Data index configuration method, configuration file determination method and related equipment

Abstract

The invention provides a data index configuration method, a configuration file determination method and related equipment. The data index configuration method comprises the following steps: selecting a target data type corresponding to a data index from each data type of a data source; determining a target configuration rule corresponding to the target data type, the target configuration rule being a configuration logic for a data source of the target data type; performing configuration processing on the data source of the target data type according to a target configuration rule to obtain a configuration result; and performing associated storage on the configuration result and the data index. Therefore, a program does not need to be written in the whole data index configuration process, the operation amount and the operation time of the user are saved, the user who understands or does not understand programming can configure the data index without paying attention to the underlying code logic, and the expandability of the data index is enhanced.

Description

Technical Field

[0001] This application relates to the technical field of data resource allocation, and in particular, to a method for configuring data metrics, a method for determining a configuration file, and related devices. Background Art

[0002] In the prior art, with the development of information processing, the amount of data is increasing, and it is necessary to use data metrics to organize and statistically analyze the data.

[0003] Generally, due to the diversity of data data sources, users often need to perform logical configuration through a large amount of programming code to obtain corresponding data metrics, which consumes too much time.

[0004] Therefore, how to configure data metrics more simply and quickly has become a technical problem to be solved urgently at present. Summary of the Invention

[0005] In view of this, the purpose of this application is to propose a method for configuring data metrics, a method for determining a configuration file, and related devices to solve or partially solve the above technical problems.

[0006] Based on the above purpose, the first aspect of this application provides a method for configuring data metrics, including:

[0007] Select a target data type corresponding to the data metric from each data type of the data source;

[0008] Determine the corresponding target configuration rule for the target data type, where the target configuration rule is the configuration logic for the data source of the target data type;

[0009] Perform configuration processing on the data source of the target data type according to the target configuration rule to obtain a configuration result;

[0010] Associate and save the configuration result with the data metric.

[0011] Based on the same concept, the second aspect of this application proposes a method for determining a configuration file, including:

[0012] Select at least one target data metric from at least one data metric determined according to the method for configuring data metrics described in the first aspect;

[0013] Determine the combination method corresponding to the at least one target data metric;

[0014] Perform combination processing on the at least one target data metric according to the combination method, and integrate the combination processing result to obtain a configuration file.

[0015] Based on the same concept, the third aspect of the present application proposes a configuration device for data metrics, including:

[0016] A type selection module, configured to select a target data type corresponding to the data metric from various data types of the data source;

[0017] A rule determination module, configured to determine a target configuration rule corresponding to the target data type, where the target configuration rule is a configuration logic for the data source of the target data type;

[0018] A configuration processing module, configured to perform configuration processing on the data source of the target data type according to the target configuration rule to obtain a configuration result;

[0019] A saving module, configured to associate and save the configuration result with the data metric.

[0020] Based on the same concept, the fourth aspect of the present application proposes a determination device for a configuration file, including:

[0021] A data metric selection module, configured to select at least one target data metric from at least one data metric determined according to the configuration method of the data metric described in the first aspect;

[0022] A combination method matching module, configured to determine a combination method corresponding to the at least one target data metric;

[0023] A combination processing module, configured to perform combination processing on the at least one target data metric according to the combination method, and integrate the combination processing result to obtain a configuration file.

[0024] Based on the same concept, the fifth aspect of the present application proposes an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where when the processor executes the program, it implements the method described in the first aspect or the second aspect.

[0025] Based on the same concept, the sixth aspect of the present application proposes a non-transitory computer-readable storage medium, where the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to cause a computer to execute the method described in the first aspect or the second aspect.

[0026] Based on the same concept, the seventh aspect of the present application proposes a computer program product, including computer program instructions, characterized in that when the computer program instructions run on a computer, they cause the computer to execute the method described in the first aspect or the second aspect.

[0027] As can be seen from the above, the present application provides a method for configuring data indicators, a method for determining a configuration file, and related devices. Since the data source contains data sources of various data types, it is necessary to screen and configure the target data type corresponding to the data indicator from them; then, based on the target data type, the user only needs to determine the corresponding target configuration rule; finally, the data source of the target data type can be configured according to the target configuration rule to obtain the corresponding configuration result, and the configuration result can be associated and saved with the data indicator to complete the configuration process of the data indicator. The entire configuration process does not require programming, thereby saving the user's operation volume and operation time, and users who understand programming and those who do not can configure data indicators without paying attention to the underlying code logic, enhancing the scalability of data indicators. In addition, subsequently, the required configuration file can be obtained by selecting and combining the associated and saved data indicators, making the process of obtaining the configuration file more convenient and simple, bringing great convenience to the user and saving labor costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions in the present application or related technologies, the following will briefly introduce the drawings required for use in the embodiments or related technology descriptions. Obviously, the drawings in the following descriptions are only embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0029] Figure 1A It is a schematic diagram of an application scenario of an embodiment of the present application;

[0030] Figure 1B It is another schematic diagram of an application scenario of an embodiment of the present application;

[0031] Figure 2 It is a flowchart of the method for configuring data indicators according to an embodiment of the present application;

[0032] Figure 3 It is a flowchart of the method for determining a configuration file according to an embodiment of the present application;

[0033] Figure 4A It is a schematic diagram of the configuration of data indicator 1 according to an embodiment of the present application;

[0034] Figure 4B It is a schematic diagram of the determination of data report A and data report B according to an embodiment of the present application;

[0035] Figure 5 It is a block diagram of the structure of the device for configuring data indicators according to an embodiment of the present application;

[0036] Figure 6 It is a block diagram of the structure of the device for determining a configuration file according to an embodiment of the present application;

[0037] Figure 7 This is a schematic structural diagram of the electronic device according to an embodiment of the present application. Detailed implementation manners

[0038] It can be understood that the data involved in the technical solution of the present application (including but not limited to the data itself, the acquisition or use of the data) should comply with the requirements of the corresponding laws, regulations and related provisions.

