Format conversion method, device and equipment for target update data

Abstract

The embodiment of the invention discloses a format conversion method, device and equipment for target update data, and the method comprises the steps: analyzing configuration update request information to obtain the target update data of a rule set type, and recognizing a rule parameter and a plurality of key parameters corresponding to a preset keyword in the target update data; combining the rule parameters to obtain a target rule set, determining a group of target rules containing the same key parameters in the target rule set as a dependent rule group, and determining the target rules not containing the same key parameters as non-dependent rules; determining a first processing priority of each dependency rule according to the transmission path of the same key parameter, and determining a second processing priority of each non-dependency rule according to the association relationship of each key parameter; and performing format conversion on each dependency rule according to the first processing priority to obtain first update data, and performing format conversion on the non-dependency rule according to the second processing priority to obtain second update data. And the timeliness and accuracy of data format conversion are improved.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of computer technology, and in particular to a method, apparatus, and device for format conversion of target update data. Background Art

[0002] In the context of increasingly complex modern computer systems and software applications, the optimization of configuration information is crucial for the stable operation, functional expansion and adaptive adjustment of the system. As the scale of software systems continues to expand and business needs change rapidly, configuration information needs to be frequently updated to meet new functional requirements, optimize system performance or address security issues.

[0003] In related technologies, when updating configuration information, it is usually necessary to convert the format of the target update data. However, during the format conversion process, the dependencies between data and the impact of the dependencies between data on the priority of format conversion are not fully considered. As a result, when the data volume is large and the dependencies are complex, data with high dependencies may be delayed or erroneous in format conversion, and cannot provide accurate data support to related business modules in a timely manner, causing system operation abnormalities and affecting data storage efficiency and system operation performance. Summary of the Invention

[0004] The present invention provides a method, device, and apparatus for format conversion of target update data, addressing the issue of highly dependent data being unable to provide timely and accurate data support to relevant business modules due to delayed or erroneous format conversion, leading to system operation anomalies and impacting data storage efficiency and system performance. By analyzing the rules for target update data and the degree of dependency between rules, the priority of corresponding data format conversion is determined, improving the timeliness and accuracy of data format conversion and, consequently, enhancing system performance.

[0005] In a first aspect, an embodiment of the present application provides a method for converting the format of target update data, comprising:

[0006] Obtaining configuration update request information, parsing the configuration update request information to obtain target update data of a rule set type, and identifying rule parameters corresponding to preset keywords in the target update data and multiple key parameters in the rule parameters;

[0007] Merging the rule parameters according to a preset rule merging condition to obtain a target rule set, determining a group of target rules in the target rule set that contain the same key parameters as a dependent rule group, and determining target rules that do not contain the same key parameters as non-dependent rules, where the number of the non-dependent rules is multiple;

[0008] Determining a first processing priority of each dependent rule according to a transmission path of the same key parameter in each dependent rule group, and determining a second processing priority of each non-dependent rule according to an association relationship between the key parameters in the non-dependent rules, wherein the first processing priority is greater than the second processing priority;

[0009] The dependent rules are format-converted according to the first processing priority to obtain first updated data, and the non-dependent rules are format-converted according to the second processing priority to obtain second updated data.

[0010] Optionally, the preset keywords include variable keywords, action keywords, and judgment keywords, and the identifying of the rule parameters corresponding to the preset keywords in the target update data and multiple key parameters in the rule parameters includes:

[0011] Identify the rule parameters corresponding to the variable-type keywords and the element parameters in the rule parameters in the target update data, identify the rule parameters corresponding to the action-type keywords and the operation parameters in the rule parameters in the target update data, and identify the rule parameters corresponding to the judgment-type keywords and the condition parameters in the rule parameters in the target update data;

[0012] Accordingly, determining a group of target rules in the target rule set that contain the same key parameters as a dependent rule group, and determining target rules that do not contain the same key parameters as non-dependent rules, includes:

[0013] A group of target rules containing the same element parameters in the target rule set are determined as dependent rules or a dependent rule group, and target rules not containing the same element parameters are determined as non-dependent rules.

[0014] Optionally, determining the second processing priority of each non-dependent rule according to the association relationship between the key parameters in the non-dependent rule includes:

[0015] A dependency matrix is ​​generated based on the first association relationship between each condition parameter and each operation parameter in the non-dependent rule, the second association relationship between each condition parameter, and the third association relationship between each operation parameter, and the second processing priority of each non-dependent rule is determined based on the dependency value in the dependency matrix.

[0016] Optionally, determining the second processing priority of each non-dependent rule according to the association relationship between the key parameters in the non-dependent rule includes:

[0017] The associated data volume of the non-dependent rule is determined according to the association relationship between each condition parameter and each operation parameter in the non-dependent rule, and the second processing priority of each non-dependent rule is determined according to the associated data volume.

[0018] Optionally, determining the first processing priority of each dependency rule according to the transmission path of the same key parameter in each dependency rule group includes:

[0019] The data transmission direction and data transmission distance are determined according to the transmission path of the same element parameters in each of the dependency rule groups, the format conversion order of each of the dependency rule groups is determined according to the data transmission distance, and the first processing priority of each of the dependency rules is determined according to the data transmission direction and the format conversion order.

[0020] Optionally, after obtaining the configuration update request information, the method further includes:

[0021] The configuration update request information is parsed to obtain target update data of key-value pair type, the target update data is stored in a dictionary set, and the target update data of the dictionary set is converted into update data of a target storage format through a preset calling function.

[0022] Optionally, after obtaining the second update data, the method further includes:

[0023] encrypting the first update data and the second update data to obtain encrypted data, wherein the encrypted data includes encrypted content and an encryption timestamp;

[0024] Current version information is generated according to the encrypted content and the encrypted timestamp, and the current version information and the encrypted data are sent to a target program.

