CN117827814A - Data verification method, device, computer equipment and storage medium - Google Patents

Abstract

The application belongs to the field of artificial intelligence and the field of financial science and technology, and relates to a data verification method, which comprises the following steps: acquiring row data meeting the conditions from a test data table, and acquiring a first row number of each row of data; determining designated line data corresponding to the first line number from a production data table; performing row and column splicing processing on each row of data and each appointed row of data to obtain corresponding first spliced data and second spliced data; converting each first spliced data and each second spliced data based on a target hash algorithm to obtain a corresponding first hash value and a corresponding second hash value; and performing data verification processing on the first hash value and the second hash value to generate a corresponding data verification result. The application also provides a data verification device, computer equipment and a storage medium. Furthermore, the data verification results of the present application may be stored in a blockchain. The method and the device can be applied to the table data verification scene in the financial field, the processing efficiency of data table verification is improved, and the accuracy of the data verification result is ensured.

Description

Data verification method, device, computer equipment and storage medium

Technical Field

The application relates to the technical field of artificial intelligence development and the field of financial science and technology, in particular to a data verification method, a data verification device, computer equipment and a storage medium.

Background

The data accuracy and consistency are the premise and key indexes of the development of data teams of financial and scientific enterprises (such as insurance enterprises and banks), and the key index consistency is ensured to be an important link before the online and is also the key content of business attention by verifying the difference between the test data and the production data between the local test data table and the production data table.

Most of the problems of business feedback of the current financial and technological enterprises are related to the difference of the signboard data of the financial and technological enterprises, and feedback such as no access to data pairs, index statistics and the like of different financial and technological platforms are common in a plurality of business data scenes in the financial and technological enterprises. Along with the business expansion of financial and scientific enterprises, the data has the characteristics of various dimensions, massive indexes and the like. The data development demands of the business are also mostly focused on two aspects of increasing dimension and index. Therefore, in particular, higher fineness is required to be put into the problems of verifying data and searching index data differences. The data result verification function developed by the financial service platform of the existing financial and scientific enterprise only supports the aggregation and summarization of a plurality of dimensions and indexes selected by a developer, compares the summarized index values, cannot realize row-by-row verification among data tables, cannot support verification of more than ten indexes at one time, causes low data verification efficiency, and cannot guarantee data verification accuracy.

Disclosure of Invention

An object of the embodiments of the present application is to provide a data verification method, apparatus, computer device, and storage medium, so as to solve the technical problems that a data result verification function developed by a financial service platform of an existing financial and scientific enterprise only supports a developer to select several dimensions and indexes to aggregate and summarize by himself, and the summarized index values are compared, and cannot realize row-by-row verification between data tables, cannot support verification exceeding ten indexes at one time, resulting in low data verification efficiency, and cannot guarantee accuracy of data verification.

In order to solve the above technical problems, the embodiments of the present application provide a data verification method, which adopts the following technical schemes:

acquiring all line data meeting data verification conditions from a preset test data table, and acquiring first line numbers corresponding to the line data respectively;

determining appointed row data corresponding to the first row number from a production data table corresponding to the test data table;

respectively performing column splicing processing on each data to obtain first spliced data respectively corresponding to each data;

respectively performing column splicing processing on each specified row data to obtain second spliced data respectively corresponding to each specified row data;

Converting each piece of first spliced data based on a preset target hash algorithm to obtain first hash values respectively corresponding to each piece of first spliced data;

converting each second spliced data based on the target hash algorithm to obtain second hash values respectively corresponding to each second spliced data;

and carrying out corresponding data verification processing on all the first hash values and all the second hash values based on the first row numbers of the row data, and generating a data verification result between the test data table and the production data table.

Further, the step of performing column splicing processing on each row of data to obtain first spliced data corresponding to each row of data, specifically includes:

acquiring a second line number corresponding to the appointed line data; wherein the specified row data is any one of all the row data;

acquiring all primary key value information corresponding to the second row number from the test data table;

performing splicing processing on all the primary key value information according to a preset splicing sequence to obtain spliced primary key value information;

and taking the spliced primary key value information as the designated spliced data corresponding to the designated data.

Further, before the step of converting each piece of first spliced data based on the preset target hash algorithm to obtain first hash values corresponding to each piece of first spliced data, the method further includes:

obtaining a plurality of hash algorithms;

acquiring the length of data input in advance and the data output efficiency;

screening a first hash algorithm which meets the data length and meets the data processing requirement of the data output efficiency at the same time from all the hash algorithms;

judging whether the number of the first hash algorithms is larger than 1;

if yes, screening a second hash algorithm with the highest use frequency value from all the first hash algorithms;

and taking the second hash algorithm as the target hash algorithm.

Further, the step of generating a data verification result between the test data table and the production data table by performing corresponding data verification processing on all the first hash values and all the second hash values based on the first row number of each row of data specifically includes:

acquiring a first specified hash value; wherein the first specified hash value is any one of all the first hash values;

Acquiring a third row number corresponding to the first specified hash value;

determining a second designated hash value corresponding to the third row number from the second hash values;

performing data matching on the first specified hash value and the second specified hash value to obtain a corresponding specified data matching result;

after the corresponding data matching processing is completed for all the first hash values and all the second hash values, a plurality of corresponding data matching results are obtained;

and generating a data verification result between the test data table and the production data table based on all the data matching results.

Further, the step of generating a data verification result between the test data table and the production data table based on all the data matching results specifically includes:

analyzing all the data matching results, and judging whether the contents of all the data matching results pass through the matching;

if yes, generating a first data verification result between the test data table and the production data table; the content of the first data verification result is verification passing;

if not, generating a second data verification result between the test data table and the production data table; and the content of the second data verification result is that verification fails.

