CN112965981A

CN112965981A - Data checking method and device, computer equipment and storage medium

Info

Publication number: CN112965981A
Application number: CN202110276166.6A
Authority: CN
Inventors: 刘泽平; 时欢
Original assignee: Ping An Property and Casualty Insurance Company of China Ltd
Current assignee: Ping An Property and Casualty Insurance Company of China Ltd
Priority date: 2021-03-15
Filing date: 2021-03-15
Publication date: 2021-06-15
Anticipated expiration: 2041-03-15
Also published as: CN112965981B

Abstract

The application relates to the field of data processing, and provides a data checking method, a device, computer equipment and a storage medium, wherein the method comprises the following steps: acquiring current time and a preset data checking time period; judging whether the current time reaches the initial endpoint time of the data checking time period; if so, acquiring first list data of the first service system and second list data of the second service system; performing data statistics processing on the first list data based on a preset service data statistical rule to obtain first service statistical data; and performing data statistics processing on the second list data to obtain second service statistical data; and performing data checking processing on the first service statistical data and the second service statistical data based on a preset data checking template to generate a data checking result. The method and the device can improve the data checking rate and the accuracy of the data checking result. The method and the device can also be applied to the field of block chains, and the data such as the data checking result can be stored on the block chains.

Description

Data checking method and device, computer equipment and storage medium

Technical Field

The present application relates to the field of data processing technologies, and in particular, to a data checking method, apparatus, computer device, and storage medium.

Background

Because a supervision department needs to supervise and count the data of the agricultural insurance claim settlement system, and the claim settlement system and the system credit system need to perform timed data check and verification on the summarized data of the claim settlement system list and the summarized data of the system credit system list for the purpose of accurate and consistent data so as to check whether data difference exists in the summarized data of the two lists. The existing data checking method for the list data is that a claim settling person and a credit managing person simultaneously acquire summary list data, and then both sides perform manual data checking together. However, when the number of the list data to be checked is large, the manual data checking method needs to occupy a large amount of human resources and spend a large amount of time, and the efficiency of data checking is low, the error of the checked data is large, the error rate is high, and the accuracy of the generated data checking result is affected.

Disclosure of Invention

The application mainly aims to provide a data checking method, a data checking device, computer equipment and a storage medium, and aims to solve the technical problems that the existing data checking method for list data needs to occupy a large amount of human resources and spend a large amount of time, the data checking efficiency is low, the error of checked data is large, and the error rate is high.

The application provides a data checking method, which comprises the following steps:

acquiring current time and acquiring a preset data checking time period;

judging whether the current time reaches the starting endpoint time of the data checking time period, wherein the data checking time period is a time period formed by a time interval contained by the starting endpoint time and the ending endpoint time;

if the current time reaches the initial end point time of the data checking time period, acquiring first list data of a first service system and acquiring second list data of a second service system;

performing data statistics processing on the first list data based on a preset service data statistics rule to obtain corresponding first service statistics data, wherein the first service statistics data comprise a first service data field and first service data information corresponding to the first service data field; and the number of the first and second groups,

performing data statistics on the second list data to obtain corresponding second service statistical data, wherein the second service statistical data comprise a second service data field and second service data information corresponding to the second service data field;

and performing data checking processing on the first service statistical data and the second service statistical data based on a preset data checking template to generate a corresponding data checking result.

Optionally, the step of performing data matching processing on the first service statistical data and the second service statistical data based on a preset data matching template to generate a corresponding data matching result includes:

filling the first service data field into the data checking template;

based on the corresponding relation between the first service data field and the first service data information, filling the first service data information to a first corresponding position in the data checking template;

judging whether the second service data fields all contain appointed service data fields which are respectively the same as the first service data fields;

if the second service data field comprises the designated service data field which is respectively the same as each first service data field, judging whether other service data fields except the designated service data field exist in the second service data field;

if the other service data fields do not exist in the second service data field, screening out appointed service data information corresponding to the appointed service data field from the second service data information;

based on the corresponding relation between the designated service data field and the first service data field, filling the designated service data information to a second corresponding position in the data checking template;

checking the first service data information contained in each first service data field in the data checking template with the appointed service data information one by one to judge whether the two data information are the same;

if the two pieces of data information contained in each first service data field are the same, generating a first checking result of successful checking;

if the two pieces of data information contained in each first service data field are not the same, generating a second checking result of the checking failure;

and acquiring a target service data field with the difference between the first service data information and the specified service data information, and adding an abnormal mark to the target service data field.

Optionally, after the step of obtaining a target service data field in which the first service data information is different from the specified service data information and adding an exception flag to the target service data field, the method includes:

acquiring target service data information corresponding to the target service data field;

generating corresponding first abnormal information based on the target service data field and the target service data information;

acquiring preset mail login information and acquiring a specified mail address;

logging in to a corresponding mail server based on the mail login information;

and sending the first abnormal information to the specified mail address through the mail server.

