Transaction data processing method, device, system, application system and big data platform

Abstract

Embodiments of the present specification disclose a transaction processing method, device, system, application system and big data platform. The method comprises: after a day-end day switching task for an account transaction data detail table is started, an application system executes the day-end day switching task based on a processing link corresponding to the day-end day switching task, the processing link being used to indicate an execution sequence between a plurality of processing sub-tasks in the day-end day switching task; after a day switching driving sub-task in the day-end day switching task is triggered, the application system generates day switching driving flow data corresponding to the day-end day switching task and writes the day switching driving flow data into a day switching state table, the day switching driving flow data comprising a day switching date and a day switching state corresponding to the day switching date; the application system synchronizes the day switching state table and the account transaction data detail table to a big data platform; and the big data platform executes day switching processing based on the synchronized day switching state table and account transaction data detail table.

Description

TECHNICAL FIELD

[0001] The present document relates to the technical field of computer, and particularly relates to a transaction processing method, device, system, application system and big data platform. BACKGROUND

[0002] Due to part of hot accounts of financial institutions, with the continuous increase of daily transaction volume, the account flow volume of the accounts occurring every day is also expanding. Through the traditional application code triggering the relational database to perform grouping statistics and online waiting, the timeout bottleneck has been gradually reached.

[0003] Therefore, at present, a solution capable of quickly and accurately performing the end-of-day processing on the massive transaction flow of the accounts is urgently needed. SUMMARY

[0004] Embodiments of the present specification aim to provide a transaction processing method, device, system, application system and big data platform, so as to quickly and accurately complete the end-of-day processing on the massive transaction flow of the accounts by means of the computing power of the big data platform and the integrity grasping and driving of the application system on the end-of-day link.

[0005] In order to achieve the above-mentioned purpose, the technical scheme adopted by the embodiments of the present specification is as follows:

[0006] In a first aspect, a transaction data processing method is provided, comprising:

[0007] After the end-of-day task of the account transaction data detail table is started, the application system executes the end-of-day task based on the processing link corresponding to the end-of-day task, and the processing link is used to indicate the execution order between the plurality of processing sub-tasks in the end-of-day task;

[0008] After the end-of-day driving sub-task in the end-of-day task is triggered, the application system generates the end-of-day driving flow data corresponding to the end-of-day task and writes it into the end-of-day state table, and the end-of-day driving flow data includes the end-of-day date and the end-of-day state corresponding to the end-of-day date;

[0009] The application system synchronizes the end-of-day state table and the account transaction data detail table to the big data platform;

[0010] The big data platform performs end-of-day processing based on the synchronized end-of-day state table and account transaction data detail table.

[0011] In a second aspect, a transaction data processing method is provided, applied to an application system, and the method comprises:

[0012] After a day-end day switching task for an account transaction data detail table is started, the day-end day switching task is executed based on a processing link corresponding to the day-end day switching task, the processing link being used to indicate an execution order between a plurality of processing sub-tasks in the day-end day switching task;

[0013] After a day switching driving sub-task in the day-end day switching task is triggered, day switching driving flow data corresponding to the day-end day switching task is generated and written into a day switching state table, the day switching driving flow data including a day switching date and a day switching state corresponding to the day switching date;

[0014] The day switching state table and the account transaction data detail table are synchronized to a big data platform, the day switching state table and the account transaction data detail table being used for the big data platform to perform day switching processing.

[0015] In a third aspect, a transaction data processing method is provided, applied to a big data platform, and the method comprises:

[0016] A day switching state table and an account transaction data detail table are synchronized from an application system, wherein the day switching state table records day switching driving flow data, the day switching driving flow data including a day switching date and a day switching state corresponding to the day switching date, the day switching driving flow data being generated and written into the day switching state table after a day switching driving sub-task in a day-end day switching task is triggered in a process in which the day-end day switching task is executed by the application system based on a processing link corresponding to the day-end day switching task, the processing link being used to indicate an execution order between a plurality of processing sub-tasks in the day-end day switching task;

[0017] Day switching processing is performed based on the synchronized day switching state table and the account transaction data detail table.

[0018] In a fourth aspect, a transaction data processing system is provided, comprising an application system and a big data platform;

[0019] After a day-end day switching task for an account transaction data detail table is started, the day-end day switching task is executed based on a processing link corresponding to the day-end day switching task, the processing link being used to indicate an execution order between a plurality of processing sub-tasks in the day-end day switching task;

[0020] After a day switching driving sub-task in the day-end day switching task is triggered, day switching driving flow data corresponding to the day-end day switching task is generated and written into a day switching state table, the day switching driving flow data including a day switching date and a day switching state corresponding to the day switching date;

[0021] The day switching state table and the account transaction data detail table are synchronized to the big data platform by the application system;

[0022] The big data platform performs the day cut processing based on the synchronized day cut state table and the account transaction data detail table.

[0023] In a fifth aspect, a transaction data processing apparatus is provided, which is applied to an application system, and the apparatus comprises:

[0024] An execution unit is configured to execute a day-end day cut task based on a processing link corresponding to the day-end day cut task after the day-end day cut task is started, the processing link being used to indicate an execution sequence between a plurality of processing sub-tasks in the day-end day cut task;

[0025] A generation unit is configured to generate day cut driving flow data corresponding to the day-end day cut task and write the day cut driving flow data into a day cut state table after a day cut driving sub-task in the day-end day cut task is triggered, the day cut driving flow data comprising a day cut date and a day cut state corresponding to the day cut date;

[0026] A first synchronization unit is configured to synchronize the day cut state table and the account transaction data detail table to a big data platform, the day cut state table and the account transaction data detail table being used for the big data platform to perform day cut processing.

[0027] In a sixth aspect, a transaction data processing apparatus is provided, which is applied to a big data platform, and the apparatus comprises:

[0028] A second synchronization unit is configured to synchronize a day cut state table and an account transaction data detail table from an application system, wherein the day cut state table records day cut driving flow data, the day cut driving flow data comprising a day cut date and a day cut state corresponding to the day cut date, the day cut driving flow data being generated and written into the day cut state table after a day cut driving sub-task in a day-end day cut task is triggered in a process in which the application system executes the day-end day cut task based on a processing link corresponding to the day-end day cut task, the processing link being used to indicate an execution sequence between a plurality of processing sub-tasks in the day-end day cut task;

[0029] A processing unit is configured to perform day cut processing based on the synchronized day cut state table and the account transaction data detail table.

[0030] In a seventh aspect, an application system is provided, which comprises:

[0031] a processor; and

[0032] a memory arranged to store computer-executable instructions that, when executed, cause the processor to perform the following operations:

[0033] after a day-end day switching task for an account transaction data detail table is started, performing the day-end day switching task based on a processing link corresponding to the day-end day switching task, the processing link being used to indicate an execution order between a plurality of processing sub-tasks in the day-end day switching task;

[0034] after a day switching driving sub-task in the day-end day switching task is triggered, generating day switching driving flow data corresponding to the day-end day switching task and writing into a day switching state table, the day switching driving flow data including a day switching date and a day switching state corresponding to the day switching date;

[0035] synchronizing the day switching state table and the account transaction data detail table to a big data platform, the day switching state table and the account transaction data detail table being used for the big data platform to perform day switching processing.

[0036] In an eighth aspect, a big data platform is provided, comprising:

[0037] a processor; and

[0038] a memory arranged to store computer executable instructions that, when executed, cause the processor to perform the following operations:

[0039] synchronizing a day switching state table and an account transaction data detail table from an application system, wherein the day switching state table records day switching driving flow data, the day switching driving flow data including a day switching date and a day switching state corresponding to the day switching date, the day switching driving flow data being generated and written into the day switching state table after a day switching driving sub-task in a day-end day switching task is triggered in a process in which the application system performs the day-end day switching task based on a processing link corresponding to the day-end day switching task, the processing link being used to indicate an execution order between a plurality of processing sub-tasks in the day-end day switching task;

[0040] performing day switching processing based on the synchronized day switching state table and the account transaction data detail table.

