Service platform data interaction processing method and system

Abstract

The invention provides a data interaction processing method and system in a service, and belongs to the technical field of data processing, and the method specifically comprises the steps: determining the correlation coefficients of different specific service types and correlation service types according to the historical use data of correlation power data corresponding to different specific service types, historical calling data of different specific service types are obtained, and when it is determined that the service influence coefficient of data interaction delay existing in the associated service type meets the requirement in combination with the association coefficients of the different specific service types and the associated service type, historical use data of the target power data are processed by using the associated service type; and in combination with the historical call data of the associated service type and the service influence coefficient, determining a data interaction processing strategy of the associated service type during the call processing of the target power data, thereby improving the processing reliability of different service types in the service platform.

Description

Technical Field

[0001] The present invention belongs to the field of data processing technology, and in particular relates to a method and system for data interaction processing in a business middleware. Background Art

[0002] To implement data interaction processing in the power grid resource business middle platform and improve the data reliability of the business middle platform, the invention patent application CN202011227556.6, "A method for verifying incremental data based on a data middle platform," compares the verification results with the number of source table records and the number of full table records in the middle platform's source layer. This ensures that the parsed daily incremental data is authentic and valid. However, this presents the following technical issues: In the business platform, in order to meet the needs of different types of power business, it is often necessary to combine different types of power data for interactive processing. This makes how to combine the needs of interactive processing of different types of power data and generate differentiated interactive processing strategies a technical problem that needs to be solved urgently.

[0003] In response to the above technical problems, the present invention provides a method and system for data interaction processing in a business middle platform. Summary of the Invention

[0004] To achieve the purpose of the present invention, the present invention adopts the following technical solutions: In order to solve the above technical problems, the present invention provides the following technical solutions to achieve the purpose of the present invention: According to one aspect of the present invention, a method for processing data interaction between a business platform and a service platform is provided.

[0005] A method for processing data interaction between a business platform and a service platform, specifically comprising: S1 proceeds to the next step when it is determined that the target power data needs to be optimized for data interaction based on the call delay data of the associated business type of the target power data; S2 determines the associated power data corresponding to different associated business types, determines the business type that has a data call relationship with the associated power data, and uses it as the specific business type, and determines the correlation coefficient between the different specific business types and the associated business types based on the historical usage data of the associated power data corresponding to the different specific business types; S3 obtains historical call data of different specific business types, and combines the correlation coefficients of different specific business types with related business types to determine that the business impact coefficient of the data interaction delay of the related business type meets the requirements, and then proceeds to the next step; S4 utilizes the historical usage data of the target power data by the associated business type, and combines the historical call data and business impact coefficient of the associated business type to determine the data interaction processing strategy of the associated business type when performing call processing on the target power data.

[0006] The beneficial effects of the present invention are: Based on the call delay data of the associated business types of the target power data, it is determined whether the target power data needs to be optimized for data interaction, thereby achieving an accurate assessment of the delay of data interaction of the target power data from the call delay of the associated business types of the target power data, thereby avoiding the technical problem of insufficient reliability of the use of the target power data due to large processing delays, and laying the foundation for improving the operational reliability of the associated business types.

[0007] Based on the historical usage data of the associated business type on the target power data, the historical call data of the associated business type and the business impact coefficient, the data interaction processing strategy of the associated business type when calling and processing the target power data is determined, thereby achieving accurate evaluation of the data interaction strategy of the target power data from multiple angles. Not only the call and use frequency of the associated business type are taken into account, but also the impact of the associated business type on other business types once there is a processing delay, thereby achieving differentiated interaction processing of the associated business type.

[0008] A further technical solution is that the associated business type of the target power data is determined according to the business type of the call of the target power data in the business platform.

[0009] A further technical solution is that the call delay data includes the number of call delays and the delay lengths of different call delay numbers.

[0010] A further technical solution is to determine that the target power data requires optimized data interaction processing, specifically including: Determine the associated business type with call delay based on the call delay data of the associated business type of the target power data, and use it as the call delay business type; The total number of call delays of the call delay business type is determined according to the number of call delays of the call delay business type, and whether the target power data needs to be optimized for data interaction is determined based on the total number of call delays.

[0011] A further technical solution is that, when the total number of call delays does not meet the requirement, it is determined that the target power data needs to be optimized for data interaction.

