CN109635300B - Data verification method and device - Google Patents
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- 238000000034 method Methods 0.000 title claims abstract description 45
- 238000013524 data verification Methods 0.000 title claims abstract description 44
- 238000012795 verification Methods 0.000 claims abstract description 223
- 238000004590 computer program Methods 0.000 claims description 10
- 230000008569 process Effects 0.000 claims description 9
- 230000006870 function Effects 0.000 claims description 8
- 230000000007 visual effect Effects 0.000 abstract description 4
- 238000004891 communication Methods 0.000 description 9
- 238000010586 diagram Methods 0.000 description 5
- 238000012545 processing Methods 0.000 description 4
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- 230000002776 aggregation Effects 0.000 description 2
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- 230000000977 initiatory effect Effects 0.000 description 2
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- 238000013461 design Methods 0.000 description 1
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- 230000003993 interaction Effects 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/232—Orthographic correction, e.g. spell checking or vowelisation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/10—Text processing
- G06F40/166—Editing, e.g. inserting or deleting
- G06F40/186—Templates
Abstract
The data verification method and device provided by the invention are characterized in that the verification of the first field in the data to be verified is arranged after the verification of the second field. Since the first field has a reference to the second field, when the verification of the first field fails, the verification of the second field is no longer performed, and the data information causing the verification of the first field fails is displayed. The data information which causes the failure of the first field verification is the key error data, and the user can directly modify the key error data, so that the problem that the verification result is not visual when a plurality of error data are displayed is avoided, and the user experience is improved.
Description
Technical Field
The present invention relates to the field of data processing, and more particularly, to a data verification method and apparatus.
Background
At present, when a report system processes service data, data interaction is generally realized in an Excel file mode. For the obtained Excel file, the data in the Excel file needs to be checked first, and after the data passes the check, the data can be stored or the subsequent business flow can be carried out. The existing data checking process is to directly perform full-table full-quantity checking; when an error occurs in one piece of check object data, all checks related to the check object data report errors, so that the output check result is not visual, and a user is required to analyze the specific data where the error exists.
Disclosure of Invention
In view of this, the present invention provides a data verification method and apparatus for achieving the purpose of automatic positioning of critical error data.
In order to achieve the above object, the following solutions have been proposed:
a data verification method, comprising:
acquiring data to be verified;
acquiring a verification rule corresponding to the data to be verified, wherein the verification rule comprises a key error verification rule and a continuous error verification rule, a first field refers to a second field, the second field is verification object data of the key error verification rule, and the first field is a verification object of the continuous error verification rule;
and checking the data to be checked by using the key error checking rule, if the data to be checked fails, displaying data information causing the check failure, and checking the data to be checked by using the associated error checking rule.
Optionally, the verification rule further includes a hint type verification rule, and the method further includes:
and checking the data to be checked by using the prompt type checking rule, and displaying prompt information if the checking fails.
Optionally, the check rule further includes a service serious error check rule, and the method further includes:
and checking the data to be checked by utilizing the service serious error checking rule, and stopping checking the data to be checked if the checking fails.
Optionally, the obtaining a verification rule corresponding to the data to be verified includes:
matching to obtain a corresponding intelligent verification template according to the key fields in the data to be verified;
and analyzing the intelligent verification template to obtain the verification rule.
Optionally, the parsing the intelligent verification template to obtain the verification rule includes:
analyzing the intelligent verification template to obtain all verification rules contained in the intelligent verification template;
and selecting the check rule corresponding to the pre-condition field in the data to be checked from all check rules.
Optionally, the step of checking rules and/or displaying data information causing checking failure uses a rule engine to analyze sentences.
Optionally, the database utilized by the method is a database stored based on distributed files.
A data verification apparatus, comprising:
the data acquisition unit is used for acquiring data to be verified;
the rule acquisition unit is used for acquiring a check rule corresponding to the data to be checked, wherein the check rule comprises a key error check rule and a continuous error check rule, a first field refers to a second field, the second field is check object data of the key error check rule, and the first field is a check object of the continuous error check rule;
and the first verification unit is used for verifying the data to be verified by utilizing the key error verification rule, if the verification fails, displaying data information which causes the verification failure, and not verifying the data to be verified by utilizing the associated error verification rule.
