Data processing method and device, electronic equipment, and storage medium

Abstract

Embodiments of the present application provide a data processing method, comprising: obtaining a to-be-configured parameter input by a user for a target database; determining an associated parameter of the to-be-configured parameter and / or a preset value range of the associated parameter based on a preset association relationship; the preset association relationship is determined based on a plurality of historical configuration files of the target database; and configuring the target database based on the associated parameter and / or the preset value range. Embodiments of the present application also provide a data processing device, an electronic device and a storage medium.

Description

Technical Field

[0001] This application relates to the field of database technology, and in particular to a data processing method and apparatus, electronic device, and storage medium. Background Technology

[0002] As the digitalization of society continues to expand and deepen, the demand for digital information storage services is also growing. Database management systems (such as MySQL and PostgreSQL) provide several parameters (knobs) for database administrators (DBAs) to adjust in order to meet the performance requirements of specific digital businesses.

[0003] Typically, databases have many configuration parameters, and these parameters are logically related (e.g., configuring parameter A should also be linked to configuring parameter B) or have numerical constraints (e.g., the value of parameter A should be less than 40% of the value of parameter B).

[0004] In existing technologies, DBAs typically use electronic documents such as "Parameter Configuration Guides" or "Parameter Configuration Manuals" to configure parameters. However, these documents have several drawbacks. First, the content of these electronic documents is updated slowly as business evolves. Second, electronic documents are described in natural language, making them static and passive, requiring DBAs to have precise textual understanding, which cannot guarantee the accuracy and stability of the configuration. Third, DBAs cannot guarantee that the logical relationships and numerical constraints between parameters are met simultaneously during the configuration process. Summary of the Invention

[0005] This application provides a data processing method, apparatus, device, and storage medium.

[0006] This application provides a data processing method, the method comprising:

[0007] Obtain the configuration parameters input by the user for the target database;

[0008] Based on a preset association relationship, the associated parameters of the parameter to be configured and / or the preset value range of the associated parameters are determined; the preset association relationship is determined based on multiple historical configuration files of the target database;

[0009] The target database is configured based on the associated parameters and / or the preset value range.

[0010] Based on the above embodiments, this application also provides a data processing apparatus, which includes: an acquisition module, a determination module, and a configuration module, wherein...

[0011] The acquisition module is used to acquire the configuration parameters input by the user for the target database;

[0012] The determining module is used to determine the associated parameters of the configuration parameters and / or the preset value range of the associated parameters based on preset association rules; the preset association rules are determined based on multiple historical configuration files;

[0013] The configuration module is used to configure the target database based on the associated parameters and / or the preset value range.

[0014] Based on the above embodiments, this application also provides an electronic device, which includes a processor and a memory for storing a computer program capable of running on the processor;

[0015] When the processor runs the computer program, it executes the steps of the method described in the above embodiments.

[0016] Based on the above embodiments, this application also provides a computer-readable storage medium storing a computer program thereon, the computer program being executed by a processor to implement the steps of the method described in the above embodiments.

[0017] The data processing method provided in this application involves: acquiring the configuration parameters input by the user for a target database; determining the associated parameters and / or preset value ranges of the associated parameters based on preset association relationships; the preset association relationships being determined based on multiple historical configuration files of the target database; and configuring the target database based on the associated parameters and / or preset value ranges. In this way, by using association relationships predetermined through historical configuration experience to determine the associated parameters and preset value ranges of the associated parameters, and by providing real-time prompts to the user to configure the target database based on the associated parameters and / or preset value ranges, the method considers the logical relationships and numerical constraints between parameters, resulting in more accurate and stable parameter configuration. Attached Figure Description

[0018] Figure 1 A flowchart illustrating a data processing method provided in an embodiment of this application;

[0019] Figure 2 A flowchart illustrating another data processing method provided in an embodiment of this application;

[0020] Figure 3 A schematic diagram of the interactive interface corresponding to the MySQL database in a data processing method provided in an embodiment of this application;

[0021] Figure 4This is a schematic diagram of the structure of a data processing device provided in an embodiment of this application;

[0022] Figure 5 This is a flowchart illustrating a data processing device provided in an embodiment of this application.

[0023] Figure 6 A schematic diagram of the electronic device provided in the embodiments of this application. Detailed Implementation

[0024] In order to gain a more detailed understanding of the features and technical content of the embodiments of this application, the implementation of the embodiments of this application will be described in detail below with reference to the accompanying drawings. The accompanying drawings are for reference and illustration only and are not intended to limit the embodiments of this application.

[0025] Unless otherwise defined, all technical and scientific terms used in the embodiments of this application have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in the embodiments of this application is for the purpose of describing the embodiments of this application only and is not intended to limit this application.

[0026] Here, we will first briefly explain the basic terms that appear in the embodiments of this application.

[0027] A database instance is a set of data structures in the computer's physical memory used to manage database files, multiple background processes (threads), and a shared memory pool that can be accessed by all background processes (threads).

[0028] Data instance parameters: The memory "size" occupied by each data structure in the database instance, the "number" of background processes (threads), etc. are all adjustable. These "sizes" and "numbers" are called "database instance parameters", or simply "database parameters".

[0029] Database instance configuration: Set specific values ​​(which can be logical or quantitative values) for "database parameters", abbreviated as "database configuration".

