deviation reason prediction information, analyzing and obtaining the deviation reason prediction information corresponding to the deviation times, and sending the deviation reason prediction information to the terminal held by the operator.

The deviation factor prediction information is prediction information for predicting the cause of the deviation, and is obtained by searching a database storing the deviation factor prediction information.

The deviation reason prediction information is obtained through deviation times numerical analysis and is sent to a terminal held by an operator, so that the operator can know the reason of the deviation in time conveniently.

In step S458 shown in fig. 4, in order to further secure the rationality of the deviation factor prediction information, further individual analysis calculation of the deviation factor prediction information is required, and specifically, the steps shown in fig. 5 will be described in detail.

Referring to fig. 5, according to the correspondence between the deviation count value and the preset deviation factor prediction information, analyzing and acquiring the deviation factor prediction information corresponding to the deviation count value includes the following steps:

in step S4581, it is determined whether the deviation count value is smaller than a preset count reference value. If yes, go to step S4582; if not, step S4583 is performed.

The number reference value refers to a reference number value which can be tolerated when header data which needs to be discarded and deleted in the process generates deviation, and the number reference value is inquired and obtained from a database storing the number reference value.

And judging whether the deviation times value is smaller than a preset times reference value or not, so as to judge whether the header data which is required to be discarded and deleted in the importing process generates deviation for a plurality of times or not.

Step S4582, outputting a preset uploading error prompt message, and taking the uploading error prompt message as deviation reason prediction information.

The uploading error prompt information is prompt information for prompting that the uploading is wrong, and the uploading error prompt information is inquired and obtained from a database storing the uploading error prompt information.

When the deviation number is smaller than the preset number reference value, it is indicated that the header data which is required to be discarded and deleted in the importing process does not generate deviation for multiple times, so that preset uploading error prompt information is output, and the uploading error prompt information is used as deviation reason prediction information, and accuracy of the obtained deviation reason prediction information is improved.

In step S4583, according to the correspondence between the deviation count value and the preset frequently used probability information, the frequently used probability information corresponding to the deviation count value is obtained by analysis, and the frequently used probability information is used as the deviation cause prediction information.

The frequent probability information refers to probability information that is frequently used, and the frequent probability information is obtained by querying from a database storing the frequent probability information.

When the deviation number value is not smaller than the preset number reference value, it is indicated that the header data which is required to be abandoned and deleted in the importing process generates deviation for a plurality of times, so that the frequently used probability information is obtained through analysis of the deviation number value, and the frequently used probability information is used as deviation reason prediction information, and the accuracy of the obtained deviation reason prediction information is improved.

In step S4584, according to the correspondence between the header discard data information and the preset field storage type information, the field storage type information corresponding to the header discard data information is obtained.

The field storage type information refers to type information used for storing the field, and the field storage type information is obtained by inquiring a database storing the field storage type information.

And analyzing and acquiring the field storage type information through the header discard data information, so that the field storage type information is convenient to use later.

In step S4585, the header discard data information is stored in the data mapping table information according to the field storage type information.

The table head reject data information is stored in the data mapping table information through the field storage type information, so that the table head reject data information can be conveniently used later.

In step S500 shown in fig. 1, in order to further secure the rationality of the imported data information, further individual analysis calculation of the imported data information is required, and specifically, the steps shown in fig. 6 will be described in detail.

Referring to fig. 6, according to the correspondence between the structured query language information and the preset imported data information, analyzing and obtaining the imported data information corresponding to the structured query language information includes the following steps:

Step S510, analyzing and obtaining the initial information of the imported data corresponding to the structured query language information according to the corresponding relation between the structured query language information and the initial information of the preset imported data.

The imported data initial information is initial data information for importing Excel data uploaded by a user, and the imported data initial information is obtained by inquiring a database storing the imported data initial information.

The initial information of the imported data is obtained through analysis of the structured query language information, so that the subsequent use of the initial information of the imported data is facilitated.

Step S520, obtaining the matched number of the header actual data information and the header reference data information.

The matching number is an actual number when the header actual data information and the header reference data information are matched, and the matching number is obtained and used as the matching number by the number when the header actual data information and the header reference data information are matched, so that the subsequent use of the matching number is convenient.

In step S530, it is determined whether the matching number is smaller than a preset number reference value. If yes, go to step S540; if not, step S550 is performed.

The number reference value refers to a reference number value when the header actual data information is matched with the header reference data information, and the number reference value is obtained by inquiring a database storing the number reference value.

And judging whether the matching number value is smaller than a preset number reference value or not, so as to judge whether a plurality of matches exist between the actual header data information and the reference header data information.

In step S540, the imported data initial information is directly used as imported data information.

When the number of the matches is smaller than the preset number reference value, it is indicated that there is no multiple matches between the header actual data information and the header reference data information, so that the initial information of the imported data is directly used as the imported data information, and accuracy of the obtained imported data information is improved.

Step S550, according to the corresponding relation between the matching number value and the preset matching number influence information, the matching number influence information corresponding to the matching number value is obtained through analysis.

The matching number influence information refers to influence information of influence of the matching number on the imported initial data, and the matching number influence information is obtained by inquiring a database storing the matching number influence information.

When the number of the matched number is not smaller than the preset number reference value, the fact that a plurality of matches exist between the actual data information of the header and the reference data information of the header is indicated, so that the number of the matched number influence information is obtained through the analysis of the number of the matched number, and the subsequent use of the number of the matched number influence information is facilitated.