Optionally, the verification rule further includes a prompt verification rule, and the apparatus further includes:
and the second verification unit is used for verifying the data to be verified by utilizing the prompt type verification rule, and if verification fails, prompt information is displayed.
Optionally, the check rule further includes a service serious error check rule, and the apparatus further includes:
and the third checking unit is used for checking the data to be checked by utilizing the business serious error checking rule, and stopping checking the data to be checked if the checking fails.
Optionally, the rule obtaining unit includes:
the template acquisition subunit is used for matching to obtain a corresponding intelligent verification template according to the key fields in the data to be verified;
and the rule analysis subunit is used for analyzing the intelligent verification template to obtain the verification rule.
Optionally, the rule parsing subunit includes:
the first rule analysis subunit is used for analyzing the intelligent verification template to obtain all verification rules contained in the intelligent verification template;
and the second rule analysis subunit is used for selecting and obtaining the check rule corresponding to the pre-condition field in the data to be checked from all the check rules.
A data verification device, comprising:
a memory;
a processor; and
a computer program;
wherein the computer program is stored in the memory and configured to be executed by the processor to implement the data verification method described above.
A computer readable storage medium having stored thereon a computer program for execution by a processor to implement the data verification method described above.
Compared with the prior art, the technical scheme of the invention has the following advantages:
according to the data verification method and device, verification of the first field in the data to be verified is set after verification of the second field. Since the first field has a reference to the second field, when the verification of the first field fails, the verification of the second field is no longer performed, and the data information causing the verification of the first field fails is displayed. The data information which causes the failure of the first field verification is the key error data, and the user can directly modify the key error data, so that the problem that the verification result is not visual when a plurality of error data are displayed is avoided, and the user experience is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present invention, and that other drawings can be obtained according to the provided drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a data verification method according to an embodiment of the present invention;
FIG. 2 is a flowchart of acquiring a verification rule corresponding to data to be verified according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a logic structure of a data verification device according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a system for implementing data verification according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a data verification device according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Fig. 1 is a schematic diagram of a data verification method according to an embodiment of the present invention, where an independent microservice may be used as a technical carrier to perform unified and independent processing on data to be verified. The method may comprise the steps of:
s11: and obtaining data to be verified.
The user can import the data to be verified into the verification device applied with the data verification method disclosed by the embodiment of the invention through the front-end equipment. The data to be verified may be data in an Excel file.
S12: and acquiring a verification rule corresponding to the data to be verified.
The verification rules include a critical error verification rule and a joint error verification rule. The first field has reference to the second field, the second field is the check object data of the key error check rule, and the first field is the check object with the error check rule. For example, the first field is tax payment of a payment amount, and the second field is payment amount; the payment amount is the verification object data of the key error verification rule, and the tax amount of the payment amount is the verification object associated with the error verification rule. Since the first field has a reference to the second field, the first field may also be erroneous when the second field has an error. In the present invention, the data having an error in the second field is defined as critical error data.
S13: and checking the data to be checked by utilizing the key error checking rule, if the checking fails, displaying the data information causing the checking failure, and checking the data to be checked by no more utilizing the error checking rule.
The execution of the associated error-checking rules in the present invention follows the critical error-checking rules. When the key error checking rule is used for checking and the checking fails, the corresponding associated error checking rule is not executed. Therefore, the display of a large number of useless error messages is effectively avoided, the real error reasons can be accurately and rapidly positioned, and the user experience is improved.
In a specific embodiment of the present invention, the verification rule may further include a prompt type verification rule, when the data to be verified is verified, the data to be verified is verified by using the prompt type verification rule, and if the verification fails, prompt information is displayed. The verification object data of the prompt type verification rule is a field which is easy to be confused when a user fills in a form in the data to be verified. The verification failure using the hinting verification rule is a failure on the verification rule expression, and does not represent that the data itself has an error. If the verification field is not empty, the verification rule expression writes that the field must be empty, if the value is not empty, the verification fails, and then prompt information is displayed. For example: when a payment application form is filled in an enterprise annual fee payment service, a plurality of amount fields are required to be filled, the names are similar, the fields are easy to be confused and misplaced, the fields are as follows, the enterprise payment is not tax, the enterprise payment is tax, the personal payment is not tax, the personal payment is tax, the correctness of the filling of the payment cannot be directly confirmed at the current service node when the verification is executed, the verification of the following flow node is required, a prompt is required at the moment to enable a user to subjectively confirm again, and when the fact that a certain amount field is not empty is verified, the user is prompted: the xxx monetary value you fill is xxxxx. Xx please confirm.
