Data processing method and device, equipment and storage medium

Abstract

The embodiment of the invention discloses a data processing method and device, equipment and a storage medium, and relates to the technical field of computers. The method comprises the steps that parameter configuration information stored in a far-end configuration center is obtained, the parameter configuration information comprises a data set of a first type of parameters and a parameter expression of a second type of parameters, an initial expression of a local target parameter is converted into a first target character string according to the parameter expression, and the first target character string comprises a data set of the first type of parameters and a data set of the second type of parameters; the initial expression comprises at least one second type of parameters, the first target character string comprises a plurality of first type of parameters and operators and does not comprise the second type of parameters, and a first parameter value of the target parameter is determined according to the first target character string and a data set of the plurality of first type of parameters contained in the first target character string. By adopting the technical scheme, the code development cost can be reduced, the effective efficiency of the second type of parameter change is improved, and the accuracy of the parameter value is ensured.

Description

Technical Field

[0001] The embodiments of the present disclosure relate to the field of computer technology, and in particular, to data processing methods, devices, equipment, and storage media. Background Art

[0002] At present, in the operation of business systems, it is usually involved in the calculation of a wide variety of business-related parameters, and there may be associations between different parameters, that is, there are derived parameters. Derived parameters need to be calculated based on multiple other parameters, and there may be derived parameters among these multiple parameters. The calculation formulas of each parameter are currently written in the form of code. When the calculation formula of a derived parameter changes, the calculation formulas of the derived parameter and the parameters further derived from the derived parameter must be adjusted accordingly. Therefore, a large amount of code needs to be manually modified. Summary of the invention

[0003] The embodiments of the present disclosure provide a data processing method, apparatus, storage medium, and device, which can optimize existing data processing solutions.

[0004] In a first aspect, an embodiment of the present disclosure provides a data processing method, including:

[0005] Acquire parameter configuration information stored in a remote configuration center, wherein the parameter configuration information includes a data set of first-category parameters and parameter expressions of second-category parameters, and the parameter expressions are determined based on at least two of the first-category parameters;

[0006] According to the parameter expression in the parameter configuration information, converting an initial expression of a local target parameter into a first target string, wherein the initial expression includes at least one parameter of the second category, and the first target string includes a plurality of parameters of the first category and operators, and does not include the parameters of the second category;

[0007] A first parameter value of the target parameter is determined according to the first target character string and a data set of a plurality of first-category parameters contained in the first target character string.

[0008] In a second aspect, the present disclosure also provides a data processing device, including:

[0009] A configuration information acquisition module, used to acquire parameter configuration information stored in a remote configuration center, wherein the parameter configuration information includes a data set of first-category parameters and parameter expressions of second-category parameters, and the parameter expressions are determined based on at least two of the first-category parameters;

[0010] a string conversion module, configured to convert an initial expression of a local target parameter into a first target string according to the parameter expression in the parameter configuration information, wherein the initial expression includes at least one parameter of the second category, and the first target string includes a plurality of parameters of the first category and operators, and does not include the parameters of the second category;

[0011] A parameter value determination module is used to determine a first parameter value of the target parameter according to the first target character string and a data set of a plurality of first-category parameters contained in the first target character string.

[0012] In a third aspect, an embodiment of the present disclosure further provides an electronic device, the electronic device comprising:

[0013] one or more processors;

[0014] a storage device for storing one or more programs,

[0015] When the one or more programs are executed by the one or more processors, the one or more processors implement the data processing method provided by the embodiment of the present disclosure.

[0016] In a fourth aspect, an embodiment of the present disclosure further provides a storage medium containing computer executable instructions, which, when executed by a computer processor, are used to execute the data processing method provided by the embodiment of the present disclosure.

[0017] The data processing scheme provided by the embodiment of the present disclosure obtains parameter configuration information stored in a remote configuration center, wherein the parameter configuration information includes a data set of first-category parameters and a parameter expression of second-category parameters, the parameter expression is determined based on at least two first-category parameters, and according to the parameter expression, an initial expression of a local target parameter is converted into a first target string, wherein the initial expression contains at least one second-category parameter, the first target string contains multiple first-category parameters and operators, and does not contain second-category parameters, and a first parameter value of the target parameter is determined according to the first target string and the data set of multiple first-category parameters contained in the first target string. By adopting the above technical solution, when it is necessary to determine the parameter value of the target parameter containing the second category parameter, the initial expression of the target parameter is dynamically converted into a string including multiple first category parameters and operators according to the parameter configuration information containing the parameter expression obtained in the remote configuration center, and then the operation is performed according to the data set of the first category parameters to obtain the corresponding parameter value. When it is necessary to modify the calculation method of the second category parameter, it is sufficient to modify the parameter expression stored in the remote configuration center, without modifying the local initial expression, that is, there is no need to modify the local code file, thereby reducing the code development cost, improving the efficiency of the second category parameter changes, and ensuring the accuracy of the parameter value. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and the originals and elements are not necessarily drawn to scale.

[0019] Figure 1 A schematic diagram of an application scenario provided by an embodiment of the present disclosure;

[0020] Figure 2 A flowchart of a data processing method provided by an embodiment of the present disclosure;

[0021] Figure 3 A flowchart of another data processing method provided by an embodiment of the present disclosure;

[0022] Figure 4 A schematic diagram of a data processing process provided by an embodiment of the present disclosure;

[0023] Figure 5 A schematic diagram of the structure of a data processing device provided by an embodiment of the present disclosure;

[0024] Figure 6 A schematic diagram of the structure of an electronic device provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0025] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments described herein, which are instead provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0026] It should be understood that the various steps described in the method embodiments of the present disclosure may be performed in different orders and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present disclosure is not limited in this respect.

[0027] The term "including" and its variations used herein are open inclusions, i.e., "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". The relevant definitions of other terms will be given in the following description.

[0028] It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0029] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0030] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0031] It is understandable that before using the technical solutions disclosed in the embodiments of the present disclosure, the types, scope of use, usage scenarios, etc. of the personal information involved in the present disclosure should be informed to the user and the user's authorization should be obtained in an appropriate manner in accordance with relevant laws and regulations.

[0032] For example, in response to receiving an active request from a user, a prompt message is sent to the user to clearly prompt the user that the operation requested to be performed will require obtaining and using the user's personal information. Thus, the user can autonomously choose whether to provide personal information to software or hardware such as an electronic device, application, server, or storage medium that performs the operation of the technical solution of the present disclosure according to the prompt message.

[0033] As an optional but non-limiting implementation, in response to receiving an active request from the user, the prompt information may be sent to the user in the form of a pop-up window, in which the prompt information may be presented in text form. In addition, the pop-up window may also carry a selection control for the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0034] It is understandable that the above notification and the process of obtaining user authorization are merely illustrative and do not constitute a limitation on the implementation of the present disclosure. Other methods that meet the relevant laws and regulations may also be applied to the implementation of the present disclosure.

