A method and apparatus for fast data rollback

Abstract

The application discloses a method and device for quickly tracing data, which constructs a data source point set, and quickly queries the data source point set based on user identity card data and a reporting date, so that quick response of data query is realized, and self-query of users is realized, and human resources are saved.

Description

Technical Field

[0001] This invention relates to the field of data processing, and more specifically to a method and apparatus for rapidly backtracking data. Background Technology

[0002] In the financial sector, revolving loan transactions can involve anywhere from dozens to hundreds of loan agreements. To prevent excessively long credit reports, credit reporting agencies use specific consolidation algorithms to merge information. These algorithms combine outstanding loans from the current month with those settled within the past month. Due to the time lag in credit report updates, customers often need to obtain a settlement certificate from the bank. For consolidated loan amounts, this certificate must match the amount on the credit report, requiring bank approval before the certificate can be issued. For example, if loan A1 is settled on date B1, the credit information won't be updated in the system until date B1+B2, necessitating a settlement certificate from the bank.

[0003] In existing technologies, loan information is often stored in ORC (Optimized Row Columnar) tables on a big data TDH platform. Based on the credit report's cutoff date, SQL query conditions are generated in reverse using a "merging algorithm." The generated SQL statement is then executed on the TDH platform to retrieve the corresponding loan information before approval. However, this existing technology is highly specialized, requiring specialized personnel to operate, leading to wasted manpower and data response delays. Summary of the Invention

[0004] The purpose of this application is to provide a method and apparatus for rapid data backtracking, which solves the problems existing in the prior art.

[0005] This invention is achieved through the following technical solution:

[0006] Firstly, this application provides a method for rapidly backtracking data, including:

[0007] Obtain the first loan information to be processed, which includes loan business data and loan amount data;

[0008] A primary key is constructed based on the loan business data, and a data source point set is constructed based on the primary key and the loan amount data;

[0009] Identify the loan business data to be queried, and based on the loan business data to be queried, query all primary keys to find the data source point set corresponding to the loan business data to be queried, and complete the rapid backtracking of data.

[0010] In one possible implementation, obtaining the first loan information to be processed includes:

[0011] The user's ID card data, reporting date, and loan receipt number are obtained from the data warehouse of the financial system, and loan business data are composed of the user's ID card data, reporting date, and loan receipt number;

[0012] Obtain the loan amount, loan disbursement date, and settlement date from the data warehouse of the financial system, and combine the loan amount, loan disbursement date, and settlement date to form the loan amount data;

[0013] Based on loan business data and loan amount data, the first lending information is obtained, wherein the loan business data and the loan amount data correspond one-to-one;

[0014] By traversing all lending transactions in the data warehouse, multiple first-level lending information entries are obtained.

[0015] In one possible implementation, constructing a primary key based on the loan business data includes:

[0016] The loan business data are arranged in chronological order of the reporting date, and a counter T=1 is set; each reporting date corresponds to one or more loan business data.

[0017] Extract at least one loan business data corresponding to the Tth reporting date, and use the extracted at least one loan business data as at least one primary key of a data source point set;

[0018] Determine if the value of counter T is greater than or equal to the number of reported dates. If yes, end the process; otherwise, increment the counter value and obtain the primary key corresponding to the new data source point set. Continue this process until the value of counter T is greater than or equal to the number of reported dates, thus obtaining the primary keys corresponding to several data source point sets.

[0019] In one possible implementation, a data source point set is constructed based on the primary key and loan amount data, including:

[0020] Based on the primary keys corresponding to several data source point sets, determine the loan amount data corresponding to each data source point set;

[0021] By associating the determined loan amount data with the primary key, a data source point set is obtained.

[0022] In one possible implementation, the loan business data to be queried is determined, and based on the loan business data to be queried, a query is performed on all primary keys to find the data source point set corresponding to the loan business data to be queried, including:

[0023] Determine the ID card data to be queried and the reporting date;

[0024] Based on the ID card data to be queried and the reporting date, query all primary keys to obtain the target data source set.

