Data processing method and device, equipment and storage medium

Abstract

The present disclosure provides a data processing method, device and equipment and storage medium, which can be applied to the fields of big data technology and financial technology. The method comprises: in response to receiving a data processing request from a target transaction node, obtaining initial transaction data and an identifier of the initial transaction data by analyzing a transaction message from a data source; querying a target public parameter from public parameter configuration information of a data processing platform according to the identifier of the initial transaction data; processing the initial transaction data by using the target public parameter to obtain public transaction data; querying a target difference parameter from difference parameter configuration information of the data processing platform according to the identifier of the target transaction node and the identifier of the initial transaction data; processing the public transaction data by using the target difference parameter to obtain target transaction data; and sending the target transaction data to the target transaction node.

Description

Technical Field

[0001] This disclosure relates to the fields of big data technology and financial technology, and in particular to a data processing method, apparatus, device, medium and program product. Background Technology

[0002] The initial transaction data that financial institutions obtain from various data sources in financial transaction centers is relatively homogeneous and difficult to meet the transaction needs of different business scenarios in different regions. The traditional approach is to deploy data processing systems in each region to process the initial transaction data according to the actual needs of different regions to obtain transaction data applicable to specific local business scenarios.

[0003] However, in the process of realizing the inventive concept of this disclosure, the inventors found that this approach not only wastes computing resources by repeatedly deploying a large number of computing systems, but also presents significant difficulties in scaling up the distributed system architecture, resulting in low data processing efficiency. Summary of the Invention

[0004] In view of the above problems, this disclosure provides a data processing method, apparatus, device, medium and program product.

[0005] According to one aspect of this disclosure, a data processing method is provided, comprising:

[0006] In response to a data processing request received from the target transaction node, the system parses the transaction message from the data source to obtain the initial transaction data and its identifier. Based on the identifier, the system retrieves the target common parameters from the common parameter configuration information of the data processing platform. The initial transaction data is then processed using the target common parameters to obtain common transaction data, which represents transaction data used for processing common business transactions. Based on the identifier of the target transaction node and the identifier of the initial transaction data, the system retrieves the target difference parameters from the difference parameter configuration information of the data processing platform. These target difference parameters represent the differences between the parameters used by the target transaction node to process the initial transaction data and the target common parameters. The common transaction data is then processed using the target difference parameters to obtain the target transaction data, which is then sent to the target transaction node. This target transaction data represents transaction data used by the target transaction node to process specific business transactions.

[0007] According to embodiments of this disclosure, in response to receiving a transaction message from a data source, the initial transaction data and an identifier of the initial transaction data are obtained by parsing the transaction message, including:

[0008] By parsing the transaction message, the transaction name field, transaction type field, transaction period field, transaction target field, and initial transaction data are obtained. Based on a preset sorting strategy, an identifier for the initial transaction data is generated according to the transaction name field, transaction type field, transaction period field, and transaction target field.

[0009] According to embodiments of this disclosure, based on a preset sorting strategy, an identifier for initial transaction data is generated according to the transaction name field, transaction type field, transaction duration field, and transaction target field, including:

[0010] By querying the code identifier dictionary, we obtain the name identifier corresponding to the transaction name field, the type identifier corresponding to the transaction type field, the term identifier corresponding to the transaction term field, and the target identifier corresponding to the transaction target field. Based on a preset sorting strategy, we sort the name identifier, type identifier, term identifier, and target identifier to obtain the identifiers for the initial transaction data.

[0011] According to embodiments of this disclosure, the target common parameters include a first operational parameter and a first result processing parameter; the initial transaction data is processed using the target common parameters to obtain common transaction data, which includes:

[0012] Using a data processing platform, the content data is processed according to the first calculation parameters to obtain the first intermediate result data. The first intermediate result data is then processed according to the first result processing parameters to obtain public transaction data.

[0013] According to embodiments of this disclosure, the difference parameter configuration information is a two-dimensional parameter matrix with the identifier of the transaction processing node and the identifier of the initial transaction data as primary keys, and the difference parameters as key values; based on the identifier of the target transaction node and the identifier of the initial transaction data, the target difference parameters are retrieved from the difference parameter configuration information of the data processing platform, including:

[0014] The two-dimensional parameter matrix is ​​reduced in dimensionality to obtain three arrays: a first array, a second array, and a third array. The first array represents the offset of the first element in each row of the two-dimensional parameter matrix relative to all elements. The second array represents the column containing the element in the two-dimensional parameter matrix. The third array represents the element itself. Based on the row number of the target transaction node in the two-dimensional parameter matrix, the first and second row offsets are retrieved from the first array. The second row offset represents the next element adjacent to the first row offset in the first array. Based on the second and first row offsets, the number of parameters corresponding to the identifier of the initial transaction data is obtained. Based on the first row offset and the number of parameters, the column containing the target difference parameter is retrieved from the second array. Based on the column containing the target parameter, the target difference parameter is retrieved from the third array.

[0015] According to embodiments of this disclosure, the target difference parameter includes a second operational parameter and a second result processing parameter. The public transaction data is processed using the target difference parameter to obtain target transaction data, which corresponds to the target transaction node. This includes:

[0016] Using a data processing platform, the public transaction data is processed according to the second calculation parameters to obtain the second intermediate result data. The second intermediate result data is then processed according to the second result processing parameters to obtain the target transaction data.

[0017] According to embodiments of this disclosure, sending target transaction data to a target transaction node includes:

[0018] Based on the target transaction node, determine the target message queue in the distributed subscription system. Send the target transaction data to the target message queue so that the target transaction node can retrieve the target transaction data from the distributed subscription system.

[0019] According to embodiments of this disclosure, the method further includes: obtaining historical transaction data information from a data processing platform; retrieving historical transaction data corresponding to the target transaction data from the historical data information based on the identifier of the initial transaction data; and sending an alert to the target transaction node when the difference between the target transaction data and the historical transaction data meets a predetermined threshold.

[0020] According to embodiments of this disclosure, the method further includes: generating a data fluctuation chart based on the target transaction data and historical transaction data; and displaying the data fluctuation chart through a visualization interface.