[0039] Next, the principles and spirits of the present application will be described with reference to several exemplary embodiments. It should be understood that these embodiments are only provided to enable those skilled in the art to better understand and then implement the present application, rather than limiting the scope of the present application in any way. On the contrary, these embodiments are provided to make the present application more thorough and complete, and to be able to convey the scope of the present application to those skilled in the art completely.

[0040] It can be understood that before using the technical solutions of the various embodiments in the present disclosure, the types, usage scopes, usage scenarios, etc. of the personal information involved will be informed to the user in an appropriate manner, and the user's authorization will be obtained.

[0041] For example, when responding to receiving an active request from the user, a prompt message is sent to the user to clearly prompt the user that the operation requested to be executed will require obtaining and using the user's personal information. Thus, the user can autonomously choose whether to provide personal information to the software or hardware such as an electronic device, an application program, a server or a storage medium that executes the operation of the technical solution of the present disclosure according to the prompt message.

[0042] As an optional but non-limiting implementation manner, the manner of sending a prompt message to the user in response to receiving an active request from the user can be, for example, in the form of a pop-up window, and the prompt message can be presented in text in the pop-up window. In addition, the pop-up window can also carry a selection control for the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0043] It can be understood that the above process of notifying and obtaining the user's authorization is only illustrative and does not limit the implementation manner of the present disclosure, and other manners that meet the relevant laws and regulations can also be applied to the implementation manner of the present disclosure.

[0044] In the present application, it should be understood that the number of any element in the drawings is for illustration rather than limitation, and any naming is only used for distinction and does not have any limiting meaning.

[0045] The corresponding configuration file of the present application can be at least one of a data report, a data graph, and a data text. The preferred configuration file is a data report.

[0046] In the related art, there is also the following situation:

[0047] As the complexity of various business systems increases day by day, the current attention to data reports is gradually increasing. However, currently, the data reports of basically each business system are calculated from the same data source, or different data sources are integrated into a unified data source and then calculated. This leads to a large amount of add, delete, query, and modify logic written in code at the bottom layer corresponding to each data indicator on the data report page (wherein, different query logics caused by different data sources, and different calculation logics corresponding to different data indicator logics), and finally different required data indicators are generated.

[0048] Currently, there is no relatively convenient solution to integrate multiple data sources and quickly calculate the corresponding data indicators. Generally, code is simply written to query programs based on various data sources (for example, data source 1, data source 2, data source 3) and assembled to obtain the data report composed of each data indicator required. This will cause a large amount of repeated queries and complex code logic, which is not conducive to subsequent maintenance. For each new data report, repeated development is required.

[0049] Based on the above-described situation, the principle and spirit of the present application will be elaborated in detail below with reference to several representative embodiments of the present application.

[0050] Refer to Figure 1A , which is a schematic diagram of an application scenario of the method for configuring data indicators and the method for determining a configuration file provided by an embodiment of the present application. The application scenario includes a terminal device 101, a server 102, and a data storage system 103. Among them, the terminal device 101, the server 102, and the data storage system 103 can all be connected through a wired or wireless communication network. The terminal device 101 includes, but is not limited to, a desktop computer, a mobile phone, a mobile computer, a tablet computer, a media player, a smart wearable device, a personal digital assistant (PDA), an in-vehicle control device, or other electronic devices capable of implementing the above functions. The server 102 and the data storage system 103 can both be independent physical servers, or a server cluster or a distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN (Content Delivery Network architecture), and big data and artificial intelligence platforms.

[0051] The data storage system 103 stores data sources. A user can select a corresponding target data type for a data metric through the terminal device 101, configure a target configuration rule corresponding to the target data type on the terminal device 101, retrieve the data source of the target data type from the data storage system 103 through the server 102, and perform configuration processing on the data source of the target data type according to the target configuration rule to obtain a configuration result. Then, the configuration result is associated with the data metric and saved in the terminal device 101.

[0052] In addition, in addition to the above situation, the application scenarios of the present application, such as Figure 1B shown, may also include the server 102 and the data storage system 103. The server 102 and the data storage system 103 may both be independent physical servers, or a server cluster or a distributed system composed of multiple physical servers. They may also be cloud servers that provide basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN (Content Delivery Network architecture), and big data and artificial intelligence platforms.

[0053] The data storage system 103 stores data sources. A user can select a corresponding target data type for a data metric through the server 102, configure a target configuration rule corresponding to the target data type on the server 102, retrieve the data source of the target data type from the data storage system 103, and perform configuration processing on the data source of the target data type according to the target configuration rule to obtain a configuration result. Then, the configuration result is associated with the data metric and saved in the server 102.

[0054] Next, in combination with Figure 1A and 1B application scenarios, the configuration method of the data metric and the determination method of the configuration file according to the exemplary embodiments of the present application will be described. It should be noted that the above application scenarios are only shown for the convenience of understanding the spirit and principle of the present application, and the embodiments of the present application are not limited in this regard. On the contrary, the embodiments of the present application can be applied to any applicable scenario.