[0041] In a ninth aspect, a computer readable storage medium is provided, the computer readable storage medium storing one or more programs, the one or more programs, when executed by a terminal device comprising a plurality of application programs, causing the terminal device to perform the following operations:

[0042] after a day-end day switching task for an account transaction data detail table is started, performing the day-end day switching task based on a processing link corresponding to the day-end day switching task, the processing link being used to indicate an execution order between a plurality of processing sub-tasks in the day-end day switching task;

[0043] After the day switching driving subtask in the day-end day switching task is triggered, day switching driving flow data corresponding to the day-end day switching task is generated and written into a day switching state table, the day switching driving flow data including a day switching date and a day switching state corresponding to the day switching date;

[0044] The day switching state table and the account transaction data detail table are synchronized to a big data platform, and the day switching state table and the account transaction data detail table are used for the big data platform to perform day switching processing.

[0045] In a tenth aspect, a computer-readable storage medium storing one or more programs is provided, the one or more programs, when executed by a terminal device including a plurality of application programs, causing the terminal device to perform the following operations:

[0046] Synchronizing a day switching state table and an account transaction data detail table from an application system, wherein the day switching state table records day switching driving flow data, the day switching driving flow data including a day switching date and a day switching state corresponding to the day switching date, the day switching driving flow data being generated and written into the day switching state table after a day switching driving subtask in a day-end day switching task is triggered in a process in which the application system executes the day-end day switching task based on a processing link corresponding to the day-end day switching task, the processing link being used to indicate an execution order between a plurality of processing subtasks in the day-end day switching task;

[0047] Performing day switching processing based on the synchronized day switching state table and the account transaction data detail table.

[0048] According to the scheme of the embodiment of the present specification, after the application system starts the end-of-day task for the account transaction data detail table, the end-of-day task is executed based on the processing link corresponding to the end-of-day task, and after the day switching driving subtask in the end-of-day task is triggered, the day switching driving flow data corresponding to the end-of-day task is generated and written into the day switching state table, and the day switching state table and the account transaction data detail table are synchronized to the big data platform. Since the application system has a time advantage in executing the end-of-day task, the corresponding data processing can be performed in the first time, and the day switching state table and the account transaction data detail table are synchronized to the big data platform according to the execution order of the processing subtasks indicated by the processing link, so that the time advantage of the application system and the integrity control and driving of the processing link can be fully utilized to ensure the integrity and accuracy of the day switching state table and the account transaction data detail table, avoid data omission in the end-of-day switching process, ensure that these data tables can be synchronized to the big data platform in time, avoid task triggering and online disconnection, and thus help to improve the accuracy and timeliness of the end-of-day switching processing. On this basis, the big data platform performs the day switching processing based on the synchronized day switching state table and the account transaction data detail table, so that the off-line computing advantage of the big data platform for massive data can be fully utilized to improve the timeliness of the end-of-day switching processing. It can be seen that the transaction data processing method of the present specification can utilize the computing capability of the big data platform and the integrity control and driving of the application system for the day switching link to quickly and accurately complete the end-of-day switching processing of the account massive transaction flow in a small time delay. BRIEF DESCRIPTION OF DRAWINGS

[0049] The drawings described herein are used to provide further understanding of the present specification, constitute a part of the present specification, the illustrative embodiments of the present specification and the description thereof are used to explain the present specification, and do not constitute improper limitation on the present specification. In the drawings:

[0050] Figure 1 A schematic system architecture diagram is provided for an embodiment of the present specification;

[0051] Figure 2 A flowchart of a transaction data processing method is provided for another embodiment of the present specification;

[0052] Figure 3 A flowchart of a transaction data processing method is provided for another embodiment of the present specification;

[0053] Figure 4 A flowchart of a transaction data processing method is provided for another embodiment of the present specification;

[0054] Figure 5 A flowchart of a transaction data processing method is provided for another embodiment of the present specification;

[0055] Figure 6 A structural schematic diagram of a transaction data processing device provided for an embodiment of the present specification;

[0056] Figure 7 A structural schematic diagram of a transaction data processing device provided for another embodiment of the present specification;

[0057] Figure 8 A structural schematic diagram of an application system provided for an embodiment of the present specification;

[0058] Figure 9 A structural schematic diagram of a big data platform provided for an embodiment of the present specification. DETAILED DESCRIPTION

[0059] For the purpose, technical solutions and advantages of the present specification to be clearer, the technical solutions of the present specification will be described clearly and completely in the following with reference to the embodiments of the present specification and corresponding drawings. Obviously, the described embodiments are only some of the embodiments of the present specification, but not all the embodiments. Based on the embodiments in the present specification, all other embodiments obtained by those skilled in the art without creative labor should belong to the scope of protection of the present document.

[0060] Related concept description:

[0061] Day-end day-cut: total the business details occurring on the specified business date as the amount of the day, and take the day-end of the previous day as the day-begin of the day, and combine the amount of the day on the basis of the day-begin of the day.

[0062] The technical solutions provided by the embodiments of the present specification will be described in detail below with reference to the drawings.

[0063] First, the application scenarios of the technical solutions provided by the embodiments of the present specification will be described. Figure 1 The application scenarios of the technical solutions provided by the embodiments of the present specification will be described.

[0064] Figure 1 A schematic system architecture schematic diagram provided for an embodiment of the present specification, Figure 1 The system architecture shown includes an application system 1 and a big data platform 2.

[0065] Application System 1 maintains an account transaction data detail table containing transaction data from a massive number of accounts. Upon detecting the initiation of a daily end-of-day cutoff task targeting this account transaction data detail table, it sequentially executes each processing subtask within the daily end-of-day cutoff task according to the corresponding processing chain, obtaining the corresponding processing results. During the execution of the daily end-of-day cutoff task according to this processing chain, if a daily cutoff driver subtask is triggered, Application System 1 generates the corresponding daily cutoff driver flow data and writes it to the daily cutoff status table. It then synchronizes the daily cutoff status table and the account transaction data detail table to Big Data Platform 2, which continues to execute subsequent daily cutoff processing. In this way, the daily end-of-day data cut-off task for the account transaction data details table is completed collaboratively by application system 1 and big data platform 2. This not only fully leverages the timeliness advantages of the application system and its control and driving of the integrity of the processing chain, avoiding data omissions during the daily end-of-day data cut-off process, thus improving the accuracy and timeliness of the daily end-of-day data cut-off processing; it also fully leverages the offline computing advantages of the big data platform for massive amounts of data, improving the timeliness of the daily end-of-day data cut-off processing.

[0066] The transaction data processing method provided in the embodiments of this specification will detail the process by which the application system and the big data platform work together to complete the daily task switching.

[0067] based on Figure 1 The system architecture described herein, and the embodiments thereof, provide a transaction data processing method. Please refer to... Figure 2 This diagram illustrates a transaction data processing method according to one embodiment of this specification. It depicts a specific implementation of the interaction between an application system and a big data platform. Figure 2 As shown, the method may include:

[0068] S202, after the application system initiates the end-of-day cutoff task for the account transaction data details table, it executes the end-of-day cutoff task based on the processing link corresponding to the end-of-day cutoff task.

[0069] In the embodiments of this specification, the account transaction data details table records transaction data for multiple accounts. The transaction data for each account may include, but is not limited to, the account identifier of the account to which each transaction belongs, the transaction serial number of each transaction, the transaction type, the transaction amount, and the transaction date. For example, Table 1 shows an example of an account transaction data details table.

[0070] Table 1

[0071] Transaction serial number Account identification Transaction type Transaction amount Transaction date 1001 id001 Inward 100 2022-01-01 1002 id001 Outward 200 2022-01-02 1003 id0002 Inward 50 2022-01-02 1004 id001 Inward 300 2022-01-03 1005 id001 Outward 200 2022-01-03 …… …… …… …… ……

[0072] The daily cut task includes a plurality of processing sub-tasks, such as at least one of a daily cut date management sub-task, a daily cut process management sub-task, a daily cut driving sub-task, a daily cut pre-check sub-task, and a daily cut driving sub-task, but is not limited thereto. The daily cut date management sub-task is used to manage the daily cut date, such as which transaction data of which transaction date in the account transaction data detail table needs to be daily cut, and which transaction data of which transaction date has been daily cut. The daily cut process management sub-task is used to manage the daily cut process, and orderly push the execution of each processing sub-task according to the execution order indicated by the processing link. The daily cut driving sub-task is used to drive the accounting system to perform daily cut on the account transaction data of the day before the daily cut date. The daily cut pre-check sub-task is used to check the daily cut balance corresponding to the day before the daily cut date, to ensure the accuracy of the daily cut balance. The daily cut driving sub-task is used to drive the big data platform to perform subsequent daily cut processing.