[0035] It is understandable that the data involved in this technical solution (including but not limited to the data itself, the acquisition or use of the data) shall comply with the requirements of relevant laws, regulations and relevant provisions.

[0036] In order to facilitate understanding of the technical solutions of the embodiments of the present disclosure, the relevant technologies are introduced below. In the operation of the business system, the calculation of a wide variety of business-related parameters (also referred to as business indicators) is usually involved. Taking the media content publishing system as an example, there are usually some statistical parameters (such as the number of clicks on the media content) or some estimated parameters (such as the estimated number of submissions to the media content), and there may be associations between different parameters, that is, there are derived parameters (recorded as second-category parameters in the embodiments of the present disclosure). The second-category parameters need to be calculated based on multiple other parameters, and the second-category parameters may also exist in these multiple parameters. For example, parameter A is calculated based on parameter B and parameter C, and parameter C is calculated based on parameter D and parameter E, and parameter E is calculated based on parameter F and parameter G. At present, the calculation formulas of parameter A and parameter C are written in code form, such as codes written in a preset code language (such as GO). Assume that A=B+D+F+G, C=D+F+G. When the calculation formula of parameter E changes, such as changing to E=F+H, then the corresponding calculation code of parameter A and the calculation code of parameter C need to be modified. In actual business scenarios, there are often a large number of parameters and many related parameters. Therefore, a large amount of code needs to be modified manually, the code writing cost is high, and the parameter changes cannot take effect in time, affecting the work efficiency and performance of the business system.

[0037] Figure 1 A schematic diagram of an application scenario provided by an embodiment of the present disclosure. Figure 1 As shown, the application scenario includes an electronic device 10 and a remote configuration center 20, wherein the electronic device 10 can be understood as a business end for calculating parameter values ​​of parameters, and the remote configuration center 20 stores parameter configuration information. When the electronic device 10 needs to calculate parameter values, the parameter configuration information can be dynamically obtained from the remote configuration center.

[0038] Figure 2 A flow chart of a data processing method provided in an embodiment of the present disclosure is applicable to a situation in which a parameter value is determined based on parameter configuration information stored in a remote configuration center. The method can be executed by a data processing device, which can be implemented in the form of software and / or hardware. Optionally, it can be implemented by an electronic device, which can be a mobile terminal such as a mobile phone, a smart watch, a tablet computer, and a personal digital assistant, or a device such as a personal computer (PC) or a server.

[0039] like Figure 2 As shown, the method includes:

[0040] Step 201: Obtain parameter configuration information stored in a remote configuration center, wherein the parameter configuration information includes a data set of first-category parameters and parameter expressions of second-category parameters, and the parameter expressions are determined based on at least two of the first-category parameters.

[0041] For example, when it is necessary to obtain parameter configuration information stored in a remote configuration center, the latest parameter configuration information can be directly obtained from the remote configuration center, or the parameter configuration information can be obtained from a preset cache (such as Redis) corresponding to the remote configuration center, without specific limitation.

[0042] Exemplarily, the parameter configuration information can be stored in the remote configuration center according to the variable structure of the parameter. The variable structure can include the variable name (which can be recorded as key), the variable type (which can be recorded as keyType) and the variable calculation logic (which can be recorded as formula). For the first type of parameters, the variable type can be the first type (or called the basic type, such as represented by 0), and the value of the variable calculation logic can be a data set or a data set identifier. The data set identifier is used to obtain the data set. The value of the first type of parameter can be calculated based on the data in the data set. Generally, the physical meaning of the data in the same data set is the same; for the second type of parameters, the variable type can be the second type (or called the derived type, such as represented by 1), and the value of the variable calculation logic is a parameter expression. The parameter expression can include at least two first type parameters and the operational relationship between the at least two first type parameters, such as connecting different first type parameters with operators.

[0043] Step 202: According to the parameter expression in the parameter configuration information, convert the initial expression of the local target parameter into a first target string, wherein the initial expression contains at least one of the second-category parameters, and the first target string contains multiple of the first-category parameters and operators, and does not contain the second-category parameters.

[0044] Exemplarily, the target parameter can be understood as the parameter that needs to be calculated currently. The code of the initial expression of the target parameter is stored locally in the electronic device, and the initial expression can be obtained by reading the code. The initial expression contains at least one second-category parameter. Since the parameter configuration information contains the parameter expression of each second-category parameter, the second-category parameter contained in the initial expression can be converted into the first-category parameter using the parameter expression to express it, and the corresponding target string is obtained. Among them, the string can include symbols involved in the calculation in the expression, including first-category parameters and operators, etc.

[0045] Optionally, the initial expression of the local target parameter is decomposed into an initial string using a preset decomposition method; for each parameter in the initial string, whether the current parameter is the second type parameter is determined according to the parameter configuration information, and if so, the current parameter is replaced with the string of the parameter expression corresponding to the parameter configuration information to obtain an intermediate string; when it is determined that the second type parameter does not exist in the current intermediate string, the current intermediate string is determined as the first target string. In this way, the first target string can be obtained quickly and accurately.

[0046] Exemplarily, the preset disassembly method may include a regular matching method, which identifies the symbols to be extracted contained in the initial expression (if expressed as an equation, it is usually the right side of the equal sign) through a preset regular expression, wherein the symbols to be extracted may include parameters, operators, and target symbols, etc., wherein the target symbols may be mathematical symbols or some special symbols, which are not specifically limited, for example, they may include brackets, etc., and do not include spaces, etc. By reasonably setting the regular expression, characters in the initial expression that may be mistakenly entered due to manual coding errors, such as spaces or other symbols that should not appear in the expression, can be accurately filtered out.

[0047] Exemplarily, the identified symbols to be extracted are arranged in the recognition order to obtain an initial string. For example, the initial expression C=D+E can be decomposed into an initial string: "D", "+", "E".

[0048] Exemplarily, for each symbol contained in the initial string, it is possible to query whether the symbol exists in the parameter configuration information, that is, to determine whether the symbol is a parameter. If so, it is possible to determine whether the current parameter is a second-category parameter according to the variable type in the parameter configuration information; if the symbol does not exist, such as a number in the initial string, it can be retained without replacement. If it is a parameter, but not a second-category parameter, that is, a first-category parameter, it can be retained without replacement. If it is a second-category parameter, the parameter expression of the second-category parameter is obtained from the parameter configuration information, the parameter expression is converted into a corresponding string according to a preset disassembly method, and the second-category parameter in the initial string is replaced with the string. For example, after querying the parameter configuration information, it is determined that E is a second-category parameter, the parameter expression is F+G, and the converted string is "F", "+", "G", and the intermediate string is obtained after replacement: "D", "+", "F", "+", "G". After traversing all symbols in the initial string and replacing all second-category parameters, if there is no second-category parameter in the current intermediate string, the current intermediate string can be determined as the first target string.

