CN119831745A

CN119831745A - Transaction data processing method and device, storage medium and electronic equipment

Info

Publication number: CN119831745A
Application number: CN202411974363.5A
Authority: CN
Inventors: 任振锋; 温泽泉; 李逶
Original assignee: Industrial and Commercial Bank of China Ltd ICBC
Current assignee: Industrial and Commercial Bank of China Ltd ICBC
Priority date: 2024-12-30
Filing date: 2024-12-30
Publication date: 2025-04-15

Abstract

The present application discloses a method, device, storage medium and electronic device for processing transaction data, which relate to the fields of financial technology and big data technology. Among them, the method includes: determining to write transaction data into a host and/or a distributed platform system according to a service double-write switch and a target list; after the transaction data is written into the host and/or the distributed platform system, performing data anti-corrosion processing on the transaction data stored in the host and/or the transaction data stored in the distributed platform system. The present application solves the problem that in the prior art, for information security, two sets of heterogeneous ecosystems of a host and a distributed platform system are used as a whole to provide external services for transaction data. However, at present, data input and data output are still maintained for each system separately, so it is difficult to maintain parallel processing and consistency of data, which makes it easy for transaction data to be processed abnormally, and then causes a high transaction failure rate.

Description

Transaction data processing method and device, storage medium and electronic equipment

Technical Field

The application relates to the technical field of finance and technology and the technical field of big data, in particular to a transaction data processing method, a transaction data processing device, a storage medium and electronic equipment.

Background

For many years, large hosts have been commonly used in large commercial core systems due to their stability, high availability, high throughput, etc. But in recent years, because of the traditional centralized architecture concept, relatively closed technical ecology, and high expansion costs, it has become increasingly difficult for industries to accommodate new periods of digital transformation trends and autonomous controllable requirements in critical core areas. In view of the above challenges, various industries explore the migration of core business to an open ecological system so as to fully utilize new technology to accelerate financial innovation, expand the application of open technology products, break through the ecology of external closed technology, realize autonomous and controllable key information infrastructure and realize long-term sustainable development.

Therefore, for financial business, the host business is actively pushed down, and for transaction data, two sets of heterogeneous ecosystems of a host and a distributed platform system are adopted as a whole to serve the outside. However, the host business downshifts have the characteristics of wide range, large investment, long construction period, complex scheme, large internal and external influences and the like, and the overall implementation risk is extremely high, so that the data input and the data output are still maintained for each system at present, and therefore, the parallel processing and the consistency of the data are difficult to maintain. This will always lead to abnormal handling of transaction data, which will cause a problem of high transaction failure rate.

In view of the above problems, no effective solution has been proposed at present.

Disclosure of Invention

The application aims to provide a transaction data processing method, a device, a storage medium and electronic equipment, which at least solve the technical problems that in the prior art, two sets of heterogeneous ecosystems of a host computer and a distributed platform system are adopted as a whole for external service for transaction data, but data input and data output are maintained for each system, so that parallel processing and consistency of the data are difficult to maintain, abnormal processing of the transaction data is easy to occur, and the transaction failure rate is high.

In order to achieve the above object, according to one aspect of the embodiment of the present application, there is provided a transaction data processing method, including determining to write transaction data into a host and/or a distributed platform system according to a service double write-in switch and a target list, wherein the target list is used for recording transaction objects excluding transaction risks, the service double write-in switch is used for determining a data write selection according to transaction attributes of the transaction data, and performing data preservative processing on the transaction data stored in the host and/or the transaction data stored in the distributed platform system after the transaction data is written into the host and/or the distributed platform system, wherein the data preservative processing is used for determining to take the transaction data stored in the host as an output result or the transaction data stored in the distributed platform system as an output result.

Optionally, the transaction data processing method further comprises the steps of carrying out consistency check on the transaction data stored in the host computer and the transaction data stored in the distributed platform system under the condition that the transaction data are written into the host computer and the distributed platform system at the same time to obtain a check result, and marking the state of the protocol routing state table as a target state under the condition that the transaction data stored in the host computer and the transaction data stored in the distributed platform system are not consistent, wherein the protocol routing state table is used for recording the state of a transaction protocol related to the transaction data, and the protocol routing state table under the target state is used for controlling all subsequent transaction requests using the transaction protocol to be processed by the host computer and not transmitted to the distributed platform system.

Optionally, consistency checking is performed on the transaction data stored in the host and the transaction data stored in the distributed platform system, wherein the consistency checking comprises the steps of acquiring a key field value returned by the host after the transaction data are written into the host, acquiring a key field value returned by the distributed platform system after the transaction data are written into the distributed platform system, determining that the transaction data stored in the host and the transaction data stored in the distributed platform system are consistent when the key field value returned by the host is detected to be identical to the key field value returned by the distributed platform system, and determining that the transaction data stored in the host and the transaction data stored in the distributed platform system are inconsistent when the key field value returned by the host is detected to be different from the key field value returned by the distributed platform system.

Optionally, the transaction data is written into the host and/or the distributed platform system according to the service double-write switch and the target list, wherein the determination of the transaction data is carried out on the host and/or the distributed platform system according to the service double-write switch and the target list comprises the steps of writing the transaction data into the host and the distributed platform system under the condition that the transaction object of the transaction data is detected to be the transaction object in the target list, detecting whether the dependent transaction attribute of the service double-write switch is matched with the transaction attribute of the transaction data or not under the condition that the transaction object of the transaction data is detected to be not the transaction object in the target list, wherein the dependent transaction attribute is a precondition for starting the service double-write switch, the service double-write switch is used for simultaneously writing the transaction data into the host and the distributed platform system after being started, writing the transaction data into the host and the distributed platform system by starting the service double-write switch under the condition that the transaction attribute of the transaction data is matched with the dependent transaction attribute, and prohibiting the service double-write switch from being started under the condition that the transaction attribute of the transaction data is not matched with the dependent transaction attribute of the transaction data.

Optionally, the dependent transaction attribute comprises at least one of a preset transaction area, a preset transaction website and a preset transaction channel.

Optionally, detecting whether the transaction dependent attribute of the service double write switch matches the transaction attribute of the transaction data includes determining that the transaction dependent attribute of the service double write switch matches the transaction attribute of the transaction data when the transaction attribute of the transaction data meets all the attributes included in the transaction dependent attribute, and determining that the transaction dependent attribute of the service double write switch does not match the transaction attribute of the transaction data when the transaction attribute of the transaction data does not meet any one of the attributes included in the transaction dependent attribute.

Optionally, before carrying out data preservative treatment on the transaction data stored in the host and/or the transaction data stored in the distributed platform system, the processing method of the transaction data further comprises copying the updated data into a data lake when the transaction data in the host and/or the distributed platform system is updated, detecting a main key and version and time information corresponding to each data received by the data lake, and carrying out screening operation on a plurality of data received by the data lake according to the main key and version and time information corresponding to each data, wherein the screening operation is used for screening and obtaining the data with the latest updating time and reserved for the target version from the plurality of data with the same main key but different versions, and the data of the target version represents the data subjected to the deleting operation.

