CN114612209A - Account checking data processing method and device, computer equipment and storage medium - Google Patents
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Abstract
The application belongs to the technical field of data processing and provides a reconciliation data processing method, a reconciliation data processing device, computer equipment and a storage medium, wherein the method comprises the following steps: the method comprises the steps of obtaining account checking data from a data source, decoupling the account checking data from actual business to obtain standard account checking data, generating an account checking script according to the standard account checking data, determining external data to be obtained according to the account checking script when a preset account checking condition is triggered, executing the account checking script, and comparing the external data with the standard account checking data to obtain an account checking result. The account checking script of the data account checking is developed by butt-jointing account checking data of other business systems to be checked according to certain logic judgment and assembly, and the external data is associated with the account checking script, so that real-time and automatic account checking of the business systems is completed, and the account checking efficiency is improved.
Description
Technical Field
The present application relates to the field of data processing technologies, and in particular, to a reconciliation data processing method, apparatus, computer device, and storage medium.
Background
With the development of internet technology, a large amount of data generating interaction exists among different systems at any moment. For example, when an item is purchased, paid or paid, the user account system interacts with the data in the merchant account system. When an event occurs between two systems, the interactive data needs to meet expectations, whether the interactive data meets expectations is judged, and the implementation means is reconciliation.
In the prior art, in terms of service data consistency and asset loss prevention and control of a service system, reports or large data platforms are mostly customized for services, so that account checking is realized, and the account checking mode is low in efficiency and high in cost.
Disclosure of Invention
The application mainly aims to provide a reconciliation data processing method, a reconciliation data processing device, a computer device and a storage medium, so that the reconciliation efficiency is improved, and the cost is saved.
In order to achieve the above object, the present application provides a reconciliation data processing method, which includes:
acquiring reconciliation data from a data source;
decoupling the account checking data from the actual service to obtain standard account checking data;
generating a reconciliation script according to the standard reconciliation data;
when a preset account checking condition is triggered, determining external data to be acquired according to the account checking script, and acquiring the external data;
And executing the account checking script, and comparing the external data with the standard account checking data to obtain an account checking result.
Preferably, the triggering a preset reconciliation condition includes:
extracting change records from the standard reconciliation data;
judging whether the change record has modified field information;
if yes, triggering a preset account checking condition.
Preferably, the acquiring the external data includes:
and querying external data depended in the reconciliation script through JSON-RPC, and integrating the external data into a uniform context.
Preferably, the comparing the external data with the standard reconciliation data to obtain a reconciliation result includes:
integrating the standard reconciliation data into the context;
acquiring account checking logic preset by executing the account checking script;
and in the context, comparing the external data with the standard reconciliation data according to the reconciliation logic to obtain a reconciliation result.
Further, after the external data is compared with the standard reconciliation data to obtain a reconciliation result, the method further includes:
extracting snapshot information recorded in the account checking script execution process from the account checking result;
When the account checking script is monitored to be abnormal or error is reported, inquiring abnormal snapshot information to obtain target snapshot information;
and storing the target snapshot information into a database.
Further, the querying the abnormal snapshot information to obtain the target snapshot information further includes:
generating an abnormal use case according to the target snapshot information;
and sending the abnormal case to a target terminal in a preset communication mode.
Preferably, the acquiring reconciliation data from the data source comprises:
acquiring a data structure of account checking required by a user;
and determining a target data source according to the data structure, and acquiring account checking data from the target data source.
The application also provides a reconciliation data processing device, which comprises:
the acquisition module is used for acquiring reconciliation data from a data source;
the decoupling module is used for decoupling the account checking data from the actual service to obtain standard account checking data;
the generating module is used for generating a reconciliation script according to the standard reconciliation data;
the determining module is used for determining external data to be acquired according to the account checking script and acquiring the external data when a preset account checking condition is triggered;
and the comparison module is used for executing the account checking script and comparing the external data with the standard account checking data to obtain an account checking result.
The present application further provides a computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the steps of any of the above methods when executing the computer program.