Step S560, according to the corresponding relation between the initial information of the imported data, the influence information of the matching number and the preset final information of the imported data, the final information of the imported data corresponding to the initial information of the imported data and the influence information of the matching number is obtained through analysis, and the final information of the imported data is used as the final information of the imported data.

The imported data final information is final data information for importing Excel data uploaded by a user, and the imported data final information is obtained by inquiring a database storing the imported data final information.

And analyzing and acquiring final information of the imported data through initial information of the imported data and influence information of the matching number, and taking the final information of the imported data as the imported data information, so that the accuracy of the acquired imported data information is improved.

Before step S100 shown in fig. 1, in order to further ensure the rationality before the user uploading data information is acquired, further separate analysis calculation is required before the user uploading data information is acquired, specifically, the steps shown in fig. 7 are described in detail.

Referring to fig. 7, the steps before acquiring the user upload data information include the steps of:

step S110, acquiring operator maintenance information.

The operator maintenance information is control information for the operator to start maintenance, and the operator maintenance information is acquired by the operator input.

Step S120, according to the corresponding relation between the operator maintenance information, the data mapping table information and the preset field remark display information, analyzing and obtaining the field remark display information corresponding to the operator maintenance information and the data mapping table information, and outputting the field remark display information.

The field remark display information is display information for displaying remarks of the fields, and the field remark display information is obtained by inquiring a database storing the field remark display information.

The field remark display information is obtained through analysis of the operator maintenance information and the data mapping table information, and the field remark display information is output, so that an operator can know each field conveniently during maintenance.

Step S130, acquiring maintenance input field information.

The maintenance input field information refers to field information input by an operator, and the maintenance input field information is acquired after being input by the operator.

Step S140, according to the corresponding relation between the maintenance input field information and the preset mapping table modification information, the mapping table modification information corresponding to the maintenance input field information is analyzed and obtained, and the mapping table modification information is added into the data mapping table information to form new data mapping table information.

The mapping table modification information refers to modification information for modifying a mapping table, and the mapping table modification information is obtained by inquiring a database storing the mapping table modification information.

And analyzing and acquiring mapping table modification information by maintaining the input field information, and adding the mapping table modification information into the data mapping table information to form new data mapping table information, so that the accuracy of the acquired data mapping table information is improved, and the data mapping table information is convenient to use subsequently.

Referring to fig. 8, based on the same inventive concept, an embodiment of the present invention provides a data import processing system, including:

the acquisition module 1 is used for acquiring user uploading data information, discarding reference data information, matching numerical values, operator maintenance information and maintenance input field information;

a memory 2 for storing a program of the data import processing method as in any one of fig. 1 to 7;

The processor 3, a program in a memory can be loaded and executed by the processor and implement the data import processing method as in any one of fig. 1 to 7.

Based on the same inventive concept, an embodiment of the present invention provides a data import processing apparatus including a memory and a processor, the memory storing a computer program capable of being loaded by the processor and executing the data import processing method as in any one of fig. 1 to 7.

It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional modules is illustrated, and in practical application, the above-described functional allocation may be performed by different functional modules according to needs, i.e. the internal structure of the apparatus is divided into different functional modules to perform all or part of the functions described above. The specific working processes of the above-described systems, devices and units may refer to the corresponding processes in the foregoing method embodiments, which are not described herein.

An embodiment of the present invention provides a computer storage medium storing a computer program capable of being loaded by a processor and executing the data import processing method as in any one of fig. 1 to 7.

The computer storage medium includes, for example: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.

The foregoing description of the preferred embodiments of the present application is not intended to limit the scope of the application, in which any feature disclosed in this specification (including abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise. That is, each feature is one example only of a generic series of equivalent or similar features, unless expressly stated otherwise.

Claims

1. A data importing processing method is characterized in that:

acquiring user uploading data information;

According to the corresponding relation between the structured query language information and the preset imported data information, analyzing and obtaining the imported data information corresponding to the structured query language information, and outputting the imported data information;

according to the matching result between the header actual data information and the data mapping table information, constructing the common data information, the header actual data information and the data mapping table information to obtain the structured query language information comprises the following steps:

2. The data import processing method according to claim 1, wherein the analyzing the header reference data information and the header actual data information according to the preset selected matching field analysis method to form selected matching field information comprises:

3. The data import processing method according to claim 1, further comprising the steps of, after taking header actual data information that does not match the header reference data information as header reject data information and deleting the header reject data information, of:

if not, obtaining a deviation number value;

4. The data import processing method according to claim 3, wherein analyzing and acquiring deviation factor prediction information corresponding to the deviation factor value according to a correspondence between the deviation factor value and preset deviation factor prediction information comprises:

5. The data import processing method according to claim 1, wherein analyzing and acquiring import data information corresponding to the structured query language information according to a correspondence between the structured query language information and preset import data information comprises:

6. The method of claim 1, further comprising the step of, prior to obtaining the user upload data information, the steps of:

acquiring operator maintenance information;

acquiring maintenance input field information;

7. A data import processing system, comprising:

The acquisition module (1) is used for acquiring user uploading data information, discarding reference data information, matching numerical values, operator maintenance information and maintenance input field information;

a memory (2) for storing a program of the data import processing method according to any one of claims 1 to 6;

a processor (3) in which a program is capable of being loaded for execution by the processor and which implements the data import processing method according to any of claims 1 to 6.

8. A data import processing apparatus, characterized by comprising a memory and a processor, the memory storing thereon a computer program capable of being loaded by the processor and executing the data import processing method according to any one of claims 1 to 6.

9. A computer storage medium storing a computer program capable of being loaded by a processor and executing the data import processing method according to any one of claims 1 to 6.