[0025] In a second aspect, an embodiment of the present application provides a target update data format conversion device, comprising:

[0026] A request information parsing module, configured to obtain configuration update request information, parse the configuration update request information, and obtain target update data of a rule set type;

[0027] A key parameter identification module, configured to identify a rule parameter corresponding to a preset keyword in the target update data and a plurality of key parameters in the rule parameter;

[0028] A rule merging module is used to merge the rule parameters according to preset rule merging conditions to obtain a target rule set;

[0029] a rule type determination module, configured to determine a group of target rules in the target rule set that contain the same key parameters as a dependent rule group, and determine target rules that do not contain the same key parameters as non-dependent rules, where the number of the non-dependent rules is multiple;

[0030] a processing priority determination module, configured to determine a first processing priority of each dependent rule according to a transmission path of the same key parameter in each dependent rule group, and to determine a second processing priority of each non-dependent rule according to an association relationship between the key parameters in the non-dependent rules, wherein the first processing priority is greater than the second processing priority;

[0031] The format conversion module is used to perform format conversion on the dependent rule according to the first processing priority to obtain first updated data, and to perform format conversion on the non-dependent rule according to the second processing priority to obtain second updated data.

[0032] In a third aspect, an embodiment of the present application provides an electronic device comprising: one or more processors; a storage device configured to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the format conversion method of the target update data described in the first aspect.

[0033] In a fourth aspect, an embodiment of the present application provides a storage medium comprising computer-executable instructions, which, when executed by a computer processor, are used to perform the method for format conversion of target update data as described in the first aspect.

[0034] The embodiment of the present application obtains configuration update request information, parses the configuration update request information to obtain target update data of the rule set type, identifies the rule parameters corresponding to the preset keywords in the target update data and multiple key parameters in the rule parameters; merges the rule parameters according to the preset rule merging conditions to obtain the target rule set, determines a group of target rules containing the same key parameters in the target rule set as a dependent rule group, and determines the target rules that do not contain the same key parameters as non-dependent rules, and the number of non-dependent rules is multiple; determines the first processing priority of each dependent rule according to the transmission path of the same key parameters in each dependent rule group, and determines the second processing priority of each non-dependent rule according to the association relationship of each key parameter in the non-dependent rule, the first processing priority is greater than the second processing priority; formats the dependent rules according to the first processing priority to obtain the first update data, and formats the non-dependent rules according to the second processing priority to obtain the second update data. In the above scheme, by merging the rule parameters, the management of the rule set can be simplified and the execution efficiency of the rules can be improved. By analyzing the degree of dependence between the rules in the rule set and determining the corresponding format conversion priority, the timeliness and accuracy of data format conversion are improved, and the system operation performance is correspondingly improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 This is a flow chart of a method for converting the format of target update data provided by an embodiment of the present application;

[0036] Figure 2 This is a flow chart of a method for identifying key parameters provided in an embodiment of the present application;

[0037] Figure 3 This is a schematic diagram of a dependency matrix of a non-dependent rule provided in an embodiment of the present application;

[0038] Figure 4 This is a flowchart of a method for determining a first processing priority provided by an embodiment of the present application;

[0039] Figure 5 This is a structural diagram of a target update data format conversion device provided by an embodiment of the present application;

[0040] Figure 6 This is a structural diagram of a target update data format conversion device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0041] In order to make the purpose, technical solutions and advantages of the present application clearer, the specific embodiments of the present application are further described in detail below in conjunction with the accompanying drawings. It is understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. It should also be noted that, for ease of description, only parts related to the present application, not all of the contents, are shown in the accompanying drawings. Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow charts describe each operation (or step) as a sequential process, many of the operations therein can be implemented in parallel, concurrently or simultaneously. In addition, the order of the operations can be rearranged. The process can be terminated when its operation is completed, but can also have additional steps not included in the accompanying drawings. The process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0042] The following will be combined with the accompanying drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the embodiments described are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field are within the scope of protection of this application.

[0043] The terms "first," "second," and the like in the specification and claims of this application are used to distinguish similar objects, and are not used to describe a specific order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate, so that the embodiments of this application can be implemented in an order other than that illustrated or described herein, and that the objects distinguished by "first," "second," and the like are generally of the same type, and do not limit the number of objects; for example, the first object can be one or more. In addition, the term "and / or" in the specification and claims refers to at least one of the connected objects, and the character " / " generally indicates that the objects connected are in an "or" relationship.

[0044] The following describes in detail the target update data format conversion method, device and equipment provided by the embodiments of the present application through specific embodiments and their application scenarios in conjunction with the accompanying drawings.

[0045] The format conversion method of target update data provided in the embodiment of the present application can be used in the scenario of updating configuration information. Based on the above application scenario, it can be understood that the executor of this solution can be a server.

[0046] Figure 1 This is a flow chart of a method for converting the format of target update data provided by an embodiment of the present application. Figure 1 Shown, including:

[0047] Step S101: Acquire configuration update request information, parse the configuration update request information to obtain target update data of a rule set type, and identify rule parameters corresponding to preset keywords in the target update data and multiple key parameters in the rule parameters.