[0021] Another aspect of this disclosure provides a data processing apparatus, comprising: a parsing module, a first query module, a first processing module, a second query module, and a second processing module. The parsing module is configured to, in response to receiving a data processing request from a target transaction node, parse a transaction message from a data source to obtain initial transaction data and an identifier for the initial transaction data. The first query module is configured to, based on the identifier of the initial transaction data, query target common parameters from the common parameter configuration information of the data processing platform. The first processing module is configured to, using the target common parameters, process the initial transaction data to obtain common transaction data, which represents transaction data used for processing common business. The second query module is configured to, based on the identifier of the target transaction node and the identifier of the initial transaction data, query target difference parameters from the difference parameter configuration information of the data processing platform, which represents the difference parameters between the parameters used by the target transaction node to process the initial transaction data and the target common parameters. The second processing module is configured to, using the target difference parameters, process the common transaction data to obtain target transaction data and send the target transaction data to the target transaction node, wherein the target transaction data represents transaction data used by the target transaction node to process specific business.

[0022] According to embodiments of this disclosure, the parsing module includes a parsing unit and a generation unit. The parsing unit is used to obtain a transaction name field, a transaction type field, a transaction duration field, a transaction target field, and initial transaction data by parsing the transaction message. The generation unit is used to generate an identifier for the initial transaction data based on a preset sorting strategy, according to the transaction name field, transaction type field, transaction duration field, and transaction target field.

[0023] According to embodiments of this disclosure, the generation unit includes a first obtaining subunit and a second obtaining subunit. The first obtaining subunit is used to obtain, by querying a code identifier dictionary, a name identifier corresponding to the transaction name field, a type identifier corresponding to the transaction type field, a term identifier corresponding to the transaction term field, and a target identifier corresponding to the transaction target field. The second obtaining subunit is used to sort the name identifier, type identifier, term identifier, and target identifier based on a preset sorting strategy to obtain identifiers for the initial transaction data.

[0024] According to embodiments of this disclosure, the target public parameters include first calculation parameters and first result processing parameters. The first processing module includes a first processing unit and a second processing unit. The first processing unit is used to process content data using a data processing platform according to the first calculation parameters to obtain first intermediate result data. The second processing unit is used to process the first intermediate result data according to the first result processing parameters to obtain public transaction data.

[0025] According to embodiments of this disclosure, the difference parameter configuration information is a two-dimensional parameter matrix with the identifier of the transaction processing node and the identifier of the initial transaction data as primary keys, and the difference parameters as key values. The second query module includes: a third processing unit, a first query unit, a second query unit, a first obtaining unit, and a third query unit. The third processing unit is used to perform dimensionality reduction processing on the two-dimensional parameter matrix to obtain a first array, a second array, and a third array. The first array represents the offset of the first element of each row in the two-dimensional parameter matrix relative to all elements; the second array represents the column where the element is located in the two-dimensional parameter matrix; and the third array represents the element in the two-dimensional parameter matrix. The first query unit is used to query the first row offset and the second row offset from the first array based on the row number of the target transaction node in the two-dimensional parameter matrix. The second row offset represents the next element in the first array adjacent to the first row offset. The first obtaining unit is used to obtain the number of parameters corresponding to the identifier of the initial transaction data based on the second row offset and the first row offset. The second query unit is used to query the column where the target difference parameter is located from the second array based on the first row offset and the number of parameters. The third query unit is used to retrieve the target difference parameter from the third array based on the column where the target parameter is located.

[0026] According to embodiments of this disclosure, the target difference parameter includes a second calculation parameter and a second result processing parameter. The second processing module includes a third processing unit and a fourth processing unit. The third processing unit is used to process the public transaction data using a data processing platform according to the second calculation parameter to obtain second intermediate result data. The fourth processing unit is used to process the second intermediate result data according to the second result processing parameter to obtain the target transaction data.

[0027] According to embodiments of this disclosure, the second processing unit includes a second determining unit and a sending unit. The second determining unit is configured to determine a target message queue in the distributed subscription system based on the target transaction node. The sending unit is configured to send target transaction data to the target message queue so that the target transaction node can obtain the target transaction data from the distributed subscription system.

[0028] According to embodiments of this disclosure, the data processing apparatus further includes: an acquisition module, a third query module, and a sending module. The acquisition module is used to acquire historical record information of transaction data from the data processing platform. The third query module is used to query historical transaction data corresponding to the target transaction data from the historical record information based on the identifier of the initial transaction data. The sending module is used to send a warning message to the target transaction node when the difference between the target transaction data and the historical transaction data meets a predetermined threshold.

[0029] According to embodiments of this disclosure, the data processing apparatus further includes a generation module and a display module. The generation module is used to generate a data fluctuation chart based on the target transaction data and historical transaction data. The display module is used to display the data fluctuation chart through a visual interface.

[0030] Another aspect of this disclosure provides an electronic device comprising: one or more processors; and a memory for storing one or more programs, wherein, when the one or more programs are executed by the one or more processors, the one or more processors perform the methods described above.

[0031] Another aspect of this disclosure provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, cause the processor to perform the methods described above.

[0032] Another aspect of this disclosure provides a computer program product including a computer program that, when executed by a processor, implements the methods described above.

[0033] According to the data processing method, apparatus, equipment, medium, and program products provided in this disclosure, initial transaction data and its identifier are obtained by parsing transaction messages from a data source. Then, the initial transaction data is processed using target common parameters in the common parameter configuration information of the data processing platform to obtain common transaction data suitable for processing common transactions. Next, the common transaction data is processed using target difference parameters corresponding to the target transaction node to obtain transaction data suitable for processing specific business operations at the target transaction node. Since the data trading platform is configured with common and difference parameters for different processing nodes, it can process transaction data from the data source to obtain transaction data applicable to specific business operations at different transaction nodes. Therefore, this at least partially solves the problem of resource waste caused by repeatedly deploying data processing systems at different transaction nodes in related technologies, achieving the technical effects of improving data processing efficiency and saving system resources. Attached Figure Description

[0034] The foregoing contents, as well as other objects, features, and advantages of this disclosure, will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0035] Figure 1 The illustrations depict application scenarios of data processing methods, apparatuses, devices, media, and program products according to embodiments of the present disclosure.

