Accounting system and accounting system data processing method and device, equipment and medium

Abstract

The invention relates to an accounting system and accounting system data processing method and device, equipment and a medium, and the method comprises the steps: receiving a customer number list, and extracting corresponding customer account transaction information from an accounting system based on the customer number list; based on the customer account transaction information, generating a T-1 day account balance summary sheet in an account system, and extracting a customer T-1 day account level accounting subject balance sheet from a big data system; a T-1 day accounting subject balance table is mapped and generated in the accounting system; and judging whether T-1 day total score checking is balanced or not based on the two generated tables. In the whole process, based on the same customer account transaction information, the T-1 day account balance summary sheet is generated in the account system and the T-1 day account level accounting subject balance sheet of the customer is extracted in the big data system, so that the two sheets have relevance, the consistency of the total score is ensured when the T-1 day total score checking is carried out, and the checking efficiency is improved. Accurate accounting system and accounting system data processing is realized.

Description

Technical Field

[0001] This application relates to the field of big data technology, and in particular to a data processing method, apparatus, computer equipment, storage medium and computer program product for accounting and accounting systems. Background Technology

[0002] In the accelerating process of digital transformation in financial services, accounting and bookkeeping systems have become key supports for the core operations of financial institutions. They need to process massive amounts of critical data such as customer information, loan receipts, transaction entries, and account balances. This data is stored in various media such as MySQL, Hadoop big data platforms, and Redis caches, and the data sources are complex and diverse.

[0003] To ensure the security and compliance of financial data, all data sources used for testing must undergo online data anonymization. The anonymized data comprehensively covers business scenarios and can meet various testing needs. However, the volume of anonymized data is still enormous, and directly using it for testing faces the challenge of inefficiently completing daily data switching and batch processing tasks, leading to extended testing cycles and excessive resource consumption. Traditional techniques are methods for obtaining test data from multi-source anonymized data. These methods extract data from the full anonymized data source based on preset rules, and then perform simple field filtering and format conversion to form test data.

[0004] While the aforementioned traditional technologies can utilize fully anonymized scenario data and possess basic filtering capabilities, they are not optimized for the core characteristics of financial accounting and bookkeeping systems. They only filter data through surface-level fields, failing to guarantee the consistency of amounts between the extracted accounting and bookkeeping data, nor can they ensure the balance between detailed account balances and general ledger balances, making accurate data processing for accounting and bookkeeping systems difficult. Summary of the Invention

[0005] Therefore, it is necessary to provide an accurate data processing method, apparatus, computer equipment, storage medium, and computer program product for accounting and bookkeeping systems to address the aforementioned technical problems.

[0006] Firstly, this application provides a data processing method for an accounting system and a bookkeeping system. The method includes:

[0007] Receive a list of customer IDs and extract the corresponding customer account transaction information from the accounting system based on the list of customer IDs;

[0008] Based on customer account transaction information, a summary table of account balances for day T-1 is generated in the accounting system, and a balance table of account-level accounting subjects for day T-1 is extracted from the big data system.

[0009] Based on the customer's account-level accounting balance sheet for day T-1, generate the account balance sheet for day T-1 in the accounting system;

[0010] Based on the summary of account balances on day T-1 and the balance sheet of accounting subjects on day T-1, determine whether the total balance on day T-1 is balanced.

[0011] In one embodiment, mapping and generating a T-1 day accounting account balance sheet in the accounting system based on the customer's T-1 day account-level accounting account balance sheet includes:

[0012] Convert the customer's T-1 day account-level accounting balance sheet into an intermediate data format to obtain intermediate data;

[0013] In the accounting system, a T-1 day account-level accounting subject balance table is created according to the intermediate data format and the corresponding data storage structure. The intermediate data is then mapped to the created T-1 day account-level accounting subject balance table to generate the T-1 day accounting subject balance table.

[0014] In one embodiment, the accounting system creates a T-1 day account-level accounting subject balance sheet with a corresponding data storage structure according to the intermediate data format, maps the intermediate data to the created T-1 day account-level accounting subject balance sheet, and generates the T-1 day accounting subject balance sheet by:

[0015] In the accounting system, create a T-1 day account-level accounting subject balance table with the corresponding data storage structure according to the intermediate data format, and add a summary status identifier field and initialize the summary status identifier field to the default value; the default value indicates that it has not been summarized.

[0016] Map the intermediate data to the created T-1 day account-level accounting subject balance sheet;

[0017] Determine the value of the summary status identifier field in the T-1 day account-level accounting subject balance sheet after mapping;

[0018] If the field value indicates that it has not been summarized, then a summary task will be performed on the account-level accounting subject balance sheet of day T-1 to generate the accounting subject balance sheet of day T-1.

[0019] In one embodiment, mapping and generating a T-1 day accounting account balance sheet in the accounting system based on the customer's T-1 day account-level accounting account balance sheet includes:

[0020] The customer's T-1 day account-level accounting balance sheet is converted into a data object HiveAccountBalanceD0 in the JVM (Java Virtual Machine) using the HiveJDBC driver.

[0021] Create an account-level account balance table in the accounting system that is consistent with the fields of the customer's T-1 day account-level account balance table, and add a summary status identifier field to the table;

[0022] Using Spring Data JPA, the account-level accounting subject balance sheet is mapped to the data object AccountBalanceD0 in the JVM;

[0023] The `javamapstruct` method is used to map and convert data objects from `HiveAccountBalanceD0` to `AccountBalanceD0`, and the summary status identifier field is assigned a default value, which indicates that the data has not been summarized.