The present application also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of any of the methods described above.
According to the reconciliation data processing method, the reconciliation data processing device, the computer equipment and the storage medium, the reconciliation data is acquired from the data source, the reconciliation data is decoupled from the actual service to obtain the standard reconciliation data, a reconciliation script is generated according to the standard reconciliation data, when the preset reconciliation condition is triggered, the external data needing to be acquired is determined according to the reconciliation script, the reconciliation script is executed, the external data is compared with the standard reconciliation data to obtain a reconciliation result so as to be docked with the reconciliation data of other service systems to be reconciled, the reconciliation script of the data reconciliation is developed through certain logic judgment and assembly, the external data is associated with the reconciliation script, the real-time and automatic reconciliation of the service systems is completed, and the reconciliation efficiency is improved.
Drawings
Fig. 1 is a schematic flowchart of an account checking data processing method according to an embodiment of the present application;
fig. 2 is a schematic flowchart of a reconciliation data processing method according to yet another embodiment of the present application;
fig. 3 is a schematic flowchart of a reconciliation data processing method according to yet another embodiment of the present application;
fig. 4 is a block diagram schematically illustrating a structure of a reconciliation data processing apparatus according to an embodiment of the present application;
fig. 5 is a block diagram illustrating a structure 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
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. 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.
According to the reconciliation data processing method provided by the application, the execution main body can be an electronic device, a terminal device, a server or other devices or equipment which can execute the application, and is not limited. The application takes an execution subject as a server (account checking platform) for explanation, and the server may be an independent server, or a cloud server that provides basic cloud computing services such as cloud service, a cloud database, cloud computing, a cloud function, cloud storage, Network service, cloud communication, middleware service, domain name service, security service, Content Delivery Network (CDN), big data, and an artificial intelligence platform.
As shown in fig. 1 and with reference to fig. 2 to 3, in one embodiment, the reconciliation data processing method includes:
s11, acquiring reconciliation data from a data source;
s12, decoupling the reconciliation data from the actual service to obtain standard reconciliation data;
s13, generating a reconciliation script according to the standard reconciliation data;
s14, when a preset account checking condition is triggered, determining external data to be acquired according to the account checking script, and acquiring the external data;
and S15, executing the reconciliation script, and comparing the external data with the standard reconciliation data to obtain a reconciliation result.
In this embodiment, the data source is a device or original media providing the required data, and the developer can send the data structure and the data source to the server, and the server obtains the data structure and the data source. All information for establishing database connections is stored in the data source, just as files can be found in the file system by specifying the file name, and the corresponding database connections can be found by providing the correct data source name. The data source of this embodiment may refer to a database or a database server used by another business system, so as to obtain reconciliation data that needs reconciliation, for example, daily transaction data obtained from a business system of a financial company.
In an embodiment, the computer device may obtain the reconciliation data from the data source in real time or at preset time intervals, and may further use a preset rule to take data meeting the rule as the reconciliation data for all data obtained from the data source. The preset rule is generally a time period, such as a data change record within an hour or a week, and the time period is determined according to a time tag corresponding to the data change record.
In this embodiment, reconciliation data and actual service are decoupled through Kafka messages to obtain standard reconciliation data, so as to ensure that a reconciliation link does not affect a core function, and a reconciliation script is generated according to the standard reconciliation data. The account checking script can be generated by adopting a Groovy script language, the effect and flexibility of real-time loading of the script are guaranteed, and complex internal logic is realized by utilizing a built-in grammar of the Groovy. The Groovy is a dynamic/agile programming language based on a JVM platform, development efficiency is very high, the Groovy can be in seamless butt joint with a Java language, when the Groovy is written, if grammar is forgotten, grammar can be directly written continuously according to the grammar of the Java, a Groovy script can be called in the Java, work can be well conducted, and cost of learning the Groovy by a Java developer is effectively reduced.
