CN112363831A - Wind control processing method and device, computer equipment and storage medium - Google Patents
Wind control processing method and device, computer equipment and storage medium Download PDFInfo
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Abstract
The application relates to a wind control processing method, a wind control processing device, computer equipment and a storage medium. The method comprises the following steps: acquiring resource exchange data sent by a client; classifying the resource exchange data under a preset classification dimension; according to the classification of each resource exchange data, distributing each resource exchange data to a rule calculation engine corresponding to the classification; performing wind control analysis on the resource exchange data sent in parallel through each rule calculation engine to obtain a wind control analysis result; and correspondingly processing resource exchange data corresponding to the risk wind control analysis result. By adopting the method, the wind control analysis efficiency can be improved.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a method and an apparatus for processing a wind control, a computer device, and a storage medium.
Background
And the resource exchange agent platform receives the delegation sent by the user through the client and carries out resource exchange in the resource exchange platform. Such as: the security company receives the order sent by the investor through the terminal and carries out the security exchange in the security exchange. In this process, the resource exchange proxy platform needs to perform wind control analysis on the resource exchange data sent by the client, so as to ensure the security of resource exchange. However, when the data volume of the client is large, the rule calculation engine of the resource exchange agent platform needs to process a large amount of resource exchange data.
In the traditional method, a chimney-type technical architecture is generally adopted, and each rule calculation engine is used for carrying out wind control processing on resource exchange data one by one, namely, wind control analysis is carried out through one rule calculation engine, and after the rule calculation engine reaches the processing limit, wind control analysis is carried out through the next rule calculation engine. However, this causes a large load on the rule calculation engine, which reduces the efficiency of the wind control analysis.
Disclosure of Invention
In view of the above, it is necessary to provide a wind control processing method, a wind control processing apparatus, a computer device, and a storage medium capable of improving the efficiency of wind control analysis.
A method of wind-controlled treatment, the method comprising:
acquiring resource exchange data sent by a client;
classifying the resource exchange data under a preset classification dimension;
according to the classification of each resource exchange data, distributing each resource exchange data to a rule calculation engine corresponding to the classification;
performing wind control analysis on the resource exchange data sent in parallel through each rule calculation engine to obtain a wind control analysis result;
and correspondingly processing resource exchange data corresponding to the risk wind control analysis result.
In one embodiment, the method further comprises:
according to a preset frequency, carrying out statistical analysis on historical resource exchange data acquired historically to obtain the activity degree of a user corresponding to the resource exchange data;
updating a routing strategy according to the activity degree; the routing strategy is a strategy for distributing the resource exchange data to a rule calculation engine;
the allocating, according to the category to which each of the resource exchange data is classified, each of the resource exchange data to the rule calculation engine corresponding to the category includes:
and according to the classification of each resource exchange data and the updated routing strategy, respectively allocating each resource exchange data to a rule calculation engine which corresponds to the classification and meets the routing strategy.
In one embodiment, the classifying the resource exchange data under the preset classification dimension includes:
under the data dimension, classifying the resource exchange data according to the data category to which the resource exchange data belongs;
the allocating, according to the category to which each of the resource exchange data is classified, each of the resource exchange data to the rule calculation engine corresponding to the category includes:
and respectively distributing the resource exchange data to a rule calculation engine corresponding to the data category according to the data category to which the resource exchange data is classified.
In one embodiment, the classifying the resource exchange data under the preset classification dimension includes:
under the user dimension, classifying the resource exchange data according to the user category to which the user corresponding to each resource exchange data belongs;
the allocating, according to the category to which each of the resource exchange data is classified, each of the resource exchange data to the rule calculation engine corresponding to the category includes:
and respectively distributing the resource exchange data to a rule calculation engine corresponding to the user category according to the user category to which the resource exchange data is classified.
In one embodiment, the classifying the resource exchange data under the preset classification dimension includes:
under the rule dimension, classifying the resource exchange data according to the complexity of a wind control analysis rule corresponding to each resource exchange data;
the allocating, according to the category to which each of the resource exchange data is classified, each of the resource exchange data to the rule calculation engine corresponding to the category includes:
and respectively distributing the resource exchange data to rule calculation engines corresponding to the rule classes according to the rule classes to which the resource exchange data are classified.
In one embodiment, the performing, by each of the rule calculation engines, a wind control analysis on the resource exchange data sent to the resource exchange engine in parallel to obtain a wind control analysis result includes:
respectively calculating an engine cluster through each rule, and performing wind control analysis on different resource exchange data sent to the engine cluster in parallel by adopting the same wind control analysis rule to obtain a wind control analysis result; the rule calculation engine cluster comprises at least one rule calculation engine.