[0024] Write the final data object AccountBalanceD0 to the account-level accounting subject balance table to generate the T-1 day accounting subject balance table.

[0025] In one embodiment, generating a T-1 day account balance summary table in the accounting system based on customer account transaction information includes:

[0026] Based on customer account transaction information, extract the relevant transaction tables for customer day T from the accounting system and associate them with the account set number;

[0027] Extract transaction entry data for day T from the accounting system by corresponding account number;

[0028] Extract customer account balance data for day T-1 from the account system;

[0029] Based on the transaction entries for day T and the customer's account balance related table for day T-1, execute a batch task to summarize the balance for day T-1 and generate a summary table of account balances for day T-1.

[0030] In one embodiment, after determining whether the total balance on T-1 is balanced based on the T-1 day account balance summary table and the T-1 day accounting account balance table, the method further includes:

[0031] If the total scores are unbalanced on day T-1, the extracted customer account transaction information is deemed abnormal.

[0032] The extracted customer account transaction information is examined.

[0033] Secondly, this application also provides a data processing device for an accounting system and a bookkeeping system. The device includes:

[0034] The data acquisition module is used to receive a list of customer numbers and extract the corresponding customer account transaction information from the accounting system based on the list of customer numbers.

[0035] The data extraction module is used to generate a T-1 day account balance summary table in the accounting system based on customer account transaction information and to extract the customer's T-1 day account-level accounting subject balance table from the big data system.

[0036] The data mapping module is used to map and generate a T-1 day accounting account balance sheet in the accounting system based on the customer's T-1 day account-level accounting account balance sheet;

[0037] The verification module is used to determine whether the total balance is balanced on T-1 based on the summary table of account balances on T-1 and the accounting account balance table on T-1.

[0038] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to perform the following steps:

[0039] Receive a list of customer IDs and extract the corresponding customer account transaction information from the accounting system based on the list of customer IDs;

[0040] Based on customer account transaction information, a summary table of account balances for day T-1 is generated in the accounting system, and a balance table of account-level accounting subjects for day T-1 is extracted from the big data system.

[0041] Based on the customer's account-level accounting balance sheet for day T-1, generate the account balance sheet for day T-1 in the accounting system;

[0042] Based on the summary of account balances on day T-1 and the balance sheet of accounting subjects on day T-1, determine whether the total balance on day T-1 is balanced.

[0043] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, performs the following steps:

[0044] Receive a list of customer IDs and extract the corresponding customer account transaction information from the accounting system based on the list of customer IDs;

[0045] Based on customer account transaction information, a summary table of account balances for day T-1 is generated in the accounting system, and a balance table of account-level accounting subjects for day T-1 is extracted from the big data system.

[0046] Based on the customer's account-level accounting balance sheet for day T-1, generate the account balance sheet for day T-1 in the accounting system;

[0047] Based on the summary of account balances on day T-1 and the balance sheet of accounting subjects on day T-1, determine whether the total balance on day T-1 is balanced.

[0048] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, performs the following steps:

[0049] Receive a list of customer IDs and extract the corresponding customer account transaction information from the accounting system based on the list of customer IDs;

[0050] Based on customer account transaction information, a summary table of account balances for day T-1 is generated in the accounting system, and a balance table of account-level accounting subjects for day T-1 is extracted from the big data system.

[0051] Based on the customer's account-level accounting balance sheet for day T-1, generate the account balance sheet for day T-1 in the accounting system;

[0052] Based on the summary of account balances on day T-1 and the balance sheet of accounting subjects on day T-1, determine whether the total balance on day T-1 is balanced.

[0053] The aforementioned accounting and accounting system data processing methods, devices, computer equipment, storage media, and computer program products receive a list of customer numbers and extract corresponding customer account transaction information from the accounting system based on the customer number list. Based on the customer account transaction information, the accounting system generates a T-1 day account balance summary table and extracts a T-1 day account-level accounting subject balance table from the big data system. Based on the customer T-1 day account-level accounting subject balance table, the accounting system maps and generates a T-1 day accounting subject balance table. Based on the T-1 day account balance summary table and the T-1 day accounting subject balance table, the system determines whether the T-1 day total balance reconciliation is balanced. Throughout this process, the generation of the T-1 day account balance summary table in the accounting system and the extraction of the customer T-1 day account-level accounting subject balance table from the big data system based on the same customer account transaction information ensures an inherent correlation between the two tables. Furthermore, by mapping the customer's T-1 day account-level accounting balance sheet from the big data system to the accounting system to generate the T-1 day accounting balance sheet, the connection between the T-1 day accounting balance sheet and the T-1 day summary accounting balance sheet is further strengthened. Due to this close correlation, the consistency and matching of total and partial data can be effectively guaranteed during T-1 day total and partial reconciliation, eliminating reconciliation errors caused by inconsistencies in data sources or processing logic, thereby achieving accurate and reliable processing of data between the accounting system and the accounting system. Attached Figure Description

[0054] Figure 1 This is an application environment diagram of the data processing method of the accounting system and the accounting system in one embodiment;

[0055] Figure 2 This is a flowchart illustrating the data processing method of the accounting system and the accounting system in one embodiment;

[0056] Figure 3 This is a flowchart illustrating the data processing method of the accounting system and the accounting system in another embodiment;

[0057] Figure 4 This is a flowchart illustrating the data processing methods of the accounting and bookkeeping systems in a specific application example.

[0058] Figure 5 This is a structural block diagram of the data processing device for the accounting system and the accounting system in one embodiment;

[0059] Figure 6 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0060] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0061] To explain in detail the technical principles and effects of the data processing methods of the accounting and accounting systems in this application, we will first introduce the traditional data processing schemes for accounting and accounting systems.