In the reconciliation script of the embodiment, conditions, time and logic for triggering the reconciliation task are defined, external data needing to be acquired is declared, when a preset reconciliation condition is triggered, the external data needing to be acquired is determined according to the reconciliation script, the external data is acquired, after multiple external data are aggregated, codes of the reconciliation script are executed in the same context, and the external data and standard reconciliation data are compared to obtain a reconciliation result.
In an embodiment, referring to fig. 3, in the process of executing the reconciliation script, snapshot information of each data is completely recorded, after the reconciliation script is abnormal or has been reported by mistake, the server automatically pushes an abnormal alarm to the developer, so that the developer queries the abnormal data snapshot and returns the abnormal data snapshot to the server, and the server follows up the abnormal alarm to process the fault. The reconciliation platform can comprise an entity module, an event module and an alarm module, wherein the entity module is used for searching entity information, packaging message objects, executing events and the like, the event module is used for searching entity event lists, executing event scripts, scanning delay events or failure events, sending alarm messages and the like, and the alarm module is used for responding to the alarm messages and pushing the alarms to users in a mode of flybook or telephone alarm.
Wherein all snapshot information is instantiated into the relational database for subsequent invocation. In addition, strategies such as delay verification, failure retry and the like are supported in the execution process of the account checking script, and the accuracy of alarming is guaranteed to be improved. For example, when a preset account checking condition is triggered, whether time delay is needed or not is determined according to time delay in an account checking script, and if the time delay is not needed, the external data is compared with the standard account checking data to obtain an account checking result; and if time delay is needed, delaying, and after the time delay is over, comparing external data with the standard reconciliation data to obtain a reconciliation result so as to realize configurable reconciliation delay and meet different reconciliation real-time requirements.
Specifically, the reconciliation data may be payment data, the external data may be payment data, the reconciliation script may be configured to compare the payment data of the payment company with the payment data recorded in the transaction platform in a consistent manner, and if the payment data of the payment company is consistent with the payment data recorded in the transaction platform, it may be determined that the reconciliation result is normal. If the payment data of the payment company is inconsistent with the payment data recorded in the transaction platform, the reconciliation result can be determined to be abnormal, and the computer equipment generates alarm information and sends the alarm information to the terminal where the developer is located, so that timely alarm is realized.
The transaction platform can acquire account checking files pushed to a file server of the transaction platform by the payment company through a zkey tool. The reconciliation file may include payment data recorded by a payment company or a payment platform, for example, payment data paid by a user to a merchant through platforms such as WeChat, Payment treasures, Unionpay, and the like. In particular, the payment data may include payment amount, payment time, payment platform, user information, and the like.
In some embodiments, if the computer device determines that the reconciliation result is abnormal, the abnormal data can be further analyzed, the abnormal data is also recorded in the reconciliation result, and the reconciliation result is sent to the terminal where the developer is located. Alternatively, the abnormal data may include a difference between payment data of the payment company and payment data recorded in the transaction platform, the payment company in which the abnormality occurs, and the like.
Optionally, if the payment data and the payment data are not consistent, it may be determined that the payment data and the payment data are not matched; if the payment data and the payment data are consistent, it can be determined that the payment data and the payment data match.
In one embodiment, the payment data may be determined to match the payment data if the difference between the payment data and the payment data is within a specified range. Otherwise, it is determined that the payment data and the payment data do not match.
If the account checking result is abnormal, acquiring abnormal data; and marking the abnormal data or/and outputting reminding information corresponding to the abnormal data. In addition, the abnormal data may be highlighted and displayed, or displayed in a specific color or a specific display mode. The computer device outputs the reminding information corresponding to the abnormal data, specifically, the reminding information can be short messages sent to a mobile terminal of the user so as to remind the user of which reconciliation data are abnormal. The prompt message includes but is not limited to short message, voice message, image message, etc.
The account checking data processing method includes the steps of obtaining account checking data from a data source, decoupling the account checking data from actual business to obtain standard account checking data, generating an account checking script according to the standard account checking data, determining external data to be obtained according to the account checking script when preset account checking conditions are triggered, executing the account checking script, comparing the external data with the standard account checking data to obtain an account checking result, so that account checking data of other business systems to be checked can be docked, developing the account checking script of data account checking through certain logic judgment and assembly, associating the external data with the external data, completing real-time and automatic account checking of the business systems, and improving account checking efficiency.