[0049] Step 203: Determine a first parameter value of the target parameter according to the first target character string and a data set of a plurality of first-category parameters contained in the first target character string.

[0050] Exemplarily, the basic parameter value of each first-category parameter can be calculated based on the data set of each first-category parameter contained in the first target string, and then the basic parameter value can be calculated using the operator between each first-category parameter in the first target string, and the final calculation result can be determined as the first parameter value of the target parameter. It is also possible that each time a first-category parameter that needs to be calculated is encountered, the basic parameter value of the first-category parameter can be calculated based on the data set of the first-category parameter and used in the calculation.

[0051] The data processing scheme of the disclosed embodiment, when it is necessary to determine the parameter value of the target parameter including the second category parameter, converts the initial expression of the target parameter into a string including multiple first category parameters and operators according to the parameter configuration information obtained in the remote configuration center, and then performs operations according to the data set of the first category parameters to obtain the corresponding parameter value. When it is necessary to modify the calculation method of the second category parameter, it is sufficient to modify the parameter expression stored in the remote configuration center without modifying the local initial expression, that is, there is no need to modify the local code file, thereby reducing the code development cost, improving the efficiency of the second category parameter change, and ensuring the accuracy of the parameter value.

[0052] In some embodiments, the first parameter value of the target parameter is determined according to the first target string and the data set of multiple first-category parameters contained in the first target string, including: determining the current substring to be calculated in the first target string based on the position of a preset symbol in the first target string, wherein the preset symbol is used to indicate the operation priority, and the current substring to be calculated includes a first operand, a substring operator and a second operand; using the substring operator, operating the first operand and the second operand to obtain the current substring value of the current substring to be calculated; replacing the current substring to be calculated in the first target string with the current substring value to update the first target string; judging whether there is a single symbol left in the current first target string, and if so, determining the value of the single symbol as the first parameter value of the target parameter. The advantage of such a setting is that the substring to be calculated can be determined according to the preset symbol used to indicate the operation priority, thereby ensuring the accuracy of the operation result.

[0053] Exemplarily, the preset symbols may include brackets. The maximum subscript (maxIndex) of "(" and the minimum subscript (minIndex) of ")" in the first target string may be first identified, that is, the string contained in the innermost brackets, and the string may be preferentially used as the string to be calculated. If the brackets are not identified, the first target string may be used as the string to be calculated. The length of the current substring to be calculated may be the minimum operation length, which is usually 3. A substring with a length of 3 may be determined from the string to be calculated as the current substring to be calculated. The current substring to be calculated includes a first operand, a substring operator, and a second operand, wherein the operands may be specific numerical values ​​or first-class parameters. After calculating the current substring value of the current substring to be calculated, the current substring to be calculated in the first target string is replaced with the current substring value, and then the next current substring to be calculated is determined, and so on, until a single symbol remains in the current first target string, and the single symbol is the first parameter value of the target parameter.

[0054] When the operand includes the first type of parameter, it is necessary to calculate according to the data set of the first type of parameter. The data in the data set increases dynamically with the change of time, such as the data generated in the last hour, and there may be abnormal data in the newly added data. Therefore, the abnormal data can be filtered during the calculation to ensure the real-time accuracy of the parameter value. Optionally, in some embodiments, when the first operand includes the first first type of parameter and the second operand includes the second first type of parameter, the use of the substring operator to operate the first operand and the second operand to obtain the current substring value of the substring to be calculated includes: determining the target data filtering mode of the first first type of parameter and / or the second first type of parameter according to the type of the substring operator; filtering the first data set of the first first type of parameter and / or the second data set of the second first type of parameter according to the target data filtering mode to obtain the first target data set and the second target data set; using the substring operator to operate the first target data set and the second target data set to obtain the current substring value of the substring to be calculated. Therefore, when filtering the data set, a suitable filtering mode can be selected according to the type of the substring operator to further ensure the accuracy of the data calculation result.

[0055] Optionally, before determining the target data filtering method, the method may further include: determining whether the first first-category parameter and the second first-category parameter are both associated with a filtered flag, and if so, using the substring operator to operate on the filtered first target data set of the first first-category parameter and the filtered second target data set of the second first-category parameter to obtain a current substring value of the substring to be calculated. If not, the target data filtering method is determined using the above method.

[0056] Exemplarily, a first-category parameter may appear multiple times in the first target string, or may appear in the target strings of other calculated target parameters. That is, the data set of the first-category parameter has been filtered recently (such as within the most recent preset time period). If it has been filtered, a filtered flag can be added to the first-category parameter, and when the first-category parameter associated with the filtered flag is encountered again, there is no need to filter it.

[0057] Exemplarily, the target data filtering method may include a box plot filtering method, may include an improved filtering method based on a box plot, and may include other filtering methods, which are not specifically limited.

[0058] In some embodiments, the type of the substring operator includes a division sign, and the target data filtering method corresponding to the division sign includes an associated filtering method. According to the associated filtering method, the first data set of the first first-category parameter and the second data set of the second first-category parameter are filtered to obtain a first target data set and a second target data set, including: using a preset abnormal data detection method, respectively determining the first abnormal data in the first data set of the first first-category parameter, and the second abnormal data in the second data set of the second first-category parameter; removing the first abnormal data and the first associated data associated with the second abnormal data from the first data set to obtain the first target data set; removing the second abnormal data and the second associated data associated with the first abnormal data from the second data set to obtain the second target data set. The advantage of such a setting is that the accuracy of the division calculation result is further improved.

[0059] Exemplarily, in a division operation, there is usually a certain correlation between the first-class parameter used as the numerator and the first-class parameter used as the denominator, and they often appear in pairs. In the related art, the filtering processes of different data sets are independent of each other. If the numerator and denominator are filtered for abnormal data separately, the calculated result may be too large or too small. For example, the like rate of media content is the number of likes of the media content divided by the number of times the media content is displayed. If there is an abnormality in a certain like data in the like data set, filtering out the abnormal like data alone will cause the calculated result to be too small. In the embodiment of the present disclosure, after determining the abnormal data in the numerator and denominator respectively, on the basis of filtering out the abnormal data, the associated data will also be filtered out to ensure the accuracy of the result. Among them, the associated data associated with the abnormal data may be data belonging to the same target object as the abnormal data. As in the above example, the association relationship can be determined based on the media content. The likes data and impressions data belonging to the same media content have an association relationship. That is, for a certain media content, if the likes data of the media content is abnormal, then the impressions data of the media content is the corresponding associated data. That is, after filtering out the abnormal likes data, the impressions data associated with the abnormal likes data in the impression data set is also filtered out.

