Data processing method and device, equipment and medium

Abstract

The embodiment of the invention discloses a data processing method and device, equipment and a medium, and the method comprises the steps: determining at least one to-be-used decision algorithm corresponding to a business request, further determining a target service corresponding to the at least one to-be-used decision algorithm, and transmitting the business request comprising a decision algorithm identifier to the target service, sending a decision algorithm identifier to the target service to call a corresponding target dependency item based on the decision algorithm identifier, and determining a feedback result based on the target dependency item and service information carried in the service request; and integrating the feedback results to obtain a target feedback result. According to the technical scheme provided by the embodiment of the invention, the problems of high network energy consumption, low decision-making efficiency and incapability of effectively multiplexing the data caused by centralized processing of all the obtained dependent data by the decision-making system are solved, the data transmission is reduced, the occupation of network resources is reduced, the multiplexing rate of the data is improved, and the user experience is improved. The technical effects of reducing the data processing pressure of the decision-making system and improving the decision-making efficiency are achieved.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of computer technology, and in particular, to a data processing method, apparatus, device, and medium. Background Art

[0002] With the development of computer technology, the requirements for decision-making services are getting higher and higher, and more and more complex decision-making algorithms are used. When making decisions using decision-making algorithms, a large amount of data needs to be obtained to participate in the algorithm decision-making calculation to obtain the decision result. The existing decision-making method is usually: when a decision request is received, all the decision-making algorithms required for decision-making are queried, and then the dependent data is queried and obtained from each data source storing the data on which the decision-making algorithm depends. After all the dependent data is obtained, the decision-making calculation is performed based on the dependent data according to the decision-making algorithm.

[0003] When the inventors implemented the present technical solution based on the above method, they found the following problems:

[0004] This method of obtaining dependent data from each data source and then making decisions based on all the dependent data in the decision-making system requires the data to be transmitted from each data source to the decision-making system for storage, and the amount of data transmitted by each data source is different, resulting in large network losses and long decision-making times. At the same time, this method of centrally processing dependent data in the decision-making system not only has high requirements for the various system performances of the decision-making system, but also has the problem of low decision-making efficiency, and the dependent data stored in the decision-making system is also difficult to reuse. Summary of the Invention

[0005] The present invention provides a data processing method, apparatus, device, and medium to reduce data transmission, reduce the occupation of network resources, improve the data reuse rate, and achieve the technical effects of reducing the data processing pressure of the decision-making system and improving the decision-making efficiency.

[0006] In a first aspect, an embodiment of the present invention provides a data processing method, which includes:

[0007] When a service request is received, determine at least one decision-making algorithm to be used corresponding to the service request;

[0008] Determine a target service corresponding to the at least one decision-making algorithm to be used, and send a service request including the decision-making algorithm identifier to the target service, so that the target service retrieves the corresponding target dependency item based on the decision-making algorithm identifier, and determines a feedback result based on the target dependency item and the service information carried in the service request;

[0009] Receive the feedback results fed back by each target service, and integrate and process the feedback results to obtain the target feedback results corresponding to the service request.

[0010] Further, the method further includes:

[0011] Configure corresponding decision algorithms to be compiled for a plurality of preset business scenarios respectively; wherein, the decision algorithms to be compiled are configured based on decisions, scripts, and rules;

[0012] Compile and process the decision algorithms to be compiled to obtain a plurality of decision algorithms;

[0013] Establish a first mapping relationship between the decision algorithms and at least one dependency to be selected, and a second mapping relationship between the decision algorithms and the service to be selected to which the at least one dependency to be selected belongs, so as to determine the target service and the target dependency in the target service based on the first mapping relationship and the second mapping relationship.

[0014] Further, the method further includes:

[0015] Store corresponding dependency data in the dependencies to be selected;

[0016] Determine the decision algorithm to be selected corresponding to the dependency to be selected, and locally store the decision algorithm to be selected, so that when a service request is received, the corresponding target dependency and target decision algorithm are retrieved based on the decision algorithm identifier.

[0017] Further, the method further includes:

[0018] Based on the second mapping relationship, determine the target service corresponding to the at least one decision algorithm to be used, and route the service request including the decision algorithm identifier to the corresponding target service;

[0019] Correspondingly, the step of enabling the target service to retrieve the corresponding target dependency based on the decision algorithm identifier includes:

[0020] Retrieve the corresponding target dependency from the target service based on the first mapping relationship and the decision algorithm identifier.

[0021] Further, the method further includes:

[0022] Obtain the dependency data in the target dependency;

[0023] Process the service information carried in the service request based on the locally stored decision algorithm and the dependency data to determine the feedback result.

[0024] Further, the method further includes:

[0025] Asynchronously receive the feedback results fed back by each target service;

[0026] Process the feedback results based on the preset merging rules stored in the result merger to obtain the target feedback result.

