CN115617355A - Operation processing method, device, system and computer readable storage medium - Google Patents
Operation processing method, device, system and computer readable storage medium Download PDFInfo
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Abstract
The application discloses an operation processing method, an operation processing device, an operation processing system and a computer readable storage medium, wherein the method is applied to a formula engine client, and the formula engine client is deployed on a big data computing node; the method comprises the following steps: responding to an operation request triggered by the big data computing node, and determining a rule identifier corresponding to an operation rule required by the operation request; sending an operation rule acquisition request carrying the rule identifier to a formula engine server; receiving a target operation rule script corresponding to the rule identifier, which is returned by the formula engine server; and executing the target operation rule script on a target calculation object corresponding to the operation request, and outputting the updated target calculation object. Therefore, by combining the formula engine with the big data, the object value can be adjusted rapidly, dynamically and distributively according to the rule, so that the calculation requirements of real-time changing and complex business scenes are met.
Description
Technical Field
The present invention relates to the field of big data technologies, and in particular, to an operation processing method, apparatus, system, and computer readable storage medium.
Background
The big data faces to a complex business scene, and needs to respond to business changes quickly, for example, flexible and variable business judgment and rules need to be supported aiming at business index type fields such as receivable, real income, arrearage, overdue, open and refund, and the like, and the big data is difficult to support and realize only by the technology of the big data.
Disclosure of Invention
The application aims to provide an operation processing method, an operation processing device, an operation processing system and a computer readable storage medium, which can realize that object values can be adjusted rapidly, dynamically and distributively according to rules so as to adapt to the calculation requirements of real-time changing and complex service scenes.
In order to achieve the above purpose:
in a first aspect, an embodiment of the present application provides an operation processing method, which is applied to a formula engine client, where the formula engine client is deployed on a big data computing node; the method comprises the following steps:
responding to an operation request triggered by the big data computing node, and determining a rule identifier corresponding to an operation rule required by the operation request;
sending an operation rule acquisition request carrying the rule identifier to a formula engine server;
receiving a target operation rule script corresponding to the rule identifier, which is returned by the formula engine server;
and executing the target operation rule script on a target calculation object corresponding to the operation request, and outputting the updated target calculation object.
Optionally, the formula engine client includes an REST interface module, and the sending an operation rule obtaining request carrying the rule identifier to the formula engine server includes:
and based on the REST interface module, sending an operation rule acquisition request carrying the rule identifier to a formula engine server side through an HTTP (hyper text transport protocol).
Optionally, the formula engine client includes an analysis module and an execution module, and the executing the target operation rule script on the target calculation object corresponding to the operation request includes:
analyzing the target operation rule script through the analysis module to obtain a target operation rule;
and executing the target operation rule on the target calculation object corresponding to the operation request through the execution module to obtain the updated target calculation object.
In a second aspect, an embodiment of the present application provides an operation processing method, which is applied to a formula engine server, where the formula engine server is deployed in a server, and the method includes:
receiving an operation rule acquisition request which is sent by a formula engine client and carries a rule identifier;
inquiring a preset operation rule base based on the rule identification to obtain a target operation rule script corresponding to the rule identification;
and sending the target operation rule script to the formula engine client.
Optionally, the method further comprises:
responding to a setting instruction, and outputting an operation rule setting interface;
and receiving a user configuration instruction through the operation rule setting interface, and configuring an operation rule according to the user configuration instruction.
Optionally, the formula engine server includes an REST service module, and the receiving an operation rule obtaining request with a rule identifier sent by the formula engine client includes:
and receiving an operation rule acquisition request which is sent by a formula engine client and carries a rule identifier through the REST service module.
In a third aspect, an embodiment of the present application provides an operation processing method, where the method includes:
the method comprises the steps that a formula engine client deployed in a big data computing node responds to an operation request triggered by the big data computing node, a rule identification corresponding to an operation rule required by the operation request is determined, and an operation rule obtaining request carrying the rule identification is sent to a formula engine server;
after receiving the operation rule obtaining request, a formula engine server deployed in a server queries a preset operation rule base based on the rule identifier to obtain a target operation rule script corresponding to the rule identifier, and sends the target operation rule script to the formula engine client;
and after receiving the target operation rule script, the formula engine client executes the target operation rule script on a target calculation object corresponding to the operation request and outputs the updated target calculation object.