[0060] In some embodiments, the use of the substring operator to operate on the first target data set and the second target data set to obtain the current substring value of the substring to be calculated includes: for each first target data in the first target data set, determining the corresponding first weight value based on the sum of parameter values ​​of at least two first weight parameters, and performing weighted calculation on the first target data based on the first weight value to obtain a first numerical value, wherein at least one of the first weight parameters is related to a first degree of association, and the first degree of association is determined according to whether the target parameter and the first target data correspond to the same function; for each second target data in the second target data set, determining the corresponding second weight value based on the sum of parameter values ​​of at least two second weight parameters, and performing weighted calculation on the second target data based on the second weight value to obtain a second numerical value, wherein at least one of the second weight parameters is related to a second degree of association, and the second degree of association is determined according to whether the target parameter and the second target data correspond to the same function; using the substring operator to operate on the first numerical value and the second numerical value to obtain the current substring value of the substring to be calculated. The advantage of this setting is that weighted calculations are performed on the target data corresponding to the numerator and denominator based on at least two different weight parameters, and at least one of the weight parameters is related to a specific function, thereby improving the accuracy of parameter calculation.

[0061] Among them, the first weight parameter and the second weight parameter can be the same or different. Exemplarily, the business system may include different functions (also referred to as sub-businesses), the data in the target data set may come from different functions, and the target parameter may be a parameter of a specific function, therefore, when a certain data in the target data set and the target parameter come from the same function, the value of the weight parameter may be higher, such as the first value, and when a certain data in the target data set and the target parameter come from different functions, the value of the weight parameter may be lower, such as the second value, and the first value is greater than the second value.

[0062] Exemplarily, taking the media content push service system as an example, different media content can be displayed in different display pages, and each display page can correspond to different functions. Assuming that the target data is the number of media content displays, and the target parameter is the click-through rate in the first page, the weight parameter value corresponding to the number of displays on the first page is greater than the weight parameter value corresponding to the number of displays on the second page (different from the first page).

[0063] Exemplarily, in addition to the weight parameters related to the first degree of association, time-related weight parameters can also be set. For example, the parameter value of the weight parameter can be negatively correlated with the target duration. The target duration can be the difference between the current time and the generation time of the target data. That is, the closer the generation time of the target data is to the current time, the larger the value of the weight parameter corresponding to the target data will be.

[0064] Figure 3 A flowchart of another data processing method provided by an embodiment of the present disclosure is shown in FIG. Figure 4 This is a schematic diagram of a data processing process provided by an embodiment of the present disclosure. The embodiment of the present disclosure is optimized based on each optional solution in the above embodiment. Specifically, the method includes the following steps:

[0065] Step 301: Obtain parameter configuration information stored in a remote configuration center.

[0066] Step 302: Decompose the initial expression of the local target parameter into an initial character string using a preset decomposition method.

[0067] For example, the initial expression of the target parameter is initialized, assuming that the target parameter is recorded as r, r = 10*(e+f / g)*h. Corresponding to a specific business scenario, for example: estimated contribution volume = 10*(resource playback parameter+control statistical parameter / resource statistical parameter)*resource delivery quantity.

[0068] For example, the initial string can be obtained by decomposing the regular matching formula, which is recorded as:

[0069] Initial List = [] string {"10","*","(","e","+","f"," / ","g",")","*","h"}.

[0070] Step 303: for each parameter in the initial character string, determine whether the current parameter is a second-category parameter according to the parameter configuration information; if so, replace the current parameter with the character string of the corresponding parameter expression in the parameter configuration information to obtain an intermediate character string.

[0071] For example, assume that the parameter configuration information is: m=[]varible{{key:"a",keyType:0,formula:"a"},{key:"b",keyType:0,formula:"b"},{key:"c",keyType:0,formula:"c"},{key:"d",keyType:0,formula:"d"},{key:"e",keyType:1,formula:"c+d"},{key:"f",keyType:1,formula:"a / b"},{key:"g",keyType:0,formula:"g"},{key:"h",keyType:0,formula:"h"}}.

[0072] By traversing each character in the initial string and replacing the second type of parameters with those represented by the first type of parameters according to the parameter configuration information, an intermediate string can be obtained.

[0073] For example, "e" can be replaced by "c", "+", "d"; "f" can be replaced by "a", " / ", "b".

[0074] Corresponding to specific business scenarios, for example: average online parameter = average playback time proportion in the first period + average playback time proportion in the second period, control statistical parameter = control click rate / resource proportion of embedded controls.

[0075] Step 304: When it is determined that the current intermediate character string does not contain the second type of parameter, the current intermediate character string is determined as the first target character string.

[0076] Exemplarily, after all the second-category parameters are replaced, the first target character string can be obtained.

[0077] For example: target List = []string{"10","*","(","c","+","d","+","a"," / ","b"," / ","g",")","*","h"}. Assume that the symbols (also called elements) in the target List determine the subscript values in the order in the target List. For example, the first subscript value starts from 0.

[0078] Step 305: Based on the position of a preset symbol in the first target string, determine the currently to-be-calculated substring in the first target string, where the preset symbol is used to indicate the operation priority, and the currently to-be-calculated substring includes a first operand, a substring operator, and a second operand.

[0079] Exemplarily, the preset character is a parenthesis. Obtain the maximum subscript maxIndex of the string "(" and the minimum subscript minIndex of ")". As in the above example, maxIndex = 2 and minIndex = 12. Determine whether both maxIndex and minIndex are greater than or equal to 0. If so, take the elements in the target List where maxIndex < index < minIndex to form the to-be-calculated List; if not, reset maxIndex = -1 and minIndex = the length of the target List. As in the above example, take the symbols in the List where 2 < index < 12, and let the to-be-calculated List = []string{"c","+","d","+","a"," / ","b"," / ","g"}.

[0080] After determining the to-be-calculated List, determine whether the length of the to-be-calculated List is 3. If so, determine it as the to-be-calculated subList; if not, select the to-be-calculated subList to be calculated first according to the four arithmetic operation relationships.

[0081] Select the to-be-calculated subList to be calculated first according to the four arithmetic operation relationships. Specifically, when the length of the to-be-calculated List is greater than 3, obtain the symbol at the subscript 3 in the to-be-calculated List, and determine whether the symbol is "*" or " / ". If so, determine the symbols at the subscripts 2, 3, and 4 as the to-be-calculated subList; if not, determine the symbols at the subscripts 0, 1, and 2 as the to-be-calculated subList. As in the above example, the symbol at the subscript 3 is "+", so "c","+","d" can be determined as the to-be-calculated subList.

[0082] Step 306: When the first operand includes a first first-category parameter, and the second operand includes a second first-category parameter, determine a target data filtering method for the first first-category parameter and the second first-category parameter according to the type of the substring operator, and filter the first data set of the first first-category parameter and the second data set of the second first-category parameter according to the target data filtering method to obtain a first target data set and a second target data set.

[0083] Exemplarily, after determining the subList to be calculated, it is determined whether the type of the substring operator is " / ", if so, an associated filtering method is used for filtering, if not, a box plot filtering method is used.