[0062] In traditional technical solutions, it is assumed that the accounting date for all current systems (accounting system, accounting system, and big data system) is T. The entire data processing process includes the following steps:

[0063] Step 1: Obtain the T-1 day transaction data from the accounting system, specifically including transaction details and interest accrual data for customer overpayment accounts and customer IOU accounts.

[0064] Step 2: The accounting transaction data is sent to the accounting system daily and recorded in the transaction entry summary table of the accounting system. The data is then aggregated and merged into a transaction summary table through the accounting system.

[0065] Step 3: The balance data of the accounting system is stored in the accounting subject balance table according to the date. The accounting subject balance on T-2 day (the accounting system's T-2 balance data) is added to the transaction summary table on T-1 day and merged to generate the accounting subject balance on T-1 day (the accounting system's T-1 balance data).

[0066] Step 4: The daily account balance data for day T-1 in the accounting system is divided into two parts. One part is generated by a batch task based on the daily account-level balance details and stored in a big data system (e.g., Hadoop). The other part is sent to the accounting system through a batch task to summarize the daily balances, generating a summary table of the account balances for day T-1.

[0067] Step 5: The accounting system performs a total reconciliation task. It compares the account balances of the accounting subjects on day T-1 with the summary of the account balances on day T-1. If they are the same, the total reconciliation is complete.

[0068] In practical applications, due to the independence of the accounting and bookkeeping systems in loan systems, data extraction in the past often only involved data from the accounting system. This made it impossible to ensure consistency of the extracted total score through total score verification. Furthermore, as described above regarding traditional technical solutions, these solutions rely on the accounting account balance sheet from day T-2 and the transaction summary sheet from day T-1 to generate the T-1 accounting account balance sheet. Moreover, this account balance cannot be linked to customers in the accounting system, making it impossible to extract data based on customers and guaranteeing total score consistency. To address these shortcomings of traditional technologies, this application uses the T-1 account-level accounting account balance sheet stored in the big data system to generate the T-1 accounting account balance sheet, without relying on the T-2 day accounting account balance sheet, thus ensuring total score consistency.

[0069] Based on the above technical principles, this application provides a data processing method for accounting and bookkeeping systems, which can be specifically applied to, for example... Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be integrated onto server 104 or placed on a cloud or other network server. Server 104 is equipped with an accounting system, a calculation system, and a big data system. Terminal 102 sends a data processing request to server 104, which responds to the request. Server 104 receives a list of customer numbers and extracts the corresponding customer account transaction information from the accounting system based on the customer number list. Based on the customer account transaction information, it generates a T-1 day account balance summary table in the accounting system and extracts a T-1 day account-level accounting subject balance table from the big data system. Based on the customer T-1 day account-level accounting subject balance table, it maps and generates a T-1 day accounting subject balance table in the calculation system. Based on the T-1 day account balance summary table and the T-1 day accounting subject balance table, it determines whether the total balance reconciliation for T-1 day is balanced. The terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, and smart in-vehicle systems. Portable wearable devices can include smartwatches, smart bracelets, and head-mounted devices. The server 104 can be implemented using a standalone server or a server cluster consisting of multiple servers.

[0070] In one embodiment, such as Figure 2As shown, a data processing method for an accounting system and a bookkeeping system is provided, which can be applied to... Figure 1 Taking server 104 as an example, the following steps are included:

[0071] S200: Receives a list of customer IDs and extracts the corresponding customer account transaction information from the accounting system based on the list of customer IDs.

[0072] The customer number list can be received externally via an interface, such as an HTTP interface (HyperTextTransferProtocolInterface). This list is collected with the explicit authorization and permission of the customers (users) and records each customer's number. Based on this customer number list, the server initiates a data extraction request to the accounting system, accurately extracting the customer account transaction information corresponding to these customer numbers. This customer account transaction information includes various customer account transaction information involved in subsequent accounting within the accounting system, such as customer information, overpayment account information, and customer loan agreement tables. This data is atomically linked, with each customer as the unit of data, and associated through the unique identifier of their customer number.

[0073] S400: Based on customer account transaction information, generate a T-1 day account balance summary table in the accounting system and extract the customer's T-1 day account-level accounting subject balance table from the big data system.

[0074] After obtaining customer account transaction information, the server uses this information to perform data aggregation operations in the accounting system. Specifically, the server generates a T-1 day account balance summary table in the accounting system based on the customer account transaction information. For example, it can obtain the customer's corresponding IOU and overpayment account balance information on T-1 day from the accounting system, and then aggregate this data based on specific key fields (such as account balance) to generate a T-1 day account balance summary table.

[0075] Simultaneously, the server extracts the customer's T-1 day account-level accounting balance sheet from the big data system. As the core platform for data storage and management, the big data system stores abundant online anonymized data. This data was collected with customer authorization and has undergone anonymization processing. By extracting the customer's T-1 day account-level accounting balance sheet from this anonymized data stored in the big data system, detailed accounting balance data for each customer account on T-1 day can be obtained. Furthermore, the big data system may specifically include a Hadoop big data system.

[0076] S600: Based on the customer's T-1 day account-level accounting subject balance sheet, generate the T-1 day accounting subject balance sheet in the accounting system.