[0030] Database administrator: A technical personnel who is responsible for tasks such as database creation, startup, performance monitoring, and database configuration.

[0031] Database configuration file: An electronic file that stores the database parameter configuration results. DBAs modify this file to configure the database. For example, the database configuration file for MySQL is named "my.cnf".

[0032] Database parameter names: A continuous string consisting of English letters and underscores, often referred to as configuration parameters. For example, MySQL database configuration parameters include: `innodb_log_file_size`, `innodb_buffer_pool_size`, etc.

[0033] Database parameter values: The values ​​that can be configured parameters. The values ​​can be numbers or strings.

[0034] To address the aforementioned problems in related technologies, embodiments of this application provide a data processing method, such as... Figure 1 As shown, the method may include the following steps:

[0035] S101. Obtain the configuration parameters input by the user for the target database.

[0036] Here, the target database can be the database that the DBA is currently configuring. The DBA configures several parameters (knobs) of the target database through the database management system (such as MySQL, PostgreSQL, etc.) to meet the performance requirements of specific digital business operations. The parameters to be configured can be one or more of several parameters, such as the parameters innodb_log_file_size and / or innodb_buffer_pool_size in the MySQL database.

[0037] S102. Based on the preset association relationship, determine the associated parameters of the parameter to be configured and / or the preset value range of the associated parameters; the preset association relationship is determined based on multiple historical configuration files of the target database.

[0038] Here, after the DBA inputs the parameters to be configured through the database management system (DBMS), the DBMS identifies the parameters and determines their associated parameters and / or preset value ranges. This ensures that the DBA can consider both the relationships and numerical constraints between parameters during configuration. First, the DBMS extracts the associated parameters and / or preset value ranges from the preset relationships. These associated parameters can be those that appear simultaneously with the parameter to be configured in multiple historical configuration files. The preset relationships can be determined based on multiple historical configuration files of the target database. Preset relationships can include parameter name relationships and / or parameter value relationships. The associated parameters are retrieved from the parameter name relationships and determined based on the parameter value relationships, identifying those related to the parameter name of the parameter to be configured. Then, the preset value ranges of the associated parameters are determined based on the parameter value relationships. In this way, the database management system can determine the associated parameters and their value ranges based on the configuration experience in historical configuration files. This allows the system to remind the DBA to configure the associated parameters during the configuration process, thereby ensuring that the logical correlation and numerical constraints between parameters are met simultaneously, thus improving the efficiency and accuracy of parameter configuration.

[0039] S103. Configure the target database based on the associated parameters and / or preset value range.

[0040] Here, after determining the associated parameters and / or preset value ranges of the parameters to be configured, the target database is configured based on the associated parameters and / or preset value ranges. Specifically, the associated parameters and / or preset value ranges are displayed in the first preset area of ​​the display interface to prompt the user to configure the target database based on the associated parameters and / or preset value ranges, thereby ensuring that the logical correlation and numerical constraints between parameters are satisfied simultaneously, improving the efficiency and accuracy of parameter configuration.

[0041] Therefore, the data processing method provided in this application embodiment obtains the configuration parameters input by the user for the target database; determines the associated parameters and / or the preset value range of the associated parameters based on preset association relationships; the preset association relationships are determined based on multiple historical configuration files of the target database; and the target database is configured based on the associated parameters and / or the preset value range. In this way, by using the association relationships predetermined through historical configuration experience to determine the associated parameters and the preset value range of the associated parameters, and by providing real-time prompts to the user to configure the target database based on the associated parameters and / or the preset value range, the logical correlation and numerical constraints between parameters are considered, resulting in more accurate and stable parameter configuration.

[0042] Based on the above embodiments, the method may further include the following steps:

[0043] S104. Obtain the associated parameter value input by the user for the associated parameter;

[0044] S105. Determine whether the value of the associated parameter is within the preset range and obtain the determination result;

[0045] S106. Display the judgment result in the second preset area of ​​the display interface.

[0046] Here, after the database management system determines the associated parameters of the parameters to be configured and the preset value range of the associated parameters, the database management system will obtain the associated parameter values ​​input by the DBA for the associated parameters, determine whether the associated parameter values ​​are within the preset range, obtain the determination result, and then display the determination result in the second preset area of ​​the display interface.

[0047] When a DBA configures parameters through the database management system (DBMS), the DBMS identifies the parameters input by the DBA, determines the associated parameters and their value ranges, and presents them to the DBA in the first preset area of ​​the display interface. After configuring the parameters, the DBA retrieves the associated parameters from the display interface in real time and continues to configure them. This ensures that the logical dependencies between parameters are satisfied.

[0048] Specifically, the database management system will identify the correlation parameter values ​​input by the DBA for the correlation parameters, determine whether the parameter values ​​are within the preset value range, obtain the determination result, and display it in the second area of ​​the display interface to prompt the DBA to adjust the correlation parameter values ​​based on the determination result.

[0049] Based on the above embodiments, the method may further include the following steps:

[0050] S107. If the judgment result indicates that the value of the associated parameter is within the preset value range, then obtain the user's configuration operation instruction for the target database.

[0051] S108. In response to the configuration operation command, configure the target database using the parameters to be configured and associated parameters.