[0084] For example, in the above example, the association filtering method is used for the data sets a and b. Specifically, the abnormal data a1 in the data set a and the abnormal data b1 in the data set b are first determined by using the box plot filtering method, and then the associated data of a1 and b1 are filtered out from the data set a, and the associated data of b1 and a1 are filtered out from the data set b. For the data sets c and d, the box plot filtering method is used to determine the abnormal data and filter out the abnormal data.

[0085] Step 307: for each first target data in the first target data set, determine the corresponding first weight value based on the sum of parameter values ​​of at least two first weight parameters, and perform weighted calculation on the first target data based on the first weight value to obtain a first numerical value.

[0086] Exemplarily, the first parameter value is determined according to whether the target parameter corresponds to the same function as the first target data, the second parameter value is determined according to the difference between the current time and the generation time of the first target data, the first weight value is determined according to the sum of the first parameter value and the second parameter value, and after determining the first weight value corresponding to each first target data, a weighted calculation is performed to obtain a first value, that is, the value of the first operand. Specifically, the weighted calculation can be a weighted average calculation.

[0087] Step 308: For each second target data in the second target data set, determine a corresponding second weight value based on the parameter values ​​of at least two second weight parameters, and perform weighted calculation on the second target data based on the second weight value to obtain a second numerical value.

[0088] Exemplarily, the first parameter value is determined according to whether the target parameter and the second target data correspond to the same function, the second parameter value is determined according to the difference between the current time and the generation time of the second target data, the second weight value is determined according to the sum of the first parameter value and the second parameter value, and after determining the second weight value corresponding to each second target data, a weighted calculation is performed to obtain a second value, that is, the value of the second operand. Specifically, the weighted calculation can be a weighted average calculation.

[0089] Step 309: Use the substring operator to operate on the first value and the second value to obtain the current substring value of the substring to be calculated.

[0090] Step 310: Replace the current substring to be calculated in the first target string with the current substring value to update the first target string.

[0091] Exemplarily, in the case where brackets exist, the length of the List to be calculated is less than the length of the target List. The update of the first target string here can also be understood as the update of the List to be calculated. After the update, it is determined whether there is a single symbol left in the List to be calculated. If so, it is determined that the calculation of the List to be calculated is completed, and the List to be calculated in the target List is replaced with the value of the List to be calculated, and it is continued to be determined whether there are brackets. If so, a new List to be calculated is continued to be determined. If not, a new subList to be calculated is determined. As in the above example, after "c", "+", "d" are calculated, "c", "+", "d" in the List to be calculated are replaced with specific substring values, and then the subList to be calculated is re-determined to be "a", " / ", "b".

[0092] Step 311: If there is a single symbol remaining in the current first target character string, the value of the single symbol is determined as the first parameter value of the target parameter.

[0093] The data processing method provided by the embodiment of the present disclosure, when it is necessary to determine the parameter value of the target parameter including the second category parameter, converts the initial expression of the target parameter into a string including multiple first category parameters and operators according to the parameter configuration information obtained in the remote configuration center, and after determining the substring to be calculated, selects a suitable data set filtering method according to the substring operator, and after filtering, uses the parameter values ​​of at least two weight parameters to add and determine the weight value of the weighted calculation of the data set, so as to ensure the accuracy of the first category parameters, and then ensure the accuracy of the parameter value of the target parameter; when it is necessary to modify the calculation method of the second category parameter, it is sufficient to modify the parameter expression stored in the remote configuration center, and there is no need to modify the local initial expression, that is, there is no need to modify the local code file, thereby reducing the code development cost, and improving the effectiveness efficiency of the second category parameter changes, and ensuring the real-time accuracy of the parameter value.

[0094] In some embodiments, after determining the first parameter value of the target parameter according to the first target string and the data set of multiple first-category parameters contained in the first target string, it also includes: in response to the parameter expression update event being triggered, obtaining the updated parameter configuration information in the remote configuration center; according to the updated parameter configuration information, converting the initial expression into a second target string, wherein the second target string contains multiple first-category parameters and operators, and does not contain the second-category parameters; according to the second target string and the data set of multiple first-category parameters contained in the second target string, determining the second parameter value of the target parameter to update the value of the target parameter. The advantage of such a setting is that when the parameter expression in the parameter configuration information is updated, the service end can be promptly notified to use the updated parameter configuration information to recalculate the new parameter value of the target parameter, further ensuring the real-time accuracy of the target parameter.

[0095] Exemplarily, a parameter expression update event can be understood as an event of updating a parameter expression in parameter configuration information in a remote configuration center. After the update is completed, an update notification can be sent to the business end to instruct the business end to obtain the updated parameter configuration information in the remote configuration center.

[0096] For example, as the number of parameters increases, the amount of data in the parameter configuration information will also increase, that is, the number of keys increases. In order to improve the efficiency of the business end in reading parameter configuration information, the Redis cache can be used to store the parameter configuration information and obtain the parameter configuration information stored in the remote configuration center. Specifically, the parameter configuration information stored in the remote configuration center can be obtained from the Redis cache. When the parameter expression in the parameter configuration information in the remote configuration center is updated, the remote configuration center can write an update event to the message queue, and the business end subscribes to the update event and consumes the update event in the message queue in real-time consumption of the message queue. The remote configuration center can be understood as the producer of the message queue, and the business end can be understood as the consumer of the message queue. When the business end consumes the update event, it triggers the update of the Redis cache, that is, the business end sends an update instruction to Redis to instruct Redis to obtain the latest parameter configuration information from the remote configuration center, to ensure the timeliness of the Redis cache update, and then to ensure the accuracy of the parameter configuration information obtained from the Redis cache when parameter value calculation is required.

[0097] Figure 5 A structural diagram of a data processing device provided by an embodiment of the present disclosure is shown in FIG. Figure 5 As shown, the device comprises:

[0098] The configuration information acquisition module 501 is used to acquire parameter configuration information stored in a remote configuration center, wherein the parameter configuration information includes a data set of first-category parameters and parameter expressions of second-category parameters, and the parameter expressions are determined based on at least two of the first-category parameters;

[0099] A string conversion module 502, configured to convert an initial expression of a local target parameter into a first target string according to the parameter expression in the parameter configuration information, wherein the initial expression includes at least one parameter of the second category, and the first target string includes multiple parameters of the first category and operators, and does not include the second category parameters;

[0100] The parameter value determination module 503 is configured to determine a first parameter value of the target parameter according to the first target character string and a data set of a plurality of first-category parameters contained in the first target character string.

