Automated Reconciliation Method, Device and Storage Medium for Order Data

Abstract

The present invention discloses an automated reconciliation method, device and storage medium for order data. The method includes offline submitting order data within a preset period to a full-scale table in a big data platform library; cleaning out the order data with incremental changes in the full-scale table of the big data platform library within the preset period and recording it in an incremental table of the big data platform library; synchronizing the data in the incremental table of the big data platform library to an incremental table of a business database MySQL library; and through a scheduled task, synchronizing the data in the incremental table of the MySQL library to the business database. The present invention uses a big data platform IDP (Internet Datagram Protocol) to replace the original real-time interface, reducing the pressure on each party's system, and can also avoid data inaccuracy caused by the jitter of each system. The enterprise reconciliation data has a high degree of accuracy, fundamentally solving the problem of true reconciliation data errors, objectively improving the personal efficiency of some operations in dealing with reconciliation problems, and also enhancing the user's reconciliation experience.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and particularly to an automated reconciliation method, device, and storage medium for order data. Background Art

[0002] In the existing reconciliation solution, all data of enterprise orders is obtained through an interface at a certain time every day or every few days, such as order basic information, invoice information, account period information, etc. Then, the amount data of each party is compared through business logic to check whether the reconciliation status of the order is successful or failed.

[0003] The above solution has a large system pressure on each party through the interface and depends on the stability of the associated party's system, resulting in the need to often re-run all the reconciliation data. Summary of the Invention

[0004] In view of the technical problem that the existing technology uses the interface method to obtain enterprise order data, which has a large system pressure on each party and depends on the stability of the associated party's system, resulting in the need to often re-run all the reconciliation data, the present invention proposes the following technical solutions.

[0005] To solve the above technical problem, a technical solution adopted by the present invention is:

[0006] An automated reconciliation method for order data, comprising:

[0007] Offline submitting order data within a preset period to a full-scale table in a big data platform library;

[0008] Cleaning out the order data with incremental changes in the full-scale table of the big data platform library within the preset period and recording it in an incremental table of the big data platform library;

[0009] Synchronizing the data in the incremental table of the big data platform library to an incremental table of a business database MySQL library;

[0010] Through a scheduled task, synchronizing the data in the incremental table of the MySQL library to the business database.

[0011] Further, the order data includes order sub-data, invoice data, account period data, and payment data; the offline submitting the full-scale aggregation of order data within a preset period to a full-scale table in a big data platform library includes:

[0012] Offline submitting the full-scale aggregation of order sub-data, invoice data, account period data, and payment data within a preset period to a full-scale table in a big data platform library.

[0013] Further, the full-scale table of the big data platform library includes the full-scale table of the Hive library; the incremental table includes the incremental table of the Hive library; the step of cleaning the order data with incremental changes within the preset period and recording it in the incremental table includes:

[0014] Through a script task, compare the reconciliation data in the MySQL library with the order data in the full-scale table of the Hive library, and synchronize the incremental data within the preset period to the incremental table of the Hive library.

[0015] Further, the step of synchronizing the data in the reconciliation incremental table to the business database MySQL library includes:

[0016] Configure a data synchronization task to synchronize the incremental data in the incremental table of the Hive library to the incremental table of the MySQL library.

[0017] Further, the step of synchronizing the data in the incremental table of the MySQL library to the business database through a scheduled task includes:

[0018] Within the preset period, through a scheduled task, use multithreaded concurrent processing to process the incremental data in the incremental table of the MySQL library and write it to the business database.

[0019] Further, the method further includes:

[0020] Judge whether the order unique identifier of the data in the incremental table of the MySQL library exists in the business database. If it does not exist, add new order data; if it already exists, update the order data.

[0021] Further, the method further includes:

[0022] For the data with reconciliation failures when synchronizing the data in the incremental table of the MySQL library to the business database, obtain the failure status, and according to the failure reasons corresponding to different failure statuses, call the verification and repair interfaces of the corresponding systems, and automatically process the data with reconciliation failures according to preset rules to make the automatic reconciliation successful.