[0052] Here, after obtaining the judgment result and displaying it in the first preset area of ​​the display interface, the database management system will identify the judgment result. If the judgment result indicates that the associated parameter value is within the preset value range, the database management system will obtain the user's configuration operation instruction for the target database. This configuration operation instruction can be a saved configuration file. This configuration file includes the parameters to be configured and the associated parameters that conform to historical configuration experience. Responding to the configuration operation instruction, the database management system configures the target database using the parameters to be configured and the associated parameters in the configuration file. Thus, configuring the target database using a configuration file that includes the parameters to be configured and the associated parameters ensures more comprehensive database configuration and higher stability.

[0053] Based on the above embodiments, the preset association relationships in S102 include: parameter name association relationships and / or parameter value association relationships; correspondingly, determining the associated parameters and / or preset value ranges of the parameters to be configured based on the preset association relationships in S102 can be achieved through the following steps:

[0054] S1021. Obtain the associated parameters related to the parameter name of the parameter to be configured from the parameter name association relationship; and / or,

[0055] S1022. Based on the parameter value correlation, determine the preset value range of the correlated parameters.

[0056] Here, when determining the associated parameters and / or preset value ranges of the parameters to be configured through preset association relationships, the preset association relationships can be a set storing parameter name association relationships and parameter value association relationships. Specifically, the database management system first traverses the parameter name association relationships in this set to find the associated parameters related to the parameter name of the parameter to be configured. These associated parameters can be one or more configuration parameters that appear simultaneously in multiple historical configuration files with the parameter to be configured. After obtaining the associated parameters, the corresponding historical associated parameter values ​​in the historical configuration files are obtained. The parameter value association relationship can be a relational expression between the historical parameter values ​​of the parameter to be configured and the historical associated parameter values ​​of the associated parameters in the historical configuration files. Based on the obtained relational expression and the parameter values ​​corresponding to the parameter to be configured input by the DBA, the preset value range of the associated parameters can be determined. In this way, the associated parameters and their value ranges corresponding to the parameter to be configured can be determined. This prompts the DBA to configure the associated parameters during configuration, ensuring that the logical correlation and numerical constraints between parameters are simultaneously satisfied, thus improving the efficiency and accuracy of parameter configuration.

[0057] Based on the above embodiments, before obtaining the configuration parameters input by the user for the target database in S101, the method may further include the following steps:

[0058] S100a. Obtain multiple historical configuration files; each historical configuration file includes multiple historical configuration parameters;

[0059] S100b: Perform association analysis on the parameter names of multiple historical configuration parameters included in each historical configuration file to obtain the parameter name association relationship; the association analysis is used to obtain the configuration parameter group that appears simultaneously in multiple historical configuration files;

[0060] S100d: Based on the parameter values ​​corresponding to multiple historical configuration parameters included in each historical configuration file, determine the parameter value association relationship between the parameter values ​​corresponding to the configuration parameter group;

[0061] S100f: Determine the parameter name association and / or parameter value association as the preset association.

[0062] Here, before obtaining the configuration parameters input by the user for the target database, a step of determining the preset association relationship is also included. Specifically, firstly, multiple historical configuration files are obtained. These multiple historical configuration files can be multiple configuration files obtained after the DBA configures the configuration parameters in the same database, or multiple configuration files obtained after configuring the configuration parameters in different databases. Each historical configuration file includes multiple historical configuration parameters.

[0063] Next, association analysis is performed on the parameter names of multiple historical configuration parameters included in each historical configuration file to obtain parameter name associations. Specifically, the historical configuration parameters are first grouped according to the configuration file. One configuration file corresponds to multiple historical configuration parameters included in that configuration file, resulting in multiple parameter groups containing multiple historical configuration parameters. Association analysis is then performed on the parameter names of all historical configuration parameters in these multiple parameter groups to obtain parameter name associations. Here, the association analysis is used to obtain configuration parameter groups that appear simultaneously in multiple historical configuration files. A configuration parameter group can be a set of configuration parameters that appear simultaneously in multiple historical configuration files. For example, if parameters x and y appear simultaneously in five historical configuration files, then parameters x and y are grouped together as a single configuration parameter group. After the association analysis, multiple configuration parameter groups are obtained, and these configuration parameter groups are identified as parameter name associations.

[0064] Next, based on the parameter values ​​corresponding to multiple historical configuration parameters included in each historical configuration file, the parameter value association relationships between parameter values ​​corresponding to configuration parameter groups are determined. Here, after determining the configuration parameter group, the parameter value corresponding to each configuration parameter in the configuration parameter group is determined. For example, in the above configuration parameter group, the parameter x has a value of 1000, and the parameter y has a value of 900. Based on x = 1000 and y = 900, the parameter value association relationship y = 0.9x can be determined for the parameter values ​​corresponding to this configuration parameter group. Similarly, the parameter value association relationships between parameter values ​​corresponding to other configuration parameter groups can be obtained, resulting in multiple parameter value association relationships.

[0065] Finally, the above parameter name associations and parameter value associations are defined as preset associations. Based on these preset associations, the DBA can determine the associated parameters and / or preset value ranges of the parameters to be configured, and provide real-time prompts to the user to configure the target database based on the associated parameters and / or preset value ranges. This approach considers the logical relationships and numerical constraints between parameters, resulting in more accurate and stable parameter configuration.