Optionally, after the step of determining whether each of the second service data fields includes a designated service data field that is the same as each of the first service data fields, the method includes:

if the second service data field does not contain the designated service data field which is the same as each first service data field, screening out a specific service data field from the first service data field, wherein the second service data field does not contain the specific service data field;

searching specific service data information corresponding to the specific service data field from the first service data information;

generating corresponding second abnormal information based on the specific service data field and the specific service data information;

and sending the second abnormal information to the specified mail address through the mail server.

Optionally, after the step of determining whether there are other service data fields except for the specified service data field in the second service data field, the method includes:

if the second service data field has the other service data field, finding out other service data information corresponding to the other service data field from the second service data information;

generating corresponding third anomaly information based on the other service data fields and the other service data information;

and sending the third exception information to the specified mail address through the mail server.

Optionally, before the step of acquiring the preset data checking time period, the method includes:

acquiring the resource consumption of each appointed time period in each day in a first preset time period, wherein the appointed time period is a time period comprising a preset time length;

performing statistical analysis on the first preset time period, the specified time period and the resource consumption to generate a corresponding resource consumption statistical table;

screening out first time periods with the resource consumption smaller than a preset resource consumption threshold value from all the specified time periods in each day in the first preset time period respectively based on the resource consumption statistical table;

screening out a second time period with the largest occurrence number from all the first time periods;

and taking the second time period as the data checking time period.

dividing a time period of one day into a plurality of unit time periods based on a preset time division threshold;

processing the recorded data based on pre-stored historical data, and counting the total data processing amount of each unit time period in a second preset time period;

screening out a first data processing total amount smaller than a preset data processing amount threshold value from all the data processing total amounts;

sequencing all the first data processing total quantities according to the sequence of the numerical values of the first data processing total quantities from small to large to obtain corresponding sequencing results;

sequentially acquiring a specified number of second data processing total amounts from a first data processing total amount ranked at the head in the sorting result;

acquiring a specified unit time period corresponding to the second data processing total amount from all the unit time periods;

the specified unit time period is taken as the data collation time period.

The present application also provides a data collation apparatus, including:

the first acquisition module is used for acquiring the current time and acquiring a preset data checking time period;

the judging module is used for judging whether the current time reaches the starting endpoint time of the data checking time period, wherein the data checking time period is a time period formed by a time interval contained by the starting endpoint time and the ending endpoint time;

a second obtaining module, configured to obtain first list data of a first service system and obtain second list data of a second service system if the current time reaches a starting endpoint time of the data checking time period;

the first processing module is used for performing data statistics processing on the first list data based on a preset service data statistics rule to obtain corresponding first service statistics data, wherein the first service statistics data comprise a first service data field and first service data information corresponding to the first service data field; and the number of the first and second groups,

the second processing module is configured to perform data statistics on the second list data to obtain corresponding second service statistical data, where the second service statistical data includes a second service data field and second service data information corresponding to the second service data field;

and the checking module is used for performing data checking processing on the first service statistical data and the second service statistical data based on a preset data checking template to generate a corresponding data checking result.

The present application further provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

The present application also provides a computer-readable storage medium having stored thereon a computer program which, when being executed by a processor, carries out the steps of the above-mentioned method.

The data checking method, the data checking device, the computer equipment and the storage medium have the following beneficial effects:

according to the data checking method, the data checking device, the computer equipment and the storage medium, when the current time reaches the starting endpoint time of the preset data checking time period, the first list data and the second list data can be automatically acquired, the first list data and the second list data are converted into corresponding business statistical data, then data checking processing is carried out on the first business statistical data and the second business statistical data based on a preset data checking template, and then the corresponding data checking result is generated. The whole data checking process is carried out automatically, manual participation is not needed, the data checking speed is high, and the accuracy is high, so that a large amount of human resources and time can be saved, the data error of checking can be reduced, the error rate is reduced, and the accuracy of the generated data checking result is effectively improved.

Drawings

FIG. 1 is a flow chart illustrating a data verification method according to an embodiment of the present application;

FIG. 2 is a schematic structural diagram of a data collation apparatus according to an embodiment of the present application;

fig. 3 is a schematic structural diagram of a computer device according to an embodiment of the present application.

The implementation, functional features and advantages of the objectives of the present application will be further explained with reference to the accompanying drawings.

Detailed Description

It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.

It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.

Referring to fig. 1, a data verification method according to an embodiment of the present application includes:

s1: acquiring current time and acquiring a preset data checking time period;

s2: judging whether the current time reaches the starting endpoint time of the data checking time period, wherein the data checking time period is a time period formed by a time interval contained by the starting endpoint time and the ending endpoint time;

s3: if the current time reaches the initial end point time of the data checking time period, acquiring first list data of a first service system and acquiring second list data of a second service system;

s4: performing data statistics processing on the first list data based on a preset service data statistics rule to obtain corresponding first service statistics data, wherein the first service statistics data comprise a first service data field and first service data information corresponding to the first service data field; and the number of the first and second groups,

s5: performing data statistics on the second list data to obtain corresponding second service statistical data, wherein the second service statistical data comprise a second service data field and second service data information corresponding to the second service data field;

s6: and performing data checking processing on the first service statistical data and the second service statistical data based on a preset data checking template to generate a corresponding data checking result.