[0023] Further, the method further includes:

[0024] Automatically process the data with reconciliation failures according to preset rules. The data that cannot be automatically reconciled successfully is summarized as the data with reconciliation failures within the preset period, and a notification message is sent.

[0025] Another technical solution adopted by the present invention is:

[0026] An order data automatic reconciliation device, the order data automatic reconciliation device includes a processor and a memory coupled to the processor, a computer program is stored in the memory, and the processor is used to execute the computer program to implement the method described above.

[0027] Another technical solution adopted by the present invention is: a computer-readable storage medium, program data is stored in the computer-readable storage medium, and when the program data is executed by a processor, it is used to implement the method described above.

[0028] The beneficial effects of the present invention are: Different from the prior art, the present invention provides an order data automatic reconciliation method, including offline submitting order data within a preset period to the full-scale table in the big data platform library; cleaning out the order data with incremental changes in the full-scale table of the big data platform library within the preset period and recording it in the incremental table of the big data platform library; synchronizing the data in the incremental table of the big data platform library to the incremental table of the business database MySQL library; through a scheduled task, synchronizing the data in the incremental table of the MySQL library to the business database. The present invention uses the big data platform IDP (Internet Datagram Protocol) to replace the original real-time interface, reducing the pressure on each party's system, and can also avoid data inaccuracies caused by the jitter of each system. The enterprise reconciliation data has a high accuracy, fundamentally solving the problem of true reconciliation data errors, objectively improving the personal efficiency of some operation and processing reconciliation problems, and also improving the user's reconciliation experience. Description of the Drawings

[0029] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for description in the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings. Among them:

[0030] Figure 1 is a flowchart of an embodiment of the order data automatic reconciliation method provided by the present invention;

[0031] Figure 2 is a flowchart of the order data automatic reconciliation method of another embodiment of the order data automatic reconciliation method provided by the present invention;

[0032] Figure 3 is the overall flowchart of the order data automatic reconciliation method provided by the present invention;

[0033] Figure 4 is a data interaction diagram between various tables of the order data automatic reconciliation of the order data automatic reconciliation method provided by the present invention;

[0034] Figure 5 is a structural block diagram of an embodiment of the order data automatic reconciliation device provided by the present invention;

[0035] Figure 6 is a structural schematic diagram of an embodiment of the computer-readable storage medium provided by the present invention. Detailed implementation manners

[0036] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. It can be understood that the specific embodiments described herein are only used to explain the present invention, rather than limiting the present invention. In addition, it should be noted that, for the convenience of description, only some but not all of the methods and processes related to the present invention are shown in the accompanying drawings. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0037] The terms "including" and "having" in the present invention and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally further includes steps or units not listed, or optionally further includes other steps or units inherent to these processes, methods, products or devices.

[0038] Referring to "embodiment" herein means that a specific feature, structure or characteristic described in conjunction with the embodiment may be included in at least one embodiment of the present invention. The phrase appears in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0039] Refer to Figure 1 , Figure 1 is a flowchart of an embodiment of the order data automatic reconciliation method provided by the present invention.

[0040] The order data automatic reconciliation method of the embodiment of the present invention includes

[0041] Step 10: Offline submit the order data within a preset period to the full-scale table in the big data platform library.

[0042] Specifically, the preset period can be set to 6 hours, 12 hours, one day, two days, three days or five days. For example, submit the order data offline to the full-scale table in the big data platform library every day.

[0043] Step 20: Clean out the order data with incremental changes in the full-scale table of the big data platform library within the preset period and record it in the incremental table of the big data platform library;

[0044] Step 30: Synchronize the data in the incremental table of the big data platform library to the incremental table of the business database MySQL library.

[0045] Step 40: Through a scheduled task, synchronize the data in the incremental table of the MySQL library to the business database.