[0027] In a second aspect, an embodiment of the present invention further provides a data processing apparatus, which includes:

[0028] A decision algorithm determination module, configured to determine at least one decision algorithm to be used corresponding to the service request when receiving the service request;

[0029] A target service determination module, configured to determine the target service corresponding to the at least one decision algorithm to be used, and send the service request including the decision algorithm identifier to the target service, so that the target service retrieves the corresponding target dependencies based on the decision algorithm identifier, and determines the feedback result based on the target dependencies and the service information carried in the service request;

[0030] A target feedback result determination module, configured to receive the feedback results fed back by each target service, and integrally process the feedback results to obtain the target feedback result corresponding to the service request.

[0031] In a third aspect, an embodiment of the present invention further provides an electronic device, which includes:

[0032] One or more processors;

[0033] A storage device, configured to store one or more programs,

[0034] When the one or more programs are executed by the one or more processors, the one or more processors implement the data processing method according to any one of the embodiments of the present invention.

[0035] In a fourth aspect, an embodiment of the present invention further provides a storage medium containing computer-executable instructions, and the computer-executable instructions are used to execute the data processing method according to any one of the embodiments of the present invention when executed by a computer processor.

[0036] In the technical solution of the embodiment of the present invention, when a service request is received, at least one decision algorithm to be used corresponding to the service request is determined, and then a target service corresponding to the at least one decision algorithm to be used is determined. The service request including the decision algorithm identifier is sent to the target service, so that the target service retrieves the corresponding target dependencies based on the decision algorithm identifier, and determines a feedback result based on the target dependencies and the service information carried in the service request; the feedback results are integrated and processed to obtain a target feedback result corresponding to the service request. The technical solution of the embodiment of the present invention solves the technical problems in the prior art that dependent data is obtained from each data terminal and then all the dependent data is centrally processed in the decision-making system, resulting in high requirements for system performance, high network energy consumption, low decision-making efficiency, and ineffective data reuse. It realizes determining each decision algorithm to be used required under the service request when the service request is received, and then determining the target services corresponding to each decision algorithm to be used, and allocating the service request including the decision algorithm identifier to each target service, so that each target service makes decision processing locally through the target dependencies corresponding to the decision algorithm identifier and the service information in the service request, avoiding intermediate data transmission, reducing the occupation of network resources while improving the utilization rate of the system resources of each target service, thereby reducing the decision-making calculation pressure of the decision-making system. By integrating the feedback results of the decisions of each target service, the final target feedback result is obtained, achieving the technical effect of improving the decision-making efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the introduced drawings are only the drawings of a part of the embodiments to be described by the present invention, rather than all the drawings. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0038] Figure 1 It is a schematic flowchart of a data processing method provided by an embodiment of the present invention;

[0039] Figure 2 It is a schematic flowchart of a data processing method provided by an embodiment of the present invention;

[0040] Figure 3 It is a schematic flowchart of a data processing method provided by an embodiment of the present invention;

[0041] Figure 4 It is a schematic structural diagram of a decision-making system provided by an embodiment of the present invention;

[0042] Figure 5 It is a schematic structural diagram of a data processing device provided by an embodiment of the present invention;

[0043] Figure 6 The structural schematic diagram of an electronic device provided by an embodiment of the present invention. Specific implementation manners

[0044] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It can be understood that the specific embodiments described herein are only used to explain the present invention, rather than limiting the present invention. In addition, it should be noted that, for the sake of convenience of description, only the parts related to the present invention are shown in the drawings, rather than all the structures.

[0045] Before introducing the technical solution, the application scenario can be described first. Exemplarily, the technical solution provided by the embodiment of the present invention can be applied to any scenario that requires decision-making. For example, for a decision request in an e-commerce risk control scenario, during the process of processing the decision request, there is a need to determine the decision algorithm required for e-commerce risk control decision-making and the data on which the algorithm depends. For example, the dependent data can be transaction data, browsing data, traffic data, account data, etc. It is necessary to make a decision based on the decision algorithm and the dependent data to obtain a decision result. When making a decision based on the decision request, the technical solution provided by this embodiment can be implemented.

[0046] Figure 1 The flowchart of a data processing method provided by an embodiment of the present invention. This embodiment is applicable to the situation of making a decision. The method can be executed by a data processing device, and the device can be implemented in the form of software and / or hardware. The hardware can be an electronic device, such as a mobile terminal, a PC or a server, etc.

[0047] As Figure 1 shown, the method includes:

[0048] S110. When receiving a service request, determine at least one decision algorithm to be used corresponding to the service request.

[0049] Among them, the service request can be a program or code that needs to make a service decision and is used to request a decision. For example, the service request can be a request for risk decision-making, a request for authorization decision-making, a request for credit rating decision-making, or a request for recommendation decision-making. The decision algorithm to be used can be a pre-developed algorithm program for decision-making, such as a set of serialized executable decision-making algorithm expressions.