As described in the above steps S1 to S6, the execution subject of the embodiment of the method is a data collation apparatus. In practical applications, the data checking device may be implemented by a virtual device, such as a software code, or by an entity device in which a relevant execution code is written or integrated, and may perform human-computer interaction with a user through a keyboard, a mouse, a remote controller, a touch panel, or a voice control device. The data checking device in the embodiment can effectively improve the data checking rate and the accuracy of the generated data checking result. Specifically, the current time is acquired first, and a preset data collation time period is acquired. The generation method of the data check time period is not particularly limited, and the data check time period may be generated by a business idle time period generated by analyzing system operation data of the device. For example, the historical resource consumption data of the data checking device may be analyzed and statistically processed, and then the idle time period of the device may be determined according to the obtained analysis result to be used as the data checking time period. Or it is also possible to intelligently determine a traffic idle period of the device to be used as the data collation period based on the analysis result by analyzing the total amount of data processing for each unit period within a preset time period, and so on. And then judging whether the current time reaches the starting endpoint time of the data checking time period, wherein the data checking time period is a time period formed by a time interval contained by the starting endpoint time and the ending endpoint time. For example, if the data collation period is 2: 00-3: 00, then the corresponding start endpoint time is 2: 00, end endpoint time 3: 00. and if the current time reaches the starting end point time of the data checking time period, acquiring first list data of a first service system and acquiring second list data of a second service system. The data acquisition task for acquiring the first list data and the second list data can be preset, and the data acquisition task comprises a first data acquisition address of the first list data and a second data acquisition address of the second list data. After the current time reaches the start endpoint time, the data acquisition task is started to acquire the first list data and the second list data from the business system. Specifically, the first list data may be obtained by sending a data obtaining request to the first data obtaining address, and the second list data may be obtained by sending a data obtaining request to the second data obtaining address. In addition, the first service system may be a claim settlement system, the first list data may be summary data of a claim settlement system list, the second service system may be a credit settlement system, and the second list data may be summary data of a credit settlement system list. The list data may be the list data in the last designated time period adjacent to the current time, and the designated time period is not limited, and may be set according to actual requirements, for example, may be set for one month. Then, performing data statistics processing on the first list data based on a preset service data statistics rule to obtain corresponding first service statistics data, wherein the first service statistics data comprises a first service data field and first service data information corresponding to the first service data field; and performing data statistics on the second list data to obtain corresponding second service statistical data, wherein the second service statistical data comprises a second service data field and second service data information corresponding to the second service data field. The service data statistical rule is rule information for performing data statistics on the list data, and specific contents of the service statistical rule are not limited, and may be set according to actual requirements, for example, the calculation may include accumulation of money amounts, calculation of money amount difference, and the like. In addition, specific fields included in the service data field are not limited, and may be set according to actual requirements, and may include, for example: the system comprises a case number, a number of claims, a total amount of set up cases, a total amount of settlement cases, a loss amount, a killing amount, a disaster area, an area of failure, a number of households in danger, a common protection position and a common protection share. And finally, performing data checking processing on the first service statistical data and the second service statistical data based on a preset data checking template to generate a corresponding data checking result. The data checking method comprises the steps of respectively filling first service statistical data and second service statistical data to corresponding positions of a data checking template, and checking the first service statistical data and the second service statistical data one by one, so that data checking can be rapidly and intelligently completed, and corresponding data checking results can be obtained. In this embodiment, when the current time reaches the starting endpoint time of the preset data checking time period, the first list data and the second list data are automatically acquired, the first list data and the second list data are converted into corresponding service statistical data, and then data checking processing is performed on the first service statistical data and the second service statistical data based on a preset data checking template, so as to generate a corresponding data checking result. The whole data checking process is carried out automatically, manual participation is not needed, the data checking speed is high, and the accuracy is high, so that a large amount of human resources and time can be saved, the data error of checking can be reduced, the error rate is reduced, and the accuracy of the generated data checking result is effectively improved.

Further, in an embodiment of the present application, the step S6 includes:

s600: filling the first service data field into the data checking template;

s601: based on the corresponding relation between the first service data field and the first service data information, filling the first service data information to a first corresponding position in the data checking template;

s602: judging whether the second service data fields all contain appointed service data fields which are respectively the same as the first service data fields;

s603: if the second service data field comprises the designated service data field which is respectively the same as each first service data field, judging whether other service data fields except the designated service data field exist in the second service data field;

s604: if the other service data fields do not exist in the second service data field, screening out appointed service data information corresponding to the appointed service data field from the second service data information;

s605: based on the corresponding relation between the designated service data field and the first service data field, filling the designated service data information to a second corresponding position in the data checking template;

s606: checking the first service data information contained in each first service data field in the data checking template with the appointed service data information one by one to judge whether the two data information are the same;

s607: if the two pieces of data information contained in each first service data field are the same, generating a first checking result of successful checking;

s608: if the two pieces of data information contained in each first service data field are not the same, generating a second checking result of the checking failure;

s609: and acquiring a target service data field with the difference between the first service data information and the specified service data information, and adding an abnormal mark to the target service data field.