Further, after the step of analyzing all the data matching results and determining whether the content of all the data matching results is passing or not, the method further includes:

if the contents of all the data matching results are not matched and pass, screening the target data matching results with the contents which are not matched from all the data matching results;

acquiring a first target hash value and a second target hash value corresponding to the target data matching result;

acquiring a target row number corresponding to the first target hash value;

generating corresponding difference data based on the first target hash value, the second target hash value, and the target row number;

and storing the difference data.

Further, after the step of generating the corresponding difference data based on the first target hash value, the second target hash value, and the target line number, the method further includes:

acquiring communication information of a tester;

generating corresponding difference processing information based on the difference data;

and sending the difference processing information to the tester based on the communication information.

In order to solve the above technical problems, the embodiments of the present application further provide a data verification device, which adopts the following technical scheme:

The first acquisition module is used for acquiring all line data meeting the data verification conditions from a preset test data table and acquiring first line numbers corresponding to the line data respectively;

a first determining module, configured to determine specified row data corresponding to the first row number from a production data table corresponding to the test data table;

the first processing module is used for respectively performing column splicing processing on each line of data to obtain first spliced data respectively corresponding to each line of data;

the second processing module is used for respectively performing column splicing processing on the specified row data to obtain second spliced data respectively corresponding to the specified row data;

the first conversion module is used for carrying out conversion processing on each piece of first spliced data based on a preset target hash algorithm to obtain first hash values respectively corresponding to each piece of first spliced data;

the second conversion module is used for carrying out conversion processing on each piece of second spliced data based on the target hash algorithm to obtain second hash values respectively corresponding to each piece of second spliced data;

and the verification module is used for carrying out corresponding data verification processing on all the first hash values and all the second hash values based on the first row numbers of the row data, and generating a data verification result between the test data table and the production data table.

In order to solve the above technical problems, the embodiments of the present application further provide a computer device, which adopts the following technical schemes:

acquiring all line data meeting data verification conditions from a preset test data table, and acquiring first line numbers corresponding to the line data respectively;

determining appointed row data corresponding to the first row number from a production data table corresponding to the test data table;

respectively performing column splicing processing on each data to obtain first spliced data respectively corresponding to each data;

respectively performing column splicing processing on each specified row data to obtain second spliced data respectively corresponding to each specified row data;

converting each piece of first spliced data based on a preset target hash algorithm to obtain first hash values respectively corresponding to each piece of first spliced data;

converting each second spliced data based on the target hash algorithm to obtain second hash values respectively corresponding to each second spliced data;

and carrying out corresponding data verification processing on all the first hash values and all the second hash values based on the first row numbers of the row data, and generating a data verification result between the test data table and the production data table.

In order to solve the above technical problems, embodiments of the present application further provide a computer readable storage medium, which adopts the following technical solutions:

acquiring all line data meeting data verification conditions from a preset test data table, and acquiring first line numbers corresponding to the line data respectively;

determining appointed row data corresponding to the first row number from a production data table corresponding to the test data table;

respectively performing column splicing processing on each data to obtain first spliced data respectively corresponding to each data;

respectively performing column splicing processing on each specified row data to obtain second spliced data respectively corresponding to each specified row data;

converting each piece of first spliced data based on a preset target hash algorithm to obtain first hash values respectively corresponding to each piece of first spliced data;

converting each second spliced data based on the target hash algorithm to obtain second hash values respectively corresponding to each second spliced data;

and carrying out corresponding data verification processing on all the first hash values and all the second hash values based on the first row numbers of the row data, and generating a data verification result between the test data table and the production data table.

Compared with the prior art, the embodiment of the application has the following main beneficial effects:

firstly, acquiring all row data meeting data verification conditions from a preset test data table, and acquiring first row numbers corresponding to the row data respectively; then determining the appointed row data corresponding to the first row number from a production data table corresponding to the test data table; then respectively performing column splicing processing on each line of data to obtain first spliced data respectively corresponding to each line of data; respectively performing column splicing processing on each piece of appointed row data to obtain second spliced data respectively corresponding to each piece of appointed row data; performing conversion processing on each piece of first spliced data based on a preset target hash algorithm to obtain first hash values respectively corresponding to each piece of first spliced data; converting each second spliced data based on the target hash algorithm to obtain second hash values respectively corresponding to the second spliced data; and finally, based on the first row number of each row of data, carrying out corresponding data verification processing on all the first hash values and all the second hash values, and generating a data verification result between the test data table and the production data table. The method for verifying the data between the test data table and the production data table by utilizing the hash algorithm aims at converting the data meeting the data verification condition in the data table storing mass data into the hash value with fixed length of each row and then performing data comparison processing of low storage capacity by using the hash value, so that consistency verification of multi-row or progressive data on the data table can be realized, the processing efficiency of data verification between the test data table and the production data table is effectively improved, and the accuracy of the data verification result between the generated test data table and the production data table is ensured.

Drawings

For a clearer description of the solution in the present application, a brief description will be given below of the drawings that are needed in the description of the embodiments of the present application, it being obvious that the drawings in the following description are some embodiments of the present application, and that other drawings may be obtained from these drawings without inventive effort for a person of ordinary skill in the art.

FIG. 1 is an exemplary system architecture diagram in which the present application may be applied;

FIG. 2 is a flow chart of one embodiment of a data verification method according to the present application;

FIG. 3 is a schematic diagram of a structure of one embodiment of a data verification device according to the present application;

FIG. 4 is a schematic structural diagram of one embodiment of a computer device according to the present application.

Detailed Description

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs; the terminology used in the description of the applications herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application; the terms "comprising" and "having" and any variations thereof in the description and claims of the present application and in the description of the figures above are intended to cover non-exclusive inclusions. The terms first, second and the like in the description and in the claims or in the above-described figures, are used for distinguishing between different objects and not necessarily for describing a sequential or chronological order.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the present application. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.

In order to better understand the technical solutions of the present application, the following description will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings.

As shown in fig. 1, a system architecture 100 may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 is used as a medium to provide communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.