[0066] Based on the above embodiments, before determining the parameter value association relationship between parameter values ​​corresponding to configuration parameter groups in S100d based on the parameter values ​​corresponding to multiple historical configuration parameters included in each historical configuration file, the following steps may also be included:

[0067] S100c: Store multiple parameter names corresponding to the configuration parameter group into the first storage unit.

[0068] Here, after obtaining the associated configuration parameter groups, it is necessary to store the multiple parameter names corresponding to the configuration parameter groups as a group. For example, x and y are stored as an associated configuration parameter group in the first storage unit.

[0069] Based on the above embodiments, after determining the parameter value association relationship between the parameter values ​​corresponding to the configuration parameter group based on the parameter values ​​corresponding to the multiple historical configuration parameters included in each historical configuration file in S100d, the following steps may also be included:

[0070] S100e: Store the parameter value association relationship in the second storage unit corresponding to the first storage unit.

[0071] Here, after obtaining the parameter value association, the relational expression corresponding to the parameter value association needs to be stored in the second storage unit corresponding to the first storage unit so that the database management system can look it up. For example, y = 0.9x is stored in the second storage unit. Here, the first storage unit and the second storage unit can be the same or different.

[0072] Therefore, the data processing method provided in this application embodiment obtains the configuration parameters input by the user for the target database; determines the associated parameters and / or the preset value range of the associated parameters based on preset association relationships; the preset association relationships are determined based on multiple historical configuration files of the target database; and the target database is configured based on the associated parameters and / or the preset value range. In this way, by using the association relationships predetermined through historical configuration experience to determine the associated parameters and the preset value range of the associated parameters, and by providing real-time prompts to the user to configure the target database based on the associated parameters and / or the preset value range, the logical correlation and numerical constraints between parameters are considered, resulting in more accurate and stable parameter configuration.

[0073] Based on the above embodiments, this application also provides a data processing method, such as... Figure 2 As shown, the method includes:

[0074] S201. Obtain multiple historical configuration files; each historical configuration file includes multiple historical configuration parameters;

[0075] S202. Perform association analysis on the parameter names of multiple historical configuration parameters included in each historical configuration file to obtain the parameter name association relationship; the association analysis is used to obtain the configuration parameter group that appears simultaneously in multiple historical configuration files;

[0076] S203. Store the multiple parameter names corresponding to the configuration parameter group into the first storage unit;

[0077] Here, we will briefly explain the process of determining the association between parameter names with examples.

[0078] Specifically, select the directory of historical database configuration files, read the multiple historical configuration files contained in the directory, each historical configuration file corresponds to a text; traverse each text, construct an association sample set based on the "equal sign (=" in each text line), and use an association analysis algorithm to obtain the parameter configuration experience represented by the parameter name association relationship.

[0079] Here, constructing the association sample set can be achieved through the following steps: First, read the contents of multiple historical configuration files one by one to obtain a text set F, where each text in F corresponds to the text content of a configuration file. Next, construct the association sample set T, where a sample t is a parameter list. Specifically, take a text f from F and initialize an empty sample t (parameter list t = (). For each line in text f, if the line contains an equal sign (=), add the parameter name on the left side of the equal sign to sample t. Add sample t to sample set T until all text f in F have been traversed. After obtaining the association sample set T, use an association analysis algorithm in machine learning (e.g., the Apriori algorithm), with the association sample set T as input, and set parameters such as support s and confidence c, to obtain the parameter association rule set AR = {X→Y}, where X is the parameter list and Y is the parameter list. Finally, determine the parameter association rule set AR as the parameter name association relationship.

[0080] After determining the parameter name associations, these associations need to be stored. Here, AR is written to the database configuration file K. First, write the line "Parameter association experience begins" in K; then repeatedly extract one rule r from AR, where r is in the form X→Y, and write r as a new line to file K; for each parameter in parameter list X and parameter list Y, write the parameter separated by a space; and add a comma "," between parameter list X and parameter list Y; complete the new line writing. Repeat extracting rule r from AR and writing it to file K on a new line until AR is empty. Finally, write the line "Parameter association experience ends" in K, thus completing the storage of the parameter name associations. The specific implementation process is shown in Table 1 below.

[0081] Parameter association experience begins Parameters X11, X12, X13, Y11, and Y12 Parameters X21, X22, X23, and Y21 …. End of parameter association experience

[0082] Table 1

[0083] S204. Based on the parameter values ​​corresponding to multiple historical configuration parameters included in each historical configuration file, determine the parameter value association relationship between the parameter values ​​corresponding to the configuration parameter group;

[0084] S205. Store the parameter value association relationship in the second storage unit corresponding to the first storage unit.

[0085] Here, we will briefly explain the process of determining the relationship between parameter values ​​with examples.

[0086] Specifically, multiple historical configuration files in the directory are read, and a parameter value sample set is constructed using the equal sign (=) in the text f corresponding to each historical configuration file as a marker. A multiple linear regression algorithm is then used to learn the empirical values ​​of the parameters. This empirical value set is E, where each element e in E is an inequality.

[0087] Next, take out an association rule r: X→Y from the association rule set AR determined in the above steps, connect the parameter list X and the parameter list Y, arrange them to form the list X|Y, obtain the parameter values ​​corresponding to the parameters in the list X|Y from the historical configuration file, and construct a sample set T about X|Y.