In a fourth aspect, an embodiment of the present application provides an operation processing system, including a formula engine client and a formula engine server, where the formula engine client is deployed in a big data computing node, and the formula engine server is deployed in a server; the formula engine client is used for executing the operation processing method of the first aspect, and the formula engine server is used for executing the operation processing method of the second aspect.
In a fifth aspect, an embodiment of the present application provides an arithmetic processing apparatus, including: a processor and a memory storing a computer program, wherein the steps of the arithmetic processing method are realized when the processor runs the computer program.
In a sixth aspect, an embodiment of the present application provides a computer-readable storage medium, where a computer program is stored, and the computer program, when executed by a processor, implements the steps of the above operation processing method.
The method, the device and the system for operation processing and the computer readable storage medium are applied to a formula engine client, wherein the formula engine client is deployed on a big data computing node; the method comprises the following steps: responding to an operation request triggered by the big data computing node, and determining a rule identifier corresponding to an operation rule required by the operation request; sending an operation rule acquisition request carrying the rule identifier to a formula engine server; receiving a target operation rule script corresponding to the rule identifier, which is returned by the formula engine server; and executing the target operation rule script on a target calculation object corresponding to the operation request, and outputting the updated target calculation object. Therefore, by combining the formula engine with the big data, the object value can be quickly, dynamically and distributively adjusted according to the rule, so that the calculation requirements of real-time changing and complex service scenes are met.
Drawings
Fig. 1 is a first flowchart illustrating an operation processing method according to an embodiment of the present invention;
FIG. 2 is a second flowchart illustrating an operation processing method according to an embodiment of the present invention;
FIG. 3 is a third schematic flowchart illustrating an operation processing method according to an embodiment of the present invention;
FIG. 4 is a schematic diagram illustrating a separation of a formula engine server and a formula engine client according to an embodiment of the present invention;
FIG. 5 is a block diagram of an embodiment of the present invention in which big data is combined with a formula engine;
FIG. 6 is a schematic diagram illustrating comparison between before and after object update according to an embodiment of the present invention;
FIG. 7 is a schematic diagram of a process for calculating big data in combination with a formula engine according to an embodiment of the present invention;
fig. 8 is a schematic structural diagram of an arithmetic processing device according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, a reference to an element identified by the phrase "comprising one of 82308230a of 82303030, or an element defined by the phrase" comprising another identical element does not exclude the presence of the same element in a process, method, article, or apparatus comprising the element, and elements having the same designation may or may not have the same meaning in different embodiments of the application, the particular meaning being determined by its interpretation in the particular embodiment or by further reference to the context of the particular embodiment.
It should be understood that although the terms first, second, third, etc. may be used herein to describe various information, such information should not be limited to these terms. These terms are only used to distinguish one type of information from another. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope herein. The word "if" as used herein may be interpreted as "at" \8230; "or" when 8230; \8230; "or" in response to a determination ", depending on the context. Also, as used herein, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context indicates otherwise. It will be further understood that the terms "comprises," "comprising," "includes" and/or "including," when used in this specification, specify the presence of stated features, steps, operations, elements, components, items, species, and/or groups, but do not preclude the presence, or addition of one or more other features, steps, operations, elements, components, species, and/or groups thereof. The terms "or" and/or "as used herein are to be construed as inclusive or meaning any one or any combination. Thus, "a, B or C" or "a, B and/or C" means "any of the following: a; b; c; a and B; a and C; b and C; A. b and C ". An exception to this definition will occur only when a combination of elements, functions, steps or operations are inherently mutually exclusive in some way.
It should be understood that, although the steps in the flowcharts in the embodiments of the present application 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 may be performed in other orders unless otherwise indicated herein. Moreover, at least some of the steps in the figures may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, in different orders, and may be performed alternately or partially with other steps or at least some of the sub-steps or stages of other steps.
It should be noted that, step numbers such as S101, S102, etc. are used herein for the purpose of more clearly and briefly describing corresponding contents, and do not constitute a substantial limitation on the sequence, and those skilled in the art may perform S102 first and then S101, etc. in the specific implementation, but these should be within the protection scope of the present application.