The user may interact with the server 105 via the network 104 using the terminal devices 101, 102, 103 to receive or send messages or the like. Various communication client applications, such as a web browser application, a shopping class application, a search class application, an instant messaging tool, a mailbox client, social platform software, etc., may be installed on the terminal devices 101, 102, 103.

The terminal devices 101, 102, 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smartphones, tablet computers, electronic book readers, MP3 players (Moving Picture Experts Group Audio Layer III, dynamic video expert compression standard audio plane 3), MP4 (Moving Picture Experts Group Audio Layer IV, dynamic video expert compression standard audio plane 4) players, laptop and desktop computers, and the like.

The server 105 may be a server providing various services, such as a background server providing support for pages displayed on the terminal devices 101, 102, 103.

It should be noted that, the data verification method provided in the embodiments of the present application is generally executed by a server/terminal device, and accordingly, the data verification device is generally disposed in the server/terminal device.

It should be understood that the number of terminal devices, networks and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers as desired.

With continued reference to FIG. 2, a flow chart of one embodiment of a data verification method according to the present application is shown. The order of the steps in the flowchart may be changed and some steps may be omitted according to various needs. The data verification method provided by the embodiment of the application can be applied to any scene needing to be subjected to table data verification, and can be applied to products of the scenes, such as table data verification in the field of financial insurance. The data verification method comprises the following steps:

Step S201, all row data meeting the data verification conditions are obtained from a preset test data table, and the first row numbers corresponding to the row data are obtained.

In this embodiment, the electronic device (for example, the server/terminal device shown in fig. 1) on which the data verification method operates may acquire all row data meeting the data verification condition in the test data table through a wired connection manner or a wireless connection manner. The execution subject of the data verification method may specifically be a financial service platform. It should be noted that the wireless connection may include, but is not limited to, 3G/4G/5G connection, wiFi connection, bluetooth connection, wiMAX connection, zigbee connection, UWB (ultra wideband) connection, and other now known or later developed wireless connection. The data accuracy and consistency are the premise and key indexes of the development of data teams of financial and scientific enterprises (such as insurance enterprises and banks), and the key index consistency is ensured to be an important link before the online and is also the key content of business attention by verifying the difference between the test data and the production data between the local test data table and the production data table. For example, in a business scenario of a financial insurance form data verification, the test data form may be a data form containing insurance data, where the insurance data may include transaction data, payment data, business data, and so on. The above-mentioned all line data meeting the data verification condition refers to comparing the test data table with the part data which needs to be verified and consistent in the production data table, that is, when the test data table is changed, other indexes which are not changed are not affected or are affected in the evaluation range. The line number corresponding to the line data can be obtained by carrying out corresponding line number inquiry on the line data in the test data table. In addition, the data verification processing is carried out on all the row data which are acquired from the test data table and meet the data verification conditions, and all the data contained in the test data table are not required to be verified, so that the processing workload of table data verification can be effectively reduced, and the processing efficiency of table data verification is further improved.

Step S202, determining the designated row data corresponding to the first row number from a production data table corresponding to the test data table.

In this embodiment, the production data table corresponding to the test data table may be queried by using the first line number to query the production data table for the specified line data corresponding to the first line number.

Step S203, performing column splicing processing on each row of data, to obtain first spliced data corresponding to each row of data.

In this embodiment, since the data table (including the test data table and the production data table) has a primary key uniqueness requirement, each row of data in the data table is unique, and the spliced data has uniqueness. The specific implementation process of performing column splicing processing on each row of data to obtain first spliced data corresponding to each row of data respectively will be described in further detail in the following specific embodiments, which are not described herein.

Step S204, respectively performing column splicing processing on each piece of specified line data to obtain second spliced data respectively corresponding to each piece of specified line data.

In this embodiment, the above-mentioned processing procedure of performing column splicing processing on each specified line data to obtain second spliced data corresponding to each specified line data may refer to the foregoing processing procedure of performing column splicing processing on each line data to obtain first spliced data corresponding to each line data, which is not described herein too much.

Step S205, performing conversion processing on each piece of first spliced data based on a preset target hash algorithm, to obtain first hash values corresponding to each piece of first spliced data respectively.

In this embodiment, the hash conversion may be performed on the first spliced data by using the target hash algorithm, so that the data outputs a hash value of a corresponding fixed length. The first hash value corresponding to the first spliced data can be obtained by acquiring a packaging function corresponding to the target hash algorithm and performing conversion processing on the first spliced data by using the packaging function. The determining process of the target hash algorithm will be described in further detail in the following specific embodiments, which will not be described herein.

Step S206, performing conversion processing on each second spliced data based on the target hash algorithm, to obtain second hash values respectively corresponding to each second spliced data.

In this embodiment, the above-mentioned converting process is performed on each second spliced data based on the target hash algorithm to obtain second hash values corresponding to each second spliced data, and the converting process may be performed on each first spliced data based on the preset target hash algorithm to obtain first hash values corresponding to each first spliced data, which is not described herein.

Step S207, performing corresponding data verification processing on all the first hash values and all the second hash values based on the first row number of each row data, and generating a data verification result between the test data table and the production data table.

In this embodiment, the foregoing data verification process is performed on all the first hash values and all the second hash values based on the first row number of each row data, so as to generate a specific implementation process of the data verification result between the test data table and the production data table, which will be described in further detail in the following specific embodiments, which will not be described herein. The test data table and the production data table can be connected in a table mode, the key words of the connection keys are hash values of each row, therefore, the hash values successfully associated represent that the row of data are consistent in test and production, and the hash values not associated represent that data differences exist, so that row-by-row verification is achieved. In addition, the number of data lines of which the hash value can be successfully matched is equivalent to the total number of data lines of the production table, and the data representing the verified test data table and the production table are identical; the number of unsuccessfully matched hash values represents the data variance, and the hash values can be re-matched for variance positioning by clipping the test data table and the production data table.