[0101] The data processing device provided by the embodiment of the present disclosure, when it is necessary to determine the parameter value of the target parameter including the second category parameter, converts the initial expression of the target parameter into a string including multiple first category parameters and operators according to the parameter configuration information obtained in the remote configuration center, and after determining the substring to be calculated, selects a suitable data set filtering method according to the substring operator, and uses the parameter values ​​of at least two weight parameters to sum up after filtering to determine the weight value of the weighted calculation of the data set, so as to ensure the accuracy of the first category parameters, and then ensure the accuracy of the parameter value of the target parameter; when it is necessary to modify the calculation method of the second category parameter, it is sufficient to modify the parameter expression stored in the remote configuration center, and there is no need to modify the local initial expression, that is, there is no need to modify the local code file, thereby reducing the code development cost, and improving the effectiveness efficiency of the second category parameter changes, and ensuring the real-time accuracy of the parameter value.

[0102] Optionally, the string conversion module includes:

[0103] A character decomposition unit, used for decomposing the initial expression of the local target parameter into an initial character string by using a preset decomposition method;

[0104] a replacement unit, configured to determine, for each parameter in the initial character string, whether the current parameter is a parameter of the second category according to the parameter configuration information, and if so, replace the current parameter with a character string of the parameter expression corresponding to the parameter configuration information to obtain an intermediate character string;

[0105] The target character string determining unit is configured to determine the current intermediate character string as a first target character string when it is determined that the second type of parameter does not exist in the current intermediate character string.

[0106] Optionally, the parameter value determination module includes:

[0107] a substring to be calculated determining unit, configured to determine a current substring to be calculated in the first target string based on a position of a preset symbol in the first target string, wherein the preset symbol is used to indicate an operation priority, and the current substring to be calculated includes a first operand, a substring operator, and a second operand;

[0108] A substring value calculation unit, configured to use the substring operator to calculate the first operand and the second operand to obtain a current substring value of the substring to be calculated;

[0109] a string updating unit, configured to replace the current substring to be calculated in the first target string with the current substring value, so as to update the first target string;

[0110] The parameter value determination unit is used to determine whether a single symbol remains in the current first target character string, and if so, determine the value of the single symbol as the first parameter value of the target parameter.

[0111] Optional, substring value calculation unit, including:

[0112] a filtering mode determining subunit, configured to determine a target data filtering mode of the first first-category parameter and / or the second first-category parameter according to a type of the substring operator when the first operand includes a first first-category parameter and the second operand includes a second first-category parameter;

[0113] a filtering subunit, configured to filter the first data set of the first first-category parameter and / or the second data set of the second first-category parameter according to the target data filtering mode to obtain a first target data set and a second target data set;

[0114] The substring value calculation subunit is used to use the substring operator to operate on the first target data set and the second target data set to obtain a current substring value of the current substring to be calculated.

[0115] Optionally, the type of the substring operator includes a division sign, and the target data filtering method corresponding to the division sign includes an associated filtering method;

[0116] The filtering subunit includes:

[0117] an abnormal data determination subunit, configured to respectively determine the first abnormal data in the first data set of the first first-category parameter and the second abnormal data in the second data set of the second first-category parameter by using a preset abnormal data detection method;

[0118] A first data removal subunit is used to remove the first abnormal data and first associated data associated with the second abnormal data from the first data set to obtain a first target data set;

[0119] The second data removal subunit is used to remove the second abnormal data and second associated data associated with the first abnormal data from the second data set to obtain a second target data set.

[0120] Optionally, the substring value calculation subunit includes:

[0121] a first calculation subunit, configured to determine, for each first target data in the first target data set, a corresponding first weight value based on the sum of parameter values ​​of at least two first weight parameters, and perform weighted calculation on the first target data based on the first weight value to obtain a first numerical value, wherein at least one of the first weight parameters is related to a first degree of association, and the first degree of association is determined according to whether the target parameter and the first target data correspond to the same function;

[0122] a second calculation subunit, configured to determine, for each second target data in the second target data set, a corresponding second weight value based on the parameter values ​​of at least two second weight parameters, and perform weighted calculation on the second target data based on the second weight value to obtain a second numerical value, wherein at least one of the second weight parameters is related to a second degree of association, and the second degree of association is determined according to whether the target parameter and the second target data correspond to the same function;

[0123] The third calculation subunit is used to use the substring operator to operate on the first value and the second value to obtain a current substring value of the substring to be calculated.

[0124] Optionally, the device further comprises:

[0125] an acquisition module, configured to acquire updated parameter configuration information in the remote configuration center in response to a parameter expression update event being triggered, after determining the first parameter value of the target parameter according to the first target string and the data set of the plurality of first-category parameters contained in the first target string;

[0126] a conversion module, configured to convert the initial expression into a second target string according to the updated parameter configuration information, wherein the second target string contains a plurality of the first type parameters and operators and does not contain the second type parameters;

[0127] A parameter value updating module is used to determine a second parameter value of the target parameter according to the second target character string and a data set of a plurality of the first type parameters contained in the second target character string, so as to update the value of the target parameter.

[0128] The data processing device provided in the embodiments of the present disclosure can execute the data processing method provided in any embodiment of the present disclosure, and has the corresponding functional modules and beneficial effects of the execution method.

[0129] It is worth noting that the various units and modules included in the above-mentioned device are only divided according to functional logic, but are not limited to the above-mentioned division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the protection scope of the embodiments of the present disclosure.

[0130] Figure 6 This is a schematic diagram of the structure of an electronic device provided by an embodiment of the present disclosure. Figure 6 , which shows an electronic device (eg, Figure 6 The terminal device in the embodiment of the present disclosure may include but is not limited to mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 6 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0131] like Figure 6 As shown, the electronic device 600 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage device 608 into a random access memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the electronic device 600 are also stored. The processing device 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An edit / output (I / O) interface 605 is also connected to the bus 604.

[0132] Typically, the following devices may be connected to the I / O interface 605: an input device 606 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 607 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 608 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 609. The communication device 609 may allow the electronic device 600 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 6 The electronic device 600 is shown with various devices, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead.

[0133] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a non-transitory computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device 609, or installed from a storage device 608, or installed from a ROM 602. When the computer program is executed by the processing device 601, the above-mentioned functions defined in the method of the embodiment of the present disclosure are executed.

[0134] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0135] The electronic device provided by the embodiment of the present disclosure and the data processing method provided by the above embodiment belong to the same inventive concept. The technical details not fully described in this embodiment can be referred to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0136] The embodiments of the present disclosure provide a computer storage medium on which a computer program is stored. When the program is executed by a processor, the data processing method provided by the above embodiments is implemented.

[0137] It should be noted that the computer-readable medium disclosed above may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, device or device. In the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. This propagated data signal may take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. The computer readable signal medium may also be any computer readable medium other than a computer readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0138] In some embodiments, the client and the server may communicate using any currently known or future developed network protocol such as HTTP (HyperText Transfer Protocol), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or future developed network.

[0139] The computer-readable medium may be included in the electronic device, or may exist independently without being installed in the electronic device.