As described in the foregoing steps S600 to S609, the step of performing data matching processing on the first service statistical data and the second service statistical data based on the preset data matching template to generate a corresponding data matching result may specifically include: first, the first service data field is filled into the data checking template. The data checking template may be an Excel table containing no data. And then, based on the corresponding relation between the first service data field and the first service data information, filling the first service data information to a first corresponding position in the data checking template. And judging whether the second service data fields all contain the appointed service data fields which are respectively the same as the first service data fields. If the second service data field contains the designated service data field which is respectively the same as each first service data field, further judging whether other service data fields except the designated service data field exist in the second service data field. And if the other service data fields do not exist in the second service data field, screening out the appointed service data information corresponding to the appointed service data field from the second service data information. And then filling the designated service data information to a second corresponding position in the data checking template based on the corresponding relation between the designated service data field and the first service data field. The data checking method comprises the steps of filling a first service data field and corresponding first service data information into a data checking template, and filling appointed service data information corresponding to the appointed service data field into the data checking template based on the corresponding relation between the appointed service data field and the first service data field, so that each first service data field comprises one piece of data information corresponding to the first service data field in first service statistical data and one piece of data information corresponding to the first service data field in second service statistical data. And subsequently, the first service data information and the specified service data information contained in each first service data field in the data checking template are checked one by one to judge whether the two data information are the same. And if the two data information contained in each first service data field are the same, generating a first checking result with successful checking. And if the two data information contained in each first service data field are not the same, generating a second checking result of the checking failure. And after the second check result is obtained, acquiring a target service data field with the difference between the first service data information and the specified service data information, and adding an abnormal mark to the target service data field. The abnormal mark is not particularly limited, and may be, for example, a color mark, a character mark, or other types of mark information. In this embodiment, the first service statistical data and the second service statistical data are respectively filled in corresponding positions of the data checking template, and then the first service statistical data and the second service statistical data are checked one by one, so that the data checking process is rapidly and intelligently completed, and a corresponding data checking result is obtained. The whole data checking process is carried out automatically, manual participation is not needed, the data checking speed is high, and the accuracy is high, so that a large amount of human resources and time can be saved, the data error of checking can be reduced, the error rate is reduced, and the accuracy of the generated data checking result is effectively improved.

Further, in an embodiment of the present application, after the step S609, the method includes:

s6090: acquiring target service data information corresponding to the target service data field;

s6091: generating corresponding first abnormal information based on the target service data field and the target service data information;

s6092: acquiring preset mail login information and acquiring a specified mail address;

s6093: logging in to a corresponding mail server based on the mail login information;

s6094: and sending the first abnormal information to the specified mail address through the mail server.

As described in steps S6090 to S6094, after the step of obtaining the target service data field where the first service data information and the specified service data information are different and adding the exception flag to the target service data field, a process of generating and sending out exception information corresponding to the target service data field may be further included. Specifically, first, target service data information corresponding to the target service data field is obtained. The target service data information comprises first service data information and appointed service data information corresponding to the target service data field. And then generating corresponding first abnormal information based on the target service data field and the target service data information. The first exception information at least includes the target service data field and the target service data information, and the first exception information may be generated by filling the target service data field and the target service data information into a preset exception information template. In addition, the abnormal information template is not particularly limited, and may be, for example, a short message template set in advance according to a use requirement. And then acquiring preset mail login information and acquiring a specified mail address. After the mail registration information is obtained, the corresponding mail server is registered based on the mail registration information. And finally, sending the first abnormal information to the specified mail address through the mail server. In this embodiment, the target service data information corresponding to the target service data field is acquired and the corresponding first abnormal information is generated, and then the mail server is used to send the first abnormal information to the specified mail address, so that the specified user corresponding to the specified mail address can know the service data field with data abnormality and the corresponding service data information in the data checking process in time through the first abnormal information, and further follow-up manual checking process can be performed on the service data field with data abnormality in time.

Further, in an embodiment of the present application, after the step S602, the method includes:

s6020: if the second service data field does not contain the designated service data field which is the same as each first service data field, screening out a specific service data field from the first service data field, wherein the second service data field does not contain the specific service data field;

s6021: searching specific service data information corresponding to the specific service data field from the first service data information;

s6022: generating corresponding second abnormal information based on the specific service data field and the specific service data information;

s6023: and sending the second abnormal information to the specified mail address through the mail server.