It should be understood that the specific embodiments described herein are merely illustrative of and not restrictive on the broad application.
In the following description, suffixes such as "module", "component", or "unit" used to indicate elements are used only for facilitating the description of the present application, and have no particular meaning in themselves. Thus, "module", "component" or "unit" may be used mixedly.
Referring to fig. 1, for an operation processing method provided in the embodiment of the present application, the operation processing method may be executed by an operation processing apparatus provided in the embodiment of the present application, and the operation processing apparatus may be implemented in a software and/or hardware manner, in this embodiment, the operation processing apparatus is taken as a formula engine client, and the formula engine client is deployed in a big data computing node, for example, the operation processing method provided in this embodiment includes:
step S101: and responding to an operation request triggered by the big data computing node, and determining a rule identifier corresponding to an operation rule required by the operation request.
Optionally, when the big data computing node processes a task, it may need to update the computing object, that is, adjust an attribute value or an attribute field of the computing object, at this time, the big data computing node may send an operation request to the formula engine client, and the formula engine client correspondingly receives the operation request triggered by the big data computing node. It should be noted that the operation request may include information indicating a required operation rule, such as a rule identifier corresponding to the required operation rule, or a name corresponding to the required operation rule. In addition, the operation request may also include a target calculation object, i.e., a calculation object that needs to update an attribute value or an attribute field. And the formula engine client can determine the rule identifier corresponding to the operation rule required by the operation request according to the operation request. Here, the formula engine client may be regarded as a JAR file that packages functions separated from the formula engine and is deployed in a big data computing node.
Step S102: and sending an operation rule acquisition request carrying the rule identifier to a formula engine server.
Optionally, since the formula engine client does not store the operation rule, the formula engine client needs to send an operation rule obtaining request carrying the rule identifier to the formula engine server to request to obtain the operation rule corresponding to the rule identifier.
In an embodiment, the sending, by the formula engine client, the operation rule obtaining request carrying the rule identifier to the formula engine server includes:
and based on the REST interface module, sending an operation rule acquisition request carrying the rule identifier to a formula engine server through an HTTP (hyper text transport protocol).
Optionally, when the formula engine client needs to acquire the operation rule corresponding to the rule identifier, the formula engine client may send an operation rule acquisition request carrying the rule identifier to the formula engine server through an HTTP protocol based on its own REST interface module. Because the HTTP protocol is a general protocol supported by most systems, and the decoupling and the integration are convenient, the acquisition speed of the operation rule can be improved, and the object value can be further quickly adjusted.
Step S103: and receiving a target operation rule script which is returned by the formula engine server and corresponds to the rule identifier.
Optionally, the formula engine client receives a target operation rule script corresponding to the rule identifier, which is returned by the formula engine server based on the operation rule obtaining request. It should be noted that the operation rule may be regarded as a mathematical expression, such as c = c + b, c = a-b, or the like.
Step S104: and executing the target operation rule script on a target calculation object corresponding to the operation request, and outputting the updated target calculation object.
Optionally, after obtaining the target operation rule script corresponding to the rule identifier, the formula engine client may execute the target operation rule script on the target calculation object corresponding to the operation request to update the attribute value or the attribute field of the target calculation object, and output the updated target calculation object to the big data calculation node. It should be noted that, the target calculation object may be included in the operation request, or the big data calculation node may be separately sent to the formula engine client, which is not limited herein. For example, assuming that the target operation rule is a +2 and a represents a calculation object, the sum of the value of the target calculation object and 2 is used as the updated value of the target calculation object.
In one embodiment, the formula engine client includes a parsing module and an executing module, and the executing the target operation rule script on the target calculation object corresponding to the operation request includes:
analyzing the target operation rule script through the analysis module to obtain a target operation rule;
and executing the target operation rule on the target calculation object corresponding to the operation request through the execution module to obtain the updated target calculation object.
Optionally, the formula engine client may analyze the target operation rule script through the analysis module to obtain a target operation rule, and then execute the target operation rule on a target calculation object corresponding to the operation request through the execution module to obtain the updated target calculation object. Here, the parsing module may also be referred to as a parser, and the executing module may also be referred to as an executor.