[0050] In this embodiment, after the decision-making system receives a service request, it is necessary to determine the decision result for the service request. At this time, the decision-making algorithm to be used for processing the service request can be queried to determine the service terminal for decision-making calculation based on the decision-making algorithm to be used. Optionally, information reflecting the request scenario can be determined through the service request, and then the decision-making algorithm to be used for processing the service request can be determined based on this information. For example, information such as the service type and decision type can be used to reflect the request scenario. Decision requests in different service scenarios correspond to different decision-making algorithms. For example, the decision-making algorithms corresponding to credit services include Algorithm A, Algorithm B, and Algorithm C, and the decision-making algorithms corresponding to e-commerce services include Algorithm D, Algorithm E, and Algorithm F; or, the decision-making algorithms corresponding to authorization decisions include Algorithm A, Algorithm D, and Algorithm H, and the decision-making algorithms corresponding to rating decisions include Algorithm D, Algorithm R, and Algorithm S; or, the corresponding decision-making algorithm to be used can be comprehensively determined based on various information reflecting the request scenario.

[0051] S120. Determine the target service corresponding to at least one decision-making algorithm to be used, and send the service request including the decision-making algorithm identifier to the target service, so that the target service retrieves the corresponding target dependencies based on the decision-making algorithm identifier, and determines the feedback result based on the target dependencies and the service information carried in the service request.

[0052] Among them, the target service can be an application program. One service can contain one or more different applications, and one service can correspond to one terminal. For example, it can be a client / server application program, a Web server, a database server, and other server-based application programs. The decision-making algorithm identifier can be used to uniquely identify the decision-making algorithm, and different decision-making algorithms can correspond to different algorithm identifiers. The target dependency can refer to the storage location of the data on which the decision depends. For example, if a decision depends on a piece of data, the location where the data is stored is the target dependency, and the target dependency can be located under the corresponding service.

[0053] Specifically, the storage location of the data relied on for the decision can be determined through the decision-making algorithm to be used, the target dependencies can be determined, and then the service where the target dependencies are located can be used as the target service corresponding to this decision-making algorithm to be used. Alternatively, a mapping relationship between the decision algorithm identifier and the target dependencies and the target service can be pre-constructed, and the target service and the target dependencies corresponding to the decision-making algorithm to be used can be determined through the mapping relationship. Further, the decision algorithm identifier can be requested as a parameter into the target service. The target service can call the target dependencies relied on by the decision algorithm that matches the identifier according to the decision algorithm identifier, and parse the service information carried in the service request. Then, the pre-loaded algorithm execution component can be used to run the decision algorithm to process the data and service information in the target dependencies, and the obtained decision result is the feedback result. The decision algorithm can be pre-loaded in the target service or sent by the decision system.

[0054] It should be noted that the data required for the decision may be stored in various different dependencies. Different dependencies may be in the same target service or in different target services. When making a decision, each different target service needs to perform decision operations based on the corresponding data in its own corresponding dependencies. Based on this, the technology of concurrent requests can be adopted to send all service requests containing the decision algorithm identifier to their respective corresponding target services. In this way, after receiving their respective decision algorithm identifiers, different target services can directly perform parallel operations locally based on the decision algorithms corresponding to the identifiers, improving the CPU utilization rate of each service while reducing the CPU calculation pressure of the decision system and improving the operation efficiency.

[0055] S130. Receive the feedback results fed back by each target service, and perform integrated processing on the feedback results to obtain the target feedback result corresponding to the service request.

[0056] In practical applications, after determining the feedback results, each target service can feed back the feedback results to the decision system. In this way, after receiving the feedback results fed back by each target service, the decision system can perform integrated processing on all the received feedback results. For example, the feedback results can be weighted and averaged to obtain the target feedback result, or all the feedback results can be summarized as the target feedback result. The target feedback result is the result after making a decision based on the service request. The technical solution provided in this embodiment first allows each target service to make a decision on the feedback result respectively, and then the decision system receives the feedback results fed back by each target service to finally determine the target feedback result. It does not require the decision system to obtain the algorithm dependencies from each data end, reducing data transmission while also reducing the occupation of network resources, reducing decision-making time, and avoiding the decision system from performing centralized processing on all data, reducing the decision operation pressure of the decision system and improving the decision-making efficiency.

[0057] In this embodiment, the feedback results fed back by each target service are received, and the feedback results are integrated and processed to obtain a target feedback result corresponding to the service request, including: asynchronously receiving the feedback results fed back by each target service; processing the feedback results based on the preset merging rules stored in the result merger to obtain the target feedback result.

[0058] Among them, the result merger can be a component for merging results. The preset merging rules can be pre-configured. Optionally, the preset merging rules can be various merging rules based on decision priorities, ascending order, descending order, randomness, etc.

[0059] In practical applications, the technology of asynchronously receiving feedback results can be adopted to asynchronously receive the feedback results fed back by each target service. Further, the result merger can be called to use the preset merging rules stored in the result merger to integrate and process the feedback results to obtain the final target feedback result. For example, the result merger can merge the feedback results into a sorted list based on the decision priority (the number of feedback results can also be pre-configured). The advantage of this setting is that: by asynchronously receiving the feedback results, the system does not need to wait for the results and can continue to process other tasks, improving the system processing performance. At the same time, by integrating the feedback results fed back by each target service through the result merger, not only the integration efficiency is improved, but also the accuracy of determining the target feedback result is improved.

