Dynamic parameter query method and system, report designer and storage medium

Abstract

The invention provides a dynamic parameter query method and system, a report designer and a storage medium. The method comprises the following steps: acquiring a query request uploaded by a target user at a user side of the report designer; determining neighborhood anchor points of query configuration information in adjacent service data through the query configuration information of all the service data; determining a query logic item of a database of the report designer in a static state according to the neighborhood anchor points and all query index values; determining a query trap door of the database of the report designer in a dynamic state according to the neighborhood anchor point and the query condition; and according to the query logic item and the query trap door, determining a query cost during dynamic parameter query, and according to the query cost, determining a target query result of the dynamic parameters in the report designer. According to the scheme, the target query result of the dynamic parameters in the report designer is determined based on the query cost, dynamic logic distribution during dynamic parameter query can be achieved, and the dynamic query compatibility during dynamic parameter query is improved.

Description

Technical Field

[0001] The present application relates to the field of parameter query technology, and more specifically, to a dynamic parameter query method, system, report designer and storage medium. Background Art

[0002] Parameter query is a data retrieval technology that allows users to provide parameter values ​​at runtime, thereby dynamically generating and executing query statements. This technology is widely used in report generation, data analysis, and search functions. By using parameter placeholders, the query conditions are changed from hard-coded to configurable. Users customize the query conditions by entering or selecting parameter values. The system replaces the placeholders with these parameter values ​​at runtime to generate specific query statements. Dynamic parameter query improves the flexibility of the query and the user experience, while enhancing security.

[0003] The dynamic parameter query method refers to a technical method for dynamically generating and executing queries in the process of database query and data retrieval by using parameter placeholders in the query statement and providing specific parameter values ​​by the user at runtime, including: defining parameter placeholders in the query statement, designing a user input interface to obtain parameter values, replacing the placeholders with the parameter values ​​provided by the user to generate an actual query statement, and executing the generated query to return results, allowing the user to adjust the query conditions as needed, while enhancing security and preventing structured query language (SQL) injection attacks. However, in the existing dynamic parameter query, the dynamic query statement is different each time the dynamic query is executed, and the query cache mechanism of the database cannot be used, so that there may be dependencies or conflicts between dynamic parameters. For example, an invalid date range or an unmatched product category is selected, resulting in the query result not meeting expectations, and the dynamic logic allocation during dynamic parameter query cannot be achieved, which in turn leads to a reduction in the dynamic query compatibility during dynamic parameter query. Therefore, how to achieve dynamic logic allocation during dynamic parameter query and improve the dynamic query compatibility during dynamic parameter query is a problem faced by the industry. Summary of the invention

[0004] The present application provides a dynamic parameter query method, system, report designer and storage medium, which can realize dynamic logic allocation during dynamic parameter query, and effectively improve the dynamic query compatibility during dynamic parameter query.

[0005] In a first aspect, the present application provides a dynamic parameter query method, comprising the following steps:

[0006] Get the query request uploaded by the target user on the user side of the report designer;

[0007] Extract query configuration information of each business data in the report designer according to the query request, and determine a neighborhood anchor point of query configuration information in adjacent business data through the query configuration information of all business data;

[0008] Determine a query index table of the database of the report designer when it is static, perform hierarchical fusion on the query index table to obtain query index values ​​of different query logic layers, and determine the query logic items of the database of the report designer when it is static according to the neighborhood anchor point and all query index values;

[0009] Acquire a dynamic data segment of the database of the report designer when it is dynamic, determine a query condition at a dynamic time node when querying according to the dynamic data segment, and determine a query trap of the database of the report designer when it is dynamic according to the neighborhood anchor point and the query condition;

[0010] The query cost of dynamic parameter query is determined according to the query logic item and the query trapdoor, and the target query result of the dynamic parameter in the report designer is determined according to the query cost.

[0011] In some embodiments, extracting query configuration information of each business data in the report designer according to the query request specifically includes:

[0012] Parsing the query request to obtain multiple query configuration items;

[0013] Classify the business data in the report designer according to all query configuration items to obtain the query configuration information of each business data.

[0014] In some embodiments, determining the neighborhood anchor point of query configuration information in adjacent service data through query configuration information of all service data specifically includes:

[0015] Determine the configuration feature quantity in the query configuration information of all business data;

[0016] Determine the mutual proximity similarity in the query configuration information of the adjacent service data according to all configuration feature quantities;

[0017] A neighborhood anchor point in the query configuration information of the adjacent service data is determined according to the mutual proximity similarity.

[0018] In some embodiments, determining the query index table of the database of the report designer when it is static specifically includes:

[0019] Get the business data collection of the report designer's database when it is static;

[0020] Determine multiple query index quantities according to the business data set;

[0021] Determine the query index table of the report designer's database at static time based on the amount of all query indexes.

[0022] In some embodiments, performing hierarchical fusion on the query index table to obtain query index values ​​of different query logic layers specifically includes:

[0023] Determine valid query features in the query index table;

[0024] Extracting query logic information from the effective query features;

[0025] All query logic information is processed in a hierarchical manner to obtain hierarchical query index degrees;

[0026] All query index degrees of each level are connected to obtain query index values ​​of different query logic layers.

[0027] In some embodiments, determining the query logic items of the database of the report designer at a static state according to the neighborhood anchor point and all query index values ​​specifically includes:

[0028] Determining a query priority value based on the neighborhood anchor point and all query index values;

[0029] Determine the query logic characteristics of the report designer's database when it is static;

[0030] The query logic items of the database of the report designer when it is static are determined according to the query priority value and the query logic characteristics.

