Clearing transaction execution method and device, electronic equipment and storage medium

Abstract

The invention provides a clearing transaction execution method and device, electronic equipment and a storage medium, the method is applied to the field of computer payment, and the method comprises the following steps: obtaining acceptance traffic generated by a clearing transaction, and obtaining feature data in each acceptance traffic; processing the feature data to obtain initial output data corresponding to the accepted flow; determining the number of batch processing services required by the liquidation transaction and a first service baseline corresponding to each batch processing service; obtaining a second service baseline corresponding to each batch processing service, wherein the second service baseline is a baseline of each batch processing service before transaction change; calling each batch processing service and generating first baseline data of each batch processing service under the first service baseline and second baseline data of each batch processing service under the second service baseline based on the initial output data; and a baseline data comparison result is generated based on the first baseline data and the second baseline data, so that the execution accuracy of the clearing transaction is improved.

Description

Technical Field

[0001] The present specification relates to the field of computer technology, and in particular to methods, devices, electronic devices and storage media for executing liquidation affairs. Background Art

[0002] With the development of computer payment, more and more transactions need to be processed through third-party payment platforms. In related technologies, when collecting transaction data, only transaction flow and data comparison detection can be performed for synchronous online transactions, which cannot cover the data of asynchronous or offline transactions, resulting in the loss of important information and affecting the accuracy of transaction decision-making. Summary of the invention

[0003] This specification provides a method, device, electronic device and storage medium for executing liquidation affairs, aiming to optimize and control the execution process of liquidation affairs, thereby improving the user experience. The technical solution is as follows:

[0004] In a first aspect, an embodiment of this specification provides a method for executing a liquidation transaction, the method comprising:

[0005] Obtain the acceptance flow generated by the clearing affairs, and obtain the characteristic data in each acceptance flow;

[0006] Process the characteristic data based on the acceptance flow baseline of the clearing transaction to obtain the initial output data corresponding to the acceptance flow;

[0007] Determine the number of batch processing services required for clearing transactions based on the acceptance flow baseline, and the first service baseline corresponding to each batch processing service;

[0008] Obtain a second service baseline corresponding to each batch processing service, where the second service baseline is a baseline of each batch processing service before the transaction is changed;

[0009] Calling each batch processing service and generating first baseline data of each batch processing service under a first service baseline and second baseline data of each batch processing service under a second service baseline based on the initial output data;

[0010] A baseline data comparison result is generated based on the first baseline data and the second baseline data.

[0011] In a second aspect, an embodiment of the present specification provides a device for executing a liquidation transaction, including:

[0012] A data acquisition unit, used to acquire the acceptance flow generated by the clearing transaction, and acquire characteristic data in each of the acceptance flows;

[0013] A data processing unit, configured to process the characteristic data based on the acceptance flow baseline of the clearing transaction to obtain initial output data corresponding to the acceptance flow;

[0014] A transaction determination unit, configured to determine the number of batch processing services required for the clearing transaction and a first service baseline corresponding to each batch processing service based on the acceptance flow baseline;

[0015] A baseline acquisition unit, configured to acquire a second service baseline corresponding to each batch processing service, wherein the second service baseline is a baseline of each batch processing service before a transaction is changed;

[0016] A service calling unit, configured to call each batch processing service and generate, based on the initial output data, first baseline data of each batch processing service under the first service baseline, and second baseline data of each batch processing service under the second service baseline;

[0017] A data comparison unit is used to generate a baseline data comparison result based on the first baseline data and the second baseline data.

[0018] In a third aspect, an embodiment of the present specification provides an electronic device, the electronic device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the computer program is executed by the processor, a method for executing a clearing transaction as described above is implemented.

[0019] In a fourth aspect, an embodiment of the present specification provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed, a method for executing a liquidation transaction as described in any one of the above items is implemented.

[0020] In the above technical solution, by obtaining the acceptance flow and input data of the clearing affairs at each acceptance stage, the characteristics and requirements of the clearing affairs can be mastered. By determining the input data characteristics corresponding to the acceptance flow to generate the acceptance flow baseline, the flow and characteristics of the clearing affairs can be controlled and the clearing efficiency can be improved. After calling the acceptance service to determine the baseline of each batch service, the service flow baseline is determined, which helps to fully grasp the key performance indicators of the clearing service. Based on this, the first baseline data and the second baseline data are generated and compared, thus avoiding the limitation of only collecting and detecting synchronous online transaction flow. At the same time, since the acceptance flow in the clearing affairs covers various transaction flow situations, under this framework, the processing and comparison of multiple baseline data can avoid data loss and ensure the accuracy of transaction decision-making, thereby optimizing the clearing process as a whole, improving management efficiency, and improving the execution efficiency of clearing affairs while ensuring data integrity. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the embodiments of this specification or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this specification. For those skilled in the art, other drawings can be obtained based on these drawings without paying any creative work.

[0022] Figure 1 It is a system architecture diagram of a method for executing a liquidation transaction provided in an embodiment of this specification;

[0023] Figure 2 It is a flowchart of a method for executing a liquidation transaction provided in an embodiment of this specification;

[0024] Figure 3 It is a scenario diagram of a method for executing a liquidation transaction provided in an embodiment of this specification;

[0025] Figure 4 It is a flowchart of a method for executing a liquidation transaction provided in an embodiment of this specification;

[0026] Figure 5 It is a flowchart of a method for executing a liquidation transaction provided in an embodiment of this specification;

[0027] Figure 6 It is a scenario diagram of a method for executing a liquidation transaction provided in an embodiment of this specification;

[0028] Figure 7 It is a scenario diagram of a method for executing a liquidation transaction provided in an embodiment of this specification;

[0029] Figure 8 It is a flowchart of a method for executing a liquidation transaction provided in an embodiment of this specification;

[0030] Fig. 9 It is a flowchart of a method for executing a liquidation transaction provided in an embodiment of this specification;

[0031] Fig.10 It is a scenario diagram of a method for executing a liquidation transaction provided in an embodiment of this specification;

[0032] Fig.11 It is a structural diagram of a liquidation affairs execution device provided in an embodiment of this specification;

[0033] Fig.12 It is a structural schematic diagram of an electronic device provided in an embodiment of this specification. DETAILED DESCRIPTION

[0034] In order to make the features and advantages of this specification more obvious and easy to understand, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments in this specification, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this specification.

[0035] The technical solutions in this specification will be described clearly and in detail below in conjunction with the accompanying drawings. In the description of the embodiments of this specification, unless otherwise specified, " / " means or, for example, A / B can mean A or B: "and / or" in the text is only a description of the association relationship of associated objects, indicating that there can be three relationships, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the description of the embodiments of this specification, "multiple" means two or more than two.

[0036] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features.

[0037] In order to improve the execution efficiency of liquidation affairs, an embodiment of this specification provides a method for executing liquidation affairs. The execution subject of the method for executing liquidation affairs is an execution device for liquidation affairs, and the execution device can specifically be a server. The following are described in detail. It should be noted that the description order of the following embodiments is not intended to limit the preferred order of the embodiments.