[0048] Configuration update request information refers to information used to request configuration updates in scenarios such as software systems, devices, or network environments. This information can include the update request identifier, the subject of the update request, the specific content of the update, and the reason or purpose for the update. A rule set is a collection of rules that typically define system behavior, decision-making logic, or data processing. Target update data refers to the data involved in performing an update operation targeting a specific target in a rule set-based system or application. Rule set-type target update data refers to the data involved in the update operation represented as a set of rules. Preset keywords are numerical identifiers used to identify rule parameters, such as if, else, and send. Rule parameters can represent the entire rule statement, such as "When the order amount is greater than 1,000 yuan, give the customer a 10% discount and send a thank-you letter." Key parameters are variables, constants, or conditional values ​​used in rule definition. They specifically describe the rule's scope of application, conditional judgment, and execution parameters.

[0049] In one embodiment, configuration update request information sent by the client is obtained, the configuration update request information is parsed, and data involved in the update operation presented in the form of a rule set is obtained. It is identified whether there is a target keyword matching a preset keyword in the data, and context data is obtained based on the location information of the keyword to determine the rule statement corresponding to the target keyword, and all key parameters in the rule statement are determined, such as constants, variables, and applicable scope.

[0050] Step S102: Merge the rule parameters according to the preset rule merging conditions to obtain a target rule set, determine a group of target rules in the target rule set that contain the same key parameters as a dependent rule group, and determine the target rules that do not contain the same key parameters as non-dependent rules, and the number of the non-dependent rules is multiple.

[0051] In one embodiment, the preset rule merging conditions refer to the various conditions or standards based on which multiple rules are merged. Through the rule merging conditions, rules with similar characteristics or satisfying specific relationships can be integrated together to simplify the management of the rule set and improve the efficiency of rule execution. The preset rule merging conditions can include merging with the same condition range, merging with the same action, or merging with the same target. For example, there are three rules, namely "If the temperature is greater than 30 degrees Celsius, turn on the air conditioner", "If the temperature is greater than 30 degrees Celsius, turn on the fan", and "If the temperature is greater than 30 degrees Celsius, adjust the indoor light brightness to low". The conditions of these three rules are "temperature is greater than 30 degrees Celsius", so they can be merged into one rule, that is, turning on the air conditioner, turning on the fan, and adjusting the light brightness to low when the temperature is greater than 30 degrees Celsius. Since the target update data includes multiple rules, after some rules are merged, the unmerged rules are also included. The set consisting of the merged rules and the unmerged rules is called the target rule set, and it is determined whether each target rule in the target rule set contains the same key parameters. A group of target rules containing the same key parameters are determined as a dependent rule group, and target rules that do not contain the same key parameters are determined as non-dependent rules. For example, rule A contains the key parameter "recharge amount 1,000 yuan", rule B contains the key parameter "recharge amount 1,000 yuan", rule C contains the key parameter "temperature is 30 degrees Celsius", rule D contains the key parameter "temperature is 30 degrees Celsius", rule E contains the key parameter "turn on the lights", and rule F contains the key parameter "turn on the air conditioner", then it can be determined that rules A and B are a group of dependent rules, rules C and D are a group of dependent rules, rule E is a non-dependent rule, and rule F is also a non-dependent rule.

[0052] Step S103: determine the first processing priority of each dependent rule according to the transmission path of the same key parameters in each dependent rule group, and determine the second processing priority of each non-dependent rule according to the association relationship between each key parameter in the non-dependent rule, and the first processing priority is greater than the second processing priority.

[0053] Among them, the transmission path refers to the combination of a series of nodes and links that data passes through from the sending end to the receiving end. The transmission path of the key parameter can refer to the transmission link from the key parameter to each rule statement. For example, if rule A is "If the age is between 18 and 25, recommend fashion products", and rule B is "If the amount of fashion products purchased exceeds 1,000 yuan, then a 10% discount is given", where "fashion products" is the key parameter, and rule B is executed after rule A is executed, then the transmission path of "fashion products" is from rule A to rule B, that is, the transmission node of the key parameter is from rule A node to rule B node. The first processing priority is used to indicate the priority order for format conversion of each dependent rule. The second processing priority is used to indicate the priority order for format conversion of each non-dependent rule. In one embodiment, the greater the degree of dependency between target rules, the higher the priority for format conversion. There is a dependency relationship between dependent rules, and there is no dependency relationship between non-dependent rules. Therefore, the first processing priority corresponding to the dependent rule is greater than the second processing priority between non-dependent rules. In one embodiment, the number of transmission nodes is determined based on the transmission path of the same key parameter in each dependency rule group. The more transmission nodes there are, the greater the degree of dependence of the dependency rule group can be considered. For example, if the transmission path of the same key parameter in the first dependency rule group contains 4 transmission nodes and the transmission path of the same key parameter in the second dependency rule group contains 2 transmission nodes, then it can be considered that the degree of dependence of each dependency rule in the first dependency rule group is greater and the degree of dependence of each dependency rule in the second dependency rule group is less. The first processing priority is that the priority of the first dependency rule is greater than the priority of the second dependency rule. The association relationship between key parameters can be used to represent the degree of dependence in non-dependent rules. The more key parameters associated in the non-dependent rules, the greater the degree of dependence and the corresponding higher priority. For example, if the number of associated key parameters in the first non-dependent rule is 4 and the number of associated key parameters in the second non-dependent rule is 3, then the second processing priority is that the priority of the first non-dependent rule is greater than the priority of the second non-dependent rule.

[0054] Step S104: convert the format of the dependent rule according to the first processing priority to obtain first updated data, and convert the format of the non-dependent rule according to the second processing priority to obtain second updated data.