Firstly, acquiring all row data meeting data verification conditions from a preset test data table, and acquiring first row numbers corresponding to the row data respectively; then determining the appointed row data corresponding to the first row number from a production data table corresponding to the test data table; then respectively performing column splicing processing on each line of data to obtain first spliced data respectively corresponding to each line of data; respectively performing column splicing processing on each piece of appointed row data to obtain second spliced data respectively corresponding to each piece of appointed row data; performing conversion processing on each piece of first spliced data based on a preset target hash algorithm to obtain first hash values respectively corresponding to each piece of first spliced data; converting each second spliced data based on the target hash algorithm to obtain second hash values respectively corresponding to the second spliced data; and finally, based on the first row number of each row of data, carrying out corresponding data verification processing on all the first hash values and all the second hash values, and generating a data verification result between the test data table and the production data table. The method for verifying the data between the test data table and the production data table by utilizing the hash algorithm aims at converting the data meeting the data verification condition in the data table storing mass data into the hash value with fixed length of each row and then performing data comparison processing of low storage capacity by using the hash value, so that consistency verification of multi-row or progressive data on the data table can be realized, the processing efficiency of data verification between the test data table and the production data table is effectively improved, and the accuracy of the data verification result between the generated test data table and the production data table is ensured.

In some alternative implementations, step S203 includes the steps of:

and acquiring a second row number corresponding to the specified row data.

In this embodiment, the above specified line data is any one of all the line data. And the second row number corresponding to the designated row data can be obtained by carrying out corresponding row number inquiry on the designated row data in the test data table.

And acquiring all primary key value information corresponding to the second row number from the test data table.

In the present embodiment, the data in the test data table is data-stored in a key-value (primary key-primary key value information) manner. And carrying out primary key value inquiry on the test data table according to all primary keys corresponding to the second row number so as to acquire all primary key value information corresponding to the second row number.

And performing splicing processing on all the primary key value information according to a preset splicing sequence to obtain spliced primary key value information.

In this embodiment, the selection of the above-mentioned splicing order is not specifically limited, and the method may be set according to actual use requirements, and only the same splicing order of all the data to be checked corresponding to the test data table and the production data table needs to be ensured. For example, the splice order may be a left-to-right order. For example, all primary key value information corresponding to the primary keys of the second row number includes names respectively: zhang III, number: 2023123, performance: a, job level: and B, performing splicing processing on all the primary key value information according to the splicing sequence, wherein the spliced primary key value information can be obtained as follows: zhang san 2023123AB.

And taking the spliced primary key value information as the designated spliced data corresponding to the designated data.

The method comprises the steps of obtaining a second row number corresponding to the appointed row data; then, acquiring all primary key value information corresponding to the second row number from the test data table; then, all the primary key value information is spliced according to a preset splicing sequence, and spliced primary key value information is obtained; and subsequently, the spliced primary key value information is used as specified spliced data corresponding to the specified data. According to the method and the device, the corresponding primary key value information is acquired from the test data table according to the row number corresponding to the data, and then all the primary key value information is subjected to column splicing according to the preset splicing sequence, so that splicing data corresponding to each row of data are obtained rapidly, and the generation efficiency of the splicing data is improved.

In some optional implementations of this embodiment, before step S205, the electronic device may further perform the following steps:

a variety of hash algorithms are obtained.

In this embodiment, hash (Hash) is also called a Hash, and is a method of mapping data of an arbitrary length into data of a fixed length. A Hash Function (Hash Function) is an algorithm used to implement hashing that maps input data into a Hash Value (Hash Value) or a Hash Code (Hash Code), typically an integer (16-ary) of a fixed length (e.g., 32 bits, 64 bits, etc.). A Hash Value (Hash Value), also called a Hash Value, digest, or fingerprint, is a process of converting binary data of an arbitrary length into a unique Value of a fixed length by a Hash algorithm (Hash Function). Hash values are commonly used in the scenarios of integrity verification of data, password storage and comparison, data fragmentation and load balancing. The hash algorithm is an algorithm that converts an input message of arbitrary length into an output message of fixed length, and is generally used to implement a hash function. The hash algorithm may include a conventional hash algorithm including, for example, MD5, SHA-1, SHA-256, etc.

And acquiring the length of the data input in advance and the data output efficiency.

In this embodiment, the data length and the data output efficiency may be input by the user according to the actual data processing requirement.

And screening a first hash algorithm which meets the data length and simultaneously meets the data processing requirement of the data output efficiency from all the hash algorithms.

In this embodiment, the first hash algorithm that meets the data length and meets the data processing requirement of the data output efficiency can be screened from all the hash algorithms by acquiring the processable data lengths of the various hash algorithms and the corresponding data processing efficiencies, and by respectively performing data matching on the input data length and the data output efficiency with the processable data lengths of the various hash algorithms and the corresponding data processing efficiencies.

And judging whether the number of the first hash algorithms is larger than 1.

In this embodiment, the number of the first hash algorithms may be 1 or more than 1. If the number of the first hash algorithms is 1, the first hash algorithm is directly taken as a target hash algorithm.

If yes, screening a second hash algorithm with the highest use frequency value from all the first hash algorithms.

In this embodiment, the usage information of the first hash algorithm may be obtained, so as to query the usage frequency value of each first hash algorithm from the usage information.

And taking the second hash algorithm as the target hash algorithm.

The application obtains a plurality of hash algorithms; then acquiring the length of the data input in advance and the data output efficiency; then screening a first hash algorithm which meets the data length and simultaneously meets the data processing requirement of the data output efficiency from all the hash algorithms; subsequently judging whether the number of the first hash algorithms is larger than 1; if yes, screening a second hash algorithm with the highest use frequency value from all the first hash algorithms; and finally, taking the second hash algorithm as the target hash algorithm. According to the data length and the data output efficiency which are input in advance, the first hash algorithm which accords with the data length and the data processing requirement which accords with the data output efficiency is screened out from a plurality of hash algorithms, so that the obtained first hash algorithm can accord with corresponding business processing requirements, and the use experience of a user is improved. In addition, if the number of the first hash algorithms is greater than 1, the second hash algorithm with the highest frequency value is intelligently selected from all the first hash algorithms to serve as a target hash algorithm, and the target hash algorithm accords with the data length, accords with the data output efficiency and has the highest frequency of use, so that the accuracy and the intelligence of determining the target hash algorithm are effectively improved.

