CN111858062A

CN111858062A - Evaluation rule optimization method, service evaluation method and related equipment

Info

Publication number: CN111858062A
Application number: CN202010729231.1A
Authority: CN
Inventors: 周剑
Original assignee: Ping An Property and Casualty Insurance Company of China Ltd
Current assignee: Ping An Property and Casualty Insurance Company of China Ltd
Priority date: 2020-07-27
Filing date: 2020-07-27
Publication date: 2020-10-30

Abstract

The invention relates to the technical field of data processing, and discloses an evaluation rule optimization method, a service evaluation method and related equipment, wherein the method comprises the steps of slicing an evaluation rule in a system through a preset rule fragmentation processing algorithm to obtain a plurality of task fragments, and then distributing the task fragments to different processing units for execution, so that the pressure of a server on service audit is reduced, the utilization rate of processor resources in a service system is also improved, the service processing efficiency is improved, and the backlog of service data is reduced; furthermore, asynchronous control is adopted among the processing units for executing the task fragments, the processing units can independently and simultaneously run without influencing each other, and the execution time of the rules is further shortened, so that the time length of service auditing is shortened, and the auditing and checking efficiency is improved. In addition, the invention also relates to a block chain technology, and the task fragments obtained by slicing can be stored in the block chain.

Description

Evaluation rule optimization method, service evaluation method and related equipment

Technical Field

The invention relates to the technical field of data processing, in particular to an evaluation rule optimization method, a service evaluation method and related equipment.

Background

With the development of scientific and technological economy, particularly the rapid development of social economy, particularly the development of enterprises, due to the requirement of enterprise development, a large amount of reimbursement, tax return and other services are indispensable part of services, and in order to facilitate the operation of the process in the enterprise or the enterprise, a large number of process systems are developed, but the process systems are basically one-stop auditing operations for the process auditing processes of reimbursement and tax return, the consumed duration of the process is reasonable under the condition of a small number of services, but under the condition of a sharp increase of the number of services, if the execution scheme is continuously executed according to the conventional designed rule engine, the execution efficiency cannot necessarily meet the daily requirements of the services, data backlog is more likely to be caused, and the whole system is more likely to be crashed due to overlarge server pressure.

In this regard, the currently adopted method is to perform processing in different time periods, or to solve the problem by replacing or adding hardware device configurations, but such a method has not very obvious effect, and especially, the method of replacing or adding devices also increases the cost, and even causes influence which is difficult to ignore in system safety.

Disclosure of Invention

The invention mainly aims to provide an evaluation rule optimization method, a service evaluation method and related equipment, and aims to solve the technical problem of low service auditing efficiency in the prior art.

The first aspect of the present invention provides an evaluation rule optimization method, including:

when a business data evaluation request is received, calling a rule engine interface to acquire an evaluation rule stored in the business processing equipment, wherein the evaluation rule is an auditing flow rule for evaluating input business data to be evaluated;

slicing the evaluation rule according to a preset rule fragmentation processing algorithm to obtain at least two task fragments;

and distributing at least two task fragments to at least two evaluation units, and controlling all the evaluation units to asynchronously operate and execute the corresponding task fragments so as to realize the evaluation processing of the service data to be evaluated.

Optionally, in a first implementation manner of the first aspect of the present invention, the slicing the evaluation rule according to a preset rule fragmentation processing algorithm to obtain at least two task fragments includes:

analyzing the auditing process node of the evaluation rule, and drawing a tree-shaped graph based on the analyzed auditing process node;

according to a task granularity completion rule, performing node classification on the dendrogram by using a linear regression model to obtain at least two node sets, wherein nodes contained in each node set are connected with the same father node;

and slicing the evaluation rule based on the node set to obtain task fragments with the same number as the node set, and establishing a parent-child association relationship among the task fragments.

Optionally, in a second implementation manner of the first aspect of the present invention, the distributing at least two task fragments to at least two evaluation units, and controlling all evaluation units to asynchronously run and execute corresponding task fragments includes:

calling the same number of evaluation units according to the number of the task fragments, and sequencing the evaluation units according to the execution priority;

and sequentially distributing the sequence of the task fragments from parent to child to the sequenced evaluation units according to the parent-child association relationship, controlling the evaluation units to execute the task fragments in an asynchronous execution mode, wherein the evaluation unit with higher priority preferentially receives the task fragments in the parent relationship.

Optionally, in a third implementation manner of the first aspect of the present invention, the controlling the evaluation unit to execute the task fragment in an asynchronous execution manner includes:

calculating the time length required by the task fragment to finish executing in the evaluation unit;

judging whether the time length is greater than a preset time value or not;

and if so, performing multi-thread operation on the task fragment, wherein the multi-thread operation is an asynchronous operation thread.

