CN113504973A - Service data concurrent processing method, device and system - Google Patents
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Abstract
The invention provides a method, a device and a system for concurrent processing of business data, belongs to the technical field of cloud computing, and can be applied to the financial field or other fields. The service data concurrent processing method comprises the following steps: acquiring a service input parameter, and determining each rule corresponding to the input parameter and element information of elements corresponding to each rule; sending the element information of each element to a corresponding cluster client so that each cluster client can obtain the element value of each element information in parallel; and concurrently executing the rules corresponding to the element values according to the element values from the cluster clients to obtain execution results. The invention can improve the system expansibility, the operation stability and the service data processing efficiency and quickly respond to the related service requirements.
Description
Technical Field
The invention relates to the technical field of cloud computing, in particular to a service data concurrent processing method, device and system.
Background
With the rise of internet finance wave, the online transaction amount of general finance and personal loan increases day by day, and the data processing requirement of high timeliness is more and more vigorous. In this situation, higher requirements need to be put forward on the real-time data processing capacity of the system, however, in the technical aspect, due to micro-service transformation and service group splitting caused by system upgrading, data are split and dispersed in each library along with the service field, service personnel expect to obtain index data of different data sources, even external index data of an off-line third party to realize comprehensive data management and control, and the factor value taking efficiency of the system is greatly reduced; in addition, in order to adapt to different requirements of the service, the rule model is continuously increased, multiple rule models are used simultaneously in one scene (for example, common rules, rule sets and scoring card rules are used simultaneously), the execution performance of the decision engine on the rules is influenced, and the system cannot meet the millisecond-level real-time response requirement of the service.
Disclosure of Invention
The embodiments of the present invention mainly aim to provide a method, an apparatus, and a system for concurrently processing service data, so as to improve system extensibility, operation stability, and service data processing efficiency, and quickly respond to related service requirements.
In order to achieve the above object, an embodiment of the present invention provides a service data concurrent processing method, including:
acquiring a service input parameter, and determining each rule corresponding to the input parameter and element information of elements corresponding to each rule;
sending the element information of each element to a corresponding cluster client so that each cluster client can obtain the element value of each element information in parallel;
and concurrently executing the rules corresponding to the element values according to the element values from the cluster clients to obtain execution results.
An embodiment of the present invention further provides a device for concurrently processing service data, including:
the rule information determining module is used for acquiring the service input parameters and determining each rule corresponding to the input parameters and the element information of the elements corresponding to each rule;
the sending module is used for sending the element information of each element to the corresponding cluster client so as to enable each cluster client to obtain the element value of each element information in parallel;
and the concurrent execution module is used for concurrently executing the rules corresponding to the element values according to the element values from the cluster clients to obtain the execution results.
The embodiment of the present invention further provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and running on the processor, and the processor implements the steps of the service data concurrent processing method when executing the computer program.
The embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the service data concurrent processing method are implemented.
The embodiment of the present invention further provides a service data concurrent processing system, including:
the business data concurrent processing device is used for acquiring business input parameters and determining each rule corresponding to the input parameters and element information of elements corresponding to each rule; sending the element information of each element to a corresponding service cluster client or a data center; concurrently executing rules corresponding to the element values according to the element values from the service cluster client or the data center station to obtain execution results;
the service cluster client is used for searching the access classes corresponding to the element information in a preset data structure and scheduling the access classes in parallel to obtain the element values corresponding to the element information;
and the data center is used for sending the element information of each element to the corresponding external application cluster client so that the external application cluster client can obtain the element value of each element information in parallel.
The business data concurrent processing method, the business data concurrent processing device and the business data concurrent processing system firstly determine each rule corresponding to the input parameters and the element information of the elements corresponding to each rule, then send the element information of each element to the corresponding cluster client so that each cluster client can obtain the element value of each element information in parallel, and finally concurrently execute the rule corresponding to each element value according to each element value from each cluster client to obtain each execution result.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained based on these drawings without creative efforts.