In a specific embodiment of the present invention, the check rule may further include a service serious error check rule, when checking the data to be checked, check the data to be checked by using the service serious error check rule, if the check fails, displaying data information that causes the check failure, and stopping the check of the data to be checked. For example: when the plan name of the payment application is checked in the annual fee payment service of an enterprise, service rules of different rear flow nodes of the plan name are different and the same member cannot participate in two plans, the rear check is mostly required to be established on the premise that the plan name is correct, and the rear check is reported to be wrong if the plan name is wrongly filled, so that when the plan name is checked to be incorrect, the check of the whole data to be checked is directly stopped, and the wrong data is displayed.
Various service forms in the enterprise annuity system are more, such as forms of services such as enterprise annuity member transfer-out, annuity payment application service, personal information change and the like. In a specific embodiment of the present invention, for different Excel files, corresponding intelligent verification templates are edited according to specific table formats and verification rules in the Excel files, where the intelligent verification templates include verification rules corresponding to the corresponding Excel files. If the business annuity member transfers out the business form without header information, only the analysis and verification of the form are required to be configured; the enterprise annuity payment service initiation form comprises a plurality of different sheet analysis checks; the business annuity payment form contains a plurality of identical sheet resolution checks and the like. And the verification rules of each service have great differences, so that payment needs to be verified for various amounts, personal information change needs to be verified whether change items are correct, and the verification rules are respectively configured and processed.
The intelligent verification template can be designed and generated through SQL (StructuralQuery Language, structured query language), and when the verification rule is required to be modified or newly added, the verification rule can be modified or newly added in a mode of modifying an SQL configuration table, so that the application does not need to be redeployed. The verification work can be simply and quickly completed by means of the intelligent verification template, and column verification, in-row verification, inter-row verification, whole-table verification, multi-sheet verification, multi-form verification and the like are supported. And data in Excel files of different services are verified by using different intelligent verification templates, so that the state of mixing together can be decoupled, and development is faster and simpler. Referring to fig. 2, when verifying data to be verified by means of an intelligent verification template, obtaining a verification rule corresponding to the data to be verified may include the steps of:
s21: and matching to obtain a corresponding intelligent verification template according to the key fields in the data to be verified.
In a specific embodiment of the present invention, the key field in the data to be verified may be a file name. And presetting a mapping relation between file names and intelligent verification templates, and acquiring corresponding intelligent verification templates by utilizing key fields in data to be verified in an actual verification process so as to acquire corresponding verification rules. Analyzing an Excel file by adopting a java POI library, inputting a related key field, matching to obtain a corresponding intelligent verification template, and completing reading and verification of data to be verified by utilizing the intelligent verification template.
S22: and analyzing the intelligent verification template to obtain a verification rule.
The data to be verified and the intelligent verification template are illustrated below.
Payment statement of annuity system
The intelligent verification template corresponding to the payment statement is as follows:
< model-config desc= "Payment detail sheet template-Taikang" >)
< field type= 'String' code= "orgName" value= "$b8" sheet= "payment list" nullable= 'false' maxlength= '40' desc= "business name"/> (header data)
< rule shaetcode= "rowDataList" expression= 'qlfuncUtils@isunique fields ([ "realName" ], "rowDataList")' msg= "members of the same she can only be one person"/> (whole table check)
< dataList sheetCode = "rowDataList" sheet= "payment details table" startrow= "12" endflag= "a, declaring: "endcolumn=" U "desc=" payment list ">
< rule expression = ' dateqlfunc@compactredate (startDate) ' msg = ' payment deadline cannot be earlier than payment initiation period "/> (in-line data verification)
< field type= 'String' code= 'real name' value= '$c' nullable= 'false' maxlength= '50' desc= 'employee name' > (table column data)
< rule level= '3' expression= ' qlfuncUtils@hasblank space (realName) ' msg= ' name "+realname+" "contains space invitation to remove space"/> (column data check)
</field>
</dataList>
</model-config>
The Excel file structure is very complex, and for the design of the corresponding intelligent verification template, the sheet page, the header (single cell), the table body, the row data and the column data in the Excel file can be first divided into a multi-layer data structure. The outer field represents the header or global field (e.g., "A company" in the table), and the dataList represents the table body needs to set the starting line number startRow; the inner field represents the body column data (e.g. "Zhang Sanj"); and then performing verification configuration, namely abstracting a plurality of verification modes such as column value verification, row-to-row verification, in-table verification, multi-sheet page verification and the like. The check is mainly divided into 4 parts, a level error level, a pre-condition of the pre-check, a rule expression of the expression check and error information of the msg check.