[0012] A further technical solution is that the call processing demand coefficient of the associated service type is determined according to an average value of a usage frequency coefficient, a call frequency coefficient and a service impact coefficient of the associated service type.

[0013] A further technical solution is to determine a data interaction processing strategy for the call processing of the target power data based on the call processing demand coefficient, specifically including: Determining a preset interaction processing strategy corresponding to the call processing demand coefficient based on the call processing demand coefficient; A data interaction processing strategy for calling and processing the target power data is determined according to the preset interaction processing strategy.

[0014] A further technical solution is that the data interaction processing strategy includes real-time processing and processing according to a preset time period.

[0015] In a second aspect, the present invention provides a computer system comprising: a memory and a processor in communication connection, and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the above-mentioned method for data interaction processing between business platforms when running the computer program.

[0016] Other features and advantages will be described in the following description, and in part will become apparent from the description, or understood by practicing the invention. The purpose and other advantages of the invention are realized and obtained by the structures particularly pointed out in the description and the drawings.

[0017] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the accompanying drawings.

[0019] Figure 1 It is a flow chart of a data interaction processing method for a business middle platform; Figure 2 is a flow chart of a method for determining a correlation coefficient between a specific business type and an associated business type; Figure 3 It is a flow chart to determine whether the service impact coefficient of data interaction delay of the associated service type meets the requirements; Figure 4 The present invention is a flowchart of a method for determining a data interaction processing strategy when an associated business type performs call processing on target power data. DETAILED DESCRIPTION

[0020] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be embodied in many forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete and will fully convey the concepts of the example embodiments to those skilled in the art. Like reference numerals in the figures represent like or similar structures, and thus their detailed description will be omitted.

[0021] The terms "a", "an", "the", and "said" are used to indicate the presence of one or more elements / components / etc.; the terms "including" and "having" are used to express an open-ended inclusive meaning and mean that additional elements / components / etc. may be present in addition to the listed elements / components / etc.

[0022] Example 1 To solve the above problems, according to one aspect of the present invention, Figure 1 According to one aspect of the present invention, a method for processing data interaction between a business platform and a service platform is provided, specifically comprising: S1 proceeds to the next step when it is determined that the target power data needs to be optimized for data interaction based on the call delay data of the associated business type of the target power data; S2 determines the associated power data corresponding to different associated business types, determines the business type that has a data call relationship with the associated power data, and uses it as the specific business type, and determines the correlation coefficient between the different specific business types and the associated business types based on the historical usage data of the associated power data corresponding to the different specific business types; S3 obtains historical call data of different specific business types, and combines the correlation coefficients of different specific business types with related business types to determine that the business impact coefficient of the data interaction delay of the related business type meets the requirements, and then proceeds to the next step; S4 utilizes the historical usage data of the target power data by the associated business type, and combines the historical call data and business impact coefficient of the associated business type to determine the data interaction processing strategy of the associated business type when performing call processing on the target power data.

[0023] Furthermore, the associated business type of the target power data is determined according to the business type of the target power data in the business platform.

[0024] It should be noted that the call delay data includes the number of call delays and the delay durations of different call delay numbers.

[0025] It is understandable that determining the target power data requires optimizing the data interaction, specifically including: Determine the associated business type with call delay based on the call delay data of the associated business type of the target power data, and use it as the call delay business type; The total number of call delays of the call delay business type is determined according to the number of call delays of the call delay business type, and whether the target power data needs to be optimized for data interaction is determined based on the total number of call delays.

[0026] Furthermore, when the total number of call delays does not meet the requirement, it is determined that the target power data needs to be optimized for data interaction.

[0027] It should also be noted that determining the target power data requires data interaction optimization processing, specifically including: Determine the associated business type with call delay based on the call delay data of the associated business type of the target power data, and use it as the call delay business type; The screening service type in the calling delay service type is determined according to the number of calling delay times of the calling delay service type, and whether the target power data needs to be optimized for data interaction is determined based on the number of the screening service types.

[0028] It can be understood that the screening service type is a call delay service type in which the number of call delay times is greater than the preset delay number.