Optionally, in a fourth implementation manner of the first aspect of the present invention, the performing multi-thread running on the task fragment includes:

calculating the total number of threads required for reducing the time length to half of the preset time value;

according to the total number of the threads, the task fragments are refined into a plurality of task fragments;

and starting threads matched with the total number of the threads through a thread pool, and controlling the threads to execute asynchronously, wherein each thread executes at least one task slice.

A second aspect of the present invention provides a service evaluation method, where the service evaluation method includes:

acquiring service data to be evaluated and an evaluation rule corresponding to the service data to be evaluated, wherein the evaluation rule is an audit process rule processed according to the provided evaluation rule optimization method;

slicing the service data to be evaluated according to the evaluation rule to obtain at least two data fragments;

extracting a key field and a factor in each data fragment, wherein the key field is a data item to be evaluated in the data fragment, and the factor is an audit rule description of the data item;

inquiring a corresponding evaluation unit from a rule search engine on the business processing equipment according to the key field and the factor;

and sending at least two data fragments to corresponding evaluation units for evaluation, and outputting evaluation results.

A third aspect of the present invention provides an evaluation rule optimization device, including:

the rule calling module is used for calling a rule engine interface to acquire an evaluation rule stored in the business processing equipment when a business data evaluation request is received, wherein the evaluation rule is an auditing flow rule for evaluating input business data to be evaluated;

the fragmentation processing module is used for carrying out slicing processing on the evaluation rule according to a preset rule fragmentation processing algorithm to obtain at least two task fragments;

and the rule execution module is used for distributing at least two task fragments to at least two evaluation units and controlling all the evaluation units to asynchronously operate and execute the corresponding task fragments so as to realize the evaluation processing of the service data to be evaluated.

Optionally, in a first implementation manner of the third aspect of the present invention, the fragmentation processing module includes:

the drawing unit is used for analyzing the auditing process node of the evaluation rule and drawing a tree-like graph based on the analyzed auditing process node;

the classification unit is used for performing node classification on the dendrogram by using a linear regression model according to task granularity completion rules to obtain at least two node sets, wherein the nodes contained in each node set are connected with the same father node;

and the cutting unit is used for slicing the evaluation rule based on the node set to obtain task fragments with the same number as the node set, and establishing a parent-child association relationship among the task fragments.

Optionally, in a second implementation manner of the third aspect of the present invention, the rule execution module includes:

the sequencing unit is used for calling the same number of evaluation units according to the number of the task fragments and sequencing the evaluation units according to the execution priority;

and the task distribution unit is used for sequentially distributing the sequence of the task fragments from the father to the son to the sequenced evaluation units according to the father-son association relationship and controlling the evaluation units to execute the task fragments in an asynchronous execution mode, wherein the evaluation unit with a high priority preferentially receives the task fragments in the father relationship.

Optionally, in a third implementation manner of the third aspect of the present invention, the task distributing unit is specifically configured to:

judging whether the time length is greater than a preset time value or not;

Optionally, in a fourth implementation manner of the second aspect of the present invention, the task distribution unit is specifically configured to:

A fourth aspect of the present invention provides a service processing apparatus, including: an evaluation device and at least one evaluation rule optimization device as described above, wherein:

the evaluation device is used for acquiring service data to be evaluated and an evaluation rule corresponding to the service data to be evaluated; slicing the service data to be evaluated according to the evaluation rule to obtain at least two data fragments; extracting a key field and a factor in each data fragment, wherein the key field is a data item to be evaluated in the data fragment, and the factor is an audit rule description of the data item; inquiring a corresponding evaluation unit from a rule search engine on the business processing equipment according to the key field and the factor; and sending at least two data fragments to corresponding evaluation units for evaluation, and outputting an evaluation result, wherein the evaluation rule is an audit process rule processed according to the evaluation rule optimization method executed by the evaluation rule optimization device.

A fifth aspect of the present invention provides a service processing apparatus, including: a memory having instructions stored therein and at least one processor, the memory and the at least one processor interconnected by a line;

the at least one processor invoking the instructions in the memory to cause the business processing device to perform the evaluation rule optimization method of any of the above;

alternatively, the first and second electrodes may be,

the at least one processor invokes the instructions in the memory to cause the business processing device to perform the business evaluation method as described above.

A sixth aspect of the present invention provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the evaluation rule optimization method according to any one of the above;

alternatively, the first and second electrodes may be,

which when executed by a processor implements the steps of the traffic assessment method as described above.

According to the technical scheme provided by the invention, the evaluation rules are fragmented and distributed to the plurality of evaluation units for execution, so that the dependence of the evaluation rules on a single evaluation unit is reduced, the overall execution time of the rules is shortened by times, the auditing efficiency is greatly improved when the business is audited, and the data backlog phenomenon of the system under the condition of large data volume is avoided.