[0055] Exemplarily, the transmission path of the same key parameter in the first dependent rule group contains 4 transmission nodes, and the transmission path of the same key parameter in the second dependent rule group contains 2 transmission nodes. The first processing priority is determined to be that the priority of the first dependent rule is greater than the priority of the second dependent rule, and according to the first processing priority, the dependent rules in the first dependent rule group are first format-converted, and then the dependent rules in the second dependent rule group are format-converted to obtain the first updated data. The number of key parameters associated in the first non-dependent rule is 4, and the number of key parameters associated in the second non-dependent rule is 3. The second processing priority is that the priority of the first non-dependent rule is greater than the priority of the second non-dependent rule. After obtaining the first updated data, the first non-dependent rule is format-converted, and after the format conversion of the first non-dependent rule is completed, the second non-dependent rule is format-converted to obtain the second updated data.

[0056] The embodiment of the present application obtains configuration update request information, parses the configuration update request information to obtain target update data of the rule set type, identifies the rule parameters corresponding to the preset keywords in the target update data and multiple key parameters in the rule parameters; merges the rule parameters according to the preset rule merging conditions to obtain a target rule set, determines a group of target rules containing the same key parameters in the target rule set as a dependent rule group, and determines the target rules that do not contain the same key parameters as non-dependent rules, and the number of non-dependent rules is multiple; determines the first processing priority of each dependent rule according to the transmission path of the same key parameters in each dependent rule group, and determines the second processing priority of each non-dependent rule according to the association relationship of each key parameter in the non-dependent rule, the first processing priority being greater than the second processing priority; formats the dependent rules according to the first processing priority to obtain the first update data, and formats the non-dependent rules according to the second processing priority to obtain the second update data. In the above scheme, by merging the rule parameters, the management of the rule set can be simplified and the execution efficiency of the rules can be improved. By analyzing the degree of dependence between the rules in the rule set and determining the corresponding format conversion priority, the timeliness and accuracy of data format conversion are improved, and the system operation performance is correspondingly improved.

[0057] In one embodiment, after obtaining the configuration update request information, the method further includes: parsing the configuration update request information to obtain target update data in the form of key-value pairs, storing the target update data in a dictionary set, and converting the target update data in the dictionary set into update data in a target storage format through a preset call function. A dictionary is a data structure with key-value pairs as elements, which can accommodate multiple key-value pairs and quickly access corresponding values ​​through keys. In one embodiment, the configuration update request information is parsed to obtain target update data in the form of key-value pairs, and the target update data is written into a dictionary set, and the target update data in the dictionary set is converted into data in a json format through a preset call function.

[0058] This embodiment of the present application parses configuration update request information to obtain target update data in the form of key-value pairs, stores the target update data in a dictionary set, and converts the target update data in the dictionary set into update data in the target storage format through a preset call function. This facilitates rapid lookup and access to corresponding values ​​based on specific keys in the dictionary set, as well as the addition, modification, or deletion of key-value pairs, adapting to dynamic data changes and facilitating the modification of abnormal data.

[0059] In one embodiment, after obtaining the second update data, the method further includes: encrypting the first update data and the second update data to obtain encrypted data, wherein the encrypted data includes encrypted content and an encrypted timestamp; generating current version information based on the encrypted content and the encrypted timestamp, and sending the current version information and the encrypted data to the target program. Exemplarily, sensitive information in the first encrypted data and the second encrypted data is identified, and the sensitive information is encrypted using the AES (Advanced Encryption Standard) encryption algorithm to obtain encrypted update information and an encrypted timestamp, wherein the encrypted timestamp is a digital signature technology that is a certificate formed after encryption that can indicate the existence of specific data at a specific point in time. After generating the encrypted content and the encrypted timestamp, a hash function is used to operate on the encrypted content to generate a fixed-length hash value, extract key time information such as date, time point, etc. from the encrypted timestamp, and normalize it into a specific format, and combine the hash value and the processed time information according to certain rules. For example, time information can be appended to the hash value, or the two can be combined into a new string or data structure through a certain algorithm. The generated combined information is encoded to generate the current version information, and the current version information and encrypted data are sent to the target program, so that the target program can obtain the latest configuration information through the SDK and apply it to the actual running environment.

[0060] This embodiment of the present application encrypts the first and second update data to obtain encrypted content and an encrypted timestamp, generates current version information based on the encrypted content and the encrypted timestamp, and sends the current version information and the encrypted data to the target program. This solution effectively protects sensitive configuration information through encryption, reducing the risk of information leakage. The generated version information allows for easy tracking and rollback of historical configurations, enhancing system maintainability and reliability.

[0061] Figure 2 This is a flow chart of a method for identifying key parameters provided by an embodiment of the present application, such as Figure 2 Shown, including:

[0062] Step S201, obtain configuration update request information, parse the configuration update request information to obtain target update data of the rule set type, identify the rule parameters corresponding to the variable type keywords in the target update data and the element parameters in the rule parameters, identify the rule parameters corresponding to the action type keywords in the target update data and the operation parameters in the rule parameters, identify the rule parameters corresponding to the judgment type keywords in the target update data and the condition parameters in the rule parameters.

[0063] Preset keywords can include variable keywords, action keywords, and judgment keywords. Variable keywords are special words used to define and manipulate variables, or to indicate avoidance, such as price, temperature, and coupon amount. Action keywords are used to represent operational behaviors, such as "issuance" and "debugging." Judgment keywords are used to represent terms that connect judgment conditions, such as "meets," "greater than," "less than," and "exceeds." Element parameters can be values ​​that define the specific attributes or characteristics of each element in a rule, such as user name, operation target, age, and gender. Operation parameters are parameters that specify the specific action to be performed and how to execute it when a rule in a rule set is triggered, such as sending a voucher, adjusting the air conditioning temperature, and adjusting the brightness of the lights. Condition parameters can be various specific parameter values ​​used in a rule to determine whether a condition is met, such as whether the consumption amount is greater than 1,000 yuan or whether the indoor temperature is above 30 degrees Celsius. In one embodiment, rule parameters corresponding to variable-type keywords in target update data and element parameters in rule parameters are identified, rule parameters corresponding to action-type keywords in target update data and operation parameters in rule parameters are identified, and rule parameters corresponding to judgment-type keywords in target update data and condition parameters in rule parameters are identified.