[0036] Figure 2 A flowchart illustrating a data processing method according to an embodiment of the present disclosure is shown schematically.

[0037] Figure 3A schematic diagram illustrating a three-dimensional matrix of difference parameters and a corresponding one-dimensional array thereof according to an embodiment of the present disclosure;

[0038] Figure 4 A schematic diagram of a message queue in a KAFKA message server according to an embodiment of the present disclosure is shown.

[0039] Figure 5 A schematic block diagram of a data processing apparatus according to embodiments of the present disclosure is shown; and

[0040] Figure 6 A block diagram schematically illustrates an electronic device suitable for implementing a data processing method according to an embodiment of the present disclosure. Detailed Implementation

[0041] The embodiments of the present disclosure will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the disclosure. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of the present disclosure for ease of explanation. However, it will be apparent that one or more embodiments may be practiced without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concepts of the present disclosure.

[0042] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0043] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0044] When using expressions such as "at least one of A, B, and C", they should generally be interpreted in accordance with the meaning that is commonly understood by a person skilled in the art (e.g., "a system having at least one of A, B, and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B, and C, etc.).

[0045] In the technical solutions disclosed herein, the collection, storage, use, processing, transmission, provision, disclosure, and application of data (including but not limited to user personal information) comply with the provisions of relevant laws and regulations, necessary confidentiality measures have been taken, and they do not violate public order and good morals.

[0046] Financial institutions typically obtain relatively simple initial transaction data from various data sources within financial trading centers, making it difficult to meet the diverse transaction needs of different regional business scenarios. For example, the initial transaction data from a data source might be the exchange rate for product A against the US dollar. However, region A typically trades product A against the euro. Therefore, it is necessary to process the initial transaction data to obtain transaction data applicable to the business scenarios of region A. For instance, converting the exchange rate for product A from the US dollar to the euro.

[0047] The traditional approach involves deploying data processing systems in various regions to process initial transaction data according to the specific needs of each region, resulting in transaction data applicable to local business scenarios. This method wastes computing resources by repeatedly deploying numerous computing systems and presents significant challenges in scaling up the distributed system architecture, leading to severe bottlenecks in the data processing process and making it difficult to improve the system's data processing capabilities through expansion.

[0048] In view of this, embodiments of the present disclosure provide a data processing method, comprising: responding to receiving a data processing request from a target transaction node, obtaining initial transaction data and an identifier of the initial transaction data by parsing a transaction message from a data source; querying target public parameters from public parameter configuration information of a data processing platform based on the identifier of the initial transaction data; processing the initial transaction data using the target public parameters to obtain public transaction data, wherein the public transaction data represents transaction data used for processing public services; querying target difference parameters from difference parameter configuration information of a data processing platform based on the identifier of the target transaction node and the identifier of the initial transaction data, wherein the target difference parameters represent the difference parameters between the parameters used by the target transaction node for processing the initial transaction data and the target public parameters; processing the public transaction data using the target difference parameters to obtain target transaction data, and sending the target transaction data to the target transaction node, wherein the target transaction data represents transaction data used by the target transaction node for processing specific services.

[0049] Figure 1 The illustration shows an application scenario diagram of a data processing method, apparatus, electronic device, storage medium, and program product according to embodiments of the present disclosure.

[0050] like Figure 1 As shown, the application scenario 100 according to this embodiment may include regional data processing nodes 101, a KAFKA message server 102, and a data processing platform 103. The data processing platform 103 may include: a public data processing node 103-1, regional data processing nodes 103-2, and parameter caching nodes 103-3.

[0051] The cached information in parameter cache node 103-3 may include: differential parameter configuration information, transaction data identifier mapping information, and common parameter configuration information.

[0052] The data processing platform 103 can obtain transaction messages 104 from the data source. It uses the public transaction data processing module to parse the transaction message 104 to obtain initial transaction data, and combines this with the transaction data identifier mapping information in the parameter cache node 103-3 to obtain the identifier of the initial transaction data. Then, using the public transaction data processing module, it queries the parameter cache node 103-3 to find the public parameters corresponding to the identifier of the initial transaction data, and obtains the public transaction data based on the public parameters and the initial transaction data.

[0053] The regional data processing node 103-2 can be configured with a regional data processing module to batch process initial transaction data according to different difference parameters, thereby obtaining regional transaction data that meets the business scenario requirements of different regions. The regional data processing module can convert the region-transaction ID difference parameter matrix into a corresponding one-dimensional array, and then combine it with public transaction data to obtain the transaction data for each region.

[0054] The KAFKA message server 102 can be configured with message queues corresponding to different regions. For example, message queue T1 corresponds to the data processing node in region A1. That is, the target transaction data obtained by the data processing platform is sent to the message queue corresponding to the data processing node in the target region, so that the data processing node in the target region can obtain the target transaction data from the message queue of the KAFKA message server 102 for processing the specific business of the data processing node in the target region.

[0055] The following will be based on Figure 1 The described scene, through Figures 2-6 The data processing method of the disclosed embodiments will be described in detail.

[0056] Figure 2 A flowchart illustrating a data processing method according to an embodiment of the present disclosure is shown schematically.

[0057] like Figure 2 As shown, the data processing method of this embodiment includes operations S210 to S250.

[0058] In operation S210, in response to receiving a data processing request from the target transaction node, the initial transaction data and its identifier are obtained by parsing the transaction message from the data source.

[0059] During operation S220, the target public parameters are retrieved from the public parameter configuration information of the data processing platform based on the identifier of the initial transaction data.

[0060] In operation S230, the initial transaction data is processed using the target common parameters to obtain common transaction data, which represents the transaction data used to process common business.

[0061] In operation S240, based on the identifier of the target transaction node and the identifier of the initial transaction data, the target difference parameter is retrieved from the difference parameter configuration information of the data processing platform. The target difference parameter represents the difference between the parameters used by the target transaction node to process the initial transaction data and the target common parameters.