In summary, in the operation processing method provided in the above embodiment, by combining the formula engine with the big data, the object value can be adjusted according to the rule quickly, dynamically, and in a distributed manner, so as to adapt to the calculation requirement of a real-time changing and complex service scenario.
The same inventive concept as the foregoing embodiment, referring to fig. 2, is an operation processing method provided in the embodiment of the present application, where the operation processing method can be executed by an operation processing device provided in the embodiment of the present application, and the operation processing device can be implemented in a software and/or hardware manner, in this embodiment, the operation processing device is a formula engine server, and the formula engine server is deployed in a server, for example, the operation processing method provided in this embodiment includes:
step S201: and receiving an operation rule acquisition request which is sent by a formula engine client and carries a rule identifier.
Optionally, the formula engine server may be specifically deployed in an HTTP server or the like. The formula engine server side can receive an operation rule acquisition request carrying a rule identifier sent by the formula engine client side in real time or in irregular time. It should be noted that, for different formula engine clients, the formula engine server may be distinguished by the identifier of the formula engine client. Here, the formula engine server may be regarded as a file that packages functions separated from the formula engine and is deployed in the HTTP server.
In an embodiment, the receiving an operation rule obtaining request with a rule identifier sent by a formula engine client includes:
and receiving an operation rule acquisition request which is sent by a formula engine client and carries a rule identifier through the REST service module.
Optionally, the formula engine server may receive, through an REST service module provided by the formula engine server, an operation rule acquisition request carrying a rule identifier sent by the formula engine client, for example, the REST service module receives, through an HTTP protocol, an operation rule acquisition request sent by the formula engine client, so as to implement stable data transmission.
Step S202: and inquiring a preset operation rule base based on the rule identification to obtain a target operation rule script corresponding to the rule identification.
Optionally, an operation rule base may be stored in the formula engine server in advance, and the operation rule base may include a plurality of operation rules and corresponding rule identifiers. The formula engine server queries a preset operation rule base based on the rule identifier in the operation rule acquisition request, so as to obtain a target operation rule corresponding to the rule identifier, and further generate the target operation rule script. It should be noted that the operation rule may be regarded as a mathematical expression, such as c = c + b, c = a-b, or the like.
Step S203: and sending the target operation rule script to the formula engine client.
Optionally, the formula engine service end sends the target operation rule script to the formula engine client, for example, the target operation rule script is sent to the formula engine client by an REST service module, so that the formula engine client obtains the required target operation rule script.
In summary, in the operation processing method provided in the above embodiment, by combining the formula engine with the big data, the object value can be adjusted according to the rule quickly, dynamically, and in a distributed manner, so as to adapt to the calculation requirement of a real-time changing and complex service scenario.
In an embodiment, the method further comprises:
responding to a setting instruction, and outputting an operation rule setting interface;
and receiving a user configuration instruction through the operation rule setting interface, and configuring an operation rule according to the user configuration instruction.
Optionally, at the formula engine service end, the user may customize or modify the operation rule as required. Optionally, after receiving the input setting instruction, the formula engine server may output an operation rule setting interface, that is, display the operation rule setting interface, where the operation rule setting interface may be provided with function keys for operation rule modification, addition, and the like, and displays a corresponding function setting interface after being triggered. And after receiving a user configuration instruction through the operation rule setting interface, the formula engine server configures an operation rule according to the user configuration instruction, and updates an operation rule base by using the operation rule obtained by configuration. Therefore, the operation rule can be configured based on the requirement customization, the requirement change can be responded immediately, and the capability of adapting to the calculation requirement of real-time change and complex service scenes is further improved.
Based on the same inventive concept of the foregoing embodiment, referring to fig. 3, an arithmetic processing method provided in the embodiment of the present application is provided, where the arithmetic processing method provided in the embodiment of the present application includes:
step S301: the method comprises the steps that a formula engine client deployed in a big data computing node responds to an operation request triggered by the big data computing node, a rule identification corresponding to an operation rule required by the operation request is determined, and an operation rule obtaining request carrying the rule identification is sent to a formula engine server.
