Transaction data migration method and device, computer equipment, readable storage medium and program product

Abstract

The invention relates to a transaction data migration method and device, computer equipment, a computer readable storage medium and a computer program product, and is applied to the technical field of big data. Acquiring first attribute value information and first attribute name information of the contract management component data from a first business system of the data migration instruction; checking and updating the contract management component data according to the first attribute value information and the first attribute name information to obtain updated data; according to a data conversion relationship between a first service system and a second service system corresponding to the data migration instruction, performing data conversion on the updated data to obtain converted data; and checking and updating the converted data according to the second attribute value information and the second attribute name information of the converted data to obtain target data, and storing the target data in a second service system corresponding to the data migration instruction. By adopting the method, the transaction data migration accuracy can be improved.

Description

Technical Field

[0001] The present application relates to the field of big data technology, and in particular to a transaction data migration method, apparatus, computer equipment, computer-readable storage medium, and computer program product. Background Art

[0002] With the development of science and technology, big data technology is becoming more and more mature. Transaction components are tools for transaction management. In order to accurately monitor the transaction process, transactions need to be recorded at the end of the transaction, usually stored in the business system in the form of transaction process data. In order to meet the complex and changing business and transaction requirements of users, it is usually accompanied by the replacement of old and new systems. Therefore, in order to ensure the normal operation of transaction management, it is necessary to migrate the transaction process data from the old and new systems.

[0003] Currently, the migration of transaction process data between the old and new systems is usually achieved by staff writing complex SQL (Structured Query Language) statements. However, the data size of transaction process data is usually large, and new transaction processes may exist during the migration process, which easily leads to low efficiency in transaction data migration. Summary of the invention

[0004] Based on this, it is necessary to provide a transaction data migration method, apparatus, computer equipment, computer-readable storage medium and computer program product that can improve the accuracy of transaction data migration in response to the above technical problems.

[0005] In a first aspect, the present application provides a transaction data migration method, comprising:

[0006] In response to the data migration instruction, acquiring first transaction process data from a first business system corresponding to the data migration instruction;

[0007] According to a preset data conversion rule, data fields of the first transaction process data are converted to obtain second transaction process data, and the second transaction process data is stored in a second business system corresponding to the data migration instruction, wherein the preset data conversion rule is used to characterize the data field correspondence relationship between the transaction process data in the first business system and the transaction process data in the second business system;

[0008] Acquire transaction component data generated by a new transaction process in the first business system, and generate first update data corresponding to the new transaction process according to the transaction component data, wherein the first update data is used to update the first transaction process data;

[0009] According to the preset data conversion rule, the first update data is converted into data fields to obtain second update data, and the second update data is stored in the second business system, wherein the second update data is used to update the second transaction process data.

[0010] In one of the embodiments, the first transaction process data includes multiple first transaction process sub-data; generating the first update data corresponding to the new transaction process based on the transaction component data includes: selecting the data to be updated from the multiple first transaction process sub-data based on the correlation between the transaction component data and the multiple first transaction process sub-data; generating the first update data corresponding to the new transaction process based on the transaction operation information of the transaction component data in the new transaction process and the data to be updated.

[0011] In one of the embodiments, the method of selecting data to be updated from the multiple first transaction process sub-data based on the correlation between the transaction component data and the multiple first transaction process sub-data respectively includes: clustering the multiple first transaction process sub-data to obtain multiple clusters; selecting a target cluster matching the transaction component data from the multiple clusters based on the correlation between the transaction component data and the cluster features of the multiple clusters; and selecting data to be updated from the first transaction process sub-data contained in the target cluster according to the transaction operation logic between the first transaction process sub-data contained in the target cluster and the transaction component data respectively.

[0012] In one embodiment, the preset data conversion rule includes a first data conversion rule and a second data conversion rule; performing data field conversion on the first transaction process data according to the preset data conversion rule to obtain the second transaction process data includes: classifying the first transaction process data to obtain a data classification result, wherein the data classification result includes at least one of a customized data classification result, a combined data classification result and a regular data classification result; if the data classification result includes the combined data classification result, splitting the first transaction process data to obtain a plurality of split data, and performing data field conversion on the plurality of split data according to at least one of the first data conversion rule and the second data conversion rule to obtain the second transaction process data; if the data classification result includes the customized data classification result, performing data field conversion on the first transaction process data according to the first data conversion rule to obtain the second transaction process data; if the data classification result includes the regular data classification result, performing data field conversion on the first transaction process data according to the second data conversion rule to obtain the second transaction process data.

[0013] In one of the embodiments, the method further includes: detecting processing status information of each processing thread during the data conversion migration process; if it is detected that there is a target processing thread whose corresponding processing status information represents thread processing abnormality during the data conversion migration process, optimizing the target processing thread.

[0014] In one of the embodiments, the method further includes at least one of the following items: if the processing status information includes processing data traffic, then when the processing data traffic is lower than a preset traffic threshold, it is determined that the processing status information represents a thread processing abnormality; if the processing status information includes processing data rate, then when the processing data rate is lower than a preset rate threshold, it is determined that the processing status information represents a thread processing abnormality; if the processing status information includes processing data duration, then when the processing data duration is higher than a preset duration threshold, it is determined that the processing status information represents a thread processing abnormality; if the processing status information includes processing progress, then when the processing progress is lower than a preset progress threshold, it is determined that the processing status information represents a thread processing abnormality.

[0015] In a second aspect, the present application also provides a transaction data migration device, comprising:

[0016] an acquisition module, configured to, in response to a data migration instruction, acquire first transaction process data from a first business system corresponding to the data migration instruction;

[0017] a first conversion module, configured to perform data field conversion on the first transaction process data according to a preset data conversion rule to obtain second transaction process data, and store the second transaction process data in a second business system corresponding to the data migration instruction, wherein the preset data conversion rule is used to characterize a data field correspondence relationship between the transaction process data in the first business system and the transaction process data in the second business system;

[0018] a generating module, configured to obtain transaction component data generated by a new transaction process in the first business system, and generate first update data corresponding to the new transaction process according to the transaction component data, wherein the first update data is used to update the first transaction process data;

[0019] The second conversion module is used to perform data field conversion on the first update data according to the preset data conversion rule to obtain second update data, and store the second update data in the second business system, wherein the second update data is used to update the second transaction process data.