In an embodiment, the triggering a preset reconciliation condition may specifically include:
extracting change records from the standard reconciliation data;
judging whether the change record has modified field information;
if yes, triggering a preset account checking condition.
In this embodiment, for a scenario in which some distributed transactions exist between service systems, but functions are unstable due to iteration based on network communication and service systems, a checking mechanism is required to ensure that unexpected problems do not occur in internal services when a system or an operation and maintenance environment changes. The health of the business is ensured in an account checking mode, the final consistency can be ensured, the problems of asset loss or serious accidents and the like can not occur, and the problems are often delayed when occurring, so that the problems can not be exposed and sensed in time. Therefore, the embodiment can convert the reconciliation data of the data source into the standard kafka message through the Canal middleware, perform data sampling, point burying and analysis in the processing process, output the field information related to modification in the change record, recognize that the change point of the record triggers the reconciliation task, and automatically trigger the preset reconciliation condition when judging that the change record has the modified field information.
The Canal is an open source middleware and can provide subscription and consumption functions of incremental data by analyzing the incremental logs of the database.
Kafka is a high-throughput distributed publish-subscribe messaging system that can handle all the action flow data of a consumer in a web site. This action (web browsing, searching and other user actions) is a key factor in many social functions on modern networks. These data are typically addressed by handling logs and log aggregations due to throughput requirements. This is a viable solution to the limitations of Hadoop-like log data and offline analysis systems, but which require real-time processing. The purpose of Kafka is to unify online and offline message processing through the parallel loading mechanism of Hadoop, and also to provide real-time messages through clustering.
In an embodiment, the acquiring the external data may specifically include:
and querying external data depended in the reconciliation script through JSON-RPC, and integrating the external data into a uniform context.
In the embodiment, external data which is depended on in the reconciliation script is inquired through JSON-RPC, the external data is integrated into a uniform context, immediate execution or delayed execution is selected according to the configuration of the reconciliation task, and when a preset reconciliation condition is triggered, a reconciliation logic is executed according to the external data in the context to obtain a reconciliation result.
The JSON-RPC is a remote calling service taking JSON as a message format, and is a set of specifications and a series of implementations which allow programs running in different operating systems and different environments to implement calling based on a transmission process. Such remote procedure calls may use http as the transport protocol, or other transport protocols, the content of the transport being the json message body. json is small compared to xml and is much easier to resolve.
In an embodiment, the comparing the external data with the standard reconciliation data to obtain a reconciliation result includes:
integrating the standard reconciliation data into the context;
acquiring account checking logic preset by executing the account checking script;
and in the context, comparing the external data with the standard reconciliation data according to the reconciliation logic to obtain a reconciliation result.
In this embodiment, the standard reconciliation data is integrated into the context, the Groovy script of the reconciliation task is dynamically loaded into the system, the reconciliation logic is executed according to the external data in the context and the standard reconciliation data, and the external data is compared with the standard reconciliation data according to the reconciliation logic to obtain a reconciliation result.
In an embodiment, in the process of executing the reconciliation script, a plurality of times of failed retries are carried out according to the execution condition, and finally, the abnormal use case is subjected to persistent storage.
In an embodiment, after the comparing the external data with the standard reconciliation data to obtain a reconciliation result, the method may further include:
extracting snapshot information recorded in the account checking script execution process from the account checking result;
when the account checking script is monitored to be abnormal or error is reported, inquiring abnormal snapshot information to obtain target snapshot information;
and storing the target snapshot information into a database.
In the execution process of the account checking script, the computer equipment can automatically record snapshot information in the execution process, when the account checking script is monitored to be abnormal or error reporting is carried out, the abnormal snapshot information is inquired from all the recorded snapshot information to obtain target snapshot information, the target snapshot information is stored in a database, and some related configuration and management end functions are maintained and managed by using a relational database. The snapshot information is a recording mode of the execution process of the account script and is stored in a form of a photo.