[0073] The processing link is used to indicate the execution order between the plurality of processing sub-tasks in the daily cut task. In S202, the application system executes each processing sub-task in the daily cut task according to the execution order of each processing sub-task indicated by the processing link.

[0074] Optionally, the execution order of the daily cut date management sub-task is before the execution order of the daily cut driving sub-task. The application system locally maintains an online daily cut state table, which records each daily cut date and the corresponding daily cut state. The daily cut state includes to be cut and completed. If the state of the daily cut date is to be cut, it means that the account transaction data belonging to the daily cut date in the account transaction data detail table needs to be cut. If the state of the daily cut date is completed, it means that the account transaction data belonging to the daily cut date in the account transaction data detail table has been cut.

[0075] In this case, in S202, before the application system executes the daily cut task based on the processing link corresponding to the daily cut task, the application system further includes: after the daily cut date management sub-task is triggered, searching the daily cut state table for a historical daily cut date closest to the current time point and having a completed daily cut state, and then determining the daily cut date corresponding to the daily cut task based on the historical daily cut date.

[0076] For example, Table 2 below shows an example of the daily cut state table.

[0077] Table 2

[0078] Day cut date Day cut status 2022-01-01 Completed 2022-01-02 Completed …… ……

[0079] Taking Table 2 above as an example, assuming that the current time point belongs to 2022-01-03, and the historical day cut date closest to the current time point and with a completed day cut state is 2022-01-02 obtained through the day cut state table query, then the day cut date corresponding to the current day-end day cut task can be obtained by adding 1 day to the historical day cut date.

[0080] It can be understood that, since the day-end day cut processing is continuous, that is, the day cut of the current day can only be performed after the day cut of the previous day is completed, by placing the day cut date management subtask before the day cut driving subtask, after the day cut date management subtask is triggered, the day cut date corresponding to the current day-end day cut task is determined on the basis of the historical day cut date closest to the current time point and with a completed day cut state, which can ensure the continuity and accuracy of the day-end day cut processing.

[0081] Alternatively, the execution order of the day-end driving subtask is before the execution order of the day cut driving subtask. The application system also maintains an online account day-end table, which records the opening balance of each day cut date for multiple accounts. For example, the account day-end table can record the opening balance, occurrence, etc. of each account on each day cut date according to different accounts.

[0082] In this case, after the day-end day cut task is executed based on the processing link corresponding to the day-end day cut task in S202 above, the application system further drives the accounting system to perform day-end processing on the account transaction data of the previous day of the day cut date based on the account transaction data detail table after the day-end driving subtask is triggered, to obtain the day-end balance of the previous day, which is the opening balance of the day cut date corresponding to the day-end day cut task; further, the application system also writes the opening balance of the day cut date corresponding to the day-end day cut task into the account day-end table and synchronizes the account day-end table to the big data platform, so that the big data platform performs corresponding processing based on the account day-end table.

[0083] In practical applications, the accounting system can summarize and count the transaction data of each account on the previous day of the day cut date based on the account, to obtain the day-end balance of the account on the day cut date, which is the opening balance of the day cut date. For example, Table 3 below shows an example of an account day-end table.

[0084] Table 3

[0085] Account Day cut date Day opening balance Amount occurred Day closing balance id001 2022-01-02 1000 200 1200 id002 2022-01-02 2000 100 2100 …… …… …… …… ……

[0086] In practical applications, in order to further ensure the continuity and accuracy of the day-end day cut processing, the execution order of the day-end driving subtask can be before the day cut date management subtask.

[0087] It can be understood that, by executing the end-of-day driving subtask before the day switching driving subtask, the driving accounting system performs end-of-day processing on the day before the day switching date corresponding to the end-of-day day switching task, and waits for the end-of-day processing of the day before to be completed before performing the day switching driving subtask, so as to ensure that the accounting demands of the accounting system for the day switching date have been completed, and there will be no data accounting for the day switching date, thereby ensuring the accuracy of the end-of-day day switching processing.

[0088] Optionally, the execution sequence of the day switching pre-checking subtask is located after the end-of-day driving subtask and before the day switching driving subtask. Accordingly, in S202, after the end-of-day day switching task is executed based on the processing link corresponding to the end-of-day day switching task, the application system checks the opening balance of the day switching date corresponding to the end-of-day day switching task based on the account transaction data detail table after the day switching pre-checking task is triggered, and writes the opening balance of the day switching date into the account end-of-day table and synchronizes it to the big data platform after the opening balance of the day switching date passes the check.

[0089] In a specific application, the application system can use various check rules commonly used in the art to check the opening balance of the day switching date corresponding to the end-of-day day switching task. If it passes, the opening balance of the day switching date is written into the corresponding field in the account end-of-day table. If it does not pass, the opening balance of the day switching date is corrected and then written into the corresponding field in the account end-of-day table.

[0090] It can be understood that, since the opening balance written into the account end-of-day table is checked, the accuracy of the account end-of-day table can be ensured, and the accuracy of the subsequent day switching processing of the big data platform can be ensured.

[0091] Optionally, the application system can also set a driving task for triggering the end-of-day day switching task, that is, the end-of-day day switching task can be started by the driving task. The driving task can be set according to actual needs, which is not limited by the embodiments of the present specification. Optionally, in order to ensure the timeliness of the end-of-day day switching processing, the driving task can be a timing task, that is, the end-of-day day switching task can be triggered and started by the timing task. For example, the timing task can be to trigger the end-of-day day switching task every 5 minutes, and the like, which is not limited by the embodiments of the present specification.

[0092] S204, the application system generates day switching driving flow data corresponding to the end-of-day day switching task and writes it into the day switching state table after the day switching driving subtask in the end-of-day day switching task is triggered.

[0093] The day switching driving flow data includes the day switching date and the day switching state corresponding to the day switching date.

[0094] In the process of performing the end-of-day switching task according to the processing link, after the switching driving subtask is triggered, the application system can obtain the switching date corresponding to the end-of-day switching task determined by the switching date management subtask, and thus obtain the corresponding switching driving flow data; further, the switching date in the switching driving flow data and the switching state corresponding to the switching date are written into the switching state table.

[0095] For example, using the switching state table shown in Table 2 above, assuming that the generated switching driving flow data is (2022-01-03, to be switched), after the switching driving flow data is written into the switching state table, the result shown in Table 4 below can be obtained:

[0096] Table 4

[0097] Day cut date Day cut status 2022-01-01 Completed 2022-01-02 Completed …… …… 2022-01-03 Pending day cut

[0098] S206, the application system synchronizes the switching state table and the account transaction data detail table to the big data platform.

[0099] Since the switching state of each switching date is recorded in the switching state table, by synchronizing the switching state table to the big data platform, the big data platform can accurately know the switching date that needs to be switched; in addition, since the account transaction data generated on different dates is recorded in the account transaction data detail table, by synchronizing the account transaction data detail table to the big data platform, the big data platform can accurately obtain the account transaction data generated on the switching date to be switched, and then accurately perform the corresponding switching processing.

[0100] In practical application, the application system can synchronize the switching state table and the account transaction data detail table to the data warehouse of the big data platform.

[0101] S208, the big data platform performs switching processing based on the synchronized switching state table and the account transaction data detail table.

[0102] The big data platform can obtain the target switching date with the switching state of to be switched from the synchronized switching state table, and obtain the account transaction data related to the target switching date from the synchronized account transaction data detail table; further, the big data platform performs switching processing based on the account transaction data related to the target switching date.

[0103] Specifically, the big data platform can perform statistics on the account transaction detail data corresponding to the target switching date in the synchronized account transaction data detail table to obtain the generation amount of the target switching date, and obtain the initial balance of the target switching date from the synchronized account end-of-day table; further, the big data platform determines the end-of-day balance of the target switching date based on the initial balance and the generation amount of the target switching date.