Fig. 1 is a flowchart of a method for concurrently processing service data in an embodiment of the present invention;
FIG. 2 is a schematic diagram of a rule relationship in an embodiment of the present invention;
FIG. 3 is a diagram illustrating concurrent invocation of elements in an embodiment of the present invention;
fig. 4 is a block diagram of a service data concurrent processing apparatus according to an embodiment of the present invention;
FIG. 5 is a block diagram of a computer apparatus according to an embodiment of the present invention;
fig. 6 is a schematic diagram of a service data concurrent processing system in an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As will be appreciated by one skilled in the art, embodiments of the present invention may be embodied as a system, apparatus, device, method, or computer program product. Accordingly, the present disclosure may be embodied in the form of: entirely hardware, entirely software (including firmware, resident software, micro-code, etc.), or a combination of hardware and software.
In view of the problems of low timeliness for obtaining the element value of the decision engine, weak expansibility of newly added similar elements and poor rule execution performance in the prior art, embodiments of the present invention provide a method, an apparatus and a system for concurrently processing service data, which use the following technical solutions: 1) analyzing the rule to obtain a full amount of elements, and classifying and calling multi-group and multi-source index data according to the sources of the elements; 2) the decision engine executes all rules according to different rule types concurrently, so that the system expansibility, the operation stability and the service data processing efficiency can be improved, and the related service requirements can be responded quickly. The method can also be applied to the field of risk control, and real-time accurate wind control is realized. The present invention will be described in detail below with reference to the accompanying drawings.
The key terms mentioned in the present invention are defined as follows:
elements (wind control elements): i.e. definition tags used in the rule (wind control rule) configuration process. For example: defining the cust _001 as an individual client risk assessment result element, if the configuration rule is if (cust _001 ═ 1') return true; return false, which indicates that if the personal client risk assessment result of the current client is 1, there is risk and hit rule, otherwise there is no client risk.
Service cluster (credit service cluster): the service cluster (credit service cluster) is mainly divided into different clusters according to different modules of the service (credit service), for example: the service system comprises a client cluster related to a client, a basic data cluster related to basic service, a loan cluster related to personal loan service and the like, wherein different service clusters deploy different types of service elements.
Relationship of service clusters (credit service clusters) to elements: the elements are configured on different service clusters (credit service clusters) according to different element meanings and element sources, one element can be configured on only one cluster, and the same cluster can be configured with a plurality of different elements. Elements and clusters are mapped many-to-many and one-to-one, and one element uniquely maps one cluster. Different elements directly complete decoupling, the elements configured on a certain group are coupled with the group, and each group realizes decoupling.
Topological description of elements and clusters: if the element source of the newly added element is the existing service group, the access interface is directly supplemented on the corresponding service group, and the decision engine does not need to change the program; if the service group is not docked, the public annotation of the decision engine can be introduced to the new group to register the access interface service of the public route for service registration, and then the access interface of the corresponding element is supplemented, and the decision engine does not need to change the program. For a service data concurrent processing system, function expansion can be completed by modifying newly added elements and expanding service clusters through zero programs.
Fig. 1 is a flowchart of a method for concurrently processing service data in an embodiment of the present invention. As shown in fig. 1, the method for concurrently processing service data includes:
s101: acquiring a service input parameter, and determining each rule corresponding to the input parameter and element information of elements corresponding to each rule.
FIG. 2 is a schematic diagram of rule relationships in an embodiment of the invention. As shown in fig. 2, determining the rule corresponding to the input parameter includes: determining a service scene corresponding to the input parameter; and determining each rule corresponding to the business scene according to the hitching relation of the rules under the scene. Wherein, the input parameters are obtained through a self-defined interface.
Each Rule includes a common Rule, a Rule set and a scoring card Rule, the rules inherit a parent Rule, and all require an execute method (execution method) of rewriting a specific Rule, and then the corresponding rules are uniformly converted into a parent Rule type to prepare for subsequent Rule execution.
In one embodiment, S101 further includes: and concurrently calling an expression analysis method of the rule engine to analyze each rule to obtain corresponding elements of each rule. The QLExpress expression analysis method can be called concurrently to analyze the element id of each rule and summarize the total elements.
S102: and sending the element information of each element to the corresponding cluster client so that each cluster client can acquire the element value of each element information in parallel.
And querying a database according to the analyzed element id to obtain corresponding element information. The element information may include an element name, an element classification, an element value data type, and an application deployment cluster of the element.