[0077] Traditional T-1 day accounting balance sheet generation methods rely on the T-2 day accounting balance sheet and the T-1 day transaction summary sheet to generate the T-1 day accounting balance sheet. Furthermore, the account balances cannot be linked to customer numbers in the accounting system, making it impossible to extract data based on customer numbers and ensuring consistency of total scores. In this application, the server performs a mapping generation operation in the accounting system based on the customer's T-1 day account-level accounting balance sheet extracted from the big data system. Specifically, the server uses the customer number (from the customer number list) as a key field to accurately map the account-level accounting balance data in the big data system to the relevant accounts in the accounting system. Through this mapping relationship, the scattered account-level accounting data is aggregated to generate the T-1 day accounting balance sheet. This method does not rely on T-2 day data, but directly generates the balance sheet based on the T-1 day account-level data, and establishes a link between the customer number and the customer in the accounting system, thus ensuring consistency of total scores. This improvement makes the generation of the accounting balance sheet more accurate and timely, and effectively corresponds to the data in the accounting system.

[0078] S800: Based on the summary of account balances on day T-1 and the balance sheet of accounting subjects on day T-1, determine whether the total balance on day T-1 is balanced.

[0079] The server invokes a batch task to reconcile total scores from the accounting system in the test environment. This task reconciles the total scores of the balance data from the accounting system on day T-1 (i.e., the data in the summary accounting balance table on day T-1) with the summary accounting account balance table (the accounting account balance table on day T-1 generated in step S600).

[0080] The specific verification process can be as follows: The server calculates and compares the total balance in the summary of account balances and the total balance in the account subject balance sheet. If the two values ​​are equal, it indicates that the total balance is balanced on day T-1, meaning that the data in the accounting system and the accounting system have maintained consistency and accuracy during extraction and processing. If the two values ​​are not equal, it indicates that the total balance is unbalanced, and the server will trigger the corresponding alarm mechanism to indicate that there may be a problem with the data, so that staff can investigate and correct it in a timely manner.

[0081] The aforementioned data processing method for the accounting and accounting systems involves receiving a list of customer IDs, extracting corresponding customer account transaction information from the accounting system based on the customer ID list, generating a T-1 day account balance summary table in the accounting system based on the customer account transaction information, and extracting a customer T-1 day account-level accounting subject balance table from the big data system, mapping and generating a T-1 day accounting subject balance table in the accounting system based on the customer T-1 day account-level accounting subject balance table, and determining whether the total balance reconciliation on T-1 day is balanced based on the T-1 day account balance summary table and the T-1 day accounting subject balance table. Throughout this process, the generation of the T-1 day account balance summary table in the accounting system and the extraction of the customer T-1 day account-level accounting subject balance table from the big data system based on the same customer account transaction information ensures an inherent correlation between the two tables. Furthermore, by mapping the customer's T-1 day account-level accounting balance sheet from the big data system to the accounting system to generate the T-1 day accounting balance sheet, the connection between the T-1 day accounting balance sheet and the T-1 day summary accounting balance sheet is further strengthened. Due to this close correlation, the consistency and matching of total and partial data can be effectively guaranteed during T-1 day total and partial reconciliation, eliminating reconciliation errors caused by inconsistencies in data sources or processing logic, thereby achieving accurate and reliable processing of data between the accounting system and the accounting system.

[0082] In one embodiment, such as Figure 3 As shown, the process of mapping and generating a T-1 day accounting account balance sheet in the accounting system based on the customer's T-1 day account-level accounting account balance sheet includes:

[0083] S620: Convert the customer's T-1 day account-level accounting balance sheet into an intermediate data format to obtain intermediate data.

[0084] Retrieve customer T-1 day account-level accounting balance sheet data from big data systems (such as Hadoop). Because the data formats in big data systems are complex and unsuitable for direct processing within the accounting system, they need to be converted into an intermediate format, i.e., an intermediate data format, that is easier for the program to process. This intermediate data format typically features a simple structure and ease of parsing and manipulation; for example, it can be common data exchange formats such as JSON or XML, or a custom-defined format, as long as it meets the subsequent processing requirements.

[0085] S640: In the accounting system, create a T-1 day account-level accounting subject balance sheet with corresponding data storage structure according to the intermediate data format, map the intermediate data to the created T-1 day account-level accounting subject balance sheet, and generate the T-1 day accounting subject balance sheet.

[0086] In the accounting system, create a new table with fields identical to those in the T-1 day account-level accounting balance table obtained from the big data system. Creating a new table with fields identical to the original data ensures the accounting system can accurately store the data obtained from the big data system. In program memory, convert the intermediate data to a format suitable for the accounting system's data structure. The accounting system has specific data structure requirements; by performing data format conversion in memory, the data structure can be quickly and efficiently adjusted to match the newly created T-1 day account-level accounting balance table in the accounting system database. Then, map the converted data to the created T-1 day account-level accounting balance table, that is, populate the new table with data according to the corresponding field mappings.

[0087] In one embodiment, the accounting system creates a T-1 day account-level accounting subject balance sheet with a corresponding data storage structure according to the intermediate data format, maps the intermediate data to the created T-1 day account-level accounting subject balance sheet, and generates the T-1 day accounting subject balance sheet by:

[0088] Step 1: In the accounting system, create a T-1 day account-level accounting subject balance table with the corresponding data storage structure according to the intermediate data format, and add a summary status identifier field and initialize the summary status identifier field to the default value; the default value indicates that it has not been summarized.

[0089] At the database operation level of the accounting system, based on the intermediate data format converted from the big data system, a T-1 day account-level accounting subject balance table corresponding to the intermediate data structure is precisely created. This operation requires in-depth analysis of key information such as field types, lengths, and constraints of the intermediate data to ensure that the newly created table structure can completely and accurately accommodate the intermediate data. Simultaneously, a "summary status identifier" field is added to this table. This field is a key identifier used to monitor and manage the data summary status. It is initialized to a default value, which explicitly indicates that the data is in an unsummated state. This initialization operation is significant because it provides a clear starting status marker for subsequent data processing, enabling the system to accurately identify which data has not yet been summarized, thus allowing for targeted execution of subsequent tasks and avoiding duplicate or missed summarizations.