[0029] Optionally, determining that the target power data requires data interaction optimization processing specifically includes: S11 determines the associated business type with call delay based on the call delay data of the associated business type of the target power data, and uses it as the call delay business type; Optionally, the above step S11 includes the following contents: Scenario 1: Based on the call delay data of the associated business type of the target power data, when it is determined that the target power data does not have an associated business type with call delay, it is determined that the target power data does not need to be optimized for data interaction; Scenario 2: When the target power data has an associated business type with a call delay, the associated business type with a call delay will be used as a call delay business type. When the number of call delay business types is greater than the preset delay type number, it is determined that the target power data requires optimized data interaction processing.

[0030] S12 determines a call delay coefficient of the call delay service type according to the number of call delay times of the call delay service type and different call delay times; Optionally, the above step S12 includes the following contents, specifically: Scenario 1: Determine the total number of call delays for each call delay service type based on the number of call delays. When the total number of call delays is greater than a preset number of delays, determine that the target power data requires optimized data interaction processing. Case 2: When the total number of call delays is not greater than the preset number of delays, a call delay coefficient of the call delay service type is determined based on the number of call delays of the call delay service type and different call delay numbers. When the average of the call delay coefficients of different call delay service types is greater than a preset coefficient threshold, the number of call delay service types is obtained. When the number of call delay service types is within a preset number range, it is determined that the target power data requires optimized data interaction processing. Scenario 3: When the number of the call delay business types is not within the preset number range, the call delay business type with a call delay coefficient greater than the preset delay coefficient will be used as the screening delay type. When the number of the screening delay types is greater than the preset delay type number, it is determined that the target power data requires optimized processing of data interaction.

[0031] S13 determines the delay processing coefficient of the target power data based on the call delay coefficient of the call delay service type, and determines whether the target power data needs to be optimized for data interaction based on the delay processing coefficient.

[0032] Furthermore, the associated power data is determined based on the power data called by the associated business type.

[0033] It should be noted that if Figure 2 As shown, the method for determining the correlation coefficient between the specific service type and the associated service type is: Determine, using historical usage data of associated power data corresponding to the specific business type, associated power data that overlaps with the associated business type, and use the associated power data as the overlapping power data; The correlation coefficient between the specific business type and the associated business type is determined according to the amount of overlapping power data.

[0034] It can be understood that the correlation coefficient is determined according to the ratio of the number of the overlapping power data to the number of associated power data of the associated business type.

[0035] It should also be noted that the correlation coefficient between the specific business type and the associated business type ranges from 0 to 1, wherein the larger the correlation coefficient between the specific business type and the associated business type, the higher the degree of correlation between the specific business type and the associated business type.

[0036] Furthermore, the historical call data of the specific business type is determined based on the analysis results of the operation log of the business middle station.

[0037] Specifically, such as Figure 3 As shown, determining that the service impact coefficient of the data interaction delay of the associated service type meets the requirements specifically includes: Determine the historical call times of the specific service type using the historical call data of the specific service type, and determine the weight coefficient of the specific service type based on the historical call times; Determining a modified correlation coefficient of the specific service type based on the weight coefficient of the specific service type and a correlation coefficient between the specific service type and the associated service type; The business impact coefficient of the associated business type is determined according to the modified association coefficient of different specific business types, and combined with the preset impact coefficient threshold, it is determined whether the business impact coefficient of the associated business type with data interaction delay meets the requirements.

[0038] Furthermore, the weight coefficient of the specific service type is determined according to the product of the number of historical calls and a preset proportional factor.

[0039] It can be understood that the modified correlation coefficient of the specific service type is determined according to the product of the weight coefficient of the specific service type and the correlation coefficient between the specific service type and the associated service type.

[0040] Specifically, such as Figure 4 As shown, the method for determining the data interaction processing strategy of the associated business type when performing the call processing of the target power data is: Determining a historical usage count of the target power data by the associated service type based on historical usage data of the target power data, and determining a usage frequency coefficient of the associated service type based on the historical usage count; Determining a historical call count of the associated service type based on historical call data of the associated service type, and determining a call frequency coefficient of the associated service type according to the historical call count; The call processing demand coefficient of the associated business type is determined according to the usage frequency coefficient, call frequency coefficient and business impact coefficient of the associated business type, and the data interaction processing strategy during the call processing of the target power data is determined based on the call processing demand coefficient.