[0060] The technical solution of the embodiment of the present invention, when receiving a service request, determines at least one decision algorithm to be used corresponding to the service request, and then determines the target service corresponding to the at least one decision algorithm to be used, and sends the service request including the decision algorithm identifier to the target service, so that the target service retrieves the corresponding target dependencies based on the decision algorithm identifier, and determines the feedback result based on the target dependencies and the service information carried in the service request; integrates and processes the feedback result to obtain the target feedback result corresponding to the service request. The technical solution of the embodiment of the present invention solves the technical problems in the prior art that dependent data is obtained from each data end and then centrally processed in the decision-making system, resulting in high requirements for system performance, high network energy consumption, low decision-making efficiency, and ineffective data reuse. It realizes that when a service request is received, the decision algorithms to be used required under the service request are determined, and then the target services corresponding to the decision algorithms to be used are determined, and the service request including the decision algorithm identifier is assigned to each target service, so that each target service makes a decision and processes locally through the target dependencies corresponding to the decision algorithm identifier and the service information in the service request, avoiding intermediate data transmission, reducing the occupation of network resources while improving the utilization rate of the system resources of each target service, thereby reducing the decision-making calculation pressure on the decision-making system. By integrating the feedback results of the decisions of each target service, the final target feedback result is obtained, achieving the technical effect of improving the decision-making efficiency.

[0061] Figure 2 It is a schematic diagram of a data processing method provided by an embodiment of the present invention. On the basis of the foregoing embodiment, corresponding decision algorithms can be pre-configured for multiple service scenarios respectively, so as to process corresponding service requests through the configured decision algorithms. The specific implementation manner can refer to the technical solution of this embodiment. Among them, the same or corresponding technical terms as those in the above embodiment will not be described in detail here.

[0062] As Figure 2 shown, the method specifically includes the following steps:

[0063] S210. Configure corresponding decision algorithms to be compiled for multiple preset service scenarios respectively.

[0064] Among them, the decision algorithm to be compiled can be custom-configured and is associated with the service scenario. It should be noted that in different industry fields, different service scenarios may be included. For example, in the retail industry, service scenarios may include product shelving, inventory management, order processing, etc.; in the e-commerce industry, service scenarios may include product operation, traffic monitoring, risk assessment, payment settlement, etc.; in the logistics industry, service scenarios may include task collection, task transportation, etc. This embodiment does not limit the specific service scenarios.

[0065] In this embodiment, different decisions, scripts, rules, etc. can be configured according to different business scenarios, and then a decision algorithm to be compiled for processing decisions in different business scenarios can be configured based on the decisions, scripts, and rules.

[0066] S220. Compile and process the decision algorithm to be compiled to obtain multiple decision algorithms.

[0067] In this embodiment, an algorithm compiler can be pre-loaded, and the decision algorithm to be compiled can be compiled and processed based on the algorithm compiler, and the decision algorithms to be compiled that need to be executed in each business scenario are compiled into individual decision algorithms. Correspondingly, multiple decision algorithms are obtained.

[0068] S230. Establish a first mapping relationship between the decision algorithm and at least one selectable dependency, and a second mapping relationship between the decision algorithm and the selectable service to which at least one selectable dependency belongs, so as to determine the target service and the target dependency in the target service based on the first mapping relationship and the second mapping relationship.

[0069] In this embodiment, after multiple decision algorithms are compiled, a mapping relationship between each decision algorithm and the dependency it depends on can be established based on the mapping technology as the first mapping relationship. A mapping relationship between each decision algorithm and the selectable service to which the dependency it depends on belongs is established as the second mapping relationship. The decision algorithm in the mapping relationship can be represented by an algorithm identifier, so that when a decision is needed, the target dependency corresponding to the decision algorithm identifier, the target service corresponding to the decision algorithm identifier, and the target dependency in the target service can be queried by querying the mapping relationship.

[0070] Exemplarily, assuming that when making an enterprise credit risk decision, decision algorithm A is required, and decision algorithm A needs to use the data in dependency 1 and dependency 2, the first mapping relationship can be A-1, A-2. If dependency 1 is located in service a, the second mapping relationship can be A-1-a.

[0071] In order to enable the target service to accurately query the data relied on by the decision algorithm and ensure the accuracy of the decision, corresponding dependency data can also be stored in the selectable dependencies; determine the selectable decision algorithm corresponding to the selectable dependency, so as to locally store the selectable decision algorithm, so that when a business request is received, the corresponding target dependency and target decision algorithm can be retrieved based on the decision algorithm identifier.

[0072] Among them, the dependency data can refer to the specific data relied on during decision-making, and can be used as input data to be input into the decision algorithm for processing.