[0046] The present invention uses the big data platform IDP (Internet Datagram Protocol) to replace the original real-time interface, reducing the pressure on each party's system and avoiding data inaccuracies caused by the jitter of each system. The accuracy of enterprise reconciliation data is relatively high, fundamentally solving the problem of true reconciliation data errors, objectively improving the personal efficiency of some operations in handling reconciliation issues, and also enhancing the user's reconciliation experience, thereby enhancing the user's repayment willingness and reducing the user's repayment overdue rate.

[0047] Specifically, the order data includes order sub-data, invoice data, account period data, and payment data; the full-scale aggregation and offline submission of the order data within the preset period to the full-scale table of the big data platform library includes:

[0048] Full-scale aggregation and offline submission of the order sub-data, invoice data, account period data, and payment data within the preset period to the full-scale table of the big data platform library. In the big data platform IDP, through the method of data extraction, the order data, invoice data, account period data, and payment data are fully aggregated and offline submitted to the platform library table every day. Specifically, data aggregation is performed in the big data platform IDP, aggregating the order data, account period data, and invoice data, comparing the amounts and statuses of each party to obtain the reconciliation status, and falling into the full-scale table of the Hive library.

[0049] In one embodiment, the full-scale table of the big data platform library includes the full-scale table of the Hive library; the incremental table includes the incremental table of the Hive library; the cleaning out of the order data with incremental changes within the preset period and recording it in the incremental table includes:

[0050] Through a script task, compare the reconciliation data in the MySQL library with the order data in the full-scale table of the Hive library, and synchronize the incremental data within the preset period to the incremental table of the Hive library. For example, through a script task, clean out the enterprise order data with daily incremental changes and record it in the incremental table.

[0051] In one embodiment, the synchronization of the data in the reconciliation incremental table to the business database MySQL library includes:

[0052] Configure a synchronization data task to synchronize the incremental data of the incremental table in the Hive library to the incremental table in the MySQL library. Among them, the MySQL library is used to receive the incremental data and is isolated from the business database of the system. Configure a task for the Hive library of the big data platform to the business database MySQL, so that the data enters the incremental table of the business database MySQL that can be operated by the program. Specifically, configure the IDP synchronization data task to synchronize the data in the diff table in the Hive library to ep_big_data, which is a MySQL library and is specifically used to receive the synchronized data from the Hive library.

[0053] In one embodiment, synchronizing the data in the incremental table of the MySQL library to the business database through a scheduled task includes:

[0054] Within the preset period, through a scheduled task, use multi-threaded concurrency to process the incremental data of the incremental table in the MySQL library and write it to the business database. Specifically, for the daily scheduled task, use multi-threaded concurrency to process the incremental data and write it to the system business library. If the order number does not exist, add it; if it already exists, update the data. Through the scheduled task, synchronize the data in the incremental table in the MySQL library. Because the data volume is relatively large, to reduce the system pressure, a thread pool is used to synchronize the data to the order reconciliation full-scale table through multi-threaded concurrency.

[0055] In one embodiment, the method further includes:

[0056] Judge whether the order unique identifier of the data in the incremental table of the MySQL library exists in the business database. If it does not exist, add the order data; if it already exists, update the order data.

[0057] Specifically, the order unique identifier is the order ID, or the order number, or other identifiers that can uniquely correspond to the order. The order unique identifier is a field in the order sub-data and also a field in the order data.

[0058] In another embodiment, combined with Figure 2 , the method further includes:

[0059] Step 50: For the data that fails to reconcile when synchronizing the data in the incremental table of the MySQL library to the business database, obtain the failure status, and according to the failure reasons corresponding to different failure statuses, call the verification and repair interfaces of the corresponding systems, and automatically process the data that fails to reconcile according to the preset rules to make it achieve successful automatic reconciliation.

[0060] For the data that fails to reconcile, according to different failure reasons, call the verification and repair interfaces of each system to automatically process the data that fails to reconcile. Repair the data correctly through an automated mode to make it achieve successful reconciliation.

