CN110865804A - Rule engine optimization method, device, system and storage medium - Google Patents
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Abstract
The embodiment of the invention discloses a method, a device, a system and a storage medium for optimizing a rule engine, wherein an algorithm library is constructed in the rule engine, and an algorithm with complex algorithm logic and a complex mathematical calculation formula required in a business rule configuration process is introduced into the rule configuration process in the form of an algorithm package. On the aspect of rule configuration, the configuration mode of the optimization method can be used for quickly introducing an algorithm packet of a complex mathematical calculation formula to quickly realize complex algorithm logic; on the aspect of rule execution, by executing the optimization method, the RETE algorithm and the calculation formula can be merged with large granularity during operation, and the performance disadvantage caused by alternate execution is reduced; in the rule multiplexing layer, the accumulation of the algorithm library is realized by introducing the algorithm package, the algorithm can be quickly multiplexed in different rule configuration projects, and the workload of repeatedly configuring and repeatedly writing codes is reduced.
Description
Technical Field
The embodiment of the invention relates to the technical field of rule configuration, in particular to a method, a device and a system for optimizing a rule engine and a storage medium.
Background
The rules engine, developed from an inference engine, can separate business rules from application code and use predefined semantic modules to write business decisions, can receive data input, interpret business rules, and make business decisions based on the business rules. The existing commercial and open source rule engines can provide business rule design tools of types such as rule sets, decision tables, decision trees, score cards, rule flows and the like, and can provide a browser editing mode for visual business rule configuration. The existing open source and commercial rule engines basically adopt RETE algorithm or similar RETE algorithm, the RETE algorithm is a rapid pattern matching algorithm, and a rule set, a decision table, a decision tree and a score card in the rule engine all need to use the pattern matching algorithm to realize rapid business logic processing.
When the rule engine is applied to the configuration of business rules with complex algorithm logics and complex mathematical calculation formulas, a great deal of work of editing the mathematical calculation formulas is carried out through the rule engine, and the work is mixed in a rule configuration scene by combining the use of a rule set, a decision tree and the like. When the rule is executed, part of logic needs to go through the execution mode of the RETE algorithm, and part of logic needs to call the execution mode of the java (a common high-level programming language of a computer), and because the RETE algorithm and the mathematical calculation formula are inserted, the execution efficiency of the mode cannot achieve the optimal effect, and a large amount of CPU (Central processing Unit) resources are easily occupied due to the complexity of the logic. When complex algorithm logic and a rule model with a complex mathematical calculation formula need to be configured for multiple times, the rule model configured in the previous project cannot be quickly multiplexed, needs to be reconfigured once, and cannot be quickly multiplexed and quickly configured.
Disclosure of Invention
Therefore, embodiments of the present invention provide a method, an apparatus, a system, and a storage medium for optimizing a rule engine, so as to solve the problems that when the existing rule engine is applied to a business rule with a complex algorithm logic and a complex mathematical calculation formula, the rule configuration process is complex, the rule execution efficiency is low, and multiplexing cannot be achieved.
In order to achieve the above object, the embodiments of the present invention provide the following technical solutions:
according to a first aspect of the embodiments of the present invention, a method for optimizing a rule engine is provided, where the method includes:
an algorithm library is constructed in a rule engine, and a preset rule related algorithm packet is stored in the algorithm library;
and in the process of configuring the business rules, calling the rule related algorithm packet in the algorithm library according to the requirement to complete the configuration of the business rules.
Further, the algorithm library comprises a standard algorithm library module, a basic algorithm library module and a self-defined algorithm library module;
the standard algorithm library module is used for providing a standard mathematical algorithm package;
the basic algorithm library module is used for providing a common algorithm package for service level induction;
the self-defining algorithm library module is used for providing self-defining and expanding functions of the algorithm.
Further, the rule-dependent algorithm package supports a java algorithm package, an R algorithm package and a Python algorithm package.
Further, the algorithm library also comprises a visualization management module, and the visualization management module is used for providing visualization editing management functions of the algorithms, including new creation, deletion and export of the algorithms and modification of basic information of the algorithms.
Further, the algorithm basic information comprises an algorithm name, an algorithm description, an entry parameter, an exit parameter and a parameter definition.