[0090] Step 2: Map the intermediate data to the created T-1 day account-level accounting subject balance sheet.

[0091] In program memory, the intermediate data undergoes further processing, converting it into a format fully compatible with the accounting system's data structure. This conversion process must consider the accounting system's specific data requirements, such as data type compatibility and field order consistency. After the in-memory data conversion is complete, the processed intermediate data is accurately mapped to the T-1 day account-level accounting subject balance table created in step 1. This mapping process ensures that every field value in the intermediate data correctly corresponds to the corresponding field in the accounting system table, guaranteeing data integrity and accuracy. Through this step, the intermediate data is successfully stored in the new table created by the accounting system, providing a data foundation for subsequent summary operations.

[0092] Step 3: Determine the value of the summary status identifier field in the T-1 day account-level accounting subject balance table after mapping.

[0093] After data mapping is complete, the server automatically queries and judges the "Summary Status Identifier" field in the T-1 day account-level accounting subject balance sheet. This operation is a key decision point for subsequent processes. By checking the value of this field, the system can accurately understand the current data summary status. For example, the system reads the specific value of the "Summary Status Identifier" field and compares it with the preset default value indicating that the data has not been summarized, thereby determining whether a summary task needs to be executed. This judgment process is fast and accurate, providing a reliable basis for subsequent process control.

[0094] Step 4: If the field value indicates that it has not been summarized, then perform a summary task on the account-level accounting subject balance sheet of day T-1 to generate the accounting subject balance sheet of day T-1.

[0095] When the "Summary Status Identifier" field indicates that data has not been summarized, the server initiates a summary task. The summary task performs comprehensive statistics and calculations on the data in the T-1 day account-level accounting balance sheet, integrating and summarizing the scattered data according to the accounting system's business rules and algorithms. For example, it may merge different accounting items for the same account, or perform summation, averaging, or other operations on data within a specific time period. By executing the summary task, the server ultimately generates a T-1 day accounting balance sheet that meets business requirements.

[0096] In one embodiment, mapping and generating a T-1 day accounting account balance sheet in the accounting system based on the customer's T-1 day account-level accounting account balance sheet includes:

[0097] Step 1: Convert the customer's T-1 day account-level accounting balance sheet into a data object HiveAccountBalanceD0 in the JVM using the HiveJDBC driver.

[0098] In the initial stage of data processing, due to the difference between the data format stored in the Hadoop big data system and the format required for subsequent processing in the JVM (Java Virtual Machine) environment, the HiveJDBC driver is needed to convert the data format. The HiveJDBC driver acts as a bridge connecting the Hadoop big data system and the JVM environment. It can parse the T-1 day account-level accounting balance sheet data stored in Hadoop and convert this data into a JVM-recognizable data object, HiveAccountBalanceD0, according to specific rules. This data object has a specific data structure and field definitions, capable of completely and accurately carrying the information of the original data, providing a unified and standardized data foundation for subsequent data processing in the JVM environment.

[0099] Step 2: Create an account-level accounting subject balance table in the accounting system that is consistent with the fields of the customer's T-1 day account-level accounting subject balance table, and add a summary status identifier field to the table.

[0100] To store and process data transferred from the big data system within the accounting system, an account-level accounting subject balance table needs to be created in the accounting system database, with the same field structure as the data object HiveAccountBalanceD0 in step 1. This operation requires precise analysis of key information such as the field types, lengths, and constraints of HiveAccountBalanceD0 to ensure that the newly created table structure can completely and accurately accommodate this data. Simultaneously, a summary status identifier field is added to this table. This field records the status information of the data during the summary process, such as whether the summary has been completed or whether any anomalies occurred during the summary process. Adding this field facilitates the tracking and management of the data status, providing convenience for subsequent data processing and querying.

[0101] Step 3: Map the account-level accounting subject balance sheet to the data object AccountBalanceD0 in the JVM using Spring Data JPA.

[0102] Spring Data JPA is a framework for simplifying database access. It can automatically generate corresponding Java data objects based on the structure of database tables. In this step, Spring Data JPA is used to map the account-level accounting subject balance table created in the accounting system database in step 2 to the data object AccountBalanceD0 in the JVM. This mapping process establishes the correspondence between database tables and Java objects, enabling the program to manipulate data in the database in an object-oriented manner. Through the mapping of Spring Data JPA, the AccountBalanceD0 data object has the same field structure as the account-level accounting subject balance table, which facilitates data processing and transfer in the JVM environment.

[0103] Step 4: Use javamapstruct to map and convert data object HiveAccountBalanceD0 to data object AccountBalanceD0, and assign the summary status identifier field to the default value, which indicates that it has not been summarized.

[0104] JavaMapStructure is an annotation-based JavaBean mapping tool that generates mapping code at compile time, enabling automatic mapping and conversion of fields between different Java objects. In this step, JavaMapStructure is used to map and convert the HiveAccountBalanceD0 data object obtained in step 1 to the AccountBalanceD0 data object obtained in step 3. During the mapping process, JavaMapStructure automatically copies the field values ​​from HiveAccountBalanceD0 to the corresponding fields in AccountBalanceD0 based on the field definitions of the two data objects. Simultaneously, the summary status flag field in AccountBalanceD0 is assigned a default value, which explicitly indicates that the data is in an unsummarized state.