As described in the above steps S6020 to S6023, there may be a case where the first service data field contains more field data than the second service data field, so that there is a data difference between the first service data information and the second service data information. After the step of determining whether the second service data field includes the designated service data field that is the same as each of the first service data fields, a process of generating and sending abnormal information that the second service data field does not include the specific service data field in the first service data field may be further included. Specifically, if the second service data field does not include the designated service data field that is the same as each of the first service data fields, a specific service data field is screened from the first service data field, where the second service data field does not include the specific service data field. And then specific service data information corresponding to the specific service data field is searched from the first service data information. And then generating corresponding second abnormal information based on the specific service data field and the specific service data information. The second exception information at least includes the specific service data field and the specific service data information, and the second exception information may be generated by filling the specific service data field and the specific service data information into a preset exception information template. And finally, sending the second abnormal information to the specified mail address through the mail server. In the embodiment, a specific service data field is screened from a first service data field and corresponding second abnormal information is generated, and then the mail server is used to send the second abnormal information to the specified mail address, so that the specified user corresponding to the specified mail address can know the service data field with data abnormality and the corresponding service data information in the data checking process in time through the second abnormal information, and further manual checking processing on the service data field with data abnormality can be adopted in time in the follow-up process.

Further, in an embodiment of the present application, after the step S603, the method includes:

s6030: if the second service data field has the other service data field, finding out other service data information corresponding to the other service data field from the second service data information;

s6031: generating corresponding third anomaly information based on the other service data fields and the other service data information;

s6032: and sending the third exception information to the specified mail address through the mail server.

As described in the above steps S6030 to S6032, there may be a case where the second service data field contains more field data than the first service data field, so that there is a data difference between the second service data information and the first service data information. After the step of determining whether there are other service data fields except the specified service data field in the second service data field, generating and sending abnormal information corresponding to the other service data fields except the first service data field in the second service data field. Specifically, if the other service data field exists in the second service data field, the other service data information corresponding to the other service data field is found from the second service data information. And generating corresponding third anomaly information based on the other service data fields and the other service data information. The third anomaly information at least includes the other service data field and the other service data information, and the third anomaly information can be generated by filling the other service data field and the other service data information into a preset anomaly information template. And finally, the third exception information is sent to the specified mail address through the mail server. In this embodiment, other service data fields except the specified service data field in the second service data field are obtained and corresponding third exception information is generated, and then the mail server is used to send the third exception information to the specified mail address, so that the specified user corresponding to the specified mail address can know the service data field with data exception and the corresponding service data information in the data checking process in time through the third exception information, and then manual checking process can be performed on the service data field with data exception in time in the following process.

Further, in an embodiment of the present application, before the step S1, the method includes:

s100: acquiring the resource consumption of each appointed time period in each day in a first preset time period, wherein the appointed time period is a time period comprising a preset time length;

s101: performing statistical analysis on the first preset time period, the specified time period and the resource consumption to generate a corresponding resource consumption statistical table;

s102: screening out first time periods with the resource consumption smaller than a preset resource consumption threshold value from all the specified time periods in each day in the first preset time period respectively based on the resource consumption statistical table;

s103: screening out a second time period with the largest occurrence number from all the first time periods;

s104: and taking the second time period as the data checking time period.

As described in steps S100 to S104, before the step of acquiring the preset data verification time period, a generation step of generating the data verification time period may be further included. Specifically, the resource consumption of each designated time period in each day in a first preset time period is first obtained, where the designated time period is a time period including a preset time length, and the preset time length may be set according to an actual requirement, for example, 1 hour may be used as the preset time length. In addition, the first preset time period is not particularly limited, and may be set according to actual requirements. For example, the first preset time period may be the last week adjacent to the current time. And then carrying out statistical analysis on the first preset time period, the specified time period and the resource consumption to generate a corresponding resource consumption statistical table. The generating process of the resource consumption statistical table may include: filling a specified time period to a row header in a preset table template in a descending order, dividing a first preset time period by taking each day as a unit, filling the first preset time period to a list header in the table template in a descending order, and filling resource consumption amounts respectively corresponding to the row header and the list header into cells of the table template in a one-to-one correspondence manner to generate the resource consumption statistical table. And then screening out first time periods with the resource consumption smaller than a preset resource consumption threshold value from all the specified time periods in each day in the first preset time period respectively based on the resource consumption statistical table. The resource consumption threshold is not particularly limited, and may be set according to actual requirements, for example, may be set to 5, and if the resource consumption of the device is less than the resource consumption threshold, it indicates that the device is currently in a service idle state. And screening out a second time period with the largest occurrence number from all the first time periods. The second time period with the largest occurrence number in all the first time periods indicates that the second time period is the most common time period corresponding to the resource consumption amount of the device being smaller than the resource consumption threshold in the first preset time period, that is, the device is usually in a service idle state in the second time period. And finally, taking the second time period as the data checking time period. According to the embodiment, the historical resource consumption data of the device is analyzed and statistically processed, the business idle time period of the device is intelligently determined based on the analysis result, and the business idle time period is used as the data checking time period, so that the accuracy of the generated data checking time period is effectively improved. And corresponding data checking processing can be carried out in the data checking time period subsequently, and data checking processing can not be carried out in the service peak period of the device, so that normal use of users can not be influenced, reasonable utilization of system resources is guaranteed, and processing speed and efficiency of data checking processing are improved.