[0062] In operation S250, the public transaction data is processed using the target difference parameter to obtain the target transaction data, and then the target transaction data is sent to the target transaction node. The target transaction data represents the transaction data used by the target transaction node to process specific business.

[0063] According to embodiments of this disclosure, the transaction message may include information about the traded product, information about the traded underlying asset, initial transaction data, etc. The initial transaction data may be transaction data where the traded product is represented by the traded underlying asset. For example, the transaction message may include the exchange rate of a certain precious metal to the US dollar, where the traded product information may be a certain precious metal, the traded underlying asset may be the US dollar, and the initial transaction data may be the exchange rate.

[0064] According to embodiments of this disclosure, the identifier for the initial transaction data can be generated using transaction product information, transaction target information, etc., from the transaction message. Alternatively, it can be directly obtained from the data source; that is, the transaction message may include a field that serves as a unique identifier for the initial transaction data within the data processing platform.

[0065] According to embodiments of this disclosure, the public parameter configuration information can be configured to store transaction data used for processing public transactions. For example, if the underlying asset of a product in region A is the same as that in other regions, then the initial transaction data for that product can be processed using public transaction parameters to obtain public transaction data. For example, the exchange rate of a product to underlying asset A obtained from the data source could be 6.181489. The public parameter can be the unit of the underlying asset; for example, if the unit of the underlying asset is 100, then the obtained public transaction data could be 618.1489.

[0066] Since different regions use different parameters for the same initial transaction data, the target difference parameters can be retrieved from the difference parameter configuration information based on the identifiers of the target transaction node and the initial transaction node. These target difference parameters are then used to process the common transaction data to obtain the target transaction data.

[0067] According to embodiments of this disclosure, the target difference parameter can be "target unit: 10", indicating that the difference parameter between the target difference parameter and the public transaction parameter can be 10. That is, the public transaction data "618.1489" can be processed using the difference parameter "10" to obtain 6181.489.

[0068] According to embodiments of this disclosure, a message server can be used to send target transaction data to a target transaction processing node so that the target transaction node can use it to process specific business.

[0069] According to embodiments of this disclosure, the data processing method, apparatus, device, medium, and program product provided herein obtains initial transaction data and its identifier by parsing transaction messages from a data source. Then, the initial transaction data is processed using target common parameters in the common parameter configuration information of the data processing platform to obtain common transaction data suitable for processing common transactions. Furthermore, the common transaction data is processed using target difference parameters corresponding to the target transaction node to obtain transaction data suitable for processing specific business operations of the target transaction node. Since the data trading platform is configured with common and difference parameters for different processing nodes, it can process transaction data from the data source to obtain transaction data applicable to specific business operations of different transaction nodes. Therefore, this at least partially solves the problem of resource waste caused by repeatedly deploying data processing systems at different transaction nodes in related technologies, achieving the technical effects of improving data processing efficiency and saving system resources.

[0070] Since the formats of web page messages received from different data sources may be different, in order to facilitate the data trading platform to query the difference parameters of different target trading nodes, the field information in the transaction message can be used to generate fields that can be used to uniquely identify the initial transaction data according to the preset rules of the data trading platform.

[0071] According to embodiments of this disclosure, in response to receiving a transaction message from a data source, obtaining initial transaction data and an identifier of the initial transaction data by parsing the transaction message may include the following operations:

[0072] By parsing the transaction message, the transaction name field, transaction type field, transaction period field, transaction target field, and initial transaction data are obtained. Based on a preset sorting strategy, an identifier for the initial transaction data is generated according to the transaction name field, transaction type field, transaction period field, and transaction target field.

[0073] According to embodiments of this disclosure, the transaction name field can represent the name information of the transaction product, such as: foreign exchange product, precious metal product, agricultural product, base metal product, etc. The transaction type field can represent the settlement type information of the transaction product, such as: transaction settlement, maturity settlement, average settlement, share adjustment closing settlement, share adjustment opening settlement, maturity rollover settlement, etc. The transaction period field can represent the duration of the period, such as: 7 days, 15 days, 30 days, 6 months, etc. The transaction underlying asset field can represent the underlying asset used to pay for the transaction product, such as: US dollar, euro, Japanese yen, etc. Initial transaction data can represent the exchange rate of the transaction product to the underlying asset.

[0074] According to embodiments of this disclosure, when the transaction name field, transaction type field, transaction period field, and transaction target field are all numeric fields, the identifier of the initial transaction data can be directly generated from the initial transaction data.

[0075] However, in practical applications, the aforementioned fields can include both numeric and textual fields. Different data sources may also use different methods to identify the same product. Therefore, the code-based identifier fields of a data trading platform can be used to transform these fields into identifier fields for the initial transaction data based on unified rules.

[0076] According to embodiments of this disclosure, generating an identifier for initial transaction data based on a preset sorting strategy, according to the transaction name field, transaction type field, transaction duration field, and transaction target field, may include the following operations: obtaining a name identifier corresponding to the transaction name field, a type identifier corresponding to the transaction type field, a duration identifier corresponding to the transaction duration field, and a target identifier corresponding to the transaction target field by querying a code identifier dictionary; and sorting the name identifier, type identifier, duration identifier, and target identifier according to the preset sorting strategy to obtain the identifier for the initial transaction data.

[0077] For example, the name identifier for the trading product "Precious Metals Product" could be "003", the type identifier for the trading type "Maturity Settlement" could be "002", the term identifier for the trading period "30 days" could be "003", and the identifier for the underlying asset "Japanese Yen" could be "027". The preset sorting strategy could be to arrange the data in the order of trading name, type, term, and underlying asset, and the identifier for the initial trading data could be "003002003027".

[0078] According to embodiments of this disclosure, by parsing transaction messages, a unique identifier for initial transaction data is generated according to the preset rules of the data processing platform, so as to facilitate the batch processing of difference parameters between the initial transaction data and the difference parameters of different regions, thereby improving the efficiency of data processing.