Optionally, the data preservative processing is performed on the transaction data stored in the host and/or the transaction data stored in the distributed platform system, and the data preservative processing comprises the steps of respectively inquiring the transaction data from the host and the distributed platform system in response to an output instruction of the transaction data, taking the transaction data in the host as an output result when the transaction data exist in the host and the transaction data do not exist in the distributed platform system, taking the transaction data in the host as an output result when the transaction data exist in the host and the distributed platform system, and taking the transaction data in the distributed platform system as an output result when the transaction data do not exist in the host and the transaction data exist in the distributed platform system.

Optionally, the processing method of the transaction data further comprises the step of determining a data source related to data rollback according to the service double-write switch and the target list when the transaction corresponding to the transaction data fails and the data rollback is needed, wherein the data source comprises a host and/or a distributed platform system, and the data rollback operation is carried out on the transaction data in the data source.

In order to achieve the above object, according to another aspect of the embodiments of the present application, there is also provided a transaction data processing apparatus including a determining unit configured to determine to write transaction data to a host and/or a distributed platform system according to a service double write switch and a target list, wherein the target list is configured to record transaction objects for which transaction risks have been excluded, the service double write switch is configured to determine a data write selection according to transaction attributes of the transaction data, and a processing unit configured to perform data corrosion processing on the transaction data stored in the host and/or the transaction data stored in the distributed platform system after the transaction data is written to the host and/or the distributed platform system, wherein the data corrosion processing is configured to determine to take the transaction data stored in the host as an output result or to take the transaction data stored in the distributed platform system as an output result.

According to another aspect of the embodiments of the present application, there is also provided an electronic device including one or more processors and a memory for storing one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to perform the above-described transaction data processing method.

According to another aspect of the embodiment of the present application, there is further provided a computer readable storage medium, in which a computer program is stored, where the computer readable storage medium is caused to execute the method for processing transaction data according to the above method when the computer program runs.

According to another aspect of the embodiments of the present application, there is also provided a computer program product comprising computer instructions which, when executed by a processor, implement the steps of the transaction data processing method described above.

In the embodiment of the application, firstly, the transaction data is written into a host computer and/or a distributed platform system according to a service double-write switch and a target list, wherein the target list is used for recording transaction objects excluding transaction risks, the service double-write switch is used for determining data writing selection according to transaction attributes of the transaction data, and then after the transaction data is written into the host computer and/or the distributed platform system, data antiseptic treatment is carried out on the transaction data stored in the host computer and/or the transaction data stored in the distributed platform system, wherein the data antiseptic treatment is used for determining the transaction data stored in the host computer as an output result or the transaction data stored in the distributed platform system as an output result.

From the foregoing, it can be seen that the core of the present application is to determine whether transaction data is written to both the host and the distributed platform system or only one of them based on the service double write switch and the target list. The service double write switch decides a data write strategy according to transaction attributes (such as transaction areas, network points, channels and the like) of transaction data, and the target list records transaction objects from which transaction risks are eliminated, so that additional guarantee is provided for high-risk transactions.

Second, after the writing of transaction data is achieved, a means of data consistency check and data preservation processing is provided to ensure that the transaction data in the host and distributed platform systems remain consistent. This includes daily incremental verification of transaction data in the dual system and, when inconsistencies are found, selecting the correct output results according to preset rules, while marking abnormal transaction protocols for subsequent analysis and administration.

Therefore, the technical scheme of the application achieves the aim of efficiently and safely processing transaction data among heterogeneous systems, thereby realizing the technical effect that two sets of heterogeneous ecosystems of a host computer and a distributed platform system are adopted as a whole for external service for the transaction data, further solving the technical problem that the prior art is high in transaction failure rate due to information security because the two sets of heterogeneous ecosystems of the host computer and the distributed platform system are adopted as a whole for external service for the transaction data, but the data input and the data output are still maintained for each system at present, so that the parallel processing and consistency of the data are difficult to maintain, the abnormal processing condition of the transaction data is easy to occur, and the technical problem of high transaction failure rate is further solved.

Drawings

The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a limitation on the application. In the drawings:

FIG. 1 shows a block diagram of the hardware architecture of a computer terminal for implementing a method of processing transaction data;

FIG. 2 is a flow chart of an alternative transaction data processing method according to an embodiment of the application;

FIG. 3 is a schematic diagram of a routing state of an alternative transaction data processing method according to an embodiment of the present application;

FIG. 4 is a schematic illustration of a check error of an alternative transaction data processing method according to an embodiment of the present application;

FIG. 5 is a schematic diagram of dual write switching parameters of an alternative transaction data processing method according to an embodiment of the present application;

FIG. 6 is a flow chart of dual write switch priority determination for an alternative transaction data processing method according to an embodiment of the present application;

FIG. 7 is a flow chart of logically merging host and platform table data in an alternative transaction data processing method according to an embodiment of the application;

FIG. 8 is a data preservation flow chart of an alternative transaction data processing method according to an embodiment of the present application;

FIG. 9 is a flow chart of a data rollback operation of an alternative transaction data processing method according to an embodiment of the present application;

FIG. 10 is a flow chart of an alternative transaction data processing method according to an embodiment of the application;

FIG. 11 is a schematic diagram of a transaction data processing device provided in accordance with an embodiment of the present application;

Fig. 12 is a block diagram of an electronic device according to an embodiment of the present application.

Detailed Description

In order that those skilled in the art will better understand the present application, a technical solution in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present application without making any inventive effort, shall fall within the scope of the present application.

It should be noted that the terms "first," "second," and the like in the description and the claims of the present application and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the application described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

It should be further noted that, the collected information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for presentation, analyzed data, etc.) related to the present application are information and data authorized by the user or sufficiently authorized by each party, and the collection, storage, use, processing, transmission, provision, disclosure, application, etc. of the related data all comply with the relevant laws and regulations and standards, necessary security measures are adopted, no prejudice to the public order, and corresponding operation entries are provided for the user to select authorization or rejection. If an interface is arranged between the system and the related user or institution, a corresponding operation inlet is provided for the user, so that the user can choose to agree or reject the automatic decision result; if the user selects refusal, the expert decision flow is entered.

According to an embodiment of the present application, there is provided a method embodiment of a transaction data processing method, it being noted that the steps shown in the flowchart of the drawings may be performed in a computer system such as a set of computer executable instructions, and that although a logical order is shown in the flowchart, in some cases the steps shown or described may be performed in an order different from that shown or described herein.

It should be noted that, a transaction data processing system may be used as an execution subject of the transaction data processing method according to the embodiments of the present application. It may be understood that the processing method of transaction data provided in the embodiment of the present application may also be implemented by other systems or devices as an execution body, which is not limited in particular in the embodiment of the present application.