s110: dividing a time period of one day into a plurality of unit time periods based on a preset time division threshold;

s111: processing the recorded data based on pre-stored historical data, and counting the total data processing amount of each unit time period in a second preset time period;

s112: screening out a first data processing total amount smaller than a preset data processing amount threshold value from all the data processing total amounts;

s113: sequencing all the first data processing total quantities according to the sequence of the numerical values of the first data processing total quantities from small to large to obtain corresponding sequencing results;

s114: sequentially acquiring a specified number of second data processing total amounts from a first data processing total amount ranked at the head in the sorting result;

s115: acquiring a specified unit time period corresponding to the second data processing total amount from all the unit time periods;

s116: the specified unit time period is taken as the data collation time period.

As described in steps S110 to S116, before the step of acquiring the preset data verification time period, a generation step of generating the data verification time period may be further included. Specifically, first, a time period of one day is divided into a plurality of unit time periods based on a preset time division threshold value. The dividing manner of the unit time periods is not particularly limited, and the time length included in each divided unit time period may also be set according to actual needs, for example, 4 hours may be used as the dividing threshold, that is, the time length included in one unit time period, and then one day (24 hours) may be divided into 6 unit time periods from 0, that is, 0: 00-4: 00,4: 00-8: 00,8: 00-12: 00, 12: 00-16: 00, 16: 00-20: 00, 20: 00-24: 00. then, the recorded data is processed based on the pre-stored historical data, and the total data processing amount of each unit time period in a second preset time period is counted. The second preset time period is not particularly limited, and may be set according to actual requirements. For example, the second preset time period may be the last week adjacent to the current time. For example, if the unit time period is 12: 00-16: 00, the unit time period 12: 00-16: 00 the total data processing amount in a week is the unit time period 12 in the week: 00-16: 00 contains the sum of the data throughput. And then screening out a first data processing total amount smaller than a preset data processing amount threshold value from all the data processing total amounts. The data throughput threshold is not particularly limited, and may be set according to actual requirements. After the first data processing total amount is obtained, all the first data processing total amounts are sorted according to the sequence from small to large of the numerical value of the first data processing total amount, and a corresponding sorting result is obtained. And after the sorting result is obtained, sequentially acquiring a specified number of second data processing total amounts from the first data processing total amount ranked at the top in the sorting result. The specified number is not specifically limited, and can be set according to actual requirements, and the specified value is not more than the value of the first data processing total amount. And finally, acquiring a designated unit time period corresponding to the second data processing total amount from all the unit time periods, and taking the designated unit time period as the data verification time period. In the embodiment, the total data processing amount of each unit time segment in the second preset time period is analyzed, the business idle time segment of the device is intelligently determined based on the analysis result, and the business idle time segment is used as the data checking time segment, so that the accuracy of the generated data checking time segment is effectively improved. And corresponding data checking processing can be carried out in the data checking time period subsequently, and data checking processing can not be carried out in the service peak period of the device, so that normal use of users can not be influenced, reasonable utilization of system resources is guaranteed, and processing speed and efficiency of data checking processing are improved.

The data checking method in the embodiment of the present application may also be applied to the field of blockchains, for example, data such as the data checking result may be stored in a blockchain. By storing and managing the data verification result using a block chain, the security and tamper resistance of the data verification result can be effectively ensured.

The block chain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism and an encryption algorithm. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.

The block chain underlying platform can comprise processing modules such as user management, basic service, intelligent contract and operation monitoring. The user management module is responsible for identity information management of all blockchain participants, and comprises public and private key generation maintenance (account management), key management, user real identity and blockchain address corresponding relation maintenance (authority management) and the like, and under the authorization condition, the user management module supervises and audits the transaction condition of certain real identities and provides rule configuration (wind control audit) of risk control; the basic service module is deployed on all block chain node equipment and used for verifying the validity of the service request, recording the service request to storage after consensus on the valid request is completed, for a new service request, the basic service firstly performs interface adaptation analysis and authentication processing (interface adaptation), then encrypts service information (consensus management) through a consensus algorithm, transmits the service information to a shared account (network communication) completely and consistently after encryption, and performs recording and storage; the intelligent contract module is responsible for registering and issuing contracts, triggering the contracts and executing the contracts, developers can define contract logics through a certain programming language, issue the contract logics to a block chain (contract registration), call keys or other event triggering and executing according to the logics of contract clauses, complete the contract logics and simultaneously provide the function of upgrading and canceling the contracts; the operation monitoring module is mainly responsible for deployment, configuration modification, contract setting, cloud adaptation in the product release process and visual output of real-time states in product operation, such as: alarm, monitoring network conditions, monitoring node equipment health status, and the like.