[0055] An embodiment of the present application provides a configuration method for a data metric, such as Figure 2 shown, including:

[0056] Step 201, select a target data type corresponding to the data metric from each data type of the data source.

[0057] In specific implementation, the data source refers to various data required or used during business processing or operation. The data sources of each data type will be stored to facilitate subsequent selection and invocation.

[0058] The corresponding data types include at least one of the following: MySQL (relational data), ES (ElasticSearch, distributed index data), Hive (a data warehouse tool based on Hadoop), tabular data, text data, and topology graph data.

[0059] In some embodiments, the user initiates a data metric setting request (this setting request can be a data metric setting request in the initial state or a new data metric request), and accordingly, a data metric setting window will be presented. The user can set the name of the data metric (e.g., Data Metric 1 or Data Metric 2, etc.) through this setting window, and then select the required target data type (e.g., select MySQL and / or ES) from various data types of the data source for this data metric. The number of the target data types is at least one.

[0060] Step 202: Determine the target configuration rule corresponding to the target data type, where the target configuration rule is the configuration logic for the data source of the target data type.

[0061] In specific implementation, the user can manually set the corresponding configuration logic (e.g., configuration formula, selection conditions, selection range, weighting coefficient, etc.) for the target data type to form the target configuration rule. Each corresponding target data type can have at least one target configuration rule set manually. It can also be that at least one configuration rule is stored in advance for each data type for the user to select from to determine at least one target configuration rule corresponding to the target data type.

[0062] Step 203: Perform configuration processing on the data source of the target data type according to the target configuration rule to obtain a configuration result.

[0063] In specific implementation, if there is one configuration logic included in the target configuration rule, directly configure the data source of the target data type according to it to obtain the configuration result; if there are multiple, these configuration logics are provided with a configuration order, and the data source of the target data type is configured in sequence according to the configuration order to obtain the configuration result.

[0064] Step 204: Associatively save the configuration result with the data metric.

[0065] In specific implementation, the association relationship between the configuration result and the data metrics includes at least one of the following: association by using a table, association by using key-value pairs, association by using an index relationship, and association by using a master-slave relationship.

[0066] The corresponding storage methods include at least one of the following: table storage, file storage, and database storage.

[0067] Through the above technical solution, since the data source contains data sources of various data types, it is necessary to screen and configure the target data type corresponding to the data metric from them; then based on the target data type, the user only needs to determine the corresponding target configuration rule; finally, the data source of the target data type can be configured according to the target configuration rule, and the corresponding configuration result can be obtained. Associating and saving the configuration result with the data metric can complete the configuration process of the data metric. The entire configuration process does not require programming, thereby saving the user's operation volume and operation time, enabling even non-programming users to perform the configuration process of the data metric, which is simple and easy to operate, and both programming and non-programming users can perform the configuration of the data metric without paying attention to the underlying code logic, enhancing the scalability of the data metric. In addition, subsequently, the configuration file required by the user can be obtained by performing selection and combination processing based on the associated and saved data metrics, making the process of obtaining the configuration file more convenient and simple, bringing great convenience to the user and saving labor costs.

[0068] In some embodiments, at least one configuration rule corresponding to each data type is pre-stored.

[0069] Then step 202 includes: selecting a target configuration rule from at least one configuration rule corresponding to the target data type.

[0070] In specific implementation, if the number of selected target data types is at least one, at least one target configuration rule will be selected for each target data type.

[0071] If there is no target configuration rule required by the user among the at least one configuration rule corresponding to the target data type, the user can choose to manually add the corresponding target configuration rule and store it in the configuration rule corresponding to the target data type.

[0072] Through the above solution, at least one configuration rule for each data type is pre-stored for the user to select when configuring data metrics. The selection process is faster than the manual setting process, which can reduce the configuration process of the data metrics.

[0073] In some embodiments, each data type corresponds to at least one data content, and each data content corresponds to at least one aggregation policy.

[0074] Step 202 includes:

[0075] Step 2021: Select a target data content from at least one data content corresponding to the target data type.

[0076] In specific implementation, the data content is various data in the data information corresponding to the data source of the target data type. For example, the data content includes at least one of tables, graphs, documents, audios, and videos.

[0077] Step 2022: Select a target aggregation policy from at least one aggregation policy corresponding to the target data content, and use the process of aggregating the target data content according to the target aggregation policy as the target configuration rule.

[0078] In specific implementation, the aggregation policy refers to the statistical processing method for the target data content (such as counting the total number of the target data content, or counting the memory occupied by the target data content, or counting the number of occurrences of a certain word, etc.). For example, the statistical processing method can be a formula, a condition, a filtering range, etc.

[0079] After the user selects the target data content, a selection window corresponding to the target data content will be displayed. After the user triggers the selection window, at least one aggregation policy corresponding to the target data content will be displayed, and the user can select the required target aggregation policy from them. The corresponding target configuration rule is: target data type → target data content → target aggregation policy. In this way, the target data content can be aggregated according to the target aggregation policy subsequently to obtain the corresponding configuration result.

[0080] Through the above solution, the target configuration rule is split into the processes of selecting the target data content and the target aggregation policy, which can increase the diversification of user selection, enable the user to have more types of target configuration rules determined by selection, enhance the user's selection requirements, and further provide convenience for the user.