The method embodiments provided by the embodiments of the present application may be performed in a mobile terminal, a computer terminal, or similar computing device. Fig. 1 shows a block diagram of a hardware structure of a computer terminal (or mobile device) for implementing a processing method of transaction data. As shown in fig. 1, the computer terminal 10 (or mobile device) may include one or more (shown in the figures as 102a,102 b.) processors 102 (the processors 102 may include, but are not limited to, a microprocessor MCU or a programmable logic device FPGA or the like processing means), a memory 104 for storing data, and a transmission means 106 for communication functions. Among other things, a display, an input/output interface (I/O interface), a Universal Serial BUS (USB) port (which may be included as one of the ports of the BUS BUS), a network interface, a power supply, and/or a camera. It will be appreciated by those of ordinary skill in the art that the configuration shown in fig. 1 is merely illustrative and is not intended to limit the configuration of the electronic device described above. For example, the computer terminal 10 may also include more or fewer components than shown in FIG. 1, or have a different configuration than shown in FIG. 1.

It should be noted that the one or more processors 102 and/or other data processing circuits described above may be referred to generally herein as "data processing circuits. The data processing circuit may be embodied in whole or in part in software, hardware, firmware, or any other combination. Furthermore, the data processing circuitry may be a single stand-alone processing module, or incorporated, in whole or in part, into any of the other elements in the computer terminal 10 (or mobile device). In the method for processing transaction data according to the embodiment of the application, the data processing circuit is used as a processor control (such as the selection of a variable resistor terminal path connected with an interface).

The memory 104 may be used to store software programs and modules of application software, such as program instructions/data storage devices corresponding to the transaction data processing method in the embodiment of the present application, and the processor 102 executes the software programs and modules stored in the memory 104, thereby executing various functional applications and data processing, that is, implementing the transaction data processing method described above. Memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include memory located remotely from the processor 102, which may be connected to the computer terminal 10 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.

The transmission means 106 is arranged to receive or transmit data via a network. The specific examples of the network described above may include a wireless network provided by a communication provider of the computer terminal 10. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, NIC) that can connect to other network devices through a base station to communicate with the internet. In one example, the transmission device 106 may be a Radio Frequency (RF) module for communicating with the internet wirelessly.

The display may be, for example, a touch screen type Liquid Crystal Display (LCD) that may enable a user to interact with a user interface of the computer terminal 10 (or mobile device).

In the above-described operating environment, the present application provides a method for processing transaction data as shown in fig. 2. Fig. 2 is a flow chart of an alternative transaction data processing method according to an embodiment of the application. As shown in fig. 2, the method comprises the steps of:

Step S201, determining to write transaction data into the host and/or the distributed platform system according to the service double write switch and the target list.

In step S201, the target list is used for recording transaction objects from which transaction risks have been excluded, and the service double write switch is used for determining a data write selection according to transaction attributes of the transaction data.

Optionally, the transaction data processing system determines to write transaction data to the host and/or the distributed platform system based on a synergistic effect of the service double write switch and the target list.

Optionally, the service dual write switch can dynamically determine whether the transaction data should be written to the host system and the distributed platform system at the same time or only select one of them for writing according to the inherent transaction attribute (such as geographic location of the transaction, website attribute, channel type, etc.) of the transaction data. This ensures efficient storage and access of data while providing a stable data processing environment in view of the complexity during system migration and parallel operation.

Optionally, the targeted list is used to record entities or transaction objects that have passed the strict risk assessment that are considered to be at a lower risk at the transaction level. The target list not only accelerates the processing of low-risk transactions, but also ensures the safe writing path of high-risk transaction data through the judgment of the service double-writing switch, namely, the high-risk transaction data is written into the host system for processing preferentially or only, thereby effectively avoiding the potential systematic risk.

Step S202, after the transaction data is written into the host computer and/or the distributed platform system, performing data antiseptic processing on the transaction data stored in the host computer and/or the transaction data stored in the distributed platform system.

In step S202, the data preservation process is used to determine whether the transaction data stored in the host computer is taken as an output result or the transaction data stored in the distributed platform system is taken as an output result.

Optionally, the data antiseptic processing is used for determining that the transaction data stored in the host computer is taken as an output result, or the transaction data stored in the distributed platform system is taken as an output result, so that the data source of the output result of the system can be scientifically determined.

Optionally, in a complex environment where the host and the distributed platform system coexist, multiple factors must be considered in selecting the output result, including timeliness, consistency of data, and stability of system operation, and the output result is selected by using data antiseptic treatment.

As can be seen from the content of steps S201 to S202, in the embodiment of the present application, the transaction data is first determined to be written into the host computer and/or the distributed platform system according to the service double-write switch and the target list, where the target list is used to record the transaction object excluding the transaction risk, the service double-write switch is used to determine the data writing selection according to the transaction attribute of the transaction data, and then after the transaction data is written into the host computer and/or the distributed platform system, the data antiseptic treatment is performed on the transaction data stored in the host computer and/or the transaction data stored in the distributed platform system, where the data antiseptic treatment is used to determine the transaction data stored in the host computer as the output result or the transaction data stored in the distributed platform system as the output result.

In an alternative embodiment, the transaction data processing system firstly performs consistency check on the transaction data stored in the host computer and the transaction data stored in the distributed platform system under the condition that the transaction data are written into the host computer and the distributed platform system at the same time, so as to obtain a check result, and then marks the state of the protocol routing state table as a target state under the condition that the transaction data stored in the host computer and the transaction data stored in the distributed platform system are not consistent, wherein the protocol routing state table is used for recording the state of a transaction protocol related to the transaction data, and the protocol routing state table under the target state is used for controlling all subsequent transaction requests using the transaction protocol to be processed by the host computer and not transmitted to the distributed platform system.

Optionally, in a heterogeneous system parallel writing environment, the consistency check operation of the transaction data lays a data integrity. When transaction data is written into the host computer and the distributed platform system at the same time, the transaction data stored in the host computer is compared with corresponding data stored in the distributed platform system, whether the difference exists between the two data is detected, the consistency state of the data is identified, and a detailed checking result is output.

Optionally, in case the transaction data stored in the host computer and the transaction data stored in the distributed platform system are checked to be inconsistent, the transaction data processing system marks the status in the auto-tune protocol routing status table to a target status, which is a predefined emergency status, indicating that all subsequent transaction requests involving the transaction protocol should be processed directly by the host computer system and not sent in parallel to the distributed platform system.

Optionally, the protocol routing state table records the protocol state related to the transaction data, so that actions can be rapidly taken under the condition of inconsistent data, accurate processing of service requests is ensured, and the influence of potential service interruption or data errors on bank operation is prevented.