Fig. 3 is a schematic diagram of concurrent invocation of elements in the embodiment of the present invention. As shown in fig. 3, the elements are divided into service cluster source elements and data center source elements according to the deployment cluster of the elements, the data center source elements are classified according to the data attribution interface (for example, external application a cluster elements and external application B cluster elements), and the service cluster source elements are classified according to the specific service cluster (for example, client cluster elements and basic data cluster elements).
As shown in fig. 3, S102 includes:
1. and when the deployment cluster in the element information is a service cluster, sending the element information of each element to the corresponding service cluster client so that the service cluster client can obtain the element value of each element information in parallel.
In one embodiment, sending the element information of each element to the corresponding service cluster client, so that the service cluster client obtains the element value of each element information in parallel includes:
and sending the element information of each element to a corresponding service cluster client so that the service cluster client searches the access class corresponding to each element information in a preset data structure, and scheduling each access class in parallel to obtain the element value of the corresponding element information.
In specific implementation, the service cluster client deployed in each service cluster receives the element information and puts the element information into an element information list. And searching an access class corresponding to each element information in a Map data structure through a decision engine SDK (software development kit) according to the element information list, and scheduling access interfaces of each access class in parallel to arrange the element information to obtain an element value. The decision engine SDK is used for realizing condition rules such as classification and naming of class setting elements and standardizing the elements. The element values are stored in the data structure of Map, the key is the element id, and the value is the element object.
2. And when the deployment cluster in the element information is an external application cluster, sending the element information of each element to a corresponding external application cluster client through a data center so that the external application cluster client can obtain the element value of each element information in parallel.
In specific implementation, the decision engine sends the Element information of each Element to a unified portal service provided by a data center station, and transmits the Element information of each Element into a List < Element > List (Element List) corresponding to the data center station and a corresponding Element index scene. And the data center station performs service distribution through the entry routing service, and distributes the element information in the element list to the external application cluster client corresponding to the element index scene. And the external application cluster client side parallelly calls each access interface to arrange the element information to obtain an element value. Wherein, the element value is stored according to the data structure of Map, the key is element id, and the value is element object.
S103: and concurrently executing the rules corresponding to the element values according to the element values from the cluster clients to obtain execution results.
Before executing S103, the method further includes: and summarizing element values, and storing the result into context of the type Map < String, Object > for subsequent rule execution.
In one embodiment, S103 includes: and concurrently executing the execution method under the rule corresponding to each element value according to each element value from each cluster client to obtain each execution result, summarizing the execution results and returning the execution results to the calling party.
The execution subject of the business data concurrent processing method shown in fig. 1 may be a decision engine. As can be seen from the flow shown in fig. 1, in the method for concurrently processing service data according to the embodiment of the present invention, each rule corresponding to an input parameter and element information of an element corresponding to each rule are determined, then the element information of each element is sent to a corresponding cluster client, so that each cluster client obtains an element value of each element information in parallel, and finally, the rule corresponding to each element value is concurrently executed according to each element value from each cluster client, so as to obtain each execution result, thereby improving system scalability, operation stability, and service data processing efficiency, and quickly responding to a related service requirement.
Fig. 4 is a block diagram of a service data concurrent processing apparatus in an embodiment of the present invention. As shown in fig. 4, the service data concurrent processing apparatus includes:
the rule information determining module is used for acquiring the service input parameters and determining each rule corresponding to the input parameters and the element information of the elements corresponding to each rule;
the sending module is used for sending the element information of each element to the corresponding cluster client so as to enable each cluster client to obtain the element value of each element information in parallel;
and the concurrent execution module is used for concurrently executing the rules corresponding to the element values according to the element values from the cluster clients to obtain the execution results.
To sum up, the service data concurrent processing apparatus according to the embodiment of the present invention determines each rule corresponding to an input parameter and element information of elements corresponding to each rule, then sends the element information of each element to a corresponding cluster client, so that each cluster client obtains element values of each element information in parallel, and finally concurrently executes the rules corresponding to each element value according to each element value from each cluster client to obtain each execution result, thereby improving system scalability, operation stability, and service data processing efficiency, and rapidly responding to related service requirements.