[0064] Step S202: Merge the rule parameters according to the preset rule merging conditions to obtain a target rule set, determine a group of target rules in the target rule set that contain the same element parameters as dependent rules as a dependent rule group, and determine the target rules that do not contain the same element parameters as non-dependent rules, and the number of non-dependent rules is multiple.

[0065] In one embodiment, since the rule parameters are merged in advance according to the preset rule merging conditions, and the preset rule merging conditions usually include similar condition merging and identical operation merging, the target rules in the rule set generated after the merger will no longer contain identical condition parameters and identical operation parameters. Therefore, non-dependent rules and dependent rules are determined based on the same element parameters, thereby improving the accuracy of rule type judgment.

[0066] Step S203: determine the first processing priority of each dependent rule according to the transmission path of the same key parameters in each dependent rule group, and determine the second processing priority of each non-dependent rule according to the association relationship between each key parameter in the non-dependent rule, and the first processing priority is greater than the second processing priority.

[0067] Step S204: Format-convert the dependent rules according to the first processing priority to obtain first updated data, and format-convert the non-dependent rules according to the second processing priority to obtain second updated data.

[0068] The embodiment of the present application identifies rule parameters corresponding to variable-type keywords and element parameters in the rule parameters in the target update data, identifies rule parameters corresponding to action-type keywords and operation parameters in the rule parameters in the target update data, and identifies rule parameters corresponding to judgment-type keywords and condition parameters in the rule parameters in the target update data. The above scheme can facilitate accurate identification of the dependency relationship between target rules, improving the accuracy of determining the degree of dependency and determining the processing priority.

[0069] In one embodiment, the second processing priority of each non-dependent rule is determined based on the association relationship between each key parameter in the non-dependent rule, including: generating a dependency matrix based on the first association relationship between each condition parameter and each operation parameter in the non-dependent rule, the second association relationship between each condition parameter, and the third association relationship between each operation parameter, and determining the second processing priority of each non-dependent rule based on the dependency value in the dependency matrix.

[0070] Among them, the dependency matrix is ​​a tool for visually displaying the interdependence between various elements in a system, project or process. It is presented in the form of a matrix, with rows and columns representing different elements respectively. The presence of dependency between elements and the type and degree of dependency are indicated by marking in the corresponding cells. In one embodiment, the first correlation coefficient between the conditional parameters and the operating parameters can be predetermined, such as 0.6, the second correlation coefficient between the conditional parameters can be 0.5, and the third correlation coefficient between the operating parameters can be 0.4. Based on the dependency relationship of the parameters in the non-dependent rules, a matrix such as Figure 3 The dependency matrix diagram of the non-dependent rules shown is as follows: Figure 3 As shown, in the current non-dependent rule, there is a first correlation relationship between the operating parameters and the conditional parameters, and the corresponding first correlation coefficient is 0.6. If there is no second correlation relationship between the conditional parameters, the corresponding first correlation coefficient is 0. The third correlation relationship between the operating parameters and the operating parameters has a corresponding third correlation coefficient of 0.4. The corresponding correlation coefficients are summed and calculated to determine the dependency value as 1.0, which is displayed in the dependency matrix. After determining the dependency value corresponding to each non-dependent rule, the dependency values ​​are sorted in descending order to determine the second processing priority of each non-dependent rule, wherein the larger the dependency value, the higher the corresponding second processing priority.

[0071] The embodiment of the present application generates a dependency matrix based on the first association relationship between each condition parameter and each operating parameter in the non-dependent rule, the second association relationship between each condition parameter, and the third association relationship between each operating parameter, and determines the second processing priority of each non-dependent rule according to the dependency value in the dependency matrix. In the above scheme, by determining the association relationship corresponding to each non-dependent rule and generating a dependency matrix based on the corresponding association relationship, the complex dependency relationship between parameters and the degree of dependency can be presented in an intuitive tabular form, thereby improving the efficiency and accuracy of determining the second priority.

[0072] In one embodiment, the second processing priority of each non-dependent rule is determined based on the association relationship of each key parameter in the non-dependent rule, including: determining the associated data volume of the non-dependent rule based on the association relationship between each condition parameter and each operation parameter in the non-dependent rule, and determining the second processing priority of each non-dependent rule based on the associated data volume. Wherein, the associated data volume is used to represent the number of parameter association parameter combinations existing in the non-dependent rule. For example, if condition parameter 1 is associated with condition parameter 2, condition parameter 3 is associated with condition parameter 1, operation parameter 1 is associated with condition parameter 3, and operation parameter 2 is associated with condition parameter 2 in the non-dependent rule, then the associated data volume 4 of the non-dependent rule is determined, and the associated data volume of each non-dependent rule is determined by the associated data volume determination method, and the associated data volume corresponding to each non-dependent rule is sorted in order from large to small, and the second processing priority is determined based on the sorting result. It can be understood that the larger the associated data volume of the non-dependent rule, the higher the second processing priority.

[0073] In the embodiment of the present application, the amount of associated data of the non-dependent rule is determined based on the association between each condition parameter and each operation parameter in the non-dependent rule, and the second processing priority of each non-dependent rule is determined based on the amount of associated data. In the above scheme, the second processing priority of the non-dependent rule can be determined by the amount of associated data of each non-dependent rule, thereby improving the efficiency of determining the second processing priority.