Optionally, when the big data computing node processes a task, it may need to update the computing object, that is, adjust an attribute value or an attribute field of the computing object, at this time, the big data computing node may send an operation request to the formula engine client, and the formula engine client correspondingly receives the operation request triggered by the big data computing node. It should be noted that the operation request may include information indicating a required operation rule, such as a rule identifier corresponding to the required operation rule, or a name corresponding to the required operation rule. In addition, the operation request may also include a target calculation object, i.e., a calculation object that needs to update an attribute value or an attribute field. And the formula engine client can determine the rule identification corresponding to the operation rule required by the operation request according to the operation request. Here, the formula engine client may be packaged into a JAR file based on the implemented functions to be deployed on a big data computing node.
Optionally, since the formula engine client does not store the operation rule, the formula engine client needs to send an operation rule obtaining request carrying the rule identifier to the formula engine server to request to obtain the operation rule corresponding to the rule identifier.
In an embodiment, the sending, by the formula engine client, the operation rule obtaining request carrying the rule identifier to the formula engine server includes:
and based on the REST interface module, sending an operation rule acquisition request carrying the rule identifier to a formula engine server side through an HTTP (hyper text transport protocol).
Optionally, when the formula engine client needs to acquire the operation rule corresponding to the rule identifier, the formula engine client may send, based on the REST interface module of the formula engine client, an operation rule acquisition request carrying the rule identifier to the formula engine server through an HTTP protocol. Because the HTTP protocol is a general protocol supported by most systems, and the decoupling and the integration are convenient, the speed of acquiring the operation rule can be increased, and the object value can be further quickly adjusted.
Step S302: and after receiving the operation rule acquisition request, a formula engine server deployed in the server queries a preset operation rule base based on the rule identifier, acquires a target operation rule script corresponding to the rule identifier, and sends the target operation rule script to the formula engine client.
Optionally, the formula engine server may be specifically deployed in an HTTP server or the like. The formula engine server side can receive an operation rule acquisition request carrying a rule identifier sent by the formula engine client side in real time or in irregular time. It should be noted that, for different formula engine clients, the formula engine server may be distinguished by the identifier of the formula engine client.
In an embodiment, the receiving an operation rule obtaining request with a rule identifier sent by a formula engine client includes:
and receiving an operation rule acquisition request carrying a regular identifier sent by a formula engine client through the REST service module.
Optionally, the formula engine server may receive, through a REST service module provided in the formula engine server, an operation rule obtaining request carrying a rule identifier sent by the formula engine client, for example, the REST service module receives, through an HTTP protocol, an operation rule obtaining request sent by the formula engine client, so as to implement stable data transmission.
Optionally, an operation rule base may be stored in the formula engine server in advance, and the operation rule base may include a plurality of operation rules and corresponding rule identifiers. The formula engine server queries a preset operation rule base based on the rule identifier in the operation rule acquisition request, so as to obtain a target operation rule corresponding to the rule identifier, and further generate the target operation rule script. It should be noted that the operation rule can be regarded as a mathematical expression, such as rule 1: calculation object c = calculation object a + calculation object b, rule 2: computational object c = computational object a-computational object b, etc.
Optionally, the formula engine server sends the target operation rule script to the formula engine client, for example, the target operation rule script is sent to the formula engine client by an REST service module, so that the formula engine client acquires the required target operation rule script.
Step S303: and after receiving the target operation rule script, the formula engine client executes the target operation rule script on a target calculation object corresponding to the operation request and outputs the updated target calculation object.
Optionally, after obtaining the target operation rule script corresponding to the rule identifier, the formula engine client may execute the target operation rule script on the target calculation object corresponding to the operation request to update the attribute value or the attribute field of the target calculation object, and output the updated target calculation object to the big data calculation node. It should be noted that the target computing object may be included in the operation request, or may be sent to the formula engine client by the big data computing node separately, and is not limited in this respect. For example, assuming that the target operation rule is a +2 and a represents a calculation object, the sum of the value of the target calculation object and 2 is used as the updated value of the target calculation object.
In one embodiment, the formula engine client includes a parsing module and an executing module, and the executing the target operation rule script on the target calculation object corresponding to the operation request includes:
analyzing the target operation rule script through the analysis module to obtain a target operation rule;
and executing the target operation rule on the target calculation object corresponding to the operation request through the execution module to obtain the updated target calculation object.