[0073] In this embodiment, the dependency data relied on during decision-making can be stored in the corresponding dependency items to be selected and pre-loaded into the memory of the dependency items to be selected in advance. For example, assume that when making an enterprise credit risk decision, data such as enterprise industrial and commercial data, judicial data, tax data, rewards and punishments information, credit data, transaction data, operation data, and transaction data are required. Each piece of data can be regarded as dependency data, and each piece of dependency data is stored in the corresponding dependency item. The dependency item is located in the target service, so the dependency data can be saved in the target service through the dependency item. It is also possible to pre-determine the decision-making algorithms to be selected corresponding to each dependency item to be selected through the first mapping relationship, and store the decision-making algorithms to be selected in the memory of the dependency items to be selected for local storage for use when the target service makes a decision. Alternatively, it can also be that before the target service uses a certain decision-making algorithm for the first time to make a decision, the decision-making system sends the decision-making algorithm and the service request including the identifier of the decision-making algorithm to the target service, so that the target service locally stores the decision-making algorithm. When receiving a service request next time, the corresponding target decision-making algorithm locally stored and the dependency data stored in the target dependency item can be directly retrieved based on the decision-making algorithm identifier, and the decision-making operation can be directly performed locally, effectively avoiding the transmission of decision-making dependency data in the network and improving the decision-making performance. At the same time, by storing the dependency data in the memory of the dependency item, these dependency data can be reused when the target service receives a service request, improving the data reuse rate.

[0074] The technical solution of the embodiment of the present invention realizes the custom configuration of decision-making and meets the business decision-making requirements by pre-configuring the corresponding decision-making algorithms to be compiled for multiple business scenarios respectively and then compiling and processing the decision-making algorithms to be compiled to obtain multiple decision-making algorithms. Further, by establishing the first mapping relationship between the decision-making algorithm and at least one dependency item to be selected, and the second mapping relationship between the decision-making algorithm and the target service to which at least one dependency item to be selected belongs, it is possible to determine the target service corresponding to the decision-making algorithm to be used based on the second mapping relationship, which is convenient for subsequent decision-making allocation. It can also enable the target service to determine the target dependency item located in the target service based on the first mapping relationship, which is convenient for the target service to perform decision-making processing, thereby improving the decision-making efficiency.

[0075] Figure 3 On the basis of the foregoing embodiment, the flowchart of a data processing method provided by the embodiment of the present invention further refines S120, and the specific implementation manner can refer to the technical solution of this embodiment. Among them, the same or corresponding technical terms as those in the above embodiment will not be described in detail here.

[0076] As Figure 3 shown, the method includes:

[0077] S310. When receiving a service request, determine at least one decision algorithm to be used corresponding to the service request.

[0078] S320. Based on the second mapping relationship, determine the target services corresponding to at least one decision algorithm to be used, and route the service request including the decision algorithm identifier to the corresponding target services.

[0079] Specifically, through the second mapping relationship, the to-be-selected services mapped to each decision algorithm to be used can be respectively found as the target services. Further, the router analyzes the network between the system and the target services, and determines which one or several target services to use to execute the decision algorithm according to the routing result, and then routes the service request including the decision algorithm identifier to the corresponding target services to ensure network security and ensure that the data is processed normally.

[0080] It should be noted that in this embodiment, due to the preloading technology, decision algorithms, decision dependencies, and dependent data are preloaded in the target services in advance. In this way, the decision-making system does not need to send the complete decision algorithm, but only needs to provide the reference identifier of the decision algorithm, thereby reducing the database that needs to be transmitted in the request, saving network consumption time, and not needing to transmit dependent data, thereby improving the execution efficiency of the decision algorithm and improving the processing performance.

[0081] S330. The target service retrieves the corresponding target dependencies from the target service based on the first mapping relationship and the decision algorithm identifier.

[0082] In this embodiment, the target service can retrieve the to-be-selected dependencies mapped to the decision algorithm identifier from the local of the target service through the first mapping relationship as the target dependencies.

[0083] S340. Obtain the dependent data in the target dependencies.

[0084] In this embodiment, the target service can directly obtain the dependent data pre-stored in the memory of the target dependencies from the local, so that the target service executes the decision algorithm based on the dependent data, thereby avoiding the problem of low decision-making efficiency caused by a large amount of dependent data being transmitted to the decision-making system and then the decision-making system running the algorithm to obtain the decision result, realizing the reduction of network loss caused by data movement, and achieving the technical effects of improving the response speed and data processing efficiency.

[0085] S350. Process the service information carried in the service request based on the locally stored decision algorithm and dependent data, and determine the feedback result.

[0086] Specifically, each decision algorithm identifier can be sent to the target service to which the corresponding target dependency belongs. The distributed target service processes the service information carried in the service request based on the decision algorithm and dependency data stored locally, and obtains the algorithm operation result, which is the feedback result.

[0087] S360. Receive the feedback results fed back by each target service, and integrally process the feedback results to obtain the target feedback result corresponding to the service request.

[0088] The technical solution of the embodiment of the present invention determines the target service corresponding to at least one decision algorithm to be used according to the second mapping relationship, and then routes the service request including the decision algorithm identifier to the corresponding target service, realizing the allocation of decision tasks. The target service can, based on the first mapping relationship and the decision algorithm identifier, retrieve the corresponding target dependency from the local service and obtain the dependency data in the target dependency, avoiding data transmission, reducing the network transmission pressure. At the same time, each target service processes the service information carried in the service request based on the decision algorithm and dependency data stored locally, realizing distributed decision processing, improving the decision processing efficiency and reducing the decision pressure on the decision system.