[0038] See also Figure 1 , Figure 1 1 is a system architecture diagram used by the execution method of the clearing affairs provided in the embodiments of this specification. The system architecture includes a server 110, a gateway 120, the Internet 130, a terminal device 140, etc.

[0039] The terminal device 140 includes but is not limited to mobile phones, computers, intelligent voice interaction devices, etc. The embodiments of this specification can be applied to various scenarios, including but not limited to cloud technology, artificial intelligence, etc. In addition, it can be a single device or a collection of multiple devices. For example, multiple desktop computers are interconnected through a local area network, share a display, etc. to work together, and together constitute a terminal device 140. The terminal device 140 can communicate with the Internet 130 in a wired or wireless manner to exchange data.

[0040] The server 110 refers to a computer system that can provide certain services to the terminal device 140. Compared with the ordinary terminal device 140, the server 110 has higher requirements in terms of stability, security, performance, etc. The server 110 can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms.

[0041] The gateway 120 is also called an internetwork connector or a protocol converter. The gateway realizes network interconnection at the transport layer and is a computer system or device that acts as a converter. The gateway is a translator between two systems that use different communication protocols, data formats or languages, or even completely different architectures. At the same time, the gateway can also provide filtering and security functions. The message sent by the terminal device 140 to the server 110 must be sent to the corresponding server 110 through the gateway 120. The message sent by the server 110 to the terminal device 140 must also be sent to the corresponding terminal device 140 through the gateway 120.

[0042] In the embodiment of the present specification, the clearing transaction processing program in the running state in the server 110 receives the clearing transaction request initiated by the terminal device 140, and performs data analysis on the transaction data in the clearing transaction request sent by the terminal device to obtain the acceptance flow generated by the terminal device 140 in the transaction acceptance stage, and further performs feature analysis on the input data of the user in the acceptance flow to obtain feature data corresponding to each acceptance flow, wherein the feature data includes information such as the clearing subject, the clearing account number, and the clearing time. In the acceptance flow baseline, each acceptance flow and the feature data corresponding to each acceptance flow are respectively associated to generate initial output data.

[0043] The clearing transaction processing procedure consists of accepting multiple batch processing services at one time, where each batch processing service is chain-connected and each batch processing service executes different transaction processing logic in the clearing transaction. The number of batch processing services can be determined based on the data size of the accepted traffic and can also be manually set by the transaction developer, and no specific limitation is made here.

[0044] It should be noted that each batch service has a first service baseline and a second service baseline, wherein the first service baseline represents the baseline after the transaction execution code or configuration file is changed, and the second service baseline represents the baseline before any change occurs to the transaction execution code or configuration file.

[0045] Taking a batch processing service among the batch processing services as an example, if the batch processing service is the first batch processing service executed among the batch processing services, the initial output data can be used as the first input data of the batch processing service, and the first service baseline of the batch processing service can be called to perform transaction processing on the first input data to obtain the first output data generated under the first service baseline, and the first output data can be used as the first shard data of the first batch processing service under the first service baseline. The second service baseline of the batch processing service can be called to perform transaction processing on the first input data to obtain the second output data under the second service baseline, and the second output data can be used as the second shard data of the first batch processing service under the second service baseline.

[0046] If the batch service is not the first batch service to be executed, the first shard data of the last executed batch service is used as the input data of the batch service. The input data is subjected to transaction processing based on the first service baseline of the batch service to obtain the first output data generated by the batch service under the first service baseline, and the first output data is used as the first shard data of the batch service under the first service baseline. The second service baseline of the batch service is called to perform transaction processing on the input data to obtain the second output data generated by the batch service under the second service baseline, and the second output data is used as the second shard data of the batch service under the second service baseline.

[0047] It should be noted that sharded data is distributed across multiple physical or logical nodes, mainly used to improve data processing efficiency, enhance data availability and disaster recovery capabilities, and avoid single point failures.

[0048] Furthermore, the first shard data and the second shard data are compared to determine whether the transaction execution results of the batch service under the first service baseline and the second service baseline for the input data meet the transaction processing expectations corresponding to the transaction processing logic of the batch service, and are recorded in the form of a log file. After the transaction execution of the first service baseline and the second service baseline of the batch service is completed, the first shard data of the batch service is used as the input data of the next batch service to be executed under the first service baseline, and the second shard data of the batch service is used as the input data of the next batch service to be executed under the second service baseline, and the steps of generating the first shard data and the second shard data of the batch service as described above are performed, which will not be repeated here.

[0049] After all batch services are executed, the first shard data generated by each batch service is assembled to generate the first baseline data, and the second shard data generated by each batch service is assembled to generate the second baseline data. At this time, the first baseline data and the second baseline data can be compared and analyzed to determine whether the overall execution effect of the clearing transaction meets the transaction expectations of the clearing transaction. If there is abnormal data, the batch service with the abnormality can be determined by querying the record log.

[0050] In the embodiments of this specification, by obtaining the acceptance flow and input data of the clearing affairs in the transaction acceptance stage, the characteristics and requirements of the clearing affairs can be grasped. By determining the input data characteristics corresponding to the acceptance flow to generate the acceptance flow baseline, the flow and characteristics of the clearing affairs can be controlled to improve the clearing efficiency. By determining the service flow baseline after determining the baseline of each batch service by calling the acceptance service, it is helpful to fully grasp the key performance indicators of the clearing service. Based on this, the first baseline data and the second baseline data are generated and compared, thus avoiding the limitation of only collecting and detecting synchronous online transaction flow. At the same time, since the acceptance flow in the clearing affairs covers various transaction flows, by processing and comparing various aspects of the baseline data, data loss can be avoided, and the accuracy of transaction execution is guaranteed, thereby improving the execution efficiency of the clearing affairs while ensuring data integrity.

[0051] based on Figure 1 The system architecture diagram shown below will be combined with Figure 2-Figure 11 , a method for executing a liquidation transaction provided in an embodiment of this specification is introduced in detail.

[0052] Based on the above situation, this specification embodiment proposes a method for executing a liquidation transaction. Figure 2 , Figure 2 1 is a flow chart of a method for executing a liquidation transaction provided in an embodiment of this specification. Figure 2 As shown, the method of the embodiment of this specification may include the following steps S101-S106.

[0053] S101, obtaining the acceptance flow generated by the clearing affairs, and obtaining characteristic data in each acceptance flow.

[0054] In the embodiments of this specification, a clearing transaction may refer to a process in which a paying user completes the exchange of payment instructions in accordance with specific rules and calculates the results of the debts and claims to be settled. Accepted traffic refers to the data traffic carried in the clearing transaction request received by the clearing transaction processing program within a certain period of time. Feature data refers to part or all of the feature data extracted from the input data of the user who accepts the traffic.

[0055] Specifically, the user generates a clearing transaction request through a terminal device and sends the clearing transaction request to a clearing transaction processing program so that the clearing transaction processing program enters a transaction acceptance stage. When the clearing transaction processing program is in the transaction acceptance stage, the clearing transaction request is parsed to obtain the acceptance traffic corresponding to the clearing transaction request. At the same time, the acceptance traffic is analyzed to obtain characteristic data from the input data of the user of the acceptance traffic, wherein the user's input data includes at least clearing subject data, clearing account data and clearing time data.