[0020] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0021] In response to the data migration instruction, acquiring first transaction process data from a first business system corresponding to the data migration instruction;

[0022] According to a preset data conversion rule, data fields of the first transaction process data are converted to obtain second transaction process data, and the second transaction process data is stored in a second business system corresponding to the data migration instruction, wherein the preset data conversion rule is used to characterize the data field correspondence relationship between the transaction process data in the first business system and the transaction process data in the second business system;

[0023] Acquire transaction component data generated by a new transaction process in the first business system, and generate first update data corresponding to the new transaction process according to the transaction component data, wherein the first update data is used to update the first transaction process data;

[0024] According to the preset data conversion rule, the first update data is converted into data fields to obtain second update data, and the second update data is stored in the second business system, wherein the second update data is used to update the second transaction process data.

[0025] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0026] In response to the data migration instruction, acquiring first transaction process data from a first business system corresponding to the data migration instruction;

[0027] According to a preset data conversion rule, data fields of the first transaction process data are converted to obtain second transaction process data, and the second transaction process data is stored in a second business system corresponding to the data migration instruction, wherein the preset data conversion rule is used to characterize the data field correspondence relationship between the transaction process data in the first business system and the transaction process data in the second business system;

[0028] Acquire transaction component data generated by a new transaction process in the first business system, and generate first update data corresponding to the new transaction process according to the transaction component data, wherein the first update data is used to update the first transaction process data;

[0029] According to the preset data conversion rule, the first update data is converted into data fields to obtain second update data, and the second update data is stored in the second business system, wherein the second update data is used to update the second transaction process data.

[0030] In a fifth aspect, the present application further provides a computer program product, including a computer program, which implements the following steps when executed by a processor:

[0031] In response to the data migration instruction, acquiring first transaction process data from a first business system corresponding to the data migration instruction;

[0032] According to a preset data conversion rule, data fields of the first transaction process data are converted to obtain second transaction process data, and the second transaction process data is stored in a second business system corresponding to the data migration instruction, wherein the preset data conversion rule is used to characterize the data field correspondence relationship between the transaction process data in the first business system and the transaction process data in the second business system;

[0033] Acquire transaction component data generated by a new transaction process in the first business system, and generate first update data corresponding to the new transaction process according to the transaction component data, wherein the first update data is used to update the first transaction process data;

[0034] According to the preset data conversion rule, the first update data is converted into data fields to obtain second update data, and the second update data is stored in the second business system, wherein the second update data is used to update the second transaction process data.

[0035] The transaction data migration method, apparatus, computer device, computer-readable storage medium and computer program product described above obtain first transaction process data from a first business system corresponding to the data migration instruction by responding to a data migration instruction; perform data field conversion on the first transaction process data according to a preset data conversion rule to obtain second transaction process data, and store the second transaction process data in a second business system corresponding to the data migration instruction, wherein the preset data conversion rule is used to characterize the data field correspondence between the transaction process data in the first business system and the transaction process data in the second business system; obtain transaction component data generated by a new transaction process in the first business system, and generate first update data corresponding to the new transaction process according to the transaction component data, wherein the first update data is used to convert the first transaction process data Data update: According to the preset data conversion rule, the data field of the first update data is converted to obtain the second update data, and the second update data is stored in the second business system, wherein the second update data is used to update the second transaction process data. First, the first transaction process data recording all transaction processes is converted and migrated from the old system to the new system. Even if the data scale of the first transaction process data is large and the data conversion and migration process takes a long time, for new transactions occurring during the data conversion and migration process, by generating the first update data, only the data conversion and migration of the old system to the new system is required for the first update data, without the need to convert and migrate the newly generated first transaction process data as a whole. Therefore, the time required for data conversion and migration for transaction records of new transactions is greatly shortened, thereby improving the efficiency of transaction data migration. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments of the present application or the related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative work.

[0037] Figure 1 A diagram of an application environment of a transaction data migration method in an embodiment;

[0038] Figure 2 A schematic diagram of a flow chart of a transaction data migration method in one embodiment;

[0039] Figure 3A schematic flow chart of a step of generating first update data corresponding to a new transaction process according to transaction component data, in which the first transaction process data includes a plurality of first transaction process sub-data in an embodiment;

[0040] Figure 4 A schematic diagram of a process flow of processing thread detection and thread optimization steps during data conversion and migration in one embodiment;

[0041] Figure 5 A schematic diagram of the execution flow of each unit in an application body of a transaction data migration method in an embodiment;

[0042] Figure 6 is a structural block diagram of a transaction data migration device in one embodiment;

[0043] Figure 7 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0045] It should be noted that the user information (including but not limited to data migration instructions, transaction component data, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the acquisition, transmission, storage, use and processing of relevant data are in compliance with the relevant provisions of national laws and regulations. The content pushed to the user (for example, the migration completion prompt information when the data migration is completed, etc.) can be rejected by the user or can be easily rejected by the content push, etc. In the embodiments of the present application, certain software, components, models and other existing solutions in the industry may be mentioned, and they should be regarded as exemplary. Their purpose is only to illustrate the feasibility of the implementation of the technical solution of this application, but it does not mean that the applicant has or will necessarily use the solution.