Optionally, the formula engine client may analyze the target operation rule script through the analysis module to obtain a target operation rule, and then execute the target operation rule on a target calculation object corresponding to the operation request through the execution module to obtain the updated target calculation object.
In summary, in the operation processing method provided in the above embodiment, by combining the formula engine with the big data, the object value can be adjusted according to the rule quickly, dynamically, and in a distributed manner, so as to adapt to the calculation requirement of a real-time changing and complex service scenario.
In one embodiment, the method further comprises:
the formula engine server responds to a setting instruction and outputs an operation rule setting interface; and receiving a user configuration instruction through the operation rule setting interface, and configuring an operation rule according to the user configuration instruction.
Optionally, at the formula engine service end, the user may customize or modify the operation rule as needed. Optionally, after receiving the input setting instruction, the formula engine server may output an operation rule setting interface, that is, display the operation rule setting interface, where the operation rule setting interface may be provided with function keys for operation rule modification, addition, and the like, and displays a corresponding function setting interface after being triggered. And after receiving a user configuration instruction through the operation rule setting interface, the formula engine server configures an operation rule according to the user configuration instruction, and updates an operation rule base by using the operation rule obtained by configuration. Therefore, the operation rule can be configured based on the requirement customization, the requirement change can be responded immediately, and the capability of adapting to the calculation requirement of real-time change and complex service scenes is further improved.
Based on the same inventive concept of the foregoing embodiments, an embodiment of the present application further provides an operation processing system, including a formula engine client and a formula engine server, where the formula engine client is deployed in the big data computing node, and the formula engine server is deployed in the server; the formula engine client and the formula engine server are respectively used for executing the corresponding operation processing method in the foregoing embodiment.
The foregoing embodiments will be described in detail below with reference to a specific example based on the same inventive concept as the foregoing embodiments.
In order to realize the combination of a big data calculation framework and a formula engine and be suitable for in-line data distributed calculation, in the operation processing method provided by this embodiment, firstly, a formula engine server and a formula engine client need to be separated, that is, the formula engine is divided into 2 project projects according to functions, that is, a server project and a client project, referring to fig. 4, the server project is responsible for user management, authority management, index management, configuration management, formula predefining and REST service provision, and the projects are packaged and deployed on an HTTP server to provide services; the client project is a JAVA project, the main function is to pull the operation rule from the server through the REST client, analyze and execute the operation rule to obtain a result, and the project is packaged into a JAR file to support deployment.
Referring to fig. 5, a schematic diagram of a framework combining big data and a formula engine is shown, wherein a formula engine server runs on an HTTP server, can provide WEB visualization configuration rules, has a rule base, can be divided into a first-level rule, a second-level rule, a third-level rule and other multi-level rules, and is convenient to manage and use; the formula engine client is compiled by JAVA, realizes a serialized interface, packages the serialized interface into a JAR file, deploys the JAR file on a big data computing node, loads and calls the JAVM through JVM, acquires a rule script from a formula engine server through an HTTP protocol, and analyzes and executes the rule script through an analyzer and an actuator; the big data computing nodes are provided with a computable object which needs to execute rules and has an attribute field reflecting business, the computable object is transmitted to a formula engine client, and after the formula engine client takes the rule script and the computable object, the rule script is executed and the attribute field of the computable object is updated, so that the big data computing nodes obtain the computable object updated by the rules.
Referring to fig. 6, for example, assuming that the attribute value of the order object a before update is 100 and the operation rule is a value multiplied by 2, the attribute value of the object a after executing the rule update is 100 × 2=200; the attribute value of the order object B before update is 100, and the operation rule is a value divided by 2, then the object B value after execution rule update is 100/2=50.
The calculation of big data in conjunction with the formula engine is explained below by way of specific examples.
Referring to fig. 7, assume that the formula engine server configures 3 rules, which are as follows:
rule 2;
The big data computing node respectively obtains the 3 rule scripts through the formula engine client, then transmits the created object and the rule scripts to an analyzer and an actuator of the formula engine client, and obtains an updated object after analysis and execution.
For rule 1, the object has attributes a =100, b =100, c =0, and then after the rule is executed, the object has attribute c =200;
for rule 2, the object has attributes a =400, b =100, c =0, and then after the rule is executed, the object has attribute c =300;
for rule 3, the property of the object a =50, b =8, c =0, and then the property of the object c =400 after the rule is executed.