[0025] In one possible implementation, after constructing the data source point set based on the primary key and loan amount data, the method further includes: validating the data source point set and marking the data source point sets that fail the validation as abnormal.

[0026] In one possible implementation, validating the data source point set includes:

[0027] Determine whether the total loan amount in the data source point set matches the credit amount in the credit report. If they match, the corresponding data source point set is considered valid; otherwise, the corresponding data source point set is considered invalid.

[0028] In one possible implementation, determining whether the total loan amount of the data source set matches the credit amount reported in the credit report includes:

[0029] Determine the reporting date corresponding to the data source point set to obtain the target reporting date;

[0030] Determine the total loan amount corresponding to the data source point set, and determine the credit amount corresponding to the target reporting date in the credit report;

[0031] Determine whether the total loan amount is the same as the credit score. If so, the corresponding data source set is deemed valid; otherwise, the corresponding data source set is deemed invalid.

[0032] In one possible implementation, after finding the data source point set corresponding to the loan business data to be queried, the method further includes: determining whether the data source point set corresponding to the loan business data to be queried is marked; if so, returning an error message to the user; otherwise, transmitting the data source point set to the user.

[0033] Secondly, this application provides a device for rapidly backtracking data, including an information acquisition module, a source point set construction module, and a data query module;

[0034] The information acquisition module is used to acquire first lending information to be processed, the first lending information including loan business data and loan amount data;

[0035] The source point set construction module is used to construct a primary key based on the loan business data, and to construct a data source point set based on the primary key and the loan amount data.

[0036] The data query module is used to determine the loan business data to be queried, and based on the loan business data to be queried, to query all primary keys, find the data source point set corresponding to the loan business data to be queried, and complete the rapid backtracking of data.

[0037] This application provides a method and apparatus for rapid data backtracking. By constructing a data source point set and using user ID data and reporting dates as a basis, the data source point set can be quickly queried, achieving a rapid response to data queries and enabling users to query independently, thus saving human resources. Attached Figure Description

[0038] To more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0039] In the picture:

[0040] Figure 1 A flowchart illustrating a method for rapidly backtracking data, as provided in this application embodiment;

[0041] Figure 2 This is a schematic diagram of a device for rapidly backtracking data, provided in an embodiment of this application.

[0042] Figure 3 This is a schematic diagram of the structure of a device for rapid data retrieval provided in an embodiment of this application.

[0043] The attached diagram shows the markings and corresponding component names:

[0044] 21-Information acquisition module, 22-Source point set construction module, 23-Data query module, 31-Memory, 32-Processor, 33-Bus. Detailed Implementation

[0045] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments and accompanying drawings. The illustrative embodiments and descriptions of the present invention are only used to explain the present invention and are not intended to limit the present invention.

[0046] Example 1

[0047] like Figure 1 As shown, this application provides a method for quickly backtracking data, including:

[0048] S11. Obtain the first loan information to be processed, which includes loan business data and loan amount data.

[0049] In this embodiment, loan transaction data may include the user's ID card data reporting date and loan receipt number, while loan amount data may include the loan receipt amount, payment date, and settlement date. Each loan transaction corresponds to a first loan information record, meaning each loan transaction corresponds to a set of loan transaction data and loan amount data.

[0050] S12. Construct a primary key rowkey based on the loan business data, and construct a data source point set based on the primary key rowkey and the loan amount data.

[0051] Using loan data as the primary key (rowkey) allows for quick querying of user loan information, enabling rapid generation of settlement certificates and improving the timeliness of data backtracking.

[0052] S13. Determine the loan business data to be queried, and based on the loan business data to be queried, query all primary key rowkeys to find the data source point set corresponding to the loan business data to be queried, and complete the rapid backtracking of data.

[0053] Optionally, the credit reporting business number, credit amount, and credit reporting expiration date can be extracted from the user's credit report. The credit reporting expiration date should be the same as the settlement date of the user's loan business.