[0031] In some embodiments, determining the query condition at the dynamic time node during query according to the dynamic data segment specifically includes:

[0032] Mapping the query data in the dynamic data segment to a configuration target location during dynamic parameter query;

[0033] Determine the amount of configuration query optimization at dynamic time nodes during query;

[0034] Generate query conditions at dynamic time nodes during querying according to the configured target position and the configured query optimization amount.

[0035] In a second aspect, the present application provides a dynamic parameter query system, comprising:

[0036] The acquisition module is used to acquire the query request uploaded by the target user on the user end of the report designer;

[0037] A processing module, configured to extract query configuration information of each business data in the report designer according to the query request, and determine a neighborhood anchor point of query configuration information in adjacent business data through the query configuration information of all business data;

[0038] The processing module is further used to determine the query index table of the database of the report designer when it is static, perform hierarchical fusion on the query index table to obtain query index values ​​of different query logic layers, and determine the query logic items of the database of the report designer when it is static according to the neighborhood anchor point and all query index values;

[0039] The processing module is further used to obtain a dynamic data segment of the database of the report designer when it is dynamic, determine a query condition at a dynamic time node when querying according to the dynamic data segment, and determine a query trap of the database of the report designer when it is dynamic according to the neighborhood anchor point and the query condition;

[0040] The execution module is used to determine the query cost of dynamic parameter query according to the query logic item and the query trapdoor, and determine the target query result of the dynamic parameter in the report designer according to the query cost.

[0041] In a third aspect, the present application provides a report designer, which includes the above-mentioned dynamic parameter query system.

[0042] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned dynamic parameter query method is implemented.

[0043] The technical solution provided by the embodiments disclosed in this application has the following beneficial effects:

[0044] The dynamic parameter query method, system, report designer and storage medium provided by the present application first obtain a query request uploaded by a target user on a user end of a report designer; secondly, extract query configuration information of each business data in the report designer according to the query request, and determine a neighborhood anchor point of query configuration information in adjacent business data through the query configuration information of all business data; then, determine a query index table of the database of the report designer when it is static, perform hierarchical fusion on the query index table to obtain query index values ​​of different query logic layers, and determine a query logic item of the database of the report designer when it is static according to the neighborhood anchor point and all query index values; then, obtain a dynamic data segment of the database of the report designer when it is dynamic, determine a query condition on a dynamic time node when querying according to the dynamic data segment, and determine a query trapdoor of the database of the report designer when it is dynamic according to the neighborhood anchor point and the query condition; finally, determine a query cost when querying a dynamic parameter according to the query logic item and the query trapdoor, and determine a target query result of the dynamic parameter in the report designer according to the query cost.

[0045] It can be seen that the present application first determines the query logic items of the report designer's database when it is static based on the neighborhood anchor points and all query index values, so that the query can be dynamically adjusted and optimized according to specific parameter conditions during runtime. When dynamic parameter queries involve different query conditions and variables, the structure and execution path of the query statement may change. By optimizing the query logic items in the static period, the system can better handle changes in dynamic parameters and ensure the consistency and accuracy of the query results. Then, the query trap of the report designer's database when it is dynamic is determined based on the neighborhood anchor points and query conditions. The query conditions can be adjusted and optimized according to dynamic parameters or user input, so as to dynamically generate query statements that meet actual needs. The specified query trap can ensure that the system can handle various possible input situations, and correctly generate and execute queries, avoiding query failures or inconsistencies caused by changes in input conditions; finally, the query cost of dynamic parameter query is determined according to the query logic items and query traps, and the target query result of the dynamic parameter in the report designer is determined according to the query cost. In order to effectively overcome the query conflicts caused by different combinations and conditions of dynamic parameters, the query logic is dynamically allocated and adjusted according to different input conditions or query requirements to minimize the query cost and optimize the query execution, so as to obtain the expected target query result; in summary, dynamic logic allocation during dynamic parameter query can be realized, and the dynamic query compatibility during dynamic parameter query can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 is an exemplary flow chart of a dynamic parameter query method according to some embodiments of the present application;

[0047] Figure 2 is a schematic diagram of a multi-level index logic structure diagram according to some embodiments of the present application;

[0048] Figure 3 is a schematic diagram of a dynamic parameter query process model according to some embodiments of the present application;

[0049] Figure 4 is a schematic diagram of exemplary hardware and / or software of a dynamic parameter query system according to some embodiments of the present application;

[0050] Figure 5 It is a structural diagram of a computer device for implementing a dynamic parameter query method according to some embodiments of the present application. DETAILED DESCRIPTION

[0051] The core of the present application is to obtain the query request uploaded by the target user on the user end of the report designer; extract the query configuration information of each business data in the report designer according to the query request, and determine the neighborhood anchor point of the query configuration information in the adjacent business data through the query configuration information of all business data; determine the query index table of the database of the report designer when it is static, hierarchically merge the query index table to obtain the query index values ​​of different query logic layers, and determine the query logic item of the database of the report designer when it is static according to the neighborhood anchor point and all query index values; obtain the dynamic data segment of the database of the report designer when it is dynamic, determine the query condition on the dynamic time node when querying according to the dynamic data segment, and determine the query trap of the database of the report designer when it is dynamic according to the neighborhood anchor point and the query condition; determine the query cost when querying dynamic parameters according to the query logic item and the query trap, and determine the target query result of the dynamic parameter in the report designer according to the query cost, and then complete the dynamic parameter query, which can realize the dynamic logic allocation when querying dynamic parameters and improve the dynamic query compatibility when querying dynamic parameters.