[0104] For example, taking the account transaction data detail table shown in Table 1, the day cut state table shown in Table 4, and the account end-of-day table shown in Table 3 as examples, after these data tables are synchronized to the big data platform, the big data platform can obtain, from the synchronized day cut state table, that the day cut date to be cut is 2022-01-03; then, the big data platform obtains, from the synchronized account transaction data detail table, the account transaction data generated on 2022-01-3, that is, the account transaction data including transaction serial numbers 1004 and 1005; then, for the account with an account identifier id001, based on the transaction type and transaction amount of the transaction data generated by the account on 2022-01-03, the occurrence amount of the account on 2022-01-03 is determined; and the end-of-day balance of the account on 2022-01-02 is obtained from the account end-of-day table as the beginning-of-day balance of the account on 2022-01-03; further, for the account, the sum of the beginning-of-day balance and the occurrence amount of the account on 2022-01-03 is determined as the end-of-day balance of the account on 2022-01-03. Thus, the big data platform completes the day cut processing of the account id001.

[0105] The day cut processing of the account id002 by the big data platform is similar and will not be repeated.

[0106] It can be understood that, since the application system has a time advantage in performing the end-of-day day cut task, can perform corresponding data processing in the first time, and the day cut state table and the account transaction data detail table are synchronized to the big data platform by the application system according to the execution order of the processing sub-tasks indicated by the processing link, the time advantage of the application system and the control and driving of the integrity of the processing link can be fully utilized, the integrity and accuracy of the day cut state table and the account transaction data detail table are ensured, data omission in the end-of-day day cut process is avoided, and these data tables can be synchronized to the big data platform in time, task triggering and online disconnection are avoided, and thus the accuracy and timeliness of the end-of-day day cut processing are improved; on this basis, the big data platform performs day cut processing based on the synchronized day cut state table and the account transaction data detail table, the off-line computing advantage of the big data platform for massive data can be fully utilized, and the timeliness of the end-of-day day cut processing is improved. It can be seen that the transaction data processing method of the embodiments of the present specification can quickly and accurately complete the end-of-day day cut processing of the massive transaction serials of the account by the computing power of the big data platform and the control and driving of the integrity of the day cut link by the application system.

[0107] In addition, since the statistics of the generated amount of the target day cut date involves the processing of a large amount of transaction flow in the account transaction data detail table, and the big data platform has the advantage of mass data calculation, by giving the statistics of the generated amount of the target day cut date to the big data platform for execution, the off-line calculation advantage of the big data platform for mass data can be fully utilized to improve the timeliness of the end-of-day day cut processing; and the opening balance of the target day cut date required in the day cut processing is obtained through the synchronized account end-of-day table, which can ensure that the accounting of the day cut date in the accounting system has been completed, and there will be no data accounting of the day cut date, thereby ensuring the accuracy of the opening balance and being beneficial to further improve the accuracy of the big data platform in executing the day cut processing.

[0108] Optionally, after S208, the transaction data processing method provided by the embodiments of the present specification can further include: returning the end-of-day balance of the target day cut date to the application system by the big data platform; further, updating the account end-of-day table based on the end-of-day balance of the target day cut date by the application system.

[0109] For example, the application system can write the end-of-day balance of the target day cut date into the account end-of-day table for use in the next end-of-day day cut task.

[0110] Of course, the big data platform can also update the synchronized account end-of-day table in the local data warehouse based on the end-of-day balance of the target day cut date.

[0111] It can be understood that the big data platform returns the corresponding processing result to the application system after executing the day cut processing, and the application system updates the account end-of-day table, which can ensure the accuracy of the account end-of-day table and provide strong data support for the next triggered end-of-day day cut task.

[0112] Optionally, after S208, the transaction data processing method provided by the embodiments of the present specification can further include: returning the end-of-day balance of the target day cut date to the application system by the big data platform; further, updating the account end-of-day table based on the end-of-day balance of the target day cut date by the application system.

[0113] For example, taking the day cut state table shown in Table 4 as an example, after completing the day cut processing of the target day cut date 2022-01-03, the big data platform can return a response message indicating the success of the day cut processing to the application system; after receiving the response message, the application system can modify the day cut state corresponding to 2022-01-03 in Table 4 to complete, and obtain the updated day cut state table as shown in Table 5.

[0114] Table 5

[0115] Day cut date Day cut status 2022-01-01 Completed 2022-01-02 Completed …… …… 2022-01-03 Completed

[0116] It can be understood that the big data platform will flow the corresponding response message to the application system after completing the day switching processing of the target day switching date, and the application system updates the day switching state table, which can ensure the accuracy of the day switching state table and provide strong data support for the next triggered day-end day switching task.

[0117] Please refer to Figure 3 A flowchart of a transaction data processing method is provided for another embodiment of the present specification, which describes another specific implementation manner of interaction between the application system and the big data platform. As shown in Figure 3 The method can include:

[0118] Firstly, the application system runs a timing task to trigger a day-end day switching task for the account transaction data detail table.

[0119] After the day-end day switching task is started, the application system executes the day-end day switching task based on the processing link corresponding to the day-end day switching task.

[0120] The day-end day switching task includes a day switching date management subtask, a day switching process management subtask, a day-end driving subtask, a day switching pre-check subtask, and a day switching driving subtask. Correspondingly, the processing link corresponding to the day-end day switching task is: day switching process management subtask -> day switching date management subtask -> day-end driving subtask -> day switching pre-check subtask -> day switching driving subtask -> ….

[0121] During the execution of the day-end day switching task by the application system, after the day switching driving subtask is triggered, the day switching driving stream data corresponding to the day-end day switching task is generated and written into the day switching state table. The day switching state table includes the day switching date and the day switching state corresponding to the day switching date.

[0122] The application system also synchronizes the day switching state table and the account transaction data detail table to the data warehouse of the big data platform.

[0123] The big data platform determines whether the synchronized day switching state table meets the day switching condition.

[0124] For example, if there is a target day switching date with a day switching state of to be switched in the synchronized day switching state table, it is determined that the synchronized day switching state table meets the day switching condition; otherwise, it is determined that the synchronized day switching state does not meet the day switching condition.

[0125] If the synchronized day switching state table does not meet the day switching condition, the day switching processing is ended.

[0126] If the synchronized day cut state table meets the day cut condition, the big data platform obtains account transaction data related to the target day cut date from the synchronized account transaction data detail table, and performs day cut processing based on the account transaction data related to the target day cut date, to obtain the end-of-day balance of the target day cut date.

[0127] Subsequently, the big data platform updates the synchronized account end-of-day table in the data warehouse based on the end-of-day balance of the target day cut date.

[0128] The big data platform also returns the end-of-day balance of the target day cut date to the application system, and the application system updates the account end-of-day table based on the end-of-day balance.

[0129] The big data platform also returns the day cut completion response corresponding to the target day cut date to the application system, and the application system modifies the day cut state corresponding to the target day cut date in the day cut state table to completion based on the day cut completion response.

[0130] One or more embodiments of the present specification provide a transaction data processing method. After the application system starts the end-of-day day cut task for the account transaction data detail table, the application system executes the end-of-day day cut task based on the processing link corresponding to the end-of-day day cut task, and after the day cut driving subtask in the end-of-day day cut task is triggered, the application system generates the day cut driving flow data corresponding to the end-of-day day cut task and writes it into the day cut state table, and synchronizes the day cut state table and the account transaction data detail table to the big data platform. Since the application system has a time advantage in executing the end-of-day day cut task, the corresponding data processing can be performed in the first time, and the day cut state table and the account transaction data detail table are synchronized to the big data platform according to the execution order of the processing subtasks indicated by the processing link, so that the time advantage of the application system and the integrity control and driving of the processing link can be fully utilized to ensure the integrity and accuracy of the day cut state table and the account transaction data detail table, avoid data omission in the end-of-day day cut process, and ensure that these data tables can be synchronized to the big data platform in time, avoid task triggering and online disconnection, and thus facilitate to improve the accuracy and timeliness of the end-of-day day cut processing. On this basis, the big data platform performs day cut processing based on the synchronized day cut state table and the account transaction data detail table, which can fully utilize the offline computing advantage of the big data platform for massive data to improve the timeliness of the end-of-day day cut processing. It can be seen that the transaction data processing method of the embodiments of the present specification can utilize the computing power of the big data platform and the integrity control and driving of the application system for the day cut link to quickly and accurately complete the end-of-day day cut processing for the account massive transaction flow in a small time delay.