[0056] S102: Process the characteristic data based on the acceptance flow baseline of the clearing transaction to obtain initial output data corresponding to the acceptance flow.

[0057] In the embodiment of the present specification, the acceptance flow baseline refers to a service baseline that establishes an association relationship based on characteristic data of each acceptance flow and its corresponding user input data during the clearing transaction processing.

[0058] Specifically, in the transaction acceptance stage of the clearing transaction processing program, feature analysis is performed on the user's input data in each accepted flow, and key data such as the clearing subject, clearing account number, and clearing time are extracted to form feature data corresponding to the accepted flow.

[0059] Furthermore, each accepted flow is associated with its corresponding characteristic data in the accepted flow baseline to generate initial output data. The establishment of such an association relationship can more accurately track and analyze the specific characteristics and changes of each accepted flow.

[0060] Please also read Figure 3 , Figure 3 Schematic diagram of a scenario of a method for executing a clearing transaction provided in an embodiment of this specification. Figure 3 As shown in the figure, there are three acceptance flows, namely, acceptance flow A, acceptance flow B, and acceptance flow C. After feature analysis and extraction of input data in acceptance flow A, acceptance flow B, and acceptance flow C, feature a corresponding to acceptance flow A, feature b corresponding to acceptance flow B, and feature c corresponding to acceptance flow C are obtained. The acceptance flow and the corresponding features are combined through the acceptance flow baseline, and the data is saved in the form of a set to obtain the initial output data corresponding to the acceptance flow.

[0061] S103: Determine the number of batch processing services required for the clearing transaction and the first service baseline corresponding to each batch processing service based on the acceptance flow baseline.

[0062] In the embodiments of this specification, the number of batch services is not fixed, but can be automatically set according to the amount of data in the accepted traffic baseline or can be set by the transaction developer according to the actual transaction scenario.

[0063] Specifically, when the amount of data in the acceptance traffic baseline increases significantly, this usually means that the transaction demand has risen sharply. At this time, the pre-set rules or algorithms can be called to automatically increase the number of batch services to quickly improve the concurrent processing capabilities of the system and avoid transaction delays or system crashes caused by insufficient processing capabilities. When the amount of data in the acceptance traffic baseline decreases, the number of batch service programs will be automatically reduced accordingly to save computer resources and reduce operating costs. At the same time, transaction developers can manually adjust the number of batch services based on actual transaction scenarios. For example, when the amount of data in the acceptance traffic surges briefly, transaction developers can increase the number of batch services in advance to ensure that they can smoothly cope with peak transaction demands. Similarly, during maintenance and upgrades, in order to reduce risks, transaction developers can manually reduce the number of batch programs to ensure the stability and security of the system.

[0064] After determining the number of batch services, the accepted traffic is sorted according to the preset transaction execution priority rules. The transaction type of each accepted traffic is determined by analyzing the characteristic data associated with each accepted traffic, and the first service baseline of each batch service is determined based on the transaction type.

[0065] S104, obtaining a second service baseline corresponding to each batch processing service, where the second service baseline is a baseline of each batch processing service before the transaction is changed.

[0066] In the embodiment of the present specification, the second service baseline refers to a baseline before any change occurs to the transaction execution code or configuration.

[0067] Specifically, developers will record the version information of all relevant execution codes and configuration files in the current transaction acceptance stage to ensure that this information can accurately reflect the initial state of the clearing transaction; these initial state execution codes and configuration files will be locked and recorded as the second service baseline.

[0068] S105 , calling each batch processing service and generating first baseline data of each batch processing service under a first service baseline and second baseline data of each batch processing service under a second service baseline based on the initial output data.

[0069] Specifically, the configuration environment of the first service baseline in each batch service is called to process the input data of the first service baseline, and the first shard data generated by each batch service under the first service baseline is obtained. The first shard data of each batch service is integrated to form a complete first baseline data. The configuration environment of the second service baseline in each batch service is called to process the input data of the second service baseline, and the second shard data generated by each batch service under the second service baseline is obtained. The second shard data of each batch service is integrated to form a complete second baseline data.

[0070] S106: Generate a baseline data comparison result based on the first baseline data and the second baseline data.

[0071] Specifically, after all batch services are executed, the first shard data generated by each batch service during the execution process is collected and assembled. This process involves checking, sorting and merging the shard data one by one to ensure the integrity and accuracy of the data. After the assembly is completed, the first baseline data of the execution results of all batch services under the first service baseline is formed. The second shard data is processed in the same way, and the second shard data generated by each batch service is assembled to generate the second baseline data generated by all batch services under the second service baseline.

[0072] Compare the first baseline data with the second baseline data to evaluate whether the transaction execution results of the clearing transaction under different baselines meet the transaction processing expectations corresponding to the transaction processing logic of the batch service. If abnormal data is found during the comparative analysis, query the detailed record log attached to each shard data to accurately locate the specific batch service that generated the abnormal data. The record log contains key information such as the batch service number, execution time, processed data range, and configuration parameters used. This information can help developers quickly diagnose problems and determine which batch service has data anomalies during the processing process, so as to take corresponding measures to repair and optimize.

[0073] As can be seen from the above, by obtaining the acceptance flow and input data of clearing affairs at each acceptance stage, the characteristics and needs of clearing affairs can be mastered. By determining the input data characteristics corresponding to the acceptance flow to generate the acceptance flow baseline, the flow and characteristics of clearing affairs can be controlled and the clearing efficiency can be improved. After calling the acceptance service to determine the baseline of each batch service, the service flow baseline is determined, which helps to fully grasp the key performance indicators of the clearing service. Based on this, the first baseline data and the second baseline data are generated and compared, thus avoiding the limitation of only collecting and detecting synchronous online transaction flow. At the same time, since the acceptance flow in clearing affairs covers various transaction flow situations, under this framework, the processing and comparison of multiple baseline data can avoid data loss and ensure the accuracy of transaction decision-making, thereby optimizing the clearing process as a whole, improving management efficiency, and improving the execution efficiency of clearing affairs while ensuring data integrity.

[0074] Since there is a large amount of traffic data in the accepted traffic, and not all traffic data needs to participate in transaction processing, it is necessary to process the traffic data to improve the overall transaction processing speed. Figure 4 , Figure 4 1 is a flow chart of a method for executing a liquidation transaction provided in an embodiment of this specification. Figure 4 As shown, the method of the embodiment of this specification may include the following steps S201-S205.

[0075] S201, acquiring transaction settlement data of each accepted flow from input data corresponding to each accepted flow.

[0076] S202: Determine characteristic data of input data corresponding to each accepted flow based on the transaction settlement data.

[0077] Specifically, in S201-S202, the transaction clearing data extracts the data features of the clearing service request sent by the user to obtain the feature data corresponding to each accepted flow, such as the payment amount and payment object entered by the user. The specific type of feature data can be set according to the transaction scenario requirements and is not specifically limited here.