In some alternative implementations, step S206 includes the steps of:

a first specified hash value is obtained.

In this embodiment, the first specified hash value is any one of all the first hash values.

And acquiring a third row number corresponding to the first specified hash value.

In the present embodiment, the line number that matches the line data corresponding to the first specified hash value may be acquired from the test data table as the third line number described above.

And determining a second appointed hash value corresponding to the third row number from the second hash value.

In this embodiment, since the row number in the production data table has a correspondence with the corresponding row data, and there is also a correspondence between the spliced data of the row data and the hash value, and further there is also a correspondence between the row number and the hash value, it is possible to determine the second specified hash value corresponding to the third row number from the second hash value.

And carrying out data matching on the first specified hash value and the second specified hash value to obtain a corresponding specified data matching result.

In this embodiment, the data matching result may include a success of data matching or a failure of data matching.

After the corresponding data matching processing is completed for all the first hash values and all the second hash values, a plurality of corresponding data matching results are obtained;

in this embodiment, the data matching process performed between all the first hash values and all the second hash values is the same as the above process of performing data matching on the first specified hash values and the second specified hash values, and redundant description is omitted herein.

And generating a data verification result between the test data table and the production data table based on all the data matching results.

In this embodiment, the specific implementation process of generating the data verification result between the test data table and the production data table based on all the data matching results will be described in further detail in the following specific embodiments, which will not be described herein.

The method comprises the steps of obtaining a first appointed hash value and obtaining a third row number corresponding to the first appointed hash value; then determining a second designated hash value corresponding to the third row number from the second hash values; then, carrying out data matching on the first appointed hash value and the second appointed hash value to obtain a corresponding appointed data matching result; after the corresponding data matching processing is completed for all the first hash values and all the second hash values, a plurality of corresponding data matching results are obtained; and generating a data verification result between the test data table and the production data table based on all the data matching results. According to the data verification method and device, through the use of the first row numbers of the row data, the corresponding data verification processing can be rapidly and accurately carried out on all the first hash values and all the second hash values, so that the data verification result between the test data table and the production data table is generated, the processing efficiency of the data verification processing is improved, and the accuracy of the generated data verification result is guaranteed.

In some optional implementations, the generating a data check result between the test data table and the production data table based on all the data matching results includes the steps of:

and analyzing all the data matching results, and judging whether the contents of all the data matching results are matched and pass or not.

In this embodiment, the content of the data matching result includes whether the matching is passed or failed.

If yes, a first data verification result between the test data table and the production data table is generated.

In this embodiment, the content of the first data verification result is verification passing.

If not, generating a second data check result between the test data table and the production data table,

in this embodiment, the content of the second data verification result is that verification fails. In this embodiment.

According to the method, whether the contents of all the data matching results are matched or not is judged by analyzing all the data matching results; if yes, generating a first data verification result between the test data table and the production data table; if not, generating a second data verification result between the test data table and the production data table; and the content of the second data verification result is that verification fails. By analyzing all the data matching results, the data verification results between the test data table and the production data table can be automatically and accurately generated, and the accuracy of the generated data verification results is ensured. According to the data matching method and device, all the data matching results are automatically analyzed, so that the data checking results between the test data table and the production data table can be quickly and accurately generated, and the accuracy of the generated data checking results is guaranteed.

In some optional implementations of this embodiment, after the step of analyzing all the data matching results and determining whether the content of all the data matching results is passing or not, the electronic device may further execute the following steps:

and if the contents of all the data matching results are not matched and pass, screening the target data matching results with the contents which are not matched and pass from all the data matching results.

And acquiring a first target hash value and a second target hash value corresponding to the target data matching result.

And acquiring a target row number corresponding to the first target hash value.

Corresponding difference data is generated based on the first target hash value, the second target hash value, and the target row number.

In this embodiment, the first target hash value, the second target hash value and the target line number may be integrated to generate the corresponding difference data.

And storing the difference data.

In this embodiment, the storage manner of the difference data is not limited, and for example, blockchain storage, local database storage, cloud storage, and the like may be used.

If the content of all the data matching results is detected to be failed in matching, screening the target data matching results with failed content from all the data matching results; then, a first target hash value and a second target hash value corresponding to the target data matching result are obtained; then, a target row number corresponding to the first target hash value is acquired; generating corresponding difference data based on the first target hash value, the second target hash value and the target row number; and finally storing the difference data. After analyzing all the data matching results, if the content of all the data matching results is detected to be not the matching passing, the method and the device also intelligently screen the target data matching results with the content of the matching failing from all the data matching results, generate corresponding difference data according to the first target hash value, the second target hash value and the target row number corresponding to the target data matching results and store the corresponding difference data, ensure the safety of the generated difference data, and facilitate the subsequent transmission of the difference data to corresponding testers, so that the testers can carry out corresponding data adjustment processing on the test data table and the production data table according to the difference data, the test data table and the production data table meet the data consistency principle, the method and the device are beneficial to improving the working efficiency of the testers and the working experience of the testers.

In some optional implementations of this embodiment, after the step of generating the corresponding difference data based on the first target hash value, the second target hash value, and the target line number, the electronic device may further perform the steps of:

and acquiring communication information of the tester.

In this embodiment, the tester may be a business person responsible for testing the test data sheet. The communication information may include a mail address or a telephone number.