[0046] The transaction data migration method provided in the embodiment of the present application can be applied to Figure 1In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other network servers. In response to the data migration instruction, the server 104 obtains the first transaction process data from the first business system corresponding to the data migration instruction, performs data field conversion on the first transaction process data according to the preset data conversion rule, obtains the second transaction process data, and stores the second transaction process data in the second business system corresponding to the data migration instruction, wherein the preset data conversion rule is used to characterize the data field correspondence relationship between the transaction process data in the first business system and the transaction process data in the second business system; obtains the transaction component data generated by the new transaction process in the first business system, and generates the first update data corresponding to the new transaction process according to the transaction component data, wherein the first update data is used to update the first transaction process data; the server 104 performs data field conversion on the first update data according to the preset data conversion rule to obtain the second update data, and stores the second update data in the second business system, wherein the second update data is used to update the second transaction process data. The terminal 102 may be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, IoT devices, and portable wearable devices. The IoT devices may be smart speakers, smart TVs, smart air conditioners, smart car devices, projection devices, etc. Portable wearable devices may be smart watches, smart bracelets, head-mounted devices, etc. Head-mounted devices may be virtual reality (VR) devices, augmented reality (AR) devices, smart glasses, etc. The server 104 may be an independent physical server, a server cluster or distributed system consisting of multiple physical servers, or a cloud server that provides cloud computing services.

[0047] In an exemplary embodiment, Figure 2 As shown, a transaction data migration method is provided, which is applied to Figure 1 The server 104 in the example is used as an example to illustrate, including the following steps 202 to 208. Among them:

[0048] Step 202: In response to the data migration instruction, first transaction process data is obtained from a first business system corresponding to the data migration instruction.

[0049] The data migration instruction in step 202 can be initiated by the user on demand, or generated when the new business system is developed. The data migration instruction includes query information of the data to be migrated, the first business system, and the second business system. The first business system is the business system where the data to be migrated is located, for example, a DB2 (relational database management system) host database, and the second business system is the business system to which the data to be migrated will be migrated, which can also be a new business system that has been developed, for example, a GDB (GNU Debugger) distributed database. The first transaction process data is used to represent the recorded data of the transaction process when it is recorded in the first business system.

[0050] Exemplarily, obtaining first transaction process data from a first business system corresponding to a data migration instruction includes: querying data stored in the first business system according to query information of data to be migrated in the data migration instruction to obtain first attribute name information of the first transaction process data and first attribute value information corresponding to the first attribute name information.

[0051] As an embodiment, according to the query information of the data to be migrated in the data migration instruction, the data stored in the first business system is queried to obtain the first attribute name information of the first transaction process data and the first attribute value information corresponding to the first attribute name information, including: the query information of the data to be migrated includes a data type keyword, and the first attribute name information of the first transaction process data corresponding to the data type matching the data type keyword and the first attribute value information corresponding to the first attribute name information are queried from the data stored in the first business data, wherein the data type keyword is used to represent the keyword for querying the transaction process data.

[0052] In this way, it is possible to obtain all transaction process data in the first business system.

[0053] As another embodiment, according to the query information of the data to be migrated in the data migration instruction, the data stored in the first business system is queried to obtain the first attribute name information of the first transaction process data, including: the query information of the data to be migrated includes a data type keyword and a data attribute keyword; the first matching data corresponding to the data type and matching the data type keyword is queried from the data stored in the first business data; the first attribute name information of the first matching data is queried for the first attribute name information of the first transaction process data matching the data attribute keyword.

[0054] Among them, the match between the data type and the data type keyword, as well as the match between the first attribute name information and the data attribute keyword, can be determined by the text similarity between the two. Specifically, if the text similarity is greater than the preset similarity threshold, it is determined that the two match. The preset similarity threshold corresponding to the data type and the data type keyword may be the same as the preset similarity threshold corresponding to the first attribute name information and the data attribute keyword, or may be different, and there is no limitation here.

[0055] As an embodiment, the data attribute keywords are set by the user as needed.

[0056] In this way, the user can customize the data content contained in the first transaction process data so that the acquired first transaction process data meets the user's expectations.

[0057] As another embodiment, the data attribute keyword is determined by a preset generation time period, specifically, the data attribute keyword is extracted from the attribute name information of the data corresponding to the transaction generation time in the first matching data within the preset generation time period.

[0058] In this way, the transaction generation time corresponding to the acquired first transaction process data is in line with expectations.

[0059] As another embodiment, the data attribute keyword is determined by the data verification result corresponding to the first matching data, specifically, the data attribute keyword is extracted from the attribute name information of the data that has passed the data verification represented by the corresponding data verification result in the first matching data.

[0060] In this way, the extracted first transaction process data is subjected to data verification, that is, the accuracy of the first transaction process data is guaranteed.

[0061] Step 204, according to the preset data conversion rules, the data fields of the first transaction process data are converted to obtain the second transaction process data, and the second transaction process data is stored in the second business system corresponding to the data migration instruction, wherein the preset data conversion rules are used to characterize the data field correspondence between the transaction process data in the first business system and the transaction process data in the second business system.

[0062] The data field conversion in step 204 includes at least one of data field format conversion and data field content conversion, and the data field content conversion includes at least one of data field value conversion and data field description conversion.

[0063] Exemplarily, step 204 includes: presetting data conversion rules including a correspondence between a representation form of each data in the first business system and a representation form in the second business system; performing data field conversion on the first transaction process data according to the correspondence between a representation form of each data in the first business system and a representation form in the second business system to obtain second transaction process data.

[0064] As an embodiment, step 204 includes: the first transaction process data includes multiple first transaction process sub-data, and the multiple first transaction process sub-data are classified respectively to obtain data classification results of the multiple first transaction process sub-data, wherein the data classification results include at least one of a customized data classification result, a combined data classification result and a conventional data classification result; if the data classification results of the first transaction process sub-data include a combined data classification result, the first transaction process sub-data is split to obtain multiple split data, and data field conversion is performed on the multiple split data according to at least one of a first data conversion rule and a second data conversion rule to obtain second transaction process sub-data; if the data classification results of the first transaction process sub-data include a customized data classification result, the first transaction process sub-data is converted into a data field according to the first data conversion rule to obtain second transaction process sub-data; if the data classification results include a conventional data classification result, the first transaction process data is converted into a data field according to the second data conversion rule to obtain second transaction process sub-data; and the second transaction process sub-data obtained by performing data field conversion on all the first transaction process sub-data respectively are collectively determined as the second transaction process data.

[0065] In this way, different data conversion rules are used for different types of first transaction process data to perform data field conversion, thereby ensuring the data conversion accuracy of the first transaction process data.