[0052] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods. Figure 1 , which is an exemplary flow chart of a dynamic parameter query method according to some embodiments of the present application. The dynamic parameter query method 100 mainly includes the following steps:

[0053] In step 101, a query request uploaded by a target user on a user end of a report designer is obtained.

[0054] In the specific implementation, first, a query input control is designed in the user interface for the user to input or select query conditions; secondly, the query conditions input by the user can be captured when the user submits the query request, for example, the query conditions captured when the user submits the query request are encapsulated into a query request object using a high-level, interpreted programming language (such as JavaScript); then, the request object can be sent to the server through technologies for creating interactive and dynamic web applications (such as AJAX) or other communication technologies; finally, the server receives and parses the request, generates a corresponding query statement or configuration, and can effectively obtain the user's query request.

[0055] It should be noted that the query request uploaded by the user side in this application indicates that the target user inputs or selects query conditions through the user interface of the report designer, and submits these conditions to the server side to generate a corresponding report or perform a data retrieval request. The query request usually contains user-specified parameters and conditions, such as time range, classification, keywords, etc.; for example, in the report designer, the query user selects a time range and specifies a product category, and then clicks the "Submit" button. This operation generates a query request, which contains the time range and product category information entered by the query user, and sends the request to the server side for corresponding data query and report generation.

[0056] In step 102, query configuration information of each business data in the report designer is extracted according to the query request, and a neighborhood anchor point of query configuration information in adjacent business data is determined through the query configuration information of all business data.

[0057] In some embodiments, reference Figure 2 As shown, this figure is a schematic diagram of the multi-level index logical structure diagram shown in some embodiments of the present application. In the present application, the business data for dynamic parameter query in the report designer is set as financial business data, and the financial business data includes macroeconomic data, financial data, market data, transaction data, etc.; financial business data is different from general data. In addition to the general characteristics of data, it also has its own unique properties such as extensiveness, reliability, and continuity. Therefore, the input review of financial data is stricter, the storage capacity is larger, the network transmission is wider, the data maintenance is more frequent, and the data distribution is more uneven. These characteristics distinguish financial business data from other data, and also pose more challenges to the retrieval query of related data. Therefore, it is necessary to use the multi-level index structure to effectively divide the massive financial business data into subsets, so that the inquirer can quickly locate the corresponding data object in the financial business database and improve the work efficiency. To this end, it is necessary to first analyze the multi-level index logical structure.

[0058] The traditional indexing method is that data files and directories directly correspond to an index value, which is the so-called first-level indexing method. This method is inefficient and may encounter data query errors due to files with the same name. In the multi-level index logical structure, the method can be divided into first-level index, second-level index, third-level index, etc. The first-level index will divide a large space so that each space corresponds to a first-level index. The second-level index will be further divided within the space corresponding to the first-level index, and so on. Multiple levels can be set to improve data query efficiency and accuracy. Moreover, this method can better handle frequently updated large-scale data, and the advantages are more obvious.

[0059] In some embodiments, extracting query configuration information of each business data in the report designer according to the query request can be implemented by the following steps:

[0060] Parsing the query request to obtain multiple query configuration items;

[0061] Classify the business data in the report designer according to all query configuration items to obtain the query configuration information of each business data.

[0062] In the specific implementation, first, in order to clarify the data range and specific conditions that the query user wants to query, the query request is parsed to extract various query parameters, such as date range, category, keyword, etc., wherein the process of parsing the query request can be to parse the query parameters in the request body after the backend receives the request, and the parsing can be completed by code, such as parsing the application layer protocol for transmitting hypertext in the programming language to perform query request parsing of the request body statement, and corresponding query configuration items can be generated according to the date range, category, keyword, etc. Each query parameter can be used as a type of query configuration item, and the query parameter setting query configuration item can be selected according to actual needs, which is not limited here; then, according to the parsed query configuration item, the business data is classified and, This process can logically classify business data according to different query dimensions (such as time, category, geographic location, etc.). For example, it can be divided into different time periods according to the time dimension, and it can be divided into different product or service categories according to the category. The data of each category will form an independent business data partition, so that query configuration information can be generated in a targeted manner later; finally, the corresponding query configuration information is generated for each divided business data partition. This configuration information will contain specific query conditions, parameters and data source information. The generated query configuration information should be stored in a structured manner for quick access and use in subsequent query processes. By generating query configuration information, it can be ensured that queries for each business data partition can be performed efficiently and accurately.

[0063] It should be noted that the query configuration items in this application represent the specific parameters and conditions used to define and manage query operations in the report designer. The query configuration items are the bridge between the query request and the actual data retrieval, ensuring that the query process is efficient and accurate. The information contained in the query configuration items helps the system generate correct query statements based on the user's query request and perform corresponding data retrieval; the query configuration information for multiple categories of business data represents a set of query configuration items generated for different categories of business data. These configuration information are used to define and manage specific query conditions and parameters for each category of business data, ensuring that the data required by the user can be accurately and efficiently retrieved and presented in the report designer.

[0064] In some embodiments, determining the neighborhood anchor point of query configuration information in adjacent service data through query configuration information of all service data may be implemented by the following steps:

[0065] Determine the configuration feature quantity in the query configuration information of all business data;

[0066] Determine the mutual proximity similarity in the query configuration information of the adjacent service data according to all configuration feature quantities;

[0067] A neighborhood anchor point in the query configuration information of the adjacent service data is determined according to the mutual proximity similarity.