The embodiment of the present invention further provides a specific implementation manner of a computer device, which can implement all the steps in the service data concurrent processing method in the foregoing embodiment. Fig. 5 is a block diagram of a computer device in an embodiment of the present invention, and referring to fig. 5, the computer device specifically includes the following:
a processor (processor)501 and a memory (memory) 502.
The processor 501 is configured to call a computer program in the memory 502, and when the processor executes the computer program, the processor implements all the steps in the service data concurrent processing method in the foregoing embodiments, for example, when the processor executes the computer program, the processor implements the following steps:
acquiring a service input parameter, and determining each rule corresponding to the input parameter and element information of elements corresponding to each rule;
sending the element information of each element to a corresponding cluster client so that each cluster client can obtain the element value of each element information in parallel;
and concurrently executing the rules corresponding to the element values according to the element values from the cluster clients to obtain execution results.
To sum up, the computer device of the embodiment of the present invention determines each rule corresponding to the input parameter and the element information of the element corresponding to each rule first, then sends the element information of each element to the corresponding cluster client, so that each cluster client obtains the element value of each element information in parallel, and finally executes the rule corresponding to each element value concurrently according to each element value from each cluster client, so as to obtain each execution result, thereby improving system scalability, operation stability and service data processing efficiency, and quickly responding to the related service requirements.
An embodiment of the present invention further provides a computer-readable storage medium capable of implementing all the steps in the service data concurrent processing method in the foregoing embodiment, where the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the computer program implements all the steps of the service data concurrent processing method in the foregoing embodiment, for example, when the processor executes the computer program, the processor implements the following steps:
acquiring a service input parameter, and determining each rule corresponding to the input parameter and element information of elements corresponding to each rule;
sending the element information of each element to a corresponding cluster client so that each cluster client can obtain the element value of each element information in parallel;
and concurrently executing the rules corresponding to the element values according to the element values from the cluster clients to obtain execution results.
To sum up, the computer-readable storage medium of the embodiment of the present invention determines each rule corresponding to the input parameter and the element information of the element corresponding to each rule first, then sends the element information of each element to the corresponding cluster client, so that each cluster client obtains the element value of each element information in parallel, and finally concurrently executes the rule corresponding to each element value according to each element value from each cluster client to obtain each execution result, which can improve system scalability, operation stability and service data processing efficiency, and quickly respond to the related service requirements.
Based on the same inventive concept, the embodiment of the present invention further provides a service data concurrent processing system, and as the problem solving principle of the system is similar to the service data concurrent processing method, the implementation of the system can refer to the implementation of the method, and repeated details are not repeated.
Fig. 6 is a schematic diagram of a service data concurrent processing system in an embodiment of the present invention. As shown in fig. 6, the service data concurrent processing system includes:
the business data concurrent processing device is used for acquiring business input parameters and determining each rule corresponding to the input parameters and element information of elements corresponding to each rule; sending the element information of each element to a corresponding service cluster client or a data center; concurrently executing rules corresponding to the element values according to the element values from the service cluster client or the data center station to obtain execution results;
the service cluster client is used for searching the access classes corresponding to the element information in a preset data structure and scheduling the access classes in parallel to obtain the element values corresponding to the element information;
and the data center is used for sending the element information of each element to the corresponding external application cluster client so that the external application cluster client can obtain the element value of each element information in parallel.
As shown in fig. 6, the service data concurrent processing system includes a decision engine, a service cluster client, and a data console.
A decision engine: and the decision engine is respectively connected with the service cluster client and the data center, and calls an interface corresponding to the element variable to acquire the value of the element. The decision engine is deployed in a single service cluster and provides services to the channel access requirements. And distinguishing different scenes according to input parameters called by the service so as to obtain corresponding rules, analyzing the rule expressions to obtain full elements, performing concurrent processing according to different attributions of the elements to obtain element values of corresponding clusters, and concurrently executing the full rules according to the obtained element values and the analyzed rules.