[0066] Furthermore, multiple first transaction process sub-data are classified respectively to obtain data classification results of multiple first transaction process sub-data, including: for each transaction process sub-data, if the data byte length of the first transaction process sub-data is greater than a preset byte length threshold, then the data classification result of the transaction process sub-data is determined to be a combined data classification result; if the data byte length of the first transaction process sub-data is not greater than the preset byte length threshold, then the first transaction process sub-data is matched with a preset conventional database and a preset customized database respectively to obtain a matching result; when the matching result indicates that the first transaction process sub-data matches the preset conventional database, the data classification result of the transaction process sub-data is determined to be a conventional data classification result; when the matching result indicates that the first transaction process sub-data matches the preset customized database, the data classification result of the transaction process sub-data is determined to be a customized data classification result.

[0067] In this way, a classification method for transaction process sub-data is provided, which ensures the classification accuracy of the transaction process sub-data, further ensures that the transaction process sub-data adopts matching data conversion rules, and improves the data conversion accuracy of the first transaction process data.

[0068] Step 206, obtaining the transaction component data generated by the new transaction process in the first business system, and generating first update data corresponding to the new transaction process based on the transaction component data, wherein the first update data is used to update the first transaction process data.

[0069] The first update data in step 206 may be replacement data for the first transaction process data, or may be a data update statement for the first transaction process data, such as an SQL statement.

[0070] Exemplarily, obtaining transaction component data generated by a new transaction process in the first business system includes: if a new transaction process in the first business system is detected, querying the transaction component data generated in the first business system within a preset transaction time period.

[0071] The earliest time point in the preset transaction time period is later than the latest time point in the preset generation time period corresponding to the first transaction process data.

[0072] Exemplarily, generating first update data corresponding to a new transaction process based on transaction component data includes: selecting data to be updated from the first transaction process data based on the transaction component data; generating first update data corresponding to the new transaction process based on the data to be updated and the transaction component data.

[0073] As an embodiment, generating first update data corresponding to a new transaction process according to the data to be updated and the transaction component data includes: generating replacement data corresponding to the data to be updated according to the transaction component data; and determining the replacement data as the first update data corresponding to the new transaction process.

[0074] In this way, replacement data corresponding to the data to be updated is directly generated, and the data to be updated is replaced by the replacement data, so as to implement the update of the data to be updated.

[0075] As another embodiment, generating first update data corresponding to a new transaction process based on the data to be updated and the transaction component data includes: generating a data update statement corresponding to the data to be updated based on the transaction component data; and determining the data update statement as the first update data corresponding to the new transaction process.

[0076] In this way, a data update statement corresponding to the data to be updated is generated, and after the data update statement is deployed to the business system and executed, the data update of the data to be updated can be realized.

[0077] Step 208, according to the preset data conversion rule, the first updated data is converted into data fields to obtain second updated data, and the second updated data is stored in the second business system, wherein the second updated data is used to update the second transaction process data.

[0078] Exemplarily, according to preset data conversion rules, data field conversion is performed on the first update data to obtain second update data, including: if the first update data includes replacement data, then according to the preset data conversion rules, data field conversion is performed on the replacement data to obtain second update data; the preset data conversion rules also include statement conversion rules, if the first update data includes a data update statement, then according to the statement conversion rules, statement field conversion is performed on the data update statement to obtain second update data.

[0079] Optionally, according to a preset data conversion rule, data field conversion is performed on the replacement data to obtain the second update data. The specific implementation method can refer to the specific implementation content of the above step 204, which will not be described in detail here.

[0080] As an embodiment, performing statement field conversion on the data update statement according to the statement conversion rule to obtain the second update data includes: converting the statement field format in the data update statement according to the statement conversion rule to obtain the second update data.

[0081] As an embodiment, if the first update data includes a data update statement, then after storing the second update data in the second business system, the method further includes: executing the second update data.

[0082] In this way, the second update data is executed in the second business system to update the second transaction process data in the second business system.

[0083] In the transaction data migration method, in response to a data migration instruction, first transaction process data is obtained from a first business system corresponding to the data migration instruction; according to a preset data conversion rule, data field conversion is performed on the first transaction process data to obtain second transaction process data, and the second transaction process data is stored in the second business system corresponding to the data migration instruction, wherein the preset data conversion rule is used to characterize the data field correspondence relationship between the transaction process data in the first business system and the transaction process data in the second business system; transaction component data generated by a new transaction process in the first business system is obtained, and first update data corresponding to the new transaction process is generated according to the transaction component data, wherein the first update data is used to update the first transaction process data; according to the preset data conversion rule, the first transaction process data is converted into the first transaction process data. The updated data is used to perform data field conversion to obtain second updated data, and the second updated data is stored in the second business system, wherein the second updated data is used to perform data update on the second transaction process data. First, the first transaction process data recording all transaction processes is used to perform data conversion and migration between the old and new systems. Even if the data scale of the first transaction process data is large and the data conversion and migration process takes a long time, for new transactions occurring during the data conversion and migration process, by generating the first updated data, only the data conversion and migration between the old and new systems of the first updated data need to be performed, without the need to perform data conversion and migration on the newly generated first transaction process data as a whole. Therefore, the time required for data conversion and migration for transaction records of new transaction processes is greatly shortened, thereby improving the efficiency of transaction data migration.

[0084] It is understandable that the first transaction process data records the transaction records of the transaction process that has occurred, so the new transaction process usually has a certain correlation with the transaction process that has occurred. If the correlation between the transaction component data generated by the new transaction process and the first transaction process data is not considered, it is easy to cause the generated first update data to be relatively separated from the first transaction process data, resulting in a relatively chaotic transaction record represented by the data obtained by the subsequent second transaction process data update. Therefore, there is an urgent need for a method for generating first update data that can improve the accuracy of the first update data.