[0054] In one possible implementation, obtaining the first loan information to be processed includes:

[0055] The system retrieves user ID data, reporting date, and loan receipt number from the financial system's data warehouse, and uses these data to create loan business data.

[0056] The loan amount, disbursement date, and settlement date are obtained from the data warehouse of the financial system, and the loan amount data is composed of the loan amount, disbursement date, and settlement date.

[0057] The reporting date indicates the time when the financial system reports the information to the credit reporting system. Based on the reporting date, the total amount of loans taken out by the user before the reporting date can be determined. Then, by comparing this amount with the credit amount reported to the credit reporting system on the reporting date, the accuracy of the data can be determined.

[0058] Based on loan business data and loan amount data, the first lending information is obtained, with a one-to-one correspondence between the loan business data and the loan amount data.

[0059] By traversing all lending transactions in the data warehouse, multiple first lending information entries are obtained. This transforms the data in the data warehouse into a data source point set, which facilitates querying and improves the efficiency of generating settlement certificates.

[0060] In one possible implementation, a primary key rowkey is constructed based on loan business data, including:

[0061] The loan transaction data is arranged in chronological order of the reporting date, and a counter T=1 is set. Each reporting date corresponds to one or more loan transaction data.

[0062] Retrieve at least one loan business data corresponding to the Tth reporting date, and use the retrieved at least one loan business data as at least one primary key rowkey of a data source point set.

[0063] Determine if the value of counter T is greater than or equal to the number of reported dates. If yes, end the process; otherwise, increment the counter value and obtain the primary key rowkey corresponding to the new data source point set. Continue this process until the value of counter T is greater than or equal to the number of reported dates, thus obtaining the primary key rowkey corresponding to several data source point sets.

[0064] In one possible implementation, a data source point set is constructed based on the primary key rowkey and loan amount data, including:

[0065] Based on the primary key rowkey corresponding to several data source point sets, determine the loan amount data corresponding to each data source point set.

[0066] The determined loan amount data is associated with the primary key rowkey to obtain the data source point set, which can be shown in Table 1.

[0067] Table 1 Example of data source point sets

[0068]

[0069] As can be seen, each primary key rowkey, composed of user ID data, reporting date, and loan number, is unique. However, the same customer may have multiple different loan transactions before a certain reporting date. Therefore, by querying all loan transactions before a specific reporting date, it is possible to determine whether the user has settled their loans. For example, if a user needs to query loan transactions before April 11, 2022, they can use their ID number and the reporting date (20220411) to query whether the loan transactions before that reporting date have been settled. A value of 0 in the table indicates that the loan transactions have not yet been settled, while a specific settlement date indicates that the loan transactions have been settled.

[0070] Once the primary key rowkey and data source point set are obtained, they are inserted into the HBase table. Due to the characteristics of HBase tables, the inserted data can be queried based on the rowkey, achieving a millisecond-level response time.

[0071] The data in the data source set is updated in real time based on the data in the financial system's data warehouse. For example, if a loan with IOU number A1 was not settled when reported to the credit reporting system on May 11, 2022, and was settled on May 13, 2022, the settlement date for A1 in the financial system's data warehouse should be updated to May 13, 2022. Then, by pulling data from the data warehouse in real time, the data source set is updated to ensure the accuracy of the data in the data source set, facilitating the issuance of settlement certificates for users. If a user wants to apply for a new loan on May 14, 2022, due to the delay in the credit reporting system, the data reported to the system on May 11, 2022, is still incomplete, which may affect their application for a new loan. Therefore, a settlement certificate is needed. By pulling the data source set corresponding to May 11, 2022, a certificate indicating that the loan has been settled can be issued.

[0072] In one possible implementation, the loan business data to be queried is determined, and based on the loan business data to be queried, all primary key rowkeys are queried to find the data source point set corresponding to the loan business data to be queried, including:

[0073] Determine the ID card data to be queried and the reporting date.

[0074] Based on the ID card data to be queried and the reporting date, query all primary key rowkeys to obtain the target data source set.

[0075] Alternatively, you can use only the user's ID card data to query the data source set, thereby retrieving all the data reported by that user.