[0068] In the specific implementation, first, a systematic analysis is performed on the query configuration information to identify key attributes or parameters that can describe the query characteristics and behaviors of each type of business data. For example, there may be a start time and an end time for time data, and there may be a product category, a price range, etc. for product data. The sales volume in the product data is used as the configuration feature quantity in the query configuration information of the business data. In other embodiments, the sales date, product category, etc. may also be used as the configuration feature quantity in the query configuration information of the business data, which is not limited here; then, a similarity measure needs to be defined. Usually, a suitable similarity measure method is selected according to the business needs and the nature of the features. Commonly used similarity measure methods include cosine similarity, Euclidean distance and Jaccard similarity coefficient. In this application, the Jaccard similarity coefficient is selected to calculate the mutual proximity similarity in the query configuration information of adjacent business data. In other embodiments, other methods may also be used to determine the adjacent business data. The mutual proximity similarity in the query configuration information is used. For example, for the time range feature, the overlap of the time periods of the two types of data or the relative size of the interval can be calculated. For the product category feature, the common product category ratio of the two types of data can be calculated. Finally, the specific intersection between the two types of business data is used as the key node for dynamic parameter query of the adjacent data category. The neighborhood anchor point is usually identified as a specific data intersection or overlapping area in the similarity analysis. Then, according to the calculated mutual proximity similarity results, the neighborhood anchor points are screened out. These anchor points span the key parameters and conditions of the adjacent business data categories during the dynamic parameter query process. The neighborhood anchor points cover the overlap of time ranges, the intersection of product categories, the proximity of geographical locations, etc. Among them, before screening out the neighborhood anchor points, the mutual proximity similarities greater than the average value of all mutual proximity similarities can be used as candidates for the neighborhood anchor points. Finally, screening is performed from the candidates, which is not limited here.

[0069] It should be noted that the configuration feature quantities in the query configuration information in the present application are key attributes or parameters used to describe and define the query behavior and characteristics of each type of business data; mutual proximity similarity is a measure of the degree of similarity of the feature quantities of adjacent business data in their query configuration information. This similarity measure is usually used to compare and evaluate the consistency and similarity of the configuration information between two adjacent business data categories. Specifically, mutual proximity similarity can calculate its similarity based on different feature quantities (such as time range, product category, geographic location, etc.), thereby determining the commonality and overlap between business data categories in terms of query parameters, data sources, logical connections, etc.; the neighborhood anchor point in the query configuration information represents a specific connection point or key parameter between adjacent business data, which is used to support effective data interaction and query operations across adjacent data categories during dynamic parameter query.

[0070] In step 103, the query index table of the report designer's database when it is static is determined, the query index table is hierarchically fused to obtain query index values ​​of different query logic layers, and the query logic items of the report designer's database when it is static are determined based on the neighborhood anchor points and all query index values.

[0071] In some embodiments, reference Figure 3 As shown, this figure is a schematic diagram of the dynamic parameter query process model shown in some embodiments of the present application. In the dynamic parameter query of the report designer, in order to completely save and efficiently query the data in the report designer, before the dynamic parameter query, the owner of the financial business data (the financial business data stored in the report designer) will encrypt the privacy data (the key is stored locally) and store it in the cloud server. When the query user needs to use the query service, he first sends a registration request to the data owner. Once the data owner receives the request and registers the user, the key will be sent to the user, and the user will send a query request to the cloud server. The cloud server queries the encrypted privacy data through a query algorithm (such as the Skyline query algorithm) and sends the query result data to the query user. After receiving the query result data, the query user decrypts it through the local key and finally obtains the plaintext query result.

[0072] In some embodiments, determining the query index table of the database of the report designer when it is static can be implemented by the following steps:

[0073] Get the business data collection of the report designer's database when it is static;

[0074] Determine multiple query index quantities according to the business data set;

[0075] Determine the query index table of the report designer's database at static time based on the amount of all query indexes.

[0076] In specific implementation, obtaining the business data set of the report designer's database when it is static can be achieved by using a coefficient method, that is: all data sources in the report designer's database from the end of the last data storage to the current time, including the data content in database tables, views, files, etc., are collected in chronological order, and all data are placed in a set to obtain the business data set of the report designer's database when it is static, wherein, when collecting data sources in chronological order, the sales volume of product data in the data source is selected as the collection object, and in other embodiments, other data can also be selected, which is not limited here.

[0077] It should be noted that the business data set of the database of the report designer in the present application when static means the set of all business data within a period of time when the business data in the report designer is stored and no operation is performed on it.

[0078] In addition, it should be noted that when the report designer's database is static, it represents the state at a specific moment when no operation is performed on the report designer's database (for example, no operation is performed on the business data stored in the report designer), and frequent data updates, insertions, or deletions will not occur. The content in the database in this static state remains unchanged for a period of time, and consistent data analysis and query optimization can be performed.

[0079] In specific implementation, determining multiple query index quantities based on the business data set can be achieved in the following manner, namely: dividing all data in the business data set into equal intervals, for example, taking each hour as a division length, and calculating the data in the last division interval that is less than one hour as one hour, and then taking the average value of all data in each interval as the query index quantity for all intervals. In other embodiments, it is also possible to determine common query operations and query patterns by analyzing historical query logs and user behaviors, identify frequently queried fields and conditions, such as time range, product category, geographic location, etc., and then select a suitable index type based on the nature of each key query field and the characteristics of the query operation, which is not limited here.

[0080] It should be noted that the query index volume in this application represents a set of specific indexes that optimize database query performance. The index is determined based on business needs and query patterns, and aims to improve query efficiency and response speed. The query index volume includes all index sets designed and created to achieve efficient query.