[0081] In some embodiments, the at least one aggregation policy includes: each data content corresponds to at least one data condition, and each data condition corresponds to at least one aggregation logic.

[0082] Step 2022 includes:

[0083] Step 20221: Select a target data condition from at least one data condition corresponding to the target data content.

[0084] In specific implementation, the data condition is a query condition for data items in the target data content. The data condition includes at least one of: query range, target data items to be queried, query fields (such as time or category of data content, etc.), query expressions (such as greater than, less than, or equal to, etc.), and parameter values corresponding to the query expressions. For example, the data condition is time > February 10, 2023.

[0085] Step 20222, select a target aggregation logic from at least one aggregation logic corresponding to the target data condition, and use the process of aggregating the data in the target data content that meets the target data condition according to the target aggregation logic as the target configuration rule.

[0086] In specific implementation, at least one aggregation logic corresponding to each data condition is stored in advance. The aggregation logic is a functional relationship for performing statistical operations on the data in the target data content that meets the target data condition. Among them, the aggregation logic includes at least one of: operation formula, field, and aggregation range.

[0087] In this way, the user can select the target aggregation logic required for the data metrics from at least one aggregation logic corresponding to the target data condition, and then use target data type → target data content → target data condition → target aggregation logic as the target configuration rule. Subsequently, the data in the target data content that meets the target data condition can be aggregated according to the target aggregation logic to obtain the corresponding configuration result.

[0088] Through the above solution, the types of user selections are further increased, so that more target configuration rules can be configured, and the diverse needs of users are improved.

[0089] In some embodiments, the at least one aggregation logic includes: each data condition corresponds to at least one aggregation field, and each aggregation field corresponds to at least one aggregation method.

[0090] Step 20222 includes:

[0091] Step 202221, select a target aggregation field from at least one aggregation field corresponding to the target data condition.

[0092] In specific implementation, the aggregation field is a specific data field in the data in the target data content that meets the target data condition (such as at least one of table header, each table item, text, number, symbol).

[0093] Step 202222, select a target aggregation method from at least one aggregation method corresponding to the target aggregation field.

[0094] In specific implementation, the aggregation method specifically refers to the corresponding aggregation formula (for example, at least one of summation, total calculation, maximum value calculation, minimum value calculation, average value calculation, variance calculation).

[0095] Step 202223: The process of aggregating the data of the target aggregation field that meets the target data conditions in the target data content according to the target aggregation method is used as the target configuration rule.

[0096] In specific implementation, according to the above steps, we can obtain: target data type → target data content → target data conditions → target aggregation field → target aggregation method, as the target configuration rule. Having more selectivity in the configuration process of at least the above five configuration items allows users to determine the most suitable target configuration rule for the data metric by making selections layer by layer.

[0097] For example, for the data source type of table, select Table 1 from the data:

[0098]

[0099]

[0100] The configuration rule for Data Metric 1 is: target data type: table → target data content: Table 1 → target data conditions: after February 10 (inclusive) → target aggregation field: Content FFF → target aggregation method: count total, and the resulting configuration result is total 12. Storing Data Metric 1: total 12 is convenient for subsequent determination of the configuration file for use.

[0101] In some embodiments, if the user is not satisfied with the configured data metric and needs to make adjustments, after step 204, the configuration method for the data metric further includes:

[0102] Step 205: Receive a first modification instruction for the configuration result of the data metric and display the configuration content of the configuration result.

[0103] Step 206: Determine the modification item and receive the new configuration rule for the modification item, where the modification item includes: target data type and / or target configuration rule.

[0104] Step 207: Perform configuration processing according to the new configuration rule to obtain a new configuration result.

[0105] Step 208: Associate and save the new configuration result with the data metric.

[0106] During specific implementation, the target data type and / or target configuration rule corresponding to the configuration result of the data indicator can be modified, where the first modification instruction includes at least one of: a deletion instruction, an update instruction, and an addition instruction.

[0107] Through the above solution, a modification function is provided for the configured data indicator, which can save the situation of incorrect or unreasonable configuration of the data indicator.

[0108] In the above embodiments:

[0109] The target configuration rule is: target data type → target data content → target aggregation strategy;

[0110] The target configuration rule is: target data type → target data content → target data condition → target aggregation logic;

[0111] The target configuration rule is: target data type → target data content → target data condition → target aggregation field → target aggregation method.

[0112] Any configuration item of the target configuration rule can be modified.

[0113] In some embodiments, the method for configuring data indicators further includes:

[0114] Step A1, receiving a rule configuration request and determining a new configuration rule.

[0115] Step A2, determining the configuration data type corresponding to the new configuration rule from the data source.

[0116] Step A3, setting at least one configuration logic for the configuration data type, and associating and saving at least one configuration logic of the configuration data type with the new configuration rule.

[0117] Through the above solution, if the user finds that there is no configuration rule desired by the user among the configuration rules corresponding to the target data type, the user can initiate a rule configuration request to set at least one configuration logic for the determined configuration data type to obtain a new configuration rule, so that the new configuration rule can be retrieved when the user needs it later.

[0118] In some embodiments, after step 204, the method for configuring data indicators further includes:

[0119] Step B1, receiving a processing function for at least one of the data indicators;

[0120] Step B2, using the processing function to perform arithmetic processing on the configuration results respectively corresponding to at least one of the data indicators, and associating and saving the arithmetic results with new data indicators.