The outer layer rule in the template represents global verification and supports multiple sheets; the rule check inside the field of the table is the check of the column field, the external rule represents the check between rows, and various field level check functions are provided inside each field. Such as: type field type, maxLength maximum length, whether the sheet belongs to sheet, nullable is not null, decmamaplplaces character precision and the like, is flexible to use, and various fields and functions can be unconfigured if not needed.
The expression verification rule is generally abstracted according to business logic, for example, to verify that the current payment start date is greater than 1 month 1 day 2014 and whether the average social wages are greater than 4% of the tax paid by individuals, and can be abstracted into the following expression, and verification can be completed by using such an expression, (startDate > toDate (2014-01-01)) & (society salary < = tprumtax 4%).
For the same Excel file, but when different verification rules are needed, the problem that the workload required by maintaining a plurality of intelligent verification templates is large can be avoided by setting the rule pre-conditions. For example, when the same form is used for a plurality of payment modes, some special verification of the payment modes can be omitted, and at the moment, verification by using different verification rules under different payment modes is realized by setting rule pre-conditions for the verification rules. Specifically, analyzing the intelligent verification template to obtain all verification rules contained in the intelligent verification template; and selecting and obtaining the check rule corresponding to the pre-condition field in the data to be checked from all check rules. For example, the pre-check represents a pre-condition, the content of the pre-condition field is special payment, if the value of the pre-check is true, the corresponding check rule is used for checking, and the program content is as follows:
< rule pre= "paynttype= special payment"
Expression= ' dateqlfunc@checkPaymentIntervalDuplex (startDate, endDa te, realName, certiTypeId, certiCode, company name, teSum, tpSum, feSum, fpSum) ' ms g= ' realName + "overlaps" +vapplyid + "with a payment time interval.
In one embodiment of the invention, the rules engine may be applied to preconditions, to the rules themselves, and to display data information that causes verification failure. Statement analysis is performed by applying a QLExpress rule engine, for example, check of a social flat wage such as (startDate > toDate (2014-01)) & (society salary < = tprumtax 4%), wherein english represents a plurality of field names of references, the rule engine can be directly used for obtaining from the context, and detail is shielded and obtained; the method can also directly calculate and return to correctness, and the configuration is very flexible and quick.
For simple form verification, the data can be first placed on the temporary surface and the inner surface of a relational database for verification. For complex forms, if a relational database is used, multiple tables need to be built, and changes to the database are also needed, which is difficult to develop and maintain. In one embodiment of the invention, the data caching is performed by utilizing a database MongoDB based on distributed file storage. The MongoDB hashed data structure does not need to create a table, all the forms only need to be serially transmitted in a map form, a great number of MongoDB aggregation functions are applied, and the processing speed of Excel files is also increased. Through testing, for an Excel form analysis and verification process of 2000 lines, 30s-40s are needed according to a relational database, and the process by using MongoDB only needs about 6s, so that the memory consumption is reduced, and the utilization rate of a system CPU is improved.
For the foregoing method embodiments, for simplicity of explanation, the methodologies are shown as a series of acts, but one of ordinary skill in the art will appreciate that the present invention is not limited by the order of acts, as some steps may, in accordance with the present invention, occur in other orders or concurrently.