[0081] In specific implementation, the query index table of the report designer's database when it is static can be determined based on all query index quantities in the following manner, namely: each query index quantity is used as a key field of the report designer's database when it is static, and based on the key field, the data in the interval where the query index quantity is located is used as the key information in the key field, and finally an index table is generated based on the key information and key data segments. This process can be implemented using a database management tool or script. Finally, the data in the sorted database is entered into the table to obtain the query index table of the report designer's database when it is static. In other embodiments, other methods can also be used to determine it, which is not limited here.

[0082] It should be noted that the query index table of the database of the report designer in this application when static represents a structured data table used to store and manage database index information to optimize and accelerate database query operations. It contains detailed information about the index, including index name, table name, field name, index type, creation time and current status, etc. This information helps the database system to quickly locate and access relevant data during query, thereby improving query efficiency and performance.

[0083] In addition, it should be noted that the index table in this application indicates that the information of a file is stored in several discontinuous physical blocks. The system establishes a dedicated data structure for each file in order to quickly and accurately find relevant financial business data in the financial business database, extract more utilization value from it, and improve the speed of financial business development.

[0084] In some embodiments, the query index table is hierarchically merged to obtain query index values ​​of different query logic layers, which can be achieved by using the following steps:

[0085] Determine valid query features in the query index table;

[0086] Extracting query logic information from the effective query features;

[0087] All query logic information is processed in a hierarchical manner to obtain hierarchical query index degrees;

[0088] All query index degrees of each level are connected to obtain query index values ​​of different query logic layers.

[0089] In the specific implementation, first, the variance of the sales of the product data corresponding to each index information in the query index table is compared with the number of sales of the product data to obtain multiple ratios, and all the ratios are used as the effective query features corresponding to each index information in the query index table; then, each effective query feature is subtracted from the mean of the effective query features, and the absolute value is taken, and the absolute value is used as the query logic information in the effective query feature. In other embodiments, other methods can also be used to determine the query logic information in the effective query feature, which is not limited here; then, the financial business data in the report designer is divided into a high priority query logic layer, a medium priority query logic layer and a low priority, that is, different query logic layers are obtained, wherein different logic The division of layers can be performed by machine learning, which will not be elaborated here. The query logic information is then mapped to each query logic layer, and the data center of the query logic information in each query logic layer is used as the tiered query index degree, wherein the data center of the query logic information in each query logic layer can be determined by a data feature fusion algorithm (such as principal component analysis), which is not limited here; finally, the query index values ​​of different query logic layers are determined according to the distance between each tiered query index degree and the mean of all tiered query index degrees (Euclidean distance can be used), that is, the distance between each tiered query index degree and the mean of all tiered query index degrees is used as the query index value of different query logic layers. In other embodiments, other methods can also be used to determine it, which is not limited here.

[0090] It should be noted that in the present application, effective query features refer to characteristic attributes that can significantly affect query performance, result accuracy or system resource utilization in dynamic parameter queries; query logic information refers to various key information and strategies that describe and plan query execution in the dynamic parameter query process; tiered query index degree refers to a metric that measures the importance or efficiency of queries at a specific logical level or priority in the dynamic parameter query process; query index values ​​at different query logical levels refer to a numerical value or score assigned to each logical level for different query logical levels or priorities in dynamic parameter queries. The index value is usually used to indicate the importance, priority or execution efficiency of the query at each logical level, which helps the system to dynamically adjust the query processing strategy according to specific business needs and performance goals.

[0091] In some embodiments, determining the query logic items of the report designer database at a static state according to the neighborhood anchor point and all query index values ​​can be implemented by the following steps:

[0092] Determining a query priority value based on the neighborhood anchor point and all query index values;

[0093] Determine the query logic characteristics of the report designer's database when it is static;

[0094] The query logic items of the database of the report designer when it is static are determined according to the query priority value and the query logic characteristics.

[0095] In the specific implementation, first, the neighborhood anchor point and all query index values ​​are normalized and then compared. If the neighborhood anchor point is greater than or equal to the query index value, the neighborhood anchor point is used as the query priority value. Conversely, if the neighborhood anchor point is less than the query index value, the query index value is used as the query priority value; then, according to the ratio of the mean of all neighborhood anchor points and the mean of query index value when the database of the report designer is static, the query logic characteristics of the database of the report designer when static are determined, that is, the ratio of the mean of all neighborhood anchor points and the mean of query index value when the database of the report designer is static is used as the query logic characteristics of the database of the report designer when static Logical characteristics. In other embodiments, other methods may also be used to determine the query logic characteristics of the report designer's database when it is static, which is not limited here. Finally, the query logic items of the report designer's database when it is static are determined based on the query priority value and the percentage of the query logic characteristics, that is, the query priority value and the percentage of the query logic characteristics are used as the query logic cost. The query logic cost represents the access cost of the query during dynamic parameter query. The smaller the query logic cost, the faster the query response speed. All query logic costs are then grouped into a set, and the set is used as the query logic item of the report designer's database when it is static.

[0096] It should be noted that the query priority value in the present application represents the ranking or hierarchical scoring of the priority of dynamic parameter queries, which helps to determine how dynamic parameter queries allocate resources and schedule the execution order of queries; the query logic feature represents the characteristics or attributes used to describe and define the query processing method, optimization strategy and data access mode in dynamic parameter queries. This feature is usually used to optimize query performance, improve system efficiency and manage data access processes; the query logic item represents the logical unit or identifier that describes and manages the query processing priority, execution order and related operations in dynamic parameter queries. By determining the query logic item, database administrators and developers can more accurately control and optimize the query processing process of the database system, thereby improving the overall performance, responsiveness and user experience of the system.