Drawings

FIG. 1 is a schematic diagram of a first embodiment of an evaluation rule optimization method according to an embodiment of the present invention;

FIG. 2 is a diagram of a second embodiment of an evaluation rule optimization method according to an embodiment of the present invention;

FIG. 3 is a schematic diagram of a tree in an embodiment of the present invention;

FIG. 4 is another schematic diagram of a tree in an embodiment of the present invention;

FIG. 5 is a diagram illustrating a process performed on task fragments according to an embodiment of the present invention;

fig. 6 is a schematic diagram of an embodiment of a service evaluation method according to an embodiment of the present invention;

FIG. 7 is a schematic diagram of an embodiment of an evaluation rule optimization apparatus according to an embodiment of the present invention;

FIG. 8 is a schematic diagram of another embodiment of an evaluation rule optimization apparatus according to an embodiment of the present invention;

FIG. 9 is a diagram of an embodiment of a service processing device in an embodiment of the present invention;

fig. 10 is a schematic diagram of another embodiment of a service processing device in the embodiment of the present invention.

Detailed Description

The embodiment of the invention provides a blocking auditing scheme, which can solve the problem of data accumulation caused by low processing efficiency of the existing business auditing process, and mainly aims at an optimizing method of auditing rules in a business processing system; furthermore, asynchronous control is adopted among the processing units for executing the task fragments, the processing units can independently and simultaneously run without influencing each other, and the execution time of the rules is further shortened, so that the time length of service auditing is shortened.

The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that the embodiments described herein may be practiced otherwise than as specifically illustrated or described herein. Furthermore, the terms "comprises," "comprising," or "having," and any variations thereof, are intended to cover non-exclusive inclusions, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

For understanding, a specific flow of the embodiment of the present invention is described below, and referring to fig. 1, an embodiment of the evaluation rule optimization method in the embodiment of the present invention includes:

101. when a service data evaluation request is received, calling a rule engine interface to acquire an evaluation rule stored in service processing equipment;

in this step, the evaluation rule is an audit process rule for evaluating the input service data to be evaluated, and may be understood as the service data itself or an audit rule for auditing the service data.

Optionally, the selection is an audit rule, but the processing mode when selecting the service data is the same as the processing mode of the audit rule. When a business data evaluation request is received, extracting a corresponding evaluation rule from a business processing system according to the type of the business data required to be evaluated in the request.

In this embodiment, when extracting the evaluation rule, the evaluation rule may be invoked according to a correspondence between an interface and a type, first identify a type of the service data from the request, query and determine a corresponding interface through a correspondence between a preset rule engine interface and the type based on the type, and extract the corresponding evaluation rule by invoking the interface; in practical application, each service is assigned with a unique docking interface, the interface is connected with a rule base for calling corresponding service auditing rules, and the rules corresponding to the services can be acquired through the interfaces.

102. Slicing the evaluation rule according to a preset rule fragmentation processing algorithm to obtain at least two task fragments;

in this embodiment, the preset rule fragmentation processing algorithm refers to a fragmentation technique for a rule of an audit service, for example, a rule execution granularity refers to a minimization unit of data, such as a relationship between a data set and a data element, and the data element may be understood as a rule execution granularity; in practical applications, it can also be understood as a minimum execution subject, for example, a business audit process includes multiple audit nodes, and each node completes a staged audit, and a complete business audit process is obtained by linking all staged audits. Correspondingly, the business rules are the same, and one business rule is an audit rule comprising a plurality of stages, and the execution subject of each stage is different. And performing staged segmentation on the evaluation rules based on different execution subjects, and outputting fragments of the rules (namely the task fragments).

In this embodiment, when the evaluation rule is segmented, the segmentation may be performed according to actual requirements, and how many times the rule fragmentation processing algorithm is executed may be determined according to the actual duration of the evaluation rule. If the received service data evaluation request carries a requirement on the time of the evaluation examination, the execution of the algorithm needs to be adjusted according to the time requirement in the request, for example, the algorithm is executed for multiple times to realize fragmentation processing on the evaluation rule, and when the time required for completing the execution of the evaluation rule is several times of the requirement, the execution times of the algorithm needs to be adjusted according to the several times of the value, the evaluation rule is sequentially segmented based on the execution times, and the object for executing the segmentation each time is the evaluation rule fragment obtained after the last segmentation is completed.

In practical application, in order to ensure the integrity of the task fragment and avoid malicious modification, the obtained task fragment may be stored in a block chain, and then, when performing evaluation, the task fragment is called from the block chain and distributed to each evaluation unit to perform evaluation.

103. And distributing at least two task fragments to at least two evaluation units, and controlling all the evaluation units to asynchronously operate and execute the corresponding task fragments so as to realize the evaluation processing of the service data to be evaluated.