[0076] In one possible implementation, after constructing the data source point set based on the primary key rowkey and loan amount data, the method further includes: validating the data source point set and marking the data source point set that fails the validation as an anomaly.

[0077] In one possible implementation, validating the data source point set includes:

[0078] Determine whether the total loan amount in the data source point set matches the credit amount in the credit report. If they match, the corresponding data source point set is considered valid; otherwise, the corresponding data source point set is considered invalid.

[0079] In one possible implementation, determining whether the total loan amount of the data source set matches the credit amount reported in the credit report includes:

[0080] Determine the reporting date corresponding to the data source point set to obtain the target reporting date;

[0081] Determine the total loan amount corresponding to the data source point set, and determine the credit amount corresponding to the target reporting date in the credit report;

[0082] Determine whether the total loan amount is the same as the credit score. If so, the corresponding data source set is deemed valid; otherwise, the corresponding data source set is deemed invalid.

[0083] As shown in Table 1, the data reported to the credit reporting system each month includes outstanding loans for the current month and those outstanding for the past month. Therefore, based on the reporting date, the data reported to the credit reporting system corresponding to that reporting date can be retrieved. The loan data corresponding to that reporting date can be extracted from the financial system's data warehouse, and the total loan amount can be determined based on the loan data. By comparing the total loan amount with the credit amount on the user's credit report, it can be determined whether the data source set is accurate and valid.

[0084] In one possible implementation, after finding the data source point set corresponding to the loan business data to be queried, the method further includes: determining whether the data source point set corresponding to the loan business data to be queried is marked; if so, returning an error message to the user; otherwise, transmitting the data source point set to the user.

[0085] Example 2

[0086] like Figure 2 As shown, this application provides a device for rapidly backtracking data, including an information acquisition module 21, a source point set construction module 22, and a data query module 23.

[0087] The information acquisition module 21 is used to acquire the first loan information to be processed, which includes loan business data and loan amount data.

[0088] The source set construction module 22 is used to construct a primary key rowkey based on loan business data, and to construct a data source set based on the primary key rowkey and loan amount data.

[0089] The data query module 23 is used to determine the loan business data to be queried, and based on the loan business data to be queried, to query all primary key rowkeys to find the data source point set corresponding to the loan business data to be queried, and to complete the rapid backtracking of data.

[0090] The device for rapid data backtracking provided in this embodiment can execute the technical solution described in Embodiment 1. Its implementation principle and beneficial effects are similar, and will not be repeated here.

[0091] Example 3

[0092] like Figure 3 As shown, this embodiment provides a device for fast data retrieval, including a memory 31 and a processor 32, which are interconnected via a bus 33.

[0093] Memory 31 stores computer-executed instructions.

[0094] The processor 32 executes computer execution instructions stored in the memory, causing the processor to perform a method for fast data backtracking as described in Embodiment 1.

[0095] For specific examples, memory may include, but is not limited to, random access memory (RAM), read-only memory (ROM), flash memory, first-in-first-out (FIFO) memory, and / or first-in-last-out (FILO) memory, etc.; specifically, processor may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor may be implemented using at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), or PLA (Programmable Logic Array). Furthermore, the processor may include a main processor and coprocessors. The main processor, also known as the CPU (Central Processing Unit), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state.

[0096] In some embodiments, the processor may integrate a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the screen. For example, the processor may not be limited to microprocessors of the STM32F105 series, reduced instruction set computer (RISC) microprocessors, x86 architecture processors, or processors with integrated neural network processing units (NPUs). The transceiver may be, but is not limited to, a Wi-Fi transceiver, a Bluetooth transceiver, a General Packet Radio Service (GPRS) transceiver, a ZigBee (a low-power LAN protocol based on the IEEE 802.15.4 standard) transceiver, a 3G transceiver, a 4G transceiver, and / or a 5G transceiver. Furthermore, the device may also include, but is not limited to, a power module, a display screen, and other necessary components.