[0089] As an optional embodiment of the above embodiment, Figure 4 It is a structural schematic diagram of a decision system provided according to the embodiment of the present invention. Specifically, the following specific content can be referred to.

[0090] As Figure 4As shown in the figure, the technical solution provided by the embodiment of the present invention can be implemented by a decision-making system, which may be composed of an algorithm dependency router, an algorithm compiler, a result combiner, decision-making algorithms - policies, decision-making algorithms - scripts, decision-making algorithms - rules, decision-making algorithm execution components, etc. Among them, decisions, scripts, and rules together constitute decision-making algorithms. The decision execution component refers to a component that can execute decision-making algorithms. The algorithm compiler can be used to compile the decisions required to be executed in each business scenario into individual decision-making algorithms. The algorithm dependency router is used to determine which target service to use to execute the algorithm based on the compiled decision-making algorithm. The result combiner is used to combine the decision results of each decision-making algorithm into the final decision result (i.e., the target feedback result) in the order of priority. Specifically, when a business request reaches the decision-making system, the decisions, scripts, rules, etc. configured for the corresponding scenario of the business request will first be compiled into decision-making algorithms according to the dependent data items, and the mapping relationships between each dependent item and the decision-making algorithm will be compiled. Then, a thread pool is started to process the mapping relationships between each dependent item and the decision-making algorithm; each decision-making algorithm is sent to the target service to which the corresponding dependent item belongs, and the distributed target service obtains the decision result, that is, the feedback result, according to the decision-making algorithm. Finally, the result combiner is used to summarize the feedback results calculated by the distributed target services and combine them according to the decision-making priority to obtain the final target feedback result.

[0091] In the technical solution of this embodiment, by saving the decision-making algorithm and the dependent data to the target service where the dependent data is located and using the method of distributed decision-making for multi-target service decision-making operations, while reducing the network loss of data movement, the data reuse rate is improved, and the utilization rate of the respective resources of the distributed target services is improved, thereby reducing the decision-making calculation pressure of the decision-making system and achieving the technical effect of improving the decision-making efficiency.

[0092] Figure 5 It is a schematic structural diagram of a data processing device provided by an embodiment of the present invention. The device includes: a decision-making algorithm determination module 510, a target service determination module 520, and a target feedback result determination module 530.

[0093] Among them, the decision-making algorithm determination module 510 is used to determine at least one decision-making algorithm to be used corresponding to the business request when receiving the business request; the target service determination module 520 is used to determine the target service corresponding to the at least one decision-making algorithm to be used, and send the business request including the decision-making algorithm identifier to the target service, so that the target service retrieves the corresponding target dependency item based on the decision-making algorithm identifier, and determines the feedback result based on the target dependency item and the business information carried in the business request; the target feedback result determination module 530 is used to receive the feedback results fed back by each target service and perform integration processing on the feedback results to obtain the target feedback result corresponding to the business request.

[0094] Based on the above device, optionally, the device further includes: a decision algorithm configuration module, configured to configure corresponding decision algorithms to be compiled for a plurality of preset service scenarios respectively; wherein, the decision algorithms to be compiled are configured based on decisions, scripts, and rules; a compilation module, configured to perform compilation processing on the decision algorithms to be compiled to obtain a plurality of decision algorithms; a mapping relationship establishment module, configured to establish a first mapping relationship between the decision algorithms and at least one selectable dependency, and a second mapping relationship between the decision algorithms and the selectable service to which the at least one selectable dependency belongs, so as to determine a target service and a target dependency in the target service based on the first mapping relationship and the second mapping relationship.

[0095] Based on the above device, optionally, the device further includes: a data storage module, configured to store corresponding dependency data in the selectable dependencies; an algorithm storage module, configured to determine the selectable decision algorithms corresponding to the selectable dependencies, so as to locally store the selectable decision algorithms, and when a service request is received, call the corresponding target dependencies and target decision algorithms based on the decision algorithm identifier.

[0096] Based on the above device, optionally, the target service determination module 520 includes a target service determination unit. The target service determination unit is configured to determine the target service corresponding to the at least one decision algorithm to be used based on the second mapping relationship, and route the service request including the decision algorithm identifier to the corresponding target service; the target service is configured to call the corresponding target dependencies from the target service based on the first mapping relationship and the decision algorithm identifier.

[0097] Based on the above device, optionally, the target service is further configured to obtain the dependency data in the target dependencies; process the service information carried in the service request based on the locally stored decision algorithm and the dependency data, and determine the feedback result.

[0098] Based on the above device, optionally, the target feedback result determination module 530 includes an asynchronous receiving unit and a target feedback result determination unit. The asynchronous receiving unit is configured to asynchronously receive the feedback results fed back by each target service; the target feedback result determination unit is configured to process the feedback results based on the preset merging rules stored in the result merger to obtain the target feedback result.