[0105] Step 5: Write the final data object AccountBalanceD0 to the account-level accounting subject balance table to generate the T-1 day accounting subject balance table.

[0106] After mapping and transforming the data objects and assigning values ​​to the summary status identifier field, the final AccountBalanceD0 data object is written into the account-level accounting subject balance table created in step 2. This write operation is implemented through corresponding database operation statements, inserting the data in AccountBalanceD0 row by row into the accounting system database table. After the data write is completed, the data in this table is the generated T-1 day accounting subject balance table, which contains processed and transformed customer account transaction information, meeting the subsequent data processing and analysis needs of the accounting system.

[0107] In one embodiment, generating a T-1 day account balance summary table in the accounting system based on customer account transaction information includes:

[0108] Step 1: Based on the customer's account transaction information, extract the relevant transaction tables for customer day T from the accounting system and associate them with the account set number.

[0109] In the accounting system, the first step is to extract data tables related to the customer's transactions on day T. This step involves retrieving a table from the database containing all of the customer's transaction records on day T. To associate these transaction records with specific account sets, the extracted transaction-related tables need to be linked to the account set number. The account set number is a unique identifier used to distinguish different account sets. By associating with the account set number, it can be ensured that subsequent data processing is targeted at specific account sets, guaranteeing data accuracy and relevance.

[0110] Step 2: Extract the transaction entry data for day T from the accounting system by matching the account set number.

[0111] After linking the transaction-related tables to the account set numbers in Step 1, these account set numbers are used as key indexes to extract the corresponding transaction entry data for day T from the accounting system. The accounting system stores detailed transaction entry information, and the account set number allows for precise location of transaction entry data related to a specific account set. This step aims to obtain key transaction data for subsequent balance summary calculations. This transaction entry data records the customer's various transactions on day T in detail and is one of the important bases for calculating the account balance on day T-1.

[0112] Step 3: Extract the customer's account balance table for day T-1 from the account system.

[0113] The accounting system needs to extract customer account balance tables for day T-1. This step directly retrieves data tables related to customer account balances for day T-1 from the accounting system's database. These tables contain balance information for each customer's account at the end of day T-1, and are the basic data for calculating the current (when summarizing on day T-1) accounting balance.

[0114] Step 4: Based on the transaction entry data of day T and the customer's account balance related table on day T-1, execute the batch task of summarizing the balance on day T-1 to generate the account balance summary table on day T-1.

[0115] After obtaining the transaction entry data for day T and the account balance related table for day T-1, a batch task for summarizing the balances for day T-1 is executed. This task integrates and calculates the transaction information in the transaction entry data for day T with the initial balance data in the account balance related table for day T-1. Specifically, the account balance for day T-1 is adjusted accordingly based on the type of transaction (such as income, expense, etc.). For example, for income transactions that occurred on day T, the amount is added to the corresponding account balance for day T-1; for expense transactions, the corresponding amount is subtracted from the account balance for day T-1.

[0116] In one embodiment, after determining whether the total balance on T-1 is balanced based on the T-1 day account balance summary table and the T-1 day accounting account balance table, the method further includes:

[0117] Step 1: If the total scores are unbalanced on day T-1, the extracted customer account transaction information is deemed abnormal.

[0118] When a reconciliation of the general ledger balance and the subsidiary ledger (accounting account) balance is performed based on the T-1 day account balance summary and the result is unbalanced, the server will directly determine that the extracted customer account transaction information is abnormal. This determination process is based on the basic logic of accounting processing. General ledger reconciliation is an important means of verifying the accuracy of accounting data. Under normal circumstances, the general ledger balance and the subsidiary ledger (accounting account) balance should maintain a balanced relationship. Once an imbalance occurs, it means that errors or omissions may have occurred in the data extraction, processing, or recording process. As the basic data source for the entire accounting data processing, customer account transaction information is identified as abnormal at this time.

[0119] Step 2: Check the extracted customer account transaction information.

[0120] After determining that the extracted customer account transaction information is abnormal, a comprehensive review of this information is required. This review involves examining each stage of the data extraction process, including but not limited to verifying the accuracy of the data source, the completeness of the extracted fields, and identifying any errors in the data transformation and mapping processes. After the review is completed, the data extraction is repeated to begin a new round of accounting.

[0121] To illustrate the technical solution of the data processing method of the accounting and bookkeeping system in this application, specific application examples will be used below, combined with... Figure 4 The following is a detailed description. In one specific application example, the data processing method of the accounting system and the accounting system in this application includes the following steps:

[0122] S01: The customer number list is transmitted via the HTTP interface. This is the starting point of the entire processing flow. With user authorization, the external system transmits the list of customer numbers to be processed to the server via the HTTP interface.

[0123] S02: With explicit user authorization, the accounting system extracts corresponding customer information, overpayment account information, and customer loan receipt related tables. Based on the received list of customer numbers, the accounting system extracts the corresponding basic customer information, overpayment account details, and customer loan receipt related data tables from its own database.

[0124] S03: The accounting system extracts the customer's transaction-related tables for day T and associates them with the account set number. The accounting system further extracts the customer's transaction-related data tables for day T from the database, and associates this transaction data with the corresponding account set number so that subsequent data processing and analysis can be performed based on the account set.

[0125] S04: Extract transaction entry data for day T from the accounting system using the account set number. Using the account set number associated in step S03 as an index, extract the transaction entry data for day T corresponding to these account set numbers from the accounting system. This data records the details of the customer's various transactions on day T.