[0079] According to embodiments of this disclosure, initial transaction data is processed using target common parameters to obtain common transaction data. Obtaining common transaction data may include the following operations:

[0080] Using a data processing platform, the content data is processed according to the first calculation parameters to obtain the first intermediate result data. The first intermediate result data is then processed according to the first result processing parameters to obtain public transaction data.

[0081] According to embodiments of this disclosure, the target common parameter includes a first calculation parameter and a first result processing parameter. The first calculation parameter can characterize the calculation processing parameters performed on the initial transaction data. For example, the first calculation parameter can be a target unit of 0.01, the initial transaction data can be "312.45", then the first intermediate result data can be 3.1245.

[0082] According to embodiments of this disclosure, the first result processing parameter can characterize parameters for processing the first intermediate result data. For example, the first result processing parameter can be "rounded to two decimal places", then the public transaction data can be "3.12".

[0083] According to embodiments of this disclosure, the target public parameter can also be a combination of multiple public parameters with different attributes, such as: target unit + base index + target method + exchange rate rounded to decimal places, and assembled into regular expression text. For example, "%UnitPrice100%KeepAfDot2". By parsing the regular expression, the parameter combination information is obtained, and then a combination calculation is performed.

[0084] According to embodiments of this disclosure, by setting common parameter configuration information, the initial transaction data of the data source can be processed centrally to obtain common transaction data for the same business scenario for different transaction processing nodes in different regions, thereby effectively reducing the deployment of redundant computing resources for the same business scenario by different transaction processing nodes and saving computing resources.

[0085] Figure 3 A schematic diagram of a three-dimensional matrix and one-dimensional data of difference parameters according to an embodiment of the present disclosure is shown.

[0086] like Figure 3As shown, in the two-dimensional matrix of difference parameters, the element corresponding to ID2 and region 1 being "1" indicates that there is no difference between the common parameters used to process the initial transaction data identified as ID2 and the parameters used by region 1 to process the same initial transaction data. The element corresponding to ID1 and region 2 being "Difference Parameter Text 1" indicates that there is a difference between the common parameters used to process the initial transaction data identified as ID1 and the parameters used by region 2 to process the same initial transaction data. Difference Parameter Text 1 can be the regular expression text of a specific difference parameter. When processing the initial transaction data, the difference parameter text can first be parsed using a regular expression to obtain the difference parameters, and then the difference parameters can be used to process the initial transaction data to obtain the target transaction data.

[0087] According to embodiments of this disclosure, retrieving target difference parameters from the difference parameter configuration information of the data processing platform based on the identifier of the target transaction node and the identifier of the initial transaction data may include the following operations:

[0088] The two-dimensional parameter matrix is ​​reduced in dimensionality to obtain three arrays: a first array, a second array, and a third array. The first array represents the offset of the first element in each row of the two-dimensional parameter matrix relative to all elements. The second array represents the column containing the element in the two-dimensional parameter matrix. The third array represents the element itself. Based on the row number of the target transaction node in the two-dimensional parameter matrix, the first and second row offsets are retrieved from the first array. The second row offset represents the next element adjacent to the first row offset in the first array. Based on the second and first row offsets, the number of parameters corresponding to the identifier of the initial transaction data is obtained. Based on the first row offset and the number of parameters, the column containing the target difference parameter is retrieved from the second array. Based on the column containing the target parameter, the target difference parameter is retrieved from the third array.

[0089] According to embodiments of this disclosure, the first array may be a row offset array, representing the offset of the first element of each row in the two-dimensional parameter matrix relative to all elements. For example... Figure 3 As shown, in the row corresponding to region 1, there is only 1 element, so the difference between the 2nd element and the 1st element in the first array is "1". In the row corresponding to region 2, there are 2 elements, so the difference between the 3rd element and the 2nd element in the first array is "2". And so on, which will not be elaborated here.

[0090] For example, the region identifier for region 9 can be "01705". By querying the 10th element "16" in the first array and the 9th element "13", we can get that the region 9 row includes 3 elements, namely the 14th to the 16th elements.

[0091] According to embodiments of this disclosure, the second array may be a row-based array, representing the column where an element is located in the two-dimensional parameter matrix, and the third array represents the elements in the two-dimensional parameter matrix. For example... Figure 3 As shown, in the row corresponding to region 1, the element "1" is located in the 2nd column. Therefore, in the second array, the first element is "2". In the row corresponding to region 2, the element "Difference Parameter Text 1" is located in the 1st column, and the element "1" is located in the 3rd column. Therefore, in the second array, the second element is "1" and the third element is "3".

[0092] For example, the region identifier for region 9 could be "01705". By querying the 14th to 16th elements in the second array based on the query results of the first array, we can obtain the elements of the region 9 row located in columns 1, 2, and 4 respectively.

[0093] According to embodiments of this disclosure, the third array may be an array of elements, representing the elements in a two-dimensional parameter matrix. For example... Figure 3 As shown, based on the query results of the second array, the elements at the corresponding positions are "1", "difference parameter text 3", and "1".

[0094] According to embodiments of this disclosure, by performing dimensionality reduction processing on the three-dimensional matrix of difference parameters, three one-dimensional arrays are obtained, which can reduce matrix sparsity and improve data query efficiency.

[0095] According to embodiments of this disclosure, processing public transaction data using target difference parameters to obtain target transaction data, and obtaining target transaction data corresponding to the target transaction node, may include the following operations:

[0096] Using a data processing platform, the public transaction data is processed according to the second calculation parameters to obtain the second intermediate result data. The second intermediate result data is then processed according to the second result processing parameters to obtain the target transaction data.

[0097] According to the embodiments of this disclosure, the second operation parameter has the same definition range as the first operation parameter, and the second result processing parameter has the same definition range as the first result processing parameter, which will not be elaborated here.

[0098] For example, if the public transaction data is 5.1632, the second operation parameter can be "target unit 10", and the second result processing parameter can be "round to 2 decimal places", then the target transaction data obtained can be 51.63.

[0099] According to embodiments of this disclosure, the target difference parameter can also be a combination of multiple difference parameters including different attributes, such as: target unit + base index + target method + exchange rate rounded to decimal places, and assembled into regular expression text. For example, "%UnitPrice100%KeepAfDot2". By parsing the regular expression, the parameter combination information is obtained, and then a combination calculation is performed.