[0088] It should be noted that since the parameters in X|Y may exist in multiple different historical configuration files and their values ​​may also be different, a set of values ​​corresponding to the parameters in X|Y is taken as a sample t in the sample set T of X|Y.

[0089] Next, all text f in F is read to construct a training sample set T for the association rule r. Initially, an empty sample t is created. The values ​​of parameter x in parameters X|Y are read from the text f, according to the following rule: if a line contains an equal sign, and the left side of the equal sign is the parameter name x and the right side is a number (denoted as d), then x = d is added to sample t. If sample t contains all parameters in parameter table X|Y, then t is added to sample set T. Otherwise, t is discarded.

[0090] It should also be noted that only a set of values ​​containing all parameters in X|Y can be used as a sample t. For example, if X|Y is x11 x12|y11, then only when all three values ​​x11 = d11, x12 = d12, and y11 = d11 appear simultaneously in a historical configuration file can this set of corresponding values ​​be used as a sample t of the sample set T.

[0091] Next, using the sample set T as input, a linear regression analysis algorithm is used to learn multiple linear inequalities of the parameter list "X|Y".

[0092] Specifically, using the linear regression analysis algorithm can be done by randomly selecting a parameter "y" from the parameter list "X|Y" as the target variable for linear regression, and using the remaining parameters "X|Y / {y}" as the independent variables. Based on the target and independent variables, each sample t in the sample set T is sorted. Using the linear regression analysis algorithm, with T as input, the linear inequality e between the target variable and the remaining variables X|Y / {y} is obtained, and e is added to the set E. This process of selecting different parameters from the parameter list "X|Y" as the target variable is repeated until all rules r in AR are traversed.

[0093] After determining set E, it needs to be written into the database configuration file K. In K, write a new line with the text: "Empirical experience in parameter values ​​begins". For each inequality e in E, start a new line in K, writing the target variable, target variable coefficient, comma, independent variable, and independent variable coefficient, separated by spaces. Finally, write a new line in K with the text: "Empirical experience in parameter values ​​ends", as shown in Table 2 below.

[0094] Parameter value experience begins Target parameter Y11, target parameter coefficient Y11, parameter X11, coefficient X11, parameter X12, coefficient X12 Target parameter Y21, target parameter coefficient Y21, parameter X21, coefficient X11 …. End of parameter value experience

[0095] Table 2

[0096] S206. Obtain the configuration parameters input by the user for the target database;

[0097] S207. Obtain the associated parameters that are associated with the parameter name of the parameter to be configured from the parameter name association relationship; and / or, determine the preset value range of the associated parameters based on the parameter value association relationship.

[0098] S208. Display the associated parameters and / or preset value range in the first preset area of ​​the display interface.

[0099] Specifically, after determining the parameter name association rules and parameter value association rules, these rules are designated as preset association rules. Next, the user-input parameters for the target database are obtained, and the associated parameters and / or preset value ranges of these parameters are determined. These associated parameters and / or preset value ranges are then displayed in the database configuration system's interface to prompt the user to configure the target database based on these parameters and / or preset value ranges. This ensures that both the logical correlation and numerical constraints between parameters are satisfied, improving the efficiency and accuracy of parameter configuration.

[0100] S209. Obtain the associated parameter value input by the user for the associated parameter;

[0101] S210. Determine whether the value of the associated parameter is within the preset range and obtain the determination result;

[0102] S211. Display the judgment result in the second preset area of ​​the display interface;

[0103] Here, when a DBA configures the parameters to be configured through the database management system (DBMS), the DBMS identifies the parameters input by the DBA, determines the associated parameters and their value ranges, and presents them to the DBA in the first preset area of ​​the display interface. After completing the configuration of the parameters to be configured, the DBA will retrieve the associated parameters from the display interface in real time and continue configuring them. This ensures that the logical dependencies between parameters are satisfied.

[0104] Specifically, the database management system will identify the correlation parameter values ​​input by the DBA for the correlation parameters, determine whether the parameter values ​​are within the preset value range, obtain the determination result, and display it in the second area of ​​the display interface to prompt the DBA to adjust the correlation parameter values ​​based on the determination result.

[0105] S212. If the judgment result indicates that the value of the associated parameter is within the preset value range, then obtain the user's configuration operation instruction for the target database.

[0106] S213. In response to the configuration operation command, configure the target database using the parameters to be configured and associated parameters.

[0107] Here, after obtaining the judgment result and displaying it in the first preset area of ​​the display interface, the database management system will identify the judgment result. If the judgment result indicates that the associated parameter value is within the preset value range, the database management system will obtain the user's configuration operation instruction for the target database. This configuration operation instruction can be a saved configuration file. This configuration file includes the parameters to be configured and the associated parameters that conform to historical configuration experience. Responding to the configuration operation instruction, the database management system configures the target database using the parameters to be configured and the associated parameters in the configuration file. Thus, configuring the target database using a configuration file that includes the parameters to be configured and the associated parameters ensures more comprehensive database configuration and higher stability.

[0108] Therefore, the data processing method provided in this application embodiment obtains the configuration parameters input by the user for the target database; determines the associated parameters and / or the preset value range of the associated parameters based on preset association relationships; the preset association relationships are determined based on multiple historical configuration files of the target database; and the target database is configured based on the associated parameters and / or the preset value range. In this way, by using the association relationships predetermined through historical configuration experience to determine the associated parameters and the preset value range of the associated parameters, and by providing real-time prompts to the user to configure the target database based on the associated parameters and / or the preset value range, the logical correlation and numerical constraints between parameters are considered, resulting in more accurate and stable parameter configuration.