According to a second aspect of the embodiments of the present invention, there is provided an optimization apparatus for a rules engine, the apparatus including:
the algorithm library module is used for constructing an algorithm library in the rule engine, and a preset rule-related algorithm package is stored in the algorithm library;
and the rule configuration module is used for calling the rule related algorithm packet in the algorithm library according to the requirement to complete the configuration of the business rule in the process of configuring the business rule.
Further, the algorithm library comprises a standard algorithm library module, a basic algorithm library module and a self-defined algorithm library module;
the standard algorithm library module is used for providing a standard mathematical algorithm package;
the basic algorithm library module is used for providing a common algorithm package for service level induction;
the self-defining algorithm library module is used for providing self-defining and expanding functions of the algorithm.
Further, the rule-dependent algorithm package supports a java algorithm package, an R algorithm package and a Python algorithm package.
According to a third aspect of an embodiment of the present invention, there is provided a system for optimizing a rule engine, the system including: a processor and a memory;
the memory is to store one or more program instructions;
the processor is configured to execute one or more program instructions to perform any one of the above method steps of the rule engine optimization method.
According to a fourth aspect of embodiments of the present invention, there is provided a computer storage medium having one or more program instructions embodied therein for execution by an optimization system of a rules engine to perform any one of the method steps of the above optimization method of the rules engine.
The embodiment of the invention has the following advantages:
according to the optimization method, device, system and storage medium of the rule engine provided by the embodiment of the invention, the algorithm library is constructed in the rule engine, and the algorithm with complex algorithm logic and complex mathematical calculation formula required in the business rule configuration process is introduced into the rule configuration process in the form of the algorithm package. On the aspect of rule configuration, the configuration mode of the optimization method can be used for quickly introducing an algorithm packet of a complex mathematical calculation formula to quickly realize complex algorithm logic; on the aspect of rule execution, by executing the optimization method, the RETE algorithm and the calculation formula can be merged with large granularity during operation, and the performance disadvantage caused by alternate execution is reduced; in the rule multiplexing layer, the accumulation of the algorithm library is realized by introducing the algorithm package, the algorithm can be quickly multiplexed in different rule configuration projects, and the workload of repeatedly configuring and repeatedly writing codes is reduced.
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 or the prior art will be briefly described below. It should be apparent that the drawings in the following description are merely exemplary, and that other embodiments can be derived from the drawings provided by those of ordinary skill in the art without inventive effort.
Fig. 1 is a schematic flowchart of a method for optimizing a rule engine according to embodiment 1 of the present invention;
fig. 2 is a schematic structural diagram of an optimization apparatus of a rule engine according to embodiment 2 of the present invention;
fig. 3 is a schematic structural diagram of an optimization system of a rule engine according to embodiment 3 of the present invention.
Detailed Description
The present invention is described in terms of particular embodiments, other advantages and features of the invention will become apparent to those skilled in the art from the following disclosure, and it is to be understood that the described embodiments are merely exemplary of the invention and that it is not intended to limit the invention to the particular embodiments disclosed. 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.
Example 1
As shown in fig. 1, the present embodiment provides a method for optimizing a rule engine, where the method includes:
Specifically, the algorithm library comprises a standard algorithm library module, a basic algorithm library module and a self-defined algorithm library module, wherein the standard algorithm library module is used for providing a standard mathematical algorithm package; the basic algorithm library module is used for providing a common algorithm package for service level induction; the self-defining algorithm library module is used for providing self-defining and expanding functions of the algorithm.
An example of a standard algorithm: in morton adjustment of the default probability, a systematic risk factor R needs to be calculated, and the formula is:
it can be seen that the R formula requires PD parameters and various coefficients, such as 1.25, 0.12, 0.24, 50, etc., and the coefficients used by different service lines may be different, and by encapsulating the coefficients into a parameter class, there are two parameters, PD and parameter class, and the metering engine and other algorithms can invoke the calculation algorithm of the R formula by setting the two parameters. The default value of the coefficient can be set in the data model definition of the metering engine, and the value of the coefficient is changed in parameter mapping only when the coefficient is different, so that the purpose of flexibly adapting to the calculation of each line is achieved.