In one embodiment, the performing, by each of the rule calculation engines, a wind control analysis on the resource exchange data sent to the resource exchange engine in parallel to obtain a wind control analysis result includes:
wind control analysis is carried out on the same resource exchange data sent in parallel by adopting wind control analysis rules respectively corresponding to each rule calculation engine cluster through each rule calculation engine cluster to obtain a wind control analysis result; the rule calculation engine cluster comprises at least one rule calculation engine.
A wind-controlled treatment device, the device comprising:
the data acquisition module is used for acquiring resource exchange data sent by the client;
the classification module is used for classifying the resource exchange data under a preset classification dimension;
the data distribution module is used for respectively distributing the resource exchange data to the rule calculation engines corresponding to the categories according to the categories to which the resource exchange data are classified;
the wind control analysis module is used for carrying out wind control analysis on the resource exchange data sent by the rule calculation engines in parallel to obtain a wind control analysis result;
and the result processing module is used for correspondingly processing the resource exchange data corresponding to the risk wind control analysis result.
A computer device comprising a memory and a processor, the memory having stored therein a computer program that, when executed by the processor, causes the processor to perform the steps of the method of wind control processing according to embodiments of the present application.
A computer-readable storage medium, having stored thereon a computer program, which, when executed by a processor, causes the processor to perform the steps of a method of processing wind control according to embodiments of the present application.
According to the wind control processing method, the wind control processing device, the computer equipment and the storage medium, the resource exchange data sent by the client side are obtained, the resource exchange data are classified under the preset classification dimensionality, the resource exchange data are respectively distributed to the rule calculation engines corresponding to the classes according to the classes to which the resource exchange data are classified, then the sent resource exchange data are subjected to wind control analysis in parallel through the rule calculation engines to obtain wind control analysis results, and the wind control analysis efficiency of the rule calculation engines is improved because the rule calculation engines can respectively perform wind control analysis in a targeted mode, so that the load of the rule calculation engines is reduced, and finally the corresponding processing is performed on the resource exchange data corresponding to the wind control analysis results with risks, so that the efficiency of the whole wind control processing process can be improved.
Drawings
FIG. 1 is a diagram of an exemplary implementation of a method for processing a wind control system;
FIG. 2 is a schematic flow chart of a method of processing wind control in one embodiment;
FIG. 3 is a diagram illustrating the distribution of data in a regular dimension in one embodiment;
FIG. 4 is a block diagram of a processing device for controlling wind in one embodiment;
FIG. 5 is a block diagram of a wind control processing device according to another embodiment;
FIG. 6 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The wind control processing method provided by the application can be applied to the application environment shown in fig. 1. The client 102 communicates with the resource exchange proxy platform 104 through a network, and the resource exchange proxy platform 104 communicates with the resource exchange platform 106 through a network. The client 102 sends the resource exchange data to the resource exchange proxy platform 104, the resource exchange proxy platform 104 performs a wind control analysis on the resource exchange data, and when the wind control analysis result indicates that there is no risk in the resource exchange data, the resource exchange proxy platform 104 may transmit the resource exchange data to the resource exchange platform 106 for resource exchange processing. When the wind control analysis result indicates that the resource exchange data has a risk, the resource exchange agent platform 104 may perform corresponding processing on the resource exchange data having the risk, thereby implementing wind control. The client 102 may be, but is not limited to, various personal computers, laptops, smartphones, tablets, and portable wearable devices. The resource exchange proxy platform 104 may be implemented as a server cluster comprised of a plurality of servers. The servers of the resource exchange agent platform 104 may be configured with rule calculation engines, and the resource exchange agent platform 104 may perform a wind control analysis on the resource exchange data through the rule calculation engines in the servers. Resource exchange platform 106 may be implemented as a stand-alone server or as a server cluster comprised of multiple servers.
In one embodiment, as shown in fig. 2, a method for processing a wind control is provided, which is described by taking the method as an example for being applied to the resource exchange proxy platform in fig. 1, and includes the following steps:
s202, acquiring resource exchange data sent by the client.