[0121] For example, for data metric 1 and data metric 2, the processing function: data metric 1 * data metric 2 can be used for arithmetic processing to obtain the arithmetic result corresponding to the new data metric m.

[0122] Through the above solution, the arithmetic result can be determined by the arithmetic processing of the configured data metrics through the processing function and associated with the new data metric. This way of obtaining the new data metric is more convenient and faster.

[0123] Based on the same concept, an embodiment of the present application provides a method for determining a configuration file, as Figure 3 shown, including:

[0124] Step 301, select at least one target data metric from at least one data metric determined according to the data metric configuration method of the above embodiment.

[0125] Step 302, determine the combination method corresponding to the at least one target data metric.

[0126] Step 303, perform combination processing on the at least one target data metric according to the combination method, and integrate the combination processing results to obtain a configuration file.

[0127] Specifically in implementation, the corresponding combination methods include: at least one of the arrangement methods of each target data metric and the combination operation formula. After combining each target data metric according to the combination method, the obtained combination processing results are integrated together to form a configuration file.

[0128] The configuration file can be at least one of a data report, a data graph, and a data text.

[0129] Through the above solution, the configuration file required by the user is obtained by selecting and combining the associated saved data metrics, which makes the process of obtaining the configuration file more convenient and simple, brings great convenience to the user, and saves labor costs.

[0130] In some embodiments, the method for determining a configuration file further includes:

[0131] Step 304, receive a second modification instruction for the configuration file.

[0132] Step 305, perform at least one of a data deletion operation, a data update operation, and a data addition operation on the data in the configuration file according to the second modification instruction.

[0133] The second modification instruction includes at least one of a deletion instruction, an update instruction, and an addition instruction.

[0134] Through the above solution, a function to modify the determined configuration file is provided. In this way, if the user is not satisfied with the content in the configuration file, they can make corresponding modifications, which provides convenience for the user.

[0135] For example, the configuration file is a data report, and the user can delete, update, or add the content corresponding to the rows or columns in the data report.

[0136] It should be noted that the method for determining the configuration file in the embodiments of the present application is executed based on the method for configuring the data indicators in the above embodiments, and has the same technical effects as the method for configuring the data indicators, which will not be elaborated here.

[0137] The method for configuring the data indicators and the method for determining the configuration file in the present application can be applied to at least one of human resource statistics business, work data statistics, project progress statistics, material statistics, engineering statistics, geographical statistics, and commodity statistics.

[0138] The following describes the execution process of the method for configuring the data indicators and the method for determining the configuration file in the present application with a specific embodiment:

[0139] The data indicator query engine constructs a simplified data indicator query engine. According to the basic modules (data indicators) defined by the engine, the query differences of the user for different data sources can be masked.

[0140] Such as Figure 4A shown:

[0141] Various data types of the data source: mysql, es, hive, and mysql is selected as the target data type.

[0142] Data table: Table 1.

[0143] Data conditions: fields (time, type, etc.), expressions (greater than, less than, equal to, etc.), values corresponding to the expressions; for example: time > February 10th, then a data condition is constructed.

[0144] Aggregation field: for example, content FFF.

[0145] Aggregation method: sum, total, maximum value, minimum value. For example, total.

[0146] According to the above configuration, the following query can be made for data indicator 1: query the total of content FFF in Table 1 in mysql where time > February 10th.

[0147] The data index query engine of this application can be displayed in the configuration interface, allowing users to manually configure the data indexes to be queried without caring about the differences in the underlying program code logic. In this way, even if the data source query methods are inconsistent and the user does not understand the code but knows how to obtain the data, they can manually configure the data indexes.

[0148] As Figure 4B shown, after obtaining data index 1, data index 2, data index 3, data index 4, and data index 5 in the data index query engine, the corresponding combination methods can be configured in the combination engine (for example, the combination method for data report A: (data index 1, data index 2, (data index 3 + data index 4) / data index 5); the combination method for data report B: (data index 1, data index 3, data index 4 + data index 5)).

[0149] For example:

[0150] 1. If there is a new business requirement later and the information of data report B needs to be modified to: data index 1, data index 3 - data index 2, data index 4 + data index 5.

[0151] Then there is no need to rewrite a new set of code, nor to modify the data indexes in the data index query engine. Just modify the combination method in the combination engine, and the purpose of modifying data report B can be achieved.

[0152] 2. If there is a new business requirement later and the information of new report C needs to be added as: data index 1, data index 4 + data index 5, data index 6, there is also no need to rewrite a new set of code. Add a data index: data index 6 in the data index query engine. The specific addition process is the same as the configuration process of data index 1 above. Then add the combination method (data index 1, data index 4 + data index 5, data index 6) (one data report corresponds to one combination method) in the combination engine, and new report C can be obtained.

[0153] 3. If there is a new requirement later and the information of new report D needs to be added as: data index 1, data index 4, data index 7 * data index 8; there is also no need to rewrite a new set of program code. Add 2 data indexes: data index 7, data index 8 in the data index query engine. Then add the combination method (data index 1, data index 4, data index 7 * data index 8) in the combination engine, and new report D can be obtained.

[0154] An example of application: Taking the lm artificial data dashboard as an example, first define three data indexes through the business scenario:

[0155] Data index 1: The number of manual consultations;

[0156] Data metric 2: The number of first-time resolutions within 24 hours;

[0157] Data metric 3: The number of first-time resolutions within 48 hours.