[0140] The above-mentioned computer-readable medium carries one or more programs. When the above-mentioned one or more programs are executed by the electronic device, the electronic device: obtains parameter configuration information stored in a remote configuration center, wherein the parameter configuration information includes a data set of first-category parameters and a parameter expression of second-category parameters, and the parameter expression is determined based on at least two of the first-category parameters; according to the parameter expression in the parameter configuration information, converts an initial expression of a local target parameter into a first target string, wherein the initial expression contains at least one of the second-category parameters, and the first target string contains multiple first-category parameters and operators, and does not contain the second-category parameters; determines a first parameter value of the target parameter according to the first target string and the data set of multiple first-category parameters contained in the first target string.

[0141] Computer program code for performing the operations of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including, but not limited to, object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0142] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0143] The units involved in the embodiments described in the present disclosure may be implemented by software or hardware. The name of a module does not limit the module itself in some cases. For example, a parameter value determination module may also be described as "a module for determining the first parameter value of the target parameter based on the first target string and a data set of multiple first-type parameters contained in the first target string".

[0144] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0145] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0146] According to one or more embodiments of the present disclosure, a data processing method is provided, including:

[0147] Acquire parameter configuration information stored in a remote configuration center, wherein the parameter configuration information includes a data set of first-category parameters and parameter expressions of second-category parameters, and the parameter expressions are determined based on at least two of the first-category parameters;

[0148] According to the parameter expression in the parameter configuration information, converting an initial expression of a local target parameter into a first target string, wherein the initial expression includes at least one parameter of the second category, and the first target string includes a plurality of parameters of the first category and operators, and does not include the parameters of the second category;

[0149] A first parameter value of the target parameter is determined according to the first target character string and a data set of a plurality of first-category parameters contained in the first target character string.

[0150] According to one or more embodiments of the present disclosure, converting the initial expression of the local target parameter into a first target string according to the parameter expression in the parameter configuration information includes:

[0151] Decompose the initial expression of the local target parameter into an initial string using the preset decomposition method;

[0152] For each parameter in the initial string, determine whether the current parameter is a parameter of the second category according to the parameter configuration information, and if so, replace the current parameter with a string of the parameter expression corresponding to the parameter configuration information to obtain an intermediate string;

[0153] When it is determined that the second type of parameters do not exist in the current intermediate character string, the current intermediate character string is determined as the first target character string.

[0154] According to one or more embodiments of the present disclosure, determining the first parameter value of the target parameter according to the first target character string and the data set of the plurality of first-category parameters contained in the first target character string includes:

[0155] Determine a current substring to be calculated in the first target string based on a position of a preset symbol in the first target string, wherein the preset symbol is used to indicate an operation priority, and the current substring to be calculated includes a first operand, a substring operator, and a second operand;

[0156] Using the substring operator, operate the first operand and the second operand to obtain a current substring value of the current substring to be calculated;

[0157] Replacing the current substring to be calculated in the first target string with the current substring value to update the first target string;

[0158] It is determined whether a single symbol remains in the current first target character string, and if so, the value of the single symbol is determined as the first parameter value of the target parameter.

[0159] According to one or more embodiments of the present disclosure, when the first operand includes a first first-category parameter and the second operand includes a second first-category parameter, using the substring operator to operate the first operand and the second operand to obtain a current substring value of the current substring to be calculated includes:

[0160] Determining a target data filtering mode for the first first-category parameter and / or the second first-category parameter according to a type of the substring operator;

[0161] According to the target data filtering method, filtering the first data set of the first first-category parameter and / or the second data set of the second first-category parameter to obtain a first target data set and a second target data set;

[0162] The substring operator is used to operate the first target data set and the second target data set to obtain a current substring value of the current substring to be calculated.

[0163] According to one or more embodiments of the present disclosure, the type of the substring operator includes a division sign, and the target data filtering method corresponding to the division sign includes an associated filtering method;

[0164] Wherein, according to the associated filtering method, filtering the first data set of the first first-category parameter and the second data set of the second first-category parameter to obtain the first target data set and the second target data set includes:

[0165] Using a preset abnormal data detection method, respectively determine first abnormal data in a first data set of the first first-category parameter and second abnormal data in a second data set of the second first-category parameter;

[0166] Removing the first abnormal data and first associated data associated with the second abnormal data from the first data set to obtain a first target data set;

[0167] The second abnormal data and second associated data associated with the first abnormal data are removed from the second data set to obtain a second target data set.

[0168] According to one or more embodiments of the present disclosure, the using the substring operator to operate on the first target data set and the second target data set to obtain the current substring value of the current substring to be calculated includes:

[0169] For each first target data in the first target data set, a corresponding first weight value is determined based on the sum of parameter values ​​of at least two first weight parameters, and a weighted calculation is performed on the first target data based on the first weight value to obtain a first numerical value, wherein at least one of the first weight parameters is related to a first degree of association, and the first degree of association is determined according to whether the target parameter and the first target data correspond to the same function;

[0170] For each second target data in the second target data set, a corresponding second weight value is determined based on the parameter values ​​of at least two second weight parameters, and a weighted calculation is performed on the second target data based on the second weight value to obtain a second numerical value, wherein at least one of the second weight parameters is related to a second degree of association, and the second degree of association is determined according to whether the target parameter and the second target data correspond to the same function;

[0171] The substring operator is used to operate the first value and the second value to obtain a current substring value of the substring to be calculated.

[0172] According to one or more embodiments of the present disclosure, after determining the first parameter value of the target parameter according to the first target character string and the data set of the plurality of first-category parameters included in the first target character string, the method further includes:

[0173] In response to a parameter expression update event being triggered, obtaining updated parameter configuration information in the remote configuration center;

[0174] According to the updated parameter configuration information, converting the initial expression into a second target string, wherein the second target string contains a plurality of the first-category parameters and operators and does not contain the second-category parameters;

[0175] According to the second target character string and a data set of a plurality of the first type parameters contained in the second target character string, a second parameter value of the target parameter is determined to update the value of the target parameter.

[0176] According to one or more embodiments of the present disclosure, there is provided a data processing device, including:

[0177] A configuration information acquisition module, used to acquire parameter configuration information stored in a remote configuration center, wherein the parameter configuration information includes a data set of first-category parameters and parameter expressions of second-category parameters, and the parameter expressions are determined based on at least two of the first-category parameters;

[0178] a string conversion module, configured to convert an initial expression of a local target parameter into a first target string according to the parameter expression in the parameter configuration information, wherein the initial expression includes at least one parameter of the second category, and the first target string includes a plurality of parameters of the first category and operators, and does not include the parameters of the second category;

[0179] A parameter value determination module is used to determine a first parameter value of the target parameter according to the first target character string and a data set of a plurality of first-category parameters contained in the first target character string.

[0180] According to one or more embodiments of the present disclosure, an electronic device is provided, the electronic device comprising:

[0181] one or more processors;

[0182] a storage device for storing one or more programs,

[0183] When the one or more programs are executed by the one or more processors, the one or more processors implement the data processing method provided by the embodiment of the present disclosure.