The resource exchange means performing equivalent exchange on resources. Resources may be real or virtual. The resource exchange agent platform is a platform for receiving the entrusts of others and carrying out resource exchange on the resource exchange platform for others. The resource exchange platform is a platform for exchanging resources. The client is a terminal used by a user who commits the resource exchange proxy platform to exchange resources on the resource exchange platform. The resource exchange data is data which is sent to the resource exchange agent platform by the client and is used for entrusting the resource exchange agent platform to carry out resource exchange in the resource exchange platform.
It can be understood that the resource exchange proxy platform may receive the resource exchange delegation data sent by the client through the client, and then perform resource exchange on the resource exchange platform on behalf of the client according to the resource exchange delegation data. Before sending the resource exchange commission data to the resource exchange platform, the resource exchange agent platform needs to perform wind control processing on the resource exchange commission data to ensure the safety of resource exchange. Such as: in a stock exchange scenario, the resource exchange platform may be a stock exchange and the resource exchange broker platform may be a stock company (i.e., a dealer). The securities trader can receive the security trading data sent by the investor through the client, and then the investor carries out security trading on a platform of the security exchange according to the security trading data. Before sending the securities trading data to the securities exchange, the securities trader needs to perform wind control processing on the securities trading data.
In one embodiment, the resource exchange may be at least one trade action of exchanging shares, options, or commodities in bulk.
Specifically, the user may send resource exchange data to the resource exchange proxy platform through the client to delegate the resource exchange proxy platform to perform resource exchange on the resource exchange platform. The resource exchange proxy platform may receive resource exchange data sent by the client.
In one embodiment, the resource exchange data may include at least one of resource target, resource exchange account, resource exchange time, resource market data, reward data, and delegation data, among others. In a stock exchange scenario, the resource exchange data may include at least one of stock, stock account, time of trade, market data, return data, deal data, and commission data, among others.
S204, classifying the resource exchange data under the preset classification dimension.
Specifically, the resource exchange agent platform may classify the resource exchange data in at least one preset classification dimension.
In one embodiment, the preset classification dimension may include at least one of a data dimension, a user dimension, a rule dimension, and the like. The resource exchange broker platform may classify the resource exchange data in at least one classification dimension of a data dimension, a user dimension, a rule dimension, and the like.
And S206, distributing the resource exchange data to the rule calculation engines corresponding to the categories according to the categories into which the resource exchange data are classified.
The Rule Computing Engine (RCE) is disposed in the server, and is configured to perform data computation according to the Rule parameters.
Specifically, the setting may be made in advance for the category of the resource exchange data subjected to the wind control analysis by each rule calculation engine. The resource exchange agent platform can distribute the resource exchange data to the rule calculation engines corresponding to the categories according to the categories to which the resource exchange data are classified.
In one embodiment, a server may be added on the basis of an original resource exchange proxy platform, and a rule calculation engine is configured in the server, so as to expand the number of the rule calculation engines.
In one embodiment, each rule calculation engine may extend a primary and a secondary server (i.e., a host and a secondary), to increase the high availability of the system,
in one embodiment, the resource exchange proxy platform may implement load balancing of the rule computation engine through a dynamically updated routing policy. The routing policy is a policy for allocating resource exchange data to the rule calculation engine.
In one embodiment, the resource exchange agent platform may dynamically update the routing policy by performing statistical analysis on historical resource exchange data, and allocate the resource exchange data to different rule calculation engines according to the updated routing policy to balance the load of the rule calculation engines.
And S208, performing wind control analysis on the sent resource exchange data in parallel through each rule calculation engine to obtain a wind control analysis result.
Wherein, the wind control analysis is the process of analyzing whether the resource exchange data has risks.
Specifically, the resource exchange agent platform may perform wind control analysis on the sent resource exchange data in parallel through each rule calculation engine to obtain a wind control analysis result.
In one embodiment, the result of the wind control analysis may be that the resource exchange data is at risk or the resource exchange data is not at risk.
In one embodiment, the resource exchange agent platform may obtain the wind control analysis results of different securities or different accounts corresponding to the resource exchange data.
In one embodiment, the resource exchange agent platform may perform wind control analysis on the sent resource exchange data in parallel through a rule calculation engine configured in each server, so as to obtain a wind control analysis result.
In one embodiment, the resource exchange agent platform may perform wind control analysis on the resource exchange data sent in parallel through each rule calculation engine by using at least one of a rule parallel mode and a data parallel mode, so as to obtain a wind control analysis result.
It can be understood that the resource exchange agent platform may perform the wind control analysis on the sent resource exchange data in parallel by using a rule parallel mode through a part of the rule computing engines, and perform the wind control analysis on the sent resource exchange data in parallel by using a data parallel mode through another part of the rule computing engines. Or the resource exchange agent platform can also adopt any one of the regular parallel mode and the data parallel mode to perform wind control analysis on the sent resource exchange data in parallel.