[0131] Figure 4 A flowchart of a transaction data processing method provided by another embodiment of the present specification. Figure 4The execution subject of the transaction data processing method shown can be an application system, and the method can include the following steps:

[0132] S402, after the end-of-day task for the account transaction data detail table is started, performing the end-of-day task based on a processing link corresponding to the end-of-day task.

[0133] The processing link is used to indicate the execution order between the multiple processing sub-tasks in the end-of-day task.

[0134] S404, after the day change driving sub-task in the end-of-day task is triggered, generating day change driving flow data corresponding to the end-of-day task and writing the day change driving flow data into a day change state table.

[0135] The day change driving flow data includes a day change date corresponding to the end-of-day task and a day change state corresponding to the day change date.

[0136] S406, synchronizing the day change state table and the account transaction data detail table to a big data platform.

[0137] The day change state table and the account transaction data detail table are used for the big data platform to perform day change processing.

[0138] Optionally, after the above S406, the method further includes: receiving a day change completion response corresponding to a target day change date returned by the big data platform; and based on the day change completion response, modifying the day change state corresponding to the target day change date in the day change state table to completion.

[0139] Optionally, the end-of-day task further includes an end-of-day driving sub-task, and the execution order of the end-of-day driving sub-task is before the day change driving sub-task.

[0140] After the end-of-day task is performed based on the processing link corresponding to the end-of-day task, the method further includes: after the end-of-day driving sub-task is triggered, driving an accounting system to perform end-of-day processing on account transaction data of a previous day of the day change date based on the account transaction data detail table, to obtain a day-beginning balance of the day change date; and writing the day-beginning balance of the day change date into an account end-of-day table and synchronizing the day-beginning balance to the big data platform.

[0141] Optionally, the daily terminal day switching task further comprises a day switching pre-check subtask, and the execution sequence of the day switching pre-check subtask is located after the daily terminal driving subtask and before the day switching driving subtask; after the daily terminal day switching task is executed based on the processing link corresponding to the daily terminal day switching task, the method further comprises: after the day switching pre-check task is triggered, checking the day-beginning balance of the day switching date based on the account transaction data detail table; and after the day-beginning balance of the day switching date is verified, writing the day-beginning balance of the day switching date into the account daily terminal table and synchronizing the day-beginning balance of the day switching date to the big data platform.

[0142] Optionally, after the S406, the method further comprises: receiving the day-end balance of the target day switching date returned by the big data platform; and updating the account daily terminal table based on the day-end balance of the target day switching date.

[0143] Optionally, the daily terminal day switching task further comprises a day switching date management subtask, and the execution sequence of the day switching date management subtask is located before the day switching driving subtask; after the daily terminal day switching task is executed based on the processing link corresponding to the daily terminal day switching task, the method further comprises: after the day switching date management subtask is triggered, searching, from the day switching state table, a historical day switching date closest to a current time point and having a completed day switching state; and determining the day switching date corresponding to the daily terminal day switching task based on the historical day switching date.

[0144] Optionally, the daily terminal day switching task is triggered and started by a timing task.

[0145] The specific implementation of each step in the above S402 to S406 can be referred to the specific implementation of the corresponding steps in the embodiments shown in Figure 2 The specific implementation of each step in the above S402 to S406 can be referred to the specific implementation of the corresponding steps in the embodiments shown in

[0146] Figure 5 A flowchart of a transaction data processing method is provided for another embodiment of the present specification. Figure 5 The execution subject of the transaction data processing method shown can be a big data platform, and the method can comprise the following steps:

[0147] S502, synchronizing a day switching state table and an account transaction data detail table from an application system.

[0148] The day switching state table records day switching driving flow data. The day switching driving flow data comprises a day switching date and a day switching state corresponding to the day switching date. The day switching driving flow data is generated and written into the day switching state table after a day switching driving subtask in the daily terminal day switching task is triggered in the process of executing the daily terminal day switching task based on the processing link corresponding to the daily terminal day switching task, and the processing link is used to indicate the execution sequence between multiple processing subtasks in the daily terminal day switching task.

[0149] S504, performing a day cut processing based on the synchronized day cut status table and the account transaction data detail table.

[0150] Optionally, the S504 can include: obtaining a target day cut date with a day cut status of to-be-day-cut from the synchronized day cut status table; obtaining account transaction data related to the target day cut date from the synchronized account transaction data detail table; and performing a day cut processing based on the account transaction data related to the target day cut date.

[0151] Optionally, the performing a day cut processing based on the account transaction data related to the target day cut date includes: counting account transaction detail data corresponding to the target day cut date in the synchronized account transaction data detail table to obtain a generated amount of the target day cut date; obtaining a day-beginning balance of the target day cut date from the synchronized account day-end table; and determining a day-ending balance of the target day cut date based on the day-beginning balance of the target day cut date and the generated amount.

[0152] Optionally, after the S504, the method further includes: returning a day cut completion response corresponding to the target day cut date to the application system, the day cut completion response being used for the application platform to modify a day cut status corresponding to the target day cut date in the day cut status table to completion.

[0153] Optionally, after the S504, the method further includes: returning the day-ending balance of the target day cut date to the application system, the day-ending balance of the target day cut date being used for the application system to update the account day-end table.

[0154] The specific implementation of each step in the S502 to S504 can refer to the specific implementation of the corresponding step in the embodiment shown in Figure 2 The specific implementation of each step in the S502 to S504 can refer to the specific implementation of the corresponding step in the embodiment shown in

[0155] The embodiments of the present specification also provide a transaction data processing system, which includes: an application system and a big data platform.

[0156] The application system executes a day-end day cut task based on a processing link corresponding to the day-end day cut task after the day-end day cut task is started, the processing link being used to indicate an execution order between a plurality of processing sub-tasks in the day-end day cut task;

[0157] The application system generates day cut driving flow data corresponding to the day-end day cut task and writes the day cut driving flow data into a day cut status table after a day cut driving sub-task in the day-end day cut task is triggered, the day cut driving flow data including a day cut date and a day cut status corresponding to the day cut date;

[0158] The application system synchronizes the day cut status table and the account transaction data detail table to the big data platform;

[0159] The big data platform performs the day cut processing based on the synchronized day cut state table and the account transaction data detail table.

[0160] Each of the embodiments in the specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other. Each of the embodiments focuses on the difference from other embodiments. In particular, for the system embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the part of the method embodiments.

[0161] In addition, corresponding to the transaction data processing method shown in the above Figure 4 The transaction data processing device provided by the embodiment of the specification can be applied to the application system. Figure 6 is a structural schematic diagram of a transaction data processing device 600 provided by the embodiment of the specification, which comprises:

[0162] The execution unit 610 is configured to execute a day-end day cut task for the account transaction data detail table based on a processing link corresponding to the day-end day cut task after the day-end day cut task is started, and the processing link is used to indicate the execution sequence between a plurality of processing sub-tasks in the day-end day cut task.

[0163] The generation unit 620 is configured to generate day cut driving flow data corresponding to the day-end day cut task and write the day cut driving flow data into a day cut state table after a day cut driving sub-task in the day-end day cut task is triggered, and the day cut driving flow data comprises a day cut date and a day cut state corresponding to the day cut date.

[0164] The first synchronization unit 630 synchronizes the day cut state table and the account transaction data detail table to a big data platform, and the day cut state table and the account transaction data detail table are used for the big data platform to perform day cut processing.

[0165] Obviously, the transaction data processing device of the embodiment of the specification can be used as the execution subject of the transaction data processing method shown in the above Figure 4 Therefore, the transaction data processing method can realize the functions shown in the above Figure 4 Since the principles are the same, they will not be described here.