Service cluster client: the system comprises a plurality of service cluster access interfaces. The service group splitting brought by the micro-service transformation divides a huge service system into a plurality of modules and a plurality of service groups according to business functions, and greatly improves the expansibility and maintainability of a program. Meanwhile, the service elements are also distributed to different service clusters according to different attributions of the functional modules, and then corresponding access interfaces are customized for each element under the same service cluster, so that the reliability, the orderliness and the high efficiency of index element acquisition are ensured.
The data center station: the system comprises a plurality of data center access interfaces. The business desires to use the internal element data and also desires to use the index elements of each external data company. The data center stations are uniformly connected with external data formulas, external application client data or external company client data are connected, different data center station access interfaces package different access interface services for a decision engine to use, the data are positioned differently, and the actual meanings of data frameworks are different. And the decision engine is used for butting a data acquisition interface in the data to acquire a corresponding index element value.
The specific process of the embodiment of the invention is as follows:
1. the business data concurrent processing device applied to the decision engine acquires business input parameters and determines each rule corresponding to the input parameters and element information of elements corresponding to each rule.
2. And when the deployment cluster in the element information is a service cluster, the service data concurrent processing device sends the element information of each element to the corresponding service cluster client.
And when the deployment cluster in the element information is an external application cluster, the service data concurrent processing device sends the element information of each element to a corresponding external application cluster client through the data center.
3. And the service cluster client searches the access classes corresponding to the element information in a preset data structure, schedules the access classes in parallel to obtain the element values corresponding to the element information, and returns the element values to the service data concurrent processing device.
4. And the data center station sends the element information of each element to the corresponding external application cluster client so that the external application cluster client can acquire the element value of each element information in parallel and return the element value from the external application cluster client to the service data concurrent processing device.
5. And the service data concurrent processing device concurrently executes the execution method under the rule corresponding to each element value according to each element value from the service cluster client or the data center station to obtain each execution result.
In conclusion, the invention is supported by the decision engine capability, realizes various rule models according to the business requirements, and supports high-efficiency concurrent execution in the same business scene. The decision engine stores the source information of the elements when initializing the elements, classifies the elements to the access interfaces under respective clusters according to the element sources after the elements are obtained by the analysis rules, and obtains all the element values simultaneously, thereby greatly improving the system execution efficiency. The invention can simultaneously meet the requirement of the service element index which is continuously increased in the follow-up process of the service or the requirement of the external data index of a third party, and the execution time of the program can not be synchronously multiplied due to the multiple increase of the data source; in addition, the program expansibility of the invention is strong, for the newly added index, the stock code almost realizes zero change, the stability and the safety of the system operation are effectively ensured, and the access logic of the factor can be defined by the service caller, the decision engine and the factor service logic are isolated on the code and the operation state, the service caller is supported to flexibly configure and realize the more specialized index factor, the usability and the transparency of the service index factor are greatly enhanced, and the invention can more accurately and effectively assist the service personnel to improve the risk identification capability in the service handling stage.
In summary, the service data concurrent processing system provided by the embodiment of the present invention has the following beneficial effects:
(1) based on a distributed technology system, efficient and stable engine service is realized by classifying the index elements and calling the access interface and executing the rules concurrently. Compared with the original scheme of acquiring the index elements in a loose serial manner, the system expansibility, the operation stability and the execution efficiency are greatly improved;
(2) the method is applied to the field of risk control, can quickly respond to the wind control variable requirement provided by a service under the condition of not adjusting a decision engine, and realizes real-time wind control and accurate wind control.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Those of skill in the art will further appreciate that the various illustrative logical blocks, units, and steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate the interchangeability of hardware and software, various illustrative components, elements, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design requirements of the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present embodiments.
The various illustrative logical blocks, or elements, or devices described in connection with the embodiments disclosed herein may be implemented or performed with a general purpose processor, a digital signal processor, an Application Specific Integrated Circuit (ASIC), a field programmable gate array or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general-purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a digital signal processor and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a digital signal processor core, or any other similar configuration.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may be stored in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. For example, a storage medium may be coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC, which may be located in a user terminal. In the alternative, the processor and the storage medium may reside in different components in a user terminal.