Alternatively, there is a routing state table of an alternative transaction data processing method, in which a product protocol routing state is recorded, as shown in fig. 3, PRTOEX represents a protocol number of a participant, a data type is VARCHAR (34), STATUS represents a routing state, a data type is TINYINT, when STATUS is 0, the routing state is normal, when STATUS is 1, the switching back to a host state is indicated, lst_date represents a last update DATE, a data type is DATE, route_key represents a routing field, and a data type is VARCHAR (34). When the data check of the host platform is failed, the state of the corresponding product protocol record is updated as a 'back cut host', all transactions initiated subsequently corresponding to the product protocol record are only carried out on the host, the lower host double-writing public component adds the corresponding record state of the technology table for checking the routing state of the product protocol in the double-writing (platform is standard) stage, and if the state is the 'back cut host', only the host branch is called (the platform branch is not called).

From the above, the transaction data processing system performs output check outside the dual-computer parallel, ensures the consistency of system output, supports manual switching back to the host computer when data are inconsistent, reflects strict requirements on data integrity, and highlights the prospective and innovation of the bank system on business continuity and data consistency management under the digital transformation background.

In an alternative embodiment, the transaction data processing system firstly acquires a key field value returned by the host after writing the transaction data into the host, then acquires a key field value returned by the distributed platform system after writing the transaction data into the distributed platform system, then determines that the transaction data stored in the host and the transaction data stored in the distributed platform system remain consistent when detecting that the key field value returned by the host is identical to the key field value returned by the distributed platform system, and finally determines that the transaction data stored in the host and the transaction data stored in the distributed platform system are inconsistent when detecting that the key field value returned by the host is different from the key field value returned by the distributed platform system.

Optionally, the transaction data processing system obtains key field values returned by the host after writing the transaction data into the host, ensures complete capture of all key field values, and establishes a solid foundation for subsequent consistency checks.

Optionally, the transaction data processing system acquires the key field value returned by the distributed platform system after the transaction data is written into the distributed platform system, so that real-time synchronization and comparison of data response in the dual-machine parallel architecture are ensured.

Optionally, when the key field values returned by the host system and the distributed platform system are completely consistent, the transaction data processing system automatically confirms that the transaction data states of the host system and the distributed platform system are kept synchronous, i.e. the data consistency is scientifically verified. When the key field value returned by the host computer is different from the key field value returned by the distributed platform system, the system immediately determines that the state of the transaction data stored by the host computer and the platform is inconsistent.

Optionally, there is an alternative CHECK error technique table of transaction data processing method, recording product protocol routing status, as shown in fig. 4, wherein PRTOEX represents the protocol number of the participant, the data type is VARCHAR (34), MAINFRAME _output represents the host return communication zone, the data type is TEXT, PLATFORM _output represents the platform return communication zone, the data type is TEXT, the check_name represents the difference field NAME, the data type is TEXT, the lst_date represents the last update DATE, the data type is DATE, the route_key represents the routing field, and the data type is VARCHAR (34). The lower host double-writing public component adds a double-machine return communication area checking logic in a double-writing (platform is in the right and host is in the right) stage, compares whether the values returned by the platform/host are consistent one by one according to important field information and checking rules of application configuration, outputs relevant information to a separate log file when checking is inconsistent, supports the application to automatically realize registration and check the inconsistent information to an error register, and updates the corresponding record state of a product protocol routing state technical table to be a 'back-cut host' when the application service needs to be back-cut.

From the above, it can be seen that the transaction data processing system provides a highly efficient and reliable transaction data consistency checking method, which ensures the accuracy of data, and can also take measures rapidly when the data state is abnormal, so as to prevent the system risk caused by inconsistent data.

In an alternative embodiment, the transaction data processing system firstly writes the transaction data into the host and the distributed platform system when detecting that the transaction object of the transaction data is the transaction object in the target list, then detects whether the dependent transaction attribute of the service double write switch is matched with the transaction attribute of the transaction data or not when detecting that the transaction object of the transaction data is not the transaction object in the target list, wherein the dependent transaction attribute is a precondition for starting the service double write switch, the service double write switch is used for writing the transaction data into the host and the distributed platform system at the same time after being started, then writes the transaction data into the host and the distributed platform system by starting the service double write switch when the transaction attribute of the transaction data is matched with the dependent transaction attribute, and finally forbids to start the service double write switch and writes the transaction data into the host when the transaction attribute of the transaction data is not matched with the dependent transaction attribute.

Optionally, the target list is a database that is scientifically screened and risk assessed, recording all entities or objects that are considered to have excluded the risk of the transaction.

Optionally, the transaction data processing system detects whether the transaction attribute of the service double-write switch is matched with the transaction attribute of the transaction data, and the matching process not only considers the basic attributes of time, place, channel and the like of the transaction, but also covers more complex business logic and risk evaluation rules, thereby providing scientific basis for dynamic opening of the service double-write switch.

Optionally, when the transaction attribute of the transaction data is completely consistent with the dependent transaction attribute of the service dual write switch, the transaction data processing system turns on the service dual write switch to execute the dual parallel write flow. When it is detected that the transaction attributes of the transaction data do not match the dependent transaction attributes, the transaction data are written into the host.

Optionally, there is an optional dual write switch priority judging flow chart of a transaction data processing method, as shown in fig. 5, where the support system application sets a target list according to information such as a client information number, a medium number, a protocol account number, and the like, and the target list information is set in an application database, and for a client transaction request belonging to the target list, bypasses the service dual write switch judgment, and directly processes according to the dual write flow (the specific processing rule can be realized by application customization). For the client transaction request which does not belong to the target list, acquiring a switch of a transaction area, a transaction site and a transaction channel, acquiring an area switch of the transaction area, the site 0 and the channel 0 if the switch is not set, acquiring a total switch of the site 0, the site 0 and the channel 0 if the switch is not set, and calling a host only by default if the total switch is not set (service flow).

According to the above, the transaction data processing system performs matching processing on the transaction data through the target list and the dependence transaction attribute, so that high efficiency and safety of transaction data processing are realized.

In an alternative embodiment, the dependent transaction attributes include at least one of a preset transaction area, a preset transaction website, and a preset transaction channel.

Optionally, the transaction data processing system provides accurate decision basis for data processing under a dual-machine parallel architecture according to the settings of three dimensions of a preset transaction area, a preset transaction website and a preset transaction channel.

Optionally, the preset transaction area attribute considers geographical positioning information of the transaction, the preset transaction website attribute focuses on a specific place of the transaction, and the preset transaction channel attribute covers an execution way of the transaction.

Optionally, there is a dual write-on switch parameter table of an optional transaction data processing method, where the support system uses service dual write-on switches according to regional, website and channel settings, and the service dual write-on switch parameters are implemented in an application database setting, as shown in fig. 6, where zone_no represents a regional number, 0 represents a full regional validation, br_no represents a website number, 0 represents all website validation in the region, chan_type represents a channel TYPE, 0 represents a full channel validation, param_value represents a parameter VALUE, 1-host-only, 2-dual write-host-only, 3-dual write-platform-only, and 4-platform-only.

As can be seen from the above, the transaction data processing system can finely analyze and determine the characteristics of each transaction data according to the preset transaction area, the preset transaction website and the preset transaction channel, so as to ensure that the opening decision of the service double-write switch is in accordance with the service logic and effectively avoid the potential risk.