In this step, the evaluation unit may be understood as a server, and before distributing the task fragments, the method further includes selecting a corresponding evaluation unit according to the specific number of the task fragments, and then sending the task fragments one by one to the corresponding evaluation unit for execution, where sending the task fragments one by one refers to that the task fragments executed by each evaluation unit are different.

In this embodiment, while distributing to the execution of the evaluation units, the method further includes setting the running time point of each evaluation unit, optionally, the time point is set in an asynchronous running mode, and based on setting the running time points of all the evaluation units as the same time point, that is, running in parallel, the execution time for completing one evaluation rule becomes the time of a single evaluation unit, and is not the sum of the times of all the evaluation units, thereby greatly shortening the running time of the rule and improving the utilization rate of the evaluation units in the system.

In practical application, when selecting the evaluation unit, the evaluation unit which is in an idle state in the system and supports the task fragment with a low execution time and low occupied power is selected according to the working state, the working time and the occupied proportion of power of each evaluation unit, wherein the occupied proportion is the occupied proportion relative to the total power consumption of a processor of the system, and the evaluation unit which is in an idle state in the system and supports the task fragment with a low execution time and occupied power is selected according to the evaluation completion time point required in the request.

By executing the method, the evaluation rules are fragmented and distributed to the plurality of evaluation units for execution, so that the dependence of the rules on a single processing unit is reduced, the overall execution time of the rules is shortened by times, the auditing efficiency is greatly improved during business auditing, and the data backlog phenomenon of a system under the condition of large data volume is avoided.

Referring to fig. 2, another embodiment of the evaluation rule optimization method according to the embodiment of the present invention includes:

201. when a service data evaluation request is received, calling a rule engine interface to acquire an evaluation rule stored in service processing equipment;

202. analyzing the auditing process node of the evaluation rule, and drawing a tree-shaped graph based on the analyzed auditing process node;

203. according to a task granularity completion rule, performing node classification on the dendrogram by using a linear regression model to obtain at least two node sets;

in this step, the nodes included in each node set are all connected to the same father node, specifically, when a linear regression model is used to draw a dendrogram of nodes in an audit process, regression calculation is performed on distances between the nodes on the dendrogram by using a linear regression algorithm.

As shown in fig. 3 and 4, the audit rule is first sorted from the perspective of the whole to obtain the graph in fig. 3, and the flow nodes are calculated by using a linear regression algorithm, the last audit node on one branch is first selected to establish a linear straight line with the parent node, based on the linear straight line, the distance between the peripheral flow nodes on the molecule and the straight line is calculated, and if the distance satisfies the condition, the flow nodes are classified as the nodes on the straight line.

Further, after the branch node set on the parent node is calculated, whether other molecules exist in the nodes on the molecule node set can be calculated, as shown in fig. 4, the classification method is the same as that of fig. 3, and repeated description is omitted here, so that classification calculation is performed layer by layer to obtain more detailed task fragments (namely, rule fragments), and then the task fragments are redistributed to evaluation units of different levels to be executed as the auditing rules of the evaluation units, thereby realizing fragmentation of the rules, reducing the overall control pressure of the processor, and greatly improving the final auditing efficiency of the service.

204. Slicing the evaluation rule based on the node set to obtain task fragments with the same number as the node set, and establishing a parent-child association relationship among the task fragments;

in this embodiment, for a rule fragmentation processing algorithm, a preferred selection is an execution granularity of a rule, where the rule execution granularity may be understood as an auditor when the rule is executed, and for a system, the auditor is a node of a process, generally, a business audit process includes a plurality of sub-processes, and each sub-process is provided with an auditor, and in an audit process, each auditor is only responsible for auditing its corresponding process, so that it can be seen that a complete evaluation rule can be partitioned according to different audit nodes.

In this embodiment, after obtaining the corresponding evaluation rule according to the type of the service data, the evaluation rule is analyzed, where the analysis refers to analyzing and extracting the audit nodes in the evaluation rule, and then in order to facilitate viewing and dividing, after extracting the audit nodes, the audit nodes are classified, and a dendrogram of the audit nodes is drawn, where the dendrogram may be drawn according to a sequence of the audit nodes, where the sequence refers to a sequence of the evaluation rule executed based on an execution manner in the prior art, and is not a sequence in the present application, and the audit nodes in the present application do not have a sequence relationship, and after drawing the dendrogram, the classification of the audit nodes is realized by marking the audit nodes in the dendrogram based on the marking.

In practical application, in the process of drawing the dendrogram, the audit nodes can be classified first, and then the dendrogram is drawn based on the classified audit nodes, and during classification, a mode based on a father node can be specifically selected for classification, that is, all child nodes connected to the same father node are classified into one class.