In one or more exemplary designs, the functions described above in connection with the embodiments of the invention may be implemented in hardware, software, firmware, or any combination of the three. If implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media that facilitate transfer of a computer program from one place to another. Storage media may be any available media that can be accessed by a general purpose or special purpose computer. For example, such computer-readable media can include, but is not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to carry or store program code in the form of instructions or data structures and which can be read by a general-purpose or special-purpose computer, or a general-purpose or special-purpose processor. Additionally, any connection is properly termed a computer-readable medium, and, thus, is included if the software is transmitted from a website, server, or other remote source via a coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL), or wirelessly, e.g., infrared, radio, and microwave. Such discs (disk) and disks (disc) include compact disks, laser disks, optical disks, DVDs, floppy disks and blu-ray disks where disks usually reproduce data magnetically, while disks usually reproduce data optically with lasers. Combinations of the above may also be included in the computer-readable medium.
Claims (10)
1. A method for concurrently processing service data is characterized by comprising the following steps:
acquiring a service input parameter, and determining each rule corresponding to the input parameter and element information of elements corresponding to each rule;
sending the element information of each element to a corresponding cluster client so that each cluster client can obtain the element value of each element information in parallel;
and concurrently executing the rules corresponding to the element values according to the element values from the cluster clients to obtain execution results.
2. The method of claim 1, wherein sending the element information of each element to the corresponding cluster client, so that each cluster client obtains the element value of each element information in parallel comprises:
when the deployment cluster in the element information is a service cluster, sending the element information of each element to a corresponding service cluster client so that the service cluster client can obtain the element value of each element information in parallel;
and when the deployment cluster in the element information is an external application cluster, sending the element information of each element to a corresponding external application cluster client through a data center so that the external application cluster client can obtain the element value of each element information in parallel.
3. The method of claim 2, wherein sending the element information of each element to the corresponding service cluster client, so that the service cluster client obtains the element value of each element information in parallel comprises:
and sending the element information of each element to a corresponding service cluster client so that the service cluster client searches the access class corresponding to each element information in a preset data structure, and scheduling each access class in parallel to obtain the element value of the corresponding element information.
4. The method for concurrently processing the service data according to claim 1, wherein determining the rule corresponding to the input parameter comprises:
determining a service scene corresponding to the input parameter;
and determining each rule corresponding to the service scene.
5. The method for concurrently processing service data according to claim 1, further comprising:
and concurrently calling an expression analysis method of the rule engine to analyze each rule to obtain corresponding elements of each rule.
6. The method of claim 1, wherein concurrently executing the rule corresponding to each element value according to each element value from each cluster client, and obtaining each execution result comprises:
and concurrently executing the execution method under the rule corresponding to each element value according to each element value from each cluster client to obtain each execution result.
7. A device for concurrently processing service data, comprising:
the rule information determining module is used for acquiring service input parameters and determining each rule corresponding to the input parameters and element information of elements corresponding to each rule;
the sending module is used for sending the element information of each element to the corresponding cluster client so as to enable each cluster client to obtain the element value of each element information in parallel;
and the concurrent execution module is used for concurrently executing the rules corresponding to the element values according to the element values from the cluster clients to obtain the execution results.
8. A computer device comprising a memory, a processor and a computer program stored on the memory and running on the processor, characterized in that the processor implements the steps of the business data concurrent processing method according to any one of claims 1 to 6 when executing the computer program.
9. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method for concurrent processing of business data according to any one of claims 1 to 6.
10. A system for concurrently processing service data, comprising:
the business data concurrent processing device is used for acquiring business input parameters and determining each rule corresponding to the input parameters and element information of elements corresponding to each rule; sending the element information of each element to a corresponding service cluster client or a data center; concurrently executing rules corresponding to the element values according to the element values from the service cluster client or the data center station to obtain execution results;
the service cluster client is used for searching the access classes corresponding to the element information in a preset data structure and scheduling the access classes in parallel to obtain the element values corresponding to the element information;
and the data center is used for sending the element information of each element to the corresponding external application cluster client so that the external application cluster client can obtain the element value of each element information in parallel.
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| CN111930288A (en) * | 2020-08-14 | 2020-11-13 | 中国工商银行股份有限公司 | Interactive service processing method and system |
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| CN103092967A (en) * | 2013-01-22 | 2013-05-08 | 交通银行股份有限公司 | Business rule decision-making method and device based on rule engine |
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