[0158] After combining the atomic data metrics, the following 7 report data metrics can be generated on the report page:

[0159] Data metric A: The number of transfers to manual consultation;

[0160] Data metric B: The number of first-time resolutions within 24 hours;

[0161] Data metric C: The number of first-time resolutions within 48 hours;

[0162] Data metric D: The first-time resolution rate within 24 hours (Data metric B / Data metric A);

[0163] Data metric E: The first-time resolution rate within 48 hours (Data metric C / Data metric A);

[0164] Data metric F: The repeated resolution rate within 24 hours (Data metric A - Data metric B) / Data metric A;

[0165] Data metric G: The repeated resolution rate within 48 hours (Data metric A - Data metric C) / Data metric A.

[0166] When the data metrics are fixed, the increase in the number of data metrics corresponding to the data report can be displayed through the combination engine to configure the combination method.

[0167] Effect:

[0168] 1. It has good scalability. Modifying or adding a data report only requires configuring the corresponding data metrics and the combination method of the data metrics to be quickly completed, without the need for independent development of the entire data report.

[0169] 2. Lower development and operation and maintenance costs. The development and regression costs are lower during the determination of the entire data report. There is no large amount of duplicate code, and the regression content in the data report is more focused, only needing to pay attention to the aggregated data content in the data report.

[0170] 3. No performance issues: When the data metrics are fixed, the more data metrics there are and the higher the concurrency, the better the efficiency.

[0171] For the data report obtained in this exemplary embodiment, without any program development process, only the corresponding data metrics need to be configured and the combination method is set for the required data metrics, then a corresponding required data report can be configured, which is simple and fast.

[0172] It should be noted that the method of the embodiments of the present application can be executed by a single device, such as a computer or a server. The method of this embodiment can also be applied to a distributed scenario and completed by multiple devices cooperating with each other. In this case of a distributed scenario, one of the multiple devices can only execute one or more steps of the method of the embodiments of the present application, and these multiple devices will interact with each other to complete the described method.

[0173] It should be noted that some embodiments of the present application have been described above. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the above embodiments and still achieve the desired result. Additionally, the processes depicted in the drawings do not necessarily require the specific order or sequential order shown to achieve the desired result. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0174] Based on the same concept, corresponding to the method for configuring data metrics in any of the above embodiments, the present application further provides a device for configuring data metrics.

[0175] Refer to Figure 5 , the device for configuring data metrics includes:

[0176] A type selection module 501, configured to select a target data type corresponding to a data metric from various data types of a data source;

[0177] A rule determination module 502, configured to determine a target configuration rule corresponding to the target data type, where the target configuration rule is a configuration logic for the data source of the target data type;

[0178] A configuration processing module 503, configured to perform configuration processing on the data source of the target data type according to the target configuration rule to obtain a configuration result;

[0179] A saving module 504, configured to associate and save the configuration result with the data metric.

[0180] In some embodiments, each data type corresponds to at least one configuration rule;

[0181] The rule determination module 502 is specifically configured to: select a target configuration rule from at least one configuration rule corresponding to the target data type.

[0182] In some embodiments, each data type corresponds to at least one data content, and each data content corresponds to at least one aggregation policy;

[0183] The rule determination module 502 is further configured to:

[0184] Select a target data content from at least one data content corresponding to the target data type; select a target aggregation policy from at least one aggregation policy corresponding to the target data content, and use the process of aggregating the target data content according to the target aggregation policy as the target configuration rule.

[0185] In some embodiments, the at least one aggregation policy includes: each data content corresponds to at least one data condition, and each data condition corresponds to at least one aggregation logic;

[0186] The rule determination module 502 is further configured to:

[0187] Select a target data condition from at least one data condition corresponding to the target data content; select a target aggregation logic from at least one aggregation logic corresponding to the target data condition, and use the process of aggregating the data in the target data content that meets the target data condition according to the target aggregation logic as the target configuration rule.

[0188] In some embodiments, the at least one aggregation logic includes: each data condition corresponds to at least one aggregation field, and each aggregation field corresponds to at least one aggregation method;

[0189] The rule determination module 502 is further configured to:

[0190] Select a target aggregation field from at least one aggregation field corresponding to the target data condition; select a target aggregation method from at least one aggregation method corresponding to the target aggregation field; and use the process of aggregating the data of the target aggregation field in the target data content that meets the target data condition according to the target aggregation method as the target configuration rule.

[0191] In some embodiments, the configuration device for data metrics further includes: a metric modification module, configured to:

[0192] After associatively saving the configuration result with the data metric, receive a first modification instruction for the configuration result of the data metric, display the configuration content of the configuration result; determine a modification item, receive a new configuration rule for the modification item, where the modification item includes: a target data type and / or a target configuration rule; perform configuration processing according to the new configuration rule to obtain a new configuration result; and associatively save the new configuration result with the data metric.

[0193] In some embodiments, the configuration device for data metrics further includes: a rule addition module, configured to:

[0194] Receive a rule configuration request, determine a new configuration rule; determine the configuration data type corresponding to the new configuration rule from the data source; set at least one configuration logic for the configuration data type, and associate and save at least one configuration logic of the configuration data type with the new configuration rule.

[0195] In some embodiments, the configuration device for data metrics further includes: a new data metric configuration module, configured to:

[0196] After associating and saving the configuration result with the data metric, receive a processing function for at least one of the data metrics; use the processing function to perform arithmetic processing on the configuration results respectively corresponding to the at least one data metric, and associate and save the arithmetic result with a new data metric.