[0078] S203, obtaining the clearing entity data, clearing account data and clearing time data in the input data of each accepted flow.

[0079] In the embodiments of this specification, the data extracted from the input data includes but is not limited to: clearing entity data, that is, the entities involved in the clearing transaction, such as banks, payment institutions, etc.; clearing account data, that is, the specific account information used for clearing to ensure that funds can be transferred accurately; clearing time data, that is, the exact time point or time period when the clearing transaction occurs, which helps to track and record the transaction status.

[0080] For example, in a payment process, the participants in the clearing entity data obtained are Bank X and Bank Y, and the clearing account data is extracted to ensure that the transfer amount can be accurately transferred from the user's Bank X account to the payee's Bank Y account. At the same time, the clearing time data is recorded, such as the transaction initiation time, the fund clearing completion time, etc., for subsequent query and verification.

[0081] S204, generating a clearing data tuple based on the clearing subject data, the clearing account data and the clearing time data.

[0082] S205, filtering the clearing data tuples to generate transaction clearing data corresponding to each accepted flow, and determining the transaction clearing data as feature data of the input data corresponding to each accepted flow.

[0083] Specifically, in S304-S305, the clearing data tuple is a set of traffic characteristics of the acceptance traffic generated by the clearing subject data, clearing account data and clearing time data extracted from the input data of each acceptance traffic. By way of example, taking a specific clearing transaction as an example, the clearing subject data obtained are X and Y, indicating that X pays Y, the clearing account data are x and y, and the clearing time data is 15, then the clearing data tuple obtained is (X, Y, x, y, 15:00).

[0084] The flow feature set of each accepted flow is obtained in the above manner. At the same time, if it is detected that the data in the clearing data tuple of the accepted flow is the same, then a clearing data tuple is retained, and the retained clearing data tuple data is shared with the same accepted volume. After deduplication and filtering of the clearing data tuple of each accepted flow, the flow feature set generated by the clearing data tuple of each accepted flow is determined as the feature data corresponding to each accepted flow.

[0085] From the above, we can see that by obtaining the clearing subject data, clearing account data and clearing time data in the input data of each accepted flow, we can accurately identify and record the key elements such as the participants, account information and transaction time of each transaction, so as to provide a structured and standardized data basis for subsequent data processing. By further filtering the clearing data tuples, the transaction clearing data corresponding to each accepted flow can be screened out, thereby ensuring the accuracy and validity of the characteristic data in the input data corresponding to each accepted flow.

[0086] Since the batch service cannot obtain the output data of each batch processing stage in the asynchronous execution process, it is necessary to design the service structure of the batch service to obtain the output data of each batch service. Figure 5 , Figure 5 1 is a flow chart of a method for executing a liquidation transaction provided in an embodiment of this specification. Figure 5 As shown, the method of the embodiment of this specification may include the following steps S301-S302.

[0087] S301, calling each batch processing service and generating first fragmented data corresponding to each batch processing service under a first service baseline based on initial output data, and assembling each first fragmented data to generate first baseline data.

[0088] Specifically, a target batch service is determined from each batch service. If the target batch service is the first batch service, that is, the target batch service is the first batch service to be executed, the initial output data is used as the input data of the target batch service under the first service baseline. Subsequently, the input data is processed under the configuration environment of the first service baseline to generate the first shard data of the target batch service. If the target batch service is the Nth batch service, the first shard data generated by the previous batch service is obtained and used as the input data of the first service baseline in the target batch service, where N is a positive integer greater than 1, and the Nth batch service indicates that the target batch service is any batch service other than the first batch service. Similarly, the input data is processed under the configuration environment of the first service baseline to generate the first shard data corresponding to the target batch service under the first service baseline. After all batch services have been processed in sequence, the first shard data obtained by all batch services are integrated to form a complete first baseline data.

[0089] S302, calling each batch processing service and initially outputting data, generating second fragmented data corresponding to each batch processing service under a second service baseline, and assembling each second fragmented data to generate second baseline data.

[0090] Specifically, if the target batch service is the first batch service, the initial output data is used as the input data of the target batch service under the second service baseline, and the input data is processed under the configuration environment of the second service baseline to generate the second shard data of the target batch service. If the target batch service is the Nth batch service, the second shard data of the previous batch service is obtained as the input data of the second service baseline in the target batch service, and the input data is processed under the second service baseline to generate the second shard data of the target batch service. Finally, the second shard data of all batch services are integrated to form a complete second baseline data.

[0091] In a possible implementation, please refer to Figure 6 , Figure 6 Schematic diagram of a scenario of a method for executing a clearing transaction provided in an embodiment of this specification. Figure 6As shown, the initial output data is used as the input data of the first service baseline and the second service baseline in batch service 1, wherein the first service baseline and the second service baseline run in parallel in the same operation space. After the transaction processing in the first service baseline, the first shard data is obtained, and after the second service baseline, the second shard data is obtained. The first shard data of batch service 1 is used as the input data of the first service baseline of batch service 2, and the second shard data of batch service 1 is used as the input data of the second service baseline of batch service 2. After the transaction processing in the first service baseline of batch service 2, the first shard data of batch service 2 is obtained, and after the second service baseline, the second shard data of batch service 2 is obtained.

[0092] exist Figure 6 In the scenario diagram shown, the comparison process of the shard data occurs during the execution of each batch service. After the first shard data and the second shard data of batch service 1 are obtained, the first shard data and the second shard data are compared and analyzed, and the data analysis results are recorded and saved in the form of a log. After the first shard data and the second shard data of batch service 2 are obtained, the first shard data and the second shard data of batch service 2 are compared and analyzed, and the data analysis results are recorded and saved in the form of a log.

[0093] In another possible implementation, please refer to Figure 7 , Figure 7 Schematic diagram of a scenario of a method for executing a clearing transaction provided in an embodiment of this specification. Figure 7 As shown, the initial output data is used as the input data of the first service baseline and the second service baseline in batch service 1, wherein the first service baseline and the second service baseline run in parallel in the same operation space. After the transaction processing in the first service baseline, the first shard data is obtained, and after the second service baseline, the second shard data is obtained. The first shard data of batch service 1 is used as the input data of the first service baseline of batch service 2, and the second shard data of batch service 1 is used as the input data of the second service baseline of batch service 2. After the transaction processing in the first service baseline of batch service 2, the first shard data of batch service 2 is obtained, and after the second service baseline, the second shard data of batch service 2 is obtained.

[0094] exist Figure 7In the scenario diagram shown, the first service baseline and the second service baseline run in different running spaces. After all batch services are executed, the first shard data and the second shard data of each batch service are uniformly acquired, and after data comparison and analysis, the data analysis results are recorded and saved in the form of logs. That is, the comparison process of shard data occurs after all batch services are executed.

[0095] As can be seen above, by chaining batch services, it is possible to ensure smooth data flow between batch services and reduce abnormal problems caused by data loss. In addition, by comparing and recording shard data, it is helpful to monitor and track the execution efficiency of the entire transaction in real time, and to promptly discover abnormal problems, further ensuring the execution stability of the entire clearing transaction process.