[0184] According to one or more embodiments of the present disclosure, a storage medium containing computer executable instructions is provided. When the computer executable instructions are executed by a computer processor, they are used to execute the data processing method provided by the embodiments of the present disclosure.

[0185] The above description is only a preferred embodiment of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of disclosure involved in the present disclosure is not limited to the technical solutions formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosed concept. For example, the above features are replaced with the technical features with similar functions disclosed in the present disclosure (but not limited to) by each other to form a technical solution.

[0186] In addition, although each operation is described in a specific order, this should not be understood as requiring these operations to be performed in the specific order shown or in a sequential order. Under certain circumstances, multitasking and parallel processing may be advantageous. Similarly, although some specific implementation details are included in the above discussion, these should not be interpreted as limiting the scope of the present disclosure. Some features described in the context of a separate embodiment can also be implemented in a single embodiment in combination. On the contrary, the various features described in the context of a single embodiment can also be implemented in multiple embodiments individually or in any suitable sub-combination mode.

[0187] Although the subject matter has been described in language specific to structural features and / or methodological logical actions, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. On the contrary, the specific features and actions described above are merely example forms of implementing the claims.

Claims

1. A data processing method, characterized in that: include: Acquire parameter configuration information stored in a remote configuration center, wherein the parameter configuration information includes a data set of first-category parameters and parameter expressions of second-category parameters, and the parameter expressions are determined based on at least two of the first-category parameters; According to the parameter expression in the parameter configuration information, converting an initial expression of a local target parameter into a first target string, wherein the initial expression includes at least one parameter of the second category, and the first target string includes a plurality of parameters of the first category and operators, and does not include the parameters of the second category; A first parameter value of the target parameter is determined according to the first target character string and a data set of a plurality of first-category parameters contained in the first target character string.

2. The method according to claim 1, characterized in that The converting the initial expression of the local target parameter into a first target character string according to the parameter expression in the parameter configuration information includes: Decompose the initial expression of the local target parameter into an initial string using the preset decomposition method; For each parameter in the initial string, determine whether the current parameter is a parameter of the second category according to the parameter configuration information, and if so, replace the current parameter with a string of the parameter expression corresponding to the parameter configuration information to obtain an intermediate string; When it is determined that the second type of parameters do not exist in the current intermediate character string, the current intermediate character string is determined as the first target character string.

3. The method according to claim 1, characterized in that The determining, according to the first target character string and a data set of a plurality of first-category parameters contained in the first target character string, a first parameter value of the target parameter comprises: Determine a current substring to be calculated in the first target string based on a position of a preset symbol in the first target string, wherein the preset symbol is used to indicate an operation priority, and the current substring to be calculated includes a first operand, a substring operator, and a second operand; Using the substring operator, operate the first operand and the second operand to obtain a current substring value of the current substring to be calculated; Replacing the current substring to be calculated in the first target string with the current substring value to update the first target string; It is determined whether a single symbol remains in the current first target character string, and if so, the value of the single symbol is determined as the first parameter value of the target parameter.

4. The method according to claim 3, characterized in that In a case where the first operand includes a first first-category parameter, and the second operand includes a second first-category parameter, using the substring operator to operate the first operand and the second operand to obtain a current substring value of the current substring to be calculated includes: Determining a target data filtering mode for the first first-category parameter and / or the second first-category parameter according to a type of the substring operator; According to the target data filtering method, filtering the first data set of the first first-category parameter and / or the second data set of the second first-category parameter to obtain a first target data set and a second target data set; The substring operator is used to operate the first target data set and the second target data set to obtain a current substring value of the current substring to be calculated.

5. The method according to claim 4, characterized in that The type of the substring operator includes a division sign, and the target data filtering method corresponding to the division sign includes an associated filtering method; Wherein, according to the associated filtering method, filtering the first data set of the first first-category parameter and the second data set of the second first-category parameter to obtain the first target data set and the second target data set includes: Using a preset abnormal data detection method, respectively determine first abnormal data in a first data set of the first first-category parameter and second abnormal data in a second data set of the second first-category parameter; Removing the first abnormal data and first associated data associated with the second abnormal data from the first data set to obtain a first target data set; The second abnormal data and second associated data associated with the first abnormal data are removed from the second data set to obtain a second target data set.

6. The method according to claim 4, characterized in that The using the substring operator to operate the first target data set and the second target data set to obtain the current substring value of the current substring to be calculated includes: For each first target data in the first target data set, a corresponding first weight value is determined based on the sum of parameter values ​​of at least two first weight parameters, and a weighted calculation is performed on the first target data based on the first weight value to obtain a first numerical value, wherein at least one of the first weight parameters is related to a first degree of association, and the first degree of association is determined according to whether the target parameter and the first target data correspond to the same function; For each second target data in the second target data set, a corresponding second weight value is determined based on the parameter values ​​of at least two second weight parameters, and a weighted calculation is performed on the second target data based on the second weight value to obtain a second numerical value, wherein at least one of the second weight parameters is related to a second degree of association, and the second degree of association is determined according to whether the target parameter and the second target data correspond to the same function; The substring operator is used to operate the first value and the second value to obtain a current substring value of the substring to be calculated.

7. The method according to any one of claims 1 to 6, characterized in that: After determining the first parameter value of the target parameter according to the first target character string and the data set of the plurality of first-type parameters included in the first target character string, the method further includes: In response to a parameter expression update event being triggered, obtaining updated parameter configuration information in the remote configuration center; According to the updated parameter configuration information, converting the initial expression into a second target string, wherein the second target string contains a plurality of the first-category parameters and operators and does not contain the second-category parameters; According to the second target character string and a data set of a plurality of the first type parameters contained in the second target character string, a second parameter value of the target parameter is determined to update the value of the target parameter.

8. A data processing device, characterized in that: include: A configuration information acquisition module, used to acquire parameter configuration information stored in a remote configuration center, wherein the parameter configuration information includes a data set of first-category parameters and parameter expressions of second-category parameters, and the parameter expressions are determined based on at least two of the first-category parameters; a string conversion module, configured to convert an initial expression of a local target parameter into a first target string according to the parameter expression in the parameter configuration information, wherein the initial expression includes at least one parameter of the second category, and the first target string includes a plurality of parameters of the first category and operators, and does not include the parameters of the second category; A parameter value determination module is used to determine a first parameter value of the target parameter according to the first target character string and a data set of a plurality of first-category parameters contained in the first target character string.

9. An electronic device, characterized in that: The electronic device comprises: 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, the one or more processors implement the data processing method according to any one of claims 1 to 7.

10. A storage medium containing computer executable instructions, characterized in that: When the computer executable instructions are executed by a computer processor, they are used to perform the data processing method according to any one of claims 1 to 7.

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