[0085] In an exemplary embodiment, Figure 3 As shown, the first transaction process data includes a plurality of first transaction process sub-data; the first transaction process data includes a plurality of first transaction process sub-data; and generating the first update data corresponding to the new transaction process according to the transaction component data includes steps 302 to 304. Among them:

[0086] Step 302 : selecting data to be updated from the plurality of first transaction process sub-data according to the correlations between the transaction component data and the plurality of first transaction process sub-data respectively.

[0087] Exemplarily, step 302 includes: selecting corresponding data to be updated whose correlations satisfy preset correlation conditions from multiple first transaction process sub-data, wherein the preset correlation condition can be the maximum value of the correlations corresponding to all first transaction process sub-data, or can be a preset correlation range, which is not limited here.

[0088] As an embodiment, step 302 includes: clustering multiple first transaction process sub-data to obtain multiple clustering clusters; selecting a target clustering cluster matching the transaction component data from the multiple clustering clusters based on the correlation between the transaction component data and the cluster features of the multiple clustering clusters; selecting the data to be updated from the first transaction process sub-data contained in the target clustering cluster based on the transaction operation logic between the first transaction process sub-data contained in the target clustering cluster and the transaction component data.

[0089] In this way, the first transaction process sub-data is clustered, and then the transaction component data is compared with the cluster features of the cluster clusters to select the data to be updated, thereby improving the accuracy of selecting the data to be updated.

[0090] Further, as an embodiment, according to the correlation between the transaction component data and the cluster features of the plurality of clustering clusters, a target clustering cluster matching the transaction component data is selected from the plurality of clustering clusters, including: the plurality of clustering clusters include a plurality of first-category clustering clusters, wherein the first-category clustering clusters are obtained by respectively clustering a plurality of first transaction process sub-data belonging to the same transaction process; if there is a target clustering cluster whose corresponding correlation representation matches the transaction component data in the first-category clustering clusters, then according to the transaction operation logic between the first transaction process sub-data contained in the target clustering cluster and the transaction component data, the data to be updated is selected from the first transaction process sub-data contained in the target clustering cluster; if there is no target clustering cluster whose corresponding correlation representation matches the transaction component data in the first-category clustering clusters, then the first transaction process sub-data belonging to the same transaction process is selected. Clustering multiple first transaction process sub-data of the transaction process generated by the image to obtain multiple second-class clustering clusters; if there is a target clustering cluster whose corresponding correlation representation matches the transaction component data in the second-class clustering clusters, then according to the transaction operation logic between the first transaction process sub-data contained in the target clustering cluster and the transaction component data, the data to be updated is selected from the first transaction process sub-data contained in the target clustering cluster; if there is no target clustering cluster whose corresponding correlation representation matches the transaction component data in the second-class clustering clusters, clustering multiple first transaction process sub-data belonging to the same transaction type to obtain multiple third-class clustering clusters; according to the correlation between the transaction component data and the cluster features of the multiple third-class clustering clusters, the target clustering cluster matching the transaction component data is selected from the multiple third-class clustering clusters.

[0091] In this way, taking into account the situations of various new transaction processes, for example, the situation of changes in a completed transaction process, the situation of a new transaction process of the same user, or the situation of a new transaction process of the same transaction type as the completed transaction process, the data to be updated can be accurately found, thereby improving the accuracy of selecting the data to be updated.

[0092] As one embodiment, according to the transaction operation logic between the first transaction process sub-data contained in the target cluster and the transaction component data, the data to be updated is selected from the first transaction process sub-data contained in the target cluster, including: determining the data in the first transaction process sub-data contained in the target cluster that belongs to the same transaction operation logic as the data to be updated as the data to be updated.

[0093] Step 304: Generate first update data corresponding to the new transaction process according to the transaction operation information and the data to be updated of the transaction component data in the new transaction process.

[0094] As an embodiment, step 304 includes: generating replacement data corresponding to the data to be updated according to transaction operation information of the transaction component data in the new transaction process, and determining the replacement data corresponding to the data to be updated as the first update data corresponding to the new transaction process.

[0095] As another embodiment, step 304 includes: generating a data update statement corresponding to the data to be updated based on the transaction operation information of the transaction component data in the new transaction process and the data to be updated, and determining the data update statement corresponding to the data to be updated as the first update data corresponding to the new transaction process.

[0096] In this embodiment, data to be updated is selected from multiple first transaction process sub-data based on the correlations between the transaction component data and the multiple first transaction process sub-data respectively; first update data corresponding to the new transaction process is generated based on the transaction operation information and the data to be updated of the transaction component data in the new transaction process; the correlations between the transaction component data and the multiple first transaction process sub-data are used as the basis for selecting the data to be updated; the accuracy of selecting the data to be updated is improved by taking into account the correlations between the multiple transaction processes; accurate data to be updated and transaction operation information are used as the basis for generating the first update data; the accuracy of generating the first update data for updating the first transaction process data is ensured.

[0097] It is understandable that during the above data migration and conversion process, there may be an exception in one of the processing threads. If the exception is not resolved in time, the processing thread may not be able to process normally, or the processing thread may take too long to process, resulting in low transaction data migration efficiency. Therefore, there is an urgent need for a method to improve the efficiency of transaction data migration.

[0098] In an exemplary embodiment, Figure 4 As shown, the method further includes steps 402 to 404. Among them:

[0099] Step 402: Detect processing status information of each processing thread during the data conversion and migration process.

[0100] The processing status information in step 402 includes at least one of processing data flow, processing data rate, processing data duration and processing progress. The processing thread includes at least one of a first processing thread corresponding to data field conversion of the first transaction process data, a second processing thread corresponding to storing the second transaction process data in the second business system, a third processing thread corresponding to data field conversion of the first update data and a fourth processing thread corresponding to storing the second update data in the second business system.

[0101] Exemplarily, step 402 includes: detecting processing status information of at least one of a first processing thread, a second processing thread, a third processing thread, and a fourth processing thread during the data conversion migration process.

[0102] Step 404: If it is detected that there is a target processing thread whose corresponding processing status information indicates thread processing abnormality during the data conversion migration process, the target processing thread is optimized.