205. And distributing at least two task fragments to at least two evaluation units, and controlling all the evaluation units to asynchronously operate and execute the corresponding task fragments so as to realize the evaluation processing of the service data to be evaluated.

In practical application, in order to further improve the execution efficiency of the rules, the task fragments are specifically set according to the time limit required by the client, and may even be set according to the specific number of servers (evaluation units) that can be executed in the business processing system at the current time.

In practical application, when the evaluation rule is sliced, the evaluation rule may be further segmented according to the dimensionalities of an execution mechanism, an audit type and the like, for example, in an reimbursement system, the evaluation rule may be segmented according to the rule execution granularity, and the evaluation rule may be segmented according to the dimensionalities of an organization to which the reimbursement slip belongs, a cost type and the like. .

In the embodiment of the invention, the evaluation rules in the system are sliced according to the preset rule fragmentation processing algorithm to obtain a plurality of task fragments, and then the task fragments are distributed to different processing units for execution, so that the pressure of a server on service audit is reduced, the utilization rate of processor resources in a service system is also improved, the service processing efficiency is improved, the backlog of service data is reduced, the time length of service audit is shortened, and the audit efficiency is improved.

In this embodiment, after the task fragments are obtained based on the above manner, in the process of selecting the corresponding evaluation units to execute according to the task fragments in step 205, when the number of the evaluation units is called, the evaluation units may be selected according to the time for executing the task fragments, as specifically shown in fig. 5:

2051. calling the same number of evaluation units according to the number of the task fragments, and sequencing the execution priority of the evaluation units;

in practical application, the evaluation unit may be understood as a server or may be understood as a complete rule executor, and when the evaluation unit is selected, a corresponding number of rule executors are selected from a rule executor library according to the number of task fragments, and specifically, the rule executors may be selected according to the type of the service data; further, the selection can be realized according to a calling interface of the rule.

In this embodiment, after the evaluation units are selected, the task fragments are sequentially sent to the corresponding evaluation units for execution, and during sending, if the number of the selected evaluation units is the same as the number of the task fragments, each evaluation unit is assigned with one task fragment; and if the number of the evaluation units is smaller than the number of the task fragments, selecting whether to distribute a plurality of task fragments or one task fragment according to the execution capacity of the evaluation units, wherein the specific distribution number is calculated according to the maximum support amount of the execution capacity.

Further, in this embodiment, before the task fragment is sent down, the evaluation units may be further prioritized, and the ranking may be performed according to the execution capacity of the evaluation units, or may be performed according to the level of the execution power of the evaluation units themselves, the task fragments are sequentially distributed based on the priorities, then all the evaluation units are controlled in an asynchronous control manner to start execution on the task fragment based on the same time point, in practical application, when the service data is evaluated by using the evaluation rule, the same is true, after the service data is obtained, the service data is respectively sent to the evaluation units used by the evaluation rule, then all the evaluation units are started to the same, and part of data corresponding to the task fragment in the service data is selected to be evaluated.

2052. Calculating the time length required by the task fragment to finish executing in the evaluation unit;

2053. judging whether the time length is greater than a preset time value or not;

2054. and if so, performing multi-thread operation on the task fragment, wherein the multi-thread operation is an asynchronous operation thread.

In practical application, each evaluation unit further includes a thread pool, that is, when the evaluation unit (i.e., a server) executes a task fragment, the evaluation unit is substantially controlled by a thread, and one thread can execute a complete task fragment, but the evaluation unit can also execute a plurality of threads, at this time, for starting multithreading, further splitting processing needs to be performed on the task fragment, and the splitting processing can be performed directly according to an audited node, or certainly, a manner of binding a plurality of audited nodes can be selected to split, specifically, how to split is calculated according to completion time required in a request.

In this embodiment, the above-mentioned time length refers to a time length consumed by one thread to execute the task fragment, and if the time length is greater than a specified time value, then multiple threads are selected to execute the task fragment, where the specified time value (i.e. the preset time value) should be understood as the longest running time of the evaluation unit, for example: in the current time period, the idle time period of the evaluation unit is set to be 1 minute by the system, other tasks need to be executed by the evaluation unit after 1 minute, the evaluation unit is called in the application to temporarily execute the task fragment, the task fragment needs to be completed within 1 minute, and if the time length of execution of one thread is longer than the time length of 1 minute, the multi-thread execution is selected.

Further, before the step 2052, the method further includes: in practical application, when distributing the task fragments, the task fragments in the parent relation in the task fragment set are distributed to the evaluation unit with the highest priority in the evaluation unit to be executed, then the rest fragment tasks are distributed to the rest evaluation units in sequence according to the precedence relation from the parent to the child, and when the task fragments are distributed to the evaluation units, the task fragments are distributed according to the priority of the evaluation units from high to low, so that the execution sequence of the fragments can be ensured, and the efficiency of the evaluation units for processing the task fragments can also be ensured.