[0074] Figure 4 This is a flow chart of a method for determining a first processing priority provided by an embodiment of the present application. Figure 4 Shown, including:

[0075] Step S301: Acquire configuration update request information, parse the configuration update request information to obtain target update data of a rule set type, and identify rule parameters corresponding to preset keywords in the target update data and multiple key parameters in the rule parameters.

[0076] Step S302: Merge the rule parameters according to the preset rule merging conditions to obtain a target rule set, determine a group of target rules in the target rule set that contain the same key parameters as a dependent rule group, and determine the target rules that do not contain the same key parameters as non-dependent rules, and the number of the non-dependent rules is multiple.

[0077] Step S303: determine the data transmission direction and data transmission distance according to the transmission path of the same element parameters in each of the dependency rule groups, determine the format conversion order of each of the dependency rule groups according to the data transmission distance, and determine the first processing priority of each of the dependency rules according to the data transmission direction and the format conversion order.

[0078] The data transmission direction may refer to the direction of data flow when transmitted between different devices, systems, or network nodes. The data transmission distance may refer to the number of transmission nodes traversed during the data transmission process; the greater the number of data transmission nodes traversed, the longer the data transmission distance. In one embodiment, if the transmission path for the same element parameter is rule node A → rule node B → rule node D → rule node F, the corresponding data transmission direction is A → B → D → F, and the data transmission distance is 4 nodes. After determining each dependent rule group, the format conversion order of each dependent rule group is determined based on the data transmission distance of each group. For example, if the data transmission distance of group ① is 5 nodes, the data transmission distance of group ⑤ is 3 nodes, and the data transmission distance of group ⑧ is 2 nodes, then the format conversion order of each dependent rule group is group ① → group ⑤ → group ⑧. However, since group ① includes multiple dependent rules, the first processing priority of each dependent rule in group ① can be determined based on the data transmission direction. For example, if the data transmission direction of group ① is A → B → D → F, then the first processing priority corresponding to group ① is rule A > rule B > rule D > rule F.

[0079] Step S304: determining a second processing priority of each non-dependent rule according to the association relationship between each key parameter in the non-dependent rule, wherein the first processing priority is greater than the second processing priority.

[0080] Step S305: convert the format of the dependent rule according to the first processing priority to obtain first updated data, and convert the format of the non-dependent rule according to the second processing priority to obtain second updated data.

[0081] The embodiment of the present application determines the data parameter direction and data transmission distance based on the transmission path of the same element parameters in each dependency rule group, determines the format conversion order of each dependency rule group based on the data transmission distance, and determines the first processing priority of each dependency rule based on the data parameter direction and format conversion order. In the above scheme, the priority of each dependency rule group and the first processing priority of each dependency rule in each dependency rule group can be accurately determined based on the data transmission distance and data transmission direction, thereby improving the accuracy of the first processing priority.

[0082] Figure 5 This is a structural diagram of a target update data format conversion device provided by an embodiment of the present application. Figure 5 Shown, including:

[0083] The request information parsing module 41 is used to obtain configuration update request information, parse the configuration update request information, and obtain target update data of the rule set type;

[0084] A key parameter identification module 42 is used to identify the rule parameters corresponding to the preset keywords in the target update data and multiple key parameters in the rule parameters;

[0085] A rule merging module 43 is configured to merge the rule parameters according to a preset rule merging condition to obtain a target rule set;

[0086] A rule type determination module 44 is configured to determine a group of target rules in the target rule set that contain the same key parameters as a dependent rule group, and determine target rules that do not contain the same key parameters as non-dependent rules, where the number of the non-dependent rules is multiple;

[0087] a processing priority determination module 45, configured to determine a first processing priority of each dependent rule according to a transmission path of the same key parameter in each dependent rule group, and to determine a second processing priority of each non-dependent rule according to an association relationship between the key parameters in the non-dependent rules, wherein the first processing priority is greater than the second processing priority;

[0088] The format conversion module 46 is configured to perform format conversion on the dependent rule according to the first processing priority to obtain first updated data, and perform format conversion on the non-dependent rule according to the second processing priority to obtain second updated data.

[0089] The embodiment of the present application obtains configuration update request information, parses the configuration update request information to obtain target update data of the rule set type, identifies the rule parameters corresponding to the preset keywords in the target update data and multiple key parameters in the rule parameters; merges the rule parameters according to the preset rule merging conditions to obtain the target rule set, determines a group of target rules containing the same key parameters in the target rule set as a dependent rule group, and determines the target rules that do not contain the same key parameters as non-dependent rules, and the number of non-dependent rules is multiple; determines the first processing priority of each dependent rule according to the transmission path of the same key parameters in each dependent rule group, and determines the second processing priority of each non-dependent rule according to the association relationship of each key parameter in the non-dependent rule, the first processing priority is greater than the second processing priority; formats the dependent rules according to the first processing priority to obtain the first update data, and formats the non-dependent rules according to the second processing priority to obtain the second update data. In the above scheme, by merging the rule parameters, the management of the rule set can be simplified and the execution efficiency of the rules can be improved. By analyzing the degree of dependence between the rules in the rule set and determining the corresponding format conversion priority, the timeliness and accuracy of data format conversion are improved, and the system operation performance is correspondingly improved.

[0090] In a possible embodiment, the preset keywords include variable keywords, action keywords, and judgment keywords; the key parameter identification module 42 is used to:

[0091] Identify the rule parameters corresponding to the variable-type keywords and the element parameters in the rule parameters in the target update data, identify the rule parameters corresponding to the action-type keywords and the operation parameters in the rule parameters in the target update data, and identify the rule parameters corresponding to the judgment-type keywords and the condition parameters in the rule parameters in the target update data;

[0092] The rule type determination module 44 is configured to determine a group of target rules in the target rule set that contain the same element parameters as dependent rules or a dependent rule group, and determine target rules that do not contain the same element parameters as non-dependent rules.