[0126] S05: The accounting system extracts the customer's account balance data for day T-1. The accounting system then extracts the customer's account balance data for day T-1 from its own database to provide basic data for subsequent calculation of the account balance summary for day T-1.

[0127] S06: Execute the batch task of summarizing the balance on day T-1. The server integrates the transaction entry data of day T obtained in step S04 with the data of the account balance related table of day T-1 obtained in step S05, and performs the calculation task of summarizing the balance on day T-1 in batches according to the predetermined calculation rules.

[0128] S07: Generate a summary table of account balances for day T-1. After the calculation in step S06, the system generates a summary table of account balances for day T-1, which summarizes the customer's account balance after transaction adjustments on day T-1.

[0129] S08: Simultaneously with the processing in S03, the big data system extracts the customer's account-level accounting balance sheet for day T-1. The big data system extracts the customer's accounting balance sheet, calculated by account level, for day T-1 from its own data storage.

[0130] S09: Generate a MySQL T-1 day account-level accounting subject balance table, initialize the "whether it has been summarized" field to "no", and execute the summary task. Generate the corresponding T-1 day account-level accounting subject balance table in the MySQL database, initialize the "whether it has been summarized" field to "no", and then execute the summary task to summarize the relevant data.

[0131] S10: Determine if data has been summarized. The server checks the "Whether data has been summarized" field in the MySQL T-1 day account-level accounting subject balance table to determine if the data summary operation has been completed. If data has been summarized, proceed to S11; otherwise, proceed to S12.

[0132] S11: If the data has been summarized, the process continues to proceed to S13.

[0133] S12: If not yet summarized, summarize and update. The server summarizes the data and updates the "Summarized or not?" field to "Yes", then the process proceeds to S13.

[0134] S13: Generate the T-1 day accounting account balance sheet. Based on the previous processing results, generate the final T-1 day accounting account balance sheet.

[0135] S14: Determine if the total balance of accounts on day T-1 is balanced. Reconcile the total balance summary table of accounts on day T-1 generated in step S07 with the accounting subject balance table of day T-1 generated in step S13 to determine if they are balanced. If the data is abnormal, check the data and re-sample the data; subsequent related steps may need to be re-executed. If balanced, proceed to S15.

[0136] S15: Execute day T transactions and subsequent tests. Once the total score is reconciled and balanced on day T-1, the system can normally execute day T transaction processing and subsequent related tests, and the entire processing flow ends.

[0137] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0138] Based on the same inventive concept, this application also provides an accounting system and accounting system data processing apparatus for implementing the above-mentioned accounting system and accounting system data processing method. The solution provided by this apparatus is similar to the implementation scheme described in the above-described method. Therefore, the specific limitations in one or more embodiments of the accounting system and accounting system data processing apparatus provided below can be found in the limitations of the accounting system and accounting system data processing method described above, and will not be repeated here.

[0139] In one embodiment, such as Figure 5 As shown, a data processing device for an accounting system and a bookkeeping system is provided, comprising:

[0140] The data acquisition module 200 is used to receive a list of customer numbers and extract corresponding customer account transaction information from the accounting system based on the list of customer numbers.

[0141] The data extraction module 400 is used to generate a T-1 day account balance summary table in the accounting system based on customer account transaction information and to extract the customer's T-1 day account-level accounting subject balance table from the big data system.

[0142] The data mapping module 600 is used to map and generate a T-1 day accounting account balance sheet in the accounting system based on the customer's T-1 day account-level accounting account balance sheet;

[0143] The verification module 800 is used to determine whether the total balance is balanced on T-1 based on the T-1 day account balance summary table and the T-1 day accounting account balance table.

[0144] In one embodiment, the data mapping module 600 is further configured to convert the customer's T-1 day account-level accounting subject balance sheet into an intermediate data format to obtain intermediate data; create a T-1 day account-level accounting subject balance sheet with a corresponding data storage structure in the accounting system according to the intermediate data format; map the intermediate data to the created T-1 day account-level accounting subject balance sheet to generate the T-1 day accounting subject balance sheet.

[0145] In one embodiment, the data mapping module 600 is further configured to create a T-1 day account-level accounting subject balance table with a corresponding data storage structure in the accounting system according to the intermediate data format, and add a summary status identifier field and initialize the summary status identifier field to a default value; the default value indicates that the data has not been summarized; map the intermediate data to the created T-1 day account-level accounting subject balance table; determine the field value of the summary status identifier field in the mapped T-1 day account-level accounting subject balance table; if the field value indicates that the data has not been summarized, then perform a summary task on the T-1 day account-level accounting subject balance table to generate the T-1 day accounting subject balance table.

[0146] In one embodiment, the data mapping module 600 is further configured to convert the customer's T-1 day account-level accounting balance table into a data object HiveAccountBalanceD0 in the JVM via a HiveJDBC driver; create an account-level accounting balance table in the accounting system with fields consistent with the customer's T-1 day account-level accounting balance table, and add a summary status identifier field to the table; map the account-level accounting balance table to the data object AccountBalanceD0 in the JVM via SpringDataJPA; perform mapping and conversion from data object HiveAccountBalanceD0 to data object AccountBalanceD0 via javamapstruct, and assign a default value to the summary status identifier field, the default value indicating that it is not summarized; and write the final data object AccountBalanceD0 to the account-level accounting balance table to generate the T-1 day accounting balance table.