In an alternative embodiment, the transaction data processing system first determines that the dependent transaction attribute of the service double write switch matches the transaction attribute of the transaction data when the transaction attribute of the transaction data meets all of the attributes included in the dependent transaction attribute, and then determines that the dependent transaction attribute of the service double write switch does not match the transaction attribute of the transaction data when the transaction attribute of the transaction data does not meet any of the attributes included in the dependent transaction attribute.

Optionally, the transaction data processing system performs comprehensive comparison analysis on attributes such as transaction areas, transaction sites and transaction channels of the transaction data, and determines that the transaction attribute of the service double-write switch is matched with the transaction attribute of the transaction data when the transaction attribute of the transaction data is completely matched with all preset conditions in the transaction attribute.

Optionally, the transaction data processing system considers that any attribute condition is not satisfied in the determination of a match of the transaction attribute to the transaction-dependent attribute. When the transaction attribute of the transaction data fails to completely match any preset condition in the dependent transaction attribute, the system immediately identifies and determines a mismatch state between the dependent transaction attribute and the transaction attribute of the transaction data.

Optionally, there is an example of detecting whether the transaction attribute of the service two-way write-once switch is matched with the transaction attribute of the transaction data, in which the transaction attribute defines an A transaction area, a B transaction website and a C transaction channel, and the transaction data just meets the A transaction area, the B transaction website and the C transaction channel, and is matched, otherwise, is not matched. The second mode is that the transaction attribute is only limited by the transaction channel C, the transaction data 1 meets the transaction area A, the transaction site B and the transaction channel C, and the transaction data 2 meets the transaction area A1, the transaction site B1 and the transaction channel C, but the transaction data 3 meets the transaction area A, the transaction site B and the transaction channel D, and the transaction data are not matched.

According to the above, the transaction data processing system realizes intelligent decision and dynamic management and control of the service double-write switch through the matching judgment of the transaction attribute and the dependence transaction attribute, and reflects the application value of data science in transaction data processing.

In an alternative embodiment, before performing data preservative processing on transaction data stored in a host and/or transaction data stored in a distributed platform system, the transaction data processing system copies updated data into a data lake when the data update occurs on the transaction data in the host and/or the distributed platform system, then detects a primary key and version and time information corresponding to each data received by the data lake, and then performs screening operation on a plurality of data received by the data lake according to the primary key and version and time information corresponding to each data, wherein the screening operation is used for screening data with the latest update time and reserved for a target version from a plurality of data with the same primary key but different versions, and the target version of data represents the data with the deletion operation performed.

Optionally, when any data update occurs to the transaction data in the host or the distributed platform system, the transaction data processing system accurately copies the updated data to the data lake, so that the data synchronism in the heterogeneous system environment is ensured, and a solid data base is provided for subsequent data consistency check and processing.

Optionally, the transaction data processing system detects the primary key, version and time information corresponding to each data received by the data lake, and can perform comprehensive attribute analysis on each data received by the data lake.

Optionally, the filtering operation is used for filtering and obtaining the data with the latest update time and the target version from the plurality of data with the same main key but different versions, and the data of the target version characterizes the data with the deleting operation, so that the efficiency of data processing is improved.

Optionally, in the process of platform tangential flow under the host, there may be a back-and-forth switching between the host and the platform table, in order to shield the influence on the downstream of the data, a layer of processing is performed on the source data generating side to implement merging of the host and the platform table data according to logic, so that the downstream user can normally use the data service, and there is an optional example of data flow according to the logic merging of the host and the platform table:

(1) The source application database performs DML operation, and the data can be recorded into a lake (such as high-efficiency DRP replication or final daily file into the lake) through a data replication mode.

(2) For the original table entering the lake, after the data lake judges that the data on the same day is completed, the data lake is processed and screened from the table through the hive data warehouse SQL storage process to enter the data into the external service table (the screening condition is different according to different tables, the general principle is that the last 1 record which is not D is taken for the record of the same main key, the record is according to the service date field workdate and the like).

(3) After the SQL storage process of the hive data warehouse runs out of the data lake, determining whether the ANTI-corrosion treatment is needed according to the configuration table BDP_ANI_CONFIG, if so, executing data backup, backing up the data generated by the treatment on the external service table data into the ANI backup table (temporarily keeping for 1 month and accessing the table after checking the problem), and then executing the SQL storage process of the hive data warehouse

The ANTI completes the ANTI-corrosion treatment, which is aimed at deciding whether to use the original host table a data or the platform table a data.

Optionally, there is an optional transaction data processing method, in which the host and platform table data flow diagrams are combined according to logic, as shown in fig. 7, for the host table a, the final daily file is put into the data lake to obtain the host source pasting table a ', for the platform table a, according to drp, the frn_temporary table (96 partitions) is obtained, 050.hql is obtained, then whether the data need to be preserved or not is judged, if so, the data need to be backed up to a ", the host source pasting table a' and/or a" is subjected to preservative treatment, finally the platform source pasting table a 'is obtained, and if not, the platform source pasting table a' is directly obtained.

According to the above, before the transaction data processing system performs data anti-corrosion processing, a layer of processing is performed on the source data generating side to logically merge the host and platform table data, so that the influence on the downstream of the data is shielded, and the response speed and accuracy of the data lake in processing complex data updating events are improved.

In an alternative embodiment, the transaction data processing system firstly responds to the output instruction of the transaction data to respectively inquire the transaction data from the host and the distributed platform system, then takes the transaction data in the host as an output result when the transaction data in the host exists and the transaction data in the distributed platform system does not exist in the inquiry, takes the transaction data in the host as an output result when the transaction data in the host and the distributed platform system exist in the inquiry, and finally takes the transaction data in the distributed platform system as an output result when the transaction data in the host does not exist and the transaction data in the distributed platform system exists in the inquiry.

Optionally, the transaction data processing system queries the transaction data from the host and the distributed platform system respectively in the face of the output instruction of the transaction data, thereby ensuring the high efficiency and synchronism of the query process.

Optionally, in the query process, if no specified transaction data exists in the distributed platform system, but the corresponding data record is stored in the host, the transaction data in the host is used as an output result, so that the complete and accurate service response can be provided based on the data backup of the host system under the condition that the distributed platform data is missing.

Optionally, there is an optional data antiseptic flow chart of a transaction data processing method, as shown in fig. 8, in BDP, according to the field comparison relationship between the host lake table a and the platform lake table B, the host is processed according to the primary key in EDI, where the host has a platform, which is an uncut or emergency cut-back scene, and is based on the host, the host has no platform, which is based on the cut-off scene, and the host has a platform, which is based on the double writing scene, and is based on the host. After the processing is finished, if the structure in the result table B' is consistent with the platform table, data corrosion prevention is carried out, and then the data after corrosion prevention is logically processed in downstream application.