Referring to fig. 2, an embodiment of the present application further provides a data collation apparatus, including:

the first acquisition module 1 is used for acquiring the current time and acquiring a preset data checking time period;

the judging module 2 is configured to judge whether the current time reaches a start endpoint time of the data checking time period, where the data checking time period is a time period formed by a time interval included in the start endpoint time and an end endpoint time;

a second obtaining module 3, configured to obtain first list data of the first service system and obtain second list data of the second service system if the current time reaches the start endpoint time of the data checking time period;

the first processing module 4 is configured to perform data statistics on the first list data based on a preset service data statistics rule to obtain corresponding first service statistics data, where the first service statistics data includes a first service data field and first service data information corresponding to the first service data field; and the number of the first and second groups,

a second processing module 5, configured to perform data statistics on the second list data to obtain corresponding second service statistical data, where the second service statistical data includes a second service data field and second service data information corresponding to the second service data field;

and the checking module 6 is configured to perform data checking processing on the first service statistical data and the second service statistical data based on a preset data checking template, and generate a corresponding data checking result.

In this embodiment, the implementation processes of the functions and actions of the first obtaining module, the judging module, the second obtaining module, the first processing module, the second processing module and the checking module in the data checking device are specifically described in the implementation processes corresponding to steps S1 to S6 in the data checking method, and are not described herein again.

Further, in an embodiment of the present application, the checking module includes:

a first filling unit, configured to fill the first service data field into the data collation template;

a second filling unit, configured to fill the first service data information to a first corresponding position in the data collation template based on a corresponding relationship between the first service data field and the first service data information;

a first judging unit, configured to judge whether each of the second service data fields includes a designated service data field that is the same as each of the first service data fields;

a second determining unit, configured to determine whether other service data fields except the designated service data field exist in the second service data field if the second service data field includes the designated service data field that is the same as each of the first service data fields;

the first screening unit is used for screening the appointed service data information corresponding to the appointed service data field from the second service data information if the other service data fields do not exist in the second service data field;

a third filling unit, configured to fill the designated service data information to a second corresponding position in the data collation template based on a corresponding relationship between the designated service data field and the first service data field;

a third judging unit, configured to check the first service data information and the specified service data information included in each first service data field in the data checking template one by one to judge whether the two pieces of data information are the same;

a first generating unit, configured to generate a first verification result that is successfully verified if two pieces of data information included in each of the first service data fields are the same;

a second generating unit, configured to generate a second checking result with a checking failure if two pieces of data information included in each of the first service data fields are not the same;

the first obtaining unit is used for obtaining a target service data field of which the first service data information is different from the specified service data information, and adding an abnormal mark to the target service data field.

In this embodiment, the implementation processes of the functions and actions of the first filling unit, the second filling unit, the first judging unit, the second judging unit, the first screening unit, the third filling unit, the third judging unit, the first generating unit, the second generating unit and the first obtaining unit in the data collating device are specifically described in the implementation processes corresponding to steps S600 to S609 in the data collating method, and are not described herein again.

a second obtaining unit, configured to obtain target service data information corresponding to the target service data field;

a third generating unit, configured to generate corresponding first exception information based on the target service data field and the target service data information;

the third acquisition unit is used for acquiring preset mail login information and acquiring a specified mail address;

a login unit for logging in to a corresponding mail server based on the mail login information;

and the first sending unit is used for sending the first abnormal information to the specified mail address through the mail server.

In this embodiment, the implementation processes of the functions and functions of the second obtaining unit, the third generating unit, the third obtaining unit, the login unit and the first sending unit in the data checking apparatus are specifically described in the implementation processes corresponding to steps S6090 to S6094 in the data checking method, and are not described herein again.

a second screening unit, configured to screen a specific service data field from the first service data fields if the second service data field does not include any designated service data field that is the same as each of the first service data fields, where the second service data field does not include the specific service data field;

the first searching unit is used for searching specific service data information corresponding to the specific service data field from the first service data information;

a fourth generating unit, configured to generate corresponding second abnormal information based on the specific service data field and the specific service data information;

and the second sending unit is used for sending the second abnormal information to the specified mail address through the mail server.

In this embodiment, the implementation processes of the functions and functions of the second screening unit, the first searching unit, the fourth generating unit and the second sending unit in the data checking apparatus are specifically described in the implementation processes corresponding to steps S6020 to S6023 in the data checking method, and are not described herein again.

a second searching unit, configured to search, if the other service data fields exist in the second service data field, other service data information corresponding to the other service data fields from the second service data information;

a fifth generating unit, configured to generate corresponding third anomaly information based on the other service data field and the other service data information;

a third sending unit configured to send the third exception information to the specified mail address through the mail server.

In this embodiment, the implementation processes of the functions and actions of the second searching unit, the fifth generating unit and the third sending unit in the data checking apparatus are specifically described in the implementation processes corresponding to steps S6030 to S6032 in the data checking method, and are not described herein again.