[0100] According to embodiments of this disclosure, sending target transaction data to a target transaction node may include the following operations:

[0101] Based on the target transaction node, determine the target message queue in the distributed subscription system. Send the target transaction data to the target message queue so that the target transaction node can retrieve the target transaction data from the distributed subscription system.

[0102] Figure 4 A schematic diagram of a KAFKA message server according to an embodiment of the present disclosure is shown.

[0103] like Figure 4 As shown, the KAFKA message server 400 in this embodiment may include message queues corresponding to multiple regions, such as message queue A1 corresponding to region 1, message queue A2 corresponding to region 2, message queue A9 corresponding to region 9, ..., message queue An corresponding to region n.

[0104] For example, message queue A9 corresponding to region 9 can include multiple target transaction data that have already been processed by the data processing platform: ID1: 5.1632, ID2: 323.58, ID3: 11.5654, etc. This allows the transaction processing nodes in region 9 to pull target transaction data from the KAFKA message server that can be directly used to process local specific business.

[0105] According to embodiments of this disclosure, message queues can be used to send the target transaction data processed by the data processing platform to the target transaction node in an orderly manner, so as to ensure that the target transaction processing node can receive the data processed in real time in a timely manner and reduce the problem of data reception disorder caused by differences in network transmission.

[0106] According to embodiments of this disclosure, the above method further includes:

[0107] Historical transaction data information is retrieved from the data processing platform. Based on the identifier of the initial transaction data, the historical transaction data corresponding to the target transaction data is retrieved from the historical data. If the difference between the target transaction data and the historical transaction data meets a predetermined threshold, an alert is sent to the target transaction node.

[0108] According to embodiments of this disclosure, historical record information may include target transaction data of a target transaction node processed by the data transaction processing platform within a historical period. The difference between the current target transaction data and the historical target transaction data can be obtained. When the difference between the transaction data meets a predetermined threshold, it indicates that the current data is abnormal. A warning message can be sent to the target transaction node to remind it to use the current target transaction data to process transactions with caution, thereby reducing the impact of abnormal data from the data source on business processing.

[0109] According to embodiments of this disclosure, the method further includes: generating a data fluctuation chart based on the target transaction data and historical transaction data; and displaying the data fluctuation chart through a visualization interface.

[0110] According to embodiments of this disclosure, a data fluctuation graph can more intuitively display the data fluctuation situation, so as to remind relevant personnel to handle abnormal data in a timely manner.

[0111] Based on the above data processing method, this disclosure also provides a data processing apparatus. The following will be combined with... Figure 5 The device is described in detail.

[0112] Figure 5 A schematic block diagram of a data processing apparatus according to an embodiment of the present disclosure is shown.

[0113] like Figure 5 As shown, the data processing device 500 in this embodiment includes a parsing module 510, a first query module 520, a first processing module 530, a second query module 540, and a second processing module 550.

[0114] The parsing module 510 is used to respond to a data processing request received from the target transaction node by parsing the transaction message from the data source to obtain the initial transaction data and its identifier. In one embodiment, the parsing module 510 can be used to perform the operation S210 described above, which will not be repeated here.

[0115] The first query module 520 is used to query the target public parameter from the public parameter configuration information of the data processing platform based on the identifier of the initial transaction data. In one embodiment, the first query module 520 can be used to perform the operation S220 described above, which will not be repeated here.

[0116] The first processing module 530 is used to process the initial transaction data using target common parameters to obtain common transaction data, which represents transaction data used for processing common business. In one embodiment, the first processing module 530 can be used to perform the operation S230 described above, which will not be repeated here.

[0117] The second query module 540 is used to query the target difference parameters from the difference parameter configuration information of the data processing platform based on the identifier of the target transaction node and the identifier of the initial transaction data. The target difference parameters represent the difference parameters between the parameters used by the target transaction node to process the initial transaction data and the target common parameters. The second query module 540 can be used to execute the operation S240 described above, which will not be repeated here.

[0118] The second processing module 550 is used to process the public transaction data using the target difference parameter to obtain the target transaction data, and then send the target transaction data to the target transaction node. The target transaction data represents the transaction data used by the target transaction node to process specific business transactions. The second processing module 550 can be used to execute the operation S250 described above, which will not be repeated here.

[0119] According to embodiments of this disclosure, the parsing module includes a parsing unit and a generation unit. The parsing unit is used to obtain a transaction name field, a transaction type field, a transaction duration field, a transaction target field, and initial transaction data by parsing the transaction message. The generation unit is used to generate an identifier for the initial transaction data based on a preset sorting strategy, according to the transaction name field, transaction type field, transaction duration field, and transaction target field.

[0120] According to embodiments of this disclosure, the generation unit includes a first obtaining subunit and a second obtaining subunit. The first obtaining subunit is used to obtain, by querying a code identifier dictionary, a name identifier corresponding to the transaction name field, a type identifier corresponding to the transaction type field, a term identifier corresponding to the transaction term field, and a target identifier corresponding to the transaction target field. The second obtaining subunit is used to sort the name identifier, type identifier, term identifier, and target identifier based on a preset sorting strategy to obtain identifiers for the initial transaction data.

[0121] According to embodiments of this disclosure, the target public parameters include first calculation parameters and first result processing parameters. The first processing module includes a first processing unit and a second processing unit. The first processing unit is used to process content data using a data processing platform according to the first calculation parameters to obtain first intermediate result data. The second processing unit is used to process the first intermediate result data according to the first result processing parameters to obtain public transaction data.