The following are examples of the apparatus of the present invention that may be used to perform the method embodiments of the present invention. For details not disclosed in the embodiments of the apparatus of the present invention, please refer to the embodiments of the method of the present invention.
Referring to fig. 3, a data verification apparatus according to an embodiment of the present invention is provided. The apparatus may include: a data acquisition unit 31, a rule acquisition unit 32 and a first verification unit 33. Wherein,
a data acquisition unit 31 for acquiring data to be verified.
The rule obtaining unit 32 is configured to obtain a verification rule corresponding to the data to be verified, where the verification rule includes a critical error verification rule and a concatenated error verification rule, a first field refers to a second field, the second field is verification object data of the critical error verification rule, and the first field is a verification object of the concatenated error verification rule.
The first checking unit 33 is configured to check the data to be checked using the key error checking rule, and if the check fails, display data information that causes the check failure, and no longer check the data to be checked using the associated error checking rule.
Optionally, the verification rule further includes a prompt verification rule, and the apparatus further includes: and the second verification unit is used for verifying the data to be verified by utilizing the prompt type verification rule, and if verification fails, prompt information is displayed.
Optionally, the check rule further includes a service serious error check rule, and the apparatus further includes: and the third checking unit is used for checking the data to be checked by utilizing the business serious error checking rule, and stopping checking the data to be checked if the checking fails.
Optionally, the rule obtaining unit includes: and the template acquisition subunit and the rule analysis subunit.
The template acquisition subunit is used for matching to obtain a corresponding intelligent verification template according to the key fields in the data to be verified;
and the rule analysis subunit is used for analyzing the intelligent verification template to obtain the verification rule.
Optionally, the rule parsing subunit includes: a first rule parsing subunit and a second rule parsing subunit.
The first rule analysis subunit is used for analyzing the intelligent verification template to obtain all verification rules contained in the intelligent verification template;
and the second rule analysis subunit is used for selecting and obtaining the check rule corresponding to the pre-condition field in the data to be checked from all the check rules.
Referring to fig. 4, a system structure capable of implementing data verification is shown. Business personnel import Excel data files or directly enter form information through an enterprise annuity VIP customer service platform and submit the Excel data files or the form information; the service interface platform of the enterprise annuity trusted system receives and stores the file, and calls the intelligent check service interface service platform after simple processing; the intelligent checking interface service platform acquires a corresponding intelligent checking template according to the key field of the data to be checked, analyzes the data file and stores the analyzed data into a MongoDB for temporary storage; and respectively checking a plurality of rules such as row data, line data, whole table, multiple tables and the like on the data to be checked by utilizing the analyzed checking rules. The application data cache reduces the access times of the relational database, and the MongoDB aggregation function operates the data to accelerate data verification. After the verification is finished, if error information is output, the data is structured and standardized to be output uniformly if no error exists.
The data verification device provided by the embodiment of the invention can be applied to data verification equipment, such as PC terminals, cloud platforms, servers, server clusters and the like. The server may be one or more of a rack server, a blade server, a tower server, and a rack server. Referring to FIG. 5, a schematic diagram of a preferred embodiment of the data verification device of the present invention is shown. The hardware structure of the data verification device may include: at least one processor 51, at least one communication interface 52, at least one memory 53 and at least one communication bus 54;
in the embodiment of the present invention, the number of the processor 51, the communication interface 52, the memory 53 and the communication bus 54 is at least one, and the processor 51, the communication interface 52 and the memory 53 complete communication with each other through the communication bus 54;
processor 51 may be a CPU (CentralProcessing Unit ) or ASIC (Application Specific Integrated Circuit, application specific integrated circuit) in some embodiments, or one or more integrated circuits configured to implement embodiments of the present invention, etc.
Communication interface 52 may include a standard wired interface, a wireless interface (e.g., WI-FI interface). Typically for establishing a communication connection between the data verification device and other electronic devices or systems.
The memory 53 includes at least one type of readable storage medium. The readable storage medium may be an NVM (non-volatile memory) such as flash memory, hard disk, multimedia card, card memory, etc. The readable storage medium may also be a high speed RAM (random access memory ) memory. The readable storage medium may in some embodiments be an internal storage unit of a data verification device, such as a hard disk of the data verification device. In other embodiments, the readable storage medium may also be an external storage device of the data verification device, for example, a plug-in hard disk, SMC (Smart Media Card), SD (Secure Digital) Card, flash Card (Flash Card) or the like, which are provided on the data verification device.