[0041] Furthermore, the call processing demand coefficient of the associated service type is determined according to an average value of a usage frequency coefficient, a call frequency coefficient, and a service impact coefficient of the associated service type.

[0042] It can be understood that the data interaction processing strategy for determining the call processing of the target power data based on the call processing demand coefficient specifically includes: Determining a preset interaction processing strategy corresponding to the call processing demand coefficient based on the call processing demand coefficient; A data interaction processing strategy for calling and processing the target power data is determined according to the preset interaction processing strategy.

[0043] A further technical solution is that the data interaction processing strategy includes real-time processing and processing according to a preset time period.

[0044] Example 2 In a second aspect, the present invention provides a computer system comprising: a memory and a processor in communication connection, and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the above-mentioned method for data interaction processing between business platforms when running the computer program.

[0045] The various embodiments in this specification are described in a progressive manner. Similar portions between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from the other embodiments. In particular, the device, apparatus, and non-volatile computer storage medium embodiments are generally similar to the method embodiments, so their descriptions are relatively simplified. For relevant details, refer to the descriptions of the method embodiments.

[0046] The foregoing description of this specification describes specific embodiments. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in an order different from that described in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order shown or the sequential order to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0047] The foregoing description is merely one or more embodiments of this specification and is not intended to limit this specification. It will be apparent to those skilled in the art that various modifications and variations may be made to one or more embodiments of this specification. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of one or more embodiments of this specification are intended to be within the scope of the claims of this specification.

Claims

1. A method for processing data interaction between a business platform and a service platform, characterized in that: Specifically include: When it is determined based on the call delay data of the associated business type of the target power data that the target power data needs to be optimized for data interaction, proceed to the next step; Determine the associated power data corresponding to different associated business types, determine the business types that have a data call relationship with the associated power data, and use them as specific business types, and determine the correlation coefficients between different specific business types and associated business types based on the historical usage data of the associated power data corresponding to different specific business types; Obtain historical call data of different specific business types, and combine the correlation coefficients of different specific business types with related business types to determine if the business impact coefficient of the data interaction delay of the related business type meets the requirements, and then proceed to the next step; The historical usage data of the target power data by the associated business type is used, and combined with the historical call data and business impact coefficient of the associated business type, a data interaction processing strategy of the associated business type when performing call processing on the target power data is determined.

2. The business middle-station data interaction processing method according to claim 1, characterized in that: The associated business type of the target power data is determined according to the business type of the target power data in the business platform.

3. The data interaction processing method for a business platform according to claim 1, characterized in that: The call delay data includes the number of call delays and the delay durations of different call delay numbers.

4. The business middle-station data interaction processing method according to claim 1, characterized in that: Determining that the target power data requires data interaction optimization processing specifically includes: Determine the associated business type with call delay based on the call delay data of the associated business type of the target power data, and use it as the call delay business type; The total number of call delays of the call delay business type is determined according to the number of call delays of the call delay business type, and whether the target power data needs to be optimized for data interaction is determined based on the total number of call delays.

5. The business middle-station data interaction processing method according to claim 4 is characterized in that: When the total number of call delays does not meet the requirement, it is determined that the target power data needs to be optimized for data interaction.

6. The business middle-station data interaction processing method according to claim 1, characterized in that: The associated power data is determined according to the power data called by the associated business type.

7. The business middle-station data interaction processing method according to claim 1, characterized in that: The method for determining the correlation coefficient between the specific service type and the associated service type is: Determine, using historical usage data of associated power data corresponding to the specific business type, associated power data that overlaps with the associated business type, and use the associated power data as the overlapping power data; The correlation coefficient between the specific business type and the associated business type is determined according to the amount of overlapping power data.

8. The data interaction processing method for a business platform according to claim 7, characterized in that: The correlation coefficient is determined according to a ratio of the number of the coincident power data to the number of associated power data of the associated business type.

9. The business middle-station data interaction processing method according to claim 1, characterized in that: The data interaction processing strategy includes real-time processing and processing according to a preset time period.

10. A computer system comprising: A memory and a processor in communication connection, and a computer program stored in the memory and capable of running on the processor, characterized in that when the processor runs the computer program, it executes a business middle-station data interaction processing method as described in any one of claims 1-9.

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