In an embodiment, after the querying the abnormal snapshot information and obtaining the target snapshot information, the method may further include:
Generating an abnormal use case according to the target snapshot information;
and sending the abnormal case to a target terminal in a preset communication mode.
According to the embodiment, the abnormal use case can be generated according to the target snapshot information, the abnormal use case is sent to the target terminal in a preset communication mode, the target terminal corresponds to the responsible personnel, when the abnormal snapshot information is inquired, the abnormal snapshot information is timely notified to the responsible personnel, and the responsible personnel operate and process the abnormal snapshot information. The preset communication mode can include mailbox, IM tool and other modes. Meanwhile, when abnormal alarm exists, all current alarm information can be inquired, the alarm processing progress is followed, and further expansion of faults is avoided.
For example, if the account checking data is inconsistent with the external data or the difference value between the account checking data and the external data is within a specified range, the account checking result is abnormal, abnormal snapshot information is inquired to obtain target snapshot information, an abnormal case is generated according to the target snapshot information, and the abnormal case is sent to the target terminal in a preset communication mode.
And if the account checking result is abnormal, acquiring abnormal data of the target snapshot information, marking the abnormal data, or/and outputting reminding information corresponding to the abnormal data. In addition, the abnormal data may be highlighted and displayed, or displayed in a specific color or a specific display mode. The computer device outputs the reminding information corresponding to the abnormal data, specifically, the reminding information can be short messages sent to a mobile terminal of the user so as to remind the user of which reconciliation data are abnormal. The prompt message includes but is not limited to short message, voice message, image message, etc.
In an embodiment, the acquiring the reconciliation data from the data source may specifically include:
acquiring a data structure of a user needing account checking;
and determining a target data source according to the data structure, and acquiring reconciliation data from the target data source.
The embodiment can record the data structure of account checking required by the user in advance, and the data structure is a way for storing and organizing data by a computer. A data structure refers to a collection of data elements that have one or more specific relationships to each other. Typically, a carefully chosen data structure can lead to greater operational or storage efficiency. The data structure includes a collection structure, a linear structure, a tree structure, and a graph structure. Wherein, the relationship between the data elements of the set structure belongs to the same set; a one-to-one relationship exists between data elements of the linear structure; one-to-many relationship exists between the data elements of the tree structure; there are many-to-many relationships between data elements of a graph structure, also known as a mesh structure. The method and the device for acquiring the account checking data determine the target data source according to the data structure required by the user, and acquire the account checking data from the target data source so as to ensure the reliability of the account checking data acquired from the data source.
Referring to fig. 4, an embodiment of the present application further provides an account checking data processing apparatus, including:
an obtaining module 11, configured to obtain reconciliation data from a data source;
the decoupling module 12 is configured to decouple the reconciliation data from the actual service to obtain standard reconciliation data;
a generating module 13, configured to generate a reconciliation script according to the standard reconciliation data;
the determining module 14 is configured to determine, according to the reconciliation script, external data that needs to be acquired when a preset reconciliation condition is triggered, and acquire the external data;
and the comparison module 15 is configured to execute the reconciliation script, and compare the external data with the standard reconciliation data to obtain a reconciliation result.
In this embodiment, the data source is a device or original media providing the required data, and the developer can send the data structure and the data source to the server, and the server obtains the data structure and the data source. All information for establishing database connections is stored in the data source, just as files can be found in the file system by specifying the file name, and the corresponding database connections can be found by providing the correct data source name. The data source of this embodiment may refer to a database or a database server used by another business system, so as to obtain reconciliation data that needs reconciliation, for example, daily transaction data obtained from a business system of a financial company.
In an embodiment, the computer device may obtain the reconciliation data from the data source in real time or at preset time intervals, and may further use a preset rule to take data meeting the rule as the reconciliation data for all data obtained from the data source. The preset rule is generally a time period, such as a data change record within an hour or a week, and the time period is determined according to a time tag corresponding to the data change record.