[0093] In one possible embodiment, the processing priority determination module 45 is configured to:

[0094] A dependency matrix is ​​generated based on the first association relationship between each condition parameter and each operation parameter in the non-dependent rule, the second association relationship between each condition parameter, and the third association relationship between each operation parameter, and the second processing priority of each non-dependent rule is determined based on the dependency value in the dependency matrix.

[0095] In one possible embodiment, the processing priority determination module 45 is configured to:

[0096] The associated data volume of the non-dependent rule is determined according to the association relationship between each condition parameter and each operation parameter in the non-dependent rule, and the second processing priority of each non-dependent rule is determined according to the associated data volume.

[0097] In one possible embodiment, the processing priority determination module 45 is configured to:

[0098] The data parameter direction and data transmission distance are determined according to the transmission path of the same element parameters in each of the dependency rule groups, the format conversion order of each dependency rule group is determined according to the data transmission distance, and the first processing priority of each dependency rule is determined according to the data parameter direction and the format conversion order.

[0099] In one possible embodiment, the format conversion module 46 is configured to:

[0100] The configuration update request information is parsed to obtain target update data of key-value pair type, the target update data is stored in a dictionary set, and the target update data of the dictionary set is converted into update data of a target storage format through a preset calling function.

[0101] In one possible embodiment, the encryption module is used to:

[0102] encrypting the first update data and the second update data to obtain encrypted data, wherein the encrypted data includes encrypted content and an encryption timestamp;

[0103] The version information generation module is used to generate current version information according to the encrypted content and the encrypted timestamp, and send the current version information and the encrypted data to the target program.

[0104] An embodiment of the present application further provides an electronic device, and the target update data format conversion device can integrate a target update data format conversion device provided in an embodiment of the present application. Figure 6 This is a schematic diagram of a target update data format conversion device provided by an embodiment of the present application, with reference to Figure 6 The target update data format conversion device includes: an input device 53, an output device 54, a memory 52, and one or more processors 51; the memory 52 is used to store one or more programs; when the one or more programs are executed by the one or more processors 51, the one or more processors 51 implement the target update data format conversion method provided in the above embodiment. The input device 53, the output device 54, the memory 52, and the processor 51 can be connected by a bus or other means. Figure 6 The bus connection is taken as an example.

[0105] The memory 52 is a computing device-readable storage medium that can be used to store software programs, computer executable programs, and modules, such as the program instructions / modules corresponding to the format conversion method for target update data provided in any embodiment of the present application. The memory 52 may mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system and at least one application required for a function; the data storage area can store data created according to the use of the device, etc. In addition, the memory 52 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some instances, the memory 52 may further include a memory remotely located relative to the processor 51, and these remote memories may be connected to the device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0106] The input device 53 may be used to receive input digital or character information and generate key signal input related to user settings and function control of the device. The output device 54 may include a display device such as a display screen.

[0107] The processor 51 executes various functional applications and data processing of the device by running the software programs, instructions and modules stored in the memory 52, that is, realizes the format conversion method of the target update data mentioned above.

[0108] The target update data format conversion device, apparatus, and computer provided above can be used to execute the target update data format conversion method provided in any of the above embodiments, and have corresponding functions and beneficial effects.

[0109] The present application also provides a storage medium storing computer-executable instructions. When executed by a computer processor, the computer-executable instructions are used to perform the target update data format conversion method provided in the above embodiment. The target update data format conversion method includes:

[0110] Obtaining configuration update request information, parsing the configuration update request information to obtain target update data of a rule set type, and identifying rule parameters corresponding to preset keywords in the target update data and multiple key parameters in the rule parameters;

[0111] Merging the rule parameters according to a preset rule merging condition to obtain a target rule set, determining a group of target rules in the target rule set that contain the same key parameters as a dependent rule group, and determining target rules that do not contain the same key parameters as non-dependent rules, where the number of the non-dependent rules is multiple;

[0112] Determining a first processing priority of each dependent rule according to a transmission path of the same key parameter in each dependent rule group, and determining a second processing priority of each non-dependent rule according to an association relationship between the key parameters in the non-dependent rules, wherein the first processing priority is greater than the second processing priority;

[0113] The dependent rules are format-converted according to the first processing priority to obtain first updated data, and the non-dependent rules are format-converted according to the second processing priority to obtain second updated data.

[0114] Storage medium - any of various types of memory devices or storage devices. The term "storage medium" is intended to include: installation media, such as CD-ROMs, floppy disks, or tape drives; computer system memory or random access memory, such as DRAM, DDR RAM, SRAM, EDO RAM, Rambus RAM, etc.; non-volatile memory, such as flash memory, magnetic media (such as hard disks or optical storage); registers or other similar types of memory elements, etc. Storage media may also include other types of memory or combinations thereof. In addition, the storage medium may be located in the first computer system in which the program is executed, or it may be located in a different second computer system that is connected to the first computer system via a network (such as the Internet). The second computer system can provide program instructions to the first computer for execution. The term "storage medium" may include two or more storage media that can reside in different locations (e.g., in different computer systems connected via a network). The storage medium can store program instructions (e.g., embodied as a computer program) that can be executed by one or more processors.

[0115] Of course, the storage medium containing computer-executable instructions provided in an embodiment of the present application is not limited to the format conversion method of the target update data as described above, and can also execute related operations in the format conversion method of the target update data provided in any embodiment of the present application.