[0122] According to embodiments of this disclosure, the difference parameter configuration information is a two-dimensional parameter matrix with the identifier of the transaction processing node and the identifier of the initial transaction data as primary keys, and the difference parameters as key values. The second query module includes: a third processing unit, a first query unit, a second query unit, a first obtaining unit, and a third query unit. The third processing unit is used to perform dimensionality reduction processing on the two-dimensional parameter matrix to obtain a first array, a second array, and a third array. The first array represents the offset of the first element of each row in the two-dimensional parameter matrix relative to all elements; the second array represents the column where the element is located in the two-dimensional parameter matrix; and the third array represents the element in the two-dimensional parameter matrix. The first query unit is used to query the first row offset and the second row offset from the first array based on the row number of the target transaction node in the two-dimensional parameter matrix. The second row offset represents the next element in the first array adjacent to the first row offset. The first obtaining unit is used to obtain the number of parameters corresponding to the identifier of the initial transaction data based on the second row offset and the first row offset. The second query unit is used to query the column where the target difference parameter is located from the second array based on the first row offset and the number of parameters. The third query unit is used to retrieve the target difference parameter from the third array based on the column where the target parameter is located.

[0123] According to embodiments of this disclosure, the target difference parameter includes a second calculation parameter and a second result processing parameter. The second processing module includes a third processing unit and a fourth processing unit. The third processing unit is used to process the public transaction data using a data processing platform according to the second calculation parameter to obtain second intermediate result data. The fourth processing unit is used to process the second intermediate result data according to the second result processing parameter to obtain the target transaction data.

[0124] According to embodiments of this disclosure, the second processing unit includes a second determining unit and a sending unit. The second determining unit is configured to determine a target message queue in the distributed subscription system based on the target transaction node. The sending unit is configured to send target transaction data to the target message queue so that the target transaction node can obtain the target transaction data from the distributed subscription system.

[0125] According to embodiments of this disclosure, the data processing apparatus further includes: an acquisition module, a third query module, and a sending module. The acquisition module is used to acquire historical record information of transaction data from the data processing platform. The third query module is used to query historical transaction data corresponding to the target transaction data from the historical record information based on the identifier of the initial transaction data. The sending module is used to send a warning message to the target transaction node when the difference between the target transaction data and the historical transaction data meets a predetermined threshold.

[0126] According to embodiments of this disclosure, the data processing apparatus further includes a generation module and a display module. The generation module is used to generate a data fluctuation chart based on the target transaction data and historical transaction data. The display module is used to display the data fluctuation chart through a visual interface.

[0127] According to embodiments of this disclosure, any plurality of modules among the parsing module 510, the first query module 520, the first processing module 530, the second query module 540, and the second processing module 550 can be combined into one module, or any one of these modules can be split into multiple modules. Alternatively, at least part of the functionality of one or more of these modules can be combined with at least part of the functionality of other modules and implemented in one module. According to embodiments of this disclosure, at least one of the parsing module 510, the first query module 520, the first processing module 530, the second query module 540, and the second processing module 550 can be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or implemented in hardware or firmware by any other reasonable means of integrating or packaging the circuitry, or implemented in any one of the three implementation methods of software, hardware, and firmware, or in a suitable combination of any of these. Alternatively, at least one of the parsing module 510, the first query module 520, the first processing module 530, the second query module 540, and the second processing module 550 may be implemented at least partially as a computer program module, which can perform corresponding functions when the computer program module is run.

[0128] Figure 6 A block diagram schematically illustrates an electronic device suitable for implementing a data processing method according to an embodiment of the present disclosure.

[0129] like Figure 6 As shown, an electronic device 600 according to an embodiment of this disclosure includes a processor 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage portion 608 into a random access memory (RAM) 603. The processor 601 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 601 may also include onboard memory for caching purposes. The processor 601 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of this disclosure.

[0130] RAM 603 stores various programs and data required for the operation of electronic device 600. Processor 601, ROM 602, and RAM 603 are interconnected via bus 604. Processor 601 performs various operations of the method flow according to embodiments of the present disclosure by executing programs in ROM 602 and / or RAM 603. It should be noted that the programs may also be stored in one or more memories other than ROM 602 and RAM 603. Processor 601 may also perform various operations of the method flow according to embodiments of the present disclosure by executing programs stored in said one or more memories.

[0131] According to embodiments of this disclosure, the electronic device 600 may further include an input / output (I / O) interface 605, which is also connected to a bus 604. The electronic device 600 may also include one or more of the following components connected to the I / O interface 605: an input section 606 including a keyboard, mouse, etc.; an output section 607 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 608 including a hard disk, etc.; and a communication section 609 including a network interface card such as a LAN card, modem, etc. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the I / O interface 605 as needed. A removable medium 611, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 610 as needed so that computer programs read from it can be installed into the storage section 608 as needed.

[0132] This disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs that, when executed, implement the method according to the embodiments of this disclosure.

[0133] According to embodiments of this disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, such as including, but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, according to embodiments of this disclosure, the computer-readable storage medium may include ROM 602 and / or RAM 603 and / or one or more memories other than ROM 602 and RAM 603 described above.

[0134] Embodiments of this disclosure also include a computer program product comprising a computer program containing program code for performing the methods shown in the flowchart. When the computer program product is run on a computer system, the program code is used to cause the computer system to implement the item recommendation method provided in the embodiments of this disclosure.

[0135] When the computer program is executed by the processor 601, it performs the functions defined in the system / apparatus of this disclosure embodiments. According to embodiments of this disclosure, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0136] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and downloaded and installed via the communication section 609, and / or installed from the removable medium 611. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0137] In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 609, and / or installed from the removable medium 611. When the computer program is executed by the processor 601, it performs the functions defined in the system of this disclosure embodiment. According to embodiments of this disclosure, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0138] According to embodiments of this disclosure, program code for executing the computer programs provided in embodiments of this disclosure can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C", or similar programming languages. The program code can execute entirely on the user's computing device, partially on the user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0139] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0140] Those skilled in the art will understand that the features described in the various embodiments and / or claims of this disclosure can be combined or combined in various ways, even if such combinations or combinations are not explicitly described in this disclosure. In particular, the features described in the various embodiments and / or claims of this disclosure can be combined or combined in various ways without departing from the spirit and teachings of this disclosure. All such combinations and / or combinations fall within the scope of this disclosure.

[0141] The embodiments of this disclosure have been described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of this disclosure. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. The scope of this disclosure is defined by the appended claims and their equivalents. Various substitutions and modifications can be made by those skilled in the art without departing from the scope of this disclosure, and all such substitutions and modifications should fall within the scope of this disclosure.