[0166] In addition, corresponding to the transaction data processing method shown in the above Figure 5 The transaction data processing device provided by the embodiment of the specification can be applied to the big data platform. Figure 7 is a structural schematic diagram of a transaction data processing device 700 provided by the embodiment of the specification, which comprises:

[0167] The second synchronization unit 710 synchronizes the daily cut status table and the account transaction data detail table from the application system. The daily cut status table records daily cut driving flow data, which includes the daily cut date and the daily cut status corresponding to the daily cut date. The daily cut driving flow data is generated and written into the daily cut status table when the daily cut driving subtask in the daily cut task is triggered during the process of the application system executing the daily cut task based on the processing link corresponding to the daily cut task. The processing link is used to indicate the execution order between multiple processing subtasks in the daily cut task.

[0168] Processing unit 720 performs daily cut-off processing based on the synchronized daily cut-off status table and account transaction data details table.

[0169] Obviously, the transaction data processing apparatus in the embodiments of this specification can be used as described above. Figure 5 The entity executing the transaction data processing method shown is therefore capable of implementing the transaction data processing method in... Figure 5 The functions implemented are the same, so they will not be described in detail here.

[0170] Figure 8 This is a schematic diagram of the structure of an application system provided in one embodiment of this specification. Please refer to it. Figure 8 At the hardware level, the application system includes a processor, and optionally also an internal bus, network interface, and memory. The memory may include main memory, such as high-speed random-access memory (RAM), or non-volatile memory, such as at least one disk drive. Of course, the application system may also include other hardware required for other business operations.

[0171] The processor, network interface, and memory can be interconnected via an internal bus, which can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus, etc. This bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 8 The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus or one type of bus.

[0172] The memory is configured to store programs. Specifically, the programs can include program codes including computer operation instructions. The memory can include an internal memory and a non-volatile memory, and provide instructions and data to the processor.

[0173] The processor reads the corresponding computer programs from the non-volatile memory into the internal memory and then runs, and forms a transaction data processing device at a logical level. The processor executes the programs stored in the memory, and is specifically configured to execute the following operations:

[0174] After a daily cut task for an account transaction data detail table is started, the daily cut task is executed based on a processing link corresponding to the daily cut task, the processing link being used to indicate an execution sequence between a plurality of processing sub-tasks in the daily cut task;

[0175] After a daily cut driving sub-task in the daily cut task is triggered, daily cut driving flow data corresponding to the daily cut task is generated and written into a daily cut state table, the daily cut driving flow data including a daily cut date and a daily cut state corresponding to the daily cut date;

[0176] The daily cut state table and the account transaction data detail table are synchronized to a big data platform, and the daily cut state table and the account transaction data detail table are used for the big data platform to perform daily cut processing.

[0177] The above as described in the specification Figure 4The method performed by the transaction data processing apparatus disclosed in the embodiments can be applied in a processor or implemented by the processor. The processor can be an integrated circuit chip having a processing capability of signals. In the implementation, each step of the above method can be completed by integrated logic circuits in hardware or instructions in software form in the processor. The processor can be a general processor including a central processing unit (CPU), a network processor (NP), etc., or a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component. Each method, step and logic block diagram disclosed in the embodiments of the present specification can be implemented or executed. The general processor can be a microprocessor or the processor can be any conventional processor. The steps of the method disclosed in combination with the embodiments of the present specification can be directly embodied as a hardware code processor for execution, or a combination of hardware and software modules in the code processor for execution. The software module can be located in a random access memory, a flash memory, a read only memory, a programmable read only memory or an electrically erasable programmable memory, a register or other mature storage medium in the art. The storage medium is located in the memory, and the processor reads the information in the memory and combines the hardware to complete the steps of the above method.

[0178] It should be understood that the application system of the embodiments of the present specification can implement the functions of the transaction data processing apparatus in the embodiments of the present specification. Figure 4 The functions of the embodiments of the present specification. Since the principles are the same, the embodiments of the present specification will not be described here.

[0179] Of course, in addition to the software implementation, the application system of the present specification does not exclude other implementation manners, such as logic devices or a combination of software and hardware, etc., that is, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or logic device.

[0180] The embodiments of the present specification also propose a computer readable storage medium storing one or more programs, the one or more programs including instructions that, when executed by an application system including a plurality of application programs, can cause the application system to perform the method of the embodiments of the present specification, and specifically to perform the following operations: Figure 4 The method of the embodiments of the present specification, and specifically to perform the following operations:

[0181] After a day-end day switching task for an account transaction data detail table is started, the day-end day switching task is executed based on a processing link corresponding to the day-end day switching task, the processing link being used to indicate an execution order between a plurality of processing sub-tasks in the day-end day switching task;

[0182] After a day switching driving sub-task in the day-end day switching task is triggered, day switching driving flow data corresponding to the day-end day switching task is generated and written into a day switching state table, the day switching driving flow data including a day switching date and a day switching state corresponding to the day switching date;

[0183] The day switching state table and the account transaction data detail table are synchronized to a big data platform, the day switching state table and the account transaction data detail table being used for the big data platform to perform day switching processing.

[0184] Figure 9 is a structural schematic diagram of a big data platform according to an embodiment of the present specification. Please refer to Figure 9 At a hardware level, the big data platform includes a processor, and optionally further includes an internal bus, a network interface, and a memory. The memory can include an internal memory such as a random-access memory (RAM), and can further include a non-volatile memory such as at least one disk memory. Of course, the big data platform can further include other hardware required by a business.

[0185] The processor, the network interface, and the memory can be connected to each other through the internal bus, which can be an industry standard architecture (ISA) bus, a peripheral component interconnect (PCI) bus, or an extended industry standard architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, and a control bus, etc. For ease of representation, Figure 9 In the figure, only one bidirectional arrow is used to represent, but it does not mean that there is only one bus or only one type of bus.

[0186] The memory is used to store a program. Specifically, the program can include program code, and the program code includes computer operation instructions. The memory can include an internal memory and a non-volatile memory, and provides instructions and data to the processor.

[0187] The processor reads the corresponding computer program from non-volatile memory into main memory and then executes it, forming a transaction data processing device at the logical level. The processor executes the program stored in memory and specifically performs the following operations:

[0188] The application system synchronizes the daily cut status table and the account transaction data details table. The daily cut status table records daily cut driving flow data, which includes the daily cut date and the daily cut status corresponding to the daily cut date. The daily cut driving flow data is generated and written into the daily cut status table when the daily cut driving subtask in the daily cut task is triggered during the execution of the daily cut task by the application system based on the processing link corresponding to the daily cut task. The processing link is used to indicate the execution order between multiple processing subtasks in the daily cut task.

[0189] Daily cut-off processing is performed based on the synchronized daily cut-off status table and account transaction data details table.

[0190] The above is as described in this instruction manual. Figure 5 The method executed by the transaction data processing apparatus disclosed in the illustrated embodiments can be applied to a processor or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by integrated logic circuits in the processor's hardware or by instructions in software form. The processor can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this specification. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this specification can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software module can reside in a mature storage medium in the field, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory, and the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method.

[0191] It should be understood that the big data platform of the embodiments of the present specification can implement the transaction data processing apparatus in the functions of the embodiments shown in the present specification. Since the principles are the same, the embodiments of the present specification will not be described here. Figure 5 Of course, in addition to the software implementation, the big data platform of the present specification does not exclude other implementation manners, such as logic devices or a combination of software and hardware, and the like, that is, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or a logic device.

[0192]

[0193] The embodiments of the present specification also propose a computer readable storage medium storing one or more programs, the one or more programs including instructions that, when executed by a portable big data platform including a plurality of application programs, can cause the portable big data platform to perform the method of the embodiments shown in the present specification, and specifically for performing the following operations: Figure 5

[0194] Synchronizing a day cut state table and an account transaction data detail table from an application system, wherein the day cut state table records day cut driving flow data, the day cut driving flow data includes a day cut date and a day cut state corresponding to the day cut date, and the day cut driving flow data is generated and written into the day cut state table after a day cut driving subtask in a day end day cut task is triggered in a process in which the application system executes the day end day cut task based on a processing link corresponding to the day end day cut task, and the processing link is used to indicate the execution order between a plurality of processing subtasks in the day end day cut task;

[0195] Performing day cut processing based on the synchronized day cut state table and the account transaction data detail table.

[0196] The above describes specific embodiments of the present specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in an order different than the order in which they are recited in the embodiments and still achieve desirable results. In addition, the processes depicted in the figures do not necessarily require the particular order shown, or sequential order, to achieve the desired results. In certain implementations, multitasking and parallel processing can be advantageous or necessary.