[0096] To improve the efficiency of liquidation transactions. Figure 8 , Figure 8 1 is a flow chart of a method for executing a liquidation transaction provided in an embodiment of this specification. Figure 8 As shown, the method of the embodiment of this specification may include the following steps S401-S403.

[0097] S401, if the target batch processing service is the first batch processing service among the batch processing services, the initial output data is determined as the first input data of the target batch processing service under the first service baseline, and the target batch processing service is called to process the first input data under the first service baseline to generate the first shard data of the target batch processing service.

[0098] Exemplarily, there are batch service O, batch service P and batch service Q respectively, where batch service O is the target batch service, that is, batch service O is the first batch service to be executed. At this time, the initial output data is determined as the first input data under the first service baseline of batch service O, and the first service baseline in batch service O is called to process the first input data to generate the first shard data of batch service O.

[0099] S402: If the target batch processing service is the Nth batch processing service among the batch processing services, the first shard data of the previous batch processing service of the target batch processing service is determined as the first input data of the target batch processing service under the first service baseline, and the target batch processing service is called to process the first input data under the first service baseline to generate the first shard data of the target batch processing service, where N is a positive integer greater than 1.

[0100] Exemplarily, according to the above example, there are batch service O, batch service P and batch service Q respectively, wherein batch service P is the target batch service and is determined to be the second batch service to be executed, and the batch service executed before batch service P is batch service O. At this time, the first shard data of batch service O is determined as the first input data under the first service baseline in batch service P, and the first input data is transactionally processed through the first service baseline in batch service P to obtain the first shard data of the first service baseline of batch service P.

[0101] S403: Assemble the first fragment data of each target batch service to generate first baseline data.

[0102] Exemplarily, according to the above example, there are batch service O, batch service P and batch service Q respectively, and batch service Q is the last batch service and after execution, the first shard data generated by batch service O, batch service P and batch service Q under the first service baseline are assembled. For example, the first shard data of batch service O is shard data o, the first shard data of batch service P is shard data p, and the first shard data of batch service Q is shard data q. Shard data o, shard data p and shard data q are assembled to generate the first baseline data.

[0103] Of course, the numbers of the above three batch processing services are only for illustration, and the specific numbers can be set according to actual transaction requirements.

[0104] As can be seen from the above, by determining the input data of each batch service and generating the first shard data, and finally assembling it into the first baseline data, the accuracy and efficiency of the data processing process can be effectively improved. In terms of determining the input data, the initial input of the first batch service and the relay input of subsequent batches are clarified to avoid data confusion and erroneous transmission. Each batch service operates according to a unified service baseline to ensure the consistency of processing logic. This model makes the data processing process have a clear context and is easy to monitor and debug. Moreover, the process of assembling the first shard data to form the first baseline data provides a reliable and complete data foundation for subsequent in-depth analysis, decision-making or model training based on the baseline data, which helps to improve the efficiency of the entire transaction processing system in dealing with complex transaction requirements.

[0105] To further improve the efficiency of liquidation transactions, please refer to Fig. 9 , Fig. 9 1 is a flow chart of a method for executing a liquidation transaction provided in an embodiment of this specification. Fig. 9 As shown, the method of the embodiment of this specification may include the following steps S501-S503.

[0106] S501, if the target batch processing service is the first batch processing service among the batch processing services, the initial output data is determined as the second input data of the target batch processing service under the second service baseline, and the target batch processing service is called to process the second input data under the second service baseline to generate second shard data of the target batch processing service.

[0107] Exemplarily, there are batch service O, batch service P and batch service Q respectively, where batch service O is the target batch service and batch service O is the first batch service to be executed. At this time, the initial output data is determined as the first input data of batch service O under the second service baseline, and the second service baseline in batch service O is called to process the second input data to generate second shard data of batch service O.

[0108] S502: If the target batch processing service is the Nth batch processing service among the batch processing services, the second shard data of the previous batch processing service of the target batch processing service is determined as the second input data of the target batch processing service under the second service baseline, and the target batch processing service is called to process the second input data under the second service baseline to generate the second shard data of the target batch processing service, where N is a positive integer greater than 1.

[0109] Exemplarily, according to the above example, there are batch service O, batch service P and batch service Q respectively, wherein batch service P is the target batch service and is determined to be the second batch service to be executed among the batch services, and the batch service executed before batch service P is batch service O. At this time, the second shard data of batch service O is determined as the second input data under the second service baseline in batch service P, and the second input data is processed through the second service baseline in batch service P to obtain the second shard data generated by batch service P under the second service baseline.

[0110] S503: Assemble the second fragment data of each target batch service to generate second baseline data.

[0111] Exemplarily, according to the above example, there are batch service O, batch service P and batch service Q respectively, and batch service Q is the last batch service and after execution, the second shard data generated by batch service O, batch service P and batch service Q under the second service baseline are assembled. For example, the second shard data of batch service O is shard data o, the second shard data of batch service P is shard data p, and the second shard data of batch service Q is shard data q. Shard data o, shard data p and shard data q are assembled to generate second baseline data.

[0112] Of course, the numbers of the above three batch processing services are only for illustration, and the specific numbers can be set according to actual transaction requirements.

[0113] As can be seen from the above, by determining the input data of each batch service and generating the second shard data, and finally assembling it into the second baseline data, the accuracy and efficiency of the data processing process can be effectively improved. In terms of determining the input data, the initial input of the first batch service and the relay input of the subsequent batches are clarified to avoid data confusion and erroneous transmission. Each batch service operates according to a unified service baseline to ensure the consistency of the processing logic. This model makes the data processing process have a clear context and is easy to monitor and debug. Moreover, the process of assembling the second shard data to form the second baseline data provides a reliable and complete data foundation for subsequent in-depth analysis, decision-making or model training based on the baseline data, which helps to improve the efficiency of the entire transaction processing system in dealing with complex transaction requirements.

[0114] In one implementation, the method of the embodiment of this specification may include the following steps.

[0115] The first shard data of the target batch processing service is compared with the second shard data to determine a comparison result of the shard data of the target batch processing service.

[0116] Please also read Fig.10 , Fig.10 Schematic diagram of a scenario of a method for executing a clearing transaction provided in an embodiment of this specification. Fig.10 As shown, each batch service has a first service baseline and a second service baseline. The first service baseline is called to process the input data to obtain the output data corresponding to the first service baseline and use it as the first shard data. The second service baseline is called to process the input data to obtain the output data corresponding to the second service baseline and use it as the second shard data.

[0117] Furthermore, the first shard data and the second shard data are compared to determine whether the transaction processing execution results of the first service baseline and the second service baseline for the input data in the batch service meet the transaction processing expectations of the batch service. After the batch service is executed, the first shard data generated by the batch service is assembled to generate the first baseline data, and the second shard data generated by each batch service is assembled to generate the second baseline data. The first baseline data and the second baseline data are compared and analyzed to determine whether the overall execution effect of the clearing transaction meets the transaction expectations. If there is abnormal data, it can be determined which batch service has data anomalies by querying the record log of the shard data.