Generating a corresponding output based on the difference data

In this embodiment, the difference data may be filled into a preset information template to generate corresponding communication information. The information template is constructed according to the reminding requirement of the difference data of the actual data table, and the content of the information template is not particularly limited.

And sending the difference processing information to the tester based on the communication information.

In this embodiment, the difference processing information may be sent to a communication terminal corresponding to the tester according to the communication information.

The method and the device acquire the communication information of the testers; then generating corresponding difference processing information based on the difference data; and then, based on the communication information, sending the difference processing information to the tester. After the corresponding difference data is generated based on the first target hash value, the second target hash value and the target row number, corresponding difference processing information is generated intelligently based on the difference data, and then the difference information is sent to corresponding testers, so that the testers can carry out corresponding data adjustment processing on the test data table and the production data table according to the difference data, the test data table and the production data table can meet the data consistency principle, the work efficiency of the testers is improved, and the work experience of the testers is improved.

It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic, and should not limit the implementation process of the embodiment of the present invention.

It should be emphasized that, to further ensure the privacy and security of the data verification results, the data verification results may also be stored in a node of a blockchain.

The blockchain referred to in the application is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, consensus mechanism, encryption algorithm and the like. The Blockchain (Blockchain), which is essentially a decentralised database, is a string of data blocks that are generated by cryptographic means in association, each data block containing a batch of information of network transactions for verifying the validity of the information (anti-counterfeiting) and generating the next block. The blockchain may include a blockchain underlying platform, a platform product services layer, an application services layer, and the like.

The embodiment of the application can acquire and process the related data based on the artificial intelligence technology. Among these, artificial intelligence (Artificial Intelligence, AI) is the theory, method, technique and application system that uses a digital computer or a digital computer-controlled machine to simulate, extend and extend human intelligence, sense the environment, acquire knowledge and use knowledge to obtain optimal results.

Artificial intelligence infrastructure technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technologies, operation/interaction systems, mechatronics, and the like. The artificial intelligence software technology mainly comprises a computer vision technology, a robot technology, a biological recognition technology, a voice processing technology, a natural language processing technology, machine learning/deep learning and other directions.

Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by computer readable instructions stored in a computer readable storage medium that, when executed, may comprise the steps of the embodiments of the methods described above. The storage medium may be a nonvolatile storage medium such as a magnetic disk, an optical disk, a Read-Only Memory (ROM), or a random access Memory (Random Access Memory, RAM).

It should be understood that, although the steps in the flowcharts of the figures are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited in order and may be performed in other orders, unless explicitly stated herein. Moreover, at least some of the steps in the flowcharts of the figures may include a plurality of sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, the order of their execution not necessarily being sequential, but may be performed in turn or alternately with other steps or at least a portion of the other steps or stages.

With further reference to fig. 3, as an implementation of the method shown in fig. 2, the present application provides an embodiment of a data verification apparatus, where an embodiment of the apparatus corresponds to the embodiment of the method shown in fig. 2, and the apparatus may be specifically applied to various electronic devices.

As shown in fig. 3, the data verification apparatus 300 according to this embodiment includes: a first acquisition module 301, a first determination module 302, a first processing module 303, a second processing module 304, a first conversion module 305, a second conversion module 306, and a verification module 307. Wherein:

a first obtaining module 301, configured to obtain all row data that meets a data verification condition from a preset test data table, and obtain a first row number corresponding to each row data;

a first determining module 302, configured to determine, from a production data table corresponding to the test data table, specified row data corresponding to the first row number;

a first processing module 303, configured to perform column splicing processing on each line of data, to obtain first spliced data corresponding to each line of data;

a second processing module 304, configured to perform column splicing processing on each piece of specified row data, to obtain second spliced data corresponding to each piece of specified row data;

The first conversion module 305 is configured to perform conversion processing on each piece of first spliced data based on a preset target hash algorithm, so as to obtain first hash values corresponding to each piece of first spliced data respectively;

the second conversion module 306 is configured to perform conversion processing on each second spliced data based on the target hash algorithm, so as to obtain second hash values corresponding to each second spliced data respectively;

and a verification module 307, configured to perform corresponding data verification processing on all the first hash values and all the second hash values based on the first row number of each row data, and generate a data verification result between the test data table and the production data table.

In this embodiment, the operations performed by the modules or units respectively correspond to the steps of the data verification method in the foregoing embodiment one by one, which is not described herein again.

In some alternative implementations of the present embodiment, the first processing module 303 includes:

the first acquisition sub-module is used for acquiring a second row number corresponding to the designated row data; wherein the specified row data is any one of all the row data;

a second obtaining sub-module, configured to obtain all primary key value information corresponding to the second row number from the test data table;

The splicing sub-module is used for carrying out splicing treatment on all the primary key value information according to a preset splicing sequence to obtain spliced primary key value information;

and the first determining sub-module uses the spliced main key value information as specified spliced data corresponding to the specified data.

In this embodiment, the operations performed by the modules or units respectively correspond to the steps of the data verification method in the foregoing embodiment one by one, which is not described herein again.

In some optional implementations of this embodiment, the data verification apparatus further includes:

the second acquisition module is used for acquiring a plurality of hash algorithms;

the third acquisition module is used for acquiring the length of the data input in advance and the data output efficiency;

the first screening module is used for screening a first hash algorithm which meets the data length and meets the data processing requirement of the data output efficiency at the same time from all the hash algorithms;

the judging module is used for judging whether the number of the first hash algorithms is larger than 1;

the second screening module is used for screening a second hash algorithm with the highest use frequency value from all the first hash algorithms if the first hash algorithm is used;

and the second determining module is used for taking the second hash algorithm as the target hash algorithm.

In this embodiment, the operations performed by the modules or units respectively correspond to the steps of the data verification method in the foregoing embodiment one by one, which is not described herein again.