[0061] Specifically, various failure states can be counted. Figure 3 The figure shows the handling of various situations of the failure state. The preset rules include different handling methods corresponding to different failure states.

[0062] Figure 4 The figure shows the data interaction diagram between the tables for automated reconciliation of order data. Figure 4 The interaction process of an embodiment of the present invention can be seen from this page.

[0063] In another embodiment, the method further includes:

[0064] Automatically process the data with failed reconciliation according to the preset rules. The data that cannot be successfully reconciled automatically is summarized as the data with failed reconciliation within the preset period, and a notification message is sent.

[0065] Furthermore, the method further includes: marking the data with failed reconciliation.

[0066] Due to various reasons, the data that cannot be automatically repaired can summarize the data of the reconciliation date, send a notification message to various places where the staff can be notified, such as the reconciliation chat group; and count the data of different failure reasons, and send it to each system developer in a private manner to urge them to process the data offline. Or label the data with failed reconciliation to ensure the normal reconciliation data of the order.

[0067] The reconciliation solutions of the prior art can roughly understand the current distribution of corporate reconciliation problems and the data of existing reconciliation problems, but cannot effectively locate specific problems. In the embodiments of the present invention, by statistically analyzing the failure status, the data that failed to be reconciled will call the verification and repair interface of each system according to the different reasons for failure, and automatically process the data that failed to be reconciled; for the data that failed to be automatically processed according to the preset rules, the data that still cannot be automatically reconciled successfully is summarized as the reconciliation failure data within the preset period, and a notification message is issued and / or a label is added, so that the specific problem can be effectively located, and the automatic processing of the data that failed to be reconciled can also greatly reduce the data that needs to be manually processed. The interface method of the prior art puts a lot of pressure on the systems of all parties, and relies on the stability of the related party systems, resulting in the reconciliation data often needing to be fully re-run. The automated reconciliation method for order data provided in the above embodiment of the present invention reduces the pressure on the systems of all parties by replacing the original real-time interface with the big data platform IDP; it can avoid the inaccuracy of data caused by the jitter of each system. After testing, the accuracy of enterprise reconciliation data is 99.99%, which can be said to fundamentally solve the authenticity data errors of reconciliation; objectively improve the user reconciliation experience, thereby improving the user's willingness to repay and reducing the user's repayment overdue rate. The automated reconciliation of order data provided in the embodiment of the present invention verifies the order data by means of the big data platform IDP+MySQL, and combines the application robot to push notification messages of reconciliation failed orders. It is a complete set of order reconciliation and error order correction system methods.

[0068] According to the above embodiments, the present invention provides an automatic reconciliation device for order data. Figure 5 , Figure 5 It is a structural schematic diagram of an embodiment of an automatic reconciliation device for order data provided by the present invention.

[0069] The order data automatic reconciliation device 100 includes a processor 110 and a memory 120. The processor 110 and the memory 120 are coupled. The memory 120 stores a computer program, which is used to execute the above-mentioned order data automatic reconciliation method.

[0070] Specific reference Figure 6 , Figure 6 It is a structural schematic diagram of an embodiment of a computer-readable storage medium provided by the present invention.

[0071] The computer-readable storage medium 200 includes program data 210. When the program data 210 is executed by the processor, the above-mentioned order data automatic reconciliation method can be implemented.

[0072] Different from the prior art, the present invention provides an automated reconciliation method for order data.

[0073] The automated reconciliation method for order data provided by the present invention includes offline submitting order data within a preset period to the full-scale table in the big data platform library; cleaning out the order data with incremental changes in the full-scale table of the big data platform library within the preset period and recording it in the incremental table of the big data platform library; synchronizing the data in the incremental table of the big data platform library to the incremental table of the business database MySQL library; and synchronizing the data in the MySQL library incremental table to the business database through a scheduled task. The present invention uses the big data platform IDP (Internet Datagram Protocol) to replace the original real-time interface, reducing the pressure on each party's system, and can also avoid data inaccuracy caused by the jitter of each system. The enterprise reconciliation data has a high degree of accuracy, fundamentally solving the problem of true reconciliation data errors, objectively improving the personal efficiency of some operation processing reconciliation problems, and also enhancing the user's reconciliation experience.