In this embodiment, the performing multi-thread running on the task fragment includes:

In practical application, when the multi-thread execution of the task fragment is started, the number of specifically started threads is specifically selected according to a time requirement, the setting of the threads is specifically set according to half or less than half of a preset time value, and then the task fragment is subjected to secondary segmentation according to the setting of the threads, so that the matching of the task fragment and the threads is realized.

Furthermore, the thread pool is controlled to start the threads to execute the split task pieces, and all the threads in the thread pool are changed into asynchronous thread tasks in an asynchronous mode for starting control of the threads when the task pieces are executed, so that simultaneous execution of the task pieces is realized, and the execution time of the evaluation rules is further shortened.

For example, in the evaluation of the reimbursement bill, the number of the reimbursement bills executed is generally large, and the service has 8 servers, and if the service is not subjected to granularity division, the service is executed on only one server; through parameter configuration, all data to be run are divided into smaller pieces according to different parameters (such as organization levels, organization areas and expense types), and then through a task scheduling platform, the divided task pieces are subjected to task allocation according to the load conditions of the 8 servers, so that a plurality of servers can execute simultaneously, and the execution efficiency is improved.

In the above, the task fragments are allocated to a plurality of servers for processing, which improves the execution efficiency at the scheduling level. Specifically, on each server, the task can be further refined into a plurality of threads to be processed concurrently, for example, one task piece allocated to the server has 100 reimbursement tickets, and if one thread needs 1 second for processing one reimbursement ticket, one thread needs 100 seconds to be processed; that is, if 10 threads are used for parallel processing through the thread pool, each thread processes 10 threads, i.e., about 10 seconds can be processed to complete

In this embodiment, since the calling of the evaluation rule needs to be performed differently according to different service data, in order to improve the calling efficiency of the evaluation rule, after the distributing at least two task fragments to at least two evaluation units for execution, the method further includes:

extracting a rule keyword of each task fragment, and establishing a corresponding relation between the rule keyword and an evaluation unit executing the task fragment;

and synchronizing the corresponding relation to a rule search engine on the business processing system.

In this embodiment, the scheme mainly synchronizes the evaluation rule after segmentation to a search engine on a service system, so that when the service uses the rule, the rule can be called quickly to perform audit processing on service data.

Further, after the fragmentation of the service rule is completed by the above embodiment, a service audit process is executed, and the service data is distributed to the corresponding evaluation unit to implement corresponding audit, where a specific process is shown in fig. 6:

601. acquiring service data to be evaluated and an evaluation rule corresponding to the service data to be evaluated;

the evaluation rule is an audit process rule processed according to the provided business rule optimization method.

602. Slicing the service data to be evaluated according to the evaluation rule to obtain at least two data fragments;

603. extracting a key field and a factor in each data fragment, wherein the key field is a data item to be evaluated in the data fragment, and the factor is an audit rule description of the data item;

604. inquiring a corresponding evaluation unit from a rule search engine on the business processing system according to the key field and the factor;

605. and sending at least two data fragments to corresponding evaluation units for evaluation, and outputting evaluation results.

In this embodiment, the key fields are some data-specific dimensions in the rules, such as employee type, organization type, department number, and the like; while the factor is composed of key fields, different rules may use the same key field, such as factor 1 "department even" and factor 2 "department odd". These 2 factors all use the key field "department number"; the rule is composed of a plurality of factors through a series of logical relation operations, and it can be understood that the rule is composed of a series of condition items through logical relations, the factors are descriptions of some data items, and the key fields are data items. The query efficiency of the optimized factor and field value is improved by storing the factor field related to the rule of the reimbursement bill into the elastic search engine.

When the evaluation rule is used for evaluating the business data, in order to improve the evaluation efficiency of the business data, the business data needs to be segmented according to the evaluation rule; of course, the service data may be directly shared to each evaluation unit without being split, and the evaluation units themselves screen the service data.

In this embodiment, the business data evaluation method may be implemented based on a search engine in a business processing system, where the search engine is provided with an evaluation rule set based on historical data, and performs segmentation processing on the business data to be evaluated based on the evaluation rule, and quickly retrieves a corresponding server to execute a corresponding rule to implement quick evaluation of the business data.

Specifically, for example, after the reimbursement bill is synchronized to the wind control system from a data provider (the data provider of the reimbursement bill is a new or old FAS system), the reimbursement bill data is classified according to the dimensions such as the rule execution granularity, the organization to which the reimbursement bill belongs, the cost type and the like to obtain the segmentation fragments of the reimbursement bill, and then the reimbursement bill fragments are respectively stored in a high-performance search engine (elastic search);

in practical application, before storing the reimbursement bill fragments into the elastic search, keywords of the reimbursement bill fragments also need to be extracted, and the corresponding servers can be quickly inquired in a search engine based on the keywords, so that the reimbursement evaluation rules are called to evaluate the reimbursement bill fragments.