[0097] Example 4

[0098] This embodiment provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement a method for fast data backtracking as described in Embodiment 1.

[0099] Example 5

[0100] This application embodiment may also provide a computer program product, including a computer program that, when executed by a processor, implements a method for fast data backtracking as described in Embodiment 1.

[0101] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for rapidly backtracking data, characterized in that, include: Obtain the first loan information to be processed, which includes loan business data and loan amount data; A primary key is constructed based on the loan business data, and a data source point set is constructed based on the primary key and the loan amount data; Identify the loan business data to be queried, and based on the loan business data to be queried, query all primary keys to find the data source point set corresponding to the loan business data to be queried, and complete the rapid backtracking of data. Obtain the first loan information to be processed, including: The user's ID card data, reporting date, and loan receipt number are obtained from the data warehouse of the financial system, and loan business data are composed of the user's ID card data, reporting date, and loan receipt number; Obtain the loan amount, loan disbursement date, and settlement date from the data warehouse of the financial system, and combine the loan amount, loan disbursement date, and settlement date to form the loan amount data; Based on loan business data and loan amount data, the first lending information is obtained, wherein the loan business data and the loan amount data correspond one-to-one; Traverse all lending transactions in the data warehouse to obtain multiple first-level lending information; Construct a primary key based on the loan business data, including: The loan business data are arranged in chronological order of the reporting date, and a counter T=1 is set; each reporting date corresponds to one or more loan business data. Extract at least one loan business data corresponding to the Tth reporting date, and use the extracted at least one loan business data as at least one primary key of a data source point set; Determine if the value of counter T is greater than or equal to the number of reported dates. If yes, end the process; otherwise, increment the counter value and obtain the primary key corresponding to the new data source point set. Continue this process until the value of counter T is greater than or equal to the number of reported dates, thus obtaining the primary keys corresponding to several data source point sets. Based on the primary key and loan amount data, a data source point set is constructed, including: Based on the primary keys corresponding to several data source point sets, determine the loan amount data corresponding to each data source point set; By associating the determined loan amount data with the primary key, a data source point set is obtained; Identify the loan business data to be queried, and based on this data, query all primary keys to find the data source point set corresponding to the loan business data to be queried, including: Determine the ID card data to be queried and the reporting date; Based on the ID card data to be queried and the reporting date, query all primary keys to obtain the target data source point set; After constructing the data source point set based on the primary key and loan amount data, the method further includes: validating the data source point set and marking the data source point sets that fail the validation as abnormal. Validating the data source point set includes: Determine whether the total loan amount in the data source point set matches the credit amount in the credit report. If they match, the corresponding data source point set is considered valid; otherwise, the corresponding data source point set is considered invalid. Determine whether the total loan amount in the data source set matches the credit amount in the credit report, including: Determine the reporting date corresponding to the data source point set to obtain the target reporting date; Determine the total loan amount corresponding to the data source point set, and determine the credit amount corresponding to the target reporting date in the credit report; Determine whether the total loan amount is the same as the credit score. If so, the corresponding data source set is deemed valid; otherwise, the corresponding data source set is deemed invalid.

2. The method for rapidly backtracking data according to claim 1, characterized in that, After finding the data source point set corresponding to the loan business data to be queried, the process also includes: determining whether the data source point set corresponding to the loan business data to be queried has been marked. If so, an error message is returned to the user terminal; otherwise, the data source point set is transmitted to the user terminal.

3. A device for rapidly backtracking data, characterized in that, The method for performing the rapid backtracking of data according to any one of claims 1 to 2, wherein the apparatus includes an information acquisition module, a source point set construction module, and a data query module; The information acquisition module is used to acquire first lending information to be processed, the first lending information including loan business data and loan amount data; The source point set construction module is used to construct a primary key based on the loan business data, and to construct a data source point set based on the primary key and the loan amount data. The data query module is used to determine the loan business data to be queried, and based on the loan business data to be queried, to query all primary keys, find the data source point set corresponding to the loan business data to be queried, and complete the rapid backtracking of data.

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