According to the above, the transaction data processing system performs antiseptic treatment on the data, so that the accuracy, consistency and timely response of the transaction data output result are realized.

In an alternative embodiment, the transaction data processing system determines a data source related to the data rollback according to the service double write switch and the target list when the transaction corresponding to the transaction data fails and the data rollback is required, wherein the data source comprises a host and/or a distributed platform system, and then performs the data rollback operation on the transaction data in the data source.

Optionally, when the transaction corresponding to the transaction data fails, and the system determines that data rollback is required to repair the possible data anomalies, the transaction data is restored to the state before failure, and the possible data anomalies and system risks are eliminated.

Optionally, there is an optional data rollback operation flow chart of a transaction data processing method, as shown in fig. 9, in which, in the case of FMTA, when the tangential region is switched on, the platform is accessed according to FMTA service interface to the platform program, if the transaction is successful, the host value is returned through the host, if the transaction is failed, the platform value is returned directly, and in the case of the host, the platform program is accessed according to FMTA service interface, and whether the transaction is successful or not, the host value is returned according to the host. When the switch of the tangential region is closed, the host value is returned directly according to the host according to FMTA serving interfaces. Under the non-gray scale condition, when the switch of the tangential region is closed, the interface is serviced according to FMTA, and the host value is returned directly according to the host.

Optionally, in addition to the data rollback operation, there is an example of a newly added host dual write base class AbstractACSBaseService, implementing the following unified scheduling, including:

(1) Check-in (DATACHECK) the application implements specific parameter check logic itself.

(2) The read service double write switch (getDoubleSwitch) obtains the double write switch according to unified rule.

(3) The pretreatment (preCheck) is realized by the application.

(4) The host processing flow (MAINFRAMEDEAL) is that the application realizes the specific host interface call by itself to realize the business processing.

(5) The platform processing flow (platformDeal) is that the application realizes the platform business logic processing by itself.

(6) The host compensation process flow (mainFrameDealRollBack) is that the application realizes the specific host interface call by itself to realize the compensation process flow processing.

(7) The platform compensation processing flow (platformDealRollBack) is that the application realizes the platform business logic compensation processing by itself.

(8) The sub-transaction orthogonal easy method executes the following steps according to the service double-write switch:

1) The switch value is MAINFRAME _ONLY, namely ONLY the host flow is called (the service transformation), ONLY MAINFRAMEDEAL is called to realize the processing of the host flow, and the processing result is returned according to the host;

2) The switch value is DOUBLE_WRITE_ MAINFRAME, namely DOUBLE writing-taking a host as a reference, firstly calling platformDeal to realize platform business logic processing, then calling MAINFRAMEDEAL to realize host flow processing, wherein the host processing flow is not affected by the fault of the platform business logic, and taking a host return result as a service return result;

3) The switch value is DOUBLE_WRITE_ PLATFORM, i.e., DOUBLE WRITE-based on the platform.

4) The switch value is PLATFORM _ONLY, namely ONLY the platform flow (off-host) is called, ONLY platformDeal is called to realize the platform business logic processing, and the platform business logic processing is returned according to the platform processing result.

(9) The sub-transaction compensation method executes the following steps according to the service double-write switch:

1) The switch value is MAINFRAME _ONLY, and ONLY mainFrameDealRollBack is called to realize the compensation processing of the host flow, and the compensation processing is returned according to the host processing result;

2) The switch value is DOUBLE_WRITE_ MAINFRAME, so that the compensation processing of the host flow is realized, and the compensation result of the platform is not concerned, and the compensation result is returned according to the host;

3) The switch value is DOUBLE_WRITE_ PLATFORM, firstly, the compensation processing of the platform business logic is realized by calling platformDealRollBack, then the host flow processing is realized by calling mainFrameDealRollBack, and the process is returned according to the platform compensation result.

(10) And the switch value is PLATFORM _ONLY, and the compensation processing of the platform service logic is realized ONLY by calling platformDealRollBack, and the compensation processing is returned according to the platform compensation result.

From the above, the transaction data processing system establishes an intelligent data backtracking and repairing framework aiming at guaranteeing data consistency and system stability through the data backtracking source judgment of failed transaction and the scientific backtracking operation of transaction data in the data source, and reflects the application value of data science in a transaction failure scene.

From the above, according to the technical solution of the present application, at least the following technical effects can be achieved:

1. The method realizes the normal and stable and efficient requirements on external service of an ultra-large core system in the host downward moving process, meets the requirements of parallel service popularization and service innovation project in the system, brings enough guarantee to the requirements on the stability and the robustness of the core system, and prevents systematic risks from being brought in the host downward moving process.

2. The security requirement of data migration of massive system data and business data in the process of downshifting along with the host is realized, the security downshifting of massive customer business data is ensured, and data service is provided normally and externally.

3. The daily business development and handling of massive clients are guaranteed, and the normal business development of hundreds of thousands of partners is guaranteed.

In an alternative embodiment, fig. 10 shows a flowchart of an alternative transaction data processing method according to an embodiment of the present application, so that the process of transaction data processing can be more clearly understood. The device is used for carrying out system output check outside the dual-machine parallel system, ensuring that the dual-machine system is transparent to the outside in different stages of the host machine downward movement and the whole system is not influenced in the external output of the host machine, and is used for carrying out incremental data check and data synchronization in the final daily state and ensuring that the system data and the service system can normally provide services in different stages of the host machine downward movement. The method comprises the following steps of firstly accessing channels into a dual-machine parallel inlet, and mainly comprising a mainframe system and a distributed platform. And then, according to a data replication technology, checking the data of the main machine source and the platform source, further performing data anti-corrosion treatment, and directly applying the anti-corrosion data to the external application of the system. If the data to be subjected to the corrosion-preventing processing is not required, the data can be directly output to the external application of the system through the output check.

According to another aspect of the embodiment of the present application, there is further provided a transaction data processing apparatus, where fig. 11 is a schematic diagram of an alternative transaction data processing apparatus according to an embodiment of the present application, and as shown in fig. 11, the transaction data processing apparatus includes a determining unit 1101 and a processing unit 1102.

The transaction data is written into the host computer and/or the distributed platform system according to the service double-write switch and the target list, wherein the target list is used for recording transaction objects with transaction risks removed, the service double-write switch is used for determining data writing selection according to transaction attributes of the transaction data, and the processing unit 1102 performs data preservative processing on the transaction data stored in the host computer and/or the transaction data stored in the distributed platform system after the transaction data is written into the host computer and/or the distributed platform system, and the data preservative processing is used for determining the transaction data stored in the host computer as an output result or the transaction data stored in the distributed platform system as an output result.

Optionally, the transaction data processing device further comprises a checking unit and a second processing unit. The second processing unit is used for marking the state of the protocol routing state table as a target state when the transaction data stored in the host computer is checked to be inconsistent with the transaction data stored in the distributed platform system, wherein the protocol routing state table is used for recording the state of a transaction protocol related to the transaction data, and the protocol routing state table in the target state is used for controlling all subsequent transaction requests using the transaction protocol to be processed by the host computer and not transmitted to the distributed platform system.