[0103] As an embodiment, the method also includes at least one of the following items: if the processing status information includes processing data traffic, then when the processing data traffic is lower than a preset traffic threshold, it is determined that the processing status information represents a thread processing abnormality; if the processing status information includes processing data rate, then when the processing data rate is lower than a preset rate threshold, it is determined that the processing status information represents a thread processing abnormality; if the processing status information includes processing data duration, then when the processing data duration is higher than a preset duration threshold, it is determined that the processing status information represents a thread processing abnormality; if the processing status information includes processing progress, then when the processing progress is lower than a preset progress threshold, it is determined that the processing status information represents a thread processing abnormality.

[0104] As an embodiment, optimizing the target processing thread includes: selecting processing data to be optimized from the target processing thread according to thread processing state distribution information of processing state information of the target processing thread; and optimizing the processing data to be optimized.

[0105] Furthermore, the target processing thread is optimized according to the thread processing state distribution information of the processing state information of the target processing thread, including: identifying abnormal thread data in the target processing thread according to the thread processing state distribution information of the processing state information of the target processing thread; and optimizing the abnormal thread data.

[0106] Wherein, when the target processing thread belongs to the first processing thread or the third processing thread, the abnormal thread data is a preset data conversion rule; when the target processing thread belongs to the second processing thread or the fourth processing thread, the abnormal thread data is communication transmission data.

[0107] Optionally, refer to Figure 5 The execution objects of the processing thread are the data acquisition unit, the data conversion unit and the data transmission unit. The data acquisition unit is used to obtain the first transaction process data from the DB2 host database; the data conversion unit is used to perform data field conversion on the first transaction process data, and to perform data field conversion on the first update data; the data transmission unit is used to transmit the second transaction process data to the GDB distributed database, and to transmit the second update data to the GDB distributed database. The monitoring unit is used to monitor the processing thread.

[0108] In this embodiment, the processing status information of each processing thread in the data conversion and migration process is detected; if it is detected that there is a target processing thread with corresponding processing status information representing thread processing exception in the data conversion and migration process, the target processing thread is optimized, and when the data migration and conversion process is in progress, the exception of the processing thread is detected, and when the exception is detected, the existing exception is resolved in time to ensure the normal processing of the processing thread, thereby improving the efficiency of transaction data migration.

[0109] As a detailed embodiment, in response to a data migration instruction, first transaction process data is obtained from a first business system corresponding to the data migration instruction; the first transaction process data is classified to obtain a data classification result, wherein the data classification result includes at least one of a customized data classification result, a combined data classification result, and a conventional data classification result; if the data classification result includes a combined data classification result, the first transaction process data is split to obtain a plurality of split data, and data fields are converted on the plurality of split data according to at least one of a first data conversion rule and a second data conversion rule to obtain second transaction process data; if the data classification result includes a customized data classification result, data fields are converted on the first transaction process data according to the first data conversion rule to obtain second transaction process data; if the data classification result includes a conventional data classification result, data fields are converted on the first transaction process data according to the second data conversion rule to obtain second transaction process data; And the second transaction process data is stored in the second business system corresponding to the data migration instruction; the transaction component data generated by the new transaction process in the first business system is obtained, and multiple first transaction process sub-data are clustered to obtain multiple cluster clusters; according to the correlation between the transaction component data and the cluster features of the multiple cluster clusters, a target cluster cluster matching the transaction component data is selected from the multiple cluster clusters; according to the transaction operation logic between the first transaction process sub-data contained in the target cluster cluster and the transaction component data, the data to be updated is selected from the first transaction process sub-data contained in the target cluster cluster; according to the transaction operation information and the data to be updated of the transaction component data in the new transaction process, the first update data corresponding to the new transaction process is generated; according to the preset data conversion rule, the data field conversion is performed on the first update data to obtain the second update data, and the second update data is stored in the second business system, wherein the second update data is used to update the second transaction process data.

[0110] Furthermore, the processing status information of each processing thread in the data conversion migration process is detected; if the processing status information includes processing data traffic, then when the processing data traffic is lower than a preset traffic threshold, it is determined that the processing status information represents thread processing abnormality; if the processing status information includes processing data rate, then when the processing data rate is lower than a preset rate threshold, it is determined that the processing status information represents thread processing abnormality; if the processing status information includes processing data duration, then when the processing data duration is higher than a preset duration threshold, it is determined that the processing status information represents thread processing abnormality; if the processing status information includes processing progress, then when the processing progress is lower than a preset progress threshold, it is determined that the processing status information represents thread processing abnormality; if it is detected that there is a target processing thread with corresponding processing status information representing thread processing abnormality in the data conversion migration process, the target processing thread is optimized.

[0111] In this way, by responding to the data migration instruction, the first transaction process data is obtained from the first business system corresponding to the data migration instruction; according to the preset data conversion rule, the data field of the first transaction process data is converted to obtain the second transaction process data, and the second transaction process data is stored in the second business system corresponding to the data migration instruction, wherein the preset data conversion rule is used to characterize the data field correspondence between the transaction process data in the first business system and the transaction process data in the second business system; the transaction component data generated by the new transaction process in the first business system is obtained, and according to the transaction component data, the first update data corresponding to the new transaction process is generated, wherein the first update data is used to update the first transaction process data; according to the preset data conversion rule, the first update data is converted to the first update data. Data field conversion is performed to obtain second updated data, and the second updated data is stored in the second business system, wherein the second updated data is used to update the second transaction process data. First, the first transaction process data recording all transaction processes is converted and migrated between the old and new systems. Even if the data scale of the first transaction process data is large and the data conversion and migration process takes a long time, for new transactions occurring during the data conversion and migration process, by generating the first updated data, only the data conversion and migration of the old and new systems is required for the first updated data, without the need for data conversion and migration of the newly generated first transaction process data as a whole. Therefore, the time required for data conversion and migration for transaction records of new transaction processes is greatly shortened, thereby improving the efficiency of transaction data migration.