The rule parallelism means that the wind control analysis rules adopted by each rule calculation engine cluster are the same, the analyzed resource exchange data are different, and the wind control analysis is performed on the sent resource exchange data in parallel. The data parallel means that the wind control analysis rules adopted by each rule calculation engine cluster are different, the analyzed resource exchange data are the same, and the wind control analysis is performed on the sent resource exchange data in parallel. A rule calculation engine cluster refers to a cluster of at least one (i.e., one or more) rule calculation engines.
And S210, correspondingly processing the resource exchange data corresponding to the risk wind control analysis result.
In one embodiment, the resource exchange agent platform may determine what processing needs to be performed on the resource exchange data according to the type of the resource exchange data, the result of the wind control analysis, the severity of the existing risk, and the like.
In one embodiment, the resource exchange agent platform may perform alarm processing on resource exchange data corresponding to the risk-existing wind control analysis result. In one embodiment, the alarm processing may be sending an alarm message to the supervisory personnel through a communication method such as a short message or a mail. In another embodiment, the alarm processing can also be prompting to the supervisor by playing an alarm prompt tone.
In one embodiment, the resource exchange agent platform may perform processing such as order deletion or order rejection for the resource exchange data corresponding to the risk-existing wind control analysis result.
According to the wind control processing method, the resource exchange data sent by the client side are obtained, the resource exchange data are classified under the preset classification dimensionality, the resource exchange data are respectively distributed to the rule calculation engines corresponding to the classes according to the classes to which the resource exchange data are classified, then the sent resource exchange data are subjected to wind control analysis in parallel through the rule calculation engines to obtain wind control analysis results, the wind control analysis efficiency of the rule calculation engines is improved because the rule calculation engines can respectively perform wind control analysis in a targeted mode, the load of the rule calculation engines is reduced, and finally the resource exchange data corresponding to the wind control analysis results with risks are correspondingly processed, so that the efficiency of the whole wind control processing process can be improved. In addition, the method and the system load the service resources as required, and realize linear expansion of the wind control processing capacity. The computing capability expansion of the system is not influenced by software, and the computing capability of the whole system can be expanded only by expanding hardware equipment, so that the wind control analysis efficiency is improved. In many practical scenarios, one dealer often only needs one master server and one standby server to satisfy all data calculation functions.
In one embodiment, the method further comprises: according to a preset frequency, carrying out statistical analysis on historical resource exchange data acquired historically to obtain the activity degree of a user corresponding to the resource exchange data; updating a routing strategy according to the activity degree; the routing policy is a policy for allocating resource exchange data to the rule calculation engine. The step of respectively allocating each resource exchange data to the rule calculation engine corresponding to the category according to the category to which each resource exchange data is classified comprises: and according to the classification of the resource exchange data and the updated routing strategy, respectively distributing the resource exchange data to the rule calculation engines which correspond to the classification and meet the routing strategy.
The preset frequency refers to the frequency of the resource exchange agent platform performing statistical analysis on historical resource exchange data and updating the routing policy, that is, how often the resource exchange agent platform updates the routing policy. The historical resource exchange data refers to the resource exchange data acquired so far, that is, the resource exchange data acquired until the statistical analysis is performed.
Specifically, the resource exchange agent platform may perform statistical analysis on historical resource exchange data acquired historically according to a preset frequency by using a weighting algorithm to obtain an activity degree of a user corresponding to the resource exchange data, and update a routing policy according to the activity degree, so that after the resource exchange data is received, the resource exchange data is distributed to a proper rule calculation engine for wind control analysis, thereby balancing a load of the rule calculation engine.
In one embodiment, the resource exchange agent platform may determine a set of rule calculation engines corresponding to the categories according to the categories to which the resource exchange data are classified, select an appropriate rule calculation engine satisfying the routing policy from the determined set of rule calculation engines according to the updated routing policy, and allocate the resource exchange data to the selected rule calculation engine for the wind control analysis.
In one embodiment, the preset frequency may be set according to actual requirements. Such as: the preset frequency may be any one of once a day, once every three days, once a week, once a month, or the like.
In one embodiment, the activity level of the user corresponding to the resource exchange data may include an activity level of a security or account, etc. of the user corresponding to the resource exchange data.