Furthermore, the search engine also introduces a cache mechanism, and adds the existing rules and factor fields into the cache, thereby avoiding directly querying the database.

The method is characterized in that the reimbursement bills with different dimensionalities, such as rule execution granularity, reimbursement bill affiliated mechanisms, expense types and the like, are subjected to physical task fragmentation according to historical data, rule execution tasks are distributed to different financial wind control instances, and parallel execution energy of the tasks is promoted on the basis of multiple threads. The design can be realized through programming, the original synchronous thread execution task is changed into an asynchronous thread task, and the waiting time of the system is reduced.

In this embodiment, the optimization of the business rules and the evaluation of the business data are realized in the manner described above, such an implementation manner has better technical scalability and business adaptability, and after the tasks are fragmented, the tasks are executed in parallel on multiple instances, which can adapt to a larger task amount.

With reference to fig. 7, the evaluation rule optimization method in the embodiment of the present invention is described above, and an evaluation rule optimization apparatus in the embodiment of the present invention is described below, where an embodiment of the evaluation rule optimization apparatus in the embodiment of the present invention includes:

a rule calling module 701, configured to, when a service data evaluation request is received, call a rule engine interface to obtain an evaluation rule stored in the service processing device, where the evaluation rule is an audit process rule for evaluating input service data to be evaluated;

a fragmentation processing module 702, configured to perform slicing processing on the evaluation rule according to a preset rule fragmentation processing algorithm to obtain at least two task fragments;

and the rule execution module 703 is configured to distribute at least two task fragments to at least two evaluation units, and control all the evaluation units to asynchronously run and execute corresponding task fragments, so as to implement evaluation processing on the service data to be evaluated.

In the embodiment of the invention, evaluation rule polarity slices in the system are processed according to a preset rule fragmentation processing algorithm to obtain a plurality of task fragments, and then the task fragments are distributed to different processing units for execution, so that the pressure of a server on service audit is reduced, the utilization rate of processor resources in a service system is also improved, the service processing efficiency is improved, and the backlog of service data is reduced; furthermore, asynchronous control is adopted among the processing units for executing the task fragments, the processing units can independently and simultaneously run without influencing each other, and the execution time of the rules is further shortened, so that the time length of service auditing is shortened, and the auditing efficiency is improved.

Referring to fig. 8, another embodiment of the evaluation rule optimization apparatus according to the embodiment of the present invention includes:

Optionally, the fragmentation processing module 702 includes: drawing unit 7021, classifying unit 7022, and cutting unit 7023:

the drawing unit 7021 is configured to analyze the audit process nodes of the evaluation rule, and draw a tree based on the analyzed audit process nodes;

the classification unit 7022 is configured to perform node classification on the dendrogram by using a linear regression model according to a task granularity completion rule to obtain at least two node sets, where nodes included in each node set are all connected to the same parent node;

the cutting unit 7023 is configured to slice the evaluation rule based on the node set to obtain task fragments with the same number as the node set, and establish a parent-child association relationship between the task fragments.

Optionally, the rule executing module 703 includes a sorting unit 7031 and a task distributing unit 7032, where:

the sorting unit 7031 is configured to invoke the same number of evaluation units according to the number of the task fragments, and sort the evaluation units according to the execution priority;

the task distributing unit 7032 is configured to sequentially distribute, according to the parent-child association relationship, the task fragments from parent to child to the ordered evaluation units, and control the evaluation units to execute the task fragments in an asynchronous execution manner, where an evaluation unit with a higher priority preferentially receives a task fragment in a parent relationship.

Optionally, the task distributing unit 7032 is specifically configured to:

judging whether the time length is greater than a preset time value or not;

Optionally, the task distributing unit 7032 is specifically configured to:

In the embodiment of the invention, the evaluation rules are fragmented and distributed to the plurality of evaluation units to be executed simultaneously, so that the dependence of the rules on a single processing unit is reduced, the overall execution time of the rules is shortened by times, the auditing efficiency is greatly improved when the business is audited, and the data backlog phenomenon of the system under the condition of large data volume is avoided.

Further, the present invention also provides the service processing device, as shown in fig. 9, the device includes: an evaluation device 902 and at least one evaluation rule optimization device 901 as provided in the above embodiments, wherein:

the evaluation device 901 is configured to obtain service data to be evaluated and an evaluation rule corresponding to the service data to be evaluated; slicing the service data to be evaluated according to the evaluation rule to obtain at least two data fragments; extracting a key field and a factor in each data fragment, wherein the key field is a data item to be evaluated in the data fragment, and the factor is an audit rule description of the data item; inquiring a corresponding evaluation unit from a rule search engine on the business processing system according to the key field and the factor; at least two data fragments are sent to corresponding evaluation units for evaluation, and an evaluation result is output, where the evaluation rule is an audit process rule processed by the rule optimization method provided in the above embodiment executed by the evaluation rule optimization device 901.