Wherein the memory 53 stores a computer program, the processor 51 may call the computer program stored in the memory 53, the computer program being for:
acquiring data to be verified;
acquiring a verification rule corresponding to the data to be verified, wherein the verification rule comprises a key error verification rule and a continuous error verification rule, a first field refers to a second field, the second field is verification object data of the key error verification rule, and the first field is a verification object of the continuous error verification rule;
and checking the data to be checked by using the key error checking rule, if the data to be checked fails, displaying data information causing the check failure, and checking the data to be checked by using the associated error checking rule.
The refinement and expansion functions of the program may be described with reference to the above.
Fig. 5 shows only a data verification device having components 51-54, but it should be understood that not all of the illustrated components are required to be implemented, and that more or fewer components may alternatively be implemented.
Optionally, the data verification device may further comprise a user interface, which may comprise an input unit (such as a keyboard), a voice input means (such as a device with voice recognition functionality comprising a microphone) and/or a voice output means (such as a sound box, a headset, etc.). Optionally, the user interface may also include a standard wired interface and/or a wireless interface.
Optionally, the data verification device may further comprise a display, which may also be referred to as a display screen or display unit. In some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) display, or the like. The display is used for displaying information processed in the data verification device and for displaying a visual user interface.
Optionally, the data verification device further comprises a touch sensor. The area provided by the touch sensor for a user to perform a touch operation is referred to as a touch area. Further, the touch sensor may be a resistive touch sensor, a capacitive touch sensor, or the like. The touch sensor may include not only a contact type touch sensor but also a proximity type touch sensor. Further, the touch sensor may be a single sensor or may be a plurality of sensors arranged in an array, for example. The user may enter identification information or initiate a data verification procedure by touching the touch area.
In addition, the area of the display of the data verification device may be the same as or different from the area of the touch sensor. Optionally, a display is layered with the touch sensor to form a touch display screen. The device detects a touch operation triggered by a user based on a touch display screen.
The data verification device may also include RF (Radio Frequency) circuits, sensors and audio circuits, etc., which are not repeated here.
The embodiment of the present invention also provides a readable storage medium storing a program adapted to be executed by a processor, the program being configured to:
acquiring data to be verified;
acquiring a verification rule corresponding to the data to be verified, wherein the verification rule comprises a key error verification rule and a continuous error verification rule, a first field refers to a second field, the second field is verification object data of the key error verification rule, and the first field is a verification object of the continuous error verification rule;
and checking the data to be checked by using the key error checking rule, if the data to be checked fails, displaying data information causing the check failure, and checking the data to be checked by using the associated error checking rule.
The refinement and expansion functions of the program may be described with reference to the above.
The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
In this document, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (8)
1. A method of data verification, comprising:
acquiring data to be verified;
acquiring a verification rule corresponding to the data to be verified, wherein the verification rule comprises a key error verification rule and a continuous error verification rule, a first field refers to a second field, the second field is verification object data of the key error verification rule, and the first field is a verification object of the continuous error verification rule;
the key error checking rule is utilized to check the data to be checked, if the checking fails, data information causing the checking failure is displayed, and the data to be checked is not checked by utilizing the associated error checking rule;
the obtaining the verification rule corresponding to the data to be verified comprises the following steps: matching to obtain a corresponding intelligent verification template according to the key fields in the data to be verified; analyzing the intelligent verification template to obtain the verification rule;
wherein the method further comprises: setting rule pre-conditions for the verification rules, wherein the rule pre-conditions are used for realizing verification by using different verification rules; the analyzing the intelligent verification template to obtain the verification rule comprises the following steps: analyzing the intelligent verification template to obtain all verification rules contained in the intelligent verification template; selecting and obtaining the check rule corresponding to the precondition field in the data to be checked from all check rules according to the rule preconditions;
the intelligent verification template creation process comprises the following steps: dividing sheet pages, headers, table bodies, row data and column data in an Excel file into a multi-layer data structure, wherein an outer layer field represents a header or a global field, a dataList represents a table body, a starting row number startRow needs to be set, and an inner layer field represents a target column data; configuring a verification rule, wherein the verification rule comprises column value verification, inter-row verification, in-table verification and multi-sheet page verification, and an outer layer rule in the intelligent verification template represents global verification and supports the multi-sheet page verification; the rule check inside the table field is a check of the column field, the external rule represents an inter-row check, and various field level check functions are provided inside each field.