In some alternative implementations of the present embodiment, the verification module 307 includes:

a third obtaining sub-module, configured to obtain a first specified hash value; wherein the first specified hash value is any one of all the first hash values;

a fourth obtaining sub-module, configured to obtain a third row number corresponding to the first specified hash value;

a second determining submodule, configured to determine a second specified hash value corresponding to the third row number from the second hash value;

the matching sub-module is used for carrying out data matching on the first appointed hash value and the second appointed hash value to obtain a corresponding appointed data matching result;

the obtaining submodule is used for obtaining a plurality of corresponding data matching results after finishing corresponding data matching processing between all the first hash values and all the second hash values;

and the generation sub-module is used for generating a data verification result between the test data table and the production data table based on all the data matching results.

In this embodiment, the operations performed by the modules or units respectively correspond to the steps of the data verification method in the foregoing embodiment one by one, which is not described herein again.

In some optional implementations of the present embodiment, generating the sub-module includes:

the judging unit is used for analyzing all the data matching results and judging whether the contents of all the data matching results pass through the matching;

the first generation unit is used for generating a first data verification result between the test data table and the production data table if yes; the content of the first data verification result is verification passing;

a second generating unit, configured to generate a second data verification result between the test data table and the production data table if not; and the content of the second data verification result is that verification fails.

In this embodiment, the operations performed by the modules or units respectively correspond to the steps of the data verification method in the foregoing embodiment one by one, which is not described herein again.

In some optional implementations of this embodiment, the generating sub-module further includes:

the screening unit is used for screening target data matching results with failed matching from all the data matching results if the contents of all the data matching results are failed to match;

A first obtaining unit, configured to obtain a first target hash value and a second target hash value corresponding to the target data matching result;

a second obtaining unit, configured to obtain a target line number corresponding to the first target hash value;

a third generating unit configured to generate corresponding difference data based on the first target hash value, the second target hash value, and the target line number;

and the storage unit is used for storing the difference data.

In this embodiment, the operations performed by the modules or units respectively correspond to the steps of the data verification method in the foregoing embodiment one by one, which is not described herein again.

In some optional implementations of this embodiment, the generating sub-module further includes:

the third acquisition unit is used for acquiring communication information of the tester;

a fourth generation unit configured to generate corresponding difference processing information based on the difference data;

and the sending unit is used for sending the difference processing information to the tester based on the communication information.

In this embodiment, the operations performed by the modules or units respectively correspond to the steps of the data verification method in the foregoing embodiment one by one, which is not described herein again.

In order to solve the technical problems, the embodiment of the application also provides computer equipment. Referring specifically to fig. 4, fig. 4 is a basic structural block diagram of a computer device according to the present embodiment.

The computer device 4 comprises a memory 41, a processor 42, a network interface 43 communicatively connected to each other via a system bus. It should be noted that only computer device 4 having components 41-43 is shown in the figures, but it should be understood that not all of the illustrated components are required to be implemented and that more or fewer components may be implemented instead. It will be appreciated by those skilled in the art that the computer device herein is a device capable of automatically performing numerical calculations and/or information processing in accordance with predetermined or stored instructions, the hardware of which includes, but is not limited to, microprocessors, application specific integrated circuits (Application Specific Integrated Circuit, ASICs), programmable gate arrays (fields-Programmable Gate Array, FPGAs), digital processors (Digital Signal Processor, DSPs), embedded devices, etc.

The computer equipment can be a desktop computer, a notebook computer, a palm computer, a cloud server and other computing equipment. The computer equipment can perform man-machine interaction with a user through a keyboard, a mouse, a remote controller, a touch pad or voice control equipment and the like.

The memory 41 includes at least one type of readable storage medium including flash memory, hard disk, multimedia card, card memory (e.g., SD or DX memory, etc.), random Access Memory (RAM), static Random Access Memory (SRAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), programmable Read Only Memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the storage 41 may be an internal storage unit of the computer device 4, such as a hard disk or a memory of the computer device 4. In other embodiments, the memory 41 may also be an external storage device of the computer device 4, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash Card (Flash Card) or the like, which are provided on the computer device 4. Of course, the memory 41 may also comprise both an internal memory unit of the computer device 4 and an external memory device. In this embodiment, the memory 41 is typically used to store an operating system and various application software installed on the computer device 4, such as computer readable instructions of a data verification method. Further, the memory 41 may be used to temporarily store various types of data that have been output or are to be output.

The processor 42 may be a central processing unit (Central Processing Unit, CPU), controller, microcontroller, microprocessor, or other data processing chip in some embodiments. The processor 42 is typically used to control the overall operation of the computer device 4. In this embodiment, the processor 42 is configured to execute computer readable instructions stored in the memory 41 or process data, such as computer readable instructions for executing the data verification method.

The network interface 43 may comprise a wireless network interface or a wired network interface, which network interface 43 is typically used for establishing a communication connection between the computer device 4 and other electronic devices.

Compared with the prior art, the embodiment of the application has the following main beneficial effects:

according to the embodiment of the application, the hash algorithm is utilized to carry out data verification between the test data table and the production data table, the purpose is to convert data meeting the data verification condition in the data table storing mass data into hash values with fixed lengths of each row, and then the hash values are used for carrying out data comparison processing with low storage capacity, so that consistency verification of multi-row or progressive data on the data table can be realized, the processing efficiency of data verification between the test data table and the production data table is effectively improved, and the accuracy of a data verification result between the generated test data table and the production data table is ensured.

The present application also provides another embodiment, namely, a computer-readable storage medium storing computer-readable instructions executable by at least one processor to cause the at least one processor to perform the steps of the data verification method as described above.

Compared with the prior art, the embodiment of the application has the following main beneficial effects:

according to the embodiment of the application, the hash algorithm is utilized to carry out data verification between the test data table and the production data table, the purpose is to convert data meeting the data verification condition in the data table storing mass data into hash values with fixed lengths of each row, and then the hash values are used for carrying out data comparison processing with low storage capacity, so that consistency verification of multi-row or progressive data on the data table can be realized, the processing efficiency of data verification between the test data table and the production data table is effectively improved, and the accuracy of a data verification result between the generated test data table and the production data table is ensured.