[0118] In one implementation, the method of the embodiment of this specification may include the following steps.

[0119] If a traffic change in the acceptance traffic and / or a service change in the acceptance service is detected, the service traffic baseline of the clearing transaction is rebuilt.

[0120] In the embodiment of the present specification, if it is detected that the acceptance flow has changed, then the service flow baseline of the clearing transaction needs to be rebuilt.

[0121] For example, in a payment system, as a promotion progresses, the acceptance traffic may experience peak changes. In order to ensure the stability and efficiency of the payment system, when a traffic change is detected, the reconstruction process of the service traffic baseline is automatically triggered. Specifically, first, the changes in traffic peaks are captured through real-time monitoring tools, and the impact of such changes on key performance indicators such as payment processing speed and success rate is analyzed. Through traffic playback technology, the previously captured peak traffic data is replayed to simulate high load conditions in a real environment. Potential performance bottlenecks are identified by comparing peak traffic data with current service performance data. Finally, based on the analysis results, the configuration of the payment system is optimized and adjusted, and the service traffic baseline is updated to ensure that in future promotions, the payment system can cope with similar traffic changes and maintain stable performance.

[0122] From the above, we can see that by automatically clearing transactions and rebuilding the service flow baseline of clearing transactions in a timely manner when facing changes in flow and service, it can ensure that clearing transactions maintain a high degree of adaptability and stability in real time when facing flow fluctuations or service adjustments.

[0123] based on Figure 1 The system architecture will be combined with Fig.11 , the execution device of the liquidation affairs provided in the embodiment of this specification is introduced in detail. It should be noted that, Fig.11 The execution device of the liquidation affairs in the Figure 2-Figure 10 For the convenience of explanation, only the part related to the embodiment of this specification is shown. For the specific technical details not disclosed, please refer to this specification. Figure 2-Figure 10 In the embodiment shown, the clearing transaction execution device 600 may include a data acquisition unit 601, a data processing unit 602, a transaction determination unit 603, a baseline acquisition unit 604, a service calling unit 605, and a data comparison unit 606, as follows:

[0124] The data acquisition unit 601 is used to acquire the acceptance flow generated by the clearing transaction and acquire characteristic data in each acceptance flow;

[0125] The data processing unit 602 is used to process the characteristic data based on the acceptance flow baseline of the clearing transaction to obtain initial output data corresponding to the acceptance flow;

[0126] The transaction determination unit 603 is used to determine the number of batch processing services required for the clearing transaction and the first service baseline corresponding to each batch processing service based on the accepted traffic baseline;

[0127] A baseline acquisition unit 604 is used to acquire a second service baseline corresponding to each batch processing service, where the second service baseline is a baseline of each batch processing service before the transaction is changed;

[0128] A service calling unit 605 is used to call each batch processing service and generate first baseline data of each batch processing service under a first service baseline and second baseline data of each batch processing service under a second service baseline based on the initial output data;

[0129] The data comparison unit 606 is configured to generate a baseline data comparison result based on the first baseline data and the second baseline data.

[0130] In some embodiments, the data acquisition unit 601 further includes a clearing data acquisition unit and a feature data acquisition unit.

[0131] A clearing data acquisition unit, used to acquire transaction clearing data of each accepted flow from input data corresponding to each accepted flow;

[0132] The characteristic data acquisition unit is used to determine the characteristic data of the input data corresponding to each accepted flow based on the transaction settlement data.

[0133] In some embodiments, the data acquisition unit 601 further includes a data analysis unit, a data generation unit, and a data filtering unit.

[0134] A data analysis unit, used to obtain clearing subject data, clearing account data and clearing time data from the input data of each accepted flow;

[0135] A data generating unit, used for generating a clearing data tuple based on the clearing subject data, the clearing account data and the clearing time data;

[0136] The data filtering unit is used to filter the clearing data tuples, generate transaction clearing data corresponding to each accepted flow, and determine the transaction clearing data as feature data of the input data corresponding to each accepted flow.

[0137] In some embodiments, the service calling unit 605 further includes a first calling unit and a second calling unit.

[0138] A first calling unit is used to call each batch processing service and generate first shard data corresponding to each batch processing service under a first service baseline based on the initial output data, and assemble each first shard data to generate first baseline data;

[0139] The second calling unit is used to call each batch processing service and generate second fragment data corresponding to each batch processing service under the second service baseline based on the initial output data, and assemble each second fragment data to generate second baseline data.

[0140] In some embodiments, the service calling unit 605 further includes a first determining unit, a second determining unit and a first assembling unit.

[0141] A first determination unit is configured to, if the target batch processing service is the first batch processing service among the batch processing services, determine the initial output data as the first input data of the target batch processing service under the first service baseline, call the target batch processing service to process the first input data under the first service baseline, and generate first shard data of the target batch processing service;

[0142] a second determination unit, configured to, if the target batch processing service is the Nth batch processing service among the batch processing services, determine the first shard data of the previous batch processing service of the target batch processing service as the first input data of the target batch processing service under the first service baseline, call the target batch processing service to process the first input data under the first service baseline, and generate the first shard data of the target batch processing service, where N is a positive integer greater than 1;

[0143] The first assembling unit is used to assemble the first shard data of each target batch processing service to generate first baseline data.

[0144] In some embodiments, the service calling unit 605 further includes a third determining unit, a fourth determining unit and a second assembling unit.

[0145] a third determination unit, configured to, if the target batch processing service is the first batch processing service among the batch processing services, determine the initial output data as the second input data of the target batch processing service under the second service baseline, call the target batch processing service to process the second input data under the second service baseline, and generate second shard data of the target batch processing service;

[0146] a fourth determination unit, configured to, if the target batch processing service is the Nth batch processing service among the batch processing services, determine the second shard data of the previous batch processing service of the target batch processing service as the second input data of the target batch processing service under the second service baseline, call the target batch processing service to process the second input data under the second service baseline, and generate the second shard data of the target batch processing service, where N is a positive integer greater than 1;

[0147] The second assembling unit assembles the second fragmented data of each target batch processing service to generate second baseline data.

[0148] In some embodiments, the service calling unit 605 also includes a fragment data comparison unit.

[0149] The shard data comparison unit is used to compare the first shard data and the second shard data of the target batch processing service to determine the shard data comparison result of the target batch processing service

[0150] In some embodiments, a baseline changing unit is further included.

[0151] The baseline changing unit is used to change the service flow baseline of the clearing transaction if it is detected that the acceptance flow has changed and / or the acceptance service has changed.