[0197] In summary, the above only describes the preferred embodiments of the present specification, and is not used to limit the protection scope of the present specification. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present specification shall be included in the protection scope of the present specification.

[0198] ​​The systems, apparatuses, modules, or units in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer can be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0199] Computer readable media includes permanent and non-permanent, removable and non-removable media, which can be implemented by any method or technology to store information. The information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read only memory (ROM), electrically erasable programmable read only memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette, magnetic tape disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible by a computing device. According to the definition herein, computer readable media does not include transitory media such as modulated data signals and carriers.

[0200] It should also be noted that the terms "comprising", "including", or any other variant thereof are intended to cover non-exclusive inclusion, so that processes, methods, articles or devices including a series of elements not only include those elements, but also include other elements not explicitly listed or inherent to such processes, methods, articles or devices. Without more limitations, the element defined by the statement "comprising a" does not exclude the presence of additional identical elements in the process, method, article or device including the element.

[0201] Each of the embodiments in the specification is described in a progressive manner, and the same or similar parts between each of the embodiments can be referred to each other. Each of the embodiments focuses on the difference from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant part can be referred to the part of the method embodiment.

Claims

1. A method for processing transaction data, comprising: After the application system initiates the end-of-day cut-off task for the account transaction data details table, it executes the end-of-day cut-off task based on the processing link corresponding to the end-of-day cut-off task. The processing link is used to indicate the execution order among multiple processing subtasks in the end-of-day cut-off task. The multiple processing subtasks include a day-cut-off date management subtask and a day-cut-off driving subtask. The execution order of the day-cut-off date management subtask is before the day-cut-off driving subtask. After the daily cut date management subtask is triggered, the application system searches the daily cut status table for the historical daily cut date that is closest to the current time and whose daily cut status is completed, and determines the daily cut date corresponding to the end-of-day daily cut task based on the historical daily cut date. After the daily cut-off driving subtask is triggered, the application system generates daily cut-off driving flow data corresponding to the end-of-day daily cut-off task and writes it into the daily cut-off status table. The daily cut-off driving flow data includes the daily cut-off date and the daily cut-off status corresponding to the daily cut-off date. The application system synchronizes the daily status table and the account transaction data details table to the big data platform; The big data platform obtains the target day cut date with the day cut status pending from the synchronized day cut status table, obtains the account transaction data related to the target day cut date from the synchronized account transaction data details table, and performs day cut processing based on the account transaction data related to the target day cut date.

2. The method as described in claim 1, further comprising, after the big data platform performs day-cutting processing based on account transaction data related to the target day-cutting date: The big data platform returns a day-cut completion response corresponding to the target day-cut date to the application system; Based on the daily cut completion response, the application system modifies the daily cut status corresponding to the target daily cut date to "completed" in the daily cut status table.

3. The method as described in claim 1, wherein the end-of-day task further includes an end-of-day driving subtask, and the execution order of the end-of-day driving subtask is prior to the end-of-day driving subtask; After executing the end-of-day task based on the processing link corresponding to the end-of-day task, the method further includes: After the end-of-day driving subtask is triggered, the application system drives the accounting system to perform end-of-day processing on the account transaction data of the day before the cut-off date based on the account transaction data details table, so as to obtain the beginning balance of the day on the cut-off date. The application system writes the beginning balance of the day on the cut-off date into the account's closing statement and synchronizes it to the big data platform.

4. The method as described in claim 3, wherein the end-of-day and end-of-day cut-off task further includes a pre-cut-off check subtask, and the execution order of the pre-cut-off check subtask is after the end-of-day driving subtask and before the end-of-day driving subtask; After executing the end-of-day task based on the processing link corresponding to the end-of-day task, the method further includes: After the pre-cut check task is triggered, the application system verifies the initial balance of the day on the day-cut date based on the account transaction data details table. After the initial balance of the cut-off date is verified, the application system writes the initial balance of the cut-off date into the account's closing statement and synchronizes it to the big data platform.

5. The method as described in claim 3 or 4, wherein the big data platform performs day-cutting processing based on account transaction data related to the target day-cutting date, including: The big data platform performs statistics on the account transaction details data corresponding to the target date cutoff date in the synchronized account transaction data details table to obtain the amount generated on the target date cutoff date; The big data platform obtains the beginning balance of the target date from the synchronized account end-of-day table; The big data platform determines the closing balance of the target date based on the initial balance and the generated amount of the target date.

6. The method of claim 5, after the big data platform determines the closing balance of the target date based on the beginning balance and the generated amount of the target date, the method further includes: The big data platform returns the end-of-day balance of the target date to the application system; The application system updates the account end-of-day table based on the end-of-day balance of the target date.

7. The method as described in claim 1, wherein the end-of-day task is triggered by a scheduled task.

8. A transaction data processing method, applied to an application system, the method comprising: After the end-of-day cutoff task for the account transaction data details table is initiated, the end-of-day cutoff task is executed based on the processing link corresponding to the end-of-day cutoff task. The processing link is used to indicate the execution order among multiple processing subtasks in the end-of-day cutoff task. The multiple processing subtasks include a day-cutoff date management subtask and a day-cutoff driving subtask. The execution order of the day-cutoff date management subtask is before the day-cutoff driving subtask. After the daily cut date management subtask is triggered, the historical daily cut date that is closest to the current time and whose daily cut status is completed is found in the daily cut status table, and the daily cut date corresponding to the end-of-day daily cut task is determined based on the historical daily cut date; After the daily cut-off driving subtask is triggered, the daily cut-off driving flow data corresponding to the end-of-day daily cut-off task is generated and written into the daily cut-off status table. The daily cut-off driving flow data includes the daily cut-off date and the daily cut-off status corresponding to the daily cut-off date. The daily cut status table and the account transaction data details table are synchronized to the big data platform. The daily cut status table and the account transaction data details table are used by the big data platform to perform the following daily cut process: obtain the target daily cut date with the daily cut status as pending from the synchronized daily cut status table, obtain the account transaction data related to the target daily cut date from the synchronized account transaction data details table, and perform daily cut process based on the account transaction data related to the target daily cut date.

9. A transaction data processing method applied to a big data platform, the method comprising: The application system synchronizes the daily cut-off status table and the account transaction data details table. The daily cut-off status table records daily cut-off driving flow data, which includes the daily cut-off date and the daily cut-off status corresponding to the daily cut-off date. The daily cut-off driving flow data is generated and written into the daily cut-off status table when the daily cut-off driving subtask in the daily cut-off task is triggered during the execution of the daily cut-off task by the application system based on the processing link corresponding to the daily cut-off task. The processing link is used to indicate the execution order among multiple processing subtasks in the daily cut-off task. The multiple processing subtasks include the daily cut-off date management subtask and the daily cut-off driving subtask. The execution order of the daily cut-off date management subtask is before the daily cut-off driving subtask. The daily cut-off date is determined after the daily cut-off date management subtask is triggered, based on the historical daily cut-off date in the daily cut-off status table that is closest to the current time and whose daily cut-off status is completed. Retrieve the target date for which the date cut status is pending from the synchronized date cut status table; Retrieve account transaction data related to the target date from the synchronized account transaction data details table; The day-cutting process is performed based on the account transaction data associated with the target day-cutting date.

10. A transaction data processing system, comprising: Application systems and big data platforms; After the application system initiates the end-of-day cut-off task for the account transaction data details table, it executes the end-of-day cut-off task based on the processing link corresponding to the end-of-day cut-off task. The processing link is used to indicate the execution order among multiple processing subtasks in the end-of-day cut-off task. The multiple processing subtasks include a day-cut-off date management subtask and a day-cut-off driving subtask. The execution order of the day-cut-off date management subtask is before the day-cut-off driving subtask. After the daily cut date management subtask is triggered, the application system searches the daily cut status table for the historical daily cut date that is closest to the current time and whose daily cut status is completed, and determines the daily cut date corresponding to the end-of-day daily cut task based on the historical daily cut date. After the daily cut-off driving subtask is triggered, the application system generates daily cut-off driving flow data corresponding to the end-of-day daily cut-off task and writes it into the daily cut-off status table. The daily cut-off driving flow data includes the daily cut-off date and the daily cut-off status corresponding to the daily cut-off date. The application system synchronizes the daily status table and the account transaction data details table to the big data platform; The big data platform obtains the target day cut date with the day cut status pending from the synchronized day cut status table, obtains the account transaction data related to the target day cut date from the synchronized account transaction data details table, and performs day cut processing based on the account transaction data related to the target day cut date.