[0099] In the technical solution of the embodiment of the present invention, when a service request is received, at least one decision algorithm to be used corresponding to the service request is determined, and then a target service corresponding to the at least one decision algorithm to be used is determined. The service request including the decision algorithm identifier is sent to the target service, so that the target service retrieves the corresponding target dependencies based on the decision algorithm identifier, and determines a feedback result based on the target dependencies and the service information carried in the service request; the feedback results are integrated and processed to obtain a target feedback result corresponding to the service request. The technical solution of the embodiment of the present invention solves the technical problems in the prior art that dependent data is obtained from each data end and then centrally processed in the decision-making system, resulting in high requirements for system performance, high network energy consumption, low decision-making efficiency, and ineffective data reuse. It realizes determining each decision algorithm to be used required under the service request when the service request is received, and then determining the target service corresponding to each decision algorithm to be used, and allocating the service request including the decision algorithm identifier to each target service, so that each target service makes a decision and processes locally through the target dependencies corresponding to the decision algorithm identifier and the service information in the service request, avoiding intermediate data transmission, reducing the occupation of network resources while improving the utilization rate of the system resources of each target service, thereby reducing the decision-making calculation pressure on the decision-making system. By integrating the feedback results of the decisions of each target service, the final target feedback result is obtained, achieving the technical effect of improving the decision-making efficiency.

[0100] The data processing device provided by the embodiment of the present invention can execute the data processing method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the method.

[0101] It should be noted that the various units and modules included in the above system are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be realized; in addition, the specific names of the functional units are only for the convenience of mutual distinction and do not limit the protection scope of the embodiment of the present invention.

[0102] Figure 6 It is a schematic structural diagram of an electronic device provided by an embodiment of the present invention. Figure 6 It shows a block diagram of an exemplary electronic device 60 suitable for implementing the embodiment mode of the embodiment of the present invention. Figure 6 The shown electronic device 60 is only an example and should not bring any limitation to the functions and usage scope of the embodiment of the present invention.

[0103] Such as Figure 6As shown, the electronic device 60 is presented in the form of a general-purpose computing device. The components of the electronic device 60 may include, but are not limited to: one or more processors or processing units 601, a system memory 602, and a bus 603 that connects different system components (including the system memory 602 and the processing unit 601).

[0104] The bus 603 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration port, a processor, or a local bus using any of the various bus structures. By way of example, these architectures include, but are not limited to, Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MAC) bus, Enhanced ISA bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.

[0105] The electronic device 60 typically includes a variety of computer system-readable media. These media can be any available media that can be accessed by the electronic device 60, including volatile and non-volatile media, removable and non-removable media.

[0106] The system memory 602 may include computer system-readable media in the form of volatile memory, such as random access memory (RAM) 604 and / or cache memory 605. The electronic device 60 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, a storage system 606 can be used for reading and writing on non-removable, non-volatile magnetic media ( Figure 6 not shown, typically referred to as a "hard disk drive"). Although Figure 6 not shown in the figure, a disk drive for reading and writing on a removable non-volatile disk (such as a "floppy disk") and an optical disk drive for reading and writing on a removable non-volatile optical disk (such as a CD-ROM, DVD-ROM, or other optical media) can be provided. In these cases, each drive can be connected to the bus 603 through one or more data media interfaces. The memory 602 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the embodiments of the present invention.

[0107] A program / utility 608 having a set (at least one) of program modules 607 can be stored, for example, in the memory 602. Such program modules 607 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include the implementation of a network environment. The program modules 607 generally execute the functions and / or methods in the embodiments described in the present invention.

[0108] The electronic device 60 can also communicate with one or more external devices 609 (such as a keyboard, a pointing device, a display 810, etc.), and can also communicate with one or more devices that enable a user to interact with the electronic device 60, and / or communicate with any device that enables the electronic device 60 to communicate with one or more other computing devices (such as a network card, a modem, etc.). Such communication can be carried out through the input / output (I / O) interface 611. Moreover, the electronic device 60 can also communicate with one or more networks (such as a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) through the network adapter 612. As shown in the figure, the network adapter 612 communicates with other modules of the electronic device 60 through the bus 603. It should be understood that although Figure 6 not shown in the figure, other hardware and / or software modules can be used in combination with the electronic device 60, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

[0109] The processing unit 601 executes various functional applications and data processing by running programs stored in the system memory 602, for example, implementing the data processing method provided by the embodiments of the present invention.

[0110] The embodiments of the present invention also provide a storage medium containing computer-executable instructions, and the computer-executable instructions are used to execute a data processing method when executed by a computer processor. The method includes:

[0111] When receiving a service request, determining at least one decision algorithm to be used corresponding to the service request;

[0112] Determining a target service corresponding to the at least one decision algorithm to be used, and sending the service request including the decision algorithm identifier to the target service, so that the target service retrieves corresponding target dependencies based on the decision algorithm identifier, and determines a feedback result based on the target dependencies and the service information carried in the service request;

[0113] Receiving the feedback results fed back by each target service, and integrally processing the feedback results to obtain a target feedback result corresponding to the service request.

[0114] The computer storage medium of the embodiments of the present invention may adopt any combination of one or more computer-readable media. The computer-readable media may be computer-readable signal media or computer-readable storage media. The computer-readable storage media may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples (a non-exhaustive list) of the computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, the computer-readable storage media may be any tangible medium that contains or stores a program, which can be used by or in combination with an instruction execution system, apparatus, or device.