It should be noted that the big data computation framework referred to in the present application is not limited to SPARK and FLINK, and other big data computation frameworks that support serialized and deserialized objects also support.
In summary, in the operation processing method provided in this embodiment, the formula engine calculation rule script may be obtained through the HTTP protocol, the rule script is distributively executed on the big data calculation node to update the internal object, the change of the demand is responded to in real time, the calculation rule is edited and modified on the WEB interface, the client is convenient to deploy, and only one JAR file needs to be deployed. Meanwhile, two technologies of a big data calculation framework and a formula engine are creatively combined, so that a synergistic effect is generated, and the object value can be rapidly and dynamically adjusted in a distributed manner according to the rule, so as to adapt to real-time changing and complex service scenes.
Based on the same inventive concept as the foregoing embodiments, an embodiment of the present invention provides an arithmetic processing device, as shown in fig. 8, including: a processor 310 and a memory 311 storing computer programs; the processor 310 illustrated in fig. 8 is not used to refer to the number of the processors 310 as one, but is only used to refer to the position relationship of the processor 310 relative to other devices, and in practical applications, the number of the processors 310 may be one or more; similarly, the memory 311 shown in fig. 8 is also used in the same sense, i.e. it is only used to refer to the position relationship of the memory 311 with respect to other devices, and in practical applications, the number of the memory 311 may be one or more. The arithmetic processing method applied to the above-described apparatus is realized when the processor 310 runs the computer program.
The apparatus may further include: at least one network interface 312. The various components of the device are coupled together by a bus system 313. It will be appreciated that the bus system 313 is used to enable communications among the components connected. The bus system 313 includes a power bus, a control bus, and a status signal bus in addition to the data bus. For clarity of illustration, however, the various buses are labeled as bus system 313 in FIG. 8.
The memory 311 may be a volatile memory or a nonvolatile memory, or may include both volatile and nonvolatile memories. Among them, the nonvolatile Memory may be a Read Only Memory (ROM), a Programmable Read Only Memory (PROM), an Erasable Programmable Read-Only Memory (EPROM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), a magnetic random access Memory (FRAM), a magnetic random access Memory (Flash Memory), a magnetic surface Memory, an optical Disc, or a Compact Disc Read-Only Memory (CD-ROM); the magnetic surface storage may be disk storage or tape storage. Volatile Memory can be Random Access Memory (RAM), which acts as external cache Memory. By way of illustration and not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), synchronous Static Random Access Memory (SSRAM), dynamic Random Access Memory (DRAM), synchronous Dynamic Random Access Memory (SDRAM), double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), enhanced Synchronous Dynamic Random Access Memory (ESDRAM), enhanced Synchronous Dynamic Random Access Memory (Enhanced DRAM), synchronous Dynamic Random Access Memory (SLDRAM), direct Memory (DRmb Access), and Random Access Memory (DRAM). The memory 311 described in connection with the embodiments of the invention is intended to comprise, without being limited to, these and any other suitable types of memory.
The memory 311 in the embodiment of the present invention is used to store various types of data to support the operation of the apparatus. Examples of such data include: any computer program for operating on the device, such as operating systems and application programs; contact data; telephone directory data; a message; a picture; video, etc. The operating system includes various system programs, such as a framework layer, a core library layer, a driver layer, and the like, and is used for implementing various basic services and processing hardware-based tasks. The application programs may include various application programs such as a Media Player (Media Player), a Browser (Browser), etc. for implementing various application services. Here, a program that implements the method of the embodiment of the present invention may be included in the application program.
Based on the same inventive concept of the foregoing embodiments, this embodiment further provides a computer storage medium, where a computer program is stored in the computer storage medium, where the computer storage medium may be a Memory such as a magnetic random access Memory (FRAM), a Read Only Memory (ROM), a Programmable Read Only Memory (PROM), an Erasable Programmable Read Only Memory (EPROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a Flash Memory (Flash Memory), a magnetic surface Memory, an optical Disc, or a Compact Disc Read Only Memory (CD-ROM), and the like; or a variety of devices, such as mobile phones, computers, tablet devices, personal digital assistants, etc., that include one or any combination of the above memories. When the computer program stored in the computer storage medium is executed by a processor, the arithmetic processing method applied to the above-described apparatus is realized. For the specific steps and processes of the computer program executed by the processor, please refer to the description of the embodiment shown in fig. 1-2, which is not repeated herein.