Further, in an embodiment of the present application, the data verification apparatus includes:

the third acquisition module is used for acquiring the resource consumption of each appointed time period in each day in a first preset time period, wherein the appointed time period is a time period comprising a preset time length;

the generation module is used for carrying out statistical analysis on the first preset time period, the specified time period and the resource consumption to generate a corresponding resource consumption statistical table;

the first screening module is used for screening out a first time period with the resource consumption smaller than a preset resource consumption threshold value from all the specified time periods in each day in the first preset time period respectively based on the resource consumption statistical table;

the second screening module is used for screening out a second time period with the largest occurrence frequency from all the first time periods;

a first determining module, configured to use the second time period as the data check time period.

In this embodiment, the implementation processes of the functions and functions of the third obtaining module, the generating module, the first screening module, the second screening module and the first determining module in the data checking apparatus are specifically described in the implementation processes corresponding to steps S100 to S104 in the data checking method, and are not described herein again.

the dividing module is used for dividing a time period of one day into a plurality of unit time periods based on a preset time dividing threshold;

the statistical module is used for processing the recorded data based on pre-stored historical data and counting the total data processing amount of each unit time period in a second preset time period;

the third screening module is used for screening out a first data processing total amount smaller than a preset data processing amount threshold value from all the data processing total amounts;

the sorting module is used for sorting all the first data processing total amounts according to the sequence from small to large of the numerical values of the first data processing total amounts to obtain corresponding sorting results;

a fourth obtaining module, configured to sequentially obtain a specified number of second data processing total amounts from a first data processing total amount ranked at the top in the sorting result;

a fifth obtaining module, configured to obtain a specified unit time period corresponding to the second data processing total amount from all the unit time periods;

a second determination module configured to take the specified unit time period as the data collation time period.

In this embodiment, the implementation processes of the functions and functions of the dividing module, the counting module, the third screening module, the sorting module, the fourth obtaining module, the fifth obtaining module and the second determining module in the data checking device are specifically described in the implementation processes corresponding to steps S110 to S116 in the data checking method, and are not described herein again.

Referring to fig. 3, a computer device, which may be a server and whose internal structure may be as shown in fig. 3, is also provided in the embodiment of the present application. The computer device comprises a processor, a memory, a network interface, a display screen, an input device and a database which are connected through a system bus. Wherein the processor of the computer device is designed to provide computing and control capabilities. The memory of the computer device comprises a storage medium and an internal memory. The storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operating system and computer programs in the storage medium to run. The database of the computer device is used for storing data checking time periods, inventory data, service data fields, service data information, data checking templates and data checking results. The network interface of the computer device is used for communicating with an external terminal through a network connection. The display screen of the computer equipment is an indispensable image-text output equipment in the computer, and is used for converting digital signals into optical signals so that characters and figures are displayed on the screen of the display screen. The input device of the computer equipment is the main device for information exchange between the computer and the user or other equipment, and is used for transmitting data, instructions, some mark information and the like to the computer. The computer program is executed by a processor to implement a data collation method.

The processor executes the steps of the data checking method:

acquiring current time and acquiring a preset data checking time period;

Those skilled in the art will appreciate that the structure shown in fig. 3 is only a block diagram of a part of the structure related to the present application, and does not constitute a limitation to the apparatus and the computer device to which the present application is applied.

An embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements a data checking method, and specifically:

acquiring current time and acquiring a preset data checking time period;

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and can include the processes of the embodiments of the methods described above when the computer program is executed. Any reference to memory, storage, database, or other medium provided herein and used in the examples may include non-volatile and/or volatile memory. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), double-rate SDRAM (SSRSDRAM), Enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, apparatus, article, or method 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, apparatus, article, or method. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, apparatus, article, or method that includes the element.

The above description is only a preferred embodiment of the present application, and not intended to limit the scope of the present application, and all modifications of equivalent structures and equivalent processes, which are made by the contents of the specification and the drawings of the present application, or which are directly or indirectly applied to other related technical fields, are also included in the scope of the present application.

Claims

1. A data collation method, comprising:

acquiring current time and acquiring a preset data checking time period;

2. The data matching method of claim 1, wherein the step of performing data matching processing on the first service statistical data and the second service statistical data based on a preset data matching template to generate corresponding data matching results comprises:

filling the first service data field into the data checking template;

3. The data matching method of claim 2, wherein said step of obtaining a target service data field where the first service data information is different from the specified service data information and adding an exception flag to the target service data field is followed by:

acquiring preset mail login information and acquiring a specified mail address;

logging in to a corresponding mail server based on the mail login information;

4. The method of claim 3, wherein said step of determining whether each of said second service data fields includes a designated service data field identical to each of said first service data fields comprises the steps of:

5. The method of claim 3, wherein said step of determining whether there are other service data fields in said second service data field other than said designated service data field is followed by the steps of:

6. The data collation method according to claim 1, wherein said step of acquiring a preset data collation time period is preceded by:

and taking the second time period as the data checking time period.

7. The data collation method according to claim 1, wherein said step of acquiring a preset data collation time period is preceded by:

the specified unit time period is taken as the data collation time period.

8. A data collation apparatus, comprising:

9. A computer device comprising a memory and a processor, the memory having stored therein a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.