[0109] Here, the method proposed in the embodiments of this application is described in conjunction with the configuration of a MySQL database instance:

[0110] See Figure 3 , Figure 3 This is a schematic diagram of the interactive interface corresponding to the MySQL database in a data processing method provided in an embodiment of this application. Assuming that in the initial state... Figure 3 Position 7 in the middle is blank and contains no text. DBA clicks... Figure 3At position 1, the system begins collecting samples from the historical configuration files my.cnf of multiple MySQL databases. The parameter name associations learned through the association analysis algorithm are AR = {X→Y}, where the symbol → indicates "dependency / association". For example, {parameter innodb_log_file_size}→{parameter innodb_buffer_pool_size} means that the parameter innodb_log_file_size is associated with the parameter innodb_buffer_pool_size.

[0111] Next, samples were collected from multiple historical configuration files to obtain inequalities between the parameters innodb_log_file_size and innodb_buffer_pool_size, where "×" is the multiplication sign and "≥" is the mathematical sign greater than or equal to, resulting in innodb_buffer_pool_size × 1.0 ≥ innodb_log_file_size × 1.0.

[0112] Next, the DBA clicks Figure 3 The button marked at position 2 opens the configuration file and allows real-time monitoring of the DBA's actions. Figure 3 The input at position 7. When the system recognizes the DBA input "innodb_log_file_size=", it identifies the parameter innodb_log_file_size, returns the parameter innodb_buffer_pool_size, and displays the parameter innodb_buffer_pool_size. Figure 3 Position 5 prompts the user to consider this parameter.

[0113] Next, the system will monitor the DBA in real time. Figure 3 The input at position 7. When the DBA input "innodb_log_file_size=1000" is detected, the system will recognize the parameter innodb_log_file_size and its value 1000, and receive an empty response. This is because the value of another parameter associated with the parameter innodb_log_file_size, innodb_buffer_pool_size, is not configured.

[0114] Next, the system will monitor the DBA in real time. Figure 3The input at position 7. When the system detects the DBA input "innodb_log_file_size=1000; innodb_buffer_pool_size=900", it identifies the parameter innodb_buffer_pool_size and its value 900. It analyzes whether the empirical inequality innodb_buffer_pool_size×1.0≥innodb_log_file_size×1.0 is satisfied. It concludes that this inequality is not satisfied when innodb_buffer_pool_size is 900 and innodb_log_file_size is 1000. Therefore, it reports that the value is not within the preset range. In other words, the values ​​of the two parameters in the same configuration file do not conform to historical experience, prompting the DBA to adjust the value of one of the parameters.

[0115] If the inequality is satisfied when the parameter innodb_buffer_pool_size is 900 and the parameter innodb_log_file_size is 1000, then click [the appropriate button]. Figure 3 Save the configuration file at position 3 and repeat the above steps to determine the associated parameter names and values ​​that are related to both innodb_log_file_size and innodb_buffer_pool_size, and check whether the associated parameter values ​​meet the requirements, until all parameters in X→Y have been assigned values ​​and all meet the requirements. At this point, click... Figure 3 Exit editing at position 4 and configure the target database using the obtained configuration file.

[0116] In this way, by using the pre-determined relationships based on historical configuration experience, the associated parameters of the parameter to be configured and the preset value range of the associated parameters are determined, and the user is prompted in real time to configure the target database based on the associated parameters and / or the preset value range. This takes into account the logical relationship and numerical constraints between parameters, making the parameter configuration more accurate and more stable.

[0117] Based on the above embodiments, this application also provides a data processing device 40, such as... Figure 4 As shown, the device 40 may include: an acquisition module 41, a determination module 42, and a configuration module 43, wherein,

[0118] The acquisition module 41 is used to acquire the configuration parameters input by the user for the target database;

[0119] The determining module 42 is used to determine the associated parameters of the configuration parameters and / or the preset value range of the associated parameters based on preset association rules; the preset association rules are determined based on multiple historical configuration files;

[0120] The configuration module 43 is used to configure the target database based on the associated parameters and / or the preset value range.

[0121] Based on the above embodiments, the device 40 may further include: a prompting module 44;

[0122] The acquisition module 41 is also used to acquire the associated parameter value input by the user for the associated parameter;

[0123] The determining module 42 is further configured to determine whether the value of the associated parameter is within the preset value range, and obtain a determination result;

[0124] The prompt module 44 is used to display the judgment result in the second preset area of ​​the display interface.

[0125] Based on the above embodiments, the configuration module 43 is further configured to, if the judgment result indicates that the value of the associated parameter is within the preset value range, obtain the user's configuration operation instruction for the target database; and, in response to the configuration operation instruction, configure the target database using the parameter to be configured and the associated parameter.

[0126] Based on the above embodiments, the determining module 42 is specifically used to obtain associated parameters related to the parameter name of the parameter to be configured from the parameter name association relationship; and / or, based on the parameter value association relationship, determine the preset value range of the associated parameters.