[0097] In step 104, the dynamic data segment of the database of the report designer is obtained, the query condition at the dynamic time node during the query is determined according to the dynamic data segment, and the query trap of the database of the report designer during the dynamic period is determined according to the neighborhood anchor point and the query condition.

[0098] In specific implementation, the dynamic data segments of the report designer's database when it is dynamic can be obtained in the following manner, namely: first, the report designer receives the query request from the user end, and secondly, parses the query request to determine the required data and conditions, and finally, executes the database query and dynamically generates data segments for all query results, that is, obtains the dynamic data segments.

[0099] It should be noted that the dynamic data segment in this application refers to a data fragment or data set that is dynamically generated or updated in the report designer according to real-time needs or changing conditions. The data segment can change dynamically based on factors such as user query requests, time periods, and changes in conditions to reflect the latest data status or specific data views.

[0100] In addition, it should be noted that the database of the report designer in the present application is in a dynamic state, which generally refers to a state in which the data and query results in the database can be dynamically updated, generated or presented according to real-time requests or changing conditions (that is, the data in the database in this state is changing rather than static, such as adding data or adjusting the position according to query instructions). This dynamism can be reflected in the report designer in real time according to user operations or external conditions, rather than a static and fixed state.

[0101] In some embodiments, determining the query condition at the dynamic time node during query according to the dynamic data segment may be implemented by the following steps:

[0102] Mapping the query data in the dynamic data segment to a configuration target location during dynamic parameter query;

[0103] Determine the amount of configuration query optimization at dynamic time nodes during query;

[0104] Generate query conditions at dynamic time nodes during querying according to the configured target position and the configured query optimization amount.

[0105] In specific implementation, first, the query data in the dynamic data segment is allocated to the corresponding query position according to the query condition, and the query position after allocation is used as the configuration target position, wherein the allocation process can adopt the query statement construction algorithm, the fruit fly algorithm, etc., which are not limited here; secondly, the data information on the dynamic time node during the query is initialized, and the initialization process can adopt uniform initialization, which is not limited here, and the initialized result is iteratively optimized until the termination condition is met to obtain the global optimal solution, and the global optimal solution is output as the configuration query optimization amount on the dynamic time node during the query, wherein the iterative optimization process can be implemented by the fruit fly algorithm; finally, the query data and the configuration query optimization amount at the configuration target position are normalized, and the reciprocal of the arithmetic square root of the sum of the squares of the normalized result is obtained, and the reciprocal is used as the query condition on the dynamic time node during the query. In other embodiments, other methods can also be used, such as determining the query condition on the dynamic time node during the query by a determination function, which is not limited here.

[0106] It should be noted that, in the present application, configuring the target position means mapping the query data in the dynamic data segment to a specific database table field or a position in the query condition during the dynamic parameter query process. The configured target position is usually a parameter, field in the query statement, or a column in a specific database table, which is used to accurately locate and obtain the required data; configuring the query optimization amount means the quantitative indicator or metric required to optimize the query condition. The optimization amount can be based on different optimization strategies, such as index usage, caching mechanism, query rewriting, etc., and is specifically quantified into certain parameters or values ​​so that these optimization measures can be applied during the query execution process; the query condition means the specific constraints and rules set in the query operation. These conditions are used to filter and obtain data that meets specific needs. The query conditions may include field value matching, range constraints, sorting rules, etc., to ensure that the result set returned by the query meets the expectations of the user or system.

[0107] In some embodiments, determining the query trap of the database of the report designer when it is dynamic according to the neighborhood anchor point and the query condition can be implemented by the following steps:

[0108] Determine the trapdoor adjustment amount of the database of the report designer when it is dynamic according to the neighborhood anchor point and the query condition;

[0109] Determine the query logic characteristics of the report designer's database when it is dynamic;

[0110] The trapdoor adjustment amount of the database of the report designer when it is dynamic is determined according to the threshold adjustment amount and the query logic characteristics.

[0111] In a specific implementation, first, after normalizing the neighborhood anchor point and the query condition, the ratio of the normalized neighborhood anchor point to the query condition is calculated and the ratio is quantized to between 0 and 1, and the quantized ratio is used as the trapdoor adjustment amount of the database of the report designer when it is dynamic; then, according to the ratio of the mean of all the neighborhood anchor points of the database of the report designer when it is dynamic and the mean of the query index value, the query logic feature of the database of the report designer when it is dynamic is determined, that is, the ratio of the mean of all the neighborhood anchor points of the database of the report designer when it is dynamic and the mean of the query index value is used as the query logic feature of the database of the report designer when it is dynamic. In other embodiments, other methods may also be used to determine the report designer. The query logic characteristics of the database of the table designer when it is dynamic are not limited here; finally, the trapdoor adjustment amount of the database of the report designer when it is dynamic is determined according to the product of the threshold adjustment amount and the query logic characteristics, that is, the product of the threshold adjustment amount and the query logic characteristics is used as the trapdoor adjustment amount of the database of the report designer when it is dynamic. In other embodiments, other methods can also be used to determine the trapdoor adjustment amount, for example, setting a query response time threshold and a complex multi-table join operation process, using index optimization, and differentiating multiple complex multi-table join operations into multiple simple queries, thereby setting traps for the query process, avoiding unnecessary query operation execution, and optimizing the rate of dynamic parameter queries.

[0112] It should be noted that the trapdoor adjustment amount in the present application represents a set of adjustable parameters and strategies introduced in the process of dynamic query of the database to optimize the query performance, so as to improve the query efficiency, reduce resource consumption and improve the system response speed; the query logic feature of the database of the report designer when it is dynamic represents the execution efficiency of the query operation in the database dynamic running environment of the report designer when the database is dynamic. By identifying and optimizing this feature, the response speed and overall performance of the database query can be improved; the trapdoor adjustment amount represents a trap set in the process of dynamic parameter query to prevent misoperation or misaccess. The larger the value of the trapdoor adjustment amount, the higher the protection level of the misquery, the larger the query cost consumption index during dynamic parameter query, and the lower the query efficiency and scalability.