2. The method of claim 1, wherein the verification rules further comprise hint-type verification rules, the method further comprising:
and checking the data to be checked by using the prompt type checking rule, and displaying prompt information if the checking fails.
3. The method of claim 1 or 2, wherein the check rules further comprise a traffic severity error check rule, the method further comprising:
and checking the data to be checked by utilizing the service serious error checking rule, if the checking fails, displaying data information causing the checking failure, and stopping checking the data to be checked.
4. The method according to claim 1, wherein the step of checking rules and/or displaying data information that causes a check failure uses a rules engine for statement parsing.
5. The method of claim 1, wherein the database utilized by the method is a distributed file storage based database.
6. A data verification apparatus, comprising:
the data acquisition unit is used for acquiring data to be verified;
the rule acquisition unit is used for acquiring a check rule corresponding to the data to be checked, wherein the check rule comprises a key error check rule and a continuous error check rule, a first field refers to a second field, the second field is check object data of the key error check rule, and the first field is a check object of the continuous error check rule;
the first verification unit is used for verifying the data to be verified by utilizing the key error verification rule, if the verification fails, displaying data information causing the verification failure, and not verifying the data to be verified by utilizing the associated error verification rule;
the rule acquisition unit is specifically configured to obtain a corresponding intelligent verification template according to matching of key fields in the data to be verified; analyzing the intelligent verification template to obtain the verification rule;
wherein the apparatus further comprises: setting rule pre-conditions for the verification rules, wherein the rule pre-conditions are used for realizing verification by using different verification rules; the analyzing the intelligent verification template to obtain the verification rule comprises the following steps: analyzing the intelligent verification template to obtain all verification rules contained in the intelligent verification template; selecting and obtaining the check rule corresponding to the precondition field in the data to be checked from all check rules according to the rule preconditions;
the intelligent verification template creation process comprises the following steps: dividing sheet pages, headers, table bodies, row data and column data in an Excel file into a multi-layer data structure, wherein an outer layer field represents a header or a global field, a dataList represents a table body, a starting row number startRow needs to be set, and an inner layer field represents a target column data; configuring a verification rule, wherein the verification rule comprises column value verification, inter-row verification, in-table verification and multi-sheet page verification, and an outer layer rule in the intelligent verification template represents global verification and supports the multi-sheet page verification; the rule check inside the table field is a check of the column field, the external rule represents an inter-row check, and various field level check functions are provided inside each field.
7. A data verification device, comprising:
a memory;
a processor; and
a computer program;
wherein the computer program is stored in the memory and configured to be executed by the processor to implement the data verification method of any one of claims 1-5.
8. A computer readable storage medium having stored thereon a computer program, the computer program being executable by a processor to implement the data verification method of any one of claims 1-5.
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| CN110399428B (en) * | 2019-07-26 | 2022-02-11 | 北京奇艺世纪科技有限公司 | Data verification method and device and electronic equipment |
| CN110765090B (en) * | 2019-10-31 | 2023-05-02 | 泰康保险集团股份有限公司 | Log data management method and device, storage medium and electronic equipment |
| CN111414739B (en) * | 2020-02-27 | 2023-04-14 | 北京中亦安图科技股份有限公司 | Excel data entry component, entry method and device |
| CN113723767A (en) * | 2021-08-10 | 2021-11-30 | 上海浦东发展银行股份有限公司 | Business process quality inspection method and device based on voice interaction data |
| CN115879164A (en) * | 2021-09-29 | 2023-03-31 | 华为技术有限公司 | Data verification method, device, equipment and storage medium |
| CN114547033B (en) * | 2022-02-22 | 2024-01-16 | 苏州浪潮智能科技有限公司 | Method, system, equipment and storage medium for managing key product data |
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