[0127] Based on the above embodiments, the device 40 may further include: a learning module 45, configured to acquire the plurality of historical configuration files; each historical configuration file includes a plurality of historical configuration parameters; perform association analysis processing on the parameter names of the plurality of historical configuration parameters included in each historical configuration file to obtain parameter name association relationships; the association analysis processing is used to acquire configuration parameter groups that appear simultaneously in the plurality of historical configuration files; determine the parameter value association relationship between the parameter values ​​corresponding to the configuration parameter groups based on the parameter values ​​corresponding to the plurality of historical configuration parameters included in each historical configuration file; and determine the parameter name association relationship and / or the parameter value association relationship as the preset association relationship.

[0128] Based on the above embodiments, the above-mentioned device 40 may further include: a storage module 46, configured to store multiple parameter names corresponding to the configuration parameter group in a first storage unit before determining the parameter value association relationship between the parameter values ​​corresponding to the configuration parameter group; and to store the parameter value association relationship in a second storage unit corresponding to the first storage unit after determining the parameter value association relationship between the parameter values ​​corresponding to the configuration parameter group.

[0129] The descriptions of the above device embodiments are similar to those of the above method embodiments, and have similar beneficial effects. For technical details not disclosed in the device embodiments of this application, please refer to the descriptions of the method embodiments of this application for understanding.

[0130] Below, in conjunction with Figure 5 In conjunction with the above-described apparatus embodiments, the process of the method embodiments in this application will be further explained.

[0131] like Figure 5 As shown, the learning module 45 obtains multiple historical configuration parameters included in multiple historical configuration files, determines the parameter names of the historical configuration parameters and performs association analysis to obtain the parameter name association relationship; then, based on the parameter values ​​corresponding to the historical configuration parameters, it determines the parameter value association relationship; and determines the parameter name association relationship and / or parameter value association relationship as the preset association relationship.

[0132] Storage module 46 stores the above parameter name associations and / or parameter value associations.

[0133] Module 41 retrieves the configuration parameters input by the user for the target database.

[0134] The determination module 42 determines the associated parameters of the configuration parameters and / or the preset value range of the associated parameters based on the preset association rules.

[0135] The configuration module 43 displays the associated parameters and / or preset value ranges in the first preset area of ​​the display interface to prompt the user to configure the target database based on the associated parameters and / or preset value ranges.

[0136] Next, module 41 obtains the associated parameter values ​​input by the user for the associated parameters.

[0137] The determination module 42 determines whether the value of the associated parameter is within the preset range and obtains the determination result.

[0138] The prompt module 44 displays the judgment result in the second preset area of ​​the display interface.

[0139] In this way, by learning the pre-determined relationships between parameters, the associated parameters and the preset value range of the associated parameters are determined, and the user is prompted in real time to configure the target database based on the associated parameters and / or the preset value range. This takes into account the logical relationship and numerical constraints between parameters, making the parameter configuration more accurate and more stable.

[0140] This application first identifies a set of parameters associated with the parameter configuration in the target database through parameter name association. Then, based on this set of highly correlated parameters, the sample range is narrowed for the next multiple linear regression process. Compared with related technologies that directly obtain all configuration parameters from historical configuration files as linear regression samples, this method can narrow the range of parameters to be considered and save computational costs.

[0141] Based on the above embodiments, this application also provides an electronic device corresponding to a data processing method; Figure 6 This is a schematic diagram of the hardware composition structure of the electronic device according to an embodiment of this application, such as... Figure 6 As shown, electronic device 60 includes a communication interface 61, a memory 62, and a processor 63; the various components are coupled together via a bus system 64. It is understood that the bus system 64 is used to implement communication between these components. In addition to a data bus, the bus system 64 also includes a power bus, a control bus, and a status signal bus. However, for clarity, in... Figure 6 The general designated all buses as Bus System 64.

[0142] Communication interface 61 is configured to receive and transmit signals during the process of sending and receiving information with other external network elements;

[0143] Memory 62 is configured to store executable instructions that can run on processor 63;

[0144] Processor 63 is configured to, when executing the executable instructions, perform:

[0145] Obtain the configuration parameters input by the user for the target database;

[0146] Based on a preset association relationship, the associated parameters of the parameter to be configured and / or the preset value range of the associated parameters are determined; the preset association relationship is determined based on multiple historical configuration files of the target database;

[0147] The target database is configured based on the associated parameters and / or the preset value range.

[0148] It is understood that the memory in this embodiment can be volatile memory or non-volatile memory, or both. Specifically, non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), magnetic random access memory (FRAM), flash memory, magnetic surface memory, optical disc, or compact disc read-only memory (CD-ROM); magnetic surface memory can be disk storage or magnetic tape storage. Volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Synchronous Static Random Access Memory (SSRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), Enhanced Synchronous Dynamic Random Access Memory (ESDRAM), SyncLink Dynamic Random Access Memory (SLDRAM), and Direct Rambus Random Access Memory (DRRAM).The memories described in the embodiments of this application are intended to include, but are not limited to, these and any other suitable types of memories.

[0149] The methods disclosed in the embodiments of this application can be applied to a processor or implemented by a processor. A processor may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above methods can be completed by integrated logic circuits in the processor's hardware or by instructions in software form. The processor may be a general-purpose processor, a DSP, or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The processor can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. A general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of the methods disclosed in the embodiments of this application can be directly manifested as execution by a hardware decoding processor, or execution by a combination of hardware and software modules in the decoding processor. The software modules may be located in a storage medium, which is located in memory. The processor reads information from the memory and, in conjunction with its hardware, completes the steps of the aforementioned methods.