In this embodiment, the resource exchange agent platform dynamically updates the routing policy according to the preset frequency, balances the load of the rule calculation engine, and achieves reasonable allocation of hardware resources, network resources, and software resources.
In one embodiment, classifying the resource exchange data under a preset classification dimension includes: and under the data dimension, classifying the resource exchange data according to the data category to which each resource exchange data belongs. According to the classification of each resource exchange data, respectively allocating each resource exchange data to the rule calculation engine corresponding to the classification comprises: and respectively distributing the resource exchange data to the rule calculation engines corresponding to the data classes according to the data classes to which the resource exchange data are classified.
The data type refers to a type to which a data attribute of the resource exchange data belongs.
In one embodiment, the data attribute may include at least one of a region attribute or a resource exchange type attribute, or the like. In one embodiment, in the data dimension, the resource exchange data is classified according to a data category to which each resource exchange data belongs, and the classifying may include classifying the resource exchange data according to at least one of a region to which each resource exchange data belongs, a resource exchange type to which each resource exchange data belongs, and the like.
Such as: in the securities trading scenario, a securities dealer can classify the securities trading data into Shanghai securities trading data, Shenzhen securities trading data and the like. The securities trader may also classify stock trading data into fund trading data, stock trading data, and the like.
In one embodiment, the resource exchange agent platform may allocate each resource exchange data to a rule calculation engine in a server corresponding to a data category according to the data category to which each resource exchange data is classified.
Such as: in the security trading scene, a dealer can distribute the Shanghai security trading data and the Shenzhen security trading data to the rule calculation engines in different servers respectively. For another example: in the stock trading scenario, the dealer may distribute the fund trading data and the stock trading data to the rule calculation engines in different servers, respectively.
In this embodiment, the resource exchange agent platform may classify the resource exchange data in the data dimension and distribute the resource exchange data to different rule calculation engines according to the classification result, so that each rule calculation engine may perform wind control analysis in a targeted manner, and the load of the rule calculation engine is reduced, thereby improving the wind control analysis efficiency of the rule calculation engine, and further improving the efficiency of wind control processing.
In one embodiment, classifying the resource exchange data under a preset classification dimension includes: and under the user dimension, classifying the resource exchange data according to the user category to which the user corresponding to each resource exchange data belongs. According to the classification of each resource exchange data, respectively allocating each resource exchange data to the rule calculation engine corresponding to the classification comprises: and respectively distributing the resource exchange data to the rule calculation engines corresponding to the user classes according to the user classes to which the resource exchange data are classified.
The user category refers to a category to which a user attribute of a user corresponding to the resource exchange data belongs.
In one embodiment, the user attributes may include the importance of the user, and the like. In an embodiment, in the user dimension, the resource exchange data is classified according to the user category to which the user corresponding to each resource exchange data belongs, which may include classifying the resource exchange data according to the importance degree of the user corresponding to each resource exchange data. Such as: the resource exchange agent platform can classify the resource exchange data into the resource exchange data of the common user, the resource exchange data of the important user and the like according to the importance degree of the user corresponding to the resource exchange data.
In one embodiment, the resource exchange agent platform may allocate each resource exchange data to a rule calculation engine in a server corresponding to a user class according to the user class to which each resource exchange data is classified. Such as: the resource exchange agent platform can distribute the resource exchange data of the common users and the resource exchange data of the important users to the rule calculation engines in different servers respectively.
In this embodiment, the resource exchange agent platform can classify the resource exchange data and distribute the resource exchange data to different rule calculation engines according to the classification result in the user dimension, so that each rule calculation engine can perform wind control analysis with pertinence, and the load of the rule calculation engine is reduced, thereby improving the wind control analysis efficiency of the rule calculation engine, and further improving the efficiency of wind control processing.
In one embodiment, classifying the resource exchange data under a preset classification dimension includes: and under the rule dimension, classifying the resource exchange data according to the complexity of the wind control analysis rule corresponding to each resource exchange data. According to the classification of each resource exchange data, respectively allocating each resource exchange data to the rule calculation engine corresponding to the classification comprises: and respectively distributing the resource exchange data to the rule calculation engines corresponding to the rule classes according to the rule classes to which the resource exchange data are classified.
The rule category refers to a category to which a rule attribute of a wind control analysis rule corresponding to the resource exchange data (that is, a wind control analysis rule required to be adopted for the resource exchange data) belongs.