Fig. 7 to 8 describe the evaluation rule optimization apparatus in the embodiment of the present invention in detail from the perspective of the modular functional entity, in practical applications, the evaluation rule optimization apparatus may be a part of a business processing device, and may even be a program module in a processor, and the business processing device in the embodiment of the present invention is described in detail from the perspective of hardware processing.

Fig. 10 is a schematic structural diagram of a service processing apparatus provided by an embodiment of the present invention, where the service processing apparatus 1000 may generate a relatively large difference due to different configurations or performances, and may include one or more processors (CPUs) 1010 (e.g., one or more processors) and a memory 1020, and one or more storage media 1030 (e.g., one or more mass storage devices) storing an application program 1033 or data 1032. Memory 1020 and storage media 1030 may be, among other things, transient or persistent storage. The program stored on the storage medium 1030 may include one or more modules (not shown), each of which may include a sequence of instructions operating on the business processing apparatus 1000. Further, the processor 1010 may be configured to communicate with the storage medium 1030, and execute a series of instruction operations in the storage medium 1030 on the service processing device 1000, where the series of instruction operations implement functions of the steps of the evaluation rule optimization method and the steps of the service evaluation method provided in the above embodiments.

The business processing device 1000 may also include one or more power supplies 1040, one or more wired or wireless network interfaces 1050, one or more input-output interfaces 1060, and/or one or more operating systems 1031, such as Windows service, Mac OS X, Unix, Linux, FreeBSD, and the like. Those skilled in the art will appreciate that the business processing device architecture shown in fig. 10 does not constitute a limitation on the evaluation rule optimization apparatus and the business processing device that perform the above-described method embodiments, and may include more or fewer components than those shown, or some components in combination, or a different arrangement of components.

The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium, and may also be a volatile computer-readable storage medium, where instructions are stored, and when the instructions are executed on a computer, the instructions cause the computer to execute the steps of the evaluation rule optimization method, or implement the steps of the service evaluation method provided in the foregoing embodiment.

It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.

The block chain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.

The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims

1. An evaluation rule optimization method, comprising:

2. The method according to claim 1, wherein the slicing the evaluation rule according to a preset rule fragmentation processing algorithm to obtain at least two task fragments comprises:

3. The method according to claim 2, wherein the distributing at least two of the task fragments to at least two evaluation units comprises:

4. The method according to claim 3, wherein the controlling the evaluation unit to execute the task fragment in an asynchronous execution manner comprises:

judging whether the time length is greater than a preset time value or not;

5. The evaluation rule optimization method according to claim 4, wherein the multi-threaded running of the task fragment comprises:

6. A service evaluation method, characterized in that the service evaluation method comprises:

acquiring service data to be evaluated and an evaluation rule corresponding to the service data to be evaluated, wherein the evaluation rule is an audit process rule processed according to the evaluation rule optimization method of any one of claims 1-5;

7. An evaluation rule optimization device, comprising:

8. A service processing device, characterized in that the service processing device comprises: evaluation device and at least one evaluation rule optimization device according to claim 7, wherein:

the evaluation device is used for acquiring service data to be evaluated and an evaluation rule corresponding to the service data to be evaluated; slicing the service data to be evaluated according to the evaluation rule to obtain at least two data fragments; extracting a key field and a factor in each data fragment, wherein the key field is a data item to be evaluated in the data fragment, and the factor is an audit rule description of the data item; inquiring a corresponding evaluation unit from a rule search engine on the business processing equipment according to the key field and the factor; at least two data fragments are sent to corresponding evaluation units for evaluation, and an evaluation result is output, wherein the evaluation rule is an audit process rule processed by the evaluation rule optimization device according to the evaluation rule optimization method of any one of claims 1 to 5.

9. A service processing device, characterized in that the service processing device comprises: a memory having instructions stored therein and at least one processor, the memory and the at least one processor interconnected by a line;

the at least one processor invoking the instructions in the memory to cause the business processing device to perform the evaluation rule optimization method of any of claims 1-5;

alternatively, the first and second electrodes may be,

the at least one processor invokes the instructions in the memory to cause the business processing device to perform the business evaluation method of claim 6.

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 evaluation rule optimization method according to any one of claims 1 to 5;

alternatively, the first and second electrodes may be,

the computer program realizing the steps of the traffic assessment method as claimed in claim 6 when executed by a processor.