[0152] In the embodiments of this specification, by obtaining the acceptance flow and input data of the clearing affairs at each acceptance stage, the characteristics and requirements of the clearing affairs can be grasped. By determining the input data characteristics corresponding to the acceptance flow to generate the acceptance flow baseline, the flow and characteristics of the clearing affairs can be controlled and the clearing efficiency can be improved. After calling the acceptance service to determine the baseline of each batch service, the service flow baseline is determined, which helps to fully grasp the key performance indicators of the clearing service. Based on this, the first baseline data and the second baseline data are generated and compared, thus avoiding the limitation of only collecting and detecting synchronous online transaction flow. At the same time, since the acceptance flow in the clearing affairs covers various transaction flow situations, under this framework, the processing and comparison of multiple baseline data can avoid data loss and ensure the accuracy of transaction decision-making, thereby optimizing the clearing process as a whole, improving management efficiency, and improving the execution efficiency of clearing affairs while ensuring data integrity.

[0153] In addition, the execution device of the liquidation affairs provided in the above embodiment and the embodiment of a method for executing liquidation affairs belong to the same concept, and the embodiment and implementation process thereof are detailed in the method embodiment, which will not be repeated here.

[0154] The serial numbers of the embodiments of the present specification are for description only and do not represent the advantages and disadvantages of the embodiments. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0155] See also Fig.12 , is a schematic diagram of the structure of an electronic device provided in the embodiment of this specification. Fig.12As shown, the electronic device 700 includes a processor 701 and a memory 702. The processor 701 is electrically connected to the memory 702.

[0156] The processor 701 is the control center of the electronic device 700 and may include one or more processing cores. The processor 701 uses various interfaces and lines to connect various parts of the entire electronic device, and executes various functions of the electronic device and processes data by running or calling computer programs stored in the memory 702, and calling data stored in the memory 702, so as to control the electronic device as a whole. Optionally, the processor 701 can be implemented in at least one hardware form of digital signal processing (DSP), field programmable gate array (FPGA), and programmable logic array (PLA). The processor 701 can integrate one or a combination of CPU, graphics processing unit (GPU), modem, etc. Among them, the CPU mainly processes the operating system, user pages, and applications; the GPU is responsible for rendering and drawing display content; and the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 701, and may be implemented separately through a communication chip.

[0157] The memory 702 can be used to store software programs and modules. The processor 701 executes various functional applications and clearing transactions by running the computer programs and modules stored in the memory 702. The memory 702 can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, a computer program required for at least one function, etc.; the data storage area can store data created according to the use of the electronic device, etc.

[0158] In addition, the memory 702 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices. Accordingly, the memory 702 may also include a memory controller to provide the processor 701 with access to the memory 702.

[0159] In the embodiment of the present specification, the processor 701 in the electronic device 700 will load instructions corresponding to the processes of one or more computer programs into the memory 702 according to the following steps, and the processor 701 will run the computer program stored in the memory 702 to implement various functions, as follows:

[0160] Acquire the acceptance traffic generated by the clearing transaction, and acquire characteristic data in each acceptance traffic; process the characteristic data based on the acceptance traffic baseline of the clearing transaction to obtain initial output data corresponding to the acceptance traffic; determine the number of batch services required for the clearing transaction and the first service baseline corresponding to each batch service based on the acceptance traffic baseline; acquire the second service baseline corresponding to each batch service, the second service baseline being the baseline of each batch service before the transaction is changed; call each batch service and generate first baseline data of each batch service under the first service baseline and second baseline data of each batch service under the second service baseline based on the initial output data; generate baseline data comparison results based on the first baseline data and the second baseline data.

[0161] Optionally, the processor 701, when executing to obtain characteristic data in each accepted flow, specifically executes: obtaining transaction settlement data of each accepted flow from input data corresponding to each accepted flow; and determining characteristic data of the input data corresponding to each accepted flow based on the transaction settlement data.

[0162] Optionally, the processor 701 determines the characteristic data of the input data corresponding to each accepted flow based on the transaction clearing data, and specifically performs the following steps: obtaining the clearing subject data, clearing account data and clearing time data in the input data of each accepted flow; generating a clearing data tuple based on the clearing subject data, clearing account data and clearing time data; filtering the clearing data tuple to generate the transaction clearing data corresponding to each accepted flow, and determining the transaction clearing data as the characteristic data of the input data corresponding to each accepted flow.

[0163] Optionally, when executing the call to each batch processing service and generating the first baseline data of each batch processing service under the first service baseline based on the initial output data, and the second baseline data of each batch processing service under the second service baseline, the processor 701 specifically performs: calling each batch processing service and generating the first shard data corresponding to each batch processing service under the first service baseline based on the initial output data, and assembling each first shard data to generate the first baseline data; calling each batch processing service and generating the second shard data corresponding to each batch processing service under the second service baseline based on the initial output data, and assembling each second shard data to generate the second baseline data.

[0164] Optionally, the processor 701 executes the call to each batch processing service and generates the first shard data corresponding to each batch processing service under the first service baseline based on the initial output data, and assembles each first shard data to generate the first baseline data. Specifically, if the target batch processing service is the first batch processing service among the batch processing services, the initial output data is determined as the first input data of the target batch processing service under the first service baseline, and the target batch processing service is called to process the first input data under the first service baseline to generate the first shard data of the target batch processing service; if the target batch processing service is the Nth batch processing service among the batch processing services, the first shard data of the previous batch processing service of the target batch processing service is determined as the first input data of the target batch processing service under the first service baseline, and the target batch processing service is called to process the first input data under the first service baseline to generate the first shard data of the target batch processing service, where N is a positive integer greater than 1; the first shard data of each target batch processing service are assembled to generate the first baseline data.

[0165] Optionally, when executing the call to each batch processing service and based on the initial output data, the processor 701 generates the second shard data corresponding to each batch processing service under the second service baseline, and assembles each second shard data to generate the second baseline data. Specifically, if the target batch processing service is the first batch processing service among the batch processing services, the initial output data is determined as the second input data of the target batch processing service under the second service baseline, and the target batch processing service is called to process the second input data under the second service baseline to generate the second shard data of the target batch processing service; if the target batch processing service is the Nth batch processing service among the batch processing services, the second shard data of the previous batch processing service of the target batch processing service is determined as the second input data of the target batch processing service under the second service baseline, and the target batch processing service is called to process the second input data under the second service baseline to generate the second shard data of the target batch processing service, where N is a positive integer greater than 1; the second shard data of each target batch processing service are assembled to generate the second baseline data.

[0166] Optionally, the processor 701 is further configured to specifically perform: comparing the first shard data and the second shard data of the target batch processing service to determine a comparison result of the shard data of the target batch processing service.

[0167] Optionally, the processor 701 is further configured to specifically execute: if a traffic change in the acceptance traffic and / or a service change in the acceptance service is detected, then the service traffic baseline of the clearing transaction is changed.

[0168] In the embodiments of this specification, by obtaining the acceptance flow and input data of the clearing affairs at each acceptance stage, the characteristics and requirements of the clearing affairs can be grasped. By determining the input data characteristics corresponding to the acceptance flow to generate the acceptance flow baseline, the flow and characteristics of the clearing affairs can be controlled and the clearing efficiency can be improved. After calling the acceptance service to determine the baseline of each batch service, the service flow baseline is determined, which helps to fully grasp the key performance indicators of the clearing service. Based on this, the first baseline data and the second baseline data are generated and compared, thus avoiding the limitation of only collecting and detecting synchronous online transaction flow. At the same time, since the acceptance flow in the clearing affairs covers various transaction flow situations, under this framework, the processing and comparison of multiple baseline data can avoid data loss and ensure the accuracy of transaction decision-making, thereby optimizing the clearing process as a whole, improving management efficiency, and improving the execution efficiency of clearing affairs while ensuring data integrity.