In this embodiment, reconciliation data and actual service are decoupled through Kafka messages to obtain standard reconciliation data, so as to ensure that a reconciliation link does not affect a core function, and a reconciliation script is generated according to the standard reconciliation data. The account checking script can be generated by adopting a Groovy script language, the effect and flexibility of real-time loading of the script are guaranteed, and complex internal logic is realized by utilizing a built-in grammar of the Groovy. The Groovy is a dynamic/agile programming language based on a JVM platform, development efficiency is very high, the Groovy can be in seamless butt joint with a Java language, when the Groovy is written, if grammar is forgotten, grammar can be directly written continuously according to the grammar of the Java, a Groovy script can be called in the Java, work can be well conducted, and cost of learning the Groovy by a Java developer is effectively reduced.
In the reconciliation script of the embodiment, conditions, time and logic for triggering the reconciliation task are defined, external data to be acquired is declared, when a preset reconciliation condition is triggered, the external data to be acquired is determined according to the reconciliation script, the external data is acquired, after multiple external data are aggregated, codes of the reconciliation script are executed in the same context, and the external data is compared with standard reconciliation data to obtain a reconciliation result.
In an embodiment, referring to fig. 3, in the process of executing the reconciliation script, snapshot information of each data is completely recorded, after the reconciliation script is abnormal or has been reported by mistake, the server automatically pushes an abnormal alarm to the developer, so that the developer queries the abnormal data snapshot and returns the abnormal data snapshot to the server, and the server follows up the abnormal alarm to process the fault. The reconciliation platform can comprise an entity module, an event module and an alarm module, wherein the entity module is used for searching entity information, packaging message objects, executing events and the like, the event module is used for searching entity event lists, executing event scripts, scanning delay events or failure events, sending alarm messages and the like, and the alarm module is used for responding to the alarm messages and pushing the alarms to users in a mode of flybook or telephone alarm.
Wherein all snapshot information is instantiated into the relational database for subsequent invocation. In addition, strategies such as delay verification, failure retry and the like are supported in the execution process of the account checking script, and the accuracy of alarming is guaranteed to be improved. For example, when a preset account checking condition is triggered, whether time delay is needed or not is determined according to time delay in an account checking script, and if the time delay is not needed, the external data is compared with the standard account checking data to obtain an account checking result; and if time delay is needed, delaying, and after the time delay is over, comparing external data with the standard reconciliation data to obtain a reconciliation result so as to realize configurable reconciliation delay and meet different reconciliation real-time requirements.
Specifically, the reconciliation data may be payment data, the external data may be payment data, the reconciliation script may be configured to compare the payment data of the payment company with the payment data recorded in the transaction platform in a consistent manner, and if the payment data of the payment company is consistent with the payment data recorded in the transaction platform, it may be determined that the reconciliation result is normal. If the payment data of the payment company is inconsistent with the payment data recorded in the transaction platform, the reconciliation result can be determined to be abnormal, and the computer equipment generates alarm information and sends the alarm information to the terminal where the developer is located, so that timely alarm is realized.
The transaction platform can acquire account checking files pushed to a file server of the transaction platform by the payment company through a zkey tool. The reconciliation file may include payment data recorded by a payment company or a payment platform, for example, payment data paid by a user to a merchant through platforms such as WeChat, Payment treasures, Unionpay, and the like. In particular, the payment data may include payment amount, payment time, payment platform, user information, and the like.
In some embodiments, if the computer device determines that the reconciliation result is abnormal, the abnormal data can be further analyzed, the abnormal data is also recorded in the reconciliation result, and the reconciliation result is sent to the terminal where the developer is located. Alternatively, the abnormality data may include a difference between payment data of the payment company and payment data recorded in the transaction platform, the payment company in which the abnormality occurs, and the like.
Optionally, if the payment data and the payment data are not consistent, it may be determined that the payment data and the payment data are not matched; if the payment data and the payment data are consistent, it can be determined that the payment data and the payment data match.