[0074] The above are only the embodiments of the present invention, and do not limit the patent scope of the present invention accordingly. Any equivalent structure or equivalent process transformation made by using the content of the specification and drawings of the present invention, or directly or indirectly applied in other related technical fields, shall be similarly included in the patent protection scope of the present invention.

Claims

1. An automated reconciliation method for order data, characterized in that Including: Offline submit the order data within a preset period to the full-scale table in the big data platform library; Clean out the order data with incremental changes in the full-scale table of the big data platform library within the preset period and record it in the incremental table of the big data platform library; Synchronize the data in the incremental table of the big data platform library to the incremental table of the business database MySQL library, specifically including: configuring an IDP data synchronization task to synchronize the data in the incremental table of the big data platform library to the incremental table of the business database MySQL library, where IDP is the Internet Datagram Protocol, that is, the datagram protocol; Through a scheduled task, synchronize the data in the incremental table of the MySQL library to the business database; The order data includes order sub-data, invoice data, account period data, and payment data; the full-scale table of the big data platform library includes the full-scale table of the Hive library; The offline submission of the full-scale aggregation of order data within a preset period to the full-scale table of the big data platform library includes: Full-scale aggregate and offline submit the order sub-data, invoice data, account period data, and payment data within a preset period to the full-scale table of the big data platform library; specifically: perform data aggregation in the big data platform IDP, aggregate the order sub-data, account period data, and invoice data, compare the amounts and statuses of all parties to obtain the reconciliation status, and fall into the full-scale table of the Hive library; The method further includes: for the data with reconciliation failure when synchronizing the data in the incremental table of the MySQL library to the business database, obtain the failure status, and according to the failure reasons corresponding to different failure statuses, call the verification and repair interfaces of the corresponding systems, and automatically process the data with reconciliation failure according to preset rules to achieve successful automatic reconciliation.

2. The method according to claim 1, wherein The incremental table includes the incremental table of the Hive library; the cleaning out of the order data with incremental changes within the preset period and recording it in the incremental table includes: Through a script task, compare the reconciliation data in the MySQL library with the order data in the full-scale table of the Hive library, and synchronize the incremental data within the preset period to the incremental table of the Hive library.

3. The method according to claim 2, characterized in that The synchronization of the data in the incremental table of the big data platform library to the incremental table of the business database MySQL library includes: Configure a data synchronization task to synchronize the incremental data in the incremental table of the Hive library to the incremental table of the MySQL library.

4. The method according to claim 3, wherein The synchronization of the data in the incremental table of the MySQL library to the business database through a scheduled task includes: Within the preset period, through a scheduled task, use multi-threaded concurrency to process the incremental data in the incremental table of the MySQL library and write it into the business database.

5. The method according to any one of claims 1-4, characterized in that, The method further includes: Judge whether the order unique identifier of the data in the incremental table of the MySQL library exists in the business database. If it does not exist, add new order data; if it already exists, update the order data.

6. The method according to any one of claims 1-4, characterized in that The method further includes: Automatically process the data with reconciliation failure according to preset rules. The data that cannot be successfully reconciled automatically is summarized as the reconciliation failure data within the preset period, and a notification message is sent.

7. The automated reconciliation device for order data, characterized in that, The automated reconciliation device for order data includes a processor and a memory coupled to the processor. A computer program is stored in the memory, and the processor is configured to execute the computer program to implement the method according to any one of claims 1-6.

8. A computer-readable storage medium, characterized in that Program data is stored in the computer-readable storage medium, and when the program data is executed by a processor, it is used to implement the method according to any one of claims 1-6.

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