[0197] Based on the same concept, corresponding to the method for determining a configuration file in any of the above embodiments, the present application further provides a device for determining a configuration file.

[0198] Reference Figure 6 , the device for determining a configuration file includes:

[0199] A data metric selection module 601, configured to select at least one target data metric from at least one data metric determined according to the data metric configuration method described in the above embodiments;

[0200] A combination mode matching module 602, configured to determine the combination mode corresponding to the at least one target data metric;

[0201] A combination processing module 603, configured to perform combination processing on the at least one target data metric according to the combination mode, and integrate the combination processing result to obtain a configuration file.

[0202] In some embodiments, the device for determining a configuration file further includes: a configuration file modification module, configured to:

[0203] Receive a second modification instruction for the configuration file; according to the second modification instruction, perform at least one of a data deletion operation, a data update operation, and a data addition operation on the data in the configuration file.

[0204] For the convenience of description, when describing the above device, it is divided into various modules according to functions for description. Of course, when implementing the present application, the functions of each module can be implemented in the same or multiple software and / or hardware.

[0205] The device in the above embodiments is used to implement the corresponding method in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be described in detail here.

[0206] Based on the same inventive concept, corresponding to the method of any of the above embodiments, the present application further provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein when the processor executes the program, the method of any of the above embodiments is implemented.

[0207] Figure 7 FIG. shows a more specific schematic diagram of the hardware structure of the electronic device provided in this embodiment. The device may include: a processor 710, a memory 720, an input / output interface 730, a communication interface 740, and a bus 750. Among them, the processor 710, the memory 720, the input / output interface 730, and the communication interface 740 are communicatively connected to each other inside the device through the bus 750.

[0208] The processor 710 may be implemented in a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, etc., and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0209] The memory 720 may be implemented in the form of a ROM (Read Only Memory), a RAM (Random Access Memory), a static storage device, a dynamic storage device, etc. The memory 720 may store an operating system and other application programs. When implementing the technical solutions provided in the embodiments of this specification through software or firmware, the relevant program codes are stored in the memory 720 and are called and executed by the processor 710.

[0210] The input / output interface 730 is used to connect to an input / output module to implement information input and output. The input / output module may be configured as a component in the device (not shown in the figure) or externally connected to the device to provide corresponding functions. Among them, the input device may include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output device may include a display, a speaker, a vibrator, an indicator light, etc.

[0211] The communication interface 740 is used to connect to a communication module (not shown in the figure) to implement communication interaction between this device and other devices. Among them, the communication module may implement communication in a wired manner (such as USB, network cable, etc.) or in a wireless manner (such as mobile network, WIFI, Bluetooth, etc.).

[0212] The bus 750 includes a path for transmitting information between various components of the device, such as the processor 710, the memory 720, the input / output interface 730, and the communication interface 740.

[0213] It should be noted that although only the processor 710, the memory 720, the input / output interface 730, the communication interface 740, and the bus 750 are shown in the above device, in the specific implementation process, the device may also include other components necessary for normal operation. In addition, those skilled in the art can understand that the above device may also only include the components necessary to implement the solution of the embodiments of the present specification, and do not necessarily include all the components shown in the figure.

[0214] The electronic device of the above embodiment is used to implement the configuration method of the corresponding data index and the determination method of the configuration file in any of the foregoing embodiments, and has the beneficial effects of the embodiments of the configuration method of the corresponding data index and the determination method of the configuration file, which will not be elaborated here.

[0215] Based on the same concept, corresponding to the method of any of the above embodiments, the present application also provides a non-transitory computer-readable storage medium storing computer instructions for causing the computer to execute the method described in any of the above embodiments.

[0216] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory, or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD), or other optical storage, magnetic cassette tapes, magnetic disk storage, or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible by a computing device.

[0217] The computer instructions stored in the storage medium of the above embodiment are used to cause the computer to execute the method described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be elaborated here.

[0218] Based on the same inventive concept, corresponding to any of the above-described method embodiments, the present application further provides a computer program product, including computer program instructions, which when running on a computer, cause the computer to execute the method described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be elaborated herein again.

[0219] Those of ordinary skill in the art should understand that: The discussion of any of the above embodiments is only exemplary, and is not intended to imply that the scope of the present application (including the claims) is limited to these examples; Under the concept of the present application, the technical features in the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations in different aspects of the embodiments of the present application as described above, and they are not provided in detail for the sake of brevity.

[0220] In addition, for the sake of simplicity of description and discussion, and in order not to make the embodiments of the present application difficult to understand, the well-known power / ground connections to integrated circuit (IC) chips and other components may or may not be shown in the provided drawings. In addition, the devices may be shown in block diagram form in order to avoid making the embodiments of the present application difficult to understand, and this also takes into account the fact that the details of the implementation of these block diagram devices are highly dependent on the platform on which the embodiments of the present application are to be implemented (i.e., these details should be completely within the understanding of those skilled in the art). In the case where specific details (such as circuits) are set forth to describe the exemplary embodiments of the present application, it will be apparent to those skilled in the art that the embodiments of the present application can be implemented without these specific details or with variations of these specific details. Therefore, these descriptions should be considered illustrative rather than restrictive.