[0115] The computer-readable signal media may include a data signal propagated in a baseband or as a part of a carrier wave, which carries the computer-readable program code. Such a propagated data signal may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal media may also be any computer-readable media other than the computer-readable storage media, which can send, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device.

[0116] The program code contained on the computer-readable media may be transmitted by any appropriate medium, including but not limited to wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0117] The computer program code for performing the operations of the embodiments of the present invention may be written in one or more programming languages or combinations thereof. The programming languages include object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, executed as an independent software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (for example, by using an Internet service provider to connect through the Internet).

[0118] Note that the above is only the preferred embodiment of the present invention and the applied technical principles. Those skilled in the art will understand that the present invention is not limited to the specific embodiments here, and various obvious changes, re-adjustments and substitutions can be made by those skilled in the art without departing from the protection scope of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments only. Without departing from the concept of the present invention, more other equivalent embodiments can be included, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A data processing method, characterized in that, it includes: When receiving a service request, determining at least one decision algorithm to be used corresponding to the service request; Determining a target service corresponding to the at least one decision algorithm to be used, and sending the service request including the decision algorithm identifier to the target service, so that the target service retrieves corresponding target dependencies based on the decision algorithm identifier, and determines a feedback result based on the target dependencies and the service information carried in the service request; Receiving the feedback results fed back by each target service, and integrally processing the feedback results to obtain a target feedback result corresponding to the service request.

2. The method according to claim 1, characterized in that, it further includes: Configuring corresponding decision algorithms to be compiled for a plurality of preset service scenarios respectively; wherein, the decision algorithms to be compiled are configured based on decisions, scripts, and rules; Compiling the decision algorithms to be compiled to obtain a plurality of decision algorithms; Establishing a first mapping relationship between the decision algorithms and at least one dependency to be selected, and a second mapping relationship between the decision algorithms and the target service to which the at least one dependency to be selected belongs, so as to determine the target service and the target dependencies in the target service based on the first mapping relationship and the second mapping relationship.

3. The method according to claim 2, characterized in that, it further includes: Storing corresponding dependency data in the dependency to be selected; Determining the decision algorithm to be selected corresponding to the dependency to be selected, so as to locally store the decision algorithm to be selected, so that when receiving a service request, corresponding target dependencies and target decision algorithms are retrieved based on the decision algorithm identifier.

4. The method according to claim 1, characterized in that, The determining the target service corresponding to the at least one decision algorithm to be used, and sending the service request including the decision algorithm identifier to the target service includes: Based on the second mapping relationship, determining the target service corresponding to the at least one decision algorithm to be used, and routing the service request including the decision algorithm identifier to the corresponding target service; Correspondingly, the enabling the target service to retrieve corresponding target dependencies based on the decision algorithm identifier includes: Based on the first mapping relationship and the decision algorithm identifier, retrieving corresponding target dependencies from the target service.

5. The method according to claim 1, characterized in that, The determining the feedback result based on the target dependencies and the service information carried in the service request includes: Obtaining the dependency data in the target dependencies; Processing the service information carried in the service request based on the locally stored decision algorithm and the dependency data to determine the feedback result.

6. The method according to claim 1, characterized in that, The receiving the feedback results fed back by each target service, and integrally processing the feedback results to obtain a target feedback result corresponding to the service request includes: Asynchronously receiving the feedback results fed back by each target service; Process the feedback result based on the preset merging rules stored in the result merger to obtain the target feedback result.

7. A data processing device characterized in that it includes: A decision algorithm determination module, configured to determine at least one decision algorithm to be used corresponding to the service request when receiving the service request; A target service determination module, configured to determine a target service corresponding to the at least one decision algorithm to be used, and send the service request including the decision algorithm identifier to the target service, so that the target service retrieves corresponding target dependencies based on the decision algorithm identifier, and determines a feedback result based on the target dependencies and the service information carried in the service request; A target feedback result determination module, configured to receive the feedback results fed back by each target service, and perform integrated processing on the feedback results to obtain a target feedback result corresponding to the service request.

8. The device according to claim 7 characterized in that it further includes: A decision algorithm configuration module, configured to respectively configure corresponding decision algorithms to be compiled for a plurality of preset service scenarios; wherein, the decision algorithms to be compiled are configured based on decisions, scripts, and rules; A compilation module, configured to perform compilation processing on the decision algorithms to be compiled to obtain a plurality of decision algorithms; A mapping relationship establishment module, configured to establish a first mapping relationship between the decision algorithm and at least one dependency to be selected, and a second mapping relationship between the decision algorithm and the target service to which the at least one dependency to be selected belongs, so as to determine the target service and the target dependencies located in the target service based on the first mapping relationship and the second mapping relationship.

9. An electronic device characterized in that the electronic device includes: One or more processors; A storage device, configured to store one or more programs, when the one or more programs are executed by the one or more processors, enabling the one or more processors to implement the data processing method according to any one of claims 1-6.

10. A storage medium containing computer-executable instructions, the computer-executable instructions being used to execute the data processing method according to any one of claims 1-6 when executed by a computer processor.

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