[0113] In step 105, a query cost for dynamic parameter query is determined according to the query logic item and the query trapdoor, and a target query result for the dynamic parameter in the report designer is determined according to the query cost.

[0114] In some embodiments, determining the query cost of a dynamic parameter query according to the query logic item and the query trapdoor may be implemented by the following steps:

[0115] Determine the time dilation amount of the current dynamic parameter query according to the query logic item;

[0116] Determine the time consumption of global dynamic parameter query according to the query trap;

[0117] The query cost of dynamic parameter query is determined according to the time expansion amount and the time consumption amount.

[0118] In specific implementation, first, the time dilation amount of the current dynamic parameter query can be determined according to the average of the time required to access the business data in all query logic items, that is, the average of the time required to access the business data in all query logic items is used as the time dilation amount of the current dynamic parameter query; then, the time consumption of the global dynamic parameter query can be determined according to the average of all the time on the query trap when executing the dynamic parameter query, that is, the average of all the time on the query trap when executing the dynamic parameter query is used as the time consumption of the global dynamic parameter query. In other embodiments, other methods can also be used to determine it, which is not limited here; finally, the query cost of the dynamic parameter query is determined according to the ratio of the time dilation amount of the current dynamic parameter query to the time consumption of the global dynamic parameter query, that is, after normalizing the ratio of the time dilation amount of the current dynamic parameter query to the time consumption of the global dynamic parameter query to between 0 and 1, the normalized result is used as the query cost of the dynamic parameter query. In other embodiments, the particle swarm algorithm or the ant colony algorithm can also be used to determine the query cost of the dynamic parameter query, which is not limited here.

[0119] It should be noted that, in the present application, the time expansion amount during the previous dynamic parameter query represents the length of time required to access the business data in the query logic item when performing the query; the time consumption during the global dynamic parameter query represents the length of time consumed for all dynamic parameter queries during the time period from the last time the database of the report designer was static to the next time the database of the report designer was static; the query cost during the dynamic parameter query represents a measure of optimizing the query performance during the dynamic parameter query, the smaller the query cost during the dynamic parameter query, the faster the dynamic parameter query, and the better the query efficiency, resource utilization and scalability of the system during the query.

[0120] In specific implementation, the target query result of the dynamic parameter in the report designer is determined according to the query cost, which can be achieved in the following manner, namely: setting a query cost threshold, comparing the query cost with the query cost threshold, when the query cost is less than or equal to the query cost threshold, there is no need to adjust the query rules of the dynamic parameter query, and when the query cost is greater than the query cost threshold, it is necessary to feedback and adjust the query rules of the dynamic parameter query to ensure the efficiency of the dynamic parameter query, thereby realizing dynamic logic allocation during dynamic parameter query and improving the dynamic query compatibility during dynamic parameter query. Among them, the query cost threshold can be set based on execution time or query cost according to expert experience, and there is no limitation here.

[0121] In addition, in another aspect of the present application, in some embodiments, the present application provides a dynamic parameter query system, referring to Figure 4 , which is a schematic diagram of exemplary hardware and / or software of a dynamic parameter query system according to some embodiments of the present application, the dynamic parameter query system 400 includes: an acquisition module 401, a processing module 402 and an execution module 403, which are described as follows:

[0122] Acquisition module 401, in this application, acquisition module 401 is mainly used to acquire the query request uploaded by the target user on the user end of the report designer;

[0123] Processing module 402, in this application, processing module 402 is mainly used to extract query configuration information of each business data in the report designer according to the query request, and determine the neighborhood anchor point of the query configuration information in the adjacent business data through the query configuration information of all business data;

[0124] The processing module 402 is further used to determine a query index table of the database of the report designer when it is static, perform hierarchical fusion on the query index table to obtain query index values ​​of different query logic layers, and determine the query logic items of the database of the report designer when it is static according to the neighborhood anchor point and all query index values;

[0125] The processing module 402 is further used to obtain a dynamic data segment of the database of the report designer when it is dynamic, determine a query condition at a dynamic time node when querying according to the dynamic data segment, and determine a query trap of the database of the report designer when it is dynamic according to the neighborhood anchor point and the query condition;

[0126] Execution module 403, in the present application, execution module 403 is mainly used to determine the query cost of dynamic parameter query according to the query logic item and the query trap, and determine the target query result of the dynamic parameter in the report designer according to the query cost.

[0127] In addition, the present application also provides a report designer, which is widely used in the fields of business, finance, medical treatment, education, etc. The report designer usually has a user-friendly interface and powerful data processing capabilities, enabling users to extract information from different data sources. The report designer in the present application includes the above-mentioned dynamic parameter query system, which can realize the dynamic parameter query function, which will not be described here.

[0128] The present application also provides a computer device, which includes a memory and a processor, wherein the memory stores codes, and the processor is configured to obtain the codes and execute the above-mentioned dynamic parameter query method.

[0129] In some embodiments, reference Figure 5 , which is a schematic diagram of the structure of a computer device for implementing a dynamic parameter query method according to some embodiments of the present application. The dynamic parameter query method in the above embodiment can be Figure 5 The computer device 500 shown in the figure is implemented, and the computer device 500 includes at least one processor 501, a communication bus 502, a memory 503 and at least one communication interface 504.