From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk), comprising several instructions for causing a terminal device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the method described in the embodiments of the present application.

It is apparent that the embodiments described above are only some embodiments of the present application, but not all embodiments, the preferred embodiments of the present application are given in the drawings, but not limiting the patent scope of the present application. This application may be embodied in many different forms, but rather, embodiments are provided in order to provide a more thorough understanding of the present disclosure. Although the present application has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that modifications may be made to the embodiments described in the foregoing, or equivalents may be substituted for elements thereof. All equivalent structures made by the specification and the drawings of the application are directly or indirectly applied to other related technical fields, and are also within the protection scope of the application.

Claims (10)

1. A data verification method, comprising the steps of:

acquiring all line data meeting data verification conditions from a preset test data table, and acquiring first line numbers corresponding to the line data respectively;

determining appointed row data corresponding to the first row number from a production data table corresponding to the test data table;

Respectively performing column splicing processing on each data to obtain first spliced data respectively corresponding to each data;

respectively performing column splicing processing on each specified row data to obtain second spliced data respectively corresponding to each specified row data;

converting each piece of first spliced data based on a preset target hash algorithm to obtain first hash values respectively corresponding to each piece of first spliced data;

converting each second spliced data based on the target hash algorithm to obtain second hash values respectively corresponding to each second spliced data;

and carrying out corresponding data verification processing on all the first hash values and all the second hash values based on the first row numbers of the row data, and generating a data verification result between the test data table and the production data table.

2. The data verification method according to claim 1, wherein the step of performing column splicing processing on each of the data to obtain first spliced data corresponding to each of the data, respectively, specifically comprises:

acquiring a second line number corresponding to the appointed line data; wherein the specified row data is any one of all the row data;

Acquiring all primary key value information corresponding to the second row number from the test data table;

performing splicing processing on all the primary key value information according to a preset splicing sequence to obtain spliced primary key value information;

and taking the spliced primary key value information as the designated spliced data corresponding to the designated data.

3. The data verification method according to claim 1, further comprising, before the step of converting each of the first spliced data based on the preset target hash algorithm to obtain a first hash value corresponding to each of the first spliced data, the step of:

obtaining a plurality of hash algorithms;

acquiring the length of data input in advance and the data output efficiency;

screening a first hash algorithm which meets the data length and meets the data processing requirement of the data output efficiency at the same time from all the hash algorithms;

judging whether the number of the first hash algorithms is larger than 1;

if yes, screening a second hash algorithm with the highest use frequency value from all the first hash algorithms;

and taking the second hash algorithm as the target hash algorithm.

4. The data verification method according to claim 1, wherein the step of performing data verification processing corresponding to all the first hash values and all the second hash values based on the first row number of each row data to generate a data verification result between the test data table and the production data table specifically includes:

Acquiring a first specified hash value; wherein the first specified hash value is any one of all the first hash values;

acquiring a third row number corresponding to the first specified hash value;

determining a second designated hash value corresponding to the third row number from the second hash values;

performing data matching on the first specified hash value and the second specified hash value to obtain a corresponding specified data matching result;

after the corresponding data matching processing is completed for all the first hash values and all the second hash values, a plurality of corresponding data matching results are obtained;

and generating a data verification result between the test data table and the production data table based on all the data matching results.

5. The data verification method according to claim 4, wherein the step of generating the data verification result between the test data table and the production data table based on all the data matching results, specifically comprises:

analyzing all the data matching results, and judging whether the contents of all the data matching results pass through the matching;

If yes, generating a first data verification result between the test data table and the production data table; the content of the first data verification result is verification passing;

if not, generating a second data verification result between the test data table and the production data table; and the content of the second data verification result is that verification fails.

6. The data verification method according to claim 1, further comprising, after the step of analyzing all the data matching results to determine whether contents of all the data matching results are matched, the step of:

if the contents of all the data matching results are not matched and pass, screening the target data matching results with the contents which are not matched from all the data matching results;

acquiring a first target hash value and a second target hash value corresponding to the target data matching result;

acquiring a target row number corresponding to the first target hash value;

generating corresponding difference data based on the first target hash value, the second target hash value, and the target row number;

and storing the difference data.

7. The data verification method according to claim 6, further comprising, after the step of generating the corresponding difference data based on the first target hash value, the second target hash value, and the target line number:

acquiring communication information of a tester;

generating corresponding difference processing information based on the difference data;

and sending the difference processing information to the tester based on the communication information.

8. A data verification apparatus, comprising:

the first acquisition module is used for acquiring all line data meeting the data verification conditions from a preset test data table and acquiring first line numbers corresponding to the line data respectively;

a first determining module, configured to determine specified row data corresponding to the first row number from a production data table corresponding to the test data table;

the first processing module is used for respectively performing column splicing processing on each line of data to obtain first spliced data respectively corresponding to each line of data;

the second processing module is used for respectively performing column splicing processing on the specified row data to obtain second spliced data respectively corresponding to the specified row data;

The first conversion module is used for carrying out conversion processing on each piece of first spliced data based on a preset target hash algorithm to obtain first hash values respectively corresponding to each piece of first spliced data;

the second conversion module is used for carrying out conversion processing on each piece of second spliced data based on the target hash algorithm to obtain second hash values respectively corresponding to each piece of second spliced data;

and the verification module is used for carrying out corresponding data verification processing on all the first hash values and all the second hash values based on the first row numbers of the row data, and generating a data verification result between the test data table and the production data table.

9. A computer device comprising a memory having stored therein computer readable instructions which when executed by a processor implement the steps of the data verification method of any one of claims 1 to 7.

10. A computer readable storage medium having stored thereon computer readable instructions which when executed by a processor implement the steps of the data verification method according to any of claims 1 to 7.