In one embodiment, the rule attribute may include at least one of a computational complexity of the rule, a computational load of the rule, and the like. In one embodiment, under the rule dimension, the resource exchange data is classified according to the complexity of the wind control analysis rule corresponding to each resource exchange data, and the classification may include classifying the resource exchange data according to at least one of the computational complexity or the computational complexity of the wind control analysis rule corresponding to the resource exchange data. Such as: the resource exchange agent platform may classify the resource exchange data into resource exchange data with complex rule calculations and resource exchange data with simple rule calculations.
In one embodiment, the resource exchange agent platform may allocate each resource exchange data to a rule calculation engine in a server corresponding to a rule class according to the rule class to which each resource exchange data is classified.
Such as: as shown in fig. 3, in a security trading scenario, a dealer may assign security trading data (e.g., data numbered as 000001, 000002, and 000003 in fig. 3) corresponding to the wind-controlled analysis rules such as tie-up and tie-down, false declaration, continuous declaration, self-purchase and self-sale, continuous trading, and large declaration to the rule calculation engine 1, and assign security trading data (e.g., data numbered as 600001, 600002, and 600003 in fig. 3) corresponding to the wind-controlled analysis rules such as high-purchase and low-sale, turn-in-the-day, and maintaining price rise and fall to the rule calculation engine 2. As shown in fig. 3, the transmitted stock exchange data may include at least one of market data, commission data, deal data, return data, and the like of all customers.
In this embodiment, the resource exchange agent platform may classify the resource exchange data in the rule dimension and distribute the resource exchange data to different rule calculation engines according to the classification result, so that each rule calculation engine may perform wind control analysis in a targeted manner, and the load of the rule calculation engine is reduced, thereby improving the wind control analysis efficiency of the rule calculation engine, and further improving the efficiency of wind control processing.
In one embodiment, the wind control analysis is performed on the sent resource exchange data in parallel through each rule calculation engine, and obtaining a wind control analysis result includes: respectively calculating an engine cluster through each rule, and performing wind control analysis on different resource exchange data sent to the engine cluster in parallel by adopting the same wind control analysis rule to obtain a wind control analysis result; at least one rule calculation engine is included in the cluster of rule calculation engines.
Wherein the rule calculation engine cluster is a cluster composed of at least one rule calculation engine.
In one embodiment, a plurality of rule calculation engine clusters may be included in the resource exchange broker platform. The resource exchange agent platform can adopt a rule parallel mode, respectively calculate an engine cluster through each rule, adopt the same wind control analysis rule, and parallelly carry out wind control analysis on different resource exchange data sent to obtain a wind control analysis result. For example: in a security trading scenario, a security dealer includes two rule calculation engines, namely a rule calculation engine cluster a and a rule calculation engine cluster B, the rule calculation engine cluster a and the rule calculation engine cluster B can simultaneously use a large-scale declaration of the wind control analysis rule to perform wind control analysis, but the rule calculation engine cluster a analyzes security trading data with a security code of 000001, and the rule calculation engine cluster B analyzes security trading data with a security code of 000002.
In this embodiment, the resource exchange agent platform adopts a rule parallel mode, and each rule calculation engine cluster performs wind control analysis on different resource exchange data sent to the resource exchange agent platform in parallel by using the same wind control analysis rule, so that the wind control analysis efficiency is improved.
In one embodiment, the wind control analysis is performed on the sent resource exchange data in parallel through each rule calculation engine, and obtaining a wind control analysis result includes: wind control analysis is carried out on the same resource exchange data sent in parallel by adopting wind control analysis rules respectively corresponding to each rule calculation engine cluster through each rule calculation engine cluster to obtain a wind control analysis result; at least one rule calculation engine is included in the cluster of rule calculation engines.
In one embodiment, a plurality of rule calculation engine clusters may be included in the resource exchange broker platform. The resource exchange agent platform can adopt a data parallel mode, and through each rule calculation engine cluster, wind control analysis is carried out on the same resource exchange data sent in parallel by adopting the wind control analysis rules respectively corresponding to each rule calculation engine cluster, so as to obtain a wind control analysis result. For example: in a security trading scene, a security dealer comprises two rule calculation engines, namely a rule calculation engine cluster A and a rule calculation engine cluster B, the rule calculation engine cluster A and the rule calculation engine cluster B can receive and analyze the same security trading data, but the wind control analysis rule adopted by the rule calculation engine cluster A is a large report, and the wind control analysis rule adopted by the rule calculation engine cluster B is a pull-lift and push-press rule.