In one embodiment, the payment data may be determined to match the payment data if the difference between the payment data and the payment data is within a specified range. Otherwise, it is determined that the payment data and the payment data do not match.
If the account checking result is abnormal, acquiring abnormal data; and marking the abnormal data, or/and outputting reminding information corresponding to the abnormal data. In addition, the abnormal data may be highlighted and displayed, or the abnormal data may be displayed in a specific color or a specific display mode. The computer device outputs the reminding information corresponding to the abnormal data, specifically, the reminding information can be short messages sent to a mobile terminal of the user so as to remind the user of which reconciliation data are abnormal. The prompt message includes but is not limited to a short message, a voice message, an image message, etc.
As described above, it can be understood that each component of the reconciliation data processing apparatus provided in the present application can implement the function of any one of the reconciliation data processing methods described above, and a detailed structure is not described again.
Referring to fig. 5, an embodiment of the present application further provides a computer device, and an internal structure of the computer device may be as shown in fig. 5. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the computer designed processor is used to provide computational 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 memory provides an environment for the operation of the operating system and computer programs in the storage medium. The database of the computer equipment is used for storing the relevant data of the reconciliation data processing method. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a reconciliation data processing method.
The processor executes the reconciliation data processing method, which comprises the following steps:
acquiring reconciliation data from a data source;
decoupling the reconciliation data from the actual service to obtain standard reconciliation data;
generating a reconciliation script according to the standard reconciliation data;
when a preset account checking condition is triggered, determining external data to be acquired according to the account checking script, and acquiring the external data;
and executing the account checking script, and comparing the external data with the standard account checking data to obtain an account checking result.
An embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the computer program implements a reconciliation data processing method, including the steps of:
acquiring reconciliation data from a data source;
decoupling the account checking data from the actual service to obtain standard account checking data;
generating a reconciliation script according to the standard reconciliation data;
when a preset account checking condition is triggered, determining external data to be acquired according to the account checking script, and acquiring the external data;
and executing the account checking script, and comparing the external data with the standard account checking data to obtain an account checking result.
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 may be implemented by hardware instructions of a computer program, and the computer program may be stored in a computer-readable storage medium, and when executed, may include the processes of the embodiments of the methods described above. 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), dual data rate SDRAM (SSRSDRAM), Enhanced SDRAM (ESDRAM), synchronous Link (Synchlink) DRAM (SLDRAM), Rambus (Rambus) direct RAM (RDRAM), direct bused dynamic RAM (DRDRAM), and bused dynamic RAM (RDRAM).
To sum up, the most beneficial effect of this application lies in:
according to the reconciliation data processing method, the reconciliation data processing device, the computer equipment and the storage medium, the reconciliation data is acquired from the data source, the reconciliation data is decoupled from the actual service to obtain the standard reconciliation data, a reconciliation script is generated according to the standard reconciliation data, when the preset reconciliation condition is triggered, the external data needing to be acquired is determined according to the reconciliation script, the reconciliation script is executed, the external data is compared with the standard reconciliation data to obtain a reconciliation result so as to be docked with the reconciliation data of other service systems to be reconciled, the reconciliation script of the data reconciliation is developed through certain logic judgment and assembly, the external data is associated with the reconciliation script, the real-time and automatic reconciliation of the service systems is completed, and the reconciliation efficiency is improved.
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 identical elements in the process, apparatus, article or method that comprises 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 (10)
1. A reconciliation data processing method is characterized by comprising the following steps:
acquiring reconciliation data from a data source;
decoupling the reconciliation data from the actual service to obtain standard reconciliation data;
generating a reconciliation script according to the standard reconciliation data;
when a preset account checking condition is triggered, determining external data to be acquired according to the account checking script, and acquiring the external data;
and executing the account checking script, and comparing the external data with the standard account checking data to obtain an account checking result.
2. The method of claim 1, wherein the triggering a preset tie-out condition comprises:
extracting change records from the standard reconciliation data;
judging whether the change record has modified field information;
if yes, triggering a preset account checking condition.