Optionally, the checking unit comprises a first acquisition subunit, a second acquisition subunit, a first determination subunit and a second determination subunit. The system comprises a first acquisition subunit, a second acquisition subunit, a first determination subunit and a second determination subunit, wherein the first acquisition subunit is used for acquiring a key field value returned by a host after the transaction data are written into the host, the second acquisition subunit is used for acquiring a key field value returned by the distributed platform system after the transaction data are written into the distributed platform system, the first determination subunit is used for determining that the transaction data stored in the host are consistent with the transaction data stored in the distributed platform system when the key field value returned by the host is detected to be the same as the key field value returned by the distributed platform system, and the second determination subunit is used for determining that the transaction data stored in the host are inconsistent with the transaction data stored in the distributed platform system when the key field value returned by the host is detected to be different from the key field value returned by the distributed platform system.

Optionally, the determining unit 1101 includes a first processing subunit, a first detecting subunit, a second processing subunit, and a third processing subunit. The system comprises a first processing subunit, a first detection subunit, a third processing subunit and a third processing subunit, wherein the first processing subunit is used for writing transaction data into a host and a distributed platform system when detecting that the transaction object of the transaction data is the transaction object in the target list, the first detection subunit is used for detecting whether the dependent transaction attribute of the service double write switch is matched with the transaction attribute of the transaction data or not when detecting that the transaction object of the transaction data is not the transaction object in the target list, the dependent transaction attribute is a precondition for starting the service double write switch, the service double write switch is started and then is used for writing the transaction data into the host and the distributed platform system at the same time, the second processing subunit is used for writing the transaction data into the host and the distributed platform system by starting the service double write switch when the transaction attribute of the transaction data is matched with the dependent transaction attribute, and the third processing subunit is used for prohibiting the service double write switch from being started and writing the transaction data into the host when the transaction attribute of the transaction data is not matched with the dependent transaction attribute.

Optionally, the first detection subunit comprises a first determination module and a second determination module. The transaction data processing system comprises a first determination module, a second determination module and a service double-write switch, wherein the first determination module is used for determining that the dependent transaction attribute of the service double-write switch is matched with the transaction attribute of the transaction data when the transaction attribute of the transaction data meets all the attributes included in the dependent transaction attribute, and the second determination module is used for determining that the dependent transaction attribute of the service double-write switch is not matched with the transaction attribute of the transaction data when the transaction attribute of the transaction data does not meet any attribute included in the dependent transaction attribute.

Optionally, the transaction data processing device further comprises a third processing unit, a detection unit and a screening unit. The system comprises a host computer, a third processing unit, a detection unit and a screening unit, wherein the third processing unit is used for copying updated data into a data lake when the data of transaction data in the host computer and/or the distributed platform system are updated, the detection unit is used for detecting a main key and version and time information corresponding to each data received by the data lake, the screening unit is used for carrying out screening operation on a plurality of data received by the data lake according to the main key and version and time information corresponding to each data, the screening operation is used for screening and obtaining data which has the latest updating time and is reserved for a target version from a plurality of data with the same main key but different versions, and the data of the target version represents the data subjected to the deleting operation.

Optionally, the processing unit 1102 includes a first query subunit, a fourth processing subunit, a fifth processing subunit, and a sixth processing subunit. The system comprises a first query subunit, a fourth processing subunit, a fifth processing subunit and a sixth processing subunit, wherein the first query subunit is used for respectively querying transaction data from a host and a distributed platform system in response to an output instruction of the transaction data, the fourth processing subunit is used for taking the transaction data in the host as an output result when the transaction data exist in the host and the distributed platform system are queried, the fifth processing subunit is used for taking the transaction data in the host as the output result when the transaction data exist in the host and the distributed platform system are queried, and the sixth processing subunit is used for taking the transaction data in the distributed platform system as the output result when the transaction data do not exist in the host and the transaction data exist in the distributed platform system.

Optionally, the transaction data processing device further comprises a second determining unit and a fourth processing unit. The system comprises a first determining unit, a second determining unit and a fourth processing unit, wherein the first determining unit is used for determining a data source related to data rollback according to a service double-write switch and a target list when a transaction corresponding to transaction data fails and the data rollback is required, the data source comprises a host and/or a distributed platform system, and the fourth processing unit is used for performing data rollback operation on the transaction data in the data source.

Embodiments of the present application may provide an electronic device, and fig. 12 is a block diagram of the electronic device according to an embodiment of the present application. As shown in fig. 12, the electronic device may include one or more processors (only one shown in fig. 12), a memory controller, and a peripheral interface, wherein the peripheral interface is connected with the radio frequency module, the audio module, and the display.

The memory may be used to store software programs and modules, such as program instructions/modules corresponding to the methods and apparatuses in the embodiments of the present application, and the processor executes the software programs and modules stored in the memory, thereby performing various functional applications and data processing, that is, implementing the methods described above. The memory may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory may further include memory remotely located with respect to the processor, the remote memory being connectable to the terminal through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.

It will be appreciated by those skilled in the art that the structure shown in fig. 12 is merely illustrative, and the electronic device may be a smart phone (such as an Android mobile phone, an iOS mobile phone, etc.), a tablet computer, a palm computer, a mobile internet device (MobileInternetDevices, MID), a PAD, etc. Fig. 12 is not limited to the structure of the electronic device. For example, the electronic device may also include more or fewer components (e.g., network interfaces, display devices, etc.) than shown in FIG. 12, or have a different configuration than shown in FIG. 12.

Those of ordinary skill in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be implemented by a program for instructing a terminal device related hardware, and the program may be stored in a computer readable storage medium, which may include a flash disk, a Read-only memory (ROM), a random access memory (RandomAccessMemory, RAM), a magnetic disk, an optical disk, or the like.

According to another aspect of the present application, there is also provided a computer readable storage medium, where a computer program is stored in the computer readable storage medium, where the computer readable storage medium is caused to execute the method for processing transaction data according to the above description when the computer program is executed.

According to another aspect of the present application, there is also provided a computer program product, where the computer program product includes computer instructions, where the computer instructions, when executed, cause a device in which the computer program product is located to perform the method for processing transaction data as described above.

The foregoing embodiments or examples of the present disclosure are not intended to be exhaustive or to limit the scope of the disclosure to the precise forms or examples disclosed. In the case of no contradiction, each step in a certain implementation or embodiment of the present application may be implemented as an independent embodiment, and the steps may be arbitrarily combined, for example, a scheme after removing part of the steps in a certain implementation or embodiment may be implemented as an independent embodiment, the order of the steps in a certain implementation or embodiment may be arbitrarily exchanged, and further, an alternative manner or alternative embodiment in a certain implementation or embodiment may be arbitrarily combined, and further, the implementation or embodiment may be arbitrarily combined, for example, part or all of the steps of different implementations or embodiments may be arbitrarily combined, and a certain implementation or embodiment may be arbitrarily combined with an alternative manner or alternative embodiment of other implementations or embodiments.