In this embodiment, the resource exchange agent platform adopts a data parallel mode, and each rule calculation engine cluster performs wind control analysis on the same resource exchange data sent to the resource exchange agent platform in parallel by adopting different wind control analysis rules, so that the wind control analysis efficiency is improved.
It should be understood that, although the steps in the flowchart of fig. 2 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a portion of the steps in fig. 2 may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed in turn or alternately with other steps or at least a portion of the other steps or stages.
In one embodiment, as shown in fig. 4, there is provided a wind-controlled processing apparatus 400, comprising: a data acquisition module 402, a classification module 404, a data distribution module 406, a wind control analysis module 408, and a result processing module 410, wherein:
a data obtaining module 402, configured to obtain resource exchange data sent by the client.
A classification module 404, configured to classify the resource exchange data according to a preset classification dimension.
The data allocating module 406 is configured to allocate each resource exchange data to a rule calculation engine corresponding to a category according to the category to which each resource exchange data is classified.
And the wind control analysis module 408 is configured to perform wind control analysis on the sent resource exchange data in parallel through each rule calculation engine to obtain a wind control analysis result.
And the result processing module 410 is configured to perform corresponding processing on resource exchange data corresponding to the risk-existing wind control analysis result.
In one embodiment, as shown in fig. 5, the wind control processing apparatus 400 further includes:
the dynamic routing module 412 is configured to perform statistical analysis on historical resource exchange data obtained in a historical manner according to a preset frequency to obtain an activity level of a user corresponding to the resource exchange data; updating a routing strategy according to the activity degree; the routing policy is a policy for allocating resource exchange data to the rule calculation engine. The data allocating module 406 is further configured to allocate, according to the category to which each resource exchange data is classified, each resource exchange data to a rule calculating engine that is corresponding to the category and satisfies the routing policy, respectively, according to the updated routing policy.
In one embodiment, the classification module 404 is further configured to classify the resource exchange data according to a data class to which each resource exchange data belongs, in the data dimension. The data allocating module 406 is further configured to allocate each resource exchange data to a rule calculating engine corresponding to a data category according to the data category to which each resource exchange data is classified.
In one embodiment, the classification module 404 is further configured to classify the resource exchange data according to a user category to which a user corresponding to each resource exchange data belongs, in the user dimension. The data allocating module 406 is further configured to allocate each resource exchange data to a rule calculation engine corresponding to a user category according to the user category to which each resource exchange data is classified.
In one embodiment, the classification module 404 is further configured to classify the resource exchange data according to a complexity of a wind control analysis rule corresponding to each resource exchange data in a rule dimension. The data allocating module 406 is further configured to allocate each resource exchange data to a rule computing engine corresponding to a rule category according to the rule category to which each resource exchange data is classified.
In an embodiment, the wind control analysis module 408 is further configured to calculate, through each rule calculation engine cluster, a same wind control analysis rule, and perform wind control analysis on different resource exchange data sent in parallel to obtain a wind control analysis result; at least one rule calculation engine is included in the cluster of rule calculation engines.
In an embodiment, the wind control analysis module 408 is further configured to perform, through each rule calculation engine cluster, wind control analysis on the same resource exchange data sent in parallel by using the wind control analysis rule corresponding to each rule calculation engine cluster, so as to obtain a wind control analysis result; at least one rule calculation engine is included in the cluster of rule calculation engines.
In the wind control processing device, the resource exchange data sent by the client is obtained, the resource exchange data are classified under the preset classification dimensionality, the resource exchange data are respectively distributed to the rule calculation engines corresponding to the classes according to the classes to which the resource exchange data are classified, then the sent resource exchange data are subjected to wind control analysis in parallel through the rule calculation engines to obtain wind control analysis results, and the wind control analysis efficiency of the rule calculation engines is improved because the rule calculation engines can respectively perform wind control analysis in a targeted manner, so that the load of the rule calculation engines is reduced, and finally the resource exchange data corresponding to the wind control analysis results with risks are correspondingly processed, so that the efficiency of the whole wind control processing process can be improved. In addition, the method and the system load the service resources as required, and realize linear expansion of the wind control processing capacity. The computing capability expansion of the system is not influenced by software, and the computing capability of the whole system can be expanded only by expanding hardware equipment, so that the wind control analysis efficiency is improved. In many practical scenarios, one dealer often only needs one master server and one standby server to satisfy all data calculation functions.
For specific limitations of the wind control processing device, reference may be made to the above limitations of the wind control processing method, which are not described herein again. All or part of each module in the wind control processing device can be realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as shown in fig. 6. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is for storing resource exchange data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method of wind-controlled processing.