3. The method of claim 1, wherein the obtaining the external data comprises:
And querying external data depended in the reconciliation script through JSON-RPC, and integrating the external data into a uniform context.
4. The method of claim 3, wherein comparing the external data with the standard reconciliation data to obtain a reconciliation result comprises:
integrating the standard reconciliation data into the context;
acquiring account checking logic preset by executing the account checking script;
and in the context, comparing the external data with the standard reconciliation data according to the reconciliation logic to obtain a reconciliation result.
5. The method of claim 1, wherein after comparing the external data with the standard reconciliation data to obtain a reconciliation result, the method further comprises:
extracting snapshot information recorded in the account checking script execution process from the account checking result;
when the account checking script is monitored to be abnormal or error is reported, inquiring abnormal snapshot information to obtain target snapshot information;
and storing the target snapshot information into a database.
6. The method according to claim 5, wherein the querying the abnormal snapshot information, after obtaining the target snapshot information, further comprises:
Generating an abnormal use case according to the target snapshot information;
and sending the abnormal use case to a target terminal in a preset communication mode.
7. The method of claim 1, wherein the obtaining reconciliation data from a data source comprises:
acquiring a data structure of a user needing account checking;
and determining a target data source according to the data structure, and acquiring reconciliation data from the target data source.
8. A reconciliation data processing apparatus comprising:
the acquisition module is used for acquiring reconciliation data from a data source;
the decoupling module is used for decoupling the account checking data from the actual service to obtain standard account checking data;
the generating module is used for generating a reconciliation script according to the standard reconciliation data;
the determining module is used for determining external data to be acquired according to the account checking script and acquiring the external data when a preset account checking condition is triggered;
and the comparison module is used for executing the account checking script and comparing the external data with the standard account checking data to obtain an account checking result.
9. A computer device, comprising:
a processor;
a memory;
wherein the memory stores a computer program which, when executed by the processor, implements the reconciliation data processing method of any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that a computer program is stored thereon, which computer program, when being executed by a processor, carries out the reconciliation data processing method of any one of claims 1 to 7.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105550103A (en) * | 2015-12-03 | 2016-05-04 | 泰华智慧产业集团股份有限公司 | Custom test script based automated testing method |
| CN111752793A (en) * | 2020-05-27 | 2020-10-09 | 中国平安财产保险股份有限公司 | System abnormity monitoring method and device, computer equipment and storage medium |
| CN112419018A (en) * | 2020-01-03 | 2021-02-26 | 上海哔哩哔哩科技有限公司 | General data reconciliation method, server and storage medium in distributed environment |
| CN114398359A (en) * | 2022-01-17 | 2022-04-26 | 深圳依时货拉拉科技有限公司 | Order data automatic reconciliation method, device and storage medium |
-
2022
- 2022-05-12 CN CN202210511412.6A patent/CN114612209A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105550103A (en) * | 2015-12-03 | 2016-05-04 | 泰华智慧产业集团股份有限公司 | Custom test script based automated testing method |
| CN112419018A (en) * | 2020-01-03 | 2021-02-26 | 上海哔哩哔哩科技有限公司 | General data reconciliation method, server and storage medium in distributed environment |
| CN111752793A (en) * | 2020-05-27 | 2020-10-09 | 中国平安财产保险股份有限公司 | System abnormity monitoring method and device, computer equipment and storage medium |
| CN114398359A (en) * | 2022-01-17 | 2022-04-26 | 深圳依时货拉拉科技有限公司 | Order data automatic reconciliation method, device and storage medium |
Non-Patent Citations (3)
| Title |
|---|
| CAPTAINHZC: "《https://blog.csdn.net/Caption_He/article/details/119062244》", 25 July 2021 * |
| 海诺: "《https://blog.csdn.net/qq_34321590/article/details/106456656》", 31 May 2020 * |
| 飞鸟与鱼: "《https://blog.csdn.net/qq_30612351/article/details/109697551》", 14 November 2020 * |
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