[0130] The processor 501 may be a general-purpose central processing unit (CPU), or an application-specific integrated circuit (ASIC) or one or more processors for controlling the execution of the dynamic parameter query method in the present application.

[0131] The communication bus 502 may be used to transmit information between the above-mentioned components.

[0132] The memory 503 may be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical disc, laser disc, optical disc, digital versatile disc, Blu-ray disc, etc.), a disk or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory 503 may exist independently and be connected to the processor 501 via the communication bus 502. The memory 503 may also be integrated with the processor 501.

[0133] The memory 503 is used to store the program code for executing the solution of the present application, and the execution is controlled by the processor 501. The processor 501 is used to execute the program code stored in the memory 503. The program code may include one or more software modules. The dynamic parameter query method in the above embodiment can be implemented by the processor 501 and one or more software modules in the program code in the memory 503.

[0134] The communication interface 504 uses any transceiver or other device for communicating with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area networks (WLAN), etc.

[0135] In a specific implementation, as an embodiment, a computer device may include multiple processors, each of which may be a single-CPU processor or a multi-CPU processor. The processor here may refer to one or more devices, circuits, and / or processing cores for processing data (e.g., computer program instructions).

[0136] The above-mentioned computer device can be a general-purpose computer device or a special-purpose computer device. In a specific implementation, the computer device can be a desktop computer, a portable computer, a network server, a personal digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device or an embedded device. The embodiment of the present application does not limit the type of computer device.

[0137] In addition, the present application also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned dynamic parameter query method is implemented.

[0138] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0139] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. If these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A dynamic parameter query method, characterized in that: The steps include: Get the query request uploaded by the target user on the user side of the report designer; Extract query configuration information of each business data in the report designer according to the query request, and determine a neighborhood anchor point of query configuration information in adjacent business data through the query configuration information of all business data; Determine a query index table of the database of the report designer when it is static, perform hierarchical fusion on the query index table to obtain query index values ​​of different query logic layers, and determine the query logic items of the database of the report designer when it is static according to the neighborhood anchor point and all query index values; Acquire a dynamic data segment of the database of the report designer when it is dynamic, determine a query condition at a dynamic time node when querying according to the dynamic data segment, and determine a query trap of the database of the report designer when it is dynamic according to the neighborhood anchor point and the query condition; The query cost of dynamic parameter query is determined according to the query logic item and the query trapdoor, and the target query result of the dynamic parameter in the report designer is determined according to the query cost.

2. The method according to claim 1, characterized in that Extracting query configuration information of each business data in the report designer according to the query request specifically includes: Parsing the query request to obtain multiple query configuration items; Classify the business data in the report designer according to all query configuration items to obtain the query configuration information of each business data.

3. The method according to claim 1, characterized in that Determining the neighborhood anchor point of query configuration information in adjacent business data through query configuration information of all business data specifically includes: Determine the configuration feature quantity in the query configuration information of all business data; Determine the mutual proximity similarity in the query configuration information of the adjacent service data according to all configuration feature quantities; A neighborhood anchor point in the query configuration information of the adjacent service data is determined according to the mutual proximity similarity.

4. The method according to claim 1, characterized in that Determine the query index table of the report designer's database when it is static, including: Get the business data collection of the report designer's database when it is static; Determine multiple query index quantities according to the business data set; Determine the query index table of the report designer's database at static time based on the amount of all query indexes.

5. The method according to claim 1, characterized in that The query index table is hierarchically merged to obtain query index values ​​of different query logic layers, specifically including: Determine valid query features in the query index table; Extracting query logic information from the effective query features; All query logic information is processed in a hierarchical manner to obtain hierarchical query index degrees; All query index degrees of each level are connected to obtain query index values ​​of different query logic layers.

6. The method according to claim 1, characterized in that Determining the query logic items of the database of the report designer at a static state according to the neighborhood anchor point and all query index values ​​specifically includes: Determining a query priority value based on the neighborhood anchor point and all query index values; Determine the query logic characteristics of the report designer's database when it is static; The query logic items of the database of the report designer when it is static are determined according to the query priority value and the query logic characteristics.

7. The method according to claim 1, characterized in that Determining the query conditions at the dynamic time node during query according to the dynamic data segment specifically includes: Mapping the query data in the dynamic data segment to a configuration target location during dynamic parameter query; Determine the amount of configuration query optimization at dynamic time nodes during querying; Generate query conditions at dynamic time nodes during querying according to the configured target position and the configured query optimization amount.

8. A dynamic parameter query system, characterized in that: include: The acquisition module is used to obtain the query request uploaded by the target user on the user end of the report designer; A processing module, configured to extract query configuration information of each business data in the report designer according to the query request, and determine a neighborhood anchor point of query configuration information in adjacent business data through the query configuration information of all business data; The processing module is further used to determine the query index table of the database of the report designer when it is static, perform hierarchical fusion on the query index table to obtain query index values ​​of different query logic layers, and determine the query logic items of the database of the report designer when it is static according to the neighborhood anchor point and all query index values; The processing module is further used to obtain a dynamic data segment of the database of the report designer when it is dynamic, determine a query condition at a dynamic time node when querying according to the dynamic data segment, and determine a query trap door of the database of the report designer when it is dynamic according to the neighborhood anchor point and the query condition; The execution module is used to determine the query cost of dynamic parameter query according to the query logic item and the query trapdoor, and determine the target query result of the dynamic parameter in the report designer according to the query cost.

9. A report designer, characterized in that: Including the dynamic parameter query system described in claim 8.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the dynamic parameter query method according to any one of claims 1 to 7 is implemented.

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