[0221] Although the present application has been described in connection with specific embodiments of the present application, many alternatives, modifications, and variations of these embodiments will be apparent to those of ordinary skill in the art based on the foregoing description. For example, other memory architectures (such as dynamic RAM (DRAM)) may be used with the embodiments discussed.

[0222] The embodiments of the present application are intended to cover all such alternatives, modifications, and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present application shall be included within the protection scope of the present application.

Claims

1. A method for configuring data indicators, characterized in that, Including: Selecting the target data type corresponding to the data metric from various data types of the data source; Determining the target configuration rule corresponding to the target data type, where the target configuration rule is the configuration logic for the data source of the target data type; Performing configuration processing on the data source of the target data type according to the target configuration rule to obtain a configuration result; Associating and saving the configuration result with the data metric.

2. The method for configuring data indicators according to claim 1, characterized in that, Each data type corresponds to at least one configuration rule; The determining the target configuration rule corresponding to the target data type includes: Selecting a target configuration rule from at least one configuration rule corresponding to the target data type.

3. The method for configuring data indicators according to claim 1, characterized in that, Each data type corresponds to at least one data content, and each data content corresponds to at least one aggregation policy; The determining the target configuration rule corresponding to the target data type includes: Selecting a target data content from at least one data content corresponding to the target data type; Selecting a target aggregation policy from at least one aggregation policy corresponding to the target data content, and taking the process of aggregating the target data content according to the target aggregation policy as the target configuration rule.

4. The method for configuring data indicators according to claim 3, characterized in that, The at least one aggregation policy includes: each data content corresponds to at least one data condition, and each data condition corresponds to at least one aggregation logic; The selecting a target aggregation policy from at least one aggregation policy corresponding to the target data content, and taking the process of aggregating the target data content according to the target aggregation policy as the target configuration rule includes: Selecting a target data condition from at least one data condition corresponding to the target data content; Selecting a target aggregation logic from at least one aggregation logic corresponding to the target data condition, and taking the process of aggregating the data in the target data content that meets the target data condition according to the target aggregation logic as the target configuration rule.

5. The method for configuring data indicators according to claim 4, characterized in that, The at least one aggregation logic includes: each data condition corresponds to at least one aggregation field, and each aggregation field corresponds to at least one aggregation method; The selecting a target aggregation logic from at least one aggregation logic corresponding to the target data condition, and taking the process of aggregating the data in the target data content that meets the target data condition according to the target aggregation logic as the target configuration rule includes: Selecting a target aggregation field from at least one aggregation field corresponding to the target data condition; Selecting a target aggregation method from at least one aggregation method corresponding to the target aggregation field; Taking the process of aggregating the data of the target aggregation field in the target data content that meets the target data condition according to the target aggregation method as the target configuration rule.

6. The method for configuring data indicators according to claim 1, characterized in that, After the associating and saving the configuration result with the data metric, it further includes: Receiving a first modification instruction for the configuration result of the data metric, and displaying the configuration content of the configuration result; Determining a modification item, and receiving a new configuration rule for the modification item, where the modification item includes: a target data type and / or a target configuration rule; Perform configuration processing according to the new configuration rules to obtain a new configuration result; Associate and save the new configuration result with the data metrics.

7. The method for configuring data indicators according to claim 1, characterized in that, Further includes: Receive a rule configuration request and determine a new configuration rule; Determine the configuration data type corresponding to the new configuration rule from the data source; Set at least one configuration logic for the configuration data type, and associate and save at least one configuration logic of the configuration data type with the new configuration rule.

8. The method for configuring data indicators according to claim 1, characterized in that,After the step of associating and saving the configuration result with the data metrics, further includes: Receive a processing function for at least one of the data metrics; Use the processing function to perform arithmetic processing on the configuration results corresponding to at least one of the data metrics, and associate and save the arithmetic results with new data metrics.

9. A method for determining a configuration file, characterized in that, Includes: Select at least one target data metric from at least one data metric determined by the data metric configuration method according to any one of claims 1 to 8; Determine the combination method corresponding to the at least one target data metric; Perform combination processing on the at least one target data metric according to the combination method, and integrate the combination processing results to obtain a configuration file.

10. The method for determining a configuration file according to claim 9, characterized in that, Further includes: Receive a second modification instruction for the configuration file; According to the second modification instruction, perform at least one of a data deletion operation, a data update operation, and a data addition operation on the data in the configuration file.

11. A configuration device for data metrics, characterized in that, Includes: A type selection module configured to select a target data type corresponding to a data metric from various data types of a data source; A rule determination module configured to determine a target configuration rule corresponding to the target data type, where the target configuration rule is a configuration logic for the data source of the target data type; A configuration processing module configured to perform configuration processing on the data source of the target data type according to the target configuration rule to obtain a configuration result; A saving module configured to associate and save the configuration result with the data metrics.

12. A device for determining a configuration file, characterized in that, Includes: A data metric selection module configured to select at least one target data metric from at least one data metric determined by the data metric configuration method according to any one of claims 1 to 8; A combination method matching module configured to determine the combination method corresponding to the at least one target data metric; A combination processing module configured to perform combination processing on the at least one target data metric according to the combination method, and integrate the combination processing results to obtain a configuration file.

13. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method according to any one of claims 1 to 10.

14. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause a computer to execute the method according to any one of claims 1 to 10.

15. A computer program product comprising computer program instructions, characterized in that, When the computer program instructions run on a computer, the computer is caused to execute the method according to any one of claims 1 - 10.

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