[0112] Furthermore, by selecting the data to be updated from the multiple first transaction process sub-data according to the correlation between the transaction component data and the multiple first transaction process sub-data respectively; generating the first update data corresponding to the new transaction process according to the transaction operation information and the data to be updated of the transaction component data in the new transaction process; using the correlation between the transaction component data and the multiple first transaction process sub-data respectively as the basis for selecting the data to be updated, taking into account the correlation between the multiple transaction processes, the accuracy of selecting the data to be updated is improved, and using the accurate data to be updated and the transaction operation information as the basis for generating the first update data, the accuracy of generating the first update data for updating the first transaction process data is ensured, and the processing status information of each processing thread in the data conversion migration process is detected; if it is detected that there is a target processing thread whose corresponding processing status information represents thread processing exception in the data conversion migration process, the target processing thread is optimized, and when the data migration conversion process is in progress, the exception of the processing thread is detected, and when the exception is detected, the existing exception is promptly resolved to ensure the normal processing of the processing thread, thereby improving the efficiency of transaction data migration.

[0113] It should be understood that, although the steps in the flowcharts involved in the above embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0114] Based on the same inventive concept, the embodiment of the present application also provides a transaction data migration device for implementing the transaction data migration method involved above. The implementation solution provided by the device to solve the problem is similar to the implementation solution recorded in the above method, so the specific limitations in one or more transaction data migration device embodiments provided below can refer to the limitations of the transaction data migration method above, and will not be repeated here.

[0115] In an exemplary embodiment, Figure 6 As shown, a transaction data migration device 600 is provided, comprising: an acquisition module 602, a first conversion module 604, a generation module 606 and a second conversion module 608, wherein:

[0116] An acquisition module 602 is used to acquire first transaction process data from a first business system corresponding to the data migration instruction in response to the data migration instruction;

[0117] A first conversion module 604 is used to perform data field conversion on the first transaction process data according to a preset data conversion rule to obtain second transaction process data, and store the second transaction process data in a second business system corresponding to the data migration instruction, wherein the preset data conversion rule is used to characterize the data field correspondence relationship between the transaction process data in the first business system and the transaction process data in the second business system;

[0118] A generating module 606 is used to obtain transaction component data generated by a new transaction process in the first business system, and generate first update data corresponding to the new transaction process according to the transaction component data, wherein the first update data is used to update the first transaction process data;

[0119] The second conversion module 608 is used to perform data field conversion on the first update data according to a preset data conversion rule to obtain second update data, and store the second update data in the second business system, wherein the second update data is used to update the second transaction process data.

[0120] In one embodiment, the first transaction process data includes multiple first transaction process sub-data; the generation module 606 is also used to select the data to be updated from the multiple first transaction process sub-data according to the correlation between the transaction component data and the multiple first transaction process sub-data; and generate the first update data corresponding to the new transaction process according to the transaction operation information and the data to be updated of the transaction component data in the new transaction process.

[0121] In one of the embodiments, the generation module 606 is further used to cluster multiple first transaction process sub-data to obtain multiple clustering clusters; select a target clustering cluster matching the transaction component data from the multiple clustering clusters based on the correlation between the transaction component data and the cluster features of the multiple clustering clusters; and select the data to be updated from the first transaction process sub-data contained in the target clustering cluster based on the transaction operation logic between the first transaction process sub-data contained in the target clustering cluster and the transaction component data.

[0122] In one embodiment, the preset data conversion rules include a first data conversion rule and a second data conversion rule; the first conversion module 604 is also used to classify the first transaction process data to obtain a data classification result, wherein the data classification result includes a customized data classification result, a combined data classification result and a regular data classification result; if the data classification result includes a combined data classification result, the first transaction process data is split to obtain a plurality of split data, and data fields are converted on the plurality of split data according to at least one of the first data conversion rule and the second data conversion rule to obtain the second transaction process data; if the data classification result includes a customized data classification result, data fields are converted on the first transaction process data according to the first data conversion rule to obtain the second transaction process data; if the data classification result includes a regular data classification result, data fields are converted on the first transaction process data according to the second data conversion rule to obtain the second transaction process data.

[0123] In one of the embodiments, the device also includes: an optimization module, which is used to detect the processing status information of each processing thread during the data conversion migration process; if it is detected that there is a target processing thread whose corresponding processing status information represents thread processing abnormality during the data conversion migration process, the target processing thread is optimized.

[0124] In one of the embodiments, the optimization module is also used to, if the processing status information includes processing data traffic, then when the processing data traffic is lower than a preset traffic threshold, determine that the processing status information represents a thread processing abnormality; if the processing status information includes processing data rate, then when the processing data rate is lower than a preset rate threshold, determine that the processing status information represents a thread processing abnormality; if the processing status information includes processing data duration, then when the processing data duration is higher than a preset duration threshold, determine that the processing status information represents a thread processing abnormality; if the processing status information includes processing progress, then when the processing progress is lower than a preset progress threshold, determine that the processing status information represents a thread processing abnormality.

[0125] Each module in the transaction data migration device can be implemented in whole or in part by software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each module.

[0126] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Figure 7 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store object information and service information. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a transaction data migration method is implemented.

[0127] Those skilled in the art will understand that Figure 7 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0128] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0129] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0130] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0131] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0132] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0133] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A transaction data migration method, characterized in that: The method comprises: In response to the data migration instruction, acquiring first transaction process data from a first business system corresponding to the data migration instruction; According to a preset data conversion rule, data fields of the first transaction process data are converted to obtain second transaction process data, and the second transaction process data is stored in a second business system corresponding to the data migration instruction, wherein the preset data conversion rule is used to characterize the data field correspondence relationship between the transaction process data in the first business system and the transaction process data in the second business system; Acquire transaction component data generated by a new transaction process in the first business system, and generate first update data corresponding to the new transaction process according to the transaction component data, wherein the first update data is used to update the first transaction process data; According to the preset data conversion rule, the first update data is converted into data fields to obtain second update data, and the second update data is stored in the second business system, wherein the second update data is used to update the second transaction process data.