[0116] The target update data format conversion device, equipment and storage medium provided in the above embodiments can execute the target update data format conversion method provided in any embodiment of the present application. For technical details not described in detail in the above embodiments, please refer to the target update data format conversion method provided in any embodiment of the present application.

[0117] The above are only preferred embodiments of the present application and the technical principles employed. The present application is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions that are possible for those skilled in the art will not depart from the scope of protection of the present application. Therefore, although the present application has been described in more detail through the above embodiments, the present application is not limited to the above embodiments and may include more other equivalent embodiments without departing from the concept of the present application. The scope of the present application is determined by the scope of the claims.

Claims

1. A method for converting the format of target update data, characterized in that: include: Obtaining configuration update request information, parsing the configuration update request information to obtain target update data of a rule set type, and identifying rule parameters corresponding to preset keywords in the target update data and multiple key parameters in the rule parameters; Merging the rule parameters according to a preset rule merging condition to obtain a target rule set, determining a group of target rules in the target rule set that contain the same key parameters as a dependent rule group, and determining target rules that do not contain the same key parameters as non-dependent rules, where the number of the non-dependent rules is multiple; Determining a first processing priority of each dependent rule according to a transmission path of the same key parameter in each dependent rule group, and determining a second processing priority of each non-dependent rule according to an association relationship between the key parameters in the non-dependent rules, wherein the first processing priority is greater than the second processing priority; The dependent rules are format-converted according to the first processing priority to obtain first updated data, and the non-dependent rules are format-converted according to the second processing priority to obtain second updated data.

2. The method for converting the target update data format according to claim 1, wherein: The preset keywords include variable keywords, action keywords, and judgment keywords. The identifying of the rule parameters corresponding to the preset keywords in the target update data and a plurality of key parameters in the rule parameters includes: Identify the rule parameters corresponding to the variable-type keywords and the element parameters in the rule parameters in the target update data, identify the rule parameters corresponding to the action-type keywords and the operation parameters in the rule parameters in the target update data, and identify the rule parameters corresponding to the judgment-type keywords and the condition parameters in the rule parameters in the target update data; Accordingly, determining a group of target rules in the target rule set that contain the same key parameters as a dependent rule group, and determining target rules that do not contain the same key parameters as non-dependent rules, includes: A group of target rules containing the same element parameters in the target rule set are determined as dependent rules or a dependent rule group, and target rules not containing the same element parameters are determined as non-dependent rules.

3. The method for converting the target update data format according to claim 2, wherein: Determining the second processing priority of each non-dependent rule according to the association relationship between the key parameters in the non-dependent rule includes: A dependency matrix is ​​generated based on the first association relationship between each condition parameter and each operation parameter in the non-dependent rule, the second association relationship between each condition parameter, and the third association relationship between each operation parameter, and the second processing priority of each non-dependent rule is determined based on the dependency value in the dependency matrix.

4. The method for converting the format of target update data according to claim 2, wherein: Determining the second processing priority of each non-dependent rule according to the association relationship between the key parameters in the non-dependent rule includes: The associated data volume of the non-dependent rule is determined according to the association relationship between each condition parameter and each operation parameter in the non-dependent rule, and the second processing priority of each non-dependent rule is determined according to the associated data volume.

5. The method for converting the format of target update data according to claim 1, wherein: Determining the first processing priority of each of the dependency rules according to the transmission path of the same key parameter in each of the dependency rule groups includes: The data transmission direction and data transmission distance are determined according to the transmission path of the same element parameters in each of the dependency rule groups, the format conversion order of each of the dependency rule groups is determined according to the data transmission distance, and the first processing priority of each of the dependency rules is determined according to the data transmission direction and the format conversion order.

6. The method for converting the format of target update data according to claim 1, wherein: After obtaining the configuration update request information, the method further includes: The configuration update request information is parsed to obtain target update data of key-value pair type, the target update data is stored in a dictionary set, and the target update data of the dictionary set is converted into update data of a target storage format through a preset calling function.

7. The method for converting the format of target update data according to claim 1, wherein: After obtaining the second update data, the method further includes: encrypting the first update data and the second update data to obtain encrypted data, wherein the encrypted data includes encrypted content and an encryption timestamp; Current version information is generated according to the encrypted content and the encrypted timestamp, and the current version information and the encrypted data are sent to a target program.

8. A target update data format conversion device, characterized in that: include: A request information parsing module, configured to obtain configuration update request information, parse the configuration update request information, and obtain target update data of a rule set type; A key parameter identification module, configured to identify a rule parameter corresponding to a preset keyword in the target update data and a plurality of key parameters in the rule parameter; A rule merging module is used to merge the rule parameters according to preset rule merging conditions to obtain a target rule set; a rule type determination module, configured to determine a group of target rules in the target rule set that contain the same key parameters as a dependent rule group, and determine target rules that do not contain the same key parameters as non-dependent rules, where the number of the non-dependent rules is multiple; a processing priority determination module, configured to determine a first processing priority of each dependent rule according to a transmission path of the same key parameter in each dependent rule group, and to determine a second processing priority of each non-dependent rule according to an association relationship between the key parameters in the non-dependent rules, wherein the first processing priority is greater than the second processing priority; The format conversion module is used to perform format conversion on the dependent rules according to the first processing priority to obtain first updated data, and to perform format conversion on the non-dependent rules according to the second processing priority to obtain second updated data.

9. An electronic device, comprising: one or more processors; A storage device for storing one or more programs, when the one or more programs are executed by the one or more processors, enables the one or more processors to implement the format conversion method of target update data according to any one of claims 1-7.

10. A storage medium storing computer-executable instructions, wherein the computer-executable instructions, when executed by a computer processor, are used to execute the method for format conversion of target update data according to any one of claims 1 to 7.

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