[0169] In addition, the device provided in the embodiments of this specification may specifically be a chip, component or module, and the chip may include a connected processor and memory; wherein the memory is used to store instructions, and when the processor calls and executes the instructions, the chip can execute a method for executing a clearing transaction provided in the above embodiments.

[0170] An embodiment of this specification also provides a computer-readable storage medium, in which a computer program code is stored. When the computer program code is executed on a computer, the computer executes the above-mentioned related method steps to implement a method for executing a liquidation transaction provided in the above embodiment.

[0171] The embodiments of this specification also provide a computer program product. When the computer program product is run on a computer, the computer is caused to execute the above-mentioned related steps to implement a method for executing a clearing transaction provided in the above-mentioned embodiments.

[0172] Among them, the devices, computer-readable storage media, computer program products or chips provided in the embodiments of this specification are all used to execute the corresponding methods provided above. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding methods provided above and will not be repeated here.

[0173] Through the description of the above implementation methods, technical personnel in the relevant field can understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0174] In the embodiments provided in this specification, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of modules or units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the coupling or direct coupling or communication connection between the related ones shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0175] The above contents are only specific implementation methods of this specification, but the protection scope of this specification is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in this specification, which should be included in the protection scope of this specification. Therefore, the protection scope of this specification should be based on the protection scope of the claims.

Claims

1. A method for executing liquidation affairs, characterized in that: The method comprises: Acquire the acceptance flow generated by the clearing affairs, and acquire characteristic data in each of the acceptance flows; Processing the characteristic data based on the acceptance flow baseline of the clearing transaction to obtain initial output data corresponding to the acceptance flow; Determining the number of batch processing services required for the clearing transaction and the first service baseline corresponding to each batch processing service based on the acceptance flow baseline; Acquire a second service baseline corresponding to each batch processing service, where the second service baseline is a baseline of each batch processing service before the transaction is changed; Calling each batch processing service and generating, based on the initial output data, first baseline data of each batch processing service under the first service baseline, and second baseline data of each batch processing service under the second service baseline; A baseline data comparison result is generated based on the first baseline data and the second baseline data.

2. The method according to claim 1, characterized in that The acquiring of characteristic data in each of the accepted flows includes: Acquire transaction settlement data of each of the accepted flows from input data corresponding to each of the accepted flows; The characteristic data of the input data corresponding to each of the accepted flows is determined based on the transaction settlement data.

3. The method according to claim 2, characterized in that The determining the characteristic data of the input data corresponding to each of the accepted flows based on the transaction settlement data includes: Acquire the clearing entity data, clearing account data and clearing time data in the input data of each of the accepted flows; Generate a clearing data tuple based on the clearing subject data, the clearing account data and the clearing time data; The clearing data tuple is subjected to data filtering to generate the transaction clearing data corresponding to each of the accepted flows, and the transaction clearing data is determined as the characteristic data of the input data corresponding to each of the accepted flows.

4. The method according to claim 1, characterized in that The calling of each batch processing service and generating, based on the initial output data, first baseline data of each batch processing service under the first service baseline, and second baseline data of each batch processing service under the second service baseline, comprises: Calling each batch processing service and generating first fragment data corresponding to each batch processing service under the first service baseline based on the initial output data, and assembling each first fragment data to generate first baseline data; The batch processing services are called and based on the initial output data, second fragment data corresponding to the batch processing services under the second service baseline are generated, and the second fragment data are assembled to generate second baseline data.

5. The method according to claim 4, characterized in that The calling of each batch processing service and generating first fragment data corresponding to each batch processing service under the first service baseline based on the initial output data, and assembling each first fragment data to generate first baseline data, includes: If the target batch processing service is the first batch processing service among the batch processing services, determining the initial output data as the first input data of the target batch processing service under the first service baseline, calling the target batch processing service to process the first input data under the first service baseline, and generating first shard data of the target batch processing service; If the target batch processing service is the Nth batch processing service among the batch processing services, the first shard data of the previous batch processing service of the target batch processing service is determined as the first input data of the target batch processing service under the first service baseline, and the target batch processing service is called to process the first input data under the first service baseline to generate the first shard data of the target batch processing service, where N is a positive integer greater than 1; The first shard data of each target batch service are assembled to generate first baseline data.

6. The method according to claim 5, characterized in that The calling of each batch processing service and generating second fragment data corresponding to each batch processing service under the second service baseline based on the initial output data, and assembling each second fragment data to generate second baseline data, includes: If the target batch processing service is the first batch processing service among the batch processing services, determining the initial output data as the second input data of the target batch processing service under the second service baseline, calling the target batch processing service to process the second input data under the second service baseline, and generating second shard data of the target batch processing service; If the target batch processing service is the Nth batch processing service among the batch processing services, the second shard data of the previous batch processing service of the target batch processing service is determined as the second input data of the target batch processing service under the second service baseline, and the target batch processing service is called to process the second input data under the second service baseline to generate the second shard data of the target batch processing service, where N is a positive integer greater than 1; The second shard data of each target batch processing service are assembled to generate second baseline data.

7. The method according to claim 6, characterized in that The method further comprises: The first shard data and the second shard data of the target batch processing service are compared to determine a shard data comparison result of the target batch processing service.

8. The method according to claim 1, characterized in that The method further comprises: If a traffic change in the acceptance traffic and / or a service change in the acceptance service is detected, the service traffic baseline of the clearing transaction is changed.

9. A liquidation affairs execution device, characterized in that: include: A data acquisition unit, used to acquire the acceptance flow generated by the clearing transaction, and acquire characteristic data in each of the acceptance flows; A data processing unit, configured to process the characteristic data based on the acceptance flow baseline of the clearing transaction to obtain initial output data corresponding to the acceptance flow; A transaction determination unit, configured to determine the number of batch processing services required for the clearing transaction and a first service baseline corresponding to each batch processing service based on the acceptance flow baseline; A baseline acquisition unit, configured to acquire a second service baseline corresponding to each batch processing service, wherein the second service baseline is a baseline of each batch processing service before a transaction is changed; A service calling unit, configured to call each batch processing service and generate, based on the initial output data, first baseline data of each batch processing service under the first service baseline, and second baseline data of each batch processing service under the second service baseline; A data comparison unit is used to generate a baseline data comparison result based on the first baseline data and the second baseline data.

10. An electronic device, characterized in that: The electronic device comprises: A memory for storing executable program codes; A processor is used to call and run the executable program code from the memory, so that the electronic device executes the method for executing a clearing transaction as described in any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed, the method for executing a clearing transaction according to any one of claims 1 to 8 is implemented.

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