Those skilled in the art will appreciate that the architecture shown in fig. 6 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is further provided, which includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of the above method embodiments when executing the computer program.
In an embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when being executed by a processor, carries out the steps of the above-mentioned method embodiments.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database or other medium used in the embodiments provided herein can include at least one of non-volatile and volatile memory. Non-volatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical storage, or the like. Volatile Memory can include Random Access Memory (RAM) or external cache Memory. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A method of wind-controlled processing, the method comprising:
acquiring resource exchange data sent by a client;
classifying the resource exchange data under a preset classification dimension;
according to the classification of each resource exchange data, distributing each resource exchange data to a rule calculation engine corresponding to the classification;
performing wind control analysis on the resource exchange data sent in parallel through each rule calculation engine to obtain a wind control analysis result;
and correspondingly processing resource exchange data corresponding to the risk wind control analysis result.
2. The method of claim 1, further comprising:
according to a preset frequency, carrying out statistical analysis on historical resource exchange data acquired historically to obtain the activity degree of a user corresponding to the resource exchange data;
updating a routing strategy according to the activity degree; the routing strategy is a strategy for distributing the resource exchange data to a rule calculation engine;
the allocating, according to the category to which each of the resource exchange data is classified, each of the resource exchange data to the rule calculation engine corresponding to the category includes:
and according to the classification of each resource exchange data and the updated routing strategy, respectively allocating each resource exchange data to a rule calculation engine which corresponds to the classification and meets the routing strategy.
3. The method of claim 1, wherein classifying the resource exchange data in a preset classification dimension comprises:
under the data dimension, classifying the resource exchange data according to the data category to which the resource exchange data belongs;
the allocating, according to the category to which each of the resource exchange data is classified, each of the resource exchange data to the rule calculation engine corresponding to the category includes:
and respectively distributing the resource exchange data to a rule calculation engine corresponding to the data category according to the data category to which the resource exchange data is classified.
4. The method of claim 1, wherein classifying the resource exchange data in a preset classification dimension comprises:
under the user dimension, classifying the resource exchange data according to the user category to which the user corresponding to each resource exchange data belongs;
the allocating, according to the category to which each of the resource exchange data is classified, each of the resource exchange data to the rule calculation engine corresponding to the category includes:
and respectively distributing the resource exchange data to a rule calculation engine corresponding to the user category according to the user category to which the resource exchange data is classified.
5. The method of claim 1, wherein classifying the resource exchange data in a preset classification dimension comprises:
under the rule dimension, classifying the resource exchange data according to the complexity of a wind control analysis rule corresponding to each resource exchange data;
the allocating, according to the category to which each of the resource exchange data is classified, each of the resource exchange data to the rule calculation engine corresponding to the category includes:
and respectively distributing the resource exchange data to rule calculation engines corresponding to the rule classes according to the rule classes to which the resource exchange data are classified.
6. The method according to any one of claims 1 to 5, wherein the performing, by each of the rule calculation engines, a wind control analysis on the resource exchange data sent in parallel to obtain a wind control analysis result comprises:
respectively calculating an engine cluster through each rule, and performing wind control analysis on different resource exchange data sent to the engine cluster in parallel by adopting the same wind control analysis rule to obtain a wind control analysis result; the rule calculation engine cluster comprises at least one rule calculation engine.
7. The method according to any one of claims 1 to 5, wherein the performing, by each of the rule calculation engines, a wind control analysis on the resource exchange data sent in parallel to obtain a wind control analysis result comprises:
wind control analysis is carried out on the same resource exchange data sent in parallel by adopting wind control analysis rules respectively corresponding to each rule calculation engine cluster through each rule calculation engine cluster to obtain a wind control analysis result; the rule calculation engine cluster comprises at least one rule calculation engine.
8. A wind-controlled treatment device, characterized in that the device comprises:
the data acquisition module is used for acquiring resource exchange data sent by the client;
the classification module is used for classifying the resource exchange data under a preset classification dimension;
the data distribution module is used for respectively distributing the resource exchange data to the rule calculation engines corresponding to the categories according to the categories to which the resource exchange data are classified;
the wind control analysis module is used for carrying out wind control analysis on the resource exchange data sent by the rule calculation engines in parallel to obtain a wind control analysis result;
and the result processing module is used for correspondingly processing the resource exchange data corresponding to the risk wind control analysis result.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 7.
10. 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 of any one of claims 1 to 7.
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