Basic algorithm example: for example, in risk management, morton adjustment of the default probability PD of a certain line is performed by combining a macro factor in a quarterly manner, and such a business-related algorithm is generally classified into a basic algorithm. The calculation formula is as follows:
the algorithm requires that the probability of the original default probability is calculated, and the adjusted default probability is calculated by Morton adjustment through combining the Wilson formula of the macroscopic factor and the R formula of the default probability. The standard algorithm encapsulates the entire process into an algorithm, loops by quarter, and calculates the morton adjusted values of the default probabilities for all quarters. By packaging the cycle into the algorithm, the speed of the whole calculation process can be effectively improved, and the defect of low performance of a large number of calling nodes caused by the cycle configuration in the rule engine is avoided.
Example of custom algorithm: for example, in the morton adjustment algorithm, the sequence of the default probability and the sequence of the macroscopic factor need to be matched one by one, because the length and the time of the PD sequence are different from those of the macroscopic factor, the processing logic needs to be encapsulated into an algorithm, and the algorithm can be encapsulated into a custom algorithm class because the processing logic is unrelated to the core service logic.
Furthermore, by introducing an algorithm component, the rule-related algorithm package supports a java algorithm package, an R algorithm package and a Python algorithm package, and the algorithm packages of different computer language types can be called as required.
Further, the algorithm library also comprises a visualization management module, and the visualization management module is used for providing visualization editing management functions of the algorithms, including new creation, deletion and export of the algorithms and modification of basic information of the algorithms. The algorithm basic information comprises an algorithm name, an algorithm description, an entry parameter, an exit parameter, a parameter definition and the like.
And step 120, in the process of configuring the service rule, calling a rule-related algorithm packet in the algorithm library according to the requirement to complete the configuration of the service rule.
After the configuration of the rule algorithm packet is completed in the algorithm library, the corresponding algorithm packet in the algorithm library can be directly and quickly called at the position where the complex mathematical formula needs to be introduced in the configuration process of the business rule corresponding to the business, so that the method is convenient and quick, and quick configuration and quick multiplexing can be realized.
The optimization method of the rule engine provided by the embodiment of the invention introduces the algorithm with complex algorithm logic and complex mathematical calculation formula required in the business rule configuration process into the rule configuration process in the form of the algorithm package by constructing the algorithm library in the rule engine, and has the following advantages:
(1) on the aspect of rule configuration, the configuration mode of the optimization method can be used for quickly introducing an algorithm packet of a complex mathematical calculation formula to quickly realize complex algorithm logic;
(2) on the aspect of rule execution, by executing the optimization method, the RETE algorithm and the calculation formula can be merged with large granularity during operation, and the performance disadvantage caused by alternate execution is reduced;
(3) in the rule multiplexing layer, the accumulation of the algorithm library is realized by introducing the algorithm package, the algorithm can be quickly multiplexed in different rule configuration projects, and the workload of repeatedly configuring and repeatedly writing codes is reduced.
Example 2
Corresponding to the above embodiment 1, an embodiment of the present invention provides an optimization apparatus for a rule engine, as shown in fig. 2, the apparatus including:
and the algorithm library module 210 is used for constructing an algorithm library in the rule engine, and the algorithm library stores a preset rule-related algorithm package.
And the rule configuration module 220 is configured to invoke a rule-related algorithm package in the algorithm library according to a requirement in the service rule configuration process to complete service rule configuration.
Further, the algorithm library comprises a standard algorithm library module, a basic algorithm library module and a self-defined algorithm library module, wherein the standard algorithm library module is used for providing a standard mathematical algorithm package; the basic algorithm library module is used for providing a common algorithm package for service level induction; the self-defining algorithm library module is used for providing self-defining and expanding functions of the algorithm. Further, the rule-dependent algorithm package supports a java algorithm package, an R algorithm package, and a Python algorithm package.
The functions executed by each component in the optimization apparatus for a rule engine provided in the embodiment of the present invention are described in detail in embodiment 1 above, and therefore, redundant description is not repeated here.
The optimization device of the rule engine provided by the embodiment of the invention introduces the algorithm with complex algorithm logic and complex mathematical calculation formula required in the business rule configuration process into the rule configuration process in the form of the algorithm package by constructing the algorithm library in the rule engine, and has the following advantages:
(1) on the aspect of rule configuration, the configuration mode of the optimization method can be used for quickly introducing an algorithm packet of a complex mathematical calculation formula to quickly realize complex algorithm logic;
(2) on the aspect of rule execution, by executing the optimization method, the RETE algorithm and the calculation formula can be merged with large granularity during operation, and the performance disadvantage caused by alternate execution is reduced;
(3) in the rule multiplexing layer, the accumulation of the algorithm library is realized by introducing the algorithm package, the algorithm can be quickly multiplexed in different rule configuration projects, and the workload of repeatedly configuring and repeatedly writing codes is reduced.