Claims

1. A data processing method, comprising: In response to receiving a data processing request from the target transaction node, the initial transaction data and the identifier of the initial transaction data are obtained by parsing the transaction message from the data source; Based on the identifier of the initial transaction data, the target public parameter is retrieved from the public parameter configuration information of the data processing platform; The initial transaction data is processed using the target common parameters to obtain common transaction data, which represents transaction data used to process common business. Based on the identifier of the target transaction node and the identifier of the initial transaction data, the target difference parameter is retrieved from the difference parameter configuration information of the data processing platform. The target difference parameter represents the difference between the parameter used by the target transaction node to process the initial transaction data and the target common parameter. The public transaction data is processed using the target difference parameter to obtain target transaction data, and the target transaction data is sent to the target transaction node, wherein the target transaction data represents the transaction data used by the target transaction node to process specific business. The target common parameters include a first calculation parameter and a first result processing parameter; the process of using the target common parameters to process the initial transaction data to obtain common transaction data includes: Using the data processing platform, the initial transaction data is processed according to the first calculation parameters to obtain the first intermediate result data; Based on the first result processing parameters, the first intermediate result data is processed to obtain the public transaction data.

2. The method according to claim 1, wherein, The response to receiving a data processing request from the target transaction node, by parsing the transaction message from the data source, includes: By parsing the transaction message, the transaction name field, transaction type field, transaction period field, transaction target field, and the initial transaction data are obtained; Based on a preset sorting strategy, the identifier of the initial transaction data is generated according to the transaction name field, the transaction type field, the transaction period field, and the transaction target field.

3. The method according to claim 2, wherein, The step of generating an identifier for the initial transaction data based on a preset sorting strategy, according to the transaction name field, the transaction type field, the transaction duration field, and the transaction target field, includes: By querying the code identifier dictionary, we can obtain the name identifier corresponding to the transaction name field, the type identifier corresponding to the transaction type field, the term identifier corresponding to the transaction term field, and the target identifier corresponding to the transaction target field. Based on a preset sorting strategy, the name identifier, the type identifier, the term identifier, and the target identifier are sorted to obtain the identifier of the initial transaction data.

4. The method according to claim 1, wherein, The difference parameter configuration information is a two-dimensional parameter matrix with the identifier of the transaction processing node and the identifier of the initial transaction data as primary keys, and the difference parameters as key values; the step of querying the target difference parameter from the difference parameter configuration information of the data processing platform based on the identifier of the target transaction node and the identifier of the initial transaction data includes: The two-dimensional parameter matrix is ​​reduced in dimension to obtain a first array, a second array, and a third array. The first array represents the offset of the first element of each row in the two-dimensional parameter matrix relative to all elements. The second array represents the column in the two-dimensional parameter matrix where the element is located. The third array represents the element in the two-dimensional parameter matrix. Based on the row number of the target transaction node in the two-dimensional parameter matrix, the first row offset and the second row offset are retrieved from the first array, where the second row offset represents the next element adjacent to the first row offset in the first array; Based on the offset of the second row and the offset of the first row, the number of parameters corresponding to the identifier of the initial transaction data is obtained; Based on the first row offset and the number of parameters, the column containing the target difference parameter is retrieved from the second array; The target difference parameter is retrieved from the third array based on the column containing the target difference parameter.

5. The method according to claim 1, wherein the target difference parameter includes a second calculation parameter and a second result processing parameter, and the step of processing the public transaction data using the target difference parameter to obtain target transaction data, and obtaining target transaction data corresponding to the target transaction node, includes: Using the data processing platform, the public transaction data is processed according to the second calculation parameters to obtain second intermediate result data; The second intermediate result data is processed according to the second result processing parameters to obtain the target transaction data.

6. The method according to claim 1, wherein, The target transaction data is sent to the target transaction node; Based on the target transaction node, determine the target message queue in the distributed subscription system; The target transaction data is sent to the target message queue so that the target transaction node can obtain the target transaction data from the distributed subscription system.

7. The method according to claim 1, further comprising: Obtain historical transaction data information from the data processing platform; Based on the identifier of the initial transaction data, historical transaction data corresponding to the target transaction data is retrieved from the historical record information; If the difference between the target transaction data and the historical transaction data meets a predetermined threshold, an early warning message is sent to the target transaction node.

8. The method according to claim 7, further comprising: A data fluctuation chart is generated based on the target transaction data and the historical transaction data; The data fluctuation chart is displayed through a visual interface.

9. A data processing apparatus, comprising: The parsing module is used to respond to a data processing request received from the target transaction node by parsing the transaction message from the data source to obtain the initial transaction data and the identifier of the initial transaction data; The first query module is used to query the target public parameter from the public parameter configuration information of the data processing platform based on the identifier of the initial transaction data. The first processing module is used to process the initial transaction data using the target public parameters to obtain public transaction data, wherein the public transaction data represents transaction data used for processing public business. The second query module is used to query the target difference parameter from the difference parameter configuration information of the data processing platform based on the identifier of the target transaction node and the identifier of the initial transaction data. The target difference parameter represents the difference parameter between the parameter used by the target transaction node to process the initial transaction data and the target common parameter. as well as The second processing module is used to process the public transaction data using the target difference parameter to obtain target transaction data, and send the target transaction data to the target transaction node, wherein the target transaction data represents the transaction data used by the target transaction node to process specific business. The target common parameters include a first calculation parameter and a first result processing parameter; the first processing module is used for: Using the data processing platform, the initial transaction data is processed according to the first calculation parameters to obtain the first intermediate result data; Based on the first result processing parameters, the first intermediate result data is processed to obtain the public transaction data.

10. An electronic device, comprising: One or more processors; Storage device for storing one or more programs. Wherein, when the one or more programs are executed by the one or more processors, the one or more processors perform the method according to any one of claims 1 to 8.

11. A computer-readable storage medium having stored thereon executable instructions that, when executed by a processor, cause the processor to perform the method according to any one of claims 1 to 8.

12. A computer program product comprising a computer program that, when executed by a processor, implements the method according to any one of claims 1 to 8.

Images