All possible combinations of the technical features of the above embodiments may not be described for the sake of brevity, but should be considered as within the scope of the present disclosure as long as there is no contradiction between the combinations of the technical features.
As used herein, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, including not only those elements listed, but also other elements not expressly listed.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (10)
1. An operation processing method is characterized by being applied to a formula engine client, wherein the formula engine client is deployed in a big data computing node; the method comprises the following steps:
responding to an operation request triggered by the big data computing node, and determining a rule identifier corresponding to an operation rule required by the operation request;
sending an operation rule acquisition request carrying the rule identifier to a formula engine server;
receiving a target operation rule script corresponding to the rule identifier, which is returned by the formula engine server;
and executing the target operation rule script on a target calculation object corresponding to the operation request, and outputting the updated target calculation object.
2. The method of claim 1, wherein the formula engine client includes a REST interface module, and the sending the operation rule obtaining request carrying the rule identifier to the formula engine server includes:
and based on the REST interface module, sending an operation rule acquisition request carrying the rule identifier to a formula engine server side through an HTTP (hyper text transport protocol).
3. The method of claim 1, wherein the formula engine client comprises a parsing module and an executing module, and wherein executing the target operation rule script on a target calculation object corresponding to the operation request comprises:
analyzing the target operation rule script through the analysis module to obtain a target operation rule;
and executing the target operation rule on the target calculation object corresponding to the operation request through the execution module to obtain the updated target calculation object.
4. An operation processing method is applied to a formula engine server, wherein the formula engine server is deployed in a server, and the method comprises the following steps:
receiving an operation rule acquisition request which is sent by a formula engine client and carries a rule identifier;
inquiring a preset operation rule base based on the rule identifier to obtain a target operation rule script corresponding to the rule identifier;
and sending the target operation rule script to the formula engine client.
5. The method of claim 4, further comprising:
responding to a setting instruction, and outputting an operation rule setting interface;
and receiving a user configuration instruction through the operation rule setting interface, and configuring an operation rule according to the user configuration instruction.
6. The method of claim 4, wherein the formula engine server includes a REST service module, and the receiving an operation rule obtaining request carrying a rule identifier sent by the formula engine client includes:
and receiving an operation rule acquisition request which is sent by a formula engine client and carries a rule identifier through the REST service module.
7. An arithmetic processing method, characterized by comprising:
the method comprises the steps that a formula engine client deployed on a big data computing node responds to an operation request triggered by the big data computing node, a rule identification corresponding to an operation rule required by the operation request is determined, and an operation rule obtaining request carrying the rule identification is sent to a formula engine server;
after receiving the operation rule obtaining request, a formula engine server deployed in a server queries a preset operation rule base based on the rule identifier to obtain a target operation rule script corresponding to the rule identifier, and sends the target operation rule script to the formula engine client;
and after receiving the target operation rule script, the formula engine client executes the target operation rule script on a target calculation object corresponding to the operation request and outputs the updated target calculation object.
8. An operation processing system is characterized by comprising a formula engine client and a formula engine server, wherein the formula engine client is deployed in a big data computing node, and the formula engine server is deployed in a server; the formula engine client is used for executing the operation processing method of any one of claims 1 to 3, and the formula engine server is used for executing the operation processing method of any one of claims 4 to 6.
9. An arithmetic processing device, comprising: a processor and a memory storing a computer program, the steps of the arithmetic processing method according to any one of claims 1 to 6 being implemented when the computer program is executed by the processor.
10. A computer-readable storage medium, characterized in that a computer program is stored, which when executed by a processor, implements the steps of the arithmetic processing method of any one of claims 1 to 6.
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| CN202211198437.1A CN115617355A (en) | 2022-09-29 | 2022-09-29 | Operation processing method, device, system and computer readable storage medium |
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| CN202211198437.1A CN115617355A (en) | 2022-09-29 | 2022-09-29 | Operation processing method, device, system and computer readable storage medium |
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