[0147] In one embodiment, the data extraction module 400 is further configured to extract customer transaction-related tables for day T from the accounting system based on customer account transaction information and associate them with the account set number; extract transaction entry data for day T from the accounting system corresponding to the account set number; extract customer account balance-related tables for day T-1 from the account system; and execute a batch task to summarize the balance for day T-1 based on the transaction entry data for day T and the customer account balance-related tables for day T-1 to generate a summary table of accounting balances for day T-1.

[0148] In one embodiment, the verification module 800 is also used to determine that the extracted customer account transaction information is abnormal when the total score reconciliation on day T-1 is unbalanced; and to check the extracted customer account transaction information.

[0149] Each module in the aforementioned accounting and data processing device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the computer device's memory as software, so that the processor can call and execute the corresponding operations of each module.

[0150] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 6As shown, the computer device includes a processor, memory, and a network interface connected via a system bus. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores preset data. The network interface communicates with external terminals via a network connection. When the computer program is executed by the processor, it implements a data processing method for an accounting and auditing system.

[0151] Those skilled in the art will understand that Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0152] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-described accounting and auditing system data processing method.

[0153] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the above-described accounting and auditing system data processing method.

[0154] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the above-described accounting and auditing system data processing method.

[0155] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0156] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0157] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0158] The above embodiments are merely illustrative of several implementation methods of this application, and their descriptions are relatively specific and detailed. However, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A data processing method for an accounting system and a bookkeeping system, characterized in that, The method includes: Receive a list of customer numbers, and extract the corresponding customer account transaction information from the accounting system based on the list of customer numbers; Based on the customer account transaction information, a summary table of account balances for day T-1 is generated in the accounting system, and a balance table of account-level accounting subjects for day T-1 is extracted from the big data system. Based on the customer's T-1 day account-level accounting subject balance sheet, the T-1 day accounting subject balance sheet is generated in the accounting system. Based on the summary of account balances on day T-1 and the balance sheet of accounting subjects on day T-1, determine whether the total balance on day T-1 is balanced.

2. The method according to claim 1, characterized in that, The step of mapping and generating the T-1 day accounting account balance sheet in the accounting system based on the customer's T-1 day account-level accounting account balance sheet includes: The customer's T-1 day account-level accounting balance sheet is converted into an intermediate data format to obtain intermediate data; In the accounting system, a T-1 day account-level accounting subject balance table with a corresponding data storage structure is created according to the intermediate data format. The intermediate data is then mapped to the created T-1 day account-level accounting subject balance table to generate the T-1 day accounting subject balance table.

3. The method according to claim 2, characterized in that, The step of creating a T-1 day account-level accounting subject balance table in the accounting system according to the intermediate data format, mapping the intermediate data to the created T-1 day account-level accounting subject balance table, and generating the T-1 day accounting subject balance table includes: In the accounting system, a T-1 day account-level accounting subject balance table with a corresponding data storage structure is created according to the intermediate data format, and a summary status identifier field is added and initialized to the default value; the default value indicates that it has not been summarized. Map the intermediate data to the created T-1 day account-level accounting subject balance sheet; Determine the value of the summary status identifier field in the account-level accounting subject balance sheet of the mapped date (T-1 day); If the field value indicates that the data has not been summarized, then a summary task is performed on the account-level accounting subject balance sheet of day T-1 to generate the accounting subject balance sheet of day T-1.

4. The method according to claim 1, characterized in that, The step of mapping and generating the T-1 day accounting account balance sheet in the accounting system based on the customer's T-1 day account-level accounting account balance sheet includes: The customer's T-1 day account-level accounting balance sheet is converted into a data object HiveAccountBalanceD0 in the JVM using the HiveJDBC driver. Create an account-level accounting account balance table in the accounting system that is consistent with the fields of the customer's T-1 day account-level accounting account balance table, and add a summary status identifier field to the table; The account-level accounting subject balance sheet is mapped to the data object AccountBalanceD0 in the JVM using Spring Data JPA; The mapping and conversion from data object HiveAccountBalanceD0 to data object AccountBalanceD0 is performed using javamapstruct, and the summary status identifier field is assigned a default value, which indicates that it has not been summarized; The final data object AccountBalanceD0 is written to the account-level accounting subject balance table to generate the T-1 day accounting subject balance table.

5. The method according to claim 1, characterized in that, Based on the aforementioned customer account transaction information, the accounting system generates a T-1 day account balance summary table, including: Based on the customer account transaction information, extract the customer's transaction-related table for day T from the accounting system and associate it with the account set number; The transaction entry data for day T in the accounting system is extracted using the account set number; Extract customer account balance data for day T-1 from the account system; Based on the transaction entry data for day T and the customer's account balance related table for day T-1, execute a batch task to summarize the balance for day T-1 and generate a summary table of account balances for day T-1.

6. The method according to claim 1, characterized in that, After determining whether the total balance on T-1 is balanced based on the summary of account balances on T-1 day and the account balance sheet on T-1 day, the process further includes: If the total score on day T-1 is unbalanced, the extracted customer account transaction information is determined to be abnormal. The extracted customer account transaction information is then examined.

7. A data processing device for an accounting system and a bookkeeping system, characterized in that, The device includes: The data acquisition module is used to receive a list of customer numbers and extract corresponding customer account transaction information from the accounting system based on the list of customer numbers. The data extraction module is used to generate a summary table of account balances for day T-1 in the accounting system and extract the account-level accounting subject balance table for day T-1 from the big data system based on the customer account transaction information. The data mapping module is used to map and generate a T-1 day accounting account balance sheet in the accounting system based on the customer's T-1 day account-level accounting account balance sheet; The verification module is used to determine whether the total balance on T-1 is balanced based on the summary table of account balances on T-1 and the accounting account balance table on T-1.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

Images