[0150] This application also provides a computer storage medium, specifically a computer-readable storage medium. It stores computer instructions thereon. As a first implementation, when the computer storage medium is located at a terminal, these computer instructions, when executed by a processor, implement any step of the data processing method described above in this application's embodiments.

[0151] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0152] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0153] In addition, each functional unit in the various embodiments of this application can be integrated into one processing unit, or each unit can be a separate unit, or at least two units can be integrated into one unit; the integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0154] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.

[0155] Alternatively, if the integrated units described above are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.

[0156] It should be noted that the technical solutions described in the embodiments of this application can be combined arbitrarily without conflict.

[0157] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A data processing method, characterized in that, The method includes: Retrieve multiple historical configuration files; each historical configuration file includes multiple historical configuration parameters; The parameter names of multiple historical configuration parameters included in each historical configuration file are subjected to association analysis to obtain the parameter name association relationship; the association analysis is used to obtain the configuration parameter group that appears simultaneously in the multiple historical configuration files. Based on the parameter values ​​corresponding to the multiple historical configuration parameters included in each historical configuration file, the parameter value association relationship between the parameter values ​​corresponding to the configuration parameter group is determined; The parameter name association and / or the parameter value association are determined as preset associations; Obtain the configuration parameters input by the user for the target database; Based on the preset association relationship, the associated parameters of the parameter to be configured and / or the preset value range of the associated parameters are determined; the preset association relationship is determined based on multiple historical configuration files of the target database; The target database is configured based on the associated parameters and / or the preset value range; The step of determining the associated parameter of the parameter to be configured and / or the preset value range of the associated parameter based on the preset association relationship includes: Obtain the associated parameters that are related to the parameter name of the parameter to be configured from the parameter name association relationship; And / or, Based on the correlation of the parameter values, a preset range of values ​​for the correlated parameters is determined.

2. The method according to claim 1, characterized in that, The method further includes: Obtain the associated parameter value input by the user for the associated parameter; Determine whether the value of the associated parameter is within the preset range to obtain the determination result; The judgment result is displayed in the second preset area of ​​the display interface.

3. The method according to claim 2, characterized in that, The method further includes: If the judgment result indicates that the value of the associated parameter is within the preset value range, then the user's configuration operation instruction for the target database is obtained; In response to the configuration operation command, the target database is configured using the parameters to be configured and the associated parameters.

4. The method according to claim 1, characterized in that, Before determining the parameter value associations between the parameter values ​​corresponding to the configuration parameter groups, the process also includes: Store the multiple parameter names corresponding to the configuration parameter group into the first storage unit; Correspondingly, after determining the parameter value association relationship between the parameter values ​​corresponding to the configuration parameter group, the method further includes: The parameter value association is stored in the second storage unit corresponding to the first storage unit.

5. A data processing apparatus, characterized in that, The device includes: a learning module, an acquisition module, a determination module, and a configuration module, wherein, The learning module is used to acquire multiple historical configuration files; each historical configuration file includes multiple historical configuration parameters; perform association analysis on the parameter names of the multiple historical configuration parameters included in each historical configuration file to obtain parameter name association relationships; the association analysis is used to acquire configuration parameter groups that appear simultaneously in the multiple historical configuration files; based on the parameter values ​​corresponding to the multiple historical configuration parameters included in each historical configuration file, determine the parameter value association relationships between the parameter values ​​corresponding to the configuration parameter groups; and determine the parameter name association relationships and / or the parameter value association relationships as preset association relationships. The acquisition module is used to acquire the configuration parameters input by the user for the target database; The determining module is used to determine the associated parameters of the configuration parameter and / or the preset value range of the associated parameters based on the preset association relationship; the preset association relationship is determined based on the multiple historical configuration files; determining the associated parameters of the configuration parameter and / or the preset value range of the associated parameters based on the preset association relationship includes: obtaining the associated parameters associated with the parameter name of the configuration parameter from the parameter name association relationship; and / or, determining the preset value range of the associated parameters based on the parameter value association relationship; The configuration module is used to configure the target database based on the associated parameters and / or the preset value range.

6. The apparatus according to claim 5, characterized in that, The device further includes: a prompting module; The acquisition module is also used to acquire the associated parameter value input by the user for the associated parameter; The determining module is further configured to determine whether the value of the associated parameter is within the preset value range, and obtain a determination result; The prompting module is used to display the judgment result in a second preset area of ​​the display interface.

7. The apparatus according to claim 5, characterized in that, The device further includes: a storage module, configured to store multiple parameter names corresponding to the configuration parameter group into a first storage unit before determining the parameter value association relationship between the parameter values ​​corresponding to the configuration parameter group; and to store the parameter value association relationship into a second storage unit corresponding to the first storage unit after determining the parameter value association relationship between the parameter values ​​corresponding to the configuration parameter group.

8. An electronic device, characterized in that, The electronic device includes a processor and a memory for storing computer programs that can run on the processor; When the processor is used to run the computer program, it performs the steps of the method according to any one of claims 1 to 4.

9. A computer-readable storage medium having a computer program stored thereon, the computer program being executed by a processor to implement the steps of the method according to any one of claims 1 to 4.

Images