11. A transaction data processing apparatus, applied to an application system, the apparatus comprising: After the end-of-day cutoff task for the account transaction data details table is initiated, the execution unit executes the end-of-day cutoff task based on the processing link corresponding to the end-of-day cutoff task. The processing link is used to indicate the execution order among multiple processing subtasks in the end-of-day cutoff task. The multiple processing subtasks include a day-cutoff date management subtask and a day-cutoff driving subtask. The execution order of the day-cutoff date management subtask is before the day-cutoff driving subtask. The generation unit, after the daily cut date management subtask is triggered, searches the daily cut status table for the historical daily cut date that is closest to the current time and whose daily cut status is completed, and determines the daily cut date corresponding to the end-of-day daily cut task based on the historical daily cut date; The generation unit generates daily cut-off drive flow data corresponding to the daily cut-off task and writes it into the daily cut-off status table after the daily cut-off drive subtask in the daily cut-off task is triggered. The daily cut-off drive flow data includes the daily cut-off date and the daily cut-off status corresponding to the daily cut-off date. The first synchronization unit synchronizes the daily cut status table and the account transaction data detail table to the big data platform. The daily cut status table and the account transaction data detail table are used by the big data platform to perform the following daily cut process: obtain the target daily cut date with the daily cut status as pending daily cut from the synchronized daily cut status table, obtain the account transaction data related to the target daily cut date from the synchronized account transaction data detail table, and perform daily cut process based on the account transaction data related to the target daily cut date.

12. A transaction data processing apparatus, applied to a big data platform, the apparatus comprising: The second synchronization unit synchronizes the daily cut status table and the account transaction data details table from the application system. The daily cut status table records daily cut driving flow data, which includes the daily cut date and the daily cut status corresponding to the daily cut date. The daily cut driving flow data is generated and written into the daily cut status table when the daily cut driving subtask in the daily cut task is triggered during the execution of the daily cut task by the application system based on the processing link corresponding to the daily cut task. The processing link is used to indicate the execution order among multiple processing subtasks in the daily cut task. The multiple processing subtasks include the daily cut date management subtask and the daily cut driving subtask. The execution order of the daily cut date management subtask is before the daily cut driving subtask. The daily cut date is determined after the daily cut date management subtask is triggered, based on the historical daily cut date in the daily cut status table that is closest to the current time and whose daily cut status is completed. The processing unit retrieves the target day-cut date whose day-cut status is pending from the synchronized day-cut status table, retrieves the account transaction data related to the target day-cut date from the synchronized account transaction data details table, and performs day-cut processing based on the account transaction data related to the target day-cut date.

13. An application system, comprising: processor; as well as A memory configured to store computer-executable instructions, which, when executed, cause the processor to perform the following operations: After the end-of-day cutoff task for the account transaction data details table is initiated, the end-of-day cutoff task is executed based on the processing link corresponding to the end-of-day cutoff task. The processing link is used to indicate the execution order among multiple processing subtasks in the end-of-day cutoff task. The multiple processing subtasks include a day-cutoff date management subtask and a day-cutoff driving subtask. The execution order of the day-cutoff date management subtask is before the day-cutoff driving subtask. After the daily cut date management subtask is triggered, the historical daily cut date that is closest to the current time and whose daily cut status is completed is found in the daily cut status table, and the daily cut date corresponding to the end-of-day daily cut task is determined based on the historical daily cut date; After the daily cut-off driving subtask is triggered, the daily cut-off driving flow data corresponding to the end-of-day daily cut-off task is generated and written into the daily cut-off status table. The daily cut-off driving flow data includes the daily cut-off date and the daily cut-off status corresponding to the daily cut-off date. The daily cut status table and the account transaction data details table are synchronized to the big data platform. The daily cut status table and the account transaction data details table are used by the big data platform to perform the following daily cut process: obtain the target daily cut date with the daily cut status as pending from the synchronized daily cut status table, obtain the account transaction data related to the target daily cut date from the synchronized account transaction data details table, and perform daily cut process based on the account transaction data related to the target daily cut date.

14. A big data platform, comprising: processor; as well as A memory configured to store computer-executable instructions, which, when executed, cause the processor to perform the following operations: The application system synchronizes the daily cut-off status table and the account transaction data details table. The daily cut-off status table records daily cut-off driving flow data, which includes the daily cut-off date and the daily cut-off status corresponding to the daily cut-off date. The daily cut-off driving flow data is generated and written into the daily cut-off status table when the daily cut-off driving subtask in the daily cut-off task is triggered during the execution of the daily cut-off task by the application system based on the processing link corresponding to the daily cut-off task. The processing link is used to indicate the execution order among multiple processing subtasks in the daily cut-off task. The multiple processing subtasks include the daily cut-off date management subtask and the daily cut-off driving subtask. The execution order of the daily cut-off date management subtask is before the daily cut-off driving subtask. The daily cut-off date is determined after the daily cut-off date management subtask is triggered, based on the historical daily cut-off date in the daily cut-off status table that is closest to the current time and whose daily cut-off status is completed. Retrieve the target date for which the date cut status is pending from the synchronized date cut status table; Retrieve account transaction data related to the target date from the synchronized account transaction data details table; The day-cutting process is performed based on the account transaction data associated with the target day-cutting date.

15. A computer-readable storage medium storing one or more programs, which, when executed by a terminal device including multiple applications, cause the terminal device to perform the following operations: After the end-of-day cutoff task for the account transaction data details table is initiated, the end-of-day cutoff task is executed based on the processing link corresponding to the end-of-day cutoff task. The processing link is used to indicate the execution order among multiple processing subtasks in the end-of-day cutoff task. The multiple processing subtasks include a day-cutoff date management subtask and a day-cutoff driving subtask. The execution order of the day-cutoff date management subtask is before the day-cutoff driving subtask. After the daily cut date management subtask is triggered, the historical daily cut date that is closest to the current time and whose daily cut status is completed is found in the daily cut status table, and the daily cut date corresponding to the end-of-day daily cut task is determined based on the historical daily cut date; After the daily cut-off driving subtask is triggered, the daily cut-off driving flow data corresponding to the end-of-day daily cut-off task is generated and written into the daily cut-off status table. The daily cut-off driving flow data includes the daily cut-off date and the daily cut-off status corresponding to the daily cut-off date. The daily cut status table and the account transaction data details table are synchronized to the big data platform. The daily cut status table and the account transaction data details table are used by the big data platform to perform the following daily cut process: obtain the target daily cut date with the daily cut status as pending from the synchronized daily cut status table, obtain the account transaction data related to the target daily cut date from the synchronized account transaction data details table, and perform daily cut process based on the account transaction data related to the target daily cut date.

16. A computer-readable storage medium storing one or more programs, which, when executed by a terminal device including multiple applications, cause the terminal device to perform the following operations: Synchronize the daily status table and account transaction data details table from the application system, among which... The daily cut status table records daily cut driving flow data, which includes the daily cut date and the daily cut status corresponding to the daily cut date. The daily cut driving flow data is generated and written into the daily cut status table when the daily cut driving subtask in the daily cut task is triggered during the process of the application system executing the daily cut task based on the processing link corresponding to the daily cut task. The processing link is used to indicate the execution order among multiple processing subtasks in the daily cut task. The multiple processing subtasks include the daily cut date management subtask and the daily cut driving subtask. The execution order of the daily cut date management subtask is before the daily cut driving subtask. The daily cut date is determined after the daily cut date management subtask is triggered, based on the historical daily cut date in the daily cut status table that is closest to the current time and whose daily cut status is completed. Retrieve the target date for which the date cut status is pending from the synchronized date cut status table; Retrieve account transaction data related to the target date from the synchronized account transaction data details table; The day-cutting process is performed based on the account transaction data associated with the target day-cutting date.

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