2. The method according to claim 1, characterized in that The first transaction process data includes a plurality of first transaction process sub-data; and generating the first update data corresponding to the new transaction process according to the transaction component data includes: Selecting data to be updated from the plurality of first transaction process sub-data according to the correlations between the transaction component data and the plurality of first transaction process sub-data respectively; Generate first update data corresponding to the new transaction process according to the transaction operation information of the transaction component data in the new transaction process and the data to be updated.

3. The method according to claim 2, characterized in that The selecting the data to be updated from the plurality of first transaction process sub-data according to the correlation between the transaction component data and the plurality of first transaction process sub-data respectively comprises: Clustering the plurality of first transaction process sub-data to obtain a plurality of clusters; Selecting a target cluster matching the transaction component data from the multiple clusters according to the correlations between the transaction component data and the cluster features of the multiple clusters; According to the transaction operation logic between the first transaction process sub-data contained in the target cluster and the transaction component data, the data to be updated is selected from the first transaction process sub-data contained in the target cluster.

4. The method according to claim 1, characterized in that The preset data conversion rule includes a first data conversion rule and a second data conversion rule; performing data field conversion on the first transaction process data according to the preset data conversion rule to obtain the second transaction process data includes: Classifying the first transaction process data to obtain a data classification result, wherein the data classification result includes at least one of a customized data classification result, a combined data classification result, and a regular data classification result; If the data classification result includes the combined data classification result, splitting the first transaction process data to obtain a plurality of split data, and performing data field conversion on the plurality of split data according to at least one of the first data conversion rule and the second data conversion rule to obtain second transaction process data; If the data classification result includes the customized data classification result, performing data field conversion on the first transaction process data according to the first data conversion rule to obtain second transaction process data; If the data classification result includes the conventional data classification result, data field conversion is performed on the first transaction process data according to the second data conversion rule to obtain second transaction process data.

5. The method according to claim 1, characterized in that: The method further comprises: Detecting the processing status information of each processing thread during the data conversion and migration process; If it is detected that there is a target processing thread whose corresponding processing status information represents thread processing abnormality during the data conversion migration process, the target processing thread is optimized.

6. The method according to claim 5, characterized in that The method further comprises at least one of the following: If the processing status information includes processing data flow, then when the processing data flow is lower than a preset flow threshold, determining that the processing status information represents thread processing abnormality; If the processing status information includes a processing data rate, then, if the processing data rate is lower than a preset rate threshold, determining that the processing status information represents a thread processing abnormality; If the processing status information includes a data processing time, then when the data processing time is higher than a preset time threshold, it is determined that the processing status information represents a thread processing exception; If the processing status information includes processing progress, then when the processing progress is lower than a preset progress threshold, it is determined that the processing status information represents thread processing abnormality.

7. A transaction data migration device, characterized in that: The device comprises: an acquisition module, configured to, in response to a data migration instruction, acquire first transaction process data from a first business system corresponding to the data migration instruction; a first conversion module, configured to perform data field conversion on the first transaction process data according to a preset data conversion rule to obtain second transaction process data, and store the second transaction process data in a second business system corresponding to the data migration instruction, wherein the preset data conversion rule is used to characterize a data field correspondence relationship between the transaction process data in the first business system and the transaction process data in the second business system; a generating module, configured to obtain transaction component data generated by a new transaction process in the first business system, and generate first update data corresponding to the new transaction process according to the transaction component data, wherein the first update data is used to update the first transaction process data; The second conversion module is used to perform data field conversion on the first update data according to the preset data conversion rule to obtain second update data, and store the second update data in the second business system, wherein the second update data is used to update the second transaction process data.

8. The device according to claim 7, characterized in that The first transaction process data includes multiple first transaction process sub-data; the generation module is also used to select the data to be updated from the multiple first transaction process sub-data according to the correlation between the transaction component data and the multiple first transaction process sub-data respectively; and generate the first update data corresponding to the new transaction process according to the transaction operation information of the transaction component data in the new transaction process and the data to be updated.

9. The device according to claim 8, characterized in that The generation module is also used to cluster the multiple first transaction process sub-data to obtain multiple clustering clusters; select a target clustering cluster matching the transaction component data from the multiple clustering clusters according to the correlation between the transaction component data and the cluster features of the multiple clustering clusters; and select data to be updated from the first transaction process sub-data contained in the target clustering cluster according to the transaction operation logic between the first transaction process sub-data contained in the target clustering cluster and the transaction component data.

10. The device according to claim 7, characterized in that The preset data conversion rules include a first data conversion rule and a second data conversion rule; the first conversion module is also used to classify the first transaction process data to obtain a data classification result, wherein the data classification result includes a customized data classification result, a combined data classification result and a regular data classification result; if the data classification result includes the combined data classification result, the first transaction process data is split to obtain a plurality of split data, and according to at least one of the first data conversion rule and the second data conversion rule, the plurality of split data are subjected to data field conversion to obtain the second transaction process data; if the data classification result includes the customized data classification result, according to the first data conversion rule, the first transaction process data is subjected to data field conversion to obtain the second transaction process data; if the data classification result includes the regular data classification result, according to the second data conversion rule, the first transaction process data is subjected to data field conversion to obtain the second transaction process data.

11. The device according to claim 7, characterized in that The device also includes: an optimization module, which is used to detect the processing status information of each processing thread during the data conversion migration process; if it is detected that there is a target processing thread whose corresponding processing status information represents thread processing abnormality during the data conversion migration process, the target processing thread is optimized.

12. The device according to claim 11, characterized in that The optimization module is further configured to, if the processing status information includes processing data flow, determine that the processing status information represents thread processing abnormality when the processing data flow is lower than a preset flow threshold; If the processing status information includes a processing data rate, then, if the processing data rate is lower than a preset rate threshold, determining that the processing status information represents a thread processing abnormality; If the processing status information includes the duration of processing data, then when the duration of processing data is higher than a preset duration threshold, it is determined that the processing status information represents a thread processing exception; if the processing status information includes processing progress, then when the processing progress is lower than a preset progress threshold, it is determined that the processing status information represents a thread processing exception.

13. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

14. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

15. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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