Example 3
In correspondence with the above embodiments, the present embodiment proposes an optimization system of a rule engine, as shown in fig. 3, the system including: a processor 310 and a memory 320;
a processor 310 for executing one or more program instructions for performing any of the method steps of the above method for rule engine optimization.
The optimization system of the rule engine provided by the embodiment of the invention introduces the algorithm with complex algorithm logic and complex mathematical calculation formula required in the business rule configuration process into the rule configuration process in the form of the algorithm package by constructing the algorithm library in the rule engine, and has the following advantages:
(1) on the aspect of rule configuration, the configuration mode of the optimization method can be used for quickly introducing an algorithm packet of a complex mathematical calculation formula to quickly realize complex algorithm logic;
(2) on the aspect of rule execution, by executing the optimization method, the RETE algorithm and the calculation formula can be merged with large granularity during operation, and the performance disadvantage caused by alternate execution is reduced;
(3) in the rule multiplexing layer, the accumulation of the algorithm library is realized by introducing the algorithm package, the algorithm can be quickly multiplexed in different rule configuration projects, and the workload of repeatedly configuring and repeatedly writing codes is reduced.
Example 4
In accordance with the above embodiments, the present embodiments provide a computer storage medium having one or more program instructions embodied therein for execution by an optimization system of a rules engine to perform any of the method steps of the above optimization method of the rules engine.
Although the invention has been described in detail above with reference to a general description and specific examples, it will be apparent to one skilled in the art that modifications or improvements may be made thereto based on the invention. Accordingly, such modifications and improvements are intended to be within the scope of the invention as claimed.
Claims (10)
1. A method for optimizing a rules engine, the method comprising:
an algorithm library is constructed in a rule engine, and a preset rule related algorithm packet is stored in the algorithm library;
and in the process of configuring the business rules, calling the rule related algorithm packet in the algorithm library according to the requirement to complete the configuration of the business rules.
2. The method for optimizing a rules engine of claim 1, wherein the algorithm library comprises a standard algorithm library module, a basic algorithm library module and a custom algorithm library module;
the standard algorithm library module is used for providing a standard mathematical algorithm package;
the basic algorithm library module is used for providing a common algorithm package for service level induction;
the self-defining algorithm library module is used for providing self-defining and expanding functions of the algorithm.
3. The method of claim 1, wherein the rule-dependent algorithm package supports java, R, and Python algorithm packages.
4. The method of claim 1, wherein the algorithm library further comprises a visualization management module, and the visualization management module is configured to provide a visualization editing management function for the algorithm, including creation, deletion, and export of the algorithm and modification of basic information of the algorithm.
5. The method of claim 4, wherein the algorithm basic information comprises an algorithm name, an algorithm description, an entry parameter, an exit parameter, and a parameter definition.
6. An apparatus for optimizing a rules engine, the apparatus comprising:
the algorithm library module is used for constructing an algorithm library in the rule engine, and a preset rule-related algorithm package is stored in the algorithm library;
and the rule configuration module is used for calling the rule related algorithm packet in the algorithm library according to the requirement to complete the configuration of the business rule in the process of configuring the business rule.
7. The optimization device of the rule engine as claimed in claim 6, wherein the algorithm library comprises a standard algorithm library module, a basic algorithm library module and a custom algorithm library module;
the standard algorithm library module is used for providing a standard mathematical algorithm package;
the basic algorithm library module is used for providing a common algorithm package for service level induction;
the self-defining algorithm library module is used for providing self-defining and expanding functions of the algorithm.
8. The apparatus of claim 6, wherein the rule-dependent algorithm package supports java, R, and Python algorithm packages.
9. A system for optimizing a rules engine, the system comprising: a processor and a memory;
the memory is to store one or more program instructions;
the processor, configured to execute one or more program instructions to perform the method of any of claims 1-5.
10. A computer storage medium comprising one or more program instructions for execution by an optimization system of a rules engine to perform the method of any one of claims 1-5.
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