The foregoing embodiment numbers of the present application are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.

In the foregoing embodiments of the present application, the descriptions of the embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.

In the several embodiments provided in the present application, it should be understood that the disclosed technology may be implemented in other manners. The above-described embodiments of the apparatus are merely exemplary, and the division of the units, for example, may be a logic function division, and may be implemented in another manner, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interfaces, units or modules, or may be in electrical or other forms.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a storage medium, including instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. The storage medium includes a U disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, etc. which can store the program code.

The foregoing is merely a preferred embodiment of the present application and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present application, which are intended to be comprehended within the scope of the present application.

Claims

1. A method of processing transaction data, comprising:

Determining to write transaction data into a host and/or a distributed platform system according to a service double-write switch and a target list, wherein the target list is used for recording transaction objects from which transaction risks are eliminated, and the service double-write switch is used for determining data writing selection according to transaction attributes of the transaction data;

And after the transaction data is written into the host computer and/or the distributed platform system, performing data preservative treatment on the transaction data stored in the host computer and/or the transaction data stored in the distributed platform system, wherein the data preservative treatment is used for determining that the transaction data stored in the host computer is used as an output result or the transaction data stored in the distributed platform system is used as an output result.

2. The method of processing transaction data according to claim 1, wherein the method of processing transaction data further comprises:

Under the condition that the transaction data is written into the host computer and the distributed platform system at the same time, consistency check is carried out on the transaction data stored in the host computer and the transaction data stored in the distributed platform system, so as to obtain a check result;

and under the condition that the transaction data stored in the host computer is checked to be inconsistent with the transaction data stored in the distributed platform system, marking the state of a protocol routing state table as a target state, wherein the protocol routing state table is used for recording the state of a transaction protocol related to the transaction data, and the protocol routing state table in the target state is used for controlling all subsequent transaction requests using the transaction protocol to be processed by the host computer and not transmitted to the distributed platform system.

3. The method of processing transaction data according to claim 2, wherein performing a consistency check of the transaction data stored in the host computer and the transaction data stored in the distributed platform system includes:

acquiring a key field value returned by the host after writing the transaction data into the host;

acquiring a key field value returned by the distributed platform system after the transaction data is written into the distributed platform system;

Under the condition that the key field value returned by the host computer is detected to be the same as the key field value returned by the distributed platform system, determining that the transaction data stored in the host computer is consistent with the transaction data stored in the distributed platform system;

and under the condition that the key field value returned by the host computer is detected to be different from the key field value returned by the distributed platform system, determining that the transaction data stored in the host computer is inconsistent with the transaction data stored in the distributed platform system.

4. The method of claim 1, wherein determining to write transaction data to the host and/or the distributed platform system based on the service double write switch and the target list comprises:

Writing the transaction data into the host and the distributed platform system under the condition that the transaction object of the transaction data is detected to be the transaction object in the target list;

Under the condition that the transaction object of the transaction data is not the transaction object in the target list, detecting whether the transaction attribute of the service double-write switch is matched with the transaction attribute of the transaction data, wherein the transaction attribute is a precondition for starting the service double-write switch, and the service double-write switch is used for simultaneously writing the transaction data into the host and the distributed platform system after being started;

under the condition that the transaction attribute of the transaction data is matched with the dependent transaction attribute, the service double-write switch is started to write the transaction data into the host and the distributed platform system;

And under the condition that the transaction attribute of the transaction data and the dependent transaction attribute are not matched, the service double-write switch is forbidden to be started, and the transaction data is written into the host.

5. The method of claim 4, wherein the transaction-dependent attributes include at least one of the following three attributes:

Presetting a transaction area;

presetting a trade site;

presetting a transaction channel.

6. The method of claim 4, wherein detecting whether the transaction-dependent attribute of the service duel switch matches the transaction attribute of the transaction data comprises:

when the transaction attribute of the transaction data meets all the attributes included in the dependent transaction attribute, determining that the dependent transaction attribute of the service double-write switch is matched with the transaction attribute of the transaction data;

And when the transaction attribute of the transaction data does not meet any attribute included in the dependent transaction attribute, determining that the dependent transaction attribute of the service double-write switch is not matched with the transaction attribute of the transaction data.

7. The method according to claim 1, wherein before performing data preservation processing on the transaction data stored in the host computer and/or the transaction data stored in the distributed platform system, the method further comprises:

When the transaction data in the host and/or the distributed platform system is updated, copying the updated data into a data lake;

detecting a primary key, a version and time information corresponding to each data received by the data lake;

and screening the plurality of data received by the data lake according to the main key, the version and the time information corresponding to each data, wherein the screening operation is used for screening and obtaining the data with the latest update time and the target version from the plurality of data with the same main key but different versions, and the data of the target version represents the data subjected to the deleting operation.

8. The method according to claim 1, wherein performing data preservation processing on the transaction data stored in the host computer and/or the transaction data stored in the distributed platform system, comprises:

responding to the output instruction of the transaction data, and respectively inquiring the transaction data from the host and the distributed platform system;

Under the condition that the transaction data exists in the host and the transaction data does not exist in the distributed platform system, the transaction data in the host is used as the output result;

Under the condition that the transaction data exist in the host and the distributed platform system, taking the transaction data in the host as the output result;

And under the condition that the transaction data does not exist in the host and the transaction data exists in the distributed platform system, taking the transaction data in the distributed platform system as the output result.

9. The method of processing transaction data according to claim 1, wherein the method of processing transaction data further comprises:

when the transaction corresponding to the transaction data fails and data rollback is needed, determining a data source related to the data rollback according to the service double-write switch and the target list, wherein the data source comprises the host and/or the distributed platform system;

and performing data rollback operation on the transaction data in the data source.

10. A transaction data processing device, comprising:

The system comprises a determining unit, a service double-write switch and a target list, wherein the target list is used for recording transaction objects excluding transaction risks, and the service double-write switch is used for determining data write-in selection according to transaction attributes of the transaction data;

And the processing unit is used for carrying out data preservative treatment on the transaction data stored in the host computer and/or the transaction data stored in the distributed platform system after the transaction data are written into the host computer and/or the distributed platform system, wherein the data preservative treatment is used for determining that the transaction data stored in the host computer are used as output results or the transaction data stored in the distributed platform system are used as output results.

11. A computer readable storage medium, wherein a computer program is stored in the computer readable storage medium, and wherein the computer program, when executed, causes a device in which the computer readable storage medium is located to perform the method for processing transaction data according to any one of claims 1 to 9.

12. An electronic device comprising one or more processors and a memory for storing one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to perform the method of processing transaction data of any of claims 1-9.

13. A computer program product comprising computer instructions which, when executed by a processor, implement